Codebase list colorcet / 3383e0e
Initial version James A. Bednar 7 years ago
119 changed file(s) with 53376 addition(s) and 2 deletion(s). Raw diff Collapse all Expand all
+256
-0
CETperceptual_csv_0_1/cyclic_grey_15-85_c0_n256.csv less more
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+256
-0
CETperceptual_csv_0_1/cyclic_grey_15-85_c0_n256_s25.csv less more
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CETperceptual_csv_0_1/diverging_gwv_55-95_c39_n256.csv less more
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CETperceptual_csv_0_1/isoluminant_cgo_70_c39_n256.csv less more
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41 0.20931,0.5275,0.43806
42 0.21508,0.53254,0.42613
43 0.22033,0.53758,0.41415
44 0.225,0.54263,0.40206
45 0.22922,0.54768,0.38989
46 0.23295,0.55275,0.37763
47 0.23626,0.55783,0.36524
48 0.23913,0.56292,0.35274
49 0.24164,0.56801,0.3401
50 0.24376,0.57311,0.32732
51 0.24561,0.57819,0.31441
52 0.24723,0.58328,0.30137
53 0.24866,0.58836,0.28822
54 0.24993,0.59342,0.27496
55 0.25123,0.59845,0.2616
56 0.25256,0.60344,0.2482
57 0.25407,0.60839,0.23474
58 0.25584,0.61326,0.22129
59 0.25802,0.61807,0.2079
60 0.26074,0.6228,0.19465
61 0.26408,0.62744,0.18153
62 0.26813,0.63197,0.16873
63 0.273,0.63639,0.15625
64 0.27873,0.64068,0.14417
65 0.28531,0.64485,0.13262
66 0.29279,0.6489,0.12165
67 0.30109,0.65281,0.1115
68 0.31019,0.65661,0.10209
69 0.31996,0.66028,0.093634
70 0.33034,0.66383,0.08618
71 0.34123,0.66728,0.079836
72 0.35254,0.67063,0.074617
73 0.36416,0.67388,0.07048
74 0.37603,0.67707,0.067441
75 0.38805,0.68017,0.065341
76 0.40017,0.68323,0.064135
77 0.41235,0.68622,0.063669
78 0.42451,0.68918,0.063793
79 0.43665,0.6921,0.064391
80 0.44873,0.69498,0.065355
81 0.46073,0.69783,0.066603
82 0.47266,0.70067,0.068066
83 0.4845,0.70348,0.06967
84 0.49625,0.70628,0.071332
85 0.50793,0.70905,0.07306
86 0.5195,0.71181,0.074792
87 0.53099,0.71455,0.076552
88 0.5424,0.71728,0.078345
89 0.55372,0.72,0.08017
90 0.56497,0.72269,0.082034
91 0.57617,0.72539,0.083799
92 0.58729,0.72805,0.085523
93 0.59835,0.73071,0.087403
94 0.60937,0.73336,0.089162
95 0.62033,0.73599,0.090964
96 0.63124,0.73861,0.092702
97 0.64211,0.74121,0.094561
98 0.65293,0.7438,0.096272
99 0.66373,0.74637,0.09813
100 0.67447,0.74893,0.099882
101 0.68519,0.75149,0.10167
102 0.69588,0.75402,0.1035
103 0.70654,0.75653,0.10524
104 0.71717,0.75904,0.10708
105 0.72776,0.76153,0.10884
106 0.73834,0.764,0.11066
107 0.7489,0.76647,0.11246
108 0.75944,0.76891,0.1142
109 0.76996,0.77134,0.11604
110 0.78045,0.77373,0.1178
111 0.79092,0.7761,0.11957
112 0.80136,0.77843,0.12132
113 0.81178,0.78071,0.12308
114 0.82215,0.78294,0.12485
115 0.83247,0.78509,0.12657
116 0.84272,0.78715,0.12828
117 0.85289,0.78908,0.12995
118 0.86295,0.79087,0.13152
119 0.87287,0.79248,0.13305
120 0.88262,0.79388,0.13451
121 0.89216,0.79501,0.13581
122 0.90143,0.79585,0.13707
123 0.9104,0.79634,0.13819
124 0.919,0.79646,0.1391
125 0.9272,0.79616,0.13987
126 0.93494,0.79542,0.1405
127 0.94218,0.7942,0.14092
128 0.94889,0.79248,0.14112
129 0.95503,0.79026,0.14111
130 0.9606,0.78755,0.14089
131 0.96559,0.78436,0.14045
132 0.97002,0.7807,0.1398
133 0.9739,0.77661,0.13901
134 0.97726,0.77212,0.13808
135 0.98015,0.76727,0.13693
136 0.9826,0.76211,0.13566
137 0.98467,0.75668,0.13433
138 0.9864,0.75102,0.13284
139 0.98784,0.74515,0.13129
140 0.98904,0.73914,0.12968
141 0.99004,0.73298,0.128
142 0.99087,0.72672,0.1263
143 0.99158,0.72038,0.12453
144 0.99217,0.71398,0.12276
145 0.99268,0.70752,0.121
146 0.99312,0.70102,0.11926
147 0.9935,0.69447,0.11747
148 0.99383,0.68791,0.11573
149 0.99412,0.68132,0.11394
150 0.99438,0.6747,0.1122
151 0.99461,0.66807,0.11045
152 0.99481,0.66142,0.10865
153 0.995,0.65473,0.10697
154 0.99516,0.64804,0.10517
155 0.99529,0.64132,0.1035
156 0.99541,0.63459,0.10176
157 0.9955,0.62783,0.10005
158 0.99557,0.62104,0.098389
159 0.99561,0.61422,0.096641
160 0.99564,0.60739,0.095059
161 0.99564,0.60052,0.093326
162 0.99562,0.59363,0.091753
163 0.99558,0.5867,0.090085
164 0.99551,0.57975,0.08846
165 0.99543,0.57276,0.086866
166 0.99532,0.56573,0.085214
167 0.9952,0.55867,0.083665
168 0.99505,0.55159,0.082128
169 0.99488,0.54446,0.080509
170 0.99469,0.53729,0.078934
171 0.99448,0.53007,0.077397
172 0.99425,0.52281,0.0759
173 0.994,0.5155,0.074438
174 0.99373,0.50816,0.07298
175 0.99343,0.50075,0.071525
176 0.99312,0.49329,0.070045
177 0.99279,0.48577,0.068661
178 0.99244,0.4782,0.067207
179 0.99206,0.47057,0.0658
180 0.99167,0.46285,0.064435
181 0.99126,0.45509,0.063129
182 0.99083,0.44724,0.061707
183 0.99038,0.43931,0.060477
184 0.98991,0.43131,0.059288
185 0.98943,0.42321,0.058031
186 0.98894,0.41505,0.05706
187 0.98843,0.40681,0.056202
188 0.98792,0.3985,0.055473
189 0.98741,0.39011,0.055034
190 0.9869,0.38168,0.054941
191 0.9864,0.37321,0.055283
192 0.98593,0.36474,0.056189
193 0.98549,0.3563,0.057588
194 0.9851,0.34792,0.059933
195 0.98478,0.33968,0.062969
196 0.98453,0.33161,0.066854
197 0.98439,0.32384,0.071751
198 0.98437,0.31645,0.077527
199 0.98449,0.30952,0.084428
200 0.98477,0.30314,0.09217
201 0.98521,0.29747,0.10081
202 0.98584,0.29256,0.1104
203 0.98667,0.28854,0.12072
204 0.98768,0.28545,0.1319
205 0.98888,0.2834,0.14376
206 0.99026,0.28237,0.15632
207 0.9918,0.28237,0.16948
208 0.9935,0.28336,0.18318
209 0.99531,0.28528,0.19743
210 0.99722,0.2881,0.21214
211 0.99921,0.29171,0.22722
212 1,0.29596,0.24264
213 1,0.3008,0.25836
214 1,0.30615,0.27432
215 1,0.31182,0.29047
216 1,0.31783,0.30679
217 1,0.32406,0.32321
218 1,0.33045,0.33974
219 1,0.33697,0.35632
220 1,0.34355,0.37295
221 1,0.3502,0.38964
222 1,0.35686,0.40637
223 1,0.36352,0.42312
224 1,0.37019,0.43991
225 1,0.37687,0.45672
226 1,0.38352,0.47355
227 1,0.39014,0.49042
228 1,0.39675,0.50731
229 1,0.40335,0.52423
230 1,0.40993,0.54118
231 1,0.41648,0.55818
232 1,0.42301,0.57522
233 1,0.42955,0.5923
234 1,0.43607,0.60942
235 1,0.44258,0.62659
236 1,0.44907,0.6438
237 1,0.45556,0.66106
238 1,0.46203,0.67837
239 1,0.4685,0.69574
240 1,0.47498,0.71314
241 1,0.48143,0.7306
242 1,0.48789,0.74812
243 1,0.49434,0.76568
244 1,0.50078,0.78329
245 1,0.50723,0.80096
246 1,0.51367,0.81867
247 1,0.5201,0.83645
248 1,0.52655,0.85427
249 1,0.53299,0.87215
250 1,0.53942,0.89007
251 1,0.54587,0.90805
252 1,0.55231,0.92608
253 0.99945,0.55874,0.94416
254 0.99597,0.56518,0.96229
255 0.99228,0.57163,0.98048
+250
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LICENSE.txt less more
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+74
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README.md less more
0 # cetcolors
1 A collection of useful perceptually uniform colormaps
0 cetcolors
1 ---------
2
3 [cetcolors](https://github.com/bokeh/cetcolors) is a collection of
4 perceptually uniform colormaps for use with Python plotting programs like
5 [bokeh](http://bokeh.pydata.org),
6 [matplotlib](http://matplotlib.org),
7 [holoviews](http://holoviews.org), and
8 [datashader](https://github.com/bokeh/datashader).
9
10 Most colormaps provided for use in Python programs are highly
11 perceptually nonuniform, which means that small changes in data values
12 result in large changes in the perceptual appearance of the
13 corresponding colors, or vice versa. For instance, the matplotlib
14 "hot" and "jet" colormaps have long stretches where the apparent
15 colors change imperceptively, such as the yellow region in "hot" and
16 the cyan/green region in "jet":
17
18 ![hot/jet](doc/images/hot_jet.png)
19
20 When colormaps are used for visualizing scientific datasets, these
21 perceptual nonlinearities can make interpretation of this data very
22 difficult, because false boundaries appear in the data, and genuine
23 boundaries and changes can be obscured.
24
25 To combat these issues, Peter Kovesi at the Center for Exploration
26 Targeting created a set of colormaps that are sampled uniformly in a
27 perceptual color space, using methods he describes in a [paper on
28 arXiv](https://arxiv.org/abs/1509.03700). For instance, the
29 perceptually uniform versions of the above colormaps are called "fire"
30 and "rainbow" in this package:
31
32 ![fire/rainbow](doc/images/fire_rainbow.png)
33
34 Peter provides [versions of 50 colormaps for a variety of different
35 plotting programs](http://peterkovesi.com/projects/colourmaps), and
36 this package provides those colormaps ready to use from within Python
37 programs. The colormaps are all illustrated in an [example
38 notebook](doc/index.html) that describes the different types available
39 and allows you to test how perceptually uniform they are on your
40 particular display device.
41
42
43 ## Installation
44
45 cetcolors is available on most platforms using the `conda` package manager,
46 from the `bokeh` channel:
47
48 ```
49 conda install -c bokeh cetcolors
50 ```
51
52 or by using pip:
53
54 ```
55 pip install cetcolors
56 ```
57
58 Alternatively, you can manually install from the repository if you
59 wish to be able to modify the code over time:
60
61 ```
62 git clone https://github.com/bokeh/cetcolors.git
63 cd cetcolors
64 python setup.py develop
65 ```
66
67 ## Learning more
68
69 You see more perceptually uniform colormaps and learn more about them
70 in [Peter Kovesi's 2015 arXiv paper](https://arxiv.org/pdf/1509.03700v1.pdf),
71 and at the [matplotlib site](https://bids.github.io/colormap/),
72 the [cmocean site](http://matplotlib.org/cmocean/), and a
73 [1996 paper from IBM](http://www.research.ibm.com/people/l/lloydt/color/color.HTM).
+113
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assets/CET_to_py.py less more
0 """
1 Generate Python versions for each of the colormaps provided in
2 http://peterkovesi.com/projects/colourmaps/CETperceptual_csv_0_1.zip
3 """
4 # The linear_kryw_mycarta map is from
5 # https://mycarta.wordpress.com/2012/10/14/the-rainbow-is-deadlong-live-the-rainbow-part-4-cie-lab-heated-body/
6
7 import os, os.path, csv
8
9 path = 'CETperceptual_csv_0_1'
10 output_file = '../cetcolors/__init__.py'
11 header = '''\
12 """
13 Python versions of the 256-color colormaps provided in
14 http://peterkovesi.com/projects/colourmaps/CETperceptual_csv_0_1.zip
15
16 Each of these colormaps can be accessed as a Bokeh palette or
17 Matplotlib colormap, either by string name:
18
19 palette['name']
20 cm['name']
21
22 or as Python attributes:
23
24 m_name
25 b_name
26
27 All colormaps are named using Peter Kovesi\'s naming scheme:
28
29 <category>_<huesequence>_<lightnessrange>_c<meanchroma>[_s<colorshift>_[r<ifreversed>]]
30
31 but some have shorter, more convenient aliases, some of which are
32 inspired by Matplotlib colormaps of the same name and others
33 based on the qualitative appearance.
34 """
35
36 __version__ = '0.9.0'
37
38 from collections import OrderedDict
39 try:
40 from matplotlib.colors import LinearSegmentedColormap
41 from matplotlib.cm import register_cmap
42 except:
43 def LinearSegmentedColormap(colorlist,name): pass
44 def register_cmap(name,cmap): pass
45
46 def rgb_to_hex(r,g,b):
47 return '#%02x%02x%02x' % (r,g,b)
48
49 def bokeh_palette(name,colorlist):
50 palette[name] = [rgb_to_hex(int(r*255),int(g*255),int(b*255)) for r,g,b in colorlist]
51 return palette[name]
52
53 def mpl_cm(name,colorlist):
54 cm[name] = LinearSegmentedColormap.from_list(name, colorlist, N=len(colorlist))
55 register_cmap("cet_"+name, cmap=cm[name])
56 return cm[name]
57
58 palette = OrderedDict()
59 cm = OrderedDict()
60 '''
61
62 # Here #mpl indicates a colormap name taken from Matplotlib
63 aliases = dict(
64 cyclic_mygbm_30_95_c78_s25 = 'colorwheel',
65 diverging_bkr_55_10_c35 = 'bkr',
66 diverging_bky_60_10_c30 = 'bky',
67 diverging_bwr_40_95_c42 = 'coolwarm', #mpl
68 diverging_gwv_55_95_c39 = 'gwv',
69 diverging_linear_bjy_30_90_c45 = 'bjy',
70 isoluminant_cgo_80_c38 = 'isolum',
71 linear_bgy_10_95_c74 = 'bgy',
72 linear_bgyw_15_100_c68 = 'bgyw',
73 linear_blue_5_95_c73 = 'kbc',
74 linear_blue_95_50_c20 = 'blues', #mpl
75 linear_bmw_5_95_c89 = 'bmw',
76 linear_bmy_10_95_c78 = 'inferno', #mpl
77 linear_green_5_95_c69 = 'kgy',
78 linear_grey_0_100_c0 = 'gray', #mpl
79 linear_grey_10_95_c0 = 'dimgray',
80 linear_kryw_0_100_c71 = 'fire', #mpl
81 linear_ternary_blue_0_44_c57 = 'kb',
82 linear_ternary_green_0_46_c42 = 'kg',
83 linear_ternary_red_0_50_c52 = 'kr',
84 rainbow_bgyr_35_85_c73 = 'rainbow',
85 )
86
87
88 with open(output_file, "w") as output:
89 output.write(header)
90 for filename in os.listdir(path):
91 if filename.endswith(".csv"):
92 base = filename[:-4].replace("-","_").replace("_n256","")
93 output.write("\n\n"+base+" = [\\\n")
94 with open(os.path.join(path,filename),'rb') as csvfile:
95 reader = csv.reader(csvfile)
96 for row in reader:
97 output.write("["+', '.join(row)+"],\n")
98 output.write("]\n")
99 output.write("b_{0} = bokeh_palette('{0}',{0})\n".format(base))
100 output.write("m_{0} = mpl_cm('{0}',{0})\n".format(base))
101 output.write("m_{0}_r = mpl_cm('{0}_r',list(reversed({0})))\n".format(base))
102 if base in aliases:
103 alias = aliases[base]
104 output.write("{0} = b_{1}\n".format(alias,base))
105 output.write("m_{0} = m_{1}\n".format(alias,base))
106 output.write("m_{0}_r = m_{1}_r\n".format(alias,base))
107 output.write("palette['{0}'] = b_{1}\n".format(alias,base))
108 output.write("cm['{0}'] = m_{1}\n".format(alias,base))
109 output.write("cm['{0}_r'] = m_{1}_r\n".format(alias,base))
110 output.write("register_cmap('cet_{0}',m_{1})\n".format(alias,base))
111 output.write("register_cmap('cet_{0}_r',m_{1}_r)\n".format(alias,base))
112 output.write("\n\n")
+256
-0
assets/CETperceptual_csv_0_1/cyclic_grey_15-85_c0_n256.csv less more
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23 0.59167,0.59179,0.59176
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30 0.63088,0.63101,0.63098
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150 0.34787,0.34794,0.34793
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152 0.33776,0.33783,0.33781
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154 0.3277,0.32778,0.32776
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157 0.31272,0.31279,0.31277
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+256
-0
assets/CETperceptual_csv_0_1/cyclic_grey_15-85_c0_n256_s25.csv less more
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19 0.24332,0.24337,0.24336
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124 0.78827,0.78843,0.78839
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126 0.79169,0.79185,0.79182
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208 0.94967,0.33772,0.19885
209 0.95189,0.33894,0.21269
210 0.95427,0.34081,0.22702
211 0.95677,0.34328,0.24176
212 0.95937,0.34627,0.25686
213 0.96202,0.34974,0.27224
214 0.96472,0.35359,0.2879
215 0.96743,0.35778,0.30376
216 0.97012,0.36222,0.31979
217 0.97279,0.36688,0.33592
218 0.97541,0.3717,0.35214
219 0.97796,0.37668,0.36845
220 0.98045,0.38173,0.3848
221 0.98286,0.38685,0.40121
222 0.98518,0.39205,0.41764
223 0.9874,0.39727,0.43409
224 0.98953,0.40253,0.45059
225 0.99155,0.40782,0.46711
226 0.99348,0.41314,0.48364
227 0.99528,0.41844,0.5002
228 0.99698,0.42377,0.51679
229 0.99858,0.42911,0.5334
230 1,0.43445,0.55005
231 1,0.43981,0.56674
232 1,0.44517,0.58345
233 1,0.45054,0.60021
234 1,0.45593,0.61701
235 1,0.46132,0.63385
236 1,0.46673,0.65073
237 1,0.47215,0.66766
238 1,0.47757,0.68462
239 1,0.48301,0.70164
240 1,0.48847,0.71871
241 1,0.49393,0.73582
242 1,0.49939,0.75297
243 1,0.50489,0.77018
244 1,0.51038,0.78744
245 1,0.51588,0.80475
246 1,0.52141,0.8221
247 1,0.52695,0.8395
248 1,0.53249,0.85695
249 1,0.53805,0.87445
250 1,0.54361,0.892
251 1,0.5492,0.9096
252 0.99848,0.55478,0.92724
253 0.9966,0.56039,0.94494
254 0.99453,0.566,0.96269
255 0.99228,0.57163,0.98048
+256
-0
assets/CETperceptual_csv_0_1/rainbow_bgyrm_35-85_c71_n256.csv less more
0 0,0.20755,0.97632
1 0,0.22113,0.96201
2 0,0.23397,0.94773
3 0,0.24623,0.93346
4 0,0.25798,0.91922
5 0,0.26932,0.905
6 0,0.28022,0.89081
7 0,0.29079,0.87663
8 0,0.30104,0.8625
9 0,0.31103,0.84838
10 0,0.32074,0.83429
11 0,0.3302,0.82023
12 0,0.33945,0.80621
13 0,0.34846,0.79222
14 0,0.35727,0.77828
15 0,0.36586,0.76439
16 0,0.37426,0.75056
17 0,0.38245,0.7368
18 0,0.39044,0.72311
19 0,0.39823,0.70952
20 0,0.4058,0.69603
21 0,0.41317,0.68264
22 0.0064797,0.42031,0.66938
23 0.016533,0.42727,0.65626
24 0.028131,0.43398,0.64326
25 0.041954,0.44052,0.63041
26 0.055821,0.44686,0.6177
27 0.069351,0.45301,0.60514
28 0.082392,0.45898,0.59273
29 0.095132,0.46479,0.58043
30 0.10747,0.47045,0.56826
31 0.11942,0.47598,0.55619
32 0.13095,0.48139,0.54423
33 0.14195,0.48671,0.53234
34 0.15241,0.49195,0.52051
35 0.16235,0.49712,0.50873
36 0.17166,0.50225,0.49697
37 0.18039,0.50733,0.48522
38 0.18854,0.51239,0.47347
39 0.19606,0.51744,0.46171
40 0.20297,0.52246,0.4499
41 0.20931,0.5275,0.43806
42 0.21508,0.53254,0.42613
43 0.22033,0.53758,0.41415
44 0.225,0.54263,0.40206
45 0.22922,0.54768,0.38989
46 0.23295,0.55275,0.37763
47 0.23626,0.55783,0.36524
48 0.23913,0.56292,0.35274
49 0.24164,0.56801,0.3401
50 0.24376,0.57311,0.32732
51 0.24561,0.57819,0.31441
52 0.24723,0.58328,0.30137
53 0.24866,0.58836,0.28822
54 0.24993,0.59342,0.27496
55 0.25123,0.59845,0.2616
56 0.25256,0.60344,0.2482
57 0.25407,0.60839,0.23474
58 0.25584,0.61326,0.22129
59 0.25802,0.61807,0.2079
60 0.26074,0.6228,0.19465
61 0.26408,0.62744,0.18153
62 0.26813,0.63197,0.16873
63 0.273,0.63639,0.15625
64 0.27873,0.64068,0.14417
65 0.28531,0.64485,0.13262
66 0.29279,0.6489,0.12165
67 0.30109,0.65281,0.1115
68 0.31019,0.65661,0.10209
69 0.31996,0.66028,0.093634
70 0.33034,0.66383,0.08618
71 0.34123,0.66728,0.079836
72 0.35254,0.67063,0.074617
73 0.36416,0.67388,0.07048
74 0.37603,0.67707,0.067441
75 0.38805,0.68017,0.065341
76 0.40017,0.68323,0.064135
77 0.41235,0.68622,0.063669
78 0.42451,0.68918,0.063793
79 0.43665,0.6921,0.064391
80 0.44873,0.69498,0.065355
81 0.46073,0.69783,0.066603
82 0.47266,0.70067,0.068066
83 0.4845,0.70348,0.06967
84 0.49625,0.70628,0.071332
85 0.50793,0.70905,0.07306
86 0.5195,0.71181,0.074792
87 0.53099,0.71455,0.076552
88 0.5424,0.71728,0.078345
89 0.55372,0.72,0.08017
90 0.56497,0.72269,0.082034
91 0.57617,0.72539,0.083799
92 0.58729,0.72805,0.085523
93 0.59835,0.73071,0.087403
94 0.60937,0.73336,0.089162
95 0.62033,0.73599,0.090964
96 0.63124,0.73861,0.092702
97 0.64211,0.74121,0.094561
98 0.65293,0.7438,0.096272
99 0.66373,0.74637,0.09813
100 0.67447,0.74893,0.099882
101 0.68519,0.75149,0.10167
102 0.69588,0.75402,0.1035
103 0.70654,0.75653,0.10524
104 0.71717,0.75904,0.10708
105 0.72776,0.76153,0.10884
106 0.73834,0.764,0.11066
107 0.7489,0.76647,0.11246
108 0.75944,0.76891,0.1142
109 0.76996,0.77134,0.11604
110 0.78045,0.77373,0.1178
111 0.79092,0.7761,0.11957
112 0.80136,0.77843,0.12132
113 0.81178,0.78071,0.12308
114 0.82215,0.78294,0.12485
115 0.83247,0.78509,0.12657
116 0.84272,0.78715,0.12828
117 0.85289,0.78908,0.12995
118 0.86295,0.79087,0.13152
119 0.87287,0.79248,0.13305
120 0.88262,0.79388,0.13451
121 0.89216,0.79501,0.13581
122 0.90143,0.79585,0.13707
123 0.9104,0.79634,0.13819
124 0.919,0.79646,0.1391
125 0.9272,0.79616,0.13987
126 0.93494,0.79542,0.1405
127 0.94218,0.7942,0.14092
128 0.94889,0.79248,0.14112
129 0.95503,0.79026,0.14111
130 0.9606,0.78755,0.14089
131 0.96559,0.78436,0.14045
132 0.97002,0.7807,0.1398
133 0.9739,0.77661,0.13901
134 0.97726,0.77212,0.13808
135 0.98015,0.76727,0.13693
136 0.9826,0.76211,0.13566
137 0.98467,0.75668,0.13433
138 0.9864,0.75102,0.13284
139 0.98784,0.74515,0.13129
140 0.98904,0.73914,0.12968
141 0.99004,0.73298,0.128
142 0.99087,0.72672,0.1263
143 0.99158,0.72038,0.12453
144 0.99217,0.71398,0.12276
145 0.99268,0.70752,0.121
146 0.99312,0.70102,0.11926
147 0.9935,0.69447,0.11747
148 0.99383,0.68791,0.11573
149 0.99412,0.68132,0.11394
150 0.99438,0.6747,0.1122
151 0.99461,0.66807,0.11045
152 0.99481,0.66142,0.10865
153 0.995,0.65473,0.10697
154 0.99516,0.64804,0.10517
155 0.99529,0.64132,0.1035
156 0.99541,0.63459,0.10176
157 0.9955,0.62783,0.10005
158 0.99557,0.62104,0.098389
159 0.99561,0.61422,0.096641
160 0.99564,0.60739,0.095059
161 0.99564,0.60052,0.093326
162 0.99562,0.59363,0.091753
163 0.99558,0.5867,0.090085
164 0.99551,0.57975,0.08846
165 0.99543,0.57276,0.086866
166 0.99532,0.56573,0.085214
167 0.9952,0.55867,0.083665
168 0.99505,0.55159,0.082128
169 0.99488,0.54446,0.080509
170 0.99469,0.53729,0.078934
171 0.99448,0.53007,0.077397
172 0.99425,0.52281,0.0759
173 0.994,0.5155,0.074438
174 0.99373,0.50816,0.07298
175 0.99343,0.50075,0.071525
176 0.99312,0.49329,0.070045
177 0.99279,0.48577,0.068661
178 0.99244,0.4782,0.067207
179 0.99206,0.47057,0.0658
180 0.99167,0.46285,0.064435
181 0.99126,0.45509,0.063129
182 0.99083,0.44724,0.061707
183 0.99038,0.43931,0.060477
184 0.98991,0.43131,0.059288
185 0.98943,0.42321,0.058031
186 0.98894,0.41505,0.05706
187 0.98843,0.40681,0.056202
188 0.98792,0.3985,0.055473
189 0.98741,0.39011,0.055034
190 0.9869,0.38168,0.054941
191 0.9864,0.37321,0.055283
192 0.98593,0.36474,0.056189
193 0.98549,0.3563,0.057588
194 0.9851,0.34792,0.059933
195 0.98478,0.33968,0.062969
196 0.98453,0.33161,0.066854
197 0.98439,0.32384,0.071751
198 0.98437,0.31645,0.077527
199 0.98449,0.30952,0.084428
200 0.98477,0.30314,0.09217
201 0.98521,0.29747,0.10081
202 0.98584,0.29256,0.1104
203 0.98667,0.28854,0.12072
204 0.98768,0.28545,0.1319
205 0.98888,0.2834,0.14376
206 0.99026,0.28237,0.15632
207 0.9918,0.28237,0.16948
208 0.9935,0.28336,0.18318
209 0.99531,0.28528,0.19743
210 0.99722,0.2881,0.21214
211 0.99921,0.29171,0.22722
212 1,0.29596,0.24264
213 1,0.3008,0.25836
214 1,0.30615,0.27432
215 1,0.31182,0.29047
216 1,0.31783,0.30679
217 1,0.32406,0.32321
218 1,0.33045,0.33974
219 1,0.33697,0.35632
220 1,0.34355,0.37295
221 1,0.3502,0.38964
222 1,0.35686,0.40637
223 1,0.36352,0.42312
224 1,0.37019,0.43991
225 1,0.37687,0.45672
226 1,0.38352,0.47355
227 1,0.39014,0.49042
228 1,0.39675,0.50731
229 1,0.40335,0.52423
230 1,0.40993,0.54118
231 1,0.41648,0.55818
232 1,0.42301,0.57522
233 1,0.42955,0.5923
234 1,0.43607,0.60942
235 1,0.44258,0.62659
236 1,0.44907,0.6438
237 1,0.45556,0.66106
238 1,0.46203,0.67837
239 1,0.4685,0.69574
240 1,0.47498,0.71314
241 1,0.48143,0.7306
242 1,0.48789,0.74812
243 1,0.49434,0.76568
244 1,0.50078,0.78329
245 1,0.50723,0.80096
246 1,0.51367,0.81867
247 1,0.5201,0.83645
248 1,0.52655,0.85427
249 1,0.53299,0.87215
250 1,0.53942,0.89007
251 1,0.54587,0.90805
252 1,0.55231,0.92608
253 0.99945,0.55874,0.94416
254 0.99597,0.56518,0.96229
255 0.99228,0.57163,0.98048
+13731
-0
cetcolors/__init__.py less more
0 """
1 Python versions of the 256-color colormaps provided in
2 http://peterkovesi.com/projects/colourmaps/CETperceptual_csv_0_1.zip
3
4 Each of these colormaps can be accessed as a Bokeh palette or
5 Matplotlib colormap, either by string name:
6
7 palette['name']
8 cm['name']
9
10 or as Python attributes:
11
12 m_name
13 b_name
14
15 All colormaps are named using Peter Kovesi's naming scheme:
16
17 <category>_<huesequence>_<lightnessrange>_c<meanchroma>[_s<colorshift>_[r<ifreversed>]]
18
19 but some have shorter, more convenient aliases, some of which are
20 inspired by Matplotlib colormaps of the same name and others
21 based on the qualitative appearance.
22 """
23
24 __version__ = '0.9.0'
25
26 from collections import OrderedDict
27 try:
28 from matplotlib.colors import LinearSegmentedColormap
29 from matplotlib.cm import register_cmap
30 except:
31 def LinearSegmentedColormap(colorlist,name): pass
32 def register_cmap(name,cmap): pass
33
34 def rgb_to_hex(r,g,b):
35 return '#%02x%02x%02x' % (r,g,b)
36
37 def bokeh_palette(name,colorlist):
38 palette[name] = [rgb_to_hex(int(r*255),int(g*255),int(b*255)) for r,g,b in colorlist]
39 return palette[name]
40
41 def mpl_cm(name,colorlist):
42 cm[name] = LinearSegmentedColormap.from_list(name, colorlist, N=len(colorlist))
43 register_cmap("cet_"+name, cmap=cm[name])
44 return cm[name]
45
46 palette = OrderedDict()
47 cm = OrderedDict()
48
49
50 cyclic_grey_15_85_c0 = [\
51 [0.46877, 0.46888, 0.46885],
52 [0.47381, 0.47391, 0.47389],
53 [0.47887, 0.47897, 0.47895],
54 [0.48395, 0.48405, 0.48403],
55 [0.48907, 0.48917, 0.48914],
56 [0.49422, 0.49432, 0.4943],
57 [0.49939, 0.49949, 0.49947],
58 [0.50462, 0.50472, 0.5047],
59 [0.50986, 0.50997, 0.50994],
60 [0.51515, 0.51526, 0.51523],
61 [0.52047, 0.52058, 0.52056],
62 [0.52583, 0.52594, 0.52592],
63 [0.53121, 0.53132, 0.5313],
64 [0.53663, 0.53674, 0.53671],
65 [0.54205, 0.54217, 0.54214],
66 [0.5475, 0.54762, 0.54759],
67 [0.55297, 0.55309, 0.55306],
68 [0.55846, 0.55857, 0.55855],
69 [0.56397, 0.56409, 0.56406],
70 [0.56948, 0.5696, 0.56957],
71 [0.57501, 0.57513, 0.5751],
72 [0.58055, 0.58067, 0.58064],
73 [0.58611, 0.58623, 0.5862],
74 [0.59167, 0.59179, 0.59176],
75 [0.59724, 0.59737, 0.59734],
76 [0.60282, 0.60295, 0.60292],
77 [0.60842, 0.60855, 0.60852],
78 [0.61401, 0.61414, 0.6141],
79 [0.61963, 0.61976, 0.61973],
80 [0.62524, 0.62537, 0.62534],
81 [0.63088, 0.63101, 0.63098],
82 [0.63652, 0.63665, 0.63662],
83 [0.64216, 0.64229, 0.64226],
84 [0.64781, 0.64795, 0.64791],
85 [0.65348, 0.65361, 0.65358],
86 [0.65915, 0.65929, 0.65926],
87 [0.66484, 0.66497, 0.66494],
88 [0.67054, 0.67067, 0.67064],
89 [0.67624, 0.67637, 0.67634],
90 [0.68194, 0.68208, 0.68205],
91 [0.68766, 0.68781, 0.68777],
92 [0.69339, 0.69353, 0.6935],
93 [0.69913, 0.69927, 0.69923],
94 [0.70487, 0.70502, 0.70498],
95 [0.71062, 0.71076, 0.71073],
96 [0.71636, 0.71651, 0.71647],
97 [0.72208, 0.72223, 0.72219],
98 [0.72779, 0.72794, 0.72791],
99 [0.73347, 0.73362, 0.73359],
100 [0.73911, 0.73926, 0.73922],
101 [0.74467, 0.74482, 0.74478],
102 [0.75014, 0.75029, 0.75026],
103 [0.75549, 0.75565, 0.75561],
104 [0.76068, 0.76083, 0.7608],
105 [0.76567, 0.76582, 0.76578],
106 [0.77039, 0.77055, 0.77051],
107 [0.77481, 0.77497, 0.77493],
108 [0.77887, 0.77903, 0.77899],
109 [0.7825, 0.78266, 0.78262],
110 [0.78566, 0.78581, 0.78578],
111 [0.78827, 0.78843, 0.78839],
112 [0.79029, 0.79045, 0.79041],
113 [0.79169, 0.79185, 0.79182],
114 [0.79244, 0.7926, 0.79257],
115 [0.79252, 0.79269, 0.79265],
116 [0.79193, 0.79209, 0.79205],
117 [0.79069, 0.79085, 0.79081],
118 [0.78881, 0.78897, 0.78893],
119 [0.78633, 0.78649, 0.78645],
120 [0.7833, 0.78346, 0.78342],
121 [0.77978, 0.77994, 0.7799],
122 [0.77582, 0.77598, 0.77594],
123 [0.77149, 0.77164, 0.7716],
124 [0.76682, 0.76698, 0.76694],
125 [0.76189, 0.76205, 0.76201],
126 [0.75675, 0.75691, 0.75687],
127 [0.75145, 0.7516, 0.75156],
128 [0.746, 0.74615, 0.74611],
129 [0.74045, 0.7406, 0.74056],
130 [0.73484, 0.73499, 0.73495],
131 [0.72917, 0.72932, 0.72928],
132 [0.72346, 0.72361, 0.72357],
133 [0.71774, 0.71789, 0.71785],
134 [0.712, 0.71215, 0.71211],
135 [0.70626, 0.70641, 0.70637],
136 [0.70052, 0.70066, 0.70062],
137 [0.69477, 0.69492, 0.69488],
138 [0.68905, 0.68919, 0.68916],
139 [0.68333, 0.68346, 0.68343],
140 [0.67762, 0.67776, 0.67772],
141 [0.67191, 0.67205, 0.67201],
142 [0.66621, 0.66635, 0.66631],
143 [0.66052, 0.66066, 0.66063],
144 [0.65485, 0.65498, 0.65495],
145 [0.64919, 0.64932, 0.64929],
146 [0.64352, 0.64365, 0.64362],
147 [0.63787, 0.63801, 0.63797],
148 [0.63223, 0.63236, 0.63233],
149 [0.6266, 0.62673, 0.6267],
150 [0.62098, 0.62111, 0.62108],
151 [0.61536, 0.61549, 0.61546],
152 [0.60976, 0.60989, 0.60986],
153 [0.60418, 0.6043, 0.60427],
154 [0.59858, 0.59871, 0.59868],
155 [0.59302, 0.59314, 0.59311],
156 [0.58744, 0.58756, 0.58753],
157 [0.58189, 0.58201, 0.58198],
158 [0.57635, 0.57647, 0.57644],
159 [0.57081, 0.57092, 0.5709],
160 [0.56528, 0.56539, 0.56537],
161 [0.55977, 0.55989, 0.55986],
162 [0.55426, 0.55438, 0.55435],
163 [0.54877, 0.54888, 0.54886],
164 [0.54328, 0.54339, 0.54336],
165 [0.53781, 0.53792, 0.53789],
166 [0.53234, 0.53245, 0.53242],
167 [0.52688, 0.52699, 0.52697],
168 [0.52143, 0.52154, 0.52151],
169 [0.51599, 0.5161, 0.51607],
170 [0.51057, 0.51067, 0.51065],
171 [0.50515, 0.50526, 0.50523],
172 [0.49974, 0.49985, 0.49982],
173 [0.49436, 0.49446, 0.49444],
174 [0.48897, 0.48907, 0.48905],
175 [0.48359, 0.4837, 0.48367],
176 [0.47824, 0.47834, 0.47831],
177 [0.47288, 0.47298, 0.47295],
178 [0.46755, 0.46764, 0.46762],
179 [0.46221, 0.46231, 0.46229],
180 [0.45689, 0.45699, 0.45697],
181 [0.45159, 0.45169, 0.45166],
182 [0.44629, 0.44638, 0.44636],
183 [0.441, 0.44109, 0.44107],
184 [0.43574, 0.43583, 0.43581],
185 [0.43047, 0.43056, 0.43054],
186 [0.42522, 0.42531, 0.42529],
187 [0.41998, 0.42007, 0.42004],
188 [0.41475, 0.41483, 0.41481],
189 [0.40953, 0.40962, 0.4096],
190 [0.40432, 0.40441, 0.40439],
191 [0.39912, 0.39921, 0.39919],
192 [0.39395, 0.39403, 0.39401],
193 [0.38878, 0.38887, 0.38885],
194 [0.38363, 0.38371, 0.38369],
195 [0.37848, 0.37856, 0.37854],
196 [0.37334, 0.37342, 0.3734],
197 [0.36822, 0.36831, 0.36829],
198 [0.36311, 0.36319, 0.36317],
199 [0.35802, 0.3581, 0.35808],
200 [0.35294, 0.35302, 0.353],
201 [0.34787, 0.34794, 0.34793],
202 [0.34282, 0.34289, 0.34287],
203 [0.33776, 0.33783, 0.33781],
204 [0.33274, 0.33281, 0.3328],
205 [0.3277, 0.32778, 0.32776],
206 [0.32271, 0.32278, 0.32276],
207 [0.31771, 0.31778, 0.31776],
208 [0.31272, 0.31279, 0.31277],
209 [0.30775, 0.30782, 0.3078],
210 [0.3028, 0.30286, 0.30285],
211 [0.29786, 0.29793, 0.29791],
212 [0.29294, 0.293, 0.29299],
213 [0.28802, 0.28809, 0.28807],
214 [0.28314, 0.2832, 0.28319],
215 [0.27826, 0.27832, 0.2783],
216 [0.27339, 0.27345, 0.27344],
217 [0.26853, 0.2686, 0.26858],
218 [0.2637, 0.26376, 0.26375],
219 [0.25887, 0.25893, 0.25892],
220 [0.25406, 0.25412, 0.2541],
221 [0.24925, 0.24931, 0.2493],
222 [0.24446, 0.24452, 0.24451],
223 [0.23973, 0.23978, 0.23977],
224 [0.23502, 0.23508, 0.23506],
225 [0.2303, 0.23036, 0.23034],
226 [0.22568, 0.22573, 0.22572],
227 [0.22109, 0.22114, 0.22113],
228 [0.21656, 0.21662, 0.2166],
229 [0.21212, 0.21217, 0.21216],
230 [0.20777, 0.20782, 0.20781],
231 [0.20358, 0.20363, 0.20361],
232 [0.19951, 0.19955, 0.19954],
233 [0.19568, 0.19573, 0.19572],
234 [0.19207, 0.19212, 0.19211],
235 [0.18876, 0.1888, 0.18879],
236 [0.18577, 0.18581, 0.1858],
237 [0.18308, 0.18313, 0.18312],
238 [0.18084, 0.18089, 0.18087],
239 [0.17906, 0.1791, 0.17909],
240 [0.17775, 0.1778, 0.17779],
241 [0.17689, 0.17694, 0.17693],
242 [0.17656, 0.1766, 0.17659],
243 [0.17676, 0.17681, 0.1768],
244 [0.1775, 0.17755, 0.17754],
245 [0.17871, 0.17875, 0.17874],
246 [0.18037, 0.18041, 0.1804],
247 [0.1825, 0.18255, 0.18254],
248 [0.18509, 0.18514, 0.18512],
249 [0.18802, 0.18807, 0.18806],
250 [0.19124, 0.19129, 0.19128],
251 [0.19481, 0.19485, 0.19484],
252 [0.19857, 0.19862, 0.19861],
253 [0.20257, 0.20262, 0.20261],
254 [0.20676, 0.20681, 0.2068],
255 [0.21105, 0.2111, 0.21109],
256 [0.21547, 0.21552, 0.21551],
257 [0.21999, 0.22004, 0.22003],
258 [0.22453, 0.22458, 0.22457],
259 [0.22919, 0.22924, 0.22923],
260 [0.23386, 0.23392, 0.2339],
261 [0.23857, 0.23863, 0.23862],
262 [0.24332, 0.24337, 0.24336],
263 [0.24812, 0.24817, 0.24816],
264 [0.2529, 0.25295, 0.25294],
265 [0.25769, 0.25775, 0.25774],
266 [0.26252, 0.26258, 0.26257],
267 [0.26734, 0.2674, 0.26739],
268 [0.27219, 0.27226, 0.27224],
269 [0.27708, 0.27714, 0.27713],
270 [0.28196, 0.28203, 0.28201],
271 [0.28684, 0.2869, 0.28688],
272 [0.29176, 0.29183, 0.29181],
273 [0.29668, 0.29675, 0.29674],
274 [0.3016, 0.30167, 0.30165],
275 [0.30657, 0.30664, 0.30662],
276 [0.31152, 0.31159, 0.31157],
277 [0.31651, 0.31658, 0.31656],
278 [0.32149, 0.32156, 0.32154],
279 [0.32649, 0.32656, 0.32654],
280 [0.33151, 0.33158, 0.33156],
281 [0.33654, 0.33662, 0.3366],
282 [0.34159, 0.34166, 0.34165],
283 [0.34664, 0.34672, 0.3467],
284 [0.3517, 0.35178, 0.35176],
285 [0.3568, 0.35688, 0.35686],
286 [0.36188, 0.36196, 0.36194],
287 [0.36698, 0.36706, 0.36704],
288 [0.37208, 0.37216, 0.37215],
289 [0.37721, 0.37729, 0.37727],
290 [0.38233, 0.38241, 0.38239],
291 [0.38746, 0.38755, 0.38753],
292 [0.3926, 0.39269, 0.39267],
293 [0.39775, 0.39784, 0.39781],
294 [0.40288, 0.40297, 0.40295],
295 [0.40802, 0.4081, 0.40808],
296 [0.41315, 0.41324, 0.41322],
297 [0.41826, 0.41834, 0.41832],
298 [0.42336, 0.42345, 0.42343],
299 [0.42846, 0.42855, 0.42853],
300 [0.43353, 0.43362, 0.4336],
301 [0.43859, 0.43868, 0.43866],
302 [0.44365, 0.44374, 0.44372],
303 [0.44868, 0.44878, 0.44875],
304 [0.4537, 0.4538, 0.45377],
305 [0.45872, 0.45882, 0.4588],
306 [0.46374, 0.46385, 0.46382],
307 ]
308 b_cyclic_grey_15_85_c0 = bokeh_palette('cyclic_grey_15_85_c0',cyclic_grey_15_85_c0)
309 m_cyclic_grey_15_85_c0 = mpl_cm('cyclic_grey_15_85_c0',cyclic_grey_15_85_c0)
310 m_cyclic_grey_15_85_c0_r = mpl_cm('cyclic_grey_15_85_c0_r',list(reversed(cyclic_grey_15_85_c0)))
311
312
313
314
315 cyclic_grey_15_85_c0_s25 = [\
316 [0.17676, 0.17681, 0.1768],
317 [0.1775, 0.17755, 0.17754],
318 [0.17871, 0.17875, 0.17874],
319 [0.18037, 0.18041, 0.1804],
320 [0.1825, 0.18255, 0.18254],
321 [0.18509, 0.18514, 0.18512],
322 [0.18802, 0.18807, 0.18806],
323 [0.19124, 0.19129, 0.19128],
324 [0.19481, 0.19485, 0.19484],
325 [0.19857, 0.19862, 0.19861],
326 [0.20257, 0.20262, 0.20261],
327 [0.20676, 0.20681, 0.2068],
328 [0.21105, 0.2111, 0.21109],
329 [0.21547, 0.21552, 0.21551],
330 [0.21999, 0.22004, 0.22003],
331 [0.22453, 0.22458, 0.22457],
332 [0.22919, 0.22924, 0.22923],
333 [0.23386, 0.23392, 0.2339],
334 [0.23857, 0.23863, 0.23862],
335 [0.24332, 0.24337, 0.24336],
336 [0.24812, 0.24817, 0.24816],
337 [0.2529, 0.25295, 0.25294],
338 [0.25769, 0.25775, 0.25774],
339 [0.26252, 0.26258, 0.26257],
340 [0.26734, 0.2674, 0.26739],
341 [0.27219, 0.27226, 0.27224],
342 [0.27708, 0.27714, 0.27713],
343 [0.28196, 0.28203, 0.28201],
344 [0.28684, 0.2869, 0.28688],
345 [0.29176, 0.29183, 0.29181],
346 [0.29668, 0.29675, 0.29674],
347 [0.3016, 0.30167, 0.30165],
348 [0.30657, 0.30664, 0.30662],
349 [0.31152, 0.31159, 0.31157],
350 [0.31651, 0.31658, 0.31656],
351 [0.32149, 0.32156, 0.32154],
352 [0.32649, 0.32656, 0.32654],
353 [0.33151, 0.33158, 0.33156],
354 [0.33654, 0.33662, 0.3366],
355 [0.34159, 0.34166, 0.34165],
356 [0.34664, 0.34672, 0.3467],
357 [0.3517, 0.35178, 0.35176],
358 [0.3568, 0.35688, 0.35686],
359 [0.36188, 0.36196, 0.36194],
360 [0.36698, 0.36706, 0.36704],
361 [0.37208, 0.37216, 0.37215],
362 [0.37721, 0.37729, 0.37727],
363 [0.38233, 0.38241, 0.38239],
364 [0.38746, 0.38755, 0.38753],
365 [0.3926, 0.39269, 0.39267],
366 [0.39775, 0.39784, 0.39781],
367 [0.40288, 0.40297, 0.40295],
368 [0.40802, 0.4081, 0.40808],
369 [0.41315, 0.41324, 0.41322],
370 [0.41826, 0.41834, 0.41832],
371 [0.42336, 0.42345, 0.42343],
372 [0.42846, 0.42855, 0.42853],
373 [0.43353, 0.43362, 0.4336],
374 [0.43859, 0.43868, 0.43866],
375 [0.44365, 0.44374, 0.44372],
376 [0.44868, 0.44878, 0.44875],
377 [0.4537, 0.4538, 0.45377],
378 [0.45872, 0.45882, 0.4588],
379 [0.46374, 0.46385, 0.46382],
380 [0.46877, 0.46888, 0.46885],
381 [0.47381, 0.47391, 0.47389],
382 [0.47887, 0.47897, 0.47895],
383 [0.48395, 0.48405, 0.48403],
384 [0.48907, 0.48917, 0.48914],
385 [0.49422, 0.49432, 0.4943],
386 [0.49939, 0.49949, 0.49947],
387 [0.50462, 0.50472, 0.5047],
388 [0.50986, 0.50997, 0.50994],
389 [0.51515, 0.51526, 0.51523],
390 [0.52047, 0.52058, 0.52056],
391 [0.52583, 0.52594, 0.52592],
392 [0.53121, 0.53132, 0.5313],
393 [0.53663, 0.53674, 0.53671],
394 [0.54205, 0.54217, 0.54214],
395 [0.5475, 0.54762, 0.54759],
396 [0.55297, 0.55309, 0.55306],
397 [0.55846, 0.55857, 0.55855],
398 [0.56397, 0.56409, 0.56406],
399 [0.56948, 0.5696, 0.56957],
400 [0.57501, 0.57513, 0.5751],
401 [0.58055, 0.58067, 0.58064],
402 [0.58611, 0.58623, 0.5862],
403 [0.59167, 0.59179, 0.59176],
404 [0.59724, 0.59737, 0.59734],
405 [0.60282, 0.60295, 0.60292],
406 [0.60842, 0.60855, 0.60852],
407 [0.61401, 0.61414, 0.6141],
408 [0.61963, 0.61976, 0.61973],
409 [0.62524, 0.62537, 0.62534],
410 [0.63088, 0.63101, 0.63098],
411 [0.63652, 0.63665, 0.63662],
412 [0.64216, 0.64229, 0.64226],
413 [0.64781, 0.64795, 0.64791],
414 [0.65348, 0.65361, 0.65358],
415 [0.65915, 0.65929, 0.65926],
416 [0.66484, 0.66497, 0.66494],
417 [0.67054, 0.67067, 0.67064],
418 [0.67624, 0.67637, 0.67634],
419 [0.68194, 0.68208, 0.68205],
420 [0.68766, 0.68781, 0.68777],
421 [0.69339, 0.69353, 0.6935],
422 [0.69913, 0.69927, 0.69923],
423 [0.70487, 0.70502, 0.70498],
424 [0.71062, 0.71076, 0.71073],
425 [0.71636, 0.71651, 0.71647],
426 [0.72208, 0.72223, 0.72219],
427 [0.72779, 0.72794, 0.72791],
428 [0.73347, 0.73362, 0.73359],
429 [0.73911, 0.73926, 0.73922],
430 [0.74467, 0.74482, 0.74478],
431 [0.75014, 0.75029, 0.75026],
432 [0.75549, 0.75565, 0.75561],
433 [0.76068, 0.76083, 0.7608],
434 [0.76567, 0.76582, 0.76578],
435 [0.77039, 0.77055, 0.77051],
436 [0.77481, 0.77497, 0.77493],
437 [0.77887, 0.77903, 0.77899],
438 [0.7825, 0.78266, 0.78262],
439 [0.78566, 0.78581, 0.78578],
440 [0.78827, 0.78843, 0.78839],
441 [0.79029, 0.79045, 0.79041],
442 [0.79169, 0.79185, 0.79182],
443 [0.79244, 0.7926, 0.79257],
444 [0.79252, 0.79269, 0.79265],
445 [0.79193, 0.79209, 0.79205],
446 [0.79069, 0.79085, 0.79081],
447 [0.78881, 0.78897, 0.78893],
448 [0.78633, 0.78649, 0.78645],
449 [0.7833, 0.78346, 0.78342],
450 [0.77978, 0.77994, 0.7799],
451 [0.77582, 0.77598, 0.77594],
452 [0.77149, 0.77164, 0.7716],
453 [0.76682, 0.76698, 0.76694],
454 [0.76189, 0.76205, 0.76201],
455 [0.75675, 0.75691, 0.75687],
456 [0.75145, 0.7516, 0.75156],
457 [0.746, 0.74615, 0.74611],
458 [0.74045, 0.7406, 0.74056],
459 [0.73484, 0.73499, 0.73495],
460 [0.72917, 0.72932, 0.72928],
461 [0.72346, 0.72361, 0.72357],
462 [0.71774, 0.71789, 0.71785],
463 [0.712, 0.71215, 0.71211],
464 [0.70626, 0.70641, 0.70637],
465 [0.70052, 0.70066, 0.70062],
466 [0.69477, 0.69492, 0.69488],
467 [0.68905, 0.68919, 0.68916],
468 [0.68333, 0.68346, 0.68343],
469 [0.67762, 0.67776, 0.67772],
470 [0.67191, 0.67205, 0.67201],
471 [0.66621, 0.66635, 0.66631],
472 [0.66052, 0.66066, 0.66063],
473 [0.65485, 0.65498, 0.65495],
474 [0.64919, 0.64932, 0.64929],
475 [0.64352, 0.64365, 0.64362],
476 [0.63787, 0.63801, 0.63797],
477 [0.63223, 0.63236, 0.63233],
478 [0.6266, 0.62673, 0.6267],
479 [0.62098, 0.62111, 0.62108],
480 [0.61536, 0.61549, 0.61546],
481 [0.60976, 0.60989, 0.60986],
482 [0.60418, 0.6043, 0.60427],
483 [0.59858, 0.59871, 0.59868],
484 [0.59302, 0.59314, 0.59311],
485 [0.58744, 0.58756, 0.58753],
486 [0.58189, 0.58201, 0.58198],
487 [0.57635, 0.57647, 0.57644],
488 [0.57081, 0.57092, 0.5709],
489 [0.56528, 0.56539, 0.56537],
490 [0.55977, 0.55989, 0.55986],
491 [0.55426, 0.55438, 0.55435],
492 [0.54877, 0.54888, 0.54886],
493 [0.54328, 0.54339, 0.54336],
494 [0.53781, 0.53792, 0.53789],
495 [0.53234, 0.53245, 0.53242],
496 [0.52688, 0.52699, 0.52697],
497 [0.52143, 0.52154, 0.52151],
498 [0.51599, 0.5161, 0.51607],
499 [0.51057, 0.51067, 0.51065],
500 [0.50515, 0.50526, 0.50523],
501 [0.49974, 0.49985, 0.49982],
502 [0.49436, 0.49446, 0.49444],
503 [0.48897, 0.48907, 0.48905],
504 [0.48359, 0.4837, 0.48367],
505 [0.47824, 0.47834, 0.47831],
506 [0.47288, 0.47298, 0.47295],
507 [0.46755, 0.46764, 0.46762],
508 [0.46221, 0.46231, 0.46229],
509 [0.45689, 0.45699, 0.45697],
510 [0.45159, 0.45169, 0.45166],
511 [0.44629, 0.44638, 0.44636],
512 [0.441, 0.44109, 0.44107],
513 [0.43574, 0.43583, 0.43581],
514 [0.43047, 0.43056, 0.43054],
515 [0.42522, 0.42531, 0.42529],
516 [0.41998, 0.42007, 0.42004],
517 [0.41475, 0.41483, 0.41481],
518 [0.40953, 0.40962, 0.4096],
519 [0.40432, 0.40441, 0.40439],
520 [0.39912, 0.39921, 0.39919],
521 [0.39395, 0.39403, 0.39401],
522 [0.38878, 0.38887, 0.38885],
523 [0.38363, 0.38371, 0.38369],
524 [0.37848, 0.37856, 0.37854],
525 [0.37334, 0.37342, 0.3734],
526 [0.36822, 0.36831, 0.36829],
527 [0.36311, 0.36319, 0.36317],
528 [0.35802, 0.3581, 0.35808],
529 [0.35294, 0.35302, 0.353],
530 [0.34787, 0.34794, 0.34793],
531 [0.34282, 0.34289, 0.34287],
532 [0.33776, 0.33783, 0.33781],
533 [0.33274, 0.33281, 0.3328],
534 [0.3277, 0.32778, 0.32776],
535 [0.32271, 0.32278, 0.32276],
536 [0.31771, 0.31778, 0.31776],
537 [0.31272, 0.31279, 0.31277],
538 [0.30775, 0.30782, 0.3078],
539 [0.3028, 0.30286, 0.30285],
540 [0.29786, 0.29793, 0.29791],
541 [0.29294, 0.293, 0.29299],
542 [0.28802, 0.28809, 0.28807],
543 [0.28314, 0.2832, 0.28319],
544 [0.27826, 0.27832, 0.2783],
545 [0.27339, 0.27345, 0.27344],
546 [0.26853, 0.2686, 0.26858],
547 [0.2637, 0.26376, 0.26375],
548 [0.25887, 0.25893, 0.25892],
549 [0.25406, 0.25412, 0.2541],
550 [0.24925, 0.24931, 0.2493],
551 [0.24446, 0.24452, 0.24451],
552 [0.23973, 0.23978, 0.23977],
553 [0.23502, 0.23508, 0.23506],
554 [0.2303, 0.23036, 0.23034],
555 [0.22568, 0.22573, 0.22572],
556 [0.22109, 0.22114, 0.22113],
557 [0.21656, 0.21662, 0.2166],
558 [0.21212, 0.21217, 0.21216],
559 [0.20777, 0.20782, 0.20781],
560 [0.20358, 0.20363, 0.20361],
561 [0.19951, 0.19955, 0.19954],
562 [0.19568, 0.19573, 0.19572],
563 [0.19207, 0.19212, 0.19211],
564 [0.18876, 0.1888, 0.18879],
565 [0.18577, 0.18581, 0.1858],
566 [0.18308, 0.18313, 0.18312],
567 [0.18084, 0.18089, 0.18087],
568 [0.17906, 0.1791, 0.17909],
569 [0.17775, 0.1778, 0.17779],
570 [0.17689, 0.17694, 0.17693],
571 [0.17656, 0.1766, 0.17659],
572 ]
573 b_cyclic_grey_15_85_c0_s25 = bokeh_palette('cyclic_grey_15_85_c0_s25',cyclic_grey_15_85_c0_s25)
574 m_cyclic_grey_15_85_c0_s25 = mpl_cm('cyclic_grey_15_85_c0_s25',cyclic_grey_15_85_c0_s25)
575 m_cyclic_grey_15_85_c0_s25_r = mpl_cm('cyclic_grey_15_85_c0_s25_r',list(reversed(cyclic_grey_15_85_c0_s25)))
576
577
578
579
580 cyclic_mrybm_35_75_c68 = [\
581 [0.97561, 0.52012, 0.97096],
582 [0.98033, 0.51722, 0.96319],
583 [0.9842, 0.51357, 0.95448],
584 [0.98725, 0.50922, 0.94488],
585 [0.98954, 0.5042, 0.93442],
586 [0.99112, 0.49856, 0.9232],
587 [0.99204, 0.49233, 0.91126],
588 [0.99239, 0.48561, 0.89871],
589 [0.99221, 0.47844, 0.88563],
590 [0.99158, 0.47088, 0.87209],
591 [0.99055, 0.46298, 0.85819],
592 [0.98919, 0.45483, 0.84399],
593 [0.98754, 0.44642, 0.82958],
594 [0.98565, 0.43783, 0.81499],
595 [0.98354, 0.42907, 0.80029],
596 [0.98125, 0.42019, 0.78551],
597 [0.97879, 0.4112, 0.77068],
598 [0.97618, 0.40212, 0.75583],
599 [0.97344, 0.39297, 0.74098],
600 [0.97057, 0.38376, 0.72614],
601 [0.96757, 0.3745, 0.71131],
602 [0.96444, 0.36519, 0.6965],
603 [0.96118, 0.35586, 0.6817],
604 [0.95779, 0.3465, 0.66694],
605 [0.95425, 0.33716, 0.65219],
606 [0.95055, 0.3278, 0.63745],
607 [0.94668, 0.31849, 0.62271],
608 [0.94264, 0.30923, 0.60798],
609 [0.93839, 0.3, 0.59322],
610 [0.93394, 0.29087, 0.57844],
611 [0.92929, 0.28185, 0.56366],
612 [0.92441, 0.27294, 0.54883],
613 [0.91931, 0.26418, 0.53396],
614 [0.91398, 0.25557, 0.51908],
615 [0.90842, 0.24712, 0.50415],
616 [0.90264, 0.23883, 0.48918],
617 [0.89665, 0.23073, 0.47419],
618 [0.89044, 0.22281, 0.45918],
619 [0.88405, 0.21501, 0.44415],
620 [0.87747, 0.2074, 0.42911],
621 [0.87072, 0.19987, 0.41407],
622 [0.86383, 0.1925, 0.39903],
623 [0.85679, 0.18523, 0.38401],
624 [0.84962, 0.17801, 0.369],
625 [0.84235, 0.17082, 0.35401],
626 [0.83498, 0.16373, 0.33907],
627 [0.82753, 0.15664, 0.32416],
628 [0.82001, 0.14962, 0.30933],
629 [0.81245, 0.14261, 0.29452],
630 [0.80486, 0.13567, 0.27982],
631 [0.79725, 0.12885, 0.26518],
632 [0.78966, 0.12217, 0.25066],
633 [0.78212, 0.11578, 0.23628],
634 [0.77464, 0.1097, 0.22201],
635 [0.7673, 0.104, 0.20795],
636 [0.76012, 0.098945, 0.19412],
637 [0.75317, 0.094721, 0.18049],
638 [0.74652, 0.091421, 0.16723],
639 [0.74022, 0.089258, 0.15426],
640 [0.73434, 0.088445, 0.14174],
641 [0.72894, 0.089069, 0.12963],
642 [0.7241, 0.091195, 0.118],
643 [0.71988, 0.094767, 0.10689],
644 [0.71631, 0.099636, 0.096236],
645 [0.71343, 0.1058, 0.086225],
646 [0.71128, 0.11302, 0.076774],
647 [0.70983, 0.12104, 0.068001],
648 [0.7091, 0.12989, 0.05981],
649 [0.70904, 0.1392, 0.052084],
650 [0.70963, 0.14902, 0.04517],
651 [0.71081, 0.15914, 0.038855],
652 [0.71251, 0.1695, 0.033292],
653 [0.7147, 0.17995, 0.028947],
654 [0.71729, 0.1905, 0.02547],
655 [0.72021, 0.20107, 0.022733],
656 [0.72342, 0.21166, 0.020622],
657 [0.72685, 0.22214, 0.019034],
658 [0.73046, 0.23256, 0.017876],
659 [0.73419, 0.24288, 0.017071],
660 [0.73802, 0.25311, 0.016547],
661 [0.74191, 0.26323, 0.016249],
662 [0.74585, 0.27322, 0.016125],
663 [0.74979, 0.28311, 0.016137],
664 [0.75375, 0.29288, 0.01625],
665 [0.75769, 0.30257, 0.01644],
666 [0.76161, 0.31217, 0.016684],
667 [0.7655, 0.32171, 0.016989],
668 [0.76932, 0.33117, 0.017296],
669 [0.7731, 0.34058, 0.0176],
670 [0.77681, 0.34994, 0.017896],
671 [0.78044, 0.35925, 0.018177],
672 [0.784, 0.36855, 0.018435],
673 [0.78746, 0.37783, 0.018665],
674 [0.79082, 0.38709, 0.018861],
675 [0.79409, 0.39636, 0.019014],
676 [0.79724, 0.40564, 0.019122],
677 [0.80029, 0.4149, 0.019179],
678 [0.80322, 0.42418, 0.019183],
679 [0.80605, 0.43346, 0.019132],
680 [0.80876, 0.44276, 0.019026],
681 [0.81136, 0.45205, 0.018866],
682 [0.81386, 0.46134, 0.018654],
683 [0.81626, 0.47063, 0.018394],
684 [0.81857, 0.47992, 0.01809],
685 [0.8208, 0.48918, 0.017747],
686 [0.82295, 0.49846, 0.017369],
687 [0.82503, 0.50771, 0.016963],
688 [0.82704, 0.51694, 0.016575],
689 [0.82898, 0.52615, 0.016225],
690 [0.83084, 0.53532, 0.015949],
691 [0.83262, 0.54446, 0.015792],
692 [0.83431, 0.55354, 0.01582],
693 [0.8359, 0.56257, 0.016118],
694 [0.83738, 0.5715, 0.016798],
695 [0.8387, 0.58035, 0.018004],
696 [0.83985, 0.58906, 0.019918],
697 [0.84077, 0.59761, 0.022763],
698 [0.84143, 0.60595, 0.02681],
699 [0.84177, 0.61404, 0.032376],
700 [0.84173, 0.62182, 0.040011],
701 [0.84125, 0.62922, 0.04912],
702 [0.84026, 0.63619, 0.059305],
703 [0.83868, 0.64264, 0.070471],
704 [0.83647, 0.6485, 0.08264],
705 [0.83356, 0.65372, 0.095596],
706 [0.82989, 0.65824, 0.10926],
707 [0.82544, 0.66201, 0.12343],
708 [0.82017, 0.66498, 0.13819],
709 [0.81408, 0.66715, 0.15321],
710 [0.80717, 0.66852, 0.16856],
711 [0.79947, 0.66908, 0.18405],
712 [0.79098, 0.66887, 0.19961],
713 [0.78178, 0.66795, 0.2152],
714 [0.7719, 0.66635, 0.23072],
715 [0.76139, 0.66416, 0.2461],
716 [0.75032, 0.66143, 0.26133],
717 [0.73873, 0.65825, 0.27636],
718 [0.72668, 0.65467, 0.29113],
719 [0.71421, 0.65077, 0.30567],
720 [0.70137, 0.64662, 0.31995],
721 [0.68818, 0.64226, 0.33397],
722 [0.67466, 0.63773, 0.34774],
723 [0.66084, 0.6331, 0.36127],
724 [0.64671, 0.62838, 0.37458],
725 [0.63228, 0.6236, 0.38765],
726 [0.61753, 0.61878, 0.40056],
727 [0.60245, 0.61393, 0.41326],
728 [0.58703, 0.60909, 0.42578],
729 [0.57126, 0.60423, 0.43817],
730 [0.55511, 0.59936, 0.4504],
731 [0.53858, 0.59449, 0.4625],
732 [0.5216, 0.58962, 0.47451],
733 [0.5042, 0.58475, 0.4864],
734 [0.48632, 0.57986, 0.49821],
735 [0.46796, 0.57493, 0.50993],
736 [0.44912, 0.56996, 0.5216],
737 [0.42978, 0.56493, 0.53322],
738 [0.40998, 0.55983, 0.5448],
739 [0.38972, 0.55461, 0.55635],
740 [0.36908, 0.54926, 0.56789],
741 [0.3481, 0.54375, 0.57943],
742 [0.32688, 0.53805, 0.59098],
743 [0.30556, 0.53211, 0.60256],
744 [0.28424, 0.52592, 0.61416],
745 [0.26316, 0.51945, 0.62583],
746 [0.2425, 0.51265, 0.63755],
747 [0.22257, 0.50551, 0.64934],
748 [0.20368, 0.49802, 0.66119],
749 [0.18619, 0.49012, 0.67313],
750 [0.17051, 0.48183, 0.68514],
751 [0.15712, 0.47312, 0.69723],
752 [0.14638, 0.46402, 0.70941],
753 [0.13859, 0.4545, 0.72164],
754 [0.1338, 0.44458, 0.73395],
755 [0.1319, 0.43426, 0.7463],
756 [0.13253, 0.42359, 0.75869],
757 [0.13519, 0.4126, 0.77109],
758 [0.1393, 0.40128, 0.7835],
759 [0.1445, 0.38969, 0.79588],
760 [0.15024, 0.3779, 0.80821],
761 [0.1563, 0.36594, 0.82045],
762 [0.16246, 0.35387, 0.83257],
763 [0.16864, 0.34179, 0.84452],
764 [0.17484, 0.32979, 0.85623],
765 [0.18105, 0.31794, 0.86767],
766 [0.18746, 0.30639, 0.87875],
767 [0.19408, 0.29524, 0.88943],
768 [0.20101, 0.28465, 0.89962],
769 [0.20848, 0.27478, 0.90926],
770 [0.2165, 0.26579, 0.9183],
771 [0.22506, 0.25778, 0.92668],
772 [0.2343, 0.25098, 0.93436],
773 [0.24409, 0.24544, 0.94131],
774 [0.25448, 0.24134, 0.94753],
775 [0.26529, 0.23866, 0.95301],
776 [0.27652, 0.2375, 0.95778],
777 [0.28798, 0.23773, 0.96185],
778 [0.29964, 0.23933, 0.9653],
779 [0.31135, 0.24218, 0.96816],
780 [0.32305, 0.24613, 0.9705],
781 [0.33464, 0.25106, 0.97238],
782 [0.34606, 0.25676, 0.97386],
783 [0.35733, 0.26313, 0.97502],
784 [0.36835, 0.27, 0.9759],
785 [0.37916, 0.27724, 0.97657],
786 [0.38973, 0.28476, 0.97706],
787 [0.40009, 0.2925, 0.97742],
788 [0.41026, 0.30036, 0.97768],
789 [0.42023, 0.3083, 0.97787],
790 [0.43006, 0.31627, 0.978],
791 [0.43977, 0.32421, 0.97811],
792 [0.4494, 0.33213, 0.9782],
793 [0.459, 0.33997, 0.97829],
794 [0.46859, 0.34772, 0.97838],
795 [0.47825, 0.35536, 0.97849],
796 [0.48802, 0.36282, 0.97864],
797 [0.49795, 0.37015, 0.97883],
798 [0.50807, 0.3773, 0.97906],
799 [0.51845, 0.38426, 0.97935],
800 [0.52912, 0.39102, 0.97969],
801 [0.5401, 0.39755, 0.9801],
802 [0.55143, 0.40386, 0.98057],
803 [0.56311, 0.40995, 0.98111],
804 [0.57513, 0.41579, 0.98173],
805 [0.58751, 0.4214, 0.98242],
806 [0.60022, 0.42681, 0.98317],
807 [0.61322, 0.43201, 0.984],
808 [0.6265, 0.437, 0.98489],
809 [0.64002, 0.44182, 0.98583],
810 [0.65371, 0.44647, 0.98682],
811 [0.66757, 0.45099, 0.98786],
812 [0.68153, 0.4554, 0.98894],
813 [0.69558, 0.4597, 0.99005],
814 [0.70967, 0.46392, 0.99118],
815 [0.72376, 0.46807, 0.99233],
816 [0.73785, 0.47218, 0.9935],
817 [0.7519, 0.47624, 0.99467],
818 [0.76589, 0.48026, 0.99582],
819 [0.77979, 0.48425, 0.99696],
820 [0.79361, 0.48821, 0.99807],
821 [0.80729, 0.49211, 0.99913],
822 [0.82083, 0.49595, 1],
823 [0.8342, 0.49972, 1],
824 [0.84736, 0.50339, 1],
825 [0.86029, 0.50693, 1],
826 [0.87292, 0.5103, 1],
827 [0.8852, 0.51345, 1],
828 [0.89709, 0.51632, 1],
829 [0.90851, 0.51889, 1],
830 [0.91939, 0.52104, 1],
831 [0.92968, 0.52273, 0.99852],
832 [0.9393, 0.52391, 0.996],
833 [0.94819, 0.5245, 0.99274],
834 [0.95631, 0.52446, 0.98864],
835 [0.9636, 0.52374, 0.98368],
836 [0.97003, 0.52229, 0.97779],
837 ]
838 b_cyclic_mrybm_35_75_c68 = bokeh_palette('cyclic_mrybm_35_75_c68',cyclic_mrybm_35_75_c68)
839 m_cyclic_mrybm_35_75_c68 = mpl_cm('cyclic_mrybm_35_75_c68',cyclic_mrybm_35_75_c68)
840 m_cyclic_mrybm_35_75_c68_r = mpl_cm('cyclic_mrybm_35_75_c68_r',list(reversed(cyclic_mrybm_35_75_c68)))
841
842
843
844
845 cyclic_mrybm_35_75_c68_s25 = [\
846 [0.24409, 0.24544, 0.94131],
847 [0.25448, 0.24134, 0.94753],
848 [0.26529, 0.23866, 0.95301],
849 [0.27652, 0.2375, 0.95778],
850 [0.28798, 0.23773, 0.96185],
851 [0.29964, 0.23933, 0.9653],
852 [0.31135, 0.24218, 0.96816],
853 [0.32305, 0.24613, 0.9705],
854 [0.33464, 0.25106, 0.97238],
855 [0.34606, 0.25676, 0.97386],
856 [0.35733, 0.26313, 0.97502],
857 [0.36835, 0.27, 0.9759],
858 [0.37916, 0.27724, 0.97657],
859 [0.38973, 0.28476, 0.97706],
860 [0.40009, 0.2925, 0.97742],
861 [0.41026, 0.30036, 0.97768],
862 [0.42023, 0.3083, 0.97787],
863 [0.43006, 0.31627, 0.978],
864 [0.43977, 0.32421, 0.97811],
865 [0.4494, 0.33213, 0.9782],
866 [0.459, 0.33997, 0.97829],
867 [0.46859, 0.34772, 0.97838],
868 [0.47825, 0.35536, 0.97849],
869 [0.48802, 0.36282, 0.97864],
870 [0.49795, 0.37015, 0.97883],
871 [0.50807, 0.3773, 0.97906],
872 [0.51845, 0.38426, 0.97935],
873 [0.52912, 0.39102, 0.97969],
874 [0.5401, 0.39755, 0.9801],
875 [0.55143, 0.40386, 0.98057],
876 [0.56311, 0.40995, 0.98111],
877 [0.57513, 0.41579, 0.98173],
878 [0.58751, 0.4214, 0.98242],
879 [0.60022, 0.42681, 0.98317],
880 [0.61322, 0.43201, 0.984],
881 [0.6265, 0.437, 0.98489],
882 [0.64002, 0.44182, 0.98583],
883 [0.65371, 0.44647, 0.98682],
884 [0.66757, 0.45099, 0.98786],
885 [0.68153, 0.4554, 0.98894],
886 [0.69558, 0.4597, 0.99005],
887 [0.70967, 0.46392, 0.99118],
888 [0.72376, 0.46807, 0.99233],
889 [0.73785, 0.47218, 0.9935],
890 [0.7519, 0.47624, 0.99467],
891 [0.76589, 0.48026, 0.99582],
892 [0.77979, 0.48425, 0.99696],
893 [0.79361, 0.48821, 0.99807],
894 [0.80729, 0.49211, 0.99913],
895 [0.82083, 0.49595, 1],
896 [0.8342, 0.49972, 1],
897 [0.84736, 0.50339, 1],
898 [0.86029, 0.50693, 1],
899 [0.87292, 0.5103, 1],
900 [0.8852, 0.51345, 1],
901 [0.89709, 0.51632, 1],
902 [0.90851, 0.51889, 1],
903 [0.91939, 0.52104, 1],
904 [0.92968, 0.52273, 0.99852],
905 [0.9393, 0.52391, 0.996],
906 [0.94819, 0.5245, 0.99274],
907 [0.95631, 0.52446, 0.98864],
908 [0.9636, 0.52374, 0.98368],
909 [0.97003, 0.52229, 0.97779],
910 [0.97561, 0.52012, 0.97096],
911 [0.98033, 0.51722, 0.96319],
912 [0.9842, 0.51357, 0.95448],
913 [0.98725, 0.50922, 0.94488],
914 [0.98954, 0.5042, 0.93442],
915 [0.99112, 0.49856, 0.9232],
916 [0.99204, 0.49233, 0.91126],
917 [0.99239, 0.48561, 0.89871],
918 [0.99221, 0.47844, 0.88563],
919 [0.99158, 0.47088, 0.87209],
920 [0.99055, 0.46298, 0.85819],
921 [0.98919, 0.45483, 0.84399],
922 [0.98754, 0.44642, 0.82958],
923 [0.98565, 0.43783, 0.81499],
924 [0.98354, 0.42907, 0.80029],
925 [0.98125, 0.42019, 0.78551],
926 [0.97879, 0.4112, 0.77068],
927 [0.97618, 0.40212, 0.75583],
928 [0.97344, 0.39297, 0.74098],
929 [0.97057, 0.38376, 0.72614],
930 [0.96757, 0.3745, 0.71131],
931 [0.96444, 0.36519, 0.6965],
932 [0.96118, 0.35586, 0.6817],
933 [0.95779, 0.3465, 0.66694],
934 [0.95425, 0.33716, 0.65219],
935 [0.95055, 0.3278, 0.63745],
936 [0.94668, 0.31849, 0.62271],
937 [0.94264, 0.30923, 0.60798],
938 [0.93839, 0.3, 0.59322],
939 [0.93394, 0.29087, 0.57844],
940 [0.92929, 0.28185, 0.56366],
941 [0.92441, 0.27294, 0.54883],
942 [0.91931, 0.26418, 0.53396],
943 [0.91398, 0.25557, 0.51908],
944 [0.90842, 0.24712, 0.50415],
945 [0.90264, 0.23883, 0.48918],
946 [0.89665, 0.23073, 0.47419],
947 [0.89044, 0.22281, 0.45918],
948 [0.88405, 0.21501, 0.44415],
949 [0.87747, 0.2074, 0.42911],
950 [0.87072, 0.19987, 0.41407],
951 [0.86383, 0.1925, 0.39903],
952 [0.85679, 0.18523, 0.38401],
953 [0.84962, 0.17801, 0.369],
954 [0.84235, 0.17082, 0.35401],
955 [0.83498, 0.16373, 0.33907],
956 [0.82753, 0.15664, 0.32416],
957 [0.82001, 0.14962, 0.30933],
958 [0.81245, 0.14261, 0.29452],
959 [0.80486, 0.13567, 0.27982],
960 [0.79725, 0.12885, 0.26518],
961 [0.78966, 0.12217, 0.25066],
962 [0.78212, 0.11578, 0.23628],
963 [0.77464, 0.1097, 0.22201],
964 [0.7673, 0.104, 0.20795],
965 [0.76012, 0.098945, 0.19412],
966 [0.75317, 0.094721, 0.18049],
967 [0.74652, 0.091421, 0.16723],
968 [0.74022, 0.089258, 0.15426],
969 [0.73434, 0.088445, 0.14174],
970 [0.72894, 0.089069, 0.12963],
971 [0.7241, 0.091195, 0.118],
972 [0.71988, 0.094767, 0.10689],
973 [0.71631, 0.099636, 0.096236],
974 [0.71343, 0.1058, 0.086225],
975 [0.71128, 0.11302, 0.076774],
976 [0.70983, 0.12104, 0.068001],
977 [0.7091, 0.12989, 0.05981],
978 [0.70904, 0.1392, 0.052084],
979 [0.70963, 0.14902, 0.04517],
980 [0.71081, 0.15914, 0.038855],
981 [0.71251, 0.1695, 0.033292],
982 [0.7147, 0.17995, 0.028947],
983 [0.71729, 0.1905, 0.02547],
984 [0.72021, 0.20107, 0.022733],
985 [0.72342, 0.21166, 0.020622],
986 [0.72685, 0.22214, 0.019034],
987 [0.73046, 0.23256, 0.017876],
988 [0.73419, 0.24288, 0.017071],
989 [0.73802, 0.25311, 0.016547],
990 [0.74191, 0.26323, 0.016249],
991 [0.74585, 0.27322, 0.016125],
992 [0.74979, 0.28311, 0.016137],
993 [0.75375, 0.29288, 0.01625],
994 [0.75769, 0.30257, 0.01644],
995 [0.76161, 0.31217, 0.016684],
996 [0.7655, 0.32171, 0.016989],
997 [0.76932, 0.33117, 0.017296],
998 [0.7731, 0.34058, 0.0176],
999 [0.77681, 0.34994, 0.017896],
1000 [0.78044, 0.35925, 0.018177],
1001 [0.784, 0.36855, 0.018435],
1002 [0.78746, 0.37783, 0.018665],
1003 [0.79082, 0.38709, 0.018861],
1004 [0.79409, 0.39636, 0.019014],
1005 [0.79724, 0.40564, 0.019122],
1006 [0.80029, 0.4149, 0.019179],
1007 [0.80322, 0.42418, 0.019183],
1008 [0.80605, 0.43346, 0.019132],
1009 [0.80876, 0.44276, 0.019026],
1010 [0.81136, 0.45205, 0.018866],
1011 [0.81386, 0.46134, 0.018654],
1012 [0.81626, 0.47063, 0.018394],
1013 [0.81857, 0.47992, 0.01809],
1014 [0.8208, 0.48918, 0.017747],
1015 [0.82295, 0.49846, 0.017369],
1016 [0.82503, 0.50771, 0.016963],
1017 [0.82704, 0.51694, 0.016575],
1018 [0.82898, 0.52615, 0.016225],
1019 [0.83084, 0.53532, 0.015949],
1020 [0.83262, 0.54446, 0.015792],
1021 [0.83431, 0.55354, 0.01582],
1022 [0.8359, 0.56257, 0.016118],
1023 [0.83738, 0.5715, 0.016798],
1024 [0.8387, 0.58035, 0.018004],
1025 [0.83985, 0.58906, 0.019918],
1026 [0.84077, 0.59761, 0.022763],
1027 [0.84143, 0.60595, 0.02681],
1028 [0.84177, 0.61404, 0.032376],
1029 [0.84173, 0.62182, 0.040011],
1030 [0.84125, 0.62922, 0.04912],
1031 [0.84026, 0.63619, 0.059305],
1032 [0.83868, 0.64264, 0.070471],
1033 [0.83647, 0.6485, 0.08264],
1034 [0.83356, 0.65372, 0.095596],
1035 [0.82989, 0.65824, 0.10926],
1036 [0.82544, 0.66201, 0.12343],
1037 [0.82017, 0.66498, 0.13819],
1038 [0.81408, 0.66715, 0.15321],
1039 [0.80717, 0.66852, 0.16856],
1040 [0.79947, 0.66908, 0.18405],
1041 [0.79098, 0.66887, 0.19961],
1042 [0.78178, 0.66795, 0.2152],
1043 [0.7719, 0.66635, 0.23072],
1044 [0.76139, 0.66416, 0.2461],
1045 [0.75032, 0.66143, 0.26133],
1046 [0.73873, 0.65825, 0.27636],
1047 [0.72668, 0.65467, 0.29113],
1048 [0.71421, 0.65077, 0.30567],
1049 [0.70137, 0.64662, 0.31995],
1050 [0.68818, 0.64226, 0.33397],
1051 [0.67466, 0.63773, 0.34774],
1052 [0.66084, 0.6331, 0.36127],
1053 [0.64671, 0.62838, 0.37458],
1054 [0.63228, 0.6236, 0.38765],
1055 [0.61753, 0.61878, 0.40056],
1056 [0.60245, 0.61393, 0.41326],
1057 [0.58703, 0.60909, 0.42578],
1058 [0.57126, 0.60423, 0.43817],
1059 [0.55511, 0.59936, 0.4504],
1060 [0.53858, 0.59449, 0.4625],
1061 [0.5216, 0.58962, 0.47451],
1062 [0.5042, 0.58475, 0.4864],
1063 [0.48632, 0.57986, 0.49821],
1064 [0.46796, 0.57493, 0.50993],
1065 [0.44912, 0.56996, 0.5216],
1066 [0.42978, 0.56493, 0.53322],
1067 [0.40998, 0.55983, 0.5448],
1068 [0.38972, 0.55461, 0.55635],
1069 [0.36908, 0.54926, 0.56789],
1070 [0.3481, 0.54375, 0.57943],
1071 [0.32688, 0.53805, 0.59098],
1072 [0.30556, 0.53211, 0.60256],
1073 [0.28424, 0.52592, 0.61416],
1074 [0.26316, 0.51945, 0.62583],
1075 [0.2425, 0.51265, 0.63755],
1076 [0.22257, 0.50551, 0.64934],
1077 [0.20368, 0.49802, 0.66119],
1078 [0.18619, 0.49012, 0.67313],
1079 [0.17051, 0.48183, 0.68514],
1080 [0.15712, 0.47312, 0.69723],
1081 [0.14638, 0.46402, 0.70941],
1082 [0.13859, 0.4545, 0.72164],
1083 [0.1338, 0.44458, 0.73395],
1084 [0.1319, 0.43426, 0.7463],
1085 [0.13253, 0.42359, 0.75869],
1086 [0.13519, 0.4126, 0.77109],
1087 [0.1393, 0.40128, 0.7835],
1088 [0.1445, 0.38969, 0.79588],
1089 [0.15024, 0.3779, 0.80821],
1090 [0.1563, 0.36594, 0.82045],
1091 [0.16246, 0.35387, 0.83257],
1092 [0.16864, 0.34179, 0.84452],
1093 [0.17484, 0.32979, 0.85623],
1094 [0.18105, 0.31794, 0.86767],
1095 [0.18746, 0.30639, 0.87875],
1096 [0.19408, 0.29524, 0.88943],
1097 [0.20101, 0.28465, 0.89962],
1098 [0.20848, 0.27478, 0.90926],
1099 [0.2165, 0.26579, 0.9183],
1100 [0.22506, 0.25778, 0.92668],
1101 [0.2343, 0.25098, 0.93436],
1102 ]
1103 b_cyclic_mrybm_35_75_c68_s25 = bokeh_palette('cyclic_mrybm_35_75_c68_s25',cyclic_mrybm_35_75_c68_s25)
1104 m_cyclic_mrybm_35_75_c68_s25 = mpl_cm('cyclic_mrybm_35_75_c68_s25',cyclic_mrybm_35_75_c68_s25)
1105 m_cyclic_mrybm_35_75_c68_s25_r = mpl_cm('cyclic_mrybm_35_75_c68_s25_r',list(reversed(cyclic_mrybm_35_75_c68_s25)))
1106
1107
1108
1109
1110 cyclic_mygbm_30_95_c78 = [\
1111 [0.93769, 0.33352, 0.94809],
1112 [0.94383, 0.34283, 0.94239],
1113 [0.94939, 0.35275, 0.93613],
1114 [0.95439, 0.36323, 0.92931],
1115 [0.95886, 0.37422, 0.92198],
1116 [0.96283, 0.38558, 0.91416],
1117 [0.96634, 0.39727, 0.90588],
1118 [0.96944, 0.40921, 0.89721],
1119 [0.97216, 0.4213, 0.88817],
1120 [0.97454, 0.4335, 0.87883],
1121 [0.97663, 0.44573, 0.86923],
1122 [0.97845, 0.45797, 0.8594],
1123 [0.98004, 0.47017, 0.84939],
1124 [0.98142, 0.48228, 0.83922],
1125 [0.98262, 0.4943, 0.82894],
1126 [0.98364, 0.5062, 0.81854],
1127 [0.98453, 0.51799, 0.80808],
1128 [0.98527, 0.52964, 0.79753],
1129 [0.98588, 0.54116, 0.78694],
1130 [0.98637, 0.55255, 0.77629],
1131 [0.98676, 0.56382, 0.76559],
1132 [0.98704, 0.57494, 0.75486],
1133 [0.98722, 0.58595, 0.74407],
1134 [0.98733, 0.59683, 0.73326],
1135 [0.98736, 0.60758, 0.72241],
1136 [0.98732, 0.61821, 0.71153],
1137 [0.98723, 0.62871, 0.7006],
1138 [0.9871, 0.63909, 0.68965],
1139 [0.98694, 0.64936, 0.67864],
1140 [0.98677, 0.65949, 0.66762],
1141 [0.9866, 0.6695, 0.65654],
1142 [0.98644, 0.67938, 0.64543],
1143 [0.9863, 0.68916, 0.63428],
1144 [0.98621, 0.69879, 0.62309],
1145 [0.98616, 0.70831, 0.61184],
1146 [0.98617, 0.71772, 0.60055],
1147 [0.98624, 0.727, 0.5892],
1148 [0.98636, 0.73618, 0.57779],
1149 [0.98653, 0.74526, 0.56632],
1150 [0.98675, 0.75426, 0.55476],
1151 [0.98702, 0.76315, 0.54311],
1152 [0.98731, 0.77198, 0.53134],
1153 [0.98761, 0.78074, 0.51946],
1154 [0.98792, 0.78944, 0.50744],
1155 [0.9882, 0.79807, 0.49526],
1156 [0.98845, 0.80666, 0.48291],
1157 [0.98864, 0.81518, 0.47039],
1158 [0.98875, 0.82365, 0.45765],
1159 [0.98875, 0.83206, 0.4447],
1160 [0.98863, 0.84039, 0.43151],
1161 [0.98834, 0.84863, 0.41804],
1162 [0.98786, 0.85677, 0.40433],
1163 [0.98715, 0.86476, 0.39033],
1164 [0.98616, 0.87259, 0.37607],
1165 [0.98485, 0.8802, 0.36152],
1166 [0.98316, 0.88754, 0.3467],
1167 [0.98105, 0.89458, 0.33163],
1168 [0.97845, 0.90123, 0.31637],
1169 [0.97534, 0.90744, 0.30092],
1170 [0.97166, 0.91315, 0.28537],
1171 [0.96737, 0.91831, 0.26983],
1172 [0.96244, 0.92285, 0.25432],
1173 [0.95686, 0.92672, 0.23895],
1174 [0.95064, 0.9299, 0.22388],
1175 [0.94377, 0.93236, 0.2092],
1176 [0.93628, 0.9341, 0.19506],
1177 [0.9282, 0.93512, 0.18153],
1178 [0.91959, 0.93544, 0.16884],
1179 [0.91047, 0.9351, 0.15697],
1180 [0.90091, 0.93414, 0.1461],
1181 [0.89097, 0.93263, 0.13623],
1182 [0.8807, 0.93061, 0.12747],
1183 [0.87014, 0.92815, 0.11977],
1184 [0.85937, 0.92531, 0.11315],
1185 [0.8484, 0.92216, 0.10742],
1186 [0.83729, 0.91874, 0.10257],
1187 [0.82605, 0.91511, 0.098502],
1188 [0.81472, 0.91132, 0.095091],
1189 [0.80332, 0.90739, 0.092162],
1190 [0.79187, 0.90336, 0.089659],
1191 [0.78036, 0.89925, 0.087518],
1192 [0.76881, 0.89508, 0.08551],
1193 [0.75723, 0.89086, 0.083837],
1194 [0.74562, 0.88662, 0.082243],
1195 [0.73398, 0.88235, 0.080673],
1196 [0.7223, 0.87807, 0.079194],
1197 [0.7106, 0.87376, 0.077792],
1198 [0.69886, 0.86946, 0.076415],
1199 [0.6871, 0.86514, 0.075063],
1200 [0.67529, 0.86082, 0.073757],
1201 [0.66346, 0.85649, 0.072319],
1202 [0.65156, 0.85215, 0.071005],
1203 [0.63963, 0.8478, 0.069678],
1204 [0.62764, 0.84345, 0.068313],
1205 [0.6156, 0.83909, 0.066946],
1206 [0.60351, 0.83473, 0.065602],
1207 [0.59134, 0.83035, 0.064284],
1208 [0.57911, 0.82597, 0.063016],
1209 [0.56681, 0.82158, 0.061599],
1210 [0.55443, 0.81718, 0.060374],
1211 [0.54195, 0.81278, 0.059088],
1212 [0.5294, 0.80837, 0.057695],
1213 [0.51672, 0.80395, 0.056522],
1214 [0.50395, 0.79952, 0.055189],
1215 [0.49106, 0.79508, 0.053903],
1216 [0.47801, 0.79064, 0.052644],
1217 [0.46484, 0.78619, 0.051424],
1218 [0.45151, 0.78173, 0.050257],
1219 [0.43803, 0.77726, 0.04922],
1220 [0.42437, 0.77277, 0.04812],
1221 [0.41056, 0.76827, 0.047322],
1222 [0.39656, 0.76375, 0.04674],
1223 [0.38239, 0.75922, 0.046427],
1224 [0.36808, 0.75466, 0.046596],
1225 [0.35361, 0.75006, 0.047299],
1226 [0.33906, 0.74543, 0.04874],
1227 [0.32443, 0.74075, 0.050897],
1228 [0.30984, 0.73602, 0.054069],
1229 [0.29532, 0.73122, 0.058336],
1230 [0.28105, 0.72634, 0.063783],
1231 [0.26717, 0.72137, 0.070322],
1232 [0.25387, 0.71631, 0.077992],
1233 [0.24134, 0.71112, 0.08687],
1234 [0.22981, 0.7058, 0.096608],
1235 [0.21961, 0.70035, 0.10741],
1236 [0.21092, 0.69475, 0.11899],
1237 [0.204, 0.68901, 0.13129],
1238 [0.19894, 0.6831, 0.14422],
1239 [0.19593, 0.67703, 0.15768],
1240 [0.19486, 0.67081, 0.17161],
1241 [0.1956, 0.66443, 0.18594],
1242 [0.19795, 0.65791, 0.2005],
1243 [0.20163, 0.65125, 0.21533],
1244 [0.20639, 0.64446, 0.2303],
1245 [0.21183, 0.63756, 0.24538],
1246 [0.21771, 0.63057, 0.26052],
1247 [0.22381, 0.62348, 0.27565],
1248 [0.22992, 0.61632, 0.29071],
1249 [0.23593, 0.6091, 0.30574],
1250 [0.24162, 0.60182, 0.32064],
1251 [0.24693, 0.5945, 0.33543],
1252 [0.25184, 0.58716, 0.35008],
1253 [0.25622, 0.5798, 0.36459],
1254 [0.26011, 0.57242, 0.37897],
1255 [0.26346, 0.56501, 0.3932],
1256 [0.26624, 0.55762, 0.4073],
1257 [0.26846, 0.55021, 0.42127],
1258 [0.27013, 0.5428, 0.43513],
1259 [0.27122, 0.53539, 0.44886],
1260 [0.27173, 0.52798, 0.46247],
1261 [0.2717, 0.52057, 0.476],
1262 [0.27112, 0.51317, 0.48942],
1263 [0.26997, 0.50576, 0.50275],
1264 [0.26823, 0.49837, 0.516],
1265 [0.26598, 0.49096, 0.52919],
1266 [0.26316, 0.48352, 0.54228],
1267 [0.25982, 0.4761, 0.55529],
1268 [0.25594, 0.46864, 0.56822],
1269 [0.25162, 0.46117, 0.58105],
1270 [0.2468, 0.45365, 0.5938],
1271 [0.24161, 0.44609, 0.60643],
1272 [0.23605, 0.43849, 0.61894],
1273 [0.23017, 0.43081, 0.63131],
1274 [0.2241, 0.42303, 0.64353],
1275 [0.21793, 0.41517, 0.6556],
1276 [0.2117, 0.40718, 0.66749],
1277 [0.2055, 0.39906, 0.67919],
1278 [0.19945, 0.39079, 0.6907],
1279 [0.19367, 0.38234, 0.70201],
1280 [0.18818, 0.37372, 0.71312],
1281 [0.183, 0.36488, 0.72404],
1282 [0.17829, 0.35585, 0.73477],
1283 [0.17392, 0.34657, 0.7453],
1284 [0.16999, 0.33707, 0.75566],
1285 [0.16639, 0.32732, 0.76586],
1286 [0.16312, 0.31735, 0.7759],
1287 [0.16005, 0.30712, 0.78581],
1288 [0.15724, 0.29667, 0.79557],
1289 [0.15457, 0.28595, 0.80522],
1290 [0.15202, 0.27505, 0.81474],
1291 [0.14966, 0.26395, 0.82414],
1292 [0.14744, 0.25264, 0.8334],
1293 [0.14554, 0.24118, 0.84252],
1294 [0.14402, 0.2296, 0.85145],
1295 [0.14312, 0.218, 0.86019],
1296 [0.14305, 0.20639, 0.86869],
1297 [0.14404, 0.19481, 0.87691],
1298 [0.1463, 0.18336, 0.88484],
1299 [0.15007, 0.17219, 0.89241],
1300 [0.15537, 0.1614, 0.8996],
1301 [0.1623, 0.15103, 0.90637],
1302 [0.17075, 0.14136, 0.9127],
1303 [0.18062, 0.13244, 0.91856],
1304 [0.19173, 0.12446, 0.92396],
1305 [0.20389, 0.11765, 0.92889],
1306 [0.21681, 0.11214, 0.93335],
1307 [0.23028, 0.10794, 0.93739],
1308 [0.24417, 0.10525, 0.94101],
1309 [0.25828, 0.10403, 0.94425],
1310 [0.27246, 0.10417, 0.94716],
1311 [0.28659, 0.1056, 0.94977],
1312 [0.30059, 0.10807, 0.95212],
1313 [0.3144, 0.11153, 0.95426],
1314 [0.32796, 0.11565, 0.95622],
1315 [0.34126, 0.12031, 0.95803],
1316 [0.35426, 0.12544, 0.95973],
1317 [0.36698, 0.13084, 0.96134],
1318 [0.37942, 0.13637, 0.96288],
1319 [0.3916, 0.1421, 0.96436],
1320 [0.40352, 0.14786, 0.96581],
1321 [0.4152, 0.15363, 0.96722],
1322 [0.42669, 0.15941, 0.9686],
1323 [0.43799, 0.16515, 0.96996],
1324 [0.44913, 0.17088, 0.97129],
1325 [0.46013, 0.1765, 0.97261],
1326 [0.47106, 0.18204, 0.97389],
1327 [0.48191, 0.18751, 0.97514],
1328 [0.49273, 0.1928, 0.97635],
1329 [0.50357, 0.19798, 0.97752],
1330 [0.51446, 0.20302, 0.97863],
1331 [0.52541, 0.2079, 0.97969],
1332 [0.53647, 0.21259, 0.98067],
1333 [0.54767, 0.21709, 0.98157],
1334 [0.55903, 0.22137, 0.98238],
1335 [0.57057, 0.22542, 0.9831],
1336 [0.5823, 0.22925, 0.98372],
1337 [0.59423, 0.23284, 0.98424],
1338 [0.60636, 0.23623, 0.98465],
1339 [0.61868, 0.23935, 0.98497],
1340 [0.63116, 0.24227, 0.98518],
1341 [0.64379, 0.24496, 0.9853],
1342 [0.65656, 0.2475, 0.98533],
1343 [0.66943, 0.24982, 0.98527],
1344 [0.68237, 0.25203, 0.98515],
1345 [0.69537, 0.25408, 0.98496],
1346 [0.70839, 0.25601, 0.98471],
1347 [0.72139, 0.25786, 0.98441],
1348 [0.73437, 0.25968, 0.98405],
1349 [0.74728, 0.26143, 0.98365],
1350 [0.76012, 0.26319, 0.98321],
1351 [0.77286, 0.26494, 0.98271],
1352 [0.78548, 0.26676, 0.98216],
1353 [0.79794, 0.26867, 0.98153],
1354 [0.81023, 0.27069, 0.98082],
1355 [0.82233, 0.27285, 0.98001],
1356 [0.83418, 0.27525, 0.97905],
1357 [0.84576, 0.27791, 0.97793],
1358 [0.85702, 0.28089, 0.97661],
1359 [0.86794, 0.2843, 0.97504],
1360 [0.87845, 0.28819, 0.97317],
1361 [0.88852, 0.29263, 0.97097],
1362 [0.8981, 0.29768, 0.96837],
1363 [0.90717, 0.3034, 0.96533],
1364 [0.91567, 0.30984, 0.96182],
1365 [0.92361, 0.317, 0.9578],
1366 [0.93095, 0.32489, 0.95323],
1367 ]
1368 b_cyclic_mygbm_30_95_c78 = bokeh_palette('cyclic_mygbm_30_95_c78',cyclic_mygbm_30_95_c78)
1369 m_cyclic_mygbm_30_95_c78 = mpl_cm('cyclic_mygbm_30_95_c78',cyclic_mygbm_30_95_c78)
1370 m_cyclic_mygbm_30_95_c78_r = mpl_cm('cyclic_mygbm_30_95_c78_r',list(reversed(cyclic_mygbm_30_95_c78)))
1371
1372
1373
1374
1375 cyclic_mygbm_30_95_c78_s25 = [\
1376 [0.18062, 0.13244, 0.91856],
1377 [0.19173, 0.12446, 0.92396],
1378 [0.20389, 0.11765, 0.92889],
1379 [0.21681, 0.11214, 0.93335],
1380 [0.23028, 0.10794, 0.93739],
1381 [0.24417, 0.10525, 0.94101],
1382 [0.25828, 0.10403, 0.94425],
1383 [0.27246, 0.10417, 0.94716],
1384 [0.28659, 0.1056, 0.94977],
1385 [0.30059, 0.10807, 0.95212],
1386 [0.3144, 0.11153, 0.95426],
1387 [0.32796, 0.11565, 0.95622],
1388 [0.34126, 0.12031, 0.95803],
1389 [0.35426, 0.12544, 0.95973],
1390 [0.36698, 0.13084, 0.96134],
1391 [0.37942, 0.13637, 0.96288],
1392 [0.3916, 0.1421, 0.96436],
1393 [0.40352, 0.14786, 0.96581],
1394 [0.4152, 0.15363, 0.96722],
1395 [0.42669, 0.15941, 0.9686],
1396 [0.43799, 0.16515, 0.96996],
1397 [0.44913, 0.17088, 0.97129],
1398 [0.46013, 0.1765, 0.97261],
1399 [0.47106, 0.18204, 0.97389],
1400 [0.48191, 0.18751, 0.97514],
1401 [0.49273, 0.1928, 0.97635],
1402 [0.50357, 0.19798, 0.97752],
1403 [0.51446, 0.20302, 0.97863],
1404 [0.52541, 0.2079, 0.97969],
1405 [0.53647, 0.21259, 0.98067],
1406 [0.54767, 0.21709, 0.98157],
1407 [0.55903, 0.22137, 0.98238],
1408 [0.57057, 0.22542, 0.9831],
1409 [0.5823, 0.22925, 0.98372],
1410 [0.59423, 0.23284, 0.98424],
1411 [0.60636, 0.23623, 0.98465],
1412 [0.61868, 0.23935, 0.98497],
1413 [0.63116, 0.24227, 0.98518],
1414 [0.64379, 0.24496, 0.9853],
1415 [0.65656, 0.2475, 0.98533],
1416 [0.66943, 0.24982, 0.98527],
1417 [0.68237, 0.25203, 0.98515],
1418 [0.69537, 0.25408, 0.98496],
1419 [0.70839, 0.25601, 0.98471],
1420 [0.72139, 0.25786, 0.98441],
1421 [0.73437, 0.25968, 0.98405],
1422 [0.74728, 0.26143, 0.98365],
1423 [0.76012, 0.26319, 0.98321],
1424 [0.77286, 0.26494, 0.98271],
1425 [0.78548, 0.26676, 0.98216],
1426 [0.79794, 0.26867, 0.98153],
1427 [0.81023, 0.27069, 0.98082],
1428 [0.82233, 0.27285, 0.98001],
1429 [0.83418, 0.27525, 0.97905],
1430 [0.84576, 0.27791, 0.97793],
1431 [0.85702, 0.28089, 0.97661],
1432 [0.86794, 0.2843, 0.97504],
1433 [0.87845, 0.28819, 0.97317],
1434 [0.88852, 0.29263, 0.97097],
1435 [0.8981, 0.29768, 0.96837],
1436 [0.90717, 0.3034, 0.96533],
1437 [0.91567, 0.30984, 0.96182],
1438 [0.92361, 0.317, 0.9578],
1439 [0.93095, 0.32489, 0.95323],
1440 [0.93769, 0.33352, 0.94809],
1441 [0.94383, 0.34283, 0.94239],
1442 [0.94939, 0.35275, 0.93613],
1443 [0.95439, 0.36323, 0.92931],
1444 [0.95886, 0.37422, 0.92198],
1445 [0.96283, 0.38558, 0.91416],
1446 [0.96634, 0.39727, 0.90588],
1447 [0.96944, 0.40921, 0.89721],
1448 [0.97216, 0.4213, 0.88817],
1449 [0.97454, 0.4335, 0.87883],
1450 [0.97663, 0.44573, 0.86923],
1451 [0.97845, 0.45797, 0.8594],
1452 [0.98004, 0.47017, 0.84939],
1453 [0.98142, 0.48228, 0.83922],
1454 [0.98262, 0.4943, 0.82894],
1455 [0.98364, 0.5062, 0.81854],
1456 [0.98453, 0.51799, 0.80808],
1457 [0.98527, 0.52964, 0.79753],
1458 [0.98588, 0.54116, 0.78694],
1459 [0.98637, 0.55255, 0.77629],
1460 [0.98676, 0.56382, 0.76559],
1461 [0.98704, 0.57494, 0.75486],
1462 [0.98722, 0.58595, 0.74407],
1463 [0.98733, 0.59683, 0.73326],
1464 [0.98736, 0.60758, 0.72241],
1465 [0.98732, 0.61821, 0.71153],
1466 [0.98723, 0.62871, 0.7006],
1467 [0.9871, 0.63909, 0.68965],
1468 [0.98694, 0.64936, 0.67864],
1469 [0.98677, 0.65949, 0.66762],
1470 [0.9866, 0.6695, 0.65654],
1471 [0.98644, 0.67938, 0.64543],
1472 [0.9863, 0.68916, 0.63428],
1473 [0.98621, 0.69879, 0.62309],
1474 [0.98616, 0.70831, 0.61184],
1475 [0.98617, 0.71772, 0.60055],
1476 [0.98624, 0.727, 0.5892],
1477 [0.98636, 0.73618, 0.57779],
1478 [0.98653, 0.74526, 0.56632],
1479 [0.98675, 0.75426, 0.55476],
1480 [0.98702, 0.76315, 0.54311],
1481 [0.98731, 0.77198, 0.53134],
1482 [0.98761, 0.78074, 0.51946],
1483 [0.98792, 0.78944, 0.50744],
1484 [0.9882, 0.79807, 0.49526],
1485 [0.98845, 0.80666, 0.48291],
1486 [0.98864, 0.81518, 0.47039],
1487 [0.98875, 0.82365, 0.45765],
1488 [0.98875, 0.83206, 0.4447],
1489 [0.98863, 0.84039, 0.43151],
1490 [0.98834, 0.84863, 0.41804],
1491 [0.98786, 0.85677, 0.40433],
1492 [0.98715, 0.86476, 0.39033],
1493 [0.98616, 0.87259, 0.37607],
1494 [0.98485, 0.8802, 0.36152],
1495 [0.98316, 0.88754, 0.3467],
1496 [0.98105, 0.89458, 0.33163],
1497 [0.97845, 0.90123, 0.31637],
1498 [0.97534, 0.90744, 0.30092],
1499 [0.97166, 0.91315, 0.28537],
1500 [0.96737, 0.91831, 0.26983],
1501 [0.96244, 0.92285, 0.25432],
1502 [0.95686, 0.92672, 0.23895],
1503 [0.95064, 0.9299, 0.22388],
1504 [0.94377, 0.93236, 0.2092],
1505 [0.93628, 0.9341, 0.19506],
1506 [0.9282, 0.93512, 0.18153],
1507 [0.91959, 0.93544, 0.16884],
1508 [0.91047, 0.9351, 0.15697],
1509 [0.90091, 0.93414, 0.1461],
1510 [0.89097, 0.93263, 0.13623],
1511 [0.8807, 0.93061, 0.12747],
1512 [0.87014, 0.92815, 0.11977],
1513 [0.85937, 0.92531, 0.11315],
1514 [0.8484, 0.92216, 0.10742],
1515 [0.83729, 0.91874, 0.10257],
1516 [0.82605, 0.91511, 0.098502],
1517 [0.81472, 0.91132, 0.095091],
1518 [0.80332, 0.90739, 0.092162],
1519 [0.79187, 0.90336, 0.089659],
1520 [0.78036, 0.89925, 0.087518],
1521 [0.76881, 0.89508, 0.08551],
1522 [0.75723, 0.89086, 0.083837],
1523 [0.74562, 0.88662, 0.082243],
1524 [0.73398, 0.88235, 0.080673],
1525 [0.7223, 0.87807, 0.079194],
1526 [0.7106, 0.87376, 0.077792],
1527 [0.69886, 0.86946, 0.076415],
1528 [0.6871, 0.86514, 0.075063],
1529 [0.67529, 0.86082, 0.073757],
1530 [0.66346, 0.85649, 0.072319],
1531 [0.65156, 0.85215, 0.071005],
1532 [0.63963, 0.8478, 0.069678],
1533 [0.62764, 0.84345, 0.068313],
1534 [0.6156, 0.83909, 0.066946],
1535 [0.60351, 0.83473, 0.065602],
1536 [0.59134, 0.83035, 0.064284],
1537 [0.57911, 0.82597, 0.063016],
1538 [0.56681, 0.82158, 0.061599],
1539 [0.55443, 0.81718, 0.060374],
1540 [0.54195, 0.81278, 0.059088],
1541 [0.5294, 0.80837, 0.057695],
1542 [0.51672, 0.80395, 0.056522],
1543 [0.50395, 0.79952, 0.055189],
1544 [0.49106, 0.79508, 0.053903],
1545 [0.47801, 0.79064, 0.052644],
1546 [0.46484, 0.78619, 0.051424],
1547 [0.45151, 0.78173, 0.050257],
1548 [0.43803, 0.77726, 0.04922],
1549 [0.42437, 0.77277, 0.04812],
1550 [0.41056, 0.76827, 0.047322],
1551 [0.39656, 0.76375, 0.04674],
1552 [0.38239, 0.75922, 0.046427],
1553 [0.36808, 0.75466, 0.046596],
1554 [0.35361, 0.75006, 0.047299],
1555 [0.33906, 0.74543, 0.04874],
1556 [0.32443, 0.74075, 0.050897],
1557 [0.30984, 0.73602, 0.054069],
1558 [0.29532, 0.73122, 0.058336],
1559 [0.28105, 0.72634, 0.063783],
1560 [0.26717, 0.72137, 0.070322],
1561 [0.25387, 0.71631, 0.077992],
1562 [0.24134, 0.71112, 0.08687],
1563 [0.22981, 0.7058, 0.096608],
1564 [0.21961, 0.70035, 0.10741],
1565 [0.21092, 0.69475, 0.11899],
1566 [0.204, 0.68901, 0.13129],
1567 [0.19894, 0.6831, 0.14422],
1568 [0.19593, 0.67703, 0.15768],
1569 [0.19486, 0.67081, 0.17161],
1570 [0.1956, 0.66443, 0.18594],
1571 [0.19795, 0.65791, 0.2005],
1572 [0.20163, 0.65125, 0.21533],
1573 [0.20639, 0.64446, 0.2303],
1574 [0.21183, 0.63756, 0.24538],
1575 [0.21771, 0.63057, 0.26052],
1576 [0.22381, 0.62348, 0.27565],
1577 [0.22992, 0.61632, 0.29071],
1578 [0.23593, 0.6091, 0.30574],
1579 [0.24162, 0.60182, 0.32064],
1580 [0.24693, 0.5945, 0.33543],
1581 [0.25184, 0.58716, 0.35008],
1582 [0.25622, 0.5798, 0.36459],
1583 [0.26011, 0.57242, 0.37897],
1584 [0.26346, 0.56501, 0.3932],
1585 [0.26624, 0.55762, 0.4073],
1586 [0.26846, 0.55021, 0.42127],
1587 [0.27013, 0.5428, 0.43513],
1588 [0.27122, 0.53539, 0.44886],
1589 [0.27173, 0.52798, 0.46247],
1590 [0.2717, 0.52057, 0.476],
1591 [0.27112, 0.51317, 0.48942],
1592 [0.26997, 0.50576, 0.50275],
1593 [0.26823, 0.49837, 0.516],
1594 [0.26598, 0.49096, 0.52919],
1595 [0.26316, 0.48352, 0.54228],
1596 [0.25982, 0.4761, 0.55529],
1597 [0.25594, 0.46864, 0.56822],
1598 [0.25162, 0.46117, 0.58105],
1599 [0.2468, 0.45365, 0.5938],
1600 [0.24161, 0.44609, 0.60643],
1601 [0.23605, 0.43849, 0.61894],
1602 [0.23017, 0.43081, 0.63131],
1603 [0.2241, 0.42303, 0.64353],
1604 [0.21793, 0.41517, 0.6556],
1605 [0.2117, 0.40718, 0.66749],
1606 [0.2055, 0.39906, 0.67919],
1607 [0.19945, 0.39079, 0.6907],
1608 [0.19367, 0.38234, 0.70201],
1609 [0.18818, 0.37372, 0.71312],
1610 [0.183, 0.36488, 0.72404],
1611 [0.17829, 0.35585, 0.73477],
1612 [0.17392, 0.34657, 0.7453],
1613 [0.16999, 0.33707, 0.75566],
1614 [0.16639, 0.32732, 0.76586],
1615 [0.16312, 0.31735, 0.7759],
1616 [0.16005, 0.30712, 0.78581],
1617 [0.15724, 0.29667, 0.79557],
1618 [0.15457, 0.28595, 0.80522],
1619 [0.15202, 0.27505, 0.81474],
1620 [0.14966, 0.26395, 0.82414],
1621 [0.14744, 0.25264, 0.8334],
1622 [0.14554, 0.24118, 0.84252],
1623 [0.14402, 0.2296, 0.85145],
1624 [0.14312, 0.218, 0.86019],
1625 [0.14305, 0.20639, 0.86869],
1626 [0.14404, 0.19481, 0.87691],
1627 [0.1463, 0.18336, 0.88484],
1628 [0.15007, 0.17219, 0.89241],
1629 [0.15537, 0.1614, 0.8996],
1630 [0.1623, 0.15103, 0.90637],
1631 [0.17075, 0.14136, 0.9127],
1632 ]
1633 b_cyclic_mygbm_30_95_c78_s25 = bokeh_palette('cyclic_mygbm_30_95_c78_s25',cyclic_mygbm_30_95_c78_s25)
1634 m_cyclic_mygbm_30_95_c78_s25 = mpl_cm('cyclic_mygbm_30_95_c78_s25',cyclic_mygbm_30_95_c78_s25)
1635 m_cyclic_mygbm_30_95_c78_s25_r = mpl_cm('cyclic_mygbm_30_95_c78_s25_r',list(reversed(cyclic_mygbm_30_95_c78_s25)))
1636 colorwheel = b_cyclic_mygbm_30_95_c78_s25
1637 m_colorwheel = m_cyclic_mygbm_30_95_c78_s25
1638 m_colorwheel_r = m_cyclic_mygbm_30_95_c78_s25_r
1639 palette['colorwheel'] = b_cyclic_mygbm_30_95_c78_s25
1640 cm['colorwheel'] = m_cyclic_mygbm_30_95_c78_s25
1641 cm['colorwheel_r'] = m_cyclic_mygbm_30_95_c78_s25_r
1642 register_cmap('cet_colorwheel',m_cyclic_mygbm_30_95_c78_s25)
1643 register_cmap('cet_colorwheel_r',m_cyclic_mygbm_30_95_c78_s25_r)
1644
1645
1646
1647
1648 cyclic_wrwbw_40_90_c42 = [\
1649 [0.873, 0.83593, 0.84864],
1650 [0.8777, 0.8339, 0.84071],
1651 [0.88194, 0.83075, 0.832],
1652 [0.88572, 0.82651, 0.82253],
1653 [0.88906, 0.82126, 0.81236],
1654 [0.89199, 0.81507, 0.80154],
1655 [0.89451, 0.80802, 0.79013],
1656 [0.89666, 0.80023, 0.77819],
1657 [0.89847, 0.79178, 0.76581],
1658 [0.89996, 0.78278, 0.75305],
1659 [0.90116, 0.77331, 0.73999],
1660 [0.9021, 0.76347, 0.72667],
1661 [0.9028, 0.75332, 0.71316],
1662 [0.90327, 0.74294, 0.69952],
1663 [0.90355, 0.73237, 0.68579],
1664 [0.90363, 0.72166, 0.67199],
1665 [0.90355, 0.71085, 0.65815],
1666 [0.9033, 0.69996, 0.64429],
1667 [0.90289, 0.68903, 0.63046],
1668 [0.90234, 0.67804, 0.61663],
1669 [0.90165, 0.66702, 0.60282],
1670 [0.90082, 0.65598, 0.58904],
1671 [0.89986, 0.64492, 0.57531],
1672 [0.89877, 0.63386, 0.56162],
1673 [0.89757, 0.62278, 0.54797],
1674 [0.89623, 0.61169, 0.53437],
1675 [0.89478, 0.60058, 0.52081],
1676 [0.8932, 0.58945, 0.5073],
1677 [0.89151, 0.57831, 0.49383],
1678 [0.8897, 0.56715, 0.48041],
1679 [0.88777, 0.55595, 0.46704],
1680 [0.88574, 0.54474, 0.4537],
1681 [0.88359, 0.53349, 0.44042],
1682 [0.88134, 0.52221, 0.42718],
1683 [0.87897, 0.5109, 0.41398],
1684 [0.87649, 0.49954, 0.40083],
1685 [0.87391, 0.48816, 0.3877],
1686 [0.87123, 0.4767, 0.37464],
1687 [0.86845, 0.4652, 0.3616],
1688 [0.86556, 0.45364, 0.34861],
1689 [0.86257, 0.44202, 0.33566],
1690 [0.85948, 0.43032, 0.32274],
1691 [0.8563, 0.41853, 0.30985],
1692 [0.85302, 0.40666, 0.29699],
1693 [0.84965, 0.3947, 0.28415],
1694 [0.84618, 0.38265, 0.27137],
1695 [0.84264, 0.3705, 0.25865],
1696 [0.83901, 0.35827, 0.24597],
1697 [0.83532, 0.34594, 0.23336],
1698 [0.83157, 0.33356, 0.22089],
1699 [0.82777, 0.3211, 0.20848],
1700 [0.82395, 0.30862, 0.19626],
1701 [0.82013, 0.29614, 0.1842],
1702 [0.81634, 0.28375, 0.17242],
1703 [0.81259, 0.2715, 0.16099],
1704 [0.80896, 0.25953, 0.14996],
1705 [0.80546, 0.24792, 0.1394],
1706 [0.80217, 0.23683, 0.12955],
1707 [0.79914, 0.22645, 0.1204],
1708 [0.7964, 0.21697, 0.11224],
1709 [0.79405, 0.20862, 0.10504],
1710 [0.79209, 0.20162, 0.099146],
1711 [0.79061, 0.19625, 0.094653],
1712 [0.78962, 0.19261, 0.091622],
1713 [0.78916, 0.19089, 0.090163],
1714 [0.78923, 0.19116, 0.09039],
1715 [0.78984, 0.19342, 0.092261],
1716 [0.79096, 0.19754, 0.095704],
1717 [0.79258, 0.20339, 0.10062],
1718 [0.79465, 0.21076, 0.10693],
1719 [0.79711, 0.21943, 0.11431],
1720 [0.79994, 0.22917, 0.12278],
1721 [0.80304, 0.23975, 0.13216],
1722 [0.8064, 0.251, 0.14222],
1723 [0.80993, 0.26273, 0.15286],
1724 [0.81359, 0.27479, 0.16406],
1725 [0.81735, 0.28707, 0.17556],
1726 [0.82116, 0.29951, 0.18745],
1727 [0.82498, 0.31196, 0.1995],
1728 [0.8288, 0.32444, 0.21181],
1729 [0.83258, 0.33689, 0.2242],
1730 [0.83632, 0.34927, 0.23677],
1731 [0.84, 0.36157, 0.24937],
1732 [0.84359, 0.37378, 0.26206],
1733 [0.84712, 0.38589, 0.27479],
1734 [0.85056, 0.39792, 0.28758],
1735 [0.8539, 0.40986, 0.30042],
1736 [0.85716, 0.42169, 0.3133],
1737 [0.86032, 0.43345, 0.32618],
1738 [0.86338, 0.44514, 0.33913],
1739 [0.86634, 0.45674, 0.35208],
1740 [0.8692, 0.46829, 0.36509],
1741 [0.87196, 0.47978, 0.37813],
1742 [0.87462, 0.49122, 0.39122],
1743 [0.87716, 0.50259, 0.40434],
1744 [0.87961, 0.51395, 0.41751],
1745 [0.88195, 0.52525, 0.43072],
1746 [0.88418, 0.53652, 0.44398],
1747 [0.8863, 0.54775, 0.45727],
1748 [0.8883, 0.55896, 0.47062],
1749 [0.89019, 0.57014, 0.484],
1750 [0.89197, 0.5813, 0.49745],
1751 [0.89363, 0.59245, 0.51092],
1752 [0.89518, 0.60356, 0.52444],
1753 [0.8966, 0.61466, 0.53802],
1754 [0.8979, 0.62575, 0.55163],
1755 [0.89908, 0.63683, 0.56528],
1756 [0.90012, 0.64788, 0.579],
1757 [0.90103, 0.65892, 0.59275],
1758 [0.9018, 0.66994, 0.60654],
1759 [0.90242, 0.6809, 0.62037],
1760 [0.90287, 0.69183, 0.63422],
1761 [0.90316, 0.70268, 0.64808],
1762 [0.90325, 0.71344, 0.66197],
1763 [0.90314, 0.72408, 0.67583],
1764 [0.9028, 0.73456, 0.68967],
1765 [0.9022, 0.74481, 0.70344],
1766 [0.90131, 0.7548, 0.71713],
1767 [0.90011, 0.76443, 0.73066],
1768 [0.89855, 0.77364, 0.74401],
1769 [0.8966, 0.78234, 0.75711],
1770 [0.89423, 0.79041, 0.7699],
1771 [0.8914, 0.79778, 0.7823],
1772 [0.88809, 0.80433, 0.79423],
1773 [0.88427, 0.80997, 0.80561],
1774 [0.87992, 0.81463, 0.8164],
1775 [0.87505, 0.81822, 0.8265],
1776 [0.86966, 0.82071, 0.83587],
1777 [0.86376, 0.82205, 0.84446],
1778 [0.85737, 0.82224, 0.85225],
1779 [0.85052, 0.8213, 0.85923],
1780 [0.84325, 0.81927, 0.8654],
1781 [0.8356, 0.81621, 0.87079],
1782 [0.8276, 0.81219, 0.87544],
1783 [0.81931, 0.80731, 0.8794],
1784 [0.81075, 0.80165, 0.88274],
1785 [0.80198, 0.79534, 0.88552],
1786 [0.79302, 0.78846, 0.88781],
1787 [0.7839, 0.78111, 0.88969],
1788 [0.77463, 0.77338, 0.89122],
1789 [0.76527, 0.76536, 0.89246],
1790 [0.75579, 0.75709, 0.89345],
1791 [0.74622, 0.74866, 0.89427],
1792 [0.73657, 0.7401, 0.89494],
1793 [0.72685, 0.73145, 0.89549],
1794 [0.71705, 0.72274, 0.89595],
1795 [0.70717, 0.71401, 0.89635],
1796 [0.69722, 0.70526, 0.89669],
1797 [0.68719, 0.69651, 0.89699],
1798 [0.67709, 0.68776, 0.89726],
1799 [0.66689, 0.67902, 0.8975],
1800 [0.65663, 0.67032, 0.89772],
1801 [0.64625, 0.66163, 0.89792],
1802 [0.63579, 0.65297, 0.89811],
1803 [0.62522, 0.64434, 0.89828],
1804 [0.61453, 0.63573, 0.89844],
1805 [0.60375, 0.62715, 0.89859],
1806 [0.59283, 0.6186, 0.89872],
1807 [0.58178, 0.61007, 0.89884],
1808 [0.57059, 0.60157, 0.89894],
1809 [0.55925, 0.59311, 0.89902],
1810 [0.54776, 0.58467, 0.8991],
1811 [0.53609, 0.57626, 0.89915],
1812 [0.52424, 0.56787, 0.8992],
1813 [0.51219, 0.55952, 0.89923],
1814 [0.49993, 0.5512, 0.89925],
1815 [0.48745, 0.54291, 0.89925],
1816 [0.47471, 0.53465, 0.89924],
1817 [0.46169, 0.52643, 0.89922],
1818 [0.44837, 0.51823, 0.89918],
1819 [0.43473, 0.51007, 0.89913],
1820 [0.42073, 0.50196, 0.89907],
1821 [0.40637, 0.49389, 0.899],
1822 [0.39159, 0.48588, 0.89891],
1823 [0.37638, 0.47795, 0.89881],
1824 [0.36067, 0.47012, 0.8987],
1825 [0.34449, 0.46237, 0.89858],
1826 [0.32777, 0.45477, 0.89845],
1827 [0.31053, 0.44731, 0.89832],
1828 [0.29269, 0.44007, 0.89817],
1829 [0.27432, 0.43307, 0.89802],
1830 [0.25544, 0.42636, 0.89787],
1831 [0.23609, 0.42002, 0.89772],
1832 [0.21638, 0.4141, 0.89757],
1833 [0.19647, 0.40866, 0.89743],
1834 [0.17659, 0.40379, 0.89729],
1835 [0.15722, 0.39953, 0.89717],
1836 [0.13894, 0.39598, 0.89707],
1837 [0.1226, 0.39316, 0.89698],
1838 [0.10959, 0.39116, 0.89692],
1839 [0.1011, 0.38996, 0.89689],
1840 [0.098617, 0.38962, 0.89687],
1841 [0.10246, 0.39014, 0.89689],
1842 [0.11205, 0.39152, 0.89693],
1843 [0.12596, 0.39371, 0.897],
1844 [0.14277, 0.39668, 0.89709],
1845 [0.16137, 0.40041, 0.8972],
1846 [0.18085, 0.40478, 0.89732],
1847 [0.20072, 0.4098, 0.89746],
1848 [0.22066, 0.41534, 0.8976],
1849 [0.24027, 0.42135, 0.89775],
1850 [0.25956, 0.42779, 0.89791],
1851 [0.27833, 0.43456, 0.89806],
1852 [0.29659, 0.44162, 0.8982],
1853 [0.31428, 0.44891, 0.89835],
1854 [0.33142, 0.45639, 0.89848],
1855 [0.34803, 0.46404, 0.89861],
1856 [0.3641, 0.4718, 0.89873],
1857 [0.37969, 0.47966, 0.89883],
1858 [0.39481, 0.48761, 0.89893],
1859 [0.40949, 0.49562, 0.89901],
1860 [0.42377, 0.5037, 0.89909],
1861 [0.4377, 0.51182, 0.89914],
1862 [0.45127, 0.51998, 0.89919],
1863 [0.46453, 0.52819, 0.89922],
1864 [0.47747, 0.53643, 0.89924],
1865 [0.49016, 0.54469, 0.89925],
1866 [0.50259, 0.55298, 0.89924],
1867 [0.51481, 0.56131, 0.89922],
1868 [0.52682, 0.56967, 0.89919],
1869 [0.53863, 0.57806, 0.89914],
1870 [0.55025, 0.58648, 0.89908],
1871 [0.56172, 0.59493, 0.89901],
1872 [0.57302, 0.60341, 0.89892],
1873 [0.58417, 0.61191, 0.89881],
1874 [0.59519, 0.62045, 0.89869],
1875 [0.60608, 0.629, 0.89856],
1876 [0.61685, 0.63759, 0.89841],
1877 [0.62751, 0.6462, 0.89825],
1878 [0.63805, 0.65483, 0.89807],
1879 [0.6485, 0.66351, 0.89788],
1880 [0.65884, 0.67219, 0.89767],
1881 [0.6691, 0.6809, 0.89745],
1882 [0.67927, 0.68965, 0.89721],
1883 [0.68936, 0.6984, 0.89695],
1884 [0.69935, 0.70719, 0.89668],
1885 [0.70928, 0.71598, 0.89638],
1886 [0.71911, 0.72477, 0.89605],
1887 [0.72887, 0.73355, 0.89569],
1888 [0.73854, 0.7423, 0.89528],
1889 [0.74812, 0.75101, 0.89481],
1890 [0.75759, 0.75963, 0.89427],
1891 [0.76695, 0.76815, 0.89362],
1892 [0.7762, 0.77652, 0.89286],
1893 [0.78529, 0.78468, 0.89193],
1894 [0.79422, 0.79255, 0.8908],
1895 [0.80295, 0.80008, 0.88943],
1896 [0.81147, 0.80717, 0.88775],
1897 [0.81973, 0.81373, 0.88571],
1898 [0.82771, 0.81967, 0.88323],
1899 [0.83537, 0.82487, 0.88026],
1900 [0.84268, 0.82926, 0.87672],
1901 [0.84961, 0.83271, 0.87256],
1902 [0.85612, 0.83516, 0.86771],
1903 [0.8622, 0.83654, 0.86213],
1904 [0.86783, 0.83681, 0.85578],
1905 ]
1906 b_cyclic_wrwbw_40_90_c42 = bokeh_palette('cyclic_wrwbw_40_90_c42',cyclic_wrwbw_40_90_c42)
1907 m_cyclic_wrwbw_40_90_c42 = mpl_cm('cyclic_wrwbw_40_90_c42',cyclic_wrwbw_40_90_c42)
1908 m_cyclic_wrwbw_40_90_c42_r = mpl_cm('cyclic_wrwbw_40_90_c42_r',list(reversed(cyclic_wrwbw_40_90_c42)))
1909
1910
1911
1912
1913 cyclic_wrwbw_40_90_c42_s25 = [\
1914 [0.10246, 0.39014, 0.89689],
1915 [0.11205, 0.39152, 0.89693],
1916 [0.12596, 0.39371, 0.897],
1917 [0.14277, 0.39668, 0.89709],
1918 [0.16137, 0.40041, 0.8972],
1919 [0.18085, 0.40478, 0.89732],
1920 [0.20072, 0.4098, 0.89746],
1921 [0.22066, 0.41534, 0.8976],
1922 [0.24027, 0.42135, 0.89775],
1923 [0.25956, 0.42779, 0.89791],
1924 [0.27833, 0.43456, 0.89806],
1925 [0.29659, 0.44162, 0.8982],
1926 [0.31428, 0.44891, 0.89835],
1927 [0.33142, 0.45639, 0.89848],
1928 [0.34803, 0.46404, 0.89861],
1929 [0.3641, 0.4718, 0.89873],
1930 [0.37969, 0.47966, 0.89883],
1931 [0.39481, 0.48761, 0.89893],
1932 [0.40949, 0.49562, 0.89901],
1933 [0.42377, 0.5037, 0.89909],
1934 [0.4377, 0.51182, 0.89914],
1935 [0.45127, 0.51998, 0.89919],
1936 [0.46453, 0.52819, 0.89922],
1937 [0.47747, 0.53643, 0.89924],
1938 [0.49016, 0.54469, 0.89925],
1939 [0.50259, 0.55298, 0.89924],
1940 [0.51481, 0.56131, 0.89922],
1941 [0.52682, 0.56967, 0.89919],
1942 [0.53863, 0.57806, 0.89914],
1943 [0.55025, 0.58648, 0.89908],
1944 [0.56172, 0.59493, 0.89901],
1945 [0.57302, 0.60341, 0.89892],
1946 [0.58417, 0.61191, 0.89881],
1947 [0.59519, 0.62045, 0.89869],
1948 [0.60608, 0.629, 0.89856],
1949 [0.61685, 0.63759, 0.89841],
1950 [0.62751, 0.6462, 0.89825],
1951 [0.63805, 0.65483, 0.89807],
1952 [0.6485, 0.66351, 0.89788],
1953 [0.65884, 0.67219, 0.89767],
1954 [0.6691, 0.6809, 0.89745],
1955 [0.67927, 0.68965, 0.89721],
1956 [0.68936, 0.6984, 0.89695],
1957 [0.69935, 0.70719, 0.89668],
1958 [0.70928, 0.71598, 0.89638],
1959 [0.71911, 0.72477, 0.89605],
1960 [0.72887, 0.73355, 0.89569],
1961 [0.73854, 0.7423, 0.89528],
1962 [0.74812, 0.75101, 0.89481],
1963 [0.75759, 0.75963, 0.89427],
1964 [0.76695, 0.76815, 0.89362],
1965 [0.7762, 0.77652, 0.89286],
1966 [0.78529, 0.78468, 0.89193],
1967 [0.79422, 0.79255, 0.8908],
1968 [0.80295, 0.80008, 0.88943],
1969 [0.81147, 0.80717, 0.88775],
1970 [0.81973, 0.81373, 0.88571],
1971 [0.82771, 0.81967, 0.88323],
1972 [0.83537, 0.82487, 0.88026],
1973 [0.84268, 0.82926, 0.87672],
1974 [0.84961, 0.83271, 0.87256],
1975 [0.85612, 0.83516, 0.86771],
1976 [0.8622, 0.83654, 0.86213],
1977 [0.86783, 0.83681, 0.85578],
1978 [0.873, 0.83593, 0.84864],
1979 [0.8777, 0.8339, 0.84071],
1980 [0.88194, 0.83075, 0.832],
1981 [0.88572, 0.82651, 0.82253],
1982 [0.88906, 0.82126, 0.81236],
1983 [0.89199, 0.81507, 0.80154],
1984 [0.89451, 0.80802, 0.79013],
1985 [0.89666, 0.80023, 0.77819],
1986 [0.89847, 0.79178, 0.76581],
1987 [0.89996, 0.78278, 0.75305],
1988 [0.90116, 0.77331, 0.73999],
1989 [0.9021, 0.76347, 0.72667],
1990 [0.9028, 0.75332, 0.71316],
1991 [0.90327, 0.74294, 0.69952],
1992 [0.90355, 0.73237, 0.68579],
1993 [0.90363, 0.72166, 0.67199],
1994 [0.90355, 0.71085, 0.65815],
1995 [0.9033, 0.69996, 0.64429],
1996 [0.90289, 0.68903, 0.63046],
1997 [0.90234, 0.67804, 0.61663],
1998 [0.90165, 0.66702, 0.60282],
1999 [0.90082, 0.65598, 0.58904],
2000 [0.89986, 0.64492, 0.57531],
2001 [0.89877, 0.63386, 0.56162],
2002 [0.89757, 0.62278, 0.54797],
2003 [0.89623, 0.61169, 0.53437],
2004 [0.89478, 0.60058, 0.52081],
2005 [0.8932, 0.58945, 0.5073],
2006 [0.89151, 0.57831, 0.49383],
2007 [0.8897, 0.56715, 0.48041],
2008 [0.88777, 0.55595, 0.46704],
2009 [0.88574, 0.54474, 0.4537],
2010 [0.88359, 0.53349, 0.44042],
2011 [0.88134, 0.52221, 0.42718],
2012 [0.87897, 0.5109, 0.41398],
2013 [0.87649, 0.49954, 0.40083],
2014 [0.87391, 0.48816, 0.3877],
2015 [0.87123, 0.4767, 0.37464],
2016 [0.86845, 0.4652, 0.3616],
2017 [0.86556, 0.45364, 0.34861],
2018 [0.86257, 0.44202, 0.33566],
2019 [0.85948, 0.43032, 0.32274],
2020 [0.8563, 0.41853, 0.30985],
2021 [0.85302, 0.40666, 0.29699],
2022 [0.84965, 0.3947, 0.28415],
2023 [0.84618, 0.38265, 0.27137],
2024 [0.84264, 0.3705, 0.25865],
2025 [0.83901, 0.35827, 0.24597],
2026 [0.83532, 0.34594, 0.23336],
2027 [0.83157, 0.33356, 0.22089],
2028 [0.82777, 0.3211, 0.20848],
2029 [0.82395, 0.30862, 0.19626],
2030 [0.82013, 0.29614, 0.1842],
2031 [0.81634, 0.28375, 0.17242],
2032 [0.81259, 0.2715, 0.16099],
2033 [0.80896, 0.25953, 0.14996],
2034 [0.80546, 0.24792, 0.1394],
2035 [0.80217, 0.23683, 0.12955],
2036 [0.79914, 0.22645, 0.1204],
2037 [0.7964, 0.21697, 0.11224],
2038 [0.79405, 0.20862, 0.10504],
2039 [0.79209, 0.20162, 0.099146],
2040 [0.79061, 0.19625, 0.094653],
2041 [0.78962, 0.19261, 0.091622],
2042 [0.78916, 0.19089, 0.090163],
2043 [0.78923, 0.19116, 0.09039],
2044 [0.78984, 0.19342, 0.092261],
2045 [0.79096, 0.19754, 0.095704],
2046 [0.79258, 0.20339, 0.10062],
2047 [0.79465, 0.21076, 0.10693],
2048 [0.79711, 0.21943, 0.11431],
2049 [0.79994, 0.22917, 0.12278],
2050 [0.80304, 0.23975, 0.13216],
2051 [0.8064, 0.251, 0.14222],
2052 [0.80993, 0.26273, 0.15286],
2053 [0.81359, 0.27479, 0.16406],
2054 [0.81735, 0.28707, 0.17556],
2055 [0.82116, 0.29951, 0.18745],
2056 [0.82498, 0.31196, 0.1995],
2057 [0.8288, 0.32444, 0.21181],
2058 [0.83258, 0.33689, 0.2242],
2059 [0.83632, 0.34927, 0.23677],
2060 [0.84, 0.36157, 0.24937],
2061 [0.84359, 0.37378, 0.26206],
2062 [0.84712, 0.38589, 0.27479],
2063 [0.85056, 0.39792, 0.28758],
2064 [0.8539, 0.40986, 0.30042],
2065 [0.85716, 0.42169, 0.3133],
2066 [0.86032, 0.43345, 0.32618],
2067 [0.86338, 0.44514, 0.33913],
2068 [0.86634, 0.45674, 0.35208],
2069 [0.8692, 0.46829, 0.36509],
2070 [0.87196, 0.47978, 0.37813],
2071 [0.87462, 0.49122, 0.39122],
2072 [0.87716, 0.50259, 0.40434],
2073 [0.87961, 0.51395, 0.41751],
2074 [0.88195, 0.52525, 0.43072],
2075 [0.88418, 0.53652, 0.44398],
2076 [0.8863, 0.54775, 0.45727],
2077 [0.8883, 0.55896, 0.47062],
2078 [0.89019, 0.57014, 0.484],
2079 [0.89197, 0.5813, 0.49745],
2080 [0.89363, 0.59245, 0.51092],
2081 [0.89518, 0.60356, 0.52444],
2082 [0.8966, 0.61466, 0.53802],
2083 [0.8979, 0.62575, 0.55163],
2084 [0.89908, 0.63683, 0.56528],
2085 [0.90012, 0.64788, 0.579],
2086 [0.90103, 0.65892, 0.59275],
2087 [0.9018, 0.66994, 0.60654],
2088 [0.90242, 0.6809, 0.62037],
2089 [0.90287, 0.69183, 0.63422],
2090 [0.90316, 0.70268, 0.64808],
2091 [0.90325, 0.71344, 0.66197],
2092 [0.90314, 0.72408, 0.67583],
2093 [0.9028, 0.73456, 0.68967],
2094 [0.9022, 0.74481, 0.70344],
2095 [0.90131, 0.7548, 0.71713],
2096 [0.90011, 0.76443, 0.73066],
2097 [0.89855, 0.77364, 0.74401],
2098 [0.8966, 0.78234, 0.75711],
2099 [0.89423, 0.79041, 0.7699],
2100 [0.8914, 0.79778, 0.7823],
2101 [0.88809, 0.80433, 0.79423],
2102 [0.88427, 0.80997, 0.80561],
2103 [0.87992, 0.81463, 0.8164],
2104 [0.87505, 0.81822, 0.8265],
2105 [0.86966, 0.82071, 0.83587],
2106 [0.86376, 0.82205, 0.84446],
2107 [0.85737, 0.82224, 0.85225],
2108 [0.85052, 0.8213, 0.85923],
2109 [0.84325, 0.81927, 0.8654],
2110 [0.8356, 0.81621, 0.87079],
2111 [0.8276, 0.81219, 0.87544],
2112 [0.81931, 0.80731, 0.8794],
2113 [0.81075, 0.80165, 0.88274],
2114 [0.80198, 0.79534, 0.88552],
2115 [0.79302, 0.78846, 0.88781],
2116 [0.7839, 0.78111, 0.88969],
2117 [0.77463, 0.77338, 0.89122],
2118 [0.76527, 0.76536, 0.89246],
2119 [0.75579, 0.75709, 0.89345],
2120 [0.74622, 0.74866, 0.89427],
2121 [0.73657, 0.7401, 0.89494],
2122 [0.72685, 0.73145, 0.89549],
2123 [0.71705, 0.72274, 0.89595],
2124 [0.70717, 0.71401, 0.89635],
2125 [0.69722, 0.70526, 0.89669],
2126 [0.68719, 0.69651, 0.89699],
2127 [0.67709, 0.68776, 0.89726],
2128 [0.66689, 0.67902, 0.8975],
2129 [0.65663, 0.67032, 0.89772],
2130 [0.64625, 0.66163, 0.89792],
2131 [0.63579, 0.65297, 0.89811],
2132 [0.62522, 0.64434, 0.89828],
2133 [0.61453, 0.63573, 0.89844],
2134 [0.60375, 0.62715, 0.89859],
2135 [0.59283, 0.6186, 0.89872],
2136 [0.58178, 0.61007, 0.89884],
2137 [0.57059, 0.60157, 0.89894],
2138 [0.55925, 0.59311, 0.89902],
2139 [0.54776, 0.58467, 0.8991],
2140 [0.53609, 0.57626, 0.89915],
2141 [0.52424, 0.56787, 0.8992],
2142 [0.51219, 0.55952, 0.89923],
2143 [0.49993, 0.5512, 0.89925],
2144 [0.48745, 0.54291, 0.89925],
2145 [0.47471, 0.53465, 0.89924],
2146 [0.46169, 0.52643, 0.89922],
2147 [0.44837, 0.51823, 0.89918],
2148 [0.43473, 0.51007, 0.89913],
2149 [0.42073, 0.50196, 0.89907],
2150 [0.40637, 0.49389, 0.899],
2151 [0.39159, 0.48588, 0.89891],
2152 [0.37638, 0.47795, 0.89881],
2153 [0.36067, 0.47012, 0.8987],
2154 [0.34449, 0.46237, 0.89858],
2155 [0.32777, 0.45477, 0.89845],
2156 [0.31053, 0.44731, 0.89832],
2157 [0.29269, 0.44007, 0.89817],
2158 [0.27432, 0.43307, 0.89802],
2159 [0.25544, 0.42636, 0.89787],
2160 [0.23609, 0.42002, 0.89772],
2161 [0.21638, 0.4141, 0.89757],
2162 [0.19647, 0.40866, 0.89743],
2163 [0.17659, 0.40379, 0.89729],
2164 [0.15722, 0.39953, 0.89717],
2165 [0.13894, 0.39598, 0.89707],
2166 [0.1226, 0.39316, 0.89698],
2167 [0.10959, 0.39116, 0.89692],
2168 [0.1011, 0.38996, 0.89689],
2169 [0.098617, 0.38962, 0.89687],
2170 ]
2171 b_cyclic_wrwbw_40_90_c42_s25 = bokeh_palette('cyclic_wrwbw_40_90_c42_s25',cyclic_wrwbw_40_90_c42_s25)
2172 m_cyclic_wrwbw_40_90_c42_s25 = mpl_cm('cyclic_wrwbw_40_90_c42_s25',cyclic_wrwbw_40_90_c42_s25)
2173 m_cyclic_wrwbw_40_90_c42_s25_r = mpl_cm('cyclic_wrwbw_40_90_c42_s25_r',list(reversed(cyclic_wrwbw_40_90_c42_s25)))
2174
2175
2176
2177
2178 diverging_isoluminant_cjm_75_c23 = [\
2179 [0, 0.78663, 1],
2180 [0, 0.78616, 0.99976],
2181 [0, 0.78569, 0.99755],
2182 [0, 0.78523, 0.99535],
2183 [0, 0.78477, 0.99315],
2184 [0, 0.7843, 0.99095],
2185 [0, 0.78383, 0.98875],
2186 [0.051263, 0.78336, 0.98655],
2187 [0.088344, 0.78289, 0.98435],
2188 [0.11524, 0.78243, 0.98215],
2189 [0.13723, 0.78197, 0.97995],
2190 [0.15612, 0.7815, 0.97775],
2191 [0.17285, 0.78103, 0.97555],
2192 [0.18805, 0.78056, 0.97335],
2193 [0.20194, 0.78009, 0.97116],
2194 [0.21488, 0.77962, 0.96896],
2195 [0.227, 0.77915, 0.96676],
2196 [0.23838, 0.77868, 0.96457],
2197 [0.24919, 0.77821, 0.96237],
2198 [0.25948, 0.77774, 0.96018],
2199 [0.26929, 0.77727, 0.95799],
2200 [0.27869, 0.7768, 0.9558],
2201 [0.28771, 0.77632, 0.9536],
2202 [0.29642, 0.77585, 0.95141],
2203 [0.30482, 0.77538, 0.94921],
2204 [0.31294, 0.7749, 0.94702],
2205 [0.32083, 0.77443, 0.94483],
2206 [0.32846, 0.77395, 0.94264],
2207 [0.33588, 0.77348, 0.94045],
2208 [0.3431, 0.77301, 0.93826],
2209 [0.35013, 0.77253, 0.93607],
2210 [0.357, 0.77206, 0.93388],
2211 [0.36367, 0.77159, 0.93169],
2212 [0.37021, 0.77111, 0.9295],
2213 [0.37662, 0.77063, 0.92732],
2214 [0.38287, 0.77015, 0.92513],
2215 [0.389, 0.76967, 0.92295],
2216 [0.395, 0.76919, 0.92075],
2217 [0.40089, 0.76872, 0.91857],
2218 [0.40666, 0.76824, 0.91639],
2219 [0.41233, 0.76776, 0.91421],
2220 [0.41789, 0.76728, 0.91202],
2221 [0.42335, 0.7668, 0.90984],
2222 [0.42874, 0.76632, 0.90765],
2223 [0.43402, 0.76584, 0.90547],
2224 [0.43922, 0.76537, 0.90329],
2225 [0.44436, 0.76488, 0.9011],
2226 [0.4494, 0.7644, 0.89892],
2227 [0.45436, 0.76391, 0.89674],
2228 [0.45926, 0.76343, 0.89456],
2229 [0.46409, 0.76295, 0.89238],
2230 [0.46884, 0.76246, 0.8902],
2231 [0.47352, 0.76198, 0.88802],
2232 [0.47815, 0.7615, 0.88584],
2233 [0.48272, 0.76101, 0.88366],
2234 [0.48724, 0.76053, 0.88148],
2235 [0.49169, 0.76004, 0.8793],
2236 [0.49607, 0.75955, 0.87712],
2237 [0.50042, 0.75907, 0.87495],
2238 [0.50472, 0.75859, 0.87277],
2239 [0.50896, 0.7581, 0.87059],
2240 [0.51314, 0.75761, 0.86842],
2241 [0.51729, 0.75712, 0.86624],
2242 [0.52138, 0.75663, 0.86407],
2243 [0.52543, 0.75614, 0.8619],
2244 [0.52945, 0.75565, 0.85972],
2245 [0.5334, 0.75517, 0.85754],
2246 [0.53734, 0.75468, 0.85537],
2247 [0.54121, 0.75418, 0.8532],
2248 [0.54506, 0.75369, 0.85102],
2249 [0.54887, 0.75319, 0.84885],
2250 [0.55263, 0.7527, 0.84668],
2251 [0.55635, 0.75221, 0.84451],
2252 [0.56005, 0.75172, 0.84234],
2253 [0.56372, 0.75123, 0.84017],
2254 [0.56734, 0.75074, 0.838],
2255 [0.57092, 0.75024, 0.83582],
2256 [0.57448, 0.74974, 0.83366],
2257 [0.57801, 0.74924, 0.83149],
2258 [0.58151, 0.74875, 0.82932],
2259 [0.58498, 0.74826, 0.82715],
2260 [0.5884, 0.74776, 0.82498],
2261 [0.59182, 0.74726, 0.82281],
2262 [0.59519, 0.74676, 0.82064],
2263 [0.59854, 0.74626, 0.81847],
2264 [0.60186, 0.74576, 0.81631],
2265 [0.60516, 0.74526, 0.81414],
2266 [0.60843, 0.74476, 0.81198],
2267 [0.61167, 0.74426, 0.80981],
2268 [0.61488, 0.74376, 0.80764],
2269 [0.61807, 0.74326, 0.80547],
2270 [0.62124, 0.74276, 0.80331],
2271 [0.62439, 0.74226, 0.80115],
2272 [0.6275, 0.74175, 0.79899],
2273 [0.6306, 0.74125, 0.79682],
2274 [0.63367, 0.74074, 0.79466],
2275 [0.63672, 0.74024, 0.79249],
2276 [0.63975, 0.73974, 0.79033],
2277 [0.64276, 0.73924, 0.78816],
2278 [0.64574, 0.73873, 0.78601],
2279 [0.6487, 0.73822, 0.78384],
2280 [0.65165, 0.73771, 0.78168],
2281 [0.65457, 0.73721, 0.77952],
2282 [0.65748, 0.7367, 0.77736],
2283 [0.66036, 0.73618, 0.77519],
2284 [0.66323, 0.73568, 0.77303],
2285 [0.66607, 0.73517, 0.77087],
2286 [0.6689, 0.73466, 0.76871],
2287 [0.6717, 0.73415, 0.76655],
2288 [0.67449, 0.73364, 0.7644],
2289 [0.67727, 0.73312, 0.76225],
2290 [0.68001, 0.73261, 0.76012],
2291 [0.68275, 0.7321, 0.758],
2292 [0.68547, 0.73158, 0.75589],
2293 [0.68816, 0.73106, 0.7538],
2294 [0.69083, 0.73054, 0.75175],
2295 [0.69348, 0.73001, 0.74973],
2296 [0.69611, 0.72948, 0.74778],
2297 [0.69871, 0.72895, 0.74588],
2298 [0.70129, 0.72841, 0.74406],
2299 [0.70383, 0.72787, 0.74233],
2300 [0.70635, 0.72732, 0.74072],
2301 [0.70883, 0.72676, 0.73924],
2302 [0.71127, 0.7262, 0.73789],
2303 [0.71366, 0.72563, 0.73671],
2304 [0.71602, 0.72504, 0.73571],
2305 [0.71832, 0.72445, 0.73489],
2306 [0.72058, 0.72384, 0.73427],
2307 [0.72279, 0.72323, 0.73384],
2308 [0.72496, 0.72261, 0.73361],
2309 [0.72707, 0.72198, 0.73357],
2310 [0.72914, 0.72134, 0.73372],
2311 [0.73116, 0.72069, 0.73405],
2312 [0.73315, 0.72005, 0.73455],
2313 [0.73509, 0.71939, 0.73518],
2314 [0.73699, 0.71872, 0.73594],
2315 [0.73887, 0.71805, 0.73683],
2316 [0.74071, 0.71739, 0.7378],
2317 [0.74254, 0.71671, 0.73887],
2318 [0.74434, 0.71603, 0.73999],
2319 [0.74612, 0.71534, 0.74115],
2320 [0.74789, 0.71465, 0.74238],
2321 [0.74964, 0.71397, 0.74362],
2322 [0.7514, 0.71328, 0.74489],
2323 [0.75313, 0.71258, 0.74618],
2324 [0.75487, 0.71189, 0.74749],
2325 [0.7566, 0.7112, 0.74879],
2326 [0.75832, 0.7105, 0.75011],
2327 [0.76003, 0.7098, 0.75143],
2328 [0.76175, 0.7091, 0.75275],
2329 [0.76346, 0.70839, 0.75408],
2330 [0.76517, 0.70768, 0.7554],
2331 [0.76687, 0.70697, 0.75672],
2332 [0.76857, 0.70626, 0.75805],
2333 [0.77028, 0.70555, 0.75937],
2334 [0.77198, 0.70483, 0.7607],
2335 [0.77367, 0.70412, 0.76202],
2336 [0.77536, 0.7034, 0.76334],
2337 [0.77706, 0.70268, 0.76467],
2338 [0.77874, 0.70195, 0.76599],
2339 [0.78042, 0.70123, 0.76731],
2340 [0.78211, 0.70051, 0.76863],
2341 [0.78379, 0.69977, 0.76996],
2342 [0.78546, 0.69904, 0.77128],
2343 [0.78714, 0.69831, 0.7726],
2344 [0.78881, 0.69758, 0.77392],
2345 [0.79048, 0.69684, 0.77525],
2346 [0.79215, 0.69611, 0.77657],
2347 [0.79382, 0.69536, 0.7779],
2348 [0.79547, 0.69461, 0.77922],
2349 [0.79713, 0.69387, 0.78054],
2350 [0.79879, 0.69313, 0.78187],
2351 [0.80045, 0.69238, 0.78318],
2352 [0.8021, 0.69162, 0.78451],
2353 [0.80375, 0.69086, 0.78583],
2354 [0.8054, 0.69011, 0.78715],
2355 [0.80705, 0.68936, 0.78847],
2356 [0.80869, 0.6886, 0.7898],
2357 [0.81033, 0.68783, 0.79112],
2358 [0.81197, 0.68706, 0.79244],
2359 [0.81361, 0.6863, 0.79377],
2360 [0.81524, 0.68553, 0.79508],
2361 [0.81688, 0.68475, 0.7964],
2362 [0.8185, 0.68398, 0.79773],
2363 [0.82013, 0.68321, 0.79905],
2364 [0.82176, 0.68242, 0.80037],
2365 [0.82338, 0.68164, 0.80169],
2366 [0.82501, 0.68086, 0.80301],
2367 [0.82663, 0.68007, 0.80434],
2368 [0.82824, 0.67928, 0.80565],
2369 [0.82986, 0.6785, 0.80698],
2370 [0.83148, 0.67771, 0.8083],
2371 [0.83309, 0.67691, 0.80962],
2372 [0.8347, 0.67611, 0.81094],
2373 [0.83631, 0.67531, 0.81226],
2374 [0.83791, 0.67451, 0.81358],
2375 [0.83952, 0.6737, 0.81491],
2376 [0.84112, 0.6729, 0.81623],
2377 [0.84272, 0.67209, 0.81755],
2378 [0.84432, 0.67128, 0.81887],
2379 [0.84591, 0.67047, 0.82019],
2380 [0.8475, 0.66965, 0.82151],
2381 [0.8491, 0.66883, 0.82284],
2382 [0.85069, 0.66801, 0.82415],
2383 [0.85228, 0.66718, 0.82548],
2384 [0.85386, 0.66635, 0.8268],
2385 [0.85545, 0.66552, 0.82812],
2386 [0.85703, 0.66469, 0.82944],
2387 [0.85861, 0.66386, 0.83076],
2388 [0.8602, 0.66302, 0.83209],
2389 [0.86177, 0.66218, 0.83341],
2390 [0.86335, 0.66134, 0.83473],
2391 [0.86492, 0.66049, 0.83605],
2392 [0.86649, 0.65964, 0.83737],
2393 [0.86807, 0.65879, 0.83869],
2394 [0.86963, 0.65794, 0.84001],
2395 [0.8712, 0.65709, 0.84133],
2396 [0.87277, 0.65623, 0.84265],
2397 [0.87433, 0.65536, 0.84397],
2398 [0.87589, 0.6545, 0.84529],
2399 [0.87745, 0.65363, 0.84661],
2400 [0.87901, 0.65276, 0.84793],
2401 [0.88056, 0.6519, 0.84926],
2402 [0.88212, 0.65102, 0.85058],
2403 [0.88368, 0.65014, 0.8519],
2404 [0.88523, 0.64927, 0.85322],
2405 [0.88678, 0.64838, 0.85454],
2406 [0.88833, 0.64749, 0.85587],
2407 [0.88987, 0.64661, 0.85718],
2408 [0.89142, 0.64571, 0.8585],
2409 [0.89296, 0.64482, 0.85983],
2410 [0.89451, 0.64392, 0.86115],
2411 [0.89605, 0.64302, 0.86248],
2412 [0.89759, 0.64212, 0.8638],
2413 [0.89912, 0.64121, 0.86511],
2414 [0.90066, 0.64031, 0.86643],
2415 [0.90219, 0.63939, 0.86776],
2416 [0.90372, 0.63848, 0.86908],
2417 [0.90526, 0.63756, 0.8704],
2418 [0.90679, 0.63664, 0.87172],
2419 [0.90832, 0.63572, 0.87304],
2420 [0.90984, 0.63479, 0.87436],
2421 [0.91137, 0.63386, 0.87569],
2422 [0.91289, 0.63293, 0.877],
2423 [0.91441, 0.63199, 0.87833],
2424 [0.91593, 0.63105, 0.87965],
2425 [0.91746, 0.63011, 0.88097],
2426 [0.91897, 0.62916, 0.88229],
2427 [0.92048, 0.62822, 0.88362],
2428 [0.922, 0.62726, 0.88494],
2429 [0.92352, 0.62631, 0.88626],
2430 [0.92503, 0.62535, 0.88758],
2431 [0.92654, 0.62439, 0.88891],
2432 [0.92805, 0.62343, 0.89022],
2433 [0.92956, 0.62245, 0.89155],
2434 [0.93106, 0.62148, 0.89287],
2435 ]
2436 b_diverging_isoluminant_cjm_75_c23 = bokeh_palette('diverging_isoluminant_cjm_75_c23',diverging_isoluminant_cjm_75_c23)
2437 m_diverging_isoluminant_cjm_75_c23 = mpl_cm('diverging_isoluminant_cjm_75_c23',diverging_isoluminant_cjm_75_c23)
2438 m_diverging_isoluminant_cjm_75_c23_r = mpl_cm('diverging_isoluminant_cjm_75_c23_r',list(reversed(diverging_isoluminant_cjm_75_c23)))
2439
2440
2441
2442
2443 diverging_isoluminant_cjm_75_c24 = [\
2444 [0, 0.79435, 0.99671],
2445 [0, 0.79384, 0.99455],
2446 [0, 0.79333, 0.99239],
2447 [0, 0.79282, 0.99023],
2448 [0, 0.79231, 0.98806],
2449 [0, 0.7918, 0.9859],
2450 [0, 0.79128, 0.98374],
2451 [0, 0.79077, 0.98158],
2452 [0, 0.79026, 0.97942],
2453 [0, 0.78975, 0.97726],
2454 [0, 0.78924, 0.9751],
2455 [0, 0.78872, 0.97295],
2456 [0, 0.7882, 0.97079],
2457 [0, 0.78769, 0.96863],
2458 [0, 0.78717, 0.96647],
2459 [0.030516, 0.78666, 0.96431],
2460 [0.077099, 0.78614, 0.96216],
2461 [0.10792, 0.78562, 0.96001],
2462 [0.13219, 0.7851, 0.95785],
2463 [0.15262, 0.78458, 0.9557],
2464 [0.17059, 0.78406, 0.95354],
2465 [0.18672, 0.78354, 0.95139],
2466 [0.20145, 0.78302, 0.94923],
2467 [0.21508, 0.7825, 0.94708],
2468 [0.22782, 0.78198, 0.94493],
2469 [0.23976, 0.78145, 0.94278],
2470 [0.25106, 0.78093, 0.94063],
2471 [0.26179, 0.7804, 0.93848],
2472 [0.272, 0.77988, 0.93633],
2473 [0.28182, 0.77935, 0.93417],
2474 [0.29123, 0.77882, 0.93203],
2475 [0.30027, 0.7783, 0.92988],
2476 [0.30902, 0.77777, 0.92773],
2477 [0.31745, 0.77725, 0.92558],
2478 [0.32562, 0.77672, 0.92344],
2479 [0.33356, 0.77618, 0.92129],
2480 [0.34126, 0.77565, 0.91914],
2481 [0.34875, 0.77512, 0.917],
2482 [0.35605, 0.77459, 0.91485],
2483 [0.36315, 0.77406, 0.91271],
2484 [0.37009, 0.77352, 0.91056],
2485 [0.37688, 0.77299, 0.90842],
2486 [0.3835, 0.77246, 0.90627],
2487 [0.38997, 0.77193, 0.90413],
2488 [0.39633, 0.77139, 0.90199],
2489 [0.40254, 0.77086, 0.89985],
2490 [0.40865, 0.77032, 0.8977],
2491 [0.41463, 0.76978, 0.89556],
2492 [0.4205, 0.76924, 0.89342],
2493 [0.42627, 0.7687, 0.89128],
2494 [0.43196, 0.76816, 0.88914],
2495 [0.43753, 0.76762, 0.887],
2496 [0.443, 0.76708, 0.88486],
2497 [0.44839, 0.76654, 0.88272],
2498 [0.4537, 0.766, 0.88058],
2499 [0.45893, 0.76546, 0.87844],
2500 [0.46409, 0.76492, 0.8763],
2501 [0.46917, 0.76437, 0.87417],
2502 [0.47416, 0.76382, 0.87203],
2503 [0.4791, 0.76328, 0.86989],
2504 [0.48396, 0.76273, 0.86776],
2505 [0.48876, 0.76219, 0.86562],
2506 [0.4935, 0.76164, 0.86349],
2507 [0.49819, 0.76109, 0.86135],
2508 [0.5028, 0.76054, 0.85922],
2509 [0.50737, 0.75999, 0.85708],
2510 [0.51187, 0.75944, 0.85495],
2511 [0.51632, 0.75889, 0.85282],
2512 [0.52073, 0.75834, 0.85068],
2513 [0.52508, 0.75779, 0.84855],
2514 [0.52939, 0.75723, 0.84641],
2515 [0.53364, 0.75668, 0.84429],
2516 [0.53786, 0.75612, 0.84216],
2517 [0.54202, 0.75557, 0.84003],
2518 [0.54615, 0.75502, 0.83789],
2519 [0.55022, 0.75446, 0.83576],
2520 [0.55426, 0.7539, 0.83363],
2521 [0.55825, 0.75334, 0.83151],
2522 [0.56222, 0.75278, 0.82938],
2523 [0.56614, 0.75222, 0.82725],
2524 [0.57001, 0.75166, 0.82511],
2525 [0.57386, 0.7511, 0.82299],
2526 [0.57767, 0.75054, 0.82086],
2527 [0.58145, 0.74997, 0.81873],
2528 [0.5852, 0.7494, 0.81661],
2529 [0.58889, 0.74884, 0.81448],
2530 [0.59258, 0.74828, 0.81235],
2531 [0.59622, 0.74772, 0.81023],
2532 [0.59983, 0.74715, 0.8081],
2533 [0.60342, 0.74658, 0.80598],
2534 [0.60697, 0.74601, 0.80385],
2535 [0.61049, 0.74544, 0.80173],
2536 [0.61398, 0.74487, 0.79961],
2537 [0.61745, 0.7443, 0.79748],
2538 [0.62089, 0.74373, 0.79536],
2539 [0.6243, 0.74316, 0.79324],
2540 [0.62769, 0.74258, 0.79111],
2541 [0.63105, 0.742, 0.78899],
2542 [0.63438, 0.74143, 0.78687],
2543 [0.63769, 0.74085, 0.78475],
2544 [0.64097, 0.74028, 0.78262],
2545 [0.64423, 0.73971, 0.7805],
2546 [0.64747, 0.73913, 0.77838],
2547 [0.65069, 0.73854, 0.77626],
2548 [0.65388, 0.73796, 0.77414],
2549 [0.65705, 0.73738, 0.77202],
2550 [0.66019, 0.7368, 0.7699],
2551 [0.66332, 0.73621, 0.76778],
2552 [0.66642, 0.73563, 0.76567],
2553 [0.66951, 0.73505, 0.76355],
2554 [0.67257, 0.73446, 0.76145],
2555 [0.6756, 0.73388, 0.75935],
2556 [0.67862, 0.73329, 0.75727],
2557 [0.68161, 0.7327, 0.75521],
2558 [0.68458, 0.73211, 0.75316],
2559 [0.68753, 0.73151, 0.75116],
2560 [0.69045, 0.73091, 0.74918],
2561 [0.69334, 0.73031, 0.74727],
2562 [0.6962, 0.72971, 0.74541],
2563 [0.69902, 0.7291, 0.74364],
2564 [0.70181, 0.72848, 0.74196],
2565 [0.70456, 0.72786, 0.74039],
2566 [0.70726, 0.72724, 0.73895],
2567 [0.70992, 0.72661, 0.73766],
2568 [0.71252, 0.72597, 0.73652],
2569 [0.71507, 0.72533, 0.73557],
2570 [0.71757, 0.72468, 0.73481],
2571 [0.72, 0.72402, 0.73423],
2572 [0.72237, 0.72335, 0.73386],
2573 [0.7247, 0.72268, 0.73368],
2574 [0.72695, 0.722, 0.7337],
2575 [0.72915, 0.72132, 0.73391],
2576 [0.7313, 0.72063, 0.73429],
2577 [0.7334, 0.71994, 0.73484],
2578 [0.73545, 0.71924, 0.73553],
2579 [0.73745, 0.71854, 0.73635],
2580 [0.73943, 0.71784, 0.73729],
2581 [0.74136, 0.71713, 0.73833],
2582 [0.74327, 0.71642, 0.73945],
2583 [0.74515, 0.71571, 0.74062],
2584 [0.74702, 0.71498, 0.74185],
2585 [0.74887, 0.71426, 0.74313],
2586 [0.75071, 0.71355, 0.74443],
2587 [0.75252, 0.71282, 0.74576],
2588 [0.75434, 0.7121, 0.74711],
2589 [0.75615, 0.71138, 0.74847],
2590 [0.75795, 0.71064, 0.74983],
2591 [0.75974, 0.70991, 0.75121],
2592 [0.76153, 0.70918, 0.75258],
2593 [0.76332, 0.70845, 0.75397],
2594 [0.76511, 0.7077, 0.75535],
2595 [0.76688, 0.70697, 0.75673],
2596 [0.76866, 0.70623, 0.75812],
2597 [0.77044, 0.70548, 0.75949],
2598 [0.77221, 0.70474, 0.76088],
2599 [0.77397, 0.70399, 0.76225],
2600 [0.77574, 0.70324, 0.76364],
2601 [0.77751, 0.70249, 0.76502],
2602 [0.77926, 0.70173, 0.7664],
2603 [0.78102, 0.70098, 0.76778],
2604 [0.78278, 0.70021, 0.76916],
2605 [0.78453, 0.69945, 0.77055],
2606 [0.78628, 0.69869, 0.77193],
2607 [0.78802, 0.69792, 0.7733],
2608 [0.78977, 0.69715, 0.77468],
2609 [0.79151, 0.69639, 0.77607],
2610 [0.79325, 0.69561, 0.77745],
2611 [0.79498, 0.69483, 0.77883],
2612 [0.79672, 0.69405, 0.78021],
2613 [0.79845, 0.69328, 0.78159],
2614 [0.80018, 0.6925, 0.78297],
2615 [0.8019, 0.69171, 0.78435],
2616 [0.80363, 0.69092, 0.78573],
2617 [0.80534, 0.69014, 0.78711],
2618 [0.80707, 0.68935, 0.78849],
2619 [0.80878, 0.68855, 0.78987],
2620 [0.81049, 0.68775, 0.79125],
2621 [0.8122, 0.68695, 0.79263],
2622 [0.81391, 0.68615, 0.79401],
2623 [0.81562, 0.68535, 0.79539],
2624 [0.81732, 0.68454, 0.79677],
2625 [0.81902, 0.68373, 0.79815],
2626 [0.82072, 0.68292, 0.79953],
2627 [0.82242, 0.68211, 0.80091],
2628 [0.82411, 0.68129, 0.80228],
2629 [0.82581, 0.68047, 0.80367],
2630 [0.8275, 0.67965, 0.80504],
2631 [0.82919, 0.67883, 0.80643],
2632 [0.83087, 0.67801, 0.8078],
2633 [0.83255, 0.67718, 0.80919],
2634 [0.83424, 0.67634, 0.81056],
2635 [0.83591, 0.67551, 0.81194],
2636 [0.83759, 0.67467, 0.81332],
2637 [0.83927, 0.67383, 0.8147],
2638 [0.84094, 0.67299, 0.81608],
2639 [0.84261, 0.67215, 0.81746],
2640 [0.84427, 0.6713, 0.81883],
2641 [0.84594, 0.67045, 0.82021],
2642 [0.8476, 0.6696, 0.8216],
2643 [0.84927, 0.66874, 0.82297],
2644 [0.85092, 0.66788, 0.82435],
2645 [0.85259, 0.66702, 0.82573],
2646 [0.85424, 0.66615, 0.82711],
2647 [0.8559, 0.66529, 0.82849],
2648 [0.85754, 0.66442, 0.82987],
2649 [0.85919, 0.66355, 0.83125],
2650 [0.86084, 0.66268, 0.83263],
2651 [0.86249, 0.6618, 0.83401],
2652 [0.86414, 0.66091, 0.83538],
2653 [0.86577, 0.66003, 0.83676],
2654 [0.86741, 0.65914, 0.83814],
2655 [0.86906, 0.65826, 0.83952],
2656 [0.87069, 0.65737, 0.8409],
2657 [0.87233, 0.65647, 0.84228],
2658 [0.87395, 0.65557, 0.84366],
2659 [0.87559, 0.65467, 0.84504],
2660 [0.87721, 0.65377, 0.84641],
2661 [0.87884, 0.65285, 0.84779],
2662 [0.88047, 0.65195, 0.84918],
2663 [0.88209, 0.65104, 0.85055],
2664 [0.88371, 0.65012, 0.85193],
2665 [0.88533, 0.64921, 0.85331],
2666 [0.88695, 0.64828, 0.85469],
2667 [0.88857, 0.64736, 0.85607],
2668 [0.89018, 0.64643, 0.85745],
2669 [0.89179, 0.64549, 0.85883],
2670 [0.8934, 0.64456, 0.86021],
2671 [0.89502, 0.64362, 0.86159],
2672 [0.89662, 0.64269, 0.86297],
2673 [0.89822, 0.64174, 0.86435],
2674 [0.89983, 0.64079, 0.86572],
2675 [0.90143, 0.63985, 0.8671],
2676 [0.90304, 0.63889, 0.86849],
2677 [0.90463, 0.63793, 0.86986],
2678 [0.90623, 0.63698, 0.87124],
2679 [0.90783, 0.63601, 0.87262],
2680 [0.90942, 0.63504, 0.874],
2681 [0.91101, 0.63408, 0.87538],
2682 [0.9126, 0.6331, 0.87675],
2683 [0.91419, 0.63213, 0.87814],
2684 [0.91578, 0.63115, 0.87951],
2685 [0.91737, 0.63016, 0.8809],
2686 [0.91895, 0.62917, 0.88227],
2687 [0.92053, 0.62819, 0.88366],
2688 [0.92212, 0.62719, 0.88504],
2689 [0.9237, 0.62619, 0.88642],
2690 [0.92527, 0.62519, 0.88779],
2691 [0.92685, 0.62419, 0.88918],
2692 [0.92842, 0.62319, 0.89055],
2693 [0.93, 0.62217, 0.89194],
2694 [0.93157, 0.62116, 0.89331],
2695 [0.93314, 0.62014, 0.8947],
2696 [0.93471, 0.61912, 0.89607],
2697 [0.93628, 0.61809, 0.89746],
2698 [0.93785, 0.61706, 0.89883],
2699 [0.93941, 0.61603, 0.90021],
2700 ]
2701 b_diverging_isoluminant_cjm_75_c24 = bokeh_palette('diverging_isoluminant_cjm_75_c24',diverging_isoluminant_cjm_75_c24)
2702 m_diverging_isoluminant_cjm_75_c24 = mpl_cm('diverging_isoluminant_cjm_75_c24',diverging_isoluminant_cjm_75_c24)
2703 m_diverging_isoluminant_cjm_75_c24_r = mpl_cm('diverging_isoluminant_cjm_75_c24_r',list(reversed(diverging_isoluminant_cjm_75_c24)))
2704
2705
2706
2707
2708 diverging_isoluminant_cjo_70_c25 = [\
2709 [0, 0.71527, 1],
2710 [0, 0.7149, 1],
2711 [0, 0.71453, 1],
2712 [0, 0.71417, 1],
2713 [0.024434, 0.7138, 1],
2714 [0.068274, 0.71344, 0.99912],
2715 [0.097664, 0.71307, 0.99639],
2716 [0.12062, 0.71271, 0.99368],
2717 [0.13997, 0.71234, 0.99096],
2718 [0.15693, 0.71199, 0.98824],
2719 [0.1721, 0.71163, 0.98553],
2720 [0.18598, 0.71126, 0.98281],
2721 [0.19872, 0.7109, 0.9801],
2722 [0.21064, 0.71054, 0.97739],
2723 [0.2218, 0.71018, 0.97467],
2724 [0.23235, 0.70981, 0.97196],
2725 [0.24234, 0.70945, 0.96925],
2726 [0.25188, 0.7091, 0.96654],
2727 [0.26097, 0.70874, 0.96383],
2728 [0.26971, 0.70837, 0.96112],
2729 [0.27808, 0.70801, 0.95841],
2730 [0.28614, 0.70765, 0.95571],
2731 [0.29394, 0.70729, 0.953],
2732 [0.30148, 0.70693, 0.95029],
2733 [0.3088, 0.70658, 0.94759],
2734 [0.31588, 0.70622, 0.94488],
2735 [0.32276, 0.70586, 0.94218],
2736 [0.32945, 0.7055, 0.93948],
2737 [0.33595, 0.70514, 0.93678],
2738 [0.3423, 0.70478, 0.93407],
2739 [0.34848, 0.70443, 0.93137],
2740 [0.35453, 0.70407, 0.92867],
2741 [0.36042, 0.70371, 0.92597],
2742 [0.3662, 0.70336, 0.92327],
2743 [0.37184, 0.703, 0.92057],
2744 [0.37737, 0.70265, 0.91788],
2745 [0.38279, 0.70229, 0.91518],
2746 [0.38809, 0.70193, 0.91249],
2747 [0.3933, 0.70158, 0.90979],
2748 [0.39841, 0.70122, 0.9071],
2749 [0.40343, 0.70087, 0.9044],
2750 [0.40835, 0.70052, 0.90171],
2751 [0.4132, 0.70016, 0.89902],
2752 [0.41795, 0.69981, 0.89633],
2753 [0.42262, 0.69945, 0.89363],
2754 [0.42723, 0.6991, 0.89094],
2755 [0.43176, 0.69875, 0.88826],
2756 [0.43621, 0.69839, 0.88557],
2757 [0.44059, 0.69804, 0.88288],
2758 [0.44493, 0.69769, 0.88019],
2759 [0.44919, 0.69734, 0.8775],
2760 [0.45337, 0.69699, 0.87482],
2761 [0.45751, 0.69664, 0.87213],
2762 [0.46159, 0.69629, 0.86945],
2763 [0.46561, 0.69594, 0.86676],
2764 [0.46959, 0.69559, 0.86408],
2765 [0.47349, 0.69524, 0.86139],
2766 [0.47736, 0.69489, 0.85871],
2767 [0.48117, 0.69453, 0.85603],
2768 [0.48494, 0.69418, 0.85335],
2769 [0.48866, 0.69384, 0.85067],
2770 [0.49233, 0.69349, 0.84799],
2771 [0.49596, 0.69315, 0.84531],
2772 [0.49954, 0.6928, 0.84264],
2773 [0.50308, 0.69245, 0.83996],
2774 [0.50659, 0.6921, 0.83728],
2775 [0.51005, 0.69175, 0.8346],
2776 [0.51348, 0.6914, 0.83193],
2777 [0.51686, 0.69105, 0.82925],
2778 [0.5202, 0.69071, 0.82658],
2779 [0.52352, 0.69036, 0.8239],
2780 [0.52679, 0.69002, 0.82123],
2781 [0.53003, 0.68967, 0.81855],
2782 [0.53323, 0.68933, 0.81588],
2783 [0.5364, 0.68898, 0.81321],
2784 [0.53953, 0.68864, 0.81053],
2785 [0.54265, 0.68829, 0.80787],
2786 [0.54572, 0.68795, 0.80519],
2787 [0.54877, 0.6876, 0.80252],
2788 [0.55178, 0.68726, 0.79986],
2789 [0.55476, 0.68691, 0.79718],
2790 [0.55772, 0.68657, 0.79452],
2791 [0.56064, 0.68622, 0.79185],
2792 [0.56355, 0.68588, 0.78919],
2793 [0.56642, 0.68554, 0.78652],
2794 [0.56925, 0.6852, 0.78385],
2795 [0.57208, 0.68485, 0.78118],
2796 [0.57487, 0.68451, 0.77852],
2797 [0.57763, 0.68416, 0.77585],
2798 [0.58038, 0.68382, 0.77318],
2799 [0.5831, 0.68348, 0.77052],
2800 [0.5858, 0.68314, 0.76786],
2801 [0.58846, 0.6828, 0.7652],
2802 [0.59111, 0.68246, 0.76253],
2803 [0.59374, 0.68212, 0.75987],
2804 [0.59634, 0.68177, 0.75721],
2805 [0.59892, 0.68143, 0.75455],
2806 [0.60148, 0.68109, 0.75189],
2807 [0.60402, 0.68075, 0.74922],
2808 [0.60653, 0.68041, 0.74656],
2809 [0.60904, 0.68007, 0.7439],
2810 [0.61151, 0.67974, 0.74124],
2811 [0.61395, 0.6794, 0.73859],
2812 [0.6164, 0.67906, 0.73592],
2813 [0.61882, 0.67872, 0.73327],
2814 [0.62121, 0.67839, 0.73061],
2815 [0.62359, 0.67805, 0.72795],
2816 [0.62595, 0.67771, 0.7253],
2817 [0.62829, 0.67738, 0.72263],
2818 [0.63062, 0.67704, 0.71998],
2819 [0.63293, 0.6767, 0.71733],
2820 [0.63522, 0.67636, 0.71467],
2821 [0.6375, 0.67601, 0.71202],
2822 [0.63977, 0.67567, 0.70938],
2823 [0.64203, 0.67533, 0.70674],
2824 [0.64428, 0.67498, 0.7041],
2825 [0.64653, 0.67463, 0.70147],
2826 [0.64878, 0.67427, 0.69886],
2827 [0.65103, 0.67391, 0.69626],
2828 [0.65329, 0.67353, 0.69367],
2829 [0.65556, 0.67315, 0.6911],
2830 [0.65785, 0.67276, 0.68857],
2831 [0.66016, 0.67235, 0.68605],
2832 [0.6625, 0.67193, 0.68357],
2833 [0.66485, 0.67148, 0.68111],
2834 [0.66726, 0.67103, 0.6787],
2835 [0.6697, 0.67055, 0.67633],
2836 [0.67218, 0.67005, 0.67399],
2837 [0.6747, 0.66953, 0.6717],
2838 [0.67726, 0.66898, 0.66945],
2839 [0.67985, 0.66842, 0.66724],
2840 [0.68249, 0.66784, 0.66507],
2841 [0.68516, 0.66723, 0.66295],
2842 [0.68786, 0.6666, 0.66084],
2843 [0.69058, 0.66596, 0.65878],
2844 [0.69332, 0.66531, 0.65675],
2845 [0.69608, 0.66464, 0.65473],
2846 [0.69884, 0.66396, 0.65274],
2847 [0.70162, 0.66328, 0.65077],
2848 [0.7044, 0.66258, 0.64882],
2849 [0.70718, 0.66187, 0.64687],
2850 [0.70995, 0.66115, 0.64493],
2851 [0.71271, 0.66044, 0.643],
2852 [0.71548, 0.65972, 0.64107],
2853 [0.71822, 0.65899, 0.63915],
2854 [0.72096, 0.65827, 0.63724],
2855 [0.72369, 0.65754, 0.63532],
2856 [0.72641, 0.65681, 0.63341],
2857 [0.72911, 0.65607, 0.6315],
2858 [0.7318, 0.65533, 0.62958],
2859 [0.73448, 0.65459, 0.62767],
2860 [0.73715, 0.65385, 0.62576],
2861 [0.7398, 0.6531, 0.62385],
2862 [0.74244, 0.65236, 0.62193],
2863 [0.74507, 0.65162, 0.62003],
2864 [0.74769, 0.65087, 0.61811],
2865 [0.75029, 0.65012, 0.61621],
2866 [0.75287, 0.64937, 0.61429],
2867 [0.75546, 0.64862, 0.61238],
2868 [0.75803, 0.64786, 0.61047],
2869 [0.76059, 0.64711, 0.60857],
2870 [0.76313, 0.64634, 0.60666],
2871 [0.76567, 0.64558, 0.60475],
2872 [0.76819, 0.64482, 0.60283],
2873 [0.77071, 0.64405, 0.60092],
2874 [0.77321, 0.64329, 0.59902],
2875 [0.7757, 0.64252, 0.59711],
2876 [0.77819, 0.64175, 0.5952],
2877 [0.78066, 0.64098, 0.59329],
2878 [0.78312, 0.64021, 0.59138],
2879 [0.78557, 0.63943, 0.58947],
2880 [0.78801, 0.63865, 0.58756],
2881 [0.79044, 0.63787, 0.58566],
2882 [0.79287, 0.63709, 0.58374],
2883 [0.79528, 0.63631, 0.58183],
2884 [0.79768, 0.63552, 0.57993],
2885 [0.80008, 0.63473, 0.57801],
2886 [0.80246, 0.63395, 0.57612],
2887 [0.80484, 0.63315, 0.5742],
2888 [0.80721, 0.63236, 0.5723],
2889 [0.80956, 0.63156, 0.57038],
2890 [0.81191, 0.63077, 0.56848],
2891 [0.81425, 0.62996, 0.56657],
2892 [0.81658, 0.62916, 0.56466],
2893 [0.8189, 0.62836, 0.56276],
2894 [0.82122, 0.62755, 0.56084],
2895 [0.82352, 0.62674, 0.55893],
2896 [0.82582, 0.62593, 0.55704],
2897 [0.82811, 0.62511, 0.55512],
2898 [0.83039, 0.6243, 0.55321],
2899 [0.83266, 0.62349, 0.55131],
2900 [0.83493, 0.62266, 0.5494],
2901 [0.83719, 0.62184, 0.54749],
2902 [0.83944, 0.62102, 0.54559],
2903 [0.84168, 0.6202, 0.54367],
2904 [0.84391, 0.61937, 0.54176],
2905 [0.84614, 0.61854, 0.53985],
2906 [0.84836, 0.6177, 0.53795],
2907 [0.85057, 0.61687, 0.53604],
2908 [0.85278, 0.61603, 0.53413],
2909 [0.85497, 0.61518, 0.53223],
2910 [0.85716, 0.61434, 0.53031],
2911 [0.85935, 0.6135, 0.52841],
2912 [0.86152, 0.61265, 0.5265],
2913 [0.86369, 0.6118, 0.52458],
2914 [0.86585, 0.61096, 0.52268],
2915 [0.86801, 0.6101, 0.52076],
2916 [0.87015, 0.60925, 0.51886],
2917 [0.8723, 0.60839, 0.51695],
2918 [0.87443, 0.60753, 0.51503],
2919 [0.87656, 0.60666, 0.51312],
2920 [0.87868, 0.60579, 0.51121],
2921 [0.8808, 0.60493, 0.5093],
2922 [0.88291, 0.60406, 0.50739],
2923 [0.88501, 0.60319, 0.50547],
2924 [0.88711, 0.60231, 0.50356],
2925 [0.8892, 0.60143, 0.50166],
2926 [0.89128, 0.60055, 0.49974],
2927 [0.89336, 0.59967, 0.49784],
2928 [0.89544, 0.59878, 0.49591],
2929 [0.8975, 0.59789, 0.49401],
2930 [0.89956, 0.59701, 0.49209],
2931 [0.90162, 0.59611, 0.49018],
2932 [0.90367, 0.59521, 0.48827],
2933 [0.90571, 0.59431, 0.48635],
2934 [0.90775, 0.59341, 0.48443],
2935 [0.90978, 0.59252, 0.48252],
2936 [0.9118, 0.5916, 0.4806],
2937 [0.91383, 0.59069, 0.47869],
2938 [0.91583, 0.58978, 0.47677],
2939 [0.91785, 0.58886, 0.47486],
2940 [0.91985, 0.58794, 0.47293],
2941 [0.92185, 0.58703, 0.47102],
2942 [0.92385, 0.58611, 0.46911],
2943 [0.92583, 0.58518, 0.46719],
2944 [0.92781, 0.58425, 0.46526],
2945 [0.92979, 0.58332, 0.46333],
2946 [0.93176, 0.58238, 0.46142],
2947 [0.93373, 0.58145, 0.4595],
2948 [0.9357, 0.58051, 0.45758],
2949 [0.93765, 0.57957, 0.45566],
2950 [0.93961, 0.57862, 0.45373],
2951 [0.94155, 0.57767, 0.45181],
2952 [0.9435, 0.57673, 0.44989],
2953 [0.94543, 0.57577, 0.44796],
2954 [0.94737, 0.5748, 0.44603],
2955 [0.94929, 0.57384, 0.44412],
2956 [0.95122, 0.57289, 0.44219],
2957 [0.95314, 0.57192, 0.44025],
2958 [0.95505, 0.57094, 0.43833],
2959 [0.95696, 0.56997, 0.4364],
2960 [0.95887, 0.56899, 0.43447],
2961 [0.96077, 0.56802, 0.43254],
2962 [0.96266, 0.56704, 0.43061],
2963 [0.96455, 0.56605, 0.42867],
2964 [0.96644, 0.56505, 0.42674],
2965 ]
2966 b_diverging_isoluminant_cjo_70_c25 = bokeh_palette('diverging_isoluminant_cjo_70_c25',diverging_isoluminant_cjo_70_c25)
2967 m_diverging_isoluminant_cjo_70_c25 = mpl_cm('diverging_isoluminant_cjo_70_c25',diverging_isoluminant_cjo_70_c25)
2968 m_diverging_isoluminant_cjo_70_c25_r = mpl_cm('diverging_isoluminant_cjo_70_c25_r',list(reversed(diverging_isoluminant_cjo_70_c25)))
2969
2970
2971
2972
2973 diverging_linear_bjr_30_55_c53 = [\
2974 [0, 0.1654, 0.84384],
2975 [0, 0.16745, 0.84024],
2976 [0, 0.16948, 0.83663],
2977 [0, 0.17145, 0.83302],
2978 [0, 0.17344, 0.82943],
2979 [0, 0.17543, 0.82582],
2980 [0, 0.17744, 0.82223],
2981 [0, 0.1794, 0.81863],
2982 [0.025922, 0.18135, 0.81503],
2983 [0.052828, 0.18332, 0.81145],
2984 [0.073384, 0.18532, 0.80785],
2985 [0.089868, 0.18726, 0.80427],
2986 [0.10397, 0.1892, 0.80068],
2987 [0.11641, 0.19113, 0.79709],
2988 [0.12754, 0.19308, 0.79352],
2989 [0.13776, 0.19502, 0.78993],
2990 [0.14712, 0.19696, 0.78636],
2991 [0.15586, 0.19885, 0.78277],
2992 [0.16403, 0.20076, 0.7792],
2993 [0.17168, 0.20269, 0.77562],
2994 [0.17895, 0.20462, 0.77205],
2995 [0.18585, 0.20653, 0.76848],
2996 [0.19237, 0.20841, 0.76492],
2997 [0.19861, 0.2103, 0.76135],
2998 [0.20461, 0.21221, 0.75779],
2999 [0.21032, 0.21409, 0.75423],
3000 [0.21583, 0.21599, 0.75066],
3001 [0.22112, 0.21785, 0.7471],
3002 [0.22622, 0.21973, 0.74355],
3003 [0.23112, 0.22159, 0.73999],
3004 [0.23587, 0.22347, 0.73643],
3005 [0.24042, 0.22532, 0.73288],
3006 [0.24486, 0.22719, 0.72933],
3007 [0.24917, 0.22905, 0.72578],
3008 [0.25333, 0.2309, 0.72223],
3009 [0.25737, 0.23274, 0.71868],
3010 [0.26128, 0.23461, 0.71514],
3011 [0.26508, 0.23645, 0.7116],
3012 [0.2688, 0.23827, 0.70806],
3013 [0.27236, 0.2401, 0.70452],
3014 [0.27589, 0.24194, 0.70098],
3015 [0.27929, 0.24376, 0.69744],
3016 [0.2826, 0.24558, 0.6939],
3017 [0.2858, 0.24742, 0.69037],
3018 [0.28896, 0.24924, 0.68684],
3019 [0.29202, 0.25106, 0.68331],
3020 [0.29499, 0.25287, 0.67978],
3021 [0.2979, 0.2547, 0.67625],
3022 [0.30074, 0.25648, 0.67273],
3023 [0.3035, 0.25829, 0.6692],
3024 [0.30623, 0.2601, 0.66568],
3025 [0.30886, 0.2619, 0.66216],
3026 [0.31142, 0.26371, 0.65863],
3027 [0.31394, 0.26549, 0.65511],
3028 [0.31639, 0.26726, 0.6516],
3029 [0.31878, 0.26908, 0.64807],
3030 [0.32112, 0.27087, 0.64456],
3031 [0.3234, 0.27263, 0.64104],
3032 [0.32562, 0.27442, 0.63753],
3033 [0.3278, 0.27621, 0.63402],
3034 [0.32994, 0.27798, 0.63051],
3035 [0.33201, 0.27975, 0.62699],
3036 [0.33404, 0.28152, 0.62349],
3037 [0.33602, 0.28329, 0.61998],
3038 [0.33795, 0.28504, 0.61647],
3039 [0.33985, 0.28681, 0.61296],
3040 [0.34169, 0.28858, 0.60946],
3041 [0.34349, 0.29033, 0.60594],
3042 [0.34525, 0.2921, 0.60244],
3043 [0.34698, 0.29385, 0.59894],
3044 [0.34865, 0.2956, 0.59544],
3045 [0.3503, 0.29736, 0.59194],
3046 [0.35188, 0.29912, 0.58843],
3047 [0.35345, 0.30085, 0.58494],
3048 [0.35499, 0.30259, 0.58143],
3049 [0.35647, 0.30434, 0.57793],
3050 [0.35792, 0.3061, 0.57443],
3051 [0.35932, 0.30781, 0.57094],
3052 [0.36069, 0.30957, 0.56744],
3053 [0.36205, 0.31129, 0.56395],
3054 [0.36335, 0.31302, 0.56045],
3055 [0.36463, 0.31475, 0.55696],
3056 [0.36588, 0.31649, 0.55345],
3057 [0.36709, 0.31821, 0.54996],
3058 [0.36827, 0.31994, 0.54647],
3059 [0.36941, 0.32165, 0.54297],
3060 [0.37053, 0.32338, 0.53947],
3061 [0.37161, 0.32509, 0.53597],
3062 [0.37267, 0.32681, 0.53248],
3063 [0.3737, 0.32854, 0.52899],
3064 [0.37469, 0.33025, 0.52549],
3065 [0.37565, 0.33196, 0.52198],
3066 [0.3766, 0.33368, 0.5185],
3067 [0.3775, 0.33539, 0.51499],
3068 [0.37838, 0.33709, 0.51149],
3069 [0.37924, 0.33879, 0.508],
3070 [0.38006, 0.3405, 0.50451],
3071 [0.38087, 0.3422, 0.501],
3072 [0.38163, 0.34389, 0.4975],
3073 [0.38237, 0.34559, 0.494],
3074 [0.3831, 0.3473, 0.4905],
3075 [0.38379, 0.34899, 0.48699],
3076 [0.38445, 0.35069, 0.48348],
3077 [0.38508, 0.35237, 0.47998],
3078 [0.3857, 0.35406, 0.47647],
3079 [0.38629, 0.35576, 0.47296],
3080 [0.38685, 0.35745, 0.46946],
3081 [0.38739, 0.35912, 0.46593],
3082 [0.38791, 0.3608, 0.46242],
3083 [0.3884, 0.3625, 0.45891],
3084 [0.38888, 0.36417, 0.45539],
3085 [0.38931, 0.36586, 0.45188],
3086 [0.38973, 0.36753, 0.44835],
3087 [0.39012, 0.36922, 0.44483],
3088 [0.3905, 0.37088, 0.4413],
3089 [0.39085, 0.37256, 0.43778],
3090 [0.39118, 0.37425, 0.43423],
3091 [0.39148, 0.37591, 0.4307],
3092 [0.39176, 0.37758, 0.42717],
3093 [0.39201, 0.37925, 0.42362],
3094 [0.39224, 0.38092, 0.42008],
3095 [0.39246, 0.38258, 0.41653],
3096 [0.39264, 0.38425, 0.41298],
3097 [0.39281, 0.3859, 0.40942],
3098 [0.39296, 0.38757, 0.40587],
3099 [0.39308, 0.38924, 0.40228],
3100 [0.39318, 0.3909, 0.39872],
3101 [0.39326, 0.39255, 0.39515],
3102 [0.39669, 0.39314, 0.39214],
3103 [0.40343, 0.39266, 0.38969],
3104 [0.41007, 0.39217, 0.38724],
3105 [0.41662, 0.39167, 0.3848],
3106 [0.42308, 0.39116, 0.38235],
3107 [0.42947, 0.39062, 0.37991],
3108 [0.4358, 0.39007, 0.37746],
3109 [0.44205, 0.38952, 0.37501],
3110 [0.44822, 0.38896, 0.37255],
3111 [0.45434, 0.38838, 0.3701],
3112 [0.46038, 0.38778, 0.36765],
3113 [0.46638, 0.38717, 0.3652],
3114 [0.47233, 0.38655, 0.36274],
3115 [0.47821, 0.38592, 0.36028],
3116 [0.48404, 0.38527, 0.35784],
3117 [0.48983, 0.38461, 0.35538],
3118 [0.49557, 0.38394, 0.35291],
3119 [0.50127, 0.38326, 0.35045],
3120 [0.50692, 0.38255, 0.34798],
3121 [0.51253, 0.38183, 0.34551],
3122 [0.5181, 0.38111, 0.34305],
3123 [0.52363, 0.38036, 0.34058],
3124 [0.52913, 0.3796, 0.33809],
3125 [0.53458, 0.37882, 0.33563],
3126 [0.54, 0.37803, 0.33316],
3127 [0.54539, 0.37723, 0.33067],
3128 [0.55075, 0.37641, 0.32819],
3129 [0.55607, 0.37556, 0.3257],
3130 [0.56137, 0.37471, 0.32323],
3131 [0.56664, 0.37384, 0.32075],
3132 [0.57188, 0.37295, 0.31825],
3133 [0.57709, 0.37204, 0.31576],
3134 [0.58227, 0.37112, 0.31326],
3135 [0.58743, 0.37018, 0.31077],
3136 [0.59258, 0.36924, 0.30826],
3137 [0.59768, 0.36827, 0.30577],
3138 [0.60277, 0.36727, 0.30324],
3139 [0.60785, 0.36627, 0.30073],
3140 [0.61288, 0.36524, 0.29821],
3141 [0.61791, 0.36419, 0.2957],
3142 [0.62292, 0.36313, 0.29318],
3143 [0.6279, 0.36205, 0.29066],
3144 [0.63287, 0.36094, 0.28813],
3145 [0.63782, 0.35983, 0.28559],
3146 [0.64275, 0.35868, 0.28307],
3147 [0.64766, 0.35754, 0.28051],
3148 [0.65255, 0.35635, 0.27798],
3149 [0.65744, 0.35515, 0.27544],
3150 [0.6623, 0.35391, 0.27288],
3151 [0.66714, 0.35267, 0.27033],
3152 [0.67198, 0.3514, 0.26774],
3153 [0.6768, 0.35012, 0.26518],
3154 [0.6816, 0.3488, 0.26261],
3155 [0.68639, 0.34747, 0.26004],
3156 [0.69116, 0.3461, 0.25745],
3157 [0.69594, 0.34472, 0.25487],
3158 [0.70069, 0.34332, 0.25226],
3159 [0.70542, 0.34189, 0.24964],
3160 [0.71015, 0.34043, 0.24704],
3161 [0.71486, 0.33896, 0.24441],
3162 [0.71957, 0.33745, 0.24181],
3163 [0.72426, 0.33591, 0.23917],
3164 [0.72895, 0.33436, 0.23654],
3165 [0.73362, 0.33277, 0.23387],
3166 [0.73828, 0.33113, 0.23124],
3167 [0.74294, 0.32951, 0.22858],
3168 [0.74758, 0.32782, 0.2259],
3169 [0.75221, 0.32611, 0.22322],
3170 [0.75684, 0.32438, 0.22053],
3171 [0.76145, 0.32263, 0.21781],
3172 [0.76606, 0.32083, 0.21509],
3173 [0.77066, 0.31899, 0.21238],
3174 [0.77525, 0.31713, 0.20964],
3175 [0.77984, 0.31523, 0.20691],
3176 [0.78442, 0.31331, 0.20416],
3177 [0.78899, 0.31134, 0.20135],
3178 [0.79355, 0.30935, 0.19857],
3179 [0.7981, 0.30729, 0.19578],
3180 [0.80264, 0.30522, 0.19297],
3181 [0.80719, 0.30309, 0.19014],
3182 [0.81172, 0.30093, 0.18732],
3183 [0.81625, 0.29874, 0.18444],
3184 [0.82077, 0.2965, 0.18155],
3185 [0.82529, 0.2942, 0.17869],
3186 [0.8298, 0.29189, 0.17574],
3187 [0.83431, 0.28951, 0.17282],
3188 [0.8388, 0.28707, 0.16989],
3189 [0.84329, 0.2846, 0.16692],
3190 [0.84778, 0.28209, 0.16393],
3191 [0.85227, 0.27951, 0.16088],
3192 [0.85675, 0.27688, 0.15783],
3193 [0.86122, 0.27419, 0.15475],
3194 [0.86569, 0.27144, 0.15165],
3195 [0.87015, 0.26865, 0.14851],
3196 [0.87462, 0.26578, 0.1454],
3197 [0.87907, 0.26285, 0.14218],
3198 [0.88353, 0.25985, 0.13893],
3199 [0.88797, 0.25678, 0.13565],
3200 [0.89242, 0.25364, 0.13237],
3201 [0.89686, 0.25041, 0.12899],
3202 [0.9013, 0.24713, 0.12563],
3203 [0.90573, 0.24374, 0.12213],
3204 [0.91016, 0.24028, 0.11869],
3205 [0.91459, 0.23676, 0.11509],
3206 [0.91901, 0.23308, 0.11151],
3207 [0.92343, 0.22934, 0.10779],
3208 [0.92784, 0.22549, 0.10405],
3209 [0.93226, 0.22153, 0.1002],
3210 [0.93668, 0.21745, 0.096258],
3211 [0.94108, 0.21323, 0.092292],
3212 [0.94549, 0.2089, 0.088179],
3213 [0.94989, 0.20443, 0.083966],
3214 [0.95429, 0.19976, 0.079537],
3215 [0.95869, 0.19499, 0.075045],
3216 [0.96309, 0.19001, 0.070373],
3217 [0.96749, 0.18486, 0.065518],
3218 [0.97188, 0.17948, 0.06046],
3219 [0.97626, 0.17389, 0.055081],
3220 [0.98065, 0.16803, 0.049511],
3221 [0.98504, 0.16195, 0.043373],
3222 [0.98943, 0.15551, 0.037065],
3223 [0.99381, 0.14872, 0.03044],
3224 [0.99819, 0.14159, 0.024101],
3225 [1, 0.13398, 0.017854],
3226 [1, 0.12585, 0.011691],
3227 [1, 0.11706, 0.0054342],
3228 [1, 0.10757, 0],
3229 [1, 0.097091, 0],
3230 ]
3231 b_diverging_linear_bjr_30_55_c53 = bokeh_palette('diverging_linear_bjr_30_55_c53',diverging_linear_bjr_30_55_c53)
3232 m_diverging_linear_bjr_30_55_c53 = mpl_cm('diverging_linear_bjr_30_55_c53',diverging_linear_bjr_30_55_c53)
3233 m_diverging_linear_bjr_30_55_c53_r = mpl_cm('diverging_linear_bjr_30_55_c53_r',list(reversed(diverging_linear_bjr_30_55_c53)))
3234
3235
3236
3237
3238 diverging_linear_bjy_30_90_c45 = [\
3239 [0.077854, 0.19343, 0.75827],
3240 [0.095213, 0.19629, 0.7569],
3241 [0.11007, 0.1991, 0.75553],
3242 [0.12317, 0.20194, 0.75416],
3243 [0.13514, 0.20481, 0.75279],
3244 [0.14608, 0.20765, 0.75143],
3245 [0.15626, 0.21049, 0.75004],
3246 [0.16572, 0.21333, 0.74867],
3247 [0.17472, 0.21621, 0.7473],
3248 [0.18318, 0.21905, 0.74592],
3249 [0.19126, 0.22188, 0.74454],
3250 [0.19897, 0.22472, 0.74317],
3251 [0.20641, 0.2276, 0.74178],
3252 [0.21348, 0.23044, 0.7404],
3253 [0.22035, 0.23329, 0.73902],
3254 [0.22695, 0.23617, 0.73763],
3255 [0.23332, 0.23902, 0.73624],
3256 [0.23953, 0.24188, 0.73486],
3257 [0.24552, 0.24472, 0.73347],
3258 [0.25139, 0.24761, 0.73208],
3259 [0.25706, 0.25045, 0.73069],
3260 [0.26259, 0.25333, 0.72929],
3261 [0.26797, 0.25618, 0.7279],
3262 [0.27326, 0.25907, 0.7265],
3263 [0.2784, 0.26192, 0.72511],
3264 [0.28343, 0.26478, 0.7237],
3265 [0.28834, 0.26764, 0.7223],
3266 [0.29316, 0.27055, 0.7209],
3267 [0.29788, 0.27341, 0.7195],
3268 [0.3025, 0.27629, 0.71809],
3269 [0.30706, 0.27916, 0.71668],
3270 [0.31151, 0.28204, 0.71527],
3271 [0.3159, 0.2849, 0.71386],
3272 [0.3202, 0.28778, 0.71244],
3273 [0.32441, 0.29066, 0.71103],
3274 [0.32858, 0.29354, 0.70962],
3275 [0.33268, 0.29643, 0.7082],
3276 [0.33669, 0.29932, 0.70678],
3277 [0.34065, 0.30219, 0.70535],
3278 [0.34455, 0.30509, 0.70393],
3279 [0.34839, 0.30797, 0.7025],
3280 [0.35217, 0.31088, 0.70108],
3281 [0.35592, 0.31377, 0.69964],
3282 [0.35959, 0.31666, 0.69821],
3283 [0.36322, 0.31955, 0.69678],
3284 [0.36681, 0.32245, 0.69535],
3285 [0.37033, 0.32533, 0.6939],
3286 [0.37383, 0.32824, 0.69247],
3287 [0.37727, 0.33113, 0.69102],
3288 [0.38067, 0.33405, 0.68958],
3289 [0.38403, 0.33695, 0.68814],
3290 [0.38734, 0.33986, 0.68669],
3291 [0.39062, 0.34277, 0.68524],
3292 [0.39386, 0.34566, 0.68378],
3293 [0.39705, 0.34858, 0.68232],
3294 [0.40023, 0.35149, 0.68086],
3295 [0.40336, 0.35441, 0.67941],
3296 [0.40645, 0.35733, 0.67795],
3297 [0.40951, 0.36023, 0.67649],
3298 [0.41254, 0.36315, 0.67502],
3299 [0.41553, 0.36607, 0.67355],
3300 [0.41848, 0.36899, 0.67208],
3301 [0.42141, 0.3719, 0.67061],
3302 [0.42432, 0.37484, 0.66913],
3303 [0.4272, 0.37776, 0.66765],
3304 [0.43004, 0.38069, 0.66616],
3305 [0.43285, 0.38362, 0.66468],
3306 [0.43564, 0.38654, 0.6632],
3307 [0.4384, 0.38948, 0.66171],
3308 [0.44113, 0.39241, 0.66021],
3309 [0.44384, 0.39535, 0.65871],
3310 [0.44652, 0.39829, 0.65722],
3311 [0.44918, 0.40123, 0.65572],
3312 [0.45181, 0.40416, 0.65421],
3313 [0.45442, 0.4071, 0.6527],
3314 [0.45699, 0.41005, 0.6512],
3315 [0.45955, 0.413, 0.64969],
3316 [0.46209, 0.41594, 0.64817],
3317 [0.46461, 0.41888, 0.64665],
3318 [0.4671, 0.42183, 0.64513],
3319 [0.46957, 0.42479, 0.6436],
3320 [0.47202, 0.42775, 0.64208],
3321 [0.47444, 0.4307, 0.64055],
3322 [0.47685, 0.43364, 0.63902],
3323 [0.47923, 0.43661, 0.63748],
3324 [0.4816, 0.43957, 0.63594],
3325 [0.48394, 0.44254, 0.6344],
3326 [0.48627, 0.44549, 0.63285],
3327 [0.48858, 0.44846, 0.6313],
3328 [0.49088, 0.45143, 0.62974],
3329 [0.49313, 0.4544, 0.62819],
3330 [0.49539, 0.45736, 0.62663],
3331 [0.49763, 0.46033, 0.62506],
3332 [0.49983, 0.4633, 0.6235],
3333 [0.50204, 0.46628, 0.62192],
3334 [0.50422, 0.46927, 0.62036],
3335 [0.50637, 0.47224, 0.61878],
3336 [0.50853, 0.47522, 0.61719],
3337 [0.51065, 0.47819, 0.6156],
3338 [0.51277, 0.48117, 0.61401],
3339 [0.51487, 0.48416, 0.61242],
3340 [0.51695, 0.48715, 0.61083],
3341 [0.51901, 0.49014, 0.60923],
3342 [0.52106, 0.49312, 0.60762],
3343 [0.52309, 0.49611, 0.606],
3344 [0.52511, 0.49911, 0.6044],
3345 [0.52712, 0.50211, 0.60277],
3346 [0.52911, 0.5051, 0.60115],
3347 [0.53107, 0.50811, 0.59953],
3348 [0.53303, 0.5111, 0.59789],
3349 [0.53497, 0.51411, 0.59626],
3350 [0.53691, 0.51711, 0.59462],
3351 [0.53882, 0.5201, 0.59298],
3352 [0.54072, 0.52312, 0.59133],
3353 [0.54261, 0.52613, 0.58967],
3354 [0.54448, 0.52914, 0.58801],
3355 [0.54635, 0.53215, 0.58635],
3356 [0.54819, 0.53516, 0.58469],
3357 [0.55002, 0.53818, 0.58301],
3358 [0.55184, 0.54119, 0.58133],
3359 [0.55364, 0.54421, 0.57966],
3360 [0.55543, 0.54723, 0.57796],
3361 [0.55722, 0.55025, 0.57628],
3362 [0.55898, 0.55327, 0.57457],
3363 [0.56074, 0.55629, 0.57288],
3364 [0.56249, 0.55933, 0.57116],
3365 [0.56422, 0.56236, 0.56945],
3366 [0.56593, 0.56538, 0.56773],
3367 [0.56883, 0.56809, 0.5657],
3368 [0.57292, 0.57047, 0.56336],
3369 [0.57698, 0.57287, 0.56099],
3370 [0.58101, 0.57525, 0.55863],
3371 [0.58503, 0.57764, 0.55626],
3372 [0.58901, 0.58005, 0.55389],
3373 [0.59299, 0.58244, 0.55151],
3374 [0.59693, 0.58486, 0.54913],
3375 [0.60085, 0.58726, 0.54673],
3376 [0.60476, 0.58967, 0.54433],
3377 [0.60865, 0.5921, 0.54191],
3378 [0.6125, 0.59451, 0.5395],
3379 [0.61635, 0.59694, 0.53708],
3380 [0.62018, 0.59936, 0.53465],
3381 [0.62399, 0.60179, 0.53221],
3382 [0.62777, 0.60423, 0.52976],
3383 [0.63154, 0.60666, 0.52731],
3384 [0.6353, 0.6091, 0.52484],
3385 [0.63904, 0.61154, 0.52237],
3386 [0.64276, 0.61398, 0.51989],
3387 [0.64646, 0.61644, 0.51741],
3388 [0.65015, 0.61889, 0.51491],
3389 [0.65382, 0.62134, 0.5124],
3390 [0.65749, 0.62381, 0.50989],
3391 [0.66112, 0.62626, 0.50736],
3392 [0.66475, 0.62873, 0.50483],
3393 [0.66837, 0.6312, 0.50229],
3394 [0.67197, 0.63367, 0.49973],
3395 [0.67556, 0.63615, 0.49717],
3396 [0.67913, 0.63862, 0.4946],
3397 [0.68269, 0.6411, 0.49202],
3398 [0.68624, 0.64358, 0.48942],
3399 [0.68978, 0.64607, 0.48682],
3400 [0.6933, 0.64856, 0.4842],
3401 [0.69681, 0.65106, 0.48158],
3402 [0.70031, 0.65355, 0.47894],
3403 [0.7038, 0.65605, 0.47629],
3404 [0.70727, 0.65855, 0.47362],
3405 [0.71074, 0.66105, 0.47096],
3406 [0.71419, 0.66357, 0.46826],
3407 [0.71764, 0.66607, 0.46556],
3408 [0.72106, 0.66859, 0.46285],
3409 [0.72449, 0.6711, 0.46013],
3410 [0.7279, 0.67362, 0.45739],
3411 [0.7313, 0.67614, 0.45465],
3412 [0.73469, 0.67866, 0.45188],
3413 [0.73807, 0.68119, 0.4491],
3414 [0.74144, 0.68372, 0.4463],
3415 [0.74481, 0.68625, 0.44349],
3416 [0.74816, 0.68879, 0.44066],
3417 [0.75151, 0.69132, 0.43783],
3418 [0.75485, 0.69386, 0.43497],
3419 [0.75817, 0.69641, 0.4321],
3420 [0.76149, 0.69895, 0.42919],
3421 [0.7648, 0.7015, 0.42628],
3422 [0.7681, 0.70405, 0.42335],
3423 [0.7714, 0.70661, 0.42041],
3424 [0.77468, 0.70917, 0.41745],
3425 [0.77796, 0.71173, 0.41446],
3426 [0.78123, 0.71428, 0.41146],
3427 [0.7845, 0.71685, 0.40844],
3428 [0.78775, 0.71942, 0.4054],
3429 [0.79099, 0.72198, 0.40232],
3430 [0.79424, 0.72456, 0.39924],
3431 [0.79747, 0.72713, 0.39614],
3432 [0.8007, 0.72971, 0.393],
3433 [0.80392, 0.73229, 0.38984],
3434 [0.80713, 0.73487, 0.38666],
3435 [0.81033, 0.73745, 0.38347],
3436 [0.81354, 0.74005, 0.38023],
3437 [0.81673, 0.74263, 0.37698],
3438 [0.81992, 0.74522, 0.37369],
3439 [0.8231, 0.74782, 0.37037],
3440 [0.82628, 0.75041, 0.36704],
3441 [0.82945, 0.75301, 0.36366],
3442 [0.83261, 0.75561, 0.36026],
3443 [0.83577, 0.75822, 0.35684],
3444 [0.83892, 0.76082, 0.35336],
3445 [0.84207, 0.76343, 0.34987],
3446 [0.84521, 0.76604, 0.34632],
3447 [0.84834, 0.76865, 0.34277],
3448 [0.85147, 0.77127, 0.33916],
3449 [0.8546, 0.77388, 0.33551],
3450 [0.85772, 0.77651, 0.33181],
3451 [0.86083, 0.77913, 0.32808],
3452 [0.86395, 0.78175, 0.3243],
3453 [0.86705, 0.78438, 0.3205],
3454 [0.87015, 0.78701, 0.31662],
3455 [0.87324, 0.78964, 0.31269],
3456 [0.87633, 0.79227, 0.30875],
3457 [0.87942, 0.79491, 0.30472],
3458 [0.8825, 0.79754, 0.30064],
3459 [0.88558, 0.80019, 0.29651],
3460 [0.88866, 0.80283, 0.29232],
3461 [0.89172, 0.80547, 0.28806],
3462 [0.89479, 0.80812, 0.28374],
3463 [0.89785, 0.81077, 0.27936],
3464 [0.9009, 0.81342, 0.27488],
3465 [0.90395, 0.81607, 0.27036],
3466 [0.907, 0.81872, 0.26572],
3467 [0.91005, 0.82138, 0.26101],
3468 [0.91309, 0.82404, 0.2562],
3469 [0.91612, 0.82671, 0.25133],
3470 [0.91915, 0.82937, 0.24631],
3471 [0.92219, 0.83204, 0.24121],
3472 [0.92521, 0.8347, 0.236],
3473 [0.92823, 0.83737, 0.23064],
3474 [0.93125, 0.84005, 0.22515],
3475 [0.93426, 0.84272, 0.21954],
3476 [0.93728, 0.84539, 0.21376],
3477 [0.94029, 0.84807, 0.20781],
3478 [0.94329, 0.85075, 0.20166],
3479 [0.94629, 0.85343, 0.19535],
3480 [0.94929, 0.85612, 0.18881],
3481 [0.95229, 0.8588, 0.18199],
3482 [0.95528, 0.86149, 0.17496],
3483 [0.95827, 0.86419, 0.16758],
3484 [0.96125, 0.86687, 0.15984],
3485 [0.96424, 0.86957, 0.15175],
3486 [0.96722, 0.87227, 0.1432],
3487 [0.9702, 0.87497, 0.13412],
3488 [0.97317, 0.87767, 0.12434],
3489 [0.97614, 0.88037, 0.11385],
3490 [0.97911, 0.88307, 0.10233],
3491 [0.98208, 0.88578, 0.089538],
3492 [0.98505, 0.88849, 0.07491],
3493 [0.98801, 0.8912, 0.057534],
3494 [0.99097, 0.89391, 0.035647],
3495 ]
3496 b_diverging_linear_bjy_30_90_c45 = bokeh_palette('diverging_linear_bjy_30_90_c45',diverging_linear_bjy_30_90_c45)
3497 m_diverging_linear_bjy_30_90_c45 = mpl_cm('diverging_linear_bjy_30_90_c45',diverging_linear_bjy_30_90_c45)
3498 m_diverging_linear_bjy_30_90_c45_r = mpl_cm('diverging_linear_bjy_30_90_c45_r',list(reversed(diverging_linear_bjy_30_90_c45)))
3499 bjy = b_diverging_linear_bjy_30_90_c45
3500 m_bjy = m_diverging_linear_bjy_30_90_c45
3501 m_bjy_r = m_diverging_linear_bjy_30_90_c45_r
3502 palette['bjy'] = b_diverging_linear_bjy_30_90_c45
3503 cm['bjy'] = m_diverging_linear_bjy_30_90_c45
3504 cm['bjy_r'] = m_diverging_linear_bjy_30_90_c45_r
3505 register_cmap('cet_bjy',m_diverging_linear_bjy_30_90_c45)
3506 register_cmap('cet_bjy_r',m_diverging_linear_bjy_30_90_c45_r)
3507
3508
3509
3510
3511 diverging_rainbow_bgymr_45_85_c67 = [\
3512 [0.032081, 0.36182, 0.97348],
3513 [0.05836, 0.37092, 0.95845],
3514 [0.075961, 0.37984, 0.94345],
3515 [0.088784, 0.38858, 0.92847],
3516 [0.098335, 0.39714, 0.91352],
3517 [0.10538, 0.40555, 0.89858],
3518 [0.1105, 0.4138, 0.88367],
3519 [0.1138, 0.42191, 0.86877],
3520 [0.11557, 0.4299, 0.85388],
3521 [0.11592, 0.43777, 0.83902],
3522 [0.11487, 0.44549, 0.82416],
3523 [0.11266, 0.45311, 0.80932],
3524 [0.10918, 0.46059, 0.79447],
3525 [0.10455, 0.46796, 0.77961],
3526 [0.099069, 0.47521, 0.76474],
3527 [0.092835, 0.4823, 0.74982],
3528 [0.08633, 0.48923, 0.73486],
3529 [0.080053, 0.496, 0.71982],
3530 [0.074782, 0.50259, 0.70469],
3531 [0.071457, 0.50899, 0.68944],
3532 [0.07085, 0.51517, 0.67403],
3533 [0.073695, 0.52113, 0.65846],
3534 [0.079835, 0.52688, 0.64271],
3535 [0.089012, 0.5324, 0.62676],
3536 [0.10026, 0.53772, 0.61062],
3537 [0.11288, 0.54284, 0.59428],
3538 [0.126, 0.54779, 0.57774],
3539 [0.1391, 0.55261, 0.56104],
3540 [0.15183, 0.55732, 0.54417],
3541 [0.16388, 0.56193, 0.52714],
3542 [0.17497, 0.56648, 0.50997],
3543 [0.18508, 0.57098, 0.49266],
3544 [0.19412, 0.57547, 0.47524],
3545 [0.20204, 0.57994, 0.45766],
3546 [0.20895, 0.58441, 0.43995],
3547 [0.21483, 0.58888, 0.4221],
3548 [0.21979, 0.59337, 0.40411],
3549 [0.22384, 0.59785, 0.38597],
3550 [0.22711, 0.60234, 0.36769],
3551 [0.22964, 0.60683, 0.3493],
3552 [0.23163, 0.6113, 0.33081],
3553 [0.23311, 0.61574, 0.3123],
3554 [0.23437, 0.62014, 0.29385],
3555 [0.23553, 0.62448, 0.27559],
3556 [0.23686, 0.62873, 0.25761],
3557 [0.23856, 0.63287, 0.24012],
3558 [0.24094, 0.63689, 0.22333],
3559 [0.24418, 0.64076, 0.2074],
3560 [0.2485, 0.64447, 0.19256],
3561 [0.25393, 0.64801, 0.17902],
3562 [0.26052, 0.65139, 0.16694],
3563 [0.26821, 0.65459, 0.15642],
3564 [0.2769, 0.65765, 0.14749],
3565 [0.28638, 0.66054, 0.14012],
3566 [0.29654, 0.66333, 0.13429],
3567 [0.30712, 0.666, 0.12971],
3568 [0.318, 0.6686, 0.12623],
3569 [0.32904, 0.67112, 0.12356],
3570 [0.34011, 0.6736, 0.12159],
3571 [0.35116, 0.67603, 0.1201],
3572 [0.36212, 0.67844, 0.11895],
3573 [0.37296, 0.68081, 0.11798],
3574 [0.38369, 0.68318, 0.11711],
3575 [0.39426, 0.68554, 0.11638],
3576 [0.40469, 0.68788, 0.11563],
3577 [0.415, 0.69021, 0.11486],
3578 [0.42518, 0.69254, 0.11414],
3579 [0.43523, 0.69484, 0.11344],
3580 [0.44516, 0.69715, 0.11268],
3581 [0.455, 0.69945, 0.1119],
3582 [0.46473, 0.70173, 0.11112],
3583 [0.47437, 0.70402, 0.11034],
3584 [0.48392, 0.7063, 0.10954],
3585 [0.4934, 0.70856, 0.10866],
3586 [0.50281, 0.71081, 0.10783],
3587 [0.51215, 0.71306, 0.10703],
3588 [0.52142, 0.7153, 0.10617],
3589 [0.53064, 0.71754, 0.10523],
3590 [0.53978, 0.71976, 0.10434],
3591 [0.5489, 0.72197, 0.10349],
3592 [0.55794, 0.72417, 0.10255],
3593 [0.56694, 0.72637, 0.1016],
3594 [0.5759, 0.72856, 0.10065],
3595 [0.58481, 0.73074, 0.099684],
3596 [0.59368, 0.73292, 0.098715],
3597 [0.60252, 0.73509, 0.097735],
3598 [0.61132, 0.73724, 0.096645],
3599 [0.62009, 0.73939, 0.095664],
3600 [0.62882, 0.74152, 0.094646],
3601 [0.63752, 0.74366, 0.09351],
3602 [0.64619, 0.74578, 0.092435],
3603 [0.65483, 0.7479, 0.091367],
3604 [0.66346, 0.75, 0.090209],
3605 [0.67205, 0.7521, 0.089055],
3606 [0.68061, 0.75419, 0.087892],
3607 [0.68917, 0.75627, 0.086685],
3608 [0.69769, 0.75835, 0.085411],
3609 [0.7062, 0.76041, 0.084247],
3610 [0.71468, 0.76246, 0.082921],
3611 [0.72315, 0.76451, 0.081681],
3612 [0.73161, 0.76655, 0.0803],
3613 [0.74005, 0.76858, 0.078922],
3614 [0.74847, 0.77061, 0.077534],
3615 [0.75687, 0.77262, 0.076136],
3616 [0.76527, 0.77462, 0.074724],
3617 [0.77364, 0.77663, 0.07331],
3618 [0.78201, 0.77861, 0.071765],
3619 [0.79036, 0.78059, 0.070194],
3620 [0.7987, 0.78257, 0.068669],
3621 [0.80704, 0.78453, 0.067],
3622 [0.81535, 0.78649, 0.065324],
3623 [0.82366, 0.78843, 0.063634],
3624 [0.83198, 0.79037, 0.061832],
3625 [0.84029, 0.7923, 0.060168],
3626 [0.84859, 0.7942, 0.058382],
3627 [0.85689, 0.79607, 0.056834],
3628 [0.8652, 0.79789, 0.055378],
3629 [0.87351, 0.79966, 0.054292],
3630 [0.88182, 0.80132, 0.053775],
3631 [0.89012, 0.80285, 0.054093],
3632 [0.8984, 0.8042, 0.055566],
3633 [0.90662, 0.8053, 0.058415],
3634 [0.91475, 0.80608, 0.063031],
3635 [0.92272, 0.80648, 0.069366],
3636 [0.93047, 0.80641, 0.077301],
3637 [0.9379, 0.80582, 0.08703],
3638 [0.94493, 0.80465, 0.097983],
3639 [0.95147, 0.80288, 0.10998],
3640 [0.95744, 0.80051, 0.12259],
3641 [0.9628, 0.79755, 0.1357],
3642 [0.9675, 0.79406, 0.14898],
3643 [0.97155, 0.79007, 0.16223],
3644 [0.97499, 0.78567, 0.17523],
3645 [0.97786, 0.78094, 0.18795],
3646 [0.98025, 0.77593, 0.20021],
3647 [0.98222, 0.77073, 0.21212],
3648 [0.98385, 0.76537, 0.22355],
3649 [0.98522, 0.75991, 0.23457],
3650 [0.98638, 0.75438, 0.24514],
3651 [0.9874, 0.74879, 0.25538],
3652 [0.98831, 0.74317, 0.26524],
3653 [0.98914, 0.73751, 0.27479],
3654 [0.98991, 0.73185, 0.28406],
3655 [0.99062, 0.72616, 0.29307],
3656 [0.9913, 0.72045, 0.30183],
3657 [0.99194, 0.71474, 0.3104],
3658 [0.99255, 0.70902, 0.31874],
3659 [0.99314, 0.70327, 0.32691],
3660 [0.99369, 0.6975, 0.33494],
3661 [0.99421, 0.69172, 0.34279],
3662 [0.9947, 0.68593, 0.35051],
3663 [0.99516, 0.68011, 0.35809],
3664 [0.9956, 0.67428, 0.36554],
3665 [0.996, 0.66843, 0.37289],
3666 [0.99638, 0.66256, 0.38013],
3667 [0.99672, 0.65667, 0.38727],
3668 [0.99704, 0.65075, 0.39432],
3669 [0.99732, 0.64482, 0.40128],
3670 [0.99758, 0.63886, 0.40815],
3671 [0.99781, 0.63289, 0.41495],
3672 [0.99801, 0.62688, 0.42166],
3673 [0.99818, 0.62086, 0.42832],
3674 [0.99832, 0.6148, 0.43492],
3675 [0.99843, 0.60874, 0.44143],
3676 [0.99851, 0.60262, 0.44789],
3677 [0.99857, 0.59649, 0.45431],
3678 [0.99859, 0.59033, 0.46065],
3679 [0.99858, 0.58414, 0.46696],
3680 [0.99855, 0.57791, 0.4732],
3681 [0.99848, 0.57166, 0.47942],
3682 [0.99839, 0.56537, 0.48557],
3683 [0.99827, 0.55905, 0.4917],
3684 [0.99812, 0.5527, 0.49778],
3685 [0.99793, 0.54631, 0.50381],
3686 [0.99772, 0.53987, 0.50981],
3687 [0.99748, 0.53339, 0.51577],
3688 [0.99721, 0.52689, 0.52171],
3689 [0.99692, 0.52032, 0.52761],
3690 [0.99659, 0.51372, 0.53348],
3691 [0.99623, 0.50706, 0.53932],
3692 [0.99585, 0.50036, 0.54514],
3693 [0.99543, 0.4936, 0.55092],
3694 [0.99499, 0.4868, 0.55668],
3695 [0.99451, 0.47994, 0.56242],
3696 [0.99401, 0.473, 0.56813],
3697 [0.99348, 0.46601, 0.57381],
3698 [0.99292, 0.45897, 0.57948],
3699 [0.99232, 0.45185, 0.58513],
3700 [0.9917, 0.44466, 0.59074],
3701 [0.99105, 0.43739, 0.59635],
3702 [0.99036, 0.43003, 0.60193],
3703 [0.98965, 0.42258, 0.60751],
3704 [0.98891, 0.41506, 0.61304],
3705 [0.98813, 0.40745, 0.61855],
3706 [0.98733, 0.39973, 0.62399],
3707 [0.98649, 0.39194, 0.62934],
3708 [0.98562, 0.38405, 0.63457],
3709 [0.98472, 0.37608, 0.63961],
3710 [0.98378, 0.36804, 0.64438],
3711 [0.98281, 0.35995, 0.64878],
3712 [0.98181, 0.35183, 0.65266],
3713 [0.98078, 0.34373, 0.65588],
3714 [0.97973, 0.3357, 0.65825],
3715 [0.97864, 0.32775, 0.65959],
3716 [0.97754, 0.31999, 0.65974],
3717 [0.97642, 0.3124, 0.65853],
3718 [0.97528, 0.30511, 0.65589],
3719 [0.97411, 0.29808, 0.65173],
3720 [0.97292, 0.2914, 0.64606],
3721 [0.97169, 0.285, 0.63895],
3722 [0.97041, 0.27897, 0.63052],
3723 [0.96907, 0.2732, 0.62092],
3724 [0.96766, 0.26768, 0.61031],
3725 [0.96618, 0.26243, 0.5989],
3726 [0.96461, 0.25735, 0.58686],
3727 [0.96297, 0.2524, 0.57435],
3728 [0.96124, 0.24756, 0.56152],
3729 [0.95942, 0.24278, 0.54846],
3730 [0.95753, 0.23806, 0.53526],
3731 [0.95556, 0.23335, 0.52198],
3732 [0.95351, 0.22869, 0.50869],
3733 [0.95138, 0.22398, 0.49537],
3734 [0.94918, 0.2193, 0.48207],
3735 [0.94691, 0.21459, 0.4688],
3736 [0.94457, 0.20987, 0.45555],
3737 [0.94216, 0.20512, 0.44234],
3738 [0.93968, 0.20033, 0.42915],
3739 [0.93714, 0.19555, 0.416],
3740 [0.93453, 0.19073, 0.40287],
3741 [0.93185, 0.1859, 0.38976],
3742 [0.92911, 0.18098, 0.3767],
3743 [0.92631, 0.17605, 0.36362],
3744 [0.92345, 0.17111, 0.35059],
3745 [0.92052, 0.16609, 0.33755],
3746 [0.91755, 0.16106, 0.32451],
3747 [0.9145, 0.15595, 0.31148],
3748 [0.9114, 0.15076, 0.29845],
3749 [0.90825, 0.14556, 0.2854],
3750 [0.90503, 0.1402, 0.27233],
3751 [0.90176, 0.13484, 0.25926],
3752 [0.89844, 0.12932, 0.24609],
3753 [0.89507, 0.12371, 0.23288],
3754 [0.89164, 0.11805, 0.21961],
3755 [0.88816, 0.11221, 0.20623],
3756 [0.88463, 0.10623, 0.19268],
3757 [0.88106, 0.10002, 0.17898],
3758 [0.87743, 0.093639, 0.16503],
3759 [0.87376, 0.087085, 0.15083],
3760 [0.87004, 0.08013, 0.13619],
3761 [0.86629, 0.072935, 0.12107],
3762 [0.86249, 0.065249, 0.10524],
3763 [0.85864, 0.057063, 0.088412],
3764 [0.85476, 0.048151, 0.069991],
3765 [0.85083, 0.038404, 0.048987],
3766 [0.84687, 0.028128, 0.024389],
3767 [0.84287, 0.018301, 0.0015175],
3768 ]
3769 b_diverging_rainbow_bgymr_45_85_c67 = bokeh_palette('diverging_rainbow_bgymr_45_85_c67',diverging_rainbow_bgymr_45_85_c67)
3770 m_diverging_rainbow_bgymr_45_85_c67 = mpl_cm('diverging_rainbow_bgymr_45_85_c67',diverging_rainbow_bgymr_45_85_c67)
3771 m_diverging_rainbow_bgymr_45_85_c67_r = mpl_cm('diverging_rainbow_bgymr_45_85_c67_r',list(reversed(diverging_rainbow_bgymr_45_85_c67)))
3772
3773
3774
3775
3776 diverging_bkr_55_10_c35 = [\
3777 [0.097481, 0.50736, 0.98205],
3778 [0.1033, 0.50389, 0.97428],
3779 [0.10863, 0.50041, 0.96653],
3780 [0.11369, 0.49694, 0.9588],
3781 [0.11841, 0.49348, 0.95107],
3782 [0.12275, 0.49002, 0.94336],
3783 [0.12692, 0.48657, 0.93566],
3784 [0.13089, 0.48312, 0.92796],
3785 [0.1346, 0.47968, 0.92028],
3786 [0.13811, 0.47624, 0.91262],
3787 [0.14143, 0.4728, 0.90497],
3788 [0.14458, 0.46938, 0.89732],
3789 [0.14758, 0.46594, 0.88969],
3790 [0.15043, 0.46252, 0.88207],
3791 [0.15312, 0.45912, 0.87446],
3792 [0.15574, 0.4557, 0.86687],
3793 [0.1582, 0.4523, 0.85929],
3794 [0.16051, 0.4489, 0.85172],
3795 [0.16277, 0.44549, 0.84416],
3796 [0.16488, 0.44211, 0.83662],
3797 [0.16693, 0.43871, 0.82909],
3798 [0.16886, 0.43534, 0.82157],
3799 [0.17068, 0.43197, 0.81406],
3800 [0.17242, 0.42859, 0.80657],
3801 [0.17409, 0.42522, 0.79909],
3802 [0.17566, 0.42185, 0.79162],
3803 [0.17718, 0.41849, 0.78417],
3804 [0.17862, 0.41515, 0.77672],
3805 [0.17995, 0.4118, 0.76929],
3806 [0.18122, 0.40846, 0.76187],
3807 [0.18243, 0.40512, 0.75448],
3808 [0.18359, 0.40179, 0.74709],
3809 [0.18468, 0.39847, 0.73972],
3810 [0.18572, 0.39515, 0.73235],
3811 [0.18665, 0.39183, 0.725],
3812 [0.18758, 0.38852, 0.71767],
3813 [0.18841, 0.38521, 0.71034],
3814 [0.18918, 0.38191, 0.70304],
3815 [0.1899, 0.37862, 0.69574],
3816 [0.19058, 0.37533, 0.68847],
3817 [0.1912, 0.37204, 0.68119],
3818 [0.19177, 0.36878, 0.67395],
3819 [0.1923, 0.3655, 0.6667],
3820 [0.19277, 0.36224, 0.65948],
3821 [0.1932, 0.35896, 0.65228],
3822 [0.19358, 0.35572, 0.64508],
3823 [0.19393, 0.35246, 0.6379],
3824 [0.19422, 0.34922, 0.63074],
3825 [0.19446, 0.34597, 0.62359],
3826 [0.19466, 0.34276, 0.61645],
3827 [0.19481, 0.33953, 0.60933],
3828 [0.19492, 0.33629, 0.60222],
3829 [0.19499, 0.33309, 0.59513],
3830 [0.19502, 0.32988, 0.58805],
3831 [0.19502, 0.32665, 0.58099],
3832 [0.19497, 0.32346, 0.57394],
3833 [0.19489, 0.32028, 0.56692],
3834 [0.19477, 0.31708, 0.55991],
3835 [0.19462, 0.31391, 0.5529],
3836 [0.19442, 0.31074, 0.54593],
3837 [0.19419, 0.30755, 0.53895],
3838 [0.19391, 0.30439, 0.532],
3839 [0.1936, 0.30123, 0.52507],
3840 [0.19325, 0.29808, 0.51815],
3841 [0.19288, 0.29493, 0.51124],
3842 [0.19247, 0.29181, 0.50436],
3843 [0.19202, 0.28867, 0.49749],
3844 [0.19154, 0.28553, 0.49064],
3845 [0.19103, 0.28244, 0.48379],
3846 [0.19049, 0.27932, 0.47697],
3847 [0.18992, 0.27622, 0.47017],
3848 [0.18932, 0.27311, 0.46338],
3849 [0.18869, 0.27002, 0.45661],
3850 [0.18804, 0.26691, 0.44986],
3851 [0.18733, 0.26385, 0.44313],
3852 [0.18658, 0.26076, 0.43641],
3853 [0.18585, 0.25769, 0.42971],
3854 [0.18505, 0.25465, 0.42302],
3855 [0.18421, 0.25159, 0.41637],
3856 [0.18335, 0.24855, 0.40972],
3857 [0.18247, 0.24548, 0.40309],
3858 [0.18156, 0.24245, 0.39648],
3859 [0.18062, 0.23944, 0.38989],
3860 [0.17967, 0.23642, 0.38333],
3861 [0.17869, 0.23338, 0.37678],
3862 [0.17768, 0.23038, 0.37023],
3863 [0.17659, 0.2274, 0.36372],
3864 [0.17551, 0.22438, 0.35724],
3865 [0.17442, 0.22142, 0.35076],
3866 [0.17327, 0.21845, 0.34429],
3867 [0.17211, 0.21547, 0.33785],
3868 [0.17093, 0.21251, 0.33143],
3869 [0.16973, 0.20955, 0.32503],
3870 [0.16847, 0.20663, 0.31867],
3871 [0.16721, 0.20368, 0.3123],
3872 [0.16588, 0.20071, 0.30599],
3873 [0.16458, 0.1978, 0.29967],
3874 [0.16324, 0.1949, 0.29336],
3875 [0.16187, 0.19198, 0.28708],
3876 [0.16042, 0.18908, 0.28083],
3877 [0.15902, 0.1862, 0.27461],
3878 [0.15755, 0.18329, 0.26841],
3879 [0.1561, 0.18041, 0.26222],
3880 [0.15456, 0.17758, 0.25605],
3881 [0.15302, 0.17471, 0.2499],
3882 [0.15147, 0.17184, 0.24379],
3883 [0.14991, 0.16902, 0.23772],
3884 [0.14827, 0.16616, 0.23164],
3885 [0.14665, 0.16336, 0.22559],
3886 [0.14505, 0.16051, 0.21957],
3887 [0.14339, 0.15773, 0.21357],
3888 [0.14175, 0.15496, 0.20763],
3889 [0.14009, 0.1522, 0.20171],
3890 [0.13851, 0.14952, 0.19588],
3891 [0.13692, 0.1468, 0.19008],
3892 [0.13541, 0.14419, 0.18437],
3893 [0.134, 0.14163, 0.17876],
3894 [0.13268, 0.1391, 0.17324],
3895 [0.1315, 0.1367, 0.16787],
3896 [0.13053, 0.13444, 0.16268],
3897 [0.12973, 0.13226, 0.15764],
3898 [0.12916, 0.13028, 0.15284],
3899 [0.12891, 0.12842, 0.1483],
3900 [0.12899, 0.12676, 0.14407],
3901 [0.12945, 0.12536, 0.14011],
3902 [0.13031, 0.12415, 0.13652],
3903 [0.13151, 0.12321, 0.13332],
3904 [0.13315, 0.12253, 0.13051],
3905 [0.13523, 0.12211, 0.12804],
3906 [0.13775, 0.12196, 0.126],
3907 [0.14065, 0.12206, 0.12429],
3908 [0.14394, 0.12241, 0.12299],
3909 [0.14762, 0.12299, 0.12205],
3910 [0.15161, 0.12379, 0.12145],
3911 [0.15595, 0.12478, 0.12115],
3912 [0.1605, 0.12596, 0.12111],
3913 [0.16531, 0.1272, 0.12131],
3914 [0.17036, 0.12863, 0.12171],
3915 [0.17553, 0.13018, 0.12228],
3916 [0.18085, 0.13174, 0.12299],
3917 [0.1863, 0.13339, 0.12382],
3918 [0.1918, 0.1351, 0.12474],
3919 [0.19738, 0.13681, 0.12575],
3920 [0.20301, 0.13858, 0.12675],
3921 [0.20867, 0.14035, 0.12784],
3922 [0.21437, 0.14214, 0.12891],
3923 [0.2201, 0.14394, 0.13008],
3924 [0.22584, 0.14575, 0.13119],
3925 [0.23158, 0.14753, 0.13232],
3926 [0.23735, 0.14933, 0.13347],
3927 [0.24308, 0.15109, 0.13464],
3928 [0.24887, 0.15287, 0.13574],
3929 [0.25465, 0.15465, 0.13692],
3930 [0.26041, 0.15645, 0.1381],
3931 [0.26621, 0.15821, 0.1392],
3932 [0.27198, 0.15993, 0.14038],
3933 [0.27781, 0.16174, 0.14154],
3934 [0.28361, 0.16349, 0.14269],
3935 [0.28944, 0.16518, 0.14384],
3936 [0.29526, 0.16697, 0.14501],
3937 [0.30109, 0.16869, 0.14614],
3938 [0.30695, 0.17041, 0.1473],
3939 [0.3128, 0.17212, 0.14842],
3940 [0.31867, 0.17385, 0.14962],
3941 [0.32454, 0.17555, 0.15074],
3942 [0.33043, 0.17728, 0.15189],
3943 [0.33632, 0.17898, 0.15304],
3944 [0.34224, 0.18066, 0.1542],
3945 [0.34815, 0.18235, 0.15536],
3946 [0.35407, 0.18405, 0.15654],
3947 [0.36001, 0.18576, 0.15766],
3948 [0.36596, 0.18743, 0.15884],
3949 [0.3719, 0.18909, 0.15995],
3950 [0.37787, 0.19075, 0.16115],
3951 [0.38385, 0.19241, 0.16231],
3952 [0.38983, 0.1941, 0.16346],
3953 [0.39584, 0.19573, 0.1646],
3954 [0.40184, 0.19738, 0.16573],
3955 [0.40786, 0.19901, 0.16693],
3956 [0.41389, 0.20064, 0.16806],
3957 [0.41994, 0.20228, 0.16925],
3958 [0.42598, 0.20394, 0.17038],
3959 [0.43206, 0.20555, 0.17153],
3960 [0.43813, 0.20718, 0.17269],
3961 [0.44421, 0.20879, 0.17385],
3962 [0.4503, 0.2104, 0.17502],
3963 [0.4564, 0.21202, 0.17614],
3964 [0.46251, 0.21361, 0.17734],
3965 [0.46864, 0.2152, 0.1785],
3966 [0.47479, 0.21681, 0.17964],
3967 [0.48092, 0.21839, 0.18078],
3968 [0.48709, 0.21998, 0.18194],
3969 [0.49325, 0.22155, 0.1831],
3970 [0.49943, 0.22314, 0.18427],
3971 [0.50562, 0.22468, 0.18546],
3972 [0.51182, 0.22628, 0.18659],
3973 [0.51804, 0.22784, 0.18779],
3974 [0.52426, 0.22938, 0.18892],
3975 [0.53049, 0.23094, 0.19008],
3976 [0.53674, 0.23249, 0.19123],
3977 [0.54299, 0.23403, 0.1924],
3978 [0.54925, 0.23559, 0.19357],
3979 [0.55552, 0.23713, 0.19474],
3980 [0.56181, 0.23863, 0.19589],
3981 [0.5681, 0.24016, 0.19706],
3982 [0.57441, 0.2417, 0.1982],
3983 [0.58073, 0.2432, 0.19936],
3984 [0.58705, 0.24472, 0.20052],
3985 [0.59339, 0.24623, 0.20169],
3986 [0.59974, 0.24776, 0.20286],
3987 [0.60609, 0.24925, 0.20405],
3988 [0.61246, 0.25075, 0.20519],
3989 [0.61885, 0.25225, 0.20639],
3990 [0.62523, 0.25374, 0.20753],
3991 [0.63163, 0.25524, 0.20869],
3992 [0.63803, 0.25671, 0.20986],
3993 [0.64445, 0.25817, 0.21103],
3994 [0.65088, 0.25967, 0.21221],
3995 [0.65732, 0.26113, 0.21335],
3996 [0.66377, 0.2626, 0.21453],
3997 [0.67023, 0.26407, 0.21571],
3998 [0.6767, 0.26552, 0.21688],
3999 [0.68317, 0.26696, 0.21804],
4000 [0.68966, 0.26842, 0.21921],
4001 [0.69616, 0.26988, 0.22039],
4002 [0.70267, 0.27131, 0.22154],
4003 [0.70919, 0.27274, 0.22272],
4004 [0.71571, 0.27418, 0.22387],
4005 [0.72224, 0.27563, 0.22504],
4006 [0.72879, 0.27705, 0.22624],
4007 [0.73535, 0.27847, 0.2274],
4008 [0.74191, 0.27988, 0.22858],
4009 [0.74849, 0.28129, 0.22972],
4010 [0.75508, 0.28272, 0.23091],
4011 [0.76167, 0.28411, 0.23209],
4012 [0.76827, 0.28551, 0.23324],
4013 [0.77488, 0.28691, 0.23444],
4014 [0.78151, 0.28831, 0.23561],
4015 [0.78814, 0.28971, 0.23679],
4016 [0.79478, 0.2911, 0.23795],
4017 [0.80143, 0.29248, 0.23912],
4018 [0.80809, 0.29385, 0.24028],
4019 [0.81476, 0.29523, 0.24148],
4020 [0.82144, 0.29662, 0.24264],
4021 [0.82812, 0.29797, 0.24381],
4022 [0.83482, 0.29935, 0.24499],
4023 [0.84153, 0.3007, 0.24617],
4024 [0.84824, 0.30205, 0.24736],
4025 [0.85497, 0.30341, 0.24855],
4026 [0.8617, 0.30477, 0.2497],
4027 [0.86845, 0.30613, 0.25089],
4028 [0.8752, 0.30745, 0.25208],
4029 [0.88196, 0.30881, 0.25325],
4030 [0.88873, 0.31015, 0.25444],
4031 [0.8955, 0.31147, 0.25561],
4032 [0.90229, 0.31279, 0.25679],
4033 ]
4034 b_diverging_bkr_55_10_c35 = bokeh_palette('diverging_bkr_55_10_c35',diverging_bkr_55_10_c35)
4035 m_diverging_bkr_55_10_c35 = mpl_cm('diverging_bkr_55_10_c35',diverging_bkr_55_10_c35)
4036 m_diverging_bkr_55_10_c35_r = mpl_cm('diverging_bkr_55_10_c35_r',list(reversed(diverging_bkr_55_10_c35)))
4037 bkr = b_diverging_bkr_55_10_c35
4038 m_bkr = m_diverging_bkr_55_10_c35
4039 m_bkr_r = m_diverging_bkr_55_10_c35_r
4040 palette['bkr'] = b_diverging_bkr_55_10_c35
4041 cm['bkr'] = m_diverging_bkr_55_10_c35
4042 cm['bkr_r'] = m_diverging_bkr_55_10_c35_r
4043 register_cmap('cet_bkr',m_diverging_bkr_55_10_c35)
4044 register_cmap('cet_bkr_r',m_diverging_bkr_55_10_c35_r)
4045
4046
4047
4048
4049 diverging_bky_60_10_c30 = [\
4050 [0.056674, 0.57959, 0.98121],
4051 [0.066107, 0.57547, 0.97345],
4052 [0.074463, 0.57135, 0.9657],
4053 [0.081994, 0.56724, 0.95796],
4054 [0.088742, 0.56314, 0.95024],
4055 [0.09499, 0.55904, 0.94252],
4056 [0.10067, 0.55495, 0.93482],
4057 [0.10603, 0.55086, 0.92713],
4058 [0.11098, 0.54678, 0.91945],
4059 [0.1156, 0.54271, 0.91178],
4060 [0.11993, 0.53864, 0.90413],
4061 [0.12401, 0.53457, 0.89649],
4062 [0.1279, 0.53052, 0.88886],
4063 [0.13155, 0.52647, 0.88124],
4064 [0.135, 0.52241, 0.87363],
4065 [0.13827, 0.51838, 0.86604],
4066 [0.14137, 0.51435, 0.85845],
4067 [0.1443, 0.51031, 0.85088],
4068 [0.14707, 0.50628, 0.84333],
4069 [0.14975, 0.50227, 0.83578],
4070 [0.15224, 0.49827, 0.82825],
4071 [0.15465, 0.49426, 0.82073],
4072 [0.15694, 0.49026, 0.81323],
4073 [0.15911, 0.48626, 0.80573],
4074 [0.1612, 0.48228, 0.79826],
4075 [0.16316, 0.4783, 0.79079],
4076 [0.16499, 0.47433, 0.78334],
4077 [0.1668, 0.47036, 0.77589],
4078 [0.16848, 0.46639, 0.76846],
4079 [0.17009, 0.46243, 0.76105],
4080 [0.1716, 0.45849, 0.75365],
4081 [0.17304, 0.45455, 0.74626],
4082 [0.17442, 0.45061, 0.73889],
4083 [0.17569, 0.44668, 0.73153],
4084 [0.17693, 0.44275, 0.72418],
4085 [0.17811, 0.43883, 0.71685],
4086 [0.17917, 0.43493, 0.70953],
4087 [0.18019, 0.43102, 0.70222],
4088 [0.18114, 0.42712, 0.69493],
4089 [0.18204, 0.42322, 0.68765],
4090 [0.18288, 0.41934, 0.68038],
4091 [0.18367, 0.41546, 0.67314],
4092 [0.1844, 0.41158, 0.6659],
4093 [0.18509, 0.40772, 0.65868],
4094 [0.18571, 0.40387, 0.65148],
4095 [0.18626, 0.40001, 0.64428],
4096 [0.18676, 0.39617, 0.6371],
4097 [0.18724, 0.39232, 0.62994],
4098 [0.18767, 0.3885, 0.62279],
4099 [0.18804, 0.38466, 0.61565],
4100 [0.18835, 0.38086, 0.60854],
4101 [0.18861, 0.37705, 0.60143],
4102 [0.18884, 0.37323, 0.59434],
4103 [0.18902, 0.36944, 0.58727],
4104 [0.18916, 0.36565, 0.58021],
4105 [0.18925, 0.36187, 0.57317],
4106 [0.18931, 0.3581, 0.56614],
4107 [0.18932, 0.35433, 0.55913],
4108 [0.18929, 0.35058, 0.55214],
4109 [0.18923, 0.34682, 0.54515],
4110 [0.18912, 0.34307, 0.53819],
4111 [0.18898, 0.33934, 0.53124],
4112 [0.1888, 0.3356, 0.52431],
4113 [0.18859, 0.33187, 0.51739],
4114 [0.18833, 0.32815, 0.51049],
4115 [0.18805, 0.32444, 0.5036],
4116 [0.18772, 0.32075, 0.49673],
4117 [0.18734, 0.31705, 0.48988],
4118 [0.18692, 0.31337, 0.48305],
4119 [0.18649, 0.3097, 0.47624],
4120 [0.18603, 0.30603, 0.46945],
4121 [0.18554, 0.30234, 0.46265],
4122 [0.18499, 0.2987, 0.45589],
4123 [0.1844, 0.29505, 0.44915],
4124 [0.18379, 0.29142, 0.44242],
4125 [0.18315, 0.28778, 0.43571],
4126 [0.18248, 0.28416, 0.429],
4127 [0.18178, 0.28053, 0.42232],
4128 [0.18105, 0.27695, 0.41567],
4129 [0.18029, 0.27335, 0.40903],
4130 [0.1795, 0.26977, 0.4024],
4131 [0.1787, 0.26618, 0.39581],
4132 [0.17786, 0.26261, 0.38922],
4133 [0.17694, 0.25905, 0.38265],
4134 [0.176, 0.25549, 0.37611],
4135 [0.17509, 0.25195, 0.36958],
4136 [0.17411, 0.24842, 0.36307],
4137 [0.1731, 0.24486, 0.35659],
4138 [0.17207, 0.24136, 0.35012],
4139 [0.17101, 0.23785, 0.34366],
4140 [0.16994, 0.23435, 0.33724],
4141 [0.16882, 0.23085, 0.33082],
4142 [0.16766, 0.22737, 0.32443],
4143 [0.16649, 0.22389, 0.31807],
4144 [0.16526, 0.22045, 0.31171],
4145 [0.16408, 0.21698, 0.3054],
4146 [0.16281, 0.21352, 0.29909],
4147 [0.16154, 0.21009, 0.2928],
4148 [0.16017, 0.20669, 0.28653],
4149 [0.15887, 0.20325, 0.28029],
4150 [0.15748, 0.19982, 0.27408],
4151 [0.15612, 0.19646, 0.26786],
4152 [0.15467, 0.19306, 0.26171],
4153 [0.15321, 0.18968, 0.25556],
4154 [0.15174, 0.18632, 0.24942],
4155 [0.15026, 0.18294, 0.2433],
4156 [0.14871, 0.17961, 0.23725],
4157 [0.14718, 0.17625, 0.23118],
4158 [0.14564, 0.17295, 0.22512],
4159 [0.14403, 0.16968, 0.21913],
4160 [0.14243, 0.16638, 0.21314],
4161 [0.14084, 0.16314, 0.20723],
4162 [0.13919, 0.15988, 0.2013],
4163 [0.13765, 0.15674, 0.19547],
4164 [0.13602, 0.15358, 0.18968],
4165 [0.13455, 0.15054, 0.18396],
4166 [0.13306, 0.14756, 0.17836],
4167 [0.13167, 0.14469, 0.1728],
4168 [0.13042, 0.14192, 0.16741],
4169 [0.12922, 0.13927, 0.16217],
4170 [0.12825, 0.13686, 0.15706],
4171 [0.12743, 0.13466, 0.15217],
4172 [0.12685, 0.13265, 0.14756],
4173 [0.12655, 0.13093, 0.14317],
4174 [0.12652, 0.12946, 0.13905],
4175 [0.12678, 0.12834, 0.1353],
4176 [0.12737, 0.12752, 0.13186],
4177 [0.12833, 0.12704, 0.12874],
4178 [0.12961, 0.12694, 0.12604],
4179 [0.13123, 0.12718, 0.12362],
4180 [0.13318, 0.1278, 0.12159],
4181 [0.13545, 0.1287, 0.11992],
4182 [0.13807, 0.12997, 0.11861],
4183 [0.14093, 0.13147, 0.11751],
4184 [0.14404, 0.13325, 0.11674],
4185 [0.14739, 0.13526, 0.11622],
4186 [0.15092, 0.1375, 0.11588],
4187 [0.15463, 0.13984, 0.11572],
4188 [0.15851, 0.14242, 0.11571],
4189 [0.16247, 0.14511, 0.11584],
4190 [0.16652, 0.14785, 0.11606],
4191 [0.17065, 0.15069, 0.11635],
4192 [0.17485, 0.15359, 0.11668],
4193 [0.17908, 0.15658, 0.11705],
4194 [0.18333, 0.15955, 0.11747],
4195 [0.18766, 0.16261, 0.11793],
4196 [0.19194, 0.16563, 0.11839],
4197 [0.19628, 0.16874, 0.11884],
4198 [0.20058, 0.17182, 0.11927],
4199 [0.20495, 0.17495, 0.11971],
4200 [0.2093, 0.17808, 0.12015],
4201 [0.21365, 0.18116, 0.12058],
4202 [0.21802, 0.18431, 0.12101],
4203 [0.22237, 0.18748, 0.12142],
4204 [0.22675, 0.19061, 0.12183],
4205 [0.23112, 0.19379, 0.12224],
4206 [0.23551, 0.19696, 0.12264],
4207 [0.23987, 0.20011, 0.12303],
4208 [0.24425, 0.20332, 0.12341],
4209 [0.24867, 0.20654, 0.12378],
4210 [0.25306, 0.20972, 0.12415],
4211 [0.25746, 0.21292, 0.12451],
4212 [0.26188, 0.21617, 0.12486],
4213 [0.2663, 0.21939, 0.12521],
4214 [0.27074, 0.22263, 0.12555],
4215 [0.27516, 0.22588, 0.12587],
4216 [0.2796, 0.22912, 0.12618],
4217 [0.28403, 0.23239, 0.12646],
4218 [0.28849, 0.23566, 0.12673],
4219 [0.29294, 0.23892, 0.12701],
4220 [0.29741, 0.24221, 0.12728],
4221 [0.30187, 0.24549, 0.12756],
4222 [0.30637, 0.24881, 0.12782],
4223 [0.31086, 0.25212, 0.12807],
4224 [0.31534, 0.25543, 0.1283],
4225 [0.31985, 0.25875, 0.12852],
4226 [0.32434, 0.26208, 0.12872],
4227 [0.32887, 0.26541, 0.12892],
4228 [0.33339, 0.26877, 0.12911],
4229 [0.3379, 0.27209, 0.12931],
4230 [0.34245, 0.27548, 0.12949],
4231 [0.34699, 0.27884, 0.12967],
4232 [0.35153, 0.28221, 0.12983],
4233 [0.35609, 0.28557, 0.12998],
4234 [0.36064, 0.28897, 0.13012],
4235 [0.36522, 0.29236, 0.13024],
4236 [0.36979, 0.29575, 0.13035],
4237 [0.37439, 0.29917, 0.13045],
4238 [0.37897, 0.30257, 0.13053],
4239 [0.38358, 0.30601, 0.13061],
4240 [0.38818, 0.30944, 0.13067],
4241 [0.39279, 0.31285, 0.13073],
4242 [0.39741, 0.31631, 0.13077],
4243 [0.40203, 0.31975, 0.1308],
4244 [0.40668, 0.3232, 0.13082],
4245 [0.41131, 0.32665, 0.13083],
4246 [0.41596, 0.33013, 0.13082],
4247 [0.42062, 0.3336, 0.13081],
4248 [0.42529, 0.33708, 0.13078],
4249 [0.42996, 0.34056, 0.13075],
4250 [0.43464, 0.34404, 0.1307],
4251 [0.43932, 0.34756, 0.13063],
4252 [0.44402, 0.35106, 0.13056],
4253 [0.44872, 0.35457, 0.13047],
4254 [0.45341, 0.35808, 0.13037],
4255 [0.45813, 0.3616, 0.13025],
4256 [0.46284, 0.36513, 0.13012],
4257 [0.46758, 0.36867, 0.12998],
4258 [0.47231, 0.3722, 0.12981],
4259 [0.47705, 0.37575, 0.12963],
4260 [0.4818, 0.3793, 0.12943],
4261 [0.48655, 0.38286, 0.12922],
4262 [0.49133, 0.38642, 0.129],
4263 [0.49608, 0.38999, 0.12877],
4264 [0.50086, 0.39357, 0.12854],
4265 [0.50564, 0.39715, 0.1283],
4266 [0.51043, 0.40075, 0.12803],
4267 [0.51523, 0.40433, 0.12773],
4268 [0.52003, 0.40793, 0.1274],
4269 [0.52484, 0.41154, 0.12707],
4270 [0.52966, 0.41515, 0.12674],
4271 [0.53448, 0.41876, 0.12641],
4272 [0.53931, 0.42238, 0.12606],
4273 [0.54415, 0.42601, 0.12567],
4274 [0.549, 0.42965, 0.12524],
4275 [0.55385, 0.43328, 0.12481],
4276 [0.5587, 0.43694, 0.12436],
4277 [0.56357, 0.44058, 0.1239],
4278 [0.56844, 0.44424, 0.12341],
4279 [0.57332, 0.44789, 0.12291],
4280 [0.5782, 0.45157, 0.1224],
4281 [0.58309, 0.45524, 0.12186],
4282 [0.58798, 0.45892, 0.12131],
4283 [0.5929, 0.46259, 0.12074],
4284 [0.5978, 0.46628, 0.12015],
4285 [0.60272, 0.46998, 0.11954],
4286 [0.60765, 0.47367, 0.11893],
4287 [0.61257, 0.47738, 0.11828],
4288 [0.61751, 0.48108, 0.11755],
4289 [0.62245, 0.48479, 0.11685],
4290 [0.6274, 0.48852, 0.11615],
4291 [0.63236, 0.49224, 0.11536],
4292 [0.63732, 0.49596, 0.11454],
4293 [0.64229, 0.4997, 0.11378],
4294 [0.64726, 0.50344, 0.11298],
4295 [0.65224, 0.50719, 0.1121],
4296 [0.65724, 0.51093, 0.11121],
4297 [0.66223, 0.5147, 0.11031],
4298 [0.66723, 0.51846, 0.10936],
4299 [0.67223, 0.52221, 0.10832],
4300 [0.67725, 0.52599, 0.10736],
4301 [0.68226, 0.52976, 0.10634],
4302 [0.68729, 0.53353, 0.10521],
4303 [0.69232, 0.53733, 0.10412],
4304 [0.69735, 0.54111, 0.103],
4305 [0.7024, 0.54491, 0.1018],
4306 ]
4307 b_diverging_bky_60_10_c30 = bokeh_palette('diverging_bky_60_10_c30',diverging_bky_60_10_c30)
4308 m_diverging_bky_60_10_c30 = mpl_cm('diverging_bky_60_10_c30',diverging_bky_60_10_c30)
4309 m_diverging_bky_60_10_c30_r = mpl_cm('diverging_bky_60_10_c30_r',list(reversed(diverging_bky_60_10_c30)))
4310 bky = b_diverging_bky_60_10_c30
4311 m_bky = m_diverging_bky_60_10_c30
4312 m_bky_r = m_diverging_bky_60_10_c30_r
4313 palette['bky'] = b_diverging_bky_60_10_c30
4314 cm['bky'] = m_diverging_bky_60_10_c30
4315 cm['bky_r'] = m_diverging_bky_60_10_c30_r
4316 register_cmap('cet_bky',m_diverging_bky_60_10_c30)
4317 register_cmap('cet_bky_r',m_diverging_bky_60_10_c30_r)
4318
4319
4320
4321
4322 diverging_bwr_40_95_c42 = [\
4323 [0.12757, 0.31619, 0.85836],
4324 [0.14675, 0.32048, 0.85923],
4325 [0.16386, 0.32476, 0.8601],
4326 [0.17936, 0.3291, 0.86096],
4327 [0.1937, 0.33343, 0.86182],
4328 [0.20708, 0.33776, 0.86268],
4329 [0.21967, 0.34213, 0.86354],
4330 [0.23162, 0.34649, 0.86439],
4331 [0.24297, 0.35089, 0.86524],
4332 [0.25389, 0.35529, 0.86609],
4333 [0.26436, 0.35969, 0.86693],
4334 [0.27445, 0.36411, 0.86778],
4335 [0.28422, 0.36855, 0.86862],
4336 [0.29369, 0.37299, 0.86945],
4337 [0.30289, 0.37746, 0.87028],
4338 [0.31184, 0.38192, 0.87112],
4339 [0.32061, 0.3864, 0.87195],
4340 [0.32914, 0.39091, 0.87277],
4341 [0.33747, 0.39542, 0.8736],
4342 [0.34563, 0.39992, 0.87442],
4343 [0.35364, 0.40445, 0.87523],
4344 [0.36151, 0.40899, 0.87605],
4345 [0.36923, 0.41355, 0.87686],
4346 [0.37682, 0.4181, 0.87767],
4347 [0.38428, 0.42267, 0.87847],
4348 [0.39164, 0.42727, 0.87927],
4349 [0.39887, 0.43186, 0.88007],
4350 [0.40603, 0.43645, 0.88087],
4351 [0.41307, 0.44106, 0.88167],
4352 [0.42002, 0.44568, 0.88245],
4353 [0.4269, 0.45032, 0.88324],
4354 [0.43367, 0.45496, 0.88403],
4355 [0.44039, 0.45961, 0.88481],
4356 [0.44703, 0.46428, 0.88559],
4357 [0.45359, 0.46894, 0.88636],
4358 [0.46009, 0.47361, 0.88713],
4359 [0.46653, 0.4783, 0.8879],
4360 [0.4729, 0.483, 0.88867],
4361 [0.47922, 0.48771, 0.88943],
4362 [0.48547, 0.49242, 0.89019],
4363 [0.49169, 0.49715, 0.89094],
4364 [0.49784, 0.50188, 0.8917],
4365 [0.50394, 0.50662, 0.89245],
4366 [0.50999, 0.51137, 0.89319],
4367 [0.516, 0.51612, 0.89394],
4368 [0.52196, 0.5209, 0.89468],
4369 [0.52789, 0.52567, 0.89541],
4370 [0.53377, 0.53046, 0.89615],
4371 [0.53962, 0.53525, 0.89688],
4372 [0.54543, 0.54005, 0.8976],
4373 [0.5512, 0.54486, 0.89832],
4374 [0.55693, 0.54968, 0.89905],
4375 [0.56263, 0.5545, 0.89976],
4376 [0.56829, 0.55933, 0.90048],
4377 [0.57392, 0.56418, 0.90119],
4378 [0.57953, 0.56902, 0.90189],
4379 [0.5851, 0.57388, 0.9026],
4380 [0.59064, 0.57874, 0.9033],
4381 [0.59616, 0.58361, 0.90399],
4382 [0.60164, 0.58849, 0.90468],
4383 [0.60711, 0.59339, 0.90538],
4384 [0.61254, 0.59828, 0.90606],
4385 [0.61795, 0.60318, 0.90674],
4386 [0.62334, 0.6081, 0.90742],
4387 [0.6287, 0.613, 0.9081],
4388 [0.63404, 0.61793, 0.90877],
4389 [0.63935, 0.62287, 0.90943],
4390 [0.64464, 0.62781, 0.9101],
4391 [0.64992, 0.63275, 0.91076],
4392 [0.65517, 0.63771, 0.91142],
4393 [0.66041, 0.64267, 0.91207],
4394 [0.66562, 0.64763, 0.91272],
4395 [0.67082, 0.65261, 0.91337],
4396 [0.67599, 0.6576, 0.91401],
4397 [0.68115, 0.66259, 0.91465],
4398 [0.68629, 0.66758, 0.91528],
4399 [0.69141, 0.67259, 0.91591],
4400 [0.69652, 0.6776, 0.91655],
4401 [0.70161, 0.68261, 0.91717],
4402 [0.70669, 0.68763, 0.91779],
4403 [0.71175, 0.69267, 0.91841],
4404 [0.71679, 0.6977, 0.91902],
4405 [0.72181, 0.70275, 0.91963],
4406 [0.72683, 0.70779, 0.92023],
4407 [0.73183, 0.71285, 0.92083],
4408 [0.73682, 0.71792, 0.92143],
4409 [0.74179, 0.72298, 0.92203],
4410 [0.74675, 0.72806, 0.92262],
4411 [0.7517, 0.73315, 0.92321],
4412 [0.75663, 0.73823, 0.92379],
4413 [0.76155, 0.74334, 0.92436],
4414 [0.76647, 0.74844, 0.92494],
4415 [0.77137, 0.75354, 0.92551],
4416 [0.77625, 0.75866, 0.92608],
4417 [0.78113, 0.76378, 0.92664],
4418 [0.78599, 0.76891, 0.9272],
4419 [0.79084, 0.77404, 0.92775],
4420 [0.79569, 0.77918, 0.9283],
4421 [0.80052, 0.78434, 0.92885],
4422 [0.80534, 0.78949, 0.92939],
4423 [0.81015, 0.79464, 0.92993],
4424 [0.81496, 0.79981, 0.93047],
4425 [0.81975, 0.80498, 0.931],
4426 [0.82454, 0.81015, 0.93152],
4427 [0.82932, 0.81534, 0.93204],
4428 [0.83408, 0.82053, 0.93256],
4429 [0.83884, 0.82573, 0.93308],
4430 [0.84359, 0.83093, 0.93358],
4431 [0.84833, 0.83612, 0.93407],
4432 [0.85306, 0.84131, 0.93455],
4433 [0.85779, 0.84648, 0.935],
4434 [0.8625, 0.85164, 0.93542],
4435 [0.86719, 0.85675, 0.9358],
4436 [0.87187, 0.86182, 0.93612],
4437 [0.87652, 0.86682, 0.93638],
4438 [0.88114, 0.87172, 0.93653],
4439 [0.88573, 0.87649, 0.93657],
4440 [0.89027, 0.8811, 0.93646],
4441 [0.89475, 0.8855, 0.93617],
4442 [0.89915, 0.88964, 0.93565],
4443 [0.90346, 0.89347, 0.93488],
4444 [0.90766, 0.89694, 0.9338],
4445 [0.91172, 0.89998, 0.93239],
4446 [0.91562, 0.90254, 0.9306],
4447 [0.91935, 0.90457, 0.9284],
4448 [0.92288, 0.90602, 0.92576],
4449 [0.92619, 0.90686, 0.92266],
4450 [0.92926, 0.90706, 0.91909],
4451 [0.93208, 0.9066, 0.91506],
4452 [0.93464, 0.90549, 0.91056],
4453 [0.93695, 0.90374, 0.90562],
4454 [0.93899, 0.90139, 0.90027],
4455 [0.94078, 0.89845, 0.89453],
4456 [0.94232, 0.89499, 0.88845],
4457 [0.94363, 0.89105, 0.88206],
4458 [0.94474, 0.8867, 0.87541],
4459 [0.94565, 0.88198, 0.86855],
4460 [0.94638, 0.87695, 0.86149],
4461 [0.94697, 0.87168, 0.85429],
4462 [0.94743, 0.86619, 0.84698],
4463 [0.94776, 0.86054, 0.83959],
4464 [0.948, 0.85477, 0.83212],
4465 [0.94815, 0.8489, 0.82461],
4466 [0.94822, 0.84295, 0.81708],
4467 [0.94823, 0.83695, 0.80952],
4468 [0.94818, 0.83092, 0.80196],
4469 [0.94808, 0.82486, 0.79439],
4470 [0.94793, 0.81878, 0.78683],
4471 [0.94774, 0.81269, 0.77926],
4472 [0.9475, 0.8066, 0.77171],
4473 [0.94722, 0.8005, 0.76417],
4474 [0.9469, 0.7944, 0.75665],
4475 [0.94655, 0.78831, 0.74913],
4476 [0.94616, 0.78221, 0.74163],
4477 [0.94574, 0.77612, 0.73414],
4478 [0.94528, 0.77003, 0.72666],
4479 [0.94479, 0.76394, 0.7192],
4480 [0.94425, 0.75785, 0.71174],
4481 [0.94369, 0.75176, 0.7043],
4482 [0.94309, 0.74567, 0.69687],
4483 [0.94245, 0.73959, 0.68946],
4484 [0.94178, 0.73349, 0.68205],
4485 [0.94108, 0.7274, 0.67466],
4486 [0.94034, 0.72131, 0.66728],
4487 [0.93957, 0.71523, 0.65991],
4488 [0.93876, 0.70914, 0.65256],
4489 [0.93793, 0.70305, 0.64521],
4490 [0.93706, 0.69695, 0.63789],
4491 [0.93616, 0.69086, 0.63058],
4492 [0.93522, 0.68477, 0.62327],
4493 [0.93425, 0.67867, 0.61598],
4494 [0.93325, 0.67258, 0.60871],
4495 [0.93222, 0.66648, 0.60143],
4496 [0.93116, 0.66038, 0.59418],
4497 [0.93006, 0.65428, 0.58694],
4498 [0.92893, 0.64818, 0.57973],
4499 [0.92777, 0.64208, 0.57251],
4500 [0.92659, 0.63597, 0.5653],
4501 [0.92537, 0.62986, 0.55812],
4502 [0.92412, 0.62375, 0.55095],
4503 [0.92285, 0.61762, 0.54379],
4504 [0.92154, 0.61151, 0.53665],
4505 [0.9202, 0.60538, 0.52951],
4506 [0.91883, 0.59925, 0.52238],
4507 [0.91743, 0.59312, 0.51527],
4508 [0.916, 0.58697, 0.50819],
4509 [0.91455, 0.58083, 0.5011],
4510 [0.91306, 0.57468, 0.49403],
4511 [0.91155, 0.56853, 0.48698],
4512 [0.91001, 0.56237, 0.47994],
4513 [0.90844, 0.55619, 0.4729],
4514 [0.90684, 0.55002, 0.46589],
4515 [0.90521, 0.54384, 0.45889],
4516 [0.90355, 0.53765, 0.45191],
4517 [0.90187, 0.53145, 0.44493],
4518 [0.90016, 0.52524, 0.43797],
4519 [0.89842, 0.51903, 0.43102],
4520 [0.89665, 0.51279, 0.42408],
4521 [0.89486, 0.50655, 0.41717],
4522 [0.89304, 0.5003, 0.41026],
4523 [0.89119, 0.49404, 0.40336],
4524 [0.88932, 0.48777, 0.39647],
4525 [0.88741, 0.48147, 0.3896],
4526 [0.88549, 0.47518, 0.38274],
4527 [0.88354, 0.46885, 0.3759],
4528 [0.88156, 0.46251, 0.36907],
4529 [0.87955, 0.45616, 0.36225],
4530 [0.87752, 0.4498, 0.35546],
4531 [0.87547, 0.44341, 0.34865],
4532 [0.87338, 0.437, 0.34187],
4533 [0.87128, 0.43057, 0.33511],
4534 [0.86914, 0.42411, 0.32834],
4535 [0.86698, 0.41764, 0.32159],
4536 [0.8648, 0.41114, 0.31485],
4537 [0.8626, 0.40461, 0.30813],
4538 [0.86036, 0.39806, 0.30141],
4539 [0.8581, 0.39148, 0.29471],
4540 [0.85582, 0.38485, 0.28802],
4541 [0.85351, 0.37821, 0.28133],
4542 [0.85118, 0.37151, 0.27466],
4543 [0.84883, 0.36479, 0.26799],
4544 [0.84645, 0.35804, 0.26135],
4545 [0.84405, 0.35123, 0.25471],
4546 [0.84163, 0.34436, 0.24807],
4547 [0.83918, 0.33747, 0.24143],
4548 [0.83671, 0.3305, 0.23481],
4549 [0.83422, 0.32349, 0.22818],
4550 [0.8317, 0.31643, 0.22155],
4551 [0.82916, 0.30929, 0.21492],
4552 [0.82659, 0.30206, 0.20831],
4553 [0.824, 0.29477, 0.20168],
4554 [0.8214, 0.2874, 0.19508],
4555 [0.81876, 0.27996, 0.18847],
4556 [0.81611, 0.27239, 0.1818],
4557 [0.81343, 0.26474, 0.17519],
4558 [0.81074, 0.25697, 0.16854],
4559 [0.80802, 0.24907, 0.16191],
4560 [0.80528, 0.24103, 0.15521],
4561 [0.80252, 0.23283, 0.1485],
4562 [0.79974, 0.22446, 0.1418],
4563 [0.79693, 0.21594, 0.13506],
4564 [0.79411, 0.20718, 0.12827],
4565 [0.79126, 0.19815, 0.12139],
4566 [0.78839, 0.18889, 0.1145],
4567 [0.78551, 0.1793, 0.10759],
4568 [0.7826, 0.16938, 0.10056],
4569 [0.77967, 0.15898, 0.093435],
4570 [0.77672, 0.14808, 0.086208],
4571 [0.77375, 0.13656, 0.078844],
4572 [0.77076, 0.12429, 0.07141],
4573 [0.76775, 0.11107, 0.063657],
4574 [0.76473, 0.096422, 0.055653],
4575 [0.76168, 0.080002, 0.047336],
4576 [0.75862, 0.060659, 0.038618],
4577 [0.75553, 0.03608, 0.029827],
4578 [0.75243, 0.0084181, 0.021805],
4579 ]
4580 b_diverging_bwr_40_95_c42 = bokeh_palette('diverging_bwr_40_95_c42',diverging_bwr_40_95_c42)
4581 m_diverging_bwr_40_95_c42 = mpl_cm('diverging_bwr_40_95_c42',diverging_bwr_40_95_c42)
4582 m_diverging_bwr_40_95_c42_r = mpl_cm('diverging_bwr_40_95_c42_r',list(reversed(diverging_bwr_40_95_c42)))
4583 coolwarm = b_diverging_bwr_40_95_c42
4584 m_coolwarm = m_diverging_bwr_40_95_c42
4585 m_coolwarm_r = m_diverging_bwr_40_95_c42_r
4586 palette['coolwarm'] = b_diverging_bwr_40_95_c42
4587 cm['coolwarm'] = m_diverging_bwr_40_95_c42
4588 cm['coolwarm_r'] = m_diverging_bwr_40_95_c42_r
4589 register_cmap('cet_coolwarm',m_diverging_bwr_40_95_c42)
4590 register_cmap('cet_coolwarm_r',m_diverging_bwr_40_95_c42_r)
4591
4592
4593
4594
4595 diverging_bwr_55_98_c37 = [\
4596 [0.14124, 0.50092, 0.99811],
4597 [0.16238, 0.50425, 0.99811],
4598 [0.18106, 0.50758, 0.99811],
4599 [0.19801, 0.51092, 0.9981],
4600 [0.21361, 0.51428, 0.9981],
4601 [0.22813, 0.51763, 0.99809],
4602 [0.24174, 0.52099, 0.99808],
4603 [0.25463, 0.52437, 0.99807],
4604 [0.26685, 0.52775, 0.99806],
4605 [0.27856, 0.53114, 0.99805],
4606 [0.28978, 0.53454, 0.99803],
4607 [0.30057, 0.53795, 0.99801],
4608 [0.31101, 0.54135, 0.99799],
4609 [0.3211, 0.54477, 0.99796],
4610 [0.33087, 0.5482, 0.99794],
4611 [0.34039, 0.55164, 0.99791],
4612 [0.34964, 0.55507, 0.99788],
4613 [0.35865, 0.55852, 0.99784],
4614 [0.36746, 0.56199, 0.99781],
4615 [0.37609, 0.56544, 0.99777],
4616 [0.38451, 0.56891, 0.99773],
4617 [0.39277, 0.57239, 0.99769],
4618 [0.40089, 0.57588, 0.99764],
4619 [0.40883, 0.57937, 0.9976],
4620 [0.41665, 0.58286, 0.99755],
4621 [0.42433, 0.58637, 0.9975],
4622 [0.4319, 0.58987, 0.99744],
4623 [0.43933, 0.59339, 0.99739],
4624 [0.44667, 0.59692, 0.99733],
4625 [0.45389, 0.60045, 0.99727],
4626 [0.46103, 0.60399, 0.99721],
4627 [0.46806, 0.60753, 0.99714],
4628 [0.47502, 0.61108, 0.99707],
4629 [0.48188, 0.61463, 0.997],
4630 [0.48866, 0.6182, 0.99693],
4631 [0.49537, 0.62176, 0.99685],
4632 [0.502, 0.62534, 0.99677],
4633 [0.50857, 0.62892, 0.99669],
4634 [0.51505, 0.63251, 0.99661],
4635 [0.52148, 0.6361, 0.99653],
4636 [0.52785, 0.6397, 0.99644],
4637 [0.53415, 0.6433, 0.99635],
4638 [0.5404, 0.64691, 0.99626],
4639 [0.5466, 0.65053, 0.99616],
4640 [0.55274, 0.65415, 0.99606],
4641 [0.55883, 0.65778, 0.99596],
4642 [0.56487, 0.66141, 0.99586],
4643 [0.57086, 0.66505, 0.99575],
4644 [0.57682, 0.6687, 0.99565],
4645 [0.58271, 0.67235, 0.99554],
4646 [0.58857, 0.676, 0.99542],
4647 [0.59439, 0.67966, 0.99531],
4648 [0.60017, 0.68333, 0.99519],
4649 [0.60591, 0.687, 0.99507],
4650 [0.61162, 0.69067, 0.99494],
4651 [0.61728, 0.69436, 0.99482],
4652 [0.62292, 0.69805, 0.99469],
4653 [0.62852, 0.70174, 0.99455],
4654 [0.63408, 0.70544, 0.99442],
4655 [0.63961, 0.70915, 0.99428],
4656 [0.64511, 0.71285, 0.99414],
4657 [0.65058, 0.71657, 0.994],
4658 [0.65603, 0.72029, 0.99386],
4659 [0.66144, 0.72401, 0.99371],
4660 [0.66681, 0.72774, 0.99356],
4661 [0.67218, 0.73148, 0.9934],
4662 [0.67751, 0.73522, 0.99325],
4663 [0.68281, 0.73897, 0.99309],
4664 [0.6881, 0.74272, 0.99292],
4665 [0.69335, 0.74647, 0.99276],
4666 [0.69858, 0.75023, 0.99259],
4667 [0.70379, 0.754, 0.99242],
4668 [0.70899, 0.75776, 0.99224],
4669 [0.71414, 0.76154, 0.99207],
4670 [0.71929, 0.76532, 0.99189],
4671 [0.72442, 0.7691, 0.9917],
4672 [0.72952, 0.77289, 0.99152],
4673 [0.7346, 0.77668, 0.99133],
4674 [0.73967, 0.78048, 0.99114],
4675 [0.74471, 0.78429, 0.99094],
4676 [0.74973, 0.78809, 0.99074],
4677 [0.75475, 0.7919, 0.99054],
4678 [0.75973, 0.79572, 0.99034],
4679 [0.76471, 0.79954, 0.99013],
4680 [0.76967, 0.80336, 0.98992],
4681 [0.77461, 0.8072, 0.98971],
4682 [0.77953, 0.81103, 0.9895],
4683 [0.78445, 0.81486, 0.98928],
4684 [0.78934, 0.81871, 0.98905],
4685 [0.79422, 0.82256, 0.98883],
4686 [0.79908, 0.82641, 0.9886],
4687 [0.80393, 0.83027, 0.98836],
4688 [0.80877, 0.83413, 0.98813],
4689 [0.81358, 0.83799, 0.98789],
4690 [0.81839, 0.84186, 0.98765],
4691 [0.82319, 0.84573, 0.98741],
4692 [0.82797, 0.84962, 0.98716],
4693 [0.83274, 0.85349, 0.98691],
4694 [0.8375, 0.85738, 0.98666],
4695 [0.84224, 0.86127, 0.9864],
4696 [0.84697, 0.86516, 0.98614],
4697 [0.85169, 0.86907, 0.98588],
4698 [0.8564, 0.87297, 0.98561],
4699 [0.8611, 0.87687, 0.98534],
4700 [0.86579, 0.88079, 0.98507],
4701 [0.87046, 0.88471, 0.98479],
4702 [0.87513, 0.88863, 0.98451],
4703 [0.87979, 0.89255, 0.98422],
4704 [0.88444, 0.89648, 0.98394],
4705 [0.88907, 0.90041, 0.98364],
4706 [0.8937, 0.90434, 0.98335],
4707 [0.89831, 0.90829, 0.98305],
4708 [0.90292, 0.91223, 0.98275],
4709 [0.90752, 0.91617, 0.98245],
4710 [0.91211, 0.92012, 0.98214],
4711 [0.91669, 0.92408, 0.98183],
4712 [0.92126, 0.92804, 0.98152],
4713 [0.92582, 0.932, 0.9812],
4714 [0.93037, 0.93597, 0.98088],
4715 [0.93492, 0.93994, 0.98055],
4716 [0.93946, 0.94392, 0.98022],
4717 [0.94399, 0.9479, 0.97989],
4718 [0.94853, 0.95188, 0.97953],
4719 [0.95311, 0.95584, 0.97909],
4720 [0.95776, 0.95967, 0.97843],
4721 [0.9625, 0.96312, 0.97726],
4722 [0.9672, 0.9657, 0.97517],
4723 [0.97158, 0.96685, 0.97187],
4724 [0.97525, 0.96617, 0.96729],
4725 [0.97801, 0.96372, 0.96172],
4726 [0.97994, 0.95996, 0.9556],
4727 [0.9813, 0.95546, 0.94924],
4728 [0.98234, 0.95064, 0.94283],
4729 [0.98324, 0.94571, 0.93643],
4730 [0.98408, 0.94075, 0.93004],
4731 [0.98488, 0.93579, 0.92366],
4732 [0.98565, 0.93083, 0.9173],
4733 [0.98638, 0.92587, 0.91093],
4734 [0.98709, 0.92091, 0.90457],
4735 [0.98776, 0.91596, 0.89822],
4736 [0.98839, 0.91101, 0.89189],
4737 [0.98901, 0.90605, 0.88555],
4738 [0.98959, 0.9011, 0.87922],
4739 [0.99014, 0.89615, 0.87291],
4740 [0.99066, 0.89119, 0.8666],
4741 [0.99115, 0.88624, 0.8603],
4742 [0.99161, 0.88129, 0.85399],
4743 [0.99205, 0.87633, 0.84771],
4744 [0.99245, 0.87139, 0.84143],
4745 [0.99283, 0.86643, 0.83516],
4746 [0.99317, 0.86148, 0.82889],
4747 [0.99349, 0.85653, 0.82263],
4748 [0.99378, 0.85158, 0.81638],
4749 [0.99404, 0.84663, 0.81014],
4750 [0.99428, 0.84168, 0.80391],
4751 [0.99448, 0.83673, 0.79768],
4752 [0.99467, 0.83179, 0.79146],
4753 [0.99482, 0.82683, 0.78525],
4754 [0.99495, 0.82188, 0.77904],
4755 [0.99505, 0.81693, 0.77284],
4756 [0.99512, 0.81198, 0.76666],
4757 [0.99517, 0.80703, 0.76048],
4758 [0.99519, 0.80207, 0.75431],
4759 [0.99519, 0.79712, 0.74814],
4760 [0.99516, 0.79217, 0.74198],
4761 [0.9951, 0.78722, 0.73583],
4762 [0.99503, 0.78226, 0.72969],
4763 [0.99492, 0.77731, 0.72355],
4764 [0.99479, 0.77235, 0.71744],
4765 [0.99464, 0.76739, 0.71132],
4766 [0.99446, 0.76243, 0.7052],
4767 [0.99425, 0.75748, 0.6991],
4768 [0.99403, 0.75251, 0.69301],
4769 [0.99378, 0.74756, 0.68692],
4770 [0.9935, 0.7426, 0.68084],
4771 [0.9932, 0.73763, 0.67478],
4772 [0.99288, 0.73267, 0.66872],
4773 [0.99253, 0.72769, 0.66267],
4774 [0.99216, 0.72272, 0.65662],
4775 [0.99177, 0.71776, 0.65058],
4776 [0.99135, 0.71278, 0.64455],
4777 [0.99091, 0.7078, 0.63853],
4778 [0.99045, 0.70283, 0.63252],
4779 [0.98996, 0.69784, 0.62651],
4780 [0.98946, 0.69287, 0.62052],
4781 [0.98893, 0.68788, 0.61452],
4782 [0.98837, 0.68289, 0.60856],
4783 [0.9878, 0.6779, 0.60258],
4784 [0.98721, 0.67291, 0.59662],
4785 [0.98659, 0.66791, 0.59066],
4786 [0.98595, 0.66291, 0.58471],
4787 [0.98529, 0.65791, 0.57877],
4788 [0.98461, 0.65289, 0.57285],
4789 [0.9839, 0.64788, 0.56693],
4790 [0.98317, 0.64287, 0.561],
4791 [0.98243, 0.63785, 0.5551],
4792 [0.98166, 0.63283, 0.54921],
4793 [0.98087, 0.6278, 0.54332],
4794 [0.98006, 0.62277, 0.53744],
4795 [0.97923, 0.61772, 0.53156],
4796 [0.97838, 0.61268, 0.5257],
4797 [0.97751, 0.60764, 0.51984],
4798 [0.97662, 0.60258, 0.514],
4799 [0.97571, 0.59752, 0.50816],
4800 [0.97478, 0.59246, 0.50233],
4801 [0.97383, 0.58738, 0.4965],
4802 [0.97286, 0.5823, 0.4907],
4803 [0.97187, 0.57722, 0.48488],
4804 [0.97086, 0.57213, 0.47909],
4805 [0.96983, 0.56703, 0.47329],
4806 [0.96878, 0.56193, 0.46752],
4807 [0.96771, 0.55681, 0.46174],
4808 [0.96662, 0.55168, 0.45597],
4809 [0.96552, 0.54655, 0.45022],
4810 [0.96439, 0.5414, 0.44448],
4811 [0.96325, 0.53626, 0.43872],
4812 [0.96208, 0.53109, 0.433],
4813 [0.9609, 0.52593, 0.42728],
4814 [0.9597, 0.52074, 0.42155],
4815 [0.95849, 0.51554, 0.41584],
4816 [0.95724, 0.51034, 0.41015],
4817 [0.95599, 0.50513, 0.40444],
4818 [0.95472, 0.49989, 0.39876],
4819 [0.95343, 0.49466, 0.39308],
4820 [0.95211, 0.4894, 0.38741],
4821 [0.95079, 0.48413, 0.38175],
4822 [0.94944, 0.47885, 0.3761],
4823 [0.94808, 0.47355, 0.37044],
4824 [0.94669, 0.46823, 0.3648],
4825 [0.9453, 0.4629, 0.35917],
4826 [0.94388, 0.45756, 0.35354],
4827 [0.94245, 0.4522, 0.34793],
4828 [0.94099, 0.44681, 0.34231],
4829 [0.93953, 0.4414, 0.3367],
4830 [0.93804, 0.43598, 0.33109],
4831 [0.93654, 0.43053, 0.32549],
4832 [0.93502, 0.42506, 0.31992],
4833 [0.93348, 0.41957, 0.31433],
4834 [0.93192, 0.41405, 0.30876],
4835 [0.93036, 0.4085, 0.30317],
4836 [0.92877, 0.40293, 0.29761],
4837 [0.92717, 0.39733, 0.29205],
4838 [0.92555, 0.39171, 0.28648],
4839 [0.92391, 0.38604, 0.28092],
4840 [0.92226, 0.38036, 0.2754],
4841 [0.92059, 0.37463, 0.26985],
4842 [0.91891, 0.36887, 0.2643],
4843 [0.91721, 0.36306, 0.25876],
4844 [0.91549, 0.35724, 0.25322],
4845 [0.91376, 0.35135, 0.24768],
4846 [0.91201, 0.34542, 0.24214],
4847 [0.91025, 0.33945, 0.23661],
4848 [0.90847, 0.33343, 0.23107],
4849 [0.90668, 0.32733, 0.22552],
4850 [0.90487, 0.32121, 0.21999],
4851 [0.90304, 0.31501, 0.21443],
4852 ]
4853 b_diverging_bwr_55_98_c37 = bokeh_palette('diverging_bwr_55_98_c37',diverging_bwr_55_98_c37)
4854 m_diverging_bwr_55_98_c37 = mpl_cm('diverging_bwr_55_98_c37',diverging_bwr_55_98_c37)
4855 m_diverging_bwr_55_98_c37_r = mpl_cm('diverging_bwr_55_98_c37_r',list(reversed(diverging_bwr_55_98_c37)))
4856
4857
4858
4859
4860 diverging_cwm_80_100_c22 = [\
4861 [0, 0.85071, 1],
4862 [0, 0.85194, 1],
4863 [0.056211, 0.85316, 1],
4864 [0.10029, 0.85438, 1],
4865 [0.13168, 0.8556, 1],
4866 [0.15712, 0.85682, 1],
4867 [0.17902, 0.85804, 1],
4868 [0.19846, 0.85925, 1],
4869 [0.21615, 0.86047, 1],
4870 [0.23241, 0.86169, 1],
4871 [0.24758, 0.8629, 1],
4872 [0.26183, 0.86412, 1],
4873 [0.27532, 0.86533, 1],
4874 [0.28813, 0.86654, 1],
4875 [0.30039, 0.86775, 1],
4876 [0.31215, 0.86897, 1],
4877 [0.32349, 0.87017, 1],
4878 [0.33443, 0.87138, 1],
4879 [0.34499, 0.87259, 1],
4880 [0.35526, 0.87379, 1],
4881 [0.36521, 0.875, 1],
4882 [0.37491, 0.87621, 1],
4883 [0.38437, 0.87741, 1],
4884 [0.3936, 0.87861, 1],
4885 [0.40262, 0.87982, 1],
4886 [0.41146, 0.88102, 1],
4887 [0.42011, 0.88222, 1],
4888 [0.4286, 0.88342, 1],
4889 [0.43693, 0.88462, 1],
4890 [0.44511, 0.88582, 1],
4891 [0.45315, 0.88702, 1],
4892 [0.46106, 0.88821, 1],
4893 [0.46885, 0.88941, 1],
4894 [0.47652, 0.8906, 1],
4895 [0.48407, 0.8918, 1],
4896 [0.49154, 0.89299, 1],
4897 [0.49889, 0.89419, 1],
4898 [0.50614, 0.89538, 1],
4899 [0.51332, 0.89657, 1],
4900 [0.5204, 0.89776, 1],
4901 [0.5274, 0.89895, 1],
4902 [0.53432, 0.90014, 1],
4903 [0.54117, 0.90132, 1],
4904 [0.54795, 0.90251, 1],
4905 [0.55466, 0.9037, 1],
4906 [0.56129, 0.90488, 1],
4907 [0.56787, 0.90607, 1],
4908 [0.57438, 0.90725, 1],
4909 [0.58084, 0.90844, 1],
4910 [0.58724, 0.90962, 1],
4911 [0.59358, 0.9108, 1],
4912 [0.59988, 0.91198, 1],
4913 [0.60611, 0.91316, 1],
4914 [0.6123, 0.91434, 1],
4915 [0.61845, 0.91551, 1],
4916 [0.62455, 0.91669, 1],
4917 [0.6306, 0.91787, 1],
4918 [0.63661, 0.91904, 1],
4919 [0.64258, 0.92021, 1],
4920 [0.6485, 0.92139, 1],
4921 [0.65439, 0.92256, 1],
4922 [0.66024, 0.92373, 1],
4923 [0.66606, 0.9249, 1],
4924 [0.67183, 0.92607, 1],
4925 [0.67758, 0.92724, 1],
4926 [0.68329, 0.92841, 1],
4927 [0.68897, 0.92958, 1],
4928 [0.69461, 0.93075, 1],
4929 [0.70023, 0.93191, 1],
4930 [0.70581, 0.93307, 1],
4931 [0.71137, 0.93424, 1],
4932 [0.7169, 0.9354, 1],
4933 [0.72239, 0.93657, 1],
4934 [0.72786, 0.93773, 1],
4935 [0.73331, 0.93889, 1],
4936 [0.73873, 0.94005, 1],
4937 [0.74412, 0.94121, 1],
4938 [0.74949, 0.94237, 1],
4939 [0.75485, 0.94352, 1],
4940 [0.76017, 0.94468, 1],
4941 [0.76547, 0.94583, 1],
4942 [0.77075, 0.94699, 1],
4943 [0.776, 0.94814, 1],
4944 [0.78124, 0.9493, 1],
4945 [0.78646, 0.95045, 1],
4946 [0.79165, 0.9516, 1],
4947 [0.79683, 0.95275, 1],
4948 [0.80199, 0.9539, 1],
4949 [0.80713, 0.95505, 1],
4950 [0.81224, 0.9562, 1],
4951 [0.81735, 0.95735, 1],
4952 [0.82244, 0.9585, 1],
4953 [0.8275, 0.95964, 1],
4954 [0.83255, 0.96079, 1],
4955 [0.83759, 0.96192, 1],
4956 [0.84261, 0.96307, 1],
4957 [0.8476, 0.96421, 1],
4958 [0.8526, 0.96535, 1],
4959 [0.85756, 0.9665, 1],
4960 [0.86253, 0.96764, 1],
4961 [0.86746, 0.96878, 1],
4962 [0.8724, 0.96991, 1],
4963 [0.87731, 0.97105, 1],
4964 [0.88221, 0.97219, 1],
4965 [0.8871, 0.97332, 1],
4966 [0.89197, 0.97446, 1],
4967 [0.89684, 0.97559, 1],
4968 [0.90168, 0.97672, 1],
4969 [0.90652, 0.97786, 1],
4970 [0.91134, 0.97899, 1],
4971 [0.91615, 0.98012, 1],
4972 [0.92095, 0.98125, 1],
4973 [0.92575, 0.98238, 1],
4974 [0.93053, 0.98351, 1],
4975 [0.93529, 0.98464, 1],
4976 [0.94005, 0.98576, 1],
4977 [0.9448, 0.98689, 1],
4978 [0.94953, 0.98801, 1],
4979 [0.95426, 0.98914, 1],
4980 [0.95897, 0.99026, 1],
4981 [0.96367, 0.99138, 1],
4982 [0.96837, 0.99251, 1],
4983 [0.97306, 0.99363, 1],
4984 [0.97773, 0.99474, 1],
4985 [0.9824, 0.99586, 1],
4986 [0.98725, 0.99702, 1],
4987 [0.9912, 0.99798, 1],
4988 [0.99685, 0.99934, 1],
4989 [0.99988, 0.9982, 0.99969],
4990 [0.99991, 0.99575, 0.99926],
4991 [0.99993, 0.9933, 0.99882],
4992 [0.99994, 0.99084, 0.99839],
4993 [0.99996, 0.98838, 0.99796],
4994 [0.99997, 0.98593, 0.99752],
4995 [0.99998, 0.98347, 0.99709],
4996 [0.99998, 0.98102, 0.99665],
4997 [0.99998, 0.97856, 0.99622],
4998 [0.99998, 0.97611, 0.99578],
4999 [0.99998, 0.97365, 0.99535],
5000 [0.99997, 0.97119, 0.99491],
5001 [0.99996, 0.96874, 0.99448],
5002 [0.99995, 0.96628, 0.99404],
5003 [0.99993, 0.96382, 0.99361],
5004 [0.99991, 0.96136, 0.99317],
5005 [0.99989, 0.9589, 0.99273],
5006 [0.99986, 0.95644, 0.99229],
5007 [0.99984, 0.95398, 0.99185],
5008 [0.9998, 0.95152, 0.99141],
5009 [0.99977, 0.94906, 0.99097],
5010 [0.99973, 0.9466, 0.99053],
5011 [0.99969, 0.94414, 0.99009],
5012 [0.99965, 0.94167, 0.98965],
5013 [0.9996, 0.93921, 0.98921],
5014 [0.99955, 0.93675, 0.98877],
5015 [0.9995, 0.93428, 0.98832],
5016 [0.99945, 0.93182, 0.98788],
5017 [0.99939, 0.92935, 0.98744],
5018 [0.99933, 0.92689, 0.987],
5019 [0.99926, 0.92442, 0.98656],
5020 [0.9992, 0.92196, 0.98611],
5021 [0.99913, 0.91949, 0.98567],
5022 [0.99905, 0.91702, 0.98522],
5023 [0.99898, 0.91455, 0.98478],
5024 [0.9989, 0.91208, 0.98433],
5025 [0.99882, 0.90961, 0.98388],
5026 [0.99873, 0.90714, 0.98343],
5027 [0.99865, 0.90467, 0.98299],
5028 [0.99855, 0.9022, 0.98254],
5029 [0.99846, 0.89973, 0.9821],
5030 [0.99837, 0.89726, 0.98165],
5031 [0.99827, 0.89478, 0.9812],
5032 [0.99816, 0.89231, 0.98075],
5033 [0.99806, 0.88983, 0.9803],
5034 [0.99795, 0.88735, 0.97985],
5035 [0.99784, 0.88488, 0.9794],
5036 [0.99773, 0.8824, 0.97894],
5037 [0.99761, 0.87992, 0.97849],
5038 [0.99749, 0.87744, 0.97804],
5039 [0.99737, 0.87496, 0.97759],
5040 [0.99725, 0.87248, 0.97714],
5041 [0.99712, 0.87, 0.97668],
5042 [0.99699, 0.86752, 0.97623],
5043 [0.99686, 0.86503, 0.97578],
5044 [0.99672, 0.86256, 0.97532],
5045 [0.99658, 0.86007, 0.97487],
5046 [0.99644, 0.85758, 0.97441],
5047 [0.9963, 0.8551, 0.97396],
5048 [0.99615, 0.85261, 0.9735],
5049 [0.996, 0.85012, 0.97305],
5050 [0.99585, 0.84763, 0.97259],
5051 [0.9957, 0.84514, 0.97214],
5052 [0.99554, 0.84265, 0.97168],
5053 [0.99538, 0.84016, 0.97122],
5054 [0.99522, 0.83767, 0.97076],
5055 [0.99505, 0.83517, 0.9703],
5056 [0.99488, 0.83267, 0.96984],
5057 [0.99471, 0.83018, 0.96938],
5058 [0.99454, 0.82768, 0.96892],
5059 [0.99436, 0.82518, 0.96846],
5060 [0.99418, 0.82268, 0.96801],
5061 [0.994, 0.82018, 0.96754],
5062 [0.99382, 0.81768, 0.96708],
5063 [0.99363, 0.81518, 0.96662],
5064 [0.99344, 0.81267, 0.96615],
5065 [0.99325, 0.81017, 0.96569],
5066 [0.99305, 0.80766, 0.96523],
5067 [0.99285, 0.80516, 0.96476],
5068 [0.99265, 0.80265, 0.9643],
5069 [0.99245, 0.80014, 0.96384],
5070 [0.99224, 0.79763, 0.96337],
5071 [0.99203, 0.79512, 0.96291],
5072 [0.99182, 0.7926, 0.96244],
5073 [0.99161, 0.79009, 0.96197],
5074 [0.99139, 0.78757, 0.96151],
5075 [0.99117, 0.78506, 0.96105],
5076 [0.99095, 0.78254, 0.96058],
5077 [0.99072, 0.78001, 0.96011],
5078 [0.9905, 0.7775, 0.95964],
5079 [0.99027, 0.77497, 0.95917],
5080 [0.99003, 0.77245, 0.95871],
5081 [0.9898, 0.76992, 0.95824],
5082 [0.98956, 0.76739, 0.95777],
5083 [0.98932, 0.76487, 0.9573],
5084 [0.98908, 0.76233, 0.95683],
5085 [0.98883, 0.7598, 0.95636],
5086 [0.98858, 0.75727, 0.95589],
5087 [0.98833, 0.75474, 0.95542],
5088 [0.98808, 0.7522, 0.95494],
5089 [0.98782, 0.74966, 0.95447],
5090 [0.98756, 0.74712, 0.954],
5091 [0.9873, 0.74458, 0.95353],
5092 [0.98704, 0.74204, 0.95305],
5093 [0.98677, 0.7395, 0.95258],
5094 [0.9865, 0.73694, 0.9521],
5095 [0.98623, 0.7344, 0.95163],
5096 [0.98596, 0.73185, 0.95115],
5097 [0.98568, 0.72929, 0.95068],
5098 [0.9854, 0.72674, 0.9502],
5099 [0.98512, 0.72418, 0.94972],
5100 [0.98484, 0.72162, 0.94925],
5101 [0.98455, 0.71907, 0.94877],
5102 [0.98426, 0.71651, 0.94829],
5103 [0.98397, 0.71394, 0.94782],
5104 [0.98367, 0.71138, 0.94734],
5105 [0.98338, 0.70881, 0.94686],
5106 [0.98308, 0.70624, 0.94638],
5107 [0.98278, 0.70366, 0.9459],
5108 [0.98247, 0.70109, 0.94542],
5109 [0.98217, 0.69851, 0.94494],
5110 [0.98186, 0.69594, 0.94446],
5111 [0.98154, 0.69335, 0.94398],
5112 [0.98123, 0.69077, 0.9435],
5113 [0.98091, 0.68819, 0.94302],
5114 [0.98059, 0.6856, 0.94253],
5115 [0.98027, 0.68301, 0.94205],
5116 [0.97995, 0.68041, 0.94156],
5117 ]
5118 b_diverging_cwm_80_100_c22 = bokeh_palette('diverging_cwm_80_100_c22',diverging_cwm_80_100_c22)
5119 m_diverging_cwm_80_100_c22 = mpl_cm('diverging_cwm_80_100_c22',diverging_cwm_80_100_c22)
5120 m_diverging_cwm_80_100_c22_r = mpl_cm('diverging_cwm_80_100_c22_r',list(reversed(diverging_cwm_80_100_c22)))
5121
5122
5123
5124
5125 diverging_gkr_60_10_c40 = [\
5126 [0.2109, 0.65114, 0.08795],
5127 [0.21113, 0.64645, 0.089674],
5128 [0.21134, 0.64175, 0.091371],
5129 [0.21153, 0.63707, 0.092907],
5130 [0.21169, 0.63239, 0.09454],
5131 [0.21184, 0.62772, 0.095984],
5132 [0.21196, 0.62306, 0.097463],
5133 [0.21206, 0.6184, 0.098858],
5134 [0.21214, 0.61374, 0.1002],
5135 [0.2122, 0.6091, 0.10151],
5136 [0.21223, 0.60446, 0.1028],
5137 [0.21225, 0.59982, 0.10401],
5138 [0.21225, 0.59519, 0.10517],
5139 [0.21224, 0.59056, 0.10638],
5140 [0.2122, 0.58596, 0.10746],
5141 [0.21215, 0.58134, 0.10849],
5142 [0.21207, 0.57674, 0.1096],
5143 [0.21198, 0.57214, 0.11058],
5144 [0.21187, 0.56755, 0.11155],
5145 [0.21174, 0.56297, 0.11249],
5146 [0.21159, 0.55838, 0.1134],
5147 [0.21142, 0.55382, 0.11421],
5148 [0.21123, 0.54926, 0.11506],
5149 [0.21103, 0.5447, 0.11592],
5150 [0.21081, 0.54014, 0.11669],
5151 [0.21057, 0.5356, 0.11742],
5152 [0.21032, 0.53106, 0.1182],
5153 [0.21005, 0.52654, 0.1189],
5154 [0.20977, 0.522, 0.11955],
5155 [0.20946, 0.5175, 0.1202],
5156 [0.20915, 0.51298, 0.12082],
5157 [0.20881, 0.50848, 0.12142],
5158 [0.20846, 0.50398, 0.122],
5159 [0.2081, 0.49948, 0.12257],
5160 [0.20772, 0.49501, 0.12311],
5161 [0.20732, 0.49053, 0.12363],
5162 [0.20692, 0.48605, 0.12413],
5163 [0.20649, 0.48159, 0.12461],
5164 [0.20604, 0.47713, 0.12507],
5165 [0.20556, 0.47268, 0.12553],
5166 [0.20508, 0.46824, 0.12595],
5167 [0.2046, 0.46381, 0.12633],
5168 [0.2041, 0.45938, 0.12668],
5169 [0.20357, 0.45497, 0.12703],
5170 [0.20302, 0.45055, 0.12737],
5171 [0.20246, 0.44614, 0.12771],
5172 [0.20189, 0.44175, 0.12802],
5173 [0.2013, 0.43736, 0.1283],
5174 [0.2007, 0.43297, 0.12855],
5175 [0.20009, 0.42859, 0.12879],
5176 [0.19947, 0.42421, 0.12902],
5177 [0.19883, 0.41986, 0.12924],
5178 [0.19818, 0.4155, 0.12945],
5179 [0.19752, 0.41115, 0.12965],
5180 [0.19686, 0.40681, 0.12982],
5181 [0.19616, 0.40247, 0.12998],
5182 [0.19543, 0.39816, 0.13012],
5183 [0.19472, 0.39383, 0.13024],
5184 [0.19399, 0.38952, 0.13034],
5185 [0.19321, 0.38522, 0.13043],
5186 [0.19244, 0.38094, 0.13051],
5187 [0.19166, 0.37665, 0.13056],
5188 [0.19086, 0.37236, 0.13061],
5189 [0.19005, 0.36809, 0.13064],
5190 [0.18924, 0.36383, 0.13066],
5191 [0.18842, 0.35958, 0.13066],
5192 [0.18757, 0.35534, 0.13065],
5193 [0.18668, 0.3511, 0.13063],
5194 [0.18583, 0.34687, 0.13059],
5195 [0.18493, 0.34265, 0.13054],
5196 [0.184, 0.33842, 0.13048],
5197 [0.18308, 0.33422, 0.13041],
5198 [0.18214, 0.33002, 0.13032],
5199 [0.1812, 0.32581, 0.13022],
5200 [0.18025, 0.32164, 0.1301],
5201 [0.17928, 0.31747, 0.12997],
5202 [0.17832, 0.31331, 0.12982],
5203 [0.17731, 0.30916, 0.12966],
5204 [0.17626, 0.305, 0.12949],
5205 [0.17526, 0.30085, 0.1293],
5206 [0.17423, 0.29673, 0.1291],
5207 [0.17316, 0.29259, 0.1289],
5208 [0.1721, 0.28848, 0.1287],
5209 [0.17102, 0.28437, 0.12849],
5210 [0.16995, 0.28027, 0.12827],
5211 [0.16885, 0.27621, 0.12802],
5212 [0.16771, 0.27209, 0.12776],
5213 [0.16659, 0.26803, 0.12748],
5214 [0.16541, 0.26399, 0.12719],
5215 [0.1643, 0.25993, 0.1269],
5216 [0.16312, 0.25587, 0.12661],
5217 [0.16194, 0.25185, 0.12632],
5218 [0.16072, 0.24783, 0.12601],
5219 [0.1595, 0.24378, 0.12567],
5220 [0.1583, 0.23979, 0.12532],
5221 [0.15704, 0.2358, 0.12495],
5222 [0.15581, 0.23181, 0.12458],
5223 [0.15452, 0.22783, 0.1242],
5224 [0.15324, 0.22384, 0.12382],
5225 [0.15195, 0.21989, 0.12342],
5226 [0.15065, 0.21594, 0.12301],
5227 [0.14935, 0.212, 0.1226],
5228 [0.148, 0.20805, 0.12217],
5229 [0.14664, 0.20414, 0.12174],
5230 [0.14533, 0.20018, 0.1213],
5231 [0.14393, 0.19632, 0.12085],
5232 [0.14254, 0.1924, 0.1204],
5233 [0.14116, 0.18853, 0.11993],
5234 [0.1397, 0.18465, 0.11946],
5235 [0.13835, 0.18077, 0.11899],
5236 [0.13693, 0.17695, 0.11852],
5237 [0.13553, 0.17313, 0.118],
5238 [0.1342, 0.16938, 0.11747],
5239 [0.13286, 0.16558, 0.11697],
5240 [0.13158, 0.16193, 0.1165],
5241 [0.13041, 0.15828, 0.116],
5242 [0.12925, 0.1547, 0.11549],
5243 [0.12828, 0.15123, 0.11499],
5244 [0.12744, 0.14789, 0.11453],
5245 [0.1268, 0.14468, 0.11413],
5246 [0.12643, 0.14163, 0.11378],
5247 [0.12631, 0.13876, 0.11346],
5248 [0.12649, 0.13609, 0.11319],
5249 [0.12701, 0.13374, 0.11297],
5250 [0.12798, 0.13162, 0.11282],
5251 [0.12929, 0.12981, 0.11275],
5252 [0.13109, 0.12828, 0.11276],
5253 [0.1333, 0.12705, 0.11287],
5254 [0.13593, 0.12624, 0.11307],
5255 [0.13905, 0.12571, 0.11335],
5256 [0.14261, 0.1255, 0.11371],
5257 [0.14653, 0.12561, 0.11414],
5258 [0.15086, 0.12602, 0.11466],
5259 [0.15553, 0.12666, 0.11531],
5260 [0.16047, 0.12758, 0.11603],
5261 [0.1657, 0.12871, 0.11675],
5262 [0.17119, 0.13008, 0.11752],
5263 [0.17685, 0.13154, 0.11839],
5264 [0.18266, 0.13315, 0.11923],
5265 [0.18863, 0.1349, 0.1201],
5266 [0.1947, 0.13667, 0.121],
5267 [0.20079, 0.13857, 0.12192],
5268 [0.20703, 0.1405, 0.12286],
5269 [0.21324, 0.14246, 0.12382],
5270 [0.21954, 0.14446, 0.12478],
5271 [0.22586, 0.14644, 0.12577],
5272 [0.23219, 0.14845, 0.12669],
5273 [0.23851, 0.1505, 0.12766],
5274 [0.24487, 0.1525, 0.12861],
5275 [0.25127, 0.15454, 0.12959],
5276 [0.25763, 0.15658, 0.13056],
5277 [0.26403, 0.1586, 0.13149],
5278 [0.27043, 0.16058, 0.13244],
5279 [0.27682, 0.16261, 0.13339],
5280 [0.28323, 0.1646, 0.13435],
5281 [0.28965, 0.1666, 0.13528],
5282 [0.29607, 0.16858, 0.13618],
5283 [0.3025, 0.17056, 0.13717],
5284 [0.30898, 0.17253, 0.13812],
5285 [0.31543, 0.17453, 0.13902],
5286 [0.3219, 0.17646, 0.13994],
5287 [0.32839, 0.17847, 0.14093],
5288 [0.33489, 0.18039, 0.14184],
5289 [0.34139, 0.18234, 0.14277],
5290 [0.34791, 0.1843, 0.1437],
5291 [0.35444, 0.18626, 0.14463],
5292 [0.36096, 0.18821, 0.14557],
5293 [0.36752, 0.19011, 0.14645],
5294 [0.3741, 0.19204, 0.14739],
5295 [0.38068, 0.19399, 0.14829],
5296 [0.38725, 0.19589, 0.14922],
5297 [0.39386, 0.1978, 0.15015],
5298 [0.40049, 0.19969, 0.15104],
5299 [0.40711, 0.2016, 0.15194],
5300 [0.41375, 0.20353, 0.15285],
5301 [0.4204, 0.20541, 0.15376],
5302 [0.42707, 0.20731, 0.15468],
5303 [0.43374, 0.20919, 0.1556],
5304 [0.44044, 0.21108, 0.15651],
5305 [0.44714, 0.21294, 0.15738],
5306 [0.45386, 0.21481, 0.15831],
5307 [0.46058, 0.21671, 0.15919],
5308 [0.46734, 0.21856, 0.16006],
5309 [0.47409, 0.22044, 0.16099],
5310 [0.48085, 0.22227, 0.1619],
5311 [0.48764, 0.22411, 0.16278],
5312 [0.49444, 0.22599, 0.16368],
5313 [0.50124, 0.22782, 0.16455],
5314 [0.50806, 0.22963, 0.1654],
5315 [0.51489, 0.2315, 0.16631],
5316 [0.52173, 0.2333, 0.16721],
5317 [0.5286, 0.23516, 0.16807],
5318 [0.53546, 0.23698, 0.16898],
5319 [0.54234, 0.23877, 0.16985],
5320 [0.54924, 0.24058, 0.17071],
5321 [0.55614, 0.2424, 0.17158],
5322 [0.56307, 0.2442, 0.17245],
5323 [0.56999, 0.246, 0.17332],
5324 [0.57695, 0.24782, 0.17421],
5325 [0.5839, 0.24959, 0.17508],
5326 [0.59087, 0.25141, 0.17591],
5327 [0.59785, 0.25318, 0.17679],
5328 [0.60485, 0.25498, 0.17769],
5329 [0.61185, 0.25674, 0.17854],
5330 [0.61888, 0.25851, 0.17939],
5331 [0.6259, 0.26028, 0.18024],
5332 [0.63295, 0.26205, 0.18109],
5333 [0.64001, 0.26383, 0.18194],
5334 [0.64708, 0.26557, 0.1828],
5335 [0.65415, 0.26731, 0.18366],
5336 [0.66125, 0.26909, 0.18452],
5337 [0.66835, 0.27084, 0.18539],
5338 [0.67547, 0.27256, 0.18622],
5339 [0.68259, 0.27431, 0.18707],
5340 [0.68974, 0.27606, 0.18793],
5341 [0.69689, 0.27778, 0.18876],
5342 [0.70405, 0.27952, 0.18959],
5343 [0.71123, 0.28123, 0.19042],
5344 [0.71841, 0.28297, 0.19126],
5345 [0.72562, 0.28467, 0.1921],
5346 [0.73282, 0.28638, 0.19294],
5347 [0.74005, 0.2881, 0.19379],
5348 [0.74728, 0.28981, 0.19463],
5349 [0.75453, 0.29152, 0.19544],
5350 [0.76178, 0.29321, 0.19629],
5351 [0.76904, 0.2949, 0.19711],
5352 [0.77633, 0.29661, 0.19792],
5353 [0.78362, 0.29829, 0.19874],
5354 [0.79092, 0.29998, 0.19955],
5355 [0.79823, 0.30166, 0.20037],
5356 [0.80555, 0.30334, 0.2012],
5357 [0.81289, 0.30503, 0.20202],
5358 [0.82024, 0.3067, 0.20285],
5359 [0.82759, 0.30837, 0.20368],
5360 [0.83497, 0.31005, 0.2045],
5361 [0.84235, 0.31169, 0.20529],
5362 [0.84974, 0.31336, 0.20613],
5363 [0.85714, 0.31501, 0.20694],
5364 [0.86455, 0.31667, 0.20773],
5365 [0.87198, 0.31832, 0.20854],
5366 [0.87941, 0.31997, 0.20934],
5367 [0.88686, 0.3216, 0.21015],
5368 [0.89431, 0.32325, 0.21095],
5369 [0.90178, 0.32488, 0.21177],
5370 [0.90925, 0.32651, 0.21256],
5371 [0.91675, 0.32815, 0.21334],
5372 [0.92424, 0.32979, 0.21416],
5373 [0.93175, 0.33139, 0.21494],
5374 [0.93927, 0.33303, 0.21575],
5375 [0.9468, 0.33465, 0.21655],
5376 [0.95434, 0.33625, 0.21733],
5377 [0.96189, 0.33786, 0.21812],
5378 [0.96945, 0.33948, 0.21891],
5379 [0.97703, 0.34108, 0.2197],
5380 [0.98461, 0.34269, 0.2205],
5381 [0.9922, 0.34427, 0.22128],
5382 ]
5383 b_diverging_gkr_60_10_c40 = bokeh_palette('diverging_gkr_60_10_c40',diverging_gkr_60_10_c40)
5384 m_diverging_gkr_60_10_c40 = mpl_cm('diverging_gkr_60_10_c40',diverging_gkr_60_10_c40)
5385 m_diverging_gkr_60_10_c40_r = mpl_cm('diverging_gkr_60_10_c40_r',list(reversed(diverging_gkr_60_10_c40)))
5386
5387
5388
5389
5390 diverging_gwr_55_95_c38 = [\
5391 [0.22157, 0.59107, 0.055073],
5392 [0.22965, 0.59389, 0.068993],
5393 [0.2376, 0.59671, 0.081291],
5394 [0.24531, 0.59952, 0.092565],
5395 [0.25292, 0.60233, 0.10315],
5396 [0.26037, 0.60514, 0.11313],
5397 [0.26768, 0.60796, 0.12253],
5398 [0.27491, 0.61076, 0.13168],
5399 [0.28202, 0.61356, 0.14045],
5400 [0.28902, 0.61637, 0.14894],
5401 [0.29592, 0.61918, 0.15721],
5402 [0.30273, 0.62197, 0.16528],
5403 [0.3095, 0.62478, 0.1732],
5404 [0.31616, 0.62758, 0.18095],
5405 [0.32276, 0.63038, 0.18859],
5406 [0.32929, 0.63317, 0.1961],
5407 [0.33575, 0.63597, 0.20349],
5408 [0.34216, 0.63876, 0.21079],
5409 [0.34851, 0.64155, 0.21802],
5410 [0.35482, 0.64434, 0.22514],
5411 [0.36105, 0.64714, 0.23224],
5412 [0.36726, 0.64993, 0.23924],
5413 [0.37343, 0.65271, 0.24619],
5414 [0.37954, 0.6555, 0.25311],
5415 [0.38562, 0.65828, 0.25997],
5416 [0.39167, 0.66106, 0.26678],
5417 [0.39767, 0.66385, 0.27357],
5418 [0.40364, 0.66662, 0.28029],
5419 [0.40958, 0.66941, 0.287],
5420 [0.41548, 0.67219, 0.29368],
5421 [0.42135, 0.67496, 0.30034],
5422 [0.42721, 0.67774, 0.30697],
5423 [0.43302, 0.68051, 0.31358],
5424 [0.43881, 0.68328, 0.32017],
5425 [0.44459, 0.68606, 0.32672],
5426 [0.45032, 0.68883, 0.33328],
5427 [0.45604, 0.6916, 0.33982],
5428 [0.46174, 0.69436, 0.34632],
5429 [0.46742, 0.69713, 0.35283],
5430 [0.47307, 0.6999, 0.35932],
5431 [0.47871, 0.70267, 0.3658],
5432 [0.48432, 0.70543, 0.37227],
5433 [0.48992, 0.70819, 0.37873],
5434 [0.49551, 0.71096, 0.38518],
5435 [0.50108, 0.71371, 0.39164],
5436 [0.50662, 0.71648, 0.39808],
5437 [0.51215, 0.71923, 0.40451],
5438 [0.51768, 0.72199, 0.41095],
5439 [0.52318, 0.72475, 0.41738],
5440 [0.52867, 0.7275, 0.42379],
5441 [0.53414, 0.73026, 0.43022],
5442 [0.5396, 0.73301, 0.43664],
5443 [0.54506, 0.73576, 0.44305],
5444 [0.5505, 0.73851, 0.44946],
5445 [0.55592, 0.74126, 0.45587],
5446 [0.56134, 0.74401, 0.46228],
5447 [0.56675, 0.74676, 0.4687],
5448 [0.57214, 0.7495, 0.47512],
5449 [0.57752, 0.75225, 0.48152],
5450 [0.58289, 0.755, 0.48794],
5451 [0.58826, 0.75775, 0.49435],
5452 [0.59362, 0.76049, 0.50076],
5453 [0.59896, 0.76323, 0.50717],
5454 [0.60431, 0.76597, 0.5136],
5455 [0.60963, 0.76871, 0.52001],
5456 [0.61495, 0.77146, 0.52644],
5457 [0.62027, 0.77419, 0.53286],
5458 [0.62557, 0.77693, 0.53928],
5459 [0.63088, 0.77967, 0.54572],
5460 [0.63617, 0.7824, 0.55215],
5461 [0.64145, 0.78514, 0.55858],
5462 [0.64673, 0.78787, 0.56502],
5463 [0.652, 0.79061, 0.57147],
5464 [0.65727, 0.79334, 0.57791],
5465 [0.66253, 0.79607, 0.58437],
5466 [0.66778, 0.7988, 0.59082],
5467 [0.67303, 0.80153, 0.59729],
5468 [0.67827, 0.80426, 0.60376],
5469 [0.68351, 0.80699, 0.61022],
5470 [0.68875, 0.80972, 0.6167],
5471 [0.69397, 0.81244, 0.62318],
5472 [0.69919, 0.81517, 0.62965],
5473 [0.70441, 0.8179, 0.63615],
5474 [0.70963, 0.82062, 0.64264],
5475 [0.71483, 0.82335, 0.64914],
5476 [0.72004, 0.82607, 0.65564],
5477 [0.72525, 0.82879, 0.66215],
5478 [0.73044, 0.83152, 0.66866],
5479 [0.73563, 0.83424, 0.67518],
5480 [0.74082, 0.83696, 0.6817],
5481 [0.74601, 0.83968, 0.68824],
5482 [0.7512, 0.84239, 0.69477],
5483 [0.75637, 0.84511, 0.70131],
5484 [0.76155, 0.84782, 0.70786],
5485 [0.76672, 0.85054, 0.71441],
5486 [0.77189, 0.85326, 0.72097],
5487 [0.77706, 0.85597, 0.72754],
5488 [0.78223, 0.85869, 0.73411],
5489 [0.78739, 0.8614, 0.74068],
5490 [0.79255, 0.86412, 0.74727],
5491 [0.7977, 0.86682, 0.75386],
5492 [0.80286, 0.86954, 0.76045],
5493 [0.80801, 0.87225, 0.76705],
5494 [0.81316, 0.87496, 0.77366],
5495 [0.81831, 0.87767, 0.78027],
5496 [0.82345, 0.88037, 0.7869],
5497 [0.8286, 0.88308, 0.79353],
5498 [0.83375, 0.88579, 0.80016],
5499 [0.83889, 0.88849, 0.80678],
5500 [0.84403, 0.89117, 0.8134],
5501 [0.84917, 0.89385, 0.82001],
5502 [0.8543, 0.8965, 0.82659],
5503 [0.85943, 0.89913, 0.83314],
5504 [0.86454, 0.90171, 0.83964],
5505 [0.86965, 0.90424, 0.84606],
5506 [0.87473, 0.9067, 0.85239],
5507 [0.87979, 0.90907, 0.85857],
5508 [0.88483, 0.91132, 0.8646],
5509 [0.88981, 0.91343, 0.87039],
5510 [0.89474, 0.91536, 0.87592],
5511 [0.8996, 0.91708, 0.88112],
5512 [0.90436, 0.91854, 0.88593],
5513 [0.90902, 0.91973, 0.89029],
5514 [0.91355, 0.92058, 0.89413],
5515 [0.91792, 0.92108, 0.8974],
5516 [0.92213, 0.9212, 0.90005],
5517 [0.92614, 0.92091, 0.90203],
5518 [0.92995, 0.9202, 0.90332],
5519 [0.93353, 0.91905, 0.9039],
5520 [0.9369, 0.91749, 0.90377],
5521 [0.94002, 0.91549, 0.90294],
5522 [0.94291, 0.91311, 0.90144],
5523 [0.94556, 0.91036, 0.89932],
5524 [0.94799, 0.90726, 0.89661],
5525 [0.95021, 0.90386, 0.89338],
5526 [0.95224, 0.90019, 0.88969],
5527 [0.95409, 0.89629, 0.8856],
5528 [0.95578, 0.89219, 0.88117],
5529 [0.95733, 0.88793, 0.87646],
5530 [0.95876, 0.88354, 0.87154],
5531 [0.96008, 0.87904, 0.86642],
5532 [0.96131, 0.87447, 0.86117],
5533 [0.96246, 0.86983, 0.85582],
5534 [0.96355, 0.86515, 0.85038],
5535 [0.96458, 0.86044, 0.8449],
5536 [0.96556, 0.8557, 0.83937],
5537 [0.9665, 0.85093, 0.83383],
5538 [0.9674, 0.84616, 0.82826],
5539 [0.96826, 0.84138, 0.82269],
5540 [0.96908, 0.83659, 0.81711],
5541 [0.96988, 0.83181, 0.81154],
5542 [0.97064, 0.82702, 0.80597],
5543 [0.97138, 0.82223, 0.80041],
5544 [0.9721, 0.81743, 0.79486],
5545 [0.97278, 0.81263, 0.78932],
5546 [0.97344, 0.80784, 0.78378],
5547 [0.97407, 0.80303, 0.77824],
5548 [0.97467, 0.79823, 0.77271],
5549 [0.97524, 0.79344, 0.76719],
5550 [0.97579, 0.78863, 0.76168],
5551 [0.97632, 0.78382, 0.75618],
5552 [0.97682, 0.77901, 0.75068],
5553 [0.97729, 0.7742, 0.74518],
5554 [0.97774, 0.76938, 0.7397],
5555 [0.97816, 0.76457, 0.73422],
5556 [0.97855, 0.75974, 0.72875],
5557 [0.97893, 0.75493, 0.72328],
5558 [0.97928, 0.7501, 0.71783],
5559 [0.9796, 0.74527, 0.71237],
5560 [0.9799, 0.74044, 0.70693],
5561 [0.98017, 0.7356, 0.70149],
5562 [0.98042, 0.73077, 0.69606],
5563 [0.98064, 0.72593, 0.69063],
5564 [0.98084, 0.72108, 0.68522],
5565 [0.98102, 0.71624, 0.6798],
5566 [0.98118, 0.71138, 0.6744],
5567 [0.98131, 0.70653, 0.66901],
5568 [0.98142, 0.70166, 0.66363],
5569 [0.9815, 0.69679, 0.65824],
5570 [0.98157, 0.69193, 0.65286],
5571 [0.98161, 0.68705, 0.6475],
5572 [0.98162, 0.68217, 0.64214],
5573 [0.98162, 0.67729, 0.63679],
5574 [0.98159, 0.6724, 0.63144],
5575 [0.98154, 0.6675, 0.6261],
5576 [0.98147, 0.6626, 0.62077],
5577 [0.98138, 0.6577, 0.61544],
5578 [0.98126, 0.65278, 0.61013],
5579 [0.98113, 0.64786, 0.60482],
5580 [0.98097, 0.64294, 0.59952],
5581 [0.98079, 0.63801, 0.59422],
5582 [0.98059, 0.63307, 0.58893],
5583 [0.98037, 0.62813, 0.58366],
5584 [0.98013, 0.62318, 0.57838],
5585 [0.97987, 0.61821, 0.57313],
5586 [0.97959, 0.61324, 0.56786],
5587 [0.97929, 0.60827, 0.56262],
5588 [0.97896, 0.60329, 0.55738],
5589 [0.97862, 0.59829, 0.55214],
5590 [0.97826, 0.59329, 0.54691],
5591 [0.97788, 0.58827, 0.54169],
5592 [0.97747, 0.58326, 0.53649],
5593 [0.97705, 0.57822, 0.53128],
5594 [0.97661, 0.57319, 0.52609],
5595 [0.97615, 0.56814, 0.5209],
5596 [0.97567, 0.56308, 0.51571],
5597 [0.97517, 0.558, 0.51054],
5598 [0.97465, 0.55292, 0.50537],
5599 [0.97411, 0.54782, 0.50022],
5600 [0.97355, 0.54272, 0.49508],
5601 [0.97298, 0.5376, 0.48993],
5602 [0.97239, 0.53246, 0.48479],
5603 [0.97177, 0.52731, 0.47968],
5604 [0.97114, 0.52213, 0.47456],
5605 [0.97049, 0.51696, 0.46946],
5606 [0.96982, 0.51176, 0.46436],
5607 [0.96914, 0.50655, 0.45926],
5608 [0.96843, 0.50133, 0.45417],
5609 [0.96771, 0.49607, 0.4491],
5610 [0.96697, 0.49082, 0.44403],
5611 [0.96621, 0.48553, 0.43896],
5612 [0.96544, 0.48023, 0.4339],
5613 [0.96464, 0.47491, 0.42887],
5614 [0.96383, 0.46957, 0.42382],
5615 [0.96301, 0.4642, 0.4188],
5616 [0.96216, 0.45881, 0.41378],
5617 [0.9613, 0.45339, 0.40877],
5618 [0.96042, 0.44795, 0.40377],
5619 [0.95952, 0.4425, 0.39877],
5620 [0.95861, 0.43701, 0.39379],
5621 [0.95768, 0.43149, 0.38882],
5622 [0.95673, 0.42593, 0.38384],
5623 [0.95577, 0.42035, 0.37888],
5624 [0.95479, 0.41474, 0.37393],
5625 [0.9538, 0.4091, 0.36899],
5626 [0.95278, 0.40342, 0.36405],
5627 [0.95175, 0.3977, 0.35912],
5628 [0.95071, 0.39194, 0.3542],
5629 [0.94964, 0.38614, 0.3493],
5630 [0.94857, 0.38031, 0.34439],
5631 [0.94747, 0.37443, 0.33951],
5632 [0.94636, 0.3685, 0.33463],
5633 [0.94524, 0.36251, 0.32975],
5634 [0.9441, 0.35648, 0.32487],
5635 [0.94294, 0.3504, 0.32002],
5636 [0.94177, 0.34423, 0.31516],
5637 [0.94058, 0.33802, 0.31033],
5638 [0.93938, 0.33175, 0.3055],
5639 [0.93816, 0.3254, 0.30066],
5640 [0.93693, 0.31899, 0.29584],
5641 [0.93568, 0.31248, 0.29104],
5642 [0.93441, 0.30592, 0.28623],
5643 [0.93313, 0.29924, 0.28145],
5644 [0.93184, 0.29246, 0.27668],
5645 [0.93053, 0.28558, 0.27188],
5646 [0.9292, 0.27862, 0.26712],
5647 ]
5648 b_diverging_gwr_55_95_c38 = bokeh_palette('diverging_gwr_55_95_c38',diverging_gwr_55_95_c38)
5649 m_diverging_gwr_55_95_c38 = mpl_cm('diverging_gwr_55_95_c38',diverging_gwr_55_95_c38)
5650 m_diverging_gwr_55_95_c38_r = mpl_cm('diverging_gwr_55_95_c38_r',list(reversed(diverging_gwr_55_95_c38)))
5651
5652
5653
5654
5655 diverging_gwv_55_95_c39 = [\
5656 [0.22157, 0.59107, 0.055073],
5657 [0.22965, 0.59389, 0.068993],
5658 [0.2376, 0.59671, 0.081291],
5659 [0.24531, 0.59952, 0.092565],
5660 [0.25292, 0.60233, 0.10315],
5661 [0.26037, 0.60514, 0.11313],
5662 [0.26768, 0.60796, 0.12253],
5663 [0.27491, 0.61076, 0.13168],
5664 [0.28202, 0.61356, 0.14045],
5665 [0.28902, 0.61637, 0.14894],
5666 [0.29592, 0.61918, 0.15721],
5667 [0.30273, 0.62197, 0.16528],
5668 [0.3095, 0.62478, 0.1732],
5669 [0.31616, 0.62758, 0.18095],
5670 [0.32276, 0.63038, 0.18859],
5671 [0.32929, 0.63317, 0.1961],
5672 [0.33575, 0.63597, 0.20349],
5673 [0.34216, 0.63876, 0.21079],
5674 [0.34851, 0.64155, 0.21802],
5675 [0.35482, 0.64434, 0.22514],
5676 [0.36105, 0.64714, 0.23224],
5677 [0.36726, 0.64993, 0.23924],
5678 [0.37343, 0.65271, 0.24619],
5679 [0.37954, 0.6555, 0.25311],
5680 [0.38562, 0.65828, 0.25997],
5681 [0.39167, 0.66106, 0.26678],
5682 [0.39767, 0.66385, 0.27357],
5683 [0.40364, 0.66662, 0.28029],
5684 [0.40958, 0.66941, 0.287],
5685 [0.41548, 0.67219, 0.29368],
5686 [0.42135, 0.67496, 0.30034],
5687 [0.42721, 0.67774, 0.30697],
5688 [0.43302, 0.68051, 0.31358],
5689 [0.43881, 0.68328, 0.32017],
5690 [0.44459, 0.68606, 0.32672],
5691 [0.45032, 0.68883, 0.33328],
5692 [0.45604, 0.6916, 0.33982],
5693 [0.46174, 0.69436, 0.34632],
5694 [0.46742, 0.69713, 0.35283],
5695 [0.47307, 0.6999, 0.35932],
5696 [0.47871, 0.70267, 0.3658],
5697 [0.48432, 0.70543, 0.37227],
5698 [0.48992, 0.70819, 0.37873],
5699 [0.49551, 0.71096, 0.38518],
5700 [0.50108, 0.71371, 0.39164],
5701 [0.50662, 0.71648, 0.39808],
5702 [0.51215, 0.71923, 0.40451],
5703 [0.51768, 0.72199, 0.41095],
5704 [0.52318, 0.72475, 0.41738],
5705 [0.52867, 0.7275, 0.42379],
5706 [0.53414, 0.73026, 0.43022],
5707 [0.5396, 0.73301, 0.43664],
5708 [0.54506, 0.73576, 0.44305],
5709 [0.5505, 0.73851, 0.44946],
5710 [0.55592, 0.74126, 0.45587],
5711 [0.56134, 0.74401, 0.46228],
5712 [0.56675, 0.74676, 0.4687],
5713 [0.57214, 0.7495, 0.47512],
5714 [0.57752, 0.75225, 0.48152],
5715 [0.58289, 0.755, 0.48794],
5716 [0.58826, 0.75775, 0.49435],
5717 [0.59362, 0.76049, 0.50076],
5718 [0.59896, 0.76323, 0.50717],
5719 [0.60431, 0.76597, 0.5136],
5720 [0.60963, 0.76871, 0.52001],
5721 [0.61495, 0.77146, 0.52644],
5722 [0.62027, 0.77419, 0.53286],
5723 [0.62557, 0.77693, 0.53928],
5724 [0.63088, 0.77967, 0.54572],
5725 [0.63617, 0.7824, 0.55215],
5726 [0.64145, 0.78514, 0.55858],
5727 [0.64673, 0.78787, 0.56502],
5728 [0.652, 0.79061, 0.57147],
5729 [0.65727, 0.79334, 0.57791],
5730 [0.66253, 0.79607, 0.58437],
5731 [0.66778, 0.7988, 0.59082],
5732 [0.67303, 0.80153, 0.59729],
5733 [0.67827, 0.80426, 0.60376],
5734 [0.68351, 0.80699, 0.61022],
5735 [0.68875, 0.80972, 0.6167],
5736 [0.69397, 0.81244, 0.62318],
5737 [0.69919, 0.81517, 0.62965],
5738 [0.70441, 0.8179, 0.63615],
5739 [0.70963, 0.82062, 0.64264],
5740 [0.71483, 0.82335, 0.64914],
5741 [0.72004, 0.82607, 0.65564],
5742 [0.72525, 0.82879, 0.66215],
5743 [0.73044, 0.83152, 0.66866],
5744 [0.73563, 0.83424, 0.67518],
5745 [0.74082, 0.83696, 0.6817],
5746 [0.74601, 0.83968, 0.68824],
5747 [0.7512, 0.84239, 0.69477],
5748 [0.75637, 0.84511, 0.70131],
5749 [0.76155, 0.84782, 0.70786],
5750 [0.76672, 0.85054, 0.71441],
5751 [0.77189, 0.85326, 0.72097],
5752 [0.77706, 0.85597, 0.72754],
5753 [0.78223, 0.85869, 0.73411],
5754 [0.78739, 0.8614, 0.74068],
5755 [0.79255, 0.86412, 0.74727],
5756 [0.7977, 0.86682, 0.75386],
5757 [0.80286, 0.86954, 0.76045],
5758 [0.80801, 0.87225, 0.76705],
5759 [0.81316, 0.87496, 0.77366],
5760 [0.81831, 0.87767, 0.78027],
5761 [0.82345, 0.88037, 0.7869],
5762 [0.8286, 0.88308, 0.79353],
5763 [0.83375, 0.88579, 0.80016],
5764 [0.83888, 0.88849, 0.8068],
5765 [0.84401, 0.89118, 0.81343],
5766 [0.84914, 0.89385, 0.82007],
5767 [0.85424, 0.89651, 0.82671],
5768 [0.85933, 0.89914, 0.83333],
5769 [0.8644, 0.90172, 0.83995],
5770 [0.86942, 0.90426, 0.84652],
5771 [0.8744, 0.90673, 0.85306],
5772 [0.87932, 0.90912, 0.85955],
5773 [0.88415, 0.91139, 0.86596],
5774 [0.88888, 0.91352, 0.87228],
5775 [0.89348, 0.91548, 0.87846],
5776 [0.89792, 0.91724, 0.8845],
5777 [0.90218, 0.91875, 0.89034],
5778 [0.90621, 0.92, 0.89596],
5779 [0.90998, 0.92093, 0.90131],
5780 [0.91347, 0.92152, 0.90637],
5781 [0.91664, 0.92174, 0.91109],
5782 [0.91948, 0.92157, 0.91546],
5783 [0.92195, 0.92098, 0.91944],
5784 [0.92406, 0.91999, 0.92303],
5785 [0.92579, 0.91859, 0.92621],
5786 [0.92715, 0.91679, 0.92898],
5787 [0.92815, 0.9146, 0.93137],
5788 [0.92881, 0.91206, 0.93337],
5789 [0.92915, 0.90919, 0.93503],
5790 [0.9292, 0.90603, 0.93636],
5791 [0.92898, 0.9026, 0.9374],
5792 [0.92854, 0.89895, 0.93818],
5793 [0.9279, 0.89512, 0.93875],
5794 [0.9271, 0.89113, 0.93913],
5795 [0.92616, 0.88701, 0.93935],
5796 [0.92511, 0.8828, 0.93945],
5797 [0.92397, 0.87851, 0.93946],
5798 [0.92276, 0.87416, 0.93938],
5799 [0.92149, 0.86976, 0.93925],
5800 [0.92018, 0.86533, 0.93907],
5801 [0.91883, 0.86089, 0.93886],
5802 [0.91747, 0.85642, 0.93862],
5803 [0.91607, 0.85195, 0.93837],
5804 [0.91467, 0.84746, 0.93811],
5805 [0.91325, 0.84298, 0.93783],
5806 [0.91182, 0.83849, 0.93754],
5807 [0.91039, 0.834, 0.93726],
5808 [0.90894, 0.82952, 0.93697],
5809 [0.9075, 0.82502, 0.93668],
5810 [0.90604, 0.82053, 0.93639],
5811 [0.90457, 0.81605, 0.93609],
5812 [0.9031, 0.81156, 0.93579],
5813 [0.90162, 0.80708, 0.93549],
5814 [0.90014, 0.80258, 0.93519],
5815 [0.89864, 0.7981, 0.93488],
5816 [0.89715, 0.79361, 0.93457],
5817 [0.89564, 0.78912, 0.93426],
5818 [0.89412, 0.78464, 0.93395],
5819 [0.8926, 0.78014, 0.93363],
5820 [0.89107, 0.77565, 0.93332],
5821 [0.88953, 0.77117, 0.93299],
5822 [0.88799, 0.76667, 0.93267],
5823 [0.88644, 0.76218, 0.93235],
5824 [0.88488, 0.75769, 0.93202],
5825 [0.88332, 0.75319, 0.93169],
5826 [0.88174, 0.7487, 0.93136],
5827 [0.88016, 0.74421, 0.93103],
5828 [0.87857, 0.73972, 0.93069],
5829 [0.87698, 0.73522, 0.93035],
5830 [0.87538, 0.73072, 0.93001],
5831 [0.87377, 0.72622, 0.92966],
5832 [0.87215, 0.72172, 0.92931],
5833 [0.87052, 0.71723, 0.92896],
5834 [0.8689, 0.71271, 0.92861],
5835 [0.86725, 0.70822, 0.92826],
5836 [0.86561, 0.70371, 0.9279],
5837 [0.86396, 0.6992, 0.92754],
5838 [0.8623, 0.69469, 0.92718],
5839 [0.86063, 0.69018, 0.92682],
5840 [0.85895, 0.68568, 0.92645],
5841 [0.85727, 0.68116, 0.92609],
5842 [0.85558, 0.67665, 0.92572],
5843 [0.85388, 0.67213, 0.92534],
5844 [0.85218, 0.66761, 0.92497],
5845 [0.85046, 0.66309, 0.92459],
5846 [0.84874, 0.65856, 0.92421],
5847 [0.84701, 0.65404, 0.92383],
5848 [0.84528, 0.64951, 0.92345],
5849 [0.84353, 0.64497, 0.92306],
5850 [0.84178, 0.64044, 0.92267],
5851 [0.84003, 0.6359, 0.92228],
5852 [0.83826, 0.63136, 0.92189],
5853 [0.83649, 0.62682, 0.92149],
5854 [0.83471, 0.62227, 0.92109],
5855 [0.83291, 0.61772, 0.92069],
5856 [0.83112, 0.61316, 0.92029],
5857 [0.82932, 0.60861, 0.91989],
5858 [0.8275, 0.60405, 0.91948],
5859 [0.82568, 0.59948, 0.91907],
5860 [0.82386, 0.59491, 0.91866],
5861 [0.82203, 0.59033, 0.91825],
5862 [0.82018, 0.58576, 0.91784],
5863 [0.81833, 0.58117, 0.91743],
5864 [0.81648, 0.57659, 0.91701],
5865 [0.81461, 0.57199, 0.91658],
5866 [0.81273, 0.56739, 0.91615],
5867 [0.81085, 0.56279, 0.91573],
5868 [0.80897, 0.55817, 0.9153],
5869 [0.80707, 0.55356, 0.91487],
5870 [0.80516, 0.54895, 0.91444],
5871 [0.80325, 0.54431, 0.91401],
5872 [0.80133, 0.53967, 0.91357],
5873 [0.7994, 0.53504, 0.91313],
5874 [0.79746, 0.53039, 0.91269],
5875 [0.79552, 0.52573, 0.91225],
5876 [0.79357, 0.52107, 0.9118],
5877 [0.7916, 0.51639, 0.91136],
5878 [0.78964, 0.51172, 0.91091],
5879 [0.78766, 0.50703, 0.91046],
5880 [0.78568, 0.50233, 0.91001],
5881 [0.78368, 0.49764, 0.90955],
5882 [0.78168, 0.49291, 0.90909],
5883 [0.77967, 0.48819, 0.90863],
5884 [0.77766, 0.48345, 0.90817],
5885 [0.77563, 0.47871, 0.90771],
5886 [0.77359, 0.47395, 0.90724],
5887 [0.77155, 0.46919, 0.90678],
5888 [0.7695, 0.46441, 0.90631],
5889 [0.76744, 0.45961, 0.90584],
5890 [0.76538, 0.45481, 0.90536],
5891 [0.76329, 0.44999, 0.90489],
5892 [0.76121, 0.44516, 0.90441],
5893 [0.75912, 0.44031, 0.90393],
5894 [0.75702, 0.43546, 0.90345],
5895 [0.75491, 0.43057, 0.90297],
5896 [0.75278, 0.42568, 0.90248],
5897 [0.75066, 0.42076, 0.90199],
5898 [0.74852, 0.41584, 0.9015],
5899 [0.74638, 0.4109, 0.90101],
5900 [0.74423, 0.40594, 0.90052],
5901 [0.74206, 0.40096, 0.90002],
5902 [0.7399, 0.39595, 0.89953],
5903 [0.73771, 0.39092, 0.89903],
5904 [0.73552, 0.38586, 0.89853],
5905 [0.73333, 0.3808, 0.89802],
5906 [0.73112, 0.37569, 0.89752],
5907 [0.7289, 0.37056, 0.89702],
5908 [0.72668, 0.36542, 0.89651],
5909 [0.72444, 0.36023, 0.896],
5910 [0.72219, 0.35504, 0.89548],
5911 [0.71995, 0.34979, 0.89497],
5912 ]
5913 b_diverging_gwv_55_95_c39 = bokeh_palette('diverging_gwv_55_95_c39',diverging_gwv_55_95_c39)
5914 m_diverging_gwv_55_95_c39 = mpl_cm('diverging_gwv_55_95_c39',diverging_gwv_55_95_c39)
5915 m_diverging_gwv_55_95_c39_r = mpl_cm('diverging_gwv_55_95_c39_r',list(reversed(diverging_gwv_55_95_c39)))
5916 gwv = b_diverging_gwv_55_95_c39
5917 m_gwv = m_diverging_gwv_55_95_c39
5918 m_gwv_r = m_diverging_gwv_55_95_c39_r
5919 palette['gwv'] = b_diverging_gwv_55_95_c39
5920 cm['gwv'] = m_diverging_gwv_55_95_c39
5921 cm['gwv_r'] = m_diverging_gwv_55_95_c39_r
5922 register_cmap('cet_gwv',m_diverging_gwv_55_95_c39)
5923 register_cmap('cet_gwv_r',m_diverging_gwv_55_95_c39_r)
5924
5925
5926
5927
5928 isoluminant_cgo_70_c39 = [\
5929 [0.21566, 0.71777, 0.92594],
5930 [0.21805, 0.71808, 0.92254],
5931 [0.2204, 0.71839, 0.91913],
5932 [0.22272, 0.7187, 0.91573],
5933 [0.22499, 0.71901, 0.91232],
5934 [0.22727, 0.71931, 0.90891],
5935 [0.2295, 0.71962, 0.9055],
5936 [0.23174, 0.71992, 0.90208],
5937 [0.23392, 0.72022, 0.89866],
5938 [0.23611, 0.72051, 0.89524],
5939 [0.23825, 0.72081, 0.89181],
5940 [0.24038, 0.7211, 0.88838],
5941 [0.2425, 0.72139, 0.88495],
5942 [0.2446, 0.72168, 0.88151],
5943 [0.24668, 0.72196, 0.87807],
5944 [0.24877, 0.72225, 0.87462],
5945 [0.25081, 0.72253, 0.87117],
5946 [0.25284, 0.72281, 0.86772],
5947 [0.25488, 0.72309, 0.86426],
5948 [0.25687, 0.72336, 0.8608],
5949 [0.25887, 0.72363, 0.85734],
5950 [0.26085, 0.7239, 0.85387],
5951 [0.26281, 0.72417, 0.8504],
5952 [0.26477, 0.72444, 0.84692],
5953 [0.26672, 0.7247, 0.84344],
5954 [0.26866, 0.72496, 0.83996],
5955 [0.27061, 0.72522, 0.83647],
5956 [0.2725, 0.72548, 0.83297],
5957 [0.27442, 0.72573, 0.82948],
5958 [0.27635, 0.72598, 0.82598],
5959 [0.27824, 0.72622, 0.82247],
5960 [0.28012, 0.72647, 0.81896],
5961 [0.28203, 0.72671, 0.81545],
5962 [0.28389, 0.72694, 0.81193],
5963 [0.28576, 0.72718, 0.8084],
5964 [0.28764, 0.72741, 0.80487],
5965 [0.28953, 0.72764, 0.80134],
5966 [0.2914, 0.72787, 0.7978],
5967 [0.29325, 0.72809, 0.79426],
5968 [0.29511, 0.72831, 0.79071],
5969 [0.29699, 0.72853, 0.78716],
5970 [0.29885, 0.72875, 0.7836],
5971 [0.3007, 0.72896, 0.78003],
5972 [0.30255, 0.72917, 0.77647],
5973 [0.30443, 0.72937, 0.77289],
5974 [0.30631, 0.72958, 0.76931],
5975 [0.30815, 0.72978, 0.76573],
5976 [0.31004, 0.72997, 0.76213],
5977 [0.31189, 0.73016, 0.75854],
5978 [0.31378, 0.73035, 0.75494],
5979 [0.31565, 0.73053, 0.75133],
5980 [0.31753, 0.73071, 0.74772],
5981 [0.31943, 0.73089, 0.74409],
5982 [0.32131, 0.73106, 0.74047],
5983 [0.32321, 0.73123, 0.73684],
5984 [0.32511, 0.7314, 0.7332],
5985 [0.32703, 0.73156, 0.72956],
5986 [0.32897, 0.73172, 0.72591],
5987 [0.33088, 0.73187, 0.72225],
5988 [0.33284, 0.73202, 0.71859],
5989 [0.33479, 0.73217, 0.71492],
5990 [0.33674, 0.73231, 0.71125],
5991 [0.33871, 0.73244, 0.70756],
5992 [0.34069, 0.73257, 0.70388],
5993 [0.34269, 0.7327, 0.70018],
5994 [0.34469, 0.73282, 0.69648],
5995 [0.34672, 0.73293, 0.69278],
5996 [0.34875, 0.73304, 0.68906],
5997 [0.35081, 0.73315, 0.68534],
5998 [0.35286, 0.73325, 0.68161],
5999 [0.35496, 0.73334, 0.67788],
6000 [0.35706, 0.73343, 0.67413],
6001 [0.35916, 0.73351, 0.67039],
6002 [0.3613, 0.73359, 0.66663],
6003 [0.36345, 0.73366, 0.66287],
6004 [0.36562, 0.73373, 0.6591],
6005 [0.36781, 0.73379, 0.65532],
6006 [0.37003, 0.73384, 0.65155],
6007 [0.37227, 0.73388, 0.64775],
6008 [0.37454, 0.73392, 0.64396],
6009 [0.37683, 0.73395, 0.64016],
6010 [0.37914, 0.73398, 0.63635],
6011 [0.38148, 0.73399, 0.63254],
6012 [0.38384, 0.734, 0.62872],
6013 [0.38622, 0.734, 0.62489],
6014 [0.38865, 0.734, 0.62106],
6015 [0.3911, 0.73398, 0.61722],
6016 [0.39357, 0.73396, 0.61337],
6017 [0.39609, 0.73392, 0.60953],
6018 [0.39863, 0.73388, 0.60567],
6019 [0.40121, 0.73383, 0.60181],
6020 [0.40382, 0.73377, 0.59795],
6021 [0.40646, 0.7337, 0.59409],
6022 [0.40914, 0.73361, 0.59021],
6023 [0.41186, 0.73352, 0.58635],
6024 [0.41461, 0.73342, 0.58247],
6025 [0.41741, 0.7333, 0.5786],
6026 [0.42024, 0.73318, 0.57472],
6027 [0.4231, 0.73304, 0.57084],
6028 [0.42602, 0.73289, 0.56698],
6029 [0.42898, 0.73273, 0.5631],
6030 [0.43199, 0.73255, 0.55923],
6031 [0.43504, 0.73236, 0.55536],
6032 [0.43813, 0.73216, 0.5515],
6033 [0.44125, 0.73194, 0.54764],
6034 [0.44444, 0.73171, 0.54379],
6035 [0.44765, 0.73146, 0.53995],
6036 [0.45093, 0.73119, 0.53612],
6037 [0.45426, 0.73092, 0.53231],
6038 [0.45762, 0.73062, 0.5285],
6039 [0.46104, 0.73032, 0.52471],
6040 [0.46451, 0.72999, 0.52094],
6041 [0.468, 0.72965, 0.51719],
6042 [0.47157, 0.72928, 0.51346],
6043 [0.47518, 0.7289, 0.50975],
6044 [0.47882, 0.7285, 0.50606],
6045 [0.48251, 0.72809, 0.50241],
6046 [0.48625, 0.72766, 0.49879],
6047 [0.49004, 0.7272, 0.4952],
6048 [0.49386, 0.72673, 0.49165],
6049 [0.49773, 0.72625, 0.48813],
6050 [0.50164, 0.72574, 0.48464],
6051 [0.50557, 0.72521, 0.48121],
6052 [0.50955, 0.72466, 0.47782],
6053 [0.51357, 0.72409, 0.47449],
6054 [0.51761, 0.72351, 0.4712],
6055 [0.52167, 0.7229, 0.46795],
6056 [0.52578, 0.72228, 0.46477],
6057 [0.5299, 0.72164, 0.46164],
6058 [0.53404, 0.72098, 0.45857],
6059 [0.53822, 0.7203, 0.45556],
6060 [0.5424, 0.71961, 0.45262],
6061 [0.5466, 0.7189, 0.44973],
6062 [0.55081, 0.71817, 0.4469],
6063 [0.55503, 0.71743, 0.44415],
6064 [0.55926, 0.71667, 0.44145],
6065 [0.5635, 0.71589, 0.43882],
6066 [0.56773, 0.71509, 0.43627],
6067 [0.57197, 0.71428, 0.43376],
6068 [0.57622, 0.71346, 0.43134],
6069 [0.58045, 0.71262, 0.42898],
6070 [0.58468, 0.71178, 0.42669],
6071 [0.5889, 0.71092, 0.42445],
6072 [0.59311, 0.71004, 0.42224],
6073 [0.5973, 0.70917, 0.42009],
6074 [0.60146, 0.70828, 0.41796],
6075 [0.60561, 0.70738, 0.41587],
6076 [0.60975, 0.70647, 0.41382],
6077 [0.61386, 0.70556, 0.4118],
6078 [0.61796, 0.70463, 0.40983],
6079 [0.62204, 0.7037, 0.40789],
6080 [0.62612, 0.70276, 0.406],
6081 [0.63017, 0.70181, 0.40413],
6082 [0.63421, 0.70085, 0.4023],
6083 [0.63822, 0.69988, 0.40055],
6084 [0.64223, 0.69891, 0.3988],
6085 [0.64621, 0.69792, 0.39711],
6086 [0.65019, 0.69693, 0.39547],
6087 [0.65415, 0.69593, 0.39385],
6088 [0.65809, 0.69492, 0.39229],
6089 [0.66202, 0.6939, 0.39078],
6090 [0.66593, 0.69288, 0.3893],
6091 [0.66983, 0.69184, 0.38787],
6092 [0.67371, 0.69079, 0.38648],
6093 [0.67758, 0.68974, 0.38515],
6094 [0.68143, 0.68868, 0.38386],
6095 [0.68527, 0.6876, 0.38261],
6096 [0.6891, 0.68652, 0.38142],
6097 [0.69291, 0.68544, 0.38026],
6098 [0.6967, 0.68433, 0.37915],
6099 [0.70047, 0.68324, 0.37809],
6100 [0.70424, 0.68212, 0.37708],
6101 [0.70798, 0.681, 0.37611],
6102 [0.71172, 0.67987, 0.37518],
6103 [0.71544, 0.67874, 0.37432],
6104 [0.71914, 0.6776, 0.37349],
6105 [0.72282, 0.67644, 0.37271],
6106 [0.7265, 0.67528, 0.37197],
6107 [0.73016, 0.67411, 0.37128],
6108 [0.7338, 0.67294, 0.37065],
6109 [0.73742, 0.67175, 0.37006],
6110 [0.74103, 0.67057, 0.36951],
6111 [0.74462, 0.66937, 0.36902],
6112 [0.74821, 0.66816, 0.36856],
6113 [0.75177, 0.66694, 0.36815],
6114 [0.75531, 0.66573, 0.36778],
6115 [0.75884, 0.6645, 0.36746],
6116 [0.76236, 0.66327, 0.36719],
6117 [0.76586, 0.66203, 0.36696],
6118 [0.76934, 0.66077, 0.36678],
6119 [0.77281, 0.65952, 0.36664],
6120 [0.77626, 0.65826, 0.36654],
6121 [0.7797, 0.65699, 0.36649],
6122 [0.78312, 0.65572, 0.36647],
6123 [0.78653, 0.65443, 0.3665],
6124 [0.78991, 0.65314, 0.36657],
6125 [0.79329, 0.65185, 0.36668],
6126 [0.79664, 0.65055, 0.36682],
6127 [0.79999, 0.64925, 0.36701],
6128 [0.80331, 0.64792, 0.36723],
6129 [0.80662, 0.64661, 0.3675],
6130 [0.80991, 0.64528, 0.36781],
6131 [0.81318, 0.64395, 0.36816],
6132 [0.81645, 0.64261, 0.36854],
6133 [0.81969, 0.64126, 0.36896],
6134 [0.82293, 0.63992, 0.36941],
6135 [0.82614, 0.63856, 0.36989],
6136 [0.82935, 0.6372, 0.37041],
6137 [0.83253, 0.63583, 0.37097],
6138 [0.8357, 0.63446, 0.37156],
6139 [0.83885, 0.63308, 0.37219],
6140 [0.84199, 0.63169, 0.37285],
6141 [0.84511, 0.6303, 0.37355],
6142 [0.84822, 0.6289, 0.37427],
6143 [0.85131, 0.6275, 0.37502],
6144 [0.85439, 0.62609, 0.3758],
6145 [0.85745, 0.62468, 0.37663],
6146 [0.86051, 0.62326, 0.37746],
6147 [0.86354, 0.62183, 0.37833],
6148 [0.86656, 0.62041, 0.37923],
6149 [0.86956, 0.61897, 0.38016],
6150 [0.87256, 0.61752, 0.38112],
6151 [0.87554, 0.61607, 0.38209],
6152 [0.8785, 0.61462, 0.38312],
6153 [0.88145, 0.61316, 0.38414],
6154 [0.88438, 0.6117, 0.3852],
6155 [0.8873, 0.61023, 0.38628],
6156 [0.89021, 0.60876, 0.3874],
6157 [0.8931, 0.60728, 0.38854],
6158 [0.89598, 0.60578, 0.38969],
6159 [0.89885, 0.60429, 0.39088],
6160 [0.9017, 0.60279, 0.39208],
6161 [0.90454, 0.60128, 0.3933],
6162 [0.90737, 0.59978, 0.39455],
6163 [0.91018, 0.59826, 0.39583],
6164 [0.91298, 0.59674, 0.3971],
6165 [0.91577, 0.59521, 0.39842],
6166 [0.91854, 0.59368, 0.39974],
6167 [0.92131, 0.59215, 0.40111],
6168 [0.92406, 0.59059, 0.40246],
6169 [0.92679, 0.58904, 0.40386],
6170 [0.92952, 0.58748, 0.40527],
6171 [0.93223, 0.58593, 0.40669],
6172 [0.93493, 0.58436, 0.40813],
6173 [0.93763, 0.58278, 0.4096],
6174 [0.9403, 0.5812, 0.41108],
6175 [0.94297, 0.57962, 0.41258],
6176 [0.94562, 0.57802, 0.41408],
6177 [0.94826, 0.57644, 0.41561],
6178 [0.95089, 0.57482, 0.41716],
6179 [0.95351, 0.57322, 0.41871],
6180 [0.95612, 0.57159, 0.42029],
6181 [0.95872, 0.56997, 0.42188],
6182 [0.9613, 0.56834, 0.42348],
6183 [0.96388, 0.56671, 0.42511],
6184 [0.96644, 0.56505, 0.42674],
6185 ]
6186 b_isoluminant_cgo_70_c39 = bokeh_palette('isoluminant_cgo_70_c39',isoluminant_cgo_70_c39)
6187 m_isoluminant_cgo_70_c39 = mpl_cm('isoluminant_cgo_70_c39',isoluminant_cgo_70_c39)
6188 m_isoluminant_cgo_70_c39_r = mpl_cm('isoluminant_cgo_70_c39_r',list(reversed(isoluminant_cgo_70_c39)))
6189
6190
6191
6192
6193 isoluminant_cgo_80_c38 = [\
6194 [0.43773, 0.82141, 1],
6195 [0.438, 0.82178, 1],
6196 [0.43825, 0.82216, 1],
6197 [0.43853, 0.82252, 1],
6198 [0.4388, 0.82289, 1],
6199 [0.43909, 0.82325, 0.99787],
6200 [0.43939, 0.82362, 0.99477],
6201 [0.43969, 0.82398, 0.99168],
6202 [0.44, 0.82433, 0.98857],
6203 [0.44031, 0.82469, 0.98546],
6204 [0.44063, 0.82504, 0.98235],
6205 [0.44095, 0.8254, 0.97923],
6206 [0.44129, 0.82575, 0.97611],
6207 [0.44163, 0.82609, 0.97299],
6208 [0.44199, 0.82644, 0.96986],
6209 [0.44234, 0.82678, 0.96673],
6210 [0.4427, 0.82712, 0.96359],
6211 [0.44307, 0.82746, 0.96045],
6212 [0.44345, 0.82779, 0.95731],
6213 [0.44384, 0.82812, 0.95416],
6214 [0.44424, 0.82845, 0.95101],
6215 [0.44464, 0.82878, 0.94785],
6216 [0.44505, 0.82911, 0.94469],
6217 [0.44546, 0.82943, 0.94152],
6218 [0.44589, 0.82975, 0.93835],
6219 [0.44634, 0.83007, 0.93517],
6220 [0.44679, 0.83038, 0.93199],
6221 [0.44725, 0.83069, 0.9288],
6222 [0.4477, 0.831, 0.92562],
6223 [0.4482, 0.83131, 0.92243],
6224 [0.44869, 0.83161, 0.91922],
6225 [0.44919, 0.83191, 0.91602],
6226 [0.4497, 0.83221, 0.91281],
6227 [0.45022, 0.8325, 0.9096],
6228 [0.45076, 0.83279, 0.90638],
6229 [0.4513, 0.83308, 0.90316],
6230 [0.45186, 0.83337, 0.89993],
6231 [0.45244, 0.83365, 0.8967],
6232 [0.45301, 0.83394, 0.89345],
6233 [0.4536, 0.83421, 0.89021],
6234 [0.45421, 0.83448, 0.88696],
6235 [0.45483, 0.83475, 0.8837],
6236 [0.45546, 0.83502, 0.88044],
6237 [0.45611, 0.83528, 0.87717],
6238 [0.45676, 0.83555, 0.8739],
6239 [0.45744, 0.8358, 0.87062],
6240 [0.45813, 0.83606, 0.86733],
6241 [0.45884, 0.83631, 0.86405],
6242 [0.45956, 0.83656, 0.86075],
6243 [0.46029, 0.8368, 0.85744],
6244 [0.46104, 0.83704, 0.85414],
6245 [0.46181, 0.83728, 0.85082],
6246 [0.46259, 0.83751, 0.8475],
6247 [0.46339, 0.83774, 0.84417],
6248 [0.46422, 0.83796, 0.84084],
6249 [0.46505, 0.83818, 0.8375],
6250 [0.46591, 0.8384, 0.83416],
6251 [0.46679, 0.83861, 0.8308],
6252 [0.46767, 0.83882, 0.82744],
6253 [0.46859, 0.83903, 0.82407],
6254 [0.46953, 0.83923, 0.8207],
6255 [0.47047, 0.83943, 0.81732],
6256 [0.47145, 0.83962, 0.81393],
6257 [0.47244, 0.83981, 0.81053],
6258 [0.47345, 0.83999, 0.80714],
6259 [0.47449, 0.84017, 0.80373],
6260 [0.47556, 0.84034, 0.80031],
6261 [0.47664, 0.84051, 0.79688],
6262 [0.47774, 0.84067, 0.79346],
6263 [0.47888, 0.84083, 0.79002],
6264 [0.48003, 0.84098, 0.78658],
6265 [0.48121, 0.84113, 0.78312],
6266 [0.48242, 0.84127, 0.77966],
6267 [0.48365, 0.8414, 0.77619],
6268 [0.48491, 0.84153, 0.77272],
6269 [0.4862, 0.84166, 0.76924],
6270 [0.48753, 0.84178, 0.76575],
6271 [0.48887, 0.84189, 0.76225],
6272 [0.49025, 0.842, 0.75875],
6273 [0.49167, 0.8421, 0.75524],
6274 [0.49309, 0.84219, 0.75172],
6275 [0.49457, 0.84228, 0.74819],
6276 [0.49605, 0.84236, 0.74465],
6277 [0.4976, 0.84243, 0.74111],
6278 [0.49917, 0.84249, 0.73756],
6279 [0.50078, 0.84255, 0.73401],
6280 [0.50242, 0.8426, 0.73045],
6281 [0.5041, 0.84264, 0.72687],
6282 [0.5058, 0.84267, 0.7233],
6283 [0.50756, 0.8427, 0.71972],
6284 [0.50935, 0.84271, 0.71613],
6285 [0.51117, 0.84272, 0.71253],
6286 [0.51304, 0.84272, 0.70893],
6287 [0.51496, 0.84271, 0.70532],
6288 [0.51691, 0.84269, 0.70171],
6289 [0.51891, 0.84266, 0.69809],
6290 [0.52094, 0.84262, 0.69447],
6291 [0.52303, 0.84257, 0.69084],
6292 [0.52516, 0.84251, 0.68722],
6293 [0.52734, 0.84243, 0.68359],
6294 [0.52957, 0.84235, 0.67995],
6295 [0.53184, 0.84226, 0.67632],
6296 [0.53416, 0.84215, 0.67268],
6297 [0.53654, 0.84203, 0.66904],
6298 [0.53896, 0.84189, 0.66541],
6299 [0.54142, 0.84175, 0.66178],
6300 [0.54396, 0.84159, 0.65814],
6301 [0.54654, 0.84142, 0.65451],
6302 [0.54917, 0.84123, 0.65088],
6303 [0.55185, 0.84103, 0.64727],
6304 [0.55458, 0.84082, 0.64365],
6305 [0.55737, 0.84059, 0.64005],
6306 [0.56021, 0.84035, 0.63646],
6307 [0.56311, 0.84009, 0.63287],
6308 [0.56606, 0.83981, 0.6293],
6309 [0.56906, 0.83952, 0.62575],
6310 [0.57213, 0.8392, 0.6222],
6311 [0.57524, 0.83888, 0.61869],
6312 [0.5784, 0.83854, 0.61518],
6313 [0.58162, 0.83818, 0.61171],
6314 [0.5849, 0.8378, 0.60826],
6315 [0.58821, 0.83741, 0.60483],
6316 [0.59159, 0.837, 0.60142],
6317 [0.595, 0.83656, 0.59805],
6318 [0.59846, 0.83612, 0.59472],
6319 [0.60197, 0.83565, 0.59142],
6320 [0.60552, 0.83517, 0.58814],
6321 [0.60913, 0.83467, 0.58492],
6322 [0.61275, 0.83415, 0.58173],
6323 [0.61642, 0.83362, 0.57858],
6324 [0.62014, 0.83306, 0.57549],
6325 [0.62388, 0.83249, 0.57243],
6326 [0.62765, 0.83191, 0.56942],
6327 [0.63145, 0.8313, 0.56646],
6328 [0.63527, 0.83068, 0.56356],
6329 [0.63912, 0.83004, 0.56069],
6330 [0.64299, 0.82939, 0.55789],
6331 [0.64689, 0.82872, 0.55514],
6332 [0.6508, 0.82803, 0.55245],
6333 [0.65472, 0.82733, 0.5498],
6334 [0.65865, 0.82662, 0.54721],
6335 [0.66261, 0.82589, 0.54468],
6336 [0.66656, 0.82515, 0.54221],
6337 [0.67053, 0.82439, 0.53979],
6338 [0.6745, 0.82363, 0.53744],
6339 [0.67847, 0.82285, 0.53513],
6340 [0.68244, 0.82206, 0.53288],
6341 [0.68642, 0.82125, 0.53068],
6342 [0.69038, 0.82043, 0.52855],
6343 [0.69435, 0.8196, 0.52647],
6344 [0.6983, 0.81877, 0.5244],
6345 [0.70224, 0.81793, 0.52237],
6346 [0.70617, 0.81709, 0.52036],
6347 [0.71008, 0.81624, 0.51839],
6348 [0.71397, 0.81537, 0.51642],
6349 [0.71785, 0.81451, 0.51449],
6350 [0.72171, 0.81363, 0.51258],
6351 [0.72557, 0.81275, 0.5107],
6352 [0.7294, 0.81187, 0.50885],
6353 [0.73323, 0.81098, 0.50702],
6354 [0.73704, 0.81008, 0.50522],
6355 [0.74083, 0.80918, 0.50344],
6356 [0.74462, 0.80826, 0.50171],
6357 [0.7484, 0.80735, 0.49999],
6358 [0.75216, 0.80642, 0.49833],
6359 [0.75591, 0.80548, 0.49666],
6360 [0.75965, 0.80455, 0.49505],
6361 [0.76337, 0.8036, 0.49346],
6362 [0.76709, 0.80265, 0.49191],
6363 [0.7708, 0.80169, 0.49039],
6364 [0.77448, 0.80072, 0.4889],
6365 [0.77817, 0.79975, 0.48745],
6366 [0.78184, 0.79876, 0.48602],
6367 [0.7855, 0.79777, 0.48463],
6368 [0.78915, 0.79678, 0.48328],
6369 [0.79278, 0.79578, 0.48198],
6370 [0.7964, 0.79477, 0.4807],
6371 [0.80002, 0.79376, 0.47946],
6372 [0.80362, 0.79273, 0.47826],
6373 [0.80722, 0.7917, 0.47709],
6374 [0.8108, 0.79066, 0.47597],
6375 [0.81437, 0.78962, 0.47489],
6376 [0.81792, 0.78857, 0.47383],
6377 [0.82147, 0.78751, 0.47283],
6378 [0.82501, 0.78645, 0.47187],
6379 [0.82853, 0.78538, 0.47094],
6380 [0.83205, 0.7843, 0.47006],
6381 [0.83555, 0.78321, 0.46922],
6382 [0.83903, 0.78212, 0.46841],
6383 [0.84251, 0.78102, 0.46765],
6384 [0.84597, 0.77992, 0.46694],
6385 [0.84943, 0.77881, 0.46626],
6386 [0.85287, 0.77769, 0.46563],
6387 [0.85629, 0.77657, 0.46504],
6388 [0.85971, 0.77544, 0.46451],
6389 [0.86311, 0.7743, 0.46401],
6390 [0.86649, 0.77316, 0.46354],
6391 [0.86986, 0.77201, 0.46313],
6392 [0.87323, 0.77086, 0.46276],
6393 [0.87657, 0.7697, 0.46244],
6394 [0.87991, 0.76853, 0.46216],
6395 [0.88323, 0.76736, 0.46193],
6396 [0.88653, 0.76619, 0.46174],
6397 [0.88982, 0.76501, 0.46159],
6398 [0.89309, 0.76382, 0.46149],
6399 [0.89636, 0.76263, 0.46143],
6400 [0.8996, 0.76143, 0.46142],
6401 [0.90283, 0.76023, 0.46145],
6402 [0.90605, 0.75903, 0.46152],
6403 [0.90924, 0.75782, 0.46164],
6404 [0.91242, 0.7566, 0.4618],
6405 [0.91559, 0.75539, 0.462],
6406 [0.91874, 0.75416, 0.46225],
6407 [0.92188, 0.75293, 0.46253],
6408 [0.92499, 0.75171, 0.46286],
6409 [0.92809, 0.75047, 0.46324],
6410 [0.93118, 0.74922, 0.46366],
6411 [0.93424, 0.74799, 0.46413],
6412 [0.9373, 0.74674, 0.46462],
6413 [0.94033, 0.74549, 0.46515],
6414 [0.94335, 0.74424, 0.46573],
6415 [0.94635, 0.74299, 0.46635],
6416 [0.94933, 0.74172, 0.46702],
6417 [0.95229, 0.74046, 0.46771],
6418 [0.95524, 0.7392, 0.46844],
6419 [0.95817, 0.73792, 0.46923],
6420 [0.96108, 0.73666, 0.47004],
6421 [0.96398, 0.73539, 0.47088],
6422 [0.96685, 0.73411, 0.47177],
6423 [0.96971, 0.73284, 0.47268],
6424 [0.97256, 0.73155, 0.47363],
6425 [0.97537, 0.73027, 0.47464],
6426 [0.97818, 0.72899, 0.47566],
6427 [0.98097, 0.7277, 0.47671],
6428 [0.98374, 0.72642, 0.47781],
6429 [0.98649, 0.72513, 0.47893],
6430 [0.98923, 0.72383, 0.4801],
6431 [0.99194, 0.72254, 0.48128],
6432 [0.99464, 0.72125, 0.4825],
6433 [0.99732, 0.71995, 0.48375],
6434 [0.99999, 0.71865, 0.48503],
6435 [1, 0.71736, 0.48634],
6436 [1, 0.71606, 0.48769],
6437 [1, 0.71476, 0.48905],
6438 [1, 0.71346, 0.49046],
6439 [1, 0.71215, 0.49188],
6440 [1, 0.71085, 0.49332],
6441 [1, 0.70955, 0.49481],
6442 [1, 0.70824, 0.4963],
6443 [1, 0.70694, 0.49785],
6444 [1, 0.70563, 0.49939],
6445 [1, 0.70432, 0.50098],
6446 [1, 0.70301, 0.50257],
6447 [1, 0.70169, 0.50421],
6448 [1, 0.70039, 0.50584],
6449 [1, 0.69907, 0.50753],
6450 ]
6451 b_isoluminant_cgo_80_c38 = bokeh_palette('isoluminant_cgo_80_c38',isoluminant_cgo_80_c38)
6452 m_isoluminant_cgo_80_c38 = mpl_cm('isoluminant_cgo_80_c38',isoluminant_cgo_80_c38)
6453 m_isoluminant_cgo_80_c38_r = mpl_cm('isoluminant_cgo_80_c38_r',list(reversed(isoluminant_cgo_80_c38)))
6454 isolum = b_isoluminant_cgo_80_c38
6455 m_isolum = m_isoluminant_cgo_80_c38
6456 m_isolum_r = m_isoluminant_cgo_80_c38_r
6457 palette['isolum'] = b_isoluminant_cgo_80_c38
6458 cm['isolum'] = m_isoluminant_cgo_80_c38
6459 cm['isolum_r'] = m_isoluminant_cgo_80_c38_r
6460 register_cmap('cet_isolum',m_isoluminant_cgo_80_c38)
6461 register_cmap('cet_isolum_r',m_isoluminant_cgo_80_c38_r)
6462
6463
6464
6465
6466 isoluminant_cm_70_c39 = [\
6467 [0.078311, 0.7275, 0.90055],
6468 [0.096546, 0.72692, 0.9011],
6469 [0.11226, 0.72635, 0.90165],
6470 [0.12614, 0.72577, 0.9022],
6471 [0.13869, 0.72519, 0.90275],
6472 [0.15028, 0.72461, 0.90329],
6473 [0.16105, 0.72402, 0.90382],
6474 [0.17113, 0.72343, 0.90436],
6475 [0.18067, 0.72284, 0.90489],
6476 [0.18976, 0.72225, 0.90541],
6477 [0.19841, 0.72165, 0.90593],
6478 [0.20674, 0.72106, 0.90644],
6479 [0.2147, 0.72046, 0.90695],
6480 [0.2224, 0.71986, 0.90745],
6481 [0.22982, 0.71926, 0.90795],
6482 [0.23706, 0.71865, 0.90845],
6483 [0.24402, 0.71804, 0.90894],
6484 [0.25084, 0.71744, 0.90942],
6485 [0.25746, 0.71682, 0.9099],
6486 [0.26394, 0.71621, 0.91038],
6487 [0.27024, 0.71559, 0.91085],
6488 [0.27641, 0.71496, 0.91131],
6489 [0.28246, 0.71434, 0.91177],
6490 [0.28836, 0.71372, 0.91222],
6491 [0.29415, 0.71309, 0.91267],
6492 [0.29986, 0.71246, 0.91312],
6493 [0.30546, 0.71183, 0.91356],
6494 [0.31096, 0.71119, 0.91399],
6495 [0.31637, 0.71055, 0.91441],
6496 [0.32169, 0.70991, 0.91483],
6497 [0.32693, 0.70927, 0.91524],
6498 [0.33212, 0.70863, 0.91565],
6499 [0.33721, 0.70797, 0.91605],
6500 [0.34224, 0.70732, 0.91645],
6501 [0.34721, 0.70668, 0.91684],
6502 [0.3521, 0.70602, 0.91723],
6503 [0.35696, 0.70536, 0.91761],
6504 [0.36174, 0.70469, 0.91797],
6505 [0.36648, 0.70403, 0.91834],
6506 [0.37114, 0.70336, 0.91869],
6507 [0.37578, 0.70269, 0.91904],
6508 [0.38037, 0.70202, 0.91938],
6509 [0.3849, 0.70134, 0.91972],
6510 [0.3894, 0.70067, 0.92005],
6511 [0.39385, 0.69998, 0.92037],
6512 [0.39827, 0.6993, 0.92068],
6513 [0.40264, 0.69861, 0.92099],
6514 [0.40698, 0.69792, 0.92129],
6515 [0.41129, 0.69723, 0.92158],
6516 [0.41555, 0.69654, 0.92187],
6517 [0.41979, 0.69584, 0.92214],
6518 [0.42399, 0.69514, 0.92241],
6519 [0.42817, 0.69443, 0.92267],
6520 [0.43232, 0.69372, 0.92292],
6521 [0.43643, 0.69302, 0.92316],
6522 [0.44051, 0.69231, 0.92339],
6523 [0.44458, 0.69158, 0.92362],
6524 [0.44861, 0.69086, 0.92383],
6525 [0.45263, 0.69014, 0.92403],
6526 [0.4566, 0.68942, 0.92423],
6527 [0.46056, 0.68869, 0.92441],
6528 [0.46452, 0.68796, 0.92459],
6529 [0.46843, 0.68722, 0.92475],
6530 [0.47233, 0.68648, 0.92491],
6531 [0.47621, 0.68574, 0.92505],
6532 [0.48007, 0.685, 0.92519],
6533 [0.4839, 0.68424, 0.92531],
6534 [0.48774, 0.6835, 0.92543],
6535 [0.49155, 0.68274, 0.92553],
6536 [0.49532, 0.68198, 0.92562],
6537 [0.49909, 0.68122, 0.9257],
6538 [0.50285, 0.68045, 0.92576],
6539 [0.50659, 0.67969, 0.92582],
6540 [0.51032, 0.67892, 0.92586],
6541 [0.51404, 0.67815, 0.92589],
6542 [0.51773, 0.67737, 0.9259],
6543 [0.52141, 0.67659, 0.92591],
6544 [0.52509, 0.6758, 0.92589],
6545 [0.52875, 0.67501, 0.92587],
6546 [0.5324, 0.67422, 0.92583],
6547 [0.53603, 0.67343, 0.92578],
6548 [0.53965, 0.67264, 0.92571],
6549 [0.54327, 0.67183, 0.92562],
6550 [0.54687, 0.67103, 0.92552],
6551 [0.55046, 0.67022, 0.92541],
6552 [0.55405, 0.66941, 0.92527],
6553 [0.55762, 0.66859, 0.92513],
6554 [0.56118, 0.66778, 0.92496],
6555 [0.56474, 0.66695, 0.92478],
6556 [0.56828, 0.66613, 0.92458],
6557 [0.57183, 0.6653, 0.92436],
6558 [0.57536, 0.66447, 0.92412],
6559 [0.57888, 0.66364, 0.92387],
6560 [0.58239, 0.6628, 0.92359],
6561 [0.58591, 0.66196, 0.92329],
6562 [0.5894, 0.66111, 0.92298],
6563 [0.5929, 0.66026, 0.92264],
6564 [0.59638, 0.65941, 0.92228],
6565 [0.59986, 0.65856, 0.92189],
6566 [0.60333, 0.65771, 0.92149],
6567 [0.6068, 0.65685, 0.92106],
6568 [0.61025, 0.65599, 0.9206],
6569 [0.6137, 0.65512, 0.92013],
6570 [0.61716, 0.65425, 0.91962],
6571 [0.6206, 0.65338, 0.91909],
6572 [0.62403, 0.65251, 0.91854],
6573 [0.62745, 0.65164, 0.91796],
6574 [0.63088, 0.65076, 0.91735],
6575 [0.63429, 0.64989, 0.91671],
6576 [0.63769, 0.64901, 0.91604],
6577 [0.64108, 0.64812, 0.91534],
6578 [0.64447, 0.64724, 0.91461],
6579 [0.64785, 0.64636, 0.91385],
6580 [0.65123, 0.64547, 0.91306],
6581 [0.65459, 0.64458, 0.91223],
6582 [0.65795, 0.6437, 0.91137],
6583 [0.66129, 0.64282, 0.91048],
6584 [0.66462, 0.64193, 0.90955],
6585 [0.66796, 0.64104, 0.90858],
6586 [0.67126, 0.64017, 0.90758],
6587 [0.67456, 0.63928, 0.90654],
6588 [0.67785, 0.6384, 0.90546],
6589 [0.68111, 0.63753, 0.90434],
6590 [0.68437, 0.63666, 0.90319],
6591 [0.68761, 0.63578, 0.90199],
6592 [0.69083, 0.63491, 0.90077],
6593 [0.69404, 0.63405, 0.89953],
6594 [0.69723, 0.63317, 0.89826],
6595 [0.7004, 0.63231, 0.89698],
6596 [0.70355, 0.63144, 0.89567],
6597 [0.70668, 0.63058, 0.89435],
6598 [0.70979, 0.62971, 0.89301],
6599 [0.71288, 0.62885, 0.89165],
6600 [0.71597, 0.62799, 0.89028],
6601 [0.71902, 0.62713, 0.88889],
6602 [0.72206, 0.62627, 0.88748],
6603 [0.72509, 0.62541, 0.88607],
6604 [0.72809, 0.62455, 0.88463],
6605 [0.73108, 0.6237, 0.88318],
6606 [0.73405, 0.62284, 0.88173],
6607 [0.737, 0.62198, 0.88025],
6608 [0.73994, 0.62113, 0.87877],
6609 [0.74285, 0.62028, 0.87728],
6610 [0.74575, 0.61942, 0.87577],
6611 [0.74863, 0.61857, 0.87426],
6612 [0.7515, 0.61771, 0.87273],
6613 [0.75435, 0.61686, 0.8712],
6614 [0.75718, 0.61601, 0.86965],
6615 [0.75999, 0.61515, 0.8681],
6616 [0.76279, 0.6143, 0.86653],
6617 [0.76558, 0.61345, 0.86496],
6618 [0.76834, 0.6126, 0.86339],
6619 [0.7711, 0.61175, 0.8618],
6620 [0.77383, 0.6109, 0.8602],
6621 [0.77656, 0.61005, 0.8586],
6622 [0.77926, 0.6092, 0.85699],
6623 [0.78195, 0.60835, 0.85538],
6624 [0.78463, 0.6075, 0.85375],
6625 [0.78729, 0.60665, 0.85212],
6626 [0.78993, 0.60579, 0.85048],
6627 [0.79257, 0.60495, 0.84884],
6628 [0.79518, 0.6041, 0.84719],
6629 [0.79779, 0.60325, 0.84554],
6630 [0.80038, 0.6024, 0.84387],
6631 [0.80295, 0.60155, 0.84221],
6632 [0.80551, 0.6007, 0.84054],
6633 [0.80806, 0.59985, 0.83886],
6634 [0.8106, 0.599, 0.83718],
6635 [0.81312, 0.59814, 0.83549],
6636 [0.81563, 0.5973, 0.83381],
6637 [0.81812, 0.59644, 0.83211],
6638 [0.82061, 0.59559, 0.83041],
6639 [0.82308, 0.59474, 0.8287],
6640 [0.82554, 0.59389, 0.82699],
6641 [0.82798, 0.59304, 0.82528],
6642 [0.83042, 0.59219, 0.82356],
6643 [0.83284, 0.59133, 0.82184],
6644 [0.83525, 0.59047, 0.82011],
6645 [0.83765, 0.58962, 0.81838],
6646 [0.84003, 0.58876, 0.81665],
6647 [0.84241, 0.58791, 0.81491],
6648 [0.84477, 0.58705, 0.81317],
6649 [0.84712, 0.5862, 0.81143],
6650 [0.84946, 0.58535, 0.80968],
6651 [0.85179, 0.58449, 0.80793],
6652 [0.8541, 0.58363, 0.80617],
6653 [0.85641, 0.58277, 0.80442],
6654 [0.85871, 0.58191, 0.80265],
6655 [0.86099, 0.58105, 0.80089],
6656 [0.86327, 0.5802, 0.79913],
6657 [0.86553, 0.57934, 0.79735],
6658 [0.86779, 0.57847, 0.79558],
6659 [0.87002, 0.57761, 0.79381],
6660 [0.87226, 0.57675, 0.79203],
6661 [0.87448, 0.57589, 0.79025],
6662 [0.87669, 0.57502, 0.78847],
6663 [0.8789, 0.57415, 0.78668],
6664 [0.88109, 0.57329, 0.78489],
6665 [0.88328, 0.57243, 0.7831],
6666 [0.88545, 0.57155, 0.78131],
6667 [0.88761, 0.57068, 0.77951],
6668 [0.88977, 0.56981, 0.77772],
6669 [0.89192, 0.56895, 0.77591],
6670 [0.89405, 0.56808, 0.77411],
6671 [0.89618, 0.56721, 0.77231],
6672 [0.8983, 0.56634, 0.7705],
6673 [0.90041, 0.56546, 0.76869],
6674 [0.90251, 0.56459, 0.76688],
6675 [0.9046, 0.56372, 0.76507],
6676 [0.90668, 0.56284, 0.76325],
6677 [0.90876, 0.56197, 0.76143],
6678 [0.91082, 0.56108, 0.75961],
6679 [0.91288, 0.56021, 0.7578],
6680 [0.91493, 0.55932, 0.75597],
6681 [0.91697, 0.55844, 0.75415],
6682 [0.91899, 0.55756, 0.75232],
6683 [0.92102, 0.55668, 0.7505],
6684 [0.92304, 0.55579, 0.74866],
6685 [0.92504, 0.55491, 0.74683],
6686 [0.92704, 0.55402, 0.745],
6687 [0.92903, 0.55313, 0.74317],
6688 [0.93102, 0.55225, 0.74133],
6689 [0.93299, 0.55136, 0.7395],
6690 [0.93496, 0.55047, 0.73765],
6691 [0.93692, 0.54957, 0.73581],
6692 [0.93887, 0.54869, 0.73397],
6693 [0.94082, 0.54779, 0.73213],
6694 [0.94276, 0.54689, 0.73028],
6695 [0.94469, 0.546, 0.72843],
6696 [0.94661, 0.5451, 0.72659],
6697 [0.94852, 0.54419, 0.72474],
6698 [0.95043, 0.5433, 0.72288],
6699 [0.95233, 0.54239, 0.72103],
6700 [0.95423, 0.54148, 0.71918],
6701 [0.95611, 0.54058, 0.71733],
6702 [0.95799, 0.53967, 0.71548],
6703 [0.95986, 0.53878, 0.71361],
6704 [0.96173, 0.53787, 0.71176],
6705 [0.96359, 0.53696, 0.7099],
6706 [0.96544, 0.53604, 0.70804],
6707 [0.96729, 0.53513, 0.70618],
6708 [0.96912, 0.53421, 0.70431],
6709 [0.97096, 0.53329, 0.70245],
6710 [0.97278, 0.53238, 0.70058],
6711 [0.9746, 0.53146, 0.69871],
6712 [0.97641, 0.53054, 0.69685],
6713 [0.97822, 0.52962, 0.69498],
6714 [0.98002, 0.5287, 0.69311],
6715 [0.98181, 0.52777, 0.69124],
6716 [0.9836, 0.52685, 0.68937],
6717 [0.98538, 0.52592, 0.6875],
6718 [0.98716, 0.52499, 0.68563],
6719 [0.98892, 0.52406, 0.68375],
6720 [0.99069, 0.52313, 0.68187],
6721 [0.99244, 0.52218, 0.67999],
6722 [0.99419, 0.52125, 0.67812],
6723 ]
6724 b_isoluminant_cm_70_c39 = bokeh_palette('isoluminant_cm_70_c39',isoluminant_cm_70_c39)
6725 m_isoluminant_cm_70_c39 = mpl_cm('isoluminant_cm_70_c39',isoluminant_cm_70_c39)
6726 m_isoluminant_cm_70_c39_r = mpl_cm('isoluminant_cm_70_c39_r',list(reversed(isoluminant_cm_70_c39)))
6727
6728
6729
6730
6731 linear_bgy_10_95_c74 = [\
6732 [0, 0.047803, 0.4883],
6733 [0, 0.049756, 0.49556],
6734 [0, 0.051605, 0.50281],
6735 [0, 0.053545, 0.51004],
6736 [0, 0.055585, 0.51721],
6737 [0, 0.057566, 0.52435],
6738 [0, 0.05978, 0.53144],
6739 [0, 0.061812, 0.53849],
6740 [0, 0.064016, 0.5455],
6741 [0, 0.066232, 0.55245],
6742 [0, 0.068551, 0.55934],
6743 [0, 0.070824, 0.5662],
6744 [0, 0.073229, 0.57299],
6745 [0, 0.07557, 0.57971],
6746 [0, 0.078003, 0.58638],
6747 [0, 0.080554, 0.59299],
6748 [0, 0.083114, 0.59951],
6749 [0, 0.085697, 0.60596],
6750 [0, 0.08842, 0.61236],
6751 [0, 0.091168, 0.61866],
6752 [0, 0.093925, 0.62487],
6753 [0, 0.096707, 0.63101],
6754 [0, 0.09963, 0.63705],
6755 [0, 0.1026, 0.64298],
6756 [0, 0.10561, 0.64881],
6757 [0, 0.10866, 0.65454],
6758 [0, 0.11183, 0.66016],
6759 [0, 0.11497, 0.66567],
6760 [0, 0.11829, 0.67103],
6761 [0, 0.12156, 0.67626],
6762 [0, 0.12498, 0.68134],
6763 [0, 0.12846, 0.68629],
6764 [0, 0.13201, 0.69107],
6765 [0, 0.13559, 0.6957],
6766 [0, 0.13927, 0.70014],
6767 [0, 0.14307, 0.70439],
6768 [0, 0.1469, 0.70845],
6769 [0, 0.15085, 0.71227],
6770 [0, 0.15487, 0.71588],
6771 [0, 0.159, 0.71923],
6772 [0, 0.16323, 0.7223],
6773 [0, 0.16754, 0.7251],
6774 [0, 0.17195, 0.72757],
6775 [0, 0.17647, 0.72972],
6776 [0, 0.18113, 0.73149],
6777 [0, 0.18594, 0.73289],
6778 [0, 0.19074, 0.73398],
6779 [0, 0.19556, 0.73486],
6780 [0, 0.20033, 0.73556],
6781 [0, 0.20512, 0.73608],
6782 [0, 0.20987, 0.73643],
6783 [0, 0.21461, 0.73659],
6784 [0, 0.21934, 0.73657],
6785 [0, 0.22402, 0.73637],
6786 [0, 0.22875, 0.73599],
6787 [0, 0.2334, 0.73544],
6788 [0, 0.23809, 0.73469],
6789 [0, 0.24275, 0.73376],
6790 [0, 0.24743, 0.73266],
6791 [0, 0.25208, 0.73137],
6792 [0, 0.25673, 0.72991],
6793 [0, 0.26137, 0.72825],
6794 [0, 0.26603, 0.72642],
6795 [0, 0.27068, 0.72441],
6796 [0, 0.27531, 0.72221],
6797 [0, 0.27995, 0.71983],
6798 [0, 0.28458, 0.71727],
6799 [0, 0.28924, 0.71452],
6800 [0, 0.29387, 0.71161],
6801 [0, 0.29852, 0.70851],
6802 [0, 0.30317, 0.70521],
6803 [0, 0.30782, 0.70174],
6804 [0, 0.31248, 0.69809],
6805 [0, 0.31716, 0.69426],
6806 [0, 0.32182, 0.69025],
6807 [0, 0.32649, 0.68607],
6808 [0, 0.33116, 0.68178],
6809 [0, 0.33582, 0.67746],
6810 [0, 0.34046, 0.6731],
6811 [0, 0.34509, 0.66871],
6812 [0, 0.3497, 0.66429],
6813 [0, 0.3543, 0.65984],
6814 [0, 0.35888, 0.65536],
6815 [0, 0.36346, 0.65085],
6816 [0, 0.36803, 0.6463],
6817 [0, 0.37258, 0.64173],
6818 [0, 0.37713, 0.63713],
6819 [0, 0.38167, 0.6325],
6820 [0, 0.38618, 0.62783],
6821 [0, 0.39071, 0.62313],
6822 [0, 0.39523, 0.6184],
6823 [0, 0.39972, 0.61363],
6824 [0, 0.40423, 0.60885],
6825 [0, 0.40872, 0.60402],
6826 [0, 0.41321, 0.59915],
6827 [0, 0.41769, 0.59426],
6828 [0, 0.42215, 0.58932],
6829 [0, 0.42663, 0.58437],
6830 [0, 0.4311, 0.57937],
6831 [0, 0.43556, 0.57433],
6832 [0, 0.44001, 0.56926],
6833 [0, 0.44446, 0.56416],
6834 [0, 0.44891, 0.55902],
6835 [0, 0.45334, 0.55384],
6836 [0, 0.45778, 0.54863],
6837 [0, 0.46222, 0.54336],
6838 [0, 0.46665, 0.53802],
6839 [0, 0.47105, 0.53253],
6840 [0, 0.47545, 0.52691],
6841 [0, 0.47982, 0.52115],
6842 [0, 0.48417, 0.51525],
6843 [0, 0.48852, 0.50921],
6844 [0, 0.49284, 0.50301],
6845 [0, 0.49717, 0.49668],
6846 [0, 0.50147, 0.49022],
6847 [0, 0.50575, 0.48359],
6848 [0, 0.51003, 0.47682],
6849 [0, 0.51431, 0.4699],
6850 [0, 0.51856, 0.4628],
6851 [0.0097866, 0.52281, 0.45558],
6852 [0.023896, 0.52704, 0.44818],
6853 [0.038383, 0.53126, 0.44061],
6854 [0.051763, 0.53547, 0.43289],
6855 [0.063442, 0.53968, 0.42499],
6856 [0.073828, 0.54388, 0.41692],
6857 [0.083244, 0.54807, 0.40866],
6858 [0.092062, 0.55225, 0.40022],
6859 [0.10019, 0.55642, 0.39159],
6860 [0.10786, 0.56059, 0.38276],
6861 [0.11513, 0.56474, 0.37372],
6862 [0.12206, 0.56889, 0.36445],
6863 [0.12871, 0.57304, 0.35498],
6864 [0.13507, 0.57718, 0.34524],
6865 [0.14115, 0.58131, 0.33527],
6866 [0.14697, 0.58544, 0.32499],
6867 [0.15257, 0.58954, 0.31449],
6868 [0.15773, 0.59367, 0.30393],
6869 [0.16231, 0.59779, 0.29352],
6870 [0.16631, 0.60191, 0.28332],
6871 [0.16984, 0.60603, 0.27332],
6872 [0.17292, 0.61015, 0.26352],
6873 [0.17565, 0.61427, 0.25387],
6874 [0.17811, 0.6184, 0.24439],
6875 [0.18021, 0.62252, 0.23514],
6876 [0.18207, 0.62664, 0.22606],
6877 [0.18374, 0.63076, 0.21715],
6878 [0.18522, 0.63487, 0.2084],
6879 [0.18649, 0.63898, 0.19982],
6880 [0.18765, 0.64309, 0.19148],
6881 [0.18863, 0.6472, 0.18334],
6882 [0.18951, 0.6513, 0.1754],
6883 [0.19029, 0.65539, 0.16767],
6884 [0.19099, 0.65948, 0.16013],
6885 [0.19162, 0.66357, 0.15293],
6886 [0.19219, 0.66765, 0.14604],
6887 [0.19272, 0.67172, 0.13937],
6888 [0.1932, 0.67579, 0.13311],
6889 [0.19366, 0.67985, 0.1272],
6890 [0.1941, 0.68391, 0.1218],
6891 [0.19451, 0.68797, 0.11692],
6892 [0.1949, 0.69202, 0.11259],
6893 [0.19529, 0.69606, 0.10881],
6894 [0.19569, 0.70009, 0.10581],
6895 [0.19611, 0.70412, 0.10358],
6896 [0.19653, 0.70814, 0.10209],
6897 [0.19694, 0.71215, 0.10139],
6898 [0.19736, 0.71617, 0.10116],
6899 [0.19779, 0.72018, 0.10101],
6900 [0.19823, 0.7242, 0.10087],
6901 [0.19868, 0.72822, 0.10073],
6902 [0.19914, 0.73225, 0.1006],
6903 [0.19961, 0.73627, 0.10048],
6904 [0.20009, 0.74031, 0.10036],
6905 [0.20058, 0.74434, 0.10025],
6906 [0.20108, 0.74838, 0.10015],
6907 [0.20159, 0.75242, 0.10006],
6908 [0.20211, 0.75647, 0.099977],
6909 [0.20265, 0.76052, 0.099902],
6910 [0.2032, 0.76457, 0.099835],
6911 [0.20376, 0.76862, 0.099777],
6912 [0.20433, 0.77267, 0.099729],
6913 [0.20488, 0.77674, 0.099691],
6914 [0.20546, 0.7808, 0.099663],
6915 [0.20608, 0.78487, 0.099645],
6916 [0.20669, 0.78894, 0.099637],
6917 [0.20729, 0.79301, 0.099641],
6918 [0.20791, 0.79708, 0.099656],
6919 [0.20855, 0.80116, 0.099683],
6920 [0.2092, 0.80523, 0.09972],
6921 [0.20987, 0.80932, 0.09977],
6922 [0.21055, 0.8134, 0.099833],
6923 [0.21125, 0.81749, 0.099908],
6924 [0.21196, 0.82159, 0.099996],
6925 [0.21266, 0.82567, 0.1001],
6926 [0.2134, 0.82977, 0.10021],
6927 [0.21454, 0.83386, 0.10034],
6928 [0.21746, 0.83784, 0.10049],
6929 [0.22334, 0.84166, 0.10065],
6930 [0.23182, 0.84531, 0.10083],
6931 [0.24228, 0.84884, 0.10102],
6932 [0.25428, 0.85224, 0.10123],
6933 [0.26735, 0.85553, 0.10145],
6934 [0.28125, 0.85872, 0.10168],
6935 [0.29571, 0.86184, 0.10193],
6936 [0.31067, 0.86485, 0.10219],
6937 [0.32594, 0.86779, 0.10246],
6938 [0.34137, 0.87065, 0.10275],
6939 [0.35684, 0.87346, 0.10306],
6940 [0.3724, 0.87619, 0.10337],
6941 [0.38805, 0.87886, 0.10369],
6942 [0.40366, 0.88147, 0.10401],
6943 [0.41921, 0.88402, 0.10433],
6944 [0.43478, 0.88651, 0.10468],
6945 [0.45028, 0.88894, 0.10507],
6946 [0.4657, 0.89133, 0.10549],
6947 [0.48111, 0.89365, 0.10592],
6948 [0.49641, 0.89593, 0.10637],
6949 [0.51169, 0.89815, 0.10681],
6950 [0.52691, 0.90032, 0.10725],
6951 [0.54202, 0.90245, 0.1077],
6952 [0.55713, 0.90452, 0.10817],
6953 [0.57212, 0.90655, 0.10869],
6954 [0.5871, 0.90852, 0.10927],
6955 [0.60201, 0.91045, 0.10983],
6956 [0.61689, 0.91232, 0.11037],
6957 [0.63169, 0.91415, 0.11095],
6958 [0.64646, 0.91593, 0.11155],
6959 [0.66118, 0.91767, 0.11216],
6960 [0.67585, 0.91934, 0.11281],
6961 [0.69049, 0.92098, 0.11347],
6962 [0.70508, 0.92257, 0.11409],
6963 [0.71966, 0.92411, 0.11477],
6964 [0.73418, 0.9256, 0.11552],
6965 [0.74868, 0.92704, 0.11627],
6966 [0.76314, 0.92844, 0.11699],
6967 [0.77759, 0.92979, 0.11777],
6968 [0.79201, 0.93109, 0.11859],
6969 [0.8064, 0.93233, 0.11937],
6970 [0.82077, 0.93353, 0.12019],
6971 [0.83511, 0.93468, 0.12102],
6972 [0.84946, 0.93578, 0.12189],
6973 [0.86375, 0.93684, 0.12278],
6974 [0.87808, 0.93783, 0.1237],
6975 [0.89234, 0.93878, 0.12464],
6976 [0.90664, 0.93968, 0.12562],
6977 [0.92088, 0.94052, 0.12657],
6978 [0.93514, 0.94131, 0.12755],
6979 [0.94939, 0.94206, 0.12857],
6980 [0.9636, 0.94275, 0.12961],
6981 [0.97785, 0.94338, 0.13068],
6982 [0.99205, 0.94397, 0.13172],
6983 [1, 0.94449, 0.13281],
6984 [1, 0.94497, 0.13392],
6985 [1, 0.94539, 0.13505],
6986 [1, 0.94574, 0.13614],
6987 [1, 0.94606, 0.13735],
6988 ]
6989 b_linear_bgy_10_95_c74 = bokeh_palette('linear_bgy_10_95_c74',linear_bgy_10_95_c74)
6990 m_linear_bgy_10_95_c74 = mpl_cm('linear_bgy_10_95_c74',linear_bgy_10_95_c74)
6991 m_linear_bgy_10_95_c74_r = mpl_cm('linear_bgy_10_95_c74_r',list(reversed(linear_bgy_10_95_c74)))
6992 bgy = b_linear_bgy_10_95_c74
6993 m_bgy = m_linear_bgy_10_95_c74
6994 m_bgy_r = m_linear_bgy_10_95_c74_r
6995 palette['bgy'] = b_linear_bgy_10_95_c74
6996 cm['bgy'] = m_linear_bgy_10_95_c74
6997 cm['bgy_r'] = m_linear_bgy_10_95_c74_r
6998 register_cmap('cet_bgy',m_linear_bgy_10_95_c74)
6999 register_cmap('cet_bgy_r',m_linear_bgy_10_95_c74_r)
7000
7001
7002
7003
7004 linear_bgyw_15_100_c67 = [\
7005 [0.10477, 0.0011197, 0.51875],
7006 [0.105, 0.0031206, 0.52587],
7007 [0.10521, 0.005201, 0.53301],
7008 [0.10541, 0.0074297, 0.5401],
7009 [0.10559, 0.0097752, 0.54718],
7010 [0.10576, 0.012459, 0.55425],
7011 [0.10592, 0.015073, 0.56126],
7012 [0.10605, 0.017812, 0.56829],
7013 [0.10619, 0.020743, 0.57524],
7014 [0.10631, 0.023778, 0.5822],
7015 [0.10643, 0.027021, 0.58909],
7016 [0.10653, 0.030386, 0.59599],
7017 [0.10663, 0.033922, 0.60282],
7018 [0.10672, 0.037861, 0.60963],
7019 [0.10682, 0.041783, 0.6164],
7020 [0.10691, 0.045535, 0.62314],
7021 [0.107, 0.049457, 0.62982],
7022 [0.10709, 0.053176, 0.63647],
7023 [0.10718, 0.057025, 0.64308],
7024 [0.10728, 0.060795, 0.64963],
7025 [0.10738, 0.064591, 0.65615],
7026 [0.1075, 0.068417, 0.6626],
7027 [0.10762, 0.072133, 0.66902],
7028 [0.10776, 0.075909, 0.67536],
7029 [0.10791, 0.079695, 0.68166],
7030 [0.10808, 0.08353, 0.6879],
7031 [0.10826, 0.087375, 0.69408],
7032 [0.10848, 0.091188, 0.7002],
7033 [0.10873, 0.095035, 0.70626],
7034 [0.10901, 0.098847, 0.71224],
7035 [0.10933, 0.10273, 0.71815],
7036 [0.10965, 0.10666, 0.724],
7037 [0.11, 0.11057, 0.72975],
7038 [0.11035, 0.11443, 0.73545],
7039 [0.11077, 0.11848, 0.74103],
7040 [0.11121, 0.1224, 0.74656],
7041 [0.11171, 0.12647, 0.75198],
7042 [0.11224, 0.13056, 0.75731],
7043 [0.11282, 0.13464, 0.76255],
7044 [0.11344, 0.13874, 0.76767],
7045 [0.11404, 0.14289, 0.77271],
7046 [0.11474, 0.14709, 0.77762],
7047 [0.11555, 0.15131, 0.78241],
7048 [0.11637, 0.1556, 0.78711],
7049 [0.11721, 0.15989, 0.79164],
7050 [0.11817, 0.16429, 0.79606],
7051 [0.11913, 0.16868, 0.80035],
7052 [0.12014, 0.17313, 0.80446],
7053 [0.12122, 0.17766, 0.80845],
7054 [0.12236, 0.18216, 0.81227],
7055 [0.12358, 0.1868, 0.8159],
7056 [0.12487, 0.19146, 0.81936],
7057 [0.12621, 0.19619, 0.82267],
7058 [0.12758, 0.20095, 0.82573],
7059 [0.12902, 0.20585, 0.82858],
7060 [0.13057, 0.21075, 0.83123],
7061 [0.13209, 0.21574, 0.83365],
7062 [0.1337, 0.22083, 0.83579],
7063 [0.13536, 0.22598, 0.83764],
7064 [0.13708, 0.23121, 0.83921],
7065 [0.13882, 0.23653, 0.84047],
7066 [0.14063, 0.24194, 0.84141],
7067 [0.14244, 0.24745, 0.84198],
7068 [0.1443, 0.25307, 0.84216],
7069 [0.14616, 0.25882, 0.84191],
7070 [0.14804, 0.26468, 0.84117],
7071 [0.14995, 0.27071, 0.8399],
7072 [0.15179, 0.27687, 0.83804],
7073 [0.15363, 0.2832, 0.83552],
7074 [0.15544, 0.28972, 0.83227],
7075 [0.15711, 0.29645, 0.82819],
7076 [0.1587, 0.30339, 0.82319],
7077 [0.16004, 0.31064, 0.81705],
7078 [0.16121, 0.31816, 0.80955],
7079 [0.16198, 0.32608, 0.80043],
7080 [0.16232, 0.33446, 0.78944],
7081 [0.16261, 0.34288, 0.77734],
7082 [0.16339, 0.351, 0.7652],
7083 [0.16458, 0.35878, 0.75318],
7084 [0.16618, 0.3663, 0.7413],
7085 [0.16813, 0.37354, 0.72954],
7086 [0.17035, 0.38056, 0.71789],
7087 [0.1728, 0.38735, 0.70636],
7088 [0.17542, 0.39397, 0.69491],
7089 [0.17821, 0.40042, 0.68357],
7090 [0.18104, 0.40669, 0.67233],
7091 [0.18398, 0.41284, 0.66117],
7092 [0.18698, 0.41883, 0.65009],
7093 [0.19, 0.42472, 0.6391],
7094 [0.19303, 0.43049, 0.62818],
7095 [0.19608, 0.43615, 0.61732],
7096 [0.19905, 0.44173, 0.60653],
7097 [0.20205, 0.4472, 0.59581],
7098 [0.20503, 0.45261, 0.58515],
7099 [0.20793, 0.45792, 0.57453],
7100 [0.2108, 0.46316, 0.56398],
7101 [0.21364, 0.46835, 0.55345],
7102 [0.21643, 0.47347, 0.54299],
7103 [0.21913, 0.47854, 0.53255],
7104 [0.22179, 0.48354, 0.52214],
7105 [0.22439, 0.4885, 0.51178],
7106 [0.22697, 0.4934, 0.50144],
7107 [0.22945, 0.49828, 0.49112],
7108 [0.23194, 0.50308, 0.48079],
7109 [0.23434, 0.50787, 0.47051],
7110 [0.23669, 0.5126, 0.4602],
7111 [0.23896, 0.51731, 0.44992],
7112 [0.24122, 0.52197, 0.43962],
7113 [0.24342, 0.52661, 0.42932],
7114 [0.2456, 0.53121, 0.419],
7115 [0.24776, 0.53578, 0.40865],
7116 [0.24982, 0.54033, 0.39827],
7117 [0.2519, 0.54485, 0.38784],
7118 [0.25394, 0.54933, 0.37747],
7119 [0.25603, 0.55376, 0.36733],
7120 [0.25825, 0.55813, 0.35754],
7121 [0.26059, 0.56246, 0.34801],
7122 [0.26305, 0.56672, 0.33878],
7123 [0.26563, 0.57092, 0.32981],
7124 [0.26835, 0.57509, 0.32108],
7125 [0.27123, 0.57921, 0.31258],
7126 [0.27426, 0.58328, 0.30433],
7127 [0.27745, 0.58731, 0.29629],
7128 [0.28078, 0.5913, 0.28844],
7129 [0.28431, 0.59525, 0.28077],
7130 [0.28799, 0.59916, 0.27333],
7131 [0.29185, 0.60303, 0.26603],
7132 [0.29585, 0.60687, 0.2589],
7133 [0.30003, 0.61067, 0.25192],
7134 [0.30437, 0.61442, 0.24507],
7135 [0.3089, 0.61816, 0.23841],
7136 [0.31357, 0.62185, 0.23192],
7137 [0.3184, 0.62552, 0.22553],
7138 [0.32339, 0.62915, 0.21927],
7139 [0.32852, 0.63275, 0.21311],
7140 [0.3338, 0.63632, 0.20712],
7141 [0.33922, 0.63986, 0.20117],
7142 [0.34475, 0.64337, 0.19538],
7143 [0.35045, 0.64686, 0.1897],
7144 [0.35629, 0.6503, 0.18415],
7145 [0.36225, 0.65372, 0.17872],
7146 [0.36834, 0.65712, 0.17336],
7147 [0.37454, 0.66048, 0.1681],
7148 [0.38085, 0.66383, 0.16297],
7149 [0.38726, 0.66714, 0.15793],
7150 [0.39382, 0.67043, 0.15302],
7151 [0.40049, 0.67368, 0.14824],
7152 [0.40723, 0.67691, 0.14356],
7153 [0.41408, 0.68011, 0.13895],
7154 [0.42102, 0.68329, 0.13455],
7155 [0.42809, 0.68644, 0.13028],
7156 [0.43524, 0.68956, 0.12609],
7157 [0.44246, 0.69267, 0.12198],
7158 [0.44975, 0.69574, 0.11813],
7159 [0.45716, 0.69877, 0.1144],
7160 [0.46465, 0.70179, 0.11092],
7161 [0.4722, 0.70479, 0.10752],
7162 [0.47982, 0.70776, 0.1043],
7163 [0.48754, 0.7107, 0.1014],
7164 [0.49532, 0.71361, 0.098689],
7165 [0.50314, 0.7165, 0.096121],
7166 [0.51106, 0.71936, 0.093905],
7167 [0.51907, 0.72219, 0.091988],
7168 [0.52711, 0.72501, 0.090242],
7169 [0.53519, 0.72779, 0.08877],
7170 [0.54339, 0.73055, 0.087727],
7171 [0.55162, 0.73328, 0.086928],
7172 [0.5599, 0.73598, 0.086341],
7173 [0.56824, 0.73866, 0.086171],
7174 [0.57666, 0.74131, 0.086363],
7175 [0.58511, 0.74394, 0.086854],
7176 [0.59362, 0.74654, 0.087647],
7177 [0.60218, 0.74911, 0.088756],
7178 [0.61075, 0.75167, 0.090091],
7179 [0.6193, 0.75421, 0.091662],
7180 [0.62776, 0.75676, 0.093291],
7181 [0.63618, 0.7593, 0.095179],
7182 [0.64452, 0.76186, 0.097055],
7183 [0.65279, 0.76442, 0.0992],
7184 [0.66101, 0.76698, 0.10144],
7185 [0.66917, 0.76954, 0.10382],
7186 [0.67726, 0.77211, 0.10635],
7187 [0.68528, 0.77468, 0.10898],
7188 [0.69324, 0.77727, 0.11176],
7189 [0.70115, 0.77985, 0.1146],
7190 [0.70899, 0.78245, 0.11768],
7191 [0.71675, 0.78505, 0.12084],
7192 [0.72446, 0.78766, 0.12415],
7193 [0.73211, 0.79027, 0.12759],
7194 [0.73969, 0.7929, 0.13116],
7195 [0.74719, 0.79554, 0.13488],
7196 [0.75463, 0.79819, 0.13869],
7197 [0.762, 0.80085, 0.14265],
7198 [0.76931, 0.80352, 0.1467],
7199 [0.77655, 0.80621, 0.15091],
7200 [0.78371, 0.80891, 0.15527],
7201 [0.79078, 0.81163, 0.15974],
7202 [0.79778, 0.81436, 0.1644],
7203 [0.80471, 0.81711, 0.16917],
7204 [0.81155, 0.81987, 0.17404],
7205 [0.8183, 0.82266, 0.17908],
7206 [0.82496, 0.82547, 0.18425],
7207 [0.83154, 0.8283, 0.18958],
7208 [0.83802, 0.83116, 0.19506],
7209 [0.84439, 0.83404, 0.20068],
7210 [0.85066, 0.83694, 0.20653],
7211 [0.85681, 0.83988, 0.21248],
7212 [0.86285, 0.84285, 0.21864],
7213 [0.86877, 0.84585, 0.22495],
7214 [0.87454, 0.84889, 0.23152],
7215 [0.88018, 0.85196, 0.23823],
7216 [0.88567, 0.85508, 0.24516],
7217 [0.89101, 0.85823, 0.25235],
7218 [0.89617, 0.86144, 0.25975],
7219 [0.90116, 0.86469, 0.26737],
7220 [0.90596, 0.868, 0.27529],
7221 [0.91052, 0.87137, 0.2835],
7222 [0.91485, 0.87481, 0.29203],
7223 [0.91894, 0.87831, 0.30086],
7224 [0.92276, 0.88189, 0.31007],
7225 [0.92625, 0.88556, 0.3197],
7226 [0.92941, 0.88931, 0.32973],
7227 [0.93217, 0.89317, 0.34027],
7228 [0.93451, 0.89714, 0.3513],
7229 [0.93634, 0.90125, 0.36298],
7230 [0.93763, 0.9055, 0.37534],
7231 [0.9387, 0.90978, 0.38837],
7232 [0.93989, 0.91399, 0.40197],
7233 [0.94123, 0.91811, 0.41613],
7234 [0.94272, 0.92216, 0.43083],
7235 [0.94436, 0.92612, 0.44608],
7236 [0.94613, 0.93, 0.46186],
7237 [0.94803, 0.9338, 0.47813],
7238 [0.95005, 0.93753, 0.49497],
7239 [0.95218, 0.94117, 0.5123],
7240 [0.95441, 0.94474, 0.53014],
7241 [0.95674, 0.94822, 0.54852],
7242 [0.95915, 0.95163, 0.56741],
7243 [0.96162, 0.95496, 0.58679],
7244 [0.96415, 0.95822, 0.60671],
7245 [0.96673, 0.96139, 0.62717],
7246 [0.96934, 0.96449, 0.64813],
7247 [0.97196, 0.96752, 0.66962],
7248 [0.97459, 0.97046, 0.69168],
7249 [0.97722, 0.97333, 0.71425],
7250 [0.9798, 0.97613, 0.73736],
7251 [0.98235, 0.97885, 0.76105],
7252 [0.98483, 0.98151, 0.78529],
7253 [0.98722, 0.98408, 0.81007],
7254 [0.98952, 0.98658, 0.83544],
7255 [0.99169, 0.98901, 0.8614],
7256 [0.99371, 0.99136, 0.88792],
7257 [0.99556, 0.99365, 0.91503],
7258 [0.99723, 0.99585, 0.94278],
7259 [0.99867, 0.99799, 0.97109],
7260 [0.99986, 1, 1],
7261 ]
7262 b_linear_bgyw_15_100_c67 = bokeh_palette('linear_bgyw_15_100_c67',linear_bgyw_15_100_c67)
7263 m_linear_bgyw_15_100_c67 = mpl_cm('linear_bgyw_15_100_c67',linear_bgyw_15_100_c67)
7264 m_linear_bgyw_15_100_c67_r = mpl_cm('linear_bgyw_15_100_c67_r',list(reversed(linear_bgyw_15_100_c67)))
7265
7266
7267
7268
7269 linear_bgyw_15_100_c68 = [\
7270 [0.10261, 0, 0.52493],
7271 [0.10283, 0, 0.53197],
7272 [0.10301, 0, 0.53902],
7273 [0.10318, 0.0009426, 0.54604],
7274 [0.10333, 0.0032938, 0.55302],
7275 [0.10346, 0.0057773, 0.56],
7276 [0.10358, 0.0084209, 0.56694],
7277 [0.10367, 0.01129, 0.57386],
7278 [0.10377, 0.014338, 0.58073],
7279 [0.10383, 0.017402, 0.5876],
7280 [0.1039, 0.020685, 0.59441],
7281 [0.10395, 0.024094, 0.60121],
7282 [0.10399, 0.027709, 0.60797],
7283 [0.10402, 0.031481, 0.61469],
7284 [0.10405, 0.035677, 0.62137],
7285 [0.10407, 0.039812, 0.62802],
7286 [0.10409, 0.043972, 0.63463],
7287 [0.1041, 0.048145, 0.64118],
7288 [0.10411, 0.052249, 0.64771],
7289 [0.10412, 0.056438, 0.65417],
7290 [0.10412, 0.060474, 0.66061],
7291 [0.10414, 0.064518, 0.66698],
7292 [0.10414, 0.068586, 0.67332],
7293 [0.10416, 0.072559, 0.67957],
7294 [0.10417, 0.076535, 0.68581],
7295 [0.1042, 0.080591, 0.69196],
7296 [0.10423, 0.084636, 0.69806],
7297 [0.10427, 0.088643, 0.7041],
7298 [0.10432, 0.092635, 0.71007],
7299 [0.10438, 0.096648, 0.71599],
7300 [0.10445, 0.10074, 0.72181],
7301 [0.10454, 0.10477, 0.72759],
7302 [0.10466, 0.1089, 0.73327],
7303 [0.10478, 0.11303, 0.73891],
7304 [0.10495, 0.11711, 0.74441],
7305 [0.10512, 0.12123, 0.74987],
7306 [0.10534, 0.12546, 0.75522],
7307 [0.10558, 0.12966, 0.76048],
7308 [0.10584, 0.13388, 0.76566],
7309 [0.10615, 0.13816, 0.77071],
7310 [0.10646, 0.14242, 0.77569],
7311 [0.10681, 0.14674, 0.78053],
7312 [0.10717, 0.15111, 0.78527],
7313 [0.10755, 0.15551, 0.7899],
7314 [0.10798, 0.15993, 0.79438],
7315 [0.10845, 0.16445, 0.79875],
7316 [0.10901, 0.16898, 0.80298],
7317 [0.10961, 0.17353, 0.80705],
7318 [0.1102, 0.17818, 0.81099],
7319 [0.11082, 0.1828, 0.81477],
7320 [0.1115, 0.18758, 0.81836],
7321 [0.11222, 0.19233, 0.82179],
7322 [0.11298, 0.19716, 0.82505],
7323 [0.11375, 0.20204, 0.82808],
7324 [0.11454, 0.20704, 0.83091],
7325 [0.11544, 0.21207, 0.83352],
7326 [0.11636, 0.21715, 0.83593],
7327 [0.11726, 0.22231, 0.83805],
7328 [0.11827, 0.22758, 0.83989],
7329 [0.11923, 0.23291, 0.84144],
7330 [0.12022, 0.23833, 0.84271],
7331 [0.12122, 0.24384, 0.84364],
7332 [0.12223, 0.24946, 0.84423],
7333 [0.12325, 0.2552, 0.84442],
7334 [0.12427, 0.26103, 0.84418],
7335 [0.12527, 0.26698, 0.84347],
7336 [0.12622, 0.2731, 0.84224],
7337 [0.12705, 0.27937, 0.84043],
7338 [0.12787, 0.28578, 0.83797],
7339 [0.12853, 0.2924, 0.83479],
7340 [0.129, 0.29923, 0.8308],
7341 [0.12928, 0.30627, 0.82589],
7342 [0.12926, 0.31358, 0.81986],
7343 [0.12882, 0.3212, 0.8125],
7344 [0.12785, 0.32922, 0.80355],
7345 [0.12621, 0.33765, 0.79274],
7346 [0.1245, 0.34613, 0.78084],
7347 [0.12367, 0.35431, 0.76889],
7348 [0.12366, 0.36214, 0.75705],
7349 [0.12444, 0.36966, 0.74532],
7350 [0.12594, 0.37693, 0.7337],
7351 [0.12792, 0.38394, 0.72217],
7352 [0.13044, 0.39074, 0.71074],
7353 [0.13327, 0.39733, 0.69939],
7354 [0.13642, 0.40376, 0.68814],
7355 [0.13984, 0.41001, 0.67697],
7356 [0.14348, 0.41611, 0.66586],
7357 [0.14722, 0.42207, 0.65483],
7358 [0.15108, 0.42792, 0.64387],
7359 [0.15499, 0.43363, 0.63298],
7360 [0.15896, 0.43925, 0.62214],
7361 [0.16291, 0.44478, 0.61137],
7362 [0.16687, 0.4502, 0.60064],
7363 [0.17081, 0.45554, 0.58996],
7364 [0.17471, 0.4608, 0.57934],
7365 [0.17858, 0.46599, 0.56874],
7366 [0.18239, 0.47111, 0.55819],
7367 [0.18617, 0.47617, 0.54768],
7368 [0.18985, 0.48116, 0.53721],
7369 [0.19353, 0.4861, 0.52675],
7370 [0.19713, 0.491, 0.51631],
7371 [0.20061, 0.49582, 0.50589],
7372 [0.20411, 0.50061, 0.4955],
7373 [0.20751, 0.50535, 0.48511],
7374 [0.21087, 0.51006, 0.47474],
7375 [0.21416, 0.51473, 0.46436],
7376 [0.21738, 0.51936, 0.45396],
7377 [0.22058, 0.52395, 0.44356],
7378 [0.2237, 0.52851, 0.43315],
7379 [0.22681, 0.53303, 0.42271],
7380 [0.22982, 0.53753, 0.41226],
7381 [0.23283, 0.54198, 0.40175],
7382 [0.23581, 0.54643, 0.39121],
7383 [0.23872, 0.55083, 0.38071],
7384 [0.24169, 0.55518, 0.37044],
7385 [0.24469, 0.55949, 0.3605],
7386 [0.24781, 0.56374, 0.35089],
7387 [0.25097, 0.56793, 0.34154],
7388 [0.25425, 0.57208, 0.33247],
7389 [0.25761, 0.5762, 0.32363],
7390 [0.26111, 0.58025, 0.31505],
7391 [0.26472, 0.58427, 0.3067],
7392 [0.26848, 0.58825, 0.29856],
7393 [0.27234, 0.5922, 0.29062],
7394 [0.27639, 0.5961, 0.28291],
7395 [0.28053, 0.59996, 0.27535],
7396 [0.28484, 0.6038, 0.26796],
7397 [0.28931, 0.60759, 0.26077],
7398 [0.29388, 0.61135, 0.25373],
7399 [0.29862, 0.61508, 0.24682],
7400 [0.3035, 0.61878, 0.24008],
7401 [0.30855, 0.62243, 0.23349],
7402 [0.31372, 0.62607, 0.22707],
7403 [0.31901, 0.62967, 0.22077],
7404 [0.32444, 0.63324, 0.21455],
7405 [0.33002, 0.63679, 0.20847],
7406 [0.3357, 0.6403, 0.20249],
7407 [0.3415, 0.64378, 0.19666],
7408 [0.34744, 0.64724, 0.1909],
7409 [0.35349, 0.65066, 0.18533],
7410 [0.35968, 0.65406, 0.17981],
7411 [0.36597, 0.65744, 0.17443],
7412 [0.37234, 0.66078, 0.16914],
7413 [0.37883, 0.6641, 0.16394],
7414 [0.38543, 0.6674, 0.15885],
7415 [0.39215, 0.67066, 0.15389],
7416 [0.39895, 0.6739, 0.14907],
7417 [0.40585, 0.67712, 0.14434],
7418 [0.41283, 0.6803, 0.13966],
7419 [0.41989, 0.68346, 0.13522],
7420 [0.42707, 0.6866, 0.1309],
7421 [0.43431, 0.68971, 0.12666],
7422 [0.44163, 0.6928, 0.12254],
7423 [0.44902, 0.69586, 0.11865],
7424 [0.45651, 0.69888, 0.11488],
7425 [0.46408, 0.70188, 0.11136],
7426 [0.4717, 0.70487, 0.1079],
7427 [0.47938, 0.70783, 0.10464],
7428 [0.48716, 0.71076, 0.10172],
7429 [0.495, 0.71367, 0.098964],
7430 [0.50288, 0.71655, 0.096355],
7431 [0.51084, 0.71941, 0.094134],
7432 [0.51888, 0.72223, 0.092156],
7433 [0.52696, 0.72504, 0.090393],
7434 [0.53508, 0.72782, 0.088892],
7435 [0.54329, 0.73057, 0.087819],
7436 [0.55155, 0.73329, 0.087005],
7437 [0.55985, 0.73599, 0.086399],
7438 [0.56821, 0.73867, 0.08621],
7439 [0.57664, 0.74131, 0.086387],
7440 [0.5851, 0.74394, 0.086866],
7441 [0.59361, 0.74654, 0.087651],
7442 [0.60218, 0.74911, 0.088758],
7443 [0.61075, 0.75167, 0.090091],
7444 [0.6193, 0.75421, 0.091662],
7445 [0.62776, 0.75676, 0.093291],
7446 [0.63618, 0.7593, 0.095179],
7447 [0.64452, 0.76186, 0.097055],
7448 [0.65279, 0.76442, 0.0992],
7449 [0.66101, 0.76698, 0.10144],
7450 [0.66917, 0.76954, 0.10382],
7451 [0.67726, 0.77211, 0.10635],
7452 [0.68528, 0.77468, 0.10898],
7453 [0.69324, 0.77727, 0.11176],
7454 [0.70115, 0.77985, 0.1146],
7455 [0.70899, 0.78245, 0.11768],
7456 [0.71675, 0.78505, 0.12084],
7457 [0.72446, 0.78766, 0.12415],
7458 [0.73211, 0.79027, 0.12759],
7459 [0.73969, 0.7929, 0.13116],
7460 [0.74719, 0.79554, 0.13488],
7461 [0.75463, 0.79819, 0.13869],
7462 [0.762, 0.80085, 0.14265],
7463 [0.76931, 0.80352, 0.1467],
7464 [0.77655, 0.80621, 0.15091],
7465 [0.78371, 0.80891, 0.15527],
7466 [0.79078, 0.81163, 0.15974],
7467 [0.79778, 0.81436, 0.1644],
7468 [0.80471, 0.81711, 0.16917],
7469 [0.81155, 0.81987, 0.17404],
7470 [0.8183, 0.82266, 0.17908],
7471 [0.82496, 0.82547, 0.18425],
7472 [0.83154, 0.8283, 0.18958],
7473 [0.83802, 0.83116, 0.19506],
7474 [0.84439, 0.83404, 0.20068],
7475 [0.85066, 0.83694, 0.20653],
7476 [0.85681, 0.83988, 0.21248],
7477 [0.86285, 0.84285, 0.21864],
7478 [0.86877, 0.84585, 0.22495],
7479 [0.87454, 0.84889, 0.23152],
7480 [0.88018, 0.85196, 0.23823],
7481 [0.88567, 0.85508, 0.24516],
7482 [0.89101, 0.85823, 0.25235],
7483 [0.89617, 0.86144, 0.25975],
7484 [0.90116, 0.86469, 0.26737],
7485 [0.90596, 0.868, 0.27529],
7486 [0.91052, 0.87137, 0.2835],
7487 [0.91485, 0.87481, 0.29203],
7488 [0.91894, 0.87831, 0.30086],
7489 [0.92276, 0.88189, 0.31007],
7490 [0.92625, 0.88556, 0.3197],
7491 [0.92941, 0.88931, 0.32973],
7492 [0.93217, 0.89317, 0.34027],
7493 [0.93451, 0.89714, 0.3513],
7494 [0.93634, 0.90125, 0.36298],
7495 [0.93763, 0.9055, 0.37534],
7496 [0.9387, 0.90978, 0.38837],
7497 [0.93989, 0.91399, 0.40197],
7498 [0.94123, 0.91811, 0.41613],
7499 [0.94272, 0.92216, 0.43083],
7500 [0.94436, 0.92612, 0.44608],
7501 [0.94613, 0.93, 0.46186],
7502 [0.94803, 0.9338, 0.47813],
7503 [0.95005, 0.93753, 0.49497],
7504 [0.95218, 0.94117, 0.5123],
7505 [0.95441, 0.94474, 0.53014],
7506 [0.95674, 0.94822, 0.54852],
7507 [0.95915, 0.95163, 0.56741],
7508 [0.96162, 0.95496, 0.58679],
7509 [0.96415, 0.95822, 0.60671],
7510 [0.96673, 0.96139, 0.62717],
7511 [0.96934, 0.96449, 0.64813],
7512 [0.97196, 0.96752, 0.66962],
7513 [0.97459, 0.97046, 0.69168],
7514 [0.97722, 0.97333, 0.71425],
7515 [0.9798, 0.97613, 0.73736],
7516 [0.98235, 0.97885, 0.76105],
7517 [0.98483, 0.98151, 0.78529],
7518 [0.98722, 0.98408, 0.81007],
7519 [0.98952, 0.98658, 0.83544],
7520 [0.99169, 0.98901, 0.8614],
7521 [0.99371, 0.99136, 0.88792],
7522 [0.99556, 0.99365, 0.91503],
7523 [0.99723, 0.99585, 0.94278],
7524 [0.99867, 0.99799, 0.97109],
7525 [0.99986, 1, 1],
7526 ]
7527 b_linear_bgyw_15_100_c68 = bokeh_palette('linear_bgyw_15_100_c68',linear_bgyw_15_100_c68)
7528 m_linear_bgyw_15_100_c68 = mpl_cm('linear_bgyw_15_100_c68',linear_bgyw_15_100_c68)
7529 m_linear_bgyw_15_100_c68_r = mpl_cm('linear_bgyw_15_100_c68_r',list(reversed(linear_bgyw_15_100_c68)))
7530 bgyw = b_linear_bgyw_15_100_c68
7531 m_bgyw = m_linear_bgyw_15_100_c68
7532 m_bgyw_r = m_linear_bgyw_15_100_c68_r
7533 palette['bgyw'] = b_linear_bgyw_15_100_c68
7534 cm['bgyw'] = m_linear_bgyw_15_100_c68
7535 cm['bgyw_r'] = m_linear_bgyw_15_100_c68_r
7536 register_cmap('cet_bgyw',m_linear_bgyw_15_100_c68)
7537 register_cmap('cet_bgyw_r',m_linear_bgyw_15_100_c68_r)
7538
7539
7540
7541
7542 linear_blue_5_95_c73 = [\
7543 [0, 0.0024382, 0.30687],
7544 [0, 0.0044692, 0.31437],
7545 [0, 0.0062324, 0.32191],
7546 [0, 0.0077305, 0.32951],
7547 [0, 0.008958, 0.33713],
7548 [0, 0.0098968, 0.34479],
7549 [0, 0.010555, 0.35249],
7550 [0, 0.011009, 0.36023],
7551 [0, 0.01114, 0.36802],
7552 [0.0018829, 0.010944, 0.37585],
7553 [0.0043414, 0.010697, 0.38371],
7554 [0.0068536, 0.010463, 0.39161],
7555 [0.0094655, 0.010231, 0.39952],
7556 [0.01235, 0.0099983, 0.4075],
7557 [0.015052, 0.0097591, 0.4155],
7558 [0.017851, 0.0094983, 0.42354],
7559 [0.020695, 0.0092222, 0.43163],
7560 [0.02357, 0.0089375, 0.43973],
7561 [0.026496, 0.0086445, 0.44787],
7562 [0.029448, 0.0083501, 0.45605],
7563 [0.032396, 0.0080591, 0.46429],
7564 [0.03558, 0.0077658, 0.47253],
7565 [0.038524, 0.0074701, 0.48082],
7566 [0.041458, 0.0071848, 0.48915],
7567 [0.044141, 0.0069073, 0.49753],
7568 [0.04679, 0.0066377, 0.50593],
7569 [0.04932, 0.0063792, 0.51438],
7570 [0.051527, 0.0061442, 0.52287],
7571 [0.053656, 0.0059329, 0.53139],
7572 [0.055683, 0.0057462, 0.53995],
7573 [0.057455, 0.0055887, 0.54857],
7574 [0.059195, 0.0054661, 0.55722],
7575 [0.060593, 0.0053876, 0.5659],
7576 [0.061766, 0.0053629, 0.57464],
7577 [0.062841, 0.0053961, 0.58343],
7578 [0.063532, 0.0054935, 0.59227],
7579 [0.063966, 0.0056647, 0.60114],
7580 [0.0641, 0.0059201, 0.61007],
7581 [0.063882, 0.0062716, 0.61907],
7582 [0.063281, 0.0067326, 0.6281],
7583 [0.062148, 0.0073175, 0.63719],
7584 [0.060493, 0.0080408, 0.64634],
7585 [0.058092, 0.008929, 0.65557],
7586 [0.055233, 0.0099623, 0.66482],
7587 [0.052105, 0.011266, 0.67402],
7588 [0.049146, 0.012683, 0.68314],
7589 [0.046014, 0.014144, 0.69216],
7590 [0.04309, 0.015741, 0.70108],
7591 [0.040435, 0.017485, 0.70992],
7592 [0.037863, 0.019379, 0.71866],
7593 [0.035616, 0.021429, 0.72731],
7594 [0.033428, 0.02364, 0.73587],
7595 [0.031841, 0.026021, 0.74433],
7596 [0.030635, 0.028579, 0.75268],
7597 [0.029823, 0.031319, 0.76095],
7598 [0.029422, 0.034249, 0.7691],
7599 [0.029449, 0.037557, 0.77717],
7600 [0.029926, 0.040864, 0.78513],
7601 [0.030874, 0.044198, 0.793],
7602 [0.032312, 0.047578, 0.80076],
7603 [0.034281, 0.051036, 0.80842],
7604 [0.036977, 0.054512, 0.81597],
7605 [0.040055, 0.058003, 0.82341],
7606 [0.043483, 0.061561, 0.83076],
7607 [0.047434, 0.065191, 0.83799],
7608 [0.051627, 0.068868, 0.84513],
7609 [0.056188, 0.072421, 0.85216],
7610 [0.060871, 0.076069, 0.85907],
7611 [0.065858, 0.079772, 0.86589],
7612 [0.071059, 0.083524, 0.87259],
7613 [0.07632, 0.087319, 0.87918],
7614 [0.081824, 0.091117, 0.88564],
7615 [0.087161, 0.095093, 0.89195],
7616 [0.092292, 0.099225, 0.89805],
7617 [0.097256, 0.10365, 0.90395],
7618 [0.10208, 0.10819, 0.90965],
7619 [0.10678, 0.11304, 0.91514],
7620 [0.11126, 0.11798, 0.92041],
7621 [0.11561, 0.12306, 0.92547],
7622 [0.11981, 0.12837, 0.93032],
7623 [0.12389, 0.13378, 0.93496],
7624 [0.12789, 0.13928, 0.9394],
7625 [0.13172, 0.14498, 0.94362],
7626 [0.13541, 0.15071, 0.94764],
7627 [0.13898, 0.15659, 0.95143],
7628 [0.14245, 0.16255, 0.95501],
7629 [0.14579, 0.16859, 0.95837],
7630 [0.14895, 0.17474, 0.96151],
7631 [0.15202, 0.18091, 0.96444],
7632 [0.15497, 0.18721, 0.96717],
7633 [0.15778, 0.19355, 0.96967],
7634 [0.16044, 0.19992, 0.97196],
7635 [0.16301, 0.20643, 0.97403],
7636 [0.16537, 0.21292, 0.97587],
7637 [0.16765, 0.21951, 0.9775],
7638 [0.16978, 0.22614, 0.9789],
7639 [0.17171, 0.23278, 0.9801],
7640 [0.17352, 0.2395, 0.98107],
7641 [0.17518, 0.24623, 0.98183],
7642 [0.17664, 0.25301, 0.98238],
7643 [0.17803, 0.25977, 0.98279],
7644 [0.17924, 0.26645, 0.98317],
7645 [0.18037, 0.27304, 0.98356],
7646 [0.18141, 0.27957, 0.98394],
7647 [0.18236, 0.28598, 0.98432],
7648 [0.18323, 0.29237, 0.98469],
7649 [0.18401, 0.29868, 0.98507],
7650 [0.1847, 0.30493, 0.98544],
7651 [0.1853, 0.31112, 0.9858],
7652 [0.1858, 0.31725, 0.98617],
7653 [0.18619, 0.32334, 0.98654],
7654 [0.18649, 0.32939, 0.9869],
7655 [0.18671, 0.33539, 0.98726],
7656 [0.18684, 0.34133, 0.98762],
7657 [0.18688, 0.34725, 0.98797],
7658 [0.18682, 0.35312, 0.98832],
7659 [0.18667, 0.35896, 0.98868],
7660 [0.18643, 0.36477, 0.98903],
7661 [0.1861, 0.37054, 0.98937],
7662 [0.18568, 0.37631, 0.98972],
7663 [0.18513, 0.38201, 0.99006],
7664 [0.18448, 0.38771, 0.9904],
7665 [0.18373, 0.39338, 0.99074],
7666 [0.18287, 0.39902, 0.99107],
7667 [0.18192, 0.40464, 0.9914],
7668 [0.18086, 0.41025, 0.99173],
7669 [0.17969, 0.41582, 0.99206],
7670 [0.17843, 0.42137, 0.99239],
7671 [0.17708, 0.42691, 0.99271],
7672 [0.17576, 0.43242, 0.99301],
7673 [0.17462, 0.43788, 0.9933],
7674 [0.17355, 0.44331, 0.99356],
7675 [0.17263, 0.44871, 0.99381],
7676 [0.17185, 0.45406, 0.99403],
7677 [0.17122, 0.4594, 0.99423],
7678 [0.17072, 0.4647, 0.99442],
7679 [0.17037, 0.46998, 0.99459],
7680 [0.17015, 0.47522, 0.99473],
7681 [0.17008, 0.48043, 0.99486],
7682 [0.17016, 0.48562, 0.99497],
7683 [0.17038, 0.4908, 0.99505],
7684 [0.17077, 0.49593, 0.99512],
7685 [0.17131, 0.50106, 0.99517],
7686 [0.17201, 0.50615, 0.99519],
7687 [0.17286, 0.51122, 0.9952],
7688 [0.17386, 0.51627, 0.99519],
7689 [0.17503, 0.52131, 0.99516],
7690 [0.17629, 0.52633, 0.9951],
7691 [0.17778, 0.53132, 0.99503],
7692 [0.17936, 0.5363, 0.99494],
7693 [0.1811, 0.54125, 0.99482],
7694 [0.18299, 0.5462, 0.99469],
7695 [0.18504, 0.55111, 0.99454],
7696 [0.1872, 0.55601, 0.99436],
7697 [0.18948, 0.5609, 0.99417],
7698 [0.19189, 0.56577, 0.99396],
7699 [0.19443, 0.57063, 0.99373],
7700 [0.19686, 0.5755, 0.99349],
7701 [0.19906, 0.58036, 0.99326],
7702 [0.2011, 0.58524, 0.99303],
7703 [0.20297, 0.59011, 0.99281],
7704 [0.20464, 0.59499, 0.9926],
7705 [0.20612, 0.59989, 0.99239],
7706 [0.2074, 0.60479, 0.99218],
7707 [0.2085, 0.60969, 0.99198],
7708 [0.20942, 0.6146, 0.99179],
7709 [0.21016, 0.61953, 0.9916],
7710 [0.21072, 0.62445, 0.99142],
7711 [0.21111, 0.62938, 0.99124],
7712 [0.21132, 0.63432, 0.99107],
7713 [0.21135, 0.63926, 0.9909],
7714 [0.2112, 0.64421, 0.99074],
7715 [0.21086, 0.64918, 0.99058],
7716 [0.21033, 0.65414, 0.99043],
7717 [0.20961, 0.65911, 0.99029],
7718 [0.2087, 0.66409, 0.99015],
7719 [0.2076, 0.66908, 0.99002],
7720 [0.20631, 0.67406, 0.98989],
7721 [0.20478, 0.67906, 0.98977],
7722 [0.20305, 0.68406, 0.98965],
7723 [0.20108, 0.68908, 0.98954],
7724 [0.1989, 0.69409, 0.98943],
7725 [0.19651, 0.69911, 0.98933],
7726 [0.19382, 0.70414, 0.98924],
7727 [0.19088, 0.70918, 0.98914],
7728 [0.18788, 0.71421, 0.98905],
7729 [0.18488, 0.71923, 0.98895],
7730 [0.18198, 0.72423, 0.98883],
7731 [0.17926, 0.72923, 0.98871],
7732 [0.17665, 0.73421, 0.98857],
7733 [0.17423, 0.73918, 0.98842],
7734 [0.17193, 0.74412, 0.98825],
7735 [0.16983, 0.74906, 0.98808],
7736 [0.16785, 0.75399, 0.98789],
7737 [0.16608, 0.7589, 0.9877],
7738 [0.16452, 0.76381, 0.98749],
7739 [0.16316, 0.76869, 0.98727],
7740 [0.16202, 0.77357, 0.98703],
7741 [0.1611, 0.77844, 0.98679],
7742 [0.16037, 0.7833, 0.98653],
7743 [0.15991, 0.78814, 0.98626],
7744 [0.1597, 0.79298, 0.98597],
7745 [0.15972, 0.7978, 0.98568],
7746 [0.15999, 0.80261, 0.98537],
7747 [0.16053, 0.80742, 0.98505],
7748 [0.16137, 0.81221, 0.98472],
7749 [0.16241, 0.81699, 0.98438],
7750 [0.16373, 0.82176, 0.98402],
7751 [0.16523, 0.82652, 0.98365],
7752 [0.16707, 0.83127, 0.98327],
7753 [0.1691, 0.83601, 0.98287],
7754 [0.17134, 0.84074, 0.98247],
7755 [0.17387, 0.84546, 0.98205],
7756 [0.17729, 0.85015, 0.98162],
7757 [0.18258, 0.85474, 0.98119],
7758 [0.19003, 0.85923, 0.98076],
7759 [0.19916, 0.86363, 0.98033],
7760 [0.20965, 0.86794, 0.97991],
7761 [0.22117, 0.87217, 0.97948],
7762 [0.23338, 0.87632, 0.97905],
7763 [0.24622, 0.88041, 0.97862],
7764 [0.25953, 0.88443, 0.9782],
7765 [0.27309, 0.8884, 0.97777],
7766 [0.28681, 0.89231, 0.97734],
7767 [0.30063, 0.89617, 0.97691],
7768 [0.31448, 0.89998, 0.97648],
7769 [0.32832, 0.90375, 0.97605],
7770 [0.34224, 0.90747, 0.97562],
7771 [0.35613, 0.91115, 0.97518],
7772 [0.36991, 0.91479, 0.97475],
7773 [0.38361, 0.9184, 0.97431],
7774 [0.39728, 0.92197, 0.97387],
7775 [0.4109, 0.9255, 0.97343],
7776 [0.42439, 0.92899, 0.973],
7777 [0.43779, 0.93247, 0.97255],
7778 [0.45116, 0.9359, 0.97211],
7779 [0.46443, 0.93931, 0.97166],
7780 [0.47755, 0.94269, 0.97121],
7781 [0.49069, 0.94603, 0.97076],
7782 [0.5037, 0.94935, 0.97031],
7783 [0.51659, 0.95265, 0.96986],
7784 [0.52949, 0.95592, 0.9694],
7785 [0.54227, 0.95916, 0.96894],
7786 [0.55496, 0.96238, 0.96849],
7787 [0.56763, 0.96557, 0.96803],
7788 [0.58018, 0.96874, 0.96756],
7789 [0.59271, 0.97189, 0.9671],
7790 [0.60515, 0.97501, 0.96663],
7791 [0.61751, 0.97812, 0.96616],
7792 [0.62987, 0.98119, 0.96569],
7793 [0.64213, 0.98425, 0.96521],
7794 [0.65436, 0.98729, 0.96474],
7795 [0.66654, 0.9903, 0.96426],
7796 [0.67864, 0.9933, 0.96378],
7797 [0.69072, 0.99626, 0.9633],
7798 [0.70271, 0.99922, 0.96282],
7799 ]
7800 b_linear_blue_5_95_c73 = bokeh_palette('linear_blue_5_95_c73',linear_blue_5_95_c73)
7801 m_linear_blue_5_95_c73 = mpl_cm('linear_blue_5_95_c73',linear_blue_5_95_c73)
7802 m_linear_blue_5_95_c73_r = mpl_cm('linear_blue_5_95_c73_r',list(reversed(linear_blue_5_95_c73)))
7803 kbc = b_linear_blue_5_95_c73
7804 m_kbc = m_linear_blue_5_95_c73
7805 m_kbc_r = m_linear_blue_5_95_c73_r
7806 palette['kbc'] = b_linear_blue_5_95_c73
7807 cm['kbc'] = m_linear_blue_5_95_c73
7808 cm['kbc_r'] = m_linear_blue_5_95_c73_r
7809 register_cmap('cet_kbc',m_linear_blue_5_95_c73)
7810 register_cmap('cet_kbc_r',m_linear_blue_5_95_c73_r)
7811
7812
7813
7814
7815 linear_blue_95_50_c20 = [\
7816 [0.94334, 0.94353, 0.94348],
7817 [0.94036, 0.94166, 0.94325],
7818 [0.93738, 0.9398, 0.94302],
7819 [0.93439, 0.93793, 0.94278],
7820 [0.93141, 0.93607, 0.94255],
7821 [0.92843, 0.9342, 0.94231],
7822 [0.92545, 0.93234, 0.94206],
7823 [0.92247, 0.93048, 0.94182],
7824 [0.91948, 0.92862, 0.94157],
7825 [0.9165, 0.92676, 0.94131],
7826 [0.91352, 0.9249, 0.94106],
7827 [0.91054, 0.92304, 0.9408],
7828 [0.90755, 0.92118, 0.94054],
7829 [0.90456, 0.91932, 0.94028],
7830 [0.90157, 0.91747, 0.94001],
7831 [0.89858, 0.91561, 0.93974],
7832 [0.8956, 0.91376, 0.93947],
7833 [0.89261, 0.9119, 0.93919],
7834 [0.88962, 0.91005, 0.93891],
7835 [0.88663, 0.9082, 0.93863],
7836 [0.88364, 0.90635, 0.93834],
7837 [0.88065, 0.90449, 0.93805],
7838 [0.87766, 0.90264, 0.93776],
7839 [0.87466, 0.90079, 0.93746],
7840 [0.87167, 0.89894, 0.93716],
7841 [0.86868, 0.8971, 0.93686],
7842 [0.86569, 0.89525, 0.93655],
7843 [0.8627, 0.89339, 0.93624],
7844 [0.8597, 0.89155, 0.93593],
7845 [0.8567, 0.8897, 0.93561],
7846 [0.8537, 0.88785, 0.93528],
7847 [0.85071, 0.88601, 0.93496],
7848 [0.84771, 0.88417, 0.93463],
7849 [0.84472, 0.88232, 0.9343],
7850 [0.84172, 0.88048, 0.93396],
7851 [0.83872, 0.87864, 0.93362],
7852 [0.83572, 0.87679, 0.93327],
7853 [0.83272, 0.87495, 0.93292],
7854 [0.82973, 0.87311, 0.93257],
7855 [0.82673, 0.87127, 0.93222],
7856 [0.82373, 0.86943, 0.93186],
7857 [0.82073, 0.86759, 0.93149],
7858 [0.81773, 0.86575, 0.93112],
7859 [0.81473, 0.86392, 0.93075],
7860 [0.81173, 0.86208, 0.93037],
7861 [0.80873, 0.86025, 0.92999],
7862 [0.80573, 0.85841, 0.9296],
7863 [0.80273, 0.85657, 0.92921],
7864 [0.79973, 0.85474, 0.92881],
7865 [0.79673, 0.85291, 0.92841],
7866 [0.79374, 0.85107, 0.928],
7867 [0.79073, 0.84924, 0.92759],
7868 [0.78773, 0.8474, 0.92717],
7869 [0.78474, 0.84557, 0.92675],
7870 [0.78174, 0.84374, 0.92633],
7871 [0.77873, 0.84191, 0.9259],
7872 [0.77573, 0.84009, 0.92546],
7873 [0.77274, 0.83825, 0.92502],
7874 [0.76974, 0.83642, 0.92457],
7875 [0.76674, 0.8346, 0.92412],
7876 [0.76375, 0.83277, 0.92366],
7877 [0.76075, 0.83094, 0.92319],
7878 [0.75776, 0.82912, 0.92272],
7879 [0.75477, 0.82729, 0.92224],
7880 [0.75178, 0.82546, 0.92176],
7881 [0.74878, 0.82363, 0.92127],
7882 [0.74579, 0.82181, 0.92077],
7883 [0.7428, 0.81998, 0.92027],
7884 [0.73982, 0.81816, 0.91976],
7885 [0.73683, 0.81634, 0.91924],
7886 [0.73384, 0.81451, 0.91871],
7887 [0.73086, 0.81269, 0.91818],
7888 [0.72788, 0.81087, 0.91765],
7889 [0.72491, 0.80905, 0.9171],
7890 [0.72192, 0.80723, 0.91654],
7891 [0.71895, 0.8054, 0.91598],
7892 [0.71599, 0.80358, 0.91541],
7893 [0.71301, 0.80176, 0.91483],
7894 [0.71005, 0.79995, 0.91424],
7895 [0.70709, 0.79812, 0.91365],
7896 [0.70413, 0.7963, 0.91304],
7897 [0.70117, 0.79449, 0.91242],
7898 [0.69822, 0.79266, 0.91179],
7899 [0.69528, 0.79084, 0.91116],
7900 [0.69234, 0.78903, 0.91051],
7901 [0.6894, 0.78721, 0.90986],
7902 [0.68646, 0.78539, 0.90919],
7903 [0.68354, 0.78357, 0.90851],
7904 [0.68061, 0.78175, 0.90782],
7905 [0.67771, 0.77993, 0.90711],
7906 [0.6748, 0.77812, 0.9064],
7907 [0.6719, 0.7763, 0.90567],
7908 [0.66901, 0.77447, 0.90492],
7909 [0.66612, 0.77266, 0.90416],
7910 [0.66325, 0.77084, 0.90339],
7911 [0.66038, 0.76902, 0.9026],
7912 [0.65753, 0.7672, 0.90179],
7913 [0.65467, 0.76538, 0.90097],
7914 [0.65185, 0.76356, 0.90013],
7915 [0.64903, 0.76174, 0.89928],
7916 [0.64622, 0.75992, 0.89839],
7917 [0.64342, 0.7581, 0.8975],
7918 [0.64065, 0.75627, 0.89658],
7919 [0.63789, 0.75445, 0.89563],
7920 [0.63514, 0.75262, 0.89466],
7921 [0.63243, 0.7508, 0.89366],
7922 [0.62972, 0.74897, 0.89264],
7923 [0.62705, 0.74715, 0.89159],
7924 [0.6244, 0.74531, 0.8905],
7925 [0.62177, 0.74349, 0.88938],
7926 [0.61919, 0.74165, 0.88823],
7927 [0.61663, 0.73982, 0.88703],
7928 [0.6141, 0.73798, 0.88579],
7929 [0.61162, 0.73613, 0.8845],
7930 [0.60918, 0.73429, 0.88317],
7931 [0.60674, 0.73245, 0.88182],
7932 [0.60432, 0.73061, 0.88046],
7933 [0.6019, 0.72876, 0.87909],
7934 [0.5995, 0.72692, 0.87772],
7935 [0.59711, 0.72508, 0.87632],
7936 [0.59471, 0.72323, 0.87492],
7937 [0.59235, 0.72139, 0.87351],
7938 [0.58997, 0.71955, 0.87209],
7939 [0.58761, 0.71771, 0.87065],
7940 [0.58527, 0.71586, 0.86921],
7941 [0.58292, 0.71402, 0.86776],
7942 [0.58059, 0.71217, 0.86629],
7943 [0.57827, 0.71033, 0.86481],
7944 [0.57597, 0.70849, 0.86333],
7945 [0.57366, 0.70665, 0.86183],
7946 [0.57136, 0.7048, 0.86033],
7947 [0.56908, 0.70296, 0.8588],
7948 [0.56682, 0.70112, 0.85727],
7949 [0.56455, 0.69927, 0.85574],
7950 [0.5623, 0.69743, 0.85418],
7951 [0.56006, 0.69559, 0.85263],
7952 [0.55782, 0.69375, 0.85105],
7953 [0.55559, 0.69191, 0.84947],
7954 [0.55338, 0.69007, 0.84788],
7955 [0.55118, 0.68823, 0.84627],
7956 [0.549, 0.68638, 0.84466],
7957 [0.54681, 0.68454, 0.84304],
7958 [0.54464, 0.6827, 0.8414],
7959 [0.54248, 0.68085, 0.83976],
7960 [0.54033, 0.67901, 0.8381],
7961 [0.53819, 0.67718, 0.83644],
7962 [0.53605, 0.67533, 0.83476],
7963 [0.53393, 0.67349, 0.83307],
7964 [0.53183, 0.67165, 0.83138],
7965 [0.52973, 0.66981, 0.82967],
7966 [0.52764, 0.66797, 0.82795],
7967 [0.52557, 0.66613, 0.82622],
7968 [0.5235, 0.66429, 0.82448],
7969 [0.52144, 0.66245, 0.82274],
7970 [0.5194, 0.6606, 0.82097],
7971 [0.51737, 0.65876, 0.8192],
7972 [0.51534, 0.65693, 0.81742],
7973 [0.51333, 0.65508, 0.81564],
7974 [0.51133, 0.65324, 0.81383],
7975 [0.50934, 0.65141, 0.81203],
7976 [0.50737, 0.64957, 0.8102],
7977 [0.50539, 0.64772, 0.80838],
7978 [0.50344, 0.64588, 0.80654],
7979 [0.5015, 0.64404, 0.80469],
7980 [0.49956, 0.64221, 0.80282],
7981 [0.49765, 0.64037, 0.80095],
7982 [0.49573, 0.63853, 0.79907],
7983 [0.49383, 0.6367, 0.79718],
7984 [0.49195, 0.63486, 0.79528],
7985 [0.49007, 0.63302, 0.79337],
7986 [0.4882, 0.63118, 0.79145],
7987 [0.48631, 0.62934, 0.78955],
7988 [0.48439, 0.62751, 0.78769],
7989 [0.48243, 0.62568, 0.78587],
7990 [0.48043, 0.62386, 0.78409],
7991 [0.4784, 0.62203, 0.78233],
7992 [0.47634, 0.62022, 0.78062],
7993 [0.47423, 0.61841, 0.77894],
7994 [0.47211, 0.6166, 0.77729],
7995 [0.46995, 0.61479, 0.77567],
7996 [0.46775, 0.61298, 0.77408],
7997 [0.46552, 0.61119, 0.77252],
7998 [0.46327, 0.60939, 0.77099],
7999 [0.461, 0.6076, 0.76947],
8000 [0.4587, 0.6058, 0.76799],
8001 [0.45636, 0.60403, 0.76653],
8002 [0.45401, 0.60223, 0.7651],
8003 [0.45164, 0.60045, 0.76367],
8004 [0.44923, 0.59867, 0.76228],
8005 [0.4468, 0.5969, 0.76091],
8006 [0.44436, 0.59512, 0.75956],
8007 [0.44188, 0.59336, 0.75823],
8008 [0.43937, 0.59159, 0.75691],
8009 [0.43686, 0.58981, 0.75562],
8010 [0.43431, 0.58805, 0.75434],
8011 [0.43176, 0.5863, 0.75308],
8012 [0.42917, 0.58454, 0.75184],
8013 [0.42655, 0.58278, 0.75061],
8014 [0.42392, 0.58102, 0.74939],
8015 [0.42127, 0.57928, 0.74821],
8016 [0.4186, 0.57752, 0.74702],
8017 [0.41591, 0.57578, 0.74586],
8018 [0.4132, 0.57403, 0.7447],
8019 [0.41046, 0.57229, 0.74357],
8020 [0.4077, 0.57054, 0.74245],
8021 [0.40491, 0.56881, 0.74133],
8022 [0.40211, 0.56708, 0.74024],
8023 [0.39929, 0.56533, 0.73915],
8024 [0.39645, 0.56361, 0.73807],
8025 [0.39358, 0.56188, 0.73701],
8026 [0.3907, 0.56015, 0.73596],
8027 [0.38779, 0.55842, 0.73493],
8028 [0.38485, 0.5567, 0.7339],
8029 [0.3819, 0.55498, 0.73288],
8030 [0.37893, 0.55325, 0.73187],
8031 [0.37593, 0.55154, 0.73088],
8032 [0.3729, 0.54983, 0.72989],
8033 [0.36986, 0.54812, 0.72892],
8034 [0.36679, 0.54641, 0.72795],
8035 [0.36369, 0.54469, 0.72699],
8036 [0.36057, 0.54299, 0.72605],
8037 [0.35745, 0.54127, 0.72511],
8038 [0.35426, 0.53957, 0.72418],
8039 [0.35108, 0.53788, 0.72326],
8040 [0.34785, 0.53617, 0.72235],
8041 [0.3446, 0.53447, 0.72144],
8042 [0.34133, 0.53278, 0.72055],
8043 [0.33801, 0.53108, 0.71967],
8044 [0.3347, 0.52939, 0.71879],
8045 [0.33131, 0.5277, 0.71792],
8046 [0.32793, 0.52601, 0.71706],
8047 [0.3245, 0.52432, 0.7162],
8048 [0.32105, 0.52263, 0.71535],
8049 [0.31756, 0.52095, 0.7145],
8050 [0.31404, 0.51927, 0.71368],
8051 [0.31049, 0.5176, 0.71284],
8052 [0.30689, 0.5159, 0.71203],
8053 [0.30325, 0.51424, 0.71122],
8054 [0.2996, 0.51256, 0.71041],
8055 [0.29588, 0.51089, 0.70961],
8056 [0.29213, 0.50922, 0.70882],
8057 [0.28834, 0.50755, 0.70803],
8058 [0.2845, 0.50587, 0.70724],
8059 [0.28061, 0.50422, 0.70647],
8060 [0.27671, 0.50255, 0.7057],
8061 [0.27272, 0.50089, 0.70494],
8062 [0.2687, 0.49923, 0.70418],
8063 [0.26461, 0.49758, 0.70343],
8064 [0.26047, 0.49591, 0.70268],
8065 [0.25627, 0.49427, 0.70194],
8066 [0.25203, 0.4926, 0.70121],
8067 [0.24771, 0.49097, 0.70048],
8068 [0.24329, 0.4893, 0.69975],
8069 [0.23883, 0.48767, 0.69903],
8070 [0.23431, 0.48601, 0.69831],
8071 [0.22967, 0.48437, 0.6976],
8072 ]
8073 b_linear_blue_95_50_c20 = bokeh_palette('linear_blue_95_50_c20',linear_blue_95_50_c20)
8074 m_linear_blue_95_50_c20 = mpl_cm('linear_blue_95_50_c20',linear_blue_95_50_c20)
8075 m_linear_blue_95_50_c20_r = mpl_cm('linear_blue_95_50_c20_r',list(reversed(linear_blue_95_50_c20)))
8076 blues = b_linear_blue_95_50_c20
8077 m_blues = m_linear_blue_95_50_c20
8078 m_blues_r = m_linear_blue_95_50_c20_r
8079 palette['blues'] = b_linear_blue_95_50_c20
8080 cm['blues'] = m_linear_blue_95_50_c20
8081 cm['blues_r'] = m_linear_blue_95_50_c20_r
8082 register_cmap('cet_blues',m_linear_blue_95_50_c20)
8083 register_cmap('cet_blues_r',m_linear_blue_95_50_c20_r)
8084
8085
8086
8087
8088 linear_bmw_5_95_c86 = [\
8089 [0, 0.0078689, 0.29563],
8090 [0, 0.01018, 0.30347],
8091 [0, 0.01249, 0.31136],
8092 [0, 0.014296, 0.31929],
8093 [0, 0.015847, 0.32724],
8094 [0, 0.01713, 0.33526],
8095 [0, 0.018143, 0.3433],
8096 [0, 0.018877, 0.35137],
8097 [0, 0.019332, 0.35948],
8098 [0, 0.019537, 0.36762],
8099 [0, 0.019696, 0.37581],
8100 [0, 0.019848, 0.38402],
8101 [0, 0.019989, 0.39226],
8102 [0.0002784, 0.020121, 0.40055],
8103 [0.0013175, 0.020246, 0.40884],
8104 [0.0023914, 0.020361, 0.41718],
8105 [0.0034883, 0.020469, 0.42554],
8106 [0.004603, 0.020572, 0.43392],
8107 [0.0057432, 0.020668, 0.44236],
8108 [0.0068995, 0.020759, 0.4508],
8109 [0.0080586, 0.020848, 0.45928],
8110 [0.0092385, 0.020933, 0.46778],
8111 [0.010387, 0.021014, 0.47632],
8112 [0.011786, 0.021099, 0.48487],
8113 [0.012932, 0.021185, 0.49346],
8114 [0.014093, 0.021272, 0.50208],
8115 [0.015228, 0.021363, 0.51072],
8116 [0.016327, 0.021464, 0.51939],
8117 [0.017385, 0.021575, 0.52808],
8118 [0.018402, 0.021697, 0.53681],
8119 [0.019367, 0.021832, 0.54555],
8120 [0.020271, 0.021984, 0.55432],
8121 [0.021093, 0.022157, 0.56312],
8122 [0.021816, 0.022358, 0.57193],
8123 [0.022431, 0.022589, 0.58078],
8124 [0.022925, 0.022854, 0.58964],
8125 [0.02328, 0.023157, 0.59854],
8126 [0.023474, 0.023505, 0.60747],
8127 [0.023484, 0.023905, 0.6164],
8128 [0.023283, 0.024365, 0.62537],
8129 [0.022843, 0.024892, 0.63435],
8130 [0.02213, 0.025497, 0.64335],
8131 [0.021108, 0.026192, 0.6524],
8132 [0.019919, 0.026976, 0.66144],
8133 [0.018888, 0.027836, 0.67043],
8134 [0.018212, 0.028767, 0.67933],
8135 [0.017924, 0.029768, 0.68816],
8136 [0.018038, 0.030843, 0.69692],
8137 [0.018576, 0.03199, 0.7056],
8138 [0.019563, 0.033222, 0.7142],
8139 [0.021022, 0.034609, 0.72273],
8140 [0.022976, 0.036126, 0.73118],
8141 [0.02546, 0.037612, 0.73955],
8142 [0.028511, 0.039192, 0.74783],
8143 [0.032139, 0.040867, 0.75603],
8144 [0.036548, 0.042546, 0.76415],
8145 [0.0414, 0.04435, 0.77219],
8146 [0.046471, 0.046119, 0.78014],
8147 [0.051815, 0.048019, 0.78801],
8148 [0.057373, 0.050007, 0.7958],
8149 [0.063189, 0.051954, 0.8035],
8150 [0.069106, 0.054002, 0.81111],
8151 [0.075029, 0.056167, 0.81863],
8152 [0.081171, 0.05824, 0.82607],
8153 [0.087403, 0.060492, 0.83342],
8154 [0.093627, 0.062774, 0.84068],
8155 [0.099985, 0.064997, 0.84785],
8156 [0.10645, 0.067338, 0.85494],
8157 [0.11293, 0.069742, 0.86194],
8158 [0.11943, 0.072103, 0.86884],
8159 [0.12606, 0.074573, 0.87564],
8160 [0.13279, 0.077004, 0.88234],
8161 [0.13992, 0.079441, 0.88889],
8162 [0.1477, 0.081844, 0.89524],
8163 [0.15601, 0.084044, 0.90139],
8164 [0.16477, 0.08607, 0.90734],
8165 [0.17399, 0.088131, 0.91308],
8166 [0.18361, 0.090027, 0.9186],
8167 [0.19359, 0.091859, 0.92392],
8168 [0.20383, 0.093506, 0.92903],
8169 [0.21429, 0.095185, 0.93394],
8170 [0.22495, 0.096634, 0.93864],
8171 [0.23584, 0.098158, 0.94313],
8172 [0.24685, 0.099485, 0.94742],
8173 [0.25802, 0.10076, 0.95149],
8174 [0.26936, 0.10196, 0.95534],
8175 [0.28076, 0.1031, 0.95898],
8176 [0.2923, 0.1041, 0.9624],
8177 [0.3039, 0.10503, 0.96562],
8178 [0.31558, 0.10597, 0.96862],
8179 [0.3273, 0.10679, 0.97142],
8180 [0.3391, 0.10749, 0.974],
8181 [0.35094, 0.10811, 0.97636],
8182 [0.36282, 0.1087, 0.9785],
8183 [0.37476, 0.10925, 0.98043],
8184 [0.38671, 0.1097, 0.98214],
8185 [0.3987, 0.11006, 0.98364],
8186 [0.41071, 0.11034, 0.98492],
8187 [0.42271, 0.11056, 0.98599],
8188 [0.43474, 0.11072, 0.98685],
8189 [0.44667, 0.11084, 0.98757],
8190 [0.45843, 0.11094, 0.98824],
8191 [0.47001, 0.11104, 0.98888],
8192 [0.48139, 0.11114, 0.9895],
8193 [0.49262, 0.11123, 0.99008],
8194 [0.50371, 0.11133, 0.99064],
8195 [0.51465, 0.11141, 0.99117],
8196 [0.52546, 0.11149, 0.99168],
8197 [0.53615, 0.11157, 0.99216],
8198 [0.54673, 0.11164, 0.99261],
8199 [0.55721, 0.1117, 0.99304],
8200 [0.56758, 0.11176, 0.99343],
8201 [0.57785, 0.11181, 0.9938],
8202 [0.58804, 0.11186, 0.99415],
8203 [0.59816, 0.1119, 0.99446],
8204 [0.6082, 0.11193, 0.99475],
8205 [0.61815, 0.11196, 0.99501],
8206 [0.62805, 0.11197, 0.99525],
8207 [0.63787, 0.11198, 0.99545],
8208 [0.64764, 0.11198, 0.99563],
8209 [0.65735, 0.11197, 0.99579],
8210 [0.66699, 0.11195, 0.99591],
8211 [0.6766, 0.11192, 0.99601],
8212 [0.68614, 0.11188, 0.99608],
8213 [0.69564, 0.11183, 0.99613],
8214 [0.7051, 0.11177, 0.99614],
8215 [0.71451, 0.1117, 0.99613],
8216 [0.72388, 0.11162, 0.9961],
8217 [0.73317, 0.11164, 0.99604],
8218 [0.7423, 0.11194, 0.99598],
8219 [0.75124, 0.11262, 0.99593],
8220 [0.75998, 0.11368, 0.99588],
8221 [0.76854, 0.1151, 0.99583],
8222 [0.77691, 0.11698, 0.9958],
8223 [0.7851, 0.11925, 0.99576],
8224 [0.79312, 0.12184, 0.99574],
8225 [0.80096, 0.12485, 0.99572],
8226 [0.80864, 0.12819, 0.9957],
8227 [0.81615, 0.13184, 0.99569],
8228 [0.8235, 0.13575, 0.99568],
8229 [0.83069, 0.14, 0.99568],
8230 [0.83772, 0.14456, 0.99569],
8231 [0.84458, 0.14935, 0.9957],
8232 [0.85129, 0.15434, 0.99571],
8233 [0.85785, 0.15956, 0.99573],
8234 [0.86427, 0.16499, 0.99576],
8235 [0.87053, 0.17062, 0.99578],
8236 [0.87664, 0.17639, 0.99582],
8237 [0.88261, 0.18234, 0.99586],
8238 [0.88844, 0.18847, 0.9959],
8239 [0.89411, 0.19472, 0.99595],
8240 [0.89964, 0.20104, 0.996],
8241 [0.90503, 0.20754, 0.99606],
8242 [0.91028, 0.21413, 0.99612],
8243 [0.91538, 0.22082, 0.99619],
8244 [0.92035, 0.22757, 0.99626],
8245 [0.92518, 0.23444, 0.99634],
8246 [0.92985, 0.24141, 0.9964],
8247 [0.93435, 0.24851, 0.99646],
8248 [0.9387, 0.25569, 0.9965],
8249 [0.9429, 0.26299, 0.99653],
8250 [0.94693, 0.27039, 0.99654],
8251 [0.9508, 0.27784, 0.99654],
8252 [0.95452, 0.28537, 0.99653],
8253 [0.95808, 0.29301, 0.9965],
8254 [0.96146, 0.30071, 0.99646],
8255 [0.96469, 0.30849, 0.9964],
8256 [0.96776, 0.31632, 0.99633],
8257 [0.97067, 0.32419, 0.99624],
8258 [0.97343, 0.33214, 0.99614],
8259 [0.97602, 0.34012, 0.99603],
8260 [0.97845, 0.34814, 0.9959],
8261 [0.98073, 0.35621, 0.99576],
8262 [0.98283, 0.36432, 0.9956],
8263 [0.98477, 0.37248, 0.99543],
8264 [0.98655, 0.38069, 0.99525],
8265 [0.98816, 0.38891, 0.99505],
8266 [0.98962, 0.39715, 0.99483],
8267 [0.9909, 0.40545, 0.9946],
8268 [0.99203, 0.41375, 0.99435],
8269 [0.99299, 0.42208, 0.99409],
8270 [0.99377, 0.43046, 0.99382],
8271 [0.99438, 0.43884, 0.99353],
8272 [0.99482, 0.44726, 0.99322],
8273 [0.9951, 0.45569, 0.99291],
8274 [0.99529, 0.46407, 0.99259],
8275 [0.99544, 0.47235, 0.99229],
8276 [0.99558, 0.48052, 0.99201],
8277 [0.99572, 0.48859, 0.99175],
8278 [0.99585, 0.49654, 0.99152],
8279 [0.99597, 0.50442, 0.99132],
8280 [0.99608, 0.51219, 0.99113],
8281 [0.99619, 0.51988, 0.99097],
8282 [0.99629, 0.52749, 0.99084],
8283 [0.99638, 0.53502, 0.99072],
8284 [0.99647, 0.54248, 0.99063],
8285 [0.99655, 0.54987, 0.99057],
8286 [0.99662, 0.55719, 0.99053],
8287 [0.99669, 0.56443, 0.99051],
8288 [0.99675, 0.57162, 0.99052],
8289 [0.9968, 0.57875, 0.99055],
8290 [0.99685, 0.58582, 0.9906],
8291 [0.99689, 0.59284, 0.99068],
8292 [0.99693, 0.5998, 0.99078],
8293 [0.99696, 0.60672, 0.9909],
8294 [0.99698, 0.61357, 0.99105],
8295 [0.997, 0.6204, 0.99122],
8296 [0.99701, 0.62716, 0.99142],
8297 [0.99702, 0.6339, 0.99164],
8298 [0.99702, 0.64058, 0.99189],
8299 [0.99701, 0.64722, 0.99216],
8300 [0.997, 0.65381, 0.99245],
8301 [0.99699, 0.66038, 0.99277],
8302 [0.99697, 0.66692, 0.9931],
8303 [0.99697, 0.67341, 0.99343],
8304 [0.99699, 0.67985, 0.99373],
8305 [0.99703, 0.68627, 0.99402],
8306 [0.99708, 0.69265, 0.99429],
8307 [0.99714, 0.69899, 0.99455],
8308 [0.9972, 0.70531, 0.99479],
8309 [0.99728, 0.7116, 0.99502],
8310 [0.99736, 0.71786, 0.99524],
8311 [0.99745, 0.72409, 0.99544],
8312 [0.99754, 0.7303, 0.99563],
8313 [0.99762, 0.73648, 0.99582],
8314 [0.99771, 0.74266, 0.99599],
8315 [0.9978, 0.7488, 0.99615],
8316 [0.99789, 0.75492, 0.9963],
8317 [0.99798, 0.76103, 0.99645],
8318 [0.99806, 0.76711, 0.99658],
8319 [0.99814, 0.77318, 0.99671],
8320 [0.99821, 0.77923, 0.99682],
8321 [0.99828, 0.78527, 0.99693],
8322 [0.99835, 0.79129, 0.99703],
8323 [0.99841, 0.79729, 0.99712],
8324 [0.99846, 0.80328, 0.9972],
8325 [0.99851, 0.80926, 0.99727],
8326 [0.99854, 0.81522, 0.99734],
8327 [0.99857, 0.82117, 0.9974],
8328 [0.9986, 0.82711, 0.99745],
8329 [0.99861, 0.83304, 0.99749],
8330 [0.99862, 0.83895, 0.99753],
8331 [0.99861, 0.84486, 0.99756],
8332 [0.9986, 0.85075, 0.99758],
8333 [0.99858, 0.85663, 0.9976],
8334 [0.99854, 0.86251, 0.99761],
8335 [0.9985, 0.86838, 0.99761],
8336 [0.99845, 0.87423, 0.9976],
8337 [0.99838, 0.88007, 0.99759],
8338 [0.99831, 0.88591, 0.99757],
8339 [0.99822, 0.89174, 0.99755],
8340 [0.99812, 0.89756, 0.99752],
8341 [0.99801, 0.90339, 0.99748],
8342 [0.99789, 0.90918, 0.99744],
8343 [0.99775, 0.91498, 0.99739],
8344 [0.9976, 0.92077, 0.99733],
8345 ]
8346 b_linear_bmw_5_95_c86 = bokeh_palette('linear_bmw_5_95_c86',linear_bmw_5_95_c86)
8347 m_linear_bmw_5_95_c86 = mpl_cm('linear_bmw_5_95_c86',linear_bmw_5_95_c86)
8348 m_linear_bmw_5_95_c86_r = mpl_cm('linear_bmw_5_95_c86_r',list(reversed(linear_bmw_5_95_c86)))
8349
8350
8351
8352
8353 linear_bmw_5_95_c89 = [\
8354 [0, 0.017709, 0.34641],
8355 [0, 0.020672, 0.3555],
8356 [0, 0.023402, 0.3646],
8357 [0, 0.025899, 0.37376],
8358 [0, 0.028159, 0.38295],
8359 [0, 0.030176, 0.39217],
8360 [0, 0.031948, 0.40143],
8361 [0, 0.03346, 0.41074],
8362 [0, 0.034886, 0.42006],
8363 [0, 0.036005, 0.42943],
8364 [0, 0.037031, 0.43882],
8365 [0, 0.038092, 0.44825],
8366 [0, 0.039171, 0.45769],
8367 [0, 0.04027, 0.46718],
8368 [0, 0.041408, 0.47668],
8369 [0, 0.042463, 0.4862],
8370 [0, 0.043503, 0.49576],
8371 [0, 0.044741, 0.50533],
8372 [0, 0.045774, 0.51494],
8373 [0, 0.047001, 0.52456],
8374 [0, 0.048092, 0.5342],
8375 [0, 0.049352, 0.54387],
8376 [0, 0.050447, 0.55355],
8377 [0, 0.051609, 0.56326],
8378 [0, 0.052795, 0.57298],
8379 [0, 0.054014, 0.58271],
8380 [0, 0.055261, 0.59247],
8381 [0, 0.056563, 0.60223],
8382 [0, 0.057716, 0.61201],
8383 [0, 0.059101, 0.6218],
8384 [0, 0.060386, 0.63161],
8385 [0, 0.061629, 0.64141],
8386 [0, 0.063072, 0.65124],
8387 [0, 0.064391, 0.66106],
8388 [0, 0.065778, 0.6709],
8389 [0, 0.067217, 0.68073],
8390 [0, 0.068717, 0.69056],
8391 [0, 0.070145, 0.7004],
8392 [0, 0.071697, 0.71023],
8393 [0, 0.073287, 0.72005],
8394 [0, 0.074826, 0.72985],
8395 [0, 0.076443, 0.73965],
8396 [0, 0.078139, 0.74942],
8397 [0, 0.079895, 0.75915],
8398 [0, 0.08168, 0.76872],
8399 [0, 0.083307, 0.77811],
8400 [0, 0.084962, 0.78731],
8401 [0, 0.086573, 0.79632],
8402 [0, 0.088156, 0.80515],
8403 [0, 0.089689, 0.81379],
8404 [0, 0.091208, 0.82225],
8405 [0, 0.092616, 0.83051],
8406 [0, 0.09408, 0.83857],
8407 [0, 0.095474, 0.84644],
8408 [0, 0.096762, 0.8541],
8409 [0, 0.098154, 0.86158],
8410 [0, 0.099403, 0.86886],
8411 [0, 0.10065, 0.87593],
8412 [0, 0.10187, 0.88281],
8413 [0, 0.10309, 0.88949],
8414 [0, 0.1042, 0.89597],
8415 [0, 0.10532, 0.90224],
8416 [0, 0.10647, 0.9083],
8417 [0, 0.10749, 0.91415],
8418 [0, 0.10849, 0.9198],
8419 [0, 0.10956, 0.92525],
8420 [0, 0.11052, 0.9305],
8421 [0, 0.11147, 0.93553],
8422 [0, 0.1124, 0.94036],
8423 [0, 0.11331, 0.94497],
8424 [0, 0.11413, 0.94937],
8425 [0, 0.11498, 0.95357],
8426 [0, 0.11585, 0.9576],
8427 [0, 0.11662, 0.96148],
8428 [0, 0.11733, 0.96522],
8429 [0, 0.11806, 0.96883],
8430 [0, 0.11873, 0.97228],
8431 [0, 0.11931, 0.97558],
8432 [0, 0.11987, 0.97874],
8433 [0, 0.12039, 0.98176],
8434 [0, 0.12087, 0.98464],
8435 [0, 0.12132, 0.98737],
8436 [0, 0.12173, 0.98995],
8437 [0.042484, 0.1221, 0.99239],
8438 [0.096239, 0.12243, 0.99468],
8439 [0.13272, 0.12272, 0.99682],
8440 [0.16225, 0.12297, 0.99881],
8441 [0.18788, 0.12318, 1],
8442 [0.21091, 0.12336, 1],
8443 [0.23216, 0.1235, 1],
8444 [0.25202, 0.1236, 1],
8445 [0.27081, 0.12366, 1],
8446 [0.28872, 0.12369, 1],
8447 [0.30596, 0.12367, 1],
8448 [0.32259, 0.12362, 1],
8449 [0.33869, 0.12354, 1],
8450 [0.35436, 0.12342, 1],
8451 [0.36964, 0.12326, 1],
8452 [0.38457, 0.12307, 1],
8453 [0.39919, 0.12286, 1],
8454 [0.41348, 0.12262, 1],
8455 [0.42736, 0.12239, 1],
8456 [0.44084, 0.12216, 1],
8457 [0.454, 0.12195, 1],
8458 [0.46684, 0.12174, 1],
8459 [0.47939, 0.12155, 1],
8460 [0.49169, 0.12136, 1],
8461 [0.50374, 0.12117, 1],
8462 [0.51557, 0.121, 1],
8463 [0.52721, 0.12083, 1],
8464 [0.53866, 0.12067, 1],
8465 [0.54992, 0.12051, 1],
8466 [0.56102, 0.12037, 1],
8467 [0.57198, 0.12022, 1],
8468 [0.58279, 0.12009, 1],
8469 [0.59347, 0.11996, 1],
8470 [0.60403, 0.11983, 1],
8471 [0.61446, 0.11971, 1],
8472 [0.62479, 0.11959, 1],
8473 [0.63501, 0.11948, 1],
8474 [0.64513, 0.11938, 1],
8475 [0.65516, 0.11927, 1],
8476 [0.66511, 0.11918, 1],
8477 [0.67497, 0.11908, 1],
8478 [0.68475, 0.11899, 1],
8479 [0.69445, 0.1189, 1],
8480 [0.7041, 0.11881, 1],
8481 [0.71366, 0.11873, 1],
8482 [0.72312, 0.11873, 1],
8483 [0.73244, 0.11896, 1],
8484 [0.74156, 0.11949, 1],
8485 [0.75051, 0.12036, 1],
8486 [0.75927, 0.12156, 1],
8487 [0.76785, 0.12312, 1],
8488 [0.77627, 0.12504, 1],
8489 [0.78452, 0.12724, 1],
8490 [0.79261, 0.12981, 1],
8491 [0.80054, 0.13262, 1],
8492 [0.80832, 0.1357, 1],
8493 [0.81594, 0.1391, 1],
8494 [0.82341, 0.14279, 1],
8495 [0.83074, 0.14669, 1],
8496 [0.83791, 0.15087, 1],
8497 [0.84494, 0.15527, 1],
8498 [0.85183, 0.15984, 1],
8499 [0.85859, 0.16467, 1],
8500 [0.8652, 0.16967, 1],
8501 [0.87169, 0.17481, 1],
8502 [0.87803, 0.1801, 1],
8503 [0.88424, 0.18562, 1],
8504 [0.89031, 0.1912, 1],
8505 [0.89626, 0.19697, 1],
8506 [0.90207, 0.20282, 1],
8507 [0.90776, 0.2088, 1],
8508 [0.91332, 0.21488, 1],
8509 [0.91875, 0.22109, 1],
8510 [0.92405, 0.22737, 1],
8511 [0.92919, 0.23379, 1],
8512 [0.93415, 0.24041, 1],
8513 [0.93894, 0.2472, 1],
8514 [0.94355, 0.25413, 1],
8515 [0.94798, 0.26118, 1],
8516 [0.95224, 0.26837, 1],
8517 [0.95633, 0.2757, 1],
8518 [0.96024, 0.28311, 1],
8519 [0.96396, 0.29064, 1],
8520 [0.96751, 0.29827, 1],
8521 [0.97089, 0.30602, 1],
8522 [0.97409, 0.31382, 1],
8523 [0.97712, 0.3217, 1],
8524 [0.97997, 0.32968, 1],
8525 [0.98265, 0.33769, 1],
8526 [0.98515, 0.34577, 1],
8527 [0.98746, 0.35394, 1],
8528 [0.9896, 0.36216, 1],
8529 [0.99155, 0.37042, 1],
8530 [0.99333, 0.37874, 1],
8531 [0.99493, 0.3871, 1],
8532 [0.99635, 0.39551, 1],
8533 [0.9976, 0.40394, 1],
8534 [0.99866, 0.41243, 1],
8535 [0.99953, 0.42094, 1],
8536 [1, 0.4295, 1],
8537 [1, 0.43809, 1],
8538 [1, 0.44668, 1],
8539 [1, 0.45524, 1],
8540 [1, 0.46369, 1],
8541 [1, 0.47203, 1],
8542 [1, 0.48024, 1],
8543 [1, 0.48835, 1],
8544 [1, 0.49634, 1],
8545 [1, 0.50426, 1],
8546 [1, 0.51206, 1],
8547 [1, 0.51978, 1],
8548 [1, 0.52742, 1],
8549 [1, 0.53498, 1],
8550 [1, 0.54247, 1],
8551 [1, 0.54988, 1],
8552 [1, 0.55722, 1],
8553 [1, 0.56449, 1],
8554 [1, 0.57169, 1],
8555 [1, 0.57884, 1],
8556 [1, 0.58594, 1],
8557 [1, 0.59297, 1],
8558 [1, 0.59995, 1],
8559 [1, 0.60688, 1],
8560 [1, 0.61374, 1],
8561 [1, 0.62058, 1],
8562 [1, 0.62736, 1],
8563 [1, 0.6341, 1],
8564 [1, 0.64079, 1],
8565 [1, 0.64743, 1],
8566 [1, 0.65405, 1],
8567 [1, 0.66063, 1],
8568 [1, 0.66718, 1],
8569 [1, 0.6737, 1],
8570 [1, 0.68019, 1],
8571 [1, 0.68667, 1],
8572 [1, 0.69312, 1],
8573 [1, 0.69954, 1],
8574 [1, 0.70595, 1],
8575 [1, 0.71233, 1],
8576 [1, 0.71869, 1],
8577 [1, 0.72504, 1],
8578 [1, 0.73136, 1],
8579 [1, 0.73767, 1],
8580 [1, 0.74396, 1],
8581 [1, 0.75023, 1],
8582 [1, 0.75649, 1],
8583 [1, 0.76273, 1],
8584 [1, 0.76895, 1],
8585 [1, 0.77517, 1],
8586 [1, 0.78137, 1],
8587 [1, 0.78755, 1],
8588 [1, 0.79372, 1],
8589 [1, 0.79988, 1],
8590 [1, 0.80602, 1],
8591 [1, 0.81215, 1],
8592 [1, 0.81826, 1],
8593 [1, 0.82437, 1],
8594 [1, 0.83047, 1],
8595 [1, 0.83656, 1],
8596 [1, 0.84263, 1],
8597 [1, 0.84869, 1],
8598 [1, 0.85475, 1],
8599 [1, 0.86079, 1],
8600 [1, 0.86683, 1],
8601 [1, 0.87286, 0.99978],
8602 [1, 0.87887, 0.9995],
8603 [1, 0.88488, 0.99921],
8604 [1, 0.89088, 0.99892],
8605 [0.99975, 0.89688, 0.99861],
8606 [0.99925, 0.90287, 0.9983],
8607 [0.99872, 0.90884, 0.99799],
8608 [0.99817, 0.91481, 0.99766],
8609 [0.9976, 0.92077, 0.99733],
8610 ]
8611 b_linear_bmw_5_95_c89 = bokeh_palette('linear_bmw_5_95_c89',linear_bmw_5_95_c89)
8612 m_linear_bmw_5_95_c89 = mpl_cm('linear_bmw_5_95_c89',linear_bmw_5_95_c89)
8613 m_linear_bmw_5_95_c89_r = mpl_cm('linear_bmw_5_95_c89_r',list(reversed(linear_bmw_5_95_c89)))
8614 bmw = b_linear_bmw_5_95_c89
8615 m_bmw = m_linear_bmw_5_95_c89
8616 m_bmw_r = m_linear_bmw_5_95_c89_r
8617 palette['bmw'] = b_linear_bmw_5_95_c89
8618 cm['bmw'] = m_linear_bmw_5_95_c89
8619 cm['bmw_r'] = m_linear_bmw_5_95_c89_r
8620 register_cmap('cet_bmw',m_linear_bmw_5_95_c89)
8621 register_cmap('cet_bmw_r',m_linear_bmw_5_95_c89_r)
8622
8623
8624
8625
8626 linear_bmy_10_95_c71 = [\
8627 [0.0018068, 0.058001, 0.36399],
8628 [0.0024107, 0.059964, 0.37048],
8629 [0.0031987, 0.061692, 0.37697],
8630 [0.0042843, 0.063571, 0.38341],
8631 [0.0057638, 0.065341, 0.38979],
8632 [0.0075093, 0.067136, 0.39617],
8633 [0.0097084, 0.068953, 0.40248],
8634 [0.012532, 0.070615, 0.40875],
8635 [0.0155, 0.07232, 0.41499],
8636 [0.019067, 0.074062, 0.42116],
8637 [0.023134, 0.075673, 0.42729],
8638 [0.027668, 0.077301, 0.43336],
8639 [0.032903, 0.078925, 0.43937],
8640 [0.038954, 0.080546, 0.44532],
8641 [0.045181, 0.082169, 0.45122],
8642 [0.051521, 0.083668, 0.45704],
8643 [0.058053, 0.085134, 0.46278],
8644 [0.06473, 0.086625, 0.46847],
8645 [0.071444, 0.088071, 0.47409],
8646 [0.078236, 0.089456, 0.4796],
8647 [0.085243, 0.090814, 0.48502],
8648 [0.092333, 0.092133, 0.49038],
8649 [0.099463, 0.093353, 0.49564],
8650 [0.10684, 0.094646, 0.50078],
8651 [0.11423, 0.095771, 0.50581],
8652 [0.12178, 0.096854, 0.51075],
8653 [0.12948, 0.097993, 0.51558],
8654 [0.13728, 0.098973, 0.52029],
8655 [0.14525, 0.099911, 0.52487],
8656 [0.1533, 0.10078, 0.5293],
8657 [0.16159, 0.10159, 0.53358],
8658 [0.16995, 0.10233, 0.53773],
8659 [0.17849, 0.103, 0.5417],
8660 [0.18715, 0.10358, 0.54552],
8661 [0.19599, 0.10402, 0.54915],
8662 [0.20499, 0.10436, 0.55259],
8663 [0.21418, 0.10461, 0.55582],
8664 [0.22355, 0.10475, 0.55884],
8665 [0.2331, 0.10475, 0.56162],
8666 [0.24286, 0.10462, 0.56415],
8667 [0.25285, 0.10434, 0.5664],
8668 [0.26305, 0.10391, 0.56836],
8669 [0.27348, 0.10327, 0.57],
8670 [0.28411, 0.10237, 0.5713],
8671 [0.29502, 0.10125, 0.57224],
8672 [0.30619, 0.099883, 0.57281],
8673 [0.31733, 0.098383, 0.57312],
8674 [0.32829, 0.096731, 0.57334],
8675 [0.33902, 0.095191, 0.57351],
8676 [0.34952, 0.093473, 0.57361],
8677 [0.35984, 0.09185, 0.57367],
8678 [0.36998, 0.090102, 0.57366],
8679 [0.37996, 0.088354, 0.5736],
8680 [0.38979, 0.086567, 0.57349],
8681 [0.39947, 0.084774, 0.57331],
8682 [0.40903, 0.082914, 0.57309],
8683 [0.41845, 0.081085, 0.5728],
8684 [0.42777, 0.079164, 0.57245],
8685 [0.43696, 0.077258, 0.57205],
8686 [0.44604, 0.075373, 0.57159],
8687 [0.45505, 0.073529, 0.57107],
8688 [0.46394, 0.071572, 0.57049],
8689 [0.47273, 0.069648, 0.56986],
8690 [0.48145, 0.067661, 0.56917],
8691 [0.49008, 0.06569, 0.56843],
8692 [0.49863, 0.063767, 0.56763],
8693 [0.5071, 0.061792, 0.56677],
8694 [0.51549, 0.059971, 0.56585],
8695 [0.52382, 0.057948, 0.56487],
8696 [0.53207, 0.056175, 0.56385],
8697 [0.54025, 0.054286, 0.56276],
8698 [0.54838, 0.052493, 0.5616],
8699 [0.55642, 0.05079, 0.5604],
8700 [0.56441, 0.049208, 0.55913],
8701 [0.57234, 0.04752, 0.55781],
8702 [0.58021, 0.045977, 0.55643],
8703 [0.588, 0.044652, 0.55502],
8704 [0.59575, 0.043191, 0.55358],
8705 [0.60343, 0.042094, 0.55214],
8706 [0.61104, 0.040933, 0.55067],
8707 [0.6186, 0.039904, 0.5492],
8708 [0.62609, 0.039006, 0.5477],
8709 [0.63354, 0.038249, 0.5462],
8710 [0.64092, 0.037647, 0.54466],
8711 [0.64826, 0.037202, 0.54313],
8712 [0.65554, 0.036908, 0.54156],
8713 [0.66278, 0.036776, 0.53999],
8714 [0.66996, 0.036816, 0.53841],
8715 [0.6771, 0.037039, 0.53681],
8716 [0.68417, 0.037443, 0.53518],
8717 [0.69122, 0.038023, 0.53354],
8718 [0.69821, 0.038789, 0.53189],
8719 [0.70517, 0.039756, 0.53022],
8720 [0.71207, 0.040926, 0.52854],
8721 [0.71894, 0.042269, 0.52684],
8722 [0.72576, 0.043681, 0.52511],
8723 [0.73255, 0.045402, 0.52338],
8724 [0.73929, 0.047268, 0.52162],
8725 [0.74598, 0.049331, 0.51985],
8726 [0.75264, 0.051385, 0.51807],
8727 [0.75926, 0.053656, 0.51626],
8728 [0.76585, 0.056145, 0.51445],
8729 [0.77239, 0.058663, 0.5126],
8730 [0.7789, 0.061273, 0.51075],
8731 [0.78537, 0.064105, 0.50888],
8732 [0.79179, 0.067003, 0.50698],
8733 [0.79815, 0.07017, 0.50503],
8734 [0.8044, 0.073831, 0.503],
8735 [0.81054, 0.077734, 0.50091],
8736 [0.81658, 0.082182, 0.49873],
8737 [0.82251, 0.086838, 0.49646],
8738 [0.82832, 0.09184, 0.49413],
8739 [0.83402, 0.097033, 0.49171],
8740 [0.83961, 0.10255, 0.48919],
8741 [0.8451, 0.10821, 0.48661],
8742 [0.85047, 0.1141, 0.48394],
8743 [0.85573, 0.12016, 0.48118],
8744 [0.86088, 0.12639, 0.47835],
8745 [0.86592, 0.13272, 0.47543],
8746 [0.87085, 0.13913, 0.47242],
8747 [0.87567, 0.14574, 0.46934],
8748 [0.88036, 0.15236, 0.46614],
8749 [0.88495, 0.15912, 0.46287],
8750 [0.88942, 0.16592, 0.45953],
8751 [0.89379, 0.17282, 0.45608],
8752 [0.89803, 0.17978, 0.45256],
8753 [0.90216, 0.18681, 0.44893],
8754 [0.90617, 0.1939, 0.44521],
8755 [0.91008, 0.20098, 0.44141],
8756 [0.91386, 0.20817, 0.43752],
8757 [0.91752, 0.21538, 0.43351],
8758 [0.92106, 0.22265, 0.42942],
8759 [0.92449, 0.22991, 0.42524],
8760 [0.9278, 0.23727, 0.42094],
8761 [0.93099, 0.24459, 0.41657],
8762 [0.93405, 0.252, 0.41209],
8763 [0.93701, 0.25939, 0.4076],
8764 [0.93986, 0.26675, 0.40316],
8765 [0.9426, 0.27411, 0.39879],
8766 [0.94522, 0.28144, 0.39449],
8767 [0.94774, 0.28878, 0.39026],
8768 [0.95015, 0.29609, 0.3861],
8769 [0.95245, 0.30338, 0.382],
8770 [0.95466, 0.31069, 0.37798],
8771 [0.95674, 0.31797, 0.37403],
8772 [0.95873, 0.32523, 0.37012],
8773 [0.96061, 0.33251, 0.36631],
8774 [0.96239, 0.33976, 0.36253],
8775 [0.96406, 0.34701, 0.35883],
8776 [0.96562, 0.35425, 0.35522],
8777 [0.96708, 0.36148, 0.35164],
8778 [0.96843, 0.36871, 0.34814],
8779 [0.96968, 0.37593, 0.3447],
8780 [0.97082, 0.38315, 0.34134],
8781 [0.97186, 0.39036, 0.33803],
8782 [0.9728, 0.39757, 0.33481],
8783 [0.97362, 0.40476, 0.33161],
8784 [0.97434, 0.41197, 0.32852],
8785 [0.97495, 0.41917, 0.32547],
8786 [0.97546, 0.42636, 0.32252],
8787 [0.97586, 0.43355, 0.31962],
8788 [0.97615, 0.44074, 0.31678],
8789 [0.97634, 0.44792, 0.31402],
8790 [0.97641, 0.45512, 0.31133],
8791 [0.97637, 0.46229, 0.30872],
8792 [0.97624, 0.46947, 0.30617],
8793 [0.97607, 0.47658, 0.30363],
8794 [0.97591, 0.4836, 0.30112],
8795 [0.97579, 0.49054, 0.29861],
8796 [0.97569, 0.49738, 0.2961],
8797 [0.97563, 0.50413, 0.29358],
8798 [0.97559, 0.5108, 0.29108],
8799 [0.97559, 0.51739, 0.28856],
8800 [0.97562, 0.5239, 0.28603],
8801 [0.97568, 0.53035, 0.28352],
8802 [0.97578, 0.53672, 0.28099],
8803 [0.9759, 0.54302, 0.27848],
8804 [0.97607, 0.54926, 0.27597],
8805 [0.97626, 0.55543, 0.27343],
8806 [0.97649, 0.56155, 0.2709],
8807 [0.97675, 0.56761, 0.26835],
8808 [0.97705, 0.57361, 0.26582],
8809 [0.97738, 0.57956, 0.26328],
8810 [0.97775, 0.58545, 0.26073],
8811 [0.97815, 0.59129, 0.25816],
8812 [0.97859, 0.59708, 0.25562],
8813 [0.97907, 0.60282, 0.25307],
8814 [0.97958, 0.60852, 0.25049],
8815 [0.98013, 0.61416, 0.24794],
8816 [0.98072, 0.61978, 0.24534],
8817 [0.98135, 0.62534, 0.24277],
8818 [0.98202, 0.63087, 0.24018],
8819 [0.98273, 0.63635, 0.23762],
8820 [0.98347, 0.64177, 0.23503],
8821 [0.98425, 0.64718, 0.23241],
8822 [0.98507, 0.65256, 0.22982],
8823 [0.98586, 0.65793, 0.22748],
8824 [0.98656, 0.66331, 0.22545],
8825 [0.98719, 0.6687, 0.22375],
8826 [0.98774, 0.6741, 0.22234],
8827 [0.98823, 0.67951, 0.22119],
8828 [0.98867, 0.68493, 0.22026],
8829 [0.98906, 0.69035, 0.21952],
8830 [0.98939, 0.69578, 0.21896],
8831 [0.98968, 0.7012, 0.2186],
8832 [0.98992, 0.70664, 0.2184],
8833 [0.99012, 0.71207, 0.21835],
8834 [0.99028, 0.7175, 0.21841],
8835 [0.9904, 0.72292, 0.21862],
8836 [0.99048, 0.72836, 0.21896],
8837 [0.99054, 0.73379, 0.2194],
8838 [0.99055, 0.73922, 0.21995],
8839 [0.99053, 0.74463, 0.22062],
8840 [0.99048, 0.75005, 0.22135],
8841 [0.9904, 0.75548, 0.22218],
8842 [0.99028, 0.7609, 0.22313],
8843 [0.99014, 0.76631, 0.22411],
8844 [0.98996, 0.77172, 0.22522],
8845 [0.98976, 0.77714, 0.22642],
8846 [0.98952, 0.78254, 0.22765],
8847 [0.98925, 0.78794, 0.22898],
8848 [0.98896, 0.79335, 0.23033],
8849 [0.98863, 0.79874, 0.23182],
8850 [0.98828, 0.80414, 0.2333],
8851 [0.9879, 0.80953, 0.23491],
8852 [0.98749, 0.81492, 0.23654],
8853 [0.98705, 0.82031, 0.23821],
8854 [0.98658, 0.82569, 0.23995],
8855 [0.98608, 0.83108, 0.24175],
8856 [0.98556, 0.83646, 0.24358],
8857 [0.98501, 0.84184, 0.24547],
8858 [0.98443, 0.84721, 0.24743],
8859 [0.98382, 0.85258, 0.2494],
8860 [0.98318, 0.85795, 0.25145],
8861 [0.98251, 0.86332, 0.25351],
8862 [0.98182, 0.86869, 0.25562],
8863 [0.98109, 0.87405, 0.25776],
8864 [0.98034, 0.87941, 0.25997],
8865 [0.97957, 0.88477, 0.26219],
8866 [0.97875, 0.89012, 0.26445],
8867 [0.97792, 0.89548, 0.26675],
8868 [0.97705, 0.90083, 0.26909],
8869 [0.97615, 0.90619, 0.27144],
8870 [0.97523, 0.91153, 0.27384],
8871 [0.97428, 0.91688, 0.27628],
8872 [0.9733, 0.92223, 0.27873],
8873 [0.97229, 0.92756, 0.2812],
8874 [0.97124, 0.93291, 0.28373],
8875 [0.97017, 0.93825, 0.28625],
8876 [0.96907, 0.94359, 0.28885],
8877 [0.96794, 0.94893, 0.29144],
8878 [0.96677, 0.95427, 0.29405],
8879 [0.96558, 0.9596, 0.29671],
8880 [0.96436, 0.96493, 0.29938],
8881 [0.9631, 0.97026, 0.30206],
8882 [0.96182, 0.97559, 0.30477],
8883 ]
8884 b_linear_bmy_10_95_c71 = bokeh_palette('linear_bmy_10_95_c71',linear_bmy_10_95_c71)
8885 m_linear_bmy_10_95_c71 = mpl_cm('linear_bmy_10_95_c71',linear_bmy_10_95_c71)
8886 m_linear_bmy_10_95_c71_r = mpl_cm('linear_bmy_10_95_c71_r',list(reversed(linear_bmy_10_95_c71)))
8887
8888
8889
8890
8891 linear_bmy_10_95_c78 = [\
8892 [0, 0.047803, 0.4883],
8893 [0, 0.049705, 0.49553],
8894 [0, 0.051451, 0.50272],
8895 [0, 0.053214, 0.50983],
8896 [0, 0.054977, 0.51684],
8897 [0, 0.056756, 0.52379],
8898 [0, 0.058368, 0.53062],
8899 [0, 0.060099, 0.53736],
8900 [0, 0.061618, 0.54402],
8901 [0, 0.063279, 0.55055],
8902 [0, 0.06478, 0.55698],
8903 [0, 0.066288, 0.56332],
8904 [0, 0.067769, 0.5695],
8905 [0, 0.069247, 0.57558],
8906 [0, 0.070546, 0.58154],
8907 [0, 0.071898, 0.58736],
8908 [0, 0.073227, 0.59303],
8909 [0, 0.074425, 0.59856],
8910 [0, 0.075597, 0.60398],
8911 [0, 0.076712, 0.60919],
8912 [0, 0.077789, 0.61423],
8913 [0, 0.078828, 0.61913],
8914 [0, 0.079825, 0.62386],
8915 [0, 0.080751, 0.62837],
8916 [0, 0.081634, 0.63267],
8917 [0, 0.082399, 0.63679],
8918 [0, 0.083056, 0.64069],
8919 [0, 0.083728, 0.64438],
8920 [0, 0.084298, 0.64781],
8921 [0, 0.084735, 0.65098],
8922 [0, 0.085075, 0.65389],
8923 [0, 0.085333, 0.65653],
8924 [0, 0.085503, 0.65887],
8925 [0, 0.085575, 0.66091],
8926 [0, 0.085538, 0.66263],
8927 [0, 0.085387, 0.664],
8928 [0.041146, 0.085117, 0.66498],
8929 [0.082348, 0.084719, 0.66559],
8930 [0.11295, 0.084153, 0.66576],
8931 [0.13887, 0.083348, 0.66549],
8932 [0.16224, 0.08245, 0.66472],
8933 [0.18389, 0.081312, 0.66345],
8934 [0.20444, 0.079918, 0.6616],
8935 [0.2241, 0.078308, 0.65916],
8936 [0.24323, 0.076464, 0.65608],
8937 [0.26189, 0.074387, 0.65234],
8938 [0.27969, 0.072084, 0.64827],
8939 [0.29634, 0.069818, 0.64421],
8940 [0.31196, 0.067486, 0.64024],
8941 [0.32675, 0.065157, 0.63634],
8942 [0.34081, 0.062906, 0.63252],
8943 [0.35421, 0.060546, 0.6288],
8944 [0.36705, 0.058179, 0.62515],
8945 [0.3794, 0.055931, 0.62158],
8946 [0.39131, 0.05356, 0.6181],
8947 [0.40281, 0.051267, 0.6147],
8948 [0.41397, 0.049057, 0.6114],
8949 [0.42479, 0.046684, 0.60817],
8950 [0.43533, 0.044376, 0.60501],
8951 [0.44558, 0.042108, 0.60193],
8952 [0.4556, 0.039763, 0.59895],
8953 [0.46537, 0.037486, 0.59604],
8954 [0.47496, 0.035294, 0.59322],
8955 [0.48432, 0.032963, 0.59047],
8956 [0.49352, 0.030903, 0.5878],
8957 [0.50254, 0.028926, 0.58523],
8958 [0.5114, 0.027022, 0.58272],
8959 [0.52012, 0.025191, 0.5803],
8960 [0.52872, 0.02343, 0.57794],
8961 [0.53717, 0.021744, 0.57569],
8962 [0.54549, 0.020131, 0.57351],
8963 [0.5537, 0.018589, 0.5714],
8964 [0.56182, 0.017116, 0.56937],
8965 [0.56982, 0.015713, 0.56743],
8966 [0.57772, 0.014383, 0.56556],
8967 [0.58556, 0.013108, 0.56378],
8968 [0.59331, 0.011906, 0.56202],
8969 [0.60102, 0.010448, 0.56026],
8970 [0.60871, 0.0092728, 0.55849],
8971 [0.61634, 0.0080608, 0.55673],
8972 [0.62394, 0.0068636, 0.55496],
8973 [0.6315, 0.0056715, 0.55317],
8974 [0.63904, 0.0044851, 0.5514],
8975 [0.64654, 0.0033027, 0.5496],
8976 [0.65401, 0.0021237, 0.54781],
8977 [0.66146, 0.00094944, 0.54601],
8978 [0.66888, 0, 0.54419],
8979 [0.67628, 0, 0.54238],
8980 [0.68364, 0, 0.54055],
8981 [0.69099, 0, 0.53873],
8982 [0.69832, 0, 0.53689],
8983 [0.70562, 0, 0.53504],
8984 [0.71291, 0, 0.53319],
8985 [0.72018, 0, 0.53134],
8986 [0.72742, 0, 0.52948],
8987 [0.73466, 0, 0.52761],
8988 [0.74187, 0, 0.52573],
8989 [0.74906, 0, 0.52385],
8990 [0.75625, 0, 0.52195],
8991 [0.76342, 0, 0.52005],
8992 [0.77058, 0, 0.51816],
8993 [0.77773, 0, 0.51624],
8994 [0.78486, 0, 0.51433],
8995 [0.79198, 0, 0.51239],
8996 [0.79909, 0, 0.51046],
8997 [0.80618, 0, 0.50853],
8998 [0.81322, 0, 0.50656],
8999 [0.82017, 0, 0.50459],
9000 [0.82703, 0, 0.50258],
9001 [0.83381, 0, 0.50056],
9002 [0.84048, 0, 0.49853],
9003 [0.84706, 0, 0.49645],
9004 [0.85355, 0, 0.49437],
9005 [0.85996, 0, 0.49225],
9006 [0.86628, 0, 0.49011],
9007 [0.8725, 0, 0.48796],
9008 [0.87863, 0.0025964, 0.48577],
9009 [0.88468, 0.0090591, 0.48356],
9010 [0.89063, 0.016464, 0.48133],
9011 [0.8965, 0.024452, 0.47908],
9012 [0.90228, 0.033265, 0.47679],
9013 [0.90796, 0.042948, 0.47449],
9014 [0.91356, 0.052352, 0.47216],
9015 [0.91907, 0.061335, 0.4698],
9016 [0.92449, 0.070106, 0.46741],
9017 [0.92982, 0.07857, 0.46499],
9018 [0.93506, 0.086993, 0.46255],
9019 [0.94022, 0.095176, 0.46008],
9020 [0.94529, 0.10322, 0.45759],
9021 [0.95027, 0.11119, 0.45507],
9022 [0.95516, 0.11907, 0.45252],
9023 [0.95996, 0.12687, 0.44993],
9024 [0.96467, 0.13467, 0.44731],
9025 [0.9693, 0.14235, 0.44468],
9026 [0.97383, 0.15004, 0.44201],
9027 [0.97827, 0.15766, 0.43929],
9028 [0.9826, 0.16532, 0.43656],
9029 [0.9868, 0.17308, 0.4338],
9030 [0.99086, 0.18089, 0.43103],
9031 [0.99477, 0.18882, 0.42822],
9032 [0.99854, 0.19681, 0.42539],
9033 [1, 0.20481, 0.42252],
9034 [1, 0.21285, 0.41965],
9035 [1, 0.22099, 0.41674],
9036 [1, 0.22914, 0.4138],
9037 [1, 0.23736, 0.41083],
9038 [1, 0.24555, 0.40783],
9039 [1, 0.25382, 0.4048],
9040 [1, 0.2621, 0.40173],
9041 [1, 0.27043, 0.39864],
9042 [1, 0.27875, 0.39552],
9043 [1, 0.28708, 0.39235],
9044 [1, 0.29545, 0.38916],
9045 [1, 0.30385, 0.38591],
9046 [1, 0.31225, 0.38264],
9047 [1, 0.3207, 0.37933],
9048 [1, 0.32913, 0.37598],
9049 [1, 0.33756, 0.37257],
9050 [1, 0.34602, 0.36914],
9051 [1, 0.35451, 0.36565],
9052 [1, 0.36297, 0.36212],
9053 [1, 0.37145, 0.35853],
9054 [1, 0.37995, 0.35492],
9055 [1, 0.38846, 0.35122],
9056 [1, 0.39696, 0.34749],
9057 [1, 0.40547, 0.34369],
9058 [1, 0.4139, 0.33986],
9059 [1, 0.4222, 0.33597],
9060 [1, 0.4304, 0.33207],
9061 [1, 0.43847, 0.3281],
9062 [1, 0.44643, 0.3241],
9063 [1, 0.45429, 0.32007],
9064 [1, 0.46204, 0.31598],
9065 [1, 0.46971, 0.31182],
9066 [1, 0.47727, 0.30763],
9067 [1, 0.48476, 0.30339],
9068 [1, 0.49217, 0.2991],
9069 [1, 0.4995, 0.29473],
9070 [1, 0.50677, 0.2903],
9071 [1, 0.51397, 0.28581],
9072 [1, 0.5211, 0.28126],
9073 [1, 0.52816, 0.27665],
9074 [1, 0.53517, 0.27191],
9075 [1, 0.54212, 0.26713],
9076 [1, 0.54902, 0.26226],
9077 [1, 0.55585, 0.2573],
9078 [1, 0.56265, 0.25223],
9079 [1, 0.56938, 0.24705],
9080 [1, 0.57609, 0.24177],
9081 [1, 0.58273, 0.23637],
9082 [1, 0.58934, 0.23082],
9083 [1, 0.59591, 0.22513],
9084 [1, 0.60244, 0.21933],
9085 [1, 0.60893, 0.21333],
9086 [1, 0.61536, 0.20719],
9087 [1, 0.62179, 0.20085],
9088 [1, 0.62814, 0.19473],
9089 [1, 0.63438, 0.18898],
9090 [1, 0.64052, 0.18363],
9091 [1, 0.64658, 0.17866],
9092 [1, 0.65258, 0.17395],
9093 [1, 0.65851, 0.16956],
9094 [1, 0.66439, 0.16532],
9095 [1, 0.67023, 0.1614],
9096 [1, 0.67601, 0.15763],
9097 [1, 0.68174, 0.1541],
9098 [1, 0.68745, 0.15075],
9099 [1, 0.69312, 0.14754],
9100 [1, 0.69875, 0.14449],
9101 [1, 0.70435, 0.14163],
9102 [1, 0.70993, 0.13886],
9103 [1, 0.71548, 0.13623],
9104 [1, 0.72099, 0.13382],
9105 [1, 0.72649, 0.1315],
9106 [1, 0.73197, 0.12928],
9107 [1, 0.73742, 0.12722],
9108 [1, 0.74286, 0.1253],
9109 [1, 0.74827, 0.12347],
9110 [1, 0.75367, 0.1218],
9111 [1, 0.75905, 0.12025],
9112 [1, 0.76442, 0.11888],
9113 [1, 0.76976, 0.11751],
9114 [1, 0.7751, 0.11639],
9115 [1, 0.78042, 0.11528],
9116 [1, 0.78573, 0.11434],
9117 [1, 0.79102, 0.11357],
9118 [1, 0.79631, 0.11289],
9119 [1, 0.80158, 0.1123],
9120 [1, 0.80685, 0.11183],
9121 [1, 0.81209, 0.1115],
9122 [1, 0.81733, 0.11127],
9123 [1, 0.82257, 0.11116],
9124 [1, 0.82778, 0.11116],
9125 [1, 0.833, 0.11128],
9126 [1, 0.8382, 0.1115],
9127 [1, 0.8434, 0.11183],
9128 [1, 0.84859, 0.11227],
9129 [1, 0.85377, 0.11282],
9130 [1, 0.85894, 0.11347],
9131 [1, 0.86412, 0.11414],
9132 [1, 0.86928, 0.115],
9133 [1, 0.87443, 0.11595],
9134 [1, 0.87958, 0.11697],
9135 [1, 0.88472, 0.11809],
9136 [1, 0.88986, 0.11929],
9137 [1, 0.89499, 0.12054],
9138 [1, 0.90012, 0.1219],
9139 [1, 0.90524, 0.12335],
9140 [1, 0.91036, 0.12486],
9141 [1, 0.91547, 0.12649],
9142 [1, 0.92058, 0.12812],
9143 [1, 0.92569, 0.1299],
9144 [1, 0.93079, 0.13165],
9145 [1, 0.93588, 0.13349],
9146 [1, 0.94097, 0.13541],
9147 [1, 0.94606, 0.13735],
9148 ]
9149 b_linear_bmy_10_95_c78 = bokeh_palette('linear_bmy_10_95_c78',linear_bmy_10_95_c78)
9150 m_linear_bmy_10_95_c78 = mpl_cm('linear_bmy_10_95_c78',linear_bmy_10_95_c78)
9151 m_linear_bmy_10_95_c78_r = mpl_cm('linear_bmy_10_95_c78_r',list(reversed(linear_bmy_10_95_c78)))
9152 inferno = b_linear_bmy_10_95_c78
9153 m_inferno = m_linear_bmy_10_95_c78
9154 m_inferno_r = m_linear_bmy_10_95_c78_r
9155 palette['inferno'] = b_linear_bmy_10_95_c78
9156 cm['inferno'] = m_linear_bmy_10_95_c78
9157 cm['inferno_r'] = m_linear_bmy_10_95_c78_r
9158 register_cmap('cet_inferno',m_linear_bmy_10_95_c78)
9159 register_cmap('cet_inferno_r',m_linear_bmy_10_95_c78_r)
9160
9161
9162
9163
9164 linear_gow_60_85_c27 = [\
9165 [0.39872, 0.60624, 0.56451],
9166 [0.40156, 0.60721, 0.56266],
9167 [0.4044, 0.60816, 0.5608],
9168 [0.40724, 0.60911, 0.55895],
9169 [0.41009, 0.61005, 0.55712],
9170 [0.41293, 0.61099, 0.55528],
9171 [0.41577, 0.61192, 0.55344],
9172 [0.41863, 0.61285, 0.55162],
9173 [0.42148, 0.61378, 0.5498],
9174 [0.42435, 0.6147, 0.54798],
9175 [0.42723, 0.61561, 0.54618],
9176 [0.4301, 0.61653, 0.54436],
9177 [0.43298, 0.61743, 0.54256],
9178 [0.43588, 0.61833, 0.54076],
9179 [0.43876, 0.61923, 0.53897],
9180 [0.44169, 0.62012, 0.53719],
9181 [0.44461, 0.621, 0.5354],
9182 [0.44752, 0.62186, 0.53362],
9183 [0.45047, 0.62274, 0.53186],
9184 [0.45342, 0.62361, 0.5301],
9185 [0.45639, 0.62446, 0.52835],
9186 [0.45937, 0.62531, 0.5266],
9187 [0.46235, 0.62615, 0.52485],
9188 [0.46536, 0.62698, 0.52312],
9189 [0.46838, 0.62781, 0.52138],
9190 [0.47142, 0.62864, 0.51966],
9191 [0.47447, 0.62944, 0.51795],
9192 [0.47754, 0.63025, 0.51623],
9193 [0.48061, 0.63105, 0.51454],
9194 [0.48372, 0.63184, 0.51285],
9195 [0.48685, 0.63262, 0.51116],
9196 [0.48999, 0.63339, 0.50949],
9197 [0.49314, 0.63416, 0.50783],
9198 [0.49633, 0.63491, 0.50616],
9199 [0.49954, 0.63565, 0.50452],
9200 [0.50277, 0.63639, 0.50287],
9201 [0.50602, 0.63711, 0.50125],
9202 [0.50931, 0.63782, 0.49961],
9203 [0.51261, 0.63852, 0.49802],
9204 [0.51594, 0.63922, 0.4964],
9205 [0.5193, 0.6399, 0.49483],
9206 [0.52268, 0.64057, 0.49323],
9207 [0.5261, 0.64122, 0.49168],
9208 [0.52955, 0.64187, 0.49012],
9209 [0.53302, 0.6425, 0.48858],
9210 [0.53654, 0.64312, 0.48705],
9211 [0.54007, 0.64372, 0.48552],
9212 [0.54365, 0.64431, 0.48402],
9213 [0.54726, 0.64489, 0.48253],
9214 [0.55092, 0.64545, 0.48105],
9215 [0.55461, 0.64599, 0.4796],
9216 [0.55833, 0.64652, 0.47815],
9217 [0.56212, 0.64704, 0.47672],
9218 [0.56592, 0.64753, 0.47532],
9219 [0.56978, 0.648, 0.47391],
9220 [0.57369, 0.64846, 0.47253],
9221 [0.57764, 0.6489, 0.47118],
9222 [0.58164, 0.64932, 0.46984],
9223 [0.5857, 0.64971, 0.46851],
9224 [0.5898, 0.65009, 0.46722],
9225 [0.59397, 0.65044, 0.46593],
9226 [0.59819, 0.65076, 0.46469],
9227 [0.60248, 0.65106, 0.46344],
9228 [0.60683, 0.65134, 0.46224],
9229 [0.61124, 0.65159, 0.46106],
9230 [0.61572, 0.6518, 0.45991],
9231 [0.62028, 0.65199, 0.45879],
9232 [0.62491, 0.65214, 0.45769],
9233 [0.62961, 0.65226, 0.45663],
9234 [0.63441, 0.65235, 0.4556],
9235 [0.63928, 0.6524, 0.45461],
9236 [0.64424, 0.65241, 0.45364],
9237 [0.6493, 0.65237, 0.45273],
9238 [0.65445, 0.6523, 0.45184],
9239 [0.65971, 0.65218, 0.451],
9240 [0.66508, 0.65201, 0.45021],
9241 [0.67058, 0.65178, 0.44946],
9242 [0.67612, 0.65152, 0.44876],
9243 [0.68161, 0.65126, 0.44805],
9244 [0.68699, 0.65102, 0.44736],
9245 [0.69226, 0.65081, 0.44667],
9246 [0.69741, 0.65061, 0.44598],
9247 [0.70245, 0.65044, 0.44529],
9248 [0.70738, 0.65029, 0.44461],
9249 [0.71221, 0.65017, 0.44392],
9250 [0.71694, 0.65007, 0.44324],
9251 [0.72155, 0.65, 0.44256],
9252 [0.72607, 0.64995, 0.44187],
9253 [0.73048, 0.64993, 0.44118],
9254 [0.7348, 0.64994, 0.4405],
9255 [0.73901, 0.64997, 0.43982],
9256 [0.74312, 0.65003, 0.43914],
9257 [0.74713, 0.65011, 0.43846],
9258 [0.75106, 0.65023, 0.43779],
9259 [0.75488, 0.65037, 0.43711],
9260 [0.7586, 0.65054, 0.43643],
9261 [0.76223, 0.65074, 0.43576],
9262 [0.76578, 0.65097, 0.43508],
9263 [0.76922, 0.65123, 0.4344],
9264 [0.77257, 0.65152, 0.43372],
9265 [0.77583, 0.65185, 0.43305],
9266 [0.779, 0.65219, 0.43239],
9267 [0.78209, 0.65257, 0.43171],
9268 [0.78507, 0.65298, 0.43103],
9269 [0.78797, 0.65343, 0.43036],
9270 [0.79078, 0.65391, 0.42968],
9271 [0.7935, 0.65441, 0.42901],
9272 [0.79612, 0.65495, 0.42833],
9273 [0.79867, 0.65553, 0.42766],
9274 [0.80112, 0.65614, 0.42699],
9275 [0.80349, 0.65678, 0.4263],
9276 [0.80576, 0.65745, 0.42564],
9277 [0.80795, 0.65816, 0.42497],
9278 [0.81006, 0.65889, 0.42428],
9279 [0.81207, 0.65966, 0.42361],
9280 [0.814, 0.66047, 0.42293],
9281 [0.81584, 0.66131, 0.42225],
9282 [0.8176, 0.66219, 0.42158],
9283 [0.81927, 0.66309, 0.4209],
9284 [0.82085, 0.66403, 0.42023],
9285 [0.82235, 0.665, 0.41956],
9286 [0.82376, 0.66601, 0.41887],
9287 [0.82508, 0.66705, 0.41819],
9288 [0.82632, 0.66813, 0.41752],
9289 [0.82747, 0.66924, 0.41684],
9290 [0.82853, 0.67039, 0.41616],
9291 [0.82952, 0.67156, 0.41547],
9292 [0.83041, 0.67278, 0.41479],
9293 [0.83123, 0.67401, 0.41414],
9294 [0.83202, 0.67526, 0.41355],
9295 [0.83279, 0.67651, 0.41307],
9296 [0.83355, 0.67776, 0.41268],
9297 [0.83429, 0.67901, 0.41239],
9298 [0.83501, 0.68025, 0.41219],
9299 [0.83572, 0.68151, 0.41208],
9300 [0.83641, 0.68277, 0.41209],
9301 [0.83708, 0.68402, 0.41219],
9302 [0.83774, 0.68528, 0.41239],
9303 [0.83838, 0.68653, 0.41269],
9304 [0.83901, 0.68779, 0.41309],
9305 [0.83962, 0.68906, 0.41358],
9306 [0.84021, 0.69031, 0.41417],
9307 [0.84079, 0.69157, 0.41487],
9308 [0.84135, 0.69284, 0.41567],
9309 [0.84189, 0.6941, 0.41657],
9310 [0.84242, 0.69537, 0.41757],
9311 [0.84293, 0.69663, 0.41865],
9312 [0.84342, 0.6979, 0.41986],
9313 [0.8439, 0.69916, 0.42115],
9314 [0.84436, 0.70044, 0.42254],
9315 [0.8448, 0.7017, 0.42404],
9316 [0.84523, 0.70298, 0.42564],
9317 [0.84563, 0.70425, 0.42735],
9318 [0.84602, 0.70552, 0.42913],
9319 [0.84639, 0.7068, 0.43103],
9320 [0.84674, 0.70808, 0.43303],
9321 [0.84707, 0.70936, 0.43513],
9322 [0.84739, 0.71063, 0.43732],
9323 [0.84768, 0.71191, 0.4396],
9324 [0.84796, 0.71319, 0.44201],
9325 [0.84821, 0.71447, 0.4445],
9326 [0.84845, 0.71577, 0.44707],
9327 [0.84866, 0.71705, 0.44976],
9328 [0.84885, 0.71833, 0.45256],
9329 [0.84903, 0.71963, 0.45543],
9330 [0.84918, 0.72091, 0.45841],
9331 [0.8493, 0.7222, 0.46149],
9332 [0.84941, 0.7235, 0.46467],
9333 [0.84949, 0.7248, 0.46793],
9334 [0.84954, 0.72609, 0.4713],
9335 [0.84958, 0.72739, 0.47477],
9336 [0.84958, 0.72869, 0.47832],
9337 [0.84956, 0.72999, 0.48199],
9338 [0.84952, 0.73129, 0.48573],
9339 [0.84945, 0.7326, 0.48957],
9340 [0.84935, 0.7339, 0.49352],
9341 [0.84922, 0.73521, 0.49757],
9342 [0.84907, 0.73652, 0.5017],
9343 [0.84889, 0.73783, 0.50591],
9344 [0.84868, 0.73916, 0.51022],
9345 [0.84848, 0.74046, 0.51454],
9346 [0.84828, 0.74176, 0.51885],
9347 [0.8481, 0.74306, 0.52316],
9348 [0.84792, 0.74435, 0.52745],
9349 [0.84775, 0.74564, 0.53175],
9350 [0.84759, 0.74692, 0.53603],
9351 [0.84743, 0.74821, 0.54032],
9352 [0.84727, 0.74947, 0.5446],
9353 [0.84712, 0.75075, 0.54888],
9354 [0.84698, 0.75202, 0.55314],
9355 [0.84684, 0.75328, 0.55742],
9356 [0.8467, 0.75455, 0.56168],
9357 [0.84656, 0.7558, 0.56594],
9358 [0.84643, 0.75706, 0.57019],
9359 [0.84629, 0.75831, 0.57444],
9360 [0.84616, 0.75955, 0.5787],
9361 [0.84603, 0.76081, 0.58295],
9362 [0.8459, 0.76205, 0.58719],
9363 [0.84577, 0.76329, 0.59144],
9364 [0.84564, 0.76453, 0.59568],
9365 [0.84551, 0.76577, 0.59993],
9366 [0.84537, 0.767, 0.60417],
9367 [0.84524, 0.76824, 0.6084],
9368 [0.84511, 0.76947, 0.61263],
9369 [0.84497, 0.77071, 0.61687],
9370 [0.84484, 0.77194, 0.6211],
9371 [0.8447, 0.77316, 0.62533],
9372 [0.84455, 0.77439, 0.62955],
9373 [0.84441, 0.77561, 0.63379],
9374 [0.84426, 0.77684, 0.63801],
9375 [0.84411, 0.77806, 0.64224],
9376 [0.84396, 0.77928, 0.64646],
9377 [0.8438, 0.7805, 0.65068],
9378 [0.84364, 0.78172, 0.6549],
9379 [0.84348, 0.78294, 0.65912],
9380 [0.84331, 0.78416, 0.66335],
9381 [0.84314, 0.78537, 0.66757],
9382 [0.84297, 0.78659, 0.67179],
9383 [0.84279, 0.7878, 0.67601],
9384 [0.84261, 0.78901, 0.68022],
9385 [0.84243, 0.79022, 0.68444],
9386 [0.84224, 0.79143, 0.68867],
9387 [0.84204, 0.79265, 0.69289],
9388 [0.84184, 0.79386, 0.6971],
9389 [0.84163, 0.79507, 0.70132],
9390 [0.84142, 0.79627, 0.70554],
9391 [0.8412, 0.79748, 0.70976],
9392 [0.84098, 0.79869, 0.71398],
9393 [0.84076, 0.7999, 0.7182],
9394 [0.84053, 0.8011, 0.72241],
9395 [0.84029, 0.80231, 0.72663],
9396 [0.84004, 0.80352, 0.73085],
9397 [0.8398, 0.80472, 0.73508],
9398 [0.83954, 0.80593, 0.7393],
9399 [0.83928, 0.80713, 0.74352],
9400 [0.83901, 0.80834, 0.74774],
9401 [0.83873, 0.80954, 0.75196],
9402 [0.83845, 0.81074, 0.75618],
9403 [0.83817, 0.81195, 0.76041],
9404 [0.83788, 0.81315, 0.76463],
9405 [0.83758, 0.81435, 0.76885],
9406 [0.83727, 0.81555, 0.77308],
9407 [0.83695, 0.81676, 0.77731],
9408 [0.83663, 0.81795, 0.78154],
9409 [0.8363, 0.81916, 0.78577],
9410 [0.83597, 0.82036, 0.78999],
9411 [0.83563, 0.82156, 0.79422],
9412 [0.83528, 0.82277, 0.79845],
9413 [0.83492, 0.82396, 0.80268],
9414 [0.83456, 0.82516, 0.80692],
9415 [0.83419, 0.82637, 0.81115],
9416 [0.83381, 0.82757, 0.81538],
9417 [0.83342, 0.82877, 0.81962],
9418 [0.83302, 0.82997, 0.82386],
9419 [0.83262, 0.83118, 0.82809],
9420 [0.83221, 0.83237, 0.83233],
9421 ]
9422 b_linear_gow_60_85_c27 = bokeh_palette('linear_gow_60_85_c27',linear_gow_60_85_c27)
9423 m_linear_gow_60_85_c27 = mpl_cm('linear_gow_60_85_c27',linear_gow_60_85_c27)
9424 m_linear_gow_60_85_c27_r = mpl_cm('linear_gow_60_85_c27_r',list(reversed(linear_gow_60_85_c27)))
9425
9426
9427
9428
9429 linear_gow_65_90_c35 = [\
9430 [0.43765, 0.67814, 0.36054],
9431 [0.44314, 0.67844, 0.361],
9432 [0.4486, 0.67874, 0.36146],
9433 [0.45399, 0.67903, 0.36192],
9434 [0.45934, 0.67932, 0.36237],
9435 [0.46465, 0.67961, 0.36282],
9436 [0.46991, 0.6799, 0.36327],
9437 [0.47513, 0.68018, 0.36373],
9438 [0.48029, 0.68047, 0.36419],
9439 [0.48542, 0.68075, 0.36465],
9440 [0.49052, 0.68102, 0.36511],
9441 [0.49557, 0.6813, 0.36557],
9442 [0.50059, 0.68157, 0.36603],
9443 [0.50556, 0.68184, 0.3665],
9444 [0.51051, 0.68211, 0.36696],
9445 [0.51542, 0.68237, 0.36741],
9446 [0.5203, 0.68264, 0.36788],
9447 [0.52515, 0.6829, 0.36835],
9448 [0.52996, 0.68316, 0.36882],
9449 [0.53474, 0.68341, 0.36928],
9450 [0.53949, 0.68366, 0.36975],
9451 [0.54422, 0.68391, 0.37021],
9452 [0.54891, 0.68416, 0.37068],
9453 [0.55357, 0.6844, 0.37115],
9454 [0.55821, 0.68465, 0.37162],
9455 [0.56283, 0.68489, 0.3721],
9456 [0.56741, 0.68514, 0.37257],
9457 [0.57197, 0.68538, 0.37305],
9458 [0.57651, 0.68561, 0.37353],
9459 [0.58101, 0.68585, 0.37401],
9460 [0.5855, 0.68608, 0.37449],
9461 [0.58995, 0.68631, 0.37496],
9462 [0.59438, 0.68654, 0.37543],
9463 [0.5988, 0.68676, 0.37592],
9464 [0.60319, 0.68699, 0.37641],
9465 [0.60756, 0.68721, 0.37689],
9466 [0.6119, 0.68744, 0.37737],
9467 [0.61622, 0.68766, 0.37785],
9468 [0.62053, 0.68788, 0.37833],
9469 [0.6248, 0.6881, 0.37882],
9470 [0.62906, 0.68831, 0.37931],
9471 [0.6333, 0.68853, 0.37979],
9472 [0.63752, 0.68875, 0.38029],
9473 [0.64171, 0.68896, 0.38078],
9474 [0.64589, 0.68917, 0.38127],
9475 [0.65005, 0.68938, 0.38175],
9476 [0.65418, 0.68959, 0.38224],
9477 [0.6583, 0.6898, 0.38274],
9478 [0.6624, 0.69001, 0.38324],
9479 [0.66647, 0.69021, 0.38374],
9480 [0.67054, 0.69042, 0.38423],
9481 [0.67457, 0.69062, 0.38472],
9482 [0.67859, 0.69083, 0.38522],
9483 [0.68259, 0.69103, 0.38572],
9484 [0.68657, 0.69124, 0.38622],
9485 [0.69054, 0.69145, 0.38672],
9486 [0.69448, 0.69166, 0.38723],
9487 [0.69841, 0.69186, 0.38773],
9488 [0.70231, 0.69207, 0.38824],
9489 [0.70621, 0.69228, 0.38876],
9490 [0.71007, 0.69248, 0.38926],
9491 [0.71392, 0.69269, 0.38976],
9492 [0.71776, 0.69289, 0.39027],
9493 [0.72157, 0.6931, 0.39079],
9494 [0.72537, 0.6933, 0.39131],
9495 [0.72914, 0.69351, 0.39182],
9496 [0.7329, 0.69372, 0.39233],
9497 [0.73663, 0.69393, 0.39284],
9498 [0.74035, 0.69414, 0.39336],
9499 [0.74405, 0.69435, 0.39388],
9500 [0.74774, 0.69457, 0.3944],
9501 [0.7514, 0.69479, 0.39492],
9502 [0.75504, 0.69501, 0.39545],
9503 [0.75865, 0.69523, 0.39597],
9504 [0.76225, 0.69545, 0.39649],
9505 [0.76584, 0.69568, 0.39701],
9506 [0.76939, 0.69591, 0.39755],
9507 [0.77293, 0.69614, 0.39808],
9508 [0.77645, 0.69638, 0.39861],
9509 [0.77995, 0.69661, 0.39913],
9510 [0.78342, 0.69685, 0.39966],
9511 [0.78688, 0.69709, 0.40021],
9512 [0.7903, 0.69734, 0.40076],
9513 [0.79372, 0.69759, 0.40129],
9514 [0.79709, 0.69785, 0.40182],
9515 [0.80046, 0.69811, 0.40236],
9516 [0.80379, 0.69838, 0.40291],
9517 [0.80711, 0.69865, 0.40346],
9518 [0.81039, 0.69893, 0.404],
9519 [0.81365, 0.69921, 0.40454],
9520 [0.81689, 0.6995, 0.40509],
9521 [0.82009, 0.6998, 0.40565],
9522 [0.82328, 0.70011, 0.40621],
9523 [0.82643, 0.70042, 0.40676],
9524 [0.82956, 0.70074, 0.40731],
9525 [0.83264, 0.70107, 0.40787],
9526 [0.83571, 0.7014, 0.40843],
9527 [0.83874, 0.70174, 0.409],
9528 [0.84174, 0.7021, 0.40956],
9529 [0.8447, 0.70247, 0.41014],
9530 [0.84763, 0.70285, 0.41071],
9531 [0.85052, 0.70324, 0.41127],
9532 [0.85337, 0.70364, 0.41185],
9533 [0.85619, 0.70405, 0.41243],
9534 [0.85896, 0.70448, 0.41301],
9535 [0.86169, 0.70492, 0.41359],
9536 [0.86438, 0.70538, 0.41418],
9537 [0.86701, 0.70586, 0.41476],
9538 [0.8696, 0.70636, 0.41536],
9539 [0.87215, 0.70687, 0.41595],
9540 [0.87463, 0.7074, 0.41656],
9541 [0.87705, 0.70795, 0.41716],
9542 [0.87942, 0.70853, 0.41776],
9543 [0.88172, 0.70913, 0.41837],
9544 [0.88395, 0.70976, 0.41899],
9545 [0.88611, 0.71042, 0.41961],
9546 [0.88818, 0.71111, 0.42023],
9547 [0.89017, 0.71183, 0.42086],
9548 [0.89208, 0.71258, 0.4215],
9549 [0.89388, 0.71338, 0.42214],
9550 [0.89558, 0.71421, 0.42279],
9551 [0.89716, 0.7151, 0.42344],
9552 [0.8986, 0.71605, 0.42411],
9553 [0.8999, 0.71704, 0.42479],
9554 [0.90104, 0.7181, 0.42548],
9555 [0.902, 0.71924, 0.42616],
9556 [0.90274, 0.72045, 0.42688],
9557 [0.90325, 0.72176, 0.42761],
9558 [0.90355, 0.72316, 0.42836],
9559 [0.90378, 0.72458, 0.42917],
9560 [0.90399, 0.726, 0.43006],
9561 [0.9042, 0.72741, 0.43102],
9562 [0.90441, 0.72883, 0.43206],
9563 [0.90462, 0.73024, 0.43315],
9564 [0.90481, 0.73165, 0.43433],
9565 [0.90501, 0.73306, 0.43559],
9566 [0.90519, 0.73447, 0.43691],
9567 [0.90537, 0.73586, 0.4383],
9568 [0.90555, 0.73727, 0.43978],
9569 [0.90572, 0.73867, 0.44132],
9570 [0.90588, 0.74007, 0.44294],
9571 [0.90604, 0.74145, 0.44463],
9572 [0.90619, 0.74285, 0.44638],
9573 [0.90633, 0.74424, 0.44821],
9574 [0.90647, 0.74563, 0.45013],
9575 [0.9066, 0.74702, 0.45211],
9576 [0.90673, 0.7484, 0.45416],
9577 [0.90684, 0.74978, 0.45628],
9578 [0.90696, 0.75117, 0.45847],
9579 [0.90706, 0.75254, 0.46074],
9580 [0.90715, 0.75392, 0.46307],
9581 [0.90724, 0.75529, 0.46549],
9582 [0.90732, 0.75666, 0.46797],
9583 [0.90739, 0.75804, 0.47054],
9584 [0.90746, 0.7594, 0.47315],
9585 [0.90751, 0.76077, 0.47586],
9586 [0.90756, 0.76213, 0.47862],
9587 [0.90759, 0.7635, 0.48146],
9588 [0.90762, 0.76487, 0.48437],
9589 [0.90764, 0.76622, 0.48736],
9590 [0.90764, 0.76758, 0.49041],
9591 [0.90764, 0.76894, 0.49353],
9592 [0.90763, 0.77029, 0.49672],
9593 [0.9076, 0.77165, 0.49998],
9594 [0.90756, 0.773, 0.50331],
9595 [0.90752, 0.77435, 0.50672],
9596 [0.90746, 0.7757, 0.51019],
9597 [0.90738, 0.77706, 0.51373],
9598 [0.9073, 0.7784, 0.51735],
9599 [0.9072, 0.77974, 0.52102],
9600 [0.90709, 0.78109, 0.52477],
9601 [0.90697, 0.78243, 0.52859],
9602 [0.90683, 0.78378, 0.53248],
9603 [0.90667, 0.78512, 0.53643],
9604 [0.90651, 0.78646, 0.54046],
9605 [0.90632, 0.78779, 0.54455],
9606 [0.90612, 0.78913, 0.54872],
9607 [0.90591, 0.79046, 0.55293],
9608 [0.90568, 0.7918, 0.55724],
9609 [0.90544, 0.79314, 0.56159],
9610 [0.9052, 0.79447, 0.56594],
9611 [0.90497, 0.79578, 0.5703],
9612 [0.90475, 0.7971, 0.57465],
9613 [0.90454, 0.79841, 0.579],
9614 [0.90433, 0.79973, 0.58333],
9615 [0.90413, 0.80102, 0.58767],
9616 [0.90394, 0.80232, 0.59201],
9617 [0.90376, 0.80361, 0.59633],
9618 [0.90358, 0.8049, 0.60065],
9619 [0.90341, 0.80619, 0.60497],
9620 [0.90323, 0.80747, 0.60929],
9621 [0.90307, 0.80875, 0.6136],
9622 [0.9029, 0.81003, 0.61791],
9623 [0.90273, 0.8113, 0.62221],
9624 [0.90257, 0.81257, 0.62652],
9625 [0.90241, 0.81384, 0.63083],
9626 [0.90225, 0.8151, 0.63512],
9627 [0.90209, 0.81637, 0.63942],
9628 [0.90194, 0.81763, 0.64371],
9629 [0.90178, 0.81888, 0.648],
9630 [0.90162, 0.82014, 0.6523],
9631 [0.90146, 0.8214, 0.65659],
9632 [0.9013, 0.82265, 0.66087],
9633 [0.90114, 0.8239, 0.66516],
9634 [0.90098, 0.82514, 0.66945],
9635 [0.90082, 0.82639, 0.67373],
9636 [0.90066, 0.82764, 0.67801],
9637 [0.90049, 0.82888, 0.68229],
9638 [0.90032, 0.83012, 0.68657],
9639 [0.90015, 0.83137, 0.69084],
9640 [0.89998, 0.8326, 0.69512],
9641 [0.89981, 0.83384, 0.6994],
9642 [0.89963, 0.83508, 0.70368],
9643 [0.89945, 0.83631, 0.70795],
9644 [0.89927, 0.83755, 0.71222],
9645 [0.89908, 0.83878, 0.7165],
9646 [0.89889, 0.84002, 0.72077],
9647 [0.89869, 0.84124, 0.72505],
9648 [0.89849, 0.84248, 0.72932],
9649 [0.89829, 0.8437, 0.73359],
9650 [0.89809, 0.84493, 0.73786],
9651 [0.89788, 0.84616, 0.74213],
9652 [0.89766, 0.84738, 0.7464],
9653 [0.89745, 0.84861, 0.75068],
9654 [0.89722, 0.84984, 0.75495],
9655 [0.897, 0.85106, 0.75921],
9656 [0.89676, 0.85229, 0.76349],
9657 [0.89652, 0.85351, 0.76776],
9658 [0.89628, 0.85474, 0.77203],
9659 [0.89603, 0.85596, 0.7763],
9660 [0.89578, 0.85718, 0.78057],
9661 [0.89552, 0.8584, 0.78485],
9662 [0.89526, 0.85962, 0.78912],
9663 [0.89499, 0.86084, 0.7934],
9664 [0.89471, 0.86207, 0.79767],
9665 [0.89443, 0.86328, 0.80194],
9666 [0.89414, 0.8645, 0.80622],
9667 [0.89385, 0.86572, 0.81049],
9668 [0.89355, 0.86694, 0.81477],
9669 [0.89324, 0.86816, 0.81904],
9670 [0.89293, 0.86938, 0.82332],
9671 [0.89262, 0.87059, 0.8276],
9672 [0.89229, 0.87181, 0.83188],
9673 [0.89196, 0.87303, 0.83616],
9674 [0.89162, 0.87424, 0.84044],
9675 [0.89128, 0.87546, 0.84472],
9676 [0.89093, 0.87667, 0.849],
9677 [0.89057, 0.87789, 0.85328],
9678 [0.8902, 0.87911, 0.85756],
9679 [0.88983, 0.88032, 0.86185],
9680 [0.88945, 0.88154, 0.86614],
9681 [0.88907, 0.88276, 0.87042],
9682 [0.88867, 0.88398, 0.87471],
9683 [0.88827, 0.88519, 0.879],
9684 [0.88786, 0.88641, 0.88329],
9685 [0.88744, 0.88762, 0.88758],
9686 ]
9687 b_linear_gow_65_90_c35 = bokeh_palette('linear_gow_65_90_c35',linear_gow_65_90_c35)
9688 m_linear_gow_65_90_c35 = mpl_cm('linear_gow_65_90_c35',linear_gow_65_90_c35)
9689 m_linear_gow_65_90_c35_r = mpl_cm('linear_gow_65_90_c35_r',list(reversed(linear_gow_65_90_c35)))
9690
9691
9692
9693
9694 linear_green_5_95_c69 = [\
9695 [0.0020082, 0.082527, 0.022201],
9696 [0.004381, 0.08615, 0.022118],
9697 [0.0067598, 0.089747, 0.022041],
9698 [0.0091625, 0.093124, 0.021981],
9699 [0.011768, 0.096433, 0.021933],
9700 [0.014187, 0.099686, 0.021895],
9701 [0.016629, 0.10283, 0.021877],
9702 [0.019082, 0.10587, 0.021867],
9703 [0.021556, 0.1088, 0.021877],
9704 [0.024018, 0.11172, 0.021897],
9705 [0.026293, 0.11459, 0.021902],
9706 [0.028361, 0.1176, 0.0219],
9707 [0.030209, 0.12061, 0.021879],
9708 [0.031836, 0.12368, 0.021843],
9709 [0.033248, 0.12681, 0.021797],
9710 [0.03448, 0.13002, 0.021732],
9711 [0.035611, 0.13318, 0.021656],
9712 [0.036308, 0.13639, 0.021568],
9713 [0.036803, 0.13965, 0.021464],
9714 [0.037067, 0.14299, 0.021348],
9715 [0.037096, 0.14631, 0.021222],
9716 [0.036881, 0.14971, 0.021083],
9717 [0.036566, 0.15305, 0.020931],
9718 [0.036258, 0.15648, 0.020778],
9719 [0.035956, 0.15982, 0.02062],
9720 [0.035648, 0.16326, 0.020454],
9721 [0.03531, 0.16666, 0.020281],
9722 [0.034935, 0.17007, 0.02011],
9723 [0.034549, 0.17347, 0.019938],
9724 [0.034194, 0.17689, 0.019764],
9725 [0.0339, 0.18031, 0.01959],
9726 [0.033658, 0.18374, 0.019418],
9727 [0.03346, 0.18719, 0.019251],
9728 [0.033308, 0.1906, 0.019094],
9729 [0.033202, 0.19407, 0.018947],
9730 [0.033153, 0.19748, 0.018811],
9731 [0.033171, 0.2009, 0.018691],
9732 [0.033269, 0.20438, 0.018588],
9733 [0.033456, 0.2078, 0.018509],
9734 [0.033755, 0.21125, 0.018457],
9735 [0.034229, 0.21467, 0.018437],
9736 [0.03498, 0.21811, 0.018456],
9737 [0.03581, 0.22154, 0.018521],
9738 [0.036701, 0.22495, 0.018622],
9739 [0.037696, 0.22842, 0.018735],
9740 [0.038702, 0.23186, 0.018848],
9741 [0.039729, 0.23531, 0.018957],
9742 [0.040766, 0.23875, 0.019061],
9743 [0.041844, 0.24222, 0.019159],
9744 [0.042758, 0.24568, 0.019252],
9745 [0.043802, 0.24918, 0.019339],
9746 [0.044931, 0.25267, 0.019419],
9747 [0.045873, 0.25616, 0.019493],
9748 [0.047009, 0.25968, 0.019561],
9749 [0.047989, 0.26319, 0.019623],
9750 [0.049157, 0.2667, 0.019676],
9751 [0.050138, 0.27025, 0.019721],
9752 [0.051173, 0.27378, 0.019758],
9753 [0.052215, 0.27732, 0.019785],
9754 [0.053276, 0.28085, 0.019802],
9755 [0.054355, 0.28442, 0.01981],
9756 [0.055446, 0.28799, 0.01981],
9757 [0.056569, 0.29158, 0.019809],
9758 [0.057528, 0.29515, 0.019834],
9759 [0.058624, 0.29874, 0.01989],
9760 [0.059734, 0.30233, 0.019977],
9761 [0.06068, 0.30596, 0.020098],
9762 [0.061651, 0.30957, 0.020253],
9763 [0.062756, 0.31318, 0.020445],
9764 [0.063696, 0.31681, 0.020677],
9765 [0.064656, 0.32045, 0.02095],
9766 [0.065612, 0.32408, 0.021258],
9767 [0.066576, 0.32773, 0.021584],
9768 [0.067549, 0.33138, 0.021916],
9769 [0.068538, 0.33506, 0.022251],
9770 [0.06952, 0.33872, 0.022589],
9771 [0.070402, 0.3424, 0.022929],
9772 [0.071419, 0.34607, 0.023272],
9773 [0.072319, 0.34977, 0.023618],
9774 [0.073361, 0.35346, 0.023966],
9775 [0.074283, 0.35718, 0.024318],
9776 [0.075218, 0.36087, 0.024672],
9777 [0.076165, 0.36459, 0.025028],
9778 [0.077123, 0.36832, 0.025388],
9779 [0.078091, 0.37204, 0.02575],
9780 [0.079071, 0.37578, 0.026116],
9781 [0.080061, 0.37952, 0.026484],
9782 [0.081061, 0.38328, 0.026854],
9783 [0.082077, 0.38702, 0.027228],
9784 [0.082984, 0.39079, 0.027604],
9785 [0.084013, 0.39456, 0.027983],
9786 [0.084952, 0.39834, 0.028365],
9787 [0.085878, 0.40211, 0.02875],
9788 [0.086941, 0.40591, 0.029138],
9789 [0.087908, 0.4097, 0.029528],
9790 [0.088876, 0.4135, 0.029921],
9791 [0.089858, 0.41731, 0.030317],
9792 [0.090847, 0.42111, 0.030716],
9793 [0.091852, 0.42494, 0.031118],
9794 [0.092761, 0.42876, 0.031521],
9795 [0.093773, 0.43259, 0.031927],
9796 [0.094809, 0.43643, 0.032341],
9797 [0.09575, 0.44027, 0.03276],
9798 [0.096692, 0.44412, 0.033171],
9799 [0.097753, 0.44796, 0.033567],
9800 [0.098721, 0.45183, 0.033985],
9801 [0.099698, 0.4557, 0.034483],
9802 [0.10069, 0.45957, 0.035028],
9803 [0.10168, 0.46344, 0.035514],
9804 [0.10269, 0.46733, 0.035934],
9805 [0.1037, 0.47122, 0.036349],
9806 [0.10463, 0.47512, 0.036789],
9807 [0.10568, 0.47902, 0.037237],
9808 [0.10671, 0.48292, 0.037682],
9809 [0.10766, 0.48683, 0.038128],
9810 [0.10865, 0.49076, 0.038578],
9811 [0.10971, 0.49468, 0.039032],
9812 [0.11069, 0.49861, 0.039489],
9813 [0.11169, 0.50254, 0.039948],
9814 [0.1127, 0.50648, 0.040406],
9815 [0.11369, 0.51042, 0.040871],
9816 [0.11464, 0.51438, 0.041351],
9817 [0.11569, 0.51834, 0.041826],
9818 [0.1167, 0.52229, 0.042253],
9819 [0.11769, 0.52627, 0.042639],
9820 [0.11873, 0.53024, 0.043044],
9821 [0.1197, 0.53421, 0.043511],
9822 [0.1207, 0.53821, 0.044017],
9823 [0.1217, 0.54219, 0.044525],
9824 [0.12271, 0.54619, 0.044992],
9825 [0.12373, 0.55018, 0.045398],
9826 [0.12476, 0.55419, 0.045806],
9827 [0.12581, 0.55819, 0.046288],
9828 [0.12679, 0.56222, 0.046801],
9829 [0.12783, 0.56624, 0.047247],
9830 [0.12882, 0.57026, 0.047653],
9831 [0.12988, 0.57429, 0.048118],
9832 [0.13089, 0.57833, 0.048645],
9833 [0.1319, 0.58237, 0.049135],
9834 [0.13292, 0.58642, 0.049563],
9835 [0.13395, 0.59047, 0.04998],
9836 [0.13498, 0.59453, 0.050418],
9837 [0.13595, 0.59859, 0.050866],
9838 [0.13701, 0.60266, 0.051311],
9839 [0.13806, 0.60673, 0.051757],
9840 [0.13904, 0.61081, 0.052205],
9841 [0.14007, 0.61488, 0.052658],
9842 [0.14114, 0.61898, 0.053112],
9843 [0.14214, 0.62307, 0.053569],
9844 [0.14318, 0.62716, 0.054029],
9845 [0.14421, 0.63127, 0.054491],
9846 [0.14526, 0.63537, 0.054953],
9847 [0.14626, 0.63949, 0.055418],
9848 [0.1473, 0.6436, 0.055896],
9849 [0.14831, 0.64772, 0.056378],
9850 [0.14938, 0.65185, 0.056824],
9851 [0.15041, 0.65599, 0.057227],
9852 [0.15143, 0.66012, 0.057637],
9853 [0.15246, 0.66426, 0.058099],
9854 [0.15349, 0.66841, 0.058598],
9855 [0.15454, 0.67256, 0.0591],
9856 [0.1556, 0.67671, 0.059581],
9857 [0.15665, 0.68086, 0.060024],
9858 [0.15766, 0.68503, 0.06044],
9859 [0.15873, 0.68921, 0.060845],
9860 [0.15973, 0.69338, 0.061267],
9861 [0.1608, 0.69755, 0.061737],
9862 [0.16187, 0.70173, 0.06225],
9863 [0.16291, 0.70593, 0.06274],
9864 [0.16396, 0.71012, 0.063178],
9865 [0.16497, 0.71431, 0.063603],
9866 [0.16602, 0.71852, 0.064042],
9867 [0.1671, 0.72272, 0.064491],
9868 [0.16812, 0.72693, 0.064939],
9869 [0.16921, 0.73115, 0.065387],
9870 [0.17024, 0.73537, 0.065837],
9871 [0.17128, 0.7396, 0.066291],
9872 [0.17233, 0.74382, 0.066748],
9873 [0.17339, 0.74806, 0.067206],
9874 [0.17446, 0.75229, 0.067663],
9875 [0.1755, 0.75654, 0.068124],
9876 [0.17654, 0.76078, 0.068597],
9877 [0.17764, 0.76504, 0.069073],
9878 [0.17869, 0.76929, 0.069516],
9879 [0.17973, 0.77355, 0.06992],
9880 [0.18078, 0.77782, 0.070337],
9881 [0.18184, 0.78209, 0.070809],
9882 [0.1829, 0.78636, 0.071291],
9883 [0.18397, 0.79063, 0.071723],
9884 [0.18506, 0.79491, 0.072134],
9885 [0.18612, 0.7992, 0.07259],
9886 [0.18718, 0.80349, 0.073087],
9887 [0.18826, 0.80779, 0.073557],
9888 [0.1893, 0.81208, 0.073983],
9889 [0.19036, 0.81639, 0.074402],
9890 [0.19143, 0.82069, 0.074835],
9891 [0.1925, 0.825, 0.075276],
9892 [0.19359, 0.82933, 0.075716],
9893 [0.19467, 0.83365, 0.076155],
9894 [0.19571, 0.83797, 0.076597],
9895 [0.19681, 0.8423, 0.077042],
9896 [0.19786, 0.84663, 0.077489],
9897 [0.19892, 0.85096, 0.077938],
9898 [0.19999, 0.85531, 0.078388],
9899 [0.20106, 0.85965, 0.078841],
9900 [0.20215, 0.864, 0.079296],
9901 [0.20324, 0.86836, 0.079753],
9902 [0.20434, 0.87271, 0.080211],
9903 [0.20539, 0.87707, 0.080669],
9904 [0.2065, 0.88144, 0.081135],
9905 [0.20756, 0.88581, 0.08161],
9906 [0.20863, 0.89017, 0.082069],
9907 [0.20974, 0.89456, 0.082489],
9908 [0.21167, 0.8989, 0.082885],
9909 [0.21577, 0.90314, 0.083267],
9910 [0.22243, 0.90724, 0.083619],
9911 [0.23129, 0.91122, 0.083917],
9912 [0.24192, 0.91509, 0.084156],
9913 [0.25398, 0.91886, 0.084342],
9914 [0.26714, 0.92253, 0.084483],
9915 [0.28122, 0.92611, 0.084587],
9916 [0.29605, 0.92959, 0.084656],
9917 [0.31138, 0.93299, 0.084696],
9918 [0.32707, 0.93632, 0.08471],
9919 [0.34303, 0.93956, 0.084701],
9920 [0.35913, 0.94274, 0.084672],
9921 [0.37535, 0.94584, 0.084623],
9922 [0.39181, 0.94887, 0.084553],
9923 [0.40832, 0.95183, 0.084465],
9924 [0.42483, 0.95473, 0.084363],
9925 [0.4413, 0.95756, 0.084247],
9926 [0.45785, 0.96033, 0.084113],
9927 [0.47443, 0.96303, 0.083964],
9928 [0.49093, 0.96567, 0.083803],
9929 [0.50737, 0.96826, 0.083635],
9930 [0.52388, 0.97077, 0.083456],
9931 [0.54033, 0.97323, 0.083278],
9932 [0.55668, 0.97564, 0.083106],
9933 [0.57311, 0.97798, 0.082937],
9934 [0.58945, 0.98026, 0.082777],
9935 [0.60571, 0.98249, 0.082624],
9936 [0.62205, 0.98465, 0.082472],
9937 [0.63831, 0.98675, 0.082325],
9938 [0.6545, 0.9888, 0.08218],
9939 [0.67074, 0.99078, 0.082035],
9940 [0.68689, 0.99272, 0.081896],
9941 [0.70305, 0.99458, 0.081762],
9942 [0.71919, 0.99639, 0.081638],
9943 [0.73525, 0.99815, 0.081527],
9944 [0.75139, 0.99984, 0.081428],
9945 [0.76742, 1, 0.081347],
9946 [0.78349, 1, 0.081282],
9947 [0.79956, 1, 0.081236],
9948 [0.81555, 1, 0.08121],
9949 [0.83159, 1, 0.081204],
9950 [0.84754, 1, 0.081223],
9951 ]
9952 b_linear_green_5_95_c69 = bokeh_palette('linear_green_5_95_c69',linear_green_5_95_c69)
9953 m_linear_green_5_95_c69 = mpl_cm('linear_green_5_95_c69',linear_green_5_95_c69)
9954 m_linear_green_5_95_c69_r = mpl_cm('linear_green_5_95_c69_r',list(reversed(linear_green_5_95_c69)))
9955 kgy = b_linear_green_5_95_c69
9956 m_kgy = m_linear_green_5_95_c69
9957 m_kgy_r = m_linear_green_5_95_c69_r
9958 palette['kgy'] = b_linear_green_5_95_c69
9959 cm['kgy'] = m_linear_green_5_95_c69
9960 cm['kgy_r'] = m_linear_green_5_95_c69_r
9961 register_cmap('cet_kgy',m_linear_green_5_95_c69)
9962 register_cmap('cet_kgy_r',m_linear_green_5_95_c69_r)
9963
9964
9965
9966
9967 linear_grey_0_100_c0 = [\
9968 [0, 0, 0],
9969 [0.0055606, 0.0055631, 0.0055625],
9970 [0.011212, 0.011219, 0.011217],
9971 [0.016877, 0.016885, 0.016883],
9972 [0.022438, 0.022448, 0.022445],
9973 [0.027998, 0.028011, 0.028008],
9974 [0.03354, 0.033554, 0.033551],
9975 [0.039316, 0.039333, 0.039329],
9976 [0.0447, 0.044719, 0.044714],
9977 [0.049695, 0.049713, 0.049709],
9978 [0.054322, 0.054343, 0.054338],
9979 [0.058797, 0.058821, 0.058815],
9980 [0.063041, 0.063062, 0.063057],
9981 [0.066996, 0.067019, 0.067014],
9982 [0.070827, 0.070853, 0.070846],
9983 [0.074487, 0.074511, 0.074505],
9984 [0.077967, 0.077992, 0.077986],
9985 [0.081449, 0.081477, 0.08147],
9986 [0.084728, 0.084752, 0.084746],
9987 [0.087913, 0.087939, 0.087933],
9988 [0.091003, 0.091031, 0.091024],
9989 [0.094004, 0.094034, 0.094027],
9990 [0.096981, 0.097012, 0.097005],
9991 [0.10004, 0.10007, 0.10006],
9992 [0.10311, 0.10314, 0.10314],
9993 [0.10618, 0.10621, 0.1062],
9994 [0.10924, 0.10928, 0.10927],
9995 [0.11232, 0.11235, 0.11234],
9996 [0.11538, 0.11541, 0.1154],
9997 [0.11852, 0.11855, 0.11854],
9998 [0.12157, 0.1216, 0.12159],
9999 [0.12471, 0.12474, 0.12473],
10000 [0.12787, 0.1279, 0.12789],
10001 [0.13102, 0.13105, 0.13105],
10002 [0.13418, 0.13421, 0.1342],
10003 [0.13734, 0.13738, 0.13737],
10004 [0.14051, 0.14055, 0.14054],
10005 [0.1437, 0.14373, 0.14372],
10006 [0.14687, 0.14691, 0.1469],
10007 [0.15011, 0.15015, 0.15014],
10008 [0.15329, 0.15333, 0.15332],
10009 [0.15656, 0.15659, 0.15659],
10010 [0.15975, 0.15979, 0.15978],
10011 [0.16304, 0.16308, 0.16307],
10012 [0.16628, 0.16632, 0.16631],
10013 [0.16957, 0.16961, 0.1696],
10014 [0.17281, 0.17286, 0.17285],
10015 [0.17608, 0.17612, 0.17611],
10016 [0.1794, 0.17944, 0.17943],
10017 [0.18269, 0.18273, 0.18272],
10018 [0.18604, 0.18608, 0.18607],
10019 [0.18934, 0.18939, 0.18938],
10020 [0.19267, 0.19272, 0.19271],
10021 [0.19602, 0.19607, 0.19606],
10022 [0.19934, 0.19939, 0.19938],
10023 [0.20271, 0.20276, 0.20275],
10024 [0.20611, 0.20616, 0.20615],
10025 [0.20946, 0.20951, 0.2095],
10026 [0.21284, 0.21289, 0.21288],
10027 [0.21626, 0.21632, 0.2163],
10028 [0.21965, 0.2197, 0.21969],
10029 [0.22307, 0.22312, 0.22311],
10030 [0.22649, 0.22654, 0.22653],
10031 [0.22988, 0.22994, 0.22992],
10032 [0.23332, 0.23337, 0.23336],
10033 [0.2368, 0.23685, 0.23684],
10034 [0.24022, 0.24027, 0.24026],
10035 [0.24368, 0.24373, 0.24372],
10036 [0.24716, 0.24722, 0.2472],
10037 [0.25063, 0.25069, 0.25067],
10038 [0.25412, 0.25418, 0.25417],
10039 [0.2576, 0.25766, 0.25765],
10040 [0.26111, 0.26117, 0.26115],
10041 [0.26461, 0.26467, 0.26465],
10042 [0.26812, 0.26818, 0.26817],
10043 [0.27164, 0.2717, 0.27168],
10044 [0.27518, 0.27525, 0.27523],
10045 [0.27872, 0.27879, 0.27877],
10046 [0.28227, 0.28234, 0.28232],
10047 [0.2858, 0.28587, 0.28585],
10048 [0.28938, 0.28945, 0.28943],
10049 [0.29294, 0.293, 0.29298],
10050 [0.29652, 0.29659, 0.29657],
10051 [0.30009, 0.30016, 0.30014],
10052 [0.30368, 0.30375, 0.30373],
10053 [0.30728, 0.30734, 0.30733],
10054 [0.3109, 0.31096, 0.31095],
10055 [0.31449, 0.31456, 0.31454],
10056 [0.31811, 0.31819, 0.31817],
10057 [0.32173, 0.32181, 0.32179],
10058 [0.32536, 0.32543, 0.32542],
10059 [0.32902, 0.32909, 0.32907],
10060 [0.33267, 0.33274, 0.33272],
10061 [0.3363, 0.33638, 0.33636],
10062 [0.33997, 0.34005, 0.34003],
10063 [0.34363, 0.3437, 0.34369],
10064 [0.34731, 0.34739, 0.34737],
10065 [0.35099, 0.35107, 0.35105],
10066 [0.35468, 0.35476, 0.35474],
10067 [0.35836, 0.35844, 0.35842],
10068 [0.36207, 0.36214, 0.36212],
10069 [0.36577, 0.36585, 0.36583],
10070 [0.36948, 0.36956, 0.36954],
10071 [0.37319, 0.37328, 0.37326],
10072 [0.37693, 0.37701, 0.37699],
10073 [0.38066, 0.38074, 0.38072],
10074 [0.38439, 0.38447, 0.38445],
10075 [0.38814, 0.38822, 0.3882],
10076 [0.39189, 0.39197, 0.39195],
10077 [0.39565, 0.39574, 0.39572],
10078 [0.3994, 0.39949, 0.39946],
10079 [0.40318, 0.40327, 0.40325],
10080 [0.40695, 0.40704, 0.40702],
10081 [0.41074, 0.41083, 0.41081],
10082 [0.41452, 0.41461, 0.41459],
10083 [0.41831, 0.4184, 0.41838],
10084 [0.42211, 0.4222, 0.42218],
10085 [0.42592, 0.42601, 0.42599],
10086 [0.42974, 0.42983, 0.42981],
10087 [0.43355, 0.43364, 0.43362],
10088 [0.43739, 0.43748, 0.43746],
10089 [0.44121, 0.44131, 0.44128],
10090 [0.44505, 0.44515, 0.44512],
10091 [0.4489, 0.449, 0.44897],
10092 [0.45275, 0.45284, 0.45282],
10093 [0.45659, 0.45669, 0.45667],
10094 [0.46045, 0.46055, 0.46052],
10095 [0.46433, 0.46443, 0.46441],
10096 [0.46819, 0.46829, 0.46826],
10097 [0.47208, 0.47218, 0.47215],
10098 [0.47596, 0.47606, 0.47603],
10099 [0.47985, 0.47995, 0.47992],
10100 [0.48373, 0.48383, 0.48381],
10101 [0.48764, 0.48775, 0.48772],
10102 [0.49155, 0.49165, 0.49163],
10103 [0.49545, 0.49556, 0.49553],
10104 [0.49936, 0.49947, 0.49944],
10105 [0.50329, 0.50339, 0.50337],
10106 [0.50722, 0.50733, 0.5073],
10107 [0.51115, 0.51126, 0.51123],
10108 [0.51509, 0.5152, 0.51517],
10109 [0.51904, 0.51915, 0.51912],
10110 [0.52299, 0.5231, 0.52307],
10111 [0.52695, 0.52706, 0.52703],
10112 [0.5309, 0.53101, 0.53099],
10113 [0.53487, 0.53498, 0.53495],
10114 [0.53884, 0.53895, 0.53893],
10115 [0.54282, 0.54293, 0.5429],
10116 [0.5468, 0.54691, 0.54688],
10117 [0.55078, 0.5509, 0.55087],
10118 [0.55478, 0.55489, 0.55486],
10119 [0.55877, 0.55888, 0.55886],
10120 [0.56278, 0.5629, 0.56287],
10121 [0.56679, 0.56691, 0.56688],
10122 [0.57079, 0.57091, 0.57088],
10123 [0.57481, 0.57493, 0.5749],
10124 [0.57884, 0.57896, 0.57893],
10125 [0.58286, 0.58298, 0.58295],
10126 [0.5869, 0.58702, 0.58699],
10127 [0.59094, 0.59106, 0.59103],
10128 [0.59498, 0.5951, 0.59507],
10129 [0.59903, 0.59916, 0.59913],
10130 [0.60309, 0.60321, 0.60318],
10131 [0.60715, 0.60728, 0.60724],
10132 [0.61121, 0.61134, 0.61131],
10133 [0.61527, 0.6154, 0.61537],
10134 [0.61936, 0.61948, 0.61945],
10135 [0.62343, 0.62356, 0.62353],
10136 [0.62751, 0.62764, 0.62761],
10137 [0.6316, 0.63173, 0.6317],
10138 [0.63569, 0.63583, 0.63579],
10139 [0.6398, 0.63993, 0.63989],
10140 [0.64389, 0.64402, 0.64399],
10141 [0.648, 0.64813, 0.6481],
10142 [0.65212, 0.65225, 0.65222],
10143 [0.65624, 0.65637, 0.65634],
10144 [0.66035, 0.66049, 0.66045],
10145 [0.66448, 0.66461, 0.66458],
10146 [0.66862, 0.66875, 0.66872],
10147 [0.67275, 0.67289, 0.67286],
10148 [0.6769, 0.67703, 0.677],
10149 [0.68103, 0.68117, 0.68114],
10150 [0.68519, 0.68533, 0.6853],
10151 [0.68935, 0.68949, 0.68945],
10152 [0.6935, 0.69364, 0.69361],
10153 [0.69766, 0.69781, 0.69777],
10154 [0.70183, 0.70197, 0.70194],
10155 [0.70601, 0.70616, 0.70612],
10156 [0.71019, 0.71033, 0.7103],
10157 [0.71437, 0.71451, 0.71448],
10158 [0.71855, 0.7187, 0.71867],
10159 [0.72274, 0.72289, 0.72286],
10160 [0.72694, 0.72709, 0.72706],
10161 [0.73114, 0.73129, 0.73126],
10162 [0.73535, 0.7355, 0.73546],
10163 [0.73957, 0.73972, 0.73968],
10164 [0.74378, 0.74393, 0.74389],
10165 [0.748, 0.74815, 0.74811],
10166 [0.75222, 0.75237, 0.75233],
10167 [0.75644, 0.7566, 0.75656],
10168 [0.76068, 0.76083, 0.76079],
10169 [0.76492, 0.76507, 0.76503],
10170 [0.76915, 0.76931, 0.76927],
10171 [0.7734, 0.77355, 0.77351],
10172 [0.77765, 0.77781, 0.77777],
10173 [0.78191, 0.78206, 0.78202],
10174 [0.78616, 0.78632, 0.78628],
10175 [0.79042, 0.79058, 0.79054],
10176 [0.79469, 0.79485, 0.79481],
10177 [0.79896, 0.79913, 0.79909],
10178 [0.80323, 0.8034, 0.80336],
10179 [0.80752, 0.80768, 0.80764],
10180 [0.8118, 0.81196, 0.81192],
10181 [0.81609, 0.81626, 0.81621],
10182 [0.82038, 0.82054, 0.8205],
10183 [0.82467, 0.82484, 0.8248],
10184 [0.82898, 0.82915, 0.82911],
10185 [0.83328, 0.83345, 0.83341],
10186 [0.83759, 0.83776, 0.83772],
10187 [0.84191, 0.84208, 0.84204],
10188 [0.84622, 0.84639, 0.84635],
10189 [0.85054, 0.85071, 0.85067],
10190 [0.85487, 0.85504, 0.855],
10191 [0.8592, 0.85937, 0.85933],
10192 [0.86354, 0.86371, 0.86367],
10193 [0.86787, 0.86805, 0.86801],
10194 [0.87222, 0.87239, 0.87235],
10195 [0.87656, 0.87673, 0.87669],
10196 [0.88091, 0.88109, 0.88104],
10197 [0.88527, 0.88544, 0.8854],
10198 [0.88962, 0.8898, 0.88976],
10199 [0.89399, 0.89417, 0.89412],
10200 [0.89835, 0.89853, 0.89849],
10201 [0.90272, 0.90291, 0.90286],
10202 [0.9071, 0.90728, 0.90724],
10203 [0.91148, 0.91166, 0.91161],
10204 [0.91585, 0.91604, 0.91599],
10205 [0.92024, 0.92043, 0.92038],
10206 [0.92463, 0.92482, 0.92477],
10207 [0.92903, 0.92921, 0.92917],
10208 [0.93342, 0.93361, 0.93356],
10209 [0.93783, 0.93802, 0.93797],
10210 [0.94224, 0.94243, 0.94238],
10211 [0.94664, 0.94683, 0.94679],
10212 [0.95106, 0.95125, 0.9512],
10213 [0.95548, 0.95567, 0.95562],
10214 [0.9599, 0.96009, 0.96004],
10215 [0.96432, 0.96451, 0.96446],
10216 [0.96875, 0.96894, 0.9689],
10217 [0.97318, 0.97338, 0.97333],
10218 [0.97762, 0.97781, 0.97777],
10219 [0.98206, 0.98226, 0.98221],
10220 [0.98651, 0.9867, 0.98666],
10221 [0.99095, 0.99115, 0.9911],
10222 [0.9954, 0.9956, 0.99555],
10223 [0.99986, 1, 1],
10224 ]
10225 b_linear_grey_0_100_c0 = bokeh_palette('linear_grey_0_100_c0',linear_grey_0_100_c0)
10226 m_linear_grey_0_100_c0 = mpl_cm('linear_grey_0_100_c0',linear_grey_0_100_c0)
10227 m_linear_grey_0_100_c0_r = mpl_cm('linear_grey_0_100_c0_r',list(reversed(linear_grey_0_100_c0)))
10228 gray = b_linear_grey_0_100_c0
10229 m_gray = m_linear_grey_0_100_c0
10230 m_gray_r = m_linear_grey_0_100_c0_r
10231 palette['gray'] = b_linear_grey_0_100_c0
10232 cm['gray'] = m_linear_grey_0_100_c0
10233 cm['gray_r'] = m_linear_grey_0_100_c0_r
10234 register_cmap('cet_gray',m_linear_grey_0_100_c0)
10235 register_cmap('cet_gray_r',m_linear_grey_0_100_c0_r)
10236
10237
10238
10239
10240 linear_grey_10_95_c0 = [\
10241 [0.10767, 0.1077, 0.1077],
10242 [0.11032, 0.11035, 0.11035],
10243 [0.11295, 0.11298, 0.11297],
10244 [0.11554, 0.11558, 0.11557],
10245 [0.1182, 0.11824, 0.11823],
10246 [0.12079, 0.12083, 0.12082],
10247 [0.12344, 0.12348, 0.12347],
10248 [0.12615, 0.12618, 0.12618],
10249 [0.12879, 0.12882, 0.12881],
10250 [0.13149, 0.13152, 0.13151],
10251 [0.13418, 0.13421, 0.1342],
10252 [0.13684, 0.13688, 0.13687],
10253 [0.13951, 0.13955, 0.13954],
10254 [0.14226, 0.1423, 0.14229],
10255 [0.14499, 0.14503, 0.14502],
10256 [0.1477, 0.14774, 0.14773],
10257 [0.15042, 0.15046, 0.15045],
10258 [0.15313, 0.15317, 0.15316],
10259 [0.15591, 0.15595, 0.15594],
10260 [0.15866, 0.1587, 0.15869],
10261 [0.16142, 0.16147, 0.16145],
10262 [0.16418, 0.16423, 0.16422],
10263 [0.16695, 0.16699, 0.16698],
10264 [0.16973, 0.16977, 0.16976],
10265 [0.17248, 0.17253, 0.17252],
10266 [0.17529, 0.17533, 0.17532],
10267 [0.17811, 0.17815, 0.17814],
10268 [0.18087, 0.18092, 0.1809],
10269 [0.18369, 0.18374, 0.18372],
10270 [0.18652, 0.18656, 0.18655],
10271 [0.18934, 0.18939, 0.18938],
10272 [0.19217, 0.19221, 0.1922],
10273 [0.19502, 0.19506, 0.19505],
10274 [0.19785, 0.1979, 0.19788],
10275 [0.20068, 0.20073, 0.20072],
10276 [0.20357, 0.20362, 0.20361],
10277 [0.20645, 0.2065, 0.20649],
10278 [0.20929, 0.20934, 0.20933],
10279 [0.21219, 0.21224, 0.21222],
10280 [0.21504, 0.21509, 0.21508],
10281 [0.21795, 0.218, 0.21799],
10282 [0.22086, 0.22091, 0.2209],
10283 [0.22374, 0.22379, 0.22377],
10284 [0.22666, 0.22671, 0.22669],
10285 [0.22954, 0.2296, 0.22958],
10286 [0.23248, 0.23253, 0.23252],
10287 [0.23542, 0.23547, 0.23546],
10288 [0.23832, 0.23838, 0.23836],
10289 [0.24127, 0.24133, 0.24131],
10290 [0.24419, 0.24425, 0.24424],
10291 [0.24716, 0.24722, 0.2472],
10292 [0.25009, 0.25015, 0.25014],
10293 [0.25308, 0.25313, 0.25312],
10294 [0.25603, 0.25608, 0.25607],
10295 [0.25902, 0.25908, 0.25906],
10296 [0.26198, 0.26204, 0.26203],
10297 [0.26496, 0.26502, 0.265],
10298 [0.26794, 0.268, 0.26798],
10299 [0.27095, 0.27101, 0.271],
10300 [0.27395, 0.27401, 0.274],
10301 [0.27695, 0.27702, 0.277],
10302 [0.27996, 0.28002, 0.28],
10303 [0.28298, 0.28304, 0.28303],
10304 [0.28598, 0.28604, 0.28603],
10305 [0.28902, 0.28909, 0.28907],
10306 [0.29205, 0.29212, 0.2921],
10307 [0.29508, 0.29514, 0.29513],
10308 [0.29812, 0.29818, 0.29817],
10309 [0.30116, 0.30123, 0.30121],
10310 [0.30422, 0.30429, 0.30427],
10311 [0.30728, 0.30734, 0.30733],
10312 [0.31036, 0.31043, 0.31041],
10313 [0.31342, 0.31349, 0.31347],
10314 [0.31649, 0.31656, 0.31654],
10315 [0.31957, 0.31964, 0.31962],
10316 [0.32266, 0.32273, 0.32271],
10317 [0.32572, 0.3258, 0.32578],
10318 [0.32883, 0.32891, 0.32889],
10319 [0.33193, 0.332, 0.33198],
10320 [0.33504, 0.33512, 0.3351],
10321 [0.33813, 0.3382, 0.33818],
10322 [0.34125, 0.34133, 0.34131],
10323 [0.34436, 0.34444, 0.34442],
10324 [0.3475, 0.34757, 0.34755],
10325 [0.35063, 0.3507, 0.35068],
10326 [0.35374, 0.35382, 0.3538],
10327 [0.35689, 0.35697, 0.35695],
10328 [0.36002, 0.3601, 0.36008],
10329 [0.36317, 0.36325, 0.36323],
10330 [0.36633, 0.36641, 0.36639],
10331 [0.36948, 0.36956, 0.36954],
10332 [0.37263, 0.37272, 0.3727],
10333 [0.3758, 0.37589, 0.37587],
10334 [0.37897, 0.37906, 0.37904],
10335 [0.38214, 0.38223, 0.38221],
10336 [0.38532, 0.3854, 0.38538],
10337 [0.38852, 0.3886, 0.38858],
10338 [0.3917, 0.39179, 0.39177],
10339 [0.39489, 0.39498, 0.39496],
10340 [0.3981, 0.39818, 0.39816],
10341 [0.4013, 0.40138, 0.40136],
10342 [0.40449, 0.40458, 0.40456],
10343 [0.40771, 0.4078, 0.40778],
10344 [0.41093, 0.41102, 0.411],
10345 [0.41415, 0.41423, 0.41421],
10346 [0.41738, 0.41747, 0.41744],
10347 [0.4206, 0.42068, 0.42066],
10348 [0.42383, 0.42392, 0.4239],
10349 [0.42708, 0.42717, 0.42715],
10350 [0.43031, 0.43041, 0.43038],
10351 [0.43355, 0.43364, 0.43362],
10352 [0.43681, 0.43691, 0.43688],
10353 [0.44007, 0.44016, 0.44014],
10354 [0.44333, 0.44342, 0.4434],
10355 [0.44659, 0.44668, 0.44666],
10356 [0.44986, 0.44995, 0.44993],
10357 [0.45313, 0.45322, 0.4532],
10358 [0.4564, 0.4565, 0.45647],
10359 [0.45968, 0.45978, 0.45976],
10360 [0.46296, 0.46306, 0.46303],
10361 [0.46625, 0.46635, 0.46633],
10362 [0.46956, 0.46966, 0.46963],
10363 [0.47284, 0.47294, 0.47292],
10364 [0.47615, 0.47625, 0.47623],
10365 [0.47946, 0.47956, 0.47953],
10366 [0.48276, 0.48286, 0.48284],
10367 [0.48607, 0.48618, 0.48615],
10368 [0.48939, 0.48949, 0.48947],
10369 [0.49271, 0.49281, 0.49279],
10370 [0.49603, 0.49614, 0.49611],
10371 [0.49936, 0.49947, 0.49944],
10372 [0.5027, 0.5028, 0.50278],
10373 [0.50603, 0.50614, 0.50612],
10374 [0.50938, 0.50949, 0.50946],
10375 [0.51273, 0.51284, 0.51281],
10376 [0.51607, 0.51618, 0.51615],
10377 [0.51943, 0.51954, 0.51951],
10378 [0.52279, 0.5229, 0.52287],
10379 [0.52615, 0.52626, 0.52624],
10380 [0.52952, 0.52963, 0.5296],
10381 [0.53289, 0.533, 0.53297],
10382 [0.53626, 0.53637, 0.53634],
10383 [0.53963, 0.53974, 0.53971],
10384 [0.54302, 0.54313, 0.5431],
10385 [0.54641, 0.54652, 0.54649],
10386 [0.54979, 0.5499, 0.54987],
10387 [0.55317, 0.55329, 0.55326],
10388 [0.55657, 0.55669, 0.55666],
10389 [0.55998, 0.56009, 0.56007],
10390 [0.56338, 0.5635, 0.56347],
10391 [0.56679, 0.56691, 0.56688],
10392 [0.57019, 0.57031, 0.57028],
10393 [0.57361, 0.57373, 0.5737],
10394 [0.57703, 0.57715, 0.57712],
10395 [0.58045, 0.58057, 0.58054],
10396 [0.58387, 0.58399, 0.58396],
10397 [0.5873, 0.58742, 0.58739],
10398 [0.59073, 0.59086, 0.59083],
10399 [0.59417, 0.5943, 0.59427],
10400 [0.59761, 0.59774, 0.59771],
10401 [0.60106, 0.60118, 0.60115],
10402 [0.60451, 0.60463, 0.6046],
10403 [0.60796, 0.60809, 0.60806],
10404 [0.61141, 0.61154, 0.61151],
10405 [0.61486, 0.61499, 0.61496],
10406 [0.61833, 0.61846, 0.61843],
10407 [0.62179, 0.62192, 0.62189],
10408 [0.62527, 0.62539, 0.62536],
10409 [0.62874, 0.62887, 0.62884],
10410 [0.63222, 0.63235, 0.63231],
10411 [0.63569, 0.63583, 0.63579],
10412 [0.63918, 0.63931, 0.63928],
10413 [0.64267, 0.6428, 0.64276],
10414 [0.64615, 0.64629, 0.64625],
10415 [0.64965, 0.64978, 0.64975],
10416 [0.65314, 0.65327, 0.65324],
10417 [0.65665, 0.65678, 0.65675],
10418 [0.66015, 0.66028, 0.66025],
10419 [0.66366, 0.6638, 0.66376],
10420 [0.66717, 0.6673, 0.66727],
10421 [0.67069, 0.67082, 0.67079],
10422 [0.6742, 0.67434, 0.6743],
10423 [0.67772, 0.67786, 0.67783],
10424 [0.68124, 0.68138, 0.68134],
10425 [0.68477, 0.68491, 0.68488],
10426 [0.68831, 0.68845, 0.68841],
10427 [0.69184, 0.69198, 0.69195],
10428 [0.69538, 0.69552, 0.69548],
10429 [0.69891, 0.69906, 0.69902],
10430 [0.70246, 0.7026, 0.70257],
10431 [0.70601, 0.70616, 0.70612],
10432 [0.70956, 0.70971, 0.70967],
10433 [0.71311, 0.71326, 0.71322],
10434 [0.71668, 0.71682, 0.71679],
10435 [0.72023, 0.72038, 0.72034],
10436 [0.7238, 0.72394, 0.72391],
10437 [0.72736, 0.72751, 0.72748],
10438 [0.73093, 0.73108, 0.73105],
10439 [0.73451, 0.73466, 0.73463],
10440 [0.73808, 0.73823, 0.7382],
10441 [0.74167, 0.74182, 0.74178],
10442 [0.74525, 0.7454, 0.74536],
10443 [0.74884, 0.74899, 0.74895],
10444 [0.75243, 0.75258, 0.75254],
10445 [0.75602, 0.75618, 0.75614],
10446 [0.75961, 0.75977, 0.75973],
10447 [0.76322, 0.76337, 0.76333],
10448 [0.76682, 0.76697, 0.76694],
10449 [0.77043, 0.77058, 0.77055],
10450 [0.77403, 0.77419, 0.77415],
10451 [0.77765, 0.77781, 0.77777],
10452 [0.78126, 0.78142, 0.78138],
10453 [0.78489, 0.78504, 0.785],
10454 [0.78851, 0.78867, 0.78863],
10455 [0.79213, 0.79229, 0.79225],
10456 [0.79576, 0.79592, 0.79588],
10457 [0.79939, 0.79955, 0.79951],
10458 [0.80302, 0.80318, 0.80314],
10459 [0.80666, 0.80683, 0.80679],
10460 [0.8103, 0.81046, 0.81042],
10461 [0.81394, 0.81411, 0.81406],
10462 [0.81759, 0.81775, 0.81771],
10463 [0.82124, 0.82141, 0.82136],
10464 [0.82489, 0.82506, 0.82501],
10465 [0.82855, 0.82872, 0.82867],
10466 [0.83221, 0.83237, 0.83233],
10467 [0.83587, 0.83604, 0.83599],
10468 [0.83953, 0.8397, 0.83966],
10469 [0.8432, 0.84337, 0.84333],
10470 [0.84687, 0.84704, 0.847],
10471 [0.85054, 0.85071, 0.85067],
10472 [0.85422, 0.85439, 0.85435],
10473 [0.8579, 0.85807, 0.85803],
10474 [0.86158, 0.86176, 0.86171],
10475 [0.86527, 0.86544, 0.8654],
10476 [0.86896, 0.86913, 0.86909],
10477 [0.87265, 0.87282, 0.87278],
10478 [0.87634, 0.87652, 0.87647],
10479 [0.88004, 0.88022, 0.88017],
10480 [0.88374, 0.88392, 0.88388],
10481 [0.88744, 0.88762, 0.88758],
10482 [0.89115, 0.89133, 0.89128],
10483 [0.89486, 0.89504, 0.895],
10484 [0.89857, 0.89875, 0.89871],
10485 [0.90229, 0.90247, 0.90242],
10486 [0.90601, 0.90619, 0.90614],
10487 [0.90972, 0.90991, 0.90986],
10488 [0.91345, 0.91363, 0.91359],
10489 [0.91718, 0.91736, 0.91732],
10490 [0.9209, 0.92108, 0.92104],
10491 [0.92463, 0.92482, 0.92477],
10492 [0.92837, 0.92855, 0.92851],
10493 [0.9321, 0.93229, 0.93224],
10494 [0.93585, 0.93604, 0.93599],
10495 [0.93959, 0.93978, 0.93973],
10496 [0.94334, 0.94353, 0.94348],
10497 ]
10498 b_linear_grey_10_95_c0 = bokeh_palette('linear_grey_10_95_c0',linear_grey_10_95_c0)
10499 m_linear_grey_10_95_c0 = mpl_cm('linear_grey_10_95_c0',linear_grey_10_95_c0)
10500 m_linear_grey_10_95_c0_r = mpl_cm('linear_grey_10_95_c0_r',list(reversed(linear_grey_10_95_c0)))
10501 dimgray = b_linear_grey_10_95_c0
10502 m_dimgray = m_linear_grey_10_95_c0
10503 m_dimgray_r = m_linear_grey_10_95_c0_r
10504 palette['dimgray'] = b_linear_grey_10_95_c0
10505 cm['dimgray'] = m_linear_grey_10_95_c0
10506 cm['dimgray_r'] = m_linear_grey_10_95_c0_r
10507 register_cmap('cet_dimgray',m_linear_grey_10_95_c0)
10508 register_cmap('cet_dimgray_r',m_linear_grey_10_95_c0_r)
10509
10510
10511
10512
10513 linear_kry_5_95_c72 = [\
10514 [0.066001, 0.066024, 0.066019],
10515 [0.07965, 0.066744, 0.064745],
10516 [0.091664, 0.06747, 0.063475],
10517 [0.10228, 0.068214, 0.06216],
10518 [0.112, 0.068994, 0.060816],
10519 [0.12092, 0.069706, 0.059585],
10520 [0.12971, 0.070185, 0.058154],
10521 [0.13843, 0.07042, 0.05692],
10522 [0.14709, 0.070382, 0.055604],
10523 [0.15576, 0.07009, 0.054295],
10524 [0.16433, 0.069694, 0.052994],
10525 [0.17278, 0.069179, 0.051712],
10526 [0.18118, 0.068484, 0.050432],
10527 [0.18954, 0.067685, 0.049199],
10528 [0.1978, 0.066788, 0.047758],
10529 [0.20605, 0.065769, 0.046454],
10530 [0.2142, 0.064648, 0.045151],
10531 [0.2223, 0.063428, 0.043725],
10532 [0.23036, 0.062012, 0.042429],
10533 [0.23838, 0.060521, 0.04109],
10534 [0.24634, 0.058898, 0.039699],
10535 [0.25428, 0.057101, 0.038324],
10536 [0.26215, 0.055158, 0.036964],
10537 [0.26998, 0.053082, 0.035663],
10538 [0.27773, 0.050917, 0.034117],
10539 [0.28544, 0.048622, 0.032846],
10540 [0.29312, 0.046013, 0.031565],
10541 [0.30072, 0.043344, 0.030323],
10542 [0.30827, 0.040658, 0.029105],
10543 [0.31576, 0.037722, 0.02791],
10544 [0.32318, 0.034637, 0.02674],
10545 [0.33052, 0.031576, 0.025595],
10546 [0.33779, 0.028628, 0.024479],
10547 [0.34497, 0.025745, 0.023396],
10548 [0.35205, 0.022943, 0.022345],
10549 [0.35905, 0.020248, 0.021325],
10550 [0.36595, 0.017697, 0.02034],
10551 [0.37272, 0.015331, 0.01939],
10552 [0.37938, 0.01319, 0.01848],
10553 [0.38589, 0.01125, 0.017611],
10554 [0.39225, 0.0096476, 0.016788],
10555 [0.39845, 0.0085386, 0.016013],
10556 [0.40447, 0.0079151, 0.015288],
10557 [0.41036, 0.0076915, 0.014615],
10558 [0.41618, 0.0076329, 0.013987],
10559 [0.42199, 0.007602, 0.01339],
10560 [0.42783, 0.0075831, 0.012837],
10561 [0.43365, 0.0075764, 0.012347],
10562 [0.4395, 0.0075827, 0.011859],
10563 [0.44534, 0.0076027, 0.011316],
10564 [0.4512, 0.0076373, 0.010796],
10565 [0.45705, 0.0076872, 0.010385],
10566 [0.46291, 0.0077536, 0.010055],
10567 [0.46879, 0.0078379, 0.0097685],
10568 [0.47467, 0.0079404, 0.0095068],
10569 [0.48054, 0.0080616, 0.0092717],
10570 [0.48643, 0.0082023, 0.0090674],
10571 [0.49232, 0.0083637, 0.0088963],
10572 [0.49823, 0.0085472, 0.008759],
10573 [0.50414, 0.0087542, 0.0086553],
10574 [0.51004, 0.008987, 0.0085858],
10575 [0.51595, 0.0092456, 0.0085516],
10576 [0.52187, 0.0095265, 0.0085507],
10577 [0.5278, 0.0098238, 0.0085815],
10578 [0.53373, 0.010138, 0.0086438],
10579 [0.53967, 0.010498, 0.0087375],
10580 [0.54563, 0.010949, 0.0088628],
10581 [0.55158, 0.011488, 0.0090195],
10582 [0.55753, 0.012012, 0.0092082],
10583 [0.56349, 0.012487, 0.0094284],
10584 [0.56945, 0.012988, 0.0096743],
10585 [0.57543, 0.013545, 0.009933],
10586 [0.5814, 0.014124, 0.010192],
10587 [0.5874, 0.014709, 0.010451],
10588 [0.59341, 0.015309, 0.010717],
10589 [0.59942, 0.015921, 0.010993],
10590 [0.60544, 0.016546, 0.011263],
10591 [0.61149, 0.017183, 0.011511],
10592 [0.61754, 0.017832, 0.011726],
10593 [0.62361, 0.018494, 0.011906],
10594 [0.62967, 0.019169, 0.012055],
10595 [0.63576, 0.019858, 0.012179],
10596 [0.64186, 0.020559, 0.01228],
10597 [0.64796, 0.021273, 0.012363],
10598 [0.65409, 0.022, 0.012427],
10599 [0.66022, 0.022741, 0.012473],
10600 [0.66635, 0.023496, 0.012501],
10601 [0.67251, 0.024264, 0.012512],
10602 [0.67867, 0.025046, 0.012503],
10603 [0.68485, 0.025842, 0.012477],
10604 [0.69103, 0.026652, 0.012431],
10605 [0.69722, 0.027476, 0.012369],
10606 [0.70343, 0.028316, 0.012312],
10607 [0.70965, 0.02917, 0.012261],
10608 [0.71588, 0.030041, 0.012218],
10609 [0.7221, 0.030928, 0.012182],
10610 [0.72835, 0.031827, 0.012155],
10611 [0.73461, 0.032755, 0.012137],
10612 [0.74086, 0.033657, 0.012129],
10613 [0.74714, 0.034746, 0.01213],
10614 [0.7534, 0.035909, 0.012143],
10615 [0.75965, 0.037152, 0.012168],
10616 [0.76588, 0.038639, 0.012207],
10617 [0.77207, 0.040359, 0.012259],
10618 [0.77825, 0.042283, 0.012323],
10619 [0.7844, 0.044355, 0.0124],
10620 [0.79052, 0.046616, 0.012491],
10621 [0.79662, 0.049121, 0.012597],
10622 [0.80269, 0.051607, 0.01272],
10623 [0.80874, 0.054357, 0.012862],
10624 [0.81476, 0.057256, 0.013025],
10625 [0.82076, 0.060328, 0.013209],
10626 [0.82673, 0.063454, 0.013414],
10627 [0.83267, 0.066671, 0.01364],
10628 [0.83859, 0.070023, 0.013884],
10629 [0.84448, 0.073512, 0.014147],
10630 [0.85034, 0.076937, 0.014432],
10631 [0.85618, 0.080598, 0.014739],
10632 [0.86199, 0.084349, 0.015072],
10633 [0.86776, 0.088098, 0.015429],
10634 [0.87351, 0.09196, 0.015811],
10635 [0.87924, 0.095821, 0.016218],
10636 [0.88494, 0.099784, 0.016653],
10637 [0.89061, 0.10383, 0.017114],
10638 [0.89625, 0.10787, 0.017605],
10639 [0.90186, 0.11205, 0.018127],
10640 [0.90744, 0.11624, 0.018679],
10641 [0.91299, 0.12043, 0.019262],
10642 [0.91846, 0.12485, 0.019871],
10643 [0.92381, 0.12964, 0.020493],
10644 [0.92898, 0.13485, 0.021122],
10645 [0.93399, 0.14044, 0.02176],
10646 [0.93881, 0.14642, 0.022407],
10647 [0.94345, 0.15278, 0.023063],
10648 [0.94791, 0.15946, 0.023731],
10649 [0.95218, 0.16642, 0.024411],
10650 [0.95628, 0.17361, 0.025105],
10651 [0.9602, 0.18101, 0.025814],
10652 [0.96394, 0.18866, 0.026541],
10653 [0.9675, 0.19646, 0.027287],
10654 [0.97086, 0.20443, 0.028053],
10655 [0.97403, 0.21254, 0.028843],
10656 [0.97702, 0.22083, 0.029658],
10657 [0.97982, 0.22918, 0.0305],
10658 [0.98243, 0.23769, 0.031373],
10659 [0.98485, 0.24624, 0.032279],
10660 [0.98708, 0.25493, 0.03322],
10661 [0.98911, 0.26367, 0.034197],
10662 [0.99095, 0.27247, 0.035441],
10663 [0.99259, 0.28137, 0.036475],
10664 [0.99402, 0.29032, 0.0376],
10665 [0.99526, 0.29935, 0.038765],
10666 [0.99629, 0.3084, 0.039989],
10667 [0.99713, 0.31749, 0.041278],
10668 [0.99777, 0.32662, 0.042522],
10669 [0.9982, 0.3358, 0.043828],
10670 [0.99844, 0.34498, 0.045261],
10671 [0.99859, 0.35407, 0.04666],
10672 [0.99869, 0.36301, 0.048013],
10673 [0.99878, 0.37178, 0.049508],
10674 [0.99884, 0.38043, 0.050843],
10675 [0.99888, 0.38894, 0.052219],
10676 [0.99889, 0.39731, 0.05362],
10677 [0.99887, 0.40558, 0.055042],
10678 [0.99884, 0.41373, 0.056502],
10679 [0.99878, 0.42178, 0.057786],
10680 [0.99869, 0.42975, 0.059296],
10681 [0.99857, 0.43763, 0.060625],
10682 [0.99844, 0.4454, 0.061996],
10683 [0.99827, 0.45312, 0.063411],
10684 [0.99808, 0.46074, 0.064752],
10685 [0.99787, 0.46831, 0.066112],
10686 [0.99763, 0.47581, 0.067489],
10687 [0.99736, 0.48323, 0.068891],
10688 [0.99707, 0.49061, 0.070164],
10689 [0.99675, 0.49792, 0.071543],
10690 [0.9964, 0.50517, 0.072849],
10691 [0.99603, 0.51237, 0.074177],
10692 [0.99563, 0.51953, 0.075448],
10693 [0.9952, 0.52664, 0.076731],
10694 [0.99474, 0.53369, 0.078024],
10695 [0.99426, 0.54072, 0.079325],
10696 [0.99375, 0.54769, 0.08063],
10697 [0.99322, 0.55463, 0.081958],
10698 [0.99265, 0.56153, 0.083158],
10699 [0.99204, 0.5684, 0.084524],
10700 [0.99138, 0.57524, 0.085856],
10701 [0.99067, 0.58206, 0.087485],
10702 [0.98991, 0.58886, 0.089115],
10703 [0.98909, 0.59566, 0.090908],
10704 [0.98821, 0.60242, 0.092755],
10705 [0.98728, 0.60918, 0.094848],
10706 [0.98629, 0.6159, 0.096892],
10707 [0.98524, 0.62262, 0.099162],
10708 [0.98414, 0.62932, 0.1015],
10709 [0.98297, 0.63601, 0.10396],
10710 [0.98175, 0.64268, 0.10656],
10711 [0.98046, 0.64934, 0.10919],
10712 [0.97912, 0.65599, 0.11195],
10713 [0.97771, 0.66262, 0.11474],
10714 [0.97623, 0.66924, 0.11771],
10715 [0.9747, 0.67585, 0.12072],
10716 [0.9731, 0.68244, 0.12383],
10717 [0.97144, 0.68904, 0.12703],
10718 [0.9697, 0.69561, 0.13037],
10719 [0.96791, 0.70217, 0.1337],
10720 [0.96603, 0.70874, 0.13715],
10721 [0.96409, 0.71529, 0.14067],
10722 [0.96208, 0.72182, 0.14425],
10723 [0.96, 0.72836, 0.14791],
10724 [0.95785, 0.73488, 0.15162],
10725 [0.95563, 0.74139, 0.15542],
10726 [0.95333, 0.74791, 0.15928],
10727 [0.95104, 0.75439, 0.16306],
10728 [0.94892, 0.76075, 0.16643],
10729 [0.94705, 0.767, 0.16936],
10730 [0.9454, 0.77315, 0.1718],
10731 [0.94394, 0.7792, 0.1739],
10732 [0.94268, 0.78516, 0.17562],
10733 [0.94159, 0.79104, 0.17704],
10734 [0.94067, 0.79684, 0.17816],
10735 [0.93991, 0.80258, 0.17893],
10736 [0.93929, 0.80825, 0.17943],
10737 [0.93881, 0.81387, 0.1797],
10738 [0.93845, 0.81943, 0.17972],
10739 [0.9382, 0.82494, 0.17952],
10740 [0.93807, 0.83042, 0.17911],
10741 [0.93806, 0.83583, 0.17845],
10742 [0.93816, 0.84121, 0.17756],
10743 [0.93835, 0.84655, 0.17643],
10744 [0.93863, 0.85186, 0.17517],
10745 [0.93901, 0.85713, 0.17363],
10746 [0.93948, 0.86238, 0.17189],
10747 [0.94002, 0.86758, 0.16998],
10748 [0.94064, 0.87277, 0.16783],
10749 [0.94135, 0.87792, 0.16542],
10750 [0.94214, 0.88305, 0.16286],
10751 [0.94298, 0.88816, 0.16003],
10752 [0.94391, 0.89324, 0.15697],
10753 [0.9449, 0.8983, 0.15365],
10754 [0.94594, 0.90334, 0.15015],
10755 [0.94707, 0.90836, 0.14627],
10756 [0.94825, 0.91336, 0.14216],
10757 [0.94948, 0.91834, 0.13776],
10758 [0.95079, 0.92331, 0.13295],
10759 [0.95212, 0.92826, 0.12782],
10760 [0.95354, 0.93319, 0.12222],
10761 [0.955, 0.93811, 0.11627],
10762 [0.95649, 0.94302, 0.1098],
10763 [0.95807, 0.94791, 0.10259],
10764 [0.95966, 0.95279, 0.094821],
10765 [0.96132, 0.95766, 0.086007],
10766 [0.96302, 0.96252, 0.076202],
10767 [0.96476, 0.96736, 0.065035],
10768 [0.96656, 0.97219, 0.051675],
10769 [0.96837, 0.97701, 0.035491],
10770 ]
10771 b_linear_kry_5_95_c72 = bokeh_palette('linear_kry_5_95_c72',linear_kry_5_95_c72)
10772 m_linear_kry_5_95_c72 = mpl_cm('linear_kry_5_95_c72',linear_kry_5_95_c72)
10773 m_linear_kry_5_95_c72_r = mpl_cm('linear_kry_5_95_c72_r',list(reversed(linear_kry_5_95_c72)))
10774
10775
10776
10777
10778 linear_kry_5_98_c75 = [\
10779 [0.066001, 0.066024, 0.066019],
10780 [0.080538, 0.066611, 0.064712],
10781 [0.093113, 0.067208, 0.063412],
10782 [0.10433, 0.067823, 0.062042],
10783 [0.11447, 0.068466, 0.060693],
10784 [0.12392, 0.069079, 0.059406],
10785 [0.13324, 0.069387, 0.057942],
10786 [0.1425, 0.069367, 0.056714],
10787 [0.1517, 0.069013, 0.055346],
10788 [0.16087, 0.068361, 0.05402],
10789 [0.16995, 0.067575, 0.052699],
10790 [0.17892, 0.066658, 0.051395],
10791 [0.18783, 0.065607, 0.050099],
10792 [0.19664, 0.064412, 0.04882],
10793 [0.20537, 0.063105, 0.047405],
10794 [0.21407, 0.061489, 0.046005],
10795 [0.2227, 0.059924, 0.044746],
10796 [0.23128, 0.057935, 0.043254],
10797 [0.23978, 0.055984, 0.042035],
10798 [0.24826, 0.053694, 0.040618],
10799 [0.25665, 0.051268, 0.039228],
10800 [0.265, 0.048696, 0.03786],
10801 [0.2733, 0.045729, 0.036506],
10802 [0.28153, 0.042641, 0.03519],
10803 [0.28972, 0.039309, 0.033667],
10804 [0.29783, 0.035771, 0.032419],
10805 [0.3059, 0.031918, 0.031169],
10806 [0.31386, 0.028215, 0.029947],
10807 [0.32176, 0.024452, 0.028752],
10808 [0.32961, 0.020653, 0.027583],
10809 [0.33736, 0.016844, 0.026442],
10810 [0.34502, 0.013048, 0.025331],
10811 [0.35258, 0.0091504, 0.024255],
10812 [0.36003, 0.005529, 0.023213],
10813 [0.36736, 0.0020418, 0.022204],
10814 [0.37459, 0, 0.021232],
10815 [0.38167, 0, 0.020297],
10816 [0.38862, 0, 0.019403],
10817 [0.39539, 0, 0.018552],
10818 [0.40197, 0, 0.017747],
10819 [0.40837, 0, 0.016994],
10820 [0.41456, 0, 0.016295],
10821 [0.42062, 0, 0.015634],
10822 [0.42666, 0, 0.014992],
10823 [0.4327, 0, 0.014366],
10824 [0.43874, 0, 0.013752],
10825 [0.44481, 0, 0.013144],
10826 [0.45086, 0, 0.012574],
10827 [0.45693, 0, 0.012021],
10828 [0.463, 0, 0.011365],
10829 [0.4691, 0, 0.010683],
10830 [0.47519, 0, 0.010135],
10831 [0.48128, 0, 0.0096387],
10832 [0.48739, 0, 0.0091289],
10833 [0.49349, 0, 0.0086244],
10834 [0.49961, 0, 0.0081373],
10835 [0.50573, 0, 0.0076619],
10836 [0.51187, 0, 0.0071948],
10837 [0.51802, 0, 0.0067375],
10838 [0.52416, 0, 0.0062922],
10839 [0.53031, 0, 0.0058577],
10840 [0.53647, 0, 0.0054319],
10841 [0.54263, 0, 0.0050145],
10842 [0.54881, 0, 0.0046053],
10843 [0.55498, 0, 0.0042044],
10844 [0.56116, 0, 0.0038134],
10845 [0.56735, 0, 0.0034314],
10846 [0.57355, 0, 0.0030565],
10847 [0.57975, 0, 0.0026882],
10848 [0.58596, 0, 0.0023271],
10849 [0.59219, 0, 0.0019742],
10850 [0.59842, 0, 0.0016322],
10851 [0.60468, 0, 0.001301],
10852 [0.61096, 0, 0.00097818],
10853 [0.61724, 0, 0.00066352],
10854 [0.62356, 0, 0.00035687],
10855 [0.62988, 0, 5.8077e-05],
10856 [0.63622, 0, 0],
10857 [0.64258, 0, 0],
10858 [0.64896, 0, 0],
10859 [0.65535, 0, 0],
10860 [0.66176, 0, 0],
10861 [0.66819, 0, 0],
10862 [0.67463, 0, 0],
10863 [0.68108, 0, 0],
10864 [0.68756, 0, 0],
10865 [0.69405, 0, 0],
10866 [0.70057, 0, 0],
10867 [0.7071, 0, 0],
10868 [0.71364, 0, 0],
10869 [0.7202, 0, 0],
10870 [0.72678, 0, 0],
10871 [0.73337, 0, 0],
10872 [0.73999, 0, 0],
10873 [0.74661, 0, 0],
10874 [0.75325, 0, 0],
10875 [0.75991, 0, 0],
10876 [0.76657, 0, 0],
10877 [0.77322, 0, 0],
10878 [0.77985, 0, 0],
10879 [0.78648, 0, 0],
10880 [0.79309, 0, 0],
10881 [0.79969, 0, 0],
10882 [0.80627, 0, 0],
10883 [0.81283, 0, 0],
10884 [0.81939, 0, 0],
10885 [0.82593, 0, 0],
10886 [0.83246, 0, 0],
10887 [0.83897, 0, 0],
10888 [0.84547, 0, 0],
10889 [0.85195, 0, 0],
10890 [0.85842, 0, 0],
10891 [0.86487, 0, 0],
10892 [0.87132, 0, 0],
10893 [0.87774, 0, 0],
10894 [0.88415, 0, 0],
10895 [0.89054, 0, 0],
10896 [0.89692, 0, 0],
10897 [0.90328, 0, 0],
10898 [0.90963, 0, 0],
10899 [0.91595, 0, 0],
10900 [0.92227, 0.0017832, 0],
10901 [0.92856, 0.0061612, 0],
10902 [0.93484, 0.010887, 0],
10903 [0.94104, 0.016478, 0],
10904 [0.9471, 0.023267, 0],
10905 [0.95296, 0.031841, 0],
10906 [0.95862, 0.042415, 0],
10907 [0.96409, 0.053281, 0],
10908 [0.96937, 0.064278, 0],
10909 [0.97446, 0.075188, 0],
10910 [0.97936, 0.086066, 0],
10911 [0.98405, 0.096997, 0],
10912 [0.98853, 0.10794, 0],
10913 [0.99282, 0.11888, 0],
10914 [0.9969, 0.12973, 0],
10915 [1, 0.14054, 0],
10916 [1, 0.1513, 0],
10917 [1, 0.1621, 0],
10918 [1, 0.17286, 0],
10919 [1, 0.18361, 0],
10920 [1, 0.19437, 0],
10921 [1, 0.20505, 0],
10922 [1, 0.21574, 0],
10923 [1, 0.22642, 0],
10924 [1, 0.23711, 0],
10925 [1, 0.24776, 0],
10926 [1, 0.25838, 0],
10927 [1, 0.26903, 0],
10928 [1, 0.27963, 0],
10929 [1, 0.2902, 0],
10930 [1, 0.30076, 0],
10931 [1, 0.31115, 0],
10932 [1, 0.32126, 0],
10933 [1, 0.33113, 0],
10934 [1, 0.34081, 0],
10935 [1, 0.35027, 0],
10936 [1, 0.35954, 0],
10937 [1, 0.36866, 0.00010807],
10938 [1, 0.3776, 0.0016338],
10939 [1, 0.3864, 0.0031726],
10940 [1, 0.39508, 0.0047225],
10941 [1, 0.40364, 0.0062803],
10942 [1, 0.41207, 0.0078416],
10943 [1, 0.42039, 0.0094129],
10944 [1, 0.42862, 0.011021],
10945 [1, 0.43675, 0.012734],
10946 [1, 0.44479, 0.014303],
10947 [1, 0.45274, 0.015864],
10948 [1, 0.4606, 0.017417],
10949 [1, 0.4684, 0.018959],
10950 [1, 0.47614, 0.020491],
10951 [1, 0.48379, 0.022011],
10952 [1, 0.4914, 0.023517],
10953 [1, 0.49892, 0.025006],
10954 [1, 0.5064, 0.026472],
10955 [1, 0.51383, 0.027913],
10956 [1, 0.52119, 0.02933],
10957 [1, 0.52852, 0.030724],
10958 [1, 0.53577, 0.032109],
10959 [1, 0.54298, 0.033495],
10960 [1, 0.55012, 0.035116],
10961 [1, 0.55721, 0.036562],
10962 [1, 0.56423, 0.038032],
10963 [1, 0.57119, 0.039515],
10964 [1, 0.57811, 0.041015],
10965 [1, 0.58499, 0.042457],
10966 [1, 0.59181, 0.043871],
10967 [1, 0.59857, 0.045349],
10968 [1, 0.6053, 0.046804],
10969 [1, 0.61199, 0.048174],
10970 [1, 0.61864, 0.049638],
10971 [1, 0.62524, 0.050967],
10972 [1, 0.6318, 0.052314],
10973 [1, 0.63833, 0.053669],
10974 [1, 0.64482, 0.05503],
10975 [1, 0.65128, 0.056416],
10976 [1, 0.6577, 0.057622],
10977 [1, 0.66409, 0.05901],
10978 [1, 0.67045, 0.060291],
10979 [1, 0.67678, 0.061456],
10980 [1, 0.68308, 0.062815],
10981 [1, 0.68935, 0.063988],
10982 [1, 0.69558, 0.065188],
10983 [1, 0.70178, 0.06638],
10984 [1, 0.70798, 0.067574],
10985 [1, 0.71415, 0.068771],
10986 [1, 0.72028, 0.069853],
10987 [1, 0.72637, 0.07091],
10988 [1, 0.73244, 0.071928],
10989 [1, 0.73847, 0.072954],
10990 [1, 0.74448, 0.073945],
10991 [1, 0.75047, 0.074848],
10992 [1, 0.75643, 0.075762],
10993 [1, 0.76237, 0.076661],
10994 [1, 0.7683, 0.077556],
10995 [1, 0.77421, 0.078448],
10996 [1, 0.78011, 0.079336],
10997 [1, 0.786, 0.080219],
10998 [1, 0.79186, 0.081101],
10999 [1, 0.79771, 0.081992],
11000 [1, 0.80356, 0.082776],
11001 [1, 0.80939, 0.083622],
11002 [1, 0.81521, 0.084477],
11003 [1, 0.82102, 0.085237],
11004 [1, 0.82682, 0.086035],
11005 [1, 0.83261, 0.086929],
11006 [1, 0.83839, 0.087733],
11007 [1, 0.84416, 0.088519],
11008 [1, 0.84993, 0.089324],
11009 [1, 0.85569, 0.090123],
11010 [1, 0.86143, 0.090933],
11011 [1, 0.86717, 0.091749],
11012 [1, 0.87291, 0.092489],
11013 [1, 0.87864, 0.093256],
11014 [1, 0.88437, 0.094098],
11015 [1, 0.89009, 0.094916],
11016 [1, 0.8958, 0.095666],
11017 [1, 0.90151, 0.096403],
11018 [1, 0.90721, 0.097221],
11019 [1, 0.91291, 0.098051],
11020 [1, 0.9186, 0.098807],
11021 [1, 0.92429, 0.099584],
11022 [1, 0.92997, 0.10036],
11023 [1, 0.93565, 0.10115],
11024 [1, 0.94133, 0.10194],
11025 [1, 0.947, 0.10274],
11026 [1, 0.95267, 0.10354],
11027 [1, 0.95834, 0.10428],
11028 [1, 0.964, 0.10506],
11029 [1, 0.96966, 0.10589],
11030 [1, 0.97532, 0.1067],
11031 [1, 0.98098, 0.10746],
11032 [1, 0.98663, 0.10821],
11033 [1, 0.99228, 0.10903],
11034 [1, 0.99792, 0.10986],
11035 ]
11036 b_linear_kry_5_98_c75 = bokeh_palette('linear_kry_5_98_c75',linear_kry_5_98_c75)
11037 m_linear_kry_5_98_c75 = mpl_cm('linear_kry_5_98_c75',linear_kry_5_98_c75)
11038 m_linear_kry_5_98_c75_r = mpl_cm('linear_kry_5_98_c75_r',list(reversed(linear_kry_5_98_c75)))
11039
11040
11041
11042
11043 linear_kryw_0_100_c71 = [\
11044 [0, 0, 0],
11045 [0.027065, 2.143e-05, 0],
11046 [0.052054, 7.4728e-05, 0],
11047 [0.071511, 0.00013914, 0],
11048 [0.08742, 0.0002088, 0],
11049 [0.10109, 0.00028141, 0],
11050 [0.11337, 0.000356, 2.4266e-17],
11051 [0.12439, 0.00043134, 3.3615e-17],
11052 [0.13463, 0.00050796, 2.1604e-17],
11053 [0.14411, 0.0005856, 0],
11054 [0.15292, 0.00070304, 0],
11055 [0.16073, 0.0013432, 0],
11056 [0.16871, 0.0014516, 0],
11057 [0.17657, 0.0012408, 0],
11058 [0.18364, 0.0015336, 0],
11059 [0.19052, 0.0017515, 0],
11060 [0.19751, 0.0015146, 0],
11061 [0.20401, 0.0015249, 0],
11062 [0.20994, 0.0019639, 0],
11063 [0.21605, 0.002031, 0],
11064 [0.22215, 0.0017559, 0],
11065 [0.22808, 0.001546, 1.8755e-05],
11066 [0.23378, 0.0016315, 3.5012e-05],
11067 [0.23955, 0.0017194, 3.3352e-05],
11068 [0.24531, 0.0018097, 1.8559e-05],
11069 [0.25113, 0.0019038, 1.9139e-05],
11070 [0.25694, 0.0020015, 3.5308e-05],
11071 [0.26278, 0.0021017, 3.2613e-05],
11072 [0.26864, 0.0022048, 2.0338e-05],
11073 [0.27451, 0.0023119, 2.2453e-05],
11074 [0.28041, 0.0024227, 3.6003e-05],
11075 [0.28633, 0.0025363, 2.9817e-05],
11076 [0.29229, 0.0026532, 1.9559e-05],
11077 [0.29824, 0.0027747, 2.7666e-05],
11078 [0.30423, 0.0028999, 3.5752e-05],
11079 [0.31026, 0.0030279, 2.3231e-05],
11080 [0.31628, 0.0031599, 1.2902e-05],
11081 [0.32232, 0.0032974, 3.2915e-05],
11082 [0.32838, 0.0034379, 3.2803e-05],
11083 [0.33447, 0.0035819, 2.0757e-05],
11084 [0.34057, 0.003731, 2.3831e-05],
11085 [0.34668, 0.0038848, 3.502e-05],
11086 [0.35283, 0.0040418, 2.4468e-05],
11087 [0.35897, 0.0042032, 1.1444e-05],
11088 [0.36515, 0.0043708, 3.2793e-05],
11089 [0.37134, 0.0045418, 3.012e-05],
11090 [0.37756, 0.0047169, 1.4846e-05],
11091 [0.38379, 0.0048986, 2.796e-05],
11092 [0.39003, 0.0050848, 3.2782e-05],
11093 [0.3963, 0.0052751, 1.9244e-05],
11094 [0.40258, 0.0054715, 2.2667e-05],
11095 [0.40888, 0.0056736, 3.3223e-05],
11096 [0.41519, 0.0058798, 2.159e-05],
11097 [0.42152, 0.0060922, 1.8214e-05],
11098 [0.42788, 0.0063116, 3.2525e-05],
11099 [0.43424, 0.0065353, 2.2247e-05],
11100 [0.44062, 0.006765, 1.5852e-05],
11101 [0.44702, 0.0070024, 3.1769e-05],
11102 [0.45344, 0.0072442, 2.1245e-05],
11103 [0.45987, 0.0074929, 1.5726e-05],
11104 [0.46631, 0.0077499, 3.0976e-05],
11105 [0.47277, 0.0080108, 1.8722e-05],
11106 [0.47926, 0.0082789, 1.9285e-05],
11107 [0.48574, 0.0085553, 3.0063e-05],
11108 [0.49225, 0.0088392, 1.4313e-05],
11109 [0.49878, 0.0091356, 2.3404e-05],
11110 [0.50531, 0.0094374, 2.8099e-05],
11111 [0.51187, 0.0097365, 6.4695e-06],
11112 [0.51844, 0.010039, 2.5791e-05],
11113 [0.52501, 0.010354, 2.4393e-05],
11114 [0.53162, 0.010689, 1.6037e-05],
11115 [0.53825, 0.011031, 2.7295e-05],
11116 [0.54489, 0.011393, 1.5848e-05],
11117 [0.55154, 0.011789, 2.3111e-05],
11118 [0.55818, 0.012159, 2.5416e-05],
11119 [0.56485, 0.012508, 1.5064e-05],
11120 [0.57154, 0.012881, 2.541e-05],
11121 [0.57823, 0.013283, 1.6166e-05],
11122 [0.58494, 0.013701, 2.263e-05],
11123 [0.59166, 0.014122, 2.3316e-05],
11124 [0.59839, 0.014551, 1.9432e-05],
11125 [0.60514, 0.014994, 2.4323e-05],
11126 [0.6119, 0.01545, 1.3929e-05],
11127 [0.61868, 0.01592, 2.1615e-05],
11128 [0.62546, 0.016401, 1.5846e-05],
11129 [0.63226, 0.016897, 2.0838e-05],
11130 [0.63907, 0.017407, 1.9549e-05],
11131 [0.64589, 0.017931, 2.0961e-05],
11132 [0.65273, 0.018471, 2.0737e-05],
11133 [0.65958, 0.019026, 2.0621e-05],
11134 [0.66644, 0.019598, 2.0675e-05],
11135 [0.67332, 0.020187, 2.0301e-05],
11136 [0.68019, 0.020793, 2.0029e-05],
11137 [0.68709, 0.021418, 2.0088e-05],
11138 [0.69399, 0.022062, 1.9102e-05],
11139 [0.70092, 0.022727, 1.9662e-05],
11140 [0.70784, 0.023412, 1.7757e-05],
11141 [0.71478, 0.024121, 1.8236e-05],
11142 [0.72173, 0.024852, 1.4944e-05],
11143 [0.7287, 0.025608, 2.0245e-06],
11144 [0.73567, 0.02639, 1.5013e-07],
11145 [0.74266, 0.027199, 0],
11146 [0.74964, 0.028038, 0],
11147 [0.75665, 0.028906, 0],
11148 [0.76365, 0.029806, 0],
11149 [0.77068, 0.030743, 0],
11150 [0.77771, 0.031711, 0],
11151 [0.78474, 0.032732, 0],
11152 [0.79179, 0.033741, 0],
11153 [0.79886, 0.034936, 0],
11154 [0.80593, 0.036031, 0],
11155 [0.81299, 0.03723, 0],
11156 [0.82007, 0.038493, 0],
11157 [0.82715, 0.039819, 0],
11158 [0.83423, 0.041236, 0],
11159 [0.84131, 0.042647, 0],
11160 [0.84838, 0.044235, 0],
11161 [0.85545, 0.045857, 0],
11162 [0.86252, 0.047645, 0],
11163 [0.86958, 0.049578, 0],
11164 [0.87661, 0.051541, 0],
11165 [0.88365, 0.053735, 0],
11166 [0.89064, 0.056168, 0],
11167 [0.89761, 0.058852, 0],
11168 [0.90451, 0.061777, 0],
11169 [0.91131, 0.065281, 0],
11170 [0.91796, 0.069448, 0],
11171 [0.92445, 0.074684, 0],
11172 [0.93061, 0.08131, 0],
11173 [0.93648, 0.088878, 0],
11174 [0.94205, 0.097336, 0],
11175 [0.9473, 0.10665, 0],
11176 [0.9522, 0.1166, 0],
11177 [0.95674, 0.12716, 0],
11178 [0.96094, 0.13824, 0],
11179 [0.96479, 0.14963, 0],
11180 [0.96829, 0.16128, 0],
11181 [0.97147, 0.17303, 0],
11182 [0.97436, 0.18489, 0],
11183 [0.97698, 0.19672, 0],
11184 [0.97934, 0.20846, 0],
11185 [0.98148, 0.22013, 0],
11186 [0.9834, 0.23167, 0],
11187 [0.98515, 0.24301, 0],
11188 [0.98672, 0.25425, 0],
11189 [0.98815, 0.26525, 0],
11190 [0.98944, 0.27614, 0],
11191 [0.99061, 0.28679, 0],
11192 [0.99167, 0.29731, 0],
11193 [0.99263, 0.30764, 0],
11194 [0.9935, 0.31781, 0],
11195 [0.99428, 0.3278, 0],
11196 [0.995, 0.33764, 0],
11197 [0.99564, 0.34735, 0],
11198 [0.99623, 0.35689, 0],
11199 [0.99675, 0.3663, 0],
11200 [0.99722, 0.37556, 0],
11201 [0.99765, 0.38471, 0],
11202 [0.99803, 0.39374, 0],
11203 [0.99836, 0.40265, 0],
11204 [0.99866, 0.41145, 0],
11205 [0.99892, 0.42015, 0],
11206 [0.99915, 0.42874, 0],
11207 [0.99935, 0.43724, 0],
11208 [0.99952, 0.44563, 0],
11209 [0.99966, 0.45395, 0],
11210 [0.99977, 0.46217, 0],
11211 [0.99986, 0.47032, 0],
11212 [0.99993, 0.47838, 0],
11213 [0.99997, 0.48638, 0],
11214 [1, 0.4943, 0],
11215 [1, 0.50214, 0],
11216 [1, 0.50991, 1.2756e-05],
11217 [1, 0.51761, 4.5388e-05],
11218 [1, 0.52523, 9.6977e-05],
11219 [1, 0.5328, 0.00016858],
11220 [1, 0.54028, 0.0002582],
11221 [1, 0.54771, 0.00036528],
11222 [1, 0.55508, 0.00049276],
11223 [1, 0.5624, 0.00063955],
11224 [1, 0.56965, 0.00080443],
11225 [1, 0.57687, 0.00098902],
11226 [1, 0.58402, 0.0011943],
11227 [1, 0.59113, 0.0014189],
11228 [1, 0.59819, 0.0016626],
11229 [1, 0.60521, 0.0019281],
11230 [1, 0.61219, 0.0022145],
11231 [1, 0.61914, 0.0025213],
11232 [1, 0.62603, 0.0028496],
11233 [1, 0.6329, 0.0032006],
11234 [1, 0.63972, 0.0035741],
11235 [1, 0.64651, 0.0039701],
11236 [1, 0.65327, 0.0043898],
11237 [1, 0.66, 0.0048341],
11238 [1, 0.66669, 0.005303],
11239 [1, 0.67336, 0.0057969],
11240 [1, 0.67999, 0.006317],
11241 [1, 0.68661, 0.0068648],
11242 [1, 0.69319, 0.0074406],
11243 [1, 0.69974, 0.0080433],
11244 [1, 0.70628, 0.0086756],
11245 [1, 0.71278, 0.0093486],
11246 [1, 0.71927, 0.010023],
11247 [1, 0.72573, 0.010724],
11248 [1, 0.73217, 0.011565],
11249 [1, 0.73859, 0.012339],
11250 [1, 0.74499, 0.01316],
11251 [1, 0.75137, 0.014042],
11252 [1, 0.75772, 0.014955],
11253 [1, 0.76406, 0.015913],
11254 [1, 0.77039, 0.016915],
11255 [1, 0.77669, 0.017964],
11256 [1, 0.78298, 0.019062],
11257 [1, 0.78925, 0.020212],
11258 [1, 0.7955, 0.021417],
11259 [1, 0.80174, 0.02268],
11260 [1, 0.80797, 0.024005],
11261 [1, 0.81418, 0.025396],
11262 [1, 0.82038, 0.026858],
11263 [1, 0.82656, 0.028394],
11264 [1, 0.83273, 0.030013],
11265 [1, 0.83889, 0.031717],
11266 [1, 0.84503, 0.03348],
11267 [1, 0.85116, 0.035488],
11268 [1, 0.85728, 0.037452],
11269 [1, 0.8634, 0.039592],
11270 [1, 0.86949, 0.041898],
11271 [1, 0.87557, 0.044392],
11272 [1, 0.88165, 0.046958],
11273 [1, 0.88771, 0.04977],
11274 [1, 0.89376, 0.052828],
11275 [1, 0.8998, 0.056209],
11276 [1, 0.90584, 0.059919],
11277 [1, 0.91185, 0.063925],
11278 [1, 0.91783, 0.068579],
11279 [1, 0.92384, 0.073948],
11280 [1, 0.92981, 0.080899],
11281 [1, 0.93576, 0.090648],
11282 [1, 0.94166, 0.10377],
11283 [1, 0.94752, 0.12051],
11284 [1, 0.9533, 0.14149],
11285 [1, 0.959, 0.1672],
11286 [1, 0.96456, 0.19823],
11287 [1, 0.96995, 0.23514],
11288 [1, 0.9751, 0.2786],
11289 [1, 0.97992, 0.32883],
11290 [1, 0.98432, 0.38571],
11291 [1, 0.9882, 0.44866],
11292 [1, 0.9915, 0.51653],
11293 [1, 0.99417, 0.58754],
11294 [1, 0.99625, 0.65985],
11295 [1, 0.99778, 0.73194],
11296 [1, 0.99885, 0.80259],
11297 [1, 0.99953, 0.87115],
11298 [1, 0.99989, 0.93683],
11299 [1, 1, 1],
11300 ]
11301 b_linear_kryw_0_100_c71 = bokeh_palette('linear_kryw_0_100_c71',linear_kryw_0_100_c71)
11302 m_linear_kryw_0_100_c71 = mpl_cm('linear_kryw_0_100_c71',linear_kryw_0_100_c71)
11303 m_linear_kryw_0_100_c71_r = mpl_cm('linear_kryw_0_100_c71_r',list(reversed(linear_kryw_0_100_c71)))
11304 fire = b_linear_kryw_0_100_c71
11305 m_fire = m_linear_kryw_0_100_c71
11306 m_fire_r = m_linear_kryw_0_100_c71_r
11307 palette['fire'] = b_linear_kryw_0_100_c71
11308 cm['fire'] = m_linear_kryw_0_100_c71
11309 cm['fire_r'] = m_linear_kryw_0_100_c71_r
11310 register_cmap('cet_fire',m_linear_kryw_0_100_c71)
11311 register_cmap('cet_fire_r',m_linear_kryw_0_100_c71_r)
11312
11313
11314
11315
11316 linear_kryw_5_100_c64 = [\
11317 [0.066001, 0.066024, 0.066019],
11318 [0.080369, 0.066784, 0.064674],
11319 [0.092822, 0.067552, 0.063341],
11320 [0.10397, 0.06834, 0.06191],
11321 [0.11402, 0.069166, 0.060555],
11322 [0.12335, 0.069862, 0.059198],
11323 [0.13261, 0.070292, 0.057702],
11324 [0.14179, 0.070442, 0.056438],
11325 [0.15095, 0.070268, 0.055015],
11326 [0.16001, 0.069905, 0.053644],
11327 [0.16905, 0.069432, 0.052281],
11328 [0.17797, 0.068765, 0.050929],
11329 [0.18676, 0.067963, 0.049608],
11330 [0.19551, 0.06705, 0.048145],
11331 [0.20423, 0.066, 0.046785],
11332 [0.21283, 0.064845, 0.045348],
11333 [0.22141, 0.063566, 0.043893],
11334 [0.22991, 0.062103, 0.042492],
11335 [0.23838, 0.060521, 0.04109],
11336 [0.24679, 0.058793, 0.039622],
11337 [0.25516, 0.056921, 0.038174],
11338 [0.26346, 0.054829, 0.03674],
11339 [0.27169, 0.052601, 0.035359],
11340 [0.27989, 0.050287, 0.033739],
11341 [0.288, 0.047729, 0.032416],
11342 [0.29607, 0.045108, 0.031085],
11343 [0.30408, 0.042249, 0.02978],
11344 [0.31201, 0.03918, 0.028501],
11345 [0.3199, 0.03606, 0.027253],
11346 [0.32767, 0.032742, 0.026037],
11347 [0.33538, 0.029627, 0.024852],
11348 [0.34298, 0.026563, 0.023698],
11349 [0.3505, 0.023574, 0.022579],
11350 [0.3579, 0.0207, 0.021495],
11351 [0.36518, 0.01798, 0.020449],
11352 [0.37234, 0.015464, 0.019443],
11353 [0.37938, 0.013196, 0.018481],
11354 [0.38624, 0.011135, 0.017565],
11355 [0.39295, 0.0095033, 0.016699],
11356 [0.39946, 0.0083814, 0.015886],
11357 [0.4058, 0.0078194, 0.015132],
11358 [0.41198, 0.0076635, 0.014439],
11359 [0.41811, 0.0076226, 0.013789],
11360 [0.42426, 0.0075941, 0.013171],
11361 [0.43042, 0.0075784, 0.012613],
11362 [0.43658, 0.0075771, 0.012105],
11363 [0.44275, 0.0075916, 0.01156],
11364 [0.44893, 0.0076225, 0.01099],
11365 [0.45511, 0.0076698, 0.010514],
11366 [0.46129, 0.0077346, 0.010144],
11367 [0.46749, 0.0078179, 0.0098304],
11368 [0.47368, 0.0079218, 0.0095481],
11369 [0.4799, 0.0080473, 0.0092968],
11370 [0.4861, 0.0081943, 0.0090788],
11371 [0.49232, 0.0083639, 0.0088967],
11372 [0.49856, 0.0085577, 0.0087515],
11373 [0.50479, 0.008779, 0.0086465],
11374 [0.51102, 0.0090297, 0.0085815],
11375 [0.51728, 0.0093076, 0.0085522],
11376 [0.52353, 0.0096083, 0.0085576],
11377 [0.52979, 0.0099253, 0.0085974],
11378 [0.53605, 0.010269, 0.0086738],
11379 [0.54232, 0.010684, 0.0087889],
11380 [0.5486, 0.011214, 0.0089401],
11381 [0.55488, 0.01179, 0.0091252],
11382 [0.56117, 0.012305, 0.0093423],
11383 [0.56747, 0.012813, 0.0095893],
11384 [0.57376, 0.013386, 0.0098594],
11385 [0.58008, 0.013995, 0.010134],
11386 [0.5864, 0.014611, 0.010408],
11387 [0.59274, 0.015241, 0.010687],
11388 [0.59909, 0.015887, 0.010978],
11389 [0.60544, 0.016546, 0.011263],
11390 [0.61182, 0.017218, 0.011525],
11391 [0.61821, 0.017905, 0.011749],
11392 [0.62462, 0.018606, 0.011933],
11393 [0.63103, 0.019321, 0.012084],
11394 [0.63746, 0.020051, 0.012209],
11395 [0.64389, 0.020795, 0.01231],
11396 [0.65035, 0.021554, 0.012391],
11397 [0.65681, 0.022328, 0.01245],
11398 [0.66329, 0.023117, 0.01249],
11399 [0.66978, 0.023921, 0.012509],
11400 [0.67628, 0.024741, 0.012509],
11401 [0.68279, 0.025575, 0.012488],
11402 [0.68932, 0.026426, 0.012446],
11403 [0.69585, 0.027292, 0.012384],
11404 [0.7024, 0.028175, 0.012321],
11405 [0.70896, 0.029075, 0.012266],
11406 [0.71553, 0.029992, 0.01222],
11407 [0.7221, 0.030928, 0.012183],
11408 [0.7287, 0.031878, 0.012154],
11409 [0.7353, 0.032858, 0.012135],
11410 [0.74191, 0.033811, 0.012128],
11411 [0.74853, 0.035044, 0.012132],
11412 [0.75514, 0.036234, 0.01215],
11413 [0.76173, 0.037634, 0.012181],
11414 [0.76828, 0.039279, 0.012225],
11415 [0.77482, 0.041197, 0.012285],
11416 [0.78133, 0.043182, 0.01236],
11417 [0.7878, 0.045551, 0.01245],
11418 [0.79425, 0.048054, 0.012555],
11419 [0.80067, 0.050754, 0.012678],
11420 [0.80707, 0.053571, 0.012821],
11421 [0.81342, 0.056666, 0.012987],
11422 [0.81976, 0.059852, 0.013177],
11423 [0.82606, 0.063125, 0.01339],
11424 [0.83234, 0.066486, 0.013626],
11425 [0.83859, 0.070019, 0.013884],
11426 [0.84481, 0.073701, 0.014163],
11427 [0.85098, 0.077343, 0.014466],
11428 [0.85714, 0.081244, 0.014794],
11429 [0.86327, 0.085127, 0.015149],
11430 [0.86936, 0.089149, 0.015532],
11431 [0.87543, 0.093173, 0.015943],
11432 [0.88146, 0.097361, 0.016384],
11433 [0.88746, 0.10157, 0.016855],
11434 [0.89343, 0.10587, 0.017358],
11435 [0.89937, 0.11022, 0.017892],
11436 [0.90527, 0.11454, 0.01846],
11437 [0.91114, 0.11904, 0.019064],
11438 [0.91695, 0.12359, 0.019699],
11439 [0.92264, 0.12853, 0.020354],
11440 [0.92813, 0.13395, 0.021017],
11441 [0.93344, 0.13977, 0.021689],
11442 [0.93854, 0.14611, 0.02237],
11443 [0.94344, 0.1528, 0.023063],
11444 [0.94814, 0.15984, 0.023768],
11445 [0.95265, 0.16722, 0.024487],
11446 [0.95695, 0.17483, 0.025222],
11447 [0.96106, 0.18267, 0.025974],
11448 [0.96494, 0.19079, 0.026746],
11449 [0.96862, 0.19909, 0.02754],
11450 [0.97211, 0.20758, 0.028357],
11451 [0.97538, 0.21622, 0.029202],
11452 [0.97845, 0.22495, 0.030075],
11453 [0.98129, 0.23387, 0.030982],
11454 [0.98393, 0.24289, 0.03192],
11455 [0.98635, 0.25203, 0.032909],
11456 [0.98856, 0.26123, 0.033896],
11457 [0.99056, 0.27053, 0.035185],
11458 [0.99233, 0.27989, 0.036297],
11459 [0.99387, 0.28935, 0.037474],
11460 [0.99519, 0.29884, 0.038698],
11461 [0.9963, 0.30839, 0.039989],
11462 [0.99718, 0.31799, 0.041353],
11463 [0.99783, 0.32763, 0.042645],
11464 [0.99825, 0.33734, 0.044084],
11465 [0.99848, 0.34702, 0.045528],
11466 [0.99862, 0.35658, 0.047065],
11467 [0.99872, 0.36596, 0.048549],
11468 [0.99881, 0.37516, 0.05001],
11469 [0.99886, 0.38422, 0.051453],
11470 [0.99888, 0.39313, 0.052916],
11471 [0.99888, 0.40191, 0.054408],
11472 [0.99885, 0.41058, 0.05593],
11473 [0.9988, 0.41912, 0.057352],
11474 [0.99871, 0.42755, 0.058876],
11475 [0.9986, 0.43588, 0.060349],
11476 [0.99846, 0.44412, 0.061737],
11477 [0.99829, 0.45227, 0.063269],
11478 [0.99809, 0.46032, 0.064678],
11479 [0.99787, 0.46831, 0.066112],
11480 [0.99761, 0.47622, 0.067563],
11481 [0.99733, 0.48405, 0.069046],
11482 [0.99701, 0.49183, 0.070378],
11483 [0.99667, 0.49952, 0.071816],
11484 [0.9963, 0.50718, 0.073256],
11485 [0.9959, 0.51477, 0.074592],
11486 [0.99546, 0.52229, 0.075945],
11487 [0.995, 0.52978, 0.077303],
11488 [0.99451, 0.53722, 0.078672],
11489 [0.99398, 0.5446, 0.080052],
11490 [0.99343, 0.55194, 0.081445],
11491 [0.99284, 0.55923, 0.08275],
11492 [0.99221, 0.5665, 0.084159],
11493 [0.99153, 0.57372, 0.085535],
11494 [0.99079, 0.58093, 0.087222],
11495 [0.98999, 0.58811, 0.088926],
11496 [0.98913, 0.59528, 0.090807],
11497 [0.9882, 0.60242, 0.092757],
11498 [0.98722, 0.60955, 0.09496],
11499 [0.98617, 0.61665, 0.097148],
11500 [0.98506, 0.62374, 0.099536],
11501 [0.98388, 0.63081, 0.10204],
11502 [0.98264, 0.63786, 0.10462],
11503 [0.98133, 0.6449, 0.1074],
11504 [0.97995, 0.65193, 0.11026],
11505 [0.9785, 0.65893, 0.11321],
11506 [0.97698, 0.66593, 0.11625],
11507 [0.97539, 0.67291, 0.11938],
11508 [0.97373, 0.67987, 0.1226],
11509 [0.972, 0.68684, 0.126],
11510 [0.97019, 0.69378, 0.12941],
11511 [0.96831, 0.70072, 0.13295],
11512 [0.96635, 0.70764, 0.13654],
11513 [0.96431, 0.71455, 0.14025],
11514 [0.9622, 0.72146, 0.14405],
11515 [0.96001, 0.72836, 0.1479],
11516 [0.95774, 0.73524, 0.15182],
11517 [0.95538, 0.7421, 0.15586],
11518 [0.95297, 0.74897, 0.16005],
11519 [0.95072, 0.75572, 0.16525],
11520 [0.94897, 0.76218, 0.17245],
11521 [0.94775, 0.76837, 0.1816],
11522 [0.94697, 0.77433, 0.19225],
11523 [0.94657, 0.7801, 0.204],
11524 [0.94649, 0.78571, 0.21653],
11525 [0.94667, 0.79118, 0.22961],
11526 [0.94708, 0.79653, 0.24318],
11527 [0.94773, 0.80176, 0.2572],
11528 [0.94857, 0.80689, 0.2715],
11529 [0.94954, 0.81193, 0.28598],
11530 [0.95065, 0.81691, 0.30062],
11531 [0.95189, 0.82181, 0.31549],
11532 [0.95324, 0.82665, 0.33046],
11533 [0.95466, 0.83144, 0.3455],
11534 [0.95617, 0.83616, 0.3607],
11535 [0.95775, 0.84084, 0.37601],
11536 [0.95937, 0.84548, 0.39137],
11537 [0.96106, 0.85008, 0.40685],
11538 [0.96275, 0.85465, 0.42235],
11539 [0.9645, 0.85917, 0.43802],
11540 [0.96626, 0.86367, 0.45372],
11541 [0.96804, 0.86814, 0.46954],
11542 [0.96981, 0.87258, 0.4854],
11543 [0.97158, 0.87699, 0.50136],
11544 [0.97335, 0.88139, 0.5174],
11545 [0.9751, 0.88577, 0.53349],
11546 [0.97684, 0.89012, 0.54971],
11547 [0.97854, 0.89447, 0.56596],
11548 [0.98023, 0.89878, 0.58234],
11549 [0.98186, 0.90309, 0.59876],
11550 [0.98347, 0.90738, 0.61531],
11551 [0.98503, 0.91166, 0.6319],
11552 [0.98655, 0.91593, 0.64861],
11553 [0.98799, 0.92019, 0.66537],
11554 [0.9894, 0.92443, 0.68224],
11555 [0.99073, 0.92867, 0.69917],
11556 [0.99199, 0.9329, 0.71621],
11557 [0.99319, 0.93713, 0.73332],
11558 [0.9943, 0.94135, 0.7505],
11559 [0.99535, 0.94556, 0.76779],
11560 [0.99629, 0.94977, 0.78512],
11561 [0.99718, 0.95397, 0.8026],
11562 [0.99795, 0.95817, 0.8201],
11563 [0.99865, 0.96236, 0.83775],
11564 [0.99923, 0.96655, 0.85544],
11565 [0.99971, 0.97075, 0.87321],
11566 [1, 0.97493, 0.8911],
11567 [1, 0.97913, 0.90901],
11568 [1, 0.98331, 0.92711],
11569 [1, 0.9875, 0.94522],
11570 [1, 0.99168, 0.96339],
11571 [1, 0.99586, 0.98169],
11572 [0.99986, 1, 1],
11573 ]
11574 b_linear_kryw_5_100_c64 = bokeh_palette('linear_kryw_5_100_c64',linear_kryw_5_100_c64)
11575 m_linear_kryw_5_100_c64 = mpl_cm('linear_kryw_5_100_c64',linear_kryw_5_100_c64)
11576 m_linear_kryw_5_100_c64_r = mpl_cm('linear_kryw_5_100_c64_r',list(reversed(linear_kryw_5_100_c64)))
11577
11578
11579
11580
11581 linear_kryw_5_100_c67 = [\
11582 [0.066001, 0.066024, 0.066019],
11583 [0.080835, 0.066624, 0.064683],
11584 [0.093644, 0.067235, 0.063358],
11585 [0.10501, 0.067862, 0.061943],
11586 [0.11533, 0.068524, 0.060589],
11587 [0.12493, 0.06913, 0.059252],
11588 [0.13446, 0.069402, 0.057766],
11589 [0.14389, 0.069337, 0.05652],
11590 [0.15329, 0.068912, 0.055114],
11591 [0.16265, 0.068217, 0.053762],
11592 [0.17186, 0.067393, 0.052418],
11593 [0.18101, 0.066415, 0.051087],
11594 [0.19008, 0.065312, 0.049777],
11595 [0.19905, 0.064056, 0.04839],
11596 [0.208, 0.06267, 0.047034],
11597 [0.21686, 0.060979, 0.045586],
11598 [0.22565, 0.059301, 0.04424],
11599 [0.2344, 0.057256, 0.042784],
11600 [0.24306, 0.055098, 0.041497],
11601 [0.2517, 0.05272, 0.040051],
11602 [0.26025, 0.050192, 0.038638],
11603 [0.26877, 0.047379, 0.037249],
11604 [0.27721, 0.044339, 0.035898],
11605 [0.28558, 0.041067, 0.034375],
11606 [0.2939, 0.0375, 0.03304],
11607 [0.30215, 0.033602, 0.031743],
11608 [0.31036, 0.029855, 0.030482],
11609 [0.31847, 0.026015, 0.029246],
11610 [0.32649, 0.022146, 0.028041],
11611 [0.33446, 0.018274, 0.026868],
11612 [0.34231, 0.014418, 0.025725],
11613 [0.35006, 0.010378, 0.024615],
11614 [0.35772, 0.0066727, 0.023538],
11615 [0.36524, 0.0030611, 0.022497],
11616 [0.37265, 0, 0.021492],
11617 [0.37993, 0, 0.020527],
11618 [0.38704, 0, 0.019604],
11619 [0.39401, 0, 0.018725],
11620 [0.40079, 0, 0.017895],
11621 [0.40735, 0, 0.017114],
11622 [0.41371, 0, 0.016389],
11623 [0.41991, 0, 0.01571],
11624 [0.42607, 0, 0.015054],
11625 [0.43225, 0, 0.014413],
11626 [0.43842, 0, 0.013785],
11627 [0.44461, 0, 0.013163],
11628 [0.4508, 0, 0.01258],
11629 [0.45699, 0, 0.012015],
11630 [0.46319, 0, 0.011343],
11631 [0.46943, 0, 0.01065],
11632 [0.47565, 0, 0.010097],
11633 [0.48187, 0, 0.0095904],
11634 [0.48811, 0, 0.0090697],
11635 [0.49436, 0, 0.0085559],
11636 [0.5006, 0, 0.0080597],
11637 [0.50686, 0, 0.0075745],
11638 [0.51313, 0, 0.0071],
11639 [0.5194, 0, 0.0066376],
11640 [0.52568, 0, 0.0061855],
11641 [0.53196, 0, 0.0057427],
11642 [0.53826, 0, 0.0053086],
11643 [0.54455, 0, 0.0048845],
11644 [0.55086, 0, 0.0044712],
11645 [0.55718, 0, 0.004067],
11646 [0.5635, 0, 0.0036703],
11647 [0.56981, 0, 0.003281],
11648 [0.57615, 0, 0.0028993],
11649 [0.58248, 0, 0.002527],
11650 [0.58883, 0, 0.0021643],
11651 [0.5952, 0, 0.0018102],
11652 [0.60158, 0, 0.0014648],
11653 [0.60799, 0, 0.0011281],
11654 [0.6144, 0, 0.0008024],
11655 [0.62084, 0, 0.00048773],
11656 [0.62729, 0, 0.00018111],
11657 [0.63377, 0, 0],
11658 [0.64026, 0, 0],
11659 [0.64676, 0, 0],
11660 [0.65328, 0, 0],
11661 [0.65983, 0, 0],
11662 [0.66638, 0, 0],
11663 [0.67297, 0, 0],
11664 [0.67955, 0, 0],
11665 [0.68617, 0, 0],
11666 [0.6928, 0, 0],
11667 [0.69944, 0, 0],
11668 [0.70611, 0, 0],
11669 [0.71279, 0, 0],
11670 [0.7195, 0, 0],
11671 [0.72621, 0, 0],
11672 [0.73295, 0, 0],
11673 [0.7397, 0, 0],
11674 [0.74647, 0, 0],
11675 [0.75325, 0, 0],
11676 [0.76005, 0, 0],
11677 [0.76685, 0, 0],
11678 [0.77364, 0, 0],
11679 [0.78042, 0, 0],
11680 [0.78719, 0, 0],
11681 [0.79394, 0, 0],
11682 [0.80067, 0, 0],
11683 [0.8074, 0, 0],
11684 [0.8141, 0, 0],
11685 [0.8208, 0, 0],
11686 [0.82748, 0, 0],
11687 [0.83414, 0, 0],
11688 [0.84079, 0, 0],
11689 [0.84742, 0, 0],
11690 [0.85404, 0, 0],
11691 [0.86065, 0, 0],
11692 [0.86723, 0, 0],
11693 [0.8738, 0, 0],
11694 [0.88036, 0, 0],
11695 [0.8869, 0, 0],
11696 [0.89342, 0, 0],
11697 [0.89993, 0, 0],
11698 [0.90642, 0, 0],
11699 [0.91289, 0, 0],
11700 [0.91935, 0, 0],
11701 [0.92579, 0.0041866, 0],
11702 [0.93221, 0.0088411, 0],
11703 [0.93858, 0.014235, 0],
11704 [0.94484, 0.020592, 0],
11705 [0.9509, 0.028663, 0],
11706 [0.95676, 0.038768, 0],
11707 [0.96242, 0.049864, 0],
11708 [0.96787, 0.061034, 0],
11709 [0.97311, 0.072263, 0],
11710 [0.97815, 0.083447, 0],
11711 [0.983, 0.094617, 0],
11712 [0.98764, 0.10571, 0],
11713 [0.99205, 0.11685, 0],
11714 [0.99626, 0.12797, 0],
11715 [1, 0.139, 0],
11716 [1, 0.15006, 0],
11717 [1, 0.16105, 0],
11718 [1, 0.17204, 0],
11719 [1, 0.18303, 0],
11720 [1, 0.19402, 0],
11721 [1, 0.20493, 0],
11722 [1, 0.21586, 0],
11723 [1, 0.22677, 0],
11724 [1, 0.23768, 0],
11725 [1, 0.24857, 0],
11726 [1, 0.25943, 0],
11727 [1, 0.27027, 0],
11728 [1, 0.28108, 0],
11729 [1, 0.29193, 0],
11730 [1, 0.30267, 0],
11731 [1, 0.31323, 0],
11732 [1, 0.32352, 0],
11733 [1, 0.33356, 0],
11734 [1, 0.34337, 0],
11735 [1, 0.35298, 0],
11736 [1, 0.3624, 0],
11737 [1, 0.37164, 0.00061699],
11738 [1, 0.38075, 0.0021825],
11739 [1, 0.38968, 0.0037567],
11740 [1, 0.3985, 0.0053395],
11741 [1, 0.40718, 0.0069314],
11742 [1, 0.41575, 0.0085283],
11743 [1, 0.4242, 0.010112],
11744 [1, 0.43257, 0.011953],
11745 [1, 0.44081, 0.013525],
11746 [1, 0.44899, 0.015122],
11747 [1, 0.45706, 0.016714],
11748 [1, 0.46506, 0.018299],
11749 [1, 0.47298, 0.019872],
11750 [1, 0.48083, 0.021427],
11751 [1, 0.48862, 0.022968],
11752 [1, 0.49633, 0.024493],
11753 [1, 0.504, 0.026001],
11754 [1, 0.51159, 0.027485],
11755 [1, 0.51914, 0.028939],
11756 [1, 0.52664, 0.030367],
11757 [1, 0.53406, 0.03178],
11758 [1, 0.54143, 0.033208],
11759 [1, 0.54875, 0.034768],
11760 [1, 0.55598, 0.036315],
11761 [1, 0.56318, 0.037812],
11762 [1, 0.5703, 0.039323],
11763 [1, 0.57737, 0.040851],
11764 [1, 0.58439, 0.04235],
11765 [1, 0.59136, 0.043767],
11766 [1, 0.59828, 0.045295],
11767 [1, 0.60516, 0.046771],
11768 [1, 0.61199, 0.048174],
11769 [1, 0.61878, 0.049666],
11770 [1, 0.62552, 0.051026],
11771 [1, 0.63222, 0.0524],
11772 [1, 0.63889, 0.053786],
11773 [1, 0.64551, 0.055176],
11774 [1, 0.65211, 0.056589],
11775 [1, 0.65866, 0.057815],
11776 [1, 0.66518, 0.05925],
11777 [1, 0.67167, 0.060511],
11778 [1, 0.67814, 0.061743],
11779 [1, 0.68456, 0.063098],
11780 [1, 0.69095, 0.064301],
11781 [1, 0.69731, 0.065521],
11782 [1, 0.70365, 0.066739],
11783 [1, 0.70997, 0.068288],
11784 [1, 0.71622, 0.071897],
11785 [1, 0.72231, 0.079934],
11786 [1, 0.72829, 0.091953],
11787 [1, 0.73416, 0.10627],
11788 [1, 0.73994, 0.12182],
11789 [1, 0.74564, 0.13819],
11790 [1, 0.75128, 0.1548],
11791 [1, 0.75686, 0.17158],
11792 [1, 0.76238, 0.18858],
11793 [1, 0.76786, 0.20562],
11794 [1, 0.7733, 0.22256],
11795 [1, 0.77871, 0.23945],
11796 [1, 0.7841, 0.2564],
11797 [1, 0.78945, 0.27335],
11798 [1, 0.79478, 0.29018],
11799 [1, 0.80008, 0.30712],
11800 [1, 0.80537, 0.32404],
11801 [1, 0.81064, 0.34096],
11802 [1, 0.81591, 0.35795],
11803 [1, 0.82116, 0.37487],
11804 [1, 0.8264, 0.39194],
11805 [1, 0.83163, 0.40902],
11806 [1, 0.83685, 0.42615],
11807 [1, 0.84207, 0.44336],
11808 [1, 0.84727, 0.4606],
11809 [1, 0.85249, 0.47795],
11810 [1, 0.85769, 0.49533],
11811 [1, 0.8629, 0.51282],
11812 [1, 0.86811, 0.53035],
11813 [1, 0.87331, 0.54803],
11814 [1, 0.87852, 0.56571],
11815 [1, 0.88373, 0.58356],
11816 [1, 0.88894, 0.60144],
11817 [1, 0.89415, 0.61947],
11818 [1, 0.89937, 0.63753],
11819 [1, 0.9046, 0.65574],
11820 [1, 0.90983, 0.67401],
11821 [1, 0.91506, 0.69239],
11822 [1, 0.9203, 0.71087],
11823 [1, 0.92556, 0.72942],
11824 [1, 0.93081, 0.74812],
11825 [1, 0.93608, 0.76684],
11826 [1, 0.94135, 0.78577],
11827 [1, 0.94664, 0.80471],
11828 [1, 0.95193, 0.82381],
11829 [1, 0.95723, 0.84299],
11830 [1, 0.96255, 0.86225],
11831 [1, 0.96787, 0.88166],
11832 [1, 0.97321, 0.90108],
11833 [1, 0.97856, 0.92074],
11834 [1, 0.98392, 0.94042],
11835 [1, 0.98928, 0.96017],
11836 [1, 0.99466, 0.98008],
11837 [0.99986, 1, 1],
11838 ]
11839 b_linear_kryw_5_100_c67 = bokeh_palette('linear_kryw_5_100_c67',linear_kryw_5_100_c67)
11840 m_linear_kryw_5_100_c67 = mpl_cm('linear_kryw_5_100_c67',linear_kryw_5_100_c67)
11841 m_linear_kryw_5_100_c67_r = mpl_cm('linear_kryw_5_100_c67_r',list(reversed(linear_kryw_5_100_c67)))
11842
11843
11844
11845
11846 linear_ternary_blue_0_44_c57 = [\
11847 [0, 0, 0],
11848 [0.00074336, 0.0024531, 0.0074342],
11849 [0.0014922, 0.0049243, 0.014921],
11850 [0.0022238, 0.0073388, 0.022238],
11851 [0.0029727, 0.0098191, 0.029727],
11852 [0.003759, 0.01243, 0.037588],
11853 [0.0044965, 0.014837, 0.045061],
11854 [0.0052171, 0.017216, 0.052174],
11855 [0.0059233, 0.019547, 0.05928],
11856 [0.0066117, 0.021819, 0.066122],
11857 [0.0072841, 0.024037, 0.07289],
11858 [0.0079425, 0.026211, 0.079443],
11859 [0.008587, 0.02834, 0.085862],
11860 [0.0092271, 0.03044, 0.092265],
11861 [0.009844, 0.03246, 0.098364],
11862 [0.010477, 0.034486, 0.10458],
11863 [0.011109, 0.036556, 0.11078],
11864 [0.01171, 0.038495, 0.11667],
11865 [0.012273, 0.040403, 0.12242],
11866 [0.012818, 0.042245, 0.1279],
11867 [0.013348, 0.043976, 0.13326],
11868 [0.013879, 0.04566, 0.1385],
11869 [0.014395, 0.047394, 0.14358],
11870 [0.014889, 0.049082, 0.14858],
11871 [0.015355, 0.050605, 0.15335],
11872 [0.015827, 0.052141, 0.15801],
11873 [0.016294, 0.053656, 0.16261],
11874 [0.016752, 0.05516, 0.16717],
11875 [0.017191, 0.056648, 0.17153],
11876 [0.017621, 0.057987, 0.17584],
11877 [0.018044, 0.059476, 0.18012],
11878 [0.018452, 0.060774, 0.18421],
11879 [0.018859, 0.062143, 0.1883],
11880 [0.019258, 0.063465, 0.19229],
11881 [0.019638, 0.064737, 0.19618],
11882 [0.019991, 0.066008, 0.19999],
11883 [0.020369, 0.06727, 0.20383],
11884 [0.020743, 0.068517, 0.20757],
11885 [0.021108, 0.069731, 0.21123],
11886 [0.021466, 0.07089, 0.21479],
11887 [0.021817, 0.072042, 0.21833],
11888 [0.022172, 0.073262, 0.22184],
11889 [0.022518, 0.074345, 0.22528],
11890 [0.022855, 0.075456, 0.22864],
11891 [0.023186, 0.076553, 0.23196],
11892 [0.023512, 0.077642, 0.23526],
11893 [0.02384, 0.078716, 0.2385],
11894 [0.024178, 0.079786, 0.24179],
11895 [0.024507, 0.080865, 0.24506],
11896 [0.024831, 0.08197, 0.24832],
11897 [0.025156, 0.08299, 0.25156],
11898 [0.02548, 0.084106, 0.2548],
11899 [0.025801, 0.085132, 0.25798],
11900 [0.026127, 0.086192, 0.26127],
11901 [0.026456, 0.087333, 0.26456],
11902 [0.026783, 0.088377, 0.26781],
11903 [0.027109, 0.089458, 0.27108],
11904 [0.027438, 0.090542, 0.27438],
11905 [0.027766, 0.091648, 0.27766],
11906 [0.02809, 0.092669, 0.28088],
11907 [0.028421, 0.093789, 0.2842],
11908 [0.028753, 0.094903, 0.28753],
11909 [0.029077, 0.095942, 0.29078],
11910 [0.029408, 0.097031, 0.29407],
11911 [0.029741, 0.09817, 0.29742],
11912 [0.030072, 0.099229, 0.30072],
11913 [0.030403, 0.10033, 0.30402],
11914 [0.030735, 0.10143, 0.30733],
11915 [0.031072, 0.10254, 0.31072],
11916 [0.031403, 0.10364, 0.31403],
11917 [0.031734, 0.1047, 0.31734],
11918 [0.032072, 0.10585, 0.32074],
11919 [0.032408, 0.10696, 0.32408],
11920 [0.032743, 0.10802, 0.32739],
11921 [0.033082, 0.10918, 0.33077],
11922 [0.033414, 0.11028, 0.33418],
11923 [0.033742, 0.11138, 0.33753],
11924 [0.034077, 0.1125, 0.3409],
11925 [0.03442, 0.11362, 0.34424],
11926 [0.034765, 0.11469, 0.34763],
11927 [0.035114, 0.11586, 0.35104],
11928 [0.035456, 0.11695, 0.35445],
11929 [0.035791, 0.1181, 0.35784],
11930 [0.036121, 0.1192, 0.36122],
11931 [0.036456, 0.12031, 0.36459],
11932 [0.036796, 0.12143, 0.36797],
11933 [0.037139, 0.12255, 0.37137],
11934 [0.037483, 0.12369, 0.37481],
11935 [0.037828, 0.12482, 0.37826],
11936 [0.038169, 0.12598, 0.38168],
11937 [0.038511, 0.12707, 0.3851],
11938 [0.038856, 0.12823, 0.38856],
11939 [0.0392, 0.12935, 0.392],
11940 [0.039546, 0.13052, 0.39546],
11941 [0.03989, 0.13163, 0.39889],
11942 [0.040235, 0.13277, 0.40233],
11943 [0.040581, 0.13392, 0.40582],
11944 [0.040922, 0.13506, 0.40923],
11945 [0.041266, 0.13617, 0.41269],
11946 [0.041619, 0.13735, 0.4162],
11947 [0.04197, 0.13849, 0.41964],
11948 [0.042315, 0.1396, 0.42308],
11949 [0.042655, 0.14079, 0.42658],
11950 [0.042998, 0.14192, 0.43006],
11951 [0.043353, 0.14307, 0.43353],
11952 [0.043707, 0.14422, 0.43705],
11953 [0.044054, 0.1454, 0.44054],
11954 [0.044401, 0.14652, 0.44404],
11955 [0.044755, 0.14769, 0.44752],
11956 [0.045109, 0.14883, 0.45103],
11957 [0.045452, 0.15001, 0.45455],
11958 [0.045792, 0.15115, 0.45803],
11959 [0.046147, 0.15231, 0.46154],
11960 [0.046509, 0.15347, 0.46506],
11961 [0.046871, 0.15464, 0.4686],
11962 [0.047221, 0.15582, 0.47216],
11963 [0.047563, 0.15696, 0.47568],
11964 [0.047916, 0.15815, 0.47921],
11965 [0.048273, 0.1593, 0.48272],
11966 [0.048631, 0.16046, 0.48628],
11967 [0.048997, 0.16167, 0.48986],
11968 [0.049352, 0.16283, 0.49342],
11969 [0.049698, 0.16401, 0.49696],
11970 [0.050046, 0.16514, 0.50048],
11971 [0.050404, 0.16634, 0.50406],
11972 [0.050762, 0.16751, 0.50763],
11973 [0.051121, 0.1687, 0.5112],
11974 [0.051479, 0.16988, 0.51479],
11975 [0.051833, 0.17105, 0.51834],
11976 [0.05219, 0.17223, 0.5219],
11977 [0.052551, 0.17342, 0.52551],
11978 [0.052909, 0.17461, 0.5291],
11979 [0.053266, 0.17577, 0.53267],
11980 [0.053628, 0.17697, 0.53628],
11981 [0.05399, 0.17818, 0.53989],
11982 [0.054349, 0.17935, 0.54349],
11983 [0.054708, 0.18053, 0.54707],
11984 [0.055067, 0.18172, 0.55067],
11985 [0.055429, 0.18292, 0.55429],
11986 [0.055793, 0.18412, 0.55793],
11987 [0.056155, 0.18533, 0.56157],
11988 [0.056521, 0.18651, 0.5652],
11989 [0.056888, 0.18772, 0.56884],
11990 [0.057244, 0.18891, 0.57245],
11991 [0.0576, 0.1901, 0.57607],
11992 [0.057967, 0.1913, 0.57969],
11993 [0.058336, 0.1925, 0.58335],
11994 [0.058702, 0.19372, 0.58701],
11995 [0.059067, 0.19492, 0.59066],
11996 [0.059436, 0.19613, 0.59432],
11997 [0.059804, 0.19733, 0.59797],
11998 [0.060167, 0.19853, 0.60161],
11999 [0.060527, 0.19973, 0.60525],
12000 [0.060887, 0.20094, 0.60892],
12001 [0.061253, 0.20216, 0.61259],
12002 [0.061628, 0.20338, 0.6163],
12003 [0.062, 0.2046, 0.61999],
12004 [0.06237, 0.20581, 0.62368],
12005 [0.062743, 0.20703, 0.62736],
12006 [0.063109, 0.20824, 0.63104],
12007 [0.063471, 0.20946, 0.63472],
12008 [0.06384, 0.21068, 0.63842],
12009 [0.064212, 0.21191, 0.64213],
12010 [0.064582, 0.2131, 0.64581],
12011 [0.064951, 0.21435, 0.64951],
12012 [0.065324, 0.21557, 0.65323],
12013 [0.065695, 0.21679, 0.65696],
12014 [0.066066, 0.21802, 0.66066],
12015 [0.066438, 0.21924, 0.66438],
12016 [0.066811, 0.22049, 0.66812],
12017 [0.067184, 0.22169, 0.67183],
12018 [0.067556, 0.22294, 0.67556],
12019 [0.067927, 0.22415, 0.67926],
12020 [0.068301, 0.2254, 0.68302],
12021 [0.068677, 0.22664, 0.68678],
12022 [0.069052, 0.22788, 0.69052],
12023 [0.069427, 0.2291, 0.69424],
12024 [0.0698, 0.23033, 0.69799],
12025 [0.07017, 0.23158, 0.70175],
12026 [0.070545, 0.23281, 0.70549],
12027 [0.070927, 0.23405, 0.70927],
12028 [0.07131, 0.23531, 0.71304],
12029 [0.071685, 0.23655, 0.71681],
12030 [0.072052, 0.23779, 0.72056],
12031 [0.072426, 0.23902, 0.72432],
12032 [0.072809, 0.24026, 0.72809],
12033 [0.073193, 0.24153, 0.73188],
12034 [0.073573, 0.24276, 0.73565],
12035 [0.073946, 0.24401, 0.73944],
12036 [0.074319, 0.24526, 0.74322],
12037 [0.0747, 0.24651, 0.74702],
12038 [0.075082, 0.24778, 0.75083],
12039 [0.075461, 0.24902, 0.75462],
12040 [0.075841, 0.25026, 0.75841],
12041 [0.076222, 0.25154, 0.76222],
12042 [0.076602, 0.25279, 0.76602],
12043 [0.076984, 0.25405, 0.76985],
12044 [0.077365, 0.25531, 0.77365],
12045 [0.077744, 0.25656, 0.77745],
12046 [0.078128, 0.25781, 0.78128],
12047 [0.078511, 0.25909, 0.78511],
12048 [0.078893, 0.26035, 0.78893],
12049 [0.079275, 0.26161, 0.79275],
12050 [0.07966, 0.26288, 0.7966],
12051 [0.080044, 0.26414, 0.80043],
12052 [0.080427, 0.26541, 0.80427],
12053 [0.08081, 0.26667, 0.80809],
12054 [0.081193, 0.26794, 0.81194],
12055 [0.081582, 0.26923, 0.81583],
12056 [0.081967, 0.27049, 0.81966],
12057 [0.082351, 0.27175, 0.8235],
12058 [0.082734, 0.27303, 0.82736],
12059 [0.08312, 0.2743, 0.83122],
12060 [0.08351, 0.27558, 0.8351],
12061 [0.083897, 0.27686, 0.83896],
12062 [0.084288, 0.27814, 0.84284],
12063 [0.084673, 0.27941, 0.84669],
12064 [0.085055, 0.28068, 0.85055],
12065 [0.085441, 0.28197, 0.85445],
12066 [0.085828, 0.28325, 0.85832],
12067 [0.086218, 0.28452, 0.8622],
12068 [0.086607, 0.2858, 0.86608],
12069 [0.087001, 0.28709, 0.86997],
12070 [0.087391, 0.28838, 0.87388],
12071 [0.087778, 0.28967, 0.87777],
12072 [0.088167, 0.29095, 0.88168],
12073 [0.088557, 0.29224, 0.88557],
12074 [0.088947, 0.29352, 0.88947],
12075 [0.089338, 0.29481, 0.89338],
12076 [0.08973, 0.29611, 0.8973],
12077 [0.090121, 0.29741, 0.90121],
12078 [0.090513, 0.29869, 0.90514],
12079 [0.090904, 0.29999, 0.90904],
12080 [0.091296, 0.30128, 0.91296],
12081 [0.09169, 0.30257, 0.91688],
12082 [0.092085, 0.30387, 0.92081],
12083 [0.092476, 0.30517, 0.92477],
12084 [0.092866, 0.30647, 0.92868],
12085 [0.093261, 0.30776, 0.93261],
12086 [0.093659, 0.30908, 0.93659],
12087 [0.094052, 0.31037, 0.94052],
12088 [0.094445, 0.31167, 0.94445],
12089 [0.094842, 0.31297, 0.9484],
12090 [0.095238, 0.31428, 0.95235],
12091 [0.095633, 0.31559, 0.95632],
12092 [0.096025, 0.31689, 0.96026],
12093 [0.096419, 0.31819, 0.96422],
12094 [0.096817, 0.3195, 0.96819],
12095 [0.097216, 0.32082, 0.97216],
12096 [0.097613, 0.32212, 0.97613],
12097 [0.098012, 0.32343, 0.9801],
12098 [0.098407, 0.32474, 0.98406],
12099 [0.098802, 0.32605, 0.98803],
12100 [0.099201, 0.32737, 0.99202],
12101 [0.099601, 0.32868, 0.99601],
12102 [0.1, 0.33, 1],
12103 ]
12104 b_linear_ternary_blue_0_44_c57 = bokeh_palette('linear_ternary_blue_0_44_c57',linear_ternary_blue_0_44_c57)
12105 m_linear_ternary_blue_0_44_c57 = mpl_cm('linear_ternary_blue_0_44_c57',linear_ternary_blue_0_44_c57)
12106 m_linear_ternary_blue_0_44_c57_r = mpl_cm('linear_ternary_blue_0_44_c57_r',list(reversed(linear_ternary_blue_0_44_c57)))
12107 kb = b_linear_ternary_blue_0_44_c57
12108 m_kb = m_linear_ternary_blue_0_44_c57
12109 m_kb_r = m_linear_ternary_blue_0_44_c57_r
12110 palette['kb'] = b_linear_ternary_blue_0_44_c57
12111 cm['kb'] = m_linear_ternary_blue_0_44_c57
12112 cm['kb_r'] = m_linear_ternary_blue_0_44_c57_r
12113 register_cmap('cet_kb',m_linear_ternary_blue_0_44_c57)
12114 register_cmap('cet_kb_r',m_linear_ternary_blue_0_44_c57_r)
12115
12116
12117
12118
12119 linear_ternary_green_0_46_c42 = [\
12120 [0, 0, 0],
12121 [0, 0.0035927, 0],
12122 [0, 0.0071431, 1.452e-17],
12123 [2.0473e-17, 0.010757, 3.0748e-17],
12124 [8.1864e-21, 0.014524, 2.5379e-17],
12125 [1.7446e-17, 0.018105, 6.1007e-18],
12126 [4.169e-17, 0.021687, 5.0758e-17],
12127 [0, 0.025284, 2.5867e-17],
12128 [6.0593e-17, 0.028821, 1.8546e-17],
12129 [0, 0.032444, 2.5867e-17],
12130 [4.253e-17, 0.036221, 5.8567e-18],
12131 [0, 0.039766, 1.269e-17],
12132 [2.4692e-17, 0.043161, 2.6355e-17],
12133 [1.4341e-16, 0.046597, 3.7093e-17],
12134 [0, 0.049768, 1.9522e-17],
12135 [5.3227e-17, 0.052749, 4.0997e-17],
12136 [1.6012e-18, 0.055759, 0],
12137 [0, 0.058542, 7.1257e-17],
12138 [5.6429e-17, 0.061269, 3.1236e-17],
12139 [6.2098e-17, 0.063951, 4.783e-17],
12140 [1.3454e-16, 0.066548, 3.026e-17],
12141 [1.454e-17, 0.069095, 2.3427e-17],
12142 [0, 0.071498, 4.6854e-17],
12143 [3.2058e-17, 0.07387, 3.9045e-18],
12144 [1.6029e-16, 0.076086, 1.9522e-17],
12145 [1.1606e-16, 0.07832, 5.271e-17],
12146 [6.2194e-17, 0.080566, 1.3666e-17],
12147 [0, 0.082735, 0],
12148 [0, 0.084825, 0],
12149 [0, 0.086923, 0],
12150 [8.7753e-18, 0.088913, 4.0997e-17],
12151 [4.5733e-17, 0.090908, 0],
12152 [5.8543e-17, 0.092798, 0],
12153 [7.9487e-17, 0.094766, 0],
12154 [0, 0.096572, 0],
12155 [0, 0.098465, 1.9522e-18],
12156 [0, 0.10025, 0],
12157 [4.9576e-17, 0.10204, 0],
12158 [1.1817e-16, 0.10382, 0],
12159 [1.1049e-16, 0.10552, 1.9522e-18],
12160 [0, 0.10725, 0],
12161 [0, 0.10892, 0],
12162 [8.1348e-18, 0.11059, 4.2949e-17],
12163 [1.5174e-16, 0.11222, 1.1713e-17],
12164 [4.2384e-06, 0.11381, 5.6236e-07],
12165 [1.619e-05, 0.11539, 2.1481e-06],
12166 [1.6699e-05, 0.11698, 2.2156e-06],
12167 [1.2756e-05, 0.11863, 1.6925e-06],
12168 [9.7295e-06, 0.12018, 1.2909e-06],
12169 [1.3177e-05, 0.12176, 1.7484e-06],
12170 [1.6418e-05, 0.12338, 2.1783e-06],
12171 [1.7338e-05, 0.12502, 2.3004e-06],
12172 [1.6062e-05, 0.12662, 2.1312e-06],
12173 [1.1099e-05, 0.12826, 1.4726e-06],
12174 [8.2989e-06, 0.1299, 1.1011e-06],
12175 [1.4157e-05, 0.1315, 1.8783e-06],
12176 [1.7475e-05, 0.13312, 2.3186e-06],
12177 [1.7885e-05, 0.13477, 2.373e-06],
12178 [1.5761e-05, 0.13635, 2.0912e-06],
12179 [1.1631e-05, 0.13803, 1.5432e-06],
12180 [8.4045e-06, 0.13962, 1.1151e-06],
12181 [1.4146e-05, 0.1413, 1.8769e-06],
12182 [1.7579e-05, 0.14293, 2.3324e-06],
12183 [1.8299e-05, 0.14458, 2.428e-06],
12184 [1.7087e-05, 0.14621, 2.2671e-06],
12185 [1.2461e-05, 0.14787, 1.6533e-06],
12186 [9.2002e-06, 0.14954, 1.2207e-06],
12187 [1.3439e-05, 0.15116, 1.7831e-06],
12188 [1.7166e-05, 0.15281, 2.2777e-06],
12189 [1.8547e-05, 0.15448, 2.4608e-06],
12190 [1.8043e-05, 0.15618, 2.394e-06],
12191 [1.5436e-05, 0.15782, 2.048e-06],
12192 [1.1288e-05, 0.15947, 1.4977e-06],
12193 [9.1088e-06, 0.16118, 1.2086e-06],
12194 [1.463e-05, 0.16284, 1.9412e-06],
12195 [1.7571e-05, 0.16452, 2.3725e-06],
12196 [9.5709e-06, 0.16618, 2.3585e-06],
12197 [0, 0.16786, 2.12e-06],
12198 [0, 0.16957, 1.7933e-06],
12199 [0, 0.17123, 1.2872e-06],
12200 [0, 0.17292, 1.0023e-06],
12201 [0, 0.17462, 1.66e-06],
12202 [0, 0.17629, 2.0398e-06],
12203 [0, 0.17804, 2.1855e-06],
12204 [0, 0.1797, 2.2541e-06],
12205 [0, 0.18139, 1.9666e-06],
12206 [0, 0.18309, 1.524e-06],
12207 [0, 0.18482, 1.1233e-06],
12208 [0, 0.18653, 1.2478e-06],
12209 [0, 0.18826, 1.8149e-06],
12210 [0, 0.18994, 2.1666e-06],
12211 [0, 0.19165, 2.2543e-06],
12212 [0, 0.19339, 2.1978e-06],
12213 [0, 0.1951, 2.0405e-06],
12214 [0, 0.19684, 1.6279e-06],
12215 [0, 0.19854, 1.1674e-06],
12216 [0, 0.20025, 1.2082e-06],
12217 [0, 0.20199, 1.6696e-06],
12218 [0, 0.20375, 2.0125e-06],
12219 [0, 0.20547, 2.2769e-06],
12220 [0, 0.20722, 2.3292e-06],
12221 [0, 0.20894, 2.1993e-06],
12222 [0, 0.21069, 1.9215e-06],
12223 [0, 0.21244, 1.5648e-06],
12224 [0, 0.21419, 1.1031e-06],
12225 [0, 0.21594, 1.1824e-06],
12226 [0, 0.21768, 1.6796e-06],
12227 [0, 0.21944, 2.0449e-06],
12228 [0, 0.2212, 2.2667e-06],
12229 [0, 0.22296, 2.3344e-06],
12230 [0, 0.22468, 2.2953e-06],
12231 [0, 0.22648, 2.1282e-06],
12232 [0, 0.22824, 1.8455e-06],
12233 [0, 0.22999, 1.3868e-06],
12234 [0, 0.23177, 1.0492e-06],
12235 [0, 0.23352, 1.2152e-06],
12236 [0, 0.23533, 1.6192e-06],
12237 [0, 0.2371, 2.0168e-06],
12238 [0, 0.23885, 2.2741e-06],
12239 [0, 0.24062, 2.3737e-06],
12240 [0, 0.24241, 2.3904e-06],
12241 [0, 0.24419, 2.2583e-06],
12242 [0, 0.24598, 2.0443e-06],
12243 [0, 0.24779, 1.7786e-06],
12244 [0, 0.24956, 1.4126e-06],
12245 [0, 0.25137, 1.0243e-06],
12246 [0, 0.25316, 1.0702e-06],
12247 [0, 0.25496, 1.5288e-06],
12248 [0, 0.25675, 1.8855e-06],
12249 [0, 0.25854, 2.1333e-06],
12250 [0, 0.26035, 2.3139e-06],
12251 [0, 0.26215, 2.3948e-06],
12252 [0, 0.26397, 2.4069e-06],
12253 [0, 0.26577, 2.301e-06],
12254 [0, 0.26756, 2.1598e-06],
12255 [0, 0.26941, 1.9587e-06],
12256 [0, 0.2712, 1.6921e-06],
12257 [0, 0.27302, 1.2675e-06],
12258 [0, 0.27484, 9.345e-07],
12259 [0, 0.27667, 1.0391e-06],
12260 [0, 0.27848, 1.4548e-06],
12261 [0, 0.2803, 1.7503e-06],
12262 [0, 0.28214, 1.9921e-06],
12263 [0, 0.28396, 2.2429e-06],
12264 [0, 0.28578, 2.3368e-06],
12265 [0, 0.28761, 2.387e-06],
12266 [0, 0.28946, 2.4145e-06],
12267 [0, 0.2913, 2.3634e-06],
12268 [0, 0.29313, 2.3021e-06],
12269 [0, 0.29497, 2.1385e-06],
12270 [0, 0.29682, 1.9682e-06],
12271 [0, 0.29866, 1.7236e-06],
12272 [0, 0.3005, 1.4728e-06],
12273 [0, 0.30234, 1.137e-06],
12274 [0, 0.30421, 8.5235e-07],
12275 [0, 0.30606, 9.2407e-07],
12276 [0, 0.30791, 1.2303e-06],
12277 [0, 0.30977, 1.5259e-06],
12278 [0, 0.31161, 1.7664e-06],
12279 [0, 0.31349, 1.8547e-06],
12280 [0, 0.31534, 8.3145e-07],
12281 [6.8048e-16, 0.31721, 9.3707e-17],
12282 [3.4536e-16, 0.31907, 3.1236e-17],
12283 [3.3512e-16, 0.32095, 6.2472e-17],
12284 [1.0248e-17, 0.32282, 0],
12285 [0, 0.32467, 6.2472e-17],
12286 [0, 0.32654, 1.0933e-16],
12287 [6.7536e-16, 0.32843, 1.0933e-16],
12288 [7.4709e-16, 0.3303, 0],
12289 [3.3512e-16, 0.33219, 6.2472e-17],
12290 [6.9585e-16, 0.33407, 4.6854e-17],
12291 [1.6756e-16, 0.33594, 3.1236e-17],
12292 [8.4804e-16, 0.33782, 1.2494e-16],
12293 [1.7781e-16, 0.33972, 0],
12294 [0, 0.3416, 6.2472e-17],
12295 [0, 0.34348, 0],
12296 [7.2147e-16, 0.34538, 0],
12297 [0, 0.34727, 0],
12298 [0, 0.34917, 0],
12299 [1.5731e-16, 0.35106, 6.2472e-17],
12300 [6.4974e-16, 0.35296, 1.8741e-16],
12301 [3.8636e-16, 0.35487, 0],
12302 [2.0855e-16, 0.35676, 0],
12303 [0, 0.35865, 0],
12304 [3.1462e-16, 0.36055, 1.2494e-16],
12305 [4.4119e-16, 0.36247, 2.8112e-16],
12306 [5.1292e-16, 0.36437, 6.2472e-17],
12307 [0, 0.3663, 0],
12308 [6.8048e-16, 0.3682, 9.3707e-17],
12309 [7.0098e-16, 0.3701, 3.1236e-17],
12310 [2.9412e-16, 0.37202, 1.8741e-16],
12311 [5.0268e-16, 0.37395, 9.3707e-17],
12312 [0, 0.37586, 3.1236e-17],
12313 [6.7023e-16, 0.37778, 1.2494e-16],
12314 [0, 0.3797, 3.1236e-17],
12315 [6.7023e-16, 0.38163, 1.2494e-16],
12316 [8.5829e-16, 0.38356, 9.3707e-17],
12317 [5.2317e-16, 0.38547, 3.1236e-17],
12318 [1.0566e-15, 0.3874, 3.1236e-17],
12319 [4.9243e-16, 0.38934, 1.2494e-16],
12320 [0, 0.39128, 6.2472e-17],
12321 [3.5561e-16, 0.3932, 0],
12322 [1.0607e-16, 0.39514, 2.1865e-16],
12323 [0, 0.39707, 9.3707e-17],
12324 [2.0855e-16, 0.39901, 0],
12325 [1.2037e-15, 0.40097, 1.2494e-16],
12326 [9.951e-16, 0.4029, 2.1865e-16],
12327 [1.1934e-15, 0.40484, 1.5618e-16],
12328 [0, 0.40679, 1.2494e-16],
12329 [0, 0.40874, 1.2494e-16],
12330 [0, 0.41069, 0],
12331 [1.3507e-15, 0.41264, 2.1865e-16],
12332 [1.0258e-15, 0.41458, 1.2494e-16],
12333 [3.1462e-16, 0.41654, 1.2494e-16],
12334 [1.3815e-15, 0.41849, 1.2494e-16],
12335 [6.9073e-16, 0.42045, 6.2472e-17],
12336 [7.0098e-16, 0.4224, 3.1236e-17],
12337 [6.0875e-16, 0.42437, 3.1236e-16],
12338 [3.4536e-16, 0.42633, 3.1236e-17],
12339 [9.3361e-16, 0.4283, 4.0607e-16],
12340 [7.0098e-16, 0.43026, 3.1236e-17],
12341 [1.3507e-15, 0.43223, 2.1865e-16],
12342 [1.0258e-15, 0.43419, 1.2494e-16],
12343 [1.3712e-15, 0.43617, 1.5618e-16],
12344 [5.4726e-16, 0.43814, 4.9977e-16],
12345 [7.1123e-16, 0.44011, 0],
12346 [1.7063e-15, 0.44209, 2.1865e-16],
12347 [6.3949e-16, 0.44406, 2.1865e-16],
12348 [3.4536e-16, 0.44603, 3.1236e-17],
12349 [6.1488e-17, 0.44801, 0],
12350 [4.4784e-16, 0.45, 0],
12351 [1.0566e-15, 0.45199, 3.1236e-17],
12352 [1.0463e-15, 0.45396, 6.2472e-17],
12353 [6.7023e-16, 0.45594, 1.2494e-16],
12354 [1.0668e-15, 0.45793, 0],
12355 [9.951e-16, 0.45992, 2.1865e-16],
12356 [7.4197e-16, 0.46191, 0],
12357 [1.1181e-15, 0.46391, 0],
12358 [9.6436e-16, 0.46589, 3.1236e-16],
12359 [1.2585e-15, 0.46789, 4.9977e-16],
12360 [1.3815e-15, 0.46989, 1.2494e-16],
12361 [6.7023e-16, 0.47189, 1.2494e-16],
12362 [3.5561e-16, 0.47388, 0],
12363 [2.0722e-15, 0.47589, 1.8741e-16],
12364 [1.1078e-15, 0.47788, 0],
12365 [1.6346e-15, 0.4799, 4.373e-16],
12366 [6.2924e-16, 0.4819, 2.4989e-16],
12367 [1.6756e-15, 0.48389, 3.1236e-16],
12368 [1.402e-15, 0.48591, 6.2472e-17],
12369 [1.0668e-15, 0.48793, 0],
12370 [0, 0.48992, 0],
12371 [0, 0.49195, 2.4989e-16],
12372 [6.7023e-16, 0.49395, 1.2494e-16],
12373 [1.4429e-15, 0.49597, 0],
12374 [2.7363e-16, 0.498, 2.4989e-16],
12375 [7.1123e-16, 0.5, 0],
12376 ]
12377 b_linear_ternary_green_0_46_c42 = bokeh_palette('linear_ternary_green_0_46_c42',linear_ternary_green_0_46_c42)
12378 m_linear_ternary_green_0_46_c42 = mpl_cm('linear_ternary_green_0_46_c42',linear_ternary_green_0_46_c42)
12379 m_linear_ternary_green_0_46_c42_r = mpl_cm('linear_ternary_green_0_46_c42_r',list(reversed(linear_ternary_green_0_46_c42)))
12380 kg = b_linear_ternary_green_0_46_c42
12381 m_kg = m_linear_ternary_green_0_46_c42
12382 m_kg_r = m_linear_ternary_green_0_46_c42_r
12383 palette['kg'] = b_linear_ternary_green_0_46_c42
12384 cm['kg'] = m_linear_ternary_green_0_46_c42
12385 cm['kg_r'] = m_linear_ternary_green_0_46_c42_r
12386 register_cmap('cet_kg',m_linear_ternary_green_0_46_c42)
12387 register_cmap('cet_kg_r',m_linear_ternary_green_0_46_c42_r)
12388
12389
12390
12391
12392 linear_ternary_red_0_50_c52 = [\
12393 [0, 0, 0],
12394 [0.0080248, 0.0015152, 4.5084e-17],
12395 [0.016166, 0.0030536, 0],
12396 [0.024126, 0.0045572, 6.0397e-18],
12397 [0.032164, 0.0060809, 1.6594e-17],
12398 [0.040345, 0.0076161, 0],
12399 [0.047917, 0.0090568, 0],
12400 [0.055209, 0.010404, 3.9777e-17],
12401 [0.06236, 0.011803, 0],
12402 [0.068888, 0.012988, 0],
12403 [0.074917, 0.014153, 0],
12404 [0.080792, 0.015256, 5.8811e-17],
12405 [0.086386, 0.016319, 8.7851e-18],
12406 [0.091832, 0.017341, 0],
12407 [0.096947, 0.018317, 0],
12408 [0.10199, 0.019262, 2.1475e-17],
12409 [0.10688, 0.020182, 0],
12410 [0.11156, 0.021071, 4.2461e-17],
12411 [0.11612, 0.021929, 0],
12412 [0.12051, 0.022761, 0],
12413 [0.12482, 0.023572, 0],
12414 [0.12901, 0.024369, 0],
12415 [0.13312, 0.025144, 0],
12416 [0.13712, 0.025899, 2.9284e-17],
12417 [0.14104, 0.026637, 0],
12418 [0.14484, 0.027362, 0],
12419 [0.14852, 0.028076, 0],
12420 [0.15218, 0.028765, 0],
12421 [0.15579, 0.029444, 0],
12422 [0.15929, 0.03011, 0],
12423 [0.16274, 0.03076, 0],
12424 [0.16612, 0.031401, 0],
12425 [0.16947, 0.032031, 0],
12426 [0.17271, 0.032655, 0],
12427 [0.1759, 0.033257, 0],
12428 [0.17909, 0.033824, 0],
12429 [0.18223, 0.034436, 0],
12430 [0.18542, 0.035067, 0],
12431 [0.18847, 0.03563, 0],
12432 [0.19142, 0.03617, 0],
12433 [0.19437, 0.036729, 0],
12434 [0.19725, 0.037267, 5.4019e-07],
12435 [0.20012, 0.037802, 1.2837e-06],
12436 [0.20303, 0.038349, 9.9959e-07],
12437 [0.20594, 0.038898, 7.7892e-07],
12438 [0.20884, 0.039449, 9.7112e-07],
12439 [0.21176, 0.039999, 1.2788e-06],
12440 [0.21466, 0.040546, 1.373e-06],
12441 [0.21761, 0.0411, 1.2556e-06],
12442 [0.22057, 0.041669, 9.5959e-07],
12443 [0.22346, 0.042219, 8.1372e-07],
12444 [0.22635, 0.042741, 1.1485e-06],
12445 [0.22925, 0.043284, 1.3628e-06],
12446 [0.23223, 0.04386, 1.3699e-06],
12447 [0.23522, 0.044439, 1.2685e-06],
12448 [0.23815, 0.045002, 1.0271e-06],
12449 [0.24106, 0.045522, 7.9582e-07],
12450 [0.24401, 0.046076, 1.0449e-06],
12451 [0.24701, 0.046672, 1.3237e-06],
12452 [0.24995, 0.047232, 1.4871e-06],
12453 [0.25293, 0.047749, 1.4007e-06],
12454 [0.25591, 0.048339, 1.1191e-06],
12455 [0.25894, 0.048928, 8.5433e-07],
12456 [0.26191, 0.049479, 9.2045e-07],
12457 [0.26486, 0.050025, 1.3084e-06],
12458 [0.26783, 0.05059, 1.4958e-06],
12459 [0.27084, 0.051156, 1.5067e-06],
12460 [0.27383, 0.051721, 1.3409e-06],
12461 [0.27682, 0.052289, 1.0257e-06],
12462 [0.27983, 0.052858, 7.8803e-07],
12463 [0.28284, 0.053424, 1.0814e-06],
12464 [0.28584, 0.053993, 1.3794e-06],
12465 [0.28888, 0.054565, 1.5209e-06],
12466 [0.2919, 0.055134, 1.522e-06],
12467 [0.29494, 0.055708, 1.3561e-06],
12468 [0.29798, 0.056296, 1.0594e-06],
12469 [0.30101, 0.056866, 8.5564e-07],
12470 [0.30401, 0.057414, 1.0969e-06],
12471 [0.30705, 0.057986, 1.3643e-06],
12472 [0.31013, 0.05858, 1.5001e-06],
12473 [0.3132, 0.05917, 1.5634e-06],
12474 [0.31627, 0.059754, 1.4993e-06],
12475 [0.31931, 0.06032, 1.2688e-06],
12476 [0.32234, 0.060876, 9.3009e-07],
12477 [0.32538, 0.061448, 8.4705e-07],
12478 [0.32848, 0.062046, 1.1943e-06],
12479 [0.33157, 0.06265, 1.4594e-06],
12480 [0.33467, 0.06322, 1.6339e-06],
12481 [0.33772, 0.063788, 1.6369e-06],
12482 [0.3408, 0.064374, 1.4847e-06],
12483 [0.34388, 0.064956, 1.2226e-06],
12484 [0.34698, 0.065538, 8.9134e-07],
12485 [0.35008, 0.066125, 8.5068e-07],
12486 [0.35318, 0.066712, 1.2269e-06],
12487 [0.35629, 0.067299, 1.4894e-06],
12488 [0.35939, 0.067883, 1.6295e-06],
12489 [0.36252, 0.068473, 1.6472e-06],
12490 [0.36565, 0.069079, 1.5852e-06],
12491 [0.36876, 0.069658, 1.4248e-06],
12492 [0.37185, 0.070223, 1.0684e-06],
12493 [0.37498, 0.070835, 7.9019e-07],
12494 [0.37813, 0.071435, 1.022e-06],
12495 [0.38125, 0.072005, 1.3647e-06],
12496 [0.38438, 0.072592, 1.5517e-06],
12497 [0.38754, 0.073217, 1.6548e-06],
12498 [0.39069, 0.073807, 1.7253e-06],
12499 [0.39382, 0.074384, 1.6463e-06],
12500 [0.39695, 0.074981, 1.4452e-06],
12501 [0.40011, 0.075576, 1.1513e-06],
12502 [0.40327, 0.076172, 8.5042e-07],
12503 [0.40643, 0.076769, 8.941e-07],
12504 [0.40959, 0.077367, 1.2367e-06],
12505 [0.41277, 0.077967, 1.4894e-06],
12506 [0.41594, 0.078566, 1.6548e-06],
12507 [0.41912, 0.079167, 1.728e-06],
12508 [0.4223, 0.079769, 1.7184e-06],
12509 [0.4255, 0.080371, 1.6249e-06],
12510 [0.4287, 0.080974, 1.4674e-06],
12511 [0.43192, 0.081588, 1.2356e-06],
12512 [0.43512, 0.082195, 9.4259e-07],
12513 [0.43828, 0.08278, 7.201e-07],
12514 [0.4415, 0.083388, 1.052e-06],
12515 [0.44472, 0.084012, 1.3338e-06],
12516 [0.44791, 0.084617, 1.593e-06],
12517 [0.45112, 0.085205, 1.7373e-06],
12518 [0.45433, 0.085801, 1.7608e-06],
12519 [0.45756, 0.086427, 1.7212e-06],
12520 [0.4608, 0.087056, 1.6842e-06],
12521 [0.46404, 0.087652, 1.5738e-06],
12522 [0.46727, 0.088257, 1.3578e-06],
12523 [0.47049, 0.088871, 1.1045e-06],
12524 [0.47373, 0.089482, 8.1745e-07],
12525 [0.47697, 0.090095, 7.8044e-07],
12526 [0.48022, 0.090707, 1.0884e-06],
12527 [0.48348, 0.091327, 1.3399e-06],
12528 [0.48673, 0.091949, 1.5673e-06],
12529 [0.48996, 0.092545, 1.7249e-06],
12530 [0.49321, 0.093154, 1.7614e-06],
12531 [0.49649, 0.093784, 1.7613e-06],
12532 [0.49977, 0.094411, 1.763e-06],
12533 [0.50305, 0.095031, 1.7236e-06],
12534 [0.50631, 0.09564, 1.6147e-06],
12535 [0.50957, 0.096244, 1.4163e-06],
12536 [0.51285, 0.096865, 1.1666e-06],
12537 [0.51615, 0.097503, 9.3008e-07],
12538 [0.51945, 0.098123, 7.3324e-07],
12539 [0.52274, 0.098737, 8.3616e-07],
12540 [0.52603, 0.099359, 1.0957e-06],
12541 [0.52932, 0.099983, 1.3165e-06],
12542 [0.53262, 0.10061, 1.4935e-06],
12543 [0.53592, 0.10123, 1.6285e-06],
12544 [0.53923, 0.10185, 1.7225e-06],
12545 [0.54255, 0.10248, 1.7716e-06],
12546 [0.54588, 0.10311, 1.8035e-06],
12547 [0.54919, 0.10374, 1.8308e-06],
12548 [0.55249, 0.10435, 1.7782e-06],
12549 [0.5558, 0.10498, 1.6557e-06],
12550 [0.55915, 0.10562, 1.5548e-06],
12551 [0.56251, 0.10626, 1.4434e-06],
12552 [0.56583, 0.10688, 1.3031e-06],
12553 [0.56915, 0.10751, 1.1028e-06],
12554 [0.57249, 0.10813, 8.5642e-07],
12555 [0.57584, 0.10877, 6.5276e-07],
12556 [0.57921, 0.10941, 6.6729e-07],
12557 [0.58255, 0.11004, 8.9887e-07],
12558 [0.58591, 0.11067, 1.1025e-06],
12559 [0.58925, 0.1113, 1.264e-06],
12560 [0.59262, 0.11194, 1.3991e-06],
12561 [0.59599, 0.11257, 1.5204e-06],
12562 [0.59936, 0.11322, 1.6369e-06],
12563 [0.60271, 0.11385, 1.7384e-06],
12564 [0.60606, 0.11447, 1.7667e-06],
12565 [0.60945, 0.11512, 1.7698e-06],
12566 [0.61284, 0.11576, 1.7921e-06],
12567 [0.61623, 0.11641, 1.8189e-06],
12568 [0.6196, 0.11703, 1.7927e-06],
12569 [0.62299, 0.11767, 1.7298e-06],
12570 [0.62639, 0.11833, 1.7048e-06],
12571 [0.62978, 0.11896, 1.6692e-06],
12572 [0.63317, 0.1196, 1.5768e-06],
12573 [0.63657, 0.12024, 1.4791e-06],
12574 [0.63997, 0.12088, 1.3801e-06],
12575 [0.64337, 0.12153, 1.2686e-06],
12576 [0.64679, 0.12217, 1.1466e-06],
12577 [0.65019, 0.12281, 1.0261e-06],
12578 [0.65362, 0.12346, 8.8816e-07],
12579 [0.65704, 0.12411, 7.6247e-07],
12580 [0.66046, 0.12475, 6.252e-07],
12581 [0.6639, 0.1254, 5.0813e-07],
12582 [0.66734, 0.12605, 5.4766e-07],
12583 [0.67075, 0.12669, 4.2573e-07],
12584 [0.67419, 0.12734, 2.3855e-08],
12585 [0.67764, 0.128, 0],
12586 [0.68106, 0.12864, 0],
12587 [0.68451, 0.12929, 0],
12588 [0.68797, 0.12996, 0],
12589 [0.69142, 0.13061, 0],
12590 [0.69486, 0.13125, 0],
12591 [0.69832, 0.1319, 0],
12592 [0.70177, 0.13256, 0],
12593 [0.70524, 0.13321, 0],
12594 [0.70871, 0.13387, 0],
12595 [0.71218, 0.13453, 0],
12596 [0.71565, 0.13518, 0],
12597 [0.7191, 0.13582, 0],
12598 [0.72258, 0.13648, 0],
12599 [0.72607, 0.13715, 0],
12600 [0.72956, 0.13781, 0],
12601 [0.73304, 0.13847, 0],
12602 [0.73651, 0.13912, 0],
12603 [0.74001, 0.13977, 0],
12604 [0.74351, 0.14044, 0],
12605 [0.74701, 0.14111, 0],
12606 [0.75051, 0.14176, 0],
12607 [0.75401, 0.14242, 0],
12608 [0.75751, 0.14309, 0],
12609 [0.76102, 0.14375, 0],
12610 [0.76454, 0.14441, 0],
12611 [0.76805, 0.14508, 0],
12612 [0.77157, 0.14575, 0],
12613 [0.77507, 0.1464, 0],
12614 [0.7786, 0.14707, 0],
12615 [0.78213, 0.14774, 0],
12616 [0.78565, 0.14839, 0],
12617 [0.78919, 0.14907, 0],
12618 [0.79273, 0.14975, 0],
12619 [0.79625, 0.1504, 0],
12620 [0.7998, 0.15107, 0],
12621 [0.80333, 0.15174, 0],
12622 [0.80688, 0.15241, 0],
12623 [0.81042, 0.15308, 0],
12624 [0.81397, 0.15375, 0],
12625 [0.81752, 0.15442, 0],
12626 [0.82108, 0.15509, 0],
12627 [0.82465, 0.15577, 0],
12628 [0.82821, 0.15645, 0],
12629 [0.83177, 0.15711, 0],
12630 [0.83534, 0.15778, 0],
12631 [0.83891, 0.15847, 0],
12632 [0.84248, 0.15914, 0],
12633 [0.84604, 0.1598, 0],
12634 [0.84963, 0.16048, 0],
12635 [0.85322, 0.16117, 0],
12636 [0.8568, 0.16184, 0],
12637 [0.86038, 0.16251, 0],
12638 [0.86398, 0.16319, 0],
12639 [0.86757, 0.16388, 0],
12640 [0.87115, 0.16455, 0],
12641 [0.87473, 0.16523, 0],
12642 [0.87834, 0.16591, 0],
12643 [0.88196, 0.16659, 0],
12644 [0.88556, 0.16727, 0],
12645 [0.88915, 0.16795, 0],
12646 [0.89277, 0.16863, 0],
12647 [0.89639, 0.16932, 0],
12648 [0.9, 0.17, 2.0303e-16],
12649 ]
12650 b_linear_ternary_red_0_50_c52 = bokeh_palette('linear_ternary_red_0_50_c52',linear_ternary_red_0_50_c52)
12651 m_linear_ternary_red_0_50_c52 = mpl_cm('linear_ternary_red_0_50_c52',linear_ternary_red_0_50_c52)
12652 m_linear_ternary_red_0_50_c52_r = mpl_cm('linear_ternary_red_0_50_c52_r',list(reversed(linear_ternary_red_0_50_c52)))
12653 kr = b_linear_ternary_red_0_50_c52
12654 m_kr = m_linear_ternary_red_0_50_c52
12655 m_kr_r = m_linear_ternary_red_0_50_c52_r
12656 palette['kr'] = b_linear_ternary_red_0_50_c52
12657 cm['kr'] = m_linear_ternary_red_0_50_c52
12658 cm['kr_r'] = m_linear_ternary_red_0_50_c52_r
12659 register_cmap('cet_kr',m_linear_ternary_red_0_50_c52)
12660 register_cmap('cet_kr_r',m_linear_ternary_red_0_50_c52_r)
12661
12662
12663
12664
12665 rainbow_bgyr_35_85_c72 = [\
12666 [0, 0.20387, 0.96251],
12667 [0, 0.21524, 0.9514],
12668 [0, 0.22613, 0.94031],
12669 [0, 0.23654, 0.92923],
12670 [0, 0.24654, 0.91817],
12671 [0, 0.2562, 0.90712],
12672 [0, 0.26557, 0.89608],
12673 [0, 0.27465, 0.88506],
12674 [0, 0.28348, 0.87405],
12675 [0, 0.29209, 0.86305],
12676 [0, 0.30047, 0.85206],
12677 [0, 0.3087, 0.84109],
12678 [0, 0.31672, 0.83013],
12679 [0, 0.32458, 0.81917],
12680 [0, 0.33232, 0.80823],
12681 [0, 0.3399, 0.7973],
12682 [0, 0.34736, 0.78638],
12683 [0, 0.3547, 0.77546],
12684 [0, 0.36191, 0.76456],
12685 [0, 0.36902, 0.75367],
12686 [0, 0.37602, 0.7428],
12687 [0, 0.38291, 0.73193],
12688 [0, 0.38969, 0.72108],
12689 [0, 0.39636, 0.71026],
12690 [0, 0.40292, 0.69946],
12691 [0, 0.40934, 0.68872],
12692 [0, 0.41561, 0.67802],
12693 [0, 0.42172, 0.66738],
12694 [0, 0.42768, 0.65684],
12695 [0, 0.43342, 0.64639],
12696 [0, 0.43896, 0.63605],
12697 [0, 0.44432, 0.62583],
12698 [0, 0.44945, 0.61575],
12699 [0, 0.45438, 0.60579],
12700 [0, 0.45911, 0.59597],
12701 [0.0043377, 0.46367, 0.58627],
12702 [0.029615, 0.46807, 0.57668],
12703 [0.055795, 0.47235, 0.56717],
12704 [0.077065, 0.47652, 0.55774],
12705 [0.095292, 0.48061, 0.54837],
12706 [0.11119, 0.48465, 0.53903],
12707 [0.1253, 0.48865, 0.52971],
12708 [0.13799, 0.49262, 0.5204],
12709 [0.14937, 0.49658, 0.5111],
12710 [0.15963, 0.50055, 0.50179],
12711 [0.169, 0.50452, 0.49244],
12712 [0.17747, 0.50849, 0.48309],
12713 [0.18517, 0.51246, 0.4737],
12714 [0.19217, 0.51645, 0.46429],
12715 [0.19856, 0.52046, 0.45483],
12716 [0.20443, 0.52448, 0.44531],
12717 [0.20974, 0.52851, 0.43577],
12718 [0.21461, 0.53255, 0.42616],
12719 [0.21905, 0.53661, 0.41651],
12720 [0.22309, 0.54066, 0.40679],
12721 [0.22674, 0.54474, 0.397],
12722 [0.23002, 0.54883, 0.38713],
12723 [0.233, 0.55292, 0.3772],
12724 [0.23568, 0.55703, 0.36716],
12725 [0.23802, 0.56114, 0.35704],
12726 [0.24006, 0.56526, 0.34678],
12727 [0.24185, 0.56939, 0.3364],
12728 [0.24334, 0.57354, 0.32588],
12729 [0.24458, 0.57769, 0.31523],
12730 [0.24556, 0.58185, 0.30439],
12731 [0.2463, 0.58603, 0.29336],
12732 [0.2468, 0.59019, 0.28214],
12733 [0.24707, 0.59438, 0.27067],
12734 [0.24714, 0.59856, 0.25896],
12735 [0.24703, 0.60275, 0.24696],
12736 [0.24679, 0.60693, 0.23473],
12737 [0.24647, 0.61109, 0.22216],
12738 [0.24615, 0.61523, 0.20936],
12739 [0.24595, 0.61936, 0.19632],
12740 [0.246, 0.62342, 0.18304],
12741 [0.24644, 0.62742, 0.16969],
12742 [0.24748, 0.63135, 0.1563],
12743 [0.24925, 0.63518, 0.14299],
12744 [0.25196, 0.6389, 0.13001],
12745 [0.2557, 0.64249, 0.11741],
12746 [0.26057, 0.64594, 0.10557],
12747 [0.26659, 0.64926, 0.094696],
12748 [0.27372, 0.65242, 0.084904],
12749 [0.28182, 0.65545, 0.076489],
12750 [0.29078, 0.65835, 0.069753],
12751 [0.30043, 0.66113, 0.064513],
12752 [0.31061, 0.66383, 0.060865],
12753 [0.32112, 0.66642, 0.058721],
12754 [0.33186, 0.66896, 0.057692],
12755 [0.34272, 0.67144, 0.057693],
12756 [0.35356, 0.67388, 0.058443],
12757 [0.36439, 0.67628, 0.059738],
12758 [0.37512, 0.67866, 0.061142],
12759 [0.38575, 0.68102, 0.062974],
12760 [0.39627, 0.68337, 0.064759],
12761 [0.40666, 0.68571, 0.066664],
12762 [0.41692, 0.68803, 0.068644],
12763 [0.42707, 0.69034, 0.070512],
12764 [0.43709, 0.69266, 0.072423],
12765 [0.44701, 0.69494, 0.074359],
12766 [0.45683, 0.69723, 0.076211],
12767 [0.46657, 0.6995, 0.07809],
12768 [0.47621, 0.70177, 0.079998],
12769 [0.48577, 0.70403, 0.081943],
12770 [0.49527, 0.70629, 0.083778],
12771 [0.5047, 0.70853, 0.085565],
12772 [0.51405, 0.71076, 0.087502],
12773 [0.52335, 0.71298, 0.089316],
12774 [0.53259, 0.7152, 0.091171],
12775 [0.54176, 0.7174, 0.092931],
12776 [0.5509, 0.7196, 0.094839],
12777 [0.55999, 0.72178, 0.096566],
12778 [0.56902, 0.72396, 0.098445],
12779 [0.57802, 0.72613, 0.10023],
12780 [0.58698, 0.72828, 0.10204],
12781 [0.5959, 0.73044, 0.10385],
12782 [0.60479, 0.73258, 0.10564],
12783 [0.61363, 0.73471, 0.10744],
12784 [0.62246, 0.73683, 0.10925],
12785 [0.63125, 0.73895, 0.11102],
12786 [0.64001, 0.74104, 0.11282],
12787 [0.64874, 0.74315, 0.11452],
12788 [0.65745, 0.74523, 0.11636],
12789 [0.66613, 0.74731, 0.11813],
12790 [0.67479, 0.74937, 0.11986],
12791 [0.68343, 0.75144, 0.12161],
12792 [0.69205, 0.75348, 0.12338],
12793 [0.70065, 0.75552, 0.12517],
12794 [0.70923, 0.75755, 0.12691],
12795 [0.71779, 0.75957, 0.12868],
12796 [0.72633, 0.76158, 0.13048],
12797 [0.73487, 0.76359, 0.13221],
12798 [0.74338, 0.76559, 0.13396],
12799 [0.75188, 0.76756, 0.13568],
12800 [0.76037, 0.76954, 0.13747],
12801 [0.76884, 0.77151, 0.13917],
12802 [0.77731, 0.77346, 0.14097],
12803 [0.78576, 0.77541, 0.14269],
12804 [0.7942, 0.77736, 0.14444],
12805 [0.80262, 0.77928, 0.14617],
12806 [0.81105, 0.7812, 0.14791],
12807 [0.81945, 0.78311, 0.14967],
12808 [0.82786, 0.78502, 0.15138],
12809 [0.83626, 0.78691, 0.15311],
12810 [0.84465, 0.7888, 0.15486],
12811 [0.85304, 0.79066, 0.15662],
12812 [0.86141, 0.79251, 0.15835],
12813 [0.86978, 0.79434, 0.16002],
12814 [0.87814, 0.79612, 0.16178],
12815 [0.88647, 0.79786, 0.16346],
12816 [0.89477, 0.79952, 0.16507],
12817 [0.90301, 0.80106, 0.1667],
12818 [0.91115, 0.80245, 0.16819],
12819 [0.91917, 0.80364, 0.16964],
12820 [0.92701, 0.80456, 0.1709],
12821 [0.93459, 0.80514, 0.172],
12822 [0.94185, 0.80532, 0.17289],
12823 [0.94869, 0.80504, 0.17355],
12824 [0.95506, 0.80424, 0.17392],
12825 [0.96088, 0.80289, 0.17399],
12826 [0.96609, 0.80097, 0.17375],
12827 [0.97069, 0.7985, 0.17319],
12828 [0.97465, 0.79549, 0.17234],
12829 [0.97801, 0.79201, 0.17121],
12830 [0.98082, 0.7881, 0.16986],
12831 [0.98314, 0.78384, 0.16825],
12832 [0.98504, 0.77928, 0.16652],
12833 [0.9866, 0.7745, 0.16463],
12834 [0.98789, 0.76955, 0.16265],
12835 [0.98897, 0.76449, 0.16056],
12836 [0.9899, 0.75932, 0.15848],
12837 [0.99072, 0.75411, 0.15634],
12838 [0.99146, 0.74885, 0.15414],
12839 [0.99214, 0.74356, 0.15196],
12840 [0.99279, 0.73825, 0.14981],
12841 [0.9934, 0.73293, 0.1476],
12842 [0.99398, 0.72759, 0.14543],
12843 [0.99454, 0.72224, 0.1432],
12844 [0.99509, 0.71689, 0.14103],
12845 [0.99562, 0.71152, 0.1388],
12846 [0.99613, 0.70614, 0.13659],
12847 [0.99662, 0.70075, 0.13444],
12848 [0.9971, 0.69534, 0.13223],
12849 [0.99755, 0.68993, 0.13006],
12850 [0.998, 0.6845, 0.12783],
12851 [0.99842, 0.67906, 0.12564],
12852 [0.99883, 0.67361, 0.1234],
12853 [0.99922, 0.66815, 0.12119],
12854 [0.99959, 0.66267, 0.11904],
12855 [0.99994, 0.65717, 0.11682],
12856 [1, 0.65166, 0.11458],
12857 [1, 0.64613, 0.11244],
12858 [1, 0.64059, 0.11024],
12859 [1, 0.63503, 0.10797],
12860 [1, 0.62945, 0.1058],
12861 [1, 0.62386, 0.1036],
12862 [1, 0.61825, 0.10135],
12863 [1, 0.61261, 0.099135],
12864 [1, 0.60697, 0.096882],
12865 [1, 0.6013, 0.094743],
12866 [1, 0.59561, 0.092465],
12867 [1, 0.58989, 0.090257],
12868 [1, 0.58416, 0.088032],
12869 [1, 0.5784, 0.085726],
12870 [1, 0.57263, 0.083542],
12871 [1, 0.56682, 0.081316],
12872 [1, 0.56098, 0.079004],
12873 [1, 0.55513, 0.076745],
12874 [1, 0.54925, 0.07453],
12875 [1, 0.54333, 0.072245],
12876 [1, 0.53739, 0.070004],
12877 [1, 0.53141, 0.067732],
12878 [1, 0.52541, 0.065424],
12879 [1, 0.51937, 0.06318],
12880 [1, 0.5133, 0.06081],
12881 [1, 0.50718, 0.058502],
12882 [1, 0.50104, 0.056232],
12883 [1, 0.49486, 0.053826],
12884 [1, 0.48863, 0.051494],
12885 [1, 0.48236, 0.049242],
12886 [1, 0.47605, 0.046828],
12887 [1, 0.46969, 0.044447],
12888 [1, 0.46327, 0.042093],
12889 [1, 0.45681, 0.039648],
12890 [1, 0.45031, 0.037261],
12891 [1, 0.44374, 0.034882],
12892 [1, 0.43712, 0.032495],
12893 [1, 0.43043, 0.030303],
12894 [1, 0.42367, 0.02818],
12895 [1, 0.41686, 0.026121],
12896 [1, 0.40997, 0.024126],
12897 [1, 0.40299, 0.022194],
12898 [1, 0.39595, 0.020325],
12899 [1, 0.38882, 0.018517],
12900 [0.99994, 0.38159, 0.016771],
12901 [0.99961, 0.37428, 0.015085],
12902 [0.99927, 0.36685, 0.013457],
12903 [0.99892, 0.35932, 0.011916],
12904 [0.99855, 0.35167, 0.010169],
12905 [0.99817, 0.3439, 0.0087437],
12906 [0.99778, 0.336, 0.0073541],
12907 [0.99738, 0.32796, 0.0060199],
12908 [0.99696, 0.31976, 0.0047429],
12909 [0.99653, 0.31138, 0.0035217],
12910 [0.99609, 0.30282, 0.0023557],
12911 [0.99563, 0.29407, 0.0012445],
12912 [0.99517, 0.2851, 0.00018742],
12913 [0.99469, 0.27591, 0],
12914 [0.9942, 0.26642, 0],
12915 [0.99369, 0.25664, 0],
12916 [0.99318, 0.24652, 0],
12917 [0.99265, 0.23605, 0],
12918 [0.99211, 0.22511, 0],
12919 [0.99155, 0.2137, 0],
12920 [0.99099, 0.20169, 0],
12921 [0.99041, 0.18903, 0],
12922 ]
12923 b_rainbow_bgyr_35_85_c72 = bokeh_palette('rainbow_bgyr_35_85_c72',rainbow_bgyr_35_85_c72)
12924 m_rainbow_bgyr_35_85_c72 = mpl_cm('rainbow_bgyr_35_85_c72',rainbow_bgyr_35_85_c72)
12925 m_rainbow_bgyr_35_85_c72_r = mpl_cm('rainbow_bgyr_35_85_c72_r',list(reversed(rainbow_bgyr_35_85_c72)))
12926
12927
12928
12929
12930 rainbow_bgyr_35_85_c73 = [\
12931 [0, 0.20755, 0.97632],
12932 [0, 0.21857, 0.96476],
12933 [0, 0.2291, 0.95322],
12934 [0, 0.23923, 0.94169],
12935 [0, 0.24899, 0.93018],
12936 [0, 0.25842, 0.91868],
12937 [0, 0.26756, 0.9072],
12938 [0, 0.27649, 0.89573],
12939 [0, 0.28513, 0.88428],
12940 [0, 0.29358, 0.87284],
12941 [0, 0.30184, 0.86141],
12942 [0, 0.30994, 0.85],
12943 [0, 0.31785, 0.83859],
12944 [0, 0.3256, 0.82721],
12945 [0, 0.33324, 0.81583],
12946 [0, 0.34073, 0.80447],
12947 [0, 0.3481, 0.79312],
12948 [0, 0.35537, 0.78178],
12949 [0, 0.3625, 0.77045],
12950 [0, 0.36954, 0.75913],
12951 [0, 0.37649, 0.74783],
12952 [0, 0.38333, 0.73654],
12953 [0, 0.39005, 0.72528],
12954 [0, 0.39667, 0.71405],
12955 [0, 0.40319, 0.70286],
12956 [0, 0.40957, 0.69171],
12957 [0, 0.4158, 0.68063],
12958 [0, 0.42188, 0.66965],
12959 [0, 0.4278, 0.65875],
12960 [0, 0.43352, 0.64799],
12961 [0, 0.43905, 0.63737],
12962 [0, 0.44438, 0.62689],
12963 [0, 0.4495, 0.61659],
12964 [0, 0.45441, 0.60644],
12965 [0, 0.45914, 0.59646],
12966 [0.0019224, 0.46368, 0.58662],
12967 [0.027932, 0.46808, 0.57693],
12968 [0.054843, 0.47236, 0.56735],
12969 [0.076598, 0.47653, 0.55785],
12970 [0.095053, 0.48062, 0.54844],
12971 [0.11106, 0.48465, 0.53907],
12972 [0.12523, 0.48865, 0.52974],
12973 [0.13795, 0.49262, 0.52042],
12974 [0.14935, 0.49658, 0.5111],
12975 [0.15962, 0.50055, 0.50179],
12976 [0.169, 0.50452, 0.49245],
12977 [0.17747, 0.50849, 0.48309],
12978 [0.18517, 0.51246, 0.4737],
12979 [0.19217, 0.51645, 0.46429],
12980 [0.19856, 0.52046, 0.45483],
12981 [0.20443, 0.52448, 0.44531],
12982 [0.20974, 0.52851, 0.43577],
12983 [0.21461, 0.53255, 0.42616],
12984 [0.21905, 0.53661, 0.41651],
12985 [0.22309, 0.54066, 0.40679],
12986 [0.22674, 0.54474, 0.397],
12987 [0.23002, 0.54883, 0.38713],
12988 [0.233, 0.55292, 0.3772],
12989 [0.23568, 0.55703, 0.36716],
12990 [0.23802, 0.56114, 0.35704],
12991 [0.24006, 0.56526, 0.34678],
12992 [0.24185, 0.56939, 0.3364],
12993 [0.24334, 0.57354, 0.32588],
12994 [0.24458, 0.57769, 0.31523],
12995 [0.24556, 0.58185, 0.30439],
12996 [0.2463, 0.58603, 0.29336],
12997 [0.2468, 0.59019, 0.28214],
12998 [0.24707, 0.59438, 0.27067],
12999 [0.24714, 0.59856, 0.25895],
13000 [0.24704, 0.60275, 0.24696],
13001 [0.24679, 0.60693, 0.23472],
13002 [0.24648, 0.61109, 0.22215],
13003 [0.24616, 0.61523, 0.20933],
13004 [0.24597, 0.61936, 0.19628],
13005 [0.24602, 0.62342, 0.18297],
13006 [0.24648, 0.62742, 0.1696],
13007 [0.24753, 0.63135, 0.15615],
13008 [0.24931, 0.63518, 0.14276],
13009 [0.25204, 0.63889, 0.12965],
13010 [0.25579, 0.64249, 0.11693],
13011 [0.2607, 0.64593, 0.10484],
13012 [0.26674, 0.64925, 0.093668],
13013 [0.2739, 0.65241, 0.083583],
13014 [0.28205, 0.65544, 0.074764],
13015 [0.29104, 0.65834, 0.067449],
13016 [0.30071, 0.66112, 0.061598],
13017 [0.31093, 0.66382, 0.057362],
13018 [0.32147, 0.66641, 0.054542],
13019 [0.33226, 0.66895, 0.052918],
13020 [0.34314, 0.67142, 0.052293],
13021 [0.35402, 0.67386, 0.052401],
13022 [0.36487, 0.67627, 0.05303],
13023 [0.37564, 0.67864, 0.054018],
13024 [0.38629, 0.681, 0.055243],
13025 [0.39683, 0.68335, 0.05664],
13026 [0.40725, 0.68569, 0.057955],
13027 [0.41755, 0.68801, 0.059542],
13028 [0.42772, 0.69031, 0.060911],
13029 [0.43777, 0.69262, 0.062454],
13030 [0.4477, 0.69491, 0.063883],
13031 [0.45755, 0.69719, 0.065334],
13032 [0.46731, 0.69947, 0.066802],
13033 [0.47698, 0.70173, 0.068291],
13034 [0.48656, 0.70399, 0.069758],
13035 [0.49607, 0.70625, 0.071211],
13036 [0.50551, 0.70848, 0.072621],
13037 [0.5149, 0.71071, 0.074107],
13038 [0.52421, 0.71293, 0.07551],
13039 [0.53346, 0.71514, 0.076938],
13040 [0.54268, 0.71735, 0.078389],
13041 [0.55183, 0.71954, 0.079862],
13042 [0.56093, 0.72172, 0.08136],
13043 [0.56998, 0.7239, 0.082779],
13044 [0.57901, 0.72607, 0.084273],
13045 [0.58797, 0.72822, 0.08563],
13046 [0.59692, 0.73037, 0.08717],
13047 [0.60581, 0.73251, 0.088583],
13048 [0.61468, 0.73464, 0.09003],
13049 [0.62353, 0.73676, 0.091506],
13050 [0.63233, 0.73887, 0.092872],
13051 [0.6411, 0.74097, 0.094388],
13052 [0.64986, 0.74307, 0.095796],
13053 [0.65858, 0.74515, 0.097234],
13054 [0.66728, 0.74722, 0.098697],
13055 [0.67595, 0.74928, 0.10013],
13056 [0.6846, 0.75135, 0.10157],
13057 [0.69324, 0.75339, 0.10305],
13058 [0.70185, 0.75543, 0.10444],
13059 [0.71045, 0.75746, 0.10594],
13060 [0.71902, 0.75947, 0.10738],
13061 [0.72758, 0.76149, 0.10881],
13062 [0.73613, 0.76349, 0.1103],
13063 [0.74466, 0.76548, 0.11173],
13064 [0.75317, 0.76746, 0.1132],
13065 [0.76167, 0.76943, 0.11457],
13066 [0.77016, 0.7714, 0.11608],
13067 [0.77864, 0.77335, 0.11749],
13068 [0.78711, 0.7753, 0.11897],
13069 [0.79556, 0.77724, 0.12038],
13070 [0.80401, 0.77916, 0.12182],
13071 [0.81244, 0.78108, 0.12327],
13072 [0.82086, 0.78299, 0.12474],
13073 [0.82929, 0.78489, 0.12623],
13074 [0.83769, 0.78678, 0.12766],
13075 [0.84609, 0.78866, 0.1291],
13076 [0.8545, 0.79053, 0.1306],
13077 [0.86289, 0.79238, 0.13203],
13078 [0.87127, 0.7942, 0.13346],
13079 [0.87964, 0.79598, 0.13491],
13080 [0.88799, 0.79771, 0.13626],
13081 [0.8963, 0.79937, 0.13769],
13082 [0.90456, 0.80091, 0.13896],
13083 [0.91273, 0.80229, 0.14021],
13084 [0.92077, 0.80347, 0.14138],
13085 [0.92863, 0.80438, 0.14238],
13086 [0.93625, 0.80495, 0.14322],
13087 [0.94355, 0.80511, 0.14385],
13088 [0.95044, 0.80481, 0.14425],
13089 [0.95686, 0.80399, 0.14437],
13090 [0.96274, 0.80262, 0.14419],
13091 [0.96803, 0.80067, 0.14372],
13092 [0.9727, 0.79816, 0.14294],
13093 [0.97674, 0.79512, 0.14188],
13094 [0.9802, 0.79159, 0.14055],
13095 [0.9831, 0.78764, 0.13895],
13096 [0.98551, 0.78333, 0.13721],
13097 [0.98751, 0.77872, 0.13526],
13098 [0.98917, 0.77389, 0.13319],
13099 [0.99056, 0.76889, 0.13103],
13100 [0.99175, 0.76376, 0.12875],
13101 [0.99279, 0.75855, 0.12647],
13102 [0.99371, 0.75327, 0.1241],
13103 [0.99455, 0.74796, 0.12173],
13104 [0.99534, 0.74261, 0.11937],
13105 [0.99608, 0.73724, 0.11697],
13106 [0.99679, 0.73185, 0.11453],
13107 [0.99748, 0.72646, 0.11217],
13108 [0.99814, 0.72104, 0.10976],
13109 [0.99879, 0.71563, 0.1073],
13110 [0.99942, 0.71019, 0.1048],
13111 [1, 0.70475, 0.10238],
13112 [1, 0.69929, 0.099908],
13113 [1, 0.69382, 0.09745],
13114 [1, 0.68834, 0.095],
13115 [1, 0.68284, 0.092452],
13116 [1, 0.67734, 0.08996],
13117 [1, 0.6718, 0.087465],
13118 [1, 0.66626, 0.08489],
13119 [1, 0.66071, 0.082364],
13120 [1, 0.65514, 0.079729],
13121 [1, 0.64955, 0.077118],
13122 [1, 0.64394, 0.074554],
13123 [1, 0.63832, 0.071927],
13124 [1, 0.63268, 0.069347],
13125 [1, 0.62702, 0.066593],
13126 [1, 0.62135, 0.063895],
13127 [1, 0.61565, 0.061104],
13128 [1, 0.60993, 0.058355],
13129 [1, 0.6042, 0.055584],
13130 [1, 0.59843, 0.052708],
13131 [1, 0.59265, 0.049893],
13132 [1, 0.58684, 0.046988],
13133 [1, 0.58101, 0.043966],
13134 [1, 0.57515, 0.041014],
13135 [1, 0.56926, 0.037943],
13136 [1, 0.56336, 0.034887],
13137 [1, 0.55742, 0.031822],
13138 [1, 0.55145, 0.028972],
13139 [1, 0.54546, 0.026194],
13140 [1, 0.53942, 0.023487],
13141 [1, 0.53336, 0.020851],
13142 [1, 0.52727, 0.018287],
13143 [1, 0.52114, 0.015792],
13144 [1, 0.51497, 0.013362],
13145 [1, 0.50878, 0.010828],
13146 [1, 0.50252, 0.0085264],
13147 [1, 0.49623, 0.0063082],
13148 [1, 0.48991, 0.0041556],
13149 [1, 0.48353, 0.0020694],
13150 [1, 0.47711, 4.915e-05],
13151 [1, 0.47065, 0],
13152 [1, 0.46413, 0],
13153 [1, 0.45754, 0],
13154 [1, 0.45092, 0],
13155 [1, 0.44423, 0],
13156 [1, 0.43748, 0],
13157 [1, 0.43065, 0],
13158 [1, 0.42375, 0],
13159 [1, 0.4168, 0],
13160 [1, 0.40976, 0],
13161 [1, 0.40263, 0],
13162 [1, 0.39544, 0],
13163 [1, 0.38813, 0],
13164 [1, 0.38075, 0],
13165 [1, 0.37324, 0],
13166 [1, 0.36564, 0],
13167 [1, 0.35792, 0],
13168 [1, 0.35006, 0],
13169 [1, 0.34208, 0],
13170 [1, 0.33395, 0],
13171 [1, 0.32564, 0],
13172 [1, 0.31719, 0],
13173 [1, 0.30856, 0],
13174 [1, 0.29971, 0],
13175 [1, 0.29063, 0],
13176 [1, 0.28132, 0],
13177 [1, 0.27173, 0],
13178 [1, 0.26187, 0],
13179 [1, 0.25167, 0],
13180 [1, 0.24106, 0],
13181 [1, 0.23001, 0],
13182 [1, 0.21851, 0],
13183 [1, 0.20642, 0],
13184 [1, 0.19361, 0],
13185 [1, 0.17996, 0],
13186 [1, 0.16528, 0],
13187 ]
13188 b_rainbow_bgyr_35_85_c73 = bokeh_palette('rainbow_bgyr_35_85_c73',rainbow_bgyr_35_85_c73)
13189 m_rainbow_bgyr_35_85_c73 = mpl_cm('rainbow_bgyr_35_85_c73',rainbow_bgyr_35_85_c73)
13190 m_rainbow_bgyr_35_85_c73_r = mpl_cm('rainbow_bgyr_35_85_c73_r',list(reversed(rainbow_bgyr_35_85_c73)))
13191 rainbow = b_rainbow_bgyr_35_85_c73
13192 m_rainbow = m_rainbow_bgyr_35_85_c73
13193 m_rainbow_r = m_rainbow_bgyr_35_85_c73_r
13194 palette['rainbow'] = b_rainbow_bgyr_35_85_c73
13195 cm['rainbow'] = m_rainbow_bgyr_35_85_c73
13196 cm['rainbow_r'] = m_rainbow_bgyr_35_85_c73_r
13197 register_cmap('cet_rainbow',m_rainbow_bgyr_35_85_c73)
13198 register_cmap('cet_rainbow_r',m_rainbow_bgyr_35_85_c73_r)
13199
13200
13201
13202
13203 rainbow_bgyrm_35_85_c69 = [\
13204 [0, 0.18656, 0.96265],
13205 [0, 0.20247, 0.94889],
13206 [0, 0.21731, 0.93516],
13207 [0, 0.23125, 0.92145],
13208 [0.011192, 0.24442, 0.90777],
13209 [0.03614, 0.257, 0.8941],
13210 [0.055678, 0.26904, 0.88045],
13211 [0.069388, 0.28056, 0.86682],
13212 [0.079257, 0.29172, 0.85322],
13213 [0.086705, 0.30246, 0.83965],
13214 [0.092118, 0.31289, 0.82609],
13215 [0.095864, 0.32302, 0.81256],
13216 [0.098322, 0.33286, 0.79906],
13217 [0.099569, 0.34241, 0.78559],
13218 [0.099878, 0.3517, 0.77216],
13219 [0.099398, 0.36075, 0.75877],
13220 [0.098334, 0.36957, 0.74542],
13221 [0.096762, 0.37814, 0.73214],
13222 [0.09515, 0.38647, 0.71891],
13223 [0.09345, 0.39458, 0.70576],
13224 [0.092187, 0.40244, 0.6927],
13225 [0.091506, 0.41008, 0.67971],
13226 [0.091673, 0.41747, 0.66683],
13227 [0.092844, 0.42463, 0.65405],
13228 [0.095394, 0.43156, 0.64138],
13229 [0.099143, 0.43827, 0.62883],
13230 [0.10417, 0.44476, 0.6164],
13231 [0.11037, 0.45105, 0.60407],
13232 [0.11743, 0.45714, 0.59186],
13233 [0.12529, 0.46306, 0.57975],
13234 [0.13367, 0.46884, 0.56772],
13235 [0.14235, 0.47446, 0.55578],
13236 [0.15115, 0.47996, 0.54393],
13237 [0.15993, 0.48534, 0.53213],
13238 [0.16859, 0.49067, 0.52036],
13239 [0.17696, 0.49589, 0.50865],
13240 [0.185, 0.50108, 0.49692],
13241 [0.1926, 0.50621, 0.48521],
13242 [0.19974, 0.51133, 0.47348],
13243 [0.20647, 0.51642, 0.46174],
13244 [0.21263, 0.5215, 0.44995],
13245 [0.21832, 0.52659, 0.43811],
13246 [0.2235, 0.53167, 0.42619],
13247 [0.2282, 0.53676, 0.41421],
13248 [0.23239, 0.54184, 0.40212],
13249 [0.23614, 0.54695, 0.38996],
13250 [0.23944, 0.55206, 0.37769],
13251 [0.24232, 0.55719, 0.3653],
13252 [0.24481, 0.56231, 0.3528],
13253 [0.24695, 0.56744, 0.34016],
13254 [0.24876, 0.57258, 0.32738],
13255 [0.25023, 0.5777, 0.31447],
13256 [0.25154, 0.58283, 0.30143],
13257 [0.25262, 0.58794, 0.28828],
13258 [0.25361, 0.59304, 0.27502],
13259 [0.25458, 0.5981, 0.26166],
13260 [0.2556, 0.60312, 0.24825],
13261 [0.25681, 0.6081, 0.2348],
13262 [0.2583, 0.61301, 0.22134],
13263 [0.26022, 0.61785, 0.20794],
13264 [0.26266, 0.6226, 0.19469],
13265 [0.26575, 0.62726, 0.18157],
13266 [0.26958, 0.63182, 0.16877],
13267 [0.27422, 0.63626, 0.15629],
13268 [0.27974, 0.64057, 0.1442],
13269 [0.28615, 0.64476, 0.13265],
13270 [0.29347, 0.64883, 0.12168],
13271 [0.30163, 0.65275, 0.11152],
13272 [0.31062, 0.65656, 0.10212],
13273 [0.3203, 0.66024, 0.093657],
13274 [0.33059, 0.6638, 0.086199],
13275 [0.34143, 0.66725, 0.079852],
13276 [0.35268, 0.67061, 0.074629],
13277 [0.36426, 0.67387, 0.07049],
13278 [0.37611, 0.67706, 0.067449],
13279 [0.3881, 0.68016, 0.065346],
13280 [0.40021, 0.68322, 0.064139],
13281 [0.41237, 0.68622, 0.063672],
13282 [0.42452, 0.68918, 0.063795],
13283 [0.43666, 0.6921, 0.064392],
13284 [0.44874, 0.69498, 0.065356],
13285 [0.46073, 0.69783, 0.066603],
13286 [0.47267, 0.70067, 0.068066],
13287 [0.4845, 0.70348, 0.06967],
13288 [0.49625, 0.70628, 0.071332],
13289 [0.50793, 0.70905, 0.07306],
13290 [0.5195, 0.71181, 0.074792],
13291 [0.53099, 0.71455, 0.076552],
13292 [0.5424, 0.71728, 0.078345],
13293 [0.55372, 0.72, 0.08017],
13294 [0.56497, 0.72269, 0.082034],
13295 [0.57617, 0.72539, 0.083799],
13296 [0.58729, 0.72805, 0.085523],
13297 [0.59835, 0.73071, 0.087403],
13298 [0.60937, 0.73336, 0.089162],
13299 [0.62033, 0.73599, 0.090964],
13300 [0.63124, 0.73861, 0.092702],
13301 [0.64211, 0.74121, 0.094561],
13302 [0.65293, 0.7438, 0.096272],
13303 [0.66373, 0.74637, 0.09813],
13304 [0.67447, 0.74893, 0.099882],
13305 [0.68519, 0.75149, 0.10167],
13306 [0.69588, 0.75402, 0.1035],
13307 [0.70654, 0.75653, 0.10524],
13308 [0.71717, 0.75904, 0.10708],
13309 [0.72776, 0.76153, 0.10884],
13310 [0.73834, 0.764, 0.11066],
13311 [0.7489, 0.76647, 0.11246],
13312 [0.75944, 0.76891, 0.1142],
13313 [0.76995, 0.77134, 0.11604],
13314 [0.78045, 0.77373, 0.11781],
13315 [0.79091, 0.7761, 0.11958],
13316 [0.80135, 0.77844, 0.12133],
13317 [0.81175, 0.78072, 0.1231],
13318 [0.8221, 0.78295, 0.12488],
13319 [0.83239, 0.78511, 0.12661],
13320 [0.84262, 0.78718, 0.12834],
13321 [0.85274, 0.78913, 0.13004],
13322 [0.86274, 0.79094, 0.13165],
13323 [0.87259, 0.79257, 0.13322],
13324 [0.88223, 0.79401, 0.13475],
13325 [0.89164, 0.79518, 0.13612],
13326 [0.90076, 0.79607, 0.1375],
13327 [0.90954, 0.79664, 0.13869],
13328 [0.91793, 0.79684, 0.13974],
13329 [0.92586, 0.79664, 0.14073],
13330 [0.93328, 0.79601, 0.14151],
13331 [0.94018, 0.79492, 0.14212],
13332 [0.94648, 0.79336, 0.14256],
13333 [0.95218, 0.79132, 0.14282],
13334 [0.95727, 0.78881, 0.14289],
13335 [0.96174, 0.78582, 0.1428],
13336 [0.9656, 0.7824, 0.14253],
13337 [0.96888, 0.77856, 0.1421],
13338 [0.97162, 0.77434, 0.14153],
13339 [0.97385, 0.76979, 0.14082],
13340 [0.97563, 0.76494, 0.13994],
13341 [0.977, 0.75981, 0.13902],
13342 [0.97803, 0.75448, 0.13804],
13343 [0.97875, 0.74895, 0.13692],
13344 [0.97924, 0.74329, 0.13575],
13345 [0.97951, 0.73749, 0.13461],
13346 [0.97962, 0.7316, 0.13337],
13347 [0.97959, 0.72564, 0.13212],
13348 [0.97946, 0.71962, 0.13087],
13349 [0.97924, 0.71355, 0.12958],
13350 [0.97896, 0.70744, 0.1283],
13351 [0.97862, 0.70131, 0.12698],
13352 [0.97824, 0.69516, 0.12574],
13353 [0.97784, 0.68899, 0.12442],
13354 [0.9774, 0.6828, 0.12313],
13355 [0.97693, 0.6766, 0.12186],
13356 [0.97644, 0.67039, 0.12061],
13357 [0.97594, 0.66416, 0.11937],
13358 [0.97542, 0.65793, 0.11815],
13359 [0.97489, 0.65168, 0.11688],
13360 [0.97433, 0.64541, 0.11567],
13361 [0.97376, 0.63914, 0.1144],
13362 [0.97318, 0.63285, 0.11325],
13363 [0.97257, 0.62654, 0.11203],
13364 [0.97195, 0.62023, 0.11083],
13365 [0.97131, 0.61388, 0.10966],
13366 [0.97065, 0.60754, 0.10841],
13367 [0.96997, 0.60116, 0.10728],
13368 [0.96928, 0.59477, 0.10613],
13369 [0.96858, 0.58836, 0.1049],
13370 [0.96785, 0.58193, 0.10381],
13371 [0.96711, 0.57549, 0.10266],
13372 [0.96635, 0.56901, 0.10152],
13373 [0.96557, 0.56253, 0.1004],
13374 [0.96478, 0.55599, 0.099296],
13375 [0.96398, 0.54946, 0.098231],
13376 [0.96315, 0.5429, 0.097093],
13377 [0.96231, 0.5363, 0.096016],
13378 [0.96146, 0.52968, 0.095014],
13379 [0.96059, 0.52303, 0.093919],
13380 [0.9597, 0.51634, 0.092832],
13381 [0.95879, 0.50964, 0.091874],
13382 [0.95787, 0.50288, 0.090828],
13383 [0.95693, 0.4961, 0.089807],
13384 [0.95599, 0.48929, 0.088805],
13385 [0.95502, 0.48244, 0.08783],
13386 [0.95403, 0.47555, 0.086854],
13387 [0.95304, 0.4686, 0.085824],
13388 [0.95202, 0.46162, 0.084968],
13389 [0.95101, 0.4546, 0.084163],
13390 [0.94997, 0.44753, 0.083344],
13391 [0.94894, 0.44044, 0.082697],
13392 [0.94791, 0.43332, 0.082226],
13393 [0.94688, 0.42618, 0.081913],
13394 [0.94587, 0.41904, 0.081847],
13395 [0.94489, 0.41191, 0.082109],
13396 [0.94394, 0.40481, 0.082728],
13397 [0.94305, 0.39778, 0.083928],
13398 [0.94223, 0.39086, 0.085608],
13399 [0.94149, 0.38408, 0.08812],
13400 [0.94088, 0.3775, 0.091363],
13401 [0.94041, 0.37118, 0.095416],
13402 [0.9401, 0.36521, 0.10035],
13403 [0.93998, 0.35964, 0.1063],
13404 [0.94007, 0.35454, 0.11316],
13405 [0.9404, 0.34999, 0.12089],
13406 [0.94096, 0.34604, 0.12965],
13407 [0.94179, 0.3428, 0.13922],
13408 [0.94288, 0.34026, 0.14972],
13409 [0.94422, 0.33847, 0.16095],
13410 [0.94582, 0.33747, 0.17292],
13411 [0.94764, 0.33723, 0.18561],
13412 [0.94967, 0.33772, 0.19885],
13413 [0.95189, 0.33894, 0.21269],
13414 [0.95427, 0.34081, 0.22702],
13415 [0.95677, 0.34328, 0.24176],
13416 [0.95937, 0.34627, 0.25686],
13417 [0.96202, 0.34974, 0.27224],
13418 [0.96472, 0.35359, 0.2879],
13419 [0.96743, 0.35778, 0.30376],
13420 [0.97012, 0.36222, 0.31979],
13421 [0.97279, 0.36688, 0.33592],
13422 [0.97541, 0.3717, 0.35214],
13423 [0.97796, 0.37668, 0.36845],
13424 [0.98045, 0.38173, 0.3848],
13425 [0.98286, 0.38685, 0.40121],
13426 [0.98518, 0.39205, 0.41764],
13427 [0.9874, 0.39727, 0.43409],
13428 [0.98953, 0.40253, 0.45059],
13429 [0.99155, 0.40782, 0.46711],
13430 [0.99348, 0.41314, 0.48364],
13431 [0.99528, 0.41844, 0.5002],
13432 [0.99698, 0.42377, 0.51679],
13433 [0.99858, 0.42911, 0.5334],
13434 [1, 0.43445, 0.55005],
13435 [1, 0.43981, 0.56674],
13436 [1, 0.44517, 0.58345],
13437 [1, 0.45054, 0.60021],
13438 [1, 0.45593, 0.61701],
13439 [1, 0.46132, 0.63385],
13440 [1, 0.46673, 0.65073],
13441 [1, 0.47215, 0.66766],
13442 [1, 0.47757, 0.68462],
13443 [1, 0.48301, 0.70164],
13444 [1, 0.48847, 0.71871],
13445 [1, 0.49393, 0.73582],
13446 [1, 0.49939, 0.75297],
13447 [1, 0.50489, 0.77018],
13448 [1, 0.51038, 0.78744],
13449 [1, 0.51588, 0.80475],
13450 [1, 0.52141, 0.8221],
13451 [1, 0.52695, 0.8395],
13452 [1, 0.53249, 0.85695],
13453 [1, 0.53805, 0.87445],
13454 [1, 0.54361, 0.892],
13455 [1, 0.5492, 0.9096],
13456 [0.99848, 0.55478, 0.92724],
13457 [0.9966, 0.56039, 0.94494],
13458 [0.99453, 0.566, 0.96269],
13459 [0.99228, 0.57163, 0.98048],
13460 ]
13461 b_rainbow_bgyrm_35_85_c69 = bokeh_palette('rainbow_bgyrm_35_85_c69',rainbow_bgyrm_35_85_c69)
13462 m_rainbow_bgyrm_35_85_c69 = mpl_cm('rainbow_bgyrm_35_85_c69',rainbow_bgyrm_35_85_c69)
13463 m_rainbow_bgyrm_35_85_c69_r = mpl_cm('rainbow_bgyrm_35_85_c69_r',list(reversed(rainbow_bgyrm_35_85_c69)))
13464
13465
13466
13467
13468 rainbow_bgyrm_35_85_c71 = [\
13469 [0, 0.20755, 0.97632],
13470 [0, 0.22113, 0.96201],
13471 [0, 0.23397, 0.94773],
13472 [0, 0.24623, 0.93346],
13473 [0, 0.25798, 0.91922],
13474 [0, 0.26932, 0.905],
13475 [0, 0.28022, 0.89081],
13476 [0, 0.29079, 0.87663],
13477 [0, 0.30104, 0.8625],
13478 [0, 0.31103, 0.84838],
13479 [0, 0.32074, 0.83429],
13480 [0, 0.3302, 0.82023],
13481 [0, 0.33945, 0.80621],
13482 [0, 0.34846, 0.79222],
13483 [0, 0.35727, 0.77828],
13484 [0, 0.36586, 0.76439],
13485 [0, 0.37426, 0.75056],
13486 [0, 0.38245, 0.7368],
13487 [0, 0.39044, 0.72311],
13488 [0, 0.39823, 0.70952],
13489 [0, 0.4058, 0.69603],
13490 [0, 0.41317, 0.68264],
13491 [0.0064797, 0.42031, 0.66938],
13492 [0.016533, 0.42727, 0.65626],
13493 [0.028131, 0.43398, 0.64326],
13494 [0.041954, 0.44052, 0.63041],
13495 [0.055821, 0.44686, 0.6177],
13496 [0.069351, 0.45301, 0.60514],
13497 [0.082392, 0.45898, 0.59273],
13498 [0.095132, 0.46479, 0.58043],
13499 [0.10747, 0.47045, 0.56826],
13500 [0.11942, 0.47598, 0.55619],
13501 [0.13095, 0.48139, 0.54423],
13502 [0.14195, 0.48671, 0.53234],
13503 [0.15241, 0.49195, 0.52051],
13504 [0.16235, 0.49712, 0.50873],
13505 [0.17166, 0.50225, 0.49697],
13506 [0.18039, 0.50733, 0.48522],
13507 [0.18854, 0.51239, 0.47347],
13508 [0.19606, 0.51744, 0.46171],
13509 [0.20297, 0.52246, 0.4499],
13510 [0.20931, 0.5275, 0.43806],
13511 [0.21508, 0.53254, 0.42613],
13512 [0.22033, 0.53758, 0.41415],
13513 [0.225, 0.54263, 0.40206],
13514 [0.22922, 0.54768, 0.38989],
13515 [0.23295, 0.55275, 0.37763],
13516 [0.23626, 0.55783, 0.36524],
13517 [0.23913, 0.56292, 0.35274],
13518 [0.24164, 0.56801, 0.3401],
13519 [0.24376, 0.57311, 0.32732],
13520 [0.24561, 0.57819, 0.31441],
13521 [0.24723, 0.58328, 0.30137],
13522 [0.24866, 0.58836, 0.28822],
13523 [0.24993, 0.59342, 0.27496],
13524 [0.25123, 0.59845, 0.2616],
13525 [0.25256, 0.60344, 0.2482],
13526 [0.25407, 0.60839, 0.23474],
13527 [0.25584, 0.61326, 0.22129],
13528 [0.25802, 0.61807, 0.2079],
13529 [0.26074, 0.6228, 0.19465],
13530 [0.26408, 0.62744, 0.18153],
13531 [0.26813, 0.63197, 0.16873],
13532 [0.273, 0.63639, 0.15625],
13533 [0.27873, 0.64068, 0.14417],
13534 [0.28531, 0.64485, 0.13262],
13535 [0.29279, 0.6489, 0.12165],
13536 [0.30109, 0.65281, 0.1115],
13537 [0.31019, 0.65661, 0.10209],
13538 [0.31996, 0.66028, 0.093634],
13539 [0.33034, 0.66383, 0.08618],
13540 [0.34123, 0.66728, 0.079836],
13541 [0.35254, 0.67063, 0.074617],
13542 [0.36416, 0.67388, 0.07048],
13543 [0.37603, 0.67707, 0.067441],
13544 [0.38805, 0.68017, 0.065341],
13545 [0.40017, 0.68323, 0.064135],
13546 [0.41235, 0.68622, 0.063669],
13547 [0.42451, 0.68918, 0.063793],
13548 [0.43665, 0.6921, 0.064391],
13549 [0.44873, 0.69498, 0.065355],
13550 [0.46073, 0.69783, 0.066603],
13551 [0.47266, 0.70067, 0.068066],
13552 [0.4845, 0.70348, 0.06967],
13553 [0.49625, 0.70628, 0.071332],
13554 [0.50793, 0.70905, 0.07306],
13555 [0.5195, 0.71181, 0.074792],
13556 [0.53099, 0.71455, 0.076552],
13557 [0.5424, 0.71728, 0.078345],
13558 [0.55372, 0.72, 0.08017],
13559 [0.56497, 0.72269, 0.082034],
13560 [0.57617, 0.72539, 0.083799],
13561 [0.58729, 0.72805, 0.085523],
13562 [0.59835, 0.73071, 0.087403],
13563 [0.60937, 0.73336, 0.089162],
13564 [0.62033, 0.73599, 0.090964],
13565 [0.63124, 0.73861, 0.092702],
13566 [0.64211, 0.74121, 0.094561],
13567 [0.65293, 0.7438, 0.096272],
13568 [0.66373, 0.74637, 0.09813],
13569 [0.67447, 0.74893, 0.099882],
13570 [0.68519, 0.75149, 0.10167],
13571 [0.69588, 0.75402, 0.1035],
13572 [0.70654, 0.75653, 0.10524],
13573 [0.71717, 0.75904, 0.10708],
13574 [0.72776, 0.76153, 0.10884],
13575 [0.73834, 0.764, 0.11066],
13576 [0.7489, 0.76647, 0.11246],
13577 [0.75944, 0.76891, 0.1142],
13578 [0.76996, 0.77134, 0.11604],
13579 [0.78045, 0.77373, 0.1178],
13580 [0.79092, 0.7761, 0.11957],
13581 [0.80136, 0.77843, 0.12132],
13582 [0.81178, 0.78071, 0.12308],
13583 [0.82215, 0.78294, 0.12485],
13584 [0.83247, 0.78509, 0.12657],
13585 [0.84272, 0.78715, 0.12828],
13586 [0.85289, 0.78908, 0.12995],
13587 [0.86295, 0.79087, 0.13152],
13588 [0.87287, 0.79248, 0.13305],
13589 [0.88262, 0.79388, 0.13451],
13590 [0.89216, 0.79501, 0.13581],
13591 [0.90143, 0.79585, 0.13707],
13592 [0.9104, 0.79634, 0.13819],
13593 [0.919, 0.79646, 0.1391],
13594 [0.9272, 0.79616, 0.13987],
13595 [0.93494, 0.79542, 0.1405],
13596 [0.94218, 0.7942, 0.14092],
13597 [0.94889, 0.79248, 0.14112],
13598 [0.95503, 0.79026, 0.14111],
13599 [0.9606, 0.78755, 0.14089],
13600 [0.96559, 0.78436, 0.14045],
13601 [0.97002, 0.7807, 0.1398],
13602 [0.9739, 0.77661, 0.13901],
13603 [0.97726, 0.77212, 0.13808],
13604 [0.98015, 0.76727, 0.13693],
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13606 [0.98467, 0.75668, 0.13433],
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13624 [0.99529, 0.64132, 0.1035],
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13626 [0.9955, 0.62783, 0.10005],
13627 [0.99557, 0.62104, 0.098389],
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13673 [0.98768, 0.28545, 0.1319],
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13675 [0.99026, 0.28237, 0.15632],
13676 [0.9918, 0.28237, 0.16948],
13677 [0.9935, 0.28336, 0.18318],
13678 [0.99531, 0.28528, 0.19743],
13679 [0.99722, 0.2881, 0.21214],
13680 [0.99921, 0.29171, 0.22722],
13681 [1, 0.29596, 0.24264],
13682 [1, 0.3008, 0.25836],
13683 [1, 0.30615, 0.27432],
13684 [1, 0.31182, 0.29047],
13685 [1, 0.31783, 0.30679],
13686 [1, 0.32406, 0.32321],
13687 [1, 0.33045, 0.33974],
13688 [1, 0.33697, 0.35632],
13689 [1, 0.34355, 0.37295],
13690 [1, 0.3502, 0.38964],
13691 [1, 0.35686, 0.40637],
13692 [1, 0.36352, 0.42312],
13693 [1, 0.37019, 0.43991],
13694 [1, 0.37687, 0.45672],
13695 [1, 0.38352, 0.47355],
13696 [1, 0.39014, 0.49042],
13697 [1, 0.39675, 0.50731],
13698 [1, 0.40335, 0.52423],
13699 [1, 0.40993, 0.54118],
13700 [1, 0.41648, 0.55818],
13701 [1, 0.42301, 0.57522],
13702 [1, 0.42955, 0.5923],
13703 [1, 0.43607, 0.60942],
13704 [1, 0.44258, 0.62659],
13705 [1, 0.44907, 0.6438],
13706 [1, 0.45556, 0.66106],
13707 [1, 0.46203, 0.67837],
13708 [1, 0.4685, 0.69574],
13709 [1, 0.47498, 0.71314],
13710 [1, 0.48143, 0.7306],
13711 [1, 0.48789, 0.74812],
13712 [1, 0.49434, 0.76568],
13713 [1, 0.50078, 0.78329],
13714 [1, 0.50723, 0.80096],
13715 [1, 0.51367, 0.81867],
13716 [1, 0.5201, 0.83645],
13717 [1, 0.52655, 0.85427],
13718 [1, 0.53299, 0.87215],
13719 [1, 0.53942, 0.89007],
13720 [1, 0.54587, 0.90805],
13721 [1, 0.55231, 0.92608],
13722 [0.99945, 0.55874, 0.94416],
13723 [0.99597, 0.56518, 0.96229],
13724 [0.99228, 0.57163, 0.98048],
13725 ]
13726 b_rainbow_bgyrm_35_85_c71 = bokeh_palette('rainbow_bgyrm_35_85_c71',rainbow_bgyrm_35_85_c71)
13727 m_rainbow_bgyrm_35_85_c71 = mpl_cm('rainbow_bgyrm_35_85_c71',rainbow_bgyrm_35_85_c71)
13728 m_rainbow_bgyrm_35_85_c71_r = mpl_cm('rainbow_bgyrm_35_85_c71_r',list(reversed(rainbow_bgyrm_35_85_c71)))
13729
13730
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conda.recipe/build.sh less more
0 #!/bin/bash
1
2 set -e
3 set -x
4
5 BLD_DIR=`pwd`
6
7 SRC_DIR=$RECIPE_DIR/..
8 pushd $SRC_DIR
9
10 $PYTHON setup.py --quiet install --single-version-externally-managed --record=record.txt
11 cp -r $SRC_DIR/examples $PREFIX/share/datashader-examples
12
13 popd
14
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conda.recipe/meta.yaml less more
0 package:
1 name: datashader
2 version: 0.4.0
3
4 requirements:
5 build:
6 - python
7 - setuptools
8
9 run:
10 - python
11 - dask >=0.7.6
12 - datashape >=0.5.1
13 - numba >=0.24.0
14 - odo >=0.4.1
15 - numpy >=1.7
16 - pandas >=0.15.0
17 - pillow >=3.1.1
18 - xarray >=0.7.0
19 - toolz >=0.7.4
20
21 test:
22 requires:
23 - pytest >=2.8.5
24 imports:
25 - datashader
26
27 about:
28 home: https://github.com/bokeh/datashader
29 license: New BSD
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conda.recipe/readme.md less more
0 ## Release Procedure
1
2 - Ensure all tests pass.
3
4 - Update version number in `conda.recipe/meta.yaml`, `datashader/__init__.py`,
5 and `setup.py`. Commit.
6
7 - Tag commit and push to github
8
9 ```bash
10 git tag -a x.x.x -m 'Version x.x.x'
11 git push upstream master --tags
12 ```
13
14 - Build conda packages
15
16 The exact procedure is platform/setup specific, so I'll define a few variables
17 here, to fill in with your specifics:
18
19 ```bash
20 # Location of your conda install. For me it's `~/anaconda/`
21 CONDA_DIR=~/anaconda/
22
23 # Platform code. For me it's `osx-64`
24 PLATFORM=osx-64
25
26 # Version number of datashader being released (e.g. 0.2.0)
27 VERSION=0.2.0
28 ```
29
30 This assumes `conda`, `conda-build`, and `anaconda-client` are installed (if
31 not, install `conda`, then use `conda` to install the others). From inside the
32 toplevel directory:
33
34 ```bash
35 conda build conda.recipe/ --python 2.7 --python 3.4 --python 3.5
36 ```
37
38 Next, `cd` into the folder where the builds end up.
39
40 ```bash
41 cd $CONDA_DIR/conda-bld/$PLATFORM
42 ```
43
44 Use `conda convert` to convert over the missing platforms (skipping the one for
45 the platform you're currently on):
46
47 ```bash
48 conda convert --platform osx-64 datashader-$VERSION*.tar.bz2 -o ../
49 conda convert --platform linux-64 datashader-$VERSION*.tar.bz2 -o ../
50 conda convert --platform win-64 datashader-$VERSION*.tar.bz2 -o ../
51 ```
52
53 Use `anaconda upload` to upload the build to the `bokeh` channel. This requires
54 you to be setup on `anaconda.org`, and have the proper credentials to push to
55 the bokeh channel.
56
57 ```bash
58 anaconda login
59 anaconda upload $CONDA_DIR/conda-bld/*/datashader-$VERSION*.tar.bz2 -u bokeh
60 ```
61
62 - Write the release notes:
63
64 1. Run `git log` to get a listing of all the changes
65 2. Remove any covered in the previous release
66 3. Summarize the rest to focus on user-visible changes and major new features
67 4. Paste the notes into github, under *n* `releases`, then `Tags`, then `Edit release notes`.
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conda.recipe/run_test.py less more
0 import datashader; datashader.test()
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doc/index.html less more
0 <!DOCTYPE html>
1 <html>
2 <head><meta charset="utf-8" />
3 <title>index</title>
4
5 <script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
6 <script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>
7
8 <style type="text/css">
9 /*!
10 *
11 * Twitter Bootstrap
12 *
13 */
14 /*!
15 * Bootstrap v3.3.6 (http://getbootstrap.com)
16 * Copyright 2011-2015 Twitter, Inc.
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18 */
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155 line-height: normal;
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159 box-sizing: border-box;
160 padding: 0;
161 }
162 input[type="number"]::-webkit-inner-spin-button,
163 input[type="number"]::-webkit-outer-spin-button {
164 height: auto;
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166 input[type="search"] {
167 -webkit-appearance: textfield;
168 box-sizing: content-box;
169 }
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171 input[type="search"]::-webkit-search-decoration {
172 -webkit-appearance: none;
173 }
174 fieldset {
175 border: 1px solid #c0c0c0;
176 margin: 0 2px;
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187 font-weight: bold;
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198 @media print {
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200 *:before,
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202 background: transparent !important;
203 color: #000 !important;
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206 }
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209 text-decoration: underline;
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212 content: " (" attr(href) ")";
213 }
214 abbr[title]:after {
215 content: " (" attr(title) ")";
216 }
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218 a[href^="javascript:"]:after {
219 content: "";
220 }
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223 border: 1px solid #999;
224 page-break-inside: avoid;
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231 page-break-inside: avoid;
232 }
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234 max-width: 100% !important;
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239 orphans: 3;
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437 }
438 .glyphicon-camera:before {
439 content: "\e046";
440 }
441 .glyphicon-font:before {
442 content: "\e047";
443 }
444 .glyphicon-bold:before {
445 content: "\e048";
446 }
447 .glyphicon-italic:before {
448 content: "\e049";
449 }
450 .glyphicon-text-height:before {
451 content: "\e050";
452 }
453 .glyphicon-text-width:before {
454 content: "\e051";
455 }
456 .glyphicon-align-left:before {
457 content: "\e052";
458 }
459 .glyphicon-align-center:before {
460 content: "\e053";
461 }
462 .glyphicon-align-right:before {
463 content: "\e054";
464 }
465 .glyphicon-align-justify:before {
466 content: "\e055";
467 }
468 .glyphicon-list:before {
469 content: "\e056";
470 }
471 .glyphicon-indent-left:before {
472 content: "\e057";
473 }
474 .glyphicon-indent-right:before {
475 content: "\e058";
476 }
477 .glyphicon-facetime-video:before {
478 content: "\e059";
479 }
480 .glyphicon-picture:before {
481 content: "\e060";
482 }
483 .glyphicon-map-marker:before {
484 content: "\e062";
485 }
486 .glyphicon-adjust:before {
487 content: "\e063";
488 }
489 .glyphicon-tint:before {
490 content: "\e064";
491 }
492 .glyphicon-edit:before {
493 content: "\e065";
494 }
495 .glyphicon-share:before {
496 content: "\e066";
497 }
498 .glyphicon-check:before {
499 content: "\e067";
500 }
501 .glyphicon-move:before {
502 content: "\e068";
503 }
504 .glyphicon-step-backward:before {
505 content: "\e069";
506 }
507 .glyphicon-fast-backward:before {
508 content: "\e070";
509 }
510 .glyphicon-backward:before {
511 content: "\e071";
512 }
513 .glyphicon-play:before {
514 content: "\e072";
515 }
516 .glyphicon-pause:before {
517 content: "\e073";
518 }
519 .glyphicon-stop:before {
520 content: "\e074";
521 }
522 .glyphicon-forward:before {
523 content: "\e075";
524 }
525 .glyphicon-fast-forward:before {
526 content: "\e076";
527 }
528 .glyphicon-step-forward:before {
529 content: "\e077";
530 }
531 .glyphicon-eject:before {
532 content: "\e078";
533 }
534 .glyphicon-chevron-left:before {
535 content: "\e079";
536 }
537 .glyphicon-chevron-right:before {
538 content: "\e080";
539 }
540 .glyphicon-plus-sign:before {
541 content: "\e081";
542 }
543 .glyphicon-minus-sign:before {
544 content: "\e082";
545 }
546 .glyphicon-remove-sign:before {
547 content: "\e083";
548 }
549 .glyphicon-ok-sign:before {
550 content: "\e084";
551 }
552 .glyphicon-question-sign:before {
553 content: "\e085";
554 }
555 .glyphicon-info-sign:before {
556 content: "\e086";
557 }
558 .glyphicon-screenshot:before {
559 content: "\e087";
560 }
561 .glyphicon-remove-circle:before {
562 content: "\e088";
563 }
564 .glyphicon-ok-circle:before {
565 content: "\e089";
566 }
567 .glyphicon-ban-circle:before {
568 content: "\e090";
569 }
570 .glyphicon-arrow-left:before {
571 content: "\e091";
572 }
573 .glyphicon-arrow-right:before {
574 content: "\e092";
575 }
576 .glyphicon-arrow-up:before {
577 content: "\e093";
578 }
579 .glyphicon-arrow-down:before {
580 content: "\e094";
581 }
582 .glyphicon-share-alt:before {
583 content: "\e095";
584 }
585 .glyphicon-resize-full:before {
586 content: "\e096";
587 }
588 .glyphicon-resize-small:before {
589 content: "\e097";
590 }
591 .glyphicon-exclamation-sign:before {
592 content: "\e101";
593 }
594 .glyphicon-gift:before {
595 content: "\e102";
596 }
597 .glyphicon-leaf:before {
598 content: "\e103";
599 }
600 .glyphicon-fire:before {
601 content: "\e104";
602 }
603 .glyphicon-eye-open:before {
604 content: "\e105";
605 }
606 .glyphicon-eye-close:before {
607 content: "\e106";
608 }
609 .glyphicon-warning-sign:before {
610 content: "\e107";
611 }
612 .glyphicon-plane:before {
613 content: "\e108";
614 }
615 .glyphicon-calendar:before {
616 content: "\e109";
617 }
618 .glyphicon-random:before {
619 content: "\e110";
620 }
621 .glyphicon-comment:before {
622 content: "\e111";
623 }
624 .glyphicon-magnet:before {
625 content: "\e112";
626 }
627 .glyphicon-chevron-up:before {
628 content: "\e113";
629 }
630 .glyphicon-chevron-down:before {
631 content: "\e114";
632 }
633 .glyphicon-retweet:before {
634 content: "\e115";
635 }
636 .glyphicon-shopping-cart:before {
637 content: "\e116";
638 }
639 .glyphicon-folder-close:before {
640 content: "\e117";
641 }
642 .glyphicon-folder-open:before {
643 content: "\e118";
644 }
645 .glyphicon-resize-vertical:before {
646 content: "\e119";
647 }
648 .glyphicon-resize-horizontal:before {
649 content: "\e120";
650 }
651 .glyphicon-hdd:before {
652 content: "\e121";
653 }
654 .glyphicon-bullhorn:before {
655 content: "\e122";
656 }
657 .glyphicon-bell:before {
658 content: "\e123";
659 }
660 .glyphicon-certificate:before {
661 content: "\e124";
662 }
663 .glyphicon-thumbs-up:before {
664 content: "\e125";
665 }
666 .glyphicon-thumbs-down:before {
667 content: "\e126";
668 }
669 .glyphicon-hand-right:before {
670 content: "\e127";
671 }
672 .glyphicon-hand-left:before {
673 content: "\e128";
674 }
675 .glyphicon-hand-up:before {
676 content: "\e129";
677 }
678 .glyphicon-hand-down:before {
679 content: "\e130";
680 }
681 .glyphicon-circle-arrow-right:before {
682 content: "\e131";
683 }
684 .glyphicon-circle-arrow-left:before {
685 content: "\e132";
686 }
687 .glyphicon-circle-arrow-up:before {
688 content: "\e133";
689 }
690 .glyphicon-circle-arrow-down:before {
691 content: "\e134";
692 }
693 .glyphicon-globe:before {
694 content: "\e135";
695 }
696 .glyphicon-wrench:before {
697 content: "\e136";
698 }
699 .glyphicon-tasks:before {
700 content: "\e137";
701 }
702 .glyphicon-filter:before {
703 content: "\e138";
704 }
705 .glyphicon-briefcase:before {
706 content: "\e139";
707 }
708 .glyphicon-fullscreen:before {
709 content: "\e140";
710 }
711 .glyphicon-dashboard:before {
712 content: "\e141";
713 }
714 .glyphicon-paperclip:before {
715 content: "\e142";
716 }
717 .glyphicon-heart-empty:before {
718 content: "\e143";
719 }
720 .glyphicon-link:before {
721 content: "\e144";
722 }
723 .glyphicon-phone:before {
724 content: "\e145";
725 }
726 .glyphicon-pushpin:before {
727 content: "\e146";
728 }
729 .glyphicon-usd:before {
730 content: "\e148";
731 }
732 .glyphicon-gbp:before {
733 content: "\e149";
734 }
735 .glyphicon-sort:before {
736 content: "\e150";
737 }
738 .glyphicon-sort-by-alphabet:before {
739 content: "\e151";
740 }
741 .glyphicon-sort-by-alphabet-alt:before {
742 content: "\e152";
743 }
744 .glyphicon-sort-by-order:before {
745 content: "\e153";
746 }
747 .glyphicon-sort-by-order-alt:before {
748 content: "\e154";
749 }
750 .glyphicon-sort-by-attributes:before {
751 content: "\e155";
752 }
753 .glyphicon-sort-by-attributes-alt:before {
754 content: "\e156";
755 }
756 .glyphicon-unchecked:before {
757 content: "\e157";
758 }
759 .glyphicon-expand:before {
760 content: "\e158";
761 }
762 .glyphicon-collapse-down:before {
763 content: "\e159";
764 }
765 .glyphicon-collapse-up:before {
766 content: "\e160";
767 }
768 .glyphicon-log-in:before {
769 content: "\e161";
770 }
771 .glyphicon-flash:before {
772 content: "\e162";
773 }
774 .glyphicon-log-out:before {
775 content: "\e163";
776 }
777 .glyphicon-new-window:before {
778 content: "\e164";
779 }
780 .glyphicon-record:before {
781 content: "\e165";
782 }
783 .glyphicon-save:before {
784 content: "\e166";
785 }
786 .glyphicon-open:before {
787 content: "\e167";
788 }
789 .glyphicon-saved:before {
790 content: "\e168";
791 }
792 .glyphicon-import:before {
793 content: "\e169";
794 }
795 .glyphicon-export:before {
796 content: "\e170";
797 }
798 .glyphicon-send:before {
799 content: "\e171";
800 }
801 .glyphicon-floppy-disk:before {
802 content: "\e172";
803 }
804 .glyphicon-floppy-saved:before {
805 content: "\e173";
806 }
807 .glyphicon-floppy-remove:before {
808 content: "\e174";
809 }
810 .glyphicon-floppy-save:before {
811 content: "\e175";
812 }
813 .glyphicon-floppy-open:before {
814 content: "\e176";
815 }
816 .glyphicon-credit-card:before {
817 content: "\e177";
818 }
819 .glyphicon-transfer:before {
820 content: "\e178";
821 }
822 .glyphicon-cutlery:before {
823 content: "\e179";
824 }
825 .glyphicon-header:before {
826 content: "\e180";
827 }
828 .glyphicon-compressed:before {
829 content: "\e181";
830 }
831 .glyphicon-earphone:before {
832 content: "\e182";
833 }
834 .glyphicon-phone-alt:before {
835 content: "\e183";
836 }
837 .glyphicon-tower:before {
838 content: "\e184";
839 }
840 .glyphicon-stats:before {
841 content: "\e185";
842 }
843 .glyphicon-sd-video:before {
844 content: "\e186";
845 }
846 .glyphicon-hd-video:before {
847 content: "\e187";
848 }
849 .glyphicon-subtitles:before {
850 content: "\e188";
851 }
852 .glyphicon-sound-stereo:before {
853 content: "\e189";
854 }
855 .glyphicon-sound-dolby:before {
856 content: "\e190";
857 }
858 .glyphicon-sound-5-1:before {
859 content: "\e191";
860 }
861 .glyphicon-sound-6-1:before {
862 content: "\e192";
863 }
864 .glyphicon-sound-7-1:before {
865 content: "\e193";
866 }
867 .glyphicon-copyright-mark:before {
868 content: "\e194";
869 }
870 .glyphicon-registration-mark:before {
871 content: "\e195";
872 }
873 .glyphicon-cloud-download:before {
874 content: "\e197";
875 }
876 .glyphicon-cloud-upload:before {
877 content: "\e198";
878 }
879 .glyphicon-tree-conifer:before {
880 content: "\e199";
881 }
882 .glyphicon-tree-deciduous:before {
883 content: "\e200";
884 }
885 .glyphicon-cd:before {
886 content: "\e201";
887 }
888 .glyphicon-save-file:before {
889 content: "\e202";
890 }
891 .glyphicon-open-file:before {
892 content: "\e203";
893 }
894 .glyphicon-level-up:before {
895 content: "\e204";
896 }
897 .glyphicon-copy:before {
898 content: "\e205";
899 }
900 .glyphicon-paste:before {
901 content: "\e206";
902 }
903 .glyphicon-alert:before {
904 content: "\e209";
905 }
906 .glyphicon-equalizer:before {
907 content: "\e210";
908 }
909 .glyphicon-king:before {
910 content: "\e211";
911 }
912 .glyphicon-queen:before {
913 content: "\e212";
914 }
915 .glyphicon-pawn:before {
916 content: "\e213";
917 }
918 .glyphicon-bishop:before {
919 content: "\e214";
920 }
921 .glyphicon-knight:before {
922 content: "\e215";
923 }
924 .glyphicon-baby-formula:before {
925 content: "\e216";
926 }
927 .glyphicon-tent:before {
928 content: "\26fa";
929 }
930 .glyphicon-blackboard:before {
931 content: "\e218";
932 }
933 .glyphicon-bed:before {
934 content: "\e219";
935 }
936 .glyphicon-apple:before {
937 content: "\f8ff";
938 }
939 .glyphicon-erase:before {
940 content: "\e221";
941 }
942 .glyphicon-hourglass:before {
943 content: "\231b";
944 }
945 .glyphicon-lamp:before {
946 content: "\e223";
947 }
948 .glyphicon-duplicate:before {
949 content: "\e224";
950 }
951 .glyphicon-piggy-bank:before {
952 content: "\e225";
953 }
954 .glyphicon-scissors:before {
955 content: "\e226";
956 }
957 .glyphicon-bitcoin:before {
958 content: "\e227";
959 }
960 .glyphicon-btc:before {
961 content: "\e227";
962 }
963 .glyphicon-xbt:before {
964 content: "\e227";
965 }
966 .glyphicon-yen:before {
967 content: "\00a5";
968 }
969 .glyphicon-jpy:before {
970 content: "\00a5";
971 }
972 .glyphicon-ruble:before {
973 content: "\20bd";
974 }
975 .glyphicon-rub:before {
976 content: "\20bd";
977 }
978 .glyphicon-scale:before {
979 content: "\e230";
980 }
981 .glyphicon-ice-lolly:before {
982 content: "\e231";
983 }
984 .glyphicon-ice-lolly-tasted:before {
985 content: "\e232";
986 }
987 .glyphicon-education:before {
988 content: "\e233";
989 }
990 .glyphicon-option-horizontal:before {
991 content: "\e234";
992 }
993 .glyphicon-option-vertical:before {
994 content: "\e235";
995 }
996 .glyphicon-menu-hamburger:before {
997 content: "\e236";
998 }
999 .glyphicon-modal-window:before {
1000 content: "\e237";
1001 }
1002 .glyphicon-oil:before {
1003 content: "\e238";
1004 }
1005 .glyphicon-grain:before {
1006 content: "\e239";
1007 }
1008 .glyphicon-sunglasses:before {
1009 content: "\e240";
1010 }
1011 .glyphicon-text-size:before {
1012 content: "\e241";
1013 }
1014 .glyphicon-text-color:before {
1015 content: "\e242";
1016 }
1017 .glyphicon-text-background:before {
1018 content: "\e243";
1019 }
1020 .glyphicon-object-align-top:before {
1021 content: "\e244";
1022 }
1023 .glyphicon-object-align-bottom:before {
1024 content: "\e245";
1025 }
1026 .glyphicon-object-align-horizontal:before {
1027 content: "\e246";
1028 }
1029 .glyphicon-object-align-left:before {
1030 content: "\e247";
1031 }
1032 .glyphicon-object-align-vertical:before {
1033 content: "\e248";
1034 }
1035 .glyphicon-object-align-right:before {
1036 content: "\e249";
1037 }
1038 .glyphicon-triangle-right:before {
1039 content: "\e250";
1040 }
1041 .glyphicon-triangle-left:before {
1042 content: "\e251";
1043 }
1044 .glyphicon-triangle-bottom:before {
1045 content: "\e252";
1046 }
1047 .glyphicon-triangle-top:before {
1048 content: "\e253";
1049 }
1050 .glyphicon-console:before {
1051 content: "\e254";
1052 }
1053 .glyphicon-superscript:before {
1054 content: "\e255";
1055 }
1056 .glyphicon-subscript:before {
1057 content: "\e256";
1058 }
1059 .glyphicon-menu-left:before {
1060 content: "\e257";
1061 }
1062 .glyphicon-menu-right:before {
1063 content: "\e258";
1064 }
1065 .glyphicon-menu-down:before {
1066 content: "\e259";
1067 }
1068 .glyphicon-menu-up:before {
1069 content: "\e260";
1070 }
1071 * {
1072 -webkit-box-sizing: border-box;
1073 -moz-box-sizing: border-box;
1074 box-sizing: border-box;
1075 }
1076 *:before,
1077 *:after {
1078 -webkit-box-sizing: border-box;
1079 -moz-box-sizing: border-box;
1080 box-sizing: border-box;
1081 }
1082 html {
1083 font-size: 10px;
1084 -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
1085 }
1086 body {
1087 font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
1088 font-size: 13px;
1089 line-height: 1.42857143;
1090 color: #000;
1091 background-color: #fff;
1092 }
1093 input,
1094 button,
1095 select,
1096 textarea {
1097 font-family: inherit;
1098 font-size: inherit;
1099 line-height: inherit;
1100 }
1101 a {
1102 color: #337ab7;
1103 text-decoration: none;
1104 }
1105 a:hover,
1106 a:focus {
1107 color: #23527c;
1108 text-decoration: underline;
1109 }
1110 a:focus {
1111 outline: thin dotted;
1112 outline: 5px auto -webkit-focus-ring-color;
1113 outline-offset: -2px;
1114 }
1115 figure {
1116 margin: 0;
1117 }
1118 img {
1119 vertical-align: middle;
1120 }
1121 .img-responsive,
1122 .thumbnail > img,
1123 .thumbnail a > img,
1124 .carousel-inner > .item > img,
1125 .carousel-inner > .item > a > img {
1126 display: block;
1127 max-width: 100%;
1128 height: auto;
1129 }
1130 .img-rounded {
1131 border-radius: 3px;
1132 }
1133 .img-thumbnail {
1134 padding: 4px;
1135 line-height: 1.42857143;
1136 background-color: #fff;
1137 border: 1px solid #ddd;
1138 border-radius: 2px;
1139 -webkit-transition: all 0.2s ease-in-out;
1140 -o-transition: all 0.2s ease-in-out;
1141 transition: all 0.2s ease-in-out;
1142 display: inline-block;
1143 max-width: 100%;
1144 height: auto;
1145 }
1146 .img-circle {
1147 border-radius: 50%;
1148 }
1149 hr {
1150 margin-top: 18px;
1151 margin-bottom: 18px;
1152 border: 0;
1153 border-top: 1px solid #eeeeee;
1154 }
1155 .sr-only {
1156 position: absolute;
1157 width: 1px;
1158 height: 1px;
1159 margin: -1px;
1160 padding: 0;
1161 overflow: hidden;
1162 clip: rect(0, 0, 0, 0);
1163 border: 0;
1164 }
1165 .sr-only-focusable:active,
1166 .sr-only-focusable:focus {
1167 position: static;
1168 width: auto;
1169 height: auto;
1170 margin: 0;
1171 overflow: visible;
1172 clip: auto;
1173 }
1174 [role="button"] {
1175 cursor: pointer;
1176 }
1177 h1,
1178 h2,
1179 h3,
1180 h4,
1181 h5,
1182 h6,
1183 .h1,
1184 .h2,
1185 .h3,
1186 .h4,
1187 .h5,
1188 .h6 {
1189 font-family: inherit;
1190 font-weight: 500;
1191 line-height: 1.1;
1192 color: inherit;
1193 }
1194 h1 small,
1195 h2 small,
1196 h3 small,
1197 h4 small,
1198 h5 small,
1199 h6 small,
1200 .h1 small,
1201 .h2 small,
1202 .h3 small,
1203 .h4 small,
1204 .h5 small,
1205 .h6 small,
1206 h1 .small,
1207 h2 .small,
1208 h3 .small,
1209 h4 .small,
1210 h5 .small,
1211 h6 .small,
1212 .h1 .small,
1213 .h2 .small,
1214 .h3 .small,
1215 .h4 .small,
1216 .h5 .small,
1217 .h6 .small {
1218 font-weight: normal;
1219 line-height: 1;
1220 color: #777777;
1221 }
1222 h1,
1223 .h1,
1224 h2,
1225 .h2,
1226 h3,
1227 .h3 {
1228 margin-top: 18px;
1229 margin-bottom: 9px;
1230 }
1231 h1 small,
1232 .h1 small,
1233 h2 small,
1234 .h2 small,
1235 h3 small,
1236 .h3 small,
1237 h1 .small,
1238 .h1 .small,
1239 h2 .small,
1240 .h2 .small,
1241 h3 .small,
1242 .h3 .small {
1243 font-size: 65%;
1244 }
1245 h4,
1246 .h4,
1247 h5,
1248 .h5,
1249 h6,
1250 .h6 {
1251 margin-top: 9px;
1252 margin-bottom: 9px;
1253 }
1254 h4 small,
1255 .h4 small,
1256 h5 small,
1257 .h5 small,
1258 h6 small,
1259 .h6 small,
1260 h4 .small,
1261 .h4 .small,
1262 h5 .small,
1263 .h5 .small,
1264 h6 .small,
1265 .h6 .small {
1266 font-size: 75%;
1267 }
1268 h1,
1269 .h1 {
1270 font-size: 33px;
1271 }
1272 h2,
1273 .h2 {
1274 font-size: 27px;
1275 }
1276 h3,
1277 .h3 {
1278 font-size: 23px;
1279 }
1280 h4,
1281 .h4 {
1282 font-size: 17px;
1283 }
1284 h5,
1285 .h5 {
1286 font-size: 13px;
1287 }
1288 h6,
1289 .h6 {
1290 font-size: 12px;
1291 }
1292 p {
1293 margin: 0 0 9px;
1294 }
1295 .lead {
1296 margin-bottom: 18px;
1297 font-size: 14px;
1298 font-weight: 300;
1299 line-height: 1.4;
1300 }
1301 @media (min-width: 768px) {
1302 .lead {
1303 font-size: 19.5px;
1304 }
1305 }
1306 small,
1307 .small {
1308 font-size: 92%;
1309 }
1310 mark,
1311 .mark {
1312 background-color: #fcf8e3;
1313 padding: .2em;
1314 }
1315 .text-left {
1316 text-align: left;
1317 }
1318 .text-right {
1319 text-align: right;
1320 }
1321 .text-center {
1322 text-align: center;
1323 }
1324 .text-justify {
1325 text-align: justify;
1326 }
1327 .text-nowrap {
1328 white-space: nowrap;
1329 }
1330 .text-lowercase {
1331 text-transform: lowercase;
1332 }
1333 .text-uppercase {
1334 text-transform: uppercase;
1335 }
1336 .text-capitalize {
1337 text-transform: capitalize;
1338 }
1339 .text-muted {
1340 color: #777777;
1341 }
1342 .text-primary {
1343 color: #337ab7;
1344 }
1345 a.text-primary:hover,
1346 a.text-primary:focus {
1347 color: #286090;
1348 }
1349 .text-success {
1350 color: #3c763d;
1351 }
1352 a.text-success:hover,
1353 a.text-success:focus {
1354 color: #2b542c;
1355 }
1356 .text-info {
1357 color: #31708f;
1358 }
1359 a.text-info:hover,
1360 a.text-info:focus {
1361 color: #245269;
1362 }
1363 .text-warning {
1364 color: #8a6d3b;
1365 }
1366 a.text-warning:hover,
1367 a.text-warning:focus {
1368 color: #66512c;
1369 }
1370 .text-danger {
1371 color: #a94442;
1372 }
1373 a.text-danger:hover,
1374 a.text-danger:focus {
1375 color: #843534;
1376 }
1377 .bg-primary {
1378 color: #fff;
1379 background-color: #337ab7;
1380 }
1381 a.bg-primary:hover,
1382 a.bg-primary:focus {
1383 background-color: #286090;
1384 }
1385 .bg-success {
1386 background-color: #dff0d8;
1387 }
1388 a.bg-success:hover,
1389 a.bg-success:focus {
1390 background-color: #c1e2b3;
1391 }
1392 .bg-info {
1393 background-color: #d9edf7;
1394 }
1395 a.bg-info:hover,
1396 a.bg-info:focus {
1397 background-color: #afd9ee;
1398 }
1399 .bg-warning {
1400 background-color: #fcf8e3;
1401 }
1402 a.bg-warning:hover,
1403 a.bg-warning:focus {
1404 background-color: #f7ecb5;
1405 }
1406 .bg-danger {
1407 background-color: #f2dede;
1408 }
1409 a.bg-danger:hover,
1410 a.bg-danger:focus {
1411 background-color: #e4b9b9;
1412 }
1413 .page-header {
1414 padding-bottom: 8px;
1415 margin: 36px 0 18px;
1416 border-bottom: 1px solid #eeeeee;
1417 }
1418 ul,
1419 ol {
1420 margin-top: 0;
1421 margin-bottom: 9px;
1422 }
1423 ul ul,
1424 ol ul,
1425 ul ol,
1426 ol ol {
1427 margin-bottom: 0;
1428 }
1429 .list-unstyled {
1430 padding-left: 0;
1431 list-style: none;
1432 }
1433 .list-inline {
1434 padding-left: 0;
1435 list-style: none;
1436 margin-left: -5px;
1437 }
1438 .list-inline > li {
1439 display: inline-block;
1440 padding-left: 5px;
1441 padding-right: 5px;
1442 }
1443 dl {
1444 margin-top: 0;
1445 margin-bottom: 18px;
1446 }
1447 dt,
1448 dd {
1449 line-height: 1.42857143;
1450 }
1451 dt {
1452 font-weight: bold;
1453 }
1454 dd {
1455 margin-left: 0;
1456 }
1457 @media (min-width: 541px) {
1458 .dl-horizontal dt {
1459 float: left;
1460 width: 160px;
1461 clear: left;
1462 text-align: right;
1463 overflow: hidden;
1464 text-overflow: ellipsis;
1465 white-space: nowrap;
1466 }
1467 .dl-horizontal dd {
1468 margin-left: 180px;
1469 }
1470 }
1471 abbr[title],
1472 abbr[data-original-title] {
1473 cursor: help;
1474 border-bottom: 1px dotted #777777;
1475 }
1476 .initialism {
1477 font-size: 90%;
1478 text-transform: uppercase;
1479 }
1480 blockquote {
1481 padding: 9px 18px;
1482 margin: 0 0 18px;
1483 font-size: inherit;
1484 border-left: 5px solid #eeeeee;
1485 }
1486 blockquote p:last-child,
1487 blockquote ul:last-child,
1488 blockquote ol:last-child {
1489 margin-bottom: 0;
1490 }
1491 blockquote footer,
1492 blockquote small,
1493 blockquote .small {
1494 display: block;
1495 font-size: 80%;
1496 line-height: 1.42857143;
1497 color: #777777;
1498 }
1499 blockquote footer:before,
1500 blockquote small:before,
1501 blockquote .small:before {
1502 content: '\2014 \00A0';
1503 }
1504 .blockquote-reverse,
1505 blockquote.pull-right {
1506 padding-right: 15px;
1507 padding-left: 0;
1508 border-right: 5px solid #eeeeee;
1509 border-left: 0;
1510 text-align: right;
1511 }
1512 .blockquote-reverse footer:before,
1513 blockquote.pull-right footer:before,
1514 .blockquote-reverse small:before,
1515 blockquote.pull-right small:before,
1516 .blockquote-reverse .small:before,
1517 blockquote.pull-right .small:before {
1518 content: '';
1519 }
1520 .blockquote-reverse footer:after,
1521 blockquote.pull-right footer:after,
1522 .blockquote-reverse small:after,
1523 blockquote.pull-right small:after,
1524 .blockquote-reverse .small:after,
1525 blockquote.pull-right .small:after {
1526 content: '\00A0 \2014';
1527 }
1528 address {
1529 margin-bottom: 18px;
1530 font-style: normal;
1531 line-height: 1.42857143;
1532 }
1533 code,
1534 kbd,
1535 pre,
1536 samp {
1537 font-family: monospace;
1538 }
1539 code {
1540 padding: 2px 4px;
1541 font-size: 90%;
1542 color: #c7254e;
1543 background-color: #f9f2f4;
1544 border-radius: 2px;
1545 }
1546 kbd {
1547 padding: 2px 4px;
1548 font-size: 90%;
1549 color: #888;
1550 background-color: transparent;
1551 border-radius: 1px;
1552 box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
1553 }
1554 kbd kbd {
1555 padding: 0;
1556 font-size: 100%;
1557 font-weight: bold;
1558 box-shadow: none;
1559 }
1560 pre {
1561 display: block;
1562 padding: 8.5px;
1563 margin: 0 0 9px;
1564 font-size: 12px;
1565 line-height: 1.42857143;
1566 word-break: break-all;
1567 word-wrap: break-word;
1568 color: #333333;
1569 background-color: #f5f5f5;
1570 border: 1px solid #ccc;
1571 border-radius: 2px;
1572 }
1573 pre code {
1574 padding: 0;
1575 font-size: inherit;
1576 color: inherit;
1577 white-space: pre-wrap;
1578 background-color: transparent;
1579 border-radius: 0;
1580 }
1581 .pre-scrollable {
1582 max-height: 340px;
1583 overflow-y: scroll;
1584 }
1585 .container {
1586 margin-right: auto;
1587 margin-left: auto;
1588 padding-left: 0px;
1589 padding-right: 0px;
1590 }
1591 @media (min-width: 768px) {
1592 .container {
1593 width: 768px;
1594 }
1595 }
1596 @media (min-width: 992px) {
1597 .container {
1598 width: 940px;
1599 }
1600 }
1601 @media (min-width: 1200px) {
1602 .container {
1603 width: 1140px;
1604 }
1605 }
1606 .container-fluid {
1607 margin-right: auto;
1608 margin-left: auto;
1609 padding-left: 0px;
1610 padding-right: 0px;
1611 }
1612 .row {
1613 margin-left: 0px;
1614 margin-right: 0px;
1615 }
1616 .col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
1617 position: relative;
1618 min-height: 1px;
1619 padding-left: 0px;
1620 padding-right: 0px;
1621 }
1622 .col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
1623 float: left;
1624 }
1625 .col-xs-12 {
1626 width: 100%;
1627 }
1628 .col-xs-11 {
1629 width: 91.66666667%;
1630 }
1631 .col-xs-10 {
1632 width: 83.33333333%;
1633 }
1634 .col-xs-9 {
1635 width: 75%;
1636 }
1637 .col-xs-8 {
1638 width: 66.66666667%;
1639 }
1640 .col-xs-7 {
1641 width: 58.33333333%;
1642 }
1643 .col-xs-6 {
1644 width: 50%;
1645 }
1646 .col-xs-5 {
1647 width: 41.66666667%;
1648 }
1649 .col-xs-4 {
1650 width: 33.33333333%;
1651 }
1652 .col-xs-3 {
1653 width: 25%;
1654 }
1655 .col-xs-2 {
1656 width: 16.66666667%;
1657 }
1658 .col-xs-1 {
1659 width: 8.33333333%;
1660 }
1661 .col-xs-pull-12 {
1662 right: 100%;
1663 }
1664 .col-xs-pull-11 {
1665 right: 91.66666667%;
1666 }
1667 .col-xs-pull-10 {
1668 right: 83.33333333%;
1669 }
1670 .col-xs-pull-9 {
1671 right: 75%;
1672 }
1673 .col-xs-pull-8 {
1674 right: 66.66666667%;
1675 }
1676 .col-xs-pull-7 {
1677 right: 58.33333333%;
1678 }
1679 .col-xs-pull-6 {
1680 right: 50%;
1681 }
1682 .col-xs-pull-5 {
1683 right: 41.66666667%;
1684 }
1685 .col-xs-pull-4 {
1686 right: 33.33333333%;
1687 }
1688 .col-xs-pull-3 {
1689 right: 25%;
1690 }
1691 .col-xs-pull-2 {
1692 right: 16.66666667%;
1693 }
1694 .col-xs-pull-1 {
1695 right: 8.33333333%;
1696 }
1697 .col-xs-pull-0 {
1698 right: auto;
1699 }
1700 .col-xs-push-12 {
1701 left: 100%;
1702 }
1703 .col-xs-push-11 {
1704 left: 91.66666667%;
1705 }
1706 .col-xs-push-10 {
1707 left: 83.33333333%;
1708 }
1709 .col-xs-push-9 {
1710 left: 75%;
1711 }
1712 .col-xs-push-8 {
1713 left: 66.66666667%;
1714 }
1715 .col-xs-push-7 {
1716 left: 58.33333333%;
1717 }
1718 .col-xs-push-6 {
1719 left: 50%;
1720 }
1721 .col-xs-push-5 {
1722 left: 41.66666667%;
1723 }
1724 .col-xs-push-4 {
1725 left: 33.33333333%;
1726 }
1727 .col-xs-push-3 {
1728 left: 25%;
1729 }
1730 .col-xs-push-2 {
1731 left: 16.66666667%;
1732 }
1733 .col-xs-push-1 {
1734 left: 8.33333333%;
1735 }
1736 .col-xs-push-0 {
1737 left: auto;
1738 }
1739 .col-xs-offset-12 {
1740 margin-left: 100%;
1741 }
1742 .col-xs-offset-11 {
1743 margin-left: 91.66666667%;
1744 }
1745 .col-xs-offset-10 {
1746 margin-left: 83.33333333%;
1747 }
1748 .col-xs-offset-9 {
1749 margin-left: 75%;
1750 }
1751 .col-xs-offset-8 {
1752 margin-left: 66.66666667%;
1753 }
1754 .col-xs-offset-7 {
1755 margin-left: 58.33333333%;
1756 }
1757 .col-xs-offset-6 {
1758 margin-left: 50%;
1759 }
1760 .col-xs-offset-5 {
1761 margin-left: 41.66666667%;
1762 }
1763 .col-xs-offset-4 {
1764 margin-left: 33.33333333%;
1765 }
1766 .col-xs-offset-3 {
1767 margin-left: 25%;
1768 }
1769 .col-xs-offset-2 {
1770 margin-left: 16.66666667%;
1771 }
1772 .col-xs-offset-1 {
1773 margin-left: 8.33333333%;
1774 }
1775 .col-xs-offset-0 {
1776 margin-left: 0%;
1777 }
1778 @media (min-width: 768px) {
1779 .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
1780 float: left;
1781 }
1782 .col-sm-12 {
1783 width: 100%;
1784 }
1785 .col-sm-11 {
1786 width: 91.66666667%;
1787 }
1788 .col-sm-10 {
1789 width: 83.33333333%;
1790 }
1791 .col-sm-9 {
1792 width: 75%;
1793 }
1794 .col-sm-8 {
1795 width: 66.66666667%;
1796 }
1797 .col-sm-7 {
1798 width: 58.33333333%;
1799 }
1800 .col-sm-6 {
1801 width: 50%;
1802 }
1803 .col-sm-5 {
1804 width: 41.66666667%;
1805 }
1806 .col-sm-4 {
1807 width: 33.33333333%;
1808 }
1809 .col-sm-3 {
1810 width: 25%;
1811 }
1812 .col-sm-2 {
1813 width: 16.66666667%;
1814 }
1815 .col-sm-1 {
1816 width: 8.33333333%;
1817 }
1818 .col-sm-pull-12 {
1819 right: 100%;
1820 }
1821 .col-sm-pull-11 {
1822 right: 91.66666667%;
1823 }
1824 .col-sm-pull-10 {
1825 right: 83.33333333%;
1826 }
1827 .col-sm-pull-9 {
1828 right: 75%;
1829 }
1830 .col-sm-pull-8 {
1831 right: 66.66666667%;
1832 }
1833 .col-sm-pull-7 {
1834 right: 58.33333333%;
1835 }
1836 .col-sm-pull-6 {
1837 right: 50%;
1838 }
1839 .col-sm-pull-5 {
1840 right: 41.66666667%;
1841 }
1842 .col-sm-pull-4 {
1843 right: 33.33333333%;
1844 }
1845 .col-sm-pull-3 {
1846 right: 25%;
1847 }
1848 .col-sm-pull-2 {
1849 right: 16.66666667%;
1850 }
1851 .col-sm-pull-1 {
1852 right: 8.33333333%;
1853 }
1854 .col-sm-pull-0 {
1855 right: auto;
1856 }
1857 .col-sm-push-12 {
1858 left: 100%;
1859 }
1860 .col-sm-push-11 {
1861 left: 91.66666667%;
1862 }
1863 .col-sm-push-10 {
1864 left: 83.33333333%;
1865 }
1866 .col-sm-push-9 {
1867 left: 75%;
1868 }
1869 .col-sm-push-8 {
1870 left: 66.66666667%;
1871 }
1872 .col-sm-push-7 {
1873 left: 58.33333333%;
1874 }
1875 .col-sm-push-6 {
1876 left: 50%;
1877 }
1878 .col-sm-push-5 {
1879 left: 41.66666667%;
1880 }
1881 .col-sm-push-4 {
1882 left: 33.33333333%;
1883 }
1884 .col-sm-push-3 {
1885 left: 25%;
1886 }
1887 .col-sm-push-2 {
1888 left: 16.66666667%;
1889 }
1890 .col-sm-push-1 {
1891 left: 8.33333333%;
1892 }
1893 .col-sm-push-0 {
1894 left: auto;
1895 }
1896 .col-sm-offset-12 {
1897 margin-left: 100%;
1898 }
1899 .col-sm-offset-11 {
1900 margin-left: 91.66666667%;
1901 }
1902 .col-sm-offset-10 {
1903 margin-left: 83.33333333%;
1904 }
1905 .col-sm-offset-9 {
1906 margin-left: 75%;
1907 }
1908 .col-sm-offset-8 {
1909 margin-left: 66.66666667%;
1910 }
1911 .col-sm-offset-7 {
1912 margin-left: 58.33333333%;
1913 }
1914 .col-sm-offset-6 {
1915 margin-left: 50%;
1916 }
1917 .col-sm-offset-5 {
1918 margin-left: 41.66666667%;
1919 }
1920 .col-sm-offset-4 {
1921 margin-left: 33.33333333%;
1922 }
1923 .col-sm-offset-3 {
1924 margin-left: 25%;
1925 }
1926 .col-sm-offset-2 {
1927 margin-left: 16.66666667%;
1928 }
1929 .col-sm-offset-1 {
1930 margin-left: 8.33333333%;
1931 }
1932 .col-sm-offset-0 {
1933 margin-left: 0%;
1934 }
1935 }
1936 @media (min-width: 992px) {
1937 .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
1938 float: left;
1939 }
1940 .col-md-12 {
1941 width: 100%;
1942 }
1943 .col-md-11 {
1944 width: 91.66666667%;
1945 }
1946 .col-md-10 {
1947 width: 83.33333333%;
1948 }
1949 .col-md-9 {
1950 width: 75%;
1951 }
1952 .col-md-8 {
1953 width: 66.66666667%;
1954 }
1955 .col-md-7 {
1956 width: 58.33333333%;
1957 }
1958 .col-md-6 {
1959 width: 50%;
1960 }
1961 .col-md-5 {
1962 width: 41.66666667%;
1963 }
1964 .col-md-4 {
1965 width: 33.33333333%;
1966 }
1967 .col-md-3 {
1968 width: 25%;
1969 }
1970 .col-md-2 {
1971 width: 16.66666667%;
1972 }
1973 .col-md-1 {
1974 width: 8.33333333%;
1975 }
1976 .col-md-pull-12 {
1977 right: 100%;
1978 }
1979 .col-md-pull-11 {
1980 right: 91.66666667%;
1981 }
1982 .col-md-pull-10 {
1983 right: 83.33333333%;
1984 }
1985 .col-md-pull-9 {
1986 right: 75%;
1987 }
1988 .col-md-pull-8 {
1989 right: 66.66666667%;
1990 }
1991 .col-md-pull-7 {
1992 right: 58.33333333%;
1993 }
1994 .col-md-pull-6 {
1995 right: 50%;
1996 }
1997 .col-md-pull-5 {
1998 right: 41.66666667%;
1999 }
2000 .col-md-pull-4 {
2001 right: 33.33333333%;
2002 }
2003 .col-md-pull-3 {
2004 right: 25%;
2005 }
2006 .col-md-pull-2 {
2007 right: 16.66666667%;
2008 }
2009 .col-md-pull-1 {
2010 right: 8.33333333%;
2011 }
2012 .col-md-pull-0 {
2013 right: auto;
2014 }
2015 .col-md-push-12 {
2016 left: 100%;
2017 }
2018 .col-md-push-11 {
2019 left: 91.66666667%;
2020 }
2021 .col-md-push-10 {
2022 left: 83.33333333%;
2023 }
2024 .col-md-push-9 {
2025 left: 75%;
2026 }
2027 .col-md-push-8 {
2028 left: 66.66666667%;
2029 }
2030 .col-md-push-7 {
2031 left: 58.33333333%;
2032 }
2033 .col-md-push-6 {
2034 left: 50%;
2035 }
2036 .col-md-push-5 {
2037 left: 41.66666667%;
2038 }
2039 .col-md-push-4 {
2040 left: 33.33333333%;
2041 }
2042 .col-md-push-3 {
2043 left: 25%;
2044 }
2045 .col-md-push-2 {
2046 left: 16.66666667%;
2047 }
2048 .col-md-push-1 {
2049 left: 8.33333333%;
2050 }
2051 .col-md-push-0 {
2052 left: auto;
2053 }
2054 .col-md-offset-12 {
2055 margin-left: 100%;
2056 }
2057 .col-md-offset-11 {
2058 margin-left: 91.66666667%;
2059 }
2060 .col-md-offset-10 {
2061 margin-left: 83.33333333%;
2062 }
2063 .col-md-offset-9 {
2064 margin-left: 75%;
2065 }
2066 .col-md-offset-8 {
2067 margin-left: 66.66666667%;
2068 }
2069 .col-md-offset-7 {
2070 margin-left: 58.33333333%;
2071 }
2072 .col-md-offset-6 {
2073 margin-left: 50%;
2074 }
2075 .col-md-offset-5 {
2076 margin-left: 41.66666667%;
2077 }
2078 .col-md-offset-4 {
2079 margin-left: 33.33333333%;
2080 }
2081 .col-md-offset-3 {
2082 margin-left: 25%;
2083 }
2084 .col-md-offset-2 {
2085 margin-left: 16.66666667%;
2086 }
2087 .col-md-offset-1 {
2088 margin-left: 8.33333333%;
2089 }
2090 .col-md-offset-0 {
2091 margin-left: 0%;
2092 }
2093 }
2094 @media (min-width: 1200px) {
2095 .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
2096 float: left;
2097 }
2098 .col-lg-12 {
2099 width: 100%;
2100 }
2101 .col-lg-11 {
2102 width: 91.66666667%;
2103 }
2104 .col-lg-10 {
2105 width: 83.33333333%;
2106 }
2107 .col-lg-9 {
2108 width: 75%;
2109 }
2110 .col-lg-8 {
2111 width: 66.66666667%;
2112 }
2113 .col-lg-7 {
2114 width: 58.33333333%;
2115 }
2116 .col-lg-6 {
2117 width: 50%;
2118 }
2119 .col-lg-5 {
2120 width: 41.66666667%;
2121 }
2122 .col-lg-4 {
2123 width: 33.33333333%;
2124 }
2125 .col-lg-3 {
2126 width: 25%;
2127 }
2128 .col-lg-2 {
2129 width: 16.66666667%;
2130 }
2131 .col-lg-1 {
2132 width: 8.33333333%;
2133 }
2134 .col-lg-pull-12 {
2135 right: 100%;
2136 }
2137 .col-lg-pull-11 {
2138 right: 91.66666667%;
2139 }
2140 .col-lg-pull-10 {
2141 right: 83.33333333%;
2142 }
2143 .col-lg-pull-9 {
2144 right: 75%;
2145 }
2146 .col-lg-pull-8 {
2147 right: 66.66666667%;
2148 }
2149 .col-lg-pull-7 {
2150 right: 58.33333333%;
2151 }
2152 .col-lg-pull-6 {
2153 right: 50%;
2154 }
2155 .col-lg-pull-5 {
2156 right: 41.66666667%;
2157 }
2158 .col-lg-pull-4 {
2159 right: 33.33333333%;
2160 }
2161 .col-lg-pull-3 {
2162 right: 25%;
2163 }
2164 .col-lg-pull-2 {
2165 right: 16.66666667%;
2166 }
2167 .col-lg-pull-1 {
2168 right: 8.33333333%;
2169 }
2170 .col-lg-pull-0 {
2171 right: auto;
2172 }
2173 .col-lg-push-12 {
2174 left: 100%;
2175 }
2176 .col-lg-push-11 {
2177 left: 91.66666667%;
2178 }
2179 .col-lg-push-10 {
2180 left: 83.33333333%;
2181 }
2182 .col-lg-push-9 {
2183 left: 75%;
2184 }
2185 .col-lg-push-8 {
2186 left: 66.66666667%;
2187 }
2188 .col-lg-push-7 {
2189 left: 58.33333333%;
2190 }
2191 .col-lg-push-6 {
2192 left: 50%;
2193 }
2194 .col-lg-push-5 {
2195 left: 41.66666667%;
2196 }
2197 .col-lg-push-4 {
2198 left: 33.33333333%;
2199 }
2200 .col-lg-push-3 {
2201 left: 25%;
2202 }
2203 .col-lg-push-2 {
2204 left: 16.66666667%;
2205 }
2206 .col-lg-push-1 {
2207 left: 8.33333333%;
2208 }
2209 .col-lg-push-0 {
2210 left: auto;
2211 }
2212 .col-lg-offset-12 {
2213 margin-left: 100%;
2214 }
2215 .col-lg-offset-11 {
2216 margin-left: 91.66666667%;
2217 }
2218 .col-lg-offset-10 {
2219 margin-left: 83.33333333%;
2220 }
2221 .col-lg-offset-9 {
2222 margin-left: 75%;
2223 }
2224 .col-lg-offset-8 {
2225 margin-left: 66.66666667%;
2226 }
2227 .col-lg-offset-7 {
2228 margin-left: 58.33333333%;
2229 }
2230 .col-lg-offset-6 {
2231 margin-left: 50%;
2232 }
2233 .col-lg-offset-5 {
2234 margin-left: 41.66666667%;
2235 }
2236 .col-lg-offset-4 {
2237 margin-left: 33.33333333%;
2238 }
2239 .col-lg-offset-3 {
2240 margin-left: 25%;
2241 }
2242 .col-lg-offset-2 {
2243 margin-left: 16.66666667%;
2244 }
2245 .col-lg-offset-1 {
2246 margin-left: 8.33333333%;
2247 }
2248 .col-lg-offset-0 {
2249 margin-left: 0%;
2250 }
2251 }
2252 table {
2253 background-color: transparent;
2254 }
2255 caption {
2256 padding-top: 8px;
2257 padding-bottom: 8px;
2258 color: #777777;
2259 text-align: left;
2260 }
2261 th {
2262 text-align: left;
2263 }
2264 .table {
2265 width: 100%;
2266 max-width: 100%;
2267 margin-bottom: 18px;
2268 }
2269 .table > thead > tr > th,
2270 .table > tbody > tr > th,
2271 .table > tfoot > tr > th,
2272 .table > thead > tr > td,
2273 .table > tbody > tr > td,
2274 .table > tfoot > tr > td {
2275 padding: 8px;
2276 line-height: 1.42857143;
2277 vertical-align: top;
2278 border-top: 1px solid #ddd;
2279 }
2280 .table > thead > tr > th {
2281 vertical-align: bottom;
2282 border-bottom: 2px solid #ddd;
2283 }
2284 .table > caption + thead > tr:first-child > th,
2285 .table > colgroup + thead > tr:first-child > th,
2286 .table > thead:first-child > tr:first-child > th,
2287 .table > caption + thead > tr:first-child > td,
2288 .table > colgroup + thead > tr:first-child > td,
2289 .table > thead:first-child > tr:first-child > td {
2290 border-top: 0;
2291 }
2292 .table > tbody + tbody {
2293 border-top: 2px solid #ddd;
2294 }
2295 .table .table {
2296 background-color: #fff;
2297 }
2298 .table-condensed > thead > tr > th,
2299 .table-condensed > tbody > tr > th,
2300 .table-condensed > tfoot > tr > th,
2301 .table-condensed > thead > tr > td,
2302 .table-condensed > tbody > tr > td,
2303 .table-condensed > tfoot > tr > td {
2304 padding: 5px;
2305 }
2306 .table-bordered {
2307 border: 1px solid #ddd;
2308 }
2309 .table-bordered > thead > tr > th,
2310 .table-bordered > tbody > tr > th,
2311 .table-bordered > tfoot > tr > th,
2312 .table-bordered > thead > tr > td,
2313 .table-bordered > tbody > tr > td,
2314 .table-bordered > tfoot > tr > td {
2315 border: 1px solid #ddd;
2316 }
2317 .table-bordered > thead > tr > th,
2318 .table-bordered > thead > tr > td {
2319 border-bottom-width: 2px;
2320 }
2321 .table-striped > tbody > tr:nth-of-type(odd) {
2322 background-color: #f9f9f9;
2323 }
2324 .table-hover > tbody > tr:hover {
2325 background-color: #f5f5f5;
2326 }
2327 table col[class*="col-"] {
2328 position: static;
2329 float: none;
2330 display: table-column;
2331 }
2332 table td[class*="col-"],
2333 table th[class*="col-"] {
2334 position: static;
2335 float: none;
2336 display: table-cell;
2337 }
2338 .table > thead > tr > td.active,
2339 .table > tbody > tr > td.active,
2340 .table > tfoot > tr > td.active,
2341 .table > thead > tr > th.active,
2342 .table > tbody > tr > th.active,
2343 .table > tfoot > tr > th.active,
2344 .table > thead > tr.active > td,
2345 .table > tbody > tr.active > td,
2346 .table > tfoot > tr.active > td,
2347 .table > thead > tr.active > th,
2348 .table > tbody > tr.active > th,
2349 .table > tfoot > tr.active > th {
2350 background-color: #f5f5f5;
2351 }
2352 .table-hover > tbody > tr > td.active:hover,
2353 .table-hover > tbody > tr > th.active:hover,
2354 .table-hover > tbody > tr.active:hover > td,
2355 .table-hover > tbody > tr:hover > .active,
2356 .table-hover > tbody > tr.active:hover > th {
2357 background-color: #e8e8e8;
2358 }
2359 .table > thead > tr > td.success,
2360 .table > tbody > tr > td.success,
2361 .table > tfoot > tr > td.success,
2362 .table > thead > tr > th.success,
2363 .table > tbody > tr > th.success,
2364 .table > tfoot > tr > th.success,
2365 .table > thead > tr.success > td,
2366 .table > tbody > tr.success > td,
2367 .table > tfoot > tr.success > td,
2368 .table > thead > tr.success > th,
2369 .table > tbody > tr.success > th,
2370 .table > tfoot > tr.success > th {
2371 background-color: #dff0d8;
2372 }
2373 .table-hover > tbody > tr > td.success:hover,
2374 .table-hover > tbody > tr > th.success:hover,
2375 .table-hover > tbody > tr.success:hover > td,
2376 .table-hover > tbody > tr:hover > .success,
2377 .table-hover > tbody > tr.success:hover > th {
2378 background-color: #d0e9c6;
2379 }
2380 .table > thead > tr > td.info,
2381 .table > tbody > tr > td.info,
2382 .table > tfoot > tr > td.info,
2383 .table > thead > tr > th.info,
2384 .table > tbody > tr > th.info,
2385 .table > tfoot > tr > th.info,
2386 .table > thead > tr.info > td,
2387 .table > tbody > tr.info > td,
2388 .table > tfoot > tr.info > td,
2389 .table > thead > tr.info > th,
2390 .table > tbody > tr.info > th,
2391 .table > tfoot > tr.info > th {
2392 background-color: #d9edf7;
2393 }
2394 .table-hover > tbody > tr > td.info:hover,
2395 .table-hover > tbody > tr > th.info:hover,
2396 .table-hover > tbody > tr.info:hover > td,
2397 .table-hover > tbody > tr:hover > .info,
2398 .table-hover > tbody > tr.info:hover > th {
2399 background-color: #c4e3f3;
2400 }
2401 .table > thead > tr > td.warning,
2402 .table > tbody > tr > td.warning,
2403 .table > tfoot > tr > td.warning,
2404 .table > thead > tr > th.warning,
2405 .table > tbody > tr > th.warning,
2406 .table > tfoot > tr > th.warning,
2407 .table > thead > tr.warning > td,
2408 .table > tbody > tr.warning > td,
2409 .table > tfoot > tr.warning > td,
2410 .table > thead > tr.warning > th,
2411 .table > tbody > tr.warning > th,
2412 .table > tfoot > tr.warning > th {
2413 background-color: #fcf8e3;
2414 }
2415 .table-hover > tbody > tr > td.warning:hover,
2416 .table-hover > tbody > tr > th.warning:hover,
2417 .table-hover > tbody > tr.warning:hover > td,
2418 .table-hover > tbody > tr:hover > .warning,
2419 .table-hover > tbody > tr.warning:hover > th {
2420 background-color: #faf2cc;
2421 }
2422 .table > thead > tr > td.danger,
2423 .table > tbody > tr > td.danger,
2424 .table > tfoot > tr > td.danger,
2425 .table > thead > tr > th.danger,
2426 .table > tbody > tr > th.danger,
2427 .table > tfoot > tr > th.danger,
2428 .table > thead > tr.danger > td,
2429 .table > tbody > tr.danger > td,
2430 .table > tfoot > tr.danger > td,
2431 .table > thead > tr.danger > th,
2432 .table > tbody > tr.danger > th,
2433 .table > tfoot > tr.danger > th {
2434 background-color: #f2dede;
2435 }
2436 .table-hover > tbody > tr > td.danger:hover,
2437 .table-hover > tbody > tr > th.danger:hover,
2438 .table-hover > tbody > tr.danger:hover > td,
2439 .table-hover > tbody > tr:hover > .danger,
2440 .table-hover > tbody > tr.danger:hover > th {
2441 background-color: #ebcccc;
2442 }
2443 .table-responsive {
2444 overflow-x: auto;
2445 min-height: 0.01%;
2446 }
2447 @media screen and (max-width: 767px) {
2448 .table-responsive {
2449 width: 100%;
2450 margin-bottom: 13.5px;
2451 overflow-y: hidden;
2452 -ms-overflow-style: -ms-autohiding-scrollbar;
2453 border: 1px solid #ddd;
2454 }
2455 .table-responsive > .table {
2456 margin-bottom: 0;
2457 }
2458 .table-responsive > .table > thead > tr > th,
2459 .table-responsive > .table > tbody > tr > th,
2460 .table-responsive > .table > tfoot > tr > th,
2461 .table-responsive > .table > thead > tr > td,
2462 .table-responsive > .table > tbody > tr > td,
2463 .table-responsive > .table > tfoot > tr > td {
2464 white-space: nowrap;
2465 }
2466 .table-responsive > .table-bordered {
2467 border: 0;
2468 }
2469 .table-responsive > .table-bordered > thead > tr > th:first-child,
2470 .table-responsive > .table-bordered > tbody > tr > th:first-child,
2471 .table-responsive > .table-bordered > tfoot > tr > th:first-child,
2472 .table-responsive > .table-bordered > thead > tr > td:first-child,
2473 .table-responsive > .table-bordered > tbody > tr > td:first-child,
2474 .table-responsive > .table-bordered > tfoot > tr > td:first-child {
2475 border-left: 0;
2476 }
2477 .table-responsive > .table-bordered > thead > tr > th:last-child,
2478 .table-responsive > .table-bordered > tbody > tr > th:last-child,
2479 .table-responsive > .table-bordered > tfoot > tr > th:last-child,
2480 .table-responsive > .table-bordered > thead > tr > td:last-child,
2481 .table-responsive > .table-bordered > tbody > tr > td:last-child,
2482 .table-responsive > .table-bordered > tfoot > tr > td:last-child {
2483 border-right: 0;
2484 }
2485 .table-responsive > .table-bordered > tbody > tr:last-child > th,
2486 .table-responsive > .table-bordered > tfoot > tr:last-child > th,
2487 .table-responsive > .table-bordered > tbody > tr:last-child > td,
2488 .table-responsive > .table-bordered > tfoot > tr:last-child > td {
2489 border-bottom: 0;
2490 }
2491 }
2492 fieldset {
2493 padding: 0;
2494 margin: 0;
2495 border: 0;
2496 min-width: 0;
2497 }
2498 legend {
2499 display: block;
2500 width: 100%;
2501 padding: 0;
2502 margin-bottom: 18px;
2503 font-size: 19.5px;
2504 line-height: inherit;
2505 color: #333333;
2506 border: 0;
2507 border-bottom: 1px solid #e5e5e5;
2508 }
2509 label {
2510 display: inline-block;
2511 max-width: 100%;
2512 margin-bottom: 5px;
2513 font-weight: bold;
2514 }
2515 input[type="search"] {
2516 -webkit-box-sizing: border-box;
2517 -moz-box-sizing: border-box;
2518 box-sizing: border-box;
2519 }
2520 input[type="radio"],
2521 input[type="checkbox"] {
2522 margin: 4px 0 0;
2523 margin-top: 1px \9;
2524 line-height: normal;
2525 }
2526 input[type="file"] {
2527 display: block;
2528 }
2529 input[type="range"] {
2530 display: block;
2531 width: 100%;
2532 }
2533 select[multiple],
2534 select[size] {
2535 height: auto;
2536 }
2537 input[type="file"]:focus,
2538 input[type="radio"]:focus,
2539 input[type="checkbox"]:focus {
2540 outline: thin dotted;
2541 outline: 5px auto -webkit-focus-ring-color;
2542 outline-offset: -2px;
2543 }
2544 output {
2545 display: block;
2546 padding-top: 7px;
2547 font-size: 13px;
2548 line-height: 1.42857143;
2549 color: #555555;
2550 }
2551 .form-control {
2552 display: block;
2553 width: 100%;
2554 height: 32px;
2555 padding: 6px 12px;
2556 font-size: 13px;
2557 line-height: 1.42857143;
2558 color: #555555;
2559 background-color: #fff;
2560 background-image: none;
2561 border: 1px solid #ccc;
2562 border-radius: 2px;
2563 -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
2564 box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
2565 -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
2566 -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
2567 transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
2568 }
2569 .form-control:focus {
2570 border-color: #66afe9;
2571 outline: 0;
2572 -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
2573 box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
2574 }
2575 .form-control::-moz-placeholder {
2576 color: #999;
2577 opacity: 1;
2578 }
2579 .form-control:-ms-input-placeholder {
2580 color: #999;
2581 }
2582 .form-control::-webkit-input-placeholder {
2583 color: #999;
2584 }
2585 .form-control::-ms-expand {
2586 border: 0;
2587 background-color: transparent;
2588 }
2589 .form-control[disabled],
2590 .form-control[readonly],
2591 fieldset[disabled] .form-control {
2592 background-color: #eeeeee;
2593 opacity: 1;
2594 }
2595 .form-control[disabled],
2596 fieldset[disabled] .form-control {
2597 cursor: not-allowed;
2598 }
2599 textarea.form-control {
2600 height: auto;
2601 }
2602 input[type="search"] {
2603 -webkit-appearance: none;
2604 }
2605 @media screen and (-webkit-min-device-pixel-ratio: 0) {
2606 input[type="date"].form-control,
2607 input[type="time"].form-control,
2608 input[type="datetime-local"].form-control,
2609 input[type="month"].form-control {
2610 line-height: 32px;
2611 }
2612 input[type="date"].input-sm,
2613 input[type="time"].input-sm,
2614 input[type="datetime-local"].input-sm,
2615 input[type="month"].input-sm,
2616 .input-group-sm input[type="date"],
2617 .input-group-sm input[type="time"],
2618 .input-group-sm input[type="datetime-local"],
2619 .input-group-sm input[type="month"] {
2620 line-height: 30px;
2621 }
2622 input[type="date"].input-lg,
2623 input[type="time"].input-lg,
2624 input[type="datetime-local"].input-lg,
2625 input[type="month"].input-lg,
2626 .input-group-lg input[type="date"],
2627 .input-group-lg input[type="time"],
2628 .input-group-lg input[type="datetime-local"],
2629 .input-group-lg input[type="month"] {
2630 line-height: 45px;
2631 }
2632 }
2633 .form-group {
2634 margin-bottom: 15px;
2635 }
2636 .radio,
2637 .checkbox {
2638 position: relative;
2639 display: block;
2640 margin-top: 10px;
2641 margin-bottom: 10px;
2642 }
2643 .radio label,
2644 .checkbox label {
2645 min-height: 18px;
2646 padding-left: 20px;
2647 margin-bottom: 0;
2648 font-weight: normal;
2649 cursor: pointer;
2650 }
2651 .radio input[type="radio"],
2652 .radio-inline input[type="radio"],
2653 .checkbox input[type="checkbox"],
2654 .checkbox-inline input[type="checkbox"] {
2655 position: absolute;
2656 margin-left: -20px;
2657 margin-top: 4px \9;
2658 }
2659 .radio + .radio,
2660 .checkbox + .checkbox {
2661 margin-top: -5px;
2662 }
2663 .radio-inline,
2664 .checkbox-inline {
2665 position: relative;
2666 display: inline-block;
2667 padding-left: 20px;
2668 margin-bottom: 0;
2669 vertical-align: middle;
2670 font-weight: normal;
2671 cursor: pointer;
2672 }
2673 .radio-inline + .radio-inline,
2674 .checkbox-inline + .checkbox-inline {
2675 margin-top: 0;
2676 margin-left: 10px;
2677 }
2678 input[type="radio"][disabled],
2679 input[type="checkbox"][disabled],
2680 input[type="radio"].disabled,
2681 input[type="checkbox"].disabled,
2682 fieldset[disabled] input[type="radio"],
2683 fieldset[disabled] input[type="checkbox"] {
2684 cursor: not-allowed;
2685 }
2686 .radio-inline.disabled,
2687 .checkbox-inline.disabled,
2688 fieldset[disabled] .radio-inline,
2689 fieldset[disabled] .checkbox-inline {
2690 cursor: not-allowed;
2691 }
2692 .radio.disabled label,
2693 .checkbox.disabled label,
2694 fieldset[disabled] .radio label,
2695 fieldset[disabled] .checkbox label {
2696 cursor: not-allowed;
2697 }
2698 .form-control-static {
2699 padding-top: 7px;
2700 padding-bottom: 7px;
2701 margin-bottom: 0;
2702 min-height: 31px;
2703 }
2704 .form-control-static.input-lg,
2705 .form-control-static.input-sm {
2706 padding-left: 0;
2707 padding-right: 0;
2708 }
2709 .input-sm {
2710 height: 30px;
2711 padding: 5px 10px;
2712 font-size: 12px;
2713 line-height: 1.5;
2714 border-radius: 1px;
2715 }
2716 select.input-sm {
2717 height: 30px;
2718 line-height: 30px;
2719 }
2720 textarea.input-sm,
2721 select[multiple].input-sm {
2722 height: auto;
2723 }
2724 .form-group-sm .form-control {
2725 height: 30px;
2726 padding: 5px 10px;
2727 font-size: 12px;
2728 line-height: 1.5;
2729 border-radius: 1px;
2730 }
2731 .form-group-sm select.form-control {
2732 height: 30px;
2733 line-height: 30px;
2734 }
2735 .form-group-sm textarea.form-control,
2736 .form-group-sm select[multiple].form-control {
2737 height: auto;
2738 }
2739 .form-group-sm .form-control-static {
2740 height: 30px;
2741 min-height: 30px;
2742 padding: 6px 10px;
2743 font-size: 12px;
2744 line-height: 1.5;
2745 }
2746 .input-lg {
2747 height: 45px;
2748 padding: 10px 16px;
2749 font-size: 17px;
2750 line-height: 1.3333333;
2751 border-radius: 3px;
2752 }
2753 select.input-lg {
2754 height: 45px;
2755 line-height: 45px;
2756 }
2757 textarea.input-lg,
2758 select[multiple].input-lg {
2759 height: auto;
2760 }
2761 .form-group-lg .form-control {
2762 height: 45px;
2763 padding: 10px 16px;
2764 font-size: 17px;
2765 line-height: 1.3333333;
2766 border-radius: 3px;
2767 }
2768 .form-group-lg select.form-control {
2769 height: 45px;
2770 line-height: 45px;
2771 }
2772 .form-group-lg textarea.form-control,
2773 .form-group-lg select[multiple].form-control {
2774 height: auto;
2775 }
2776 .form-group-lg .form-control-static {
2777 height: 45px;
2778 min-height: 35px;
2779 padding: 11px 16px;
2780 font-size: 17px;
2781 line-height: 1.3333333;
2782 }
2783 .has-feedback {
2784 position: relative;
2785 }
2786 .has-feedback .form-control {
2787 padding-right: 40px;
2788 }
2789 .form-control-feedback {
2790 position: absolute;
2791 top: 0;
2792 right: 0;
2793 z-index: 2;
2794 display: block;
2795 width: 32px;
2796 height: 32px;
2797 line-height: 32px;
2798 text-align: center;
2799 pointer-events: none;
2800 }
2801 .input-lg + .form-control-feedback,
2802 .input-group-lg + .form-control-feedback,
2803 .form-group-lg .form-control + .form-control-feedback {
2804 width: 45px;
2805 height: 45px;
2806 line-height: 45px;
2807 }
2808 .input-sm + .form-control-feedback,
2809 .input-group-sm + .form-control-feedback,
2810 .form-group-sm .form-control + .form-control-feedback {
2811 width: 30px;
2812 height: 30px;
2813 line-height: 30px;
2814 }
2815 .has-success .help-block,
2816 .has-success .control-label,
2817 .has-success .radio,
2818 .has-success .checkbox,
2819 .has-success .radio-inline,
2820 .has-success .checkbox-inline,
2821 .has-success.radio label,
2822 .has-success.checkbox label,
2823 .has-success.radio-inline label,
2824 .has-success.checkbox-inline label {
2825 color: #3c763d;
2826 }
2827 .has-success .form-control {
2828 border-color: #3c763d;
2829 -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
2830 box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
2831 }
2832 .has-success .form-control:focus {
2833 border-color: #2b542c;
2834 -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
2835 box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
2836 }
2837 .has-success .input-group-addon {
2838 color: #3c763d;
2839 border-color: #3c763d;
2840 background-color: #dff0d8;
2841 }
2842 .has-success .form-control-feedback {
2843 color: #3c763d;
2844 }
2845 .has-warning .help-block,
2846 .has-warning .control-label,
2847 .has-warning .radio,
2848 .has-warning .checkbox,
2849 .has-warning .radio-inline,
2850 .has-warning .checkbox-inline,
2851 .has-warning.radio label,
2852 .has-warning.checkbox label,
2853 .has-warning.radio-inline label,
2854 .has-warning.checkbox-inline label {
2855 color: #8a6d3b;
2856 }
2857 .has-warning .form-control {
2858 border-color: #8a6d3b;
2859 -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
2860 box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
2861 }
2862 .has-warning .form-control:focus {
2863 border-color: #66512c;
2864 -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
2865 box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
2866 }
2867 .has-warning .input-group-addon {
2868 color: #8a6d3b;
2869 border-color: #8a6d3b;
2870 background-color: #fcf8e3;
2871 }
2872 .has-warning .form-control-feedback {
2873 color: #8a6d3b;
2874 }
2875 .has-error .help-block,
2876 .has-error .control-label,
2877 .has-error .radio,
2878 .has-error .checkbox,
2879 .has-error .radio-inline,
2880 .has-error .checkbox-inline,
2881 .has-error.radio label,
2882 .has-error.checkbox label,
2883 .has-error.radio-inline label,
2884 .has-error.checkbox-inline label {
2885 color: #a94442;
2886 }
2887 .has-error .form-control {
2888 border-color: #a94442;
2889 -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
2890 box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
2891 }
2892 .has-error .form-control:focus {
2893 border-color: #843534;
2894 -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
2895 box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
2896 }
2897 .has-error .input-group-addon {
2898 color: #a94442;
2899 border-color: #a94442;
2900 background-color: #f2dede;
2901 }
2902 .has-error .form-control-feedback {
2903 color: #a94442;
2904 }
2905 .has-feedback label ~ .form-control-feedback {
2906 top: 23px;
2907 }
2908 .has-feedback label.sr-only ~ .form-control-feedback {
2909 top: 0;
2910 }
2911 .help-block {
2912 display: block;
2913 margin-top: 5px;
2914 margin-bottom: 10px;
2915 color: #404040;
2916 }
2917 @media (min-width: 768px) {
2918 .form-inline .form-group {
2919 display: inline-block;
2920 margin-bottom: 0;
2921 vertical-align: middle;
2922 }
2923 .form-inline .form-control {
2924 display: inline-block;
2925 width: auto;
2926 vertical-align: middle;
2927 }
2928 .form-inline .form-control-static {
2929 display: inline-block;
2930 }
2931 .form-inline .input-group {
2932 display: inline-table;
2933 vertical-align: middle;
2934 }
2935 .form-inline .input-group .input-group-addon,
2936 .form-inline .input-group .input-group-btn,
2937 .form-inline .input-group .form-control {
2938 width: auto;
2939 }
2940 .form-inline .input-group > .form-control {
2941 width: 100%;
2942 }
2943 .form-inline .control-label {
2944 margin-bottom: 0;
2945 vertical-align: middle;
2946 }
2947 .form-inline .radio,
2948 .form-inline .checkbox {
2949 display: inline-block;
2950 margin-top: 0;
2951 margin-bottom: 0;
2952 vertical-align: middle;
2953 }
2954 .form-inline .radio label,
2955 .form-inline .checkbox label {
2956 padding-left: 0;
2957 }
2958 .form-inline .radio input[type="radio"],
2959 .form-inline .checkbox input[type="checkbox"] {
2960 position: relative;
2961 margin-left: 0;
2962 }
2963 .form-inline .has-feedback .form-control-feedback {
2964 top: 0;
2965 }
2966 }
2967 .form-horizontal .radio,
2968 .form-horizontal .checkbox,
2969 .form-horizontal .radio-inline,
2970 .form-horizontal .checkbox-inline {
2971 margin-top: 0;
2972 margin-bottom: 0;
2973 padding-top: 7px;
2974 }
2975 .form-horizontal .radio,
2976 .form-horizontal .checkbox {
2977 min-height: 25px;
2978 }
2979 .form-horizontal .form-group {
2980 margin-left: 0px;
2981 margin-right: 0px;
2982 }
2983 @media (min-width: 768px) {
2984 .form-horizontal .control-label {
2985 text-align: right;
2986 margin-bottom: 0;
2987 padding-top: 7px;
2988 }
2989 }
2990 .form-horizontal .has-feedback .form-control-feedback {
2991 right: 0px;
2992 }
2993 @media (min-width: 768px) {
2994 .form-horizontal .form-group-lg .control-label {
2995 padding-top: 11px;
2996 font-size: 17px;
2997 }
2998 }
2999 @media (min-width: 768px) {
3000 .form-horizontal .form-group-sm .control-label {
3001 padding-top: 6px;
3002 font-size: 12px;
3003 }
3004 }
3005 .btn {
3006 display: inline-block;
3007 margin-bottom: 0;
3008 font-weight: normal;
3009 text-align: center;
3010 vertical-align: middle;
3011 touch-action: manipulation;
3012 cursor: pointer;
3013 background-image: none;
3014 border: 1px solid transparent;
3015 white-space: nowrap;
3016 padding: 6px 12px;
3017 font-size: 13px;
3018 line-height: 1.42857143;
3019 border-radius: 2px;
3020 -webkit-user-select: none;
3021 -moz-user-select: none;
3022 -ms-user-select: none;
3023 user-select: none;
3024 }
3025 .btn:focus,
3026 .btn:active:focus,
3027 .btn.active:focus,
3028 .btn.focus,
3029 .btn:active.focus,
3030 .btn.active.focus {
3031 outline: thin dotted;
3032 outline: 5px auto -webkit-focus-ring-color;
3033 outline-offset: -2px;
3034 }
3035 .btn:hover,
3036 .btn:focus,
3037 .btn.focus {
3038 color: #333;
3039 text-decoration: none;
3040 }
3041 .btn:active,
3042 .btn.active {
3043 outline: 0;
3044 background-image: none;
3045 -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
3046 box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
3047 }
3048 .btn.disabled,
3049 .btn[disabled],
3050 fieldset[disabled] .btn {
3051 cursor: not-allowed;
3052 opacity: 0.65;
3053 filter: alpha(opacity=65);
3054 -webkit-box-shadow: none;
3055 box-shadow: none;
3056 }
3057 a.btn.disabled,
3058 fieldset[disabled] a.btn {
3059 pointer-events: none;
3060 }
3061 .btn-default {
3062 color: #333;
3063 background-color: #fff;
3064 border-color: #ccc;
3065 }
3066 .btn-default:focus,
3067 .btn-default.focus {
3068 color: #333;
3069 background-color: #e6e6e6;
3070 border-color: #8c8c8c;
3071 }
3072 .btn-default:hover {
3073 color: #333;
3074 background-color: #e6e6e6;
3075 border-color: #adadad;
3076 }
3077 .btn-default:active,
3078 .btn-default.active,
3079 .open > .dropdown-toggle.btn-default {
3080 color: #333;
3081 background-color: #e6e6e6;
3082 border-color: #adadad;
3083 }
3084 .btn-default:active:hover,
3085 .btn-default.active:hover,
3086 .open > .dropdown-toggle.btn-default:hover,
3087 .btn-default:active:focus,
3088 .btn-default.active:focus,
3089 .open > .dropdown-toggle.btn-default:focus,
3090 .btn-default:active.focus,
3091 .btn-default.active.focus,
3092 .open > .dropdown-toggle.btn-default.focus {
3093 color: #333;
3094 background-color: #d4d4d4;
3095 border-color: #8c8c8c;
3096 }
3097 .btn-default:active,
3098 .btn-default.active,
3099 .open > .dropdown-toggle.btn-default {
3100 background-image: none;
3101 }
3102 .btn-default.disabled:hover,
3103 .btn-default[disabled]:hover,
3104 fieldset[disabled] .btn-default:hover,
3105 .btn-default.disabled:focus,
3106 .btn-default[disabled]:focus,
3107 fieldset[disabled] .btn-default:focus,
3108 .btn-default.disabled.focus,
3109 .btn-default[disabled].focus,
3110 fieldset[disabled] .btn-default.focus {
3111 background-color: #fff;
3112 border-color: #ccc;
3113 }
3114 .btn-default .badge {
3115 color: #fff;
3116 background-color: #333;
3117 }
3118 .btn-primary {
3119 color: #fff;
3120 background-color: #337ab7;
3121 border-color: #2e6da4;
3122 }
3123 .btn-primary:focus,
3124 .btn-primary.focus {
3125 color: #fff;
3126 background-color: #286090;
3127 border-color: #122b40;
3128 }
3129 .btn-primary:hover {
3130 color: #fff;
3131 background-color: #286090;
3132 border-color: #204d74;
3133 }
3134 .btn-primary:active,
3135 .btn-primary.active,
3136 .open > .dropdown-toggle.btn-primary {
3137 color: #fff;
3138 background-color: #286090;
3139 border-color: #204d74;
3140 }
3141 .btn-primary:active:hover,
3142 .btn-primary.active:hover,
3143 .open > .dropdown-toggle.btn-primary:hover,
3144 .btn-primary:active:focus,
3145 .btn-primary.active:focus,
3146 .open > .dropdown-toggle.btn-primary:focus,
3147 .btn-primary:active.focus,
3148 .btn-primary.active.focus,
3149 .open > .dropdown-toggle.btn-primary.focus {
3150 color: #fff;
3151 background-color: #204d74;
3152 border-color: #122b40;
3153 }
3154 .btn-primary:active,
3155 .btn-primary.active,
3156 .open > .dropdown-toggle.btn-primary {
3157 background-image: none;
3158 }
3159 .btn-primary.disabled:hover,
3160 .btn-primary[disabled]:hover,
3161 fieldset[disabled] .btn-primary:hover,
3162 .btn-primary.disabled:focus,
3163 .btn-primary[disabled]:focus,
3164 fieldset[disabled] .btn-primary:focus,
3165 .btn-primary.disabled.focus,
3166 .btn-primary[disabled].focus,
3167 fieldset[disabled] .btn-primary.focus {
3168 background-color: #337ab7;
3169 border-color: #2e6da4;
3170 }
3171 .btn-primary .badge {
3172 color: #337ab7;
3173 background-color: #fff;
3174 }
3175 .btn-success {
3176 color: #fff;
3177 background-color: #5cb85c;
3178 border-color: #4cae4c;
3179 }
3180 .btn-success:focus,
3181 .btn-success.focus {
3182 color: #fff;
3183 background-color: #449d44;
3184 border-color: #255625;
3185 }
3186 .btn-success:hover {
3187 color: #fff;
3188 background-color: #449d44;
3189 border-color: #398439;
3190 }
3191 .btn-success:active,
3192 .btn-success.active,
3193 .open > .dropdown-toggle.btn-success {
3194 color: #fff;
3195 background-color: #449d44;
3196 border-color: #398439;
3197 }
3198 .btn-success:active:hover,
3199 .btn-success.active:hover,
3200 .open > .dropdown-toggle.btn-success:hover,
3201 .btn-success:active:focus,
3202 .btn-success.active:focus,
3203 .open > .dropdown-toggle.btn-success:focus,
3204 .btn-success:active.focus,
3205 .btn-success.active.focus,
3206 .open > .dropdown-toggle.btn-success.focus {
3207 color: #fff;
3208 background-color: #398439;
3209 border-color: #255625;
3210 }
3211 .btn-success:active,
3212 .btn-success.active,
3213 .open > .dropdown-toggle.btn-success {
3214 background-image: none;
3215 }
3216 .btn-success.disabled:hover,
3217 .btn-success[disabled]:hover,
3218 fieldset[disabled] .btn-success:hover,
3219 .btn-success.disabled:focus,
3220 .btn-success[disabled]:focus,
3221 fieldset[disabled] .btn-success:focus,
3222 .btn-success.disabled.focus,
3223 .btn-success[disabled].focus,
3224 fieldset[disabled] .btn-success.focus {
3225 background-color: #5cb85c;
3226 border-color: #4cae4c;
3227 }
3228 .btn-success .badge {
3229 color: #5cb85c;
3230 background-color: #fff;
3231 }
3232 .btn-info {
3233 color: #fff;
3234 background-color: #5bc0de;
3235 border-color: #46b8da;
3236 }
3237 .btn-info:focus,
3238 .btn-info.focus {
3239 color: #fff;
3240 background-color: #31b0d5;
3241 border-color: #1b6d85;
3242 }
3243 .btn-info:hover {
3244 color: #fff;
3245 background-color: #31b0d5;
3246 border-color: #269abc;
3247 }
3248 .btn-info:active,
3249 .btn-info.active,
3250 .open > .dropdown-toggle.btn-info {
3251 color: #fff;
3252 background-color: #31b0d5;
3253 border-color: #269abc;
3254 }
3255 .btn-info:active:hover,
3256 .btn-info.active:hover,
3257 .open > .dropdown-toggle.btn-info:hover,
3258 .btn-info:active:focus,
3259 .btn-info.active:focus,
3260 .open > .dropdown-toggle.btn-info:focus,
3261 .btn-info:active.focus,
3262 .btn-info.active.focus,
3263 .open > .dropdown-toggle.btn-info.focus {
3264 color: #fff;
3265 background-color: #269abc;
3266 border-color: #1b6d85;
3267 }
3268 .btn-info:active,
3269 .btn-info.active,
3270 .open > .dropdown-toggle.btn-info {
3271 background-image: none;
3272 }
3273 .btn-info.disabled:hover,
3274 .btn-info[disabled]:hover,
3275 fieldset[disabled] .btn-info:hover,
3276 .btn-info.disabled:focus,
3277 .btn-info[disabled]:focus,
3278 fieldset[disabled] .btn-info:focus,
3279 .btn-info.disabled.focus,
3280 .btn-info[disabled].focus,
3281 fieldset[disabled] .btn-info.focus {
3282 background-color: #5bc0de;
3283 border-color: #46b8da;
3284 }
3285 .btn-info .badge {
3286 color: #5bc0de;
3287 background-color: #fff;
3288 }
3289 .btn-warning {
3290 color: #fff;
3291 background-color: #f0ad4e;
3292 border-color: #eea236;
3293 }
3294 .btn-warning:focus,
3295 .btn-warning.focus {
3296 color: #fff;
3297 background-color: #ec971f;
3298 border-color: #985f0d;
3299 }
3300 .btn-warning:hover {
3301 color: #fff;
3302 background-color: #ec971f;
3303 border-color: #d58512;
3304 }
3305 .btn-warning:active,
3306 .btn-warning.active,
3307 .open > .dropdown-toggle.btn-warning {
3308 color: #fff;
3309 background-color: #ec971f;
3310 border-color: #d58512;
3311 }
3312 .btn-warning:active:hover,
3313 .btn-warning.active:hover,
3314 .open > .dropdown-toggle.btn-warning:hover,
3315 .btn-warning:active:focus,
3316 .btn-warning.active:focus,
3317 .open > .dropdown-toggle.btn-warning:focus,
3318 .btn-warning:active.focus,
3319 .btn-warning.active.focus,
3320 .open > .dropdown-toggle.btn-warning.focus {
3321 color: #fff;
3322 background-color: #d58512;
3323 border-color: #985f0d;
3324 }
3325 .btn-warning:active,
3326 .btn-warning.active,
3327 .open > .dropdown-toggle.btn-warning {
3328 background-image: none;
3329 }
3330 .btn-warning.disabled:hover,
3331 .btn-warning[disabled]:hover,
3332 fieldset[disabled] .btn-warning:hover,
3333 .btn-warning.disabled:focus,
3334 .btn-warning[disabled]:focus,
3335 fieldset[disabled] .btn-warning:focus,
3336 .btn-warning.disabled.focus,
3337 .btn-warning[disabled].focus,
3338 fieldset[disabled] .btn-warning.focus {
3339 background-color: #f0ad4e;
3340 border-color: #eea236;
3341 }
3342 .btn-warning .badge {
3343 color: #f0ad4e;
3344 background-color: #fff;
3345 }
3346 .btn-danger {
3347 color: #fff;
3348 background-color: #d9534f;
3349 border-color: #d43f3a;
3350 }
3351 .btn-danger:focus,
3352 .btn-danger.focus {
3353 color: #fff;
3354 background-color: #c9302c;
3355 border-color: #761c19;
3356 }
3357 .btn-danger:hover {
3358 color: #fff;
3359 background-color: #c9302c;
3360 border-color: #ac2925;
3361 }
3362 .btn-danger:active,
3363 .btn-danger.active,
3364 .open > .dropdown-toggle.btn-danger {
3365 color: #fff;
3366 background-color: #c9302c;
3367 border-color: #ac2925;
3368 }
3369 .btn-danger:active:hover,
3370 .btn-danger.active:hover,
3371 .open > .dropdown-toggle.btn-danger:hover,
3372 .btn-danger:active:focus,
3373 .btn-danger.active:focus,
3374 .open > .dropdown-toggle.btn-danger:focus,
3375 .btn-danger:active.focus,
3376 .btn-danger.active.focus,
3377 .open > .dropdown-toggle.btn-danger.focus {
3378 color: #fff;
3379 background-color: #ac2925;
3380 border-color: #761c19;
3381 }
3382 .btn-danger:active,
3383 .btn-danger.active,
3384 .open > .dropdown-toggle.btn-danger {
3385 background-image: none;
3386 }
3387 .btn-danger.disabled:hover,
3388 .btn-danger[disabled]:hover,
3389 fieldset[disabled] .btn-danger:hover,
3390 .btn-danger.disabled:focus,
3391 .btn-danger[disabled]:focus,
3392 fieldset[disabled] .btn-danger:focus,
3393 .btn-danger.disabled.focus,
3394 .btn-danger[disabled].focus,
3395 fieldset[disabled] .btn-danger.focus {
3396 background-color: #d9534f;
3397 border-color: #d43f3a;
3398 }
3399 .btn-danger .badge {
3400 color: #d9534f;
3401 background-color: #fff;
3402 }
3403 .btn-link {
3404 color: #337ab7;
3405 font-weight: normal;
3406 border-radius: 0;
3407 }
3408 .btn-link,
3409 .btn-link:active,
3410 .btn-link.active,
3411 .btn-link[disabled],
3412 fieldset[disabled] .btn-link {
3413 background-color: transparent;
3414 -webkit-box-shadow: none;
3415 box-shadow: none;
3416 }
3417 .btn-link,
3418 .btn-link:hover,
3419 .btn-link:focus,
3420 .btn-link:active {
3421 border-color: transparent;
3422 }
3423 .btn-link:hover,
3424 .btn-link:focus {
3425 color: #23527c;
3426 text-decoration: underline;
3427 background-color: transparent;
3428 }
3429 .btn-link[disabled]:hover,
3430 fieldset[disabled] .btn-link:hover,
3431 .btn-link[disabled]:focus,
3432 fieldset[disabled] .btn-link:focus {
3433 color: #777777;
3434 text-decoration: none;
3435 }
3436 .btn-lg,
3437 .btn-group-lg > .btn {
3438 padding: 10px 16px;
3439 font-size: 17px;
3440 line-height: 1.3333333;
3441 border-radius: 3px;
3442 }
3443 .btn-sm,
3444 .btn-group-sm > .btn {
3445 padding: 5px 10px;
3446 font-size: 12px;
3447 line-height: 1.5;
3448 border-radius: 1px;
3449 }
3450 .btn-xs,
3451 .btn-group-xs > .btn {
3452 padding: 1px 5px;
3453 font-size: 12px;
3454 line-height: 1.5;
3455 border-radius: 1px;
3456 }
3457 .btn-block {
3458 display: block;
3459 width: 100%;
3460 }
3461 .btn-block + .btn-block {
3462 margin-top: 5px;
3463 }
3464 input[type="submit"].btn-block,
3465 input[type="reset"].btn-block,
3466 input[type="button"].btn-block {
3467 width: 100%;
3468 }
3469 .fade {
3470 opacity: 0;
3471 -webkit-transition: opacity 0.15s linear;
3472 -o-transition: opacity 0.15s linear;
3473 transition: opacity 0.15s linear;
3474 }
3475 .fade.in {
3476 opacity: 1;
3477 }
3478 .collapse {
3479 display: none;
3480 }
3481 .collapse.in {
3482 display: block;
3483 }
3484 tr.collapse.in {
3485 display: table-row;
3486 }
3487 tbody.collapse.in {
3488 display: table-row-group;
3489 }
3490 .collapsing {
3491 position: relative;
3492 height: 0;
3493 overflow: hidden;
3494 -webkit-transition-property: height, visibility;
3495 transition-property: height, visibility;
3496 -webkit-transition-duration: 0.35s;
3497 transition-duration: 0.35s;
3498 -webkit-transition-timing-function: ease;
3499 transition-timing-function: ease;
3500 }
3501 .caret {
3502 display: inline-block;
3503 width: 0;
3504 height: 0;
3505 margin-left: 2px;
3506 vertical-align: middle;
3507 border-top: 4px dashed;
3508 border-top: 4px solid \9;
3509 border-right: 4px solid transparent;
3510 border-left: 4px solid transparent;
3511 }
3512 .dropup,
3513 .dropdown {
3514 position: relative;
3515 }
3516 .dropdown-toggle:focus {
3517 outline: 0;
3518 }
3519 .dropdown-menu {
3520 position: absolute;
3521 top: 100%;
3522 left: 0;
3523 z-index: 1000;
3524 display: none;
3525 float: left;
3526 min-width: 160px;
3527 padding: 5px 0;
3528 margin: 2px 0 0;
3529 list-style: none;
3530 font-size: 13px;
3531 text-align: left;
3532 background-color: #fff;
3533 border: 1px solid #ccc;
3534 border: 1px solid rgba(0, 0, 0, 0.15);
3535 border-radius: 2px;
3536 -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
3537 box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
3538 background-clip: padding-box;
3539 }
3540 .dropdown-menu.pull-right {
3541 right: 0;
3542 left: auto;
3543 }
3544 .dropdown-menu .divider {
3545 height: 1px;
3546 margin: 8px 0;
3547 overflow: hidden;
3548 background-color: #e5e5e5;
3549 }
3550 .dropdown-menu > li > a {
3551 display: block;
3552 padding: 3px 20px;
3553 clear: both;
3554 font-weight: normal;
3555 line-height: 1.42857143;
3556 color: #333333;
3557 white-space: nowrap;
3558 }
3559 .dropdown-menu > li > a:hover,
3560 .dropdown-menu > li > a:focus {
3561 text-decoration: none;
3562 color: #262626;
3563 background-color: #f5f5f5;
3564 }
3565 .dropdown-menu > .active > a,
3566 .dropdown-menu > .active > a:hover,
3567 .dropdown-menu > .active > a:focus {
3568 color: #fff;
3569 text-decoration: none;
3570 outline: 0;
3571 background-color: #337ab7;
3572 }
3573 .dropdown-menu > .disabled > a,
3574 .dropdown-menu > .disabled > a:hover,
3575 .dropdown-menu > .disabled > a:focus {
3576 color: #777777;
3577 }
3578 .dropdown-menu > .disabled > a:hover,
3579 .dropdown-menu > .disabled > a:focus {
3580 text-decoration: none;
3581 background-color: transparent;
3582 background-image: none;
3583 filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
3584 cursor: not-allowed;
3585 }
3586 .open > .dropdown-menu {
3587 display: block;
3588 }
3589 .open > a {
3590 outline: 0;
3591 }
3592 .dropdown-menu-right {
3593 left: auto;
3594 right: 0;
3595 }
3596 .dropdown-menu-left {
3597 left: 0;
3598 right: auto;
3599 }
3600 .dropdown-header {
3601 display: block;
3602 padding: 3px 20px;
3603 font-size: 12px;
3604 line-height: 1.42857143;
3605 color: #777777;
3606 white-space: nowrap;
3607 }
3608 .dropdown-backdrop {
3609 position: fixed;
3610 left: 0;
3611 right: 0;
3612 bottom: 0;
3613 top: 0;
3614 z-index: 990;
3615 }
3616 .pull-right > .dropdown-menu {
3617 right: 0;
3618 left: auto;
3619 }
3620 .dropup .caret,
3621 .navbar-fixed-bottom .dropdown .caret {
3622 border-top: 0;
3623 border-bottom: 4px dashed;
3624 border-bottom: 4px solid \9;
3625 content: "";
3626 }
3627 .dropup .dropdown-menu,
3628 .navbar-fixed-bottom .dropdown .dropdown-menu {
3629 top: auto;
3630 bottom: 100%;
3631 margin-bottom: 2px;
3632 }
3633 @media (min-width: 541px) {
3634 .navbar-right .dropdown-menu {
3635 left: auto;
3636 right: 0;
3637 }
3638 .navbar-right .dropdown-menu-left {
3639 left: 0;
3640 right: auto;
3641 }
3642 }
3643 .btn-group,
3644 .btn-group-vertical {
3645 position: relative;
3646 display: inline-block;
3647 vertical-align: middle;
3648 }
3649 .btn-group > .btn,
3650 .btn-group-vertical > .btn {
3651 position: relative;
3652 float: left;
3653 }
3654 .btn-group > .btn:hover,
3655 .btn-group-vertical > .btn:hover,
3656 .btn-group > .btn:focus,
3657 .btn-group-vertical > .btn:focus,
3658 .btn-group > .btn:active,
3659 .btn-group-vertical > .btn:active,
3660 .btn-group > .btn.active,
3661 .btn-group-vertical > .btn.active {
3662 z-index: 2;
3663 }
3664 .btn-group .btn + .btn,
3665 .btn-group .btn + .btn-group,
3666 .btn-group .btn-group + .btn,
3667 .btn-group .btn-group + .btn-group {
3668 margin-left: -1px;
3669 }
3670 .btn-toolbar {
3671 margin-left: -5px;
3672 }
3673 .btn-toolbar .btn,
3674 .btn-toolbar .btn-group,
3675 .btn-toolbar .input-group {
3676 float: left;
3677 }
3678 .btn-toolbar > .btn,
3679 .btn-toolbar > .btn-group,
3680 .btn-toolbar > .input-group {
3681 margin-left: 5px;
3682 }
3683 .btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
3684 border-radius: 0;
3685 }
3686 .btn-group > .btn:first-child {
3687 margin-left: 0;
3688 }
3689 .btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
3690 border-bottom-right-radius: 0;
3691 border-top-right-radius: 0;
3692 }
3693 .btn-group > .btn:last-child:not(:first-child),
3694 .btn-group > .dropdown-toggle:not(:first-child) {
3695 border-bottom-left-radius: 0;
3696 border-top-left-radius: 0;
3697 }
3698 .btn-group > .btn-group {
3699 float: left;
3700 }
3701 .btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
3702 border-radius: 0;
3703 }
3704 .btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
3705 .btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
3706 border-bottom-right-radius: 0;
3707 border-top-right-radius: 0;
3708 }
3709 .btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
3710 border-bottom-left-radius: 0;
3711 border-top-left-radius: 0;
3712 }
3713 .btn-group .dropdown-toggle:active,
3714 .btn-group.open .dropdown-toggle {
3715 outline: 0;
3716 }
3717 .btn-group > .btn + .dropdown-toggle {
3718 padding-left: 8px;
3719 padding-right: 8px;
3720 }
3721 .btn-group > .btn-lg + .dropdown-toggle {
3722 padding-left: 12px;
3723 padding-right: 12px;
3724 }
3725 .btn-group.open .dropdown-toggle {
3726 -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
3727 box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
3728 }
3729 .btn-group.open .dropdown-toggle.btn-link {
3730 -webkit-box-shadow: none;
3731 box-shadow: none;
3732 }
3733 .btn .caret {
3734 margin-left: 0;
3735 }
3736 .btn-lg .caret {
3737 border-width: 5px 5px 0;
3738 border-bottom-width: 0;
3739 }
3740 .dropup .btn-lg .caret {
3741 border-width: 0 5px 5px;
3742 }
3743 .btn-group-vertical > .btn,
3744 .btn-group-vertical > .btn-group,
3745 .btn-group-vertical > .btn-group > .btn {
3746 display: block;
3747 float: none;
3748 width: 100%;
3749 max-width: 100%;
3750 }
3751 .btn-group-vertical > .btn-group > .btn {
3752 float: none;
3753 }
3754 .btn-group-vertical > .btn + .btn,
3755 .btn-group-vertical > .btn + .btn-group,
3756 .btn-group-vertical > .btn-group + .btn,
3757 .btn-group-vertical > .btn-group + .btn-group {
3758 margin-top: -1px;
3759 margin-left: 0;
3760 }
3761 .btn-group-vertical > .btn:not(:first-child):not(:last-child) {
3762 border-radius: 0;
3763 }
3764 .btn-group-vertical > .btn:first-child:not(:last-child) {
3765 border-top-right-radius: 2px;
3766 border-top-left-radius: 2px;
3767 border-bottom-right-radius: 0;
3768 border-bottom-left-radius: 0;
3769 }
3770 .btn-group-vertical > .btn:last-child:not(:first-child) {
3771 border-top-right-radius: 0;
3772 border-top-left-radius: 0;
3773 border-bottom-right-radius: 2px;
3774 border-bottom-left-radius: 2px;
3775 }
3776 .btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
3777 border-radius: 0;
3778 }
3779 .btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
3780 .btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
3781 border-bottom-right-radius: 0;
3782 border-bottom-left-radius: 0;
3783 }
3784 .btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
3785 border-top-right-radius: 0;
3786 border-top-left-radius: 0;
3787 }
3788 .btn-group-justified {
3789 display: table;
3790 width: 100%;
3791 table-layout: fixed;
3792 border-collapse: separate;
3793 }
3794 .btn-group-justified > .btn,
3795 .btn-group-justified > .btn-group {
3796 float: none;
3797 display: table-cell;
3798 width: 1%;
3799 }
3800 .btn-group-justified > .btn-group .btn {
3801 width: 100%;
3802 }
3803 .btn-group-justified > .btn-group .dropdown-menu {
3804 left: auto;
3805 }
3806 [data-toggle="buttons"] > .btn input[type="radio"],
3807 [data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
3808 [data-toggle="buttons"] > .btn input[type="checkbox"],
3809 [data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
3810 position: absolute;
3811 clip: rect(0, 0, 0, 0);
3812 pointer-events: none;
3813 }
3814 .input-group {
3815 position: relative;
3816 display: table;
3817 border-collapse: separate;
3818 }
3819 .input-group[class*="col-"] {
3820 float: none;
3821 padding-left: 0;
3822 padding-right: 0;
3823 }
3824 .input-group .form-control {
3825 position: relative;
3826 z-index: 2;
3827 float: left;
3828 width: 100%;
3829 margin-bottom: 0;
3830 }
3831 .input-group .form-control:focus {
3832 z-index: 3;
3833 }
3834 .input-group-lg > .form-control,
3835 .input-group-lg > .input-group-addon,
3836 .input-group-lg > .input-group-btn > .btn {
3837 height: 45px;
3838 padding: 10px 16px;
3839 font-size: 17px;
3840 line-height: 1.3333333;
3841 border-radius: 3px;
3842 }
3843 select.input-group-lg > .form-control,
3844 select.input-group-lg > .input-group-addon,
3845 select.input-group-lg > .input-group-btn > .btn {
3846 height: 45px;
3847 line-height: 45px;
3848 }
3849 textarea.input-group-lg > .form-control,
3850 textarea.input-group-lg > .input-group-addon,
3851 textarea.input-group-lg > .input-group-btn > .btn,
3852 select[multiple].input-group-lg > .form-control,
3853 select[multiple].input-group-lg > .input-group-addon,
3854 select[multiple].input-group-lg > .input-group-btn > .btn {
3855 height: auto;
3856 }
3857 .input-group-sm > .form-control,
3858 .input-group-sm > .input-group-addon,
3859 .input-group-sm > .input-group-btn > .btn {
3860 height: 30px;
3861 padding: 5px 10px;
3862 font-size: 12px;
3863 line-height: 1.5;
3864 border-radius: 1px;
3865 }
3866 select.input-group-sm > .form-control,
3867 select.input-group-sm > .input-group-addon,
3868 select.input-group-sm > .input-group-btn > .btn {
3869 height: 30px;
3870 line-height: 30px;
3871 }
3872 textarea.input-group-sm > .form-control,
3873 textarea.input-group-sm > .input-group-addon,
3874 textarea.input-group-sm > .input-group-btn > .btn,
3875 select[multiple].input-group-sm > .form-control,
3876 select[multiple].input-group-sm > .input-group-addon,
3877 select[multiple].input-group-sm > .input-group-btn > .btn {
3878 height: auto;
3879 }
3880 .input-group-addon,
3881 .input-group-btn,
3882 .input-group .form-control {
3883 display: table-cell;
3884 }
3885 .input-group-addon:not(:first-child):not(:last-child),
3886 .input-group-btn:not(:first-child):not(:last-child),
3887 .input-group .form-control:not(:first-child):not(:last-child) {
3888 border-radius: 0;
3889 }
3890 .input-group-addon,
3891 .input-group-btn {
3892 width: 1%;
3893 white-space: nowrap;
3894 vertical-align: middle;
3895 }
3896 .input-group-addon {
3897 padding: 6px 12px;
3898 font-size: 13px;
3899 font-weight: normal;
3900 line-height: 1;
3901 color: #555555;
3902 text-align: center;
3903 background-color: #eeeeee;
3904 border: 1px solid #ccc;
3905 border-radius: 2px;
3906 }
3907 .input-group-addon.input-sm {
3908 padding: 5px 10px;
3909 font-size: 12px;
3910 border-radius: 1px;
3911 }
3912 .input-group-addon.input-lg {
3913 padding: 10px 16px;
3914 font-size: 17px;
3915 border-radius: 3px;
3916 }
3917 .input-group-addon input[type="radio"],
3918 .input-group-addon input[type="checkbox"] {
3919 margin-top: 0;
3920 }
3921 .input-group .form-control:first-child,
3922 .input-group-addon:first-child,
3923 .input-group-btn:first-child > .btn,
3924 .input-group-btn:first-child > .btn-group > .btn,
3925 .input-group-btn:first-child > .dropdown-toggle,
3926 .input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
3927 .input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
3928 border-bottom-right-radius: 0;
3929 border-top-right-radius: 0;
3930 }
3931 .input-group-addon:first-child {
3932 border-right: 0;
3933 }
3934 .input-group .form-control:last-child,
3935 .input-group-addon:last-child,
3936 .input-group-btn:last-child > .btn,
3937 .input-group-btn:last-child > .btn-group > .btn,
3938 .input-group-btn:last-child > .dropdown-toggle,
3939 .input-group-btn:first-child > .btn:not(:first-child),
3940 .input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
3941 border-bottom-left-radius: 0;
3942 border-top-left-radius: 0;
3943 }
3944 .input-group-addon:last-child {
3945 border-left: 0;
3946 }
3947 .input-group-btn {
3948 position: relative;
3949 font-size: 0;
3950 white-space: nowrap;
3951 }
3952 .input-group-btn > .btn {
3953 position: relative;
3954 }
3955 .input-group-btn > .btn + .btn {
3956 margin-left: -1px;
3957 }
3958 .input-group-btn > .btn:hover,
3959 .input-group-btn > .btn:focus,
3960 .input-group-btn > .btn:active {
3961 z-index: 2;
3962 }
3963 .input-group-btn:first-child > .btn,
3964 .input-group-btn:first-child > .btn-group {
3965 margin-right: -1px;
3966 }
3967 .input-group-btn:last-child > .btn,
3968 .input-group-btn:last-child > .btn-group {
3969 z-index: 2;
3970 margin-left: -1px;
3971 }
3972 .nav {
3973 margin-bottom: 0;
3974 padding-left: 0;
3975 list-style: none;
3976 }
3977 .nav > li {
3978 position: relative;
3979 display: block;
3980 }
3981 .nav > li > a {
3982 position: relative;
3983 display: block;
3984 padding: 10px 15px;
3985 }
3986 .nav > li > a:hover,
3987 .nav > li > a:focus {
3988 text-decoration: none;
3989 background-color: #eeeeee;
3990 }
3991 .nav > li.disabled > a {
3992 color: #777777;
3993 }
3994 .nav > li.disabled > a:hover,
3995 .nav > li.disabled > a:focus {
3996 color: #777777;
3997 text-decoration: none;
3998 background-color: transparent;
3999 cursor: not-allowed;
4000 }
4001 .nav .open > a,
4002 .nav .open > a:hover,
4003 .nav .open > a:focus {
4004 background-color: #eeeeee;
4005 border-color: #337ab7;
4006 }
4007 .nav .nav-divider {
4008 height: 1px;
4009 margin: 8px 0;
4010 overflow: hidden;
4011 background-color: #e5e5e5;
4012 }
4013 .nav > li > a > img {
4014 max-width: none;
4015 }
4016 .nav-tabs {
4017 border-bottom: 1px solid #ddd;
4018 }
4019 .nav-tabs > li {
4020 float: left;
4021 margin-bottom: -1px;
4022 }
4023 .nav-tabs > li > a {
4024 margin-right: 2px;
4025 line-height: 1.42857143;
4026 border: 1px solid transparent;
4027 border-radius: 2px 2px 0 0;
4028 }
4029 .nav-tabs > li > a:hover {
4030 border-color: #eeeeee #eeeeee #ddd;
4031 }
4032 .nav-tabs > li.active > a,
4033 .nav-tabs > li.active > a:hover,
4034 .nav-tabs > li.active > a:focus {
4035 color: #555555;
4036 background-color: #fff;
4037 border: 1px solid #ddd;
4038 border-bottom-color: transparent;
4039 cursor: default;
4040 }
4041 .nav-tabs.nav-justified {
4042 width: 100%;
4043 border-bottom: 0;
4044 }
4045 .nav-tabs.nav-justified > li {
4046 float: none;
4047 }
4048 .nav-tabs.nav-justified > li > a {
4049 text-align: center;
4050 margin-bottom: 5px;
4051 }
4052 .nav-tabs.nav-justified > .dropdown .dropdown-menu {
4053 top: auto;
4054 left: auto;
4055 }
4056 @media (min-width: 768px) {
4057 .nav-tabs.nav-justified > li {
4058 display: table-cell;
4059 width: 1%;
4060 }
4061 .nav-tabs.nav-justified > li > a {
4062 margin-bottom: 0;
4063 }
4064 }
4065 .nav-tabs.nav-justified > li > a {
4066 margin-right: 0;
4067 border-radius: 2px;
4068 }
4069 .nav-tabs.nav-justified > .active > a,
4070 .nav-tabs.nav-justified > .active > a:hover,
4071 .nav-tabs.nav-justified > .active > a:focus {
4072 border: 1px solid #ddd;
4073 }
4074 @media (min-width: 768px) {
4075 .nav-tabs.nav-justified > li > a {
4076 border-bottom: 1px solid #ddd;
4077 border-radius: 2px 2px 0 0;
4078 }
4079 .nav-tabs.nav-justified > .active > a,
4080 .nav-tabs.nav-justified > .active > a:hover,
4081 .nav-tabs.nav-justified > .active > a:focus {
4082 border-bottom-color: #fff;
4083 }
4084 }
4085 .nav-pills > li {
4086 float: left;
4087 }
4088 .nav-pills > li > a {
4089 border-radius: 2px;
4090 }
4091 .nav-pills > li + li {
4092 margin-left: 2px;
4093 }
4094 .nav-pills > li.active > a,
4095 .nav-pills > li.active > a:hover,
4096 .nav-pills > li.active > a:focus {
4097 color: #fff;
4098 background-color: #337ab7;
4099 }
4100 .nav-stacked > li {
4101 float: none;
4102 }
4103 .nav-stacked > li + li {
4104 margin-top: 2px;
4105 margin-left: 0;
4106 }
4107 .nav-justified {
4108 width: 100%;
4109 }
4110 .nav-justified > li {
4111 float: none;
4112 }
4113 .nav-justified > li > a {
4114 text-align: center;
4115 margin-bottom: 5px;
4116 }
4117 .nav-justified > .dropdown .dropdown-menu {
4118 top: auto;
4119 left: auto;
4120 }
4121 @media (min-width: 768px) {
4122 .nav-justified > li {
4123 display: table-cell;
4124 width: 1%;
4125 }
4126 .nav-justified > li > a {
4127 margin-bottom: 0;
4128 }
4129 }
4130 .nav-tabs-justified {
4131 border-bottom: 0;
4132 }
4133 .nav-tabs-justified > li > a {
4134 margin-right: 0;
4135 border-radius: 2px;
4136 }
4137 .nav-tabs-justified > .active > a,
4138 .nav-tabs-justified > .active > a:hover,
4139 .nav-tabs-justified > .active > a:focus {
4140 border: 1px solid #ddd;
4141 }
4142 @media (min-width: 768px) {
4143 .nav-tabs-justified > li > a {
4144 border-bottom: 1px solid #ddd;
4145 border-radius: 2px 2px 0 0;
4146 }
4147 .nav-tabs-justified > .active > a,
4148 .nav-tabs-justified > .active > a:hover,
4149 .nav-tabs-justified > .active > a:focus {
4150 border-bottom-color: #fff;
4151 }
4152 }
4153 .tab-content > .tab-pane {
4154 display: none;
4155 }
4156 .tab-content > .active {
4157 display: block;
4158 }
4159 .nav-tabs .dropdown-menu {
4160 margin-top: -1px;
4161 border-top-right-radius: 0;
4162 border-top-left-radius: 0;
4163 }
4164 .navbar {
4165 position: relative;
4166 min-height: 30px;
4167 margin-bottom: 18px;
4168 border: 1px solid transparent;
4169 }
4170 @media (min-width: 541px) {
4171 .navbar {
4172 border-radius: 2px;
4173 }
4174 }
4175 @media (min-width: 541px) {
4176 .navbar-header {
4177 float: left;
4178 }
4179 }
4180 .navbar-collapse {
4181 overflow-x: visible;
4182 padding-right: 0px;
4183 padding-left: 0px;
4184 border-top: 1px solid transparent;
4185 box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
4186 -webkit-overflow-scrolling: touch;
4187 }
4188 .navbar-collapse.in {
4189 overflow-y: auto;
4190 }
4191 @media (min-width: 541px) {
4192 .navbar-collapse {
4193 width: auto;
4194 border-top: 0;
4195 box-shadow: none;
4196 }
4197 .navbar-collapse.collapse {
4198 display: block !important;
4199 height: auto !important;
4200 padding-bottom: 0;
4201 overflow: visible !important;
4202 }
4203 .navbar-collapse.in {
4204 overflow-y: visible;
4205 }
4206 .navbar-fixed-top .navbar-collapse,
4207 .navbar-static-top .navbar-collapse,
4208 .navbar-fixed-bottom .navbar-collapse {
4209 padding-left: 0;
4210 padding-right: 0;
4211 }
4212 }
4213 .navbar-fixed-top .navbar-collapse,
4214 .navbar-fixed-bottom .navbar-collapse {
4215 max-height: 340px;
4216 }
4217 @media (max-device-width: 540px) and (orientation: landscape) {
4218 .navbar-fixed-top .navbar-collapse,
4219 .navbar-fixed-bottom .navbar-collapse {
4220 max-height: 200px;
4221 }
4222 }
4223 .container > .navbar-header,
4224 .container-fluid > .navbar-header,
4225 .container > .navbar-collapse,
4226 .container-fluid > .navbar-collapse {
4227 margin-right: 0px;
4228 margin-left: 0px;
4229 }
4230 @media (min-width: 541px) {
4231 .container > .navbar-header,
4232 .container-fluid > .navbar-header,
4233 .container > .navbar-collapse,
4234 .container-fluid > .navbar-collapse {
4235 margin-right: 0;
4236 margin-left: 0;
4237 }
4238 }
4239 .navbar-static-top {
4240 z-index: 1000;
4241 border-width: 0 0 1px;
4242 }
4243 @media (min-width: 541px) {
4244 .navbar-static-top {
4245 border-radius: 0;
4246 }
4247 }
4248 .navbar-fixed-top,
4249 .navbar-fixed-bottom {
4250 position: fixed;
4251 right: 0;
4252 left: 0;
4253 z-index: 1030;
4254 }
4255 @media (min-width: 541px) {
4256 .navbar-fixed-top,
4257 .navbar-fixed-bottom {
4258 border-radius: 0;
4259 }
4260 }
4261 .navbar-fixed-top {
4262 top: 0;
4263 border-width: 0 0 1px;
4264 }
4265 .navbar-fixed-bottom {
4266 bottom: 0;
4267 margin-bottom: 0;
4268 border-width: 1px 0 0;
4269 }
4270 .navbar-brand {
4271 float: left;
4272 padding: 6px 0px;
4273 font-size: 17px;
4274 line-height: 18px;
4275 height: 30px;
4276 }
4277 .navbar-brand:hover,
4278 .navbar-brand:focus {
4279 text-decoration: none;
4280 }
4281 .navbar-brand > img {
4282 display: block;
4283 }
4284 @media (min-width: 541px) {
4285 .navbar > .container .navbar-brand,
4286 .navbar > .container-fluid .navbar-brand {
4287 margin-left: 0px;
4288 }
4289 }
4290 .navbar-toggle {
4291 position: relative;
4292 float: right;
4293 margin-right: 0px;
4294 padding: 9px 10px;
4295 margin-top: -2px;
4296 margin-bottom: -2px;
4297 background-color: transparent;
4298 background-image: none;
4299 border: 1px solid transparent;
4300 border-radius: 2px;
4301 }
4302 .navbar-toggle:focus {
4303 outline: 0;
4304 }
4305 .navbar-toggle .icon-bar {
4306 display: block;
4307 width: 22px;
4308 height: 2px;
4309 border-radius: 1px;
4310 }
4311 .navbar-toggle .icon-bar + .icon-bar {
4312 margin-top: 4px;
4313 }
4314 @media (min-width: 541px) {
4315 .navbar-toggle {
4316 display: none;
4317 }
4318 }
4319 .navbar-nav {
4320 margin: 3px 0px;
4321 }
4322 .navbar-nav > li > a {
4323 padding-top: 10px;
4324 padding-bottom: 10px;
4325 line-height: 18px;
4326 }
4327 @media (max-width: 540px) {
4328 .navbar-nav .open .dropdown-menu {
4329 position: static;
4330 float: none;
4331 width: auto;
4332 margin-top: 0;
4333 background-color: transparent;
4334 border: 0;
4335 box-shadow: none;
4336 }
4337 .navbar-nav .open .dropdown-menu > li > a,
4338 .navbar-nav .open .dropdown-menu .dropdown-header {
4339 padding: 5px 15px 5px 25px;
4340 }
4341 .navbar-nav .open .dropdown-menu > li > a {
4342 line-height: 18px;
4343 }
4344 .navbar-nav .open .dropdown-menu > li > a:hover,
4345 .navbar-nav .open .dropdown-menu > li > a:focus {
4346 background-image: none;
4347 }
4348 }
4349 @media (min-width: 541px) {
4350 .navbar-nav {
4351 float: left;
4352 margin: 0;
4353 }
4354 .navbar-nav > li {
4355 float: left;
4356 }
4357 .navbar-nav > li > a {
4358 padding-top: 6px;
4359 padding-bottom: 6px;
4360 }
4361 }
4362 .navbar-form {
4363 margin-left: 0px;
4364 margin-right: 0px;
4365 padding: 10px 0px;
4366 border-top: 1px solid transparent;
4367 border-bottom: 1px solid transparent;
4368 -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
4369 box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
4370 margin-top: -1px;
4371 margin-bottom: -1px;
4372 }
4373 @media (min-width: 768px) {
4374 .navbar-form .form-group {
4375 display: inline-block;
4376 margin-bottom: 0;
4377 vertical-align: middle;
4378 }
4379 .navbar-form .form-control {
4380 display: inline-block;
4381 width: auto;
4382 vertical-align: middle;
4383 }
4384 .navbar-form .form-control-static {
4385 display: inline-block;
4386 }
4387 .navbar-form .input-group {
4388 display: inline-table;
4389 vertical-align: middle;
4390 }
4391 .navbar-form .input-group .input-group-addon,
4392 .navbar-form .input-group .input-group-btn,
4393 .navbar-form .input-group .form-control {
4394 width: auto;
4395 }
4396 .navbar-form .input-group > .form-control {
4397 width: 100%;
4398 }
4399 .navbar-form .control-label {
4400 margin-bottom: 0;
4401 vertical-align: middle;
4402 }
4403 .navbar-form .radio,
4404 .navbar-form .checkbox {
4405 display: inline-block;
4406 margin-top: 0;
4407 margin-bottom: 0;
4408 vertical-align: middle;
4409 }
4410 .navbar-form .radio label,
4411 .navbar-form .checkbox label {
4412 padding-left: 0;
4413 }
4414 .navbar-form .radio input[type="radio"],
4415 .navbar-form .checkbox input[type="checkbox"] {
4416 position: relative;
4417 margin-left: 0;
4418 }
4419 .navbar-form .has-feedback .form-control-feedback {
4420 top: 0;
4421 }
4422 }
4423 @media (max-width: 540px) {
4424 .navbar-form .form-group {
4425 margin-bottom: 5px;
4426 }
4427 .navbar-form .form-group:last-child {
4428 margin-bottom: 0;
4429 }
4430 }
4431 @media (min-width: 541px) {
4432 .navbar-form {
4433 width: auto;
4434 border: 0;
4435 margin-left: 0;
4436 margin-right: 0;
4437 padding-top: 0;
4438 padding-bottom: 0;
4439 -webkit-box-shadow: none;
4440 box-shadow: none;
4441 }
4442 }
4443 .navbar-nav > li > .dropdown-menu {
4444 margin-top: 0;
4445 border-top-right-radius: 0;
4446 border-top-left-radius: 0;
4447 }
4448 .navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
4449 margin-bottom: 0;
4450 border-top-right-radius: 2px;
4451 border-top-left-radius: 2px;
4452 border-bottom-right-radius: 0;
4453 border-bottom-left-radius: 0;
4454 }
4455 .navbar-btn {
4456 margin-top: -1px;
4457 margin-bottom: -1px;
4458 }
4459 .navbar-btn.btn-sm {
4460 margin-top: 0px;
4461 margin-bottom: 0px;
4462 }
4463 .navbar-btn.btn-xs {
4464 margin-top: 4px;
4465 margin-bottom: 4px;
4466 }
4467 .navbar-text {
4468 margin-top: 6px;
4469 margin-bottom: 6px;
4470 }
4471 @media (min-width: 541px) {
4472 .navbar-text {
4473 float: left;
4474 margin-left: 0px;
4475 margin-right: 0px;
4476 }
4477 }
4478 @media (min-width: 541px) {
4479 .navbar-left {
4480 float: left !important;
4481 float: left;
4482 }
4483 .navbar-right {
4484 float: right !important;
4485 float: right;
4486 margin-right: 0px;
4487 }
4488 .navbar-right ~ .navbar-right {
4489 margin-right: 0;
4490 }
4491 }
4492 .navbar-default {
4493 background-color: #f8f8f8;
4494 border-color: #e7e7e7;
4495 }
4496 .navbar-default .navbar-brand {
4497 color: #777;
4498 }
4499 .navbar-default .navbar-brand:hover,
4500 .navbar-default .navbar-brand:focus {
4501 color: #5e5e5e;
4502 background-color: transparent;
4503 }
4504 .navbar-default .navbar-text {
4505 color: #777;
4506 }
4507 .navbar-default .navbar-nav > li > a {
4508 color: #777;
4509 }
4510 .navbar-default .navbar-nav > li > a:hover,
4511 .navbar-default .navbar-nav > li > a:focus {
4512 color: #333;
4513 background-color: transparent;
4514 }
4515 .navbar-default .navbar-nav > .active > a,
4516 .navbar-default .navbar-nav > .active > a:hover,
4517 .navbar-default .navbar-nav > .active > a:focus {
4518 color: #555;
4519 background-color: #e7e7e7;
4520 }
4521 .navbar-default .navbar-nav > .disabled > a,
4522 .navbar-default .navbar-nav > .disabled > a:hover,
4523 .navbar-default .navbar-nav > .disabled > a:focus {
4524 color: #ccc;
4525 background-color: transparent;
4526 }
4527 .navbar-default .navbar-toggle {
4528 border-color: #ddd;
4529 }
4530 .navbar-default .navbar-toggle:hover,
4531 .navbar-default .navbar-toggle:focus {
4532 background-color: #ddd;
4533 }
4534 .navbar-default .navbar-toggle .icon-bar {
4535 background-color: #888;
4536 }
4537 .navbar-default .navbar-collapse,
4538 .navbar-default .navbar-form {
4539 border-color: #e7e7e7;
4540 }
4541 .navbar-default .navbar-nav > .open > a,
4542 .navbar-default .navbar-nav > .open > a:hover,
4543 .navbar-default .navbar-nav > .open > a:focus {
4544 background-color: #e7e7e7;
4545 color: #555;
4546 }
4547 @media (max-width: 540px) {
4548 .navbar-default .navbar-nav .open .dropdown-menu > li > a {
4549 color: #777;
4550 }
4551 .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
4552 .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
4553 color: #333;
4554 background-color: transparent;
4555 }
4556 .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
4557 .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
4558 .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
4559 color: #555;
4560 background-color: #e7e7e7;
4561 }
4562 .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
4563 .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
4564 .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
4565 color: #ccc;
4566 background-color: transparent;
4567 }
4568 }
4569 .navbar-default .navbar-link {
4570 color: #777;
4571 }
4572 .navbar-default .navbar-link:hover {
4573 color: #333;
4574 }
4575 .navbar-default .btn-link {
4576 color: #777;
4577 }
4578 .navbar-default .btn-link:hover,
4579 .navbar-default .btn-link:focus {
4580 color: #333;
4581 }
4582 .navbar-default .btn-link[disabled]:hover,
4583 fieldset[disabled] .navbar-default .btn-link:hover,
4584 .navbar-default .btn-link[disabled]:focus,
4585 fieldset[disabled] .navbar-default .btn-link:focus {
4586 color: #ccc;
4587 }
4588 .navbar-inverse {
4589 background-color: #222;
4590 border-color: #080808;
4591 }
4592 .navbar-inverse .navbar-brand {
4593 color: #9d9d9d;
4594 }
4595 .navbar-inverse .navbar-brand:hover,
4596 .navbar-inverse .navbar-brand:focus {
4597 color: #fff;
4598 background-color: transparent;
4599 }
4600 .navbar-inverse .navbar-text {
4601 color: #9d9d9d;
4602 }
4603 .navbar-inverse .navbar-nav > li > a {
4604 color: #9d9d9d;
4605 }
4606 .navbar-inverse .navbar-nav > li > a:hover,
4607 .navbar-inverse .navbar-nav > li > a:focus {
4608 color: #fff;
4609 background-color: transparent;
4610 }
4611 .navbar-inverse .navbar-nav > .active > a,
4612 .navbar-inverse .navbar-nav > .active > a:hover,
4613 .navbar-inverse .navbar-nav > .active > a:focus {
4614 color: #fff;
4615 background-color: #080808;
4616 }
4617 .navbar-inverse .navbar-nav > .disabled > a,
4618 .navbar-inverse .navbar-nav > .disabled > a:hover,
4619 .navbar-inverse .navbar-nav > .disabled > a:focus {
4620 color: #444;
4621 background-color: transparent;
4622 }
4623 .navbar-inverse .navbar-toggle {
4624 border-color: #333;
4625 }
4626 .navbar-inverse .navbar-toggle:hover,
4627 .navbar-inverse .navbar-toggle:focus {
4628 background-color: #333;
4629 }
4630 .navbar-inverse .navbar-toggle .icon-bar {
4631 background-color: #fff;
4632 }
4633 .navbar-inverse .navbar-collapse,
4634 .navbar-inverse .navbar-form {
4635 border-color: #101010;
4636 }
4637 .navbar-inverse .navbar-nav > .open > a,
4638 .navbar-inverse .navbar-nav > .open > a:hover,
4639 .navbar-inverse .navbar-nav > .open > a:focus {
4640 background-color: #080808;
4641 color: #fff;
4642 }
4643 @media (max-width: 540px) {
4644 .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
4645 border-color: #080808;
4646 }
4647 .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
4648 background-color: #080808;
4649 }
4650 .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
4651 color: #9d9d9d;
4652 }
4653 .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
4654 .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
4655 color: #fff;
4656 background-color: transparent;
4657 }
4658 .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
4659 .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
4660 .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
4661 color: #fff;
4662 background-color: #080808;
4663 }
4664 .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
4665 .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
4666 .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
4667 color: #444;
4668 background-color: transparent;
4669 }
4670 }
4671 .navbar-inverse .navbar-link {
4672 color: #9d9d9d;
4673 }
4674 .navbar-inverse .navbar-link:hover {
4675 color: #fff;
4676 }
4677 .navbar-inverse .btn-link {
4678 color: #9d9d9d;
4679 }
4680 .navbar-inverse .btn-link:hover,
4681 .navbar-inverse .btn-link:focus {
4682 color: #fff;
4683 }
4684 .navbar-inverse .btn-link[disabled]:hover,
4685 fieldset[disabled] .navbar-inverse .btn-link:hover,
4686 .navbar-inverse .btn-link[disabled]:focus,
4687 fieldset[disabled] .navbar-inverse .btn-link:focus {
4688 color: #444;
4689 }
4690 .breadcrumb {
4691 padding: 8px 15px;
4692 margin-bottom: 18px;
4693 list-style: none;
4694 background-color: #f5f5f5;
4695 border-radius: 2px;
4696 }
4697 .breadcrumb > li {
4698 display: inline-block;
4699 }
4700 .breadcrumb > li + li:before {
4701 content: "/\00a0";
4702 padding: 0 5px;
4703 color: #5e5e5e;
4704 }
4705 .breadcrumb > .active {
4706 color: #777777;
4707 }
4708 .pagination {
4709 display: inline-block;
4710 padding-left: 0;
4711 margin: 18px 0;
4712 border-radius: 2px;
4713 }
4714 .pagination > li {
4715 display: inline;
4716 }
4717 .pagination > li > a,
4718 .pagination > li > span {
4719 position: relative;
4720 float: left;
4721 padding: 6px 12px;
4722 line-height: 1.42857143;
4723 text-decoration: none;
4724 color: #337ab7;
4725 background-color: #fff;
4726 border: 1px solid #ddd;
4727 margin-left: -1px;
4728 }
4729 .pagination > li:first-child > a,
4730 .pagination > li:first-child > span {
4731 margin-left: 0;
4732 border-bottom-left-radius: 2px;
4733 border-top-left-radius: 2px;
4734 }
4735 .pagination > li:last-child > a,
4736 .pagination > li:last-child > span {
4737 border-bottom-right-radius: 2px;
4738 border-top-right-radius: 2px;
4739 }
4740 .pagination > li > a:hover,
4741 .pagination > li > span:hover,
4742 .pagination > li > a:focus,
4743 .pagination > li > span:focus {
4744 z-index: 2;
4745 color: #23527c;
4746 background-color: #eeeeee;
4747 border-color: #ddd;
4748 }
4749 .pagination > .active > a,
4750 .pagination > .active > span,
4751 .pagination > .active > a:hover,
4752 .pagination > .active > span:hover,
4753 .pagination > .active > a:focus,
4754 .pagination > .active > span:focus {
4755 z-index: 3;
4756 color: #fff;
4757 background-color: #337ab7;
4758 border-color: #337ab7;
4759 cursor: default;
4760 }
4761 .pagination > .disabled > span,
4762 .pagination > .disabled > span:hover,
4763 .pagination > .disabled > span:focus,
4764 .pagination > .disabled > a,
4765 .pagination > .disabled > a:hover,
4766 .pagination > .disabled > a:focus {
4767 color: #777777;
4768 background-color: #fff;
4769 border-color: #ddd;
4770 cursor: not-allowed;
4771 }
4772 .pagination-lg > li > a,
4773 .pagination-lg > li > span {
4774 padding: 10px 16px;
4775 font-size: 17px;
4776 line-height: 1.3333333;
4777 }
4778 .pagination-lg > li:first-child > a,
4779 .pagination-lg > li:first-child > span {
4780 border-bottom-left-radius: 3px;
4781 border-top-left-radius: 3px;
4782 }
4783 .pagination-lg > li:last-child > a,
4784 .pagination-lg > li:last-child > span {
4785 border-bottom-right-radius: 3px;
4786 border-top-right-radius: 3px;
4787 }
4788 .pagination-sm > li > a,
4789 .pagination-sm > li > span {
4790 padding: 5px 10px;
4791 font-size: 12px;
4792 line-height: 1.5;
4793 }
4794 .pagination-sm > li:first-child > a,
4795 .pagination-sm > li:first-child > span {
4796 border-bottom-left-radius: 1px;
4797 border-top-left-radius: 1px;
4798 }
4799 .pagination-sm > li:last-child > a,
4800 .pagination-sm > li:last-child > span {
4801 border-bottom-right-radius: 1px;
4802 border-top-right-radius: 1px;
4803 }
4804 .pager {
4805 padding-left: 0;
4806 margin: 18px 0;
4807 list-style: none;
4808 text-align: center;
4809 }
4810 .pager li {
4811 display: inline;
4812 }
4813 .pager li > a,
4814 .pager li > span {
4815 display: inline-block;
4816 padding: 5px 14px;
4817 background-color: #fff;
4818 border: 1px solid #ddd;
4819 border-radius: 15px;
4820 }
4821 .pager li > a:hover,
4822 .pager li > a:focus {
4823 text-decoration: none;
4824 background-color: #eeeeee;
4825 }
4826 .pager .next > a,
4827 .pager .next > span {
4828 float: right;
4829 }
4830 .pager .previous > a,
4831 .pager .previous > span {
4832 float: left;
4833 }
4834 .pager .disabled > a,
4835 .pager .disabled > a:hover,
4836 .pager .disabled > a:focus,
4837 .pager .disabled > span {
4838 color: #777777;
4839 background-color: #fff;
4840 cursor: not-allowed;
4841 }
4842 .label {
4843 display: inline;
4844 padding: .2em .6em .3em;
4845 font-size: 75%;
4846 font-weight: bold;
4847 line-height: 1;
4848 color: #fff;
4849 text-align: center;
4850 white-space: nowrap;
4851 vertical-align: baseline;
4852 border-radius: .25em;
4853 }
4854 a.label:hover,
4855 a.label:focus {
4856 color: #fff;
4857 text-decoration: none;
4858 cursor: pointer;
4859 }
4860 .label:empty {
4861 display: none;
4862 }
4863 .btn .label {
4864 position: relative;
4865 top: -1px;
4866 }
4867 .label-default {
4868 background-color: #777777;
4869 }
4870 .label-default[href]:hover,
4871 .label-default[href]:focus {
4872 background-color: #5e5e5e;
4873 }
4874 .label-primary {
4875 background-color: #337ab7;
4876 }
4877 .label-primary[href]:hover,
4878 .label-primary[href]:focus {
4879 background-color: #286090;
4880 }
4881 .label-success {
4882 background-color: #5cb85c;
4883 }
4884 .label-success[href]:hover,
4885 .label-success[href]:focus {
4886 background-color: #449d44;
4887 }
4888 .label-info {
4889 background-color: #5bc0de;
4890 }
4891 .label-info[href]:hover,
4892 .label-info[href]:focus {
4893 background-color: #31b0d5;
4894 }
4895 .label-warning {
4896 background-color: #f0ad4e;
4897 }
4898 .label-warning[href]:hover,
4899 .label-warning[href]:focus {
4900 background-color: #ec971f;
4901 }
4902 .label-danger {
4903 background-color: #d9534f;
4904 }
4905 .label-danger[href]:hover,
4906 .label-danger[href]:focus {
4907 background-color: #c9302c;
4908 }
4909 .badge {
4910 display: inline-block;
4911 min-width: 10px;
4912 padding: 3px 7px;
4913 font-size: 12px;
4914 font-weight: bold;
4915 color: #fff;
4916 line-height: 1;
4917 vertical-align: middle;
4918 white-space: nowrap;
4919 text-align: center;
4920 background-color: #777777;
4921 border-radius: 10px;
4922 }
4923 .badge:empty {
4924 display: none;
4925 }
4926 .btn .badge {
4927 position: relative;
4928 top: -1px;
4929 }
4930 .btn-xs .badge,
4931 .btn-group-xs > .btn .badge {
4932 top: 0;
4933 padding: 1px 5px;
4934 }
4935 a.badge:hover,
4936 a.badge:focus {
4937 color: #fff;
4938 text-decoration: none;
4939 cursor: pointer;
4940 }
4941 .list-group-item.active > .badge,
4942 .nav-pills > .active > a > .badge {
4943 color: #337ab7;
4944 background-color: #fff;
4945 }
4946 .list-group-item > .badge {
4947 float: right;
4948 }
4949 .list-group-item > .badge + .badge {
4950 margin-right: 5px;
4951 }
4952 .nav-pills > li > a > .badge {
4953 margin-left: 3px;
4954 }
4955 .jumbotron {
4956 padding-top: 30px;
4957 padding-bottom: 30px;
4958 margin-bottom: 30px;
4959 color: inherit;
4960 background-color: #eeeeee;
4961 }
4962 .jumbotron h1,
4963 .jumbotron .h1 {
4964 color: inherit;
4965 }
4966 .jumbotron p {
4967 margin-bottom: 15px;
4968 font-size: 20px;
4969 font-weight: 200;
4970 }
4971 .jumbotron > hr {
4972 border-top-color: #d5d5d5;
4973 }
4974 .container .jumbotron,
4975 .container-fluid .jumbotron {
4976 border-radius: 3px;
4977 padding-left: 0px;
4978 padding-right: 0px;
4979 }
4980 .jumbotron .container {
4981 max-width: 100%;
4982 }
4983 @media screen and (min-width: 768px) {
4984 .jumbotron {
4985 padding-top: 48px;
4986 padding-bottom: 48px;
4987 }
4988 .container .jumbotron,
4989 .container-fluid .jumbotron {
4990 padding-left: 60px;
4991 padding-right: 60px;
4992 }
4993 .jumbotron h1,
4994 .jumbotron .h1 {
4995 font-size: 59px;
4996 }
4997 }
4998 .thumbnail {
4999 display: block;
5000 padding: 4px;
5001 margin-bottom: 18px;
5002 line-height: 1.42857143;
5003 background-color: #fff;
5004 border: 1px solid #ddd;
5005 border-radius: 2px;
5006 -webkit-transition: border 0.2s ease-in-out;
5007 -o-transition: border 0.2s ease-in-out;
5008 transition: border 0.2s ease-in-out;
5009 }
5010 .thumbnail > img,
5011 .thumbnail a > img {
5012 margin-left: auto;
5013 margin-right: auto;
5014 }
5015 a.thumbnail:hover,
5016 a.thumbnail:focus,
5017 a.thumbnail.active {
5018 border-color: #337ab7;
5019 }
5020 .thumbnail .caption {
5021 padding: 9px;
5022 color: #000;
5023 }
5024 .alert {
5025 padding: 15px;
5026 margin-bottom: 18px;
5027 border: 1px solid transparent;
5028 border-radius: 2px;
5029 }
5030 .alert h4 {
5031 margin-top: 0;
5032 color: inherit;
5033 }
5034 .alert .alert-link {
5035 font-weight: bold;
5036 }
5037 .alert > p,
5038 .alert > ul {
5039 margin-bottom: 0;
5040 }
5041 .alert > p + p {
5042 margin-top: 5px;
5043 }
5044 .alert-dismissable,
5045 .alert-dismissible {
5046 padding-right: 35px;
5047 }
5048 .alert-dismissable .close,
5049 .alert-dismissible .close {
5050 position: relative;
5051 top: -2px;
5052 right: -21px;
5053 color: inherit;
5054 }
5055 .alert-success {
5056 background-color: #dff0d8;
5057 border-color: #d6e9c6;
5058 color: #3c763d;
5059 }
5060 .alert-success hr {
5061 border-top-color: #c9e2b3;
5062 }
5063 .alert-success .alert-link {
5064 color: #2b542c;
5065 }
5066 .alert-info {
5067 background-color: #d9edf7;
5068 border-color: #bce8f1;
5069 color: #31708f;
5070 }
5071 .alert-info hr {
5072 border-top-color: #a6e1ec;
5073 }
5074 .alert-info .alert-link {
5075 color: #245269;
5076 }
5077 .alert-warning {
5078 background-color: #fcf8e3;
5079 border-color: #faebcc;
5080 color: #8a6d3b;
5081 }
5082 .alert-warning hr {
5083 border-top-color: #f7e1b5;
5084 }
5085 .alert-warning .alert-link {
5086 color: #66512c;
5087 }
5088 .alert-danger {
5089 background-color: #f2dede;
5090 border-color: #ebccd1;
5091 color: #a94442;
5092 }
5093 .alert-danger hr {
5094 border-top-color: #e4b9c0;
5095 }
5096 .alert-danger .alert-link {
5097 color: #843534;
5098 }
5099 @-webkit-keyframes progress-bar-stripes {
5100 from {
5101 background-position: 40px 0;
5102 }
5103 to {
5104 background-position: 0 0;
5105 }
5106 }
5107 @keyframes progress-bar-stripes {
5108 from {
5109 background-position: 40px 0;
5110 }
5111 to {
5112 background-position: 0 0;
5113 }
5114 }
5115 .progress {
5116 overflow: hidden;
5117 height: 18px;
5118 margin-bottom: 18px;
5119 background-color: #f5f5f5;
5120 border-radius: 2px;
5121 -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
5122 box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
5123 }
5124 .progress-bar {
5125 float: left;
5126 width: 0%;
5127 height: 100%;
5128 font-size: 12px;
5129 line-height: 18px;
5130 color: #fff;
5131 text-align: center;
5132 background-color: #337ab7;
5133 -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
5134 box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
5135 -webkit-transition: width 0.6s ease;
5136 -o-transition: width 0.6s ease;
5137 transition: width 0.6s ease;
5138 }
5139 .progress-striped .progress-bar,
5140 .progress-bar-striped {
5141 background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5142 background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5143 background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5144 background-size: 40px 40px;
5145 }
5146 .progress.active .progress-bar,
5147 .progress-bar.active {
5148 -webkit-animation: progress-bar-stripes 2s linear infinite;
5149 -o-animation: progress-bar-stripes 2s linear infinite;
5150 animation: progress-bar-stripes 2s linear infinite;
5151 }
5152 .progress-bar-success {
5153 background-color: #5cb85c;
5154 }
5155 .progress-striped .progress-bar-success {
5156 background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5157 background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5158 background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5159 }
5160 .progress-bar-info {
5161 background-color: #5bc0de;
5162 }
5163 .progress-striped .progress-bar-info {
5164 background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5165 background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5166 background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5167 }
5168 .progress-bar-warning {
5169 background-color: #f0ad4e;
5170 }
5171 .progress-striped .progress-bar-warning {
5172 background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5173 background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5174 background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5175 }
5176 .progress-bar-danger {
5177 background-color: #d9534f;
5178 }
5179 .progress-striped .progress-bar-danger {
5180 background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5181 background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5182 background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
5183 }
5184 .media {
5185 margin-top: 15px;
5186 }
5187 .media:first-child {
5188 margin-top: 0;
5189 }
5190 .media,
5191 .media-body {
5192 zoom: 1;
5193 overflow: hidden;
5194 }
5195 .media-body {
5196 width: 10000px;
5197 }
5198 .media-object {
5199 display: block;
5200 }
5201 .media-object.img-thumbnail {
5202 max-width: none;
5203 }
5204 .media-right,
5205 .media > .pull-right {
5206 padding-left: 10px;
5207 }
5208 .media-left,
5209 .media > .pull-left {
5210 padding-right: 10px;
5211 }
5212 .media-left,
5213 .media-right,
5214 .media-body {
5215 display: table-cell;
5216 vertical-align: top;
5217 }
5218 .media-middle {
5219 vertical-align: middle;
5220 }
5221 .media-bottom {
5222 vertical-align: bottom;
5223 }
5224 .media-heading {
5225 margin-top: 0;
5226 margin-bottom: 5px;
5227 }
5228 .media-list {
5229 padding-left: 0;
5230 list-style: none;
5231 }
5232 .list-group {
5233 margin-bottom: 20px;
5234 padding-left: 0;
5235 }
5236 .list-group-item {
5237 position: relative;
5238 display: block;
5239 padding: 10px 15px;
5240 margin-bottom: -1px;
5241 background-color: #fff;
5242 border: 1px solid #ddd;
5243 }
5244 .list-group-item:first-child {
5245 border-top-right-radius: 2px;
5246 border-top-left-radius: 2px;
5247 }
5248 .list-group-item:last-child {
5249 margin-bottom: 0;
5250 border-bottom-right-radius: 2px;
5251 border-bottom-left-radius: 2px;
5252 }
5253 a.list-group-item,
5254 button.list-group-item {
5255 color: #555;
5256 }
5257 a.list-group-item .list-group-item-heading,
5258 button.list-group-item .list-group-item-heading {
5259 color: #333;
5260 }
5261 a.list-group-item:hover,
5262 button.list-group-item:hover,
5263 a.list-group-item:focus,
5264 button.list-group-item:focus {
5265 text-decoration: none;
5266 color: #555;
5267 background-color: #f5f5f5;
5268 }
5269 button.list-group-item {
5270 width: 100%;
5271 text-align: left;
5272 }
5273 .list-group-item.disabled,
5274 .list-group-item.disabled:hover,
5275 .list-group-item.disabled:focus {
5276 background-color: #eeeeee;
5277 color: #777777;
5278 cursor: not-allowed;
5279 }
5280 .list-group-item.disabled .list-group-item-heading,
5281 .list-group-item.disabled:hover .list-group-item-heading,
5282 .list-group-item.disabled:focus .list-group-item-heading {
5283 color: inherit;
5284 }
5285 .list-group-item.disabled .list-group-item-text,
5286 .list-group-item.disabled:hover .list-group-item-text,
5287 .list-group-item.disabled:focus .list-group-item-text {
5288 color: #777777;
5289 }
5290 .list-group-item.active,
5291 .list-group-item.active:hover,
5292 .list-group-item.active:focus {
5293 z-index: 2;
5294 color: #fff;
5295 background-color: #337ab7;
5296 border-color: #337ab7;
5297 }
5298 .list-group-item.active .list-group-item-heading,
5299 .list-group-item.active:hover .list-group-item-heading,
5300 .list-group-item.active:focus .list-group-item-heading,
5301 .list-group-item.active .list-group-item-heading > small,
5302 .list-group-item.active:hover .list-group-item-heading > small,
5303 .list-group-item.active:focus .list-group-item-heading > small,
5304 .list-group-item.active .list-group-item-heading > .small,
5305 .list-group-item.active:hover .list-group-item-heading > .small,
5306 .list-group-item.active:focus .list-group-item-heading > .small {
5307 color: inherit;
5308 }
5309 .list-group-item.active .list-group-item-text,
5310 .list-group-item.active:hover .list-group-item-text,
5311 .list-group-item.active:focus .list-group-item-text {
5312 color: #c7ddef;
5313 }
5314 .list-group-item-success {
5315 color: #3c763d;
5316 background-color: #dff0d8;
5317 }
5318 a.list-group-item-success,
5319 button.list-group-item-success {
5320 color: #3c763d;
5321 }
5322 a.list-group-item-success .list-group-item-heading,
5323 button.list-group-item-success .list-group-item-heading {
5324 color: inherit;
5325 }
5326 a.list-group-item-success:hover,
5327 button.list-group-item-success:hover,
5328 a.list-group-item-success:focus,
5329 button.list-group-item-success:focus {
5330 color: #3c763d;
5331 background-color: #d0e9c6;
5332 }
5333 a.list-group-item-success.active,
5334 button.list-group-item-success.active,
5335 a.list-group-item-success.active:hover,
5336 button.list-group-item-success.active:hover,
5337 a.list-group-item-success.active:focus,
5338 button.list-group-item-success.active:focus {
5339 color: #fff;
5340 background-color: #3c763d;
5341 border-color: #3c763d;
5342 }
5343 .list-group-item-info {
5344 color: #31708f;
5345 background-color: #d9edf7;
5346 }
5347 a.list-group-item-info,
5348 button.list-group-item-info {
5349 color: #31708f;
5350 }
5351 a.list-group-item-info .list-group-item-heading,
5352 button.list-group-item-info .list-group-item-heading {
5353 color: inherit;
5354 }
5355 a.list-group-item-info:hover,
5356 button.list-group-item-info:hover,
5357 a.list-group-item-info:focus,
5358 button.list-group-item-info:focus {
5359 color: #31708f;
5360 background-color: #c4e3f3;
5361 }
5362 a.list-group-item-info.active,
5363 button.list-group-item-info.active,
5364 a.list-group-item-info.active:hover,
5365 button.list-group-item-info.active:hover,
5366 a.list-group-item-info.active:focus,
5367 button.list-group-item-info.active:focus {
5368 color: #fff;
5369 background-color: #31708f;
5370 border-color: #31708f;
5371 }
5372 .list-group-item-warning {
5373 color: #8a6d3b;
5374 background-color: #fcf8e3;
5375 }
5376 a.list-group-item-warning,
5377 button.list-group-item-warning {
5378 color: #8a6d3b;
5379 }
5380 a.list-group-item-warning .list-group-item-heading,
5381 button.list-group-item-warning .list-group-item-heading {
5382 color: inherit;
5383 }
5384 a.list-group-item-warning:hover,
5385 button.list-group-item-warning:hover,
5386 a.list-group-item-warning:focus,
5387 button.list-group-item-warning:focus {
5388 color: #8a6d3b;
5389 background-color: #faf2cc;
5390 }
5391 a.list-group-item-warning.active,
5392 button.list-group-item-warning.active,
5393 a.list-group-item-warning.active:hover,
5394 button.list-group-item-warning.active:hover,
5395 a.list-group-item-warning.active:focus,
5396 button.list-group-item-warning.active:focus {
5397 color: #fff;
5398 background-color: #8a6d3b;
5399 border-color: #8a6d3b;
5400 }
5401 .list-group-item-danger {
5402 color: #a94442;
5403 background-color: #f2dede;
5404 }
5405 a.list-group-item-danger,
5406 button.list-group-item-danger {
5407 color: #a94442;
5408 }
5409 a.list-group-item-danger .list-group-item-heading,
5410 button.list-group-item-danger .list-group-item-heading {
5411 color: inherit;
5412 }
5413 a.list-group-item-danger:hover,
5414 button.list-group-item-danger:hover,
5415 a.list-group-item-danger:focus,
5416 button.list-group-item-danger:focus {
5417 color: #a94442;
5418 background-color: #ebcccc;
5419 }
5420 a.list-group-item-danger.active,
5421 button.list-group-item-danger.active,
5422 a.list-group-item-danger.active:hover,
5423 button.list-group-item-danger.active:hover,
5424 a.list-group-item-danger.active:focus,
5425 button.list-group-item-danger.active:focus {
5426 color: #fff;
5427 background-color: #a94442;
5428 border-color: #a94442;
5429 }
5430 .list-group-item-heading {
5431 margin-top: 0;
5432 margin-bottom: 5px;
5433 }
5434 .list-group-item-text {
5435 margin-bottom: 0;
5436 line-height: 1.3;
5437 }
5438 .panel {
5439 margin-bottom: 18px;
5440 background-color: #fff;
5441 border: 1px solid transparent;
5442 border-radius: 2px;
5443 -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
5444 box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
5445 }
5446 .panel-body {
5447 padding: 15px;
5448 }
5449 .panel-heading {
5450 padding: 10px 15px;
5451 border-bottom: 1px solid transparent;
5452 border-top-right-radius: 1px;
5453 border-top-left-radius: 1px;
5454 }
5455 .panel-heading > .dropdown .dropdown-toggle {
5456 color: inherit;
5457 }
5458 .panel-title {
5459 margin-top: 0;
5460 margin-bottom: 0;
5461 font-size: 15px;
5462 color: inherit;
5463 }
5464 .panel-title > a,
5465 .panel-title > small,
5466 .panel-title > .small,
5467 .panel-title > small > a,
5468 .panel-title > .small > a {
5469 color: inherit;
5470 }
5471 .panel-footer {
5472 padding: 10px 15px;
5473 background-color: #f5f5f5;
5474 border-top: 1px solid #ddd;
5475 border-bottom-right-radius: 1px;
5476 border-bottom-left-radius: 1px;
5477 }
5478 .panel > .list-group,
5479 .panel > .panel-collapse > .list-group {
5480 margin-bottom: 0;
5481 }
5482 .panel > .list-group .list-group-item,
5483 .panel > .panel-collapse > .list-group .list-group-item {
5484 border-width: 1px 0;
5485 border-radius: 0;
5486 }
5487 .panel > .list-group:first-child .list-group-item:first-child,
5488 .panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
5489 border-top: 0;
5490 border-top-right-radius: 1px;
5491 border-top-left-radius: 1px;
5492 }
5493 .panel > .list-group:last-child .list-group-item:last-child,
5494 .panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
5495 border-bottom: 0;
5496 border-bottom-right-radius: 1px;
5497 border-bottom-left-radius: 1px;
5498 }
5499 .panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
5500 border-top-right-radius: 0;
5501 border-top-left-radius: 0;
5502 }
5503 .panel-heading + .list-group .list-group-item:first-child {
5504 border-top-width: 0;
5505 }
5506 .list-group + .panel-footer {
5507 border-top-width: 0;
5508 }
5509 .panel > .table,
5510 .panel > .table-responsive > .table,
5511 .panel > .panel-collapse > .table {
5512 margin-bottom: 0;
5513 }
5514 .panel > .table caption,
5515 .panel > .table-responsive > .table caption,
5516 .panel > .panel-collapse > .table caption {
5517 padding-left: 15px;
5518 padding-right: 15px;
5519 }
5520 .panel > .table:first-child,
5521 .panel > .table-responsive:first-child > .table:first-child {
5522 border-top-right-radius: 1px;
5523 border-top-left-radius: 1px;
5524 }
5525 .panel > .table:first-child > thead:first-child > tr:first-child,
5526 .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
5527 .panel > .table:first-child > tbody:first-child > tr:first-child,
5528 .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
5529 border-top-left-radius: 1px;
5530 border-top-right-radius: 1px;
5531 }
5532 .panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
5533 .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
5534 .panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
5535 .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
5536 .panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
5537 .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
5538 .panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
5539 .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
5540 border-top-left-radius: 1px;
5541 }
5542 .panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
5543 .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
5544 .panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
5545 .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
5546 .panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
5547 .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
5548 .panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
5549 .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
5550 border-top-right-radius: 1px;
5551 }
5552 .panel > .table:last-child,
5553 .panel > .table-responsive:last-child > .table:last-child {
5554 border-bottom-right-radius: 1px;
5555 border-bottom-left-radius: 1px;
5556 }
5557 .panel > .table:last-child > tbody:last-child > tr:last-child,
5558 .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
5559 .panel > .table:last-child > tfoot:last-child > tr:last-child,
5560 .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
5561 border-bottom-left-radius: 1px;
5562 border-bottom-right-radius: 1px;
5563 }
5564 .panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
5565 .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
5566 .panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
5567 .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
5568 .panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
5569 .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
5570 .panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
5571 .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
5572 border-bottom-left-radius: 1px;
5573 }
5574 .panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
5575 .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
5576 .panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
5577 .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
5578 .panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
5579 .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
5580 .panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
5581 .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
5582 border-bottom-right-radius: 1px;
5583 }
5584 .panel > .panel-body + .table,
5585 .panel > .panel-body + .table-responsive,
5586 .panel > .table + .panel-body,
5587 .panel > .table-responsive + .panel-body {
5588 border-top: 1px solid #ddd;
5589 }
5590 .panel > .table > tbody:first-child > tr:first-child th,
5591 .panel > .table > tbody:first-child > tr:first-child td {
5592 border-top: 0;
5593 }
5594 .panel > .table-bordered,
5595 .panel > .table-responsive > .table-bordered {
5596 border: 0;
5597 }
5598 .panel > .table-bordered > thead > tr > th:first-child,
5599 .panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
5600 .panel > .table-bordered > tbody > tr > th:first-child,
5601 .panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
5602 .panel > .table-bordered > tfoot > tr > th:first-child,
5603 .panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
5604 .panel > .table-bordered > thead > tr > td:first-child,
5605 .panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
5606 .panel > .table-bordered > tbody > tr > td:first-child,
5607 .panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
5608 .panel > .table-bordered > tfoot > tr > td:first-child,
5609 .panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
5610 border-left: 0;
5611 }
5612 .panel > .table-bordered > thead > tr > th:last-child,
5613 .panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
5614 .panel > .table-bordered > tbody > tr > th:last-child,
5615 .panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
5616 .panel > .table-bordered > tfoot > tr > th:last-child,
5617 .panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
5618 .panel > .table-bordered > thead > tr > td:last-child,
5619 .panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
5620 .panel > .table-bordered > tbody > tr > td:last-child,
5621 .panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
5622 .panel > .table-bordered > tfoot > tr > td:last-child,
5623 .panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
5624 border-right: 0;
5625 }
5626 .panel > .table-bordered > thead > tr:first-child > td,
5627 .panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
5628 .panel > .table-bordered > tbody > tr:first-child > td,
5629 .panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
5630 .panel > .table-bordered > thead > tr:first-child > th,
5631 .panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
5632 .panel > .table-bordered > tbody > tr:first-child > th,
5633 .panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
5634 border-bottom: 0;
5635 }
5636 .panel > .table-bordered > tbody > tr:last-child > td,
5637 .panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
5638 .panel > .table-bordered > tfoot > tr:last-child > td,
5639 .panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
5640 .panel > .table-bordered > tbody > tr:last-child > th,
5641 .panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
5642 .panel > .table-bordered > tfoot > tr:last-child > th,
5643 .panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
5644 border-bottom: 0;
5645 }
5646 .panel > .table-responsive {
5647 border: 0;
5648 margin-bottom: 0;
5649 }
5650 .panel-group {
5651 margin-bottom: 18px;
5652 }
5653 .panel-group .panel {
5654 margin-bottom: 0;
5655 border-radius: 2px;
5656 }
5657 .panel-group .panel + .panel {
5658 margin-top: 5px;
5659 }
5660 .panel-group .panel-heading {
5661 border-bottom: 0;
5662 }
5663 .panel-group .panel-heading + .panel-collapse > .panel-body,
5664 .panel-group .panel-heading + .panel-collapse > .list-group {
5665 border-top: 1px solid #ddd;
5666 }
5667 .panel-group .panel-footer {
5668 border-top: 0;
5669 }
5670 .panel-group .panel-footer + .panel-collapse .panel-body {
5671 border-bottom: 1px solid #ddd;
5672 }
5673 .panel-default {
5674 border-color: #ddd;
5675 }
5676 .panel-default > .panel-heading {
5677 color: #333333;
5678 background-color: #f5f5f5;
5679 border-color: #ddd;
5680 }
5681 .panel-default > .panel-heading + .panel-collapse > .panel-body {
5682 border-top-color: #ddd;
5683 }
5684 .panel-default > .panel-heading .badge {
5685 color: #f5f5f5;
5686 background-color: #333333;
5687 }
5688 .panel-default > .panel-footer + .panel-collapse > .panel-body {
5689 border-bottom-color: #ddd;
5690 }
5691 .panel-primary {
5692 border-color: #337ab7;
5693 }
5694 .panel-primary > .panel-heading {
5695 color: #fff;
5696 background-color: #337ab7;
5697 border-color: #337ab7;
5698 }
5699 .panel-primary > .panel-heading + .panel-collapse > .panel-body {
5700 border-top-color: #337ab7;
5701 }
5702 .panel-primary > .panel-heading .badge {
5703 color: #337ab7;
5704 background-color: #fff;
5705 }
5706 .panel-primary > .panel-footer + .panel-collapse > .panel-body {
5707 border-bottom-color: #337ab7;
5708 }
5709 .panel-success {
5710 border-color: #d6e9c6;
5711 }
5712 .panel-success > .panel-heading {
5713 color: #3c763d;
5714 background-color: #dff0d8;
5715 border-color: #d6e9c6;
5716 }
5717 .panel-success > .panel-heading + .panel-collapse > .panel-body {
5718 border-top-color: #d6e9c6;
5719 }
5720 .panel-success > .panel-heading .badge {
5721 color: #dff0d8;
5722 background-color: #3c763d;
5723 }
5724 .panel-success > .panel-footer + .panel-collapse > .panel-body {
5725 border-bottom-color: #d6e9c6;
5726 }
5727 .panel-info {
5728 border-color: #bce8f1;
5729 }
5730 .panel-info > .panel-heading {
5731 color: #31708f;
5732 background-color: #d9edf7;
5733 border-color: #bce8f1;
5734 }
5735 .panel-info > .panel-heading + .panel-collapse > .panel-body {
5736 border-top-color: #bce8f1;
5737 }
5738 .panel-info > .panel-heading .badge {
5739 color: #d9edf7;
5740 background-color: #31708f;
5741 }
5742 .panel-info > .panel-footer + .panel-collapse > .panel-body {
5743 border-bottom-color: #bce8f1;
5744 }
5745 .panel-warning {
5746 border-color: #faebcc;
5747 }
5748 .panel-warning > .panel-heading {
5749 color: #8a6d3b;
5750 background-color: #fcf8e3;
5751 border-color: #faebcc;
5752 }
5753 .panel-warning > .panel-heading + .panel-collapse > .panel-body {
5754 border-top-color: #faebcc;
5755 }
5756 .panel-warning > .panel-heading .badge {
5757 color: #fcf8e3;
5758 background-color: #8a6d3b;
5759 }
5760 .panel-warning > .panel-footer + .panel-collapse > .panel-body {
5761 border-bottom-color: #faebcc;
5762 }
5763 .panel-danger {
5764 border-color: #ebccd1;
5765 }
5766 .panel-danger > .panel-heading {
5767 color: #a94442;
5768 background-color: #f2dede;
5769 border-color: #ebccd1;
5770 }
5771 .panel-danger > .panel-heading + .panel-collapse > .panel-body {
5772 border-top-color: #ebccd1;
5773 }
5774 .panel-danger > .panel-heading .badge {
5775 color: #f2dede;
5776 background-color: #a94442;
5777 }
5778 .panel-danger > .panel-footer + .panel-collapse > .panel-body {
5779 border-bottom-color: #ebccd1;
5780 }
5781 .embed-responsive {
5782 position: relative;
5783 display: block;
5784 height: 0;
5785 padding: 0;
5786 overflow: hidden;
5787 }
5788 .embed-responsive .embed-responsive-item,
5789 .embed-responsive iframe,
5790 .embed-responsive embed,
5791 .embed-responsive object,
5792 .embed-responsive video {
5793 position: absolute;
5794 top: 0;
5795 left: 0;
5796 bottom: 0;
5797 height: 100%;
5798 width: 100%;
5799 border: 0;
5800 }
5801 .embed-responsive-16by9 {
5802 padding-bottom: 56.25%;
5803 }
5804 .embed-responsive-4by3 {
5805 padding-bottom: 75%;
5806 }
5807 .well {
5808 min-height: 20px;
5809 padding: 19px;
5810 margin-bottom: 20px;
5811 background-color: #f5f5f5;
5812 border: 1px solid #e3e3e3;
5813 border-radius: 2px;
5814 -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
5815 box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
5816 }
5817 .well blockquote {
5818 border-color: #ddd;
5819 border-color: rgba(0, 0, 0, 0.15);
5820 }
5821 .well-lg {
5822 padding: 24px;
5823 border-radius: 3px;
5824 }
5825 .well-sm {
5826 padding: 9px;
5827 border-radius: 1px;
5828 }
5829 .close {
5830 float: right;
5831 font-size: 19.5px;
5832 font-weight: bold;
5833 line-height: 1;
5834 color: #000;
5835 text-shadow: 0 1px 0 #fff;
5836 opacity: 0.2;
5837 filter: alpha(opacity=20);
5838 }
5839 .close:hover,
5840 .close:focus {
5841 color: #000;
5842 text-decoration: none;
5843 cursor: pointer;
5844 opacity: 0.5;
5845 filter: alpha(opacity=50);
5846 }
5847 button.close {
5848 padding: 0;
5849 cursor: pointer;
5850 background: transparent;
5851 border: 0;
5852 -webkit-appearance: none;
5853 }
5854 .modal-open {
5855 overflow: hidden;
5856 }
5857 .modal {
5858 display: none;
5859 overflow: hidden;
5860 position: fixed;
5861 top: 0;
5862 right: 0;
5863 bottom: 0;
5864 left: 0;
5865 z-index: 1050;
5866 -webkit-overflow-scrolling: touch;
5867 outline: 0;
5868 }
5869 .modal.fade .modal-dialog {
5870 -webkit-transform: translate(0, -25%);
5871 -ms-transform: translate(0, -25%);
5872 -o-transform: translate(0, -25%);
5873 transform: translate(0, -25%);
5874 -webkit-transition: -webkit-transform 0.3s ease-out;
5875 -moz-transition: -moz-transform 0.3s ease-out;
5876 -o-transition: -o-transform 0.3s ease-out;
5877 transition: transform 0.3s ease-out;
5878 }
5879 .modal.in .modal-dialog {
5880 -webkit-transform: translate(0, 0);
5881 -ms-transform: translate(0, 0);
5882 -o-transform: translate(0, 0);
5883 transform: translate(0, 0);
5884 }
5885 .modal-open .modal {
5886 overflow-x: hidden;
5887 overflow-y: auto;
5888 }
5889 .modal-dialog {
5890 position: relative;
5891 width: auto;
5892 margin: 10px;
5893 }
5894 .modal-content {
5895 position: relative;
5896 background-color: #fff;
5897 border: 1px solid #999;
5898 border: 1px solid rgba(0, 0, 0, 0.2);
5899 border-radius: 3px;
5900 -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
5901 box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
5902 background-clip: padding-box;
5903 outline: 0;
5904 }
5905 .modal-backdrop {
5906 position: fixed;
5907 top: 0;
5908 right: 0;
5909 bottom: 0;
5910 left: 0;
5911 z-index: 1040;
5912 background-color: #000;
5913 }
5914 .modal-backdrop.fade {
5915 opacity: 0;
5916 filter: alpha(opacity=0);
5917 }
5918 .modal-backdrop.in {
5919 opacity: 0.5;
5920 filter: alpha(opacity=50);
5921 }
5922 .modal-header {
5923 padding: 15px;
5924 border-bottom: 1px solid #e5e5e5;
5925 }
5926 .modal-header .close {
5927 margin-top: -2px;
5928 }
5929 .modal-title {
5930 margin: 0;
5931 line-height: 1.42857143;
5932 }
5933 .modal-body {
5934 position: relative;
5935 padding: 15px;
5936 }
5937 .modal-footer {
5938 padding: 15px;
5939 text-align: right;
5940 border-top: 1px solid #e5e5e5;
5941 }
5942 .modal-footer .btn + .btn {
5943 margin-left: 5px;
5944 margin-bottom: 0;
5945 }
5946 .modal-footer .btn-group .btn + .btn {
5947 margin-left: -1px;
5948 }
5949 .modal-footer .btn-block + .btn-block {
5950 margin-left: 0;
5951 }
5952 .modal-scrollbar-measure {
5953 position: absolute;
5954 top: -9999px;
5955 width: 50px;
5956 height: 50px;
5957 overflow: scroll;
5958 }
5959 @media (min-width: 768px) {
5960 .modal-dialog {
5961 width: 600px;
5962 margin: 30px auto;
5963 }
5964 .modal-content {
5965 -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
5966 box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
5967 }
5968 .modal-sm {
5969 width: 300px;
5970 }
5971 }
5972 @media (min-width: 992px) {
5973 .modal-lg {
5974 width: 900px;
5975 }
5976 }
5977 .tooltip {
5978 position: absolute;
5979 z-index: 1070;
5980 display: block;
5981 font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
5982 font-style: normal;
5983 font-weight: normal;
5984 letter-spacing: normal;
5985 line-break: auto;
5986 line-height: 1.42857143;
5987 text-align: left;
5988 text-align: start;
5989 text-decoration: none;
5990 text-shadow: none;
5991 text-transform: none;
5992 white-space: normal;
5993 word-break: normal;
5994 word-spacing: normal;
5995 word-wrap: normal;
5996 font-size: 12px;
5997 opacity: 0;
5998 filter: alpha(opacity=0);
5999 }
6000 .tooltip.in {
6001 opacity: 0.9;
6002 filter: alpha(opacity=90);
6003 }
6004 .tooltip.top {
6005 margin-top: -3px;
6006 padding: 5px 0;
6007 }
6008 .tooltip.right {
6009 margin-left: 3px;
6010 padding: 0 5px;
6011 }
6012 .tooltip.bottom {
6013 margin-top: 3px;
6014 padding: 5px 0;
6015 }
6016 .tooltip.left {
6017 margin-left: -3px;
6018 padding: 0 5px;
6019 }
6020 .tooltip-inner {
6021 max-width: 200px;
6022 padding: 3px 8px;
6023 color: #fff;
6024 text-align: center;
6025 background-color: #000;
6026 border-radius: 2px;
6027 }
6028 .tooltip-arrow {
6029 position: absolute;
6030 width: 0;
6031 height: 0;
6032 border-color: transparent;
6033 border-style: solid;
6034 }
6035 .tooltip.top .tooltip-arrow {
6036 bottom: 0;
6037 left: 50%;
6038 margin-left: -5px;
6039 border-width: 5px 5px 0;
6040 border-top-color: #000;
6041 }
6042 .tooltip.top-left .tooltip-arrow {
6043 bottom: 0;
6044 right: 5px;
6045 margin-bottom: -5px;
6046 border-width: 5px 5px 0;
6047 border-top-color: #000;
6048 }
6049 .tooltip.top-right .tooltip-arrow {
6050 bottom: 0;
6051 left: 5px;
6052 margin-bottom: -5px;
6053 border-width: 5px 5px 0;
6054 border-top-color: #000;
6055 }
6056 .tooltip.right .tooltip-arrow {
6057 top: 50%;
6058 left: 0;
6059 margin-top: -5px;
6060 border-width: 5px 5px 5px 0;
6061 border-right-color: #000;
6062 }
6063 .tooltip.left .tooltip-arrow {
6064 top: 50%;
6065 right: 0;
6066 margin-top: -5px;
6067 border-width: 5px 0 5px 5px;
6068 border-left-color: #000;
6069 }
6070 .tooltip.bottom .tooltip-arrow {
6071 top: 0;
6072 left: 50%;
6073 margin-left: -5px;
6074 border-width: 0 5px 5px;
6075 border-bottom-color: #000;
6076 }
6077 .tooltip.bottom-left .tooltip-arrow {
6078 top: 0;
6079 right: 5px;
6080 margin-top: -5px;
6081 border-width: 0 5px 5px;
6082 border-bottom-color: #000;
6083 }
6084 .tooltip.bottom-right .tooltip-arrow {
6085 top: 0;
6086 left: 5px;
6087 margin-top: -5px;
6088 border-width: 0 5px 5px;
6089 border-bottom-color: #000;
6090 }
6091 .popover {
6092 position: absolute;
6093 top: 0;
6094 left: 0;
6095 z-index: 1060;
6096 display: none;
6097 max-width: 276px;
6098 padding: 1px;
6099 font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
6100 font-style: normal;
6101 font-weight: normal;
6102 letter-spacing: normal;
6103 line-break: auto;
6104 line-height: 1.42857143;
6105 text-align: left;
6106 text-align: start;
6107 text-decoration: none;
6108 text-shadow: none;
6109 text-transform: none;
6110 white-space: normal;
6111 word-break: normal;
6112 word-spacing: normal;
6113 word-wrap: normal;
6114 font-size: 13px;
6115 background-color: #fff;
6116 background-clip: padding-box;
6117 border: 1px solid #ccc;
6118 border: 1px solid rgba(0, 0, 0, 0.2);
6119 border-radius: 3px;
6120 -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
6121 box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
6122 }
6123 .popover.top {
6124 margin-top: -10px;
6125 }
6126 .popover.right {
6127 margin-left: 10px;
6128 }
6129 .popover.bottom {
6130 margin-top: 10px;
6131 }
6132 .popover.left {
6133 margin-left: -10px;
6134 }
6135 .popover-title {
6136 margin: 0;
6137 padding: 8px 14px;
6138 font-size: 13px;
6139 background-color: #f7f7f7;
6140 border-bottom: 1px solid #ebebeb;
6141 border-radius: 2px 2px 0 0;
6142 }
6143 .popover-content {
6144 padding: 9px 14px;
6145 }
6146 .popover > .arrow,
6147 .popover > .arrow:after {
6148 position: absolute;
6149 display: block;
6150 width: 0;
6151 height: 0;
6152 border-color: transparent;
6153 border-style: solid;
6154 }
6155 .popover > .arrow {
6156 border-width: 11px;
6157 }
6158 .popover > .arrow:after {
6159 border-width: 10px;
6160 content: "";
6161 }
6162 .popover.top > .arrow {
6163 left: 50%;
6164 margin-left: -11px;
6165 border-bottom-width: 0;
6166 border-top-color: #999999;
6167 border-top-color: rgba(0, 0, 0, 0.25);
6168 bottom: -11px;
6169 }
6170 .popover.top > .arrow:after {
6171 content: " ";
6172 bottom: 1px;
6173 margin-left: -10px;
6174 border-bottom-width: 0;
6175 border-top-color: #fff;
6176 }
6177 .popover.right > .arrow {
6178 top: 50%;
6179 left: -11px;
6180 margin-top: -11px;
6181 border-left-width: 0;
6182 border-right-color: #999999;
6183 border-right-color: rgba(0, 0, 0, 0.25);
6184 }
6185 .popover.right > .arrow:after {
6186 content: " ";
6187 left: 1px;
6188 bottom: -10px;
6189 border-left-width: 0;
6190 border-right-color: #fff;
6191 }
6192 .popover.bottom > .arrow {
6193 left: 50%;
6194 margin-left: -11px;
6195 border-top-width: 0;
6196 border-bottom-color: #999999;
6197 border-bottom-color: rgba(0, 0, 0, 0.25);
6198 top: -11px;
6199 }
6200 .popover.bottom > .arrow:after {
6201 content: " ";
6202 top: 1px;
6203 margin-left: -10px;
6204 border-top-width: 0;
6205 border-bottom-color: #fff;
6206 }
6207 .popover.left > .arrow {
6208 top: 50%;
6209 right: -11px;
6210 margin-top: -11px;
6211 border-right-width: 0;
6212 border-left-color: #999999;
6213 border-left-color: rgba(0, 0, 0, 0.25);
6214 }
6215 .popover.left > .arrow:after {
6216 content: " ";
6217 right: 1px;
6218 border-right-width: 0;
6219 border-left-color: #fff;
6220 bottom: -10px;
6221 }
6222 .carousel {
6223 position: relative;
6224 }
6225 .carousel-inner {
6226 position: relative;
6227 overflow: hidden;
6228 width: 100%;
6229 }
6230 .carousel-inner > .item {
6231 display: none;
6232 position: relative;
6233 -webkit-transition: 0.6s ease-in-out left;
6234 -o-transition: 0.6s ease-in-out left;
6235 transition: 0.6s ease-in-out left;
6236 }
6237 .carousel-inner > .item > img,
6238 .carousel-inner > .item > a > img {
6239 line-height: 1;
6240 }
6241 @media all and (transform-3d), (-webkit-transform-3d) {
6242 .carousel-inner > .item {
6243 -webkit-transition: -webkit-transform 0.6s ease-in-out;
6244 -moz-transition: -moz-transform 0.6s ease-in-out;
6245 -o-transition: -o-transform 0.6s ease-in-out;
6246 transition: transform 0.6s ease-in-out;
6247 -webkit-backface-visibility: hidden;
6248 -moz-backface-visibility: hidden;
6249 backface-visibility: hidden;
6250 -webkit-perspective: 1000px;
6251 -moz-perspective: 1000px;
6252 perspective: 1000px;
6253 }
6254 .carousel-inner > .item.next,
6255 .carousel-inner > .item.active.right {
6256 -webkit-transform: translate3d(100%, 0, 0);
6257 transform: translate3d(100%, 0, 0);
6258 left: 0;
6259 }
6260 .carousel-inner > .item.prev,
6261 .carousel-inner > .item.active.left {
6262 -webkit-transform: translate3d(-100%, 0, 0);
6263 transform: translate3d(-100%, 0, 0);
6264 left: 0;
6265 }
6266 .carousel-inner > .item.next.left,
6267 .carousel-inner > .item.prev.right,
6268 .carousel-inner > .item.active {
6269 -webkit-transform: translate3d(0, 0, 0);
6270 transform: translate3d(0, 0, 0);
6271 left: 0;
6272 }
6273 }
6274 .carousel-inner > .active,
6275 .carousel-inner > .next,
6276 .carousel-inner > .prev {
6277 display: block;
6278 }
6279 .carousel-inner > .active {
6280 left: 0;
6281 }
6282 .carousel-inner > .next,
6283 .carousel-inner > .prev {
6284 position: absolute;
6285 top: 0;
6286 width: 100%;
6287 }
6288 .carousel-inner > .next {
6289 left: 100%;
6290 }
6291 .carousel-inner > .prev {
6292 left: -100%;
6293 }
6294 .carousel-inner > .next.left,
6295 .carousel-inner > .prev.right {
6296 left: 0;
6297 }
6298 .carousel-inner > .active.left {
6299 left: -100%;
6300 }
6301 .carousel-inner > .active.right {
6302 left: 100%;
6303 }
6304 .carousel-control {
6305 position: absolute;
6306 top: 0;
6307 left: 0;
6308 bottom: 0;
6309 width: 15%;
6310 opacity: 0.5;
6311 filter: alpha(opacity=50);
6312 font-size: 20px;
6313 color: #fff;
6314 text-align: center;
6315 text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
6316 background-color: rgba(0, 0, 0, 0);
6317 }
6318 .carousel-control.left {
6319 background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
6320 background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
6321 background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
6322 background-repeat: repeat-x;
6323 filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
6324 }
6325 .carousel-control.right {
6326 left: auto;
6327 right: 0;
6328 background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
6329 background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
6330 background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
6331 background-repeat: repeat-x;
6332 filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
6333 }
6334 .carousel-control:hover,
6335 .carousel-control:focus {
6336 outline: 0;
6337 color: #fff;
6338 text-decoration: none;
6339 opacity: 0.9;
6340 filter: alpha(opacity=90);
6341 }
6342 .carousel-control .icon-prev,
6343 .carousel-control .icon-next,
6344 .carousel-control .glyphicon-chevron-left,
6345 .carousel-control .glyphicon-chevron-right {
6346 position: absolute;
6347 top: 50%;
6348 margin-top: -10px;
6349 z-index: 5;
6350 display: inline-block;
6351 }
6352 .carousel-control .icon-prev,
6353 .carousel-control .glyphicon-chevron-left {
6354 left: 50%;
6355 margin-left: -10px;
6356 }
6357 .carousel-control .icon-next,
6358 .carousel-control .glyphicon-chevron-right {
6359 right: 50%;
6360 margin-right: -10px;
6361 }
6362 .carousel-control .icon-prev,
6363 .carousel-control .icon-next {
6364 width: 20px;
6365 height: 20px;
6366 line-height: 1;
6367 font-family: serif;
6368 }
6369 .carousel-control .icon-prev:before {
6370 content: '\2039';
6371 }
6372 .carousel-control .icon-next:before {
6373 content: '\203a';
6374 }
6375 .carousel-indicators {
6376 position: absolute;
6377 bottom: 10px;
6378 left: 50%;
6379 z-index: 15;
6380 width: 60%;
6381 margin-left: -30%;
6382 padding-left: 0;
6383 list-style: none;
6384 text-align: center;
6385 }
6386 .carousel-indicators li {
6387 display: inline-block;
6388 width: 10px;
6389 height: 10px;
6390 margin: 1px;
6391 text-indent: -999px;
6392 border: 1px solid #fff;
6393 border-radius: 10px;
6394 cursor: pointer;
6395 background-color: #000 \9;
6396 background-color: rgba(0, 0, 0, 0);
6397 }
6398 .carousel-indicators .active {
6399 margin: 0;
6400 width: 12px;
6401 height: 12px;
6402 background-color: #fff;
6403 }
6404 .carousel-caption {
6405 position: absolute;
6406 left: 15%;
6407 right: 15%;
6408 bottom: 20px;
6409 z-index: 10;
6410 padding-top: 20px;
6411 padding-bottom: 20px;
6412 color: #fff;
6413 text-align: center;
6414 text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
6415 }
6416 .carousel-caption .btn {
6417 text-shadow: none;
6418 }
6419 @media screen and (min-width: 768px) {
6420 .carousel-control .glyphicon-chevron-left,
6421 .carousel-control .glyphicon-chevron-right,
6422 .carousel-control .icon-prev,
6423 .carousel-control .icon-next {
6424 width: 30px;
6425 height: 30px;
6426 margin-top: -10px;
6427 font-size: 30px;
6428 }
6429 .carousel-control .glyphicon-chevron-left,
6430 .carousel-control .icon-prev {
6431 margin-left: -10px;
6432 }
6433 .carousel-control .glyphicon-chevron-right,
6434 .carousel-control .icon-next {
6435 margin-right: -10px;
6436 }
6437 .carousel-caption {
6438 left: 20%;
6439 right: 20%;
6440 padding-bottom: 30px;
6441 }
6442 .carousel-indicators {
6443 bottom: 20px;
6444 }
6445 }
6446 .clearfix:before,
6447 .clearfix:after,
6448 .dl-horizontal dd:before,
6449 .dl-horizontal dd:after,
6450 .container:before,
6451 .container:after,
6452 .container-fluid:before,
6453 .container-fluid:after,
6454 .row:before,
6455 .row:after,
6456 .form-horizontal .form-group:before,
6457 .form-horizontal .form-group:after,
6458 .btn-toolbar:before,
6459 .btn-toolbar:after,
6460 .btn-group-vertical > .btn-group:before,
6461 .btn-group-vertical > .btn-group:after,
6462 .nav:before,
6463 .nav:after,
6464 .navbar:before,
6465 .navbar:after,
6466 .navbar-header:before,
6467 .navbar-header:after,
6468 .navbar-collapse:before,
6469 .navbar-collapse:after,
6470 .pager:before,
6471 .pager:after,
6472 .panel-body:before,
6473 .panel-body:after,
6474 .modal-header:before,
6475 .modal-header:after,
6476 .modal-footer:before,
6477 .modal-footer:after,
6478 .item_buttons:before,
6479 .item_buttons:after {
6480 content: " ";
6481 display: table;
6482 }
6483 .clearfix:after,
6484 .dl-horizontal dd:after,
6485 .container:after,
6486 .container-fluid:after,
6487 .row:after,
6488 .form-horizontal .form-group:after,
6489 .btn-toolbar:after,
6490 .btn-group-vertical > .btn-group:after,
6491 .nav:after,
6492 .navbar:after,
6493 .navbar-header:after,
6494 .navbar-collapse:after,
6495 .pager:after,
6496 .panel-body:after,
6497 .modal-header:after,
6498 .modal-footer:after,
6499 .item_buttons:after {
6500 clear: both;
6501 }
6502 .center-block {
6503 display: block;
6504 margin-left: auto;
6505 margin-right: auto;
6506 }
6507 .pull-right {
6508 float: right !important;
6509 }
6510 .pull-left {
6511 float: left !important;
6512 }
6513 .hide {
6514 display: none !important;
6515 }
6516 .show {
6517 display: block !important;
6518 }
6519 .invisible {
6520 visibility: hidden;
6521 }
6522 .text-hide {
6523 font: 0/0 a;
6524 color: transparent;
6525 text-shadow: none;
6526 background-color: transparent;
6527 border: 0;
6528 }
6529 .hidden {
6530 display: none !important;
6531 }
6532 .affix {
6533 position: fixed;
6534 }
6535 @-ms-viewport {
6536 width: device-width;
6537 }
6538 .visible-xs,
6539 .visible-sm,
6540 .visible-md,
6541 .visible-lg {
6542 display: none !important;
6543 }
6544 .visible-xs-block,
6545 .visible-xs-inline,
6546 .visible-xs-inline-block,
6547 .visible-sm-block,
6548 .visible-sm-inline,
6549 .visible-sm-inline-block,
6550 .visible-md-block,
6551 .visible-md-inline,
6552 .visible-md-inline-block,
6553 .visible-lg-block,
6554 .visible-lg-inline,
6555 .visible-lg-inline-block {
6556 display: none !important;
6557 }
6558 @media (max-width: 767px) {
6559 .visible-xs {
6560 display: block !important;
6561 }
6562 table.visible-xs {
6563 display: table !important;
6564 }
6565 tr.visible-xs {
6566 display: table-row !important;
6567 }
6568 th.visible-xs,
6569 td.visible-xs {
6570 display: table-cell !important;
6571 }
6572 }
6573 @media (max-width: 767px) {
6574 .visible-xs-block {
6575 display: block !important;
6576 }
6577 }
6578 @media (max-width: 767px) {
6579 .visible-xs-inline {
6580 display: inline !important;
6581 }
6582 }
6583 @media (max-width: 767px) {
6584 .visible-xs-inline-block {
6585 display: inline-block !important;
6586 }
6587 }
6588 @media (min-width: 768px) and (max-width: 991px) {
6589 .visible-sm {
6590 display: block !important;
6591 }
6592 table.visible-sm {
6593 display: table !important;
6594 }
6595 tr.visible-sm {
6596 display: table-row !important;
6597 }
6598 th.visible-sm,
6599 td.visible-sm {
6600 display: table-cell !important;
6601 }
6602 }
6603 @media (min-width: 768px) and (max-width: 991px) {
6604 .visible-sm-block {
6605 display: block !important;
6606 }
6607 }
6608 @media (min-width: 768px) and (max-width: 991px) {
6609 .visible-sm-inline {
6610 display: inline !important;
6611 }
6612 }
6613 @media (min-width: 768px) and (max-width: 991px) {
6614 .visible-sm-inline-block {
6615 display: inline-block !important;
6616 }
6617 }
6618 @media (min-width: 992px) and (max-width: 1199px) {
6619 .visible-md {
6620 display: block !important;
6621 }
6622 table.visible-md {
6623 display: table !important;
6624 }
6625 tr.visible-md {
6626 display: table-row !important;
6627 }
6628 th.visible-md,
6629 td.visible-md {
6630 display: table-cell !important;
6631 }
6632 }
6633 @media (min-width: 992px) and (max-width: 1199px) {
6634 .visible-md-block {
6635 display: block !important;
6636 }
6637 }
6638 @media (min-width: 992px) and (max-width: 1199px) {
6639 .visible-md-inline {
6640 display: inline !important;
6641 }
6642 }
6643 @media (min-width: 992px) and (max-width: 1199px) {
6644 .visible-md-inline-block {
6645 display: inline-block !important;
6646 }
6647 }
6648 @media (min-width: 1200px) {
6649 .visible-lg {
6650 display: block !important;
6651 }
6652 table.visible-lg {
6653 display: table !important;
6654 }
6655 tr.visible-lg {
6656 display: table-row !important;
6657 }
6658 th.visible-lg,
6659 td.visible-lg {
6660 display: table-cell !important;
6661 }
6662 }
6663 @media (min-width: 1200px) {
6664 .visible-lg-block {
6665 display: block !important;
6666 }
6667 }
6668 @media (min-width: 1200px) {
6669 .visible-lg-inline {
6670 display: inline !important;
6671 }
6672 }
6673 @media (min-width: 1200px) {
6674 .visible-lg-inline-block {
6675 display: inline-block !important;
6676 }
6677 }
6678 @media (max-width: 767px) {
6679 .hidden-xs {
6680 display: none !important;
6681 }
6682 }
6683 @media (min-width: 768px) and (max-width: 991px) {
6684 .hidden-sm {
6685 display: none !important;
6686 }
6687 }
6688 @media (min-width: 992px) and (max-width: 1199px) {
6689 .hidden-md {
6690 display: none !important;
6691 }
6692 }
6693 @media (min-width: 1200px) {
6694 .hidden-lg {
6695 display: none !important;
6696 }
6697 }
6698 .visible-print {
6699 display: none !important;
6700 }
6701 @media print {
6702 .visible-print {
6703 display: block !important;
6704 }
6705 table.visible-print {
6706 display: table !important;
6707 }
6708 tr.visible-print {
6709 display: table-row !important;
6710 }
6711 th.visible-print,
6712 td.visible-print {
6713 display: table-cell !important;
6714 }
6715 }
6716 .visible-print-block {
6717 display: none !important;
6718 }
6719 @media print {
6720 .visible-print-block {
6721 display: block !important;
6722 }
6723 }
6724 .visible-print-inline {
6725 display: none !important;
6726 }
6727 @media print {
6728 .visible-print-inline {
6729 display: inline !important;
6730 }
6731 }
6732 .visible-print-inline-block {
6733 display: none !important;
6734 }
6735 @media print {
6736 .visible-print-inline-block {
6737 display: inline-block !important;
6738 }
6739 }
6740 @media print {
6741 .hidden-print {
6742 display: none !important;
6743 }
6744 }
6745 /*!
6746 *
6747 * Font Awesome
6748 *
6749 */
6750 /*!
6751 * Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
6752 * License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
6753 */
6754 /* FONT PATH
6755 * -------------------------- */
6756 @font-face {
6757 font-family: 'FontAwesome';
6758 src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
6759 src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
6760 font-weight: normal;
6761 font-style: normal;
6762 }
6763 .fa {
6764 display: inline-block;
6765 font: normal normal normal 14px/1 FontAwesome;
6766 font-size: inherit;
6767 text-rendering: auto;
6768 -webkit-font-smoothing: antialiased;
6769 -moz-osx-font-smoothing: grayscale;
6770 }
6771 /* makes the font 33% larger relative to the icon container */
6772 .fa-lg {
6773 font-size: 1.33333333em;
6774 line-height: 0.75em;
6775 vertical-align: -15%;
6776 }
6777 .fa-2x {
6778 font-size: 2em;
6779 }
6780 .fa-3x {
6781 font-size: 3em;
6782 }
6783 .fa-4x {
6784 font-size: 4em;
6785 }
6786 .fa-5x {
6787 font-size: 5em;
6788 }
6789 .fa-fw {
6790 width: 1.28571429em;
6791 text-align: center;
6792 }
6793 .fa-ul {
6794 padding-left: 0;
6795 margin-left: 2.14285714em;
6796 list-style-type: none;
6797 }
6798 .fa-ul > li {
6799 position: relative;
6800 }
6801 .fa-li {
6802 position: absolute;
6803 left: -2.14285714em;
6804 width: 2.14285714em;
6805 top: 0.14285714em;
6806 text-align: center;
6807 }
6808 .fa-li.fa-lg {
6809 left: -1.85714286em;
6810 }
6811 .fa-border {
6812 padding: .2em .25em .15em;
6813 border: solid 0.08em #eee;
6814 border-radius: .1em;
6815 }
6816 .pull-right {
6817 float: right;
6818 }
6819 .pull-left {
6820 float: left;
6821 }
6822 .fa.pull-left {
6823 margin-right: .3em;
6824 }
6825 .fa.pull-right {
6826 margin-left: .3em;
6827 }
6828 .fa-spin {
6829 -webkit-animation: fa-spin 2s infinite linear;
6830 animation: fa-spin 2s infinite linear;
6831 }
6832 @-webkit-keyframes fa-spin {
6833 0% {
6834 -webkit-transform: rotate(0deg);
6835 transform: rotate(0deg);
6836 }
6837 100% {
6838 -webkit-transform: rotate(359deg);
6839 transform: rotate(359deg);
6840 }
6841 }
6842 @keyframes fa-spin {
6843 0% {
6844 -webkit-transform: rotate(0deg);
6845 transform: rotate(0deg);
6846 }
6847 100% {
6848 -webkit-transform: rotate(359deg);
6849 transform: rotate(359deg);
6850 }
6851 }
6852 .fa-rotate-90 {
6853 filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
6854 -webkit-transform: rotate(90deg);
6855 -ms-transform: rotate(90deg);
6856 transform: rotate(90deg);
6857 }
6858 .fa-rotate-180 {
6859 filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
6860 -webkit-transform: rotate(180deg);
6861 -ms-transform: rotate(180deg);
6862 transform: rotate(180deg);
6863 }
6864 .fa-rotate-270 {
6865 filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
6866 -webkit-transform: rotate(270deg);
6867 -ms-transform: rotate(270deg);
6868 transform: rotate(270deg);
6869 }
6870 .fa-flip-horizontal {
6871 filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
6872 -webkit-transform: scale(-1, 1);
6873 -ms-transform: scale(-1, 1);
6874 transform: scale(-1, 1);
6875 }
6876 .fa-flip-vertical {
6877 filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
6878 -webkit-transform: scale(1, -1);
6879 -ms-transform: scale(1, -1);
6880 transform: scale(1, -1);
6881 }
6882 :root .fa-rotate-90,
6883 :root .fa-rotate-180,
6884 :root .fa-rotate-270,
6885 :root .fa-flip-horizontal,
6886 :root .fa-flip-vertical {
6887 filter: none;
6888 }
6889 .fa-stack {
6890 position: relative;
6891 display: inline-block;
6892 width: 2em;
6893 height: 2em;
6894 line-height: 2em;
6895 vertical-align: middle;
6896 }
6897 .fa-stack-1x,
6898 .fa-stack-2x {
6899 position: absolute;
6900 left: 0;
6901 width: 100%;
6902 text-align: center;
6903 }
6904 .fa-stack-1x {
6905 line-height: inherit;
6906 }
6907 .fa-stack-2x {
6908 font-size: 2em;
6909 }
6910 .fa-inverse {
6911 color: #fff;
6912 }
6913 /* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
6914 readers do not read off random characters that represent icons */
6915 .fa-glass:before {
6916 content: "\f000";
6917 }
6918 .fa-music:before {
6919 content: "\f001";
6920 }
6921 .fa-search:before {
6922 content: "\f002";
6923 }
6924 .fa-envelope-o:before {
6925 content: "\f003";
6926 }
6927 .fa-heart:before {
6928 content: "\f004";
6929 }
6930 .fa-star:before {
6931 content: "\f005";
6932 }
6933 .fa-star-o:before {
6934 content: "\f006";
6935 }
6936 .fa-user:before {
6937 content: "\f007";
6938 }
6939 .fa-film:before {
6940 content: "\f008";
6941 }
6942 .fa-th-large:before {
6943 content: "\f009";
6944 }
6945 .fa-th:before {
6946 content: "\f00a";
6947 }
6948 .fa-th-list:before {
6949 content: "\f00b";
6950 }
6951 .fa-check:before {
6952 content: "\f00c";
6953 }
6954 .fa-remove:before,
6955 .fa-close:before,
6956 .fa-times:before {
6957 content: "\f00d";
6958 }
6959 .fa-search-plus:before {
6960 content: "\f00e";
6961 }
6962 .fa-search-minus:before {
6963 content: "\f010";
6964 }
6965 .fa-power-off:before {
6966 content: "\f011";
6967 }
6968 .fa-signal:before {
6969 content: "\f012";
6970 }
6971 .fa-gear:before,
6972 .fa-cog:before {
6973 content: "\f013";
6974 }
6975 .fa-trash-o:before {
6976 content: "\f014";
6977 }
6978 .fa-home:before {
6979 content: "\f015";
6980 }
6981 .fa-file-o:before {
6982 content: "\f016";
6983 }
6984 .fa-clock-o:before {
6985 content: "\f017";
6986 }
6987 .fa-road:before {
6988 content: "\f018";
6989 }
6990 .fa-download:before {
6991 content: "\f019";
6992 }
6993 .fa-arrow-circle-o-down:before {
6994 content: "\f01a";
6995 }
6996 .fa-arrow-circle-o-up:before {
6997 content: "\f01b";
6998 }
6999 .fa-inbox:before {
7000 content: "\f01c";
7001 }
7002 .fa-play-circle-o:before {
7003 content: "\f01d";
7004 }
7005 .fa-rotate-right:before,
7006 .fa-repeat:before {
7007 content: "\f01e";
7008 }
7009 .fa-refresh:before {
7010 content: "\f021";
7011 }
7012 .fa-list-alt:before {
7013 content: "\f022";
7014 }
7015 .fa-lock:before {
7016 content: "\f023";
7017 }
7018 .fa-flag:before {
7019 content: "\f024";
7020 }
7021 .fa-headphones:before {
7022 content: "\f025";
7023 }
7024 .fa-volume-off:before {
7025 content: "\f026";
7026 }
7027 .fa-volume-down:before {
7028 content: "\f027";
7029 }
7030 .fa-volume-up:before {
7031 content: "\f028";
7032 }
7033 .fa-qrcode:before {
7034 content: "\f029";
7035 }
7036 .fa-barcode:before {
7037 content: "\f02a";
7038 }
7039 .fa-tag:before {
7040 content: "\f02b";
7041 }
7042 .fa-tags:before {
7043 content: "\f02c";
7044 }
7045 .fa-book:before {
7046 content: "\f02d";
7047 }
7048 .fa-bookmark:before {
7049 content: "\f02e";
7050 }
7051 .fa-print:before {
7052 content: "\f02f";
7053 }
7054 .fa-camera:before {
7055 content: "\f030";
7056 }
7057 .fa-font:before {
7058 content: "\f031";
7059 }
7060 .fa-bold:before {
7061 content: "\f032";
7062 }
7063 .fa-italic:before {
7064 content: "\f033";
7065 }
7066 .fa-text-height:before {
7067 content: "\f034";
7068 }
7069 .fa-text-width:before {
7070 content: "\f035";
7071 }
7072 .fa-align-left:before {
7073 content: "\f036";
7074 }
7075 .fa-align-center:before {
7076 content: "\f037";
7077 }
7078 .fa-align-right:before {
7079 content: "\f038";
7080 }
7081 .fa-align-justify:before {
7082 content: "\f039";
7083 }
7084 .fa-list:before {
7085 content: "\f03a";
7086 }
7087 .fa-dedent:before,
7088 .fa-outdent:before {
7089 content: "\f03b";
7090 }
7091 .fa-indent:before {
7092 content: "\f03c";
7093 }
7094 .fa-video-camera:before {
7095 content: "\f03d";
7096 }
7097 .fa-photo:before,
7098 .fa-image:before,
7099 .fa-picture-o:before {
7100 content: "\f03e";
7101 }
7102 .fa-pencil:before {
7103 content: "\f040";
7104 }
7105 .fa-map-marker:before {
7106 content: "\f041";
7107 }
7108 .fa-adjust:before {
7109 content: "\f042";
7110 }
7111 .fa-tint:before {
7112 content: "\f043";
7113 }
7114 .fa-edit:before,
7115 .fa-pencil-square-o:before {
7116 content: "\f044";
7117 }
7118 .fa-share-square-o:before {
7119 content: "\f045";
7120 }
7121 .fa-check-square-o:before {
7122 content: "\f046";
7123 }
7124 .fa-arrows:before {
7125 content: "\f047";
7126 }
7127 .fa-step-backward:before {
7128 content: "\f048";
7129 }
7130 .fa-fast-backward:before {
7131 content: "\f049";
7132 }
7133 .fa-backward:before {
7134 content: "\f04a";
7135 }
7136 .fa-play:before {
7137 content: "\f04b";
7138 }
7139 .fa-pause:before {
7140 content: "\f04c";
7141 }
7142 .fa-stop:before {
7143 content: "\f04d";
7144 }
7145 .fa-forward:before {
7146 content: "\f04e";
7147 }
7148 .fa-fast-forward:before {
7149 content: "\f050";
7150 }
7151 .fa-step-forward:before {
7152 content: "\f051";
7153 }
7154 .fa-eject:before {
7155 content: "\f052";
7156 }
7157 .fa-chevron-left:before {
7158 content: "\f053";
7159 }
7160 .fa-chevron-right:before {
7161 content: "\f054";
7162 }
7163 .fa-plus-circle:before {
7164 content: "\f055";
7165 }
7166 .fa-minus-circle:before {
7167 content: "\f056";
7168 }
7169 .fa-times-circle:before {
7170 content: "\f057";
7171 }
7172 .fa-check-circle:before {
7173 content: "\f058";
7174 }
7175 .fa-question-circle:before {
7176 content: "\f059";
7177 }
7178 .fa-info-circle:before {
7179 content: "\f05a";
7180 }
7181 .fa-crosshairs:before {
7182 content: "\f05b";
7183 }
7184 .fa-times-circle-o:before {
7185 content: "\f05c";
7186 }
7187 .fa-check-circle-o:before {
7188 content: "\f05d";
7189 }
7190 .fa-ban:before {
7191 content: "\f05e";
7192 }
7193 .fa-arrow-left:before {
7194 content: "\f060";
7195 }
7196 .fa-arrow-right:before {
7197 content: "\f061";
7198 }
7199 .fa-arrow-up:before {
7200 content: "\f062";
7201 }
7202 .fa-arrow-down:before {
7203 content: "\f063";
7204 }
7205 .fa-mail-forward:before,
7206 .fa-share:before {
7207 content: "\f064";
7208 }
7209 .fa-expand:before {
7210 content: "\f065";
7211 }
7212 .fa-compress:before {
7213 content: "\f066";
7214 }
7215 .fa-plus:before {
7216 content: "\f067";
7217 }
7218 .fa-minus:before {
7219 content: "\f068";
7220 }
7221 .fa-asterisk:before {
7222 content: "\f069";
7223 }
7224 .fa-exclamation-circle:before {
7225 content: "\f06a";
7226 }
7227 .fa-gift:before {
7228 content: "\f06b";
7229 }
7230 .fa-leaf:before {
7231 content: "\f06c";
7232 }
7233 .fa-fire:before {
7234 content: "\f06d";
7235 }
7236 .fa-eye:before {
7237 content: "\f06e";
7238 }
7239 .fa-eye-slash:before {
7240 content: "\f070";
7241 }
7242 .fa-warning:before,
7243 .fa-exclamation-triangle:before {
7244 content: "\f071";
7245 }
7246 .fa-plane:before {
7247 content: "\f072";
7248 }
7249 .fa-calendar:before {
7250 content: "\f073";
7251 }
7252 .fa-random:before {
7253 content: "\f074";
7254 }
7255 .fa-comment:before {
7256 content: "\f075";
7257 }
7258 .fa-magnet:before {
7259 content: "\f076";
7260 }
7261 .fa-chevron-up:before {
7262 content: "\f077";
7263 }
7264 .fa-chevron-down:before {
7265 content: "\f078";
7266 }
7267 .fa-retweet:before {
7268 content: "\f079";
7269 }
7270 .fa-shopping-cart:before {
7271 content: "\f07a";
7272 }
7273 .fa-folder:before {
7274 content: "\f07b";
7275 }
7276 .fa-folder-open:before {
7277 content: "\f07c";
7278 }
7279 .fa-arrows-v:before {
7280 content: "\f07d";
7281 }
7282 .fa-arrows-h:before {
7283 content: "\f07e";
7284 }
7285 .fa-bar-chart-o:before,
7286 .fa-bar-chart:before {
7287 content: "\f080";
7288 }
7289 .fa-twitter-square:before {
7290 content: "\f081";
7291 }
7292 .fa-facebook-square:before {
7293 content: "\f082";
7294 }
7295 .fa-camera-retro:before {
7296 content: "\f083";
7297 }
7298 .fa-key:before {
7299 content: "\f084";
7300 }
7301 .fa-gears:before,
7302 .fa-cogs:before {
7303 content: "\f085";
7304 }
7305 .fa-comments:before {
7306 content: "\f086";
7307 }
7308 .fa-thumbs-o-up:before {
7309 content: "\f087";
7310 }
7311 .fa-thumbs-o-down:before {
7312 content: "\f088";
7313 }
7314 .fa-star-half:before {
7315 content: "\f089";
7316 }
7317 .fa-heart-o:before {
7318 content: "\f08a";
7319 }
7320 .fa-sign-out:before {
7321 content: "\f08b";
7322 }
7323 .fa-linkedin-square:before {
7324 content: "\f08c";
7325 }
7326 .fa-thumb-tack:before {
7327 content: "\f08d";
7328 }
7329 .fa-external-link:before {
7330 content: "\f08e";
7331 }
7332 .fa-sign-in:before {
7333 content: "\f090";
7334 }
7335 .fa-trophy:before {
7336 content: "\f091";
7337 }
7338 .fa-github-square:before {
7339 content: "\f092";
7340 }
7341 .fa-upload:before {
7342 content: "\f093";
7343 }
7344 .fa-lemon-o:before {
7345 content: "\f094";
7346 }
7347 .fa-phone:before {
7348 content: "\f095";
7349 }
7350 .fa-square-o:before {
7351 content: "\f096";
7352 }
7353 .fa-bookmark-o:before {
7354 content: "\f097";
7355 }
7356 .fa-phone-square:before {
7357 content: "\f098";
7358 }
7359 .fa-twitter:before {
7360 content: "\f099";
7361 }
7362 .fa-facebook:before {
7363 content: "\f09a";
7364 }
7365 .fa-github:before {
7366 content: "\f09b";
7367 }
7368 .fa-unlock:before {
7369 content: "\f09c";
7370 }
7371 .fa-credit-card:before {
7372 content: "\f09d";
7373 }
7374 .fa-rss:before {
7375 content: "\f09e";
7376 }
7377 .fa-hdd-o:before {
7378 content: "\f0a0";
7379 }
7380 .fa-bullhorn:before {
7381 content: "\f0a1";
7382 }
7383 .fa-bell:before {
7384 content: "\f0f3";
7385 }
7386 .fa-certificate:before {
7387 content: "\f0a3";
7388 }
7389 .fa-hand-o-right:before {
7390 content: "\f0a4";
7391 }
7392 .fa-hand-o-left:before {
7393 content: "\f0a5";
7394 }
7395 .fa-hand-o-up:before {
7396 content: "\f0a6";
7397 }
7398 .fa-hand-o-down:before {
7399 content: "\f0a7";
7400 }
7401 .fa-arrow-circle-left:before {
7402 content: "\f0a8";
7403 }
7404 .fa-arrow-circle-right:before {
7405 content: "\f0a9";
7406 }
7407 .fa-arrow-circle-up:before {
7408 content: "\f0aa";
7409 }
7410 .fa-arrow-circle-down:before {
7411 content: "\f0ab";
7412 }
7413 .fa-globe:before {
7414 content: "\f0ac";
7415 }
7416 .fa-wrench:before {
7417 content: "\f0ad";
7418 }
7419 .fa-tasks:before {
7420 content: "\f0ae";
7421 }
7422 .fa-filter:before {
7423 content: "\f0b0";
7424 }
7425 .fa-briefcase:before {
7426 content: "\f0b1";
7427 }
7428 .fa-arrows-alt:before {
7429 content: "\f0b2";
7430 }
7431 .fa-group:before,
7432 .fa-users:before {
7433 content: "\f0c0";
7434 }
7435 .fa-chain:before,
7436 .fa-link:before {
7437 content: "\f0c1";
7438 }
7439 .fa-cloud:before {
7440 content: "\f0c2";
7441 }
7442 .fa-flask:before {
7443 content: "\f0c3";
7444 }
7445 .fa-cut:before,
7446 .fa-scissors:before {
7447 content: "\f0c4";
7448 }
7449 .fa-copy:before,
7450 .fa-files-o:before {
7451 content: "\f0c5";
7452 }
7453 .fa-paperclip:before {
7454 content: "\f0c6";
7455 }
7456 .fa-save:before,
7457 .fa-floppy-o:before {
7458 content: "\f0c7";
7459 }
7460 .fa-square:before {
7461 content: "\f0c8";
7462 }
7463 .fa-navicon:before,
7464 .fa-reorder:before,
7465 .fa-bars:before {
7466 content: "\f0c9";
7467 }
7468 .fa-list-ul:before {
7469 content: "\f0ca";
7470 }
7471 .fa-list-ol:before {
7472 content: "\f0cb";
7473 }
7474 .fa-strikethrough:before {
7475 content: "\f0cc";
7476 }
7477 .fa-underline:before {
7478 content: "\f0cd";
7479 }
7480 .fa-table:before {
7481 content: "\f0ce";
7482 }
7483 .fa-magic:before {
7484 content: "\f0d0";
7485 }
7486 .fa-truck:before {
7487 content: "\f0d1";
7488 }
7489 .fa-pinterest:before {
7490 content: "\f0d2";
7491 }
7492 .fa-pinterest-square:before {
7493 content: "\f0d3";
7494 }
7495 .fa-google-plus-square:before {
7496 content: "\f0d4";
7497 }
7498 .fa-google-plus:before {
7499 content: "\f0d5";
7500 }
7501 .fa-money:before {
7502 content: "\f0d6";
7503 }
7504 .fa-caret-down:before {
7505 content: "\f0d7";
7506 }
7507 .fa-caret-up:before {
7508 content: "\f0d8";
7509 }
7510 .fa-caret-left:before {
7511 content: "\f0d9";
7512 }
7513 .fa-caret-right:before {
7514 content: "\f0da";
7515 }
7516 .fa-columns:before {
7517 content: "\f0db";
7518 }
7519 .fa-unsorted:before,
7520 .fa-sort:before {
7521 content: "\f0dc";
7522 }
7523 .fa-sort-down:before,
7524 .fa-sort-desc:before {
7525 content: "\f0dd";
7526 }
7527 .fa-sort-up:before,
7528 .fa-sort-asc:before {
7529 content: "\f0de";
7530 }
7531 .fa-envelope:before {
7532 content: "\f0e0";
7533 }
7534 .fa-linkedin:before {
7535 content: "\f0e1";
7536 }
7537 .fa-rotate-left:before,
7538 .fa-undo:before {
7539 content: "\f0e2";
7540 }
7541 .fa-legal:before,
7542 .fa-gavel:before {
7543 content: "\f0e3";
7544 }
7545 .fa-dashboard:before,
7546 .fa-tachometer:before {
7547 content: "\f0e4";
7548 }
7549 .fa-comment-o:before {
7550 content: "\f0e5";
7551 }
7552 .fa-comments-o:before {
7553 content: "\f0e6";
7554 }
7555 .fa-flash:before,
7556 .fa-bolt:before {
7557 content: "\f0e7";
7558 }
7559 .fa-sitemap:before {
7560 content: "\f0e8";
7561 }
7562 .fa-umbrella:before {
7563 content: "\f0e9";
7564 }
7565 .fa-paste:before,
7566 .fa-clipboard:before {
7567 content: "\f0ea";
7568 }
7569 .fa-lightbulb-o:before {
7570 content: "\f0eb";
7571 }
7572 .fa-exchange:before {
7573 content: "\f0ec";
7574 }
7575 .fa-cloud-download:before {
7576 content: "\f0ed";
7577 }
7578 .fa-cloud-upload:before {
7579 content: "\f0ee";
7580 }
7581 .fa-user-md:before {
7582 content: "\f0f0";
7583 }
7584 .fa-stethoscope:before {
7585 content: "\f0f1";
7586 }
7587 .fa-suitcase:before {
7588 content: "\f0f2";
7589 }
7590 .fa-bell-o:before {
7591 content: "\f0a2";
7592 }
7593 .fa-coffee:before {
7594 content: "\f0f4";
7595 }
7596 .fa-cutlery:before {
7597 content: "\f0f5";
7598 }
7599 .fa-file-text-o:before {
7600 content: "\f0f6";
7601 }
7602 .fa-building-o:before {
7603 content: "\f0f7";
7604 }
7605 .fa-hospital-o:before {
7606 content: "\f0f8";
7607 }
7608 .fa-ambulance:before {
7609 content: "\f0f9";
7610 }
7611 .fa-medkit:before {
7612 content: "\f0fa";
7613 }
7614 .fa-fighter-jet:before {
7615 content: "\f0fb";
7616 }
7617 .fa-beer:before {
7618 content: "\f0fc";
7619 }
7620 .fa-h-square:before {
7621 content: "\f0fd";
7622 }
7623 .fa-plus-square:before {
7624 content: "\f0fe";
7625 }
7626 .fa-angle-double-left:before {
7627 content: "\f100";
7628 }
7629 .fa-angle-double-right:before {
7630 content: "\f101";
7631 }
7632 .fa-angle-double-up:before {
7633 content: "\f102";
7634 }
7635 .fa-angle-double-down:before {
7636 content: "\f103";
7637 }
7638 .fa-angle-left:before {
7639 content: "\f104";
7640 }
7641 .fa-angle-right:before {
7642 content: "\f105";
7643 }
7644 .fa-angle-up:before {
7645 content: "\f106";
7646 }
7647 .fa-angle-down:before {
7648 content: "\f107";
7649 }
7650 .fa-desktop:before {
7651 content: "\f108";
7652 }
7653 .fa-laptop:before {
7654 content: "\f109";
7655 }
7656 .fa-tablet:before {
7657 content: "\f10a";
7658 }
7659 .fa-mobile-phone:before,
7660 .fa-mobile:before {
7661 content: "\f10b";
7662 }
7663 .fa-circle-o:before {
7664 content: "\f10c";
7665 }
7666 .fa-quote-left:before {
7667 content: "\f10d";
7668 }
7669 .fa-quote-right:before {
7670 content: "\f10e";
7671 }
7672 .fa-spinner:before {
7673 content: "\f110";
7674 }
7675 .fa-circle:before {
7676 content: "\f111";
7677 }
7678 .fa-mail-reply:before,
7679 .fa-reply:before {
7680 content: "\f112";
7681 }
7682 .fa-github-alt:before {
7683 content: "\f113";
7684 }
7685 .fa-folder-o:before {
7686 content: "\f114";
7687 }
7688 .fa-folder-open-o:before {
7689 content: "\f115";
7690 }
7691 .fa-smile-o:before {
7692 content: "\f118";
7693 }
7694 .fa-frown-o:before {
7695 content: "\f119";
7696 }
7697 .fa-meh-o:before {
7698 content: "\f11a";
7699 }
7700 .fa-gamepad:before {
7701 content: "\f11b";
7702 }
7703 .fa-keyboard-o:before {
7704 content: "\f11c";
7705 }
7706 .fa-flag-o:before {
7707 content: "\f11d";
7708 }
7709 .fa-flag-checkered:before {
7710 content: "\f11e";
7711 }
7712 .fa-terminal:before {
7713 content: "\f120";
7714 }
7715 .fa-code:before {
7716 content: "\f121";
7717 }
7718 .fa-mail-reply-all:before,
7719 .fa-reply-all:before {
7720 content: "\f122";
7721 }
7722 .fa-star-half-empty:before,
7723 .fa-star-half-full:before,
7724 .fa-star-half-o:before {
7725 content: "\f123";
7726 }
7727 .fa-location-arrow:before {
7728 content: "\f124";
7729 }
7730 .fa-crop:before {
7731 content: "\f125";
7732 }
7733 .fa-code-fork:before {
7734 content: "\f126";
7735 }
7736 .fa-unlink:before,
7737 .fa-chain-broken:before {
7738 content: "\f127";
7739 }
7740 .fa-question:before {
7741 content: "\f128";
7742 }
7743 .fa-info:before {
7744 content: "\f129";
7745 }
7746 .fa-exclamation:before {
7747 content: "\f12a";
7748 }
7749 .fa-superscript:before {
7750 content: "\f12b";
7751 }
7752 .fa-subscript:before {
7753 content: "\f12c";
7754 }
7755 .fa-eraser:before {
7756 content: "\f12d";
7757 }
7758 .fa-puzzle-piece:before {
7759 content: "\f12e";
7760 }
7761 .fa-microphone:before {
7762 content: "\f130";
7763 }
7764 .fa-microphone-slash:before {
7765 content: "\f131";
7766 }
7767 .fa-shield:before {
7768 content: "\f132";
7769 }
7770 .fa-calendar-o:before {
7771 content: "\f133";
7772 }
7773 .fa-fire-extinguisher:before {
7774 content: "\f134";
7775 }
7776 .fa-rocket:before {
7777 content: "\f135";
7778 }
7779 .fa-maxcdn:before {
7780 content: "\f136";
7781 }
7782 .fa-chevron-circle-left:before {
7783 content: "\f137";
7784 }
7785 .fa-chevron-circle-right:before {
7786 content: "\f138";
7787 }
7788 .fa-chevron-circle-up:before {
7789 content: "\f139";
7790 }
7791 .fa-chevron-circle-down:before {
7792 content: "\f13a";
7793 }
7794 .fa-html5:before {
7795 content: "\f13b";
7796 }
7797 .fa-css3:before {
7798 content: "\f13c";
7799 }
7800 .fa-anchor:before {
7801 content: "\f13d";
7802 }
7803 .fa-unlock-alt:before {
7804 content: "\f13e";
7805 }
7806 .fa-bullseye:before {
7807 content: "\f140";
7808 }
7809 .fa-ellipsis-h:before {
7810 content: "\f141";
7811 }
7812 .fa-ellipsis-v:before {
7813 content: "\f142";
7814 }
7815 .fa-rss-square:before {
7816 content: "\f143";
7817 }
7818 .fa-play-circle:before {
7819 content: "\f144";
7820 }
7821 .fa-ticket:before {
7822 content: "\f145";
7823 }
7824 .fa-minus-square:before {
7825 content: "\f146";
7826 }
7827 .fa-minus-square-o:before {
7828 content: "\f147";
7829 }
7830 .fa-level-up:before {
7831 content: "\f148";
7832 }
7833 .fa-level-down:before {
7834 content: "\f149";
7835 }
7836 .fa-check-square:before {
7837 content: "\f14a";
7838 }
7839 .fa-pencil-square:before {
7840 content: "\f14b";
7841 }
7842 .fa-external-link-square:before {
7843 content: "\f14c";
7844 }
7845 .fa-share-square:before {
7846 content: "\f14d";
7847 }
7848 .fa-compass:before {
7849 content: "\f14e";
7850 }
7851 .fa-toggle-down:before,
7852 .fa-caret-square-o-down:before {
7853 content: "\f150";
7854 }
7855 .fa-toggle-up:before,
7856 .fa-caret-square-o-up:before {
7857 content: "\f151";
7858 }
7859 .fa-toggle-right:before,
7860 .fa-caret-square-o-right:before {
7861 content: "\f152";
7862 }
7863 .fa-euro:before,
7864 .fa-eur:before {
7865 content: "\f153";
7866 }
7867 .fa-gbp:before {
7868 content: "\f154";
7869 }
7870 .fa-dollar:before,
7871 .fa-usd:before {
7872 content: "\f155";
7873 }
7874 .fa-rupee:before,
7875 .fa-inr:before {
7876 content: "\f156";
7877 }
7878 .fa-cny:before,
7879 .fa-rmb:before,
7880 .fa-yen:before,
7881 .fa-jpy:before {
7882 content: "\f157";
7883 }
7884 .fa-ruble:before,
7885 .fa-rouble:before,
7886 .fa-rub:before {
7887 content: "\f158";
7888 }
7889 .fa-won:before,
7890 .fa-krw:before {
7891 content: "\f159";
7892 }
7893 .fa-bitcoin:before,
7894 .fa-btc:before {
7895 content: "\f15a";
7896 }
7897 .fa-file:before {
7898 content: "\f15b";
7899 }
7900 .fa-file-text:before {
7901 content: "\f15c";
7902 }
7903 .fa-sort-alpha-asc:before {
7904 content: "\f15d";
7905 }
7906 .fa-sort-alpha-desc:before {
7907 content: "\f15e";
7908 }
7909 .fa-sort-amount-asc:before {
7910 content: "\f160";
7911 }
7912 .fa-sort-amount-desc:before {
7913 content: "\f161";
7914 }
7915 .fa-sort-numeric-asc:before {
7916 content: "\f162";
7917 }
7918 .fa-sort-numeric-desc:before {
7919 content: "\f163";
7920 }
7921 .fa-thumbs-up:before {
7922 content: "\f164";
7923 }
7924 .fa-thumbs-down:before {
7925 content: "\f165";
7926 }
7927 .fa-youtube-square:before {
7928 content: "\f166";
7929 }
7930 .fa-youtube:before {
7931 content: "\f167";
7932 }
7933 .fa-xing:before {
7934 content: "\f168";
7935 }
7936 .fa-xing-square:before {
7937 content: "\f169";
7938 }
7939 .fa-youtube-play:before {
7940 content: "\f16a";
7941 }
7942 .fa-dropbox:before {
7943 content: "\f16b";
7944 }
7945 .fa-stack-overflow:before {
7946 content: "\f16c";
7947 }
7948 .fa-instagram:before {
7949 content: "\f16d";
7950 }
7951 .fa-flickr:before {
7952 content: "\f16e";
7953 }
7954 .fa-adn:before {
7955 content: "\f170";
7956 }
7957 .fa-bitbucket:before {
7958 content: "\f171";
7959 }
7960 .fa-bitbucket-square:before {
7961 content: "\f172";
7962 }
7963 .fa-tumblr:before {
7964 content: "\f173";
7965 }
7966 .fa-tumblr-square:before {
7967 content: "\f174";
7968 }
7969 .fa-long-arrow-down:before {
7970 content: "\f175";
7971 }
7972 .fa-long-arrow-up:before {
7973 content: "\f176";
7974 }
7975 .fa-long-arrow-left:before {
7976 content: "\f177";
7977 }
7978 .fa-long-arrow-right:before {
7979 content: "\f178";
7980 }
7981 .fa-apple:before {
7982 content: "\f179";
7983 }
7984 .fa-windows:before {
7985 content: "\f17a";
7986 }
7987 .fa-android:before {
7988 content: "\f17b";
7989 }
7990 .fa-linux:before {
7991 content: "\f17c";
7992 }
7993 .fa-dribbble:before {
7994 content: "\f17d";
7995 }
7996 .fa-skype:before {
7997 content: "\f17e";
7998 }
7999 .fa-foursquare:before {
8000 content: "\f180";
8001 }
8002 .fa-trello:before {
8003 content: "\f181";
8004 }
8005 .fa-female:before {
8006 content: "\f182";
8007 }
8008 .fa-male:before {
8009 content: "\f183";
8010 }
8011 .fa-gittip:before {
8012 content: "\f184";
8013 }
8014 .fa-sun-o:before {
8015 content: "\f185";
8016 }
8017 .fa-moon-o:before {
8018 content: "\f186";
8019 }
8020 .fa-archive:before {
8021 content: "\f187";
8022 }
8023 .fa-bug:before {
8024 content: "\f188";
8025 }
8026 .fa-vk:before {
8027 content: "\f189";
8028 }
8029 .fa-weibo:before {
8030 content: "\f18a";
8031 }
8032 .fa-renren:before {
8033 content: "\f18b";
8034 }
8035 .fa-pagelines:before {
8036 content: "\f18c";
8037 }
8038 .fa-stack-exchange:before {
8039 content: "\f18d";
8040 }
8041 .fa-arrow-circle-o-right:before {
8042 content: "\f18e";
8043 }
8044 .fa-arrow-circle-o-left:before {
8045 content: "\f190";
8046 }
8047 .fa-toggle-left:before,
8048 .fa-caret-square-o-left:before {
8049 content: "\f191";
8050 }
8051 .fa-dot-circle-o:before {
8052 content: "\f192";
8053 }
8054 .fa-wheelchair:before {
8055 content: "\f193";
8056 }
8057 .fa-vimeo-square:before {
8058 content: "\f194";
8059 }
8060 .fa-turkish-lira:before,
8061 .fa-try:before {
8062 content: "\f195";
8063 }
8064 .fa-plus-square-o:before {
8065 content: "\f196";
8066 }
8067 .fa-space-shuttle:before {
8068 content: "\f197";
8069 }
8070 .fa-slack:before {
8071 content: "\f198";
8072 }
8073 .fa-envelope-square:before {
8074 content: "\f199";
8075 }
8076 .fa-wordpress:before {
8077 content: "\f19a";
8078 }
8079 .fa-openid:before {
8080 content: "\f19b";
8081 }
8082 .fa-institution:before,
8083 .fa-bank:before,
8084 .fa-university:before {
8085 content: "\f19c";
8086 }
8087 .fa-mortar-board:before,
8088 .fa-graduation-cap:before {
8089 content: "\f19d";
8090 }
8091 .fa-yahoo:before {
8092 content: "\f19e";
8093 }
8094 .fa-google:before {
8095 content: "\f1a0";
8096 }
8097 .fa-reddit:before {
8098 content: "\f1a1";
8099 }
8100 .fa-reddit-square:before {
8101 content: "\f1a2";
8102 }
8103 .fa-stumbleupon-circle:before {
8104 content: "\f1a3";
8105 }
8106 .fa-stumbleupon:before {
8107 content: "\f1a4";
8108 }
8109 .fa-delicious:before {
8110 content: "\f1a5";
8111 }
8112 .fa-digg:before {
8113 content: "\f1a6";
8114 }
8115 .fa-pied-piper:before {
8116 content: "\f1a7";
8117 }
8118 .fa-pied-piper-alt:before {
8119 content: "\f1a8";
8120 }
8121 .fa-drupal:before {
8122 content: "\f1a9";
8123 }
8124 .fa-joomla:before {
8125 content: "\f1aa";
8126 }
8127 .fa-language:before {
8128 content: "\f1ab";
8129 }
8130 .fa-fax:before {
8131 content: "\f1ac";
8132 }
8133 .fa-building:before {
8134 content: "\f1ad";
8135 }
8136 .fa-child:before {
8137 content: "\f1ae";
8138 }
8139 .fa-paw:before {
8140 content: "\f1b0";
8141 }
8142 .fa-spoon:before {
8143 content: "\f1b1";
8144 }
8145 .fa-cube:before {
8146 content: "\f1b2";
8147 }
8148 .fa-cubes:before {
8149 content: "\f1b3";
8150 }
8151 .fa-behance:before {
8152 content: "\f1b4";
8153 }
8154 .fa-behance-square:before {
8155 content: "\f1b5";
8156 }
8157 .fa-steam:before {
8158 content: "\f1b6";
8159 }
8160 .fa-steam-square:before {
8161 content: "\f1b7";
8162 }
8163 .fa-recycle:before {
8164 content: "\f1b8";
8165 }
8166 .fa-automobile:before,
8167 .fa-car:before {
8168 content: "\f1b9";
8169 }
8170 .fa-cab:before,
8171 .fa-taxi:before {
8172 content: "\f1ba";
8173 }
8174 .fa-tree:before {
8175 content: "\f1bb";
8176 }
8177 .fa-spotify:before {
8178 content: "\f1bc";
8179 }
8180 .fa-deviantart:before {
8181 content: "\f1bd";
8182 }
8183 .fa-soundcloud:before {
8184 content: "\f1be";
8185 }
8186 .fa-database:before {
8187 content: "\f1c0";
8188 }
8189 .fa-file-pdf-o:before {
8190 content: "\f1c1";
8191 }
8192 .fa-file-word-o:before {
8193 content: "\f1c2";
8194 }
8195 .fa-file-excel-o:before {
8196 content: "\f1c3";
8197 }
8198 .fa-file-powerpoint-o:before {
8199 content: "\f1c4";
8200 }
8201 .fa-file-photo-o:before,
8202 .fa-file-picture-o:before,
8203 .fa-file-image-o:before {
8204 content: "\f1c5";
8205 }
8206 .fa-file-zip-o:before,
8207 .fa-file-archive-o:before {
8208 content: "\f1c6";
8209 }
8210 .fa-file-sound-o:before,
8211 .fa-file-audio-o:before {
8212 content: "\f1c7";
8213 }
8214 .fa-file-movie-o:before,
8215 .fa-file-video-o:before {
8216 content: "\f1c8";
8217 }
8218 .fa-file-code-o:before {
8219 content: "\f1c9";
8220 }
8221 .fa-vine:before {
8222 content: "\f1ca";
8223 }
8224 .fa-codepen:before {
8225 content: "\f1cb";
8226 }
8227 .fa-jsfiddle:before {
8228 content: "\f1cc";
8229 }
8230 .fa-life-bouy:before,
8231 .fa-life-buoy:before,
8232 .fa-life-saver:before,
8233 .fa-support:before,
8234 .fa-life-ring:before {
8235 content: "\f1cd";
8236 }
8237 .fa-circle-o-notch:before {
8238 content: "\f1ce";
8239 }
8240 .fa-ra:before,
8241 .fa-rebel:before {
8242 content: "\f1d0";
8243 }
8244 .fa-ge:before,
8245 .fa-empire:before {
8246 content: "\f1d1";
8247 }
8248 .fa-git-square:before {
8249 content: "\f1d2";
8250 }
8251 .fa-git:before {
8252 content: "\f1d3";
8253 }
8254 .fa-hacker-news:before {
8255 content: "\f1d4";
8256 }
8257 .fa-tencent-weibo:before {
8258 content: "\f1d5";
8259 }
8260 .fa-qq:before {
8261 content: "\f1d6";
8262 }
8263 .fa-wechat:before,
8264 .fa-weixin:before {
8265 content: "\f1d7";
8266 }
8267 .fa-send:before,
8268 .fa-paper-plane:before {
8269 content: "\f1d8";
8270 }
8271 .fa-send-o:before,
8272 .fa-paper-plane-o:before {
8273 content: "\f1d9";
8274 }
8275 .fa-history:before {
8276 content: "\f1da";
8277 }
8278 .fa-circle-thin:before {
8279 content: "\f1db";
8280 }
8281 .fa-header:before {
8282 content: "\f1dc";
8283 }
8284 .fa-paragraph:before {
8285 content: "\f1dd";
8286 }
8287 .fa-sliders:before {
8288 content: "\f1de";
8289 }
8290 .fa-share-alt:before {
8291 content: "\f1e0";
8292 }
8293 .fa-share-alt-square:before {
8294 content: "\f1e1";
8295 }
8296 .fa-bomb:before {
8297 content: "\f1e2";
8298 }
8299 .fa-soccer-ball-o:before,
8300 .fa-futbol-o:before {
8301 content: "\f1e3";
8302 }
8303 .fa-tty:before {
8304 content: "\f1e4";
8305 }
8306 .fa-binoculars:before {
8307 content: "\f1e5";
8308 }
8309 .fa-plug:before {
8310 content: "\f1e6";
8311 }
8312 .fa-slideshare:before {
8313 content: "\f1e7";
8314 }
8315 .fa-twitch:before {
8316 content: "\f1e8";
8317 }
8318 .fa-yelp:before {
8319 content: "\f1e9";
8320 }
8321 .fa-newspaper-o:before {
8322 content: "\f1ea";
8323 }
8324 .fa-wifi:before {
8325 content: "\f1eb";
8326 }
8327 .fa-calculator:before {
8328 content: "\f1ec";
8329 }
8330 .fa-paypal:before {
8331 content: "\f1ed";
8332 }
8333 .fa-google-wallet:before {
8334 content: "\f1ee";
8335 }
8336 .fa-cc-visa:before {
8337 content: "\f1f0";
8338 }
8339 .fa-cc-mastercard:before {
8340 content: "\f1f1";
8341 }
8342 .fa-cc-discover:before {
8343 content: "\f1f2";
8344 }
8345 .fa-cc-amex:before {
8346 content: "\f1f3";
8347 }
8348 .fa-cc-paypal:before {
8349 content: "\f1f4";
8350 }
8351 .fa-cc-stripe:before {
8352 content: "\f1f5";
8353 }
8354 .fa-bell-slash:before {
8355 content: "\f1f6";
8356 }
8357 .fa-bell-slash-o:before {
8358 content: "\f1f7";
8359 }
8360 .fa-trash:before {
8361 content: "\f1f8";
8362 }
8363 .fa-copyright:before {
8364 content: "\f1f9";
8365 }
8366 .fa-at:before {
8367 content: "\f1fa";
8368 }
8369 .fa-eyedropper:before {
8370 content: "\f1fb";
8371 }
8372 .fa-paint-brush:before {
8373 content: "\f1fc";
8374 }
8375 .fa-birthday-cake:before {
8376 content: "\f1fd";
8377 }
8378 .fa-area-chart:before {
8379 content: "\f1fe";
8380 }
8381 .fa-pie-chart:before {
8382 content: "\f200";
8383 }
8384 .fa-line-chart:before {
8385 content: "\f201";
8386 }
8387 .fa-lastfm:before {
8388 content: "\f202";
8389 }
8390 .fa-lastfm-square:before {
8391 content: "\f203";
8392 }
8393 .fa-toggle-off:before {
8394 content: "\f204";
8395 }
8396 .fa-toggle-on:before {
8397 content: "\f205";
8398 }
8399 .fa-bicycle:before {
8400 content: "\f206";
8401 }
8402 .fa-bus:before {
8403 content: "\f207";
8404 }
8405 .fa-ioxhost:before {
8406 content: "\f208";
8407 }
8408 .fa-angellist:before {
8409 content: "\f209";
8410 }
8411 .fa-cc:before {
8412 content: "\f20a";
8413 }
8414 .fa-shekel:before,
8415 .fa-sheqel:before,
8416 .fa-ils:before {
8417 content: "\f20b";
8418 }
8419 .fa-meanpath:before {
8420 content: "\f20c";
8421 }
8422 /*!
8423 *
8424 * IPython base
8425 *
8426 */
8427 .modal.fade .modal-dialog {
8428 -webkit-transform: translate(0, 0);
8429 -ms-transform: translate(0, 0);
8430 -o-transform: translate(0, 0);
8431 transform: translate(0, 0);
8432 }
8433 code {
8434 color: #000;
8435 }
8436 pre {
8437 font-size: inherit;
8438 line-height: inherit;
8439 }
8440 label {
8441 font-weight: normal;
8442 }
8443 /* Make the page background atleast 100% the height of the view port */
8444 /* Make the page itself atleast 70% the height of the view port */
8445 .border-box-sizing {
8446 box-sizing: border-box;
8447 -moz-box-sizing: border-box;
8448 -webkit-box-sizing: border-box;
8449 }
8450 .corner-all {
8451 border-radius: 2px;
8452 }
8453 .no-padding {
8454 padding: 0px;
8455 }
8456 /* Flexible box model classes */
8457 /* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
8458 /* This file is a compatability layer. It allows the usage of flexible box
8459 model layouts accross multiple browsers, including older browsers. The newest,
8460 universal implementation of the flexible box model is used when available (see
8461 `Modern browsers` comments below). Browsers that are known to implement this
8462 new spec completely include:
8463
8464 Firefox 28.0+
8465 Chrome 29.0+
8466 Internet Explorer 11+
8467 Opera 17.0+
8468
8469 Browsers not listed, including Safari, are supported via the styling under the
8470 `Old browsers` comments below.
8471 */
8472 .hbox {
8473 /* Old browsers */
8474 display: -webkit-box;
8475 -webkit-box-orient: horizontal;
8476 -webkit-box-align: stretch;
8477 display: -moz-box;
8478 -moz-box-orient: horizontal;
8479 -moz-box-align: stretch;
8480 display: box;
8481 box-orient: horizontal;
8482 box-align: stretch;
8483 /* Modern browsers */
8484 display: flex;
8485 flex-direction: row;
8486 align-items: stretch;
8487 }
8488 .hbox > * {
8489 /* Old browsers */
8490 -webkit-box-flex: 0;
8491 -moz-box-flex: 0;
8492 box-flex: 0;
8493 /* Modern browsers */
8494 flex: none;
8495 }
8496 .vbox {
8497 /* Old browsers */
8498 display: -webkit-box;
8499 -webkit-box-orient: vertical;
8500 -webkit-box-align: stretch;
8501 display: -moz-box;
8502 -moz-box-orient: vertical;
8503 -moz-box-align: stretch;
8504 display: box;
8505 box-orient: vertical;
8506 box-align: stretch;
8507 /* Modern browsers */
8508 display: flex;
8509 flex-direction: column;
8510 align-items: stretch;
8511 }
8512 .vbox > * {
8513 /* Old browsers */
8514 -webkit-box-flex: 0;
8515 -moz-box-flex: 0;
8516 box-flex: 0;
8517 /* Modern browsers */
8518 flex: none;
8519 }
8520 .hbox.reverse,
8521 .vbox.reverse,
8522 .reverse {
8523 /* Old browsers */
8524 -webkit-box-direction: reverse;
8525 -moz-box-direction: reverse;
8526 box-direction: reverse;
8527 /* Modern browsers */
8528 flex-direction: row-reverse;
8529 }
8530 .hbox.box-flex0,
8531 .vbox.box-flex0,
8532 .box-flex0 {
8533 /* Old browsers */
8534 -webkit-box-flex: 0;
8535 -moz-box-flex: 0;
8536 box-flex: 0;
8537 /* Modern browsers */
8538 flex: none;
8539 width: auto;
8540 }
8541 .hbox.box-flex1,
8542 .vbox.box-flex1,
8543 .box-flex1 {
8544 /* Old browsers */
8545 -webkit-box-flex: 1;
8546 -moz-box-flex: 1;
8547 box-flex: 1;
8548 /* Modern browsers */
8549 flex: 1;
8550 }
8551 .hbox.box-flex,
8552 .vbox.box-flex,
8553 .box-flex {
8554 /* Old browsers */
8555 /* Old browsers */
8556 -webkit-box-flex: 1;
8557 -moz-box-flex: 1;
8558 box-flex: 1;
8559 /* Modern browsers */
8560 flex: 1;
8561 }
8562 .hbox.box-flex2,
8563 .vbox.box-flex2,
8564 .box-flex2 {
8565 /* Old browsers */
8566 -webkit-box-flex: 2;
8567 -moz-box-flex: 2;
8568 box-flex: 2;
8569 /* Modern browsers */
8570 flex: 2;
8571 }
8572 .box-group1 {
8573 /* Deprecated */
8574 -webkit-box-flex-group: 1;
8575 -moz-box-flex-group: 1;
8576 box-flex-group: 1;
8577 }
8578 .box-group2 {
8579 /* Deprecated */
8580 -webkit-box-flex-group: 2;
8581 -moz-box-flex-group: 2;
8582 box-flex-group: 2;
8583 }
8584 .hbox.start,
8585 .vbox.start,
8586 .start {
8587 /* Old browsers */
8588 -webkit-box-pack: start;
8589 -moz-box-pack: start;
8590 box-pack: start;
8591 /* Modern browsers */
8592 justify-content: flex-start;
8593 }
8594 .hbox.end,
8595 .vbox.end,
8596 .end {
8597 /* Old browsers */
8598 -webkit-box-pack: end;
8599 -moz-box-pack: end;
8600 box-pack: end;
8601 /* Modern browsers */
8602 justify-content: flex-end;
8603 }
8604 .hbox.center,
8605 .vbox.center,
8606 .center {
8607 /* Old browsers */
8608 -webkit-box-pack: center;
8609 -moz-box-pack: center;
8610 box-pack: center;
8611 /* Modern browsers */
8612 justify-content: center;
8613 }
8614 .hbox.baseline,
8615 .vbox.baseline,
8616 .baseline {
8617 /* Old browsers */
8618 -webkit-box-pack: baseline;
8619 -moz-box-pack: baseline;
8620 box-pack: baseline;
8621 /* Modern browsers */
8622 justify-content: baseline;
8623 }
8624 .hbox.stretch,
8625 .vbox.stretch,
8626 .stretch {
8627 /* Old browsers */
8628 -webkit-box-pack: stretch;
8629 -moz-box-pack: stretch;
8630 box-pack: stretch;
8631 /* Modern browsers */
8632 justify-content: stretch;
8633 }
8634 .hbox.align-start,
8635 .vbox.align-start,
8636 .align-start {
8637 /* Old browsers */
8638 -webkit-box-align: start;
8639 -moz-box-align: start;
8640 box-align: start;
8641 /* Modern browsers */
8642 align-items: flex-start;
8643 }
8644 .hbox.align-end,
8645 .vbox.align-end,
8646 .align-end {
8647 /* Old browsers */
8648 -webkit-box-align: end;
8649 -moz-box-align: end;
8650 box-align: end;
8651 /* Modern browsers */
8652 align-items: flex-end;
8653 }
8654 .hbox.align-center,
8655 .vbox.align-center,
8656 .align-center {
8657 /* Old browsers */
8658 -webkit-box-align: center;
8659 -moz-box-align: center;
8660 box-align: center;
8661 /* Modern browsers */
8662 align-items: center;
8663 }
8664 .hbox.align-baseline,
8665 .vbox.align-baseline,
8666 .align-baseline {
8667 /* Old browsers */
8668 -webkit-box-align: baseline;
8669 -moz-box-align: baseline;
8670 box-align: baseline;
8671 /* Modern browsers */
8672 align-items: baseline;
8673 }
8674 .hbox.align-stretch,
8675 .vbox.align-stretch,
8676 .align-stretch {
8677 /* Old browsers */
8678 -webkit-box-align: stretch;
8679 -moz-box-align: stretch;
8680 box-align: stretch;
8681 /* Modern browsers */
8682 align-items: stretch;
8683 }
8684 div.error {
8685 margin: 2em;
8686 text-align: center;
8687 }
8688 div.error > h1 {
8689 font-size: 500%;
8690 line-height: normal;
8691 }
8692 div.error > p {
8693 font-size: 200%;
8694 line-height: normal;
8695 }
8696 div.traceback-wrapper {
8697 text-align: left;
8698 max-width: 800px;
8699 margin: auto;
8700 }
8701 /**
8702 * Primary styles
8703 *
8704 * Author: Jupyter Development Team
8705 */
8706 body {
8707 background-color: #fff;
8708 /* This makes sure that the body covers the entire window and needs to
8709 be in a different element than the display: box in wrapper below */
8710 position: absolute;
8711 left: 0px;
8712 right: 0px;
8713 top: 0px;
8714 bottom: 0px;
8715 overflow: visible;
8716 }
8717 body > #header {
8718 /* Initially hidden to prevent FLOUC */
8719 display: none;
8720 background-color: #fff;
8721 /* Display over codemirror */
8722 position: relative;
8723 z-index: 100;
8724 }
8725 body > #header #header-container {
8726 padding-bottom: 5px;
8727 padding-top: 5px;
8728 box-sizing: border-box;
8729 -moz-box-sizing: border-box;
8730 -webkit-box-sizing: border-box;
8731 }
8732 body > #header .header-bar {
8733 width: 100%;
8734 height: 1px;
8735 background: #e7e7e7;
8736 margin-bottom: -1px;
8737 }
8738 @media print {
8739 body > #header {
8740 display: none !important;
8741 }
8742 }
8743 #header-spacer {
8744 width: 100%;
8745 visibility: hidden;
8746 }
8747 @media print {
8748 #header-spacer {
8749 display: none;
8750 }
8751 }
8752 #ipython_notebook {
8753 padding-left: 0px;
8754 padding-top: 1px;
8755 padding-bottom: 1px;
8756 }
8757 @media (max-width: 991px) {
8758 #ipython_notebook {
8759 margin-left: 10px;
8760 }
8761 }
8762 #noscript {
8763 width: auto;
8764 padding-top: 16px;
8765 padding-bottom: 16px;
8766 text-align: center;
8767 font-size: 22px;
8768 color: red;
8769 font-weight: bold;
8770 }
8771 #ipython_notebook img {
8772 height: 28px;
8773 }
8774 #site {
8775 width: 100%;
8776 display: none;
8777 box-sizing: border-box;
8778 -moz-box-sizing: border-box;
8779 -webkit-box-sizing: border-box;
8780 overflow: auto;
8781 }
8782 @media print {
8783 #site {
8784 height: auto !important;
8785 }
8786 }
8787 /* Smaller buttons */
8788 .ui-button .ui-button-text {
8789 padding: 0.2em 0.8em;
8790 font-size: 77%;
8791 }
8792 input.ui-button {
8793 padding: 0.3em 0.9em;
8794 }
8795 span#login_widget {
8796 float: right;
8797 }
8798 span#login_widget > .button,
8799 #logout {
8800 color: #333;
8801 background-color: #fff;
8802 border-color: #ccc;
8803 }
8804 span#login_widget > .button:focus,
8805 #logout:focus,
8806 span#login_widget > .button.focus,
8807 #logout.focus {
8808 color: #333;
8809 background-color: #e6e6e6;
8810 border-color: #8c8c8c;
8811 }
8812 span#login_widget > .button:hover,
8813 #logout:hover {
8814 color: #333;
8815 background-color: #e6e6e6;
8816 border-color: #adadad;
8817 }
8818 span#login_widget > .button:active,
8819 #logout:active,
8820 span#login_widget > .button.active,
8821 #logout.active,
8822 .open > .dropdown-togglespan#login_widget > .button,
8823 .open > .dropdown-toggle#logout {
8824 color: #333;
8825 background-color: #e6e6e6;
8826 border-color: #adadad;
8827 }
8828 span#login_widget > .button:active:hover,
8829 #logout:active:hover,
8830 span#login_widget > .button.active:hover,
8831 #logout.active:hover,
8832 .open > .dropdown-togglespan#login_widget > .button:hover,
8833 .open > .dropdown-toggle#logout:hover,
8834 span#login_widget > .button:active:focus,
8835 #logout:active:focus,
8836 span#login_widget > .button.active:focus,
8837 #logout.active:focus,
8838 .open > .dropdown-togglespan#login_widget > .button:focus,
8839 .open > .dropdown-toggle#logout:focus,
8840 span#login_widget > .button:active.focus,
8841 #logout:active.focus,
8842 span#login_widget > .button.active.focus,
8843 #logout.active.focus,
8844 .open > .dropdown-togglespan#login_widget > .button.focus,
8845 .open > .dropdown-toggle#logout.focus {
8846 color: #333;
8847 background-color: #d4d4d4;
8848 border-color: #8c8c8c;
8849 }
8850 span#login_widget > .button:active,
8851 #logout:active,
8852 span#login_widget > .button.active,
8853 #logout.active,
8854 .open > .dropdown-togglespan#login_widget > .button,
8855 .open > .dropdown-toggle#logout {
8856 background-image: none;
8857 }
8858 span#login_widget > .button.disabled:hover,
8859 #logout.disabled:hover,
8860 span#login_widget > .button[disabled]:hover,
8861 #logout[disabled]:hover,
8862 fieldset[disabled] span#login_widget > .button:hover,
8863 fieldset[disabled] #logout:hover,
8864 span#login_widget > .button.disabled:focus,
8865 #logout.disabled:focus,
8866 span#login_widget > .button[disabled]:focus,
8867 #logout[disabled]:focus,
8868 fieldset[disabled] span#login_widget > .button:focus,
8869 fieldset[disabled] #logout:focus,
8870 span#login_widget > .button.disabled.focus,
8871 #logout.disabled.focus,
8872 span#login_widget > .button[disabled].focus,
8873 #logout[disabled].focus,
8874 fieldset[disabled] span#login_widget > .button.focus,
8875 fieldset[disabled] #logout.focus {
8876 background-color: #fff;
8877 border-color: #ccc;
8878 }
8879 span#login_widget > .button .badge,
8880 #logout .badge {
8881 color: #fff;
8882 background-color: #333;
8883 }
8884 .nav-header {
8885 text-transform: none;
8886 }
8887 #header > span {
8888 margin-top: 10px;
8889 }
8890 .modal_stretch .modal-dialog {
8891 /* Old browsers */
8892 display: -webkit-box;
8893 -webkit-box-orient: vertical;
8894 -webkit-box-align: stretch;
8895 display: -moz-box;
8896 -moz-box-orient: vertical;
8897 -moz-box-align: stretch;
8898 display: box;
8899 box-orient: vertical;
8900 box-align: stretch;
8901 /* Modern browsers */
8902 display: flex;
8903 flex-direction: column;
8904 align-items: stretch;
8905 min-height: 80vh;
8906 }
8907 .modal_stretch .modal-dialog .modal-body {
8908 max-height: calc(100vh - 200px);
8909 overflow: auto;
8910 flex: 1;
8911 }
8912 @media (min-width: 768px) {
8913 .modal .modal-dialog {
8914 width: 700px;
8915 }
8916 }
8917 @media (min-width: 768px) {
8918 select.form-control {
8919 margin-left: 12px;
8920 margin-right: 12px;
8921 }
8922 }
8923 /*!
8924 *
8925 * IPython auth
8926 *
8927 */
8928 .center-nav {
8929 display: inline-block;
8930 margin-bottom: -4px;
8931 }
8932 /*!
8933 *
8934 * IPython tree view
8935 *
8936 */
8937 /* We need an invisible input field on top of the sentense*/
8938 /* "Drag file onto the list ..." */
8939 .alternate_upload {
8940 background-color: none;
8941 display: inline;
8942 }
8943 .alternate_upload.form {
8944 padding: 0;
8945 margin: 0;
8946 }
8947 .alternate_upload input.fileinput {
8948 text-align: center;
8949 vertical-align: middle;
8950 display: inline;
8951 opacity: 0;
8952 z-index: 2;
8953 width: 12ex;
8954 margin-right: -12ex;
8955 }
8956 .alternate_upload .btn-upload {
8957 height: 22px;
8958 }
8959 /**
8960 * Primary styles
8961 *
8962 * Author: Jupyter Development Team
8963 */
8964 ul#tabs {
8965 margin-bottom: 4px;
8966 }
8967 ul#tabs a {
8968 padding-top: 6px;
8969 padding-bottom: 4px;
8970 }
8971 ul.breadcrumb a:focus,
8972 ul.breadcrumb a:hover {
8973 text-decoration: none;
8974 }
8975 ul.breadcrumb i.icon-home {
8976 font-size: 16px;
8977 margin-right: 4px;
8978 }
8979 ul.breadcrumb span {
8980 color: #5e5e5e;
8981 }
8982 .list_toolbar {
8983 padding: 4px 0 4px 0;
8984 vertical-align: middle;
8985 }
8986 .list_toolbar .tree-buttons {
8987 padding-top: 1px;
8988 }
8989 .dynamic-buttons {
8990 padding-top: 3px;
8991 display: inline-block;
8992 }
8993 .list_toolbar [class*="span"] {
8994 min-height: 24px;
8995 }
8996 .list_header {
8997 font-weight: bold;
8998 background-color: #EEE;
8999 }
9000 .list_placeholder {
9001 font-weight: bold;
9002 padding-top: 4px;
9003 padding-bottom: 4px;
9004 padding-left: 7px;
9005 padding-right: 7px;
9006 }
9007 .list_container {
9008 margin-top: 4px;
9009 margin-bottom: 20px;
9010 border: 1px solid #ddd;
9011 border-radius: 2px;
9012 }
9013 .list_container > div {
9014 border-bottom: 1px solid #ddd;
9015 }
9016 .list_container > div:hover .list-item {
9017 background-color: red;
9018 }
9019 .list_container > div:last-child {
9020 border: none;
9021 }
9022 .list_item:hover .list_item {
9023 background-color: #ddd;
9024 }
9025 .list_item a {
9026 text-decoration: none;
9027 }
9028 .list_item:hover {
9029 background-color: #fafafa;
9030 }
9031 .list_header > div,
9032 .list_item > div {
9033 padding-top: 4px;
9034 padding-bottom: 4px;
9035 padding-left: 7px;
9036 padding-right: 7px;
9037 line-height: 22px;
9038 }
9039 .list_header > div input,
9040 .list_item > div input {
9041 margin-right: 7px;
9042 margin-left: 14px;
9043 vertical-align: baseline;
9044 line-height: 22px;
9045 position: relative;
9046 top: -1px;
9047 }
9048 .list_header > div .item_link,
9049 .list_item > div .item_link {
9050 margin-left: -1px;
9051 vertical-align: baseline;
9052 line-height: 22px;
9053 }
9054 .new-file input[type=checkbox] {
9055 visibility: hidden;
9056 }
9057 .item_name {
9058 line-height: 22px;
9059 height: 24px;
9060 }
9061 .item_icon {
9062 font-size: 14px;
9063 color: #5e5e5e;
9064 margin-right: 7px;
9065 margin-left: 7px;
9066 line-height: 22px;
9067 vertical-align: baseline;
9068 }
9069 .item_buttons {
9070 line-height: 1em;
9071 margin-left: -5px;
9072 }
9073 .item_buttons .btn,
9074 .item_buttons .btn-group,
9075 .item_buttons .input-group {
9076 float: left;
9077 }
9078 .item_buttons > .btn,
9079 .item_buttons > .btn-group,
9080 .item_buttons > .input-group {
9081 margin-left: 5px;
9082 }
9083 .item_buttons .btn {
9084 min-width: 13ex;
9085 }
9086 .item_buttons .running-indicator {
9087 padding-top: 4px;
9088 color: #5cb85c;
9089 }
9090 .item_buttons .kernel-name {
9091 padding-top: 4px;
9092 color: #5bc0de;
9093 margin-right: 7px;
9094 float: left;
9095 }
9096 .toolbar_info {
9097 height: 24px;
9098 line-height: 24px;
9099 }
9100 .list_item input:not([type=checkbox]) {
9101 padding-top: 3px;
9102 padding-bottom: 3px;
9103 height: 22px;
9104 line-height: 14px;
9105 margin: 0px;
9106 }
9107 .highlight_text {
9108 color: blue;
9109 }
9110 #project_name {
9111 display: inline-block;
9112 padding-left: 7px;
9113 margin-left: -2px;
9114 }
9115 #project_name > .breadcrumb {
9116 padding: 0px;
9117 margin-bottom: 0px;
9118 background-color: transparent;
9119 font-weight: bold;
9120 }
9121 #tree-selector {
9122 padding-right: 0px;
9123 }
9124 #button-select-all {
9125 min-width: 50px;
9126 }
9127 #select-all {
9128 margin-left: 7px;
9129 margin-right: 2px;
9130 }
9131 .menu_icon {
9132 margin-right: 2px;
9133 }
9134 .tab-content .row {
9135 margin-left: 0px;
9136 margin-right: 0px;
9137 }
9138 .folder_icon:before {
9139 display: inline-block;
9140 font: normal normal normal 14px/1 FontAwesome;
9141 font-size: inherit;
9142 text-rendering: auto;
9143 -webkit-font-smoothing: antialiased;
9144 -moz-osx-font-smoothing: grayscale;
9145 content: "\f114";
9146 }
9147 .folder_icon:before.pull-left {
9148 margin-right: .3em;
9149 }
9150 .folder_icon:before.pull-right {
9151 margin-left: .3em;
9152 }
9153 .notebook_icon:before {
9154 display: inline-block;
9155 font: normal normal normal 14px/1 FontAwesome;
9156 font-size: inherit;
9157 text-rendering: auto;
9158 -webkit-font-smoothing: antialiased;
9159 -moz-osx-font-smoothing: grayscale;
9160 content: "\f02d";
9161 position: relative;
9162 top: -1px;
9163 }
9164 .notebook_icon:before.pull-left {
9165 margin-right: .3em;
9166 }
9167 .notebook_icon:before.pull-right {
9168 margin-left: .3em;
9169 }
9170 .running_notebook_icon:before {
9171 display: inline-block;
9172 font: normal normal normal 14px/1 FontAwesome;
9173 font-size: inherit;
9174 text-rendering: auto;
9175 -webkit-font-smoothing: antialiased;
9176 -moz-osx-font-smoothing: grayscale;
9177 content: "\f02d";
9178 position: relative;
9179 top: -1px;
9180 color: #5cb85c;
9181 }
9182 .running_notebook_icon:before.pull-left {
9183 margin-right: .3em;
9184 }
9185 .running_notebook_icon:before.pull-right {
9186 margin-left: .3em;
9187 }
9188 .file_icon:before {
9189 display: inline-block;
9190 font: normal normal normal 14px/1 FontAwesome;
9191 font-size: inherit;
9192 text-rendering: auto;
9193 -webkit-font-smoothing: antialiased;
9194 -moz-osx-font-smoothing: grayscale;
9195 content: "\f016";
9196 position: relative;
9197 top: -2px;
9198 }
9199 .file_icon:before.pull-left {
9200 margin-right: .3em;
9201 }
9202 .file_icon:before.pull-right {
9203 margin-left: .3em;
9204 }
9205 #notebook_toolbar .pull-right {
9206 padding-top: 0px;
9207 margin-right: -1px;
9208 }
9209 ul#new-menu {
9210 left: auto;
9211 right: 0;
9212 }
9213 .kernel-menu-icon {
9214 padding-right: 12px;
9215 width: 24px;
9216 content: "\f096";
9217 }
9218 .kernel-menu-icon:before {
9219 content: "\f096";
9220 }
9221 .kernel-menu-icon-current:before {
9222 content: "\f00c";
9223 }
9224 #tab_content {
9225 padding-top: 20px;
9226 }
9227 #running .panel-group .panel {
9228 margin-top: 3px;
9229 margin-bottom: 1em;
9230 }
9231 #running .panel-group .panel .panel-heading {
9232 background-color: #EEE;
9233 padding-top: 4px;
9234 padding-bottom: 4px;
9235 padding-left: 7px;
9236 padding-right: 7px;
9237 line-height: 22px;
9238 }
9239 #running .panel-group .panel .panel-heading a:focus,
9240 #running .panel-group .panel .panel-heading a:hover {
9241 text-decoration: none;
9242 }
9243 #running .panel-group .panel .panel-body {
9244 padding: 0px;
9245 }
9246 #running .panel-group .panel .panel-body .list_container {
9247 margin-top: 0px;
9248 margin-bottom: 0px;
9249 border: 0px;
9250 border-radius: 0px;
9251 }
9252 #running .panel-group .panel .panel-body .list_container .list_item {
9253 border-bottom: 1px solid #ddd;
9254 }
9255 #running .panel-group .panel .panel-body .list_container .list_item:last-child {
9256 border-bottom: 0px;
9257 }
9258 .delete-button {
9259 display: none;
9260 }
9261 .duplicate-button {
9262 display: none;
9263 }
9264 .rename-button {
9265 display: none;
9266 }
9267 .shutdown-button {
9268 display: none;
9269 }
9270 .dynamic-instructions {
9271 display: inline-block;
9272 padding-top: 4px;
9273 }
9274 /*!
9275 *
9276 * IPython text editor webapp
9277 *
9278 */
9279 .selected-keymap i.fa {
9280 padding: 0px 5px;
9281 }
9282 .selected-keymap i.fa:before {
9283 content: "\f00c";
9284 }
9285 #mode-menu {
9286 overflow: auto;
9287 max-height: 20em;
9288 }
9289 .edit_app #header {
9290 -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
9291 box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
9292 }
9293 .edit_app #menubar .navbar {
9294 /* Use a negative 1 bottom margin, so the border overlaps the border of the
9295 header */
9296 margin-bottom: -1px;
9297 }
9298 .dirty-indicator {
9299 display: inline-block;
9300 font: normal normal normal 14px/1 FontAwesome;
9301 font-size: inherit;
9302 text-rendering: auto;
9303 -webkit-font-smoothing: antialiased;
9304 -moz-osx-font-smoothing: grayscale;
9305 width: 20px;
9306 }
9307 .dirty-indicator.pull-left {
9308 margin-right: .3em;
9309 }
9310 .dirty-indicator.pull-right {
9311 margin-left: .3em;
9312 }
9313 .dirty-indicator-dirty {
9314 display: inline-block;
9315 font: normal normal normal 14px/1 FontAwesome;
9316 font-size: inherit;
9317 text-rendering: auto;
9318 -webkit-font-smoothing: antialiased;
9319 -moz-osx-font-smoothing: grayscale;
9320 width: 20px;
9321 }
9322 .dirty-indicator-dirty.pull-left {
9323 margin-right: .3em;
9324 }
9325 .dirty-indicator-dirty.pull-right {
9326 margin-left: .3em;
9327 }
9328 .dirty-indicator-clean {
9329 display: inline-block;
9330 font: normal normal normal 14px/1 FontAwesome;
9331 font-size: inherit;
9332 text-rendering: auto;
9333 -webkit-font-smoothing: antialiased;
9334 -moz-osx-font-smoothing: grayscale;
9335 width: 20px;
9336 }
9337 .dirty-indicator-clean.pull-left {
9338 margin-right: .3em;
9339 }
9340 .dirty-indicator-clean.pull-right {
9341 margin-left: .3em;
9342 }
9343 .dirty-indicator-clean:before {
9344 display: inline-block;
9345 font: normal normal normal 14px/1 FontAwesome;
9346 font-size: inherit;
9347 text-rendering: auto;
9348 -webkit-font-smoothing: antialiased;
9349 -moz-osx-font-smoothing: grayscale;
9350 content: "\f00c";
9351 }
9352 .dirty-indicator-clean:before.pull-left {
9353 margin-right: .3em;
9354 }
9355 .dirty-indicator-clean:before.pull-right {
9356 margin-left: .3em;
9357 }
9358 #filename {
9359 font-size: 16pt;
9360 display: table;
9361 padding: 0px 5px;
9362 }
9363 #current-mode {
9364 padding-left: 5px;
9365 padding-right: 5px;
9366 }
9367 #texteditor-backdrop {
9368 padding-top: 20px;
9369 padding-bottom: 20px;
9370 }
9371 @media not print {
9372 #texteditor-backdrop {
9373 background-color: #EEE;
9374 }
9375 }
9376 @media print {
9377 #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
9378 #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
9379 background-color: #fff;
9380 }
9381 }
9382 @media not print {
9383 #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
9384 #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
9385 background-color: #fff;
9386 }
9387 }
9388 @media not print {
9389 #texteditor-backdrop #texteditor-container {
9390 padding: 0px;
9391 background-color: #fff;
9392 -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
9393 box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
9394 }
9395 }
9396 /*!
9397 *
9398 * IPython notebook
9399 *
9400 */
9401 /* CSS font colors for translated ANSI colors. */
9402 .ansibold {
9403 font-weight: bold;
9404 }
9405 /* use dark versions for foreground, to improve visibility */
9406 .ansiblack {
9407 color: black;
9408 }
9409 .ansired {
9410 color: darkred;
9411 }
9412 .ansigreen {
9413 color: darkgreen;
9414 }
9415 .ansiyellow {
9416 color: #c4a000;
9417 }
9418 .ansiblue {
9419 color: darkblue;
9420 }
9421 .ansipurple {
9422 color: darkviolet;
9423 }
9424 .ansicyan {
9425 color: steelblue;
9426 }
9427 .ansigray {
9428 color: gray;
9429 }
9430 /* and light for background, for the same reason */
9431 .ansibgblack {
9432 background-color: black;
9433 }
9434 .ansibgred {
9435 background-color: red;
9436 }
9437 .ansibggreen {
9438 background-color: green;
9439 }
9440 .ansibgyellow {
9441 background-color: yellow;
9442 }
9443 .ansibgblue {
9444 background-color: blue;
9445 }
9446 .ansibgpurple {
9447 background-color: magenta;
9448 }
9449 .ansibgcyan {
9450 background-color: cyan;
9451 }
9452 .ansibggray {
9453 background-color: gray;
9454 }
9455 div.cell {
9456 /* Old browsers */
9457 display: -webkit-box;
9458 -webkit-box-orient: vertical;
9459 -webkit-box-align: stretch;
9460 display: -moz-box;
9461 -moz-box-orient: vertical;
9462 -moz-box-align: stretch;
9463 display: box;
9464 box-orient: vertical;
9465 box-align: stretch;
9466 /* Modern browsers */
9467 display: flex;
9468 flex-direction: column;
9469 align-items: stretch;
9470 border-radius: 2px;
9471 box-sizing: border-box;
9472 -moz-box-sizing: border-box;
9473 -webkit-box-sizing: border-box;
9474 border-width: 1px;
9475 border-style: solid;
9476 border-color: transparent;
9477 width: 100%;
9478 padding: 5px;
9479 /* This acts as a spacer between cells, that is outside the border */
9480 margin: 0px;
9481 outline: none;
9482 border-left-width: 1px;
9483 padding-left: 5px;
9484 background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
9485 }
9486 div.cell.jupyter-soft-selected {
9487 border-left-color: #90CAF9;
9488 border-left-color: #E3F2FD;
9489 border-left-width: 1px;
9490 padding-left: 5px;
9491 border-right-color: #E3F2FD;
9492 border-right-width: 1px;
9493 background: #E3F2FD;
9494 }
9495 @media print {
9496 div.cell.jupyter-soft-selected {
9497 border-color: transparent;
9498 }
9499 }
9500 div.cell.selected {
9501 border-color: #ababab;
9502 border-left-width: 0px;
9503 padding-left: 6px;
9504 background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
9505 }
9506 @media print {
9507 div.cell.selected {
9508 border-color: transparent;
9509 }
9510 }
9511 div.cell.selected.jupyter-soft-selected {
9512 border-left-width: 0;
9513 padding-left: 6px;
9514 background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
9515 }
9516 .edit_mode div.cell.selected {
9517 border-color: #66BB6A;
9518 border-left-width: 0px;
9519 padding-left: 6px;
9520 background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
9521 }
9522 @media print {
9523 .edit_mode div.cell.selected {
9524 border-color: transparent;
9525 }
9526 }
9527 .prompt {
9528 /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
9529 min-width: 14ex;
9530 /* This padding is tuned to match the padding on the CodeMirror editor. */
9531 padding: 0.4em;
9532 margin: 0px;
9533 font-family: monospace;
9534 text-align: right;
9535 /* This has to match that of the the CodeMirror class line-height below */
9536 line-height: 1.21429em;
9537 /* Don't highlight prompt number selection */
9538 -webkit-touch-callout: none;
9539 -webkit-user-select: none;
9540 -khtml-user-select: none;
9541 -moz-user-select: none;
9542 -ms-user-select: none;
9543 user-select: none;
9544 /* Use default cursor */
9545 cursor: default;
9546 }
9547 @media (max-width: 540px) {
9548 .prompt {
9549 text-align: left;
9550 }
9551 }
9552 div.inner_cell {
9553 /* Old browsers */
9554 display: -webkit-box;
9555 -webkit-box-orient: vertical;
9556 -webkit-box-align: stretch;
9557 display: -moz-box;
9558 -moz-box-orient: vertical;
9559 -moz-box-align: stretch;
9560 display: box;
9561 box-orient: vertical;
9562 box-align: stretch;
9563 /* Modern browsers */
9564 display: flex;
9565 flex-direction: column;
9566 align-items: stretch;
9567 /* Old browsers */
9568 -webkit-box-flex: 1;
9569 -moz-box-flex: 1;
9570 box-flex: 1;
9571 /* Modern browsers */
9572 flex: 1;
9573 }
9574 @-moz-document url-prefix() {
9575 div.inner_cell {
9576 overflow-x: hidden;
9577 }
9578 }
9579 /* input_area and input_prompt must match in top border and margin for alignment */
9580 div.input_area {
9581 border: 1px solid #cfcfcf;
9582 border-radius: 2px;
9583 background: #f7f7f7;
9584 line-height: 1.21429em;
9585 }
9586 /* This is needed so that empty prompt areas can collapse to zero height when there
9587 is no content in the output_subarea and the prompt. The main purpose of this is
9588 to make sure that empty JavaScript output_subareas have no height. */
9589 div.prompt:empty {
9590 padding-top: 0;
9591 padding-bottom: 0;
9592 }
9593 div.unrecognized_cell {
9594 padding: 5px 5px 5px 0px;
9595 /* Old browsers */
9596 display: -webkit-box;
9597 -webkit-box-orient: horizontal;
9598 -webkit-box-align: stretch;
9599 display: -moz-box;
9600 -moz-box-orient: horizontal;
9601 -moz-box-align: stretch;
9602 display: box;
9603 box-orient: horizontal;
9604 box-align: stretch;
9605 /* Modern browsers */
9606 display: flex;
9607 flex-direction: row;
9608 align-items: stretch;
9609 }
9610 div.unrecognized_cell .inner_cell {
9611 border-radius: 2px;
9612 padding: 5px;
9613 font-weight: bold;
9614 color: red;
9615 border: 1px solid #cfcfcf;
9616 background: #eaeaea;
9617 }
9618 div.unrecognized_cell .inner_cell a {
9619 color: inherit;
9620 text-decoration: none;
9621 }
9622 div.unrecognized_cell .inner_cell a:hover {
9623 color: inherit;
9624 text-decoration: none;
9625 }
9626 @media (max-width: 540px) {
9627 div.unrecognized_cell > div.prompt {
9628 display: none;
9629 }
9630 }
9631 div.code_cell {
9632 /* avoid page breaking on code cells when printing */
9633 }
9634 @media print {
9635 div.code_cell {
9636 page-break-inside: avoid;
9637 }
9638 }
9639 /* any special styling for code cells that are currently running goes here */
9640 div.input {
9641 page-break-inside: avoid;
9642 /* Old browsers */
9643 display: -webkit-box;
9644 -webkit-box-orient: horizontal;
9645 -webkit-box-align: stretch;
9646 display: -moz-box;
9647 -moz-box-orient: horizontal;
9648 -moz-box-align: stretch;
9649 display: box;
9650 box-orient: horizontal;
9651 box-align: stretch;
9652 /* Modern browsers */
9653 display: flex;
9654 flex-direction: row;
9655 align-items: stretch;
9656 }
9657 @media (max-width: 540px) {
9658 div.input {
9659 /* Old browsers */
9660 display: -webkit-box;
9661 -webkit-box-orient: vertical;
9662 -webkit-box-align: stretch;
9663 display: -moz-box;
9664 -moz-box-orient: vertical;
9665 -moz-box-align: stretch;
9666 display: box;
9667 box-orient: vertical;
9668 box-align: stretch;
9669 /* Modern browsers */
9670 display: flex;
9671 flex-direction: column;
9672 align-items: stretch;
9673 }
9674 }
9675 /* input_area and input_prompt must match in top border and margin for alignment */
9676 div.input_prompt {
9677 color: #303F9F;
9678 border-top: 1px solid transparent;
9679 }
9680 div.input_area > div.highlight {
9681 margin: 0.4em;
9682 border: none;
9683 padding: 0px;
9684 background-color: transparent;
9685 }
9686 div.input_area > div.highlight > pre {
9687 margin: 0px;
9688 border: none;
9689 padding: 0px;
9690 background-color: transparent;
9691 }
9692 /* The following gets added to the <head> if it is detected that the user has a
9693 * monospace font with inconsistent normal/bold/italic height. See
9694 * notebookmain.js. Such fonts will have keywords vertically offset with
9695 * respect to the rest of the text. The user should select a better font.
9696 * See: https://github.com/ipython/ipython/issues/1503
9697 *
9698 * .CodeMirror span {
9699 * vertical-align: bottom;
9700 * }
9701 */
9702 .CodeMirror {
9703 line-height: 1.21429em;
9704 /* Changed from 1em to our global default */
9705 font-size: 14px;
9706 height: auto;
9707 /* Changed to auto to autogrow */
9708 background: none;
9709 /* Changed from white to allow our bg to show through */
9710 }
9711 .CodeMirror-scroll {
9712 /* The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
9713 /* We have found that if it is visible, vertical scrollbars appear with font size changes.*/
9714 overflow-y: hidden;
9715 overflow-x: auto;
9716 }
9717 .CodeMirror-lines {
9718 /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
9719 /* we have set a different line-height and want this to scale with that. */
9720 padding: 0.4em;
9721 }
9722 .CodeMirror-linenumber {
9723 padding: 0 8px 0 4px;
9724 }
9725 .CodeMirror-gutters {
9726 border-bottom-left-radius: 2px;
9727 border-top-left-radius: 2px;
9728 }
9729 .CodeMirror pre {
9730 /* In CM3 this went to 4px from 0 in CM2. We need the 0 value because of how we size */
9731 /* .CodeMirror-lines */
9732 padding: 0;
9733 border: 0;
9734 border-radius: 0;
9735 }
9736 /*
9737
9738 Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
9739 Adapted from GitHub theme
9740
9741 */
9742 .highlight-base {
9743 color: #000;
9744 }
9745 .highlight-variable {
9746 color: #000;
9747 }
9748 .highlight-variable-2 {
9749 color: #1a1a1a;
9750 }
9751 .highlight-variable-3 {
9752 color: #333333;
9753 }
9754 .highlight-string {
9755 color: #BA2121;
9756 }
9757 .highlight-comment {
9758 color: #408080;
9759 font-style: italic;
9760 }
9761 .highlight-number {
9762 color: #080;
9763 }
9764 .highlight-atom {
9765 color: #88F;
9766 }
9767 .highlight-keyword {
9768 color: #008000;
9769 font-weight: bold;
9770 }
9771 .highlight-builtin {
9772 color: #008000;
9773 }
9774 .highlight-error {
9775 color: #f00;
9776 }
9777 .highlight-operator {
9778 color: #AA22FF;
9779 font-weight: bold;
9780 }
9781 .highlight-meta {
9782 color: #AA22FF;
9783 }
9784 /* previously not defined, copying from default codemirror */
9785 .highlight-def {
9786 color: #00f;
9787 }
9788 .highlight-string-2 {
9789 color: #f50;
9790 }
9791 .highlight-qualifier {
9792 color: #555;
9793 }
9794 .highlight-bracket {
9795 color: #997;
9796 }
9797 .highlight-tag {
9798 color: #170;
9799 }
9800 .highlight-attribute {
9801 color: #00c;
9802 }
9803 .highlight-header {
9804 color: blue;
9805 }
9806 .highlight-quote {
9807 color: #090;
9808 }
9809 .highlight-link {
9810 color: #00c;
9811 }
9812 /* apply the same style to codemirror */
9813 .cm-s-ipython span.cm-keyword {
9814 color: #008000;
9815 font-weight: bold;
9816 }
9817 .cm-s-ipython span.cm-atom {
9818 color: #88F;
9819 }
9820 .cm-s-ipython span.cm-number {
9821 color: #080;
9822 }
9823 .cm-s-ipython span.cm-def {
9824 color: #00f;
9825 }
9826 .cm-s-ipython span.cm-variable {
9827 color: #000;
9828 }
9829 .cm-s-ipython span.cm-operator {
9830 color: #AA22FF;
9831 font-weight: bold;
9832 }
9833 .cm-s-ipython span.cm-variable-2 {
9834 color: #1a1a1a;
9835 }
9836 .cm-s-ipython span.cm-variable-3 {
9837 color: #333333;
9838 }
9839 .cm-s-ipython span.cm-comment {
9840 color: #408080;
9841 font-style: italic;
9842 }
9843 .cm-s-ipython span.cm-string {
9844 color: #BA2121;
9845 }
9846 .cm-s-ipython span.cm-string-2 {
9847 color: #f50;
9848 }
9849 .cm-s-ipython span.cm-meta {
9850 color: #AA22FF;
9851 }
9852 .cm-s-ipython span.cm-qualifier {
9853 color: #555;
9854 }
9855 .cm-s-ipython span.cm-builtin {
9856 color: #008000;
9857 }
9858 .cm-s-ipython span.cm-bracket {
9859 color: #997;
9860 }
9861 .cm-s-ipython span.cm-tag {
9862 color: #170;
9863 }
9864 .cm-s-ipython span.cm-attribute {
9865 color: #00c;
9866 }
9867 .cm-s-ipython span.cm-header {
9868 color: blue;
9869 }
9870 .cm-s-ipython span.cm-quote {
9871 color: #090;
9872 }
9873 .cm-s-ipython span.cm-link {
9874 color: #00c;
9875 }
9876 .cm-s-ipython span.cm-error {
9877 color: #f00;
9878 }
9879 .cm-s-ipython span.cm-tab {
9880 background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
9881 background-position: right;
9882 background-repeat: no-repeat;
9883 }
9884 div.output_wrapper {
9885 /* this position must be relative to enable descendents to be absolute within it */
9886 position: relative;
9887 /* Old browsers */
9888 display: -webkit-box;
9889 -webkit-box-orient: vertical;
9890 -webkit-box-align: stretch;
9891 display: -moz-box;
9892 -moz-box-orient: vertical;
9893 -moz-box-align: stretch;
9894 display: box;
9895 box-orient: vertical;
9896 box-align: stretch;
9897 /* Modern browsers */
9898 display: flex;
9899 flex-direction: column;
9900 align-items: stretch;
9901 z-index: 1;
9902 }
9903 /* class for the output area when it should be height-limited */
9904 div.output_scroll {
9905 /* ideally, this would be max-height, but FF barfs all over that */
9906 height: 24em;
9907 /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
9908 width: 100%;
9909 overflow: auto;
9910 border-radius: 2px;
9911 -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
9912 box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
9913 display: block;
9914 }
9915 /* output div while it is collapsed */
9916 div.output_collapsed {
9917 margin: 0px;
9918 padding: 0px;
9919 /* Old browsers */
9920 display: -webkit-box;
9921 -webkit-box-orient: vertical;
9922 -webkit-box-align: stretch;
9923 display: -moz-box;
9924 -moz-box-orient: vertical;
9925 -moz-box-align: stretch;
9926 display: box;
9927 box-orient: vertical;
9928 box-align: stretch;
9929 /* Modern browsers */
9930 display: flex;
9931 flex-direction: column;
9932 align-items: stretch;
9933 }
9934 div.out_prompt_overlay {
9935 height: 100%;
9936 padding: 0px 0.4em;
9937 position: absolute;
9938 border-radius: 2px;
9939 }
9940 div.out_prompt_overlay:hover {
9941 /* use inner shadow to get border that is computed the same on WebKit/FF */
9942 -webkit-box-shadow: inset 0 0 1px #000;
9943 box-shadow: inset 0 0 1px #000;
9944 background: rgba(240, 240, 240, 0.5);
9945 }
9946 div.output_prompt {
9947 color: #D84315;
9948 }
9949 /* This class is the outer container of all output sections. */
9950 div.output_area {
9951 padding: 0px;
9952 page-break-inside: avoid;
9953 /* Old browsers */
9954 display: -webkit-box;
9955 -webkit-box-orient: horizontal;
9956 -webkit-box-align: stretch;
9957 display: -moz-box;
9958 -moz-box-orient: horizontal;
9959 -moz-box-align: stretch;
9960 display: box;
9961 box-orient: horizontal;
9962 box-align: stretch;
9963 /* Modern browsers */
9964 display: flex;
9965 flex-direction: row;
9966 align-items: stretch;
9967 }
9968 div.output_area .MathJax_Display {
9969 text-align: left !important;
9970 }
9971 div.output_area .rendered_html table {
9972 margin-left: 0;
9973 margin-right: 0;
9974 }
9975 div.output_area .rendered_html img {
9976 margin-left: 0;
9977 margin-right: 0;
9978 }
9979 div.output_area img,
9980 div.output_area svg {
9981 max-width: 100%;
9982 height: auto;
9983 }
9984 div.output_area img.unconfined,
9985 div.output_area svg.unconfined {
9986 max-width: none;
9987 }
9988 /* This is needed to protect the pre formating from global settings such
9989 as that of bootstrap */
9990 .output {
9991 /* Old browsers */
9992 display: -webkit-box;
9993 -webkit-box-orient: vertical;
9994 -webkit-box-align: stretch;
9995 display: -moz-box;
9996 -moz-box-orient: vertical;
9997 -moz-box-align: stretch;
9998 display: box;
9999 box-orient: vertical;
10000 box-align: stretch;
10001 /* Modern browsers */
10002 display: flex;
10003 flex-direction: column;
10004 align-items: stretch;
10005 }
10006 @media (max-width: 540px) {
10007 div.output_area {
10008 /* Old browsers */
10009 display: -webkit-box;
10010 -webkit-box-orient: vertical;
10011 -webkit-box-align: stretch;
10012 display: -moz-box;
10013 -moz-box-orient: vertical;
10014 -moz-box-align: stretch;
10015 display: box;
10016 box-orient: vertical;
10017 box-align: stretch;
10018 /* Modern browsers */
10019 display: flex;
10020 flex-direction: column;
10021 align-items: stretch;
10022 }
10023 }
10024 div.output_area pre {
10025 margin: 0;
10026 padding: 0;
10027 border: 0;
10028 vertical-align: baseline;
10029 color: black;
10030 background-color: transparent;
10031 border-radius: 0;
10032 }
10033 /* This class is for the output subarea inside the output_area and after
10034 the prompt div. */
10035 div.output_subarea {
10036 overflow-x: auto;
10037 padding: 0.4em;
10038 /* Old browsers */
10039 -webkit-box-flex: 1;
10040 -moz-box-flex: 1;
10041 box-flex: 1;
10042 /* Modern browsers */
10043 flex: 1;
10044 max-width: calc(100% - 14ex);
10045 }
10046 div.output_scroll div.output_subarea {
10047 overflow-x: visible;
10048 }
10049 /* The rest of the output_* classes are for special styling of the different
10050 output types */
10051 /* all text output has this class: */
10052 div.output_text {
10053 text-align: left;
10054 color: #000;
10055 /* This has to match that of the the CodeMirror class line-height below */
10056 line-height: 1.21429em;
10057 }
10058 /* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
10059 div.output_stderr {
10060 background: #fdd;
10061 /* very light red background for stderr */
10062 }
10063 div.output_latex {
10064 text-align: left;
10065 }
10066 /* Empty output_javascript divs should have no height */
10067 div.output_javascript:empty {
10068 padding: 0;
10069 }
10070 .js-error {
10071 color: darkred;
10072 }
10073 /* raw_input styles */
10074 div.raw_input_container {
10075 line-height: 1.21429em;
10076 padding-top: 5px;
10077 }
10078 pre.raw_input_prompt {
10079 /* nothing needed here. */
10080 }
10081 input.raw_input {
10082 font-family: monospace;
10083 font-size: inherit;
10084 color: inherit;
10085 width: auto;
10086 /* make sure input baseline aligns with prompt */
10087 vertical-align: baseline;
10088 /* padding + margin = 0.5em between prompt and cursor */
10089 padding: 0em 0.25em;
10090 margin: 0em 0.25em;
10091 }
10092 input.raw_input:focus {
10093 box-shadow: none;
10094 }
10095 p.p-space {
10096 margin-bottom: 10px;
10097 }
10098 div.output_unrecognized {
10099 padding: 5px;
10100 font-weight: bold;
10101 color: red;
10102 }
10103 div.output_unrecognized a {
10104 color: inherit;
10105 text-decoration: none;
10106 }
10107 div.output_unrecognized a:hover {
10108 color: inherit;
10109 text-decoration: none;
10110 }
10111 .rendered_html {
10112 color: #000;
10113 /* any extras will just be numbers: */
10114 }
10115 .rendered_html em {
10116 font-style: italic;
10117 }
10118 .rendered_html strong {
10119 font-weight: bold;
10120 }
10121 .rendered_html u {
10122 text-decoration: underline;
10123 }
10124 .rendered_html :link {
10125 text-decoration: underline;
10126 }
10127 .rendered_html :visited {
10128 text-decoration: underline;
10129 }
10130 .rendered_html h1 {
10131 font-size: 185.7%;
10132 margin: 1.08em 0 0 0;
10133 font-weight: bold;
10134 line-height: 1.0;
10135 }
10136 .rendered_html h2 {
10137 font-size: 157.1%;
10138 margin: 1.27em 0 0 0;
10139 font-weight: bold;
10140 line-height: 1.0;
10141 }
10142 .rendered_html h3 {
10143 font-size: 128.6%;
10144 margin: 1.55em 0 0 0;
10145 font-weight: bold;
10146 line-height: 1.0;
10147 }
10148 .rendered_html h4 {
10149 font-size: 100%;
10150 margin: 2em 0 0 0;
10151 font-weight: bold;
10152 line-height: 1.0;
10153 }
10154 .rendered_html h5 {
10155 font-size: 100%;
10156 margin: 2em 0 0 0;
10157 font-weight: bold;
10158 line-height: 1.0;
10159 font-style: italic;
10160 }
10161 .rendered_html h6 {
10162 font-size: 100%;
10163 margin: 2em 0 0 0;
10164 font-weight: bold;
10165 line-height: 1.0;
10166 font-style: italic;
10167 }
10168 .rendered_html h1:first-child {
10169 margin-top: 0.538em;
10170 }
10171 .rendered_html h2:first-child {
10172 margin-top: 0.636em;
10173 }
10174 .rendered_html h3:first-child {
10175 margin-top: 0.777em;
10176 }
10177 .rendered_html h4:first-child {
10178 margin-top: 1em;
10179 }
10180 .rendered_html h5:first-child {
10181 margin-top: 1em;
10182 }
10183 .rendered_html h6:first-child {
10184 margin-top: 1em;
10185 }
10186 .rendered_html ul {
10187 list-style: disc;
10188 margin: 0em 2em;
10189 padding-left: 0px;
10190 }
10191 .rendered_html ul ul {
10192 list-style: square;
10193 margin: 0em 2em;
10194 }
10195 .rendered_html ul ul ul {
10196 list-style: circle;
10197 margin: 0em 2em;
10198 }
10199 .rendered_html ol {
10200 list-style: decimal;
10201 margin: 0em 2em;
10202 padding-left: 0px;
10203 }
10204 .rendered_html ol ol {
10205 list-style: upper-alpha;
10206 margin: 0em 2em;
10207 }
10208 .rendered_html ol ol ol {
10209 list-style: lower-alpha;
10210 margin: 0em 2em;
10211 }
10212 .rendered_html ol ol ol ol {
10213 list-style: lower-roman;
10214 margin: 0em 2em;
10215 }
10216 .rendered_html ol ol ol ol ol {
10217 list-style: decimal;
10218 margin: 0em 2em;
10219 }
10220 .rendered_html * + ul {
10221 margin-top: 1em;
10222 }
10223 .rendered_html * + ol {
10224 margin-top: 1em;
10225 }
10226 .rendered_html hr {
10227 color: black;
10228 background-color: black;
10229 }
10230 .rendered_html pre {
10231 margin: 1em 2em;
10232 }
10233 .rendered_html pre,
10234 .rendered_html code {
10235 border: 0;
10236 background-color: #fff;
10237 color: #000;
10238 font-size: 100%;
10239 padding: 0px;
10240 }
10241 .rendered_html blockquote {
10242 margin: 1em 2em;
10243 }
10244 .rendered_html table {
10245 margin-left: auto;
10246 margin-right: auto;
10247 border: 1px solid black;
10248 border-collapse: collapse;
10249 }
10250 .rendered_html tr,
10251 .rendered_html th,
10252 .rendered_html td {
10253 border: 1px solid black;
10254 border-collapse: collapse;
10255 margin: 1em 2em;
10256 }
10257 .rendered_html td,
10258 .rendered_html th {
10259 text-align: left;
10260 vertical-align: middle;
10261 padding: 4px;
10262 }
10263 .rendered_html th {
10264 font-weight: bold;
10265 }
10266 .rendered_html * + table {
10267 margin-top: 1em;
10268 }
10269 .rendered_html p {
10270 text-align: left;
10271 }
10272 .rendered_html * + p {
10273 margin-top: 1em;
10274 }
10275 .rendered_html img {
10276 display: block;
10277 margin-left: auto;
10278 margin-right: auto;
10279 }
10280 .rendered_html * + img {
10281 margin-top: 1em;
10282 }
10283 .rendered_html img,
10284 .rendered_html svg {
10285 max-width: 100%;
10286 height: auto;
10287 }
10288 .rendered_html img.unconfined,
10289 .rendered_html svg.unconfined {
10290 max-width: none;
10291 }
10292 div.text_cell {
10293 /* Old browsers */
10294 display: -webkit-box;
10295 -webkit-box-orient: horizontal;
10296 -webkit-box-align: stretch;
10297 display: -moz-box;
10298 -moz-box-orient: horizontal;
10299 -moz-box-align: stretch;
10300 display: box;
10301 box-orient: horizontal;
10302 box-align: stretch;
10303 /* Modern browsers */
10304 display: flex;
10305 flex-direction: row;
10306 align-items: stretch;
10307 }
10308 @media (max-width: 540px) {
10309 div.text_cell > div.prompt {
10310 display: none;
10311 }
10312 }
10313 div.text_cell_render {
10314 /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
10315 outline: none;
10316 resize: none;
10317 width: inherit;
10318 border-style: none;
10319 padding: 0.5em 0.5em 0.5em 0.4em;
10320 color: #000;
10321 box-sizing: border-box;
10322 -moz-box-sizing: border-box;
10323 -webkit-box-sizing: border-box;
10324 }
10325 a.anchor-link:link {
10326 text-decoration: none;
10327 padding: 0px 20px;
10328 visibility: hidden;
10329 }
10330 h1:hover .anchor-link,
10331 h2:hover .anchor-link,
10332 h3:hover .anchor-link,
10333 h4:hover .anchor-link,
10334 h5:hover .anchor-link,
10335 h6:hover .anchor-link {
10336 visibility: visible;
10337 }
10338 .text_cell.rendered .input_area {
10339 display: none;
10340 }
10341 .text_cell.rendered .rendered_html {
10342 overflow-x: auto;
10343 overflow-y: hidden;
10344 }
10345 .text_cell.unrendered .text_cell_render {
10346 display: none;
10347 }
10348 .cm-header-1,
10349 .cm-header-2,
10350 .cm-header-3,
10351 .cm-header-4,
10352 .cm-header-5,
10353 .cm-header-6 {
10354 font-weight: bold;
10355 font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
10356 }
10357 .cm-header-1 {
10358 font-size: 185.7%;
10359 }
10360 .cm-header-2 {
10361 font-size: 157.1%;
10362 }
10363 .cm-header-3 {
10364 font-size: 128.6%;
10365 }
10366 .cm-header-4 {
10367 font-size: 110%;
10368 }
10369 .cm-header-5 {
10370 font-size: 100%;
10371 font-style: italic;
10372 }
10373 .cm-header-6 {
10374 font-size: 100%;
10375 font-style: italic;
10376 }
10377 /*!
10378 *
10379 * IPython notebook webapp
10380 *
10381 */
10382 @media (max-width: 767px) {
10383 .notebook_app {
10384 padding-left: 0px;
10385 padding-right: 0px;
10386 }
10387 }
10388 #ipython-main-app {
10389 box-sizing: border-box;
10390 -moz-box-sizing: border-box;
10391 -webkit-box-sizing: border-box;
10392 height: 100%;
10393 }
10394 div#notebook_panel {
10395 margin: 0px;
10396 padding: 0px;
10397 box-sizing: border-box;
10398 -moz-box-sizing: border-box;
10399 -webkit-box-sizing: border-box;
10400 height: 100%;
10401 }
10402 div#notebook {
10403 font-size: 14px;
10404 line-height: 20px;
10405 overflow-y: hidden;
10406 overflow-x: auto;
10407 width: 100%;
10408 /* This spaces the page away from the edge of the notebook area */
10409 padding-top: 20px;
10410 margin: 0px;
10411 outline: none;
10412 box-sizing: border-box;
10413 -moz-box-sizing: border-box;
10414 -webkit-box-sizing: border-box;
10415 min-height: 100%;
10416 }
10417 @media not print {
10418 #notebook-container {
10419 padding: 15px;
10420 background-color: #fff;
10421 min-height: 0;
10422 -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
10423 box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
10424 }
10425 }
10426 @media print {
10427 #notebook-container {
10428 width: 100%;
10429 }
10430 }
10431 div.ui-widget-content {
10432 border: 1px solid #ababab;
10433 outline: none;
10434 }
10435 pre.dialog {
10436 background-color: #f7f7f7;
10437 border: 1px solid #ddd;
10438 border-radius: 2px;
10439 padding: 0.4em;
10440 padding-left: 2em;
10441 }
10442 p.dialog {
10443 padding: 0.2em;
10444 }
10445 /* Word-wrap output correctly. This is the CSS3 spelling, though Firefox seems
10446 to not honor it correctly. Webkit browsers (Chrome, rekonq, Safari) do.
10447 */
10448 pre,
10449 code,
10450 kbd,
10451 samp {
10452 white-space: pre-wrap;
10453 }
10454 #fonttest {
10455 font-family: monospace;
10456 }
10457 p {
10458 margin-bottom: 0;
10459 }
10460 .end_space {
10461 min-height: 100px;
10462 transition: height .2s ease;
10463 }
10464 .notebook_app > #header {
10465 -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
10466 box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
10467 }
10468 @media not print {
10469 .notebook_app {
10470 background-color: #EEE;
10471 }
10472 }
10473 kbd {
10474 border-style: solid;
10475 border-width: 1px;
10476 box-shadow: none;
10477 margin: 2px;
10478 padding-left: 2px;
10479 padding-right: 2px;
10480 padding-top: 1px;
10481 padding-bottom: 1px;
10482 }
10483 /* CSS for the cell toolbar */
10484 .celltoolbar {
10485 border: thin solid #CFCFCF;
10486 border-bottom: none;
10487 background: #EEE;
10488 border-radius: 2px 2px 0px 0px;
10489 width: 100%;
10490 height: 29px;
10491 padding-right: 4px;
10492 /* Old browsers */
10493 display: -webkit-box;
10494 -webkit-box-orient: horizontal;
10495 -webkit-box-align: stretch;
10496 display: -moz-box;
10497 -moz-box-orient: horizontal;
10498 -moz-box-align: stretch;
10499 display: box;
10500 box-orient: horizontal;
10501 box-align: stretch;
10502 /* Modern browsers */
10503 display: flex;
10504 flex-direction: row;
10505 align-items: stretch;
10506 /* Old browsers */
10507 -webkit-box-pack: end;
10508 -moz-box-pack: end;
10509 box-pack: end;
10510 /* Modern browsers */
10511 justify-content: flex-end;
10512 display: -webkit-flex;
10513 }
10514 @media print {
10515 .celltoolbar {
10516 display: none;
10517 }
10518 }
10519 .ctb_hideshow {
10520 display: none;
10521 vertical-align: bottom;
10522 }
10523 /* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
10524 Cell toolbars are only shown when the ctb_global_show class is also set.
10525 */
10526 .ctb_global_show .ctb_show.ctb_hideshow {
10527 display: block;
10528 }
10529 .ctb_global_show .ctb_show + .input_area,
10530 .ctb_global_show .ctb_show + div.text_cell_input,
10531 .ctb_global_show .ctb_show ~ div.text_cell_render {
10532 border-top-right-radius: 0px;
10533 border-top-left-radius: 0px;
10534 }
10535 .ctb_global_show .ctb_show ~ div.text_cell_render {
10536 border: 1px solid #cfcfcf;
10537 }
10538 .celltoolbar {
10539 font-size: 87%;
10540 padding-top: 3px;
10541 }
10542 .celltoolbar select {
10543 display: block;
10544 width: 100%;
10545 height: 32px;
10546 padding: 6px 12px;
10547 font-size: 13px;
10548 line-height: 1.42857143;
10549 color: #555555;
10550 background-color: #fff;
10551 background-image: none;
10552 border: 1px solid #ccc;
10553 border-radius: 2px;
10554 -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
10555 box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
10556 -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
10557 -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
10558 transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
10559 height: 30px;
10560 padding: 5px 10px;
10561 font-size: 12px;
10562 line-height: 1.5;
10563 border-radius: 1px;
10564 width: inherit;
10565 font-size: inherit;
10566 height: 22px;
10567 padding: 0px;
10568 display: inline-block;
10569 }
10570 .celltoolbar select:focus {
10571 border-color: #66afe9;
10572 outline: 0;
10573 -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
10574 box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
10575 }
10576 .celltoolbar select::-moz-placeholder {
10577 color: #999;
10578 opacity: 1;
10579 }
10580 .celltoolbar select:-ms-input-placeholder {
10581 color: #999;
10582 }
10583 .celltoolbar select::-webkit-input-placeholder {
10584 color: #999;
10585 }
10586 .celltoolbar select::-ms-expand {
10587 border: 0;
10588 background-color: transparent;
10589 }
10590 .celltoolbar select[disabled],
10591 .celltoolbar select[readonly],
10592 fieldset[disabled] .celltoolbar select {
10593 background-color: #eeeeee;
10594 opacity: 1;
10595 }
10596 .celltoolbar select[disabled],
10597 fieldset[disabled] .celltoolbar select {
10598 cursor: not-allowed;
10599 }
10600 textarea.celltoolbar select {
10601 height: auto;
10602 }
10603 select.celltoolbar select {
10604 height: 30px;
10605 line-height: 30px;
10606 }
10607 textarea.celltoolbar select,
10608 select[multiple].celltoolbar select {
10609 height: auto;
10610 }
10611 .celltoolbar label {
10612 margin-left: 5px;
10613 margin-right: 5px;
10614 }
10615 .completions {
10616 position: absolute;
10617 z-index: 110;
10618 overflow: hidden;
10619 border: 1px solid #ababab;
10620 border-radius: 2px;
10621 -webkit-box-shadow: 0px 6px 10px -1px #adadad;
10622 box-shadow: 0px 6px 10px -1px #adadad;
10623 line-height: 1;
10624 }
10625 .completions select {
10626 background: white;
10627 outline: none;
10628 border: none;
10629 padding: 0px;
10630 margin: 0px;
10631 overflow: auto;
10632 font-family: monospace;
10633 font-size: 110%;
10634 color: #000;
10635 width: auto;
10636 }
10637 .completions select option.context {
10638 color: #286090;
10639 }
10640 #kernel_logo_widget {
10641 float: right !important;
10642 float: right;
10643 }
10644 #kernel_logo_widget .current_kernel_logo {
10645 display: none;
10646 margin-top: -1px;
10647 margin-bottom: -1px;
10648 width: 32px;
10649 height: 32px;
10650 }
10651 #menubar {
10652 box-sizing: border-box;
10653 -moz-box-sizing: border-box;
10654 -webkit-box-sizing: border-box;
10655 margin-top: 1px;
10656 }
10657 #menubar .navbar {
10658 border-top: 1px;
10659 border-radius: 0px 0px 2px 2px;
10660 margin-bottom: 0px;
10661 }
10662 #menubar .navbar-toggle {
10663 float: left;
10664 padding-top: 7px;
10665 padding-bottom: 7px;
10666 border: none;
10667 }
10668 #menubar .navbar-collapse {
10669 clear: left;
10670 }
10671 .nav-wrapper {
10672 border-bottom: 1px solid #e7e7e7;
10673 }
10674 i.menu-icon {
10675 padding-top: 4px;
10676 }
10677 ul#help_menu li a {
10678 overflow: hidden;
10679 padding-right: 2.2em;
10680 }
10681 ul#help_menu li a i {
10682 margin-right: -1.2em;
10683 }
10684 .dropdown-submenu {
10685 position: relative;
10686 }
10687 .dropdown-submenu > .dropdown-menu {
10688 top: 0;
10689 left: 100%;
10690 margin-top: -6px;
10691 margin-left: -1px;
10692 }
10693 .dropdown-submenu:hover > .dropdown-menu {
10694 display: block;
10695 }
10696 .dropdown-submenu > a:after {
10697 display: inline-block;
10698 font: normal normal normal 14px/1 FontAwesome;
10699 font-size: inherit;
10700 text-rendering: auto;
10701 -webkit-font-smoothing: antialiased;
10702 -moz-osx-font-smoothing: grayscale;
10703 display: block;
10704 content: "\f0da";
10705 float: right;
10706 color: #333333;
10707 margin-top: 2px;
10708 margin-right: -10px;
10709 }
10710 .dropdown-submenu > a:after.pull-left {
10711 margin-right: .3em;
10712 }
10713 .dropdown-submenu > a:after.pull-right {
10714 margin-left: .3em;
10715 }
10716 .dropdown-submenu:hover > a:after {
10717 color: #262626;
10718 }
10719 .dropdown-submenu.pull-left {
10720 float: none;
10721 }
10722 .dropdown-submenu.pull-left > .dropdown-menu {
10723 left: -100%;
10724 margin-left: 10px;
10725 }
10726 #notification_area {
10727 float: right !important;
10728 float: right;
10729 z-index: 10;
10730 }
10731 .indicator_area {
10732 float: right !important;
10733 float: right;
10734 color: #777;
10735 margin-left: 5px;
10736 margin-right: 5px;
10737 width: 11px;
10738 z-index: 10;
10739 text-align: center;
10740 width: auto;
10741 }
10742 #kernel_indicator {
10743 float: right !important;
10744 float: right;
10745 color: #777;
10746 margin-left: 5px;
10747 margin-right: 5px;
10748 width: 11px;
10749 z-index: 10;
10750 text-align: center;
10751 width: auto;
10752 border-left: 1px solid;
10753 }
10754 #kernel_indicator .kernel_indicator_name {
10755 padding-left: 5px;
10756 padding-right: 5px;
10757 }
10758 #modal_indicator {
10759 float: right !important;
10760 float: right;
10761 color: #777;
10762 margin-left: 5px;
10763 margin-right: 5px;
10764 width: 11px;
10765 z-index: 10;
10766 text-align: center;
10767 width: auto;
10768 }
10769 #readonly-indicator {
10770 float: right !important;
10771 float: right;
10772 color: #777;
10773 margin-left: 5px;
10774 margin-right: 5px;
10775 width: 11px;
10776 z-index: 10;
10777 text-align: center;
10778 width: auto;
10779 margin-top: 2px;
10780 margin-bottom: 0px;
10781 margin-left: 0px;
10782 margin-right: 0px;
10783 display: none;
10784 }
10785 .modal_indicator:before {
10786 width: 1.28571429em;
10787 text-align: center;
10788 }
10789 .edit_mode .modal_indicator:before {
10790 display: inline-block;
10791 font: normal normal normal 14px/1 FontAwesome;
10792 font-size: inherit;
10793 text-rendering: auto;
10794 -webkit-font-smoothing: antialiased;
10795 -moz-osx-font-smoothing: grayscale;
10796 content: "\f040";
10797 }
10798 .edit_mode .modal_indicator:before.pull-left {
10799 margin-right: .3em;
10800 }
10801 .edit_mode .modal_indicator:before.pull-right {
10802 margin-left: .3em;
10803 }
10804 .command_mode .modal_indicator:before {
10805 display: inline-block;
10806 font: normal normal normal 14px/1 FontAwesome;
10807 font-size: inherit;
10808 text-rendering: auto;
10809 -webkit-font-smoothing: antialiased;
10810 -moz-osx-font-smoothing: grayscale;
10811 content: ' ';
10812 }
10813 .command_mode .modal_indicator:before.pull-left {
10814 margin-right: .3em;
10815 }
10816 .command_mode .modal_indicator:before.pull-right {
10817 margin-left: .3em;
10818 }
10819 .kernel_idle_icon:before {
10820 display: inline-block;
10821 font: normal normal normal 14px/1 FontAwesome;
10822 font-size: inherit;
10823 text-rendering: auto;
10824 -webkit-font-smoothing: antialiased;
10825 -moz-osx-font-smoothing: grayscale;
10826 content: "\f10c";
10827 }
10828 .kernel_idle_icon:before.pull-left {
10829 margin-right: .3em;
10830 }
10831 .kernel_idle_icon:before.pull-right {
10832 margin-left: .3em;
10833 }
10834 .kernel_busy_icon:before {
10835 display: inline-block;
10836 font: normal normal normal 14px/1 FontAwesome;
10837 font-size: inherit;
10838 text-rendering: auto;
10839 -webkit-font-smoothing: antialiased;
10840 -moz-osx-font-smoothing: grayscale;
10841 content: "\f111";
10842 }
10843 .kernel_busy_icon:before.pull-left {
10844 margin-right: .3em;
10845 }
10846 .kernel_busy_icon:before.pull-right {
10847 margin-left: .3em;
10848 }
10849 .kernel_dead_icon:before {
10850 display: inline-block;
10851 font: normal normal normal 14px/1 FontAwesome;
10852 font-size: inherit;
10853 text-rendering: auto;
10854 -webkit-font-smoothing: antialiased;
10855 -moz-osx-font-smoothing: grayscale;
10856 content: "\f1e2";
10857 }
10858 .kernel_dead_icon:before.pull-left {
10859 margin-right: .3em;
10860 }
10861 .kernel_dead_icon:before.pull-right {
10862 margin-left: .3em;
10863 }
10864 .kernel_disconnected_icon:before {
10865 display: inline-block;
10866 font: normal normal normal 14px/1 FontAwesome;
10867 font-size: inherit;
10868 text-rendering: auto;
10869 -webkit-font-smoothing: antialiased;
10870 -moz-osx-font-smoothing: grayscale;
10871 content: "\f127";
10872 }
10873 .kernel_disconnected_icon:before.pull-left {
10874 margin-right: .3em;
10875 }
10876 .kernel_disconnected_icon:before.pull-right {
10877 margin-left: .3em;
10878 }
10879 .notification_widget {
10880 color: #777;
10881 z-index: 10;
10882 background: rgba(240, 240, 240, 0.5);
10883 margin-right: 4px;
10884 color: #333;
10885 background-color: #fff;
10886 border-color: #ccc;
10887 }
10888 .notification_widget:focus,
10889 .notification_widget.focus {
10890 color: #333;
10891 background-color: #e6e6e6;
10892 border-color: #8c8c8c;
10893 }
10894 .notification_widget:hover {
10895 color: #333;
10896 background-color: #e6e6e6;
10897 border-color: #adadad;
10898 }
10899 .notification_widget:active,
10900 .notification_widget.active,
10901 .open > .dropdown-toggle.notification_widget {
10902 color: #333;
10903 background-color: #e6e6e6;
10904 border-color: #adadad;
10905 }
10906 .notification_widget:active:hover,
10907 .notification_widget.active:hover,
10908 .open > .dropdown-toggle.notification_widget:hover,
10909 .notification_widget:active:focus,
10910 .notification_widget.active:focus,
10911 .open > .dropdown-toggle.notification_widget:focus,
10912 .notification_widget:active.focus,
10913 .notification_widget.active.focus,
10914 .open > .dropdown-toggle.notification_widget.focus {
10915 color: #333;
10916 background-color: #d4d4d4;
10917 border-color: #8c8c8c;
10918 }
10919 .notification_widget:active,
10920 .notification_widget.active,
10921 .open > .dropdown-toggle.notification_widget {
10922 background-image: none;
10923 }
10924 .notification_widget.disabled:hover,
10925 .notification_widget[disabled]:hover,
10926 fieldset[disabled] .notification_widget:hover,
10927 .notification_widget.disabled:focus,
10928 .notification_widget[disabled]:focus,
10929 fieldset[disabled] .notification_widget:focus,
10930 .notification_widget.disabled.focus,
10931 .notification_widget[disabled].focus,
10932 fieldset[disabled] .notification_widget.focus {
10933 background-color: #fff;
10934 border-color: #ccc;
10935 }
10936 .notification_widget .badge {
10937 color: #fff;
10938 background-color: #333;
10939 }
10940 .notification_widget.warning {
10941 color: #fff;
10942 background-color: #f0ad4e;
10943 border-color: #eea236;
10944 }
10945 .notification_widget.warning:focus,
10946 .notification_widget.warning.focus {
10947 color: #fff;
10948 background-color: #ec971f;
10949 border-color: #985f0d;
10950 }
10951 .notification_widget.warning:hover {
10952 color: #fff;
10953 background-color: #ec971f;
10954 border-color: #d58512;
10955 }
10956 .notification_widget.warning:active,
10957 .notification_widget.warning.active,
10958 .open > .dropdown-toggle.notification_widget.warning {
10959 color: #fff;
10960 background-color: #ec971f;
10961 border-color: #d58512;
10962 }
10963 .notification_widget.warning:active:hover,
10964 .notification_widget.warning.active:hover,
10965 .open > .dropdown-toggle.notification_widget.warning:hover,
10966 .notification_widget.warning:active:focus,
10967 .notification_widget.warning.active:focus,
10968 .open > .dropdown-toggle.notification_widget.warning:focus,
10969 .notification_widget.warning:active.focus,
10970 .notification_widget.warning.active.focus,
10971 .open > .dropdown-toggle.notification_widget.warning.focus {
10972 color: #fff;
10973 background-color: #d58512;
10974 border-color: #985f0d;
10975 }
10976 .notification_widget.warning:active,
10977 .notification_widget.warning.active,
10978 .open > .dropdown-toggle.notification_widget.warning {
10979 background-image: none;
10980 }
10981 .notification_widget.warning.disabled:hover,
10982 .notification_widget.warning[disabled]:hover,
10983 fieldset[disabled] .notification_widget.warning:hover,
10984 .notification_widget.warning.disabled:focus,
10985 .notification_widget.warning[disabled]:focus,
10986 fieldset[disabled] .notification_widget.warning:focus,
10987 .notification_widget.warning.disabled.focus,
10988 .notification_widget.warning[disabled].focus,
10989 fieldset[disabled] .notification_widget.warning.focus {
10990 background-color: #f0ad4e;
10991 border-color: #eea236;
10992 }
10993 .notification_widget.warning .badge {
10994 color: #f0ad4e;
10995 background-color: #fff;
10996 }
10997 .notification_widget.success {
10998 color: #fff;
10999 background-color: #5cb85c;
11000 border-color: #4cae4c;
11001 }
11002 .notification_widget.success:focus,
11003 .notification_widget.success.focus {
11004 color: #fff;
11005 background-color: #449d44;
11006 border-color: #255625;
11007 }
11008 .notification_widget.success:hover {
11009 color: #fff;
11010 background-color: #449d44;
11011 border-color: #398439;
11012 }
11013 .notification_widget.success:active,
11014 .notification_widget.success.active,
11015 .open > .dropdown-toggle.notification_widget.success {
11016 color: #fff;
11017 background-color: #449d44;
11018 border-color: #398439;
11019 }
11020 .notification_widget.success:active:hover,
11021 .notification_widget.success.active:hover,
11022 .open > .dropdown-toggle.notification_widget.success:hover,
11023 .notification_widget.success:active:focus,
11024 .notification_widget.success.active:focus,
11025 .open > .dropdown-toggle.notification_widget.success:focus,
11026 .notification_widget.success:active.focus,
11027 .notification_widget.success.active.focus,
11028 .open > .dropdown-toggle.notification_widget.success.focus {
11029 color: #fff;
11030 background-color: #398439;
11031 border-color: #255625;
11032 }
11033 .notification_widget.success:active,
11034 .notification_widget.success.active,
11035 .open > .dropdown-toggle.notification_widget.success {
11036 background-image: none;
11037 }
11038 .notification_widget.success.disabled:hover,
11039 .notification_widget.success[disabled]:hover,
11040 fieldset[disabled] .notification_widget.success:hover,
11041 .notification_widget.success.disabled:focus,
11042 .notification_widget.success[disabled]:focus,
11043 fieldset[disabled] .notification_widget.success:focus,
11044 .notification_widget.success.disabled.focus,
11045 .notification_widget.success[disabled].focus,
11046 fieldset[disabled] .notification_widget.success.focus {
11047 background-color: #5cb85c;
11048 border-color: #4cae4c;
11049 }
11050 .notification_widget.success .badge {
11051 color: #5cb85c;
11052 background-color: #fff;
11053 }
11054 .notification_widget.info {
11055 color: #fff;
11056 background-color: #5bc0de;
11057 border-color: #46b8da;
11058 }
11059 .notification_widget.info:focus,
11060 .notification_widget.info.focus {
11061 color: #fff;
11062 background-color: #31b0d5;
11063 border-color: #1b6d85;
11064 }
11065 .notification_widget.info:hover {
11066 color: #fff;
11067 background-color: #31b0d5;
11068 border-color: #269abc;
11069 }
11070 .notification_widget.info:active,
11071 .notification_widget.info.active,
11072 .open > .dropdown-toggle.notification_widget.info {
11073 color: #fff;
11074 background-color: #31b0d5;
11075 border-color: #269abc;
11076 }
11077 .notification_widget.info:active:hover,
11078 .notification_widget.info.active:hover,
11079 .open > .dropdown-toggle.notification_widget.info:hover,
11080 .notification_widget.info:active:focus,
11081 .notification_widget.info.active:focus,
11082 .open > .dropdown-toggle.notification_widget.info:focus,
11083 .notification_widget.info:active.focus,
11084 .notification_widget.info.active.focus,
11085 .open > .dropdown-toggle.notification_widget.info.focus {
11086 color: #fff;
11087 background-color: #269abc;
11088 border-color: #1b6d85;
11089 }
11090 .notification_widget.info:active,
11091 .notification_widget.info.active,
11092 .open > .dropdown-toggle.notification_widget.info {
11093 background-image: none;
11094 }
11095 .notification_widget.info.disabled:hover,
11096 .notification_widget.info[disabled]:hover,
11097 fieldset[disabled] .notification_widget.info:hover,
11098 .notification_widget.info.disabled:focus,
11099 .notification_widget.info[disabled]:focus,
11100 fieldset[disabled] .notification_widget.info:focus,
11101 .notification_widget.info.disabled.focus,
11102 .notification_widget.info[disabled].focus,
11103 fieldset[disabled] .notification_widget.info.focus {
11104 background-color: #5bc0de;
11105 border-color: #46b8da;
11106 }
11107 .notification_widget.info .badge {
11108 color: #5bc0de;
11109 background-color: #fff;
11110 }
11111 .notification_widget.danger {
11112 color: #fff;
11113 background-color: #d9534f;
11114 border-color: #d43f3a;
11115 }
11116 .notification_widget.danger:focus,
11117 .notification_widget.danger.focus {
11118 color: #fff;
11119 background-color: #c9302c;
11120 border-color: #761c19;
11121 }
11122 .notification_widget.danger:hover {
11123 color: #fff;
11124 background-color: #c9302c;
11125 border-color: #ac2925;
11126 }
11127 .notification_widget.danger:active,
11128 .notification_widget.danger.active,
11129 .open > .dropdown-toggle.notification_widget.danger {
11130 color: #fff;
11131 background-color: #c9302c;
11132 border-color: #ac2925;
11133 }
11134 .notification_widget.danger:active:hover,
11135 .notification_widget.danger.active:hover,
11136 .open > .dropdown-toggle.notification_widget.danger:hover,
11137 .notification_widget.danger:active:focus,
11138 .notification_widget.danger.active:focus,
11139 .open > .dropdown-toggle.notification_widget.danger:focus,
11140 .notification_widget.danger:active.focus,
11141 .notification_widget.danger.active.focus,
11142 .open > .dropdown-toggle.notification_widget.danger.focus {
11143 color: #fff;
11144 background-color: #ac2925;
11145 border-color: #761c19;
11146 }
11147 .notification_widget.danger:active,
11148 .notification_widget.danger.active,
11149 .open > .dropdown-toggle.notification_widget.danger {
11150 background-image: none;
11151 }
11152 .notification_widget.danger.disabled:hover,
11153 .notification_widget.danger[disabled]:hover,
11154 fieldset[disabled] .notification_widget.danger:hover,
11155 .notification_widget.danger.disabled:focus,
11156 .notification_widget.danger[disabled]:focus,
11157 fieldset[disabled] .notification_widget.danger:focus,
11158 .notification_widget.danger.disabled.focus,
11159 .notification_widget.danger[disabled].focus,
11160 fieldset[disabled] .notification_widget.danger.focus {
11161 background-color: #d9534f;
11162 border-color: #d43f3a;
11163 }
11164 .notification_widget.danger .badge {
11165 color: #d9534f;
11166 background-color: #fff;
11167 }
11168 div#pager {
11169 background-color: #fff;
11170 font-size: 14px;
11171 line-height: 20px;
11172 overflow: hidden;
11173 display: none;
11174 position: fixed;
11175 bottom: 0px;
11176 width: 100%;
11177 max-height: 50%;
11178 padding-top: 8px;
11179 -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
11180 box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
11181 /* Display over codemirror */
11182 z-index: 100;
11183 /* Hack which prevents jquery ui resizable from changing top. */
11184 top: auto !important;
11185 }
11186 div#pager pre {
11187 line-height: 1.21429em;
11188 color: #000;
11189 background-color: #f7f7f7;
11190 padding: 0.4em;
11191 }
11192 div#pager #pager-button-area {
11193 position: absolute;
11194 top: 8px;
11195 right: 20px;
11196 }
11197 div#pager #pager-contents {
11198 position: relative;
11199 overflow: auto;
11200 width: 100%;
11201 height: 100%;
11202 }
11203 div#pager #pager-contents #pager-container {
11204 position: relative;
11205 padding: 15px 0px;
11206 box-sizing: border-box;
11207 -moz-box-sizing: border-box;
11208 -webkit-box-sizing: border-box;
11209 }
11210 div#pager .ui-resizable-handle {
11211 top: 0px;
11212 height: 8px;
11213 background: #f7f7f7;
11214 border-top: 1px solid #cfcfcf;
11215 border-bottom: 1px solid #cfcfcf;
11216 /* This injects handle bars (a short, wide = symbol) for
11217 the resize handle. */
11218 }
11219 div#pager .ui-resizable-handle::after {
11220 content: '';
11221 top: 2px;
11222 left: 50%;
11223 height: 3px;
11224 width: 30px;
11225 margin-left: -15px;
11226 position: absolute;
11227 border-top: 1px solid #cfcfcf;
11228 }
11229 .quickhelp {
11230 /* Old browsers */
11231 display: -webkit-box;
11232 -webkit-box-orient: horizontal;
11233 -webkit-box-align: stretch;
11234 display: -moz-box;
11235 -moz-box-orient: horizontal;
11236 -moz-box-align: stretch;
11237 display: box;
11238 box-orient: horizontal;
11239 box-align: stretch;
11240 /* Modern browsers */
11241 display: flex;
11242 flex-direction: row;
11243 align-items: stretch;
11244 line-height: 1.8em;
11245 }
11246 .shortcut_key {
11247 display: inline-block;
11248 width: 20ex;
11249 text-align: right;
11250 font-family: monospace;
11251 }
11252 .shortcut_descr {
11253 display: inline-block;
11254 /* Old browsers */
11255 -webkit-box-flex: 1;
11256 -moz-box-flex: 1;
11257 box-flex: 1;
11258 /* Modern browsers */
11259 flex: 1;
11260 }
11261 span.save_widget {
11262 margin-top: 6px;
11263 }
11264 span.save_widget span.filename {
11265 height: 1em;
11266 line-height: 1em;
11267 padding: 3px;
11268 margin-left: 16px;
11269 border: none;
11270 font-size: 146.5%;
11271 border-radius: 2px;
11272 }
11273 span.save_widget span.filename:hover {
11274 background-color: #e6e6e6;
11275 }
11276 span.checkpoint_status,
11277 span.autosave_status {
11278 font-size: small;
11279 }
11280 @media (max-width: 767px) {
11281 span.save_widget {
11282 font-size: small;
11283 }
11284 span.checkpoint_status,
11285 span.autosave_status {
11286 display: none;
11287 }
11288 }
11289 @media (min-width: 768px) and (max-width: 991px) {
11290 span.checkpoint_status {
11291 display: none;
11292 }
11293 span.autosave_status {
11294 font-size: x-small;
11295 }
11296 }
11297 .toolbar {
11298 padding: 0px;
11299 margin-left: -5px;
11300 margin-top: 2px;
11301 margin-bottom: 5px;
11302 box-sizing: border-box;
11303 -moz-box-sizing: border-box;
11304 -webkit-box-sizing: border-box;
11305 }
11306 .toolbar select,
11307 .toolbar label {
11308 width: auto;
11309 vertical-align: middle;
11310 margin-right: 2px;
11311 margin-bottom: 0px;
11312 display: inline;
11313 font-size: 92%;
11314 margin-left: 0.3em;
11315 margin-right: 0.3em;
11316 padding: 0px;
11317 padding-top: 3px;
11318 }
11319 .toolbar .btn {
11320 padding: 2px 8px;
11321 }
11322 .toolbar .btn-group {
11323 margin-top: 0px;
11324 margin-left: 5px;
11325 }
11326 #maintoolbar {
11327 margin-bottom: -3px;
11328 margin-top: -8px;
11329 border: 0px;
11330 min-height: 27px;
11331 margin-left: 0px;
11332 padding-top: 11px;
11333 padding-bottom: 3px;
11334 }
11335 #maintoolbar .navbar-text {
11336 float: none;
11337 vertical-align: middle;
11338 text-align: right;
11339 margin-left: 5px;
11340 margin-right: 0px;
11341 margin-top: 0px;
11342 }
11343 .select-xs {
11344 height: 24px;
11345 }
11346 .pulse,
11347 .dropdown-menu > li > a.pulse,
11348 li.pulse > a.dropdown-toggle,
11349 li.pulse.open > a.dropdown-toggle {
11350 background-color: #F37626;
11351 color: white;
11352 }
11353 /**
11354 * Primary styles
11355 *
11356 * Author: Jupyter Development Team
11357 */
11358 /** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
11359 * of chance of beeing generated from the ../less/[samename].less file, you can
11360 * try to get back the less file by reverting somme commit in history
11361 **/
11362 /*
11363 * We'll try to get something pretty, so we
11364 * have some strange css to have the scroll bar on
11365 * the left with fix button on the top right of the tooltip
11366 */
11367 @-moz-keyframes fadeOut {
11368 from {
11369 opacity: 1;
11370 }
11371 to {
11372 opacity: 0;
11373 }
11374 }
11375 @-webkit-keyframes fadeOut {
11376 from {
11377 opacity: 1;
11378 }
11379 to {
11380 opacity: 0;
11381 }
11382 }
11383 @-moz-keyframes fadeIn {
11384 from {
11385 opacity: 0;
11386 }
11387 to {
11388 opacity: 1;
11389 }
11390 }
11391 @-webkit-keyframes fadeIn {
11392 from {
11393 opacity: 0;
11394 }
11395 to {
11396 opacity: 1;
11397 }
11398 }
11399 /*properties of tooltip after "expand"*/
11400 .bigtooltip {
11401 overflow: auto;
11402 height: 200px;
11403 -webkit-transition-property: height;
11404 -webkit-transition-duration: 500ms;
11405 -moz-transition-property: height;
11406 -moz-transition-duration: 500ms;
11407 transition-property: height;
11408 transition-duration: 500ms;
11409 }
11410 /*properties of tooltip before "expand"*/
11411 .smalltooltip {
11412 -webkit-transition-property: height;
11413 -webkit-transition-duration: 500ms;
11414 -moz-transition-property: height;
11415 -moz-transition-duration: 500ms;
11416 transition-property: height;
11417 transition-duration: 500ms;
11418 text-overflow: ellipsis;
11419 overflow: hidden;
11420 height: 80px;
11421 }
11422 .tooltipbuttons {
11423 position: absolute;
11424 padding-right: 15px;
11425 top: 0px;
11426 right: 0px;
11427 }
11428 .tooltiptext {
11429 /*avoid the button to overlap on some docstring*/
11430 padding-right: 30px;
11431 }
11432 .ipython_tooltip {
11433 max-width: 700px;
11434 /*fade-in animation when inserted*/
11435 -webkit-animation: fadeOut 400ms;
11436 -moz-animation: fadeOut 400ms;
11437 animation: fadeOut 400ms;
11438 -webkit-animation: fadeIn 400ms;
11439 -moz-animation: fadeIn 400ms;
11440 animation: fadeIn 400ms;
11441 vertical-align: middle;
11442 background-color: #f7f7f7;
11443 overflow: visible;
11444 border: #ababab 1px solid;
11445 outline: none;
11446 padding: 3px;
11447 margin: 0px;
11448 padding-left: 7px;
11449 font-family: monospace;
11450 min-height: 50px;
11451 -moz-box-shadow: 0px 6px 10px -1px #adadad;
11452 -webkit-box-shadow: 0px 6px 10px -1px #adadad;
11453 box-shadow: 0px 6px 10px -1px #adadad;
11454 border-radius: 2px;
11455 position: absolute;
11456 z-index: 1000;
11457 }
11458 .ipython_tooltip a {
11459 float: right;
11460 }
11461 .ipython_tooltip .tooltiptext pre {
11462 border: 0;
11463 border-radius: 0;
11464 font-size: 100%;
11465 background-color: #f7f7f7;
11466 }
11467 .pretooltiparrow {
11468 left: 0px;
11469 margin: 0px;
11470 top: -16px;
11471 width: 40px;
11472 height: 16px;
11473 overflow: hidden;
11474 position: absolute;
11475 }
11476 .pretooltiparrow:before {
11477 background-color: #f7f7f7;
11478 border: 1px #ababab solid;
11479 z-index: 11;
11480 content: "";
11481 position: absolute;
11482 left: 15px;
11483 top: 10px;
11484 width: 25px;
11485 height: 25px;
11486 -webkit-transform: rotate(45deg);
11487 -moz-transform: rotate(45deg);
11488 -ms-transform: rotate(45deg);
11489 -o-transform: rotate(45deg);
11490 }
11491 ul.typeahead-list i {
11492 margin-left: -10px;
11493 width: 18px;
11494 }
11495 ul.typeahead-list {
11496 max-height: 80vh;
11497 overflow: auto;
11498 }
11499 ul.typeahead-list > li > a {
11500 /** Firefox bug **/
11501 /* see https://github.com/jupyter/notebook/issues/559 */
11502 white-space: normal;
11503 }
11504 .cmd-palette .modal-body {
11505 padding: 7px;
11506 }
11507 .cmd-palette form {
11508 background: white;
11509 }
11510 .cmd-palette input {
11511 outline: none;
11512 }
11513 .no-shortcut {
11514 display: none;
11515 }
11516 .command-shortcut:before {
11517 content: "(command)";
11518 padding-right: 3px;
11519 color: #777777;
11520 }
11521 .edit-shortcut:before {
11522 content: "(edit)";
11523 padding-right: 3px;
11524 color: #777777;
11525 }
11526 #find-and-replace #replace-preview .match,
11527 #find-and-replace #replace-preview .insert {
11528 background-color: #BBDEFB;
11529 border-color: #90CAF9;
11530 border-style: solid;
11531 border-width: 1px;
11532 border-radius: 0px;
11533 }
11534 #find-and-replace #replace-preview .replace .match {
11535 background-color: #FFCDD2;
11536 border-color: #EF9A9A;
11537 border-radius: 0px;
11538 }
11539 #find-and-replace #replace-preview .replace .insert {
11540 background-color: #C8E6C9;
11541 border-color: #A5D6A7;
11542 border-radius: 0px;
11543 }
11544 #find-and-replace #replace-preview {
11545 max-height: 60vh;
11546 overflow: auto;
11547 }
11548 #find-and-replace #replace-preview pre {
11549 padding: 5px 10px;
11550 }
11551 .terminal-app {
11552 background: #EEE;
11553 }
11554 .terminal-app #header {
11555 background: #fff;
11556 -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
11557 box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
11558 }
11559 .terminal-app .terminal {
11560 float: left;
11561 font-family: monospace;
11562 color: white;
11563 background: black;
11564 padding: 0.4em;
11565 border-radius: 2px;
11566 -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
11567 box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
11568 }
11569 .terminal-app .terminal,
11570 .terminal-app .terminal dummy-screen {
11571 line-height: 1em;
11572 font-size: 14px;
11573 }
11574 .terminal-app .terminal-cursor {
11575 color: black;
11576 background: white;
11577 }
11578 .terminal-app #terminado-container {
11579 margin-top: 20px;
11580 }
11581 /*# sourceMappingURL=style.min.css.map */
11582 </style>
11583 <style type="text/css">
11584 .highlight .hll { background-color: #ffffcc }
11585 .highlight { background: #f8f8f8; }
11586 .highlight .c { color: #408080; font-style: italic } /* Comment */
11587 .highlight .err { border: 1px solid #FF0000 } /* Error */
11588 .highlight .k { color: #008000; font-weight: bold } /* Keyword */
11589 .highlight .o { color: #666666 } /* Operator */
11590 .highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
11591 .highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
11592 .highlight .cp { color: #BC7A00 } /* Comment.Preproc */
11593 .highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
11594 .highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
11595 .highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
11596 .highlight .gd { color: #A00000 } /* Generic.Deleted */
11597 .highlight .ge { font-style: italic } /* Generic.Emph */
11598 .highlight .gr { color: #FF0000 } /* Generic.Error */
11599 .highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
11600 .highlight .gi { color: #00A000 } /* Generic.Inserted */
11601 .highlight .go { color: #888888 } /* Generic.Output */
11602 .highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
11603 .highlight .gs { font-weight: bold } /* Generic.Strong */
11604 .highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
11605 .highlight .gt { color: #0044DD } /* Generic.Traceback */
11606 .highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
11607 .highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
11608 .highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
11609 .highlight .kp { color: #008000 } /* Keyword.Pseudo */
11610 .highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
11611 .highlight .kt { color: #B00040 } /* Keyword.Type */
11612 .highlight .m { color: #666666 } /* Literal.Number */
11613 .highlight .s { color: #BA2121 } /* Literal.String */
11614 .highlight .na { color: #7D9029 } /* Name.Attribute */
11615 .highlight .nb { color: #008000 } /* Name.Builtin */
11616 .highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
11617 .highlight .no { color: #880000 } /* Name.Constant */
11618 .highlight .nd { color: #AA22FF } /* Name.Decorator */
11619 .highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
11620 .highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
11621 .highlight .nf { color: #0000FF } /* Name.Function */
11622 .highlight .nl { color: #A0A000 } /* Name.Label */
11623 .highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
11624 .highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
11625 .highlight .nv { color: #19177C } /* Name.Variable */
11626 .highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
11627 .highlight .w { color: #bbbbbb } /* Text.Whitespace */
11628 .highlight .mb { color: #666666 } /* Literal.Number.Bin */
11629 .highlight .mf { color: #666666 } /* Literal.Number.Float */
11630 .highlight .mh { color: #666666 } /* Literal.Number.Hex */
11631 .highlight .mi { color: #666666 } /* Literal.Number.Integer */
11632 .highlight .mo { color: #666666 } /* Literal.Number.Oct */
11633 .highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
11634 .highlight .sc { color: #BA2121 } /* Literal.String.Char */
11635 .highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
11636 .highlight .s2 { color: #BA2121 } /* Literal.String.Double */
11637 .highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
11638 .highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
11639 .highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
11640 .highlight .sx { color: #008000 } /* Literal.String.Other */
11641 .highlight .sr { color: #BB6688 } /* Literal.String.Regex */
11642 .highlight .s1 { color: #BA2121 } /* Literal.String.Single */
11643 .highlight .ss { color: #19177C } /* Literal.String.Symbol */
11644 .highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
11645 .highlight .vc { color: #19177C } /* Name.Variable.Class */
11646 .highlight .vg { color: #19177C } /* Name.Variable.Global */
11647 .highlight .vi { color: #19177C } /* Name.Variable.Instance */
11648 .highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
11649 </style>
11650 <style type="text/css">
11651
11652 /* Temporary definitions which will become obsolete with Notebook release 5.0 */
11653 .ansi-black-fg { color: #3E424D; }
11654 .ansi-black-bg { background-color: #3E424D; }
11655 .ansi-black-intense-fg { color: #282C36; }
11656 .ansi-black-intense-bg { background-color: #282C36; }
11657 .ansi-red-fg { color: #E75C58; }
11658 .ansi-red-bg { background-color: #E75C58; }
11659 .ansi-red-intense-fg { color: #B22B31; }
11660 .ansi-red-intense-bg { background-color: #B22B31; }
11661 .ansi-green-fg { color: #00A250; }
11662 .ansi-green-bg { background-color: #00A250; }
11663 .ansi-green-intense-fg { color: #007427; }
11664 .ansi-green-intense-bg { background-color: #007427; }
11665 .ansi-yellow-fg { color: #DDB62B; }
11666 .ansi-yellow-bg { background-color: #DDB62B; }
11667 .ansi-yellow-intense-fg { color: #B27D12; }
11668 .ansi-yellow-intense-bg { background-color: #B27D12; }
11669 .ansi-blue-fg { color: #208FFB; }
11670 .ansi-blue-bg { background-color: #208FFB; }
11671 .ansi-blue-intense-fg { color: #0065CA; }
11672 .ansi-blue-intense-bg { background-color: #0065CA; }
11673 .ansi-magenta-fg { color: #D160C4; }
11674 .ansi-magenta-bg { background-color: #D160C4; }
11675 .ansi-magenta-intense-fg { color: #A03196; }
11676 .ansi-magenta-intense-bg { background-color: #A03196; }
11677 .ansi-cyan-fg { color: #60C6C8; }
11678 .ansi-cyan-bg { background-color: #60C6C8; }
11679 .ansi-cyan-intense-fg { color: #258F8F; }
11680 .ansi-cyan-intense-bg { background-color: #258F8F; }
11681 .ansi-white-fg { color: #C5C1B4; }
11682 .ansi-white-bg { background-color: #C5C1B4; }
11683 .ansi-white-intense-fg { color: #A1A6B2; }
11684 .ansi-white-intense-bg { background-color: #A1A6B2; }
11685
11686 .ansi-bold { font-weight: bold; }
11687
11688 </style>
11689
11690
11691 <style type="text/css">
11692 /* Overrides of notebook CSS for static HTML export */
11693 body {
11694 overflow: visible;
11695 padding: 8px;
11696 }
11697
11698 div#notebook {
11699 overflow: visible;
11700 border-top: none;
11701 }
11702
11703 @media print {
11704 div.cell {
11705 display: block;
11706 page-break-inside: avoid;
11707 }
11708 div.output_wrapper {
11709 display: block;
11710 page-break-inside: avoid;
11711 }
11712 div.output {
11713 display: block;
11714 page-break-inside: avoid;
11715 }
11716 }
11717 </style>
11718
11719 <!-- Custom stylesheet, it must be in the same directory as the html file -->
11720 <link rel="stylesheet" href="custom.css">
11721
11722 <!-- Loading mathjax macro -->
11723 <!-- Load mathjax -->
11724 <script src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS_HTML"></script>
11725 <!-- MathJax configuration -->
11726 <script type="text/x-mathjax-config">
11727 MathJax.Hub.Config({
11728 tex2jax: {
11729 inlineMath: [ ['$','$'], ["\\(","\\)"] ],
11730 displayMath: [ ['$$','$$'], ["\\[","\\]"] ],
11731 processEscapes: true,
11732 processEnvironments: true
11733 },
11734 // Center justify equations in code and markdown cells. Elsewhere
11735 // we use CSS to left justify single line equations in code cells.
11736 displayAlign: 'center',
11737 "HTML-CSS": {
11738 styles: {'.MathJax_Display': {"margin": 0}},
11739 linebreaks: { automatic: true }
11740 }
11741 });
11742 </script>
11743 <!-- End of mathjax configuration --></head>
11744 <body>
11745 <div tabindex="-1" id="notebook" class="border-box-sizing">
11746 <div class="container" id="notebook-container">
11747
11748 <div class="cell border-box-sizing text_cell rendered">
11749 <div class="prompt input_prompt">
11750 </div>
11751 <div class="inner_cell">
11752 <div class="text_cell_render border-box-sizing rendered_html">
11753 <h1 id="CET-perceptually-uniform-colormaps">CET perceptually uniform colormaps<a class="anchor-link" href="#CET-perceptually-uniform-colormaps">&#182;</a></h1><p>Peter Kovesi at the Center for Exploration Targeting created a very useful set of <a href="https://arxiv.org/abs/1509.03700">perceptually uniform colormaps</a>, many of which can replace the highly non-uniform colormaps provided with Python plotting programs. Here we will show how to use them via the new <a href="https://github.com/bokeh/cetcolors">cetcolors</a> python package, listing all the ones available and allowing you to evaluate how perceptually uniform they are for you, your particular monitor, etc.
11754 We will plot them using <a href="http://matplotlib.org">matplotlib</a> via <a href="http://holoviews.org">holoviews</a>, but identical <a href="http://bokeh.pydata.org">bokeh</a> palettes are also provided, and both Bokeh palettes and Matplotlib colormaps are usable in <a href="https://github.com/bokeh/datashader">datashader</a>. Thus these colormaps can be used in any of those Python packages, as well as any other package that accepts a Python list of normalized RGB tuples or hex colors. See
11755 <a href="http://peterkovesi.com/projects/colourmaps/">Peter's site</a> to download versions for other non-Python packages.</p>
11756 <p>We first make some utilities for sorting and visualizing colormaps:</p>
11757
11758 </div>
11759 </div>
11760 </div>
11761 <div class="cell border-box-sizing code_cell rendered">
11762 <div class="input">
11763 <div class="prompt input_prompt">In&nbsp;[1]:</div>
11764 <div class="inner_cell">
11765 <div class="input_area">
11766 <div class=" highlight hl-ipython2"><pre><span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
11767 <span class="kn">import</span> <span class="nn">holoviews</span> <span class="kn">as</span> <span class="nn">hv</span>
11768 <span class="kn">import</span> <span class="nn">cetcolors</span> <span class="kn">as</span> <span class="nn">cc</span>
11769
11770 <span class="n">hv</span><span class="o">.</span><span class="n">notebook_extension</span><span class="p">()</span>
11771
11772 <span class="kn">import</span> <span class="nn">param</span>
11773 <span class="k">with</span> <span class="n">param</span><span class="o">.</span><span class="n">logging_level</span><span class="p">(</span><span class="s1">&#39;CRITICAL&#39;</span><span class="p">):</span>
11774 <span class="n">hv</span><span class="o">.</span><span class="n">plotting</span><span class="o">.</span><span class="n">mpl</span><span class="o">.</span><span class="n">LayoutPlot</span><span class="o">.</span><span class="n">v17_layout_format</span> <span class="o">=</span> <span class="bp">True</span>
11775 </pre></div>
11776
11777 </div>
11778 </div>
11779 </div>
11780
11781 <div class="output_wrapper">
11782 <div class="output">
11783
11784
11785 <div class="output_area"><div class="prompt"></div>
11786
11787 <div class="output_html rendered_html output_subarea ">
11788
11789 <script src="https://code.jquery.com/ui/1.10.4/jquery-ui.min.js" type="text/javascript"></script>
11790 <script type="text/javascript">function HoloViewsWidget(){
11791 }
11792
11793 HoloViewsWidget.comms = {};
11794 HoloViewsWidget.comm_state = {};
11795
11796 HoloViewsWidget.prototype.init_slider = function(init_val){
11797 if(this.load_json) {
11798 this.from_json()
11799 } else {
11800 this.update_cache();
11801 }
11802 }
11803
11804 HoloViewsWidget.prototype.populate_cache = function(idx){
11805 this.cache[idx].html(this.frames[idx]);
11806 if (this.embed) {
11807 delete this.frames[idx];
11808 }
11809 }
11810
11811 HoloViewsWidget.prototype.process_error = function(msg){
11812
11813 }
11814
11815 HoloViewsWidget.prototype.from_json = function() {
11816 var data_url = this.json_path + this.id + '.json';
11817 $.getJSON(data_url, $.proxy(function(json_data) {
11818 this.frames = json_data;
11819 this.update_cache();
11820 this.update(0);
11821 }, this));
11822 }
11823
11824 HoloViewsWidget.prototype.dynamic_update = function(current){
11825 if (current === undefined) {
11826 return
11827 }
11828 if(this.dynamic) {
11829 current = JSON.stringify(current);
11830 }
11831 function callback(initialized, msg){
11832 /* This callback receives data from Python as a string
11833 in order to parse it correctly quotes are sliced off*/
11834 if (msg.content.ename != undefined) {
11835 this.process_error(msg);
11836 }
11837 if (msg.msg_type != "execute_result") {
11838 console.log("Warning: HoloViews callback returned unexpected data for key: (", current, ") with the following content:", msg.content)
11839 this.time = undefined;
11840 this.wait = false;
11841 return
11842 }
11843 this.timed = (Date.now() - this.time) * 1.1;
11844 if (msg.msg_type == "execute_result") {
11845 if (msg.content.data['text/plain'].includes('Complete')) {
11846 this.wait = false;
11847 if (this.queue.length > 0) {
11848 this.time = Date.now();
11849 this.dynamic_update(this.queue[this.queue.length-1]);
11850 this.queue = [];
11851 }
11852 return
11853 }
11854 }
11855 }
11856 this.current = current;
11857 var kernel = IPython.notebook.kernel;
11858 callbacks = {iopub: {output: $.proxy(callback, this, this.initialized)}};
11859 var cmd = "holoviews.plotting.widgets.NdWidget.widgets['" + this.id + "'].update(" + current + ")";
11860 kernel.execute("import holoviews;" + cmd, callbacks, {silent : false});
11861 }
11862
11863 HoloViewsWidget.prototype.update_cache = function(force){
11864 var frame_len = Object.keys(this.frames).length;
11865 for (var i=0; i<frame_len; i++) {
11866 if(!this.load_json || this.dynamic) {
11867 frame = Object.keys(this.frames)[i];
11868 } else {
11869 frame = i;
11870 }
11871 if(!(frame in this.cache) || force) {
11872 if ((frame in this.cache) && force) { this.cache[frame].remove() }
11873 this.cache[frame] = $('<div />').appendTo("#"+"_anim_img"+this.id).hide();
11874 var cache_id = "_anim_img"+this.id+"_"+frame;
11875 this.cache[frame].attr("id", cache_id);
11876 this.populate_cache(frame);
11877 }
11878 }
11879 }
11880
11881 HoloViewsWidget.prototype.update = function(current){
11882 if(current in this.cache) {
11883 $.each(this.cache, function(index, value) {
11884 value.hide();
11885 });
11886 this.cache[current].show();
11887 this.wait = false;
11888 }
11889 }
11890
11891 HoloViewsWidget.prototype.init_comms = function() {
11892 if ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel !== undefined)) {
11893 var widget = this;
11894 comm_manager = Jupyter.notebook.kernel.comm_manager;
11895 comm_manager.register_target(this.id, function (comm) {
11896 comm.on_msg(function (msg) { widget.process_msg(msg) });
11897 });
11898 }
11899 }
11900
11901 HoloViewsWidget.prototype.process_msg = function(msg) {
11902 }
11903
11904 function SelectionWidget(frames, id, slider_ids, keyMap, dim_vals, notFound, load_json, mode, cached, json_path, dynamic){
11905 this.frames = frames;
11906 this.id = id;
11907 this.slider_ids = slider_ids;
11908 this.keyMap = keyMap
11909 this.current_frame = 0;
11910 this.current_vals = dim_vals;
11911 this.load_json = load_json;
11912 this.mode = mode;
11913 this.notFound = notFound;
11914 this.cached = cached;
11915 this.dynamic = dynamic;
11916 this.cache = {};
11917 this.json_path = json_path;
11918 this.init_slider(this.current_vals[0]);
11919 this.queue = [];
11920 this.wait = false;
11921 if (!this.cached || this.dynamic) {
11922 this.init_comms()
11923 }
11924 }
11925
11926 SelectionWidget.prototype = new HoloViewsWidget;
11927
11928
11929 SelectionWidget.prototype.get_key = function(current_vals) {
11930 var key = "(";
11931 for (var i=0; i<this.slider_ids.length; i++)
11932 {
11933 val = this.current_vals[i];
11934 if (!(typeof val === 'string')) {
11935 if (val % 1 === 0) { var fixed = 1;}
11936 else { var fixed = 10;}
11937 val = val.toFixed(fixed)
11938 }
11939 key += "'" + val + "'";
11940 if(i != this.slider_ids.length-1) { key += ', ';}
11941 else if(this.slider_ids.length == 1) { key += ',';}
11942 }
11943 key += ")";
11944 return this.keyMap[key];
11945 }
11946
11947 SelectionWidget.prototype.set_frame = function(dim_val, dim_idx){
11948 this.current_vals[dim_idx] = dim_val;
11949 var current = this.get_key(this.current_vals);
11950 if(current === undefined && !this.dynamic) {
11951 return
11952 }
11953 if (this.dynamic || !this.cached) {
11954 if (this.time === undefined) {
11955 // Do nothing the first time
11956 } else if ((this.timed === undefined) || ((this.time + this.timed) > Date.now())) {
11957 var key = this.current_vals;
11958 if (!this.dynamic) {
11959 key = this.get_key(key);
11960 }
11961 this.queue.push(key);
11962 return
11963 }
11964 }
11965 this.queue = [];
11966 this.time = Date.now();
11967 this.current_frame = current;
11968 if(this.dynamic) {
11969 this.dynamic_update(this.current_vals)
11970 } else if(this.cached) {
11971 this.update(current)
11972 } else {
11973 this.dynamic_update(current)
11974 }
11975 }
11976
11977
11978 /* Define the ScrubberWidget class */
11979 function ScrubberWidget(frames, num_frames, id, interval, load_json, mode, cached, json_path, dynamic){
11980 this.slider_id = "_anim_slider" + id;
11981 this.loop_select_id = "_anim_loop_select" + id;
11982 this.id = id;
11983 this.interval = interval;
11984 this.current_frame = 0;
11985 this.direction = 0;
11986 this.dynamic = dynamic;
11987 this.timer = null;
11988 this.load_json = load_json;
11989 this.mode = mode;
11990 this.cached = cached;
11991 this.frames = frames;
11992 this.cache = {};
11993 this.length = num_frames;
11994 this.json_path = json_path;
11995 document.getElementById(this.slider_id).max = this.length - 1;
11996 this.init_slider(0);
11997 this.wait = false;
11998 this.queue = [];
11999 if (!this.cached || this.dynamic) {
12000 this.init_comms()
12001 }
12002 }
12003
12004 ScrubberWidget.prototype = new HoloViewsWidget;
12005
12006 ScrubberWidget.prototype.set_frame = function(frame){
12007 this.current_frame = frame;
12008 widget = document.getElementById(this.slider_id);
12009 if (widget === null) {
12010 this.pause_animation();
12011 return
12012 }
12013 widget.value = this.current_frame;
12014 if(this.cached) {
12015 this.update(frame)
12016 } else {
12017 this.dynamic_update(frame)
12018 }
12019 }
12020
12021
12022 ScrubberWidget.prototype.process_error = function(msg){
12023 if (msg.content.ename === 'StopIteration') {
12024 this.pause_animation();
12025 this.stopped = true;
12026 var keys = Object.keys(this.frames)
12027 this.length = keys.length;
12028 document.getElementById(this.slider_id).max = this.length-1;
12029 document.getElementById(this.slider_id).value = this.length-1;
12030 this.current_frame = this.length-1;
12031 }
12032 }
12033
12034
12035 ScrubberWidget.prototype.get_loop_state = function(){
12036 var button_group = document[this.loop_select_id].state;
12037 for (var i = 0; i < button_group.length; i++) {
12038 var button = button_group[i];
12039 if (button.checked) {
12040 return button.value;
12041 }
12042 }
12043 return undefined;
12044 }
12045
12046
12047 ScrubberWidget.prototype.next_frame = function() {
12048 if (this.dynamic || !this.cached) {
12049 if (this.wait) {
12050 return
12051 }
12052 this.wait = true;
12053 }
12054 if (this.dynamic && this.current_frame + 1 >= this.length) {
12055 this.length += 1;
12056 document.getElementById(this.slider_id).max = this.length-1;
12057 }
12058 this.set_frame(Math.min(this.length - 1, this.current_frame + 1));
12059 }
12060
12061 ScrubberWidget.prototype.previous_frame = function() {
12062 this.set_frame(Math.max(0, this.current_frame - 1));
12063 }
12064
12065 ScrubberWidget.prototype.first_frame = function() {
12066 this.set_frame(0);
12067 }
12068
12069 ScrubberWidget.prototype.last_frame = function() {
12070 this.set_frame(this.length - 1);
12071 }
12072
12073 ScrubberWidget.prototype.slower = function() {
12074 this.interval /= 0.7;
12075 if(this.direction > 0){this.play_animation();}
12076 else if(this.direction < 0){this.reverse_animation();}
12077 }
12078
12079 ScrubberWidget.prototype.faster = function() {
12080 this.interval *= 0.7;
12081 if(this.direction > 0){this.play_animation();}
12082 else if(this.direction < 0){this.reverse_animation();}
12083 }
12084
12085 ScrubberWidget.prototype.anim_step_forward = function() {
12086 if(this.current_frame < this.length || (this.dynamic && !this.stopped)){
12087 this.next_frame();
12088 }else{
12089 var loop_state = this.get_loop_state();
12090 if(loop_state == "loop"){
12091 this.first_frame();
12092 }else if(loop_state == "reflect"){
12093 this.last_frame();
12094 this.reverse_animation();
12095 }else{
12096 this.pause_animation();
12097 this.last_frame();
12098 }
12099 }
12100 }
12101
12102 ScrubberWidget.prototype.anim_step_reverse = function() {
12103 this.current_frame -= 1;
12104 if(this.current_frame >= 0){
12105 this.set_frame(this.current_frame);
12106 } else {
12107 var loop_state = this.get_loop_state();
12108 if(loop_state == "loop"){
12109 this.last_frame();
12110 }else if(loop_state == "reflect"){
12111 this.first_frame();
12112 this.play_animation();
12113 }else{
12114 this.pause_animation();
12115 this.first_frame();
12116 }
12117 }
12118 }
12119
12120 ScrubberWidget.prototype.pause_animation = function() {
12121 this.direction = 0;
12122 if (this.timer){
12123 clearInterval(this.timer);
12124 this.timer = null;
12125 }
12126 }
12127
12128 ScrubberWidget.prototype.play_animation = function() {
12129 this.pause_animation();
12130 this.direction = 1;
12131 var t = this;
12132 if (!this.timer) this.timer = setInterval(function(){t.anim_step_forward();}, this.interval);
12133 }
12134
12135 ScrubberWidget.prototype.reverse_animation = function() {
12136 this.pause_animation();
12137 this.direction = -1;
12138 var t = this;
12139 if (!this.timer) this.timer = setInterval(function(){t.anim_step_reverse();}, this.interval);
12140 }
12141
12142 function extend(destination, source) {
12143 for (var k in source) {
12144 if (source.hasOwnProperty(k)) {
12145 destination[k] = source[k];
12146 }
12147 }
12148 return destination;
12149 }
12150
12151 function update_widget(widget, values) {
12152 if (widget.hasClass("ui-slider")) {
12153 widget.slider('option',
12154 {'min': 0, 'max': values.length-1,
12155 'dim_vals': values, 'value': 0,
12156 'dim_labels': values})
12157 widget.slider('option', 'slide').call(widget, event, {'value': 0})
12158 } else {
12159 widget.empty();
12160 for (var i=0; i<values.length; i++){
12161 widget.append($("<option>", {
12162 value: i,
12163 text: values[i]
12164 }))};
12165 widget.data('values', values);
12166 widget.data('value', 0);
12167 widget.trigger("change");
12168 };
12169 }
12170
12171 // Define MPL specific subclasses
12172 function MPLSelectionWidget() {
12173 SelectionWidget.apply(this, arguments);
12174 }
12175
12176 function MPLScrubberWidget() {
12177 ScrubberWidget.apply(this, arguments);
12178 }
12179
12180 // Let them inherit from the baseclasses
12181 MPLSelectionWidget.prototype = Object.create(SelectionWidget.prototype);
12182 MPLScrubberWidget.prototype = Object.create(ScrubberWidget.prototype);
12183
12184 // Define methods to override on widgets
12185 var MPLMethods = {
12186 init_slider : function(init_val){
12187 if(this.load_json) {
12188 this.from_json()
12189 } else {
12190 this.update_cache();
12191 }
12192 this.update(0);
12193 if(this.mode == 'nbagg') {
12194 this.set_frame(init_val, 0);
12195 }
12196 },
12197 populate_cache : function(idx){
12198 var cache_id = "_anim_img"+this.id+"_"+idx;
12199 if(this.mode == 'mpld3') {
12200 mpld3.draw_figure(cache_id, this.frames[idx]);
12201 } else {
12202 this.cache[idx].html(this.frames[idx]);
12203 }
12204 if (this.embed) {
12205 delete this.frames[idx];
12206 }
12207 },
12208 process_msg : function(msg) {
12209 if (!(this.mode == 'nbagg')) {
12210 var data = msg.content.data;
12211 this.frames[this.current] = data;
12212 this.update_cache(true);
12213 this.update(this.current);
12214 }
12215 }
12216 }
12217 // Extend MPL widgets with backend specific methods
12218 extend(MPLSelectionWidget.prototype, MPLMethods);
12219 extend(MPLScrubberWidget.prototype, MPLMethods);
12220 </script>
12221
12222
12223 <link rel="stylesheet" href="https://code.jquery.com/ui/1.10.4/themes/smoothness/jquery-ui.css">
12224 <style>div.hololayout {
12225 display: flex;
12226 align-items: center;
12227 margin: 0;
12228 }
12229
12230 div.holoframe {
12231 width: 75%;
12232 }
12233
12234 div.holowell {
12235 display: flex;
12236 align-items: center;
12237 margin: 0;
12238 }
12239
12240 form.holoform {
12241 background-color: #fafafa;
12242 border-radius: 5px;
12243 overflow: hidden;
12244 padding-left: 0.8em;
12245 padding-right: 0.8em;
12246 padding-top: 0.4em;
12247 padding-bottom: 0.4em;
12248 }
12249
12250 div.holowidgets {
12251 padding-right: 0;
12252 width: 25%;
12253 }
12254
12255 div.holoslider {
12256 min-height: 0 !important;
12257 height: 0.8em;
12258 width: 60%;
12259 }
12260
12261 div.holoformgroup {
12262 padding-top: 0.5em;
12263 margin-bottom: 0.5em;
12264 }
12265
12266 div.hologroup {
12267 padding-left: 0;
12268 padding-right: 0.8em;
12269 width: 50%;
12270 }
12271
12272 .holoselect {
12273 width: 92%;
12274 margin-left: 0;
12275 margin-right: 0;
12276 }
12277
12278 .holotext {
12279 width: 100%;
12280 padding-left: 0.5em;
12281 padding-right: 0;
12282 }
12283
12284 .holowidgets .ui-resizable-se {
12285 visibility: hidden
12286 }
12287
12288 .holoframe > .ui-resizable-se {
12289 visibility: hidden
12290 }
12291
12292 .holowidgets .ui-resizable-s {
12293 visibility: hidden
12294 }
12295 </style>
12296
12297
12298 <div>
12299 <img src='data:image/png;base64,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'
12300 style='width:25px;height:25px; border-radius:12px;'/>
12301
12302 HoloViewsJS successfully loaded in this cell.
12303 </div>
12304
12305 </div>
12306
12307 </div>
12308
12309 </div>
12310 </div>
12311
12312 </div>
12313 <div class="cell border-box-sizing code_cell rendered">
12314 <div class="input">
12315 <div class="prompt input_prompt">In&nbsp;[2]:</div>
12316 <div class="inner_cell">
12317 <div class="input_area">
12318 <div class=" highlight hl-ipython2"><pre><span class="o">%</span><span class="k">opts</span> Image [xaxis=&#39;bare&#39; yaxis=&#39;bare&#39; sublabel_format=None aspect=3 fontsize=13]
12319
12320 <span class="c1"># Collapse all colormap aliases into a single string, and then sort by it</span>
12321 <span class="n">inverse</span> <span class="o">=</span> <span class="p">{}</span>
12322 <span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">cc</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
12323 <span class="k">if</span> <span class="ow">not</span> <span class="n">k</span><span class="p">[</span><span class="o">-</span><span class="mi">2</span><span class="p">:]</span> <span class="o">==</span> <span class="s2">&quot;_r&quot;</span><span class="p">:</span>
12324 <span class="n">inverse</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="o">=</span> <span class="n">inverse</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="p">[])</span>
12325 <span class="n">inverse</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">k</span><span class="p">)</span>
12326 <span class="n">all_cms</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="n">v</span><span class="p">)):</span><span class="n">k</span> <span class="k">for</span> <span class="p">(</span><span class="n">k</span><span class="p">,</span><span class="n">v</span><span class="p">)</span> <span class="ow">in</span> <span class="n">inverse</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span><span class="o">.</span><span class="n">items</span><span class="p">()</span>
12327 <span class="n">all_cms</span><span class="o">.</span><span class="n">sort</span><span class="p">()</span>
12328
12329 <span class="n">aliased_cms</span><span class="o">=</span><span class="p">[(</span><span class="n">k</span><span class="p">,</span><span class="n">v</span><span class="p">)</span> <span class="k">for</span> <span class="p">(</span><span class="n">k</span><span class="p">,</span><span class="n">v</span><span class="p">)</span> <span class="ow">in</span> <span class="n">all_cms</span> <span class="k">if</span> <span class="s2">&quot;,&quot;</span> <span class="ow">in</span> <span class="n">k</span><span class="p">]</span>
12330
12331 <span class="k">def</span> <span class="nf">lay_out_in_columns</span><span class="p">(</span><span class="n">_list</span><span class="p">,</span> <span class="n">cols</span><span class="p">,</span> <span class="n">spacer</span><span class="o">=</span><span class="bp">None</span><span class="p">):</span>
12332 <span class="sd">&quot;&quot;&quot;Given a list, reorder it into the number of columns specified, filling missing items with the given spacer.&quot;&quot;&quot;</span>
12333 <span class="n">rows</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">_list</span><span class="p">)</span><span class="o">*</span><span class="mf">1.0</span><span class="o">/</span><span class="n">cols</span><span class="p">))</span>
12334 <span class="n">padded</span> <span class="o">=</span> <span class="n">_list</span> <span class="o">+</span> <span class="p">[</span><span class="n">spacer</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="n">rows</span><span class="o">*</span><span class="n">cols</span><span class="o">-</span><span class="nb">len</span><span class="p">(</span><span class="n">_list</span><span class="p">))</span>
12335 <span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">padded</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">cols</span><span class="p">,</span><span class="n">rows</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">flat</span><span class="p">)</span>
12336
12337 <span class="n">xs</span><span class="p">,</span><span class="n">ys</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">80</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">10</span><span class="p">))</span>
12338
12339 <span class="k">def</span> <span class="nf">colormaps</span><span class="p">(</span><span class="n">named_cms</span><span class="p">,</span><span class="n">cols</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span><span class="n">array</span><span class="o">=</span><span class="n">xs</span><span class="p">):</span>
12340 <span class="n">images</span> <span class="o">=</span> <span class="p">[</span><span class="n">hv</span><span class="o">.</span><span class="n">Image</span><span class="p">(</span><span class="n">array</span><span class="p">,</span> <span class="n">group</span><span class="o">=</span><span class="n">name</span><span class="p">)(</span><span class="n">style</span><span class="o">=</span><span class="nb">dict</span><span class="p">(</span><span class="n">cmap</span><span class="o">=</span><span class="n">cm</span><span class="p">))</span>
12341 <span class="k">for</span> <span class="n">name</span><span class="p">,</span><span class="n">cm</span> <span class="ow">in</span> <span class="n">named_cms</span><span class="p">]</span>
12342 <span class="k">return</span> <span class="n">hv</span><span class="o">.</span><span class="n">Layout</span><span class="p">(</span><span class="n">lay_out_in_columns</span><span class="p">(</span><span class="n">images</span><span class="p">,</span><span class="n">cols</span><span class="p">,</span><span class="n">hv</span><span class="o">.</span><span class="n">Empty</span><span class="p">()))</span><span class="o">.</span><span class="n">display</span><span class="p">(</span><span class="s1">&#39;all&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">cols</span><span class="p">(</span><span class="n">cols</span><span class="p">)</span>
12343
12344 <span class="k">def</span> <span class="nf">colormaps_by_name</span><span class="p">(</span><span class="n">names</span><span class="p">,</span><span class="n">cols</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span><span class="n">array</span><span class="o">=</span><span class="n">xs</span><span class="p">):</span>
12345 <span class="k">return</span> <span class="n">colormaps</span><span class="p">({(</span><span class="n">k</span><span class="p">,</span><span class="n">v</span><span class="p">)</span> <span class="k">for</span> <span class="p">(</span><span class="n">k</span><span class="p">,</span><span class="n">v</span><span class="p">)</span> <span class="ow">in</span> <span class="n">cc</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">items</span><span class="p">()</span> <span class="k">if</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">names</span><span class="p">},</span><span class="n">cols</span><span class="p">,</span><span class="n">array</span><span class="p">)</span>
12346 </pre></div>
12347
12348 </div>
12349 </div>
12350 </div>
12351
12352 </div>
12353 <div class="cell border-box-sizing text_cell rendered">
12354 <div class="prompt input_prompt">
12355 </div>
12356 <div class="inner_cell">
12357 <div class="text_cell_render border-box-sizing rendered_html">
12358 <h2 id="Named-colormaps">Named colormaps<a class="anchor-link" href="#Named-colormaps">&#182;</a></h2><p>The full list of colormaps included will be shown below, but a useful subset of these maps that cover the various types have been given more convenient names, and we will focus on those first.</p>
12359 <p><strong>For Matplotlib users</strong>: After importing <code>cetcolors</code>, all the colormaps shown here will be available by string name prefixed with <code>cet_</code>, along with reversed versions suffixed with <code>_r</code> (not shown below). For instance, the <code>cetcolors</code> version of "hot" is available as "cet_hot" and "cet_hot_r" (as well as the more verbose names "cet_linear_kryw_0_100_c71" and "cet_linear_kryw_0_100_c71_r" as described below).</p>
12360 <h3 id="Linear-(sequential)-colormaps,-for-plotting-magnitudes:">Linear (sequential) colormaps, for plotting magnitudes:<a class="anchor-link" href="#Linear-(sequential)-colormaps,-for-plotting-magnitudes:">&#182;</a></h3>
12361 </div>
12362 </div>
12363 </div>
12364 <div class="cell border-box-sizing code_cell rendered">
12365 <div class="input">
12366 <div class="prompt input_prompt">In&nbsp;[3]:</div>
12367 <div class="inner_cell">
12368 <div class="input_area">
12369 <div class=" highlight hl-ipython2"><pre><span class="n">colormaps</span><span class="p">([</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">aliased_cms</span> <span class="k">if</span> <span class="s2">&quot;linear&quot;</span> <span class="ow">in</span> <span class="n">i</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="ow">and</span> <span class="s2">&quot;diverging&quot;</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">i</span><span class="p">[</span><span class="mi">0</span><span class="p">]])</span>
12370 </pre></div>
12371
12372 </div>
12373 </div>
12374 </div>
12375
12376 <div class="output_wrapper">
12377 <div class="output">
12378
12379
12380 <div class="output_area"><div class="prompt output_prompt">Out[3]:</div>
12381
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12383 <img 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ty5svzXX39dhIeHV9iP1NRUoVary+zP+Pj4lNl3M8Xcfs9HH30khg4dKoQwvT7L89VXX4l69eqJwsJCk/k//fSTyMzMFEVFReLo0aPC19dXvPPOOybLhoWFiR49ephtsyKGbffjjz8WdevWFQcOHJDlh4aGii5dusjSRo4cKSIiIqrc1iO9R8bd3V12/V+dOnWkm8yTk5ORkpICZ2dn6S8oKAgWFhb4888/AQBLly5Fq1at4OzsDCcnJ3zzzTey064qlQo+Pj5V6pO3t7f0Wq/XIy8vDzdu3MDVq1fh7u4OGxsbKb903WPGjEF8fDyuXLmCM2fOIDExESEhIVVq3xSNRoOsrCxZWmZmJrRardlpQ0JCEBkZiZdeegmenp5ITExEUFCQdKkCUHwK1traGtbW1hg6dChGjRqFmJgYs3UnJydX6gb9VatW4dlnn5Utrw0bNuDGjRsYP348gOpf2lZa6XWi1+ul+4HS0tLK5Jd+P3bsWERHRwMA1q9fjxYtWkin60kZlDSuGNStW1d6bW9vD3d3d9n09vb20jzY2dnhpZdewmeffQYAWL16NUJCQmrl6WjVHWssLCywa9cuXLp0CXq9Hs8//zxGjhwJANJY07x5c9SvXx9A8efus88+w48//mj2YQLJyclwd3eHg4NDheUuXryI/fv3S2OKwfjx43H69GmkpKQgPz8fe/bsQUREhOwymJqysLCAs7Oz9N54mzMlKSkJGzdulLZBJycnzJkzB9evX5fKqNVqk5cAGm8rderUAQCprdTUVOj1eilfpVJBr9dX+pIXqrrHcbwxlpSUhNzcXHh4eEh9aNy4Mezt7XH58mWpnKk2PD09Ze+N5y03NxevvfYafH194ejoCCcnJ2RmZsr67unpCUtLS1kdNfmONd62De9L3+9bWUlJSVi4cKHsM7h27Vpcu3atwuk0Gg2EENUaJ83t91y8eBEfffQRli1bZjK/IsnJyWjUqJHJ2xMA4IknnoBOp4NKpULHjh0xd+5crF+/vky5nJwcfPnll2XG0epauHAhnn/+eekSfmO1tT4f25v9fXx80LRpU9y8eVP6u3XrFu7cuQNPT0/88MMPmDp1KqKioqS8vn37llnx5a3U8qSkpEivk5KSYGNjA1dXV3h5eSEjIwN5eXkmywLFXzB9+vRBdHQ0oqOjMWDAANmXW3UFBgbi/PnzsmtIT5w4gcDAwEpNHxkZid9++w0ZGRlYvnw5zp49a3KjMlCpVJX6AOn1epPXqRu7desWNm/eXOZDsXfvXiQmJkpPOHrjjTdw6dIluLu748yZM5WaL1NKr5Pk5GRp58nLy6tMvvFADgADBgxAdnY2Dh06hOjo6Fp7PCA9Hh63caW6IiIisGnTJiQnJ2PXrl0IDw+vdl3GAgMDcfLkSen97du3ceHChUqNNU2aNEFsbCyuX7+Oc+fOwdbWFvXq1avwYEdlxhq9Xo/09HTZfQWmrFy5Eq1bty5zA+3JkycREhIijQNPPvkknnnmGdkTe/5uPj4+eOWVV2TbYGZmJn7++WepTHVu8m3QoAGSk5Ol90IIJCcnm3yIDD18f/d4o1ary0zr4+MDBweHMn24ffs2OnXqVOU2DBYvXoyEhATExcUhMzMTt27dgqOjo6x9U3XW5DvWeNs2vDd8rkvTaDSyexFLP/nLx8cHs2bNki2TrKws7Nq1q8I+6HQ6eHt7y8bJixcvIicnB61atapwWnP7PQkJCbhx4wYCAgLg5uaGdu3aQQiBVq1amb0nWq/XIykpqUrBj6my69atg4ODAwYOHFjpesqjUqnwzTff4Pjx45gwYUKZ/Kqsz4o8toFM3759kZ+fjwULFkhfYGlpadKj4LKzs2FpaQlXV1cIIbB79258++23sjqqepRfCIFp06YhJycH6enpmD17tnRGpVOnTvD29sa0adOQl5eHpKSkMjfcAkB4eDiio6MRExNTpZ2LvLw85ObmQgiB+/fvIy8vD4WFhQCALl26wMfHB++88w5yc3Nx6tQprFq1SnZDa3mys7Px22+/ASi+UW7cuHFwdHSU5uvs2bM4duwY7t+/j4KCAmzfvh3r16/Hiy++aLbuV199FZ9++im+//57FBYWIicnp8yDDdasWQM3Nzf06dNHlv7xxx/jt99+Q2JiIhITEzFnzhz4+PggMTERLVq0AADMmjULDRs2NL/wjFy7dg2LFi1CQUEBTp06haioKISGhgIAhg0bhqNHj2LLli0oKipCXFxcmUcLWlpaIjQ0FBMnTsQff/yB4cOHV6l9erw9buNKdbVs2RItWrTA4MGD8cQTT6Bp06aVmq6wsBB5eXnIz8+HEAJ5eXmygzNjx47FypUrcfr0ady9exfvvPMOGjVqhKefftps3b/88gvu3LmDwsJC7Nu3D3PnzpXdbLtt2zbpLFRaWhrGjx+P9u3bo1GjRhXW2759e7Rt2xZhYWHIyMiAEAJnzpyRjmgDxU9EWrt2rcmjiE899RRiYmKkHZmjR48iPj5eFvCo1Wp88cUXZuextkyYMAFffvklvvnmGxQUFKCwsBC//vorDh06VOW6jLfH0NBQfPDBB7hw4QLu37+PefPmobCwsMz4S3+Pv3u8cXNzg4WFhewAY/v27REYGIjXX38dN2/eBFC8L7Bp06YazVtOTg5sbGzg5OSEvLw8zJkzB5mZmWanq8l37Pbt2xEXF4eioiJs3LgRJ06cwIgRI0yWbdeuHbZv344bN24gJycHM2bMkB0cePPNN7FkyRIkJCSgqKgI+fn5OHnyJE6cOGG2H2PHjsXChQuRnJyMrKwsTJkyBb169ZKdeTfF3H7Piy++iIsXL+L06dNITEyUDrbs3bvX7HdGnz59YG1tjYkTJyI7OxuFhYU4evQo7ty5g6ysLOzevVsK7E6dOoXZs2dj2LBhZepZtWoVxowZAwsLC1m64cETVRmjhBCoW7cuDh48iOPHj2PUqFHSfi0A/PTTT9i0aROKiopw4MABbN26Vdpfq4qHGsiUPqJUlSNMdnZ2OHDgAM6dO4dmzZrB0dERwcHBSExMBAA899xzCAkJQYcOHeDm5oatW7di0KBB1W4PKP6A9enTBy1btkTz5s3RuHFjLF68GEDxpQM7d+7EiRMn4ObmhkGDBiEkJKTMEx2effZZqNVq6HQ69OjRo0rzW6dOHaSmpuKVV16Bvb299MQRtVqNXbt24cyZM3BxcUG/fv0wderUSv2OQXZ2NoYMGQKtVovmzZujoKAAcXFx0iVyGRkZGD16NJydneHh4YH58+fj888/r9QXX+/evbF69WpMmzYNzs7OaNasGfbs2SMrExUVhfDw8DLrQqfToV69etKfk5MTLCws4OnpKX2AUlNTq7QMAeCZZ57BtWvXULduXfTv3x8TJ06UPqy+vr7YvHkz3n33XTg6OmLJkiUICQmRXS4IAGFhYTh9+jRefPHFGj+GmmrfP2lcqWx9pspERETg1KlTVTqiOW/ePNjZ2WHcuHG4dOkS7OzsYG9vL+WPGDECb731Fvr06QN3d3f8+uuv2LlzZ6X6uHXrVuj1euh0Orz11lv45JNPZI8k/frrr+Hv7w+NRoPOnTvD1dUVO3fuNFuvSqXCrl27YGdnh9atW8PJyQljxoyRnaHZunUr8vLyTO7ULFq0CP7+/ujYsSN0Oh1GjRqFyMhIqezly5dhZWWFp556ymxfjPtUFaXL+/v745tvvsHHH38MT09PeHh4YPTo0bLLDSvbrnFaZGQkhg8fjmeffRZ169ZFfHw89uzZY/ayPCqfksYbW1tbzJ07F8OGDYOzszMWLFgAlUqFHTt2QAiBdu3aQafToXPnzrLfk6tsG8blJk2aJH2P+/n5wcHBodIHHqvzHatSqTBmzBgsXrwYOp0O8+bNw9atW8sNHiZOnIjmzZvD19cXbdu2Rd++fWX5wcHBiIqKQmRkpHTVzaRJk2RnccozdepU9OvXDx06dIC3tzdUKhXWrVtndjpz+z2Gs9iGv7p160KlUsHDw0M2Tptib2+PAwcO4PLly/Dz84ObmxsmT56M+/fvSwc16tevD51Oh+HDh2PkyJFlnup29OhR/PLLLyYPwqekpMDJyanSVwIBD7YXJycnHDhwQHqCn+FR3EOHDkVsbCycnJwQHh6O5cuXy84SVrodUVs3J/wPWrlyJZYsWSKd8TDo3r07evXqhSlTpjyinv0zNGvWDPv37y/3UbG1YcSIEdBqtbLTtnfv3oW7uzv279//2P7wGdHBgwcxcOBAXL16Fba2to+6O4r1+eef4+TJk9J16UT0cPE7VnlmzpwJrVaLt95661F3pQwGMlVw5MgReHp6olGjRvj555+lszLvvvuuVObQoUPo06cPkpOT4eLi8gh7S6bs2rULTz/9NLRaLb755hu8+OKL2LNnD7p06QKg+FTo/PnzsXPnThw9evQR95bItNzcXAwZMgT+/v54//33H3V3iIgqhd+xVNse23tkHgaNRgOtVlvmr7LXD6empqJ79+5wcHDAv/71LwwePBhTp06V8jt27IiBAwfiP//5jyyISUhIKNO24X1Nd0KUWvejcujQITRp0gROTk6YPn06Vq5cKQUxGRkZ0g/WVebHRomAmo8rVbVt2za4uLggOzsb77zzjiyvd+/e5X5ma0qpdRP9k/zd401tqug7dsGCBeWOAeZ+VLy2jR8/vty+mHuqVkBAQJl1Y/gBz5p6mHUrGc/IEBERERGR4vxPnZEhIiIiIqJ/BkvzRcpXnefcE/0T8cTmo8fxiKgYx6NHi2MR0QMPezyqUSADAHCYAaiMHkGsLvl1aZXRr0yrS/ItTJST/ht1xVDOwjjNQv4fACxLXlsaDRqG14Zixj92bVmyMC1E2TTLQqO0kteWRSXlCx7kWRWUTTOUN5Vmed8ordS0snrzS9KMyxe/VhulaS1zAQA2FsXlrS0f/AaElUVeSdqDxwdaWOSW1PGgnKrktdrqwQ9soqQ+laEt2bzcL8kzWm4Wpf4DUBlel6w2lfHWZVGqjHE5ozR1yWtbozSdRfE6rVNy/tDB6Dyi4bWjxYNtwKHkZR210a8tl7zUlaTVMdpk6qjKpumkNKM6UPzaGkYFVSqodBdBj4nS45Gq1DhjnCYrV2qjlW2oJjb2km3A+Ke76pYM1tqiIilNI4rHgTpFxf8dih58ruxKytkUPRh7bErS7IzqsBHFr61L6rcWD/JsS9KsjNKsUVIOD9KsStJsTaRZlaQZpgMAm5I0K1n54teW1g/KWdsV993SpmyehXVJHbaFZdLU1g/qhXVJvlE5lNQn5dkYlbctWYY2RuUN5axNpBnKWxmNadam0krGPiujMdiqgmkNY7yVUd8M3xmytJJlYmXie8ewWRqPlYbXxt9rVqqyaZam0tQcjx4nRvtBKsN+kNo4zTA+PfgJAJVhDDLaJ1KVGZ+M80q+BI3HLKmc2qicRZk0QzmVLK1UOeO2YKottbyPsmnL7iCoTNRbpk1Zf03VYWJ8Vj9Ie5BvYp5LlqvK1M6LcfvS8i+/nEpd8U6OyXlQVzAPxtOqS30Xmay3ssuwbDnTy9dSnlde+6X7ZqrekvqubXn4QT0vLSMiIiIiIsVhIENERERERIrDQIaIiIiIiBSHgQwRERERESkOAxkiIiIiIlIcBjJERERERKQ4DGSIiIiIiEhxGMgQEREREZHiMJAhIiIiIiLFYSBDRERERESKw0CGiIiIiIgUh4EMEREREREpDgMZIiIiIiJSHAYyRERERESkOAxkiIiIiIhIcRjIEBERERGR4jCQISIiIiIixWEgQ0REREREisNAhoiIiIiIFIeBDBERERERKQ4DGSIiIiIiUhwGMkREREREpDgMZIiIiIiISHEYyBARERERkeIwkCEiIiIiIsVhIENERERERIrDQIaIiIiIiBSHgQwRERERESkOAxkiIiIiIlIcBjJERERERKQ4DGSIiIiIiEhxGMgQEREREZHiMJAhIiIiIiLFYSBDRERERESKw0CGiIiIiIgUh4EMEREREREpDgMZIiIiIiJSHAYyRERERESkOAwoR9P9AAAgAElEQVRkiIiIiIhIcRjIEBERERGR4jCQISIiIiIixWEgQ0REREREisNAhoiIiIiIFIeBDBERERERKQ4DGSIiIiIiUhwGMkREREREpDgMZIiIiIiISHEYyBARERERkeIwkCEiIiIiIsVhIENERERERIrDQIaIiIiIiBSHgQwRERERESkOAxkiIiIiIlIcBjJERERERKQ4DGSIiIiIiEhxGMgQEREREZHiMJAhIiIiIiLFYSBDRERERESKw0CGiIiIiIgUh4EMEREREREpDgMZIiIiIiJSHAYyRERERESkOAxkiIiIiIhIcVRCCFHtiVWq2uwLkWLV4GNEtYTjEVExjkePFsciogce9nhUo0CGiIiIiIjoUeClZUREREREpDgMZIiIiIiISHEYyBARERERkeIwkCEiIiIiIsVhIENERERERIrDQIaIiIiIiBSHgQwRERERESkOAxkiIiIiIlIcBjJERERERKQ4DGSIiIiIiEhxGMgQEREREZHiMJAhIiIiIiLFYSBDRERERESKw0CGiIiIiIgUh4EMEREREREpDgMZIiIiIiJSHAYyRERERESkOAxkiIiIiIhIcRjIEBERERGR4jCQISIiIiIixWEgQ0REREREisNAhoiIiIiIFIeBDBERERERKQ4DGSIiIiIiUhwGMkREREREpDgMZIiIiIiISHEYyBARERERkeIwkCEiIiIiIsVhIENERERERIrDQIaIiIiIiBSHgQwRERERESkOAxkiIiIiIlIcBjJERERERKQ4DGSIiIiIiEhxGMgQEREREZHiMJAhIiIiIiLFYSBDRERERESKw0CGiIiIiIgUh4EMEREREREpDgMZIiIiIiJSHAYyRERERESkOAxkiIiIiIhIcRjIEBERERGR4jCQISIiIiIixWEgQ0REREREisNAhoiIiIiIFIeBDBERERERKQ4DGSIiIiIiUhwGMkREREREpDgMZIiIiIiISHEYyBARERERkeIwkCEiIiIiIsVhIENERERERIrDQIaIiIiIiBSHgQwRERERESkOAxkiIiIiIlIcBjJERERERKQ4DGSIiIiIiEhxGMgQEREREZHiMJAhIiIiIiLFYSBDRERERESKw0CGiIiIiIgUh4EMEREREREpDgMZIiIiIiJSHAYyRERERESkOAxkiIiIiIhIcRjIEBERERGR4jCQISIiIiIixWEgQ0REREREisNAhoiIiIiIFIeBDBERERERKQ4DGSIiIiIiUhwGMkREREREpDgMZIiIiIiISHEYyBARERERkeIwkCEiIiIiIsVhIENERERERIrDQIaIiIiIiBSHgQwRERERESkOAxkiIiIiIlIcBjJERERERKQ4DGSIiIiIiEhxGMgQEREREZHiMJAhIiIiIiLFYSBDRERERESKw0CGiIiIiIgUh4EMEREREREpjtlApnv37pg/f770XqPR4OjRow+1U9V18OBBWFlZPepu0GNi9OjRGDt27KPuBj1CShq/6J+rYcOG2LBhw6PuBpnB8YLo4Vm7di38/Pxqvd4qn5HJycnBE088UesdqS0qlepRd8GsTZs2oUuXLtDpdLC2ti6Tv3btWlhYWECr1UKj0UCr1eKll16qlboB4IsvvkDjxo3h4OCAJ598EidPnpTlHz9+HE888QTq1KkDPz8/xMTEVH0mTcjIyEBoaChcXV2h0+nQtm1b/Pnnn1J+bGws2rdvD0dHR9SvXx9vvPEG8vPza6VtIuDxH7+UpiZj1c2bNxEaGgpPT084OTlh5MiRyMzMrJW6zTl58iSCg4Oh1Wrh4uKCAQMGyPJXrFiBpk2bQqvVol27djh48GCttEvK8jiPFykpKVCr1bh69eqj7gqheP9m0KBB0Gq18PDwwNSpU6tcx7fffgu1Wm3yAOyyZcvQtGlTODg4wMfHB2vWrKmFXhf7+eefYWNjg2effVZKy8/Px7hx49CkSRNotVro9XpMnjwZeXl5NWrrYeyjK+rSssLCQgghHnU3aszZ2RmvvvoqPv7443LL+Pr6Ijs7Gzk5OcjOzq50MGGu7oSEBEyYMAErV67ErVu3MGjQIPTu3Ru3b98GAGRnZ6N3794YMmQIMjMz8emnn2LcuHE1PiqVl5eHnj17wtbWFhcuXEBWVhZiYmLg4OAAoHgQGDx4MMLDw5GZmYn//ve/iI+Px9y5c2vULtHjorbHLyEECgsLa62+6qruWDVq1CjcuXMHFy9eRFJSEm7cuIFRo0bVSt0V+e2339CjRw8MHToU6enpSE9Px7///W8pf/PmzZg5cya2bNmCrKwsjB07Fn369MGVK1dq3DZRZZkbL4QQtbJTeP/+/RrX8XfU+Ti1Z8qIESOkwPLo0aPYtm0bPvzww0pPn52djTfffBNPP/10mbx58+Zh+fLl+PLLL3H79m2cPn0aTz31VK30u7CwEGPGjEGXLl1k6QUFBXBzc8Pu3buRlZWFw4cP48CBA5gyZUqttFubqhzIqNVq/PDDDwAenCZatmwZGjRoABcXF4wbN0724UtNTcWQIUPg6ekJLy8vRERESDvNADB9+nT4+vpCo9HAz88Pn3zyiZRnOOIQHR0Nf39/ODg4ICMjw2wfv/jiC+j1eri6umL06NG4e/eulHfhwgV069YNOp0Obdq0wdKlS6FWFy+G7777Du7u7igoKJDK3759GxqNBkeOHMGSJUvw3HPPSXkhISGws7OTItSvvvoK/v7+ZvsXHByMF198EY0aNTJbtqrM1f3ZZ59h8ODB6NmzJ6ysrBAZGQlbW1ts27YNAPD111+jTp06ePvtt2FlZYWgoCAMHDgQq1atqlT7q1atQqtWraDT6eDj44Ply5cDANasWYOsrCz83//9H5ycnAAAzZs3lwKZK1euID8/H6+88goAoF69eujbty8SExNrtDzu3r2LkJAQ6HQ6+Pn5Ye3atbL81atXo3HjxnB0dERISAhGjRol9WHYsGF48803ZeWjo6PRpEkTAEBgYCC+/PJLAEBubi5sbW0RGhoqle3Tpw8WLVpUo/5T7Xrcx6/du3fD398fWq0W/fv3x6RJk9C9e3dZ/5cuXYoOHTrAwcEBJ06cAABERUWhZcuWcHR0RLt27bB3715Zvdu3b0f79u3h5OQEf39/2WVOlVkOte3u3bv47rvvMHPmTNjb28PR0RHvvPMOYmNjayVguHPnDt5++234+vpCq9UiICAAR44cAQDMmTMHvXv3Rnh4OGxtbWFhYYF27dpJ027ZsgUjR45Ey5YtoVKpEBERAXd391o7Anr37l0MGDAA/fr1k76bqjMOPYxLNEjucR4vWrduDQDSEfP33nsPQPGZzrCwMHh7e8PDwwPDhg1Denq6NF3Dhg0xd+5c9OjRA1qtFtu2bcPs2bMRFBSE6dOnw8PDA3Xr1sWsWbOkae7du4fBgwfD09MTOp0O7du3x759+6R8w7JZtGgRGjRogLZt22Lq1KllznQeOHAAOp0O9+7dq3C53759GyEhIXBxcUHDhg2xbt06WFlZ4dChQwCA2bNno2fPnoiMjETdunWldi5fvlzh8q/MslmwYAGCgoKg0WjQqlUr/PjjjxX2FQCSk5Oxf/9+LFq0CA4ODtDr9ZgyZQpWrFhhdlqDSZMmISwsDL6+vrL0rKwsLFiwAEuXLkWbNm0AAE5OTpX+/B88eBBdunSBi4sL3N3dpXHFYMGCBejYsWOZAMre3h5z586Fn58fVCoVGjRogPDwcMTHx1d6nsz57rvvUK9ePcTGxgIArl+/jn79+sHR0RHNmjVDdHQ01Go1Ll++XGE9NT4jk5KSgvT0dFy6dAn//e9/sXnzZmnnLi8vDz169EBAQABSUlJw7tw5pKWl4f/9v/8nTe/v748ffvgBOTk5iIqKwrRp08p8CW/cuBHx8fHIycmBm5tbhf0pKCjAN998g19++QW//vorzp8/j4kTJwIojjz79euHNm3aICMjA9u2bUNUVJR0VOO5556Dg4MDduzYIdW3YcMGeHt746mnnkJQUBCOHDkiRf/79++Ht7c3Dh8+DADYt28fgoODa7hEi6WmpqJevXrw8fHB8OHDkZycXCv1JiYmyr60geIB0RAw/Pzzz9KHxaBt27aVCig+/fRTzJkzBytXrkRWVhZOnTolnZaPj4+Hn58fXn75Zbi6uqJFixays0atW7fG888/jxUrVqCwsBApKSnYuXMnBg4cWKP53bx5M55//nncunULK1aswPjx4/HTTz8BAA4dOoTXX38dq1evxs2bN9G7d2989dVX0rQRERGIiYmRHe1ZvXo1wsPDAQBBQUHSYH7o0CF4e3tj//79AIqPEB06dKjWtgd6OB6n8evixYsYPHgwZs6ciczMTLz55ptYvXp1maOu0dHR2Lx5M27fvo02bdogKioKH374ITZu3IjMzEy89957GDRoEC5dugQA2Lt3L8LDw7F06VLcunULa9euxWuvvYaEhIRKLQdzqjNWCSEghEBRUZGUZjgCffr06RrVDQCvvPIKjh07hri4OGRnZ2Pnzp3w9PQEAMTFxUGj0aBLly5wdXVFp06dZOvM0LfS/TXuV3Vdv34d3bp1Q/369bFz507Y29tXexzi/X9/v8dpvDB8J1+4cAHZ2dmYPn06AGDAgAGwsLDAuXPnkJKSAo1GgxEjRsim/eyzz/Dxxx8jOzsb//rXvwAAhw8fhl6vx7Vr17Bjxw7Mnz9f2okvKirC4MGDcfHiRdy8eRPDhw/H4MGD8ddff0l1Jicn49q1a/jjjz9w7NgxjB07Ft999x2uX78ulVm9ejVGjhwJOzu7CpfzG2+8geTkZJw/fx5nzpzB7t27ZWOFob9eXl64cuUKvv76a+mqj4qWf2WWzeeff47//Oc/yM7ORlBQEF5++eUK+2pYF46OjtDr9VJa27ZtkZycLAukyvP9998jMTERb7/9dpm8n376Cbm5uTh16hQaNWoELy8vjBgxQhaAlefnn39Gr169EB4ejj///BOpqamyg61nzpzB2rVrsXDhQrN1AcX7vIGBgZUqa87KlSsRERGB2NhY9O7dG0DxWS1bW1ukpaUhISEB69atq9xZR2FGt27dxHvvvSe9V6lU4siRI0IIIdasWSN0Op0oKiqS8ocMGSImTZokhBBi8+bNonHjxrL6jh8/LmxsbGTTGHvhhRfElClThBBCJCcnC5VKJRISEsx1UwghRHx8vFCr1SIpKUlK27dvn7CzsxNCCHH48GFha2srcnNzpfzVq1cLtVotvZ83b57o1auX9P6JJ54QS5Yskd7XrVtXxMXFibNnzwpfX1/x/vvvi8mTJwshhGjUqJHYtWtXpfpq6K+VlVWZ9KSkJHHhwgUhhBDXr18XoaGhonHjxuLu3bs1rtvX11esWbNGlvbyyy+L8PBwIYQQY8aMEaGhobL8zz//XPj5+Zlts0WLFuLTTz81mRcUFCTUarVYtmyZuH//vjh+/LhwdXUVGzZskMp89dVXwsPDQ1hZWQm1Wi1GjRpV7nZSGaGhoaJLly6ytJEjR4qIiAghhBBhYWHi5ZdfluU/88wzYvTo0dL7pk2bik2bNgkhhDh37pywsbER169fF0IIERsbK/R6vRBCiMjISDF37lzRrFkzce7cOXHw4EHh5uZW7b5T7VDS+DVv3jzRtWtXWdqoUaNE9+7dZf1fv369rExAQIBYt26dLK1fv37SfPft21fMnTtXlv/6669Ln3lzy6EiNRmrevToIQYOHCgyMzNFenq6CA4OFmq1WsTExNSo7vT0dKFSqcSvv/5qMt/S0lJoNBqRkJAgCgoKxLp164SdnZ24dOmSEEKItWvXCjc3N3H8+HFx//59sWzZMqFWq0VwcLDZeSqPXq8X06ZNEw0bNhSLFi2S5dV0HKLao6TxIjk5WajVapGWliZrr06dOiI/P19Ku3HjhlCpVFI5vV4v5s2bJ6tr1qxZIiAgQJbWoUMHsXTp0nLbd3V1Fd9++60QonjZ2Nvbi/v378vKBAcHi4ULFwohhLh586aws7MTp06dqnC+CgsLhY2NjYiPj5fSLl68KFQqlTh48KDU39LLesuWLRUu/2PHjlVq2SxevFjKP3v2rFCr1SI7O7vCPq9bt07aFzBISkoqs35Myc7OFo0aNRKJiYlCiOL9FsPYLIQQ69evFyqVSvTs2VPcuHFDZGVliQEDBlRqPJowYYIYOnSoybyCggLRvn17ERsbK4QoXqYV1blkyRLh4eEhUlNTzbZbnjVr1ghfX18xefJkERAQIKvrypUrQqVSieTkZClt//79Qq1Wi5SUlArrrfEZGXd3d1nEVKdOHeTk5AAojtBTUlLg7Ows/QUFBcHCwkK6yXvp0qVo1aoVnJ2d4eTkhG+++UZ2OlWlUsHHx6dKffL29pZe6/V65OXl4caNG7h69Src3d1hY2Mj5Zeue8yYMYiPj8eVK1dw5swZJCYmIiQkRMrv0aMH9u7dK5196dmzJ/bs2YNLly7hypUr6NatW5X6aoper0fjxo0BFC/fqKgoXLt2TTqTUBMajQZZWVmytMzMTGi12krlVyQ5Obnc050ajQZeXl547bXXYGlpiXbt2mHkyJHS2a+4uDi8/PLLWLt2LfLy8vDnn38iKyurUkdDKmJ8hMTw3nDpSlpaWpn1X/p9WFgYPvvsMwDFR7H69u0Ld3d3AEDXrl1x7do1XLhwQdoegoKCsGfPHuzbtw89evSoUd/p4Xucxq/KbI+m0pKSkvDqq69KfXRyckJ8fLx0E3BSUhIWLlwoy1+7di2uXbtWqeVQkZqMVevXr4eNjQ2aN2+OTp06YcCAARBCwNXVtUZ1JycnQ6VSVTgWDRw4EE899RQsLCwwcuRING3aFN9//z2A4kuGIyMj8dJLL8HT0xOJiYkICgqS+lVda9asgYODA8aPHy9Lr+k4RH+fx2m8MCUpKQm5ubnw8PCQ+tC4cWPY29vLLs8x1YbhjKWpecvNzcVrr70GX19fODo6wsnJCZmZmbK+e3p6wtLSUlbH2LFjER0dDaD4896iRQvpkrjy3LhxA/n5+bL9uMqOgxUt/+Tk5Eotm7p168qWAQCzY2F5+02GvIq89dZbGDZsGFq1alVu3SqVCtOnT4eLiwu0Wi1mzZqFAwcOmL1ELzk5WboUvrSFCxeiSZMmeP755yusAwCWLFmCDz74AHFxcahfv77Z8hVJT0/H8uXL8fbbb8vqSktLky5hM6jsZ8HSfJHq8/HxQdOmTXHmzBmT+T/88AOmTp2KuLg46RKkIUOGlDmtb7iHpbJSUlLQsGFDAMUbt42NDVxdXeHl5YWMjAzk5eVJwUxKSops2rp166JPnz6Ijo7GrVu3MGDAADg7O0v5QUFBWLFiBTw8PBAaGop27dohNTUVGzZskK5bf1hKL5fqCAwMLPOUslOnTuGFF16Q8o0vrQOKn/BTmdOJer0eFy5cQM+ePcvktW7dWrqe35jhS+HkyZNo3bq1dA+Sm5sbwsPDZUFkdZS+FCU5OVn68Hh5eZVZ/5cvX5ZdoxoaGoqZM2fiwoULWL9+PdatWyfl2dvbo1OnTvjyyy+RkpKCjh074tq1a/jss89w8+bNMteikrL83eOXl5dXmctMTF0bXLo+vV6P2bNnY/DgweXOx+jRo/HWW29Vqh+1oTJjlaenJzZu3Ci93717N+zs7NCpU6ca1W04eHHhwgU0a9asTH55O1LGO6iRkZGIjIwEUHyZaMOGDTFz5swK2zXn/fffx/fff4+goCDExsbC0dERQM3HIXo8/N3jhVqtLjOtj48PHBwccPPmTbPTVsXixYuRkJCAuLg4KcBwc3OTtW+qzgEDBuCNN97AoUOHEB0dXSaIN8XV1RXW1tay/bjSnw9T7Zlb/pVdNtURGBiIrKwsJCcnS+PPiRMnoNfrzQYye/fuRXZ2tnQfsuFStH379uHSpUto3bq1yUtdK8OwT1Zeu6dOnZIuX7x79y4KCgrg7u6O8+fPS+PT3LlzERUVhUOHDkkHlmqibt26WLt2Lfr37y8dSAKKx0GgeOwzLENT692Uh/rUsr59+yI/Px8LFiyQVk5aWhq2b98OoPgpDZaWlnB1dYUQArt378a3334rq6OqO+9CCEybNg05OTlIT0/H7NmzpZ3hTp06wdvbG9OmTUNeXh6SkpJkN9sZhIeHIzo6GjExMdL9EAZBQUE4efIkDh8+jB49ekClUqFr165YtGgRgoKCKtXHoqIi5OXlSQ8JMH4NFD+GOC0tDUDxzWkTJkyAm5ub2S/4ytQdHh6OrVu3Ii4uDvn5+fjggw+Qn58v3Sw3cOBA3LlzB4sXL0Z+fj727duH7du3IyIiwmzbr776KubPn4+ffvoJQgj89ddfOH78OIDiL+K//voLn376KYqKipCYmIiYmBhp5+vJJ5/Ezz//LO3I3bhxA1FRUWjfvr1U/+jRo6t8luOnn37Cpk2bUFRUhAMHDmDr1q3SNaKjRo3Cli1bcPDgQRQVFWHTpk1ljva6urqif//+GDZsGOzt7WWPJwSAnj17YvHixejWrRtUKhW6d++Ow4cP48SJE5XeHujx9HePX8OGDcPRo0exZcsWFBUVIS4uTmqrIm+++SZmzZolXTN/7949HDlyBL///ruUv2TJEiQkJKCoqAj5+fk4efKkyQMLVVWTser8+fO4desWhBA4duwYJk6ciGnTpklnf6tbt5ubG1544QVMmDBB+iK8ePEiLl68CACYMGECtm3bhh9//BFCCGzcuBF//PEHevXqBaB4vf72228Aip+mOG7cOOkmfIOGDRtizpw5VVlUsLS0RExMDAICAtC9e3fpaHZtjEP06P3d44WbmxssLCxkO6rt27dHYGAgXn/9dWmHPSMjA5s2barRvOXk5MDGxgZOTk7Iy8vDnDlzZI9KL4+lpSVCQ0MxceJE/PHHHxg+fLjZadRqNUaMGIFZs2bhxo0byMnJwYwZM8zeK2Fu+Vd32VRmnej1egQFBWHy5MnIycnBpUuX8MEHH2DcuHFmpz169Kh09U9iYiL69++PwYMHS/cneXt7o0+fPliwYAFu3bqFnJwczJs3D7169TJ7r1FERAR27tyJmJgY5OfnIzc3V3qU/JYtW3Du3Dmp3XHjxqFTp07S/T5A8QGd1atX4+DBgyaDmDVr1lQ5KAaK9/f27NmDyMhI6YEIXl5e6NatG6ZOnYrbt28jIyNDeoCFOWZ7UHrjqcrj/uzs7HDgwAGcO3cOzZo1g6OjI4KDg6Uv3Oeeew4hISHo0KED3NzcsHXrVgwaNKja7QHFH5w+ffqgZcuWaN68ORo3bozFixcDACwsLLBz506cOHECbm5uGDRoEEJCQsr83sqzzz4LtVoNnU5XZse5QYMG8PX1leYHKA5ucnJyKr3jum7dOtjZ2eH5559HYWEh7OzsZKc34+Pj0bFjR2g0GrRs2RKZmZnYu3cv7O3ta1z3U089heXLlyMsLAxOTk7YunUrvv32W+lMkk6nQ2xsLL766is4OTlh3LhxWLlyJTp27Gi27QkTJmDatGkYM2aM9PsLhkDG29sbsbGxiIqKgk6nw9ChQzFnzhzpTFDnzp3x6aefYtKkSXB0dERAQABsbW3x+eefS/VfvnxZ9gSnyhg6dChiY2Ph5OSE8PBwLF++XNoR6tKlCz755BOMHj0azs7OiI2NxcCBA2WXHgLFg8GpU6cwZsyYMvUb1r1hx0Kn06FZs2bw9vYuc1kb/f2UNH75+vpi8+bNePfdd+Ho6IglS5YgJCREtj2aqi8sLAyTJ0+WtmO9Xo958+ZJT18MDg5GVFQUIiMjpTPTkyZNwp07dyrdt/LUZKw6dOgQ/P39odFoMHLkSLzxxhuYMWNGrdQdHR2N1q1bo2vXrtBqtRgwYIB00/ELL7yA999/H8OHD4ejoyM++eQT7N69W7qMITs7G0OGDIFWq0Xz5s1RUFCAuLg4aT3k5+cjPT29SmOR8XpbtWoVevTogS5duuDKlSu1Mg5R7VDSeGFra4u5c+di2LBhcHZ2xoIFC6BSqbBjxw4IIdCuXTvodDp07txZ9jtIlW3DuNykSZOg0+lQr149+Pn5wcHBQTpbYk5YWBhOnz6NF1980ezZCYOlS5fC29sbTZo0QatWraTv19KfCWPmln91l01ll1dMTAwKCwvh5eWFTp06YdCgQdJZ3Yq4u7ujXr160p+9vT3s7e3h4eEhlVm3bh3c3Nyg1+vRpEkT1KlTp8wTWE1p1aoVYmNjsXz5cnh4eMDHxwfr168HALi4uMja1Wq1sLGxkS4xvHz5MhYvXozr168jMDBQ+j2vli1bSvWnpqZW+3aKNm3aIC4uDu+99x4++OADAMXL8M6dO6hfvz6eeeYZDB06FEDF6x0AVKI2rldSsJUrV2LJkiXSETiD7t27o1evXo/lM7P/F+Xm5qJ58+Y4e/ZspXZkqqtz587o37+/7MesDNeZJiUlSac/if4OI0aMgFarrdJjPOnhiouLw0cffYRdu3Y9tDY4DtE/xd27d+Hu7o79+/dX+8dFf//9d7Ro0QJpaWmye1jo0erevTs+/PBD2ZUzten777/HwIEDZT+hYoqifhCzNhw5ckR6LOnPP/+MDz/8sMzj9w4dOoTjx48jLCzsUXSRTLC1tUVSUlKtBzFff/017ty5g/z8fKxatQonTpzAkCFDpPyCggK8//77GDhwIHce6KHbtWsXbt26hcLCQuzYsQNbt24tMz7Ro9W9e/daD2I4DtE/kRACS5Ysgb+/f5WCmKSkJPz4448oKirC9evXMWnSJHTt2pVBzGMmLi6uVoOYxMRE6R6nS5cu4d///jeGDRtmfsJqP0ftEXFwcBAajabMX+/evSs1/caNG4W3t7eoU6eO0Ov1YvLkySIvL0/K79Chg3B2di7ziOKqGDduXJl+Gt7X5NF1D7tuc2JiYspt2/gxykoyfPhw4ejoKFootj8AACAASURBVLRarWjbtq30KEIhHjzKMjAwUFy+fPkR9pL+KcyNX2+//bZwdXUVGo1G+Pv712gcqg01+cz/U8fBh4HjEJlS0/2dRyk9PV04ODgIX19fcfLkSVne/Pnzy/38JiQkiHPnzomAgACh0WiEh4eHGDp0qLh69eojmpNi/v7+ZdaDg4NDmcdWl3b58uVy53X8+PE16tPDrPtRiIuLE40bNxYODg7Cy8tLhIeHi6ysLLPT/c9fWkZERERERMrzP3dpGRERERERKV+Nfkemqk8UI/qn4onNR4/jEVExjkePFsciogce9nhU4x/ErIf3ABg9vlhtJf8PABYl+ZZG5SysTP83LmdhWba80S/HqiwN01oYpZW8LvmvsjLOKzkBZakySiv5b130oC3rwuL/VvkAAGGT+6C8ze2S2Xvwi6oWJa8trB6Us7Asfm1pdadMmtoiV/a+eNq7srzi2TKUf/A7MJYlbVio80tmM9+o/P3i7ls+SLNSF5SUK3iQVvLatqR8cbniebY2/LcolPJsLYpK8h5sjIbXNmqVUVrxa7uS54pbGz1f3NpEmm3J+rVWP1hHViWvrdQP1rNNyfZjSLM02lYs1SV5lrZSmoW6+FF9aosHaSqL4ocEqKy0JXkPHgOpUmtK0nQP6rAo/tVstfrBj6Gq1S4l5V2NpnWHml9ajw83Kxg/1t6waRmnqdTyPACARan/RuWFYVM02v5NlTOMJTCq19CWysJQRlVunvG0pvqmsihbXqrPuB9SOVXZNOMRvyS/onpN9U1Wr6U8TVaHiXkuPS+yaY36VqZ9M30r3Q9T7cvmxVR5S/n/cufLynzfbI3qsC/JdzBaRw4laU4l/zXGeSWvNUaLzdFClElzUMn/A4AGQDPVDdBjwviaFxPbi8k0dan/AKAqVc74K0ddyTRVJcuVTqtsvab6ayqtquVrkmYqr7LzUJllU52+Vbf96tRb0bZU3fLmpi2dNhsPHS8tIyIiIiIixWEgQ0REREREisNAhoiIiIiIFIeBDBERERERKQ4DGSIiIiIiUhwGMkREREREpDgMZIiIiIiISHEYyBARERERkeIwkCEiIiIiIsVhIENERERERIrDQIaIiIiIiBSHgQwRERERESkOAxkiIiIiIlIcBjJERERERKQ4DGSIiIiIiEhxGMgQEREREZHiMJAhIiIiIiLFYSBDRERERESKw0CGiIiIiIgUh4EMEREREREpDgMZIiIiIiJSHAYyRERERESkOAxkiIiIiIhIcRjIEBERERGR4jCQISKi/8/e/cfnWC9+HH/v3sbM7nsbG5vR5sfmtxVCp8hEOFF+lIMQjh9JdaRDpIP5fdBJTik/Twj5EhWqU8dviSilUhG2hvyK2ciG7fr+oV12220bmx+fej0fDw+7r+tzfa7Pdd3X/bmu9339uAEAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4XpZlWdc8sZdXYbYFMFYBPkYoJPRHwEX0RzcXfRFwyfXujwoUZAAAAADgZuDSMgAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgA+B3Ly4uTuPGjbNfO51Obd269Sa2CICp6E9+X8aOHau4uLib3Yzfjcs/H9fbDQsyJn3w169fL19f31zLlC9fXgsXLrxBLUJeevTooT59+ngcl5iYKIfDoUOHDt3gVuFWlZqaqvr169/sZhhj7969atasmQICAnTbbbfpX//6V76mO3TokNq0aaOoqCg5HA6PfWZedZ89e1Y9e/ZUcHCwSpQood69eys9Pb3Ay3Ts2DG1a9dOLpdLpUuX1pAhQwpcJ/6YbuX+hP1f/nh5eeWr3IcffqgaNWrI399ftWrV0scff5yv6eLj4+Xr6yuXyyWn0ymXy6WhQ4cWSt25mTt3rry9vd3m++ijj9rjt27dqlatWiksLEzBwcG688479e677xZ4vjfSTTsjcyt/8KX8b9TXW1YnlLUBOp1O3XbbbfmaNjMzU6NHj1aFChXkcrl077336uuvvy6UunMzfvx4u86seh0OhwYMGCBJOnnypO69916VLl1aQUFBio6Ovu7p/VZ5P4GMjAxZllVo9VmWpYyMjEKr73KZmZlq3bq1qlevrl9++UXvvvuu/vnPf2rJkiV5TutwONS8eXMtWrRI5cqVu6a6n376ae3evVt79uzR7t27tWvXLg0cOLDAy9W5c2f7AG/r1q1avny5Jk2aVOB68+v8+fM3bF74/cqrP7Esq1D2f9djey3sOq/3Z2r//v1q3769hg0bppSUFA0ZMkRt27bVTz/9lK/p4+LilJKSotTUVKWkpGj8+PGFVnduKlas6DbfBQsW2ONOnDihjh07ateuXTp58qReeOEFderUSZ9//nmB55sfhfGe/SEvLSvsA4nrzcvLS7t377Y3xPxu2C+++KIWLlyotWvX6sSJE7rnnnvUvHlznTlzpsB152bo0KH2ByYlJUVffPGFHA6HunbtKkkqXry4Xn/9dR06dEjJycn63//+pzfffFOzZs0q8LyB/HA4HNq8ebOki99YRUdH69///rfKlSunkiVL6vHHH3frI5KSkvTII48oPDxcERER6tu3r06fPm2PHzZsmCpWrCin06no6Gi9/PLL9risLwzmzJmj6tWrKyAgQMeOHcu1fatWrVL16tXlcrn04IMPauDAgW6XPjgcDk2dOlV33nmnAgIC7J3OzJkzVbNmTQUFBalOnTr2N3rJycny9/fXV1995TafRo0aaezYsbm2Zf369frpp580btw4FS1aVHfccYf69u2r119/PdfpJCksLEz9+vXTXXfdJYcj5+4mr7rT0tK0YMECjRkzRiEhIQoJCdHo0aM1d+5cnTt3Ls/579y5Uy1btlSpUqUUEhKi+++/X9LFg4bVq1dr8uTJCggIUFRUlJ577rl8LVNuxo0bp3LlyikkJEQDBw5U06ZNNWrUKHtZfX199eabb6pixYoKCQmRJE2dOlVVq1aVy+VSVFSUnn/+eXvbGzJkiNq0aeM2jzVr1igwMFBnz54tUFtReG7l/uT222+XJMXExMjlctmf9xMnTqhXr1667bbbVLp0aXXs2FFHjx61pytfvrxGjx6tJk2ayOVyafny5YqPj1fTpk01bNgwlS5dWmFhYRo5cqQ9zdmzZ9W+fXuFh4crMDBQdevW1f/+9z97fNa6mTx5ssqVK6fatWsXaBuPi4vTM888o7Zt2yooKEgvvfSSJGnjxo1q2LChSpYsqejo6BxneS/vX48fP57rfLK3v27duurUqZN8fHzUuXNn1a5dW3Pnzs3X9Ner7gsXLmjcuHGqUqWKXC6XoqOjtWzZsnzNt2XLlurSpYtKlCghSXrooYcUGxurjRs3Fmh5smRmZqpfv35q0KCBjh07dsV+sCBuWpC5lT/4WebNm6eoqCiFhISoR48ebgEgO0+XosXHx6tZs2b267w6jdxYlqXMzMx8lc1u6dKleuKJJxQZGSkfHx/Fx8frl19+0fLlywtctyTNmDFDtWrVUmBgoCIjIzVt2jSP5aZPn6477rhDderUkSQVKVJEVatWlbe3t6SLG7rD4dAPP/xwTe3wZMyYMapSpYr27t0r6eJyfvDBB6pcubKCg4PVtm1bt23gzJkz+vvf/66KFSvK5XKpRo0a+uSTTwqtPbi1JSYm6ujRo9q3b58+++wzLVmyRG+99ZYkKT09XU2aNFGNGjWUmJioXbt26eDBg/rb3/5mT1+9enVt3rxZqampmjlzpoYOHZrjsoBFixZp3bp1Sk1NVWho6BXbsnfvXrVv314jRoxQcnKyBgwYoNmzZ+f4VnXOnDlasmSJTp8+rTvuuEMzZ87UpEmTtGjRIiUnJ2vs2LFq166d9u3bp6CgIHXo0MHty4Ldu3dr69at+utf/5rrutm5c6diYmLk7+9vD6tdu3aOUHQt8qr7+++/V3p6umrXru02/tdff9Xu3btzrfvw4cNq3Lix4uLilJiYqMOHD9uXj+3cuVNBQUGKiopyqzchIcFtv3I15s2bp3//+99atWqVjhw5ovDwcG3YsMGtTEZGhj744AN9+eWXOnLkiCSpXLly+u9//6uUlBS9++67mjNnjv0+9enTRx9++KFdVpJmz56tLl26qFixYtfUTlx/t1J/kvVZ2rNnj1JSUjRs2DBJUps2beTt7a1du3YpMTFRTqdTnTt3dpt21qxZmjJlilJSUvTQQw9JuhgSoqKi9PPPP+vdd9/VuHHj9Omnn0q6uC9v37699u7dqxMnTqhTp05q3769fvnlF7vOhIQE/fzzz/rxxx+1bdu2Am/j//nPfzRgwAAlJyfr6aef1q5du/TAAw/oueee0y+//KJVq1bp1Vdf1ZtvvinpUv/6wgsvKDk5WU899ZRmzpyZ53yy1mXWcUyWq+kLt2zZolKlSqlixYrq06ePW4AqSN3Dhg3TwoUL9fbbbyslJUXr169XTEyMPT4pKUllypRRZGSkOnXqpISEhCvWdfjwYX377bd2AC6I06dPq3Xr1jpy5IjWr19vb6ee+sGCuGXOyNxKH3zpYsJduXKlvvnmG3333XfavXt3rpczeDp1m31YfjqN3Opu0KCBSpUqpSZNmmj9+vX5ms6yLLcwmPX6yy+/LHDdr732mkaNGqXp06fr1KlT2rFjh8dLBc+dO6e5c+fq8ccfzzGudevW8vf3V8WKFXX69Gn17ds3X/POzYULF9SzZ099+OGH+vTTT1WxYkV73Pz587Vp0yYlJSXJy8tLXbp0scf17NlT27Zt09q1a5WSkqL33ntP4eHhBW4PzODv769Ro0bJ19dXFStW1H333aft27dLklasWCFJGjFihIoUKaLAwEDFx8drwYIF9uerc+fOKl26tCSpcePGeuCBB7R69Wq3eYwcOVKhoaHy8fHJ9VKPt956Sw0aNFCHDh3kcDjUpEkT+yAiu0GDBikqKkpeXl7y9fXV1KlTNXz4cNWoUUOS1KJFC8XFxdn9aO/evbVw4UL7TMbs2bPVokULhYWF5bpuUlNTFRgY6DYsKChIKSkpuU6XH3nVnRUqXC6XPT6rfF7znz9/vqKjozV48GAVK1ZMPj4+atKkSa7zzU+9uc2vb9++qlWrlry9vTVo0CCVKVPGrYyXl5cmTpwop9MpPz8/SVLbtm3tS3pjY2PVtWtXe9upUKGCGjVqZH8re/LkSS1fvly9e/e+pjbixriV+pMs2Y8FPv/8c33xxRd65ZVXFBAQID8/P02YMEFr1qxxu5emT58+qlWrliSpaNGiki6e2endu7ccDofq16+v22+/3V624sWLq3PnzvL395e3t7eeffZZFSlSRNu2bbPrLFKkiP75z3+qaNGi8vPzK/A2/vDDD+vee++VJPn5+em1115Thw4d1KpVK7u9/fv317x58yRJixcvVv369dWpUyc5HA41a9YsxxmhKylIX9ihQwft2rVLR48e1Zo1a3Tw4EG3fr0gdU+bNk2TJ09W9erVJUllypSx9wNZtxQcOnRI27Ztk5+fn5o1a+bxbNevv/6qhx9+WK1bt1bjxo3znG9uDhw4oIYNGyomJkbLli2ztx/Jcz9YELdMkLnVPvhZKzogIEChoaEaNWqU5s+ff03Ltn379nx1Gp6EhITo008/1f79+5WYmKh27dqpZcuW+uabb/Kcb6tWrfTqq6/qxx9/VHp6ul544QVlZmbaH4yC1P3KK6/ohRde0F133SVJKlGiRI5vEyRpyZIlOn/+vDp16pRj3IoVK3TmzBlt2bJFXbt2LfApxuTkZLVs2VKnT5/WmjVrFBwc7DY+6/0PCAjQpEmT9PHHH+vw4cM6duyYlixZounTp9sHFBUqVFCFChUK1B6Yo1SpUm59QvHixZWamirp4jeIiYmJKlGihP2vadOm8vb21uHDhyVdvDyoVq1aKlGihIKDg7Vy5Uq3M35eXl6KjIzMV1sOHjyYo6ynaS8ftn//fvXv399uY3BwsNatW6eDBw9Kku6++26VKVNGS5cuVUZGhubNm3fFB2Rk53Q6derUKbdhycnJbuHiWuVVt9PplOQeLrLK5zX/hIQEt28l8zPf7PO8Wp7et8vvC3I4HIqIiHAbtmjRItWrV08hISEKDg7WtGnT3LadPn36aM6cOZKkN998U9WqVSuUb0tx/dxK/Ykn+/fvV1pamkqXLm23oVKlSvL393e7vNzTPC7/gi/7sqWlpenJJ59UxYoVFRQUpODgYCUnJ7u1PTw8XD4+Pm51FGQbz35WNWvZFi1a5NYPjho1yl63Bw4cyDFN+fLl8zWvgvSFVatWVdmyZSVdXK+zZs2yj78KUvexY8d05swZRUdHexwfFRWlSpUqSbq4Xc6cOVM///yztmzZ4lYuNTVVLVu2VFhYWKFcKrd8+XIdPnw4xwMNJM/9YEHcMkHmVvzgZ7/xPSoqSunp6fm+ljK7hISEfHUanhQvXlz16tWTj4+PihUrpieffFINGzbM1422WTeL3X///YqMjJS3t7eqVKliB4aC1J2QkHDFD052M2bMUJcuXdwuHcnOy8tL9erVk8vl0hNPPJFnfbnZuHGjNm/erNGjR6tIkSI55pP9/c/qyA4cOKCEhAR5eXnla3nwxxMZGanKlSvrxIkT9r+TJ0/qzJkzCg8P1+bNmzVkyBDNnDnTHteqVasc9+F5ukfEk4iICCUmJroN89RPXF5fVFSU5syZ49bGlJQUvfrqq3aZPn36aNasWVq5cqV8fHz05z//Oc/2xMbGavfu3W7f4H3++eeKjY3N1/IUpO7KlSvLz89PX3zxhdt4f3//K4aULFFRUdqzZ88V53vq1Cm3Syw+//xzRUVFXXOQ8fS+JSUlub2+/Au0AwcOqGvXrho+fLiOHDmikydP6oknnnDbdtq0aaOUlBRt2LBBc+bMyVf4xK3rRvcnDocjx7SRkZEKCAjI0YbTp0+rQYMGVz2PLC+++KI2bdqktWvXKjk5WSdPnlRQUJDb/D3VWZBt/PL6IiMj1bNnT7flSk5O1s6dOyVd/JxefmlVbpdaZRcbG+vWF0nSF198cc19oZeXl71urrXu0NBQFS9e/Ip93ZVkf09OnDihpk2bqmzZsvq///u/HEHzWjz11FPq1q2bGjZsmGc/WFC3TJDJzY3+4GfJvlPav3+/ihYt6vGsgdPpVEZGhtvTF7Kfaclvp5Ff2Tf+3BQpUkQTJkzQvn37dPjwYT377LPat29frs9Lz2/duR0kZNm1a5c2btzo8bKyy124cEE//vhjnuVy07p1a02cOFGNGze2O60slmW5dVb79++Xl5eXypYta4eaq+0I8MfQqlUrnTt3TuPHj7cvdTp48KDeeecdSRfPFvj4+CgkJESWZWnVqlX64IMP3Oq4moeLdOzYUVu3btXSpUuVmZmptWvX2vPKzYABAzRy5Ej7muqzZ8/qk08+cbv3rGvXrvrss88UHx+vHj165GuH0qhRI0VGRur5559XWlqaduzYoRkzZuTrcy1dvDQ4LS1NlmXp/PnzSk9Pt5+yllfdfn5+evTRRzV8+HAdO3ZMR48e1fDhw/XYY4/l+LLicl26dNEPP/ygSZMm6ezZszp//rx9lj4qKkpNmzbV4MGDlZqaqn379mnixIluyzRy5Mh8f1MrXVy3M2bM0FdffaULFy7oxRdf1M8//5zrNKdPn5ZlWQoJCZG3t7e2bNmS48y/j4+PunfvrmeeeUY//vijx7PbMMeN7k9CQ0Pl7e3ttn+rW7euYmNj9dRTT+nEiROSLn6zv3jx4gItW2pqqooWLarg4GClp6dr1KhR9pnO3BTmNv7EE0/orbfe0sqVK3XhwgVlZGTou+++s+9Xy+pfFy9erIyMDP3vf//LV/8qSd26ddP27du1ePFinT9/XgsWLNCOHTv02GOP5Tnt8uXL7S/CDx48qH79+qlu3br2lR8Fqbtfv34aPHiwvv32W7v+rCfUvv/++/ZZ+RMnTuiJJ55QaGiofex55MgRNWrUSNWqVdP8+fM9HifHxcWpZ8+e+VhD7v75z3+qS5cuatiw4XU9vjIiyNzoD35W+aynbx09elTx8fHq1q2bx7IxMTEKCAjQrFmzZFmWNm3apKVLl9rjC9JpbN26Vd9++60yMjKUnp6uGTNmaMOGDWrbtm2e0x45csQOY0lJSerevbvuvvtu+yEEBam7f//+GjdunLZs2SLLsvTLL7/YlwJmmT59uu666y77Ws3sy7RmzRqlpaUpMzNTGzZs0Msvv+z27XCPHj3s69mvRv/+/TV+/Hg1bdo0x6nT0aNH6+jRo/ajDZs1a6awsDCFhobq4Ycf1hNPPGGvr71799oPCoD5Lj9gv5pvhIoVK6Y1a9Zo165dqlKlioKCgtSsWTM7MDRv3lzdunXTnXfeqdDQUC1btkzt2rW75vlVrFhRS5Ys0fDhw+0n8XTr1i3HNcaX69WrlwYPHqwePXqoRIkSioqK0pgxY3ThwgW7TFBQkB5++GHt3Lkzz5v8szgcDq1YsUJff/21SpYsqdatW2vIkCF65JFH8jV9sWLFVLx4cSUlJalnz57y9/e3n5yUn7qnTJmimJgYxcTEqEqVKqpevXq+fscmPDxc69at00cffaSyZcsqPDxckydPtscvWLBAGRkZioiIUIMGDdSuXTsNGjTIHp+UlHRVfVC3bt3Uv39//fnPf1ZYWJgOHTqkBg0auL1vl6tSpYri4+P14IMPKjg4WBMnTvR472SvXr305Zdf6i9/+cs1nzFC4TGpP/Hz89Po0aPVsWNHlShRQuPHj5eXl5feffddWZalOnXqKDAwUH/605/c7pHN7zyylxs4cKACAwNVpkwZRUdHKyAgIN9fBlzLNu6pjdWrV9fKlSs1ZcoUhYeHq3Tp0urRo4cdIipWrKilS5cqPj5ewcHBevnll/N9P06FChW0bNkyjR49WkFBQZowYYLeeeedfP1sxdtvv63q1avL6XTqT3/6k0JCQvTee+8VSt3jxo1Thw4d1KZNGzmdTsXFxdnHL+vWrVO9evXkdDpVs2ZNJScn6+OPP7avkpk+fbq+++47LV26VIGBgfZPZ0yYMMGu/6effrqqHwzN/r784x//0DPPPKPGjRvn67aFa2LdIHFxcdbYsWPt1w6Hw/rkk08sy7KsN954w4qOjnYr3717d6t379726wMHDlhdunSxIiIirMDAQKtq1arWyJEjLcuyrMzMTKt///5WcHCwVbJkSatnz55W165drR49eliWZVkJCQmWw+GwDh48mK+2rlu3zvL19bXmzZtnRUZGWiVKlLC6d+9unT592i5Tvnx5a8GCBfbrt99+26pQoYLlcrmsDh06WAMHDrSaNWtmjz958qTVv39/KyoqynK5XFalSpWsfv365dmWRYsWWZUqVbICAgKskJAQq1GjRtbq1avztRzbt2+3oqOjreLFi1thYWHW008/bZ05c6ZQ6rYsy5o2bZpVrVo1KyAgwIqMjLRee+01e9zZs2etEiVKWPPnz88x3YYNG6w6depYLpfLCgwMtKpVq2aNHz/eyszMtMs0adLEGjVqVL7bcvn2smTJEqtkyZLWmjVr7Pd/9uzZVkxMjBUUFGQ99NBD1pEjR+zyp0+ftp555hkrMjLScjqdVo0aNeztE7jZOnXqZPXt27dQ6ho5cqTVvHnzQqnr96xy5crWgQMHrnn6zMxMKyIiwlq0aFGB23LmzBmrePHi1pYtWwpcF3ArYhu/Ne3bt8+KjY292c3IlZdlGfSDKvhDSEtLU9WqVfXtt99e8d4a0OrSMQAAIABJREFU4PdsxYoVuueee+RyubRy5Ur95S9/0UcffaRGjRoVqN4jR46oTp06mjVrllq0aFFIrUWWxYsXq02bNsrIyND48eM1bdo07du3L8fTiK6GZVkaN26c3nvvPW3durUQWwvcGtjGURBGXFqGPxY/Pz/t37+fEIPfrazT95f/e+CBByRJGzZsUExMjIKDgzVs2DBNnz69wCHm2WefVaVKlfTQQw/lCDF5tedKNm3alGNaT5cmXC/X2u7r5ZVXXlFYWJgiIiK0bt06ffDBBwUKMceOHZPL5dJ//vOfAv9YJ36/brXPwdXIbRsfP378FfuX6/E7bwXpz65nW2/0ejDNH/aMjNPp9Hh9ZcOGDbVq1aob1o6kpCRVq1bNrS2WZdm/c3KlH5mUpIULF6pv374ep50+fXqBbpi7nnUDAAAABfWHDTIAAAAAzFWgh0UX9rOgAVPxfcDNR38EXER/dHPRFwGXXO/+qOC/eqMHJa9sz/P38v3tj0vDHL/97a1iOYY5rN/+16VHVHrL72JV2YZd+vtSvZle/r/9XzTbsIt/ZzoulrMcl+Yp79/m5bhUh7f3xfb6+FyqwydrmD3u0mry8b04zNvH+9Ky+F7829vXkW3YxY7MUfTSsKxVY68i30udnb0KfXWJz2/js71Lv60uWb+Vs3yydZg+7uPcps1Wh5fPZe2Q5PBxH+fwzjYuq90+2TZGD/VePv/MbHVk+rj/L0kZ9jJcqtfKqiPbtLps/o5sdWS108/3Uh3FfhtWPFsd/t4Xx7t+m7a4I+c4/2zlnVnDspXLqreY49K8/B1Sa0dx4dbh9nn97W9Pw7y9L73hWX9nPUM/t3F5Dcs+7eX15bfe7O3NTx3XUu/l0+a33uzDLl+XnsrnNs9raZun9y+39zQ/4/Iq552tnG8uy+xpe8tt+XIrn71e36z9Tl7L7OMjBwfRt4wiXjn/zrbbt//OPizr3fT2MCxrd599nCOX8g4P5bLfGJ01TW7D8prXtQ7Lvot3eBrmoQ5P7c36O/uh0OX1eVq+/K7D/C5DbuvSU7m8lv/ycp7a4ZPHusnP/D2t37yWy+cqliHiW1133OwPAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjeFmWZV3zxF5ehdkWwFgF+BihkNAfARfRH91c9EXAJde7PypQkAEAAACAm4FLywAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAGCUuLk7jxo2zXzudTm3duvUmtgh/BM2aNdOoUaMkSUlJSXK5XDp8+PBNbhUA/LEVKMiYdECxfv16+fr65lqmfPnyWrhw4Q1qEQpq7ty5io6OzrWMw+HQ5s2bb1CLcDOkpqaqfv36N7sZxujdu7dq1KghX19f9enTJ8f4s2fPqmfPngoODlaJEiXUu3dvpaen56vu9evX66677lJgYKAqVKigV1991W1848aN5efnJ5fLJafTKZfLpffff7/Ay3Ts2DG1a9dOLpdLpUuX1pAhQwpcZ27KlSunlJQUhYWFXdf5AAByV6hnZG71AwovL6+b3QTbsmXLFBsbK6fTqapVq2rp0qVu46OiolSsWDG3Hf63336bZ72JiYlyOBz2NE6nU7fddptbmeux09+zZ48eeeQRlS1bVoGBgapZs6Zmz57tVqYgB0hXciu9p/jjycjIkGVZhVafZVnKyMgotPo8iY2N1UsvvaSHHnrI4/inn35au3fv1p49e7R7927t2rVLAwcOzLPexMREtWrVSs8884xOnTqlRYsWaejQoVq2bJldxsvLSyNGjFBKSopSU1OVkpKiP//5zwVeps6dO8vhcOjQoUPaunWrli9frkmTJhW43lvJ+fPnb3YTAOCW87u5tKywDyiupy1btqhr166aOnWqUlNTNWnSJD366KPatm2bXcbLy0tz5sxx2+FXr149X/V7eXlp9+7d9rQ//fST2/jrsdM/efKkmjRpou3bt+vUqVN6/fXX9fe//13vvPOOXeZaD5CA3GQ/65Z1lu7f//63ypUrp5IlS+rxxx936xuSkpL0yCOPKDw8XBEREerbt69Onz5tjx82bJgqVqwop9Op6Ohovfzyy/a4rC8K5syZo+rVqysgIEDHjh3LtX2rVq1S9erV5XK59OCDD2rgwIGKi4tza//UqVN15513KiAgQJ9//rkkaebMmapZs6aCgoJUp04dffzxx5Kk5ORk+fv766uvvnKbT6NGjTR27Ng819eTTz6pZs2ayel05hiXlpamBQsWaMyYMQoJCVFISIhGjx6tuXPn6ty5c7nW+/777ysmJkYdOnSQJNWvX18PP/ywpk2b5lbuWvvpnTt3qmXLlipVqpRCQkJ0//33S5L279+v1atXa/LkyQoICFBUVJSee+45vf7669c0nyzjx49XuXLlFBISooEDB7q1O2s7OHTokCQpPj5eTZs21ZAhQ1SqVCmFhobqpZde0k8//aT77rtPLpdLd955p3744Qe7jtOnT6tbt24qWbKkypcvr/nz58vX11cbNmyw67zvvvs0aNAghYWFqU2bNpKknj176rbbbpPL5VKNGjW0aNEiu84GDRq4ba+SNHz4cDVr1qxA6wIAblWFGmRu9QMKSZo3b56ioqIUEhKiHj166MyZMx7LeboULT4+3m2HcOLECfXq1Uu33XabSpcurY4dO+ro0aN5tmH58uVq0aKF7r33XklSq1atdPfdd2v69Olu5a51h29ZljIzMz2OS0hIKNBOf/369WrUqJFKliypUqVKqWfPnpKkevXqqV+/fvalFnfffbdatGihdevWSSrYAVJeJk6cqDJlyigsLEx///vfr/iNtqdL0Xr06OF2eU1+tsmIiIgrXjqDmy8xMVFHjx7Vvn379Nlnn2nJkiV66623JEnp6elq0qSJatSoocTERO3atUsHDx7U3/72N3v66tWra/PmzUpNTdXMmTM1dOhQO0RkWbRokdatW6fU1FSFhoZesS179+5V+/btNWLECCUnJ2vAgAGaPXt2jjOJc+bM0ZIlS3T69GndcccdmjlzpiZNmqRFixYpOTlZY8eOVbt27bRv3z4FBQWpQ4cOmjVrlj397t27tXXrVv31r38t0Lr74YcflJ6ertq1a9vDateurV9//VW7d+/OdVrLsnL0WRkZGfryyy/dhk2ZMkUhISGqWbOmJkyYoAsXLuTZrsOHD6tx48aKi4tTYmKiDh8+bJ9J3rlzp4KCghQVFeXW5oSEBLfP7tWYP3++Xn75Za1YsUKHDx9WSEiIHTCyXP4ebty4UZUrV9aRI0c0f/58DRo0SL169dJrr72mkydPqkqVKnr66aft8k8//bQSEhK0e/duff3111q1alWOfnvjxo2KiIjQgQMH9Pbbb0uSGjZsqJ07d+rUqVMaPny4unfvru+//16S1LdvX7cz4ZZl6Y033vB4CSEA/B5c1zMyt9IBhSRduHBBK1eu1DfffKPvvvtOu3fvzvWMgKfLlrIPa9Omjby9vbVr1y4lJibK6XSqc+fOea4XTzv8zMzMHDv8gQMHKiQkRLVr19aMGTPyrDd7Gxs0aKBSpUqpSZMmWr9+vT3uq6++uuad/s6dO9WiRQv17t1bhw8fVlJSkrp37+6x7K+//qotW7bo9ttvl1SwA6TcJCQkKCkpSQkJCfr000+1YsWKXM8u5XYp2pW2yQEDBkiSPv74Y82bN0/btm3TqVOn9Nlnn+mee+655rbj+vD399eoUaPk6+urihUr6r777tP27dslSStWrJAkjRgxQkWKFFFgYKDi4+O1YMEC+zPZuXNnlS5dWtLFezoeeOABrV692m0eI0eOVGhoqHx8fHLdpt566y01aNBAHTp0kMPhUJMmTTxe0jVo0CBFRUXJy8tLvr6+mjp1qoYPH64aNWpIklq0aKG4uDi7/+zdu7cWLlxofwkwe/ZstWjRosD3bKSmpkqSXC6XPSwwMFCSlJKSkuu0zZo103fffacFCxYoIyNDmzZt0jvvvOM23YQJE7Rnzx4dO3ZMs2fP1qxZszRixIg82zV//nxFR0dr8ODBKlasmHx8fNSkSRO7zVltzBIUFJSvNuc2v759++r222+Xj4+Phg4dmue6jYmJUY8ePeTl5aUWLVqoZMmSat68uWJiYuTt7a3OnTvb22FmZqYWLlyo0aNHq2TJkgoICNC4ceNy7BciIyM1YMAA+fj4yM/PT9LFL1+CgoLk5eWlDh06qFatWvYXRh07dlRSUpI+++wzSdKHH36otLQ0+2wOAPzeXNcgcysdUEgXD2InTpyogIAAhYaGatSoUZo/f/41Ldv27dv1xRdf6JVXXlFAQID8/Pw0YcIErVmzxr7c4EoeeOABffjhh1q9erUyMjK0fPlyffLJJ2473Xnz5mnfvn06cuSIJk6cqOeff14zZ87Ms10hISH69NNPtX//fiUmJqpdu3Zq2bKlvvnmG0kF2+lPnz5dDz74oLp27SpfX18VLVpUjRo1ylEuMzNTXbt2VWRkpLp27WrPV7q2A6TceHt7a/LkySpSpIjKly+vwYMH64033rimuq60Tb755puyLEtFihRRenq6vv76a6WnpyskJESxsbHX3HZcH6VKlXLrC4oXL25vfwkJCUpMTFSJEiXsf02bNpW3t7f9BKqpU6eqVq1aKlGihIKDg7Vy5Uq3s71eXl6KjIzMV1sOHjyYo6ynaS8ftn//fvXv399uY3BwsNatW6eDBw9KunjGs0yZMlq6dKkyMjI0b968QvnWPetys+yfyVOnTkly/+x6Eh0drWXLlmnKlCkqXbq0/vGPf6hHjx4KCQmxy9SvX1+BgYHy8vJSvXr1NHr0aL355pt5tishIUExMTFXbHNWG7MkJye7Lc/VOnDggNuXPfl5z8PDw91e+/v7uw3z9/e3t8Pjx4/r3Llzbvcv5me7sCxLw4cPV5UqVRQcHKzg4GDt3LnT3j6LFSumRx991D5bN3v2bHXr1i3PB90AgKmua5C5lQ4osmTfcURFRSk9PV3Hjx+/6mVLSEhQWlqaSpcubbe/UqVK8vf3z3FPyuXuvfdevf7663rmmWdUunRpzZs3Tx07dnTb4Tds2FD+/v7y9vZW06ZN9eyzz+Zrh1+8eHHVq1dPPj4+KlasmJ588kk1bNhQS5YskVSwnX5uBxNZLly4oI4dO+rIkSNasWKFvL293eq+lgOk3JQqVUpFixa1X0dFRenAgQPXVFde2+S9996rcePGacyYMSpVqpRatGhh388AM0RGRqpy5co6ceKE/e/kyZM6c+aMwsPDtXnzZg0ZMkQzZ860x7Vq1SrHN+UOR/66zoiICCUmJroN89Q/XF5fVFSU5syZ49bGlJQUt0sZ+/Tpo1mzZmnlypXy8fEplJvmK1euLD8/P33xxRf2sM8//1z+/v55fvYlqWXLltq2bZuOHz+utWvX6tChQ2rcuHGu0+TnEtqoqCjt2bPH47jY2FidOnVKCQkJbm2Oioq65iATERHhVp+kHO9jQYSEhKhIkSJudXqq//LtYtGiRZo9e7aWL1+ukydP6uTJk6pVq5bbOuzbt68WL16shIQErVixQr179y60dgPAream3ex/ow8osmTfWezfv19FixZ1CxBZnE6nMjIy3J4Uk/1MS2RkpAICAnK0//Tp02rQoEGe7ejWrZt27typ48ePa/ny5frhhx/cbgD25FrvmfHy8rKnLchOP7eDCenipVlt27bVL7/8oo8//titvoIeIF3J0aNHlZaWZr/ev3+/ypYt67Gs0+nMcU/U5e9pbtukJPXq1UsbN27UkSNHFBsbq3bt2l1z23HjtWrVSufOndP48ePtSykPHjxoP5QiJSVFPj4+CgkJkWVZWrVqlT744AO3Oq7mc9ixY0dt3bpVS5cuVWZmptauXev2AIwrGTBggEaOHGnf0H/27Fl98sknbjeLd+3aVZ999pni4+PtS5ry4/z580pLS1NGRoYyMjKUnp5u93N+fn569NFHNXz4cB07dkxHjx7V8OHD9dhjj6lIkSJ51r19+3ZduHBBv/76q1577TX997//tS8dO3XqlFatWmV/Bnfs2KH4+Hh17Ngxz3q7dOmiH374QZMmTdLZs2d1/vx5++x8VFSUmjZtqsGDBys1NVX79u3TxIkT9fjjj9vTjxw5UuXLl8/X+pEurtsZM2Zox44dunDhgsaPH5/jN2MK8nAZh8Ohzp07a+TIkTp+/LhSU1P1wgsv5PkepqSkyNfXVyVLltSFCxc0Z86cHA99qFmzpqpVq6b27durfv36qly58jW3EwBudTctyNzoA4qs8kOHDlVqaqqOHj2q+Ph4devWzWPZmJgYBQQEaNasWbIsS5s2bXJ7RHLdunUVGxurp556SidOnJB08bHGixcvzrMdGRkZ2rFjhzIzM3Xq1Cn94x//0IEDB+x7MX766SetW7dO6enpyszM1Pr16zVlypR87fC3bt2qb7/91j5AmTFjhjZs2KC2bdtKyt9O/0r69u2r9957TwsWLNC5c+eUlpZm339z5swZtWjRQufPn9f777+vYsWKuU2bnwOkN95446qDaUZGhp577jmlpaVp3759evHFF694387tt9+uo0eP6v3335dlWVq+fLnbDbx5bZPbtm3Tpk2bdO7cOfn6+srpdMrHx+eq2ouCu/xg72oewV2sWDGtWbNGu3btUpUqVRQUFKRmzZrZB4PNmzdXt27ddOeddyo0NFTLli3LEVavZn4VK1bUkiVLNHz4cAUFBemll15St27d3M4ieqqvV69eGjx4sHr06KESJUooKipKY8aMcbsxPigoSA8//LB27tx5VTf533///fL399eCBQv0xhtvyN/fX82bN7fHT5kyRTExMYqJiVGVKlVUvXp1/etf/8pX3SNGjFBISIjCwsK0bNkyrVu3zj6QPn/+vMaMGWM/or1Tp07q0qWL22+RXUl4eLjWrVunjz76SGXLllV4eLgmT55sj8+6LyciIkINGjRQu3btNGjQIHt8UlKSfU9NfnTr1k1PPfWUWrdurbCwMB0/ftx+OEuW/FzKnJupU6fqtttuU0xMjGrVqmU/hS37tnG5xx57TPXr11elSpVUrlw5ff/99x4v7+3bt6927NjBTf4Afv+sAoiLi7PGjh1rv3Y4HNYnn3xiWZZlvfHGG1Z0dLRb+e7du1u9e/e2Xx84cMDq0qWLFRERYQUGBlpVq1a1Ro4caVmWZWVmZlr9+/e3goODrZIlS1o9e/a0unbtavXo0cOyLMtKSEiwHA6HdfDgwXy1dd26dZavr681b948KzIy0ipRooTVvXt36/Tp03aZ8uXLWwsWLLBfv/3221aFChUsl8tldejQwRo4cKDVrFkze/zJkyet/v37W1FRUZbL5bIqVapk9evXL8+2pKenW3Xr1rVcLpcVGBhotWnTxtq7d689fteuXdYdd9xhj69Zs6Y1bdq0fC3nokWLrEqVKlkBAQFWSEiI1ahRI2v16tVuZY4dO2a1a9fOcjqdVmhoqDVkyJB81W1ZlrV27VrrT3/6kxUUFGSVKlXK6tWrl2VZljV37lzL4XBYxYsXtwICAqyAgADL6XS6rY8zZ85Yf/3rX62goCArODjY6t27t5WWlmaPHzVqlBUXF5fvtmRtYxMnTrTCwsKsUqVKWQMHDrQuXLhgl8m+TVqWZb366qtWmTJlrODgYOvxxx+3unTpku9tcs2aNVbt2rUtl8tlBQcHW40aNbK2bduW7/YClmVZnTp1svr27VsodY0cOdJq3rx5odT1e1a5cmXrwIEDN7sZufr+++8th8Nh/fzzzwWua926dVZwcLB19uzZQmgZANy6vCzLkB9fwe9eXFycJk2apLp1697spgCFZsWKFbrnnnvkcrm0cuVK/eUvf9FHH33k8Zv0q3HkyBHVqVNHs2bNUosWLQqptbhR9u/fr8OHD6t+/fo6duyYevbsqbNnz2rNmjUFqjctLU2PPPKIqlevrgkTJhRSawHg1vS7+UFMmG/t2rWEGBjH6XTK5XLl+PfAAw9IkjZs2KCYmBgFBwdr2LBhmj59eoFDzLPPPqtKlSrpoYceyhFi8mpPQZha960oLS1Nffr0UVBQkGJjYxUQEKAFCxYUqM7ly5erZMmSSklJ0fPPP19ILQWAW9fv6oyM0+n0eF1yw4YNtWrVqhvWjqSkJFWrVs2tLZZlycvLS126dMnxS9d/hLoBAACAwlSgIHM1N70Cv2e/o+8DjEV/BFxEfwTgj6LAj1xKTk5WZrY+MyPz4v/Zh2X+9iLDbZjchmVmm8BTHfku99uLrGFZZS4OszwMc58u+zBP7b68/uzl3NtruZW/WM69HW7L4mGYlUs567fKMq3s9ecsn2nlLGfZ5TKzlXMfZrnV66kOD+Wy5pVL/dnLZ3hsr+X2v1s5D+sj08N6trcVD+vmgsdtIOt9vlT+gr195lz32ae9YFnaPDbnL7Xj5oiIiHB78l3W356GZf3Gkady2ctnlcurjtzKXW353MplL5/11Lz8Ll9u9XoaV9h1eFrm/JTLPs7TMtvls9fx2/jcyue3vbkNuxF12MvgYfkunzbrB44B4I+Ae2QAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcL8uyrGue2MurMNsCGKsAHyMUEvoj4CL6IwB/FAUKMgAAAABwM3BpGQAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAACgUovFAAAZb0lEQVQAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAMD/t3fv0TWdiRvHn3NyjyRyF6oSbQilqEvNmHFNojTRMlqrY4hraJdZrWJ1XEZ/LqsYdJYy7bjULR0zZszQohRRQtEx7jWsMkXcKUUOlSDZvz8i2zmEhGh59ftZKytnv/vd73735eyzn7P3TgAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAA8slq2bKkxY8bYw8HBwfr3v//9AHt0e1lZWfLx8XnQ3cAPaNy4cYqJiVFISIi2bt2q559/XhMnTnzQ3QIAY933IMOJA34sc+fOVbVq1R50N2AQl8ulxo0bP+hu3JbD4XjQXSjWZ599ptq1ayswMFB16tTRqlWrSjXd559/rqSkJEVGRsrpdOr48eN33fY333yj5ORkBQUFqUqVKvrjH/9Y5uX561//quDgYIWEhCgkJETBwcHy9vZW+/bt7TrDhw9X/fr15efnp9atW5d5nseOHdOwYcOUlZWlnJwcNWjQQMuWLdOgQYPK3DYA/FT94FdkOHG4N3FxcQoICLA/ZENCQvTf//63VNMuXLhQdevWVXBwsGrWrKl//vOf963tO1m2bJkaNmyo0NBQVa5cWa+//rquXLlijz98+LA6dOigqKgoRUVFqV+/frp69WqZ5vmwbj/gZvn5+bIs6761V9b3TmkdPHhQHTt21LBhw5STk6PBgwerQ4cOOnz4cInTlitXTt26ddNHH31U7Hu1pLYLCgrUrl071apVS2fPntUnn3yiP/zhD1qwYEGZlqlz585yuVzKyclRTk6Ojh07Jn9/f3Xt2tWuEx8fr9GjR6tv375lmleRgwcPysvLSwkJCaWqf7/3FwB4FD3St5aZ/EHgcDg0a9Ys5eTk2B+4tWrVKnG6L7/8Ul27dtXkyZPlcrk0YcIE/eY3v9F//vOfMrd9J99++606duyo9PR0nT9/Xps3b9batWs1evRoSTdOSGJjY3X8+HHt3LlTmzZt0sCBA8s0X+BuOJ1Obdy4UdKNK3pTpkzR448/roiICL366qsex4wjR47o5ZdfVsWKFfXYY4+pb9++unjxoj1+2LBhevLJJxUcHKxq1arpvffes8dlZ2fL6XRq1qxZqlWrloKCgvTtt9+Wuq9btmxRlSpVNHPmTEmFV7vffPNNdejQQaGhoZowYYIqV66sTz75xGO6tLQ0paen67vvvpO3t7dOnjwpqfDqiNPp1Jw5cyQVHh9DQ0O1ZcuWO/Zj7ty5atiwoX7961/L29tbnTt3Vv369TV37twSl6Fx48bq2rWrnnrqqXtqOysrS4cPH9aYMWPk5+enZ555Rn379tXUqVNLnLdU+KVOo0aNFBYWpkqVKmn48OHF1svIyFBISIjHFZlu3bopJSVFERERpZrXnfzjH/9Q69atlZ+fb+8rkucdDLfbX/Lz8zVmzBglJCQoPDxcTZs21datW8vcJwB4FPzgQcaEE4eMjAzFxcUpMjJSPXr00KVLlzz6//7776tRo0YKCgrSL3/5Sx07dkyTJk1SlSpVFBUVpd///vd2/RdffFHjxo2zh6tUqaIWLVrYw/369dNvf/vbUq27ewlhixYtUps2bdS8eXNJUmpqqn7xi19o2rRpZW5bKjyxaNasmSIiIhQdHa2ePXtKko4ePaorV67Yw5UqVVJqaqp27twpSfr666+1e/dujR49Wj4+PqpUqZL69++v2bNne1y1uRfjx49XpUqVFBMTo0GDBik/P1/Sjf0hIyPD3h9SU1N1/vx5DRkyRBUqVFClSpX0wQcf2G3VrVtX8+fPlyTl5ubK399f3bt3t8enpKRwT/sjJDs7W6dPn9aBAwe0efNmLViwwN7+eXl5atWqlWrXrq3s7Gzt2bNHx44d0xtvvGFPX6tWLW3cuFEul0szZszQkCFDbrk16m9/+5vWrl0rl8ulqKioUvVr8eLFeuGFFzRz5kz16tXLLp89e7b69++v8+fPa8CAAerdu7dmzJhhj8/JydG//vUv9enTR+Hh4apXr54yMzMlSZmZmapWrZo9/OWXX8rLy0sNGza8Y1927typBg0aeJTVr1/ffm+XRUlt79q1S9WrV1dgYOBdz3v58uXq3r27Ro0apbNnz2rfvn1q27ZtsXWnT5+uXr16ycvLqwxLc3udOnXS8uXL5eXlJZfLpf3799+2rvv+EhkZqbfffltLlizRypUrdfbsWfXs2VNt2rTRhQsXfpC+AoBJfvQrMg/bicO1a9e0dOlS7d69W3v37tW+ffs0YMAAjzrz5s3T4sWLdebMGfn5+alVq1Y6f/68Dhw4oNWrV2vixInatGmTJCkpKck+Udi3b58KCgq0a9cuff/995KkVatWKTk5uVTrasCAAYqMjFT9+vU1ffr0Uk1jWdYtIaWgoEA7duwoc9u7du1SmzZtlJ6erpMnT+rIkSP2SX69evXUtm1bTZ06Vfn5+crOztbixYvVoUMHu1/uv6XCb4S///577du3r1TzL86hQ4d05MgRHTp0SJs2bdKSJUs0YcIEjzoLFy7Uxo0bdeTIER08eFCNGzdWfHy8Tpw4oVmzZql///46evSoJM/tt27dOlWpUkWrV6+WVHgrz7p160q9/fDwCwwM1KhRo+Tj46Mnn3xSiYmJ9hWKJUuWSJL+7//+T76+vipfvrxGjhypefPm2ftx586dVaFCBUlSixYtlJKSYu8vRUaMGKGoqCh5e3uX6lbIKVOm6PXXX9eKFStu2ddeeukl+0sKf39/9erVS5mZmTpx4oSkwmNVfHy8GjVqJElKTEz0CDKjR4+2+7d69Wq1bNmyxP64XC6VL1/eoyw0NFQ5OTklTlvWtssy7z/96U967bXX1LZtWzmdTgUFBalJkya31NuwYYP27t2r3r17l2FJ7h/3/cXpdGrKlCmaMGGCYmNj5XA41KNHD1WsWFGffvrpg+4qADxwP3qQedhOHBwOh8aPH6+goCBFRUVp1KhR+uijjzzqDBo0SBUrVpS/v79eeuklnTp1SiNGjJC3t7fq1KmjunXr2suQlJSkjRs3Ki8vT5mZmWrTpo0aN26srKws+0S6NCcPGRkZOnDggE6dOqXx48dr6NChHt+83k5KSoo+++wzrV69Wvn5+Vq0aJE2bNjg8cF/r21PmzZNL7zwgrp27SofHx/5+fmpWbNm9nrs1q2b3nnnHQUEBOiJJ55Q/fr17aCTkJCg+Ph4DR06VJcvX1Z2drYmT54sSWU6IfLy8tLEiRPl6+urqlWr6q233rJvnSny9ttvq3z58goLC1Nqaqp8fX3Vq1cvOZ1OtWnTRmFhYdq+fbukwu1XtD9lZmYqLS1NQUFB2rt3rzZt2qSAgADVrVv3nvuLh0t0dLTHMaJcuXJyuVySCkNydna2wsPD7Z+kpCR5eXnZt2tNnjxZderUUXh4uMLCwrR06VKPq8AOh0OxsbGl7k/RbUQ9evTQ008/fcv4uLg4j+HHH39cycnJmj17tiRp5syZ6tOnjz2+aH8+d+6c9u/fr44dOyoyMlI7d+5UZmamkpKSSuxTcHDwLd/+nz9/XiEhIaVernttuyzzPnTokKpXr15ivenTp6t169Z3tZ1+KDfvL2fOnNHFixfVrl07ex8MCwvTwYMH7S9fAOCn7EcPMg/biYNUePtXkbi4OOXl5enMmTN2WUxMjP06MDBQ0dHRHtMHBgbay1CzZk1FRERo3bp1yszMVHJyspKSkrRy5UqtWrVKDRo0KNWHcNOmTRUYGCgvLy8lJSVp4MCB+stf/lLidM2bN9fUqVP15ptvqkKFCsrIyNArr7yiyMjIMrd9pxODNWvWqFu3bpo7d67y8vJ08uRJXbhwQd26dZNUGDiWLFmiAwcOKC4uTm3btlWXLl0kyaNvdys6Olp+fn72cFxcnMcHvMPhuGX7VaxY0aMN9+3XvHlznThxQvv3779l+2VmZqpVq1b33FeYJTY2VgkJCfruu+/sn3PnzunSpUuqWLGiNm7cqMGDB2vGjBn2uNTU1FuuiDqdpT/Menl5KSsrSzNnzvS4RfVObfXp00ezZ8/Wjh07tHfvXvt9JRW+18+cOaP3339fTZs2lZeXlxITE7Vo0SJt3ry5VEGmbt262rZtm0fZtm3b7kugL6ntunXrat++fbp8+bI9fuvWraWad1xc3B1v4ZKkc+fOacGCBXrttdfuofc/DPdtHBkZqaCgIGVmZnrsgy6XS2+99dYD7CUAPBweqof9H8SJg1R4u1uRgwcPys/Pr0wn14mJiVqxYoXWrVunxMREJSYmatWqVaX+BvR2SvtcS1pamnbt2qUzZ85o0aJF+vrrr0u8ClSatu90YrBt2zbVq1dPzz33nBwOh6KiopSenq6lS5fadapXr65ly5bp1KlT2rNnj/z9/VWpUqVSfWt6O6dPn1Zubq49fPDgQVWuXPme2wsMDNTPfvYzzZ8/X9nZ2Xr22Wfv2/aDWVJTU3XlyhWNHTvWfk7v2LFj+vjjjyUVXkn09vZWZGSkLMvSp59+quXLl3u0cS/PolWvXl3r16/Xhx9+qKFDh5ZYPyUlRbm5uerVq5c6duzocSuWv7+/mjRpookTJ9q3qSUmJmrSpEmKiYlRfHx8ie2npaVpy5Yt+vvf/66rV69q3rx52r59u/0lxZ1YlqW8vDzl5ubKsizl5uYqLy/PXi8ltd2sWTPFxsZq6NChys3N1fbt2zV9+nS9+uqrJc67X79++vOf/6wVK1YoPz9fLpdLGzZs8KgzZ84cRUVFKSUl5Zbpr127ptzcXF29elUFBQXKy8vzeJ5vxIgRqlq1aon9uBvF7S9vvPGGBg4cqP/973+SpIsXL2rlypX2l3sA8FP2UAWZB3HiYFmWhgwZIpfLpdOnT2vkyJFKS0sr03IkJibqww8/VGxsrCIjI1WvXj2dPn1ay5cvL9WJ8OHDh7V27Vrl5eWpoKBAWVlZmjRpkl555ZUSp83Pz9f27dtVUFCgCxcuaPjw4Tp69Kj69+9f5rb79u2rxYsXa968ebpy5Ypyc3OVlZUlSfr5z3+uXbt22c8rnTlzRjNmzPB4kHj37t26dOmS8vPz7fv13f/n0Jw5c+46hObn5+t3v/udcnNzdeDAAb377rseD+ffy4lkYmKi3n33XbVo0UIOh0MtW7bU+vXrtXXrVoKMYW6+tfRu/lx3QECAPv/8c+3Zs0c1atRQaGiokpOT7QfNn3vuOaWlpalRo0aKiorSwoUL9atf/eqe5+cuNjZWX3zxhZYsWWL/cZDbteV0OtWrVy/t2LHD47ayIklJSXK5XHaQadGihS5fvlzqZ72eeOIJLVy4UKNHj1ZoaKjGjRunjz/+2ONK9u2sW7dOAQEBeuqpp+RwOBQfH6/AwECtX7++VG07nU4tWbJEX331lSIiItSuXTsNHjxYL7/8conzfv755zVz5kwNGTJE4eHhqlGjhlauXOlRZ8aMGUpPTy923aanpyswMFBjx47VmjVrFBAQoBo1atjjjxw5UuYrtKXZP0eOHKn27dvrxRdfVGhoqBISEjRt2jQVFBSUad4A8Eiw7rOWLVta77zzjj3sdDqtDRs2WJZlWXPmzLGqVavmUb979+5Wenq6PXz06FGrS5cu1mOPPWaVL1/eqlmzpjVixAjLsiyroKDA6tevnxUWFmZFRERYPXv2tLp27Wr16NHDsizLOnTokOV0Oq1jx46Vqq9r1661fHx8rIyMDCs2NtYKDw+3unfvbl28eLHY/t9uGW5e5uPHj1tOp9MaPHiwXdapUycrKCjIunLlSon92rNnj/XMM89YISEhVvny5a2nn37a+uCDD0q1THl5eVbDhg3tadu3b299880396Vty7KsNWvWWE2aNLFCQ0Ot6Ohoq3fv3va4jIwMq3bt2lb58uWtChUqWJ06dbKOHj1qjx85cqQVGRlplStXzqpTp441f/58j7ZHjRpltWzZstR9KdoW48ePt2JiYqzo6GhrwIAB1rVr1yzLKn5/GDFihJWcnOzRTtWqVa158+bZwxs3brScTqc1depUu+zZZ5+14uPjS9034Mc0Z84cq0aNGg+6Gz8pCQkJHsc3AMCPz2FZhv6jFTxyWrZsqQkTJpT452AB3OByudS8eXP16dOnVLdcAQDwqHiobi3DT9uaNWsIMXikBQcHKyQk5Jaf4p7RKI333ntPMTExqlq1qtLT0++pjS+++OKWfhUNF/cHB9yNHTv2ttPe/DzK/VaWfgMAHg2P/BWZ4ODgYu87btq06QP9O/y1a9fW4cOHPcosy1JcXJy++uqr20535MgR+35z9+kcDoe6dOni8c8d79YP2TYAAABwPz3yQQYAAADAo8e7LBPf61/kAR41fB/w4HE8AgpxPALwU1GmIFPYwiuS88Y/JLRfO9zKdP21M/DWMof/rfWL6hWNcx/vURboOU+Per7Xx7nV1/Uyh49bfe/bl8nr+rD7o0SFZTFuZRWuP2oU5lar6F9ehrqVlbv+u2gtBLp91gRd/+3e24Drv93XZLmbyopZywrwulHme72bPm5lRa/9fN3Kri+yt4/nb0nyvt6wl1v9otdOtzLnzavcfbP43lpmL6xbG/Zrt/nb0xQ3zuemOu5l3neoV9w493aLm5d34QazPMokZzSPmj1Mwt1eF73X3N9Xxb13bt5litsVittl3Mt8HbdOe/Ou5VvcOMetZcX1zaeY9v1uGlfcPN375ldcPYdnHfd67u36FlPmd/1YUnScKe644R10o8zr+kHNEXCjrOiQ7ix3o0w3fyy4r5CiaYs5bjiKW3HFHWeKW0lFC13SRvK9qcxj5RezMu16bscJ76J611egxwG66GDs9nnp+/j1soQbZc4Ghb8djW+UORoQ6AH8pHAGBgAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAch2VZ1j1P7HDcz74AxirD2wj3CccjoBDHIwA/FWUKMgAAAADwIHBrGQAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGAcggwAAAAA4xBkAAAAABiHIAMAAADAOAQZAAAAAMYhyAAAAAAwDkEGAAAAgHEIMgAAAACMQ5ABAAAAYByCDAAAAADjEGQAAAAAGIcgAwAAAMA4BBkAAAAAxiHIAAAAADAOQQYAAACAcQgyAAAAAIxDkAEAAABgHIIMAAAAAOMQZAAAAAAYhyADAAAAwDgEGQAAAADGIcgAAAAAMA5BBgAAAIBxCDIAAAAAjEOQAQAAAGCc/wdU266WzDWabgAAAABJRU5ErkJggg==' 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12384 </div>
12385
12386 </div>
12387
12388 </div>
12389 </div>
12390
12391 </div>
12392 <div class="cell border-box-sizing text_cell rendered">
12393 <div class="prompt input_prompt">
12394 </div>
12395 <div class="inner_cell">
12396 <div class="text_cell_render border-box-sizing rendered_html">
12397 <h3 id="Diverging-colormaps,-for-plotting-magnitudes-increasing-or-decreasing-from-a-central-point:">Diverging colormaps, for plotting magnitudes increasing or decreasing from a central point:<a class="anchor-link" href="#Diverging-colormaps,-for-plotting-magnitudes-increasing-or-decreasing-from-a-central-point:">&#182;</a></h3>
12398 </div>
12399 </div>
12400 </div>
12401 <div class="cell border-box-sizing code_cell rendered">
12402 <div class="input">
12403 <div class="prompt input_prompt">In&nbsp;[4]:</div>
12404 <div class="inner_cell">
12405 <div class="input_area">
12406 <div class=" highlight hl-ipython2"><pre><span class="n">colormaps</span><span class="p">([</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">aliased_cms</span> <span class="k">if</span> <span class="s2">&quot;diverging&quot;</span> <span class="ow">in</span> <span class="n">i</span><span class="p">[</span><span class="mi">0</span><span class="p">]])</span>
12407 </pre></div>
12408
12409 </div>
12410 </div>
12411 </div>
12412
12413 <div class="output_wrapper">
12414 <div class="output">
12415
12416
12417 <div class="output_area"><div class="prompt output_prompt">Out[4]:</div>
12418
12419 <div class="output_html rendered_html output_subarea output_execute_result">
12420 <img 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' 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12421 </div>
12422
12423 </div>
12424
12425 </div>
12426 </div>
12427
12428 </div>
12429 <div class="cell border-box-sizing text_cell rendered">
12430 <div class="prompt input_prompt">
12431 </div>
12432 <div class="inner_cell">
12433 <div class="text_cell_render border-box-sizing rendered_html">
12434 <h3 id="Misc-colormaps:">Misc colormaps:<a class="anchor-link" href="#Misc-colormaps:">&#182;</a></h3><ul>
12435 <li>cyclic: for cyclic quantities like orientation or phase (where the highest and lowest values need the same color)</li>
12436 <li>isoluminant: to highlight low spatial-frequency information</li>
12437 <li>rainbow: to highlight local differences in sequential data</li>
12438 </ul>
12439
12440 </div>
12441 </div>
12442 </div>
12443 <div class="cell border-box-sizing code_cell rendered">
12444 <div class="input">
12445 <div class="prompt input_prompt">In&nbsp;[5]:</div>
12446 <div class="inner_cell">
12447 <div class="input_area">
12448 <div class=" highlight hl-ipython2"><pre><span class="n">colormaps</span><span class="p">([</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">aliased_cms</span> <span class="k">if</span> <span class="s2">&quot;cyclic&quot;</span> <span class="ow">in</span> <span class="n">i</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="ow">or</span> <span class="s2">&quot;rainbow&quot;</span> <span class="ow">in</span> <span class="n">i</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="ow">or</span> <span class="s2">&quot;isoluminant&quot;</span> <span class="ow">in</span> <span class="n">i</span><span class="p">[</span><span class="mi">0</span><span class="p">]])</span>
12449 </pre></div>
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12451 </div>
12452 </div>
12453 </div>
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12456 <div class="output">
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12459 <div class="output_area"><div class="prompt output_prompt">Out[5]:</div>
12460
12461 <div class="output_html rendered_html output_subarea output_execute_result">
12462 <img 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nkdHR0tb7zxhoiIFBQUiIuLixw/flxZP9MDrYjIhAkT6gVVn376qfK6tLRUnJyclI6oOctkDZ1OJ9u2bZNFixYpO8PChQtl4MCBZuWSk5OtGryuWrVK/Pz85MiRI1JZWSnvv/++qNVqs0557969UlFRIRUVFbJ+/XpxcXGRr7/+2mLdQ4YMkYSEBIvlDh48KPb29pKVlWWWvmfPHunYsaM4ODiIWq2WqKgoZRDXlLi4OBk2bFij7dfozJkz4u/vL8uXL1fSrl+/LmlpaVJZWSmlpaXy/vvvi4uLizLgaw43Nzf56quvGszr1KmTfPLJJ8prg8Egbdq0kc8//1xEzA+Qubm5olKpzAZqZ86cEZVKpXxBoNVq5bXXXjObx9KlS5X2PGbMGElKShJvb28pLi6WVatWSVhYmFJWq9XK22+/rbw+deqUqNVqKS4uFhGR++67T+l8jIYOHars04899pgSwBk9++yzyiDstxJUrVy5Ujp16iQHDhyQqqoqs3JTp06V8ePHm6U98cQTMm3aNBFp3iDVw8PDLD88PLzB/sX4OTU0sGrqc63ryy+/lJYtW5qtu+n8bty4ISqVSk6ePKks480MkpvaJzp27CgrV65UXpeVlYmTk5MSVFnavk05f/68REVFiUqlEgcHB+nQoYOcOXNGyQ8KCjKbt4jIU089Ve/zqcvSMdPUtWvX5L333jP7cqqqqkoWLFggjo6O4uDgIA4ODvLhhx9arKspd1N7pYY11J/XlZ6eLmq1Wjk23uy+HxcXJ/379zerc/z48fLMM8+IiOX2sWPHDtFqtSIiEh8fLwsXLpTOnTvL6dOnZd++feLn52dxPVNSUkStVktmZqaSZgzuREQOHDggzs7OUl5eruR/8sknSlAl0vS4VKR6zLZmzRqLy9KQU6dOyYsvvig5OTlK2rFjxyQvL09EqttzeHi42RdRTbE0tmlu3f/+97+ldevWotfrLZbt1KlTvWO1qYb6qZtlDIgOHjzYZLkPPvhAHnzwQeV1Q0GV6dj5ww8/lPvvv195rdVq633h3rZtW/nss89ExPI4KyEhQZ566ikREXnggQdk/fr10qpVKxGp/pLP9CRDY5q8/C8rKwsqlarRG48nTZqElJQUXLx4Eenp6Thx4gQmTpyonKrz9/eHm5tb06fKGplvp06dbvp9ABAQEKBMt2jRAgDQqlUrszTThytMnToVSUlJAIA1a9agS5cu6NGjBwAgNzcX7dq1M6u/7uu6aS4uLvDz8zO7F+lml8kaDg4OGDZsGFJSUvDPf/4TQPXNh9euXTMrV1RUBI1GY7G+iRMnIj4+Hk8++SQCAgJw4sQJREVFwdfXVykTEREBR0dHODo6IjY2FhMmTMDatWst1m3t57l8+XIMGjTIbHueO3cOjz76KF566SWUlZWhqKgIHTp0wCOPPGKxvrfeegtarRZDhw5FYGAg/vKXv9S7zPL06dN4+OGHkZCQgClTpijprq6uCA8Ph729PVxcXDBz5kz069fPqvvTGpKfn48bN240ui9duHABWq1Wea1SqaDVanHhwoV6ZS9evKjkGwUFBSn1GNVtq1FRUTh06BCuX7+O5ORkPProo+jTpw/27t2L3bt3Iyoqyqy8aRt1dXUFAKWdZmZm4s9//jO8vb3h7e0NLy8vpKSk4NKlS0r+G2+8YZa/atUqXL582dKmuquMHz8ekydPxqxZs+Dj44PRo0crl+BcuHAB7du3NysfFBTU4GdqLX9/f7PXLVq0aLB/aao/aepzPXbsGAYPHoyAgAB4enrWu/wPaLg/a84DayztE7m5uWYPh3F2doafn5/yurnbV0QQFRWFkJAQlJSUoLS0FPPnz8dDDz2krGtz+1JLx0xTGo0GM2fOxJ/+9CflcqJXX30V69atw8mTJ6HT6XDixAm88847+PTTTy3WZ427sb1Stbr9+fnz5zFq1Ci0adMGnp6eeOihhwCg3v5qqql9H4DZMcX42jiWsdQ+BgwYgMuXL+Ps2bPYvXs3oqOjERUVhZ07d2L37t14+OGHrV5X0/1eq9WioqICP//8My5dugR/f384OTkp+XW3S1Pj0sbeY60uXbqge/fuGDt2rJLWs2dPpV+69957sWTJEmzcuNHifW/WjG2aW3dWVhY6dOigXBbZmL179yIrKwuTJk1qtExD/VRzqFSqett9165d6N+/P/z9/eHp6Ym//vWvTbZflUpVrw3X7TvqzqNt27ZmbbipcVZUVBT27NmDwsJCnD17FqNGjYKvry9OnDjR4BipIU1ucePMG7sPqlWrVoiJiUFSUhKSkpIwfPhw5TpMrVaLvLy8Zl2DqdVqG53nrTZ8+HAUFxdj//79SEpKMhtYBwYGIjs726x8Qw8ryMrKUqZLS0uRn5+v3Pt0u1VVVSnbqnv37vjxxx/Nrkk9evQounfvblVd8fHx+N///of8/HwsXboUp06dqnf/mCnjPV2WWPN5FhYWYsOGDWbX9QLAiRMn4OPjg4kTJ8LOzg7u7u549tlncfDgQRQXFzdZp4+PD959912cPXsWqampSE5OxptvvqnkHzt2DBEREZg/fz5mz55tcT2sXd+G+Pn5wdXVtdHtcM8995i1IxFBVlZWg08cNLYt0/IZGRlQqVRm5et2qMHBwWjVqhWWLFmCgIAAtGrVCpGRkdi1axf27NljVYdhpNVqkZSUhIKCAhQUFKCwsBDFxcX44IMPAFR3bAsWLDDLv3btGr744gur53E3sLOzQ3x8PA4fPoycnBy4uLgo93/W/UyB6oFQY32Du7u7WdBfVVWFvLy827bsDfnjH/+IsLAwnDt3DkVFRfjss89u6v2WDuKmLO0TdfvfsrIyswPuzW5fo4KCAmRmZuK5556Dq6urck+VwWBQ7jHp3r17vaf9HT9+3GJfaumYWZder4dOp1Puwz127BhGjRqFkJAQANUDqeHDh9+y/ea31l5/T+ruW9OmTYNGo8H333+PoqIi5Z6h5h6jANT7/LOystCmTRsAlttHixYt0Lt3b3z++efIzs5GeHi4cnyxdkBqZLrfZ2ZmwsnJCb6+vggMDER+fj4qKioaLAs0PS41upl+qq7KykrlPvamWPocbBnbWKpbq9UiMzPTYrlly5bhscceM/uioyF1+6nmMt3ulZWVGDFiBMaNG4eLFy+iqKgIb7zxhs0PsKjbRnNycpQ22tg4y5jfr18//Pzzz/jwww/Rr18/2NnZITIyElu2bMG3335re1Dl5+eH0aNHY8aMGUrDzcjIMNuwU6ZMQVJSEtauXWsWkPTq1Qv3338/Jk+ejPz8fIgI0tPTlZvAmvLMM89g+/btWLt2LXQ6HcrLy+s93ttalj4ge3t7xMXFYdasWTh37hzGjRun5P3xj39EWloaNm7cCIPBgOTk5AZv3F28eDHOnz+P8vJyzJ07F0FBQQgPD2/2MjVm8+bN+P7776HX61FRUYEVK1YgOTkZgwcPBgD0798f7dq1w/z581FeXo7jx49j+fLlVj0tpri4WHlIQ35+PqZNmwZPT0/lG55Tp07h8OHDqKysRFVVFbZu3Yo1a9aYfWPTmD//+c/46KOP8PXXX0Ov16OkpKTezckrV66En58fYmJizNLDwsJQVFSEdevWwWAwoKSkBO+//z46dOhg8Vvjf//738oO5O7uDkdHR9jZ2QEAUlNTERUVhcTERMyYMaPee9PS0nDq1CllWy9fvhz79+/HiBEjlDIRERFWPUDFaPr06UhISFBujMzNzVUeUxoXF4dFixbh7NmzqKysxGuvvQa9Xt/gE3cCAgIwaNAgzJ49G9euXUNhYSHmzJmDIUOG1PtmuK7IyEi89dZbyg3MkZGRWLNmDQoLC9GvX78m32vabp9//nksWLBAuam2rKwMqampyjdZzz//PBYvXoyDBw/CYDBAp9Ph2LFjFm8KvtskJyfj2LFjqKqqgpOTE1xdXZU29tRTT2HTpk3YtWsXDAYDvvrqK2zZsqXRNhMWFoY9e/YgKysLOp0OL774otkN19a62f7FtHxJSQk8PDzg6uqKnJwc/OMf/7ipulq1aoW8vDyrzzw0tU9MmDABb775JrKyslBeXo558+aZLevNbl8jHx8fhISE4MMPP0RpaSn0ej2SkpJw/fp1dOvWDUD1cW3z5s1ITk6GTqfDokWLoNPpzPb/hjR2zDSeDVq2bBlyc3MBVD/IaebMmXBxcVF+TqRv377YsmWLMmj74YcflAe+GLVv377e08es9Vtor1StuLgYrq6u0Gg0+Pnnn/H3v//9puuou+0PHTqE9evXw2AwYO/evdi8ebPysAlr2kdkZCTefvttDBw4ECqVChEREThw4ACOHj1qdVAlIpg3bx5KSkqQl5eHV155RRmH9O7dG23btsW8efNQUVGBzMxMvPvuu/XqaGxcerPOnDmDbdu24caNGxARHD9+HAsXLjQ7Lq9fv145q3327FnMmTMHjz/+OBwdHZus25qxTXPrjomJgaOjI2bNmoXi4mLo9XqkpaWZfQly5coVbN26td4X2YDlfsr40AhLDyIyVbet6XQ66HQ6eHp6wtHREadPn1a+lLW2joYkJSXh+PHjqKqqwqJFi1BWVqZ8Xo2Ns4zjTmdnZ/Tp06feGGnJkiVo1aoVOnbsaHH+FsP1pKQk9OjRAwMGDFCeymb6tI1BgwZBrVbDw8PD7PSuSqXCF198ARcXF+VpMZMmTVLOXNV97K7p627dumHHjh1YunQpWrZsiXbt2mHNmjUWV6ahR/la83jfyZMn47vvvsPYsWPNHhEeFBSEDRs24O9//zs8PT2xePFiTJw40ezUs0qlwuTJkzFy5Ei0bNkS6enp2LZtmzLf5i5TQy5fvoyRI0fCy8sLgYGBWLlyJT7//HNlu6vVanzxxRdIT0+Hj48Phg4dirlz52LMmDEW6y4uLsaYMWOg0Whw7733oqqqCsnJycq65ufn4+mnn1aeCpaYmIhPP/20XhDUkCFDhuCTTz7BvHnz4O3tjc6dO2Pnzp1mZVasWIEpU6bU2zZarRabNm3CkiVL4Ovriw4dOuDChQtW/f7G8ePHMWDAALi7u6Nr167o1asX4uPjAQAvvfQSiouLMWvWLLi7uytPKzMGe5mZmRg+fDg8PT3Rpk0brF27Fl9++SV69uyp1J+Tk9Pkmby6EhMTERsbi+HDh8Pd3R0RERHKFxTx8fF44oknMGjQILRq1QopKSnYuXNno5fPrlmzBu7u7ggJCUGXLl3g7e1t9qSmxtpYVFQUSkpKlA6ja9eucHFxQd++feu167pM0yZPnoyEhASlTWi1Wrz22mvKoCo6OhorVqxAfHy88g3jCy+8YNVTLn/tTLfDlStXMGHCBHh7eyMwMBA5OTlYvnw5AKBPnz5YtWoVZs+eDW9vb8ydOxdr165VnuxW15NPPolhw4bh/vvvR8eOHaHVahEYGGj1sjSVZm355cuXY8WKFdBoNBg9ejRiY2Nv6v0RERGIjo5Wnh514MCBJpe/qX1i3rx5iI6ORnh4ODp06IDAwEAEBAQo7fRmt6+prVu3IiMjA+3atYOvry8++ugjbNy4UTnT1LdvXyxduhSTJ0+Gl5cXNm/ejK+++sqqy9kbOmYav0w8fPgwwsPDlaev/fTTT9i9ezd8fHwAVPcDI0aMQHR0NDQaDR599FGMHDkSf/3rXwFUD0Ty8vJuqt+5m9srVWtoGy1evBj79++Hh4cHBgwYgKFDh950HXXTYmNjsWPHDnh5eWHKlClYunQpevfuDcC69mE8vgwaNAgA4OHhgc6dO6Nt27b1Li1sjL29PWJiYtC1a1fce++96NixI95++20A1Wdat2/fjqNHj8LPzw8jR47ExIkT6wUZjY1LG9sOjRERLFq0CPfccw88PT0xduxYDB8+3Oy34z7++GMEBQXB3d0dgwcPRp8+fZRbSppizdimuXW3aNECe/fuRU5ODoKDg+Hn54eEhASzywZXrlyJdu3aNRjsWuqnsrOz4eXlZfVVUED97e7q6oqPPvoI8fHx0Gg0ePbZZ/Hkk082+R5Ln51KpcLUqVO30hiOAAAHhklEQVTx3HPPwcvLCxs2bMCOHTuUcb0146y6Y6SBAweirKzM7EmaTS6D3IKviSIiIjB48GCl47/blJaWwt/fH3v27LH4A8Tjxo27ZT/ARnevzMxMjBgxAt99992dXhSi34UbN27Ay8sL+/fvVwZ6vzfJycl45513fnOX0RI117Jly7B48WKzn0MB7v5x6a/Zyy+/DI1GY9VtE783NgdV+/fvR0xMDLKyspQo9m4iIkhMTMT27duRlpZWL/+LL77AQw89BI1Ggy+//BJjx47Fzp070b9//zuwtEREvw+FhYX49ttvERkZiRs3bmDWrFlITU3F6dOnlUvWiOj3JTU1FQEBAejQoQNOnjypnK0yvfzxbh+X0t2r+XfrAQgPD8eIESPwwQcf/CIN9/XXX1cu0zL+1b1s62bk5+dDo9Hg008/bfTM0/79+9GpUyd4eXnhxRdfxLJly25bQHXw4MFG1+9m7234rdTdlAsXLjQ634bukyKiX5YtfbbBYMDf/vY3+Pj4ICgoCJcuXcL27dutCqimT5/e6HxNn8zaHLezbqLfurr7jvHPmlsJgOrjfkREBNzc3PD4449j1KhRmDt3rpJ/s+PS++67r96yGG8ZsNXdWjc13y25/I+IiIiIiOj3yqYzVURERERERL939nd6AW4lPkWIqBZPQt9Z7I+IqrEvurPYFxHVup390W8qqAKAbu3z4FJZu1otDNUn41xVtSflXO2qp90cazsaF/vqaReH2nLONdW41qS5mFzK72JXXb6Fybk+95rpFuraD6xFzSxcTMq51eQ72xmUNCeH6mlHx+pHUju00Cl5di7VP3Sndqn9wTtVzbTK3eQR1c7lNTMrq59m/N/C5MeYnWrSnEzK10yrnEvqpYlj7byM03rHIiWtyr667kp1dZ4OtfXeMJQCAMoNtb9jUqbXV6fpa7fD9UqpyROTctXTpVXV/69X1ZYvrckrq5J6aTdMfjKluGb6RlXtZ36jyr6m3tpHiZdXVj9aUyqrf23eruY/ADjoqvMcKjyUNHtddb7apJxK16K6jora39Ey1KRVKf9dlDxdefXjPit1zkqavqI6X19eu2z60pp6y2rTjNPqstpHyjpUOODUudpfHac75y8nzDtvlcrYdg0mqfo6/03L6euVVxnTVCblUbe8abkG3lvzX2Vl+YbKGedpmqdGVZ3labgOdc20uoE0VQN5dg2VF71Znum0nZJnMMkzmOVVTxvqlbOvSTP+N3+v1CxH/fJ2Jgdq47RZGoxpxvJourySVlvOeGgxL2f+X21Wr/F/bb+nVsqpGi2nNitfP01lnDZJU6ZFbZamGvYy6FegVzngUl772njcd6x//IeTybjCmO9gUs6hph7jmMDepN6aaR+72vGKp3318d/ZJM2xZtreJM2+ppydSX0qu3Lz//Ym4xC76vIw/gegqpl2sK8dwziqq8dTTuraQYFxTOasrm63rna1bdmpJgg15lW/t2aMaPIDtsY0J1XT5RzrlHM0qddFyatf3lFVv5xpmnHawfi6tmuDumZcpTIZS6lqxk6qSpPjT820ymRcBeN0A+VQqTcvYzqt09cvX9VAHRWm761ZPuOQt/ap70BFA2m6Ov8BKEPNCpO08jp5AFAKqE7jtuLlf0RERERERDZgUEVERERERGQDBlVEREREREQ2YFBFRERERERkAwZVRERERERENmBQRUREREREZAMGVURERERERDZgUEVERERERGQDBlVEREREREQ2YFBFRERERERkAwZVRERERERENmBQRUREREREZAMGVURERERERDZgUEVERERERGQDBlVEREREREQ2YFBFRERERERkAwZVRERERERENmBQRUREREREZAMGVURERERERDZgUEVERERERGQDBlVEREREREQ2YFBFRERERERkAwZVRERERERENmBQRUREREREZAMGVURERERERDZgUEVERERERGQDBlVEREREREQ2YFBFRERERERkAwZVRERERERENmBQRUREREREZAMGVURERERERDZgUEVERERERGQDBlVEREREREQ2YFBFRERERERkAwZVRERERERENmBQRUREREREZAMGVURERERERDZgUEVERERERGQDBlVEREREREQ2YFBFRERERERkAwZVRERERERENmBQRUREREREZAMGVURERERERDZgUEVERERERGQDBlVEREREREQ2YFBFRERERERkAwZVRERERERENmBQRUREREREZAMGVURERERERDZgUEVERERERGQDBlVEREREREQ2YFBFRERERERkAwZVRERERERENmBQRUREREREZAMGVURERERERDZgUEVERERERGQDBlVEREREREQ2YFBFRERERERkAwZVRERERERENmBQRUREREREZAMGVURERERERDZgUEVERERERGQDBlVEREREREQ2UImI3OmFuFVUKtWdXgSiX43f0K59V2J/RFSNfdGdxb6IqNbt7I9+U0EVERERERHRL42X/xEREREREdmAQRUREREREZENGFQRERERERHZgEEVERERERGRDRhUERERERER2eD/AzwfC6XNheF8AAAAAElFTkSuQmCC' style='max-width:100%; margin: auto; display: block; '/>
12463 </div>
12464
12465 </div>
12466
12467 </div>
12468 </div>
12469
12470 </div>
12471 <div class="cell border-box-sizing text_cell rendered">
12472 <div class="prompt input_prompt">
12473 </div>
12474 <div class="inner_cell">
12475 <div class="text_cell_render border-box-sizing rendered_html">
12476 <h2 id="Full-list-of-available-colormaps">Full list of available colormaps<a class="anchor-link" href="#Full-list-of-available-colormaps">&#182;</a></h2><p>This list includes all those above, plus other variants and alternatives. Each colormap has a name in the form:</p>
12477 <p><em>category</em><code>_</code><em>huesequence</em><code>_</code><em>lightnessrange</em><code>_c</code><em>meanchroma</em><code>[_</code>s<em>colorshift</em><code>_[</code>r<em>ifreversed</em><code>]]</code></p>
12478 <p>along with any shorter alias that may be defined above.</p>
12479
12480 </div>
12481 </div>
12482 </div>
12483 <div class="cell border-box-sizing code_cell rendered">
12484 <div class="input">
12485 <div class="prompt input_prompt">In&nbsp;[6]:</div>
12486 <div class="inner_cell">
12487 <div class="input_area">
12488 <div class=" highlight hl-ipython2"><pre><span class="n">colormaps</span><span class="p">(</span><span class="n">all_cms</span><span class="p">,</span> <span class="n">cols</span><span class="o">=</span><span class="mi">4</span><span class="p">)</span>
12489 </pre></div>
12490
12491 </div>
12492 </div>
12493 </div>
12494
12495 <div class="output_wrapper">
12496 <div class="output">
12497
12498
12499 <div class="output_area"><div class="prompt output_prompt">Out[6]:</div>
12500
12501 <div class="output_html rendered_html output_subarea output_execute_result">
12502 <img 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jzxxBN15naPMh750gQXL16ETCar904cQUFBSE5ORl5eHs6cOYPTp0/D398fQHUG19HRscHDNXWts6ELOTbk2rVrqKiogLOzs7TMxcWlTr3ay7Kzs5GTk4NWrVpJ/3x8fGBkZCRdZC00NBTR0dEAgK1bt6JLly735QJrjo6O6N69u3Rh3PDwcNjZ2eGHH37Q+d4JEybgzp07KCgoQFlZGaKjozFy5EicO3euSbELCgpQWlra4J1XLC0tta4rAwCFhYWwsrLSc6vpcZCXlweZTKbVHzt06NBg/cDAQMTGxkKpVGL//v0oKiqCn58fgOrxQFcfBer27fz8fK31m5mZ6fylp02bNlqvW7ZsiZKSEile7XXUN8bUR5+2XL16FatXr8aCBQvQrl27OjH0XZf6SJE333wTzs7O0qk///3vf3H+/HmpjqH68b3GvnjxYoP7jKysLHz22Wf44osvANR/CDHHJmqIo6Oj1lFumv1an/ElIiICPXr0QKtWrWBra4vvv/9e65B9mUymd/9U0xwPXF1dUV5ejmvXruHy5ctwdHSEqampVF47dmNzLwAYNmwY9u3bJx3lMnz4cPz000+4cOEC8vLyMGTIkLtqa31cXV3h7u4OoPrvu379evzxxx84cuRIk2Pr6stN6esXL15sdH7j5OSEOXPmwNjYGH369MG0adPqvTj8hg0b0Llz5/t2IwOiB22cUiqVCA8PR2BgILp3716n3NXVVet1+/bt4evri40bNwKoPktA36Nenn32WbRo0QJGRkbw8fHBW2+9ha1bt+p8n7e3N9auXSud1r1lyxZMmTIF9vb2TY6t73dRXWPBypUr8cknn+DgwYP1zu0eVUy+NIG6c9V3rZbWrVtj1KhRiI6ORnR0NMaNGyfdutXV1RVXr169p4sdurq6NnhtmIbY29vDxMQEOTk50jLN52rq86bVXFxc8OSTT+L69evSvxs3bqC0tFT6IjZu3DgUFxcjNTUV0dHReg8m90Imk+l1buKJEycwc+ZM2NnZQS6XY/To0XBzc6tziOHdxnZwcEDLli0b/Pt7eXnVuevAyZMnH69D6Ugn9fVANPtgY3e88fX1hampKRISErB582ZMmTJF+vKhTx8F6vZtJycnrfXfvn37rs5xrm+bao8pDZ06pOu99bWldevW+Omnn7BgwYJ6Jwa1t68hTz75ZJ1TItX9Xj2xq92Pb968iczMzPvSj+81dmP7jPT0dFy7dg3dunWDg4MD+vTpAyEEevTogbVr19a7XoBjE+mma3w5fPgwFi9ejPXr10tlo0ePrrMv1bd/qtUeG01NTWFvbw8nJycUFBRo3RWj9rjT2NwLAHx8fJCUlCQlX/r06YPc3FzExsZK18UyFH3mL7o01JfVP3p5eXnVOa3gxIkTevX1xuaXPXv2rPfmCLWXKZVKREdHY9asWTrXR3Q/NMc4ZWRkhJSUFERFRWHZsmV1yuuLFRoaio0bN+LUqVM4d+4cpk2bdvcbq6LvWOLv74+MjAxcu3YNu3btwu+//46hQ4c2ObY+30V1jQUfffQRVq5cidTUVHh6eupc56OEyZcmcHBwwEsvvYTZs2dLE4CsrCzp+gEhISGIjo5GTEyM1kWVnnrqKfTu3RvBwcEoKCiAEAJnzpzR+qW6ITNnzkRCQgJiYmJQUVGBsrIypKSkNPoeuVyOqVOnYsmSJbh27RpKSkrw3nvv6bxV2ujRo1FRUYGPP/5YmvTn5+fju+++k+oYGxsjICAA8+bNw//+9z+8/PLLOrcBqO7c5eXlKCsrgxACZWVlKC8vlzr9wYMHkZWVBSEESktLsWTJEly9elXrYnkNGTRoEDZs2IAbN25ACIE9e/bg7Nmz0nnSTYn92muvYdGiRdKt2PLz83HmzBkA1f/f8fHxOHjwICoqKvDJJ5+goqJCOkqBCKhONgwZMgSLFi1CSUkJrly5go8++qjB+nK5HP7+/oiIiMCuXbu0LmqmTx+tz/Tp07F8+XJcvHgRZWVlCAsLa9IXg+nTp+Pbb79FSkoKqqqqsH37dr1/5dW3LU8//TR++uknLFy4UEoq3C1TU1MEBgZi1apVyMvLQ3l5Od5//31069ZN+hUnNDQUkZGROHXqFG7duoV33nkHHTt21OtXXKVSifLyclRUVEhjnOYXxXuN3dg+Y/LkycjKysKpU6dw+vRp6ULE+/btk37x59hE90LX+FJcXAxjY2PY29tL+9raR5De7bgiVBfFLikpwdWrV/HBBx9In+MBAwbA2dkZYWFhKC8vR3Z2ttaFM9UamnsB1cmXEydOIC0tDcOGDYNMJoO3tzc+/fRT+Pj46NXGqqoqrb5du58nJiYiPz8fAHD9+nXMnj0bDg4OGDBgQJNjN9SX1Tc/8PPzQ2lpKVasWIGKigokJSXhu+++w8yZM3Wu+/XXX0d4eDiOHDkCIQT++usvHDt2DAAQEBCAv/76C2vWrEFVVRVOnz6NmJgYTJgwQStGQkICCgsLtY42IjKk5hinAKBTp05IS0vDhg0b8M477+isP2rUKJSVlSEoKAgTJkyo9/pstV26dAnJyckoLy9HVVUVUlJS8Pnnn2PKlCk636tUKnHy5ElUVVWhqKgI77//PvLy8vDmm282ObY+30UbGwsWLlyIqKgopKSkSEcJPk6YfGmi6Oho9OzZE97e3rCyssK4ceOkC9A+99xzkMvlsLa2xrBhw6T3yGQy7N69G+bm5ujZsydsbW0RFBQkDRq1kyKar3v06IHExESsXr0aTzzxBFxcXPQ6RCwiIgLOzs7o1KkTevTogeeeew4AtA7frc3c3BwHDhzA2bNn0blzZ9jY2MDX17fOhduCg4Nx6tQpTJ48Wa+LBgPVF+g0NzdHly5dIJPJ4O7ujhYtWkgXvjt9+jSGDx8OKysruLm54ejRo0hKSmrwLiKaNm7cCIVCAU9PT9ja2mLx4sX46quvMHDgwCbHDg8Px6RJkzBu3DhYWlpi6NChUrJt4MCBWL16NYKDg2Fra4v4+Hj88MMPBv0ljR5OsbGxKCsrQ/v27eHt7Y0ZM2Y0Wj8gIACpqano2LEjnnrqKWm5Pn20viRrWFgYfH190a9fP3Ts2BFOTk5o06ZNo+NBbZpxBw8ejFWrViEwMBCtWrVCYmIi/Pz89Ip3N23p1asXDh48iH/+85/45JNPGty+xnz22WcYNGgQvLy80L59e+Tm5mL37t1aFzl+6623MGrUKDg6OuLcuXNISEjQaz1Lly6Fubk5Zs2ahQsXLsDc3BwtWrSQyu81dmP7DDMzM7Rt21b617p1a8hkMjzxxBPSujk2Pd5kMpn0Gbub/qJrfHn++efh7++Pvn37wsHBAfHx8Rg/fnyddd8NY2NjjBo1Ct27d4enpyfc3d2xYsUKANW/NickJOD48eNwcHDA+PHj4e/vDxMTE60YDc29gOrD/93c3KTtAaoTMiUlJXonX77++muYm5vjhRdegFKplPq5+mi/5ORk9OvXD5aWlujevTsKCwuxb98+rbHgXmPr6svW1tZITEzEjh07YGtri1mzZiEyMhL9+vXTue7Zs2cjLCwMQUFBsLKyQp8+faTki7OzMxITE7F+/XpYW1tj0qRJ+PDDD/HSSy9pxVi3bh2mTJnCUxrprj1M45Sai4sL0tPTsXv3bsyZM6fRWHK5HEFBQTh16pTeZwmUlpZi/vz5cHR0RKtWrfDGG29gyZIlmD17ts73KpVK6Q6VLi4u+PXXX5Geni6d1t2U2Pp8F21oLLh06RJWrFiBK1euwMvLC1ZWVtJY+biQiftxHCQ1aOjQoRgxYsQDd//y33//HV26dEF+fr50S+Z7devWLTg6OmL//v3SlfGJ6OFRWloKW1tbpKam6vXrrD6eeeYZjBkzBosXL272thDRoykyMhIrV67Ef//7X63lD+rci4geX5s3b8ayZcuka1DS44lHvhhQamoqjh07huDg4OZuCrKzs/Gf//wHVVVVuHLlCubPnw9vb+8mJ16EEFi5ciW6du3KxAvRQ+LGjRv48ccfUVlZiaKiIrzxxhvo0KED+vbte88x4+LiUFpaioqKCqxbtw7Hjx/HxIkTm6UtRPRoOnToEC5cuACg+nany5cvx9SpU7XqPEhzLyIiACgpKcGqVau0boFNjycmXwykX79+8PPzw5dfftnovc3vl48//hiWlpawsrKS/qlfHzp0CGVlZQgNDYWNjQ28vLxgYWGBmJiYJq2zoKAAVlZW2LhxY51rMOhqT1M8rLGJHhRVVVV47733YGdnBzc3N1y+fBkJCQkwMjK655hxcXFo164dHBwcEBkZie+++w5ubm6IjY1tsE9t27btvrdl5MiRDa6vqR7W2EQPitqfcfW/UaNG6fX+3NxcDB06FBYWFhg7diwmTJigdXTd/Zh7vfbaaw32xby8vHuK+XfE1kXXWExE1Zo6TtW2atUqtG7dGh06dKhzHapu3brVWY8+p+Hk5uY22J/1OXWouWITTzsiIiIiIiIiIjIo4+ZugKHc68WTiB5mzKX+/TjW0OOG40zz4FhDjxuONX8/jjP0OPo7x5pHNvkCAG+//TaMjWs2Uf289iMA6Wr5jdXXvKK+eplCodArVu166tcApMPr1feF1xz4qqqqAFRftVpN/byyshIAUFFRIZWpl925c0frNQDcUZdp1K9dT7O+Om59ZY2tu776ja1HiqWqAwDKu4il+bdpLL76Uf031XxeX6dT/3+oH4G6nwnNUyMa+0yo6zX2majvs1dfrIbqq+/+Qn+/vrGOQGVNv5WpnytVjxpl6udCc5lUT/X6Tt0yof6Y13y0NWKp69YUSfU1YqmX1RdLHaNOHY16olLUKauvvrSs0frVZVWabVDWqq/ZhqrqMpmq+2qeM2uE6m1UaPzZFKpx1Fj1qJDXFJrK1WWoU6Z+n7qOQmNFinpiqddZU79uLHUMU42x3URdX1Z3Pep6JvXEMqm1Ps11qssUGusxa6RMHV+7XarHWutTLzPart8txMkw2mIpIKuZP8jkqnmJkWqZvKYMxqbaZZrP1Y/GNfMamVRmrP0IQGasUNVR7fM09j8yI9W+UmGkUV81n1F1MrnGbFNuqurLiurOLzOp2ffD5HZ1HbObqpi3a95nfFvV9DKNZWWqZaVarzWfy4zUdW5ptK96mdxI/VhzO2cjdUyjCtVjTfuMVc8VxjVzH2O5aplR9fYo5DUDl6nxHa1lJhplJkbVz82MqlRlNfMQ9XPNfq7ur+aqOYmJxtzEpNYyM43/OxO5kaoN6seaMlMjkzrLjFWfA2PVZ0thbCaVGcmrP1Nyo+plMqOaOzjJFFaqsuq7XsrkNXe/lBtV31bXyMixZpm8lerRTlXfviaW3BFyJgGajY2NDVrIaj6Ppqh+bqJ6VL8GADPV/NlEYx6tfm6i2m+bKTXKVMsUtR4BwFT1PmONKbl69DJWt0FWX5n2a816ml90pfrq/ajGZ0yKIdOuq11fI5ZMu0xz/mGiGgrVQ6Kx5jxCtczEWGPd0rCqmptoNNpYtVIj9VCv8QeQq57LzTXmn6a1GqvZaHU9k1qPDSwTpnLtjdMsUy1T1xFaE7DqZVUa+wRhaqRapq5fU6auV6X6w2nFMq71CAAmqg+I6oMiM67SqF/9XK7evxjVTDJlqvFYZlyusewWWpjW7Gf+DrzmCxERERERERGRATH5QkRERERERERkQEy+EBEREREREREZEJMvREREREREREQGxOQLEREREREREZEBMflCRERERERERGRATL4QERERERERERkQky9ERERERERERAbE5AsRERERERERkQEx+UJEREREREREZEBMvhARERERERERGRCTL0REREREREREBsTkCxERERERERGRATH5QkRERERERERkQEy+EBEREREREREZEJMvREREREREREQGxOQLEREREREREZEBMflCRERERERERGRATL4QERERERERERkQky9ERERERERERAbE5AsRERERERERkQEx+UJEREREREREZEBMvhARERERERERGRCTL0REREREREREBsTkCxERERERERFS53tCAAAgAElEQVSRATH5QkRERERERERkQEy+EBEREREREREZEJMvREREREREREQGxOQLEREREREREZEBMflCRERERERERGRATL4QERERERERERkQky9ERERERERERAbE5AsRERERERERkQEx+UJEREREREREZEBMvhARERERERERGRCTL0REREREREREBsTkCxERERERERGRATH5QkRERERERERkQEy+EBEREREREREZEJMvREREREREREQGxOQLEREREREREZEBMflCRERERERERGRATL4QERERERERERkQky9ERERERERERAbE5AsRERERERERkQEx+UJEREREREREZEBMvhARERERERERGRCTL0REREREREREBsTkCxERERERERGRATH5QkRERERERERkQEy+EBEREREREREZEJMvREREREREREQGxOQLEREREREREZEBMflCRERERERERGRATL4QERERERERERkQky9ERERERERERAbE5AsRERERERERkQEx+UJEREREREREZEBMvhARERERERERGRCTL0REREREREREBsTkCxERERERERGRAcmEEKK5G2EIMpmsuZtA9Ld7RLvzA41jDT1uOM40D4419LjhWPP34zhDj6O/c6x5ZJMvREREREREREQPAp52RERERERERERkQEy+EBEREREREREZEJMvREREREREREQGxOQLEREREREREZEBMflCRERERERERGRATL4QERERERERERkQky9ERERERERERAbE5AsRERERERERkQEx+UJEREREREREZEBMvhARERERERERGRCTL0REREREREREBsTkCxERERERERGRATH5QkRERERERERkQEy+EBEREREREREZEJMvREREREREREQGxOQLEREREREREZEBMflCRERERERERGRATL4QERERERERERkQky8GMnToUISHh0uvLS0t8fPPPzdji4joQZSfnw+5XI5Lly7h448/xtixY5u1Penp6WjVqlWztoHocfIwzRdSUlKgUCiauxn0gAgMDERoaGhzN4MeAZrjIMdAepQx+fI3KSkpQf/+/Zu7GffVgQMH4OPjA3t7e8jlcly+fFmrPCUlBXK5HFZWVrC0tISlpSUGDRqkV+xbt24hNDQUbdq0ga2tLZ5++mkkJyffl9i6bNmyBe7u7rCwsMDTTz+NEydONCleQUEBZsyYAVdXV1hZWaFTp05YtmyZVp3AwECYmJhI22NlZYW1a9c2ab308JDJZACAsLAw/Pvf/27WtgwaNAjXr19v1jb8HXT1uc2bN8PIyEir/JVXXtEr9vXr1xEQECCNX9OmTUNhYeF9id2YL7/8Ek8++SRsbW3h4OCAF154AWfOnNGq8+mnn8Ld3R3W1tZ48sknsWbNmiavl+6vB32+oB6vHmTbt2/H4MGDYW1tDRMTkzrlTemDumIDuucRx44dQ//+/dGyZUt4eHggJibm7jeyHgUFBQgICIC9vT2sra3Ru3dv/Pnnn1J5YmIinnrqKdjY2KBdu3aYO3cuKioq7su6ie4XjoE1XF1dYW5urjVW/fbbb3q9Nz4+Hl5eXrC0tISnpye+/fZbrfKff/4Z3t7esLW1RZs2beDv79/k+V96errUTvU/hUKBnj17SnWGDBkCMzMzrW1KTExs0nofJky+PMLu3Llj0PgtW7bEjBkz8PXXXzc4EBkbG6O4uBglJSUoKSlBenq6XrHfe+89HD16FCdPnsSNGzfwyiuvYMyYMSgqKmpy7Makp6dj9uzZiIyMxI0bNzB+/HiMHDkSN2/evOeYN2/eRNeuXZGSkoLi4mLs2rULkZGR+Pzzz7XqBQQESNtTXFyMWbNmNXVziCRCCCiVyuZuxt9Gn/FPV59zc3PTKtf3C9L06dNRWlqKrKwsZGdn49q1a5g+ffp9id2YUaNG4T//+Q9u3LiBP/74A76+vhg5cqRUnpCQgCVLlmDbtm0oKirC5s2bsXDhQuzfv7/J66ZHg1KphBCiuZvRZK1atcLrr79eZz+r6V77oK7YuuYRxcXFGDlyJCZOnIjCwkKsWbMGs2bNavIv/eXl5Rg+fDjMzMyQmZmJoqIixMTEwMLCAkB1YmbChAkICQlBYWEhjh49iuTkZHz00UdNWi/Ro+R+j4FN/S4mk8kQHR2tNVZ17dpV5/uOHDmC6dOnIyIiAiUlJVi+fDleeeUV/PLLLwCAqqoqvPjiixg0aBD++usvnDt3DpcvX8Y//vGPJrV30KBBUjuLi4tRVFQEJycnrTmQTCbD//3f/2ltk+Zc5VHH5AuA0tJSLFiwAG5ubrC2tka3bt2wdOlSODo6orKyUqp38+ZNWFpa4tChQwCAa9euITg4GC4uLrCxscFTTz2FzMzMetchl8tx+PBh6XVKSgoGDx4MOzs7ODo64tVXX9XZzps3b8Lf3x92dnbo0KEDvv76aygUCqSmpgIAPvjgAwwfPhwLFy5E69atMW7cOADApUuXMHHiRLRp0wZOTk6YOXMmSktLAQCLFy+W6qkdOHAA1tbWuH37dqPt6d+/P6ZPn44uXbrobPvdysrKwqhRo9C6dWsAQEhICG7evImsrKwmx66srER4eDg6d+4MKysreHh4ID4+HgCwYcMGTJgwAcOHD4dCocDChQthZmaGXbt26YwbERGBjh07wtraGu3bt8d7770HAOjQoQMWLVoEFxcXAEDXrl0xZcoUrSN56PFx5coVjBkzBjY2NujcuTP27t0rlX3wwQfw9fUFAKxevRq9evXSem92djaMjY1x6dIlAEBubm6dvq2ZKJTL5YiIiEDfvn1hYWGB48ePo7KyEvPmzcMTTzyBtm3bYvny5fDw8MCWLVsA1D2kNjAwEP7+/ggNDYWtrS3at2+PdevWabUrKioK7u7usLGxgb+/P6ZPn67XmKarLV5eXvjmm28AAGVlZTAzM0NAQID0/lGjRuHTTz8FUH3I8rx58+Dn5wcbGxusXLlS5/oN4datW9i7dy/+7//+Dy1atICNjQ3eeecdJCYmIi8vr8nxNfdXVlZW6Natm7RP6tChg3TKWFVVlXREovozkZWVBS8vL/Tt2xcAMGDAAPTo0QOnT59ucrvo/tGcL2zevBkeHh744osv0L59e9jZ2WHWrFlaXw50jQPvvvsu3NzcYGlpCQ8PD6xatUoqy8nJgVwuR3R0NLp27QoLCwsUFBTobOOWLVvg6uoKe3t7BAYG4tatW1JZZmYmhgwZAmtra/Tq1QsRERGQy6unm3v37m10brVy5Uo8//zzUpm/vz/Mzc1RXl4OANixY4deXzx8fX0xefJkdOzYUWfdu6Urtq55RFxcHFq2bIkFCxZAoVDAx8cHfn5+dcbVhqxbtw49evSAtbU1XFxcsHr1agDApk2bUFRUhK+++gq2trYAAE9PTyn5kpeXh4qKCmlsbtu2LUaPHt3k/n/r1i34+/vD2toaHh4e2Lx5s1Z5Y/uHKVOm4M0339SqHx0djU6dOgG4u30APToehjFQ7dixY3B2dkZUVBSAunOR5cuXo127dnWOavb390dISIhe67iXZNCuXbswYsQIeHt7AwBGjx6NgQMHIjIyEgBQVFSEv/76CwEBAZDL5bCxscGkSZP0Hg/0/R67Z88eXLlyRavf3us2PSqYfAHw6quv4pdffsHBgwdRVFSEhIQETJ48GRYWFlqdJTY2Fs7Ozhg4cCCEEHjxxRdRVFSE48ePo7CwEJs2bYKlpaXO9WVkZGDEiBEICQnBn3/+idzc3DofyvrMnTsXFy9exPnz53HmzBns2bMHVVVVWnXS0tLg5OSEvLw8xMXFSb+EdOvWDTk5OTh79izy8/Mxd+5cAEBoaCj27t2LK1euSDGioqIwbdo0mJub6/kXbJhSqYSLiwvatGmDF198ERkZGXq9b+7cuTh48CByc3OhVCqxZs0aeHh4oFu3bk2O/e677yI2NhZxcXEoLi5GSkqKtKM/ffo0+vTpo1W/Z8+eOgejzMxMhIWFITExEUVFRfjtt98wZsyYeusKIZCcnAwvLy+t5XFxcbC3t0fnzp2xaNEiKUFGj5apU6dCoVAgLy8Pqamp2LRpk1a5+iiyqVOn4vfff9f6XG/atAlDhw6Fs7MzysvLMWzYsDp9u/avFtHR0di5cydu3ryJnj17Ijw8HD/++COOHj2K7Oxs5OXlScmc2m1Qi4uLw9ixY3Hjxg1ERERgzpw5yM3NBQCkpqbijTfeQFRUFK5fv46RI0dix44dev0tdLXFx8cHSUlJ0nqcnZ2lozTu3LmD1NRUKVkFABs3bsSbb76JwsJCaYxrjK4+l5ubi7Zt28LFxQUvv/wyLl68qDOmEAJCCK2xWf1L2qlTp5oUG9DeXxUXFyMhIQFt2rSRyg8dOgRbW1uYm5tjwYIFWLRokfTla8qUKSgpKcHhw4chhEBaWhoyMzPxwgsv6LVuah45OTm4evUqLly4gKNHj2Lnzp3SF1J9xoGuXbvi8OHDKCkpwfr16xEWFoZ9+/ZprWPbtm1ITk5GSUkJHBwcGm1PZWUlvv/+e/z66684d+4czp8/j3nz5gGo/qy/+OKL6NWrFwoKCrBr1y6sX79eGlOef/75RudWPj4+OHTokPRr8f79++Hs7Iy0tDQAQFJSklafb4p77YO66JpHZGRk1Ems9+7dW68vPWvWrMGHH36IyMhIFBUV4eTJk9LpGcnJyfDw8MCMGTNgb2+PLl26aB2d07NnT7zwwgtYu3YtlEolcnJykJCQAD8/vyZt786dO/HCCy/gxo0bWLt2LV577TUcOXIEgO79w8yZMxETE6N1dEBUVJT0pfRu9wH0aHrQxkC1hIQEjBkzBlFRUQgKCpKWa85F5s+fj+DgYKxfv14qLy4uRlxcnN7XS5o/fz7s7e3Ru3dvvZO06rmIpqqqKmkeYmtri5kzZ2LDhg2oqKjA1atX8c0332D8+PE6Y9/N99jIyEhMmDABdnZ2Wss///xz2Nvbo3v37li2bJlWQv6RJx5zV69eFTKZTJw7d65O2dKlS8WIESOk1/379xcrV64UQgjx888/CxMTE1FSUlJv3CFDhoh//vOf0muZTCYOHTokhBBi9uzZYtKkSXfVTqVSKUxNTUVycrK0LCsrS8hkMpGSkiKEEGLJkiXC3d1d633ffvttnWXHjh0TpqamoqqqSgghhK+vr/jXv/4lhBDi+vXrwtzcXJw8eVLvtl28eFHI5XKRn5+vtfzKlSsiIyNDKJVKUVRUJMLCwoSdnZ34448/dMYsKCgQkydPFjKZTCgUCuHg4CAOHz58X2JbWFiIH374od4yNzc3sWnTJq1lM2bMECEhIY3GvHDhgmjRooXYuXOnuHnzZqN1//GPf4jOnTuL4uJiadmJEyfE1atXhRBCnD17VvTr109MnTpV57bQwyU/P1/IZDKRnZ0tLdu3b5+Qy+UiJydHLFmyRPj6+kplkydPFm+++ab02tXVVWzbtk0IIcTOnTt19m2ZTCa2bt2qVcfd3V3rM3779m1hamoqNm/eLIQQIjk5WSgUCqk8ICBAjB49WiuGg4ODSEhIEEIIERwcLGbMmKFV/uyzz4rAwECdfw9dbUlMTBSurq5CCCEWLlwoPvroI9G5c2dx9uxZkZKSIhwcHKT3DhkyRAQFBelcp5quPpednS0yMzOFENXjTUBAgHB3dxe3bt3SGXvYsGHCz89PFBYWiqtXrwpfX18hl8tFTExMk2I3tr+qraioSERERIj4+HhpWWVlpViyZIkwMTERCoVCKBQK8dVXX+mMRYbV2Hxh06ZNwtraWurTQggxceJEMX/+fCGEfuNAbS+99JJ4++23hRDV+2+ZTCbS09P1amtycrKQy+VaY1hSUpIwNzcXQgiRlpYmzMzMRFlZmVQeFRUl5HK59LqxuZUQQrRu3VocPHhQ/Pbbb8LNzU0sW7ZMLFq0SAghRMeOHcXu3bv1aqu6vZrjmVpT+reu2LrmEUFBQSIgIECrfOPGjcLDw0PnOrt06SLWrFlTb5mPj4+Qy+Xiiy++EHfu3BHHjh0T9vb2IjY2VqqzY8cO8cQTTwiFQiHkcrmYPn16g58TfQQEBIjBgwdrLZs2bZqYOXOmEEK//cOTTz4ptm/fLoSoHotNTU3FlStXhBB3tw+gh5vmOPigj4EKhUJEREQIFxcXkZGRUWc7as9FLl26JExNTcXly5eFEEKsXr1a9OjRQ6/1paamitLSUlFZWSn27dsn7OzsxLp16/Rqp7m5uUhKShKVlZUiPj5eGBsba40z+/fvF+7u7tJ44OPjI27fvq0ztr7fY3NycoSRkZFIS0vTWn7kyBFRWFgoqqqqxM8//yzc3NzEO++8ozPeo+KxP/Ll4sWLkMlk8PDwqFMWFBSE5ORk5OXl4cyZMzh9+jT8/f0BVGdhHR0dpV8U73ad6iMt9HXt2jVUVFTA2dlZWqY+jUVT7WXZ2dnIyclBq1atpH8+Pj4wMjKSLsIWGhqK6OhoAMDWrVvRpUsXrQsj3StHR0d0795dujBueHg47Ozs8MMPP+h874QJE3Dnzh0UFBSgrKwM0dHRGDlyJM6dO9ek2AUFBSgtLa33/xuovsK65nVlAKCwsBBWVlaNxu3QoQNiYmKwbt06tG3bFoMHD66TVQeqs9c//vgjDhw4oHWUVK9evaRMu6enJz7//HN8++23Br9uD/298vLyIJPJtPpxhw4dGqwfGBiI2NhYKJVK7N+/H0VFRdKvlBcvXtTZt4G6Y0J+fr7W+s3MzHT+yqN5ZAVQfb2nkpISKV7tddQ3NtVHV1u8vb3xxx9/IDMzU/rF28fHBz/99BOSkpIwbNgwrXiurq56rRfQ3edcXV3h7u4OoHq8Wb9+Pf744w/pF93GbN26FaampvD09MSAAQMwbtw4CCFgb2/fpNiN7a9qs7Kywpw5c/Dqq6/i999/BwB8+OGHiI2NRUZGBioqKnD69Gl89tln2Lhxo8541HwcHR21jkbT7H/6jAMRERHo0aMHWrVqBVtbW3z//fdah9XLZDK9+6yaZr91dXVFeXk5rl27hsuXL8PR0RGmpqZSee3Yjc2tAGDYsGHYt2+f1OeHDx+On376CRcuXEBeXh6GDBlyV22tT1P6ty665hH3Os8Aqv+/G5u/ODk5Yc6cOTA2NkafPn0wbdo06SijgwcPYsaMGdi8eTPKy8vx559/oqioCDNmzLiXzZTUHnddXV2lUyz12T8EBwdjw4YNAKpP2Ro9ejQcHR0B3P0+gB5ND9oYqFQqER4ejsDAQHTv3r1Oee0+0b59e/j6+kr72qioKL2Penn22WfRokULGBkZwcfHB2+99Ra2bt2q833e3t5Yu3atdGr3li1bMGXKFGkeoj7q9f3338ft27dRWFiIjh07ap322RB9v8du2LABnTt3rnNDlP79+8Pa2hoymQz9+vXDRx99pNc2PSoe++SLuoPUd62W1q1bY9SoUYiOjkZ0dDTGjRsnnU/v6uqKq1ev3tOFWF1dXRu8NkxD7O3tYWJigpycHGmZ5nM19XnVai4uLnjyySdx/fp16d+NGzdQWloqfaEaN24ciouLkZqaiujoaIPeNlAmk+l1nt+JEycwc+ZM2NnZQS6XY/To0XBzc6s3oXE3sR0cHNCyZcsG//5eXl517kpw8uTJOqcI1WfcuHH46aef8Ndff2HixIkYO3YsysrKAFQf/hcSEoKkpCSkpqbW+TLbEH3+VvTwcHJyAqDdd7Ozsxus7+vrC1NTUyQkJGDz5s2YMmWK9KVGn74N1B0TnJyctNZ/+/btuzq/ub5tqj0W1T6NSd/31m5LixYtMGDAAHzzzTfIyclBv379MHz4cOmLmY+Pj1a82tt6L3T1OX36ZJs2bbBt2zZcvnwZWVlZcHFxgbm5OQYMGNCk2I3tr+qjVCpRUVEhXSvrxIkTmDBhAp588kkA1UmncePGYffu3XrFowePrnHg8OHDWLx4MdavXy+VjR49us5n7W77Tu0xzNTUFPb29nByckJBQYF0jZbadYHG51ZAzakm6i/bffr0QW5uLmJjY6XrVxnK/djnNjSPUP+o5eXlpXUKIlDdN/WZZzQ2f+zZs2e9Nz9QLztx4gR69uyJ559/HjKZDA4ODggJCcH333+v13Y1pPbpWhcvXkS7du0A6Ld/CAgIwKFDh5CZmYmtW7dqzUHvdh9Aj5/mGAONjIyQkpKCqKioOncvbShWaGgoNm7ciFOnTuHcuXOYNm3a3W+sir7jlL+/PzIyMnDt2jXs2rULv//+O4YOHQqg+tQhOzs7+Pv7w8jICJaWlnjjjTeQnp6O4uLiRuPq8z1WqVQiOjpa75uHPE7fdx775IuDgwNeeuklzJ49W9pBZGVlSZPVkJAQREdHIyYmRuvCSE899RR69+6N4OBgFBQUQAiBM2fOaP3i3JCZM2ciISEBMTExqKioQFlZGVJSUhp9j1wux9SpU7FkyRJcu3YNJSUleO+993Te7mz06NGoqKjAxx9/LCWK8vPz8d1330l1jI2NERAQgHnz5uF///sfXn75ZZ3bAFR3lPLycpSVlUEIgbKyMpSXl0sd6ODBg8jKyoIQAqWlpViyZAmuXr2qV1Z10KBB2LBhA27cuAEhBPbs2YOzZ89K51E3JfZrr72GRYsWSbdqy8/Pl27HGhISgvj4eBw8eBAVFRX45JNPUFFRofOc6PPnz+PHH3/E7du3YWxsDCsrK8jlcsjlciiVSkydOhUnTpxAcnJyvUcZbN++XfolLDMzEwsWLMDYsWMbvI0lPZycnJwwZMgQLFq0CCUlJbhy5Uqjd5qQy+Xw9/dHREQEdu3apXVBM336dn2mT5+O5cuX4+LFiygrK0NYWFiTdnrTp0/Ht99+i5SUFFRVVWH79u16/3qsT1uGDx+OFStWYMiQIZDJZBg6dCjS0tJw/PjxJk28dfW5xMRE5OfnA6i+dfTs2bPh4OCgM4ECVI8H6rHrl19+wbx58xAWFib9sn2vsRvaX124cAFA9bnV6rjXrl3DnDlzYG5uLl0TYuDAgdi1axf+97//AQDOnTuH7777Dk899ZT+fzh6oOgaB4qLi2FsbAx7e3tpX1r7CNG77f9CCISFhaGkpARXr17FBx98IB25MmDAADg7OyMsLAzl5eXIzs7WurilWkNzK6A6+XLixAmkpaVh2LBhkMlk8Pb2xqeffqp3n6+qqkJ5ebmUBNJ8DjStf+uK3dA8Qn1zAz8/P5SWlmLFihWoqKhAUlISvvvuO8ycOVPnul9//XWEh4fjyJEjEELgr7/+wrFjxwBUJzH++usvrFmzBlVVVTh9+jRiYmIwYcIEAMDTTz+NjIwM6Uesa9euYf369Vr9PzAw8K6PJjly5Ai2b9+OqqoqHDhwAPHx8dL1H/TZP9jb22PMmDGYMmUKWrRogeeee06r3FD7AHo0NMcYCACdOnVCWloaNmzYgHfeeUdn/VGjRqGsrAxBQUGYMGECrK2tdb7n0qVLSE5ORnl5OaqqqpCSkoLPP/8cU6ZM0flepVKJkydPoqqqCkVFRXj//feRl5cnXeC6T58+KCwsRGxsLKqqqlBSUoIvvvgCHTt21HkUnj7fYxMSElBYWKh1VCNQfaHfPXv2SNfYO3nyJD744AO9tulR8dgnX4DqC1L27NkT3t7esLKywrhx46QL0D733HOQy+WwtrbW2iHJZDLs3r0b5ubm6NmzJ2xtbREUFCR1/NpJEc3XPXr0QGJiIlavXo0nnngCLi4ueh1uFRERAWdnZ3Tq1Ak9evSQdlCah/fWZm5ujgMHDuDs2bPo3LkzbGxs4OvrW+fCbsHBwTh16hQmT56s10WDgeqLn5mbm6NLly6QyWRwd3dHixYtpAvjnT59GsOHD4eVlRXc3Nxw9OhRJCUlSb/+N2bjxo1QKBTw9PSEra0tFi9ejK+++goDBw5scuzw8HBMmjQJ48aNg6WlJYYOHSol2wYOHIjVq1cjODgYtra2iI+Pxw8//KDzl7aKigp8+OGHaNu2LWxtbfHll18iPj4eJiYmOHToEHbs2IFz587BxcVFuqf9qFGjpPevXbtWuhL7iBEj8Mwzz0ingtGjJTY2FmVlZWjfvj28vb11HvIdEBCA1NRUdOzYUWuSrE/fri85GxYWBl9fX/Tr1w8dO3aEk5MT2rRp0+g4Uptm3MGDB2PVqlUIDAxEq1atkJiYCD8/P73i6dMWHx8flJSUSOOdtbU1OnfuDGdnZ61De3UlomvT1eeSk5PRr18/WFpaonv37igsLMS+ffvQokULnbFTU1PRtWtXWFpaYtq0aZg7d65097Omxq5vf6VO+v/yyy9S3B49euDPP/9EUlKSdKG7hQsXws/PD76+vrCyssILL7yA8ePH4+23376rvx3dX43NF3TRNQ48//zz8Pf3R9++feHg4ID4+Pg6F1S8275jbGyMUaNGoXv37vD09IS7uztWrFgBoPoX4YSEBBw/fhwODg4YP348/P396/yQ0NDcCqg+RN/NzU3aHqBmHND3y/bXX38Nc3NzvPDCC1AqlTA3N0eLFi2koy6a0gd1xdY1j7C2tkZiYiJ27NgBW1tbzJo1C5GRkejXr5/Odc+ePRthYWEICgqClZUV+vTpIyVfnJ2dkZiYiPXr18Pa2hqTJk3Chx9+iJdeegkA8Mwzz2DNmjWYP38+bGxs0K1bN5iZmWmddnjp0iXpl3F9TZo0CYmJibC1tUVISAhWr14tJbH03T/MnDkTJ0+e1LpoqZq++wB6uMlkMmksetDHQDUXFxekp6dj9+7dmDNnTqOx5HI5goKCcOrUKb3PMCgtLcX8+fPh6OiIVq1a4Y033sCSJUswe/Zsne9VKpXSXSpdXFzw66+/Ij09XfoB2NXVFXFxcdKFbzt27Ijc3Nw6d2Wqjz7fY9etW4cpU6bUSeTcuXMHS5cuRbt27WBtbY2XX34Z0yKWcX0AACAASURBVKZNQ3h4uF5/k0eBTDxOx/nco6FDh2LEiBEP3AT1999/R5cuXZCfny/dkvle3bp1C46Ojti/f7/0KykRPfpKS0tha2uL1NRUvX711cczzzyDMWPGYPHixc3eFiJqXpGRkVi5ciX++9//ai1/UOdWj6uysjJ4enrit99+0ysJda/q2z+oryGRnZ2t149oRA+jzZs3Y9myZdL1K+nxxCNfdEhNTcWxY8cQHBzc3E1BdnY2/vOf/6CqqgpXrlzB/Pnz4e3t3eTEixACK1euRNeuXZl4IXrE3bhxAz/++CMqKytRVFSEN954Ax06dEDfvn3vOWZcXBxKS0tRUVGBdevW4fjx45g4cWKztIWImtehQ4ekU+EyMjKwfPlyTJ06VavOgzS3ompmZmbIzs6+74kXXfuHyspKLFu2DH5+fky80COrpKQEq1at0roFNj2emHxpRL9+/eDn54cvv/yyzv3JDeHjjz+WTklR/1O/PnToEMrKyhAaGgobGxt4eXnBwsICMTExTVpnQUEBrKyssHHjRqxdu/au2tMUD2Ps1157rcG46iv7Ez3oqqqq8N5778HOzg5ubm64fPkyEhISYGRkdM8x4+Li0K5dOzg4OCAyMhLfffcd3NzcEBsb22Cf2bZtm0HaombI/vqwxibSR+3Pn/qf5qmyjcnNzcXQoUNhYWGBsWPHYsKECVpHOdyPudWj2gd1jZkPo4b2DwBw/Phx2NjY4MiRI/j000+buaVE1Zo6Bta2atUqtG7dGh06dKhzjatu3brVWY/6dMjG5ObmNjhW6HNaUnPFJp52RERERERERERkUMbN3QBDudeLJxE9zJhL/ftxrKHHDceZ5sGxhh43HGv+fhxn6HH0d441j2zyBUD1IVsag4hc9Vx9SLvmoe0KhQJA9VX81dTl6mXqOprLatcBAIWJKpaRcZ36jcWq/dhQu2rX07yLgD7r0be+ul597apvWe0BW/ODXFlZWf2oVFY/3rlTp6yioqLOsjuqeurXmvWkmBpl9dVXL6uvrLH11Be/sXWrt+2Oqo5S9VrfttZXX11Hs6yqqkrrUU19u2z6+w1YbQUTubn02sTIDACgkJuoHmvu7GBqZKpVVv1c1c9Vy0yM6itTaL0GAIUUS7uO5nPNWMa16hkbacRStbF2nep6qrGjVh3NGPWtW4ppVLesdh3tMuO6MWWqMtXZsnKN/aSRaqyRa/QvmarPyFTLZEqNsjuqsUZdVlkzHkFVT6Yeo+or01iPOgZqxdSsX1OnJpaorFWm0T5R0XAsUanUrqNRT12m+T6hWqe4o66jWaZaVqHZLqV22R3N+krY/5gEaj5t8U8AGncOUvcR9aNGf4ex6rlG/5Oeqx+NNeqr5yxSmcb+3Vj9PiPVa41TA1XPZQojjfqqs9qNVXcv0ZhtykxU+y4T1edVUfNZFqZl1XVMb6o267ZG02+rHss0mlz93FhRqvUaAORGZVrLjBS36papHuVGNbeKNlbFN5JXqDavpn1GRtV9xcS4ZplCXqmqV/2oMKrpM2aq+gp59baayGv25SZGSlWdKlVZzaCmfm4ql2ksq35uLperXss1yrSXmWnMP03kRqo2qB9rykyNTOosqxnTVWXGZjXbrxqv5ap9nMyo5vowMoWVqqz6jpkyec2dM+VG1bfVNTJyrFkmb6V6tFPVt6+JJXeU5uz097OxsUELWc3n0RTVz81UjyYa83tz1XPTKo3Pr+q5+tG8sqZModQuU6DuejS/nCqkR9X7tMq062uMdDCBqLNMUevRpJGy+t5nWs+y/2fvzsOjqNK3AT/V2UM6+8qSBEjYF1mVkUBigoMEBwFBRAKEsDguqDAiIDOERWBE/Sk6DERA1iATUJQRZAtJQBQEFfjEEYSwBSFA9kBClvf7I+miKwnphlCA+tzXlatTdU6dOtVd59Spt6uqa8rvUEuaqa4OZg/+sKusiKmp2TiapdWr/Mc0xDRLU/+vV8M8hyrTAOBY2aYcKl/tzSphr2hfNfkqX+3MK12lLDulepr5PHvl5mm2VdeD6mmasqqk2Zqvu8r6zNPUHUW7bsVwd2/p5jNfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEeKiMi9roQeFEW511Uguut+p835vsa+hv5o2M/cG+xr6I+Gfc3dx36G/ojuZl/zuw2+EBERERERERHdD3jbERERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvOouIiMCcOXPUaaPRiH379t3DGlmvcePGSExMvNfVILovZGRkwGAw4MyZMwCAuXPnol+/fve0Tnv27IGnp+c9rQMRERH9/vyWzmFSU1NhZ2d3r6tBOpo3bx78/f3h6uqKgwcPok+fPnjrrbfudbVuGYMvd1l+fj4efPDBe12N+86xY8fQrVs3eHt7w93dHW3atMGHH36oyRMcHAwnJye4urrCaDTC1dUVP/74o8WyExMT1fymZW1tbfHEE0/UuWxLysrKMH36dAQHB8PFxQWhoaHYunWrZrujo6Ph7e0NX19f9O/fH6dPn67zekkfiqKo/0+ZMgWfffbZPawN0L17d2RlZd3TOtxNqampMBgMajs1Go3o3r27Jo/BYICLi4umLefn51tV/qJFi9C8eXO4urqiU6dOSE1NvWNl34w1fd+RI0cQFRUFT09PNGjQANOnT6/TOun35/d2ksQvf+4vsbGxGDt2bI1pp0+fhsFgwPnz5+9yrehuu9/PYczHaPeTL7/8Em3atIGzszPatWuH7du3W7VccnIyoqKi4O3tfdM2ZqnsEydOoFevXnBxcUFgYCDeeeedOm+PNedVf//739GxY0c4ODjg0UcfrfM6MzIy8PrrryM1NRV5eXno1KkTNm/ejL/97W91LvtuY/DlD0hEUFZWdq+roREQEIDVq1fj0qVLyMnJwdq1azFt2jTs2LFDzaMoCpYtW4a8vDzk5+cjLy8PrVu3tlj20KFD1fx5eXnIyMiAo6MjYmJi6ly2JePGjcOOHTuwfft2FBQUYPfu3WjZsqWaPmTIEHh7eyMjIwOnT5+Gi4sLnnnmmTqvl37b7sc2er+wtbVV22l+fj727NlTLc/27ds1bdloNFosNykpCdOnT8f69euRm5uLsWPHIjo6GufOnatz2bWx1Pfl5eWhd+/eeOyxx3D58mXs3LkTy5cvvyMDKPr94kmSdUyBA9OJhNFoRGBgoFXLlpeXY9asWWjSpAlcXV3Rs2dPHDly5I6UXZu5c+dWO/ExGAx4+eWXAQDZ2dno2bMn/Pz84O7ujtDQUE1gTg/3y+dJv19lZWUQkTtWXklJyR0rqzbp6ekYOHAgXn/9deTl5WHy5Mno37+/ehV1berVq4cRI0Zg1apVNbYxS2WXl5fj8ccfR+vWrXHlyhV89tln+Oc//4mkpKQ6bZM151UhISGYNWsWxo0bV6d1maSnp8PGxgbNmze3Kv+d3l/uJAZfzBQWFuJvf/sbmjZtCjc3N7Rp0wazZ8+Gr68vSktL1XwFBQUwGo346quvAACXL1/G6NGjERQUBHd3d3Tu3BnHjx+vcR0GgwF79+5Vp1NTU9GjRw94eXnB19cXo0aNsljPiIgITJw4EQMGDICrqytCQ0ORnJyMnTt3om3btnB3d8fAgQNRWFioWe+CBQvQpUsXuLi44Ntvv4WDgwMuX76sKbtJkyZYs2aNOn3ixAmEhYXBaDSia9euOHDggJoWGxuL4cOHIy4uDh4eHmjUqBE+/vhjHDp0CF27doWbmxsiIyNx4cIFi9tkNBrRtGlTTeeiKAp+/vlnTb470ZBWrlwJV1dXTYS2LmXf7DP8+eefsWzZMnz00UcIDQ0FAPj7+2sGXydPnsSwYcPg4OAAJycnxMTE4PDhw7e5ZXQnXbx4EX/5y1/g7u6OFi1a4Msvv9Skz5gxQ43mL1y4EB06dNCkp6enw9bWVj0Inj17FoMGDUJAQAAaNGiAcePGoaCgQM1ftY0ePHgQpaWleOWVV+Dn54f69etj/vz5CA0NxcqVKwFU/wbZ1CbHjh2rtsmEhARNvZYuXYqQkBC4u7tj+PDhiImJsarfsVSX9u3b4+OPPwYAFBUVwdHRESNHjlSXj46OxltvvYXNmzfDz89PE1wqLCyE0WjE7t27LdbDGrfTltevX49hw4ahbdu2UBQF48aNg6+vL5YvX17nsgHgk08+QZcuXeDh4YH69evj73//OwDLfd9XX32F4uJiTJw4EQaDAS1atEBcXBwWLlx4W/UwmTNnDho1agRvb29MmDABUVFRmDlzJgCgX79+mDdvnpo3MDAQ4eHh6vTzzz+PF154AUePHoWDgwOuXLmiKbtp06ZYtWpVnepHv13386C3Joqi4NixY2pQ1ZqTIgB4++23kZiYiF27diErKwvdu3fHn//8Z83Y63bLrs2UKVM0Jz7fffcdDAaDeuJTr149LFq0COfPn0dOTg527NiB1atXY8mSJXVeN/2xmZ/DrFixAqGhoXj//ffRqFEjeHl54dlnn9W0fUvjntdffx1NmzaF0WhEaGgo3nvvPTXNFLxctmwZWrduDRcXF1y6dMnquh44cACBgYFYunQpgIpzp1deeQX9+/eHu7s75s+fj4YNG1a7gnn48OEYM2YMsrKyYGtrq57DJCcnw2AwqGOCsrIyuLu7a86LarJixQp07twZTz/9NGxtbTF06FB07NgRK1assLgNDz74IGJiYtCqVavbKjs1NRVnzpzBnDlz4ODggA4dOmDcuHFYtGiRxXUDNx+3VFXTedWIESMQHR0NLy8vq9ZVm//85z949NFHUVZWpu4rgPaKz5vtL2VlZZgzZw6aN28OT09PhIWF4eDBg3WuU10w+GJm1KhR+Pbbb7Fr1y7k5ubi888/x1NPPQUXFxdN40xMTERgYCAefvhhiAgef/xx5Obm4uDBg8jJycHy5cut+jb08OHD6N27N8aMGYMLFy7g7NmzmpOV2qxevRpTp05Fbm4uBg8ejJiYGHz44YfYs2cPTp06hf/9739YsGCBZplly5YhKSkJBQUF6NixI7p166Zp/Nu2bUNubi4GDRqkzlu8eDHef/99ZGdnY+DAgejTp4+m49ywYQMGDRqE7OxsTJs2DWPGjMH06dPx2Wef4eLFiwBwS5fIt2/fHk5OTmjfvj38/Pzw9NNPa9InTJgAb29vdOzYsdpJpbUSEhIQFxcHGxubOpdd22eYkpICNzc3rFu3Dg0bNkRwcDCee+45zfs3efJkrFy5EgUFBcjLy8Py5csxYMCA29ouurOGDh0KOzs7nDt3DmlpadVOwqvm/fnnnzWBs+XLlyMiIgKBgYEoLi7GI488gjZt2uD06dM4evQoMjIy8NJLL2nKMW+jDzzwAObMmYOtW7di//79SE9Px7lz56oN3qt+G7Jhwwb069cP2dnZWLBgAV544QWcPXsWAJCWloYXX3wRS5cuRVZWFvr06YP//Oc/Vr0fluoSFRWlXq2RlpaGwMBA7Ny5E0DFN0xpaWno1asXevfuDTs7O3zxxRfqsv/5z38QEBCAsLAwi/UoKytDUFAQAgIC8Pjjj9cYrBw0aBB8fHzQrVs3fPrpp1Ztn4hUO2EUEfzwww91LnvLli0YOXIkZs6ciStXruDYsWN47LHHNHlu1vfVVK+ysjKkp6dr+pJbsXLlSrz//vv44osvcPHiRQQEBCAtLU1NN/8sjx07hvLychw+fBhXr14FUHH1T69evdCqVSt06NBBE7DftWsXrly5ojmO0N33WzhJWrlyJYKDg+Ht7Y3Y2FhN0MJcTbcpzZgxA7169VKns7KyMHr0aAQGBsLPzw9DhgxBZmamVe+ViKC8vNyqvObWr1+P5557DkFBQbC1tcWMGTNw5coVTb9wu2UDFWOVdu3awc3NDUFBQTcNuC5evBgdOnRAp06dAAD29vZo2bKlOsYpLy+HwWCo9mVWXcyePRstWrTAiRMnAFRs55YtW9C8eXN4eHigf//+mn3A/MtNV1dXtGnTRv0Ck367Tp8+jczMTJw8eRL79+9HUlKS+iWMNeOe1q1bY+/evcjPz8eHH36IKVOmVLttZu3atUhJSUF+fj58fHysqtfnn3+Ov/zlL1i6dCni4uLU+R999BFefvll5OTkYMKECRg9erTmNt+8vDxs2LABY8eOhaenJx544AH1WLhjxw6Ehoaq09988w1sbGzQuXPnWuty6NAhtW2adOzYEYcOHbJqW+pS9uHDh9GsWTM4Ozvf8rqtGbeY3Oy86k4ZPHgwtmzZAhsbG+Tn59/0AgdAu794e3vjH//4BzZt2oRt27bhypUrGDVqFHr37o3c3Fxd6moVIRERyczMFEVR5KeffqqWNnv2bOndu7c6/eCDD8r//d//iYjIvn37xN7eXvLz82ssNzw8XN544w11WlEU+eqrr0RE5LnnnpPBgwffcl3Dw8PlhRdeUKePHj0qBoNBDh48qM6bNGmSDBgwQLPe1atXa8pZvXq1tGzZUp1+6qmnZPz48ep0cHCwTJ8+XbNMYGCgrF27VkRERo4cKX379lXTrl69KoqiyIYNG9R5CxculI4dO97S9pWWlkpycrLEx8dLUVGROj8tLU0KCwultLRUtm/fLl5eXpKQkHBLZe/Zs0dsbW3l1KlTmvm3W3Ztn+Hs2bNFURQZOnSoFBQUyIULF6Rbt24yduxYNc93330nnTt3FhsbG7GxsZEOHTpIZmbmLW0T3XkZGRmiKIqkp6er87Zv3y4Gg0FOnz4tIiLx8fHSq1cvNf2pp56Sl19+WZ0ODg5W20pSUpKEhIRo1nHgwAFxcHCQ8vJyEam5jYaEhMjy5cvV6WvXromDg4OsWLFCRERSUlLEzs5OTa/aJkVEfHx85PPPPxcRkdGjR8uIESM06WFhYRIbG2vxPbFUl82bN0twcLCIiLz66qsya9YsadGihRw9elRSU1PFx8dHXfa1116Tfv36qdM9evSQuXPnWqzDxYsX5fDhw1JWVia5ubkyZcoU8fLykl9//VXNk5ycLMXFxVJcXCzr1q0TJycn2bp1q8WyV6xYIT4+PnLgwAEpKSmR999/XwwGg+Yzvt2y+/TpI5MmTbKYr6a+LysrS7y9vWXu3Lly/fp1OXLkiDRq1EgMBoNkZGRYLLMmUVFR1fr2oKAgmTFjhohUHFOcnJykqKhI/vWvf0lcXJz07t1bNm/eLGfOnBFbW1vJzc0VEZF///vf0r59e7Wc4cOHa/o4ujtqG2ssX75c7OzsZNq0aXL9+nX55ZdfxNPTUxITE0VEpKioSEJCQiQ+Pl6Ki4slJydHoqOjZdSoUWp5a9askQsXLoiIyK5du8TJyUm2bdsmIiKnTp0SRVEkKipKMjMzpaSkRO3XapKSkiKKosigQYMkPz9fMjMz5U9/+pNmvwkODpY1a9ao+c37OZHq/W9YWJiMHTtW8vPz5dq1azJ69GiJjIy0+L6dOnVKDAaDNGzYUHx8fCQiIkJSUlIsLici0qVLF3nvvffU6evXr4udnZ1MnDixzmUvXLhQGjRoIHv37hURkStXrsiBAweq5SsuLhZvb29ZsmRJtbS+ffuKk5OTKIoiQUFBcvz4cavWXZORI0fKmDFjpKSkRGJjY+Xhhx+WrKwsdTsVRZGePXtKZmam5OfnS//+/eXRRx9Vlx88eLD06NFDPX6eOHFCTpw4cdv1obvDUr/i5uamaeuDBg2SCRMmiIh1456qnnzySXnttddE5MZ+tWfPHqvqauonFixYIEFBQXL48OFq2xIXF6eZd+bMGXFwcJDz58+LSEW7a9eunZo+adIkdczUpUsXWbdunfj7+4uIyIwZM2TgwIEW6xUZGSnx8fGaedOnT9f0X5aY+pKqx3xLZc+aNUvCw8M16bt27arWn9bE2nHLzc6rTKr21berpuOA+f55s/3FaDTK7t27NfPatm2rHl/uBV75UunUqVNQFEW9lMlcXFwcUlJScO7cORw5cgSHDh3C8OHDAVREfX19feHi4nJb62zWrNlt1TcgIED93xTR9Pf318yr+iDIoKAgzfSTTz6JS5cuYe/evcjKysLGjRsxZsyYWpcJDAzUPAPBvB5OTk5W1cMSGxsbREREIDMzU70MHgDCwsLg7OwMGxsbREVFYeLEiVi9evUtlZ2QkIBHH3202nbdbtm1fYZGoxGKomD27NmoV68e/Pz88Nprr6lXUeXk5CAyMhIDBgxAYWEhCgoK0K9fP3Tv3h3Xr1+/pe2iO+vcuXNQFEVzi1jjxo1rXSY2NhaJiYkoKyvDzp07kZubi/79+wOo2E9Onz4NT09P9S8qKgo2Njaa2/Kq7pcZGRmaOjg6Olr85se8TQIVl6Cb2mBGRka1dVSdvhlLdenZsyd+/fVXHD9+HDt27ECvXr0QFRWFbdu2YceOHXjkkUfUvLGxsfjyyy9x+fJlnDhxAl9//bXap9bG19cXbdu2VR+6O2fOHHh5eWHLli1qnoiICNjb28Pe3l69KtD8yoybGT58OF599VU888wzCAgIwKFDh9QH3dW1bGv7+pr6Pg8PD3zxxRfYsmULAgICMHLkSMTFxcFgMMDDw8NimTWpaT9o1KiR+n/Lli3h5eWFtLS0ap/l9u3b0alTJ7i6ugIAnn76aRw7dgw//PADCgoKsGHDBs03jXR/cHZ2xsyZM2FnZ4emTZsiMjJSvVx+06ZNACquUrW3t4ebmxtmzJiBNWvWqFfHDB06FH5+fgCA8PBwREdHq1e2mcTHx8PHxwe2trYWnwGiKArefPNNuLi4wMfHBzNnzrztW9UOHDiA7777Dh988AFcXFzg6OiIefPmITk52eJDYL29vfH1118jPT0dp0+fxoABA/DYY4/h//2//2dxvX379sW//vUv/PLLLyguLsa0adNQXl6OvLy8Opf9wQcfYNq0aejWrRsAwNPTs9o33EDFs6pKSkqqXSUMVHyuhYWF+OabbxATE6Ppy25HTk4OHnvsMRQUFCA5Obla/2P6/F1cXDB//nxs374dFy5cwKVLl5CUlITFixerx5AmTZqgSZMmdaoP3Xu+vr6atm4+3rBm3LNgwQK0a9cOnp6e8PDwwH//+1/NFVOKolg9RgGg3mISGxuLtm3bVksPDg7WTDdq1Ai9evXCRx99BKDitmzzB0tHRUVh586dyM7OxvHjxzFw4EB4e3vj0KFD2LFjB6KioizWyWg0VrvKIicnRz2G1oWlsuuybmvHLTc7r7oXqu4vly9fRkFBAR5//HF1H/Tw8FCv3r5XbO/Zmu8zpgZ5/PhxtGjRQpPm7++P6OhoLFu2DNnZ2XjiiSfUn3cNDg5GZmYmCgoKbjkAExwcXOulU3eawaCNtTk4OGDEiBFYsmQJ2rdvjw4dOqBNmzaaPKdOndJMnzlzRjNI11NpaanF90du4b7y7OxsJCUlWX2bhTVl1/YZPvDAAzWWaTpQnThxArm5uZgwYQIcHBwAABMnTsSMGTPwv//9D+3atbOqnnTnNWjQAEBFcNUUdElPT691mV69esHBwQGff/45Pv30UwwZMkT9XIOCgtC8eXPNwxhrUrWNNmjQQPPrV9euXbule56rqloeUNGmmzZtesvLVq2Ls7MzHnroIXz88cc4ffo0unbtil9//RVLlixBVlaW5rkyzZs3R6dOnbBq1SpkZ2cjKioK9evXv61tUhSl1rZqKd3cq6++ildffRVAxa1SjRs3rvW2SWvLvtW+vmrf17VrV80vL7366qvo0qWLGvC+VTXtB6Zb00wiIyOxdetWpKWlISEhAefOncOwYcNw+Y6H4QAAIABJREFU8eJFzYDTzc0N/fv3x0cffYT27dsjKCgIXbt2va16kX6sPUkyERH1JCkgIAALFizAkiVLcO7cOYgIioqKMHToUDX/rZ4kAdAEc4ODg1FcXIzLly/fcpDg1KlTKCoqUoNDpvo7OzvjzJkztfYt9erVU/dXW1tbvPDCC9i0aROSkpKqjYeqmjx5Mq5evYpHH30UV69exahRo9CiRQu1/nUp+9SpUzV+GVhVQkIChg0bprmtwJyiKGr/8dxzz9XpF6R2796tPmPG3t6+2nrMP3/TmNq0v9zsy036/bI07tm7dy8mT56MXbt2qQ8HHzRoULVjatVxUW1sbGyQmpqKqKgoODg4YPLkyRbLGjt2LCZMmIA+ffrgp59+wrBhw9S0sLAwXL58Gf/6178QFhYGGxsbREZG4tNPP8X+/fuxbNkyi3Vq3749UlJSNPO+++47zW2Tt8tS2e3bt8exY8dw7do1dbxw8OBBtG/f3mLZ1oxbbvW86m4w/4y9vb3h4uKCHTt21Bi8vld45UslHx8fPPnkk3juuefUQemJEyfU+1nHjBmDZcuWYc2aNZqrQzp37oyOHTti9OjRuHTpEkQER44cseohs+PGjcPnn3+ONWvW4Pr16ygqKqr206bWupUghLkxY8YgKSkJixYtqnbVC1DxDIrvv/8epaWlePPNN3Ht2jX06dPnttZVm23btmH//v0oKSlBaWkpPvvsM6xZs0Zd15kzZ5CSkoLi4mKUl5cjNTUV7777LoYMGWL1OpYvXw4fHx9ER0dr5tel7No+w7CwMLRt2xbTp0/H1atXkZmZibfeegsDBw4EALRo0QKenp547733UFJSguLiYrz99ttwc3NDSEiI1dtFd16DBg0QHh6OSZMmIT8/HxcvXsSsWbNqXcZgMGD48OFYsGABPv30U02woW/fvrh+/Trmzp2rPkchIyMDGzdurLXMmJgYzJ8/Xz25mDJlSp0eZBkTE4P169cjNTUV5eXlWLduHb755hurl7VUl8jISLz99tsIDw+HoiiIiIjA7t27cfDgwWrfEI0cORLLli3DypUrrXrgL1DxPJETJ05ARFBYWIj4+HhkZmbiz3/+MwDgxx9/xLfffqv2Ixs3bsTq1avx1FNPWSw7Ly8P//vf/wAAly5dwrPPPqs+lLiuZT///PP497//ja1bt6KsrAz5+fnq8w4s9X0A8P3336O4uBjXr19HUlISlixZovn1kvj4eItXZpmLiYlBQkICDh06hNLSUrz99tv49ddfNXkiIyOxZMkSBAUFwdvbGw888AAyMzOxZcuWGj/LxMREJCQkIDY21up60P3BdJKUlZWl/mVnZ6OwsBABAQHqSdKHH36opvXt27dOJ0kANAHA9PR0ODg41Bh4MRqNKCsr0/w6ifkVLUFBQXBxcalW/4KCAjz00EO3VCfA+qCqvb095s2bh5MnT+LChQuYOHEiTp48iYiIiDqXbc2Jz9GjR7F79248++yzFssrLS3FL7/8YjFfbR5//HG8+eabCA8Pr/asLRHRfFmXnp4ORVHU590BuKtfNtK9Z2nck5eXB1tbW3h7e0NE1Cs8zd3OeKdZs2bYvXs3lixZgqlTp1rMHx0djaKiIsTFxWHgwIFwc3NT0xwdHfGnP/0Jb731lhrQiIyMxLvvvgt/f3+rxurDhw/HgQMHsG7dOpSUlGDNmjX4/vvvMWLECIvLigiKi4tRVFSkBr2Li4vV98VS2T169EBQUBCmTp2KoqIifP/990hISLCqz6ht3GJys/MqoKLPKSoqQklJCcrLy9UxjMmtjlusUdP+8tJLL2HixIlq/1dQUIBt27ZZdZ6uFwZfzCxbtgwPPPAAevbsqT612fTQ2EcffRQGgwFubm6ay+cVRcGmTZvg5OSEBx54AB4eHoiLi1M7mqqX3ppPt2vXDps3b8bChQvh5+eHoKAgq251qelyXmsu8a2J6Rvo8+fPVws2KIqCsWPHYvz48fDw8EBSUhI2b95c68OEb/fnBvPy8jBq1Cj1F4NmzpyJd955R314bWFhISZMmABfX194enrixRdfRHx8PJ577jmr1/Hhhx9izJgx1epYl7Jr+wxN+8aVK1fg5+eHTp06oUuXLpg/fz6Aim/F/vvf/2Lz5s3w9/dH/fr1kZycjC+++OKm32LR3ZOYmIiioiI0atQIPXv2tOpAOXLkSKSlpaFJkyaah7A5OTkhOTkZR48eRYsWLeDu7o5evXppHnpWU9uZMmUKevXqha5du6JJkyZo0KABAgIC1CtqrGFebo8ePfDee+8hNjYWnp6e2Lx5M/r3729VedbUJSoqCvn5+eqvQLm5uaFFixYIDAysdrnvkCFDcPLkSVy9ehX9+vWzalsOHTqEyMhIuLq6omnTpti/fz927NihXql06dIlddv8/PwwZ84cfPTRRzUODKrKy8vDoEGD4OrqipYtW6K0tBS7du1St68uZffp0wdLly7FlClT4OnpiRYtWmDbtm3qemvr+wBg0aJFCAgIgJeXF9555x2sX79e8+tDZ8+e1RyXLBk+fDief/559OnTB/7+/jh//jweeuihWj9LoOK2q9LSUjz88MOa8qKiouDs7Izvv//eqtvH6P5yL06SRET91Z7MzEzMmDHjpvtOs2bN4OLigiVLlkBEsGfPHqxfv15N79y5M9q3b48XX3wRWVlZACra67p16yzWY9++ffjxxx9RVlaG4uJiJCQkIC0tTb1ltDYXL15UA0imh+0//PDD6klaXcp+/vnnMWfOHHzzzTcQEVy5cqXar6osXrwY3bp1q3YVzb59+5CcnIyioiKUl5cjLS0N7733niagGxsbe0t9hnm95s6di6ioqGqB+1mzZiEzM1P9ydtevXrB39/f4pebdP+q7RzGEkvjnj//+c8YPnw4unTpAh8fH3zyySfVfnDids8pgoKCsGfPHmzatAkvvPBCrWUZDAbExcXhhx9+0NxyZGI6FpradXh4OK5du2b1lStNmjTBJ598glmzZsHd3R3z5s3Dxo0brfrZ+bS0NDg5OaFVq1ZQFAUhISFwdnZWfxnSUtkGgwGbNm3CkSNH4OXlhccffxyTJ0+26oH4tY1bTG52XgVUfLnv7OyMuXPnYteuXXByctLcWXKr45aaWLN/zpgxA0888QT69esHd3d3NG/eHIsXL77tB6HfEfo/Vub3Izw8XObNm3evq3HHjRw5UsaNG3evq0FEFhQUFIidnZ18/fXXd6zMbt26WfWw27tRF7o9zZs3l3Pnzt328uXl5dKgQQP1AdH02xMREaF5MKbBYNA8GDM0NFST3/QAVZNz587JsGHDpEGDBuLm5iYtW7ZUH+RYXl4uzz//vHh4eIiXl5eMGjVKYmJi1Ad13+xhkDdjenDiypUrJSgoSDw9PWXkyJFSUFCg5mncuLHmgYgbNmyQJk2aiKurqwwePFgmTJigeYhjdna2PP/88xIcHCyurq4SEhIif/3rXy3WZe3atRISEiIuLi7i7e0tPXr0kJ07d1q1HQcOHJDQ0FCpV6+e+Pv7y/jx46WwsPCOlC1S8fDPVq1aiYuLiwQFBcm///1vNe3atWvi6ekpq1atqrZcWlqadOrUSVxdXcXNzU1atWolc+fO1Tzk9JFHHpGZM2daXZeq+0tSUpJ4eXlJcnKy+vkvXbpUmjVrJu7u7tKvXz+5ePGimr+goEBeeeUVCQoKEqPRKG3atFH3T6J7bfny5dKiRYt7XY0/lLqOW37LFJE6XMP+B5KWlobo6GicOnXqjvxm+f3i2LFj6NSpE/bv34+WLVve6+oQkZns7Gzs378fkZGRKCwsxCuvvIKvvvoKR48eve2f9NuwYYP6c8/Lly/Hiy++iKNHj1p87osedaF7Z926dXjiiSdQVlaGuXPnYuHChTh58qTmkmsi+v0pKipCy5Yt8eOPP/IqW/rDy8/PR8+ePTF27FirbschqivedmSFrl27on///vjggw/uSuBl7ty5MBqNcHV1Vf9M01Xvt6uLQYMGoUuXLpg6darugZezZ8/edJtu5dah31PZRJaUl5dj2rRp8PLyQtOmTXH+/Hl8/vnndQp2bNiwAQ0bNoSPjw8WL16MjRs3omnTpkhMTLzpvr527Vpd6lLVnj17blqHefPm/SHL1ssHH3wAf39/NGjQACkpKdiyZQsDL0R/AI6OjkhPT2fghX5zqh5nTX/W3P5bk/feew/+/v5o3Lhxjc+9tEZdjv9363zvTteb6oZXvhARERHRHWM0Gmu8/z4sLAxffPHFXavH2bNn1eclmEjlr+8MGzYMCxcuvOmyiYmJGDduXI3LLl68uMafd7aWnmUTEdH9i8EXIiIiIiIiIiId2d7rCujldp+QTfRbxljq3ce+hv5o2M/cG+xr6I+Gfc3dx36G/ojuZl/zuw2+AEDR7GuwKStWp5XSoop/Sq4CAKS4UE0rv5Zb8Wo+r7jiJxfLKueVVuYBgFLTvMo8JddvLFdcnAMAuG42r6Sk4v/rJRX5i67n3Ugrq6hPqXKtYn0219Q0caqos+JYos4zOJYBAGwcK3YUW7Pbdm0cK18dtK8AYDDNc64+r+orABicKl4VB9OrWYdsb1dRP4d66qyyyoJLDBXzrsNFTSsscwcAXC2rp3kFgMLSiuVySm7kzy+rmJdXWlGJ3FJHNS3zuktl/oq0vOtOatrVyv9Li25spE1hRX67a86Vrzfy212rKNexcp5jmZ2a5qRUPMvCyebGdtezr3hMkqM9NK8A4FD5v3NlVR1vFAUnu4oynM1anKtpXmX59czXU/m/q23Fq5PZ05lM/zsoN34mzR6lcHrd+p8fpjvroYWusDfc2K/sKxuincG+8vXGZ+NQ2ShNaRX/V+wstpXz7G1qSrPTTAOAnVqWNo/5/+Zl2VbJZ2tjVlZlHavmqchXsePaV8ljXkZN61bLtKmeVjVPTWk25tuqVPxvUCrqYhCzZ82UVzaKMrM+qqKbhJRWvpaZZS8xzZNqaWr+ytfy0hsHZKlSpvm88pKbl1VeuZ7ykurLSWX55ebLlWiX05alXV9NaWJW5/IqZZnXvdy0nFlZ5aW1539sbUPQvfQXQDE78CimNlIxz4AbaTZwqjbPIKZ8DpV5bhxblcp5pleYLVeuOFe+OmheAaC8st8Ssz4Qlf2OoTLNxrwPsNX2C5r+wbaifdvaVfYBtjfaucGu4n8bO4PZvIo2b3ComKeYHXfV/yvzmL9tMKVVHmPNR8OVbxGkMo/YmvUrtto0zbKVr4pZWaY6GGpIM9iYtsGUZjb4r1JmTesuN+8CbbWvZkMZSGW5Ylre/DFdNazbVFdT/RztbqQ5Vc6rV/nqbHMjzbVyuXqG6mnOlfmN5vMM2jKdDNq0xw03xol093ma/W8aUZt6C/PRpun/mpqEtneqOc18F7dXqpdlV+W1pmZsV8NyNdWraj6HWtLMlzPVy/w0qOq67c3STPlqSjPNczBrh5WnFrCtLNTWrGK2ladGNqZzMrNuVqn8QDRNpXKe2kWbb6RpWfsqr+b5zTfcsUq+mj4Y08bW9sFoylCqp1V9ozRppjfHvKzKN8/O9Gq2F5lOiu0bVU43v5Fm6FTxqjx4Y57S6a4HHPnAXSIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOFBGRe10JPSiKcq+rQHTX/U6b832NfQ390bCfuTfY19AfDfuau4/9DP0R3c2+5ncbfCEiIiIiIiIiuh/wtiMiIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX6wQERGBOXPmqNNGoxH79u27hzWyXuPGjZGYmHivq0F038vIyIDBYMCZM2cwd+5c9OvX757WZ8+ePfD09Lwr67qT22swGLB37947UlZN7ub7cqf9lutORER0q8zPoe7n86fU1FTY2dnd62rQHwCDL7chPz8fDz744L2uxn3n2LFj6NatG7y9veHu7o42bdrgww8/1OQJDg6Gk5MTXF1dYTQa4erqih9//NFi2YmJiWp+07K2trZ44okn6ly2JWVlZZg+fTqCg4Ph4uKC0NBQbN26VbPd0dHR8Pb2hq+vL/r374/Tp0/XaZ1btmxBZGQkfHx84OXlhZ49e2LPnj2aPAaDAS4uLprtzc/Pr9N6/+gURQEATJkyBZ999tk9rUv37t2RlZV1V9Z1P2yvte7m+wIAp0+fhsFgwPnz5+tclp51v1d95PHjxzFo0CA0bNgQbm5uaNu2LZYuXarJExcXh8DAQLi5uaFBgwYYPXo0cnJy6rTeP4rf0pc/1py88Auh35YVK1YgNDS01jx6B9zp9+N+P38yjQHvJ6mpqTAYDOpx22g0onv37lYtm5ycjKioKHh7e990HPPll1+iTZs2cHZ2Rrt27bB9+3ZN+okTJ9CrVy+4uLggMDAQ77zzzh3ZrqtXr2L8+PGoX78+jEYjWrdujUOHDlXLd+HCBXh6eqJZs2Z3ZL33AwZffqNEBGVlZfe6GhoBAQFYvXo1Ll26hJycHKxduxbTpk3Djh071DyKomDZsmXIy8tDfn4+8vLy0Lp1a4tlDx06VM2fl5eHjIwMODo6IiYmps5lWzJu3Djs2LED27dvR0FBAXbv3o2WLVuq6UOGDIG3tzcyMjJw+vRpuLi44JlnnqnTOrOzszF+/HicOHECly5dwtNPP43HHnsMGRkZmnzbt2/XbK/RaKzTekl/92PbpZsTkftyQFbVveojs7Oz8cgjj+DAgQPIzc3FokWL8Le//Q0bN25U80ycOBE///wzcnNz8dNPP6GwsBDPP/98ndb7R8WTF+t98sknaN++PYxGI1q2bIn169dr0m83GGkKyJqWMRqNCAwM1OS5dOkSBgwYAFdXV/j5+WHy5Ml13h5rAp3Xrl3DqFGj4OHhAU9PT4wZMwbFxcV1Wu/99JkS3a6ysjKIyB0rr6Sk5I6VZYmtra163M7Pz6/2ZezN1KtXDyNGjMCqVatqbMfp6ekYOHAgXn/9deTl5WHy5Mno378/zpw5AwAoLy/H448/jtatW+PKlSv47LPP8M9//hNJSUl13qZ+/frhzJkzOHDgAPLz8/HFF1+gfv361fKNGzcOnTt3rvP67ie/u+BLYWEh/va3v6Fp06Zwc3NDmzZtMHv2bPj6+qK0tFTNV1BQAKPRiK+++goAcPnyZYwePRpBQUFwd3dH586dcfz48RrXUTXKn5qaih49esDLywu+vr4YNWqUxXpGRERg4sSJ6sE5NDQUycnJ2LlzJ9q2bQt3d3cMHDgQhYWFmvUuWLAAXbp0gYuLC7799ls4ODjg8uXLmrKbNGmCNWvWqNMnTpxAWFgYjEYjunbtigMHDqhpsbGxGD58OOLi4uDh4YFGjRrh448/xqFDh9C1a1e4ubkhMjISFy5csLhNRqMRTZs21TRwRVHw888/a/Ldic5v5cqVcHV11XyrW5eyb/YZ/vzzz1i2bBk++ugj9dsff39/zUDr5MmTGDZsGBwcHODk5ISYmBgcPnzY4jpzcnIwePBg9Uqhtm3bqvvj0KFD0a9fP7i6usJgMODZZ59VP/M7sb0EXLx4EX/5y1/g7u6OFi1a4Msvv1TTZsyYgV69egEAFi5ciA4dOmiWTU9Ph62trXqAOnv2LAYNGoSAgAA0aNAA48aNQ0FBgZq/ats9ePAgSktL8corr8DPzw/169fH/PnzERoaipUrVwKo/i2yqa2OHTtWbasJCQmaei1duhQhISFwd3fH8OHDERMTY1V/ZL69ALBgwQI0adIEbm5uaNSoEaZNm6amHT58GJGRkfD09ERISAjeeOMNlJeX11huTd+axsbGYuzYsQBunMSsXLkSrVu3houLC/r27YucnBxMmTJFfW8WLlyoLn+r70tGRgYee+wx+Pr6wsPDAz169MB3332n2faoqCi8/vrr8PPzg7+/P+Lj49X0Bx54AADQrFkzuLq64o033rD4fn7yySfo0qULPDw8UL9+ffz9738HAKSkpNRY9zvR/1Z1t/rIrl274q9//Sv8/f0BAA8//DB69+6NlJQUddlWrVrByckJQMVgzmAw4NixY7dVD7p37vTJi56++eYbxMTEYMGCBcjPz8f8+fPxzDPPaI6hdQlGKoqCY8eOqcuajgUmQ4cOVb9p3rdvHz799FPMnz+/TttkTaBz/PjxOHbsGI4fP45jx47h6NGjmDBhQp3WS3SnmJ8/mcYH77//Pho1agQvLy88++yzmj7G0tjq9ddfR9OmTWE0GhEaGor33ntPTTONL5YtW6aOLy5dumR1XQ8cOIDAwEA1wBkREYFXXnkF/fv3h7u7O+bPn4+GDRtWu2p4+PDhGDNmDLKysmBra6sev5OTk2EwGLB8+XIAFf2pu7u75pzsTnvwwQcRExODVq1a1Zi+YsUKdO7cGU8//TRsbW0xdOhQdOzYEStWrABQcdw/c+YM5syZAwcHB3To0AHjxo3DokWLrFr/zcZCW7duxddff43ly5erAZfg4GD4+Pholl+1ahXKysrq/IX2fUd+ZwYPHiw9evSQ06dPi4jIiRMn5NixY9K4cWNZv369mm/x4sXSqlUrEREpLy+Xhx56SJ588km5dOmSiIgcOXJEfv31VxERCQ8PlzfeeENdVlEU+eqrr0RE5NChQ+Lo6CgrV66U69evS1FRkaSmplqsZ3h4uPj6+sq3334r5eXlMnXqVKlfv7489dRTkpOTI9nZ2dKqVSuZM2eOZr3t27eX9PR0KS8vl+LiYunZs6e89dZbap6tW7eKp6enFBcXi4hIcHCwNGjQQL7//nspKSmRefPmiY+Pj+Tn54uIyMiRI8XZ2Vm2bNkiIiKLFi0SFxcX6devn5w/f16uXbsmjzzyiIwdO9bqz6Bdu3bi6OgoiqJIu3bt5MqVK2pacHCw+Pn5iZeXl3To0EEWL15sdbnm2rZtK9OmTdPMu92ya/sMFy1aJO7u7jJz5kxp0KCBBAUFyV//+lf1/RMRmTt3rgwbNkzy8/MlNzdXnn76aRkxYoTF9U6dOlX69u0rV69eFRGR48ePy6lTp2rMe/jwYbGzs5NffvlFnacoitSvX1+8vb3loYcekk8++cSq7aUKjzzyiAwYMEDy8/Pl4sWL0r17dzEYDHL69GmJj4+XXr16iYhIdna2ODk5yaFDh9Rl//GPf0hUVJSIiBQVFUlISIjEx8dLcXGx5OTkSHR0tIwaNUrNX1PbnTFjhrRs2VJOnTolRUVFMn78eLG3t5cVK1aIiEhKSorY2dmpZZja6n//+18REfnkk0/Ezs5Ozpw5IyIiqamp4uTkJCkpKVJWViZr164Ve3t7iY2NtfhemG/vsWPHxNnZWX766ScREcnNzZV9+/ap//v5+ckbb7wh169fl59++kmaNGmi6YPM+8fly5dLaGioZl0jR46UMWPGiIjIqVOnRFEU6devn+Tk5EhWVpa0atVKmjVrJkuWLJGysjLZsmWL2NnZydmzZ2/rfTlz5oxs2rRJioqKpKioSF5++WUJCgqS0tJSddvt7e0lISFBysrK5JtvvhE7OzvZu3evWkeDwSDnz5+3+D6KiGzevFmMRqNs3rxZysrKJD8/X30/blb3O9n/mtytPrKqwsJCCQ4Olo8++kgzf968eWI0GkVRFKlXr55s3Ljxlrfpj6i28cfy5cslJCREFixYIA0bNhRPT08ZN26clJeXq/nPnDkjTz75pPj7+0v9+vVl7NixmuPX1KlTpUmTJuLi4iIhISHy7rvvqmmm9rl06VJp1aqVODo6ysWLF29aV9P+vWLFCgkKChIvLy8ZOXKkFBQUqHmCg4NlzZo1an73mZncAAAgAElEQVRbW1tNGfHx8WrfKiJy5coViYuLk0aNGomvr6889dRTtdbBZNKkSTJgwADNvIiICImLi6uxLrfC9L6cO3euxvT09HRRFEXS09PVeUuXLpUmTZpYVX5KSoqEhYWJp6en+Pj41NqHDxkyRF566SUREbl27Zo4OTnJrl271PSdO3dKvXr11DHhrTL14f/85z8lICBA/Pz8ZOLEiWr/KVLzPmnOvM8XsW6frF+/vri6ukrjxo3lgw8+uK260/3BvA+ruq/Y2dnJtGnT5Pr16/LLL7+Ip6enJCYmioh1Y6s1a9bIhQsXRERk165d4uTkJNu2bRORG+00KipKMjMzpaSkRNM3VmV+fP7ss88kICBALcu0HW5ubpKSkiIiFe1t+vTpEh0drebJzc0VZ2dn2b9/v4iIdOrUSVatWiUiIlOmTJFmzZrJM888IyIie/bsEU9PT4vvX0pKihgMBgkMDBR/f3/p27evZjxqDdM4JiMjQzP/iSeekFdeeUUz76WXXpKBAweKiMi7774rHTp00KR/+umn4uXlZXGdtY2FJk+eLG3atJEXX3xRfH19JSQkRKZOnarpV3799VcJCgqSs2fP1jiW/C37XQVfMjMzRVEU9aTB3OzZs6V3797q9IMPPij/93//JyIi+/btE3t7e03nb662wc9zzz0ngwcPvuW6hoeHywsvvKBOHz16VAwGgxw8eFCdV3XwoCiKrF69WlPO6tWrpWXLlur0U089JePHj1eng4ODZfr06ZplAgMDZe3atSJScVDs27evmnb16lVRFEU2bNigzlu4cKF07NjxlravtLRUkpOTJT4+XoqKitT5aWlpUlhYKKWlpbJ9+3bx8vKShISEWyp7z549YmtrWy1Qcbtl1/YZzp49WxRFkaFDh0pBQYFcuHBBunXrpjkZ+u6776Rz585iY2MjNjY20qFDB8nMzLS43vj4eOnWrZscPHiw1gPCxYsXpVmzZjJ16lTN/OTkZCkuLpbi4mJZt26dODk5ydatWy2ul0QyMjKqDY63b99eY/BFpKJdvfzyy+p0cHCw2oaSkpKqDTYPHDggDg4O6udaU9sNCQmR5cuXq9PXrl0TBweHWoMv5m1VRMTHx0c+//xzEREZPXp0taBfWFjYLQdfTp48Kc7OzpKUlKQ5aRIRSUxMlMDAQM28xYsXS4sWLdTp2wm+VO332rRpo1nG19dX3c5bfV+qysvL0xwn4uPjq62vS5cusmDBArWONQ1abqZPnz4yadKkGtMs1f1O9b93s480V1ZWJgMGDJCePXtqBlHmTp06Jf/4xz/k8OHD1m3MH5yl4Mv9dvKiKIoMGjRI8vPzJTMzU/70pz9pjpdVgy/m7UFEqvW9YWFh6sn5tWvXZPTo0RIZGWnxfXv11Velf//+mnk9e/aUTp06aepyO8FIU5/QsGFD8fHxkYiICPWETERk48aN4uHhoVnm+++/F4PBcNNxpkldAp0//PCDGAwGyc3NVfNkZ2eLoihy5MgRq7atKtM+9sILL0hxcbGcPHlSmjVrJnPnzlXz3Eqff7N90hQU27ZtmzRs2FDtby9duiQ//PDDbdWd7g+1BV/c3Nw0fcqgQYNkwoQJImLd2KqqJ598Ul577TURudF/7dmzx6p6mvqjBQsWSFBQULVjVHh4uCZ4K1IRSHRwcFC/nFm4cKG0a9dOTZ80aZI6LuvSpYusW7dO/P39RURkxowZapCjNhcvXpTDhw9LWVmZ5ObmypQpU8TLy0u9QMAaNxvHREZGSnx8vGbe9OnT1T541qxZEh4erknftWtXtX67JrWNhUaPHi2KosikSZOkuLhYjh8/LqGhoZoLDp544glZuHChiNTcr/yW/a5uOzp16hQURanx4WBxcXFISUnBuXPncOTIERw6dAjDhw8HUHFpmq+vL1xcXG5rnbf7EKCAgAD1f2dnZwBQL902zav6ANWgoCDN9JNPPolLly5h7969yMrKwsaNGzFmzJhalwkMDMS5c+dqrIfp0nBL9bDExsYGERERyMzMxMyZM9X5YWFhcHZ2ho2NDaKiojBx4kSsXr36lspOSEjAo48+Wm27brfs2j5Do9EIRVEwe/Zs1KtXD35+fnjttdfUywxzcnIQGRmJAQMGoLCwEAUFBejXrx+6d++O69ev17reSZMmITIyEiNGjICvry9iY2ORmZmpyXP+/Hk88sgj6N27d7XbHSIiImBvbw97e3sMHjwYMTExmtvN6ObOnTsHRVE0t481btz4pvljY2ORmJiIsrIy7Ny5E7m5uejfvz+Aiv3n9OnT8PT0VP+ioqJgY2OjuV2k6v6akZGhWb+jo2O1Sy6rMm+rQMX9vKa2mZGRUW0dVaet0bhxY6xZswYJCQmoX78+evTooT6A7ezZs9XKbNq0Kc6ePXvL6zFRFKVaf1N1Oy31QbW9L1euXMGIESPUW0oDAwOhKIrm8uPalr9Vt3pM0KP/vZt9pElpaSmGDBmCixcvYtOmTbCxsakxX1BQEPr27Ys+ffpYv0F0U87Ozpg5cybs7OzQtGlTREZGqpexb9q0CQAwffp02Nvbw83NDTNmzMCaNWvUS/uHDh0KPz8/AEB4eDiio6Oxc+dOzTri4+Ph4+MDW1tbi8//UBQFb775JlxcXODj44OZM2di1apVt7VtBw4cwHfffYcPPvgALi4ucHR0xLx585CcnGzxAdjR0dH48sv/z96dx0VV7n8A/8wwwyYMO7iEIOCSu7l0KzcCyiJzN28Jam6V7d1MbXG7amnd1Nv1qplbadeXu6al5gKR5VJGlpmGmtsvNBdAhAGG7++PmTnMYR3AA6af9+vFa2ae5znPec6ZOc95zpeZ53yBnTt3wmKxYP369fj666+RmZmplFm+fDlOnDiB9PR0zJw5ExMmTChxk4DSBAYG4ptvvsHJkyfx+++/o2/fvnjooYfw008/AbDOy+Pj46NaxtfXFwBU6y/NggUL8OijjyIhIQFGoxFubm7o2rVriXKFhYVISEhAWFiYMq+TvZ8wmUxKOXs7KlpveVxcXPDuu+/C1dUVjRo1wtixY5WfTlRWWZ/JTz75BCICV1dXmM1mHD58GGazGYGBgWjTpk2V2043t+DgYFWf4njudWZsNXfuXLRu3Rr+/v7w8/PDZ599pjq363S6So2DLBYLpk+fjmHDhqFVq1Yl8sPDw1WvQ0NDERcXhyVLlgCw/vTb/rNqAIiNjcXOnTtx5coVHD9+HP369UNgYCBSU1Px5ZdfIjY21ql91KpVK2XS3enTpyMgIACff/6509tVFm9vb2RkZKjSrl69qvQhFeWXp6JrK4PBgGnTpsHV1RVRUVEYM2aMcm21cuVK/Pnnn3j66acB3HpTLNxSwRf7QVHaXC1169ZFfHw8Fi9ejMWLF6N3797KLT/Dw8Nx4cIF1e8IK7POsuaG0YJer37L3NzcMGTIECxatAgff/wx2rVrh5YtW6rKnDp1SvX69OnTCA0N1bqpAKwD8or2T2UOqitXrmD16tXKAVkRZ+ou7z20z/dQvE77ySItLQ0ZGRl4+eWX4ebmBnd3d7zyyis4fvw4jh49Wu56PTw8MHXqVBw+fBg///wzzp49i7Fjxyr5p06dQteuXREfH6/6HWtZdDrdLddBaaVBgwYAoLor1cmTJ8ssHxcXBzc3N2zatAnLli3DoEGD4ObmBsB6Mdm0aVNcvnxZ+bty5Qqys7NVF9bFj90GDRqo1p+Tk1Op3yOXtk3F77JVfB4CZ/Xu3Rvbt2/HpUuXMGDAAPTq1Qu5ubkIDQ0tsY60tLQy+xNvb2/VvFUAbshdgypj3Lhx+OOPP3DgwAFcvXoVZ86cgVi/9enU8nq9vlLHVU2fE4qr6T4SAMxmM/r06YNLly5hx44dFU78nZ+fj/Pnz5f4bFDl3WwXLwBUQeXw8HCYzeYSc9M549SpU8jNzUVISIjS/qioKHh6elbYt3Xr1g3z589X5tVavny5Mjm+XVWDkXXq1EGnTp1gMBjg4eGBZ599Fl26dFEmoSzrgsWeV9E2VzXQaa/bMdBib4czF0tlCQ4OVs53gPU9dfwHXmVU9Jns1q0bpk+frszV2KNHD3z33XdVbjv9dVU0ttq7dy/GjRuHDz/8UMl75JFHSpzTio+9yuPi4oKkpCR89NFHePvtt0vkl1bXqFGjsGTJEvzwww/45ZdfMHjwYCWvS5cu+PPPP/Gf//wHXbp0gYuLC2JiYrB+/Xrs37/fqeBLaW7UeL9NmzaqOfAA4Pvvv1cCnm3atMGxY8eQk5Oj5H/33XdOBUSdubZy3AbHa6sdO3YgNTUVQUFBCAoKwvPPP48TJ04gODgYhw8frtxG3oRuqeBLUFAQ+vfvj2eeeUa5QEhLS0NaWhoAYOTIkVi8eDFWrFih+nZIhw4dcNddd2HEiBG4ePEiRASHDx92apLD0aNHY9OmTVixYgXy8vKQm5uLpKSkKrW/qgfSyJEjsXr1asyfP7/Et14AYPHixTh06BAKCgowc+ZM5OTkaPJfx+3bt2P//v3Iz89HQUEBNm7ciBUrVijrOn36NPbs2QOz2YzCwkIkJSVh9uzZGDRokNPrWLp0KYKCghAfH69Kr07d5b2HXbp0QatWrTBx4kRcv34dFy5cwLvvvot+/foBAJo1awZ/f3/MmTMH+fn5MJvNeO+99+Dj44OoqKhy1/vZZ5/h6NGjKCwshKenJ9zd3ZVB1NGjR9GlSxc8/vjjeOedd0os+/PPP+PAgQPKvt6wYQM++eQTPPbYY07tx9tdgwYN0L17d4wdOxZZWVlIT0/H1KlTyyyv1+uRmJiIuXPnYv369apJbB955BHk5eVhxowZSgD33LlzqkkQS5OQkIBZs2YpFxjjx4+v1sk0ISEBa9asQVJSEgoLC7Fq1Sp8++23la7n2LFj2LZtG3JycmAwGJRJn/V6PeLj42E2mzFjxgzk5+fj119/xcyZMzFixIhS62rbti0uXLiArVu3QkSwfv16JCcnq8poHTDMysqCp6cnfHx8cO3aNYwdO7ZSd+8ICgqCi4uL0wGVMWPG4L///S+2bdsGi8WCrKwsZSLtmlDTfWR2djZ69OiB/Px8bN26Vfn2jt3Fixfx8ccfKxeBx44dw2uvvYYuXbqgTp06N2irqTS1cfEClAxqu7m5qYIedt7e3rBYLKq7hjgGZ8PCwuDl5VWi/deuXcPf/va3CtuRmJiIH3/8EX/++SfWr1+PX3/9FdHR0eUuU9X+yPFiqE2bNsjIyFD94+u7775DeHh4hcGX6gQ6mzZtCnd3d9XF1HfffQdPT89q3ab1woULyM3NVV6fPHkSd9xxR6llKwq4O/PPihEjRuCrr75Ceno62rRpg759+1a57fTXVdHYKjMzEwaDAYGBgRARbNmypcS3QapyPDdp0gRfffUVFi1ahAkTJlRYPj4+Hrm5uRg+fDj69eun+tabu7s77r33Xrz77rvKTQ1iYmIwe/Zs1K1bt8LrBADYvXs30tLSICLIzs7GpEmTcOHCBTz44IMVLisiMJvNyM3NhYggNzcXZrNZ2S+JiYk4ePAgVq1ahfz8fKxYsQKHDh3CkCFDAABdu3ZFWFgYJkyYgNzcXBw6dAgLFy7EU089VeG6yxsL9e3bF0FBQZg4cSLy8/Nx8uRJzJ8/X7m2mj17No4ePYrU1FSkpqZiypQpCAsLQ2pqapmTB/+V3FLBF8AaaGjbti26deum3OkhPT0dAPDAAw9Ar9fDx8cH999/v7KMTqfD5s2b4eHhgbZt28LPzw/Dhw9XDvbiA3XH161bt8bWrVsxb948hISEICwszKn/nJQ2+Hfm67yladq0Kdq3b4/z58+XGEjrdDqMGjUKzz//PPz8/LB69Wps3bq13AFAVW8rmJmZiSeffFK5G8aUKVPwr3/9C0OHDgVgHaS//PLLCA4Ohr+/P5577jlMmjQJzzzzjNPr+PDDDzFy5MgSbaxO3eW9h/bPxqVLlxASEoL27dujY8eOyl0L6tSpg88++wxbt25F3bp1Ub9+fezatQtbtmxRfkpWlrS0NPTs2RM+Pj6IiIiAp6enEmiZOXMmzp8/j9mzZ8Pb21u5peWnn34KwHpBM2zYMPj7+yMkJATTp0/HkiVLSlxwUdlWrlypfJujW7duysmmLEOHDkVycjIiIiJUt73z8PDArl27cOTIETRr1gy+vr6Ii4tDamqqUqa0Y2r8+PGIi4tDp06dEBERgQYNGqBevXqq/zBWxLHerl27Ys6cOcrnYuvWrejTp0+l6gOAvLw8TJkyBfXr14efnx8++OADrFu3Dq6urjCZTNi+fTt27NiBkJAQPPTQQxg6dCheeumlUtsUERGBOXPmYOTIkQgICMD27dvRv3//MrfBme10hmP5KVOmID09HQEBAWjbti06d+5c5k9iSlve3d0dU6dOxaBBg+Dv748ZM2aUu+zDDz+Mjz76COPHj4e/vz+aNWuG7du3V6ntVVHTfeTatWuRnJyMlJQUBAYGKn2VvV6dToelS5cqd6R48MEH0bp16xtyq0oqX21cvIgIxo8fj6ysLFy4cAGTJ09WfuJdXJMmTeDl5YVFixZBRJCSkqK6HXSHDh3Qpk0bPPfcc7h8+TIA67lv1apVFbbDYrHg0KFDKCwsREZGBt58802cPXsWL774IoDqBSP37duHn3/+GRaLBWazGQsXLkRycrLyU9Tw8HDExsYqwf0TJ05g5syZTl2wVCfQ6e7ujieeeAJvvfUWLl68iAsXLuCtt97CkCFD4OrqCsAanK1sMM1iseC1115Dbm4uTpw4gffee08Z1xVXUcC9os/kgQMHkJKSgry8PBiNRuXnCfTXpdPplPNRZc5vFY2tHnzwQSQmJqJjx44ICgrCunXrSgTqqno+DQsLQ0pKCjZv3oxnn3223Lr0ej2GDx+OH374QfWTI7vY2FhkZWUpwZfu3bsjJydHdYfJ8qSmpiImJgYmkwmRkZHYv38/vvzyS+Ub3OVJTk6Gh4cHmjdvDp1Op3xz8KuvvgJgHaOtW7cOU6dOha+vL95++21s2LBB+faiXq/H5s2bcfjwYQQEBKBnz54YN24cBgwYUOG6yxsLeXl5Ydu2bUhJSYG/vz/uv/9+PPHEE3jllVcAWH8uWb9+feXPz88PLi4uqFevXoXjt78ErSeVudl0795d3n777dpuxg03dOhQGT16dG03g4iq6Nq1a2I0GuWbb765YXXec889qokRqXbZ7zxC5Kzo6GjVhLt6vd7pyU1FRM6ePSuDBw+WBg0aiI+Pj9x5553KBIuFhYUyZswY8fPzk4CAAHnyySclISFBmaS7spNN2yesXL58uYSFhYm/v3+Jux01atRIdYehtWvXSkREhJhMJhk4cKC8/PLLqgl3r1y5ImPGjJHw8HAxmUwSFRUlTz/9dIVtMZvN0qFDBzGZTOLj4yO9e/eWtLQ0Jf/IkSPSrl07Jb9Vq1bK5I4V+fTTTyUqKkq8vLwkMDBQunbtKjt37lSVuXjxovTt21e8vb0lKChIxo0b51TdItYJLe+9917x9fWV4OBgGTFihIiILFu2TPR6vdSpU0e8vLzEy8tLvL29VfsjOztbhg8fLr6+vuLn5ycjR45U3fRgypQpEh0d7XRb7J+xmTNnSt26dSU4OFhefvll1YTajp9JEZH//Oc/Ur9+ffHz85OnnnpKBg8e7PRncteuXXLXXXeJyWQSPz8/6dq1qxw4cMDp9hLVhqVLl6puPEBUHp3I7TNJRHJyMuLj43Hq1CkEBATUdnNumGPHjqF9+/bYv38/7rzzztpuDhE54cqVK9i/fz9iYmKQnZ2Nl156CV9//TWOHDlS5cj+2rVr0aNHDxiNRixduhTPPfccjhw5gsjIyBvceqqKWbNmYcWKFfjhhx9quylEdBuKjo7GrFmzVN/eJKKqy8rKQrdu3TBq1Cinvt1GdMv97KgsnTp1Qp8+ffDBBx/USOBlxowZytev7X/21zfy9/8DBgxAx44dMWHCBM0DL2fOnClzmyrz06Fbqe6KFF+v/Y8/D6LCwkK88cYbCAgIQGRkJM6fP49NmzZV6yuVa9euxR133IGgoCAsWLAAGzZsQGRkJFauXFnmMWD/KRs5JyUlpcx9WdoEfXb9+/fHggUL8N5771VpvbdqH0lENWf37t0MvNBt60aPyefMmYO6deuiUaNGpc656YyqjimAmrvWvNHtvt3dVt98ISIiIqKq8fb2LnXugy5dumDLli011o4zZ84o8xjYie1uGYMHD8a8efNuu7qJiOjmx+ALEREREREREZGGbtkpxKt7xwiivyLGUmse+xq63bCfqR3sa+h2w76m5rGfodtRTfY1t2zwBQC6dr0K98KiTfTQWae48TBYH92NRR1MHXfro5tr0fL25+62xzquReU9jNZHT4M1rY7DnjTZ6q/jMHWDp4utnO3RyyHPQ299w11RCAAwSr6SZyjIAQDo8nOUNMnPtj6arY+WnAwlr9CWZn+0mK8peRZbWr5D+Xxbfn6eLS+/qLw511ouz7Y++yMA5BXY0ixZSlqB3trGQkOutX1ueUqe3tP6XO9u3UYX96IPuYtt3xsc7szsYrs7rt5NXQYAXDzUeXqHO+nqSkvzsOfZpjhyLXqTxWjNLDCYrNujq6PkmcULAJBb6KWkZRX4AACyLdbGZhcUNfpagbWuK/nW23hnWIoanaHkFd0a8qLZWm9WnjUt11xUV6HZmma8Zq3LmFO0nMH23DW3aCNdzW74OskfVEu+FcB2/AIAbJ14qC3NxyHPW6zPPRzS3ETdB7g75Blt5Y32/gFSZp6LFC1nsJUzikVJc7GluZRS3l6H3pbm4rAee3mDLU/v0D4XW9tVacXqd8zTFyvv2AZ7mt62br041imq5R2Hh7YuVDWJmU50tjSd6rW1vC2ttDwlTa8qW1Z5e5pSZ6l12cvoSyync2I5Vbli66s4T1/q/ihr3UVtVddpzwt4MhRUe65evYpChzGixXaI2NMKHTItShpKSRPV8o51FC9T2nosDnlFaY51SanLOS5bXpuLl3Esp6pLWY+U2FZ7G5RtdRhc29OkWBnHcmKrrLCU5QpV268uJ455xeoodGigFEtzXI993Y4XBMp6CkvWpay72P5QlRf1o2O5UrexlLqUz0Yp+62gxHtecp8WqD6L6vfF8fNTIIK903qBaoevry88dUXvn5vt/Fv8EQA87OMXh8+CMqaxfUbdLUV59nJGW5qrw/HsalvO6NAW+5jHdrkFh+G9chFrL+9wWQfXUtKKyulK1GUvpzyWkueqL6W8Lc3ocF3n6qJOM7oUNcJ+53RXY8k0g+06U+9wvWlQrnls52Q3h3Oyu+25h0PD7PnFHwHAXt5Wv5S2QQ7rFjd1OTEWlVfS3KwbWeiYZ9vwQteinVLoatvbtusux4s+ncF67aUzWq+x9C5eDnnW5zqHNL3RT5Wmc/EuKm97rjfarolUeSZbmqmorQYT9DUccLxtJtwlIiIiIiIiIqoNDL4QEREREREREWmIwRciIiIiIiIiIg0x+EJEREREREREpCEGX4iIiIiIiIiINMTgCxERERERERGRhhh8ISIiIiIiIiLSEIMvREREREREREQaYvCFiIiIiIiIiEhDDL4QEREREREREWmIwRciIiIiIiIiIg0x+EJEREREREREpCEGX4iIiIiIiIiINMTgCxERERERERGRhhh8ISIiIiIiIiLSEIMvREREREREREQaYvCFiIiIiIiIiEhDDL4QEREREREREWmIwRciIiIiIiIiIg0x+EJEREREREREpCEGX4iIiIiIiIiINMTgCxERERERERGRhhh8ISIiIiIiIiLSEIMvREREREREREQaYvCFiIiIiIiIiEhDDL4QEREREREREWmIwRciIiIiIiIiIg0x+EJEREREREREpCEGX4iIiIiIiIiINMTgCxERERERERGRhhh8ISIiIiIiIiLSEIMvREREREREREQaYvCFiIiIiIiIiEhDDL4QEREREREREWmIwRciIiIiIiIiIg0x+EJEREREREREpCEGX4iIiIiIiIiINMTgCxERERERERGRhhh8ISIiIiIiIiLSEIMvREREREREREQaYvCFiIiIiIiIiEhDDL4QEREREREREWmIwRciIiIiIiIiIg0x+EJEREREREREpCEGX4iIiIiIiIiINMTgCxERERERERGRhhh8ISIiIiIiIiLSEIMvREREREREREQaYvCFiIiIiIiIiEhDDL4QEREREREREWmIwRciIiIiIiIiIg0x+EJEREREREREpCEGX4iIiIiIiIiINMTgCxERERERERGRhhh8ISIiIiIiIiLSEIMvREREREREREQaYvCFiIiIiIiIiEhDDL4QEREREREREWmIwRciIiIiIiIiIg0x+EJEREREREREpCGdiEhtN0ILOp2utptAVONu0cP5psa+hm437GdqB/saut2wr6l57GfodlSTfc0tG3whIiIiIiIiIroZ8GdHREREREREREQaYvCFiIiIiIiIiEhDDL4QEREREREREWmIwRciIiIiIiIiIg0x+EJEREREREREpCEGX4iIiIiIiIiINMTgCxERERERERGRhhh8ISIiIiIiIiLSEIMvREREREREREQaYvCFiIiIiIiIiEhDDL4QEREREREREWmIwRciIiIiIiIiIg0x+EJEREREREREpCEGX4iIiIiIiIiINMTgCxERERERERGRhhh8ISIiIiIiIiLSEIMvREREREREREQaYvCFiIiIiIiIiEhDDL5oKDo6GtOnT1dee3t7Y9++fbXYoqrR6/XYu3dvbTeDSFPnzp2DXq/H6dOnMWPGDPTq1atW25OSkgJ/f/8aWdeN3F6t+4ua3C832l+57URERJXleC10M18HJSUlwWg01nYz6DbA4EsNysrKwt13313bzbippaSkoH379qFmbDIAACAASURBVAgICICfnx86dOiA9evXq8qkpaUhLi4OXl5eaNiwIf71r385Xf/8+fPRtGlTmEwmtG/fHklJSap8vV4PLy8vmEwmeHt7w2QyISsrq1rbtHLlSqUue70GgwG9e/dWyuzbtw/dunWDn58f6tWrh8TERFy+fLla66XK0+l0AIDx48dj48aNtdqWzp0719hn4GbYXmfV5H4BgN9//x16vR7nz5+vdl1att2ZfiY8PBweHh6q/u3nn3+u1nqPHz+OAQMG4I477oCPjw9atWqFjz76qNSy169fR2RkJFxdXau1TtIGL5KISEs3+3WQfQx4M0lKSoJer1fO297e3ujcubNTy+7atQuxsbEIDAwscxzzxRdfoGXLlvD09ETr1q2xY8cOVX51rrnKc/36dTz//POoX78+vL290aJFC6SmpgIAzpw5oxrPmEwmuLm5wdfX94asu7Yx+EI3lWbNmmHDhg24dOkSrly5gvfffx+DBw/Gr7/+CgAoLCxEz5490aJFC1y6dAkbN27EO++8g9WrV1dY9+rVqzFx4kSsWbMGGRkZGDVqFOLj43H27FlVuR07diAzMxNZWVnIzMyEt7d3tbbp8ccfV+rKzMzEuXPn4O7ujoSEBNU2de7cGZcuXcIvv/yC8+fP44UXXqjWeunmJCKwWCy13QxykojclAOy4irqZwDrwHLx4sWq/q1FixbVWu+VK1dw//334+DBg8jIyMD8+fPxj3/8Axs2bChRdty4cYiMjKzW+qhm8CKpaqoT4Fy3bh3atGkDb29v3HnnnVizZs0Nq7s8W7duRYcOHeDr64s77rgDzz//PPLy8lRl/ve//6FNmzbw8vJC/fr1MWPGjGqvl6gmWSwWiMgNqy8/P/+G1VURg8GgnLezsrKQkpLi1HJ16tTBkCFD8PHHH5faZ548eRL9+vXD66+/jszMTIwbNw59+vTB6dOnAVTvmqsivXr1wunTp3Hw4EFkZWVhy5YtqF+/PgAgNDRUNZ7JzMxEx44dVeOZvzIGX2yys7Pxj3/8A5GRkfDx8UHLli3xz3/+E8HBwSgoKFDKXbt2Dd7e3vj6668BAH/++SdGjBiBsLAw+Pr6okOHDjh+/Hip6yj+dfykpCR07doVAQEBCA4OxpNPPllhO6Ojo/HKK6+gb9++MJlMaNy4MXbt2oWdO3eiVatW8PX1Rd++fZGdnQ3AOth1/M8nYI2E+vj4ICcnBwCwZcsWtGjRAiaTCY8++ihefvllREdHq5Y5cOAA2rVrB5PJhJiYGKSlpVWqTf369VPaVJ7AwECEhoYCKLroERH89ttvyj47ffo0pk+fDjc3N7Rr1w6jR4/G/PnzK6x7zZo1GDx4MFq1agWdTofRo0cjODgYS5cuVZWraue8bt06dOzYEX5+fqhfvz7efPPNUsstX74cJpNJeV8yMjJw6dIlDB06FHq9Hr6+vhg4cKASASZtpKen49FHH4Wvry+aNWuGL774QsmbPHky4uLiAADz5s1Du3btVMuePHkSBoNBOUGdOXMGAwYMQL169dCgQQOMHj0a165dU8rr9XrMnTsXHTt2hJeXF7777jsUFBTgpZdeQkhICOrXr49Zs2ahcePGWL58OYCS/90dNmwYEhMTMWrUKPj5+SE0NBQLFy5Uteujjz5CVFQUfH19kZiYiISEBKf6FcftBYC5c+ciIiICPj4+CA0NxRtvvKHk/fjjj4iJiYG/vz+ioqIwbdo0FBYWllrvsmXL0LhxY1XasGHDMGrUKABF3ypZvnw5WrRoAS8vLzzyyCO4evUqxo8fr+ybefPmKctXdr+cO3cODz30EIKDg+Hn54euXbvi+++/V217bGwsXn/9dYSEhKBu3bqYNGmSkt+2bVsAQJMmTWAymTBt2rQK92dZfcGePXtKbfvw4cOVtv/vf/9DamoqOnXqBB8fH8TExOCPP/6ocJ3FFe9n7Krav5V1vurUqROefvpp1K1bFwBw3333oUePHtizZ49q+eTkZKSkpOC1116r0vrp9nGjL5JqUlUDnN9++y0SEhIwd+5cZGVlYdasWXjiiSdw4MCBatddnosXL6Jfv34YOXIkrl69iv3792PPnj2YOnWqUubjjz/GK6+8gjlz5iAzMxPHjx/Ho48+Wq310u3J8TrIPj7497//jdDQUAQEBOCpp55SHfsVja1ef/11REZGwtvbG40bN8acOXOUPPv4YvHixcr44uLFi0639eDBg2jYsKHyTc7o6Gi89NJL6NOnD3x9fTFr1izccccdJb41nJiYiJEjR+Ly5cswGAzK+XvXrl3Q6/XKNYfFYoGvry8OHjxYuZ1YCXfffTcSEhLQvHnzUvOXLVuGDh064O9//zsMBgMef/xx3HXXXVi2bBmA6l1zAWWPhbZt24ZvvvkGS5cuVQIu4eHhCAoKKrWen376CXv37sVTTz1V2V1wcxISEZGBAwdK165d5ffffxcRkbS0NDl27Jg0atRI1qxZo5RbsGCBNG/eXERECgsL5W9/+5v0799fLl68KCIihw8flv/7v/8TEZHu3bvLtGnTlGV1Op18/fXXIiKSmpoq7u7usnz5csnLy5Pc3FxJSkqqsJ3du3eX4OBgOXDggBQWFsqECROkfv368thjj8nVq1flypUr0rx5c5k+fbqyHW5ubvLHH38odTz++OPyzDPPiIjIb7/9Jm5ubrJq1SqxWCyyc+dOMZlMEh0drWp3ixYt5MSJE5KbmyvPPvusNG/eXAoLC6vUJmf4+vqKq6ur6HQ66d69u+Tl5YmIyOzZs6Vdu3aqsuvXr5eAgIAK6xwwYIC89NJLqrTw8HDp16+falvr168vgYGB8re//U3WrVvnVHu3bt0q3t7esnXrVrFYLJKVlaW818W1atVK3njjDVXa008/LWPHjhWz2Szp6ekSHR0tEydOdGrdVDX333+/9O3bV7KysiQ9PV06d+4ser1efv/9d5k0aZLExcWJiMiVK1fEw8NDUlNTlWXfeustiY2NFRGR3NxciYqKkkmTJonZbJarV69KfHy8PPnkk0p5nU4nbdq0kZMnT0phYaGYzWaZPHmy3HnnnXLq1CnJzc2V559/XlxdXWXZsmUiIrJnzx4xGo1KHUOHDhVPT0/57LPPRERk3bp1YjQa5fTp0yIikpSUJB4eHrJnzx6xWCzy6aefiqurqwwbNqzCfeG4vceOHRNPT0/55ZdfREQkIyND9u3bpzwPCQmRadOmSV5envzyyy8SEREh7777rmpb7Z/9pUuXSuPGjVXrGjp0qIwcOVJERE6dOiU6nU569eolV69elcuXL0vz5s2lSZMmsmjRIrFYLPL555+L0WiUM2fOVGm/nD59WjZv3iy5ubmSm5srL774ooSFhUlBQYGy7a6urrJw4UKxWCzy7bffitFolL179ypt1Ov1cv78+Qr3o0j5fUFZbf/8889FRGT+/Pni5eUlvXr1kvPnz0tOTo7cf//9MmrUKKfW7ai0fiY8PFxCQkIkICBA2rVrJwsWLHCqrsqcr7KzsyU8PFyWLFmipF2/fl2aNm0q33//fYl9QDcPxzFL8eM4KipK5s6dK3fccYf4+/vL6NGjlTGAiPU469+/v9StW1fq168vo0aNkqysLCV/woQJEhERIV5eXhIVFSWzZ89W8uz9wEcffSTNmzcXd3d3SU9PL7Od9s/QsmXLJCwsTAICAmTo0KFy7do1pYxOp5MPPvhAOnToIHXq1JH77rtPzp49K++//76EhoZKYGCgvP7660r5Rx99VGbMmKG8Dg0NlW7duimvn3nmGRkzZkyF+zA8PFxWrFhRYbnixo4dK3379lWlRUdHy/Dhw6tdt4h1n3Xp0kX8/f0lKChIOS98//33otfrlTGWiMj48eOlZ8+eImId5zZo0EAWLlxYpfUSldevGI1GeeONNyQvL09+++038ff3l5UrV4qIc2OrFStWKNc3u3fvFg8PD9m+fbuIFPUrsbGxcuHCBcnPz1f1WcU5nps2btwo9erVU+qyb4ePj4/s2bNHRERycnJk4sSJEh8fr5TJyMgQT09P2b9/v4iItG/fXj7++GMRsR5XTZo0kSeeeEJERFJSUsTf37/C/bdnzx7R6/XSsGFDqVu3rjzyyCOq8agz7OOYc+fOqdJ79+5d4rrohRdeUK6LqnPNVd5YaNy4cdKyZUt57rnnJDg4WKKiomTChAnKuKy4MWPGyH333ef09t7sGHwRkQsXLohOp1MuNhz985//lB49eiiv7777bnn//fdFRGTfvn3i6uqqGmA4Ki/48swzz8jAgQMr3dbu3bvLs88+q7w+cuSI6PV6+e6775S04ifxuLg4eeedd0RE5PLly+Lh4SGHDh1Sts9xgCEikpCQUCL4Unwg7ebmJt98802V2+SMvLw82bhxo8ycOVPpMKdOnSrdu3dXldu9e7dTg/lly5ZJUFCQHDx4UPLz8+Xf//636PV65aJTRGTXrl1iNpvFbDbLqlWrxMPDQ7Zt21Zh3Q8//LCMHTu2wnIpKSliMBjk1KlTqvSdO3dKVFSUGI1G0ev1EhsbKzk5ORXWR1Vz7tw50el0cvLkSSVtx44dpQZfREQee+wxefHFF5XX4eHh8umnn4qIyOrVqyUqKkpV/8GDB8XNzU353Op0Ovnkk09UZaKiomTp0qXK65ycHHFzcys3+PLII4+o6ggKCpJNmzaJiMiIESNkyJAhqvwuXbpUOvhy4sQJ8fT0lNWrV6suZkREVq5cKQ0bNlSlLViwQJo1a6a8rkrwpXhf0bJlS9UywcHBynZWdr8Ul5mZqervJ02aVGJ9HTt2lLlz5yptLG3QUpby+oKK2n79+nXR6XSydu1aJW3evHly1113ObVuu7L6meTkZMnOzpaCggLZsWOHBAQEOHVR5ez5ymKxSN++faVbt26qQdQLL7yg7BMGX25ef6WLJJ1OJwMGDJCsrCy5cOGC3HvvvaogpU6nk3vuuUcVxGzSpIlMnDhR8vPzJTU1Vdzc3JQg69y5cyUmJkZERH799Vdp0KCB+Pn5SXZ2toiING7cWDZs2FDhPqxqgPPVV1+VPn36qNK6desm7du3r3bd5QVPCwsLJT4+XubOnSsFBQVy6tQpadGihSxevFhERI4ePSo6nU4mTZokzZo1k5CQEOnZs6f89ttvTq2bqLx+xcfHR3WsDxgwQF5++WURcW5sVVz//v3ltddeE5GifiUlJcWpdtrPTXPnzpWwsDD58ccfS2yHYzBUxBp0dnNzU/45M2/ePGndurWSP3bsWGVc1rFjR1m1apXUrVtXREQmT56s+udvWdLT0+XHH38Ui8UiGRkZMn78eAkICFD+0e+MssYxMTExMmnSJFXaxIkTlfFgda65yhsLjRgxQnQ6nfJP5+PHj0vjxo1L/Sf99evXxdfXVwli3Qr4syMAp06dgk6nK/H1eAAYPnw49uzZg7Nnz+Lw4cNITU1FYmIiAOtX2oKDg+Hl5VWldTZp0qRK7a1Xr57y3NPTEwCUr3zb0xwniR01ahQWL14MAPjkk0/QvHlz5av0586dQ1hYmKr+4q+Lp3l4eCAoKEg1V0pl2+QMo9GIRx99FHv27MGiRYsAWCcBzMjIUJW7evUqTCZThfUlJibi1VdfxRNPPIF69eohNTVVmYjKLjo6Gq6urnB1dcXAgQORkJCAFStWVFi3s+/nwoUL8cADD6j252+//YaHHnoIb775JnJycnD16lVERETgwQcfrLA+qpqzZ89Cp9OhYcOGSlqjRo3KLD9s2DCsXLkSFosFO3fuREZGBvr06QPA+t7//vvv8Pf3V/5iY2Ph4uKi+rlI8ePq3LlzqvW7u7uX+ZVLO8fjDLD+ntd+XDl7LFekUaNGWLFiBRYuXIj69euja9euygRsZ86cKVFnZGQkzpw5U+n12Ol0uhJ9RfHtrKj/KG+/XLp0CUOGDFF+GtqwYUPodDrV14/LW76yKtu3O67bw8MDQPX7ztL6GQDo0qULPD094eLigtjYWLzyyiv45JNPKqzPmW0qKCjAoEGDkJ6ejs2bN8PFxQWAdRL1zz//HJMnTwZQ9Z89Ue3y9PTElClTYDQaERkZiZiYGOXr8ps3bwYATJw4Ea6urvDx8cHkyZOxYsUK5f1+/PHHERISAgDo3r074uPjsXPnTtU6Jk2ahKCgIBgMhgrndNHpdJg5cya8vLwQFBSEKVOm4OOPP1aV+cc//oF69erB3d0d/fv3R3p6OiZNmgSDwYDWrVujTZs2yjbExsZi7969MJvN+PLLL9GjRw/cfffdSEpKwpkzZ3Dy5MkSP8cuzfLly3HixAmkp6dj5syZmDBhAj788MMKl4uPj8cXX3yBnTt3wmKxYP369fj666+RmZlZ7boXLFiARx99FAkJCTAajXBzc0PXrl2V/ThkyBBMmzYNHh4eiIiIwF133YWhQ4cCsP60HrD+fGDbtm04deoUQkND0bNnzzJ/bkrkrODgYNWx7njudWZsNXfuXLRu3Rr+/v7w8/PDZ599pjq363S6So2DLBYLpk+fjmHDhqFVq1Yl8sPDw1WvQ0NDERcXhyVLlgCw/vTb/rNqwNqv7Ny5E1euXMHx48fRr18/BAYGIjU1FV9++SViY2Od2ketWrVSJt2dPn06AgIC8Pnnnzu9XWWp6JqqOtdc5Y0b7DcEmDZtGlxdXREVFYUxY8aUeuOHTz/9FC4uLhg4cKCzm3XTY/AFRQdTaXO11K1bF/Hx8Vi8eDEWL16M3r17K7cKDQ8Px4ULF1S/P6zMOsuaG+ZG6927NzIzM5GcnIzFixdj5MiRSl6DBg3w+++/q8rb57FwdOrUKeX59evXcfHiRWVuFq0VFBQo+6pNmzY4duyYMl8NAHz33Xdo06aNU3W9+uqrOHr0KC5evIh58+bh559/LndAZZ9zpiLOvJ9XrlzB6tWr8fTTT6vSU1NTERAQgMTERLi4uMDb2xvPPfccUlJSVAMvunEaNGgAAKrP/smTJ8ssHxcXBzc3N2zatAnLli3DoEGD4ObmBsAa4GjatCkuX76s/F25cgXZ2dmqC2u9Xt3dFj/2cnJyKvV75NK2yZlj2Rm9e/fG9u3bcenSJQwYMAC9evVCbm4uQkNDS6wjLS2tzL7A29u7xFxPN+KuQZUxbtw4/PHHHzhw4ACuXr2KM2fOQKzf+nRqeb1eX6mAQU327aUpq58py43o38xmM/r06YNLly5hx44dqknKd+7cibNnzyI0NBRBQUHo3bs3CgoKEBwcjC1btjjVRqp9N9tFEgBV8Do8PBxms1kJFgAlg5jBwcGq5R0Dm3feeScCAgKQnJyML7/8EnFxcYiNjcX27duxY8cOtG/f3qkLjqoGOLt164b58+cr84AtX74cgwYNUv1zSIvg6e7duzFkyBAsW7YMZrMZf/zxBzIyMjBkyBAAUI7lF198EQ0bNoS7uzumT5+Oo0eP4tixYxWum6iqKhpb7d27F+PGjcOHH36o5D3yyCMlzmnFx17lcXFxQVJSEj766CO8/fbbJfJLq2vUqFFYsmQJfvjhB/zyyy8YPHiwktelSxf8+eef+M9//oMuXbrAxcUFMTExWL9+Pfbv3+9U8KU0zl6bVKRNmzaqOfAA4Pvvv1euqapzzVXeuMH+BYDi21Ba0H3BggUYOnToLXWXRAZfAAQFBaF///545plnlAuLtLQ0ZVLZkSNHYvHixVixYoUqcNGhQwfcddddGDFiBC5evAgRweHDh52aHHH06NHYtGkTVqxYgby8POTm5pa47bGzKjoADQYDhg4dipdeegm//fYbHn/8cSVv0KBB2LdvH9asWYPCwkLs3r271LtUvP/++zhx4gRyc3OVO1Z06tSpym0qy7p16/DTTz/BYrHAbDbjww8/xO7du9GjRw8AQNeuXREWFoYJEyYgNzcXhw4dwsKFC52ahCkzMxNHjx4FYJ1k7qmnnlImJgWAn3/+GQcOHEB+fj4KCgqwYcMGfPLJJ3jssccqrHvMmDH473//i23btsFisSArK0uZlNlu6dKlCAoKQnx8vCq9ffv2uHr1KlauXInCwkJkZWXh3//+NyIiIpwa7FHlNWjQAN27d8fYsWORlZWF9PR01QSDxen1eiQmJmLu3LlYv369ahLbRx55BHl5eZgxY4YSiD137lypx5GjhIQEzJo1C6dOnUJubi7Gjx9frZNpQkIC1qxZg6SkJBQWFmLVqlX49ttvK13PsWPHsG3bNuTk5MBgMMBkMkGv10Ov1yM+Ph5msxkzZsxAfn4+fv31V8ycORMjRowota62bdviwoUL2Lp1K0QE69evR3JysqqM1t+EyMrKgqenJ3x8fHDt2jWMHTu2UndKCQoKgouLi9MBFWf6Ai2V1c+cPn0ae/bsgdlsRmFhIZKSkjB79mwMGjSowjrLO19lZ2ejR48eyM/Px9atW5Vv79i98sorOH78OFJTU5GamopFixbBYDAo3zykv77auEgCSgbP3dzcVMGKyoqJicG2bduQnJyMmJgYxMTEYMeOHU7/h7oszvZxiYmJ+PHHH/Hnn39i/fr1+PXXXyv8tk11g6fff/892rZtiwcffBA6nQ5BQUEYOXIkPvvsMwBA06ZNSxzT9nXerHecoltDRWOrzMxMGAwGBAYGQkSwZcuWEt8Gqcr4okmTJvjqq6+waNEiTJgwocLy8fHxyM3NxfDhw9GvXz/4+Pgoee7u7rj33nvx7rvvKjc1iImJwezZs1G3bl1ERUVVWP/u3buRlpYGEUF2djYmTZqECxcuOPXteBGB2WxGbm4uRAS5ubkwm83KfklMTMTBgwexatUq5OfnY8WKFTh06JASfK3ONVd5Y6G+ffsiKCgIEydORH5+Pk6ePIn//ve/6Nevn6qOQ4cO4eDBg7fORLs2DL7YLF68GG3btkW3bt2UO0Skp6cDAB544AHo9Xr4+Pjg/vvvV5bR6XTYvHkzPDw80LZtW/j5+WH48OFKJ1H8xOT4unXr1ti6dSvmzZuHkJAQhIWFOfUfjNJOds6cAEeMGIEffvgBjz32mOq/kpGRkVi9ejXeeust+Pr64v3330diYqLyX317/SNGjEDfvn0REhKCw4cPY+PGjcp6q9qm0vzf//0f+vbtCz8/PzRo0ABLly7F//73P2W/6/V6bN68GYcPH0ZAQAB69uyJcePGYcCAARXWnZmZiQEDBsBkMuHOO+9EQUEBdu/erWzrxYsXMWzYMPj7+yMkJATTp0/HkiVLSlzElObhhx/GRx99hPHjx8Pf3x/NmjXD9u3bVWU+/PBDjBw5ssS+CQ8Px9q1azF79mwEBgYiIiICZ86cKfXrd3TjrFy5Uvk2R7du3ZSTTVmGDh2K5ORkREREoEOHDkq6h4cHdu3ahSNHjqBZs2bw9fVFXFyc6m5VpR0P48ePR1xcHDp16oSIiAg0aNAA9erVUx17FXGst2vXrpgzZ47yGd66dSv69OlTqfoAIC8vD1OmTEH9+vXh5+eHDz74AOvWrYOrqytMJpPyn+CQkBA89NBDSmC3tDZFRERgzpw5GDlyJAICArB9+3b079+/zG1wZjud4Vh+ypQpSE9PR0BAANq2bYvOnTsrP4lxZnl3d3dMnToVgwYNgr+/f4W3WHWmL3B23VVRVj+TnZ2Nl19+GcHBwfD398dzzz2HSZMm4ZlnnqmwzvLOV2vXrlXuZBQYGKjcAtder/3WtPY/+0/rKvtZp5tXbVwkiQjGjx+PrKwsXLhwAZMnT1b+kVJVMTExWLRoEcLCwhAYGKgEjz///HOngi/VCXBaLBYcOnQIhYWFyMjIwJtvvomzZ8/ixRdfrHbd5QVP77nnHvz444/KT0v//PNPfPjhh8o5zs3NDcOGDcOcOXNw9uxZmM1mvPnmm2jZsmWVfzpPtxedTlfu9UJZKhpbPfjgg0hMTETHjh0RFBSEdevWoW/fviXWXRVhYWFISUnB5s2b8eyzz5Zbl16vx/Dhw/HDDz+ofnJkFxsbi6ysLCX40r17d+Tk5KjuMFme1NRUxMTEwGQyITIyEvv378eXX36pfIO7PMnJyfDw8EDz5s2h0+kQFRUFT09PfPXVVwCsY7R169Zh6tSp8PX1xdtvv40NGzYo3yqszjVXeWMhLy8vbNu2DSkpKfD398f999+PJ554Aq+88oqqjoULFyI6OtqpINVfSo3MLHML6N69u7z99tu13Ywqy87Oljp16si3335bYdm///3vMnr06BpoFRHZXbt2TYxGozKR9Y1wzz33qO7gQbVr586dUqdOndpuBlGpoqOjlQkP9Xq90xNni4icPXtWBg8eLA0aNBAfHx+58847lYkcCwsLZcyYMeLn5ycBAQHy5JNPSkJCgjIZeGUntbZPjLl8+XIJCwsTf3//Enc7cmx/WdsQHR2tuinC+fPnRa/Xy7hx45S0gQMHipeXl+puQGU5cuSItGvXTkwmk/j4+EirVq1k3rx5Tm2T2WyWDh06KMv27t1b0tLSbkjdItZJMu+9917x9fWV4OBgGTFihJK3fPlyadmypfj4+EhISIgMHDhQzp49q2rbmDFjlDsl9erVq8Rk3kS3s6VLl6puPEBUHp0IZ7+rSHJyMuLj43Hq1CkEBATUdnMqTUQwffp0bNq0Cfv27SuRv3nzZnTu3BkmkwmfffYZHnvsMWzfvl2ZkI2IbrwrV65g//79iImJQXZ2Nl566SV8/fXXOHLkSIXfzCjL2rVr0aNHDxiNRixduhTPPfccjhw5gsjIyBvceqqKWbNmYcWKFfjhhx9quylERERUTVlZWejWrRtGjRp1y/08hrTBnx1VoFOnTujTpw8++OCDGgm8zJgxQ/natv3P/roq8wZcvHgRJpMJS5Yswfz580stk5ycjCZNmsDPzw+vv/46FixYoFngJSUlpcztK21yq9uhbro9FRYW4o033kBAQAAiIyNx/vx5bNq0qcqBXohd/gAAIABJREFUF8AafLnjjjsQFBSEBQsWYMOGDYiMjMTKlSvL/Px++umnN3Crbn1V7Qv69++PBQsW4L333qvSes+cOVPmep356VBt1U1ERHQzKH6es/85M71AaebMmYO6deuiUaNGqjlBK6M61xc3+pqxptp9u+M3X4iIiIjopuHt7V3qHAtdunSp1btktWzZssRd5EQE4eHhOHz4cJnLnTlzRpl3wXE5nU6HwYMHY968eVVuk5Z1ExHRjcXgCxERERERERGRhgy13QCt8BZ4dDtiLLXmsa+h2w37mdrBvoZuN+xrah77Gbod1WRfc8sGXwDgyoAMGNzyldcuHnkAAL3tUeeRq+Tpva9bn7jnFFVgz3e3PdbJLspzy1HnuTkuZ7vVtKtDmpu1fnG1PbpnKFmFRmt5i8H6mK8vWk+uLsv6KEVtzS20blOOxQIAyC6wKHk5BWLLUz86Ps/KL5l23bbcdYfymbZy2ba07IKiDjnbYv3oZOW5K2l5BR7W7SjwBADo8+soea65vgAAgy3NkFeUZy+nzzUpaWLLl3xrXZY8z6L15HoBAPJtaQV5HkpegdnaHou5qF2WbGu5wlzrbU0lx+E22jmu1vZdt6a55xUdEnUKrHNv1EHRHBwmg3WaJA+DdV94GIv2iT2tjqv10d3gkOdiK+8wnYe3Lc3TNvOSh8P5zlNv3efeSl7R++LhYn3uZihU0lyNFgSsK7qFONWw/YUAit4PiP25FHsNBNjKBTiU97Z1+p62NE+H8m62NDdbmhFFn4WiNPUjABhsdbo6pLnYyhtsaQaHk40BFlWai+NytnUaxKJ67VinXrUedR0uDtujV9JKrkdvK2evXy8l26CzLec4YZntcIEeuhJpOrHd4lKVp1eVt5dxfF5anl6pS1+yfKnrUafZ16tqV3nLOa67WHtKrau8NpdbZznb47hvoIPf8Ipvb0ka0scDOtei18pz26PO8fbd1vOgDkXldXAr9uheIg/2R1Vd1vOs2NMc2qCzpRl0RXUZ9K62NOujUV9U3lXvZksz2l4blTw3nfV5HVuau67opOlhe+6hK/q8etiORS9bWtFoAPCwfb7taXUcjjH7lrkXe3Rczl0pW9Tf2U7v8HDogIy2Jrrahg9Gh5G1q22zDbY0g2tRGwy2zTbYGuPi8Lbad5feVUqk6Wwb5PgxUDbIVl7nuEHFPiIwOuS5lZJmb6M9zXE9xmKPDuMcpS5DsTKOaaXVVUZ5fTCnpawtvr6+8HQYd7rbjgH7seDmMHbwsD13K3Q4TmzP3WzXD+4FDuNV2yWLURmjOCxne+74UbCPeewfE8fjseRHyGF8VKyMupy6jGNa8UdruypXvvi6VdtjO2RcHY4Fg+14NXioXwOAzn65ZO/IHI9t+/M6paQp3bnDMWrvuOzHuEN/VGqaW7HyDtc8ynN7mdLyHNPsG2y0XsPB4HDNYn/u6ld2nmOa0b9YnsmhvO250TZPq8GnZJ5Dmhh9oa/hgCN7NiIiIiIiIiIiDTH4QkRERERERESkIQZfiIiIiIiIiIg0xOALEREREREREZGGGHwhIiIiIiIiItIQgy9ERERERERERBpi8IWIiIiIiIiISEMMvhARERERERERaYjBFyIiIiIiIiIiDTH4QkRERERERESkIQZfiIiIiIiIiIg0xOALEREREREREZGGGHwhIiIiIiIiItIQgy9ERERERERERBpi8IWIiIiIiIiISEMMvhARERERERERaYjBFyIiIiIiIiIiDTH4QkRERERERESkIQZfiIiIiIiIiIg0xOALEREREREREZGGGHwhIiIiIiIiItIQgy9ERERERERERBpi8IWIiIiIiIiISEMMvhARERERERERaYjBFyIiIiIiIiIiDTH4QkRERERERESkIQZfiIiIiIiIiIg0xOALEREREREREZGGGHwhIiIiIiIiItIQgy9ERERERERERBpi8IWIiIiIiIiISEMMvhARERERERERaYjBFyIiIiIiIiIiDTH4QkRERERERESkIQZfiIiIiIiIiIg0xOALEREREREREZGGGHwhIiIiIiIiItIQgy9ERERERERERBpi8IWIiIiIiIiISEMMvhARERERERERaYjBFyIiIiIiIiIiDTH4QkRERERERESkIQZfiIiIiIiIiIg0xOALEREREREREZGGGHwhIiIiIiIiItIQgy9ERERERERERBpi8IWIiIiIiIiISEMMvhARERERERERaYjBFyIiIiIiIiIiDTH4QkRERERERESkIQZfiIiIiIiIiIg0xOALEREREREREZGGGHwhIiIiIiIiItIQgy9ERERERERERBpi8IWIiIiIiIiISEMMvhARERERERERaYjBFyIiIiIiIiIiDTH4QkRERERERESkIQZfiIiIiIiIiIg0xOALEREREREREZGGGHwhIiIiIiIiItKQTkSkthuhBZ1OV9tNIKpxt+jhfFNjX0O3G/YztYN9Dd1u2NfUPPYzdDuqyb7mlg2+EBERERERERHdDPizIyIiIiIiIiIiDTH4QkRERERERESkIQZfiIiIiIiIiIg0xOALEREREREREZGGGHwhIiIiIiIiItIQgy9ERERERERERBpi8IWIiIiIiIiISEMMvhARERERERERaYjBFyIiIiIiIiIiDTH4QkRERERERESkIQZfiIiIiIiIiIg0xOALEREREREREZGGGHwhIiIiIiIiItIQgy9ERERERERERBpi8IWIiIiIiIiISEMMvhARERERERERaYjBFyIiIiIiIiIiDTH4QkRERERERESkoVoLvkRHR2P69OnKa29vb+zbt6+2mlNler0ee/fure1m0C1u8uTJiIuLq7H1NWrUCCtXrtSs/qSkJBiNRs3qr45z585Br9fj9OnTmDFjBnr16lWr7UlJSYG/v3+NrOtGbq/WfWNN7pcb7a/cdiIiunndKtdXf3XF34fili1bhsaNG9dgi6g8v//+O/R6Pc6fP19q/rBhwzBq1Kgbsq6b5psvWVlZuPvuu2u7GTe1lJQUtG/fHgEBAfDz80OHDh2wfv16VZm0tDTExcXBy8sLDRs2xL/+9S+n658/fz6aNm0Kk8mE9u3bIykpSZWv1+vh5eUFk8kEb29vmEwmZGVlVWubVq5cqdRlr9dgMKB3795KmX379qFbt27w8/NDvXr1kJiYiMuXL1drvR9//DHuu+8++Pv7Izg4GPHx8fjpp5+UfPtBaG+bt7c3GjZsWK11VpdOp6vV9d9oN/P22Ns2fvx4bNy4sVbb0rlz52p/3p11M2yvs2pyvwAVn5gr40a1/cyZM6r+02Qywc3NDb6+vkqZwsJCvPrqqwgODoaPjw8GDBiAS5cuVWu9eXl5eOqpp9CkSROYTCaEh4dj7NixMJvNSpnJkyfDaDSqzhfjx4+v1nrpr3VhdTMH2alivDi8NdzM11c38rz6V1RT4+AbMQ74448/4O/vjyZNmpSaLyK49957b9j72b17d7i7u6vGEFu3blXyH374YdX4p06dOtDr9diwYUOV11lT78dNE3yhijVr1gwbNmzApUuXcOXKFbz//vsYPHgwfv31VwDWg6tnz55o0aIFLl26hI0bN+Kdd97B6tWrK6x79erVmDhxItasWYOMjAyMGjUK8fHxOHv2rKrcjh07kJmZiaysLGRmZsLb27ta2/T4448rdWVmZuLcuXNwd3dHQkKCaps6d+6MS5cu4ZdffsH58+fxwgsvVGu9165dw5QpU3Du3DmcO3cO7dq1wwMPPIDc3FyljE6nw7Fjx5TtPX36dLXWWZvy8/NruwlUjIjAYrHUdjPISSJy0wUMQ0NDVf1nZmYmOnbsqPSfgPXbTJs3b8aBAwdw9uxZiIgqvyoKCgoQFBSELVu2ICMjA1999RV27dqF1157TVUuOjpadb6YMWNGtdZLJd3MF1bAzRtkDw8Ph4eHx/+zd99hUVzrH8C/szSpS1uqygpi7BU119gQSOyxa4wSVNQYTa4VWxKxRK/tatB4YyNgLClGE3tUBI0Na7DlxkRpoiJEuhTZfX9/4I47sLALump+9/08j4/snDNnzrQzZ95pko799evXDRp3165daNGiBWxtbdGoUSPs3LnzuZVdlQMHDsDPzw/29vaoXbs2PvroI5SUlIjpKSkp6N+/PxQKBRQKBSZOnPjMx/5Xdf2xvweVSgUiqjT9eR1XjdHH/f/Ub34e/YDx48fDz8+v0vR///vfsLGxeW5thiAImDdvnqQP0bNnTzH9wIEDkv7P559/DicnJ0meV5Xe4EtBQQGmT58OHx8f2NnZoWnTpjh16hQOHToEFxcXlJaWinnz8/Nha2uLU6dOAQAyMzMRGhoKLy8v2Nvbw8/PD3/88YfuipS7Rf348ePo3LkznJyc4OLigtGjR+udGX9/f0ybNg0DBgyAnZ0dfH19cezYMcTExKBZs2awt7fHgAEDUFBQAACYNWuW5A4LADh27BjkcjkKCwsBAPv370eTJk1gZ2eHvn37YurUqfD395eMc/78ebRq1Qp2dnYICAjArVu3qlWngQMHinWqirOzM+rUqQPgaYNFRPjzzz/FZZaSkoLFixfDwsICrVq1wvjx4/Hll1/qLXvnzp0YMWIEmjVrBkEQMH78eLi4uCAqKkqSr6pGtCq7du1C27Zt4eDgAA8PD3zyySc6823ZsgV2dnbiesnJycFff/2FkJAQyGQy2NvbY8iQIUhISNA7zeTkZHTv3h0ODg5wdHSUbH8TJkxAQEAALC0tYWZmhk8++QT379/Hf//7X8m8qtXqGs2vLqWlpVi8eDEaNmwobgu7du0CUHaAWrBgAXx8fODk5ISgoKAqO2sPHz5EcHAw3N3d4eHhgZCQEGRlZYnp9erVw8KFC9GtWzfY2dlh586dcHR0xNmzZwEAiYmJkMlkCA8PF8dp0qSJpBOZnJyMwMBA2Nraonnz5jhz5oykDhs3bhS34TZt2uDIkSOS9B9//BF+fn5wcHBAkyZNjPoY07NIT09H3759YW9vj4YNG+LQoUNimvbjXuvWrUOrVq0k4yYmJsLU1FQMzKWmpmLw4MFwd3eHp6cnxo8fj/z8fDG/TCZDREQE2rZtCxsbG1y8eBGlpaWYMmUKXF1d4eHhgeXLl8PX1xdbtmwBUPHq8ahRoxAcHIxx48bBwcEBderUwYYNGyT12rx5M+rXrw97e3sEBwdj5MiRBrWh5R9vi4iIgLe3N+RyOerUqYOPP/5YTLty5QoCAgLg6OiI+vXr47PPPqt0f9F1BVX7Fk7N1a8tW7agSZMmsLGxQe/evZGdnY3Zs2eLy2bdunXi+NVdLmlpaejRowdcXFzg4OCAzp0749KlS5J5DwwMxNy5c+Hq6go3NzfJ/tGyZUsAEO/2+Oyzz/Quz8ravbi4OEndq7v/V+batWs4ffo03n//fXHYxo0bMWvWLHh5ecHW1hbLli3DoUOHkJqaqre85ORkDBkyBB4eHnB0dESnTp2QlZUFKysrLFy4EL6+vhAEAXXq1MHYsWMRFxdX7Tqzvy99J1avMkEQEBkZKenYN2nSRO94Z8+exciRIxEREYG8vDwsX74c7777Ls6fP//MZVclIyMDAwcOxNixY5GdnY1z584hLi4OCxcuBPD0QpWXlxfu3r2LhIQEnDlzBtOmTXum6bK/P+3zK82xeM2aNahTpw6cnJzw/vvvS/Zjff2YuXPnwsfHB7a2tvD19cXnn38upmmO5ZGRkeKxPCMjo9K6VXZcffjwIUJDQ1G3bl24urpi2LBhePDggThe+T7u7t279R7DCwsLMXDgQLi7u0Mul8PPzw9Hjx4V0zXLZsWKFahTpw5at25t0HliVTIyMtCnTx/Y2tqiWbNmkv5leboeUyp/blzTfvWz9AOAsqcFVCoV3n33XZ3pN2/exJdffokVK1ZU65hQWR9DozplrV+/HiEhITA3Nzd4nKrcvn0bjRo1wvz588Vhjx49QnBwMORyOXx9fREdHV2zwkmPIUOGUOfOnSk5OZmIiG7dukW3bt0itVpN9erVo507d4p5169fT40bNyYiIrVaTa+//joNGjSIMjIyiIjo6tWrdO/ePSIi6tq1K3322WfiuIIg0KlTp4iIKCEhgWrVqkVbtmyhkpISKioqouPHj+urKnXt2pVcXFzo/PnzpFarac6cOeTh4UFDhw6l7OxsysrKosaNG9PixYvFebGwsKD79++LZQwfPpw++OADIiL6888/ycLCgr799ltSqVQUExNDdnZ25O/vL6l3kyZN6Pbt21RUVESTJk2ixo0bk1qtrlGdDGFvb0/m5uYkCAJ17dqVSkpKiIho9erV1KpVK0ne3bt3k5OTk94yBw8eTFOmTJEMUyqVNHDgQMm8enh4kLOzM73++uu0a9cug+p74MABsrW1pQMHDpBKpaK8vDxxXZfXrFkz+vjjjyXDJkyYQGFhYVRcXEzp6enk7+9P8+bN0zvd4cOH07hx4+jx48ekVqvp6tWr4rZY3r59+8jGxoby8/OJiCgpKYlkMhnVrl2bFAoF+fv7U1xcnEHzW5mwsDBq0qQJXbt2jYiI0tLS6OrVq0REtHjxYvL19aWbN29SSUkJhYeHk7u7O+Xl5RERUXh4OAUFBYllvfXWW9S3b1/Kycmh7Oxs6tWrF/Xq1UtMVyqVVLduXUpISCAiosLCQho4cCAtXLiQiMr21QYNGtAbb7xBRER37twhU1NTysrKEsf39fWl3377jdRqNU2ZMoV8fX3F8jds2EC+vr5i/Q8ePEg2NjZ069YtIiI6fPgwOTs7i+v5/Pnz5ODgQL/88gsREcXFxZGZmdkzLc/npVu3bjRgwADKy8uj9PR06tixI8lkMkpOTpYs96ysLLK0tBSXKRHRp59+SoGBgUREVFRURPXr16fw8HAqLi4W18vo0aPF/IIgUIsWLSgxMZHUajUVFxfT/PnzqVGjRpSUlERFRUX00Ucfkbm5OUVHRxNRxWUVEhJCVlZWtG/fPiIi2rVrF5mZmVFKSgoRER0/fpwsLS0pLi6OVCoV7dixg8zNzWnUqFF6l4X2/N68eZOsrKzot99+IyKinJwcio+PF/92dXWlzz77jEpKSui3334jb29vWrFihWReNes/KipKsv1o5mPs2LFEVLa/CYJAb7/9NmVnZ9PDhw+pcePG1KBBA9q0aROpVCo6ePAgmZmZUWpqao2WS0pKCu3du5eKioqoqKiIJk+eTF5eXlRaWirOu7m5OW3YsIFUKhWdPXuWzMzM6PTp02IdZTIZ3b17V+9yJKq63Stfd337v6EmTpwo7tNERNnZ2SQIgmSbJSKSy+W0d+/eKst69OgReXt704cffkh5eXmkUqkoPj5ebCPLGzx4MAUHB4u/w8PDydbWlhQKBXl7e9PYsWMrbX+Z4arqO0VFRVH9+vUpIiKCateuTY6OjjR+/HixP0JUth8MGjSI3NzcyMPDg8aNGyfZzubMmUPe3t5kY2ND9evXp9WrV4tpmv108+bN1LhxY6pVqxalp6dXWlfNdh4dHU1eXl7k5OREISEhkm1IEARau3Yt+fn5kbW1Nb3xxht0584dWrVqFdWpU4ecnZ1p7ty5Yv6+ffvSkiVLxN916tShLl26iL8/+OADmjhxot7lqFQqadu2bXrzlRcWFkYDBgyQDPP396cxY8Y8c9lEZcusU6dO5OjoSAqFQmy3L126RDKZTOzvERHNnj2b+vTpQ0REN27cIJlMRrm5uWJ6dHQ02djYUHFxcY3qomm3ly5dSu7u7uTq6krTpk0T20zN9hAdHU2NGzcma2tr6tWrF2VlZdGsWbPIxcWF3N3d6YsvvhDLbN68Oe3YsYOIyvolFhYW9N5774npPXv2pOXLl9eovqyMvjbCzMyMPv74YyopKaE///yTHB0dafv27URkWD9m27Zt4nlTbGwsWVpa0uHDh4no6TYRGBhIDx48EPvflansuNqpUyexbSosLKTQ0FAKCAgQ08v3cYuKivQew/Pz82nbtm1UUFBApaWltGLFCrKzs6PMzExx2ZiamtLUqVOpqKiICgsL9Z4n6lsPdnZ2FBMTQyqVirZt20a1atUSz6fL94vKr7fy605Xv9rR0VHsV1fmWfoBRET37t0jLy8vSk1N1dmXU6vV1LFjR/rpp5/E9Z+Wlqa3XH19jK5du5JCoSAnJydq2rQpLVmyhB4/fqyzrPPnz5NMJqM//vhD73Qro9kW09LS6PTp0+Tp6UlbtmwR00NCQsjc3Jy2b99OKpWKjh49SpaWlnTmzJlqT6vK4MuDBw9IEASx813eokWLqHv37uLv9u3b06pVq4iIKD4+nszNzSvtPFbVOHzwwQc0ZMiQ6s3JkzInTZok/tYcjC5evCgOK3/gDAoKoqVLlxIR0cOHD8nS0pIuX74szp/2QZ2IaOTIkRWCL1999ZX4+9GjR2RhYSGujJrUyRAlJSX0008/0bJly8SGbeHChdS1a1dJvtjYWINOcqOjo0mhUNCFCxfo8ePHtGbNGpLJZJIT/mPHjlFxcTEVFxfTt99+S5aWlvTzzz/rLbtnz54UFhamN9/JkyfJ1NSUkpKSJMNjYmKofv36ZGZmRjKZjAIDA6mwsFBveSEhIdS3b99Kt1+N33//nVxcXGjDhg3isPz8fIqPj6fHjx/To0ePaM2aNWRpaSkGG2rCxsaGDh48qDOtQYMGtHnzZvG3Wq2m2rVr0zfffENE0pPitLQ0EgRBDHRo5kEQBPEAoVQqadGiRZJprFu3TtyeBw8eTJGRkeTo6Ei5ubkUHR1Nbdq0EfMqlUpauXKl+Pv69euSjl3Tpk3p66+/lpTfp08fcZ/u3bu3GOjR+PDDD8WT7Vcl+KJZlomJieKwI0eO6Ay+EBENHTqUJk+eLP5WKpViR/L777+n+vXrS8q/cOECWVhYiPuoIAi0detWSZ769etTVFSU+FvTIa0q+NK7d29JGQqFgvbs2UNERKGhoZLOLFFZR6a6wZfbt2+TlZUVff/99xVOuLdv305169aVDFu/fj01bNhQ/F2T4Ev5drFp06aScVxcXMT5rO5yKS83N1dyfAsPD68wvbZt21JERIRYR82B2RBVtXvl665v/zfEo0ePyN7eXrJfpqamkkwmq9Cmenl56T05/O6778jDw4NUKpXeaa9atYpcXV3FwBhR2bFO8zspKYl69uxJHTp0MHh+mG5/pxOruLg4EgSBBg8eTHl5efTgwQPq0KEDjRs3TlL/f/zjH3T37l0qLCykbt26UYMGDWjevHn0+PFjSkhIIAsLC/EEKiIiQjwJ+/3338nT05McHByooKCAiIh8fX3pxx9/1LsclUolubq6kpOTE7Vq1YrWr1+vf+ET0YwZM6h///6SYV26dKlw/KxJ2VVdeFSr1dSrVy+KiIig0tJSSkpKoiZNmlBkZCQRPT1G5+TkiOVFRkaSTCarcb9Fsz1NmjSJiouL6fbt29SgQQMx+FWToPnUqVPFQNXPP/9Mvr6+VLt2bSIq69fa2NjQr7/+WqP6sjL62gi5XC7ZbwcPHkxTp04lIsP6MeUNGjSIZs6cSURPt4mTJ08aVFddx9ULFy6QtbW1JNCYmZkpOanX1cfVdwzXxdnZWeyXR0VFkZWVVYUT/KrOE6vStWtXyQUJIqKOHTuK+091gy/6+tWVeZZ+ABFRv379aN26dTrrTET073//Wzxnr04/SV8f4+zZs5SdnU1qtZri4+PJx8eH5syZozNvaGgodevWTe80q6LZdlevXk1ubm507NgxSXpISAh17txZMmzEiBE0fvz4ak+ryseOkpKSIAhCpS/cGjNmDOLi4nDnzh1cvXoVCQkJCA4OBlB2K5GLiwtsbGyqfTdOUlJSpS/00cfd3V3828rKCgDg5uYmGab9kthx48YhMjISALB161Y0btxYvA0uLS0NXl5ekvLL/y4/zNLSEgqFQvKulOrWyRBmZmbo27cv4uLisGnTJgBlL97LycmR5MvOzoadnZ3e8oKDgzFjxgy8++67cHd3R0JCAgIDA+Hs7Czm8ff3h7m5OczNzTFkyBCMHDkS27Zt01u2oetzw4YNePPNNyXL888//0SPHj3wySefoLCwENnZ2fD29sZbb72lt7wVK1ZAqVSiT58+8PT0xD//+c8Kj3fduHED3bp1Q1hYGMaOHSsOt7a2Rrt27WBqagpLS0tMmjQJnTp1Muj9ObpkZGSgoKCg0n0pNTUVSqVS/C0IApRKpc5bAu/cuSOma/j4+IjlaJTfVgMDA3H27Fnk5+cjNjYWPXr0QIcOHXDs2DEcPXoUgYGBkvza26i1tTUAiNtpYmIiJk6cCEdHRzg6OsLBwQFxcXHiS7YSExOxdOlSSXp0dDTu3bunb1G9UJplqf0y5Xr16lWaf9SoUdi+fTtUKhViYmKQk5OD/v37AyjbzpOTk8V5dnR0RGBgIExMTHD//n2xjPLrJS0tTTL9WrVqQaFQVFlv7TYFKFs/mnVjaLulT7169bBt2zZs2LABHh4e6Ny5s/hoWWpqaoUyfXx8DL6FVRdBECq0i+XnU19bWdVy+euvv/Dee++Jj8HWrVsXgiBIbomuavzqqs5xrDr7f2V27NgBExMTDBkyRBxma2sLIqrRcSEpKQne3t6Qyap+OnnVqlVYtmwZYmNjUbt2bXF4o0aNxN9eXl7YtGkTzpw5g8TERIPniVWflZUVFixYADMzM/j4+CAgIAAXLlwAAOzduxcAMG/ePJibm0Mul2P+/PnYtm2beHv38OHD4erqCqDshYe9evVCTEyMZBrh4eFQKBQwNTXV+3y/IAhYtmwZbGxsoFAosGDBAnz99deSPNOnT4e7uztq1aqFQYMGIT09HeHh4TA1NUXz5s3RokULcR4CAwNx+vRpFBcX4+jRo+jevTvat2+P48ePIzU1FYmJiRUeDddly5YtuH37NtImMzqeAAAgAElEQVTT07Fs2TLMmTMHGzdu1Dter169cOjQIcTExEClUmH37t04deoUcnNzn7ns9evXo2/fvhg5ciTMzMxgYWGBzp07i8vxvffew2effQZLS0t4e3ujdevWCAkJAQC89tprqF+/PubMmYPCwkIkJycjIiICACR1qy4TExOsWLEC5ubmqFevHsLCwio8jv7pp59CLpfDwcEBvXv3hrm5OcaMGQOZTCY++n358mUAZetPsz0dPXoUwcHBsLGxwW+//YYzZ87A0tISLVq0qHF9mX4uLi6S/Vb7OGdIPyYiIgLNmzcX+3b79u2THEcFQahRn0MjMTERRUVFcHV1FetQv359WFlZSd69qGsaVR3Di4qKMGnSJPj4+MDe3h4ODg7Izs6u0AcwNTWVlFHVeaI+2sd1ze/y79I0VE371c/SD9i+fTsyMzMxYcIEABUfA7p16xb+/e9/Y82aNTrTq6Kvj9G+fXvI5XIIgoB27dph4cKF2Lp1a4V8eXl5+Oabb8Q6PqulS5eiR48eOo8jz2t9Vtmr0kyksve0uLm5oVevXoiMjERkZCT69esnfj5TqVTiwYMHkucEDaVUKiud5vPWr18/5Obm4sSJE4iMjJScgHt6eiI5OVmSX9dLV5OSksS/Hz16hIyMDPHdLMZWWloqLqsWLVrg5s2bkucQL168aPCBbMaMGfjvf/+LjIwMrFu3DtevX6+yE6N554w+hqzPrKwsfP/99xV2noSEBDg5OSE4OBgmJiawtbXFhx9+iJMnT+rtUDg5OeHzzz/HH3/8gVOnTiE2NhbLly8X0y9dugR/f3/MmTPHoOeiDZ1fXRQKBaytrStdDnXq1JFsR0SEpKQknV9Y0mxb2vlv3bpVIYhQvkHz9fWFm5sbVq9eDXd3d7i5uSEgIABHjhxBTExMheBLVZRKJSIjI/Hw4UM8fPgQWVlZyM3Nxdq1awGUHRTDw8Ml6Tk5OWLn/1Xh6ekJAJL9vKqTw6CgIFhYWGDPnj2Ijo7GsGHDYGFhAaBsnl977TVxnjXzXVBQIOkQlF8v5duZwsLCKp+RNmSeDGm3DNGvXz8cPnwYf/31FwYPHoy3334bRUVFqFOnToVp3Lp1q9J2z9bWtkLg80V/3WDWrFm4f/8+zp8/j+zsbKSmpoLK7v40aHyZTFat/b86x7HK9v/qHEd0Pe8sl8tRt25dybttbt26hby8PDRv3lxv/RMTE6uc54ULF2LVqlU4ceIEGjVqpLeOz9KGMsO8iidW2sclpVKJ4uJiZGZmisPKB11dXFwk42sHXRs1agQnJyecOHECR48eRVBQEAIDA3H48GEcOXIEbdq0MeiCU6dOnWBlZQUTExMEBgZi2rRpOjv25XXp0gVffvml+J6uLVu2YNiwYZILVTUtu6qAbWxsLN577z1ER0ejuLgY9+/fR05ODt577z0AZUGSvXv34vbt21AqlejRowdGjBgBAJK6VZeLi4t4jAMqnmxUN2jepUsX3Lt3D3/88UeF9Xf06FF069atxnVlz05fP+b06dOYNWsWNm7cKKb17t27QruuL2ivna/8uF5eXrCxsalQh/z8fLz++uvVnobGypUrcfLkScTGxiI7OxtZWVmwt7eXTF9XmeXPE6vzuWHt47rmt/ZFCm3l+0nl+0g17Vc/Sz/gyJEjSEhIEF/i/dFHH+H27dtwcXHB1atXcfLkSWRmZqJp06ZQKBRo06YNiAjNmzfX+75RQ/oY5enK+/XXX8PGxka8EPosBEHAvn37cOHCBXzwwQcV0quzPqtS5ZarUCgwaNAgfPDBB2JH+9atW5IXyo4dOxaRkZHYtm2bJHDh5+eH1q1bIzQ0FBkZGSAiXL16VXIFuDLjx4/Hnj17sG3bNpSUlKCoqKjCZ48NpW+lmpqaIiQkBFOmTMGff/6J4cOHi2nDhg1DfHw8du7cCbVajdjYWJ2fsFq1ahVu376NoqIizJo1Cz4+PmjXrl2N61SZXbt24dq1a1CpVCguLsbGjRsRGxuL7t27AwA6d+4MLy8vzJkzB0VFRbh8+TI2bNggefliZXJzc8WXzWZkZOD9998XX9YJANevX8f58+fx+PFjlJaW4scff8TWrVsxdOhQvWVPnDgR//nPf/Dzzz9DpVIhLy9PfCmzRlRUFBQKBXr16iUZ3qZNG2RnZ2P79u1Qq9XIy8vDmjVr4O3trbeD9d1334k7iq2tLczNzWFiYgIAOHXqFAIDA7F48WKdO1h8fDyuX78uLusNGzbgxIkTkp3b39/foJeYakyYMAFhYWHiizTT0tJw9epVAEBISAiWLVuGP/74A48fP8aiRYugUql0vrXb3d0db775JqZNm4acnBxkZWVh+vTp6NmzZ4VOa3kBAQFYsWKF+FLVgIAAbN26FVlZWejUqVOV42pvt5MnT0Z4eLj44uPCwkKcOnVK/PLW5MmTsWrVKpw8eRJqtRolJSW4dOkSLl68aODSejE8PT3RtWtXhIWFIS8vD+np6eILDHWRyWQIDg5GREQEdu/eLVn/vXv3RklJCZYsWSIGndPS0vR+9m7kyJFYvnw5kpKSUFRUhNmzZz/TCerIkSOxc+dOHD9+HGq1Gt9++634ouXquHnzJn7++WcUFhbC1NQUdnZ2kMlkkMlk6NWrF4qLi7FkyRI8fvwYv//+O5YtW4bQ0FCdZbVs2RIPHjzAgQMHQETYvXs3Tpw4Iclj7JPyvLw8WFlZQS6XIz8/H2FhYdV6K79CoYCJiYnBARVD2j2Nyvb/8u1hZS5fvowLFy7obOvHjRuHpUuXIikpCTk5OZg5cya6d++uM7CrrVevXjA3N8eUKVOQm5sLlUqF+Ph4sXM4Y8YMbN68GcePH0f9+vUrjL97927xBDstLQ0TJkyAn58fvL29DZon9vy96BMrjfLBbQsLi2cKCAQEBODnn3/GiRMnEBAQIF5E0HUHZ3UY2gYFBwfjypUryMzMxO7du/H777/rvdvmWS9UXbp0CS1btsRbb70FQRCgUCgwduxY7Nu3T8zToEEDHDhwAOnp6bhx4wZq1aoFDw+PGt9JDgAPHjyQfAUyMTGxRicbGlZWVnj99dfxzTffIDk5Ge3atXtu6489O339mNzcXJiamsLZ2RlEhP379+PgwYOSMqpzLNd1XPXz80OLFi3w4Ycf4uHDhwDKzku+/fbbZ5q3vLw8WFhYwMHBAcXFxViwYAGys7P1jlf+PPGdd94xeJo//vgjYmNjoVarsWPHDly8eFFynqmtTZs2+PHHH5GZmYm8vDx8/PHHkj7Ks/Sra9oPWL16Nf773/8iISEBCQkJWLBgAby8vJCQkIDGjRtj6NChuHXrFn799VckJCSIn4I+cuSIeP5Ymar6GDk5Odi/f7/Y37h8+TLmz5+PYcOGVShnw4YNGDNmjHh+p6F5+XP5vmZViAhubm44fvw4Lly4gJEjR0q+Snr27Fl8++23UKvVOHbsGHbt2iXefVgdeo+gkZGRaNmyJbp06SJ+hSY9PV1Mf/PNNyGTySCXyyURa0EQsHfvXlhaWqJly5ZwcHDAmDFjxJ25fKdX+3fz5s1x4MABrFu3Dq6urvDy8jLoqoGujrQhnevQ0FD8+uuvGDp0qOTTyT4+Pvj+++/x6aefwt7eHqtWrUJwcLDkKoAgCAgNDcWAAQPg6uqKq1ev4qeffhKnW9M66XLv3j0MGDAADg4O8PT0RFRUFL755htxuctkMuzduxdXr16Fk5MT+vTpg1mzZmHw4MF6y87NzcXgwYNhZ2eHRo0aobS0FLGxseK8ZmRkYNSoUXB0dISrqysWL16Mr776yqCTg549e2Lz5s2YPXs2HB0d0bBhQxw+fFiSZ+PGjRg7dmyFZaNUKvHDDz9g9erVcHZ2hre3N1JTU/HTTz/pne7ly5fRpUsX8S3jfn5+mDFjBgDgk08+QW5uLqZMmQJbW1vxc5Cak6PExET069dP/KTjtm3bsG/fPsnXblJSUgy6vVlj8eLFGDJkCPr16wdbW1v4+/uLgcwZM2bgnXfewZtvvgk3NzfExcXh8OHDlT62t3XrVtja2uK1115D48aN4ejoKHnrdmXbWGBgIPLy8sTgS7NmzWBpaYk33nijwnZdnvaw0NBQhIWFiduEUqnEokWLxK+fBQUFYePGjZgxYwacnZ3h6emJqVOnGvRVrxdt+/bt4t0cXbp0Ea8kViYkJAQnTpyAt7e35LN7lpaWOHbsGG7cuIGGDRvC3t4eQUFBki9z6Vqus2fPRlBQENq1awdvb294enrC3d1dsj700S63c+fO+Pzzz8V1c+DAAfTv379a5QFASUkJFixYAA8PDzg4OGDt2rXYtWsXzM3NYWdnJ15pdnV1RY8ePcTOia46eXt74/PPP8fYsWPh5OSEw4cPY9CgQZXOgyHzaQjt/AsWLEB6ejqcnJzQsmVLdOzYscLBuqrxa9WqhYULF2LYsGFwdHTU+9lkQ9o9jeru/+Vt2LAB/v7+OoMgs2bNQp8+fdC2bVvxUavyj33oYmVlhWPHjiElJQW+vr5QKBQICwvD48ePkZKSgpUrVyI9PR0tWrQQP6nbrFkzcfwffvgBTZo0ga2tLTp06ABnZ2fs2bPHoPlhxvGiT6w0+WfPno28vDw8ePAA8+fP19sp1ycgIACbNm2Cl5cXnJ2dxeDuwYMHDTp5T0lJQVxcHIqLi6FWq3H8+HGsXr1aZ8e+PJVKhcuXL0OtViMnJweffPIJ7ty5g8mTJz9z2VVdePzHP/6BK1euiI9+ZmZmYuPGjZJj0LVr11BQUACVSoWjR49i4cKFkq+nREVFVTtwplKpMHPmTBQVFeH27dtYuXKl5GSjJkHzgIAArFy5El27doUgCPD398cvv/yCixcvcvDlOajq/Eofff2Yt956C8HBwWjbti0UCgV27dqFAQMG1Hh6uo6rgiDgp59+AhGhTZs2kMvl6NChg+QivKHT0M43depUyOVyeHh4wNfXFzY2NlU+Zq6tsvNEfdMeM2YMVq5cCblcjkWLFmHXrl2VBjymTJmCRo0awcfHB61bt0bv3r0l6c/Sr65pP0CzvDT/HBwcYGJiAnd3d5iYmIgBXs0/Nzc3CIIAV1dX8TUblamqj6G5CFW7dm3I5XK88847GDFiRIWvQcXHx+PatWuSmz80kpOT4eDgUK3HGDXbi4ODA44dOyZ++Uvz2fEhQ4bgwIEDcHBwwNixY7Fu3TrJ3VgGq/ZbYnTo2rUr/etf/3oeRb0UBQUFZG1tTWfPntWb95133qnRy3XY/y+3b9+mFi1avOxqsP+H8vPzyczMrEZvUK/MP/7xD8kXQtjLFRMTQ9bW1i+7GuxvyN/fX/JSRplMZvCLrYnKvmw3YsQI8vT0JLlcTo0aNaLw8HAiKnup68SJE8nBwYGcnJxo9OjRNHLkSPFl3dV96bTmxdJbtmwhLy8vcnR0rPC1I+36VzYP5ef57t27JJPJaNasWeKwIUOGkI2NjeQlnZW5ceMGtWrViuzs7Egul1OzZs3EF0rqU1xcTH5+fuK4/fr1k7z8/lnKJip7yXGHDh3I3t6eXFxcKDQ0VEzbsmULNW3alORyObm6utKQIUPozp07Yvr8+fPJ2dmZrK2tqXnz5hVe2L1gwQLJByP00ayLZcuWkZubG7m4uNDUqVMlXzsqvz2Uf0k9EVG9evUkL/Y8ffo0yWQy+vLLL8Vh7dq1q/CiV8ZeFdU5T2Svhk8//VTyBc5XiUD0bPd6nzhxAr169UJSUhKcnJyepaiXgoiwePFi7NmzB/Hx8RXS9+7di44dO8LOzg779u3D0KFDcfjwYfElaIwx9iyysrJw7tw5BAQEoKCgAFOmTMGpU6dw48YNvXdmVOaHH35A9+7dYWZmhqioKHz44Ye4ceOG+GJm9nItX74c27Ztw6+//vqyq8IY+x/h7++P5cuXS+6WYYxVTd95ImPVVb37D8tp164d+vfvj7Vr176QwMuSJUvEx0M0/8o/LlIdGRkZsLOzw1dffVXpi4FOnDiBBg0awMHBAXPnzsX69euNFng5efJkpfP3r3/963+y7KqkpqZWOl1d73Fh7FWkVqvx8ccfw8nJCT4+Prh79y727NlT48ALUBZ8qV27NhQKBdavX48ff/wRPj4+2L59e6X7zI4dO57jXP3/V9N2b9CgQVi/fj1Wrlxp0HSaNm0qmYauR3xqyphlM8ZeLbGxsRx4YS9c+eOk5p+h7zR7mao6T3ze56TPYsKECZXWRd/XeLiP8eI9850vjDHGGGPsf4+tra3O9y906tQJ+/fvfwk1KtO0adMKX3kjIiiVSvFF97qkpqaicePGknkiIgiCgBEjRmDdunU1rpMxy2aMMfb38P82+FLTl9oy9nf2/3R3fqVxW8P+13A783JwW8P+13Bb8+JxO8P+F73Itsb0hU3pJWhe7wEsHz+dRSt12VNW1sKT/02ePnVlY17W2FiaPm10LM3K0ms9KcLa7Gl+SxPN/2X5rbQe4LJ98reV7OmKtHpSrOWTNButtFomagCAhVnZ/+bmpWKamVUJAMDEslgcJnvyt6D531brTde1nnwS0LJQ+lv7b6v8p8MsngyzKJT+D0ColScZRuZPp6P5W2X+9DNtpaZl5T6WlaWV4GlZBepHAIAiddm8FWp9uqtIVTbf+Y+fLpNCFUn+f1T6NC2/tCz/I00erTTNsIKnixC5T/4uKBWe/P90m3hUWvYFmKLHZV8VocfWYprJk7/NSp5+ccSsWA4AMC0pS5Np5RdKyt7sTcVln8BWlzx903fpk79LSyzFYSVFZW9Mf1xSCwCgKn6apioqq5fq0ZMyC59+qUbzt6zQXKteZrj+pxvYS3JA2mi7PWnE7VG2rVrh6fZuTU/29ydpAGD+5G/zJ/ks6Gma6ZM0syf/m9LTsjTDTDRpWmWakGbY0/yafJo0E+38T/Jp0mSSNLUkj0yrfpp82vll4nRUlabJxOmoKqQJ5fLoHk87jSTTK8tH5cZ7uo5Myg2TTkdTlo7pPMkvVJVfK00AScbTPT+VpwladX463xXzCyQtSzNd7XqVz1OWT8dyLjePkjpADavJa8FeItNhgEzry2WavwXNMO00q4rDhFrS/DKrytM0vwFAsKpkegCEJ8cimVZ+PBkmmD35X6u7WWGY1iOWgkwyzE142rlyffKkvIPWVOye/G//5H9rrTTNnFk92YS1vx2mqanmqKv9LTjrcsO00zR/W2pV2fxJFc1MpP8DgMWTxWD2ZFZNzZ6maf42fVKoydNDuvi3TGuYrPxi1rEKxGE6VoX4v1YdxPxa0xHTzcrl0R5mWu63dj5daZq/dU3HtGwFkXZ+U0Dm8kxvRmDPSni6QgRx4zN78ltrZT1pEwTtfVxmKh0m2f81aU/Wr2BSIQ1a+72gSRfzm2qllStDazxxOtpv2CiXT1LnCmU9rZegY9oVyzLRkWZSMU3T3sm0yzeRpmnPh2ZZomK9xGnLtE/ny+XTXpYyU915tOugXb6sfP0rzqNYpo75F3SuWx31EodVLEtnvcRtSFda9et1b+eLDThyy8YYY4wxxhhjjDFmRBx8YYwxxhhjjDHGGDMiDr4wxhhjjDHGGGOMGREHXxhjjDHGGGOMMcaMiIMvjDHGGGOMMcYYY0bEwRfGGGOMMcYYY4wxI+LgC2OMMcYYY4wxxpgRcfCFMcYYY4wxxhhjzIg4+MIYY4wxxhhjjDFmRBx8YYwxxhhjjDHGGDMiDr4wxhhjjDHGGGOMGREHXxhjjDHGGGOMMcaMiIMvjDHGGGOMMcYYY0bEwRfGGGOMMcYYY4wxI+LgC2OMMcYYY4wxxpgRcfCFMcYYY4wxxhhjzIg4+MIYY4wxxhhjjDFmRBx8YYwxxhhjjDHGGDMiDr4wxhhjjDHGGGOMGREHXxhjjDHGGGOMMcaMiIMvjDHGGGOMMcYYY0bEwRfGGGOMMcYYY4wxI+LgC2OMMcYYY4wxxpgRcfCFMcYYY4wxxhhjzIg4+MIYY4wxxhhjjDFmRBx8YYwxxhhjjDHGGDMiDr4wxhhjjDHGGGOMGREHXxhjjDHGGGOMMcaMiIMvjDHGGGOMMcYYY0bEwRfGGGOMMcYYY4wxI+LgC2OMMcYYY4wxxpgRcfCFMcYYY4wxxhhjzIg4+MIYY4wxxhhjjDFmRBx8YYwxxhhjjDHGGDMiDr4wxhhjjDHGGGOMGREHXxhjjDHGGGOMMcaMiIMvjDHGGGOMMcYYY0bEwRfGGGOMMcYYY4wxI+LgC2OMMcYYY4wxxpgRcfCFMcYYY4wxxhhjzIg4+MIYY4wxxhhjjDFmRBx8YYwxxhhjjDHGGDMiDr4wxhhjjDHGGGOMGREHXxhjjDHGGGOMMcaMiIMvjDHGGGOMMcYYY0bEwRfGGGOMMcYYY4wxI+LgC2OMMcYYY4wxxpgRcfCFMcYYY4wxxhhjzIg4+MIYY4wxxhhjjDFmRBx8YYwxxhhjjDHGGDMiDr4wxhhjjDHGGGOMGREHXxhjjDHGGGOMMcaMiIMvjDHGGGOMMcYYY0bEwRfGGGOMMcYYY4wxI+LgC2OMMcYYY4wxxpgRcfCFMcYYY4wxxhhjzIg4+MIYY4wxxhhjjDFmRBx8YYwxxhhjjDHGGDMiDr4wxhhjjDHGGGOMGREHXxhjjDHGGGOMMcaMiIMvjDHGGGOMMcYYY0YkEBG97EoYgyAIL7sKjL1w/09351catzXsfw23My8HtzXsfw23NS8etzPsf9GLbGv+3wZfGGOMMcYYY4wxxl4F/NgRY4wxxhhjjDHGmBFx8IUxxhhjjDHGGGPMiDj4whhjjDHGGGOMMWZEHHxhjDHGGGOMMcYYMyIOvjDGGGOMMcYYY4wZEQdfGGOMMcYYY4wxxoyIgy+MMcYYY4wxxhhjRsTBF8YYY4wxxhhjjDEj4uALY4wxxhhjjDHGmBFx8IUxxhhjjDHGGGPMiDj4whhjjDHGGGOMMWZEHHxhjDHGGGOMMcYYMyIOvjDGGGOMMcYYY4wZEQdfGGOMMcYYY4wxxoyIgy+MMcYYY4wxxhhjRsTBF8YYY4wxxhhjjDEj4uALY4wxxhhjjDHGmBFx8IUxxhhjjDHGGGPMiDj48gL4+/tj8eLF4m9bW1vEx8e/xBoZLjk5GTKZDHfv3n3ZVWHslZGWlgaZTIaUlBQsWbIEb7/99kutz8mTJ+Ho6PhCpjV//nwEBQWJv3v27IkVK1a8kGnXhEwmw+nTpytNnzBhAj766KMXWCPGXh3a/ZNXuW9y/PhxmJmZvexqMPZK+TufXzD2qouOjoavr+9zL5eDLy9BXl4e2rdv/7KrYTBBEF7o9IYOHarzhOnQoUNo2rQprKys0Lx5cxw5csSg8goLCzF58mTUqVMHcrkcffr0QWpq6nMp21AzZ86ETCbD9u3bxWHx8fHo3bs33Nzc4ODggLZt2+Knn356rtNlxqPZL2bPnv3S11vHjh3x8OHDFzY97TbhwIEDmD59+gub9vP2n//8BxERETUev3v37vDw8IBcLoeXlxemT5+Ox48fi+lqtRozZsyAi4sL5HI5Bg8ejL/++sugspVKJSwtLWFnZwdbW1vY2dnh+vXrYvqoUaNgbm4uSf/yyy9rPC8aXbt2Ra1atSTlHjhwQExfu3YtXnvtNTg4OEChUKBHjx64evXqM0+XvVyvet/kRfdFqrJmzRq8/vrrsLa2RoMGDXTmWb58OWrXrg1bW1u8+eabSExMNKjslJQU9O/fHwqFAgqFAhMnTkRJSYmYPn/+fJiZmUn2z9mzZz/zPDVt2hR2dnbiPysrK8hkMvz6668AgCtXrqBnz55wd3fXG9RmL8ervA/zxdxXS0ZGBgYMGAA7Ozu4urpi1qxZ1S7j4MGDkMlkGDduXIW0NWvW4LXXXoONjQ28vLwQFRX1HGpd5sqVK7CwsMCbb74pDispKcH777+PBg0awM7ODkqlEmFhYSguLn6maRnjuMPBl/8xKpUKRPSyq1Gp3bt34+HDhxU29sTERAwcOBBz585Fbm4uZs2ahf79+yMlJUVvmdOnT8fFixfx66+/Ij09HU5OTujdu/dzKdsQ586dw6FDh+Dh4SEZ/vDhQwwbNgw3btxAVlYWPv74Y7zzzju4ePHic5ku+/sjIqhUqpddjVeadqDjeTNk+S9btgzJycnIycnBhQsXcOHCBcyfP19MX7JkCfbu3Yvz58/jzp07ICKMHDnSoOkLgoDIyEjk5uYiLy8Pubm5aNKkiSRPSEiIJP3999+v/ozqmO68efMk5fbs2VNM79WrF86cOYOsrCzcu3cPQUFBknTGqutV75uU5+npiZkzZ2Lu3Lk607dt24aVK1di//79yMjIQKNGjdC3b1+986hWq9GnTx94eXnh7t27SEhIwJkzZyoEuP39/SX755IlS555nq5du4bc3Fzx39SpU9GkSRO0bNkSAGBubo6BAwdi//79r1QgjL0a9O3DRPRcthtjHPON2Y94Faany/Dhw8VgWHx8PHbv3o3ly5cbPH5ubi4mT56Mjh07VkhbtGgR1q1bh2+++Qb5+fn49ddf8cYbbzyXeqtUKowZMwadO3eWDC8tLYVCocD+/fuRk5ODX375BceOHcPMmTOfy3SfJw6+lFNQUIDp06fDx8cHcrkcTZs2xaJFi+Di4oLS0lIxX35+PmxtbXHq1CkAQGZmJkJDQ+Hl5QV7e3v4+fnhjz/+0DmN8lcMjh8/js6dO8PJyQkuLi4YPXp0lXW8fPkybG1txZOCyMhIyGQyxMXFAQDS09NhamqKjIwMMdIcGRmJJk2awMbGBmfPnjV4fKCswTx48KB4pbN///7IzMwEUBYsee2118S6ffrpp5DJZEhKSgJQFniwt7eHWq3Wu+z/+usvzJgxA5s2barQgEdHR8PPzw/vvPMOTE1NMXz4cLRu3RrR0dF6y925cydmzpwJJycn1KpVCwsWLMDVq1dx8niHbxsAACAASURBVOTJZy67tLQUixcvRsOGDWFnZwdfX1/s2rVLTC8pKUFoaCg2bNhQ4ZbpHj16YMSIEeLjIm+//TZatGiBX375Re902YuVnp6Ovn37wt7eHg0bNsShQ4fENO3HcNatW4dWrVpJxk1MTISpqakYzEtNTcXgwYPh7u4OT09PjB8/Hvn5+WJ+mUyGiIgItG3bFjY2Nrh48SJKS0sxZcoUuLq6wsPDA8uXL4evry+2bNkCoOIt+aNGjUJwcDDGjRsHBwcH1KlTBxs2bJDUa/Pmzahfvz7s7e0RHByMkSNH6m17dNG+7VnT3mzduhVNmjSBXC5H9+7dkZ6eLuYvLCzE9OnT4e3tDWdnZ/Ts2RO3bt0S07/99lu0bNkScrkcnp6eeP/991FYWCim16tXDwsXLkS3bt1gZ2eH3bt3663j+fPn0apVK9jZ2SEgIEAyvVGjRkmu2uha/lVp3ry5uOzVajVkMhl+//13MX3jxo2YNWsWvLy8YGtri2XLluHQoUMV7r6rjLFOSJOTkzFkyBB4eHjA0dERnTp1QlZWlkHTrVevnthuaeb57t27ku2Y/f1o9000t1uvWbMGderUgZOTE95//33JdqGvLZs7dy58fHxga2sLX19ffP7552Karr6Jps9RlS1btkCpVMLZ2RmjRo1CQUGBpP5ffPGFuO927NgRaWlpWL16NerWrQuFQoGPP/5YzP/6669L6gSU9WG0H6uszIABA9C/f394enrqTN+4cSPGjx+PFi1aoFatWli8eDFu374t9jsq8/vvv+PatWtYuHAhzMzM4OHhgcmTJ+Orr76S3P1SU4b2VVUqFSIjIyXB3IYNG2LMmDFo3br13ypQ9r/kVd6HNUE8zZ0Jn332GYCyC5GhoaGoW7cuXF1dMWzYMDx48EAcT9cxf/78+QgMDMTcuXPh6uoKNzc3hIeHi+MUFhZi4MCBcHd3h1wuh5+fH44ePSqma5bNihUrUKdOHbRu3RqzZs1Cv379JHU+duwY5HK5pA+iS35+PoKDg+Hk5IR69erh66+/hpmZGU6cOAGgrJ8YEBCAGTNmwM3NTZxOSkpKlcvfkGWzZMkSBAYGwtbWFs2bN8eZM2eqrCsAJCUlISYmBitWrICNjQ2USiVmzpxZrTtnp06ditDQUPj4+EiG5+TkYMmSJYiIiBD7ww4ODgY/vqPvnHjJkiVo165dhaCPlZUVFi5cCF9fXwiCgDp16mDs2LHiue3zoLmQrrkTOD09HX369BHPDTTn0/ou3nPwpZzRo0fj/PnziI2NRU5ODvbs2YOhQ4fCxsZG8mjB9u3bUbduXbzxxhsgIvTp0wc5OTm4ePEisrOzERUVBVtbW73Tu3LlCrp3746xY8fi/v37SE1NRUhISJXjtGrVCpaWluIOdvToUfj6+ooNy9GjR9G0aVMoFApxnB07diA2Nla8JbG643/99dc4efIkUlNTIQgC3n33XQBAt27dkJiYiDt37lRaVteuXSGT6d/UPvzwQ3z00Ufw8vKqkJaQkIA2bdpIhrVu3RoJCQl6yyUiSfBHE3TS3Er7LGXPnTsX27dvxw8//IDc3FwcP35ccgvyvHnzEBgYaNBtoPfv38f169fFAxR7dQwfPhxmZma4c+cOTpw4UeH2Sc3VnOHDh+P333/HlStXxLSoqCj4+/ujbt26KC4uRrdu3dC0aVMkJyfjxo0bSEtLwz//+U9JeZGRkfj++++Rn5+Pli1bYvHixfj5559x7tw5cX8r37iXv6L0ww8/4O2330ZWVhYiIiIwadIk8YT/xIkT+PDDD7F582Y8fPgQPXv2xHffffe8Fhe+++47nDx5EmlpacjPz8enn34qpoWGhuLmzZs4d+4c7t+/j/bt26N3797ifmlvb48dO3aIVy5OnjyJRYsWScrftGkTVq9ejdzcXIPet7Nx40bs2rULGRkZaNy4sd4r0NrLv3wwTZeJEyfCxsYG7u7uuHLliniVOicnBykpKWjdurWY19vbG3Z2dga1L0BZB8fZ2RmtW7euEEADytazs7MzGjZsiLCwMMnJaGUKCwvRrVs3uLm54ebNm8jMzMTKlSthbm4u5lm9ejWcnZ3RrFkz/Otf/5JcfACAU6dOwcHBAZaWlpg+fTrCwsJgY2Nj0Dyxv4fk5GQ8ePAAt2/fxrlz5/D999/jm2++AQCD2rImTZrg9OnTyMvLw8aNGzF79uwKj/Tu2LEDcXFxyMvLk/Q5dCktLcW+fftw7do1/Pbbb7h58yamTp0qybNt2zbs2bMHmZmZsLCwQLdu3ZCdnY3bt2+LJxuavs/48eOxefNmcVwiQlRUlM5b6KurfL/C2toavr6+evd7Tbuk3T6pVCo8evQIN2/eFIedPXsWLi4u8PHxwbhx48QLYvrKNrSvunv3buTm5hp8lx57Nb1K+7Bm2//jjz+Qm5sr3jXWr18/mJiY4MaNG0hOToatrS2GDx8uGVfXMf+XX36BUqnEvXv38NNPP2Hx4sXivq1WqzFw4EDcunULDx8+xDvvvIOBAwdKHvlNSkrCvXv38Oeff+L8+fMYN24cDh06JLlYtHnzZowYMQKWlpZVLuePPvoISUlJuHnzJq5evYr9+/dXuOj8yy+/wNPTE3fu3MEPP/yA4uJiBAQEVLn8DVk2X331FdauXYvc3FwEBgbivffeq7KumnVhb28PpVIpDmvdujWSkpIMuojy888/IyEhQecj52fPnkVRUREuX74Mb29veHp6Yvjw4ZKgUWX0nRNfvXoV0dHRWLp0qd6yACAmJgYtWrQwKK8+69evx/jx43HgwAHxTt/hw4ejVq1aSEtLw8mTJ/H1118bdncXMdGDBw9IEAT67bffKqQtWrSIunfvLv5u3749rVq1ioiI4uPjydzcnPLy8nSW27VrV/rss8/E34Ig0KlTp4iI6IMPPqAhQ4ZUu65DhgyhefPmERGRq6srfffdd9SuXTsiIho1ahRNmzaNiIiSkpJIEAQ6efLkM40fGxsrjvvnn3+SIAh07949IiJq164dffXVV5Sbm0t2dnYUHR0tzpO/vz+tWbNG7/zs3r2bXn/9dfG39jIiIgoICKDw8HDJOPPmzaOgoCC9ZY8aNYo6dOhA9+7do9zcXBoxYgSZmJiI6+RZyraxsaGDBw/qTDt//jz5+vrSo0ePiIhIqVTStm3bdOYtKCigN954g4YPH653muzFSktLI0EQKDExURx25MgRkslklJycTOHh4ZJtZejQoTR58mTxt1KppB07dhAR0ffff0/169eXlH/hwgWysLAgtVpNRGXb/tatWyV56tevT1FRUeLvwsJCsrCwoOjoaCIiiouLIzMzMzE9JCSEevfuLSlDoVDQnj17iIgoNDSU3nvvPUl6p06daNSoUXqXR/n51W7fNO3FxYsXxfQvvviCWrduTUREGRkZJAgCpaamiukqlYrkcrlkf9e2du1aat++vfhbqVTSokWL9NZTQxAE+uqrr8Tfjx49IgsLCzpz5gwRlS2rsWPHSvKXX/6Gun79Os2dO5dSUlKIiCg1NZVkMhklJSVJ8nl5eVXaFmg7ceIEFRQUUGlpKR05coScnJxow4YNYvqlS5fowYMHRER048YNateunUFtyHfffUceHh6kUql0pp89e5ays7NJrVZTfHw8+fj40Jw5c3TmzcnJoYiICNq1a5fe6bJXj/b+q33cjYqKIrlcLrZLRESDBw+mqVOnEpFhbVl5gwYNopkzZxJR5X2TysTFxZFMJpO0w0ePHiVLS0vxtyAI9MMPP4i/161bR3K5XFJOu3btKCIigojK2gJ7e3uKj48nIqIDBw6QQqGgkpISg+pEVLacfH19Kww3MTGhuLg4ybAuXbpI+oK6lJaWUoMGDWjixIn06NEjSkpKopYtW5JMJhPXzY0bN8Q2NCkpiXr27EkdOnTQW9dz585V2VfVFhQURKNHj640vXwfjb0cVZ1fvGr7cFJSEslkMkpLS5NMz9raWrLPZWZmkiAIYj5dx/zw8HBq2rSpZFjbtm3FfVsXZ2dnsb8eFRVFVlZW9PjxY0meoKAgWrp0KRERPXz4kCwtLeny5ctVzpdKpSILCwvJ/n7r1i0SBIGOHz8u1rf8st65c2eVy//8+fMGLZuVK1eK6devXyeZTEa5ublV1vnrr78mpVIpGZaYmFhh/eiSm5tL3t7elJCQQEQV+1Bbt24lQRAoICCAMjMzKScnh/r162fQOVVV58SlpaXk5+dHBw4cIKKKfdHyVq1aRa6urpL+ZnVFRUWRj48PhYWFUdOmTSVl3blzhwRBkPTvYmJixHODqvCdL1qSkpIgCILOW6PGjBmDuLg43LlzB1evXkVCQgKCg4MBlEWWXVxcanTVLykpqdKXtVUlMDAQR48exZUrV+Dg4CCJ8MbExCAwMFDMKwhChbtJnmV8TaRUc7eLpqzY2Fh06NABPXr0QGxsLAoKCnDmzBlJWbpkZWXhn//8JzZt2lRpHltbW+Tk5EiGZWdnw87OruoFBeDzzz9Hs2bN0K5dOzRu3Bh+fn6wtraGs7PzM5WdkZGBgoICndvL48ePMXr0aHzxxRd6I+Z5eXno0aMH3NzcDHrUib1Yd+7cgSAIqFu3rjisXr16leYfNWoUtm/fDpVKhZiYGOTk5KB///4Ayvb35ORkODo6iv8CAwNhYmKC+/fvi2WU31/T0tIk069Vq5beq8Tu7u6S39bW1sjLyxPLKz8NXXec1YQgCHBzc9M5Xc3jiM2bNxfn38nJCaWlpeJdOUeOHEHnzp3h4uICe3t7zJw5s8KtzNWtq3Z+S0tLKBQKsf3Sl786GjdujBYtWmDo0KEAytoWIqpx29WpUydYWVnBxMQEgYGBmDZtGrZu3Sqmt2rVStwOGjVqhNWrV2Pnzp16nydPSkqCt7d3pXcktm/fHnK5HIIgoF27dli4cKFkutrs7OwwadIkjB49WvK4Ffv7c3FxkVzFK78v62vLIiIixH3dwcEB+/btk+zLuvom+mi3g0qlEsXFxZK7PrTbHisrK7i4uEjGt7KyEufB0tIS7777rtj32Lx5M4KDg5/LV5Vq2q8wMTHB3r17cfv2bSiVSvHxZABin6VRo0aoXbs2gLK2atOmTThz5ozeF/omJSUZ1Fe9desWYmJiMGHChCrzsVffq7gPa0tMTERRURFcXV3FOtSvXx9WVlaSu3t1TaOqPk5RUREmTZoEHx8f2Nvbw8HBAdnZ2ZK6u7u7w9TUVFLGuHHjEBkZCQDYunUrGjdurPdu9MzMTJSUlEjaJl31LT8sMTGxyuWflJRk0LIp398CIC6HylTWPmnSqjJt2jQMGzYMzZs3r7RsQRAwd+5cODk5wc7ODuHh4Th27Jjex7eqOideunQpGjRogB49elRZBgCsWrUKy5YtQ2xsrNhW1tSDBw+wbt06TJ8+XVJWWlqa+HiThqH7AgdftGiCCrqef3Vzc0OvXr0QGRmJyMhI9OvXT3zmXalU4sGDBzV63l2pVFb6bpiqBAYG4ty5c9i1axeCgoIgk8nQqVMn/Oc//0F6ejq6dOkiyV++k12d8YlIPGkCyhoMQRDEjTAwMBAxMTE4cuQIgoKCoFAo4OHhId623rBhwyrn5cqVK7h37x78/f3Ft/sDQO/evTFnzhwAQIsWLXDp0iXJeJcuXTLodjJbW1t8+eWXSElJQWpqKgIDA5Gfnw9/f/9nKluhUMDa2lrn+rt79y5u3LiBd999V5yn1NRUTJgwQXIb78OHDxEYGIjatWvju+++q3AgYC+f5pn+5ORkcVhVndygoCBYWFhgz549iI6Oxv+xd+dxUVX9H8A/M+zbzCCLigsoYuYSVkhkbiiYqZlouaU8kiTSo09ZmvLk8+SWVuaTmi1mbima5V7aoqaSLVamZuqvTMEFFSmWYZH9/P6YmctcGJhhueDyeb9evJg559xz7p2599xzv3OXUaNGwcnJCYChY77rrruQkZEh/WVmZiIvL082kKi4vbZo0ULW/o0bN2y6P0J1y2ReH4B6u8F0dfz9/aFSqXD27FnZ8ufm5mLkyJEoLi5GVFQUxowZg8uXLyMrKwuvvfZapUuEbLmM0Zx5/5Wfn4/09HTZDrOimtZvrri4GH/++ScAQKvVonXr1rL+5dy5c8jJyaly4GJNxc+iNmUCAgKQnJxco/s2VFe2tLQURUVFsnvp0O3NWl/23XffYebMmVi5cqWUN3jw4DpvyxX7YScnJykoURtxcXHYvHkzUlJS8Omnn+Lpp5+udV3mKo4rcnNzcfbsWZvGLO3bt8eePXuQlpaG06dPw9nZGX5+ftX+UKdSqWza7m0Zq65YsQJdu3ZFSEiI1XmlW1dDb8NqtbrStP7+/nB3d680D7m5uQgLC6txGyaLFy/G4cOHceDAAWRlZSEzMxM6nU7WvqU6hw4dCr1ej6SkJKxevdqmSxC9vb3h6Ogo65sqjq8stWft87f1s6mN4OBgZGdny8ZGR48eRUBAgNXgy969e/Hee+9JxzYfffQR1q9fj7Zt2wIw3Nun4vds61ijumPivXv3Yvfu3VK7r7/+Og4dOgRfX18pcAQA8+bNw5tvvomkpCTcfffdNrVbnWbNmuGrr77CtGnTZD9CmY4NzMfOlr53Sxh8MePj44PHH38czzzzjPQBnjt3ThpQPv3001i9ejUSExNlO+iQkBDcd999iI2NRXp6OoQQOHnypOyX7KrExcVh165dSExMRFFREQoKCnDo0CGr07Vp0watWrXCkiVLpJvD9e3bF4sWLUJYWJjsbAtLK31NpgcMK/P169elpwFFRkZK0daHHnoIer0eGzZskOrq168fFi1ahH79+lldlu7duyMlJQXHjx/HiRMnpOtC165dKz36LDo6Gj///DM2b96M4uJiJCYm4tixYzZd25iSkiJ9F//3f/+HCRMmICYmRjpjpS51x8fH48UXX5Qe/5qamoqTJ0+idevWuHjxomyZ/Pz8sGDBAumxtmlpaejVqxc6duyI9evX1+mAj5TTokUL9OnTBy+++CJycnKQlpaGefPmVVlerVYjOjoay5Ytw/bt22U3Cxs8eDCKioqwcOFCaQCcmpqKHTt2VDsP48aNw6JFi6RfQhISEup0w8Nx48Zhy5YtOHToEMrKyrB582b88MMPta7PXHXz5ePjgzFjxiA+Pl563GRWVhZ27NiB/Px8FBUVoaioCDqdDo6Ojjh9+jSWL19e53l68803cf78eRQUFGDmzJkIDAxEaGhonev9/fffsXPnTuTl5UEIgWPHjmHevHmyJ/9MnDgRr732GlJSUpCdnY0ZM2ZgwIABsl/JLLl48SIOHjyIwsJClJWV4dChQ1iyZAlGjRolldm8ebP069XZs2cxbdo0PPbYY7J7t1gyaNAgODo6YurUqdDr9SgtLcWRI0eQl5eH7Oxs7N69W7p3zLFjxzBnzhxZuytWrEBqaioAw69+kydPhouLy037iFOqf9b6Mr1eD3t7e3h7e0MIgd27d+Pzzz+X1VHTPkwIgYSEBOTk5OD69euYM2eOdAZybXXp0gUdO3bE8OHD8cADD8geIFCd0tJSFBYWoqioCEIIFBYWyh5pOnHiRKxYsQLHjx9Hfn4+/v3vf6Nt27YWnwxS0W+//Ya8vDyUlpZi3759mDdvnnRTc8BwPxbT2T6pqamIj49HSEiIdPBTFVvGqsXFxVi3bl2VZ70UFhaioKAAgOGBAqb+iW49Db0N+/j4wM7OTnZwHRISguDgYEyZMgUZGRkADGeVb968uU7LlpOTAycnJ3h6eqKwsBBz586VHaBXxd7eHuPHj8fUqVPx559/YvTo0VanUavVGDNmDGbPno2//voLOTk5mDVrltV7f1j7/Gv72djynQQEBCAiIkIa154/fx6vv/66TU9LPHLkiHQFyIkTJzBkyBAMHz5cut9O69atMWjQICxcuBCZmZnIycnB/PnzMWDAAKtXAlR3TLxlyxacPn1aanfSpEkICwuT7l8DANOnT8eqVatw6NAhtGvXrlL9a9eurdWx1oMPPoivvvoK06dPl25KbDo2mDlzJnJzc5Geni7dRNoaHu1VsHr1anTt2hW9e/eGRqPB0KFDpZsv9e/fH2q1GlqtFn379pWmUalU+PTTT+Hi4oKuXbvC09MTEyZMkDamihug+ft77rkHe/bswTvvvIOmTZvC39+/ytO7K4qIiEBBQYF0BkdERARycnIq3am/qg6gJtOPHTsWPXv2hL+/P0pKSqSnrACGxw/26NEDLi4u6NKlS7V1WWK6o7/5n0qlgre3t3SKbtu2bbFt2zbMmzcPOp0Or776Knbs2GH1AAYATp06hbCwMLi7u2PAgAEYMGCA7MaVdal7wYIFGDFiBIYOHQoPDw+Eh4fj3LlzUKlUlZbJ3t4enp6e8PT0BGA4gDlz5gy2bNkCrVYLDw8PaDQavPrqq1bbpYa1ceNGFBQUoFWrVujdu7fVwNz48eORlJSEtm3byn49dHFxwddff43Tp0+jQ4cO0Ol0iIyMlN2E0dL2mpCQgMjISISGhko3MGvevLl0Ro0tzOvt1asXli5dipiYGDRp0gR79uxBVFRUjeqran6tDThWrlyJDh06oE+fPtBqtQgODsaWLVugUqng5uaGd999F9OnT4dGo8GUKVOkm3vbWr+l+YuNjcWwYcPQtGlTnDx5Ejt37qyynprUL4TA66+/jlatWkGn02HkyJEYOnQo3n33XanMzJkz8eijj6Jbt25o3bo1VCoV1q9fb7XuvLw8PP/88/D19UWTJk0wZcoUzJ49G88884xU5r333pOeRDFgwAB0795dOmW6Oq6urvj6669x8eJFBAUFwcfHBy+++CKKi4tRXFyM+fPno2XLltBqtRg9ejTGjh0rO/j76aefEBoaKj1d4dq1a9i3bx+8vLxs/uzo5qBSqaR1vibrvrW+7OGHH0Z0dDS6desGHx8fbNu2DcOGDavUdk3Y29tj0KBB6NKlC+6++260a9cOixcvrlF9lsrExcXh2LFjNbrR7vz58+Hi4oJJkybh/PnzcHFxgaurq5Q/ZswYvPDCCxg0aBB8fX1x5swZ7Nq1y6Z53LZtGwICAqDVavHCCy9g6dKlsjNmt27dik6dOsHDwwPdu3eHt7c3du3aZbVea2NVU9uFhYWVbuoJGH7VdXFxgZubG1QqFfr16wdXV1ebx6xU/2q6/zXX0Nuws7Mz5s2bh1GjRqFJkyZYuHAhVCoVdu7cCSEE7r//fmi1WnTv3l32I7StbZiXe/7556HVauHn54egoCC4u7tXe7m4udjYWBw/fhwjR4606cEpgOHyrNatW6N9+/a455570L9/fwCodkxl7fOv7Wdj6+eVmJiI0tJStGjRAmFhYRg2bBimT59udTpfX1/ZsY2rqytcXV3RtGlTqcz69evh4+ODgIAAtG/fHm5ubjbdVqG6Y2IvLy9ZuxqNBk5OTtJZ4xcvXsTixYuRlpaG4OBgaDQaeHh4SMelgOHpXn369LHp86no3nvvxYEDB/DKK6/g9ddfB2D4DPPy8tCyZUv07NkTI0aMAFD99w4AKlGXn0/vQOHh4RgwYMBN+dxwIroz5OXlwdPTE0lJSXU+/dSke/fuGDJkiHS22Z0iOjoaGo2mXs6wIaJbz6FDhxAVFYUrV67A2dm5sWeHiBpRfn4+fH19sX///lqfzfn777+jY8eOSE1Nld2ThRpXeHg4Fi1apNgllV9++SWioqKQn59fbTme+VIDSUlJ+PnnnxEbG9vYs0JEd5DMzEx8+eWXKCkpQXZ2NqZMmYI2bdqgW7duta5z69atyMvLQ1FREd5//30cPXoUTzzxRD3O9c2vqKgIp06dsnh6KhHd/goKCvDGG29g4sSJDLwQ3eGEEHjzzTfRqVOnGgVekpOT8f3336OsrAxpaWl4/vnn0bt3bwZebjIHDhyo18DLiRMncPLkSQDA+fPn8Z///Ed2iXZVGHyxUWhoKKKiorB8+fIGObV64cKF0mUopj/T+2+//Vbx9uubkstzq9ZNZKuysjLMmjULXl5eCAwMxJUrV7Br1y7Y2dnVus6tW7eiZcuW8PHxwYoVK7Bjxw4EBgZi48aNVa7zmzZtqselqh8DBw6scn6rk5GRAW9vb/j6+sruy1NR586dZXVbOpW1tm7VuomUUHE7Nv0NGjRIkfa2b98OLy8v6PV66eb+JrXtV2xxq9ZNZE1Db8P1KT09HRqNBmvWrJHu62Fi7VigoKAAEydOhE6nQ3BwMNzd3ZGYmNhIS2JQ2zHApUuXqlxW88uea0PJuhtDZmYmhg0bBg8PD/Tq1Qtdu3bFkiVLrE7Hy46IiIiIiIiIiBR02z7XtqY3ciO6HTCW2vDY19Cdhv1M42BfQ3ca9jUNj/0M3Ykasq+5bYMvAHD+1P/BrrT80X92JYbH46kKbxj/55UXztMb/t8ov0mOKDDkC2NamakMAFFgTLsh/w8Apbk5hv9maab80nxD2yVmd5cvvWGYr7KiYmNCqZSnMl5WoHIqf3SonbPhLsp2roZHdtmb3Y3bzsVwt3218XFeahfXynlu5aefqkxpzq7G927leaZyxjw4l+cJY1qpc3nbpXaG66WLVYb5KxYOUt6NIsNyFBYbrnQrLCzv3AuKDP+NH40hrdCUp5K9B4DcG6Y6jdMVleflG8vlmqVlGdP0RYYNK7ukPM/0Ot+4zTmZ7XM0xis6tGZbiZexgLvx63A3e6Krm/G1h/FJai5meabXzmY3wHZzMTTqbMwzvzm2qZyLsYyTY3mn4ORgeO1gV76eOKhKENipPaiRdDwDqMq/D6gNrz2MaR7q8kdxuqkNK52jWXlHY769Mc1BXb6SmtLsjGXszKazN5ZTG/PUZnlqabrKaSpjmlpVPl9qY10qqUx5nqrCdCqzdirmGdLKjGnG5VBVrgsW6jKlSZ+l+XRSXZXn3UEYpQ2vZQAAIABJREFUXjuhPM3emOZgTDO9BwBHYajDXsor375MaVIZs+nsROW6pHYs5FUs71BWWmWendnjWk3l7MzbKZOXk9VlfC2VMduHOBhf21X4DwD2xtf2xcXlacWGz9nOmKY2y0NBGVTlT6WlxqAZC5W6fN+qUhleq43/7c3yHFWGnYuDyt4szV7239lCnpPxinQnlF/W6GpMcxGGfaCz2TjV2biaupqlOZUZ913GNMey8kwXY3lH43bnaLb9mV47G9dlR5TnORhfy9KM/YCTWsjeA4CDKc3Ylzk6mOXZG7c/03+zPHsn43bhYNxmHM36UFOac/l2YWdMUxnLmcoAgNrZ2K9KZcwey2wqZ/oAzeYBjhbSTK+N7ajM8+zl5VUWplOZytiXf34q43hCdjRgWoXsjQMiB7OBUYU0YW+W56A2pqnlZc3ShKO6UhrsK0xnfO3m/CmoEZnfmMKuiv/mr83Lm16rKpQxT6tYpqo0VYX/agt51U1nqXx91mXLclQ3nbX5qliXpXaUmq+atG3te7SlfGPVNQcNivd8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgWphBCisWdCCSqVqrFngajB3aab802NfQ3dadjPNA72NXSnYV/T8NjP0J2oIfua2zb4QkRERERERER0M+BlR0RERERERERECmLwhYiIiIiIiIhIQQy+EBEREREREREpiMEXIiIiIiIiIiIFMfhCRERERERERKQgBl+IiIiIiIiIiBTE4AsRERERERERkYIYfCEiIiIiIiIiUhCDL0RERERERERECmLwhYiIiIiIiIhIQQy+EBEREREREREpiMEXIiIiIiIiIiIFMfhCRERERERERKQgBl+IiIiIiIiIiBTE4AsRERERERERkYIYfCEiIiIiIiIiUhCDL0RERERERERECmLwhYiIiIiIiIhIQQy+2Cg8PBwLFiyQ3nt4eODIkSONOEe2u3DhAtRqNa5cudLYs0LUqFJTU6FWq3Hx4kUAwMKFC/HYY4816jwdPnwYTZo0aZC25syZg8jISOn9wIED8cYbbzRI27WhVqvx3XffVZkfHx+Pf/3rXw04R1SdivvJijZu3Ih77723Aefo1nErjTEOHToEBweHxp4NqmedO3fGJ598YnP55ORkPPTQQ9DpdBg+fLiCc0Z1dSv1L2TdK6+8gvDw8MaejduGtbFLfWPwpZZycnLwwAMPNPZs2EylUjVoeyNHjrR44PTFF1+gc+fOcHV1xT333IO9e/faVN+NGzfw3HPPoVWrVtBqtXj00Udx6dKleqnbVjNmzIBarcbGjRultCNHjmDw4MFo1qwZPD090a1bN+zcubPObc2cOROdO3eGVqtFy5YtMXHiRGRmZkr569atg52dHTQaDTw8PKDRaPDkk0/Wud07gfm2kJCQUC/fV1306NEDGRkZDdae+fLv2bMH06ZNa7C269u7776LZcuW1bme5cuX46677oKnpyd8fHzwyCOP4OTJk7Iyt1vfZQrKm/oPDw8PtG7dul7brWjMmDE4duyYom3cLm72MUZDjymq89ZbbyEsLAxubm5o3769xTKLFi1Cy5Yt4eHhgf79+yM5Odmmui9evIioqCj4+PjAx8cH//znP1FUVCTlz5kzBw4ODrJ9cUJCQp2XqXPnztBoNNKfq6sr1Go1jh8/DgAoKyvDjBkz0Lp1a2i1WgQHB2Pr1q11avO3337DE088YXP5V199Fa1bt0ZWVlad26aGdTP3L/zB2Da29sG1HV/Y0rcpMXaxdnyj1HFXQ2Lw5RZUWloKIURjz0aVtm/fjoyMjEodQ3JyMoYPH46XXnoJer0eM2fORFRUlHQWQnWmTZuGo0eP4vjx40hLS4OXlxcGDx5cL3Xb4scff8QXX3wBPz8/WXpGRgZGjRqF06dPIzMzE7NmzcLo0aNx9OjROrVnb2+PxMREZGRk4MSJE7h8+TLGjx8vKxMYGAi9Xo+cnBzo9XokJibWqU2qX0IIlJaWNvZs3NSKi4sbexYAAIMGDcL333+PzMxMXL16FZGRkRg4cKCUfzv2XYBh8PbHH39I/Uh9tUm3tpt9jFFRixYtMGPGDLz00ksW8xMTE7F48WLs3r0b6enpuPvuuzFkyBCry1hWVoZHH30U/v7+uHLlCk6cOIHvv/++UsA6PDxcti9euHBhnZfpt99+g16vl/6ef/55dOrUCV27dgVgCBgnJibi66+/RnZ2NubOnYsxY8bgjz/+qHPbtjp//jy6dOlS6+lvlv6fGpa1/kUIUS/BXSXWr/quU+ltoK7ji+r6NiXHLtUd3yh13GWr+vjObsvgS15eHqZNm4bAwEBotVp07twZ8+fPh6+vL0pKSqRyubm58PDwwLfffgsA+OuvvxAbGwt/f3/odDqEhITg7NmzFtuoeFbHoUOH0KtXL3h5ecHX1xdPPfVUtfN47NgxeHh4SAdnq1evhlqtxsGDBwEAaWlpsLe3R3p6uhQFXr16NTp16gR3d3f88MMPNk8PGDqzzz//XPp1NyoqCn/99RcAQ7Dkrrvukubtv//9L9RqNVJSUgAYBu86nQ5lZWVWP/u///4b06dPxwcffFCpc123bh1CQkIwevRo2NvbY8yYMbjvvvuwbt06q/Vu2bIFM2bMgJeXF5ydnTF37lycPHkShw8frnPdJSUlWLBgATp06ACNRoOgoCBs27ZNyi8qKkJsbCzef//9SqdaP/LIIxg7dqx02chjjz2G4OBgfPPNN1bb3bdvH+677z7odDr4+vqif//+Ut78+fMRHBwMOzs7eHl54dlnn8WhQ4es1klyaWlpGDJkCHQ6HTp06IAvvvhClj9nzhzpc3/nnXcqXRKRnJwMe3t7aWdy6dIlPPHEE2jevDlatGiBuLg45ObmSuXVajWWLVuGbt26wd3dHUePHkVJSQmmTp2Kpk2bws/PD4sWLUJQUBA+/PBDAJVP4Y+JiUF0dDQmTpwIT09PtGrVCu+//75svlatWoV27dpBp9MhOjoa48aNs9rnWGJ+qqWpn9mwYQM6deoErVaLAQMGIC0tTSp/48YNTJs2DW3btoW3tzcGDhyIc+fOSfmbN29G165dodVq0aJFC0yaNAk3btyQ8tu0aYN58+ahb9++0Gg02L59u9V5/Omnn3DvvfdCo9GgX79+svZiYmIwceJEAIazxYYOHSqb9uuvv4ZWq5XNgyVt2rSRtuGysjLpVzfTd3s79l2AYb9gS79eE+np6Xj00Ufh4eGBLl26yLa5devWISgoCIDhFzNr++Q7mfkYw/S5vfXWW2jVqhW8vLwwadIk2T7WWt/00ksvITAwEB4eHggKCsLSpUulPEtjDNPYoToffvghAgIC4O3tjZiYGOTl5cnm/+2335b6wh49eiA1NRVLlixB69at4ePjg1mzZknlw8LCZPMEGMYi5pdJVmXYsGGIiopCixYtLOavXLkScXFxCA4OhrOzMxYsWIDz589L22BVfv/9d/z222+YN28eHBwc4Ofnh+eeew5r1qyRnf1SW7aOOUtLS7F69WpMmjRJSjt37hx69+6Ndu3aATCMPby8vPDbb7/Ven7atGkjnR1n2i99/PHHaNeuHTw9PTFy5EjpO+7atSsOHjyIuXPnQqPRYM2aNQCAb775Bj179oSXlxeCgoLwv//9T6rfVOeGDRsQGBgIb29vqd2FCxciIiICHh4euOeee/D999/Lln/u3LkIDAyEl5cXIiMjcerUqVovJ93c/YspwNi+fXtoNBq88sorAAwH3bGxsWjdujWaNm2KUaNG4fr169J0lsYXc+bMQUREBF566SU0bdoUzZo1w+zZs6Vpbty4geHDh6N58+bQarUICQnBvn37pHzTZ/PGG2+gVatWuO++++o01ggPD8fUqVMRFRUFnU6HN998E0D12w0A7N69G506dYJGo8GQIUOk4zdr6jK+ULJua2OX6tTluMsWZWVliI+PR1hYGNLT06vst+ritgy+PPXUU/jpp59w4MABZGdnY9euXRg5ciTc3d1lpyZt3LgRrVu3xkMPPQQhBB599FFkZ2fj6NGjyMrKwtq1a+Hh4WG1vV9//RUDBgzA008/jWvXruHSpUuVzlKo6N5774WLi4u0g9m3bx+CgoKkjX7fvn3o3LkzfHx8pGk2bdqEAwcOSKcL1nT69evX4/Dhw7h06RJUKpV0Glffvn2RnJyMy5cvV1lXnz59oFZbX12mTJmCf/3rX/D396+Ud+LECdx///2ytPvuuw8nTpywWm/FgwRT0Ml0Cm5d6n7ppZewceNGbN26FXq9HocOHZKduvzyyy8jIiLCplM0r127hlOnTkk7j+r84x//wLPPPousrCykpqbKBqIV7du3D8HBwbK0S5cuwc/PD/7+/hg9erQULKNyY8aMgYODAy5fvoykpCSsXbu22rK///47fv31Vylt7dq1CA8PR+vWrVFYWIi+ffuic+fOuHDhAk6fPo3U1FQ8++yzsnpWr16NTz75BLm5uejatSsWLFiAL7/8Ej/++KO0nVX8ZaDirzxbt27FY489hszMTCxbtgyTJ0+WLlVJSkrClClTsGrVKmRkZGDgwIH4+OOP6/hJlfv4449x+PBhpKamIjc3F//973+lvNjYWPzxxx/48ccfce3aNTzwwAMYPHiwtD3qdDps2rQJ2dnZ+Oabb3D48GHMnz9fVv8HH3yAJUuWQK/X23S/nZUrV2Lbtm1IT09Hx44dq/zFeuLEifjiiy9kwaJVq1Zh7NixcHFxsdrOt99+C09PT7i4uGDatGl48cUX4e7uDuD27btUKhXCwsLg6+uLvn371kuAd/Xq1Zg6dSqys7ORkJBQ6Zcw07r+8MMPV7tPJrkLFy7g+vXrOH/+PH788Ud88skn+OijjwDApr6pU6dO+O6775CTk4OVK1ciISGh0inimzZtwsGDB5GTkyMbO1hSUlKCzz77DL/99hvOnDmDP/74A88//7ysTGJiInbt2oW//voLTk5O6Nu3L7KysnD+/Hns378fb7zxhjSGiYuLw6pVq6RphRBYu3atFFyti4rbmJubG4KCgqxuY6Z+xry/KS0tRX5+vuwMkx9++AG+vr4IDAzExIkTbTowqsmYc/v27dDr9Rg3bpyU9vTTT+PUqVM4c+YMysrKsGXLFpSWlqJXr15W27ZVaWkp9u7di5MnT+KPP/7AsWPHpMs8jx8/jh49euC///0v9Ho9YmJicPr0aQwaNAgzZszA33//jd27d+Ptt9/Ghg0bZHV+/vnn0pmAJmvWrMHy5cuh1+sRERGBf/zjH1Le66+/jg0bNuCLL77AtWvX0KNHD0RGRsoO/qlubqb+xbRdnj17Fnq9XjqjbejQobCzs8Pp06dx4cIFeHh4YMyYMbJpLY0vvvnmGwQEBODq1avYuXMnFixYIPU7ZWVlGD58OM6dO4eMjAyMHj0aw4cPx99//y3VmZKSgqtXr+LPP//ETz/9VOexxpo1a/Dcc88hKysL//rXv6xuN+fOncPw4cMxa9YsZGVlYcqUKVi5cqXVdkyfZW3HF0D1fZuSY5eaHN/U5LjLmtzcXDz66KNIS0vDoUOHpPW0qn6r1sRt5vr160KlUokzZ85Uyps/f74YMGCA9P6BBx4Qb775phBCiCNHjghHR0eRk5Njsd4+ffqIV155RXqvUqnEt99+K4QQ4plnnhEjRoyo8byOGDFCvPzyy0IIIZo2bSo+/vhjERoaKoQQIiYmRrzwwgtCCCFSUlKESqUShw8frtP0Bw4ckKb9888/hUqlElevXhVCCBEaGirWrFkj9Hq90Gg0Yt26ddIyhYeHi7feesvq8mzfvl2EhYVJ780/IyGE6Nevn5g9e7ZsmpdffllERkZarTsmJkZ0795dXL16Vej1ejF27FhhZ2cnfSd1qdvd3V18/vnnFvN++uknERQUJPLz84UQQgQEBIjExESLZfPy8sRDDz0kxowZY7VNIYRo06aN+M9//iOuXbtWbbktW7YIjUYjjh8/LqUlJyeLs2fPCiGESEtLE+PHjxft2rWT5pOESE1NFSqVSiQnJ0tpe/fuFWq1Wly4cEEIIcTs2bNl68jIkSPFc889J70PCAgQmzZtEkII8cknn4h27drJ2vj555+Fk5OTKCsrE0IY1vkNGzbIyrRr106sXbtWen/jxg3h5OQk1q1bJ4QQ4uDBg8LBwUHKHz9+vBg8eLCsDh8fH7Fr1y4hhBCxsbHiH//4hyy/Z8+eIiYmxupnUnF5zfs1Uz9x9OhRKf/tt98W9913nxBCiPT0dKFSqcSlS5ek/NLSUqHVamXbubnly5eLBx54QHofEBAg5s+fb3U+TVQqlVizZo30Pj8/Xzg5OYnvv/9eCGH4rJ5++mkpPzIyUrz22mtCCCEyMjKEi4uLOHbsmM3tCSFEdna2WLZsmdi6dauUdjv2Xbm5ueLIkSOiuLhY5Ofni7feeku4uLiIkydPWm23Kn369BHR0dGytB49eoiFCxcKIYRYu3atCAoKkvKq2yffaaobY6xdu1ZotVqpnxFCiCeeeEI8//zzQgjb+qaKHn/8cTFjxgwhRNVjjKocPHhQqNVqWd+6b98+4eLiIpt/823onXfeEVqtVlZPaGioWLZsmRDCsG3rdDpx5MgRIYQQe/bsET4+PqKoqMimeRKi8vplYmdnJw4ePChL6927t+zztqSkpES0b99e/POf/xT5+fkiJSVFdO3aVajVaum7OX36tNQnpqSkiIEDB4ru3btbndcff/yx2jGnucjISPHUU0/J0vLy8sQ///lPoVarhYODg3B3dxfbt2+3Wld1zPsI03f8999/S/nTp08Xw4YNk95XXGcnT54sJkyYIKtz8eLFIiIiQlbn5cuXK7W7ePFi6f2pU6eEWq0Wer1eCCFE+/btxapVq6T8srIy0bJlS/HRRx/VaXnvJLdS/5KSkiLUarVITU2Vtefm5ibrD/766y+hUqmkcpbGF7NnzxadO3eWpXXr1k3qdyzx9vaW9qtr164Vrq6uori4WFamtmONPn36VNpGqtpuTGOAV155RfTq1UuW/+STT4rw8HCr7dVlfGGtb1Nq7FKT45uaHndVpU+fPiI+Pl507dpVdgwgRNX9Vl3cdme+pKSkQKVSSac2m5swYQIOHjyIy5cv4+TJkzhx4gSio6MBGKK+vr6+0i+dNW2zqpu8VSciIgL79u3Dr7/+Ck9PT1n0df/+/YiIiJDKqlSqSmeT1GX6gIAAAJDOdjHVdeDAAXTv3h2PPPIIDhw4gLy8PHz//feyuizJzMzEs88+iw8++KDKMh4eHsjOzpalZWVlQaPRVP9BAVi6dCm6dOmC0NBQdOzYESEhIXBzc5NO/6pt3enp6cjLy7O4vhQXF+Opp57C22+/bTWanZOTg0ceeQTNmjWz+XS+nTt34o8//kCXLl3QuXPnSqdcA8Ann3yCuLg4fPrpp7IzXwICAqTTjX19fbFy5UpcvXoVP/zwg01t3wkuX74MlUolu4lomzZtqp0mJiYGGzduRGlpKfbv34/s7GxERUUBMGznFy5cQJMmTaS/iIgI2NnZ4dq1a1IdFbfT1NRU2Tw4Oztb/VW5efPmsvdubm7IycmR6qvYhqUzzWpDpVKhWbNmFts1/fJwzz33SMvv5eWFkpIS6aycvXv3olevXvD19YVOp8OMGTMqnV5c03k1L+/i4gIfHx+p36po4sSJWL16NQBgw4YN6NixY41/DdFoNJg8eTImTJiA33//HcDt2Xe5ubkhNDQU9vb2cHFxweTJk9GzZ88aPe3EEtO+xfx9Vd9XdftkkvP19ZWdIVdx27TWNy1btkzadj09PfHZZ5/Jtk1LYwxrzPu1gIAAFBYWyn4ZNe9LXF1d4evrK5ve1dVVWgYXFxc8+eST0hhi1apViI6OrpenKtV2G7Ozs8Onn36K8+fPIyAgQDrdHYC0/d59991o2bIlAENf9cEHH+D777+3ekPflJQUm8ac586dw/79+xEfHy9Lj4+Px/Hjx3HhwgUUFRXhq6++QlxcnOySibqys7OTPYnPfJ2zJDk5GZs2bZLWQU9PT8ydO1f2S7FarbZ4eVjF/Q4Aqa1Lly7J+hWVSoWAgIBKNy6n2rsZ+xdzycnJKCgoQNOmTaV5aNeuHVxdXWVnVlpqo7rxVEFBASZPnozAwEDodDp4enoiKytLNu/NmzeHvb29rI66jDUq7iOr2m5Mn+3ly5crTWNtLGtSl7GLtb5NibELYPvxTW2Ou6qzfft2XLt2zeIN06vqt2rrtgu+mFZQS9fNNmvWDIMGDcLq1auxevVqDB06VNqxBAQE4Pr167U6jTEgIKDKe8NUJyIiAj/++CO2bduGyMhIqNVq9OzZE++++y7S0tLQu3dvWfmKl/3UZHohhOy0reTkZKhUKmnDioiIwP79+7F3715ERkbCx8cHfn5+WLJkCby9vdGhQ4dql+XXX3/F1atXER4eLj0VAAAGDx6Mf//73wCA4OBg/PLLL7Lpfvnll0qX01ji4eGB9957DxcvXsSlS5cQERGB3Nxc6VFrta3bx8cHbm5uFr+/K1eu4PTp03jyySelZbp06RLi4+Nlp/9mZGQgIiICLVu2xMcff1ypk65Kly5d8NFHH+H69et47733kJCQIN2zBzCcmhgfH4/PPvvM5lOJxS10k0SlmTrKCxcuSGnWBsSRkZFwcnLCrl27sG7dOowaNQpOTk4ADDufu+66CxkZGdJfZmYm8vLyZDv3ittpixYtZPNw48YNm+6nUN1ymdcHoEFulOrv7w+VSoWzZ8/Klj83NxcjR45EcXExoqKiMGbMGFy+fBlZWVl47bXXKq2Ttly+aM6838rPz0d6ejpatWplsezQoUOh1+uRlJSE1atX1/qShdLSUhQVFUn3l7ld+66KVCpVnfuQiqcHp6SkSPuZiqrbJ5PtrPVN3333HWbOnImVK1dKeYMHD67ztlmxb3VycqrT9fBxcXHYvHkzUlJS8Omnn+Lpp5+udV3mKm5jubm5OHv2rE3bb/v27bFnzx6kpaXh9OnTcHZ2hp+fX7U/uNmyHdk65lyxYgW6du2KkJAQWfovv/yC6Ohoadt68MEH0bNnT+zZs8fqMinF398fTz31lGwdzMrKkl3KW5sbqbZq1UrWr5jGs1XtB6h+NXT/olarK03r7+8Pd3f3SvOQm5uLsLCwGrdhsnjxYhw+fBgHDhxAVlYWMjMzodPpZO1bqrMuY42K9Vnbblq0aGFxv2qLuoxdLDHv25QYu1TH/Dup7XFXdaZMmYLo6Gj07NmzUmC3vp/ud9sFX3x8fPD444/jmWeekQYG586dkwbRTz/9NFavXo3ExETZjj0kJAT33XcfYmNjkZ6eDiEETp48KftFuypxcXHYtWsXEhMTUVRUhIKCApuunW/Tpg1atWqFJUuWSDeV69u3LxYtWoSwsDDZL5aWduQ1mR4A5s2bh+vXr0t3pY6MjJR+bXjooYeg1+uxYcMGqa5+/fph0aJF6Nevn9Vl6d69O1JSUnD8+HGcOHFCuuZv7dq1mDlzJgAgOjoaP//8MzZv3ozi4mIkJibi2LFjsmt7q5KSkiJ9F//3f/+HCRMmICYmRoqc1qXu+Ph4vPjii9IN3FJTU3Hy5Em0bt0aFy9elC2Tn58fFixYIF33nJaWhl69eqFjx45Yv369zR1/cXExPvzwQ+m6Up1OBzs7O9jZ2QEw/Iowffp0fPnll7Idi8mePXuQmpoKwNAJPfPMM/Dx8bFY9k7VokUL9OnTBy+++CJycnKQlpaGefPmVTuNWq1GdHQ0li1bhu3bt8tuYjt48GAUFRVh4cKF0oA5NTUVO3bsqLbOcePGYdGiRUhJSUFBQQESEhLqdIA7btw4bNmyBYcOHUJZWRk2b95cb2c8VTdfPj4+GDNmDOLj46VHQGZlZWHHjh3Iz89HUVERioqKoNPp4OjoiNOnT2P58uV1nqc333wT58+fR0FBAWbOnInAwECEhoZaLGtvb4/x48dj6tSp+PPPPzF69Gib2lixYoW0Pf3bfLmGAAAgAElEQVT111+YPHkyXFxcpHul3I5915EjR3Dq1CmUlpaisLAQ77//PpKSkqQzvQDDzQFreiPnHTt24MCBAygrK8OmTZtw9OjRStflm6tqn0y2s9Y36fV62Nvbw9vbG0II7N69G59//rmsjpr2SUIIJCQkICcnB9evX8ecOXPqfNZSly5d0LFjRwwfPhwPPPCA7EEA1TGtw0VFRRBCoLCwEIWFhVL+xIkTsWLFChw/fhz5+fn497//jbZt26JHjx5W6/7tt9+Ql5eH0tJS7Nu3D/PmzZNuUg4Yfi01ne2TmpqK+Ph4hISEoG3bttXWa8uYs7i4GOvWrat01gtgGLMlJiZKffGRI0dw8OBBWZBGrVZLN3ZvCM888ww++ugjfPbZZygpKUFpaSnOnDmDpKSkGtdlvj6OHz8er7/+Os6ePYvi4mLMnz8fpaWlGDRoUH3OPlWhofsXHx8f2NnZyQ7OQ0JCEBwcjClTpiAjIwOA4QyKzZs312nZcnJy4OTkBE9PTxQWFmLu3LnIysqyOl1txxqWWNtuRo0ahSNHjmDz5s1SP2Rt3GlSl/GFtb5NibELYP34xpbjrtqMXQDgtddew9ixY9GzZ89anVRhq9su+AIYbvjXtWtX9O7dGxqNBkOHDpVOe+zfvz/UajW0Wi369u0rTaNSqfDpp5/CxcUFXbt2haenJyZMmCB1NBWjXubv77nnHuzZswfvvPMOmjZtCn9/f9kNxqoTERGBgoIC6VfQiIgI5OTkVLrDf1VRt5pMb1qh/P39UVJSItspOzo6okePHnBxcZEeHVhVXZaYngRg/qdSqeDt7S2dgta2bVts27YN8+bNg06nw6uvvoodO3bITl2uyqlTpxAWFgZ3d3cMGDAAAwYMkD0Bpi51L1iwACNGjMDQoUPh4eGB8PBwnDt3DiqVqtIy2dvbw9PTE56engAMB21nzpzBli1boNVqpWfSv/rqq1bb3bx5M+6++25pHZ07dy569uwJAHjuueeQk5OD8PBw2bPuTQ4ePIjQ0FDpiSJZWVnYu3cvXF1drbZ7J9m4cSMKCgrQqlUr9O7d26adwvjx45GUlIS2bdvKBrIuLi74+uuvcfr0aXTo0AE6nQ6RkZGym4tZ2k4TEhIQGRmJ0NBQtG3bFi1atEDz5s2lM2psYV5vr169sHTpUsTExKBJkybYs2cPoqKialRfVfNrLbq/cuVKdOjQAX369IFWq0VwcDC2bNkClUoFNzc3vPvuu5g+fTo0Gg2mTJki3dTb1votzV9sbCyGDRuGpk2b4uTJk9i5c2e19cTGxuL48eMYOXKkTTdMBwxPVDJtT/fccw+uXbuGffv2wcvLC8Dt2XclJydj6NCh0Ol0aNmyJRITE/HZZ5/Jnvh18eJFad9iC5VKhQkTJmDx4sXQarWYP38+tm3bVu2yVLVPvtPUdFs0Z61vevjhhxEdHY1u3brBx8cH27Ztw7Bhw2rdHmA4+Bg0aBC6dOmCu+++G+3atcPixYtrVJ+lMnFxcTh27FiNfkmeP38+XFxcMGnSJJw/fx4uLi6yfeGYMWPwwgsvYNCgQfD19cWZM2ewa9cum+Zx27ZtCAgIgFarxQsvvIClS5fKzh7bunUrOnXqBA8PD3Tv3h3e3t7YtWuX1XqtjTlNbRcWFloMXr7xxhvo1KkTQkNDodVqMW7cOEyfPl0qe/HiRTg4ONTo5tW16Z/NderUCZ999hmWLFmC5s2bo2nTpoiJibF6A2JL7ZqnTZ8+HaNHj0b//v3RrFkzHDx4EF999VWtbhNwp7qV+hdnZ2fMmzcPo0aNQpMmTbBw4UKoVCrs3LkTQgjcf//90Gq16N69u+yHblvbMC/3/PPPQ6vVws/PD0FBQXB3d7f5kp7ajDUszaO17SYwMBBbtmzBnDlz4OnpiaVLl9r8Q0VdxhfW+jYlxi6A9eMbW467ajN2MfnPf/6DqVOnok+fPnV6ely17Yk78DqF8PBwDBgwADNmzGjsWSGiO0xeXh48PT2RlJRUb2cqde/eHUOGDJHOMrtTREdHQ6PRyM6wyc/Ph6+vL/bv32/TE8rIsuTkZERFRUlPZaoPq1evxv/+979KAxruk8nk0KFDiIqKwpUrV+Ds7NzYs3PLWrNmDX755Re89dZbjT0rRLcljjVuTkqMXerbbXnmS3WSkpLw888/IzY2trFnhYjuAJmZmfjyyy9RUlKC7OxsTJkyBW3atEG3bt1qXefWrVuRl5eHoqIivP/++zh69CieeOKJepzrm19RURFOnTol3ZgNMJza/Oabb6JTp04cDNVRmzZt6n3w8ssvv8i+L4D7ZCpXUFCAN954AxMnTmTgpY5iYmIYeCFSCMcaNy8lxi717Y4KvoSGhiIqKgrLly+XTidX0sKFC6XToUx/pvfffvut4u3XNyWX51atuzobN26sst1NmzYp1i7dXMrKyjBr1ix4eXkhMDAQV65cwa5du6T7+9TG1q1b0bJlS/j4+GDFihXYsWMHAgMDb7l1buDAgVXOb3UyMjLg7e0NX19f6bre9PR0aDQarFmzBu+9956s/K3av9xO+5DQ0FAkJSVhzpw5srSG3CeT7Squd6Y/pe6zsX37dnh5eUGv10s36TepbT9hi1u1bqJbWUP3L/WpscYalhw+fLjK9qzd/oBjl8ZzR152RERERERERETUUOr+bKabVH0/ForoVsBYasNjX0N3GvYzjYN9Dd1p2Nc0PPYzdCdqyL7mtg2+AIDfhMtwNbuwSms8y1/rYPivcSjvYHTGy4vdHcvLuxpfuxofIuJudgmyszHNxdH0vvxLczU+4dnZrC7Tg0icjOVczMo7OZQBABzUpQAAe1WxlGdfcgMAoC6+IaWpCvMN/wsM/5Gnl/JEQZ7hxY18+XsAZca0MrPyUpr0v7ydkly9LK00P1/KK71RYPifV55WVlxifGFYNpVd+YevdjV8eHYupv/lj8G2M97B2s69/G7hdi6GNHWF/wBg52YopzKmqZzdpDxLaXAznOIrnA15wqk8r8zRMB/F9oa0YpR/acVlhs2jsLh8OW4UGl4XFBrWncKi8mYKjE+2zL+hMpY1yytCpbTcAmN5Y16eeZ4xLdOYpi8uX1+yjauHvqy8fJEArq5qCWocXvcegru6/DtyNr52Mv53tDPb3tXG7d0szd5YzvTfPM/OmGZnnM7OfDo7UaFMeZ7aVKddWaU0tXE6tVl5O2M5qYx5XaZ2KpQBAJXF8mVVtqNSV8izs5CnNvUhletUVfg8zF/bW0ir+N/mPDtDf2ynMv/8bCivtlS+VPbfUp7abDp7u5JKaeoKddgZy1jKU6vL8+zUJbI0O3Wx2XTGNLtCs7QiY7lC4/sbZnk5sG9V/p4agfssQGU2uFAZBzRqB/l7oLycymyoZ3qtMl32aH75o+m1YR9mvkdpZhyYasoM66SHKF+X3coMr93Lytc7F2M5J2OeU1lZ5Txh+O9oNuh1NKY5G9McRPl0jjD2pyhPczCmORvTTO8Nr8tk0znJpiuT/bd3NJsHF+NYzKlynp2jcTrn0kppauN/OJbnwVTOyUKeKc3Z+Lk5meWZyjlaSDOVdygxy6uQ5li+ncOhWJ5naTp7s3aMY1LYl8nfA4C98bNwEPL3AGBa9ewr/AcAe+N422zcLaVV/A8A9mqotOdAjcdRVfm1g4Wv0fRa1pNUSDP/ak156grvzcurzdLUqLp8xTTze2nYklbTusyXUV0hzWJ5C3WZXpt/JrWty9J82fL51rQuS99LxbqqmwegfHltabu6ebZWvuLnW913Zpq2xSk0qDvqni9ERERERERERA2NwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRghh8ISIiIiIiIiJSEIMvREREREREREQKYvCFiIiIiIiIiEhBDL4QERERERERESmIwRciIiIiIiIiIgUx+EJEREREREREpCAGX4iIiIiIiIiIFMTgCxERERERERGRglRCCNHYM6EElUrV2LNA1OBu0835psa+hu407GcaB/sautOwr2l47GfoTtSQfc1tG3whIiIiIiIiIroZ8LIjIiIiIiIiIiIFMfhCRERERERERKQgBl+IiIiIiIiIiBTE4AsRERERERERkYIYfCEiIiIiIiIiUhCDL0RERERERERECmLwhYiIiIiIiIhIQQy+EBEREREREREpiMEXIiIiIiIiIiIFMfhCRERERERERKQgBl+IiIiIiIiIiBTE4AsRERERERERkYIYfCEiIiIiIiIiUhCDL0RERERERERECmLwhYiIiIiIiIhIQQy+EBEREREREREpiMEXIiIiIiIiIiIFMfhCRERERERERKSg2zb4kpqaCrVajYsXLwIAFi5ciMcee6xR5+nw4cNo0qRJg7QVExODiRMnVpm/bt06BAUFNci8kO3UajW+++67KvPDw8OxYMGCBpyj24N5f3Cn9QW1UdP5u1n6E2vbDxFVZr5f8fDwwJEjRxp5jojodlfTsZi145qGcOjQITg4ODTqPNCt77YNvgCASqWSXickJGDnzp2NODdAjx49kJGR0ajzYM7886mrPn36wNnZGRqNBh4eHtBoNNizZ4+UP2fOHDg4OMjyExISbKr7rbfeQlhYGNzc3NC+fXuLZRYtWoSWLVvCw8MD/fv3R3Jycp2XadasWWjbti20Wi2aNWuGESNG4NKlS1L+unXrYGdnJ1umJ598ss7tkjJM6zv7AutqM3/12Z8QcO3aNTRp0qRSnxcTEwNHR0dZv/Pee+/ZVOeRI0fQu3dveHp6onnz5oiOjpZ9z3Wp25qPPvoIwcHBcHd3h5+fHxYuXCjlDRw4UGpPo9HAzc0NarUaO3bsqJe2yXY5OTl44IEHGns2bnr79u3Dgw8+CA8PD/j6+mLy5Mmy/A8//BDt2rWDu7s7HnzwQfzyyy821ZuWloaRI0fC19cXXl5eiIiIwK+//irlKzXu+N///of7778fOp0OzZs3x6hRo2TjnYULF8q2UQ8PD6jVajz33HN1bpvuTDfDWKw2braxzoABA+Dn5wetVgt/f39MmzYNRUVFUv6tOGYw72s0Gg2cnZ3h4OAgtW2tv7rZ3dbBl4YihEBpaWljz4aiiouLq81XqVR4+eWXodfrkZOTA71ej4EDB8rKhIeHy/LNB9/VadGiBWbMmIGXXnrJYn5iYiIWL16M3bt3Iz09HXfffTeGDBkCIYRtC1eF6OhonDhxAtnZ2UhJSUGrVq0watQoWZnAwEDZMiUmJtapzfpk7Tuj+ncr9AVcLxpPTdaPuLg4hISEWMwbP368rN+ZNGmS1frKysrw6KOPokePHvj7779x5swZXLlyBc8++2yd67Zm/fr1eOGFF7B06VLo9XqcPXsWQ4YMkfL37NkjtafX67F06VJ4eXlV2ofQ7a20tLTO++2GcPDgQTzxxBN48cUXkZmZicuXLyM2NlbKP3z4MJ555hmsWLECmZmZGDZsGAYOHIjc3FyrdcfHxyMrKwt//vkn0tLScP/992Pw4MGyMkqMO4qLi7F8+XJcv34df/75J1xdXWXtJiQkyLbRX375BWq1GuPGjatz23R74lij7mwZM7z++uu4cOECsrOz8fPPP+Pnn3/G3LlzZWVutTGDeV+j1+vx+OOP4+GHH5bOyLbWX93sbpvgS1paGoYMGQKdTocOHTrgiy++kOXPmTMH/fv3BwC88847uPfee2X5ycnJsLe3ly5TunTpEp544gk0b94cLVq0QFxcnGzHqVarsWzZMnTr1g3u7u44evQoSkpKMHXqVDRt2hR+fn5YtGgRgoKC8OGHHwKofLpaTEwMoqOjMXHiRHh6eqJVq1Z4//33ZfO1atUqtGvXDjqdDtHR0Rg3bhyeeuopmz6T/Px8REdHQ6vVIigoCOvWrauy7BdffAE/Pz/pbJU2bdpg3rx56Nu3LzQaDbZv3261PaUGTcOGDUNUVBRatGhhMX/lypWIi4tDcHAwnJ2dsWDBApw/fx6HDx+2Wvdff/2F2NhY+Pv7Q6fTISQkBGfPngUAtG/fHh4eHgAMg0KVSoU//vij/hasCj/99BPuvfdeaDQa9OvXD+fOnbNYrqysDPHx8QgLC0N6erq0fm3YsAGBgYHw9vZWfF5vVtX1B3PmzEFkZCSAO6MviImJwdixYxETEwMvLy8899xzuHHjBoYPH47mzZtDq9UiJCQE+/btk6apzfwBhkGAn58fmjVrhmnTpskGDb/++iv69euHJk2aoF27dnjllVekPuPZZ59FXFycVLZXr14ICAiQ3i9atMjmHWt1209ubi6io6Ph5eWFNm3aYP369XBwcEBSUhKysrLg6uqKEydOyOrr1asXXnnlFQCGAPILL7yAYcOGQaPRICgoCF9//TX279+PLl26QKfTYfjw4cjLy5Omt7R+WLN+/XqUlpbW65l02dnZ+PvvvzF+/Hio1WrodDqMGDGi0vLW1oULFzBixAj4+fmhSZMm6NmzJzIzMyGEQEJCAmbPno0+ffpArVbDzc0NnTp1qrKuFStWYPz48XB0dKyXeSPbmV+6Z7qc8K233kKrVq3g5eWFSZMmyfb11vrHl156CYGBgfh/9u47PIpq/QP4dzedkE3dUFNIoXekCiRAokiQXhQhhF5+6JUWARVBFLwgF0RFQUTwAoJAEKRITWgCSpEuF1KAACaUhISQuvv+/kgyZJKQTcAVlO/nefJsZs6ZM2Vnzpx5d+aMg4MD/P398cknnyhply9fhlarxdKlS1GnTh2UL18eN2/eLHH5tmzZgjp16kCn06FLly4YN24c2rVrp6RfuXIF3bp1g16vh5eXF8aOHYvMzEwAwLx58/Diiy8qeUNDQ2FnZ6ekf//99yXul/mmTJmCUaNGoXv37rC0tIS1tTUaNmyopC9ZsgQ9e/ZEhw4dYGVlhYkTJ8LW1rZU7ajo6Gj06tULOp0OlpaWGDJkCK5du/an3CmZlpaGCRMmwNfXFzqdDnXr1sXBgwcBAG+99RZatmwJa2tr2Nvb46233sKZM2eQnJxcbFmLFi1Co0aN0KRJk8deLvpnKHzd8NFHHyEwMBB6vV4JpsfExCj5C7bF8qefNWsWgoKC4ODggPr16+PQoUOqeZi6rlm/fj0aNmwIZ2dnNGrUSHX3ZIMGDbB69WoAQEZGBmxtbREWFqakh4SE4OOPPy7Vun777bfw9vaGm5sbBg0ahPv37ytpFy9eRGBgIBwdHdGoUSMsWLAAWm3u5fZPP/0Ed3d35OTkKPnv3bsHBwcH5Vgsa5uhfv36SnvNaDRCq9XiwoULpVqPkjypNkNht2/fxvr16zFq1ChlXFnrq6eO/EO0b99eevToIampqZKQkCCtW7cWrVYrly9fFhGRadOmSXBwsIiIJCUliZ2dnZw8eVKZfurUqRIUFCQiIhkZGeLn5yfTpk2TzMxMSU5OlpCQEBk8eLCSX6PRSIMGDSQ2NlaMRqNkZmbK9OnTpVatWhIXFycZGRnyxhtviLW1tSxfvlxERKKiosTKykopIywsTMqVKyebN28WEZGIiAixsrKSK1euiIjI3r17xc7OTqKiosRgMMh3330n1tbWMmjQIJPbIywsTKytrWXVqlViMBhk165dYmdnJ4cOHRIRkWXLlom/v7+IiHz55Zfi6ekpJ06cUKb39vYWT09PZRtlZGSUOL/AwEDR6/Xi6uoqdevWlVmzZkl2draSPm3aNHFwcBC9Xi8+Pj4ybNgwuXnzpsn1KKjgMhfk5OQkGzduVI1r0KCBfPrppyWWZzQapUWLFtKrVy9lWU6fPi03btxQ8qxatUocHR1Fo9GItbW1fP7556rlsbW1lUqVKomnp6e88sorEhsbW6Z1Kkyj0UidOnUkJiZGMjIyZMyYMVK7dm0xGo0ikrudP/zwQ0lNTZVOnTpJ9+7dle8mKipKNBqN9OvXT1JSUiQ9Pf2xluXvrKT64FmsC2xsbGTt2rViNBolPT1d7t27JytXrpS0tDTJycmRjz/+WHQ6ndy6deuRlm/ZsmViZWUlY8aMkczMTImJiZHq1avLrFmzRETk7t27UqFCBfnwww8lKytLzp8/Lz4+PvLxxx+LiMimTZvE19dXRETu3bsnDg4O4uXlJRcvXhQRkeDgYJk3b57JdTV1/AwaNEjatGkjt27dktTUVOnbt69otVrZu3eviIgMHDhQxowZo5R34cIFsba2VuqEwMBAcXd3l19//VWMRqNMmTJFKleuLH379pXk5GRJSkqS2rVry8yZM1XLVHD/yMrKKnEdbty4IV5eXnL16tVi67ywsDBxcXERV1dXqVGjhkycOFHu3btnctuIiIwaNUrCw8MlMzNTEhISpF27dvLee+89dtn3798XHx8fef311yU1NVUMBoMcOXJE7t27J7///rtoNBqZNm2a1KxZUypUqCAvv/yyXLp0qdiyfv31V9Fqtcp3T+aXf14Ryd1fDx48KCIPjut33nlHsrKy5NKlS+Li4iKrVq0SkdLVjytXrpQ//vhDREQiIyPFzs5OduzYISIicXFxotFoJCgoSBITEyU7O1s5Votz6dIlsbGxkTVr1ojBYJDdu3eLTqeTdu3aiYhITk6O1K1bV0aNGiXp6ely/fp1adq0qXJMnzp1Suzt7ZVjsHLlylK9enXZuXOniIgMGzZM/vWvf5W4rdLS0sTCwkImTJggjRs3Fjc3N2nXrp0cPXpUydOwYUP55JNPVNN17dpVxo8fX2LZIiIrVqyQF198UW7evCnp6ekybtw4CQgIUNIfp93Rp08fadu2rdIujo6Olujo6GLzfvbZZ+Lp6VlsWmZmpri5ucmSJUtKNV96NhS+bjh16pRERUVJdna2pKSkSJ8+faRly5ZK/oJtsfzp/f395fz582I0GmXs2LGq85+p65qDBw+Kra2tbN++XQwGg2zZskVsbW3ll19+ERGRcePGyZAhQ0REZPv27eLv7y9Vq1YVEZGsrCwpX768/PbbbyWuY347u3fv3pKamiqJiYnSqlUrGT58uIjk1kE1atSQN998UzIzMyU2Nlbq1q0rWq1WRHKvO6pVqybr1q1Tyly0aJHUrl1bGS5rm0FEZPTo0WJvby8ajUZcXV3l8OHDqu32d2ozFDZnzhzx9PQs8dxQUn31NPpHBF+uXbsmGo1GdQLauXPnQ4MvIiJ9+/aVN998Uxn29vaW7777TkRE1q5dK35+fqp5HD16VGxsbJQvX6PRyIoVK1R5/Pz8ZNmyZcpwenq62NjYlHjB1blzZ1UZer1eNm3aJCIiQ4cOlYEDB6rS27RpU+oLrrZt26rG9e/fX0aMGCEiuSdwX19fCQ8Pl7p168rVq1dVeb29veWDDz4wOZ98hw8fluTkZDEajXLkyBHx9fWVKVOmKOnnzp1T5hEXFyedOnWSVq1albr8/GUuLvhiYWEhUVFRqnEBAQFKY/JhfvnlF7G2tpbU1FST805ISJCZM2eq5hMbG6tcICQkJEhYWJj4+fnJ/fv3S7M6xdJoNPLNN98ow/fv3xcbGxvl5BIYGCijRo2Shg0bqvZfkdz9S6vVSnx8/CPP/5/AVH3wLNYFHTp0MJnPzc1Ntm3b9kjLl39BUDBIu2TJEqlRo4aI5F6AFT4xLlq0SGrWrCkiIikpKWJtbS2xsbGyZcsW6dChg4wcOVIWLlwomZmZUq5cOTl9+rTJdSjp+DEYDGJjY6M6hqOjo0Wj0SjBlwMHDoiLi4tkZmaKiEh4eLh06dJFyR8YGKgKzpw7d060Wq0cO3ZMGRceHi49evRQLVPh/aMk3bp1k4ULF4pI8XXe8ePHJTExUZl/s2bNpF+/fqUqe/fu3eLn5ydWVlai1WolKChIFaR91LK///57qVy5shgMhiJpBw4cEI1GI/Xr15fLly9Lenq6jB49WmrVqlVs/qFDh0r79u1LtT705ygp+OLo6Khq9Pbu3VvGjRsnIqWrHwvr1auXvPXWWyLyIPhy4MCBUi3nBx98oApEiIgMGDBACb7kX3wV3Ke3b98u5cqVU4YrVqwokZGRcvbsWfH19ZWPPvpIwsPDRUTEx8dHfvzxxxKXIT4+XjQajVStWlXOnDkj2dnZMnPmTHF3d5e7d++KiIivr6+q/hfJDewOGzbM5DrGxMRIUFCQaDQasbKyEh8fH7lw4YKS/qjtjsTERNFoNHL+/HmTy3Dw4IQ92+IAACAASURBVEFxcHBQzgeFrVixQhwdHSUtLc1kWfTsMHXdcPr0adFqtcrxWVzwZe7cucrw2bNnRavVSkpKioiYvq4ZPny49O/fX5X+6quvysiRI0VEZOvWreLt7S0iIhMnTpQZM2ZIzZo15dy5c7J3717R6/Um1zG/nV2wfZkfBBIR2b9/f5G20Ndff60EX0Ry67GOHTsqw82bN1f9uFTWNkNBZ8+elbffflv5YUzk79dmKKx69eoyY8aMh6abqq+eRv+Ix47i4+Oh0Wjg6empjKtWrVqJ0wwaNAirVq2CwWDA7t27cffuXXTv3h0AEBcXh8uXL8PFxUX5CwoKgoWFBf744w+lDC8vL1WZ165dUy2Dra0t9Hp9ictRqVIl1bC9vT1SU1OV8grPo/BwSQretp8/HB8frwwnJiZi4cKFmDBhAqpWrVpk+rLMq3nz5nB0dIRGo0GzZs0wY8YMrFixQkmvVauWMg8vLy8sWbIEhw4d+lM6xnVwcMDdu3dV45KTk6HT6UqcLi4uDu7u7ihfvrzJebi7u2Po0KHo3Lmzclubt7c3/Pz8lPSvvvoKN27cwOHDhx9xTXIV3O52dnbQ6/Wq723Dhg34448/iu2wWKvVPvTxrGdFWeuDZ7EuyMjIwJgxY+Dr6wsnJyc4OzsjOTm5xFv+S1o+IPcYsLGxUc0zf7+Nj48vsry+vr5KB2kODg5o2rQpdu7ciV27diE4OBhBQUHYsWMHDhw4oNwiXxoPO35u3bqFrKws1fdSeJmef/55VK5cGevWrYPBYMC3335b5O0KBbdDuXLlAAAVK1ZUjSu4XYqbz8OsWrUKt27dUm6vlWIe5WzUqJGyL9WqVQvz58/HunXrTD5ff+nSJbz00kt49913kZ6ejuTkZPj4+Kgew3jUsuPi4uDj46PcWl1Q/qObb775Jjw9PZVHQ3///fcij3GmpqZi9erVqtuL6clyd3dXdTBZ8LgvTf24YMEC1K9fHy4uLnB2dsbmzZtV9YxGoyn18WGqHoyPj4der4etra0yztfXFxkZGbh16xYAoH379qp6pkOHDtixYwdiYmIQHx+PwMDAEpchf38ePHgw6tSpA0tLS0yePBnZ2dnK41qP2iYREQQFBaFGjRpITU3F/fv3MWXKFLRu3VrZZo/a7oiLi4NGozH5Vrr9+/fj5ZdfxpIlS9CxY8di8yxevBj9+/dX6j+ifAWPx5iYGPTs2RNVq1aFk5MTWrduDQAltjMKnkvt7e0BQHU+Lem65urVq0XaegXbGQEBAbhx4wYuXrxYpJ2xa9cutG/fvtTrWbAd4e3tjczMTNy6dQvXr18v0hYqXGcNGTIEUVFRiI+Px+nTp3Hy5EmEhoaq8pSlfVdQ7dq10aBBA/Tt21cZ93drMxS0Z88exMXFYciQIcWml6a+ehr9I4Iv+Rebly9fVsaZuqgPDg6GjY0NNm3ahOXLl+OVV15RDhYvLy/UqFEDd+7cUf6SkpKQlpamangX3mmqVKmiWob09HSTzy+bWq+C5QFQ+qEojbi4uCLDBYMsFStWxI4dOzBhwgRVoCSfqYPClOIuHArSaDR/Sj8xDRo0UL1J4N69e7h48SIaNGhQ4nTe3t5ITEwsVSd4QG4HT2lpabh+/XqJ+R53nQp+b/fv38fNmzfh4eGhjHv99dcRGhqKNm3aFOnd+2nrhf1JKGt98CzUBYWXb+7cuThw4AAiIyORnJyMpKQkODk5Pda+m5iYiIyMDGU4NjZWqW88PDyKLH90dLRqv+7QoQN27dqF3bt3Izg4GO3atcPevXuxfft2dOjQodTL8bDjx83NDdbW1qrlKLxMADB8+HAsWbIEmzdvhqWl5Z/S6Wtp69KdO3fi5MmT0Ov10Ov1eOONNxATEwN3d3ecPn26xGlNfXcnT56Eq6srQkNDYWFhAQcHB7z++us4cOAAUlJSHqtsb29vxMbGFpuvRo0asLOzK7a8wvXVf//7X5QvX14JftLTzVT9+PPPP2PSpEn46quvlLTOnTsX2U9Ke3yYqgc9PDxw8+ZNVT0UHR0NW1tbpQ+0oKAg7Nq1S7n4atKkCa5evYpVq1YpfSyURKfTFbkABHL35fz9uXCbBABOnDhhsk1y584dxMbG4o033oC9vb3S54vRaCzS90VhpTlGASh92hVn+/bt6Nq1K5YuXYo+ffoUm+fcuXPYv3//n9KpJv3zFDyWR44cCZ1Op/TFkd+nyeO0M0q6rvHw8CiSHhMTo7QzypUrhxYtWmD16tW4fPkymjVrhg4dOijB2KCgoFIvR+H2pY2NDdzc3FClShXcvHlT6UeqcF4g99orJCQES5cuxdKlS9GtWzelI9l8j3P9lZ2djUuXLpnM97S2GQpatGgROnfuXOTHP6B09dXT6h8TfAkMDER4eDhSU1ORkJCAGTNmlDiNVqtFaGgoFixYgA0bNqg6ruzcuTOysrIwa9Ys5cL82rVrJl97OWDAAMyZMwdxcXHIyMjA5MmTH6uSGTBgANatW4e9e/fCaDRizZo1Zbqr4vDhw1izZg2MRiP27NmDiIgIVedSANCyZUvs2LEDEydOfOTXg929exdbtmxROpk8ceIEpk+frnoz0IYNG5Rfnq5du4ZRo0bhueeeg4+Pj8nyDQYDMjMzkZWVBRFBZmamqmIbPnw4Fi1ahN9++035pcjHx0eJsj/Mc889h8aNG2Po0KG4efMmRASnT5/GH3/8ARHB559/rlwwx8fH4//+7//g4+ODmjVrAsh9Q8e1a9cA5DaaRo8eDb1ejxYtWijz0Gq1SierpTVv3jzExMQgIyMDkyZNgq+vL5o1a6bK8+9//xv9+/dHmzZtSmxMPYvKWh88C3VBYampqbCxsYGzszMyMzPx/vvvP3ZHZQaDAW+99RYyMjIQExODuXPnKvVNSEgIMjMzMWvWLGRnZ+PChQuYPXu26g0hQUFB+Omnn3Djxg00btwYLi4uqFatGhYtWlSmRtHDjh+tVot+/fph2rRpuHXrFlJTU/HOO+8UCQAMGDAAv/zyC6ZPn45BgwaZDGj+GQHkfPPnz8fvv/+OkydP4uTJk3j//ffh5eWFkydPonbt2gCANWvWKL+qX7x4ERMmTEDXrl1Ndk7bpEkTJCcnY9WqVTAajUhNTcWnn34KHx8f5Rf5Ry07JCQE1tbWGDt2LFJSUmAwGHDkyBGkpaXBxsYGgwYNwieffIL4+HhkZmbi3XffRd26dYu8Rnvx4sUYMmQILCwsHmn70V/LVP2YkpICS0tLuLm5QUSwZcsWbNu2TVVGWY6fV155BUeOHMG6detgNBoRGRmpqoubNWsGPz8/jB8/Hunp6bh+/TqmTp2qqtODgoJw/Phx7N+/H+3bt4dGo0FAQAA+/vjjUtczo0ePxjfffIPz58/DYDBg9uzZsLW1RatWrQAAw4YNQ0REBCIjI5GVlYXZs2cjKyvLZFDR1dUVNWrUwOeff4779+/DYDBg6dKluHfvHurXrw+gdO2O4uj1evTq1QujR49WLgajo6OVDsnXr1+PPn36YOXKlejatetDy1m0aBFatmxZ6jsR6dmVkpICe3t76HQ63Lp1C1OnTi1zGYXrh5KuawYOHIj169dj586dMBqN2LZtW5E2XYcOHTB37lwEBgZCo9GgXbt22L9/P44dO1bq41/yOpFPTU1FYmIipk+frty50qJFC3h6emLy5MnIzMxEbGysqpPxfMOGDcPSpUuxcuVKDBs2rMzbJd+FCxewceNGpKWlQURw4sQJzJgxQ/Wj0d+tzZAvISEBP/zwQ7F3wpa2vnpa/SOCL0Du7doZGRnw8PBAQEAABg4caHKasLAw7Nu3Dz4+PqpXetrZ2WHPnj04d+4catasCScnJwQHB6t6eC6uQT558mQEBwejWbNm8PHxQZUqVVCpUiXV7WemFCy3bdu2+OSTTzBo0CC4uLhg69at6N69e6nL69OnD7Zu3QpnZ2cMGzYMCxcuLPYE3ahRI0RGRuLDDz/E7NmzH7p+D5OdnY0PPvgAVatWhaOjI1599VX0798fM2fOVPKsX78ederUgYODA1q1agU3Nzds2rSpVOV/8MEHsLOzw8iRIxETEwM7OzvV7a79+vXD+PHjERISAnd3d5w/fx6bNm0yuQ4ajQY//vgj7OzslN7RhwwZojQit27dinr16sHBwQEtW7ZE+fLlsXPnTiUiHRUVhWbNmsHBwQH16tVDcnIydu7cqSzblStXYGVlheeff77U21Kj0WDo0KHo0aMHKlSogNOnT2Pjxo3KuhRcp3fffRdjx45FYGAgzpw5U+p5PAvKWh/80+uCwsaNGwdHR0dUrlwZ/v7+KF++vMlHNUtaPiD3l4yqVauiWrVqaNmyJTp16oSJEycCyP21eMeOHdi5cycqVKiAl156CWFhYRg7dqwyfcuWLSEiqrtcgoKCkJqaWupGkanjZ8GCBfD09ET16tVRv3595Q14Bbejk5MTevXqhVOnThW51bW477o09Uxp5X8n+X/Ozs6wsLBApUqVlIDEl19+qbw9pmPHjmjVqhWWLl1qsmxvb2+sX78e8+fPh5ubG3x8fHD16lVs3LhRyfOoZZcrVw579uzBlStX4O/vD71ej/DwcOXW4//85z9o3bo1GjRoAA8PD1y9ehU//vijatscOXIEZ86ceayGKD2agndtlGV/NVU/vvjiiwgNDUXTpk2h1+sRERGBHj16FJl3afn6+mLt2rWYOnUqnJycMG/ePISGhirHr4WFBTZv3oyrV6/C09MTLVq0QMuWLTFnzhylDA8PD/j6+irLC5S9npkwYQIGDx6M9u3bQ6/XY/v27di2bZvySNLzzz+PhQsXYujQoXB2dkZERAS2bdtWqkecf/jhB0RHR8PLywtubm744osvsG7dOuXOFVPtjpIsXboUDRs2REBAAHQ6Hbp164aEhAQAwMSJE5Geno6+fftCp9PBwcEBOp1O9chzRkYGVqxYwccCqViFj+V58+Zh3759cHR0REBAAF5++eUyTV/cuJKua1q1aoXly5dj/PjxcHFxwaRJk7By5Uo0bdpUmT7/WM8/9zs6OqJmzZrw9PQs9o624lhaWiIkJAT16tVDrVq14Ofnh7lz5wLIrYM2bdqEY8eOQa/Xo0ePHggNDS0SjHjhhReg1Wrh6OhY5HGnstSJIoLZs2fDw8MDTk5O6Nu3L7p164YvvvhCyfN3bDMAwLJly+Dl5VVsvVya+uppppE/82c7UklLS4OzszP27dtn8leJ0mrVqhW6dOmCSZMm/Snlkfl88803OH78OD799NMnvSj0hLEueDpduHABtWvXxrVr11TPmk+fPh2HDh1SvaKciJ4+/fr1g06ne+Q7d4mIzGnRokWYN28efv/9d9X4du3aoWPHjnjrrbee0JLRk/KPufPlaZCUlITt27cjJycHd+/exeuvv45q1aqpoq5ltX79eqSlpSErKwuLFy/GsWPH0Lt37z9xqclcBg0axMDLM4p1wdMpNjYWhw4dgtFoREJCAsaNG4eAgABV4CUhIQFfffUV3nzzzSe4pERUnB9//BFJSUkwGAzYuHEjIiIi0K9fvye9WEREAICDBw8iJiYGAHDq1CnMmTOnSB21b98+HD16VPXoNT07GHz5ExmNRrzzzjtwdXWFr68vrl+/jk2bNj3W8+vr169H1apVodfrsWjRIvzwww/w9fXFqlWrlNus8v/yh7/77rs/ca1yderU6aHze1bLJnqYf3Jd8CQ97vGckZGB4cOHw8nJCQ0aNED58uWxcuVKJX38+PHw8/ND165dzdZzft26dVXLn78O9erVe2bLJspX+PjO/wsJCQGQe9FSvXp1ODs74+2338aiRYvQtm3bP3UZRo0a9dB65nFva/+7lk30rDBVB5ly9epVtGvXDuXLl0fXrl3Rs2dP1R3KzZo1Q/fu3fHZZ5/B1dXVZHl/1/M62wwPx8eOiIiIiIiIiIjMyPJJL4C58JW79CxiLPWvx7qGnjWsZ54M1jX0rGFd89djPUPPor+yrvnHBl8AoOL0LFgaspRhS2Pu/xZ547QF0iwMmUXGafLya5T8D15vnD8Oxmz1MABNfr4C4/LzKeMKlAVj/rhsdV4AopRVYFyh/FJgPpI3rfKpmi5/XGaBcTnFTgcAxrxyH6TlPHQ6ANCIAQCghag+AcBKk/u/ZV6lblmgcrfMe/jNusB77S01+dPl5dc+yG+dN85KW7Ss4vLbFBpnVXDeef/blFBWwfzWhcqwUuVXr0dxaQXH2ZRYlka17MWlqZZLo0HljZGgJ8O2fwZ0NveUYWvr3NflaaxzxxmtH7w+L9sm97V8OVYP8mvz/re1zP10sEp6ULZFKgDAyjIFAGBhkVJgutu588nLY2HxoEwr7X0AQDmLB/WDrdYIALDTSt7wg2O0XN7/NloUSbPJO37tLPLyFGib2eTlsy4uf3Fp+eM0+ctgfGha/icA2GlyT1dWyH2ziZXxwds9LAy5/2uzHZRxmmzb3M+cvDcZ5Tx4o5EmKzcN2dZ5eawerFDeOGTlfarSrNSfBf/PzM0v2QVOq/n/5+WRjAfTSVbe/1mWecMPHkmTDG1eWQ+2jWTn1cfZGQAAY3bqgzRD7ndtzMn7zBsGAENePiUtp0Ba3v+GrJQC+fPGZd/LS3swH0NGEmo/OA3QEzBs8TxoCxwXFpr8823uvqJOKzouP1/+dPl5ctNElZafFwAsNVJsHgCwyMtnqRon6s8CaVZ54yyVzwfyx1nJw9MKPrxpUaisAqd+JS2/ZaHaDhr1Ohe83tRopNBngRlqYHpcgUTlQlb51BZI06rHFUiDxuLh47RW6mFV/txP0Vg9NE09nfnKkmLLLFqWkk9jqUrj66yfoCZpgF36g2GbDPWndYE027z2jXXGg3FWeelW+fkftIFgmXsNorHMTXOxeHBN4mSZe/6xLTDOOu9/y/xPywfnMIu8MjQW6s/c8nPnKRYP8iPvf03ep6XlgzaTjTYz7zP3WsauwKFnm9euL2fx4Ni2zTs289vytgWuYey06jQb1XWEVpWnuHzWqrLyxhWaX+44TZGy8scp10oocP1gyKsT8z41hgd1oibHmPdZIAiRZVCPy3lwTsj/X5NlLCYtL3+BNozyf3Yx+bNFNT/1dMWUlakuS7IKLnPe/xl5aQUut5H3vxTYVZEOWP6GvxT7fCEiIiIiIiIiMiMGX4iIiIiIiIiIzIjBFyIiIiIiIiIiM2LwhYiIiIiIiIjIjBh8ISIiIiIiIiIyIwZfiIiIiIiIiIjMiMEXIiIiIiIiIiIzYvCFiIiIiIiIiMiMGHwhIiIiIiIiIjIjBl+IiIiIiIiIiMyIwRciIiIiIiIiIjNi8IWIiIiIiIiIyIwYfCEiIiIiIiIiMiMGX4iIiIiIiIiIzIjBFyIiIiIiIiIiM2LwhYiIiIiIiIjIjBh8ISIiIiIiIiIyIwZfiIiIiIiIiIjMiMEXIiIiIiIiIiIzYvCFiIiIiIiIiMiMGHwhIiIiIiIiIjIjBl+IiIiIiIiIiMyIwRciIiIiIiIiIjNi8IWIiIiIiIiIyIwYfCEiIiIiIiIiMiMGX4iIiIiIiIiIzIjBFyIiIiIiIiIiM2LwhYiIiIiIiIjIjBh8ISIiIiIiIiIyIwZfiIiIiIiIiIjMiMEXIiIiIiIiIiIzYvCFiIiIiIiIiMiMGHwhIiIiIiIiIjIjBl+IiIiIiIiIiMyIwRciIiIiIiIiIjNi8IWIiIiIiIiIyIwYfCEiIiIiIiIiMiMGX4iIiIiIiIiIzIjBFyIiIiIiIiIiM2LwhYiIiIiIiIjIjBh8ISIiIiIiIiIyIwZfiIiIiIiIiIjMiMEXIiIiIiIiIiIzYvCFiIiIiIiIiMiMGHwhIiIiIiIiIjIjBl+IiIiIiIiIiMyIwRciIiIiIiIiIjNi8IWIiIiIiIiIyIwYfCEiIiIiIiIiMiMGX4iIiIiIiIiIzIjBFyIiIiIiIiIiM2LwhYiIiIiIiIjIjBh8ISIiIiIiIiIyIwZfiIiIiIiIiIjMiMEXIiIiIiIiIiIzYvCFiIiIiIiIiMiMGHwhIiIiIiIiIjIjBl+IiIiIiIiIiMyIwRciIiIiIiIiIjNi8IWIiIiIiIiIyIwYfCEiIiIiIiIiMiONiMiTXghz0Gg0T3oRiP5y/9DD+anGuoaeNaxnngzWNfSsYV3z12M9Q8+iv7Ku+ccGX4iIiIiIiIiIngZ87IiIiIiIiIiIyIwYfCEiIiIiIiIiMiMGX4iIiIiIiIiIzIjBFyIiIiIiIiIiM2LwhYiIiIiIiIjIjBh8ISIiIiIiIiIyIwZfiIiIiIiIiIjMiMEXIiIiIiIiIiIzYvCFiIiIiIiIiMiMGHwhIiIiIiIiIjIjBl+IiIiIiIiIiMyIwRciIiIiIiIiIjNi8IWIiIiIiIiIyIwYfCEiIiIiIiIiMiMGX4iIiIiIiIiIzIjBFyIiIiIiIiIiM2LwhYiIiIiIiIjIjBh8ISIiIiIiIiIyo39U8OXatWvQarW4cuUKAGDWrFno2rXrE12mAwcOwMXF5S+Z16BBgzB8+PCHpi9fvhz+/v5/ybJQ2fH7ezZ16tQJH3/88WOVsXfvXlhZWf1JS1S8p6E+JaI/X7t27TBz5kwAgIODA44cOfKEl4iIzK2s53RTbdS/wl/R1qG/j7K2n6tVq4ZVq1aZcYlK5x8VfAEAjUaj/D958mRs3LjxCS4N0Lp1a9y5c+eJLkNBBbfPnykmJgY9evSAk5MTnJyc0KpVKxgMBiX96NGjaN68Oezt7eHv74+VK1eWqtxTp06hU6dOqFSpErRaLX7++ecieR617JIcOHAATZo0gaurK5ydnfHcc89hw4YNqjzR0dEIDg5G+fLl4enpif/85z+PPV9TzPX90ZOzdetWTJgw4bHLMfe+8VfXp3+XYGPdunWh0+mUv3LlykGr1eK3335T8nz77bfw8/ND+fLl0bJlSxw/fvyx5/vZZ5+hRo0acHZ2hl6vx0svvYTTp0+r8nz55ZeoUaMGdDodmjRpgr179z72fOmfLTU1Fc2bN3/Si/HU27VrF1q2bAkHBwe4u7tjzJgxStry5cthYWEBnU4HBwcH6HQ6vPbaa6Uq986dOwgLC0OlSpXg7OyM/v37Izk5WZXnSdQne/fuhVarVdbJwcEBrVu3fuz50pPzNFwjPYqnrR3csWNHVK5cGY6OjvDy8sKECROQlZWlpA8aNAjW1taq+uDLL78sVdlHjhxBQEAAnJ2dUalSJYSGhqquKR+n7JLkl5X/Z2trCysrK2XepWl//BX+rPbzX+0fF3z5q4iIKrjwLLt16xbatGmDRo0aIT4+HklJSfjss89gYWEBAEhJSUGnTp3Qu3dvJCcn44svvsDIkSNL9euatbU1evbsiS1bthRb4T5O2SWpWbMmfvjhB9y+fRtJSUmYN28e+vfvjwsXLgAAjEYjXn75ZdSpUwe3b9/Gxo0b8e9//xtr1659rPkSUS4ReeoaWcU5c+YMUlJSlL9x48ahTp06aNiwIYDcQO7o0aOxaNEiJCUloUePHujUqRPu3bv3WPMNCQnBoUOHkJSUhBs3biA4OBidOnVS0teuXYv33nsP69atw927dzF8+HCEhIQgPj7+seZLZC4GgwEi8qQXw6SoqCj07t0b4eHhSEpKQnx8PIYOHarK4+vri5SUFKSmpiIlJaXUPwoNGDAAaWlpiI6ORmxsLG7duoUBAwYo6U+qPgEAS0tLZZ1SU1Nx4MCBx5onmU92dvaTXoR/hNJc682ePRuXL1/G3bt3cfToURw9ehTvv/++Kk9YWJiqPhg5cqTJeedfZ7Ru3Rq3b9/G+fPncf36dfzrX/967LJNyS8r/69Xr1548cUXlSc5SlNfPI6/y7ngUf2tgy8JCQno0qULnJycULNmTfz000+q9OnTp+OFF14AACxcuBCNGjVSpcfGxsLS0lJ5TOnq1avo3bs3KlWqhCpVqmDEiBGqE5pWq8WCBQvQtGlTlC9fHseOHUNOTg7Gjh2LChUqoHLlypgzZw78/f3x7bffAih6i9ygQYMQGhqK4cOHw9nZGR4eHli8eLFqub7++mv4+fnByckJoaGhGDBgAAYPHlyqbXL//n2EhobC0dER/v7+WL58+UPz/vTTT6hcuTK2bt2KL7/8UrlYyBcdHQ0rKytcvXq1xHnOnTsXXl5eePfdd1G+fHloNBo0btxYSY+IiIC9vT0mTJgAKysrBAUFoXv37kXWuzg1a9bEkCFD0Lhx42IPxMcpGwAWL16M+vXrKxHrhQsXAgDc3Nzg4eEB4MFFoIjg0qVLAHK/1ytXrmDmzJmwsbFBo0aNMGLEiMeOOD+J74+erPxb/rOysjB8+HBUqFABTk5OqFGjBtavX6/kW79+PRo2bAhnZ2c0atQIP/zww0PLLO724IK3W+bfVTJ//nx4eHjA0dER4eHhuHPnDnr16gVHR0fUrl0bBw8eVKafPn06goODVeXNmjULQUFBcHBwQP369XHo0CElfc+ePWjRogVcXFxQoUIFvPrqq7h586ZqvSdMmIBevXpBp9PB398fmzZtAgAcPnwYo0aNQkxMjPILzL59+0rcjjk5OZg5cyZq1qyplBcREaGklVRPl3X7PozBYMDSpUtVjZ8lS5agZ8+e6NChA6ysrDBx4kTY2toWuZOuOGlpaZgwYQJ8fX2h0+lQt25d5TupVq2a0hAyGo3QarW4fv26cs5at24d+vfvj3r16kGj0WDEiBFwd3fHsmXLyrxe9OwoeIdpfj3x6aefwsPDA66urhg5cqTqXGyq3fT222/D19cXDg4O8Pf3xyeffKKkXb58GVqtFkuXLkWdOnVQvnx5VR1RnC1btqBOnTrQ6XTo0qULxo0bh3bt2inpV65cQbdu3aDX6+Hl5YWxY8ciMzMTADBv3jy8+OKLSt7Q0FDY2dkp6d9/jNAIDQAAIABJREFU/z3q1KljchtNmTIFo0aNQvfu3WFpaQlra+si599Hcf/+ffz000947733UK5cOTg5OWHKlCnYsmWLEjR9UvUJPd2qVauGGTNmoH379tDpdNiwYQNOnTqFwMBA6PV6uLq6olOnToiJiVGmKes5HTDdRi3pPNqgQQOsXr0aAJCRkQFbW1uEhYUp6SEhIaV+hOTbb7+Ft7c33NzcMGjQINy/f19Ju3jxIgIDA+Ho6IhGjRphwYIF0GpzL3d/+uknuLu7IycnR8l/7949ODg4KMdCcdd6Jalfv75ynZd/7OT/UPs47t69i9u3byMsLAxarRZOTk7o06cPTp48+dhlA7n1b58+fVC5cmW4uLigTZs2SEpKKpLv9u3bWL9+PUaNGqWM+7Pri4edC9asWYOGDRvC0dERVapUwciRI5Genq5MV/CR2fwyVqxYgTp16sDR0REdO3ZEQkKCal7R0dFo06YNHBwc0KxZMxw9elRJMxgMeP/99+Hr6wtXV1cEBwfj7NmzAHLvSrS0tMQff/wBILeNq9VqlTaVwWCAk5OTqryHkr+x9u3bS48ePSQ1NVUSEhKkdevWotVq5fLlyyIiMm3aNAkODhYRkaSkJLGzs5OTJ08q00+dOlWCgoJERCQjI0P8/Pxk2rRpkpmZKcnJyRISEiKDBw9W8ms0GmnQoIHExsaK0WiUzMxMmT59utSqVUvi4uIkIyND3njjDbG2tpbly5eLiEhUVJRYWVkpZYSFhUm5cuVk8+bNIiISEREhVlZWcuXKFRER2bt3r9jZ2UlUVJQYDAb57rvvxNraWgYNGmRye4SFhYm1tbWsWrVKDAaD7Nq1S+zs7OTQoUMiIrJs2TLx9/cXEZEvv/xSPD095cSJEyIikpKSIg4ODnL06FGlvMmTJ8tLL71kcr4tWrSQ3r17S0hIiLi4uEiDBg1k5cqVSvqbb74p3bt3V00zb948adKkicmyC9JoNHLw4EHVuMcpe+HChVKlShX5+eefRUTk9u3bqvUXEXFychJra2vRaDQSGBgoWVlZIiIyf/58adSokSrvhg0bxNXVtUzrVNCT+v7oyQoMDJQPP/xQFi9eLI0bN5akpCQREYmPj5fz58+LiMjBgwfF1tZWtm/fLgaDQbZs2SK2trbyyy+/iEjx9cywYcNU8/H29laOy2XLlomVlZVMnz5dsrOz5dSpU2JjYyPNmzeXX375RYxGo0yZMkXZ30TU9Wl+ef7+/nL+/HkxGo0yduxYVf6DBw/K0aNHxWg0SkJCggQEBEi/fv1U663X6+Xw4cMiknvcOjk5SXp6urKMBcszJTw8XOrUqSNnzpwREZFr167J6dOnRURM1tOmtm9prV27Vuzt7eXu3bvKuIYNG8onn3yiyte1a1cZP368yfL69Okjbdu2Vc5p0dHREh0draQfOHBAnJycRKvVioWFhUyaNElJ6927t4wdO1ZVnre3t/Ts2bNM60T/fPl1kIj6PJtfT7zzzjuSlZUlly5dEhcXF1m1apWIlK7dtHLlSvnjjz9ERCQyMlLs7Oxkx44dIiISFxcnGo1GgoKCJDExUbKzs8VoND50OS9duiQ2NjayZs0aMRgMsnv3btHpdNKuXTsREcnJyZG6devKqFGjJD09Xa5fvy5NmzaVMWPGiIjIqVOnxN7eXjmPV65cWapXry47d+4UEZFhw4bJv/71rxK3VVpamlhYWMiECROkcePG4ubmJu3atVOde5ctWya2trZSqVIl8fT0lFdeeUViY2NNfg/37t0TjUajaqfu2bNHNBqN/PjjjyLy5OqTqKgo0Wq14unpKRUrVpTOnTurlpOeLG9vb/H09FS+k4yMDDl16pRERUVJdna2pKSkSJ8+faRly5bKNGU9p5tqo5o6j44bN06GDBkiIiLbt28Xf39/qVq1qoiIZGVlSfny5eW3334rcT2joqJEo9FI7969JTU1VRITE6VVq1YyfPhwEcmtA2rUqCFvvvmmZGZmSmxsrNStW1e0Wq2IiBiNRqlWrZqsW7dOKXPRokVSu3ZtZbjwtV5+fVGS0aNHi729vWg0GnF1dVXaNfnbzcXFRVxdXaVGjRoyceJEuXfvnskyRURGjRol4eHhkpmZKQkJCdKuXTt57733Hrvs+/fvi4+Pj7z++uuSmpoqBoNBjhw5Uuy0c+bMEU9PzyJ1c0n1RVkVdy4wGAzy008/yblz50Qkt76qU6eOTJkyRZmu4Lkrv4yXX35Z7ty5I6mpqfL8888r+4ZI7j5epUoVOXHihGRnZ8tHH30ker1eUlNTRURk5syZ4u/vL//73/8kKytLpk2bJpUqVVLSmzRpIv/9739FJPcaq3r16vLaa68p28PFxaVU6/u3Db5cu3ZNNBqN6oS2c+fOhwZfRET69u0rb775pjLs7e0t3333nYjkNpr9/PxU8zh69KjY2NgoO5xGo5EVK1ao8vj5+cmyZcuU4fT0dLGxsSkx+NK5c2dVGXq9XjZt2iQiIkOHDpWBAweq0tu0aVPq4Evbtm1V4/r37y8jRowQkdwGga+vr4SHh0vdunXl6tWrqrxDhw6VkSNHioiIwWCQKlWqyIYNG0zO18/PTywtLSUiIkIMBoPs3LlTbG1tlQbckCFDJCwsTDXNN998U6YLK5Higy+PU3bt2rXliy++MJkvKytLNm7cKLNnz1b2hRkzZkhgYKAqX2RkpOq7Lqsn9f3Rk5V/8li2bJlUr15d9u/fLzk5Oao8w4cPl/79+6vGvfrqq8r3/SjBF0dHR1V6s2bNlIsUEZFz586JVquVlJQUESm+oTZ37lxl+OzZs6r8hW3evFkqVKigWu+C80tLSxONRiOnTp1SlrEsdUT58uVl27ZtxaaZqqdNbd/SCg4OVl14ioj4+vqq5i0iMnDgwCLfT2GJiYmi0WiUAFxJ7t69KwsWLJD169cr45YvXy56vV6OHj0q2dnZ8umnn4pWq1V9h0QiJQdfHB0dVY3u3r17y7hx40SkdO2mwnr16iVvvfWWiDxoLB84cKBUy/nBBx9IQECAatyAAQOU4Ev+xV9+AFck9yKvXLlyynDFihUlMjJSzp49K76+vvLRRx9JeHi4iIj4+PgoQY6HiY+PF41GI1WrVpUzZ85Idna2zJw5U9zd3ZWga2xsrFy8eFFERBISEiQsLEz8/Pzk/v37Jtexffv20r17d0lOTpbExEQJDg4WrVar1N1/ZX0SERGhjEtISJBTp06JwWCQu3fvyuTJk8XV1VVu3LhhsjwyP29vb/nggw9KzHP69GnRarXK8VHWc7qpNqqp8+jWrVvF29tbREQmTpwoM2bMkJo1a8q5c+dk7969otfrTa5nfhCw4LVffhBIRGT//v1ia2srGRkZSvrXX3+tBF9EcuuRjh07KsPNmzeXefPmKcPFXeuV1tmzZ+Xtt99WflAXETl+/LgkJiaKSG67qlmzZqofokqye/du8fPzEysrK9FqtRIUFKSq3x617O+//14qV64sBoPBZN7q1avLjBkzHppeXH1RVqU9F3z22WfSvHlzZbi44MuxY8eU9M8//1waN26sDHt7e6uCVyIinp6eSiygevXq8vXXXytpRqNRqlatKqtXrxaR3B/58q/RmzZtKmvWrJGKFSuKSO6PfKX9cetv+9hRfHw8NBoNPD09lXHVqlUrcZpBgwZh1apVMBgM2L17N+7evYvu3bsDAOLi4nD58mW4uLgof0FBQbCwsFBuMQIALy8vVZnXrl1TLYOtrS30en2Jy1GpUiXVsL29PVJTU5XyCs+j8HBJvL29iwwXfMY/MTERCxcuxIQJE1C1alVV3hEjRmD16tXIyMjAli1bYDAY8PLLL5ucp4ODA1q2bInu3btDq9UiKCgIHTt2VB4hcHBwwN27d1XTJCcnQ6fTlXq9Spr3o5YdFxdXqg49rays0KVLF0RFRWHJkiWPPd+SPInvj54OAwYMwNChQzF27Fi4urqiV69eyi3CV69eLVK/+fr6PtYjZe7u7qrhcuXKqeqmcuXKAYBSNxWnYsWKyv/29vaq/MePH0fHjh1RqVIlODk5FXnsCECZ5/cwN2/eRFpa2kOPZ1P19J+xfaOjo7F7927VrbnAo9cVcXFx0Gg0paqjdDodxowZgyFDhii3O4eGhmLixIl47bXXUKlSJZw8eRJBQUFwc3Mr9ToRubu7q/peKtheKU27acGCBahfvz5cXFzg7OyMzZs3q+oBjUZT6jaOqfZRfHw89Ho9bG1tlXG+vr7IyMjArVu3AADt27fHzp07sWvXLgQHB6NDhw7YsWMHYmJiEB8fj8DAwBKXwcHBAQAwePBg1KlTB5aWlpg8eTKys7OVx7W8vb3h5+enbL+vvvoKN27cwOHDh02u44oVK2BjY4NatWqhRYsW6NatG0REqa/+yvpk8ODBSn3i7u6OevXqKZ3uzpw5E66urti2bZvJ8uivUfjYiImJQc+ePVG1alU4OTkpHSSX9GhfSed0oOQ2qqnzaEBAAG7cuIGLFy8qx19QUBB27NiBXbt2oX379qVe14Lnc29vb2RmZuLWrVu4fv063N3dYWNjo6QX3i5DhgxBVFQU4uPjcfr0aZw8eRKhoaGqPGW57iqodu3aaNCgAfr27auMa9SokXL81qpVC/Pnz8e6detM9stz6dIlvPTSS3j33XeRnp6O5ORk+Pj4qB6dfNSy4+Li4OPjozyO9TB79uxBXFwchgwZ8tA8xdUXj6K4c8HOnTvRtm1buLu7w8nJCW+99VaJ+69GoymyDxduUxaeh6enp2ofLriPazQaeHt7K/twUFAQdu/ejaSkJFy8eBE9e/aEm5sbTp48iV27diEoKKhU6/q3Db5UqVIFQO4zXvliY2NLnCY4OBg2NjbYtGkTli9fjldeeUU5QL28vFCjRg3cuXNH+UtKSkJaWprqAqHwjlqlShXVMqSnp5t8ZtnUehUsD4DSJ01pxMXFFRkueJFesWJF7NixAxMmTMCKFStUeZ977jn4+vri+++/x9KlSxEWFqZ0mluShg0bFtsxZv64Bg0aqN78AeRemDVo0KC0q/VQj1O2t7c3Ll68WOp55eTkKPkbNGiA//3vf6pnD48dO/bY6/Qkvj96Omi1WkycOBG//vorrly5Ajs7O6WvJw8PjyL7RkxMjNIvUWEODg5IS0tThnNycpCYmGi2ZS/OK6+8giZNmuDSpUtITk7Gd999V6bpTTUKCtLr9bC3t3/o8Wyqni7r9i3OokWL0LBhQzz33HOq8Q0aNCjyNpITJ06YrCvyGwClraMMBgOysrIQHR2tjJs4cSJ+//133Lx5EwsXLsTZs2dV/WMQPQ5T7aaff/4ZkyZNwldffaWkde7cuUj/baU91k21jzw8PHDz5k1kZGQo46Kjo2Fra6sEHYOCgrBr1y7l4q9Jkya4evUqVq1apfTxUBKdTlfkAhTIbe+Y6iC88HoXp1KlSvjuu+9w/fp1REdHw8vLC3Z2dsobqJ5kfVJYfl949HQofByNHDkSOp0OZ86cQXJystKnyeN8ZyW1UU2dR8uVK4cWLVpg9erVuHz5Mpo1a4YOHToowdDSXrgCRa/9bGxs4ObmhipVquDmzZtKP06F8wK57eiQkBAsXboUS5cuRbdu3ZT+S/KVpf1RWHZ2ttI/ZElMfQ8nT56Eq6srQkNDYWFhAQcHB7z++us4cOAAUlJSHqtsb29vxMbGmsy3aNEidO7cuchNA4WVpr4ojYLbPTs7G927d0e/fv0QHx+P5ORk/Pvf/37sOqfwPnrlyhVlHy28D4sI4uLilPQ2bdrg1q1b+Pzzz9GmTRtYWFigQ4cO2LBhA3755ZdnI/gSGBiI8PBwpKamIiEhATNmzChxGq1Wi9DQUCxYsAAbNmxQdWLbuXNnZGVlYdasWUqHQdeuXTPZ6eKAAQMwZ84cxMXFISMjA5MnT36sHWPAgAFYt24d9u7dC6PRiDVr1pTq15J8hw8fxpo1a2A0GrFnzx5ERESoOrQCgJYtW2LHjh2YOHFikQ5ihw0bhrlz52Lbtm1Feu9/mBEjRuDw4cPYtGkTRASRkZHYuXMnunXrBgDo3r070tLSMHfuXGRlZWHXrl344YcfMGLEiFKVn5mZqTSmsrKykJmZCaPR+Nhl/9///R9mzpyJw4cPQ0Rw+/ZtpaOkiIgInDlzBgaDAZmZmfjqq68QGRmJjh07AgDatm0LLy8vTJkyBRkZGThx4gQWL16s6mhz0KBBZYrkA0/m+6OnQ2RkJI4fP46cnBzY2NjA3t5eCZ4NHDgQ69evx86dO2E0GrFt27YidVhBTZo0we7duxEXF4esrCy8/fbbqg7mSqusdVnB/KmpqXB0dIS9vT2uXLmCjz76qExlVaxYEYmJiaW+E2bUqFEIDw9XOke7du2a8upDU/V0WbdvYdnZ2Vi+fHmRu16A3GMyIiICkZGRyMrKwuzZs5GVlaXcdfkwer0evXr1wujRo5XGY3R0tHI31KJFi3Dt2jUAuW+cGzNmjOoiLSUlBb///juA3F86R44cqXTiTvRnMNVuSklJgaWlJdzc3CAi2LJlS5E7JcpSx7zyyis4cuQI1q1bB6PRiMjISFUbrVmzZvDz88P48eORnp6O69evY+rUqarjOCgoCMePH8f+/fvRvn17aDQaBAQE4OOPPy51w3n06NH45ptvcP78eRgMBsyePRu2trZo1aoVgNzXn+Yfm3fu3MHo0aOh1+vRokULk2X/73//Q1JSEkQEv/76K8aOHYvJkycrd7Y8qfokMjIS0dHREBGkpaVh2rRpSExMVP0KT0+XlJQU2NvbQ6fT4datW5g6dWqZyyh8fJbURi3NebRDhw6YO3cuAgMDodFo0K5dO+zfvx/Hjh0r9fEnIpg8eTJSU1ORmJiI6dOnK+e1Fi1awNPTE5MnT0ZmZiZiY2NVnXznGzZsGJYuXYqVK1di2LBhZd4u+S5cuICNGzciLS0NIoITJ05gxowZqjf/rFmzRrlb7eLFi5gwYQK6du0Ka2vrEstu0qQJkpOTsWrVKhiNRqSmpuLTTz+Fj4+PUh88atkhISGwtrbG2LFjkZKSAoPBgCNHjqh+tEtISMAPP/xQbLvGVH2R3/mtqRclFFR4X8vKykJWVhacnJxgbW2Nc+fO4bPPPitTGcVZunQpTpw4gZycHMyePRvp6enK9xUWFobZs2fj4sWLyM7OxgcffACDwYCQkBAAUOr5jz/+WOmsukOHDpg/fz4qVqyo3PFoyt82+AIAq1atQkZGBjw8PBAQEICBAweanCYsLAz79u2Dj4+P6hdKOzs77NmzB+fOnUPNmjXh5OSE4OBgVa/Sxf2qMXnyZAQHB6NZs2bw8fFBlSpVUKlSJdUtb6YULLdt27b45JNPMGjQILi4uGDr1q3o3r17qcvr06cPtm7dCmdnZwwbNgwLFy4s9oTfqFEjREZG4sMPP8Ts2bOV8a+99hpiY2PRunVr+Pr6lmqezZs3x6pVqxAeHg6dTod//etf+Pbbb5WD0NHREVu3bsX3338PZ2dnjBw5EosWLUKzZs1Mln358mXY2dnB3t4eGo0GHTp0QLly5ZS7Ph6n7NGjR2Py5MkYMmQIdDodmjRpogRfbty4gR49esDZ2RlVqlTBsmXLsHr1aiWYotVq8eOPP+L06dNwdXXFyy+/jEmTJqF3795K+VeuXCnzr8xP4vujJyv/+E9ISMCAAQPg4uKCKlWq4MqVK8pbu1q1aoXly5dj/PjxcHFxwaRJk7By5Uo0bdq02DJfe+01dOnSBY0bN4afnx+8vb2VuwVNLYepcaXNv3jxYnz11VfQ6XTo1asX+vTpU6bp27Vrh+DgYKVX/f3795e4/DNnzkSfPn3QrVs3ODg4oF27dsqvMKbq6bJu38IiIiKQmZmJfv36FUl7/vnnsXDhQgwdOhTOzs6IiIjAtm3bTP7CDuQ2Eho2bIiAgADodDp069ZNeZzj119/RbNmzZS3Uvzxxx/YtWsXXF1dAeQ2vHv37g2dTodatWohJycHkZGRZTo30bOh4F0bZXm9u6l204svvojQ0FA0bdoUer0eERER6NGjR5F5l5avry/Wrl2LqVOnwsnJCfPmzUNoaKiyT1tYWGDz5s24evUqPD090aJFC7Rs2RJz5sxRyvDw8ICvr6+yvEBuQCY1NbXUF38TJkzA4MGD0b59e+j1emzfvh3btm1THkmKiopSjs169eohOTkZO3fuVB6tLMm+fftQp04dODg4oH///njjjTfwzjvvKOlPqj45efIkOnToAJ1OB19fX/zyyy/YtWuXyfMK/TWKO47mzZuHffv2wdHREQEBASYfQy9NG6CkNmppzqP5x1r+m2gdHR1Rs2ZNeHp6FntHWXEsLS0REhKCevXqoVatWvDz88PcuXMB5NYBmzZtwrFjx6DX69GjRw+EhoYWCUa88MIL0Gq1cHR0LPIjaVnqJBHB7Nmz4eHhAScnJ/Tt2xfdunXDF198oeT58ssvlTe+dezYEa1atcLSpUtNlu3t7Y3169dj/vz5cHNzg4+PD65evYqNGzc+dtnlypXDnj17cOXKFfj7+0Ov1yM8PFz1uNKyZcvg5eVVbL1oqr64fPkynJ2dy/Q0QOHtbm9vjy+++AITJ06ETqfD66+/jtdee63EaUx9dxqNBsOHD8cbb7wBZ2dnrF27Flu3blXq7okTJ+LVV1/FCy+8gIoVKyIqKgo7duxQ1a/5+3B+8CUwMBDp6emqN4eZXFfhPYN/qrS0NDg7O2Pfvn2l+pWjNFq1aoUuXbpg0qRJf0p5pvj4+GDWrFmqZxapbDIyMlCrVi2cPXu2VA2uPxO/P6KSmaOeJqK/Xr9+/aDT6YrcBUr0/+zdd3gU1foH8O9ssimQbHoAaYtJCEiXC4IiJCG5KiBVEBGQjlgpAoJeaSoWrih6uQKKhEvRnxQBKUpLEMQG14DiFQhBSiBBSSM92ff3R7KTnbRNYRLK9/M8eXZ3zpkzZ2ZnzpzzZmaHCCi4SmPx4sXqlaBWoaGhePDBBzFz5sxaqtmta86cOTCZTJg2bVptV+WGdFNf+XIjSEpKwldffYW8vDykpKTg2WefRbNmzSr8H9PSbNy4Eenp6cjJycHy5ctx5MgRzRUVelqzZg1yc3MxaNCgGlnercrFxQVxcXE1Hnjh90dUkh7tNBHVvG3btiEpKQn5+fnYsmULNm3aVOoVZ0R0ezp06JB6O92xY8fw9ttvl2gjDhw4gJ9++om35+tk3rx5DLyUg8GXarJYLHj55Zfh4+ODgIAAxMfHY+vWrdX6odONGzeiUaNG8PPzw7Jly/DFF18gICAA69atg7u7O0wmk/pn/VzZH7Msjb+/P2bOnImPP/4Yjo6O6nQ9l3uzln0jKuv7I7oVLFy4sMzj2fpDgmWpTjs9adKkMpdr+ySyqtCzbKKbUfHjwfpnvef+wIEDaN68Oby8vPDSSy9h2bJl6N69+3Wtw816zLM9oVuBvTbAnvPnzyM0NBRubm7o168fBg0apLlzoHPnzhgwYAA++OAD9TaZ8rRu3bpEXay3FFbXzVo2VQ9vOyIiIiIiIiIi0tEt++/xyvxgEtGtgrHUmse2hm43bGdqB9saut2wral5bGfodlSTbc0tG3wBANP7OXDKz1E/GwvfOxa+OtikOeYVPMrYkF/0S8+GwnQlr+DVkFf03HjFmqa+Fs2nFJYFS9E0FM9nU5Y1DdY0m7LEms9SVFcplk9syhJLsTTbsix5JfNb8xWmWWzzF9bLmsdiKXpUrTW/Zh0lv2AdUfAYaINStCM7GKTwFZrXgvcFDb3RwXZa4atDQZqjTX7rHTWOhfM5lDKfo800a7nWsmyXbc1XlKdkmm1+o2PZaY4Oos1ju44O2jzafFLKsouVZTOf9b1mmkHw8IxLoNrReeefMCBf/Wx9byg8FhTbNCVfk8f2fdGxU3SsKeWVhbzC/CXTiubLs8lvKZZWWlnaumjXJ6/Mupc2zUHKzu+gvhbVz0Gs0ywl5nMsLMuxMM2a1za/o+00KZwG0XwuyGctQzTz204rnkeT3+Yc7VBYvqOl4NVQSpo1v4PFJk20r7bzOYpSYppBzV/YjlmUMtMMUpSmTrOUTLO+d5Cixqp4vuL560wu/1GPpK/nNzwOR5vBkWOJ16I0o1JymkOx/EbbNMWaR9HksX1vTbO9Yc9aH9v8xfMZSsnvUCxvadNsl2NQSuY3FM9vM240FE5T89hsN+s7g/UpT5rlWJ/8ZM1sk2p9byg5TR20KjZra31f/BUADNZpDtpXTX7baQXvRTGWmQal8FswOJaZJpr5HEspy7HU+UotQzNfsXrZpBXlN5ayPqUtxwFNmjQB1ZK/ZQGuWUWfnTMLXp0ytZ8BwDldmwYAxsL3xsIynIoeYQzHLM2rj0PRmMTTMQMA4GIzzanwvaP1tTAPADgUlqE4aF8BQHEsWKY4FOVH4Xul8NXomFa0HEPBmMfZUNDXcLU5VF0Kj/e6Ng2Mc+Hxbk1ztmkTXAuPbes0Z5s2xDrNmqdg2dp8TpqyrGmGEmlOiqLJYzvN+mpzxMGpsItkyC/sC+YXdTKUvMJpuTYdlcL31jTklUwrei3qf6G0/Dn52vyllZVtTbPp/FiHvzbDTWQXm5Zjk2Z9n1ksLwBkFUsDgAxAOYEaxd98ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIi8JlMnAAAgAElEQVSIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0x+EJEREREREREpCMGX4iIiIiIiIiIdMTgCxERERERERGRjhh8ISIiIiIiIiLSEYMvREREREREREQ6YvCFiIiIiIiIiEhHDL4QEREREREREemIwRciIiIiIiIiIh0pIiK1XQk9KIpS21UgqnG36OF8Q2NbQ7cbtjO1g20N3W7Y1tQ8tjN0O6rJtuaWDb4QEREREREREd0IeNsREREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItJRrQZfLl68CIPBgHPnzgEAFi5ciH79+tVmlXDw4EF4e3vXyLJGjx6NCRMm1Miy6ObD/aPm9erVC4sWLap2OdHR0TAajdehRmW7EdpLql030/5K109oaChef/119bO7uzu+//77WqwR3Y6aNWuGdevW1XY16AZW2X7KjdDv5fmQ9FbrV74oiqK+nzVrFrZs2VKLtQG6deuGq1ev1modapKI4N5774XBYEB8fLwmbfXq1QgMDISbmxu6du2Ko0ePVqjMq1evYtSoUWjQoAG8vLwwfPhwJCcnq+mRkZFwcHCAyWSCu7s7TCYTHn/88eu6Xo8++igMBgO+/fZbddrOnTvRs2dP+Pn5wcfHBz169MDBgwev63Lp5rZjxw688MIL16Us27ZNDzXdXkZGRiIoKKjGlldVCQkJePTRR+Hv7w8fHx+Eh4fj2LFjmjxVbdvK88EHHyA4OBheXl7w8/PDQw89hOPHj2vyLFq0CIGBgfDw8EBwcDD+/e9/V2uZN9P+SvpJS0vDPffcU9vVuGVUp49Sm/2fo0ePIiIiAiaTCT4+Pujfv78m/cMPP0RwcDBMJhM6duyI6Ojo67JcorLcCOO6qrjZz4cnT55E165d4evrC09PT7Ru3RorVqzQ5DGbzXB1ddW0Rb/++muFyl+9ejVat24NDw8PNGvWDPPmzbtuZZcnPz8fc+bMgdlshpubG4KCgvDVV1+p6efOncOAAQPg5+cHPz8/PP3008jNza32cq+3Wg++1BQRQX5+fm1Xo8ZUdGd755134ObmVqKhOXjwIJ566iksW7YMSUlJGDhwIHr16oVr167ZLXPEiBFIT09HbGws4uLi8Oeff2LEiBGaPAEBAUhNTUVaWhpSU1Oxdu3aiq+cHZs3b8bVq1dLrFNSUhKee+45xMbG4sqVK3jsscfw0EMP4eLFi9dt2TejG7FhohuPiNwUHZJJkyYhOTkZp0+fRkJCAjp27Ig+ffqo6dVp28rTu3dvHD58GElJSbh06RIiIiLQq1cvNX3r1q2YO3cu1q9fj5SUFERGRmL69OnYu3dvtZZLVJvy8/MhItetvBulr1bVPkpt9X/+97//ISwsDEOGDEFiYiISExPxj3/8Q03//PPPMWfOHGzYsAEpKSmYMGECevfujQsXLlR72XT7Yv+x+vRo8xo0aIA1a9bgypUrSE5Oxvr16/Hyyy9jz549ah5FUbBy5UpNW9SqVSu7ZR87dgxjx47Fm2++iZSUFOzatQvLli3Dxx9/XO2y7Zk4cSL27NmD3bt349q1a/jmm2/QsmVLAIDFYsHDDz+Mpk2bIj4+HjExMTh8+DCmTZtW7eVebzUafElISEDfvn3h6emJFi1aYNeuXZr0efPm4e9//zsAYOnSpejQoYMmPS4uDo6OjuptSufPn8fgwYPRoEEDNGzYEBMnTtR0oA0GA5YsWYJOnTrBzc0NR44cQV5eHqZMmYJ69erhjjvuwNtvv42goCCsXr0aQMnLzUaPHo2RI0diwoQJ8PLyQuPGjbF8+XJNvT7++GMEBgbC09MTI0eOxIgRIzBmzJgKbZOMjAyMHDkSHh4eCAoKQmRkpJrWrl07fPrppwCArKwsuLi4YNSoUWp679691UvOQ0NDMWXKFAwYMACenp5YvHix3WWfPHkSH374IRYtWlSi8/TRRx9h0KBB6NmzJ4xGI6ZPnw4XFxds3rzZ7vrs2rULc+bMQZ06deDp6YnZs2djx44d1+Ukn56ejhdeeAEBAQEwmUxo3bo1Dh06pKb/9ddfmD59Oj766KMS6zRs2DD069cPJpMJBoMBTz75JNzc3PDjjz/qUp/MzEw8//zzaNKkCfz9/TFw4ECcP39enddeuq3FixfjgQceUD+PHDkSrq6uyM7OBgD83//9n9qwXbx4EQ899BD8/f3h5eWF7t27a/6zP2/ePPTs2RPTp09H/fr10b9/f/zxxx8wGAxYvXo1WrVqBTc3N/Tp0wfJycmYNWuWerwsXbq0ytvqZmB7OX9OTg4mTJiAevXqwdPTE8HBwdi4caOad+PGjWjfvj28vLzQoUMHfPHFF2WWW9qltLaXbFuvKnn33XfRuHFjeHh4YMaMGbh69SoeeeQReHh44K677tLs6/PmzUNERISmvIULFyI8PBzu7u5o27YtDh8+rKbv27cPXbp0gbe3N+rVq4fHHnsMV65c0az7Cy+8gEceeQQmkwlBQUHYunUrAOC7777DpEmTcObMGfW/GAcOHCh3W+bl5eH1119HixYt1PI2bdqkppXXDld2+9qKjY1V18HR0RFjx47FxYsX1Ssaq9q2AeUf782aNVNvWbVYLOrVhNZzUmxsLNq1a4dOnToBALp06YK2bdsiJiamQutVmptpfyX92F7laf1u3n//fTRu3Bg+Pj548sknNedDe32nl156CQEBAXB3d0dQUBDee+89Nc16rli5cqV6rrBtR0qzfft2tGrVCiaTCX379sXUqVMRGhqqqX/xvhoArFixAm3atIGnpyc6duyI3bt3a8r94osv8Le//Q1eXl5o1aqV5haYimyH6602+z/z589Hr169MH78eLi4uMDBwQEdO3ZU592wYQOGDx+ONm3aQFEUTJw4Ef7+/li1alW16wUUrHv//v3x8MMPIyMjA0D5feOhQ4di8uTJmjJWrlx5U1xdeTtr1qwZFixYgLCwMJhMJrzxxhsICQlRryjv1asXzpw5o+avbD8FKH9cBJR/LqvMuMme1atXw2w2w9fXF6NHj1b3awA4deoUQkJC4OHhgQ4dOmDJkiUwGAqG1Lt27YK/vz/y8vLU/NeuXYO7u7t6vJbW5lnHm2PHjlXHm59++iliYmLQuXNneHh4oGfPnrh8+bLduru7uyMgIEDzDzNFUfD7779r8lWlPYyNjYW/vz969+4NAAgODkZISEiJvkxV29ro6Gh0794dPj4+8Pf3V9uM33//HStXrsQnn3yithP169dHkyZN1PRffvkFCxYsgNFoxB133IHJkyfjk08+QU5OTpXqohupQWFhYTJw4EBJS0uThIQE6datmxgMBvnjjz9ERGTu3LkSEREhIiJJSUni6uoqMTEx6vyvvPKKhIeHi4hIVlaWBAYGyty5cyU7O1uSk5Old+/eMmbMGDW/oijSrl07iYuLE4vFItnZ2TJv3jxp2bKlnD17VrKysuS5554TJycniYyMFBGRqKgoMRqNahmjRo2SOnXqyJdffikiIps2bRKj0Sjnzp0TEZHo6GhxdXWVqKgoyc/Pl/Xr14uTk5OMHj3a7vYYNWqUODk5ybp16yQ/P1/27Nkjrq6ucvjwYRERmTp1qowdO1ZERL766isJCgqSRo0aiYhITk6OuLm5yc8//ywiIiEhIeLh4SFRUVEiIpKZmVnusi0Wi3Tr1k22bNkiZ8+eFUVR5OLFi2p6+/bt5b333tPM069fP5k2bVq55V67dk0URdF8b/v27RNFUWTbtm0iIrJq1SpxcXGRBg0aSJMmTWTo0KESFxdnb3OJiMiQIUOke/fu6j4TGxsrsbGxavpjjz2m1ltRFDl06FCZZR07dkyMRqOcPn26QsuubH0mTJggXbp0kUuXLklGRoaMGzdO2rVrJxaLpULpo0aNkvHjx6t1rVu3ruTk5IiIyB133CHNmzeX3bt3i4jI+PHj5fnnnxcRkXPnzsm2bdskKytLsrKyZPLkydK0aVPJy8sTkYLjzGg0yuLFiyU3N1cyMzPVfaBfv36SnJwsV69elbvuukuaN28uH330keTn58vOnTvFaDTK+fPnq7y9bnQhISHy2muviYjI8uXL5e6775akpCQREblw4YL89ttvIiJy6NAhcXFxka+++kry8/Nl+/bt4uLiIj/88IOIlN6OWL9LK7PZLGvXrhWRgmPCaDTKvHnzJDc3V44dOybOzs5yzz33yA8//CAWi0Vmz54tQUFB6vy27aW1vKCgIPntt9/EYrHIlClTNPkPHTokP/30k1gsFklISJAePXrIsGHDNOvu5+cn3333nYiILF68WDw9PdW2ZNWqVZry7JkxY4a0atVKfvnlFxERuXjxohw/flxExG47bG/7lmfNmjXywAMPyJUrVyQzM1OmTp0qPXr0UNOr2raJ2G9/Dh48KJ6enmIwGMTBwUFefPFFNS0+Pl7atGkjhw4dEovFIgcOHBBfX185ceKE3eWW5WbaX+n6sf3eRbTnOut38/LLL0tOTo6cPn1avL29Zd26dSJSsb7T2rVr5fLlyyIisn//fnF1dZWvv/5aREQ9V4SHh0tiYqLk5uaq56zSnD59WpydneWzzz6T/Px82bt3r5hMJgkNDdXU37avlpOTI8uXL5egoCC1zdi5c6e4ubmpx9vXX38tvr6+6nr/+OOP4uXlJd98802FtkN5qtpHqc3+T/369WXChAly//33i4+Pj9xzzz3qdyYiMnjwYJkyZYqmPLPZLIMGDarQsktjbRMuX74snTp1kqefflrdF+z1jfft2ye+vr5qn0ZE5N5775W33nqryvUh/ZnNZmnSpIm6jx87dkyioqIkNzdXUlNTZciQIdK1a1c1f2X7KfbGRfbOZZUZN5UlKipKFEWRwYMHS1pamiQmJsq9994rEyZMEBGRvLw8CQ4OlsmTJ0t2drbExcVJ69atxWAwiEjB+KpZs2ayYcMGtcxly5bJXXfdpX4ubXxqHW/u3LlTREQ+/PBDcXNzk379+kl8fLxkZmZKWFiYWo+KaNu2rbi4uIiiKNK2bVv566+/NN9FvXr1xMfHRzp06CDLli2rUJnp6enSqVMn2bx5s1gsFjl+/Lg0atRI9uzZU+2yY2JixMXFRVavXi05OTmSlZUl0dHR6vbw9PSU+fPnS8OGDaVp06YyadIkSUtLExGRX3/9VQwGg6SkpKjlrVy5UgwGg3oeuVHUWPDl4sWLoiiK5iSze/fuMoMvIiKPPvqoTJ48Wf1sNptl/fr1IiLy+eefS2BgoGYZP/30kzg7O6uNv6IosmbNGk2ewMBAWbVqlfo5MzNTnJ2dyw2+9OnTR1OGn5+fbN26VURExo0bJ0888YQm/f77769w8KV79+6aacOHD5eJEyeKiMiOHTvEbDaLiMj06dNlwYIF0qJFCzlx4oRER0eLn5+fOl9ISIja4FTEO++8I0OGDBGRgs6UwWDQBF8CAgI020lE5IknnijRIS9NWFiYDBgwQJKTkyUxMVEiIiLEYDCoHfe4uDg5deqUiIgkJCTIqFGjJDAwUDIyMsotNzExURRFUQcUxW3evFm6dOmifi4v+JKQkCDNmzeX2bNn212fqtTHYrGIi4uL7N27V5127do1cXJyku+++85uukjJAVD9+vVl//798uuvv0pAQIC88cYbMmPGDBERufPOO9XOXXGpqamaes6dO7fEsWPtUB85ckSdNmPGDGndurUmn7+/v7rv34psBzWrVq2S5s2byzfffKMGrqwmTJggw4cP10x77LHH5MknnxSRqg1mPTw8NOmdO3eWZ555Rv184sQJMRgMkpqaKiKld2r++c9/qp+tJyJr/uK+/PJLqVevnmbdbZeXnp4uiqLIsWPH1DpWZjDt5uamdiKKs9cO29u+5Tlz5oyEh4eLoihiNBrlzjvvlN9//11Nr2rbZq/9sZWSkiJLliyRTZs2qdPy8vJk7ty54uTkJEajUYxGo/zrX/+yW1Z5bqb9la4fe8EXDw8PTUBk8ODBMnXqVBGpWN+puEceeURmzpwpIkXnioMHD1aorq+++qom+CkiMmLEiBLBl+J9tdatW8t//vMfzbSHH35YXe8+ffrIggULNOnPPvusut/a2w7lqWofRaT2+j+Ojo7i7u4uBw8elLy8PPnPf/4jrq6ucubMGRERiYyMFD8/P/npp58kNzdX3n//fTEYDJpzSGWZzWaZNWuWNGvWTBYtWqRJq0jfODg4WD777DMRKWgvnJ2dJSEhocr1If2ZzWZ59dVXy0w/fvy4GAwG9Z82le2n2BsX2TuXVWbcVJaoqCgxGAya8ao1CCQi8s0334iLi4tkZWWp6R9//LEafBEpaPcefPBB9fM999wjixcvVj+X1uYVH29mZGSIoiiyceNGddrSpUvl7rvvtrsOtvLy8mTfvn0yd+5cTZ0PHDgg6enpkpeXJ7t37xYfHx9Zvnx5hcr817/+Je7u7mI0GsVgMMisWbM06VUt+6mnnlLHpsW9+uqroiiKDBs2TK5duyaXL1+Wrl27aoJizZs3l6effloyMjLk7Nmz0r59ezEYDOX+I7421NhtRxcuXICiKOrlQUDB5WflGT16NNatW4f8/Hzs3bsXKSkpGDBgAADg7Nmz+OOPP+Dt7a3+hYeHw8HBQXNJVtOmTTVlXrx4UVMHFxcX+Pn5lVuPBg0aaD7XrVsXaWlpannFl1H8c3nMZnOJz9bLU3v06IFLly7h1KlT2LNnDyIiIhAeHo6vv/4ae/bsQVhYWLlllSU2NhbvvPMO3n//fQClXxrm7u6OlJQUzbTk5GSYTCa75a9ZswbOzs5o2bIlunTpgv79+0NE4Ovrq9YzMDAQAODv748VK1bg0qVL+O6778ot9+zZs1AUpdTLUpOSkvD888/jo48+slu/+Ph4hIWF4cEHH8Rrr71mN39V6nPlyhVkZ2drvpO6devC398f58+ft5temrCwMOzevVvdF3r27Imvv/4aZ86cwYULFxASEgKg4NarJ554Ak2bNoWnpyeaNGkCRVE0l4aXto8qioL69eurn+vUqVNi369Tp46679/qhg8fjnHjxmHKlCnw8fHBI488ol5Oe/78+RLtV0BAQJnfXUX4+/trPhff/nXq1AGAcre/7fdXt25dTf6jR4/iwQcfRIMGDeDp6VnitiMAlV5eWa5cuYL09PQyLyG31w5XdfuKCMLDwxEcHIy0tDRkZGRg9uzZ6Natm7quVW3byjveizOZTHjmmWcwZswY9TLf+fPnY926dTh27BhycnIQExODd955B5988ond8iriZtxfSR/+/v6ay81t+ywV6TstWbIEbdu2hbe3N7y8vPDll19q2gpFUSrcz6loH6n4tLi4ODz99NNqHb28vBAVFaU+GCAuLg5vvvmmJj0yMhKXLl2q0HYoT1X7KEDt9H+AgnZtwIABuO++++Dg4IDhw4cjODhY/THKkSNHYvr06Xj88cfRoEEDxMTEIDw8XK1XVa1atQpubm6YNGmSZnpFvvdx48apfbaPPvoIffr0KdGu0I3H9ns8c+YMBg0ahEaNGsHT0xPdunUDgHJvRSyvnwKUPy6ydy6r7LipPLZ9FLPZjOzsbPz555+Ij4+Hv78/nJ2d1fTi+/bYsWMRFRWFCxcu4Pjx44iJicHIkSM1eUprB23Poa6urgBQol9e2XOqg4MDQkNDkZiYiPnz56vT77//ftSpUwcODg4IDw/HtGnTsGbNGrvlffLJJ5g7dy727t2LnJwcnDlzBvv378ecOXOqXfbZs2fRvHnzUtPc3d2hKApeffVV1K1bF/Xq1cPMmTPVH3R2cHDAtm3bcObMGZjNZjz00EMYPnw4AFS7nbveaiz40rBhQwAF9wtbxcXFlTtPREQEnJ2dsXXrVkRGRmLo0KHqzt60aVMEBwfj6tWr6l9SUhLS09M1O6/1HjzbetjWITMz0+79yvbWy7Y8AOpv0lTE2bNnS3xu1KgRgIKDrEuXLvj000/xxx9/oHPnzujZs6c6AA8PD9fMW3xdy3Lw4EH8+eefaN26Nfz8/NCxY0eICNq2bYsPP/wQQMF9k8WfAPLf//4X7dq1s1t+gwYNsH79esTHxyM2NhZNmzaFq6srunTpUu58pQWBbFkb5FOnTpVIO3bsGC5duoTQ0FD1V64BoE+fPpg9e7aa7+zZs+jevTt69+6tuY+9Ksqrj5+fH5ydnTXf77Vr15CYmIgmTZrYTS9NeHg49uzZo55QOnbsiPPnz2PdunXqfaNAwa/LX758GT/++COSk5Nx/vx5SMFVbmpZFd1XbmcODg6YPn06fvzxR5w7dw6urq7qvaeNGzcuceyeOXMGjRs3LrUsd3d3pKenq5/z8vKQmJioW91LM3ToUHTs2BGnT59Wf4CtMiqzz/j5+aFu3bqlHhuA/Xa4stvX6urVq4iLi8Nzzz2HunXrqr/5YrFY1PvKq9q2lXe8lyY/Px85OTmIjY0FUBD8GjRoEIKDgwEALVu2RP/+/bFt27YKlWfPrba/kj7s9Z2+/fZbvPjii1ixYoWa1qdPnxLn54q2BxXtIxUvz2w2Y+XKlZo6pqam4oMPPlDXY+7cuZr0lJSU63Y8lcZeHwWonf4PALRv377U6bbBp+nTp+N///sfrly5gqVLl+LXX3/V/PZOVbzxxhto06YNwsPDNU91qsj3PmrUKBw6dAinTp3CmjVrav0Rw1Qxtsfqk08+CZPJhF9++QXJycnqb5pU5FgpS3njInvnssqOm8pTfLzq7OwMX19fNGzYUP0Haml5gYKASe/evbFy5UqsXLkS/fv3V38Tzqqm++F5eXl2+y8V+d6OHj2K8PBw9ffrmjZtiscff9xu21uRss1mc6XaOCn2IIjmzZtjx44dSEhIwIkTJ+Di4oI77rijzIBObanR4EtISAhmzJiBtLQ0JCQkYMGCBeXOYzAYMHLkSCxZsgSbN2/W/Ihtnz59kJOTg4ULF6o/FHfx4kW7P8o4YsQIvP322zh79iyysrIwa9asajUSI0aMwIYNGxAdHQ2LxYLPPvusQv8dsfruu+/w2WefwWKxYN++fdi0aZPmx6F69uyJf/7znwgJCYGiKAgNDcU333yDI0eOVKoRsfXoo48iNjYWP//8M2JiYrBjxw4AwO7du9XI7Pjx47Fp0ybs378fOTk5eOutt5CTk6NeeVSekydPIikpCSKCH3/8EVOmTMGsWbPU/yzv2LFDfcLQ1atX8dRTT8HPz89u58TPzw+PPPIInnrqKbWhi42NRWxsLO69916cPXtWXSfrDz+tWrUKL774IoCCpwHcf//9GDZsGN58881Sl9GsWTNNZLgq9Tlz5gwURcHIkSPxj3/8A5cuXUJGRgamTZuGli1bolOnTnbTSxMeHo6jR4/im2++QVhYGBRFQY8ePbBo0SLNvpCamoo6derAw8MD165dw4wZMyr0lJrqHAe3ov379+Po0aPIy8uDs7Mz6tatCwcHBwDAE088gY0bN2L37t2wWCzYuXNniTbKVseOHbF3716cPXsWOTk5eOmllzQ/xlZRlf2ObPOnpaXBw8MDdevWxblz5/DGG29Uqqz69esjMTGxwv91mTRpEmbMmKE+XvDixYvqo5fttcOV3b5WPj4+CA4Oxr/+9S9kZGQgPz8fK1euxLVr19C2bVsAVW/byjveAWDZsmVqu/bnn3/imWeegaurq/oI4Pvuuw+bN2/G6dOnAQC//fab+oOhVpVpf4q7FfZX0p+9vlNqaiocHR3h6+sLEcH27duxc+dOTRmV+V6HDh2K77//Hhs2bIDFYsH+/fsr9OPZkydPxty5c9VzeWZmJg4dOqReSTZ58mQsXrwYBw8ehMViQU5ODo4ePar+WG91VLWPAtRO/wcAnnrqKWzevBmHDx+GiGD9+vU4ffo0HnzwQQAF3+v//vc/AAVXJTz55JPqD+FaVaX9cXR0xNq1a9G6dWuEhoaqQfSK9I19fX3Rt29fDB06FHXq1FEfuEE3j9TUVNStWxcmkwl//vknXnnllUqXUbw9KW9cVJFz2fUYN4kIZs2ahbS0NCQmJmLevHnqsdKlSxc0adIEs2bNQnZ2NuLi4kr9Z+748eOxcuVKrF27FuPHj6/0dqmOr7/+Gj/88ANyc3ORl5eHLVu2YO3ateoTGM+dO4eoqChkZ2fDYrEgOjoa7777LoYOHWq37Pvuuw/79u1T/4l1/vx5rFmzRu3LVKnYVrMAACAASURBVKfsiRMnYuvWrVi7di1ycnKQlZWF6OhoAAVX07Rp0wZz5sxBRkYGEhMTsWjRIgwaNEid/5dffkF6ejry8/OxZ88eLFiwQH0owY2kRsNu69atQ1ZWFho3bowePXrgiSeesDvPqFGjcODAAdx5552aTqqrqyv27duHEydOoEWLFvD09ERERITm15ZLG3DOmjULERER6Ny5M+688040bNgQDRo00Fw+Zo9tud27d8d7772H0aNHw9vbGzt27MCAAQMqXN6QIUOwY8cOeHl5Yfz48Vi6dKnmJBweHo60tDT1pOTh4YEWLVqgSZMmmkvzKvMIWGsk0PpXv359KIqCevXqqZeK33fffVi6dCnGjRsHLy8vbNq0CTt37lSvrijPgQMH0KpVK7i7u2P48OF47rnn8PLLL6vpUVFR6Ny5M9zd3dGmTRskJydj9+7d6rLLs3LlSrRv3x49evSAyWRC//79kZCQoP6yte2foijw9fVVOz1vvfUW4uPj8e6778Ld3V19aov1CoCcnBwkJiZW6j9BpdXHeun24sWL8be//Q2dOnWC2WxGQkICtm7dqn5X7777brnpxTVu3BgBAQHq/g4U7R+2J5T58+cjISEBPj4+aN++Pbp166YOwspTkX3oZnjUcHXYrl9CQgJGjBgBb29vNGzYEOfOnVOfdHbvvfciMjIS06ZNg7e3N1588UWsXbu2zMDZ448/jr59++Luu+9GYGAgzGazejVgRepS3rSK5l++fDlWrFgBk8mERx55BEOGDKnU/KGhoYiIiFCf6vPNN9+UW//XX38dQ4YMQf/+/eHu7o7Q0FB1oGCvHa7s9rX1xRdfqP9x9vX1xb///W9s2LBBbS+r07aVd7z/+OOParvWtm1bXL58GXv27IGPjw+Agv86DxgwABERETCZTHjooYcwcOBAzJw5E0DV2p+beX+lqiu+XSuzne31nR544AGMHDkSnTp1gp+fHzZt2oSBAwdWeXkBAQH4/PPP8corr6hPYhw5cqSmj1RaeePGjcOMGTPUvpXZbMarr76qBgEjIiKwYsUKTJ8+Xf1v9NSpUzVXbFVVdfootdH/AYBHHnkEb7zxBh577DF4enrivffew/bt29VbG1JTUzF48GCYTCa0bNkSeXl52L9/v/o9VLf9Wb58OcLCwtC9e3dcuHChwn3jiRMn4r///S/Gjh1b4eVS7Sl+rC5evBgHDhyAh4cHevTogYcffrhS85c2rbxxUUXOZRUdN5XH0dERvXv3Rps2bdCyZUsEBgbin//8J4CCq0y3bt2KI0eOwM/PDwMHDsTIkSPh5OSkKePvf/87DAYDPDw8StzuVNE2tKrn0NTUVIwZM0Z9YtD8+fPxzjvvqEGs9PR0TJ06Ff7+/vD29sazzz6LuXPn4qmnnrJb9tChQzF9+nQMHToUHh4e6Nq1K9q2batun+qU3bZtW+zYsQNLly5FvXr10LRpU/V2JUVRsG3bNvz111+oV68eOnbsiE6dOuHtt99W59+0aRPMZjM8PDwwbdo0vPfeexgxYkQVtqC+FLnN/zWVnp4OLy8vHDhwoEL/1aiIe++9F3379lWvuKCbw/79+/HOO+/oetkyEZWkRzt8s2H7Q7eLYcOGwWQyqbc5U+2rifantL6x9Tce4uLi7AZ4iW5Uy5Ytw+LFi9Wry6xCQ0Px4IMPqv9kIQJq+MqXG0FSUhK++uor5OXlISUlBc8++yyaNWtWof+olmXjxo1IT09HTk4Oli9fjiNHjmDw4MHXsdZUE0JDQznwIaoBerTDNzu2P3Sr2rZtG5KSkpCfn48tW7Zg06ZNGDZsWG1Xi2zo0f7Y6xvn5eXhjTfewIABAxh4oZvKoUOH1FuOjx07hrfffrtEm3bgwAH89NNPGDduXG1UkW5gt13wxWKx4OWXX4aPjw8CAgIQHx+PrVu3Vui2jLJs3LgRjRo1gp+fH5YtW4YvvvgCAQEBWLdunXpri/Wv+K0uepk0aVKZy7b+avjtVjYRXT8LFy4s81i1/uheWarTDrP9IbqxFD9mrH+9e/cGUDAIad68Oby8vPDSSy9h2bJl6N69e63Vtzp9M7Y/FVdW3xgAjhw5Ak9PT3z33XdYtGhRLdeUbjf22ix7zp8/j9DQULi5uaFfv34YNGiQ5oquzp07Y8CAAfjggw/UW4+vp/Pnz5fZVlTk9p5bseybyW1/2xERERERERERkZ4ca7sCeuEP/dHtiLHUmse2hm43bGdqB9saut2wral5bGfodlSTbc0tG3wBAHP/k3B3KGpE6joWvHcpvLLdxSbN1Vjw3tnmqnenwvzGwnwuxqL8xsItZ00z2mxJJ6N2PgBwtOa3lmksym/N5+ioaPIW5Cs5zdFBO81oLLmc0spyKGXZxfM5lLNsB00drPMX7awOigUAYJB8AIAiRY8mNeRmF7zJyyl8zS0qLLdwWk5W0TRremGaWPMAkJxsbVqeTVqudj4AsBTmFzV/rk3+HE2ZllzbtNwSy7YUyyc2+a3TiucpmJZbclp2tjYtpygt3zotsyBPfpZNHTIL09KLpuVfzUaoxWabUo16PkbbaCuFxwJgfc23Sc0vlsc2vWCaYptfKcxfSllqPqWU+azLqWB+pVj+ouUVTTMgr8w027IMan7tq7asgleH0uaTkmnW9w5qmsUmzaJJK3hv0aQ5SlF+x2JpDjYnXUOx/LZp1veaabBOs+ZHmfm1ZRUuT1Bmmm1ZBimeppRIMxRO09ZB0aQZNPMVvFdspsH6Xn01aNKUvnNAtcjPCIPNV2IoPBdbpymlpMH2bj7r+8J8YtsLVHcybR4AUKz5HEouR7FOcyzaj6zpSil1KF4vxSatRFmlLcemb1WU31pmKWml1a9EHWzSHLXTyq1fKetRalmOJcuCQ9lpxetQ2rI1ZRWvs833Wu76GO3Xy8WmrDqFaW6F34ubzXxehe/dDdo8AOBeuBqeNo2TdZpbsVcAcAfQQvkTVEvapQN1i54cZqqTAQBwcS14dXC2eapYnTQAgMXJZppTJgDAYCzI7+ScpiY5O2ZqXo2FrwDgZLwGAHC0mWZwLChDKZymGFPVNKUwzeCQUThfhprmUvjexaGor+xiKOgj1Cls62z3X1eHgh3W1aBoXgvmK0ir61C0U7so2nwuNg2zNZ+zNU2xLatwPptG1KnwfGssPDwcbbqHhryCiUpuYWLR0AqwTsspmkHUfKLNA0CyC95LaWnWIURp+QunSU7J/NY8yFFs0go3bF5R46HkFTzRTRHXgvVSip7wZnAoeNqkg2PBk1wNju5F8zm6lZhmMHoVvLFOM9o8rVKd5q39DADGgvfiaCqqq6MJDs9rn1Slt9vuN1+IiIiIiIiIiGoSgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHTH4QkRERERERESkIwZfiIiIiIiIiIh0xOALEREREREREZGOGHwhIiIiIiIiItIRgy9ERERERERERDpi8IWIiIiIiIiISEcMvhARERERERER6YjBFyIiIiIiIiIiHSkiIrVdCT0oilLbVSCqcbfo4XxDY1tDtxu2M7WDbQ3dbtjW1Dy2M3Q7qsm25pYNvhARERERERER3Qh42xERERERERERkY4YfCEiIiIiIiIi0hGDL0REREREREREOmLwhYiIiIiIiIhIRwy+EBERERERERHpiMEXIiIiIiIiIiIdMfhCRERERERERKQjBl+IiIiIiIiIiHTE4AsRERERERERkY4YfCEiIiIiIiIi0hGDL0REREREREREOmLwhYiIiIiIiIhIRwy+EBERERERERHpiMEXIiIiIiIiIiIdMfhCRERERERERKQjBl+IiIiIiIiIiHTE4AsRERERERERkY4YfCEiIiIiIiIi0hGDL2W4ePEiDAYDzp07h4ULF6Jfv361Wp+DBw/C29u7RpY1evRoTJgwoUaWRURERJUXGhqK119/Xf3s7u6O77//vhZrRERUpLLjpxth/BEdHQ2j0VirdaBbG4Mv5VAUBQAwa9YsbNmypVbr0q1bN1y9erVW61ATRo8eDScnJ5hMJri7u8NkMuHDDz9U0yMjI+Hg4KBJf/zxxytU9tWrVzFq1Cg0aNAAXl5eGD58OJKTk9V0i8WCmTNnokmTJvDw8EC7du2wcePGaq/TBx98gODgYHh5ecHPzw8PPfQQjh8/rqYvXLhQXRfrehkMBkyePLnay6abQ69evbBo0aJqlVETHYYbIRBNRKVLS0vDPffcU9vVuGnExsYiIiICbm5uaNKkCd55550KzRcfH4/+/fvDbDbDYDBg3bp1lS47MzMTY8aMgZeXF7y9vTF+/HhkZ2dXe52uXLmCgQMHwmQyoV69enjxxRerXSZRVd0I46eqsI7/blYnT55E165d4evrC09PT7Ru3RorVqzQ5DGbzXB1ddWMp3799dcKlb969Wq0bt0aHh4eaNasGebNm3fdyi7LwYMHNWMlk8kEo9GI9u3bq3nef/99dOnSBXXr1kXz5s2rtTw9MfhSy0QE+fn5tV2NGpObm2s3z6hRo5Camoq0tDSkpqbiySef1KQHBARo0teuXVuhZY8YMQLp6emIjY1FXFwc/vzzT4wYMUJN/+CDD7B27Vrs27cPKSkpmD9/PoYNG4aTJ09WbiWL6d27Nw4fPoykpCRcunQJERER6NWrl5o+a9YsdV1SU1Nx9OhRGAwGTd3o1rZjxw688MIL1S5H7w5DTXekIiMjERQUVGPLq6h169aVCJg6Ojqif//+ah49BkFJSUno0aMH6tWrB09PTwQFBWmufACAc+fOYcCAAfDz84Ofnx+efvrpCrW7RNWRn58PEblu5endN7JYLHj44YfRqlUr/PXXX9iyZQvefPNNfP7553bnNRgMeOCBB7B+/Xo0bty4SmU/99xzOHnyJE6dOoWTJ0/ixIkTmDp1arXXa9iwYTAYDIiPj8f333+PzZs34+233652uRXFtub2wu+7+vRo6xo0aIA1a9bgypUrSE5Oxvr16/Hyyy9jz549ah5FUbBy5UrNeKpVq1Z2yz527BjGjh2LN998EykpKdi1axeWLVuGjz/+uNpll6dbt26asVJKSgoaNmyoGSs1bNgQM2fOxEsvvVStZemNwZdCCQkJ6Nu3Lzw9PdGiRQvs2rVLTZs3bx4iIiIAAEuXLkWHDh0088bFxcHR0RHnzp0DAJw/fx6DBw9GgwYN0LBhQ0ycOBHXrl1T8xsMBixZsgSdOnWCm5sbjhw5gry8PEyZMgX16tXDHXfcgbfffhtBQUFYvXo1gJL/1R49ejRGjhyJCRMmwMvLC40bN8by5cs19fr4448RGBgIT09PjBw5EiNGjMCYMWMqtD0yMjIwcuRIeHh4ICgoCJGRkWpau3bt8OmnnwIAsrKy4OLiglGjRqnpvXv3Vv+LHxoaiilTpmDAgAHw9PTE4sWLK7T86y0jIwO7du3CnDlzUKdOHXh6emL27NnYvn07Lly4AKDgP1U9evRAYGAgAKBfv37w8fHBL7/8Yrf89PR0vPDCCwgICIDJZELr1q1x6NAhAECzZs3UW8YsFovaMbLdJ2wtW7YMHTp0QMeOHa/HqhPdtETkhvwP1LBhwzSdgIsXL8LFxUXTCdBjEFS3bl18+OGHiI+PR3JyMvbs2YM1a9bgo48+AlA06GvatCni4+MRExODw4cPY9q0adVaLt0cDAYDvv32WwBFgcv3338fjRs3ho+PD5588klNgMReX+Wll15CQEAA3N3dERQUhPfee09N++OPP2AwGLBy5Uq0atUKbm5uuHLlSrn12759O1q1agWTyYS+ffti6tSpCA0N1dS/eN8IAFasWIE2bdrA09MTHTt2xO7duwEAycnJqFOnDmJiYjTL6d69O1577bVy6xIdHY1z587h9ddfh7OzMzp06ICJEydqrrQtS/369TFp0iR07doVBkPJbrS9srOysrB27Vq8+uqr8PX1ha+vLxYsWIDIyEjk5OTYXf6xY8fw0EMPwd/fH76+vvj73/8OoKAvunfvXixatAhubm4wm82YOXNmhdapPK+//joaN24MX19fTJ06FeHh4Zg/f766rkajEWvWrEFAQAB8fX0BAEuWLEHLli1hMplgNpsxe/Zsdd978cUXNYFqANi3bx88PDyQmZlZrbqSvpo1a4YFCxYgLCwMJpMJb7zxBkJCQuDn5wcfHx/06tULZ86cUfPbjp+s8y9cuBDh4eFwd3dH27ZtcfjwYc0yyht/AMDGjRvRvn17eHl5oUOHDvjiiy/UtMqMT+xZvXo1zGYzfH19MXr0aGRkZKhpp06dQkhICDw8PNChQwcsWbJEbQt27doFf39/5OXlqfmvXbsGd3d3dVxQWltnHdeNHTtWHdd9+umniImJQefOneHh4YGePXvi8uXLduvu7u6OgIAATf9JURT8/vvvmnxVCZjHxsbC398fvXv3BgAEBwcjJCSkRDtc1WB8dHQ0unfvDh8fH/j7+5c5bt2+fTsSEhI03+/AgQMxYMAANGzYsErLrjFCIiISFhYmAwcOlLS0NElISJBu3bqJwWCQP/74Q+bOnSsREREiIpKUlCSurq4SExOjzvvKK69IeHi4iIhkZWVJYGCgzJ07V7KzsyU5OVl69+4tY8aMUfMriiLt2rWTuLg4sVgskp2dLfPmzZOWLVvK2bNnJSsrS5577jlxcnKSyMhIERGJiooSo9GoljFq1CipU6eOfPnllyIismnTJjEajXLu3DkREYmOjhZXV1eJioqS/Px8Wb9+vTg5Ocno0aPtbotRo0aJk5OTrFu3TvLz82XPnj3i6uoqhw8fFhGRqVOnytixY0VE5KuvvpKgoCBp1KiRiIjk5OSIm5ub/PzzzyIiEhISIh4eHhIVFSUiIpmZmXaX7e3tLT4+PhIcHCzTp0+Xa9euqemrVq0SFxcXadCggTRp0kSGDh0qcXFxdtfp2rVroiiK5nvbt2+fGAwG2bZtm4iIHD9+XNq1aycnTpyQ/Px8+fzzz8Xf31+uXLlit/whQ4ZI9+7d5Y8//hARkdjYWImNjVXTDx48KJ6enmIwGMTBwUFefPHFUsvJzs4WX19f+eijj+wuk24dISEh8tprr0l2draMHz9e/P39xcPDQ5o3by4bNmxQ823YsEHatWsnnp6e0r59e9m8ebOaVlobMX78eM1yzGazrF27VkQKjqXAwEBZvHixNGrUSEwmk0yfPl3++usvGTRokJhMJmnZsqUcPHhQnX/u3LlqW2ct7/XXX5eePXuKm5ubtGnTRr799ls1fe/evXLPPfeIl5eX+Pv7y9ChQyUxMVGz3tOmTZNBgwaJu7u7BAYGypYtW0RE5PDhw+Li4iIODg7i5uYm7u7uEh0dXe52zM3Nlddee02Cg4PV8jZu3KhujxEjRsiYMWPE09NTGjVqJOvXr5eff/5ZOnXqJCaTScLCwuTSpUv2v7Bi3n//fWnQoIHk5eWJiEhcXJwoiqJpmz7++GO58847K1ReVFSU3H///eLt7S1+fn5ltttnzpyRVq1ayQsvvCAiIidOnBCDwSCpqalqnsjISHFzc5Ps7OxKrxfd2KzthpWiKHLo0CERKTi+jUajvPzyy5KTkyOnT58Wb29vWbdunYhUrK+ydu1auXz5soiI7N+/X1xdXeXrr78WEZGzZ8+KoigSHh4uiYmJkpubKxaLpcy6nj59WpydneWzzz6T/Px82bt3r5hMJgkNDdXU37ZvlJOTI8uXL5egoCA5fvy4iIjs3LlT3Nzc1PPrE088Ic8884xaxu+//y5OTk52j+N3331XOnTooJm2efNm8fHxKXe+4mzb1IqW/d///lcMBoOkpKSo6UlJSaIoirqeZbl06ZJ4eXnJm2++KRkZGZKbmyt79+4VEZEvvvhCvLy8NPmty0pLS6vUellFRkZK/fr1JSYmRvLy8uStt94So9Eo8+bNE5GCtkpRFBk2bJikpqaqfbxNmzap/aGff/5Z6tWrJ8uXLxeRgv6Rs7Ozum+JiAwbNkyeeuqpKtWRao7ZbJYmTZqofeljx45JVFSU5ObmSmpqqgwZMkS6du2q5rcdP1nnDwoKkt9++00sFotMmTJFgoKC1HR7449Dhw6Ji4uLfPXVV5Kfny/bt28XFxcX+eGHH0SkcuOTslj36cGDB0taWpokJibKvffeKxMmTBARkby8PAkODpbJkydLdna2xMXFSevWrcVgMIiIiMVikWbNmmn6bsuWLZO77rpL/VzaONA6rtu5c6eIiHz44Yfi5uYm/fr1k/j4eMnMzJSwsDC1HhXRtm1bcXFxEUVRpG3btvLXX39pvot69eqJj4+PdOjQQZYtW1ahMtPT06VTp06yefNmsVgscvz4cWnUqJHs2bOn2mXHxMSIi4uLrF69WnJyciQrK6vMfl+fPn3k8ccfLzVt1apVmv3qRsPgi4hcvHixREd59+7dpQZfREQeffRRmTx5svrZbDbL+vXrRUTk888/l8DAQE35P/30kzg7O6sdE0VRZM2aNZo8gYGBsmrVKvVzZmamODs7lxt86dOnj6YMPz8/2bp1q4iIjBs3Tp544glN+v3331/h4Ev37t0104YPHy4TJ04UEZEdO3aI2WwWEZHp06fLggULpEWLFnLixAmJjo4WPz8/db6QkBC1IayIo0ePqoOzEydOSOfOnWXYsGFqelxcnJw6dUpERBISEmTUqFESGBgoGRkZdssOCwuTAQMGSHJysiQmJkpERIQYDAa145Seni5PP/20GAwGMRqN4ubmphncliUxMVEURZHffvvNbt6UlBRZsmSJbNq0qdT0NWvWiIeHh6Snp9sti24d1kHU8uXL5e6775akpCQREblw4YK6X9nrdFQl+GLtROfm5sqxY8fE2dlZ7rnnHvnhhx/EYrHI7NmzNSewynakDh06JD/99JNY/r+9O4+Posj/P/6eSQI5yH1I5IpyCgKrLIe6CggoopyCIpIIyu3xExQE10UQBA8UZF0UkAhyyXIpKCpnCOAXVEBAWUWBIIdcCgQiuev3R5JmJgnJhNCA8no+HnlMpqqmunpmurr6M93V2dnmyJEjpmnTpm7bc7NmzUxkZKTZuHGjMcaY8ePHm5CQEGsAX9Id6JAhQ0ydOnXMd999Z4zJ6dvzDmbsGNjkqVu3rnnhhRes56U5CPJk8HHfffcZPz8/43A4TJUqVaw+8fvvvy9wUBcfH2+cTmexB3X48yku+BIcHOwWEOnSpYsZNGiQMcazsUp+nTt3Ns8995wx5lzwxTU4W5TRo0ebpk2buqXFxsYWCL7kHxvdeOONZubMmW5pbdu2tdZ7/fr1JiwszAouDhkyxLRr167Y9owaNco0a9bMLW3NmjVufagnCgu+FFf3unXrrAO1PNnZ2W6f3/m89tprplGjRoXmzZw50xqb5dm7d69xOp3m4MGDHq1Pfi1btjQvvviiW1qVKlXcgi9Op9McOHCgyHqeffZZ8+CDD1rPW7VqZV599VVjjDG///678fPzM1u3br2gNuLSiYmJMaNHjz5v/o4dO4zT6bT24YWNGd544w3red4+K+8Hg+KOP/r06WO6d+/ulv/QQw+Zfv36GWNKdnxyPnnfaddjwrwgkDE526+vr69JTU218qdNm+a2TY8ePdq0bt3aet64cWMzfvx463lhfV3+47o//vjDOBwO6wckY4yZNGmSufnmm4tdB1eZmZlm9erVZsSIEW5tTkxMNCkpKSYzM9OsWLHChIeHWwHS4vznP/8xgYGBxsfHxzidTjNs2DC3/Aute8CAAeaBBx4otty+ffuMl5eXWbduXaH5V3rwhcuOJB04cEAOh0OVK1e20q677rrzlu/Zs6fmzJmjrKwsrVq1SqdOnVLHjh0lSUlJSdq3b5/CwsKsv5YtW8rLy8vtVLEqVaq41Xnw4EG35fv6+ioyMrLIdkdHR7s9DwgI0OnTp6368i8j//OixMTEFHied3lO06ZN9euvv+qnn37SypUr1apVK7Vs2VLLly/XypUrdeeddxZZV1Fuuukma71vuOEGTZgwQQsWLLCuK42JibEuC4qKitLUqVP166+/auPGjcXWPWvWLJUtW1Y33HCDmjRpog4dOsgYY50m279/f3377bfat2+f0tPTtXz5cvXt29ftGsnCJCUlyeFweDQ3RVBQkJ544gk9+uijXrJP9QAAIABJREFUBU7/k6QpU6aoe/fu8vf3L7Yu/PWUKVNGZ86c0XfffaesrCxVqFBBtWrVkpRzGUHnzp111113yel0qk2bNurYsaPi4+MveHn+/v4aPny4vL29VbduXdWvX18NGzZUw4YN5XA41L17d+3evdvqVwrTr18/1apVSw6HQ7169XIrf+utt6pBgwZyOByKiorS4MGDtWrVKrfXP/jgg9YkoX369NGpU6f0008/XdD6TJo0SePGjbOuLb722mt14403Wvl33nmnWrduLUmKi4tTSkqK4uLiFB0dLV9fX3Xu3FnffPNNiZa5YcMG/e9//1OvXr2stNOnTys4ONitXEhIiCQpOTm5yPomT56sdu3aKTY2Vj4+PipbtqzuuOMOtzJLly5VSkqKNm7cqNjYWIWHh0vKOf23WrVqev7553X27Fnt27dPEydO9Gi5+OuJiopyO+3cdYzgyVhl4sSJqlevnsLCwhQaGqpPPvnE7dIih8Ph8bjC0zFJ/rS9e/fq8ccft9oYGhqqhIQEHTx4UJJ022236dprr9WCBQuUlZWlDz74wKO7pQQGBurUqVNuaSdPnlRQUJBH61OaugMDAyW5b5N55YtbflJS0nknkjzfcl2XWVKFfW7557lxOp0FTvOfO3euGjVqpIiICIWGhmrSpElu350+ffpY+65Zs2apdu3abhNn4srl+n3Ys2eP7r//flWsWFEhISH6xz/+IUlFXoJYvnx56/+AgABJchtjFHX8sX///gLHZ1WrVtX+/fsllfz4pCiux2QxMTFKS0vT8ePHdejQIUVFRals2bJWfv5t5LHHHlNCQoIOHDigHTt2aNu2bYqLi3MrU1j/53pc5+fnJ8n9/fL39y9yPFYYLy8vNW/eXEePHrUuF5Sk22+/Xf7+/vLy8lLLli31zDPPaNasWcXW9/7772vEiBFatWqV0tPTtWfPHq1Zs0Yvvvhiqesuqn9z9d5776lWrVrW9+3PhuCLZO009u3bZ6Xt3bv3vOVbtWqlsmXLasmSJZoxY4a6du1qbYRVqlRRzZo19fvvv1t/J06cUEpKittGlf864QoVKrgt/+zZs8VeP13cOrnWJ8mak8YTSUlJBZ5XrFhRUs7G36RJE3344Yfat2+fGjVqpBYtWmjFihVauXKlWrZs6fbawq6JLilTzLWDxeVLOZ3a3LlzdejQIe3evVtVqlSRn5+fmjRpIknasmWL4uLirPW85ZZbdPvtt2vZsmVF1pu3o/D0gDErK0vp6enavXu3W/rOnTu1bt26AhMM4+oRGxurXr16aeDAgQoPD1fnzp2t66eLG3RciKioKLfn/v7+bv1UXhCwqJ19UQOpLVu2qHXr1oqOjlZISIgeeuihAv1aSZd3PseOHVNKSkqRQVA7BjZTpkzRXXfd5TaQKs1BkKeDD4fDoUaNGikoKEiPP/64pJxB1tKlS7Vnzx7FxMTonnvuUffu3SXJCjIDUvFjlS+//FJDhw7V1KlTrbz77ruvwL7W0/27p2OS/PXFxMQoPj7erY3Jycn6z3/+Y5Xp06eP3nvvPX3yySfy9vZ2m9D+fOrXr69du3a5zTGyefNm1a9f36P1KU3dNWvWlK+vr7Zs2eKW7+/vX+y2HxMTc96xRv369XXq1Cm38dvmzZsVExNzwcGXwj63/Puc/PNyHThwQLGxsRo+fLiOHDmiEydOaMCAAW7fnQ4dOig5OVmJiYmKj4+/7LcXhudct9F+/fopKChI3333nU6ePGnNaeLJmPx8ijr+qFSpUoH8PXv2WAHBkh6fFCX/MWHZsmUVERGhChUq6NixY253J8u/jZQvX1733nuv4uPjFR8frw4dOlhzP+a5GMdGJZGZmVnscYonn9uWLVvUsmVLNWzYUFLOvuThhx/W0qVLS113Uf1bnqysLMXHx/+pj5UIvihn59KsWTMNGTJEp0+f1pEjRzRq1Kjzlnc6nYqLi9PEiRO1ePFit8mA7rvvPqWnp2vs2LHWxHUHDx50mxCqMLGxsXr99deVlJSk1NRUDRs2rFSdV2xsrBYsWKC1a9cqOztb8+bN8+jskDwbN27UvHnzlJ2drdWrV2vRokVukxq1aNFCb7zxhpo1ayaHw6HmzZtr3bp12rx5c4k6t/zmzZtnHbT89NNPevbZZ9W+fXuVKVNGUs5dYfJ+8fr99981YMAARUZGWgGUouzatUsnTpyQMUZff/21Bg4cqGHDhlm/NN12222aPXu2Dh06JEnatGmTEhIS9Pe//73IeiMjI9W5c2cNGDDA6oB3795tHTRPnjzZavPx48f1xBNPyM/Pr8AtQSdPnqxbbrnF7Zd6XF2cTqcGDx6sr7/+Wr/88ov8/Pys/qW4QUd+gYGBSklJsZ5nZmbq6NGjtrW9MF27dlWDBg30888/WzPul0RJBieRkZEKCAi44LNmLsSJEyc0f/589e/f3y29NAdBngw+XGVmZurnn3+2nteoUUPLli3TkSNHtHPnTvn6+uraa6+9om+7iEuvuLFKcnKyvL29FRERIWOMPv30U3322WdudZRkjNK1a1dt2rRJCxYsUHZ2ttasWVPsuEiSnn76aY0YMcKazPHs2bPasGGD25mjsbGx+uqrrzRy5Ej17NnTo0m677jjDlWpUkXPP/+8UlNTtXXrVk2ZMsXjAX1aWppSU1NljFFGRobS0tKsO5YUV7evr68efvhhDR8+XMeOHdPRo0c1fPhwPfLII9ZY53y6d++uH3/8Ua+//rrOnj2rjIwM62zCmJgYtWzZ0hrL7tmzR6+99prbOo0YMaLIM7vzi42N1ZQpU7Rt2zZlZmbqjTfe0K+//lrka86cOWOdVezl5aWNGzdq5syZbmW8vb3Vo0cPDRw4UD///LMeeughj9uEK0dycrICAgIUFBSk48ePa/jw4SWuI38/UtTxxyOPPKKFCxdqxYoVys7O1meffVbgOOxiHJ8YY6w7kR49elQjR460zlxp0qSJKleurGHDhiktLU179+51m4w8T+/evRUfH6/Zs2erd+/eJX5fSmP58uX66quvlJGRoczMTH388ceaPXu2FZj+5ZdflJCQoLS0NGVnZ2vt2rWaMGGCunbtWmzdt912m1avXm0Fj/fv369Zs2ZZx0qlqbtv375asmSJZs+erfT0dKWmpmrt2rVuZZYsWaKTJ08WOJNIygnMpKWlKT09XcYYpaWluQXJrhQEX3LNmTNHqampqlSpkpo2bapHHnmkyPI9evRQYmKirr/+ereDcz8/P61evVo7d+5UrVq1FBISolatWrnNAl3YwGDYsGFq1aqVGjVqpOuvv14VKlRQdHS022ltxXGt94477tBbb72lnj17KiwsTMuWLVPHjh09ru+BBx7QsmXLFBoaqt69e2vSpEluAY6WLVvq9OnT1iz7wcHBqlWrlipXrux2ymBJ71Ty7rvvWndXaN26tW699Va3yyoSEhLUqFEjBQYGqm7dujp58qRWrFjh0WU6iYmJqlOnjgIDA9W9e3c99dRTeuGFF6z8vMsV8mYVj42N1eDBg9WtW7di646Pj9ff/vY3NW3aVEFBQerQoYN16vbXX39ttblevXo6fPiwVq5caV0qIOXMyj5r1qwCB3G4uqxZs0ZbtmxRZmamypYtq4CAAHl5eUnybNDhqkGDBlq1apWSkpKUnp6uf/7zn26z73uqpEFg1/J5l98EBATol19+0SuvvFKiusqXL6+jR496fDZK//79NWTIEH3//feScg4md+zYUaJllsT06dMVGRlpzfqfx5ODoPMpavCxadMmrV69WqmpqcrOzlZiYqLeeustt1/6v/vuO6WkpCgrK0srV67UqFGjCtyOGn8N+fevJdnfFjdWufvuuxUXF6eGDRsqMjJSixYtUqdOnS54eVWrVtX8+fM1fPhw686HcXFxbmOSwurr1auXhgwZYo1lYmJiNHr0aLe+LCQkRJ07d7ZugeoJp9OppUuXaseOHQoPD1fbtm01dOhQdenSxaPX+/n5KSAgQPv379ejjz4qf39/6w5LntQ9YcIE1ahRQzVq1FCtWrVUp04dvfnmm8UuNzo6WgkJCVq+fLkqVqyo6Ohot7u3zJ4927pktUmTJurUqZMGDx5s5e/fv79El17ExcXp8ccfV5s2bVS+fHkdOnRITZo0KXIsWatWLY0cOVLt2rVTaGioXnvttULHUb169dK3336rBx988ILPzMGllX8bHT9+vBITExUcHKymTZuqbdu2JXp9YWlFHX/ceuutmjFjhp555hmFhYVp6NChmj17tnUWhuT58UlRvL29de+996pu3bq64YYbVK1aNb3xxhuScs4wXbJkiTZv3qzIyEh16tRJcXFxBQKneZeIBwcHF9jmPO07L/Ruj8nJyXr00UetOwa99NJLevPNN60gVkpKigYNGqSoqCiFhYXpySef1IgRIzRgwIBi6+7atasGDx6srl27Kjg4WLfccovq1atnvT+lqbtevXpatmyZJk2apGuuuUZVqlQpcLnSlClT1LVr10Iv0Rw9erT8/PzUr18/7dmzR35+flfmNA6XeI4ZeOjMmTPGx8fHmuH7YrjlllvM2LFjL1p9AC6O5s2bm5dfftnMnTvX1K5d2wQGBprw8HBzzz33mJ9//tkqN3/+fFO3bl0THBxs6tWr5zZxc/4JdzMyMkzv3r1NaGioqVSpkpk0aZK57rrr3CbczT8hWV478iQlJblN1ph/8jzX+gorv2TJElOtWjUTGBhoGjZsaCZOnOg2KV3+5RljjNPptCadzMjIMJ07dzbh4eEmNDTUJCYmFvk+ZmRkmFGjRplq1aqZcuXKmerVq1uTZhc2AbHrss73nhTlhhtuMKNGjSo079ixY6ZTp04mMDDQREZGnvcOZ4VZs2aNufXWW01ISIiJiooyvXr1MsbkTGLXoEEDExQUZIKDg03t2rXN2LFj3SZIHTlypImIiDABAQGmXr165sMPP/R4ucCl9NBDD1kTaZbWiBEjzN13331R6vorq1mzZrGT4xYlOzvbVKhQwbrJRGmkpKSYgIAAa8J14M/q3XffNTVr1iyQ3qxZM/PKK69chhbhSuYwphTXtuCiOXHihL766iu1aNFCKSkpGjhwoDZs2KCdO3dav3yX1MKFC9W6dWv5+Pho+vTpevLJJ7Vz505VrVr1IrceAADg/JYuXap//OMfCgoK0ieffKIHH3xQy5cvLzChdEkdOXJEDRo00HvvvWdNqI2LZ968eerQoYOysrI0duxYTZo0SXv27CkwqXhJGGM0ZswYLVmyRJs2bbqIrQXst2HDBkVHR+v666/X9u3brbNfXC+7SkxM1L333qukpCS3M90BLju6QmRnZ+uFF15QeHi4qlatqkOHDmnJkiUXHHiRcoIvFStWVGRkpCZPnqyPPvpIVatW1Zw5cxQYGKigoCDrL+95SedkKKn+/fufd9l5s5lfbXUDAPBnl38fmfeXd1leYmKiatSoodDQUP3zn//U5MmTSx14eeaZZ1StWjW1b9++QOCluPacz/r168+7vy/ppZMX4kLbbZe3335b5cuXV4UKFZSQkKDPPvusVIGXY8eOKSgoSO+//77efffdi9hSwDOl3cb279+v5s2bq1y5cmrfvr3uv/9+DR061Mpv1KiROnbsqLffftuWwMv+/fvP20d5cnnPX7HuPxPOfAEA/CmMHTtWY8aMcbsO2hgjh8Ohzz77TLfddttFWc7+/ftVu3btQpfTvXt3TZo06YqsGwAAAFeuv2zw5UInKQL+zP6im/MVjb4GVxv6mcuDvgZXG/qaS49+BlejS9nXeF+yJV0G1V7MVpDLVTsBuRdZ+eem+brk5aWVcUkr63RPK+vybpXJzfPxcn90Le/jde6DzMv3zluOS13eTvc817p8vN3zcv435y3vnW85XoW8zsdl2V5ehb9Okry93ZfjVchyfLzPraNXbv1eJud2i46sDCvPkZF7q6/cOxQ4Ms/lKfd/q4wkZWW65cm1fEb6+fPyv86lvLHKn7tLgpVmlXG5G0xu+13TjAd1mULqyvvfuLQrOz3D/XWFlM9OL6SujNw8l7pMRqau/egr4fII/+KgAnVuwOKXu1nk3Q+ijDmX55v76OOS5pP7mLc5lXGpK68b8bbKuLwuN8/LKnsu71z5c+30KlBeLuUd7mVc8vKuT/W28ly2+7wyrsvJV97pWj4vzSrjmmfc6vJSYXmmQJ6VZrILlpf761zLOfOVKayuwvKcLss5V797na55jtw81/Y5CrTPpc5C6nIUWE52IXnuy3Mrr8LyCi7bka+cWxtMtrxe6CxcXt7e3gX+z/8oybps2fXy5bzbt3uS53qr9/zli8orrJxrXl4bC8vLX1dRdbqm5dVZ0roKy8tfV2GvK+p9vtC6inqdp+vqyffAyyXP5wLrKqrNRbXPx8enQFqh5b295SQIcPn8PVXy/+Pcc7+UnEff3MeyKS55yTmPZc6lOcrkvNbPJ+cxqMyZc8W9c9J8vc/mVJX7KEllfHLKebukOXPLO3PTnD7J55aTl+f1R+7rzrXZN285Xunn0pw5xyf+uYOMci7HNX5eOf2Kn9Ph9pjzupy8AK9zfY+vw72cr0u/lFfONzevrMO1rpz//R3nypfJ3c3mjem8z+2S5ZWRu0/OzH3McNknZ+QWTHMZgOWl5ZVzKa+0fHnpLguy0lzKp+b8b/LyXJeTW86k5tXtsr2m576xGee2d2Xk3HXIoZxHpyPg3Hp45f5fJjTn0cfl7mc+5QqmlQ1zT3MrH+hexts1L8j9UVK2T5C8/p/7narsxpwvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANnIYY8zlboQdHA7H5W4CcMn9RTfnKxp9Da429DOXB30Nrjb0NZce/QyuRpeyr/nLBl8AAAAAAACuBFx2BAAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANiL4AgAAAAAAYCOCLwAAAAAAADYi+AIAAAAAAGAjgi8AAAAAAAA2IvgCAAAAAABgI4IvAAAAAAAANrqqgy8HDx6U0+nUL7/8orFjx6p9+/aXtT3r169XWFjYZW0DgNJr3ry5xowZYz0PDAzUpk2bLmOLzm/t2rXy8fG53M1AKYwcOVKtWrW63M1AKfyZ+gz8dbRq1UovvfSSJGn//v0KCgrS4cOHL3OrAOCv66oOvkiSw+GQJA0bNkwff/zxZW3LP/7xD/3++++XtQ2XU3Z2tp577jlVrlxZwcHBql+/vhYuXOhW5ptvvlHjxo0VEBCg6tWra/bs2R7VvX37drVp00bR0dFyOp368ssvC5Qpru5jx46pU6dOCgoK0jXXXKOhQ4de+Mrm+umnn9SlSxdVrFhRwcHBqlu3rqZNm2blp6enq1+/fqpRo4aCgoIUExOjIUOGKC0trdTLxqVz+vRpNW7c+HI347zy+sFL7dChQ+rQoYNiYmLkdDo1Z86cAmV2796tVq1aqVy5cqpcubLefPNNj+t/9913VbNmTQUFBalBgwZau3atW77T6VS5cuUUFBSkwMBABQUF6fTp06Vapzlz5lh15dXr7e2tDh06FCh7+PBhhYWFqUaNGqVapnT5PkPY40rvM640vXv31o033igfHx/16dOnQP7Zs2f16KOPKjQ0VGFhYerdu7fH+9G1a9fqlltuUXBwsK6//nr95z//cctv1qyZfH193fqRZcuWlXqd7BhzFKVSpUpKTk5W+fLlbV0OAFzNrvrgy6VgjFFWVtblbsYV7+2339bs2bO1evVqnTp1Si+99JK6deumXbt2SZKSk5PVpk0bdenSRSdPntQ777yjfv36efTrYJkyZXT//ffr008/LfQgxZO6u3XrJqfTqUOHDmnTpk1avHixXn/99VKt84kTJ3TnnXfqm2++0alTp/Tuu+/q2Wef1UcffSRJyszMVGRkpD799FOdOnVK69at0+rVq/Xcc8+Varm4emRlZckYc7mbUSin06m7775bc+fOVaVKlQrkZ2dnq23btqpTp45+++03ffzxx3r11Vc1f/78YuueP3++XnzxRS1YsECnTp1Snz59dO+99+rAgQNu5VasWKHk5GSdPn1aycnJCgwMLNU6devWzaorOTlZBw8elK+vr2JjYwuU7du3r/7+97+XannAxXax+4xLMQaqX7++xo8ff94zmJ966int2rVLP/30k3bt2qWdO3dq0KBBxda7b98+3XfffRo4cKBOnTqluXPnatiwYVq0aJFVxuFw6MUXX3TrR9q0aVPqdbJjzHGlycjIuNxNAIBL6qoKvhw5ckTt2rVTSEiIatWqpc8//9zKcz1te9KkSbrpppvcXrt37155e3vrl19+kZRzemaXLl0UHR2tChUqqG/fvjpz5oxV3ul0auLEiWrYsKHKlSunzZs3KzMzUwMHDtQ111yja6+9Vq+//rqqV6+uDz74QFLB0/979uypuLg49enTR6GhoapUqZKmTJni1q5p06apWrVqCgkJUVxcnGJjY/Xoo4969H5MmTJF9erVU3BwsKpUqaJJkybJGKOwsDBt3LjRWm+n06kRI0ZYr6tTp44WLFggSbruuuv08ssv684771RgYKDq16+vHTt26MMPP1T16tUVGhqq3r17Kzs7u9j27N69W02bNlW1atUkSe3bt1d4eLi+++47SdLChQsVEBCgZ599Vj4+PmrZsqU6duxY4D0pTK1atfTYY4/p5ptvLnRQuWjRoiLr3rt3r1atWqVx48apXLlyiomJ0XPPPad333232GVLOZ/tHXfcofDwcEVFRVmfUaNGjdS/f3/rl6bbbrtNrVu3VkJCgiTJ399fo0aNUvXq1eVwOFSpUiX17t3bysefg+vZVjNmzFD16tX173//W5UqVVJ4eLj69evn9r0srn/55z//qapVqyowMFDVq1fXW2+9ZeXt27dPTqdT8fHxqlOnjsqVK6djx44V28YPPvhAMTExioiIUM+ePfXHH39YeT/99JOaNWum4OBg3XTTTZo4caKczpzdx+eff66oqChlZmZa5c+cOaPAwEBt2LChyGWWL19e/fv31y233GLV52rt2rX65ZdfNGbMGJUtW1Y33XST+vbt69F2t2DBAnXv3l1169aVw+FQ3759FRUVpenTp7uVu9CDzEWLFqlhw4YKDQ3Vtddeq3/961+Flvvggw8UFBRU4MyXmTNnKisrSw8//PAFLT+/7OxsDRo0SBEREapcubJeffVVt/xPP/1UderUUVBQkNq1a6dBgwapefPmkqShQ4cWaN/q1asVHByss2fPXpT2oWSu9D6jqO9TXvvzj4EkaerUqapbt65CQkLUoEEDrVixQpJ08uRJ+fv7a9u2bW7LueOOO/Tyyy8X+3498cQTatWqVaHB09TUVM2ePVujR49WRESEIiIiNGrUKM2YMUPp6elF1rts2TLVqFFDDzzwgCSpcePG6ty5syZNmuRW7kL7ke3bt+uee+5RVFSUIiIidNddd0kq/ZjjfMaOHatKlSopIiJCgwYNcmt33vfg0KFDknLGxS1bttTQoUMVFRWlyMhIjR8/Xr/88otatGihoKAgNWzYUD/++KNVx5kzZxQXF6fw8HBdd911mjlzpnx8fJSYmGjV2aJFCw0ePFjly5e3+p1HH31UlStXVlBQkG688UbNnTvXqrNJkyZu31dJGj58OJdaAvhTuqqCL926dZOPj48OHDigxMTEAoPwvDMiunXrph9//FHbt2+38qZPn67mzZurcuXKSktL05133qkbb7xR+/bt086dO3Xw4EH9v//3/9zqi4+P1/z583XmzBn97W9/05gxY/TFF1/oq6++0t69e3XgwAErmJO/DXkWLlyo9u3b68SJE5o4caKeeOIJ7d+/X5KUmJioJ598UtOmTdPvv/+uNm3a6L///a9H78U777yjl156SZMnT9apU6e0detWNW7cWA6HQ82bN9fKlSsl5fwqXL16dev5wYMHtWvXLrVs2dKq64MPPtC7776rkydPql69eurYsaMSEhK0Y8cObd++XUuWLNG8efOKbVPv3r31/fff63//+5+ys7O1YMECZWVl6Y477pCUM0jJHxS7+eabCwzWLsS2bdsqyd2IAAAaaElEQVSKrHv79u0KCQlRTEyMW35SUpLbALcw27dvV+vWrdW7d28dPnxY+/fvV48ePQot+8cff2jjxo3629/+dt76Vq1apfr163u2Yrgi7du3T0ePHtWePXv01Vdfaf78+frwww8lyaP+pU6dOvryyy91+vRpTZ06VcOGDbMOYvLMnTtXCQkJOn36tCIjI4tsT2Zmpj755BN99913+t///qddu3Zp4MCBknJ+BW/btq1uuukmHTt2TIsXL9bUqVOtvuruu+9WuXLl3C7bnDNnjipXrqzbbrutVO/T9u3bVaNGDfn7+1tpnm7zxpgCB0TGGH377bduaV26dFFkZKRuueUWLV682KN2ffbZZ+rRo4deeukl/fbbb9q1a5fuueeeQstOmTJFjz32mLy8vKy0w4cP61//+lepD6RcJSYmKjo6WocPH9ZHH32kN9980/pO7d69W/fff79efPFFnTx5Uk8//bSmTZtmfYZ9+vTR559/riNHjlj1TZs2Td27d5efn99FayMu3JXUZxT3fcrjOga66aabNHXqVL3++uuaO3euTp48qZdfflmdOnXSnj17FBISogceeEDvvfee9fpdu3Zp06ZNeuyxx0r13v34449KS0vTzTffbKXdfPPN+uOPP6wza8+nsH4kKyurQD8yYcIERUREqG7dunrllVfcgtHnc/jwYTVr1kzNmzfXvn37dPjwYevSotKMOc5n5syZeuutt7R06VIdPnxYERERVlAkT/7PcN26dapZs6aOHDmimTNnavDgwerVq5feeecdnThxQrVq1dJTTz1llX/qqaeUlJSkXbt2aceOHfr0008L/Pi2bt06VahQQQcOHLAuLb/99tu1fft2nTp1SsOHD1ePHj30ww8/SMo5Q9D1cmxjjKZPn17o5WUAcMUzV4mDBw8ah8Nh9u7da6WtWLHCOJ1Os2/fPjNixAjTqlUrK+/BBx80Tz/9tPU8JibGzJ071xhjzPz58021atXc6v/mm29M2bJlTXZ2tjHGGIfDYWbNmuVWplq1amb69OnW87Nnz5qyZcuaGTNmGGOMSUhIMD4+PlZ+jx49zH333edWR2RkpFmyZIkxxphevXqZRx55xC3/9ttvNz179iz2/ahdu7Z55513Cs2bNGmSadq0qTHGmC5dupj4+HgTFhZmkpOTzYwZM0yDBg2ssjExMWbcuHHW82XLlhmn02l+++03K+2BBx4wgwYNKrZNKSkp5vHHHzdOp9P4+PiYcuXKmcWLF1v5jz32mOnRo4fba95//31TvXr1Yut25XA4zIYNG9zSiqt75syZJiYmxi1/7969xul0moMHDxa5vAEDBpgHHnig2HZlZWWZTp06maZNm5rMzMxCy4wfP95cc801Zv/+/cXWh8unWbNm5uWXX7aeu37npk+fboKDg62+wpic7SxvG/Gkf8mvc+fO5rnnnjPGGJOUlGQcDodZv369R21NSEgwTqfTrW9cuXKl8fPzM8YYs27dOuPr62tSU1Ot/GnTphmn02k9Hz16tGndurX1vHHjxmb8+PEeLT9PTEyMmT17tlvaqFGjTLNmzdzS1qxZ49ZPns+MGTNMZGSk+eabb0xGRob597//bZxOp1s/v3r1apOWlmbS0tLMvHnzjJ+fn/niiy+KrbtNmzZmyJAhxZZbv3698fb2NklJSW7pHTp0MJMmTTLG5HwfStqH5TdixAhTpUoVt7QXXnjB3H333caYnM8nr0/PExsba5o3b249b9WqlXn11VeNMcb8/vvvxs/Pz2zdurVU7YLn/kx9hiffp8LGQDfeeKOZOXOmW1rbtm2t9V6/fr0JCwszaWlpxhhjhgwZYtq1a+dRm/L06NHD9O7d2y1t3bp1bv2VMcZkZ2cXOhbIb9euXcbX19fMmjXLZGZmmnXr1pmgoCC3Pmjjxo3m5MmTJjs722zatMlUrVrVPP/888W29bXXXjONGjUqNK80Y47zadWqlRk+fLj1PDs721SqVMmMHDnSGJPzPXCtf8SIEebGG290qyMqKqrAmC8sLMwYkzOGKVu2rElISLDyd+/ebRwOh1m7dq1VZ/7vamH+/ve/W2PUP/74w4SEhJhNmzZZy4yMjDTp6eklfg8A4HK7as58OXDggBwOhypXrmylXXfddect37NnT82ZM0dZWVlatWqVTp06pY4dO0qSkpKStG/fPoWFhVl/LVu2lJeXl9ss8VWqVHGr8+DBg27L9/X1LfYX6ejoaLfnAQEB1oSQBw8eLLCM/M/PJykpSdWrVy80r2XLltq4caPOnDmjNWvW6J577tGtt96q1atXa+XKlW5nveRvo7+/v7y8vNzu2uTv7+/RJJb9+/fXt99+q3379ik9PV3Lly9X3759rbNuAgMDderUKbfXnDx5UkFBQR6tc1GKq/t8+Xl5RUlKSip2Qs3MzEx17dpVR44c0dKlS91+Jc8zfvx4vfbaa1qzZo0qVqxY7DrhyhUVFeX2C6Prdu1J/zJx4kTVq1dPYWFhCg0N1SeffOJ2mYDD4fC4L8jj2jfFxMQoLS1Nx48f16FDhxQVFaWyZcta+fnrfuyxx5SQkKADBw5ox44d2rZtm+Li4kq0/MKUZpuPi4vT4MGD9fDDDys6Olrbtm1Ty5YtFRERYZVp3ry5ypQpozJlyuiBBx5QbGysR5N4e7JNSzlnvdx1111u79ecOXN0/Phx9e/fX9KFX66QX/7PJCYmxprfxpN9RZ8+fRQfHy9JmjVrlmrXrl3kGXi4tK6kPsPTsUf+tL179+rxxx+32hgaGqqEhAQdPHhQUs5lt9dee6111usHH3xwUc5uyNtHJycnW2l5/UpxfUn16tW1aNEiTZgwQddcc43+9a9/qWfPnm79SOPGjRUcHCyHw6FGjRpp1KhRmjVrVrHtKqofKc2Y43wOHDjgdiaNJ595/jGov79/gTFf3vfw+PHjSk9Pd9uXePK9MMZo+PDhqlWrlkJDQxUaGqrt27db308/Pz89/PDD1llR06ZNU1xcHHfpA/CndNUEXypUqCAp59TdPHv37j1v+VatWqls2bJasmSJZsyYoa5du1oHH1WqVFHNmjX1+++/W38nTpxQSkqK204p/xwGFSpUcFv+2bNnPZqLoah1cq1PUoHLmM4nJiZGP/30U6F51atXV/ny5TVhwgRFR0erfPnyatGihVasWKFVq1YVCL5cLFu2bFFcXJwVWLjlllt0++23W3cNqF+/foFTfbds2XJRLsEpru769evr1KlTSkpKsvI3b96smJiYYgdCRb3XUs4p4x07dtRvv/2mFStWFFrfqFGjNH78eCUmJuqGG24owZrhz6a4/uXLL7/U0KFDNXXqVCvvvvvuK3AQX9gcKkXJ3zeWLVtWERERqlChgo4dO+Z2Z5D8/U758uV17733Kj4+XvHx8erQoYNbAPZC1a9fX7t27XKbd2Tz5s0eb/ODBw/WDz/8oGPHjmnSpEn6/vvv3ealyM/hcHgUDClum5ZyJtOeP3++FWTJs2LFCm3btk2RkZGKjIzUU089pT179igqKko7duzwaL0Kk/8zSUpKsvpST/YVHTp0UHJyshITExUfH88p/X8il7rP8HTskb++mJgYxcfHu7UxOTnZ7e5Bffr00XvvvadPPvlE3t7eF2Xi2po1a8rX11dbtmyx0jZv3ix/f3+Pgqj33HOPvv76ax0/flxr1qzRoUOH1KxZsyJfU9p+pDRjjvOpUKGCW31SwX6jNCIiIlSmTBm3OgurP//3Yu7cuZo2bZoWL16sEydO6MSJE6pXr57be9i3b1/NmzdPSUlJWrp0qXr37n3R2g0Al9JVFXxp1qyZhgwZotOnT+vIkSMaNWrUecs7nU7FxcVp4sSJWrx4sdsktvfdd5/S09M1duxY69rbgwcPWneoOZ/Y2Fi9/vrrSkpKUmpqqoYNG1aqXz1jY2O1YMECrV27VtnZ2Zo3b541UW5xHn/8cY0ZM0YbN26UMUa//fabvvnmGyu/RYsWGjdunDWhWYsWLTRr1iydOHFCt99++wW3uSi33XabZs+ebU32tmnTJiUkJFh3A+nYsaNSUlL0xhtvKD09XStXrtRHH32kvn37elR/WlqaUlNTJeXcwjktLc26Frm4umNiYtSyZUvr+7Nnzx699tpr6tevX7HL7du3r5YsWaLZs2crPT1dqamp1i1vU1JS1Lp1a2VkZGjZsmWFzq8wePBgTZs2TWvXrrUmI8ZfV3H9S3Jysry9vRURESFjjD799FN99tlnbnWUtF8xxmjYsGE6ffq0jh49qpEjR1pnrjRp0kSVK1fWsGHDlJaWpr179xaY/FDKmbMpPj5es2fPLtHAOG+7NMYoIyNDaWlp1p1R7rjjDlWpUkXPP/+8UlNTtXXrVk2ZMsWj7S45OdmaM+DYsWPq16+fNTG5JH3//ff6+uuvlZGRoczMTH300UeaNWuWHnzwwWLrfvzxx/XOO+/oiy++UFZWlk6fPl1gcuHp06crMjJS9957r1v6hAkT9MMPP2jbtm3atm2bXnrpJVWpUkXbtm1T7dq1JUkjRowo8szMwvz6668aN26cMjMztXXrVk2dOtWaW6pr167atGmTFixYoOzsbK1Zs6bA/srb21s9evTQwIED9fPPP+uhhx4q0fJx+VzqPsOT71Nhnn76aY0YMcKas+ns2bPasGGD24StsbGx+uqrrzRy5Ej17NnT41uoZ2RkKDU1VVlZWcrKylJaWpp1Jx1fX189/PDDGj58uI4dO6ajR49q+PDheuSRR1SmTJli6/7mm2+UmZmpP/74w9ruX3zxRUk5Z9B8+umnSklJkSRt3bpVI0eOVNeuXYutt3v37vrxxx/1+uuv6+zZs8rIyNCqVaskeTbmKGk/ERsbqylTpmjr1q3KzMzU2LFj3c7Wlkp3Jp7T6VS3bt00YsQIHT9+XKdPn9YLL7xQ7GeYnJwsHx8fhYeHKzMzU/Hx8QXm9apbt65q166t+++/X40bN1bNmjUvuJ0AcDldNcEXKed079TUVFWqVElNmzbVI488UmT5Hj16KDExUddff73b7UD9/Py0evVq7dy5U7Vq1VJISIhatWrltrMobGczbNgwtWrVSo0aNdL111+vChUqKDo62u10/uK41nvHHXforbfeUs+ePRUWFqZly5apY8eOHtU3YMAADRs2TI899piCgoLUoEEDt+BLy5Ytdfr0aSv4UrduXfn5+em2225zq9/TgZEnxo0bpzp16qhRo0YKDg5WbGysBg8erG7dukmSgoODtWzZMv33v/9VaGio+vXrp8mTJ6tRo0bF1r1v3z75+fkpICBADodDLVq0kL+/v3VqsCd1z549W1lZWapQoYKaNGmiTp06afDgwcUuu169elq2bJkmTZqka665RlWqVLGWu3DhQiUmJmr9+vWKiIhQYGCggoKCNGDAAEk5vya+8cYbOnLkiOrXr6+goCAFBgaqbt26JX5/cenk3y5Ksp0U17/cfffdiouLU8OGDRUZGalFixapU6dOF7w8KefA+95771XdunV1ww03qFq1anrjjTckSV5eXlqyZIk2b96syMhIderUSXFxcQUOWu666y45nU4FBwfrzjvvLNH6BgQEaP/+/Xr00Ufl7+9v3d3E6XRq6dKl2rFjh8LDw9W2bVsNHTpUXbp0Kbbe5ORkdenSRUFBQbrhhhuUmZmpNWvWWP3XsWPHrL7zmmuu0ZgxY/T+++8XCJYUpk2bNpo2bZqGDRumsLAw1apVS8uXL3crM3XqVPXu3bvAZxEcHKxrr73W+gsNDZWXl5eio6Otyw33799fovdQypmw8tdff1X58uXVrl07DRw40DoArFq1qubPn6/hw4crJCRE48ePV1xcXIF9Ra9evfTtt9/qwQcfLPUtt1Eyf6Y+w5PvU2H19erVS0OGDLG2u5iYGI0ePdptctqQkBB17txZ27dvL9FEu3fddZf8/f01e/ZsTZ8+Xf7+/rr77rut/AkTJqhGjRqqUaOGatWqpTp16ujNN9/0qO4XX3xRERERKl++vBYtWqSEhATr4D8jI0OjR49WxYoVFRwcrIceekjdu3fXmDFjiq03OjpaCQkJWr58uSpWrKjo6GiNGzfOyi9uzFHSfiIuLk5PPvmk2rZtq/Lly+v48eNq2rSpW5nivgfF5U+cOFGVK1dWjRo1VK9ePevuTUWNSx955BE1btxY1apVU6VKlfTDDz9YN1pw1bdvX23dupWz8gD8qTnMxbrgHCWWkpKi0NBQJSYmqkmTJhelzltvvVXt2rWzZswHgItt8uTJGj9+vHVmSZ7mzZurdevWeu655y5Ty/4aatWqpVWrVlmXy9qhW7duCgoKcrvj0h9//KGoqCitWrVKjRs3tm3Z+Osp7Pt0oUaOHKn/+7//0+eff34RWvbXdSn6idL68ccfVbt2bR08eFDly5cvVV1r165Vx44ddejQIfn6+l6kFgLApXVVnflyuZ04cUJffPGFMjMzderUKT355JO67rrr1LBhwwuuc+HChUpJSVF6erqmTJmizZs3e/SrMAB4asOGDdqzZ4+knFugvv7669YZaXkSExP1zTffqFevXpejiX8pP/zww0U/oFq6dKlOnDihrKwsffzxx1q0aJHbZ2iM0fjx41WnTh0CLyhWcd+nC3XkyBFNnTpVTz/99EVo5V+bHf1Eae3du1f/93//p+zsbB05ckSDBg1S06ZNSx14SU1N1bhx49SnTx8CLwD+1Ai+XELZ2dl64YUXFB4erqpVq+rQoUNasmRJoXe28dTChQtVsWJFRUZGavLkyfroo49UtWpVzZkzx7qEJe8v7/ncuXMv4lp5zs42Xc713b9//3mXnXf5EHA55f9+5v15comNlPMdb968ucqVK6f27dvr/vvvdzu7rlGjRurYsaPefvtthYeHW+nr168/77bxyiuvlGqd/qx1Xy6JiYmqUaOGQkND9c9//lOTJ0+2Tu0/duyYgoKC9P7771+UMxfw51dcn1HU9+lCPfPMM6pWrZrat2+v1q1bl6g9pfFnrftKlJqaqj59+igkJET169dXuXLlPLqDXFEWL16s8PBwJScn6/nnn79ILQWAy4PLjgAAAAAAAGzkfbkbYJeLOREs8GdBLPXSo6/B1YZ+5vKgr8HVhr4GwF/NXzb4Ikn6wSjaZawSkft/UO5jgEteudz/fV3S8v4vk/vo55JXJl+ej0te2Xx5rvneDvcyrmn5y7jW4V1EeZ9C8vI/FvY61zQvFSyfvz1exdSVl+/M21m67jOzch+zcxOzXfKy8+UVllZU+YtQl8kqJC+vCte68q2H8bhdBdNMUe9J3ltYWLsKqytbKnt/iHCZlHtBcrjc/cfpk/PoyH10uuR5lXEv4/q/09u9jCR55aV5uT9Kknfu/4Vt8HnFXBYj79zvjpdxfy5J3ln5Hl2+YF65dyPxyXR/7lq+sDTvjNxHlzyvfHX4pLvkZbi9zpn3XFKQd85t4st65ZQv451m5fl4peWmpZyryis1t46cPIfXufJOn7O5hdJz884tx2pXbhscXi7vkVe+R0kOq/PMfe66V/UqvIxrmjP30delzuDczjTA5cLgck73xxCXDjlv/xXgzH2dy9cgOF9agMsBfF5asFtabnnlPJaRS2UOhxzBu4XLp0KFCnI6z30x8v7P/yjJuqS5qPKulz0XlZe/rsLq9LR8Xl5R7fP29vZoOfnTPM3Lv+yS5l1o+cLeh8LW1SrvWlcR703+5RTVBk/Xx468vLa7rpvXed63kBDGNAD+epjzBQAAAAAAwEYEXwAAAAAAAGxE8AUAAAAAAMBGBF8AAAAAAABsRPAFAAAAAADARgRfAAAAAAAAbETwBQAAAAAAwEYEXwAAAAAAAGxE8AUAAAAAAMBGBF8AAAAAAABsRPAFAAAAAADARgRfAAAAAAAAbETwBQAAAAAAwEYEXwAAAAAAAGxE8AUAAAAAAMBGBF8AAAAAAABsRPAFAAAAAADARgRfAAAAAAAAbETwBQAAAAAAwEYEXwAAAAAAAGxE8AUAAAAAAMBGBF8AAAAAAABsRPAFAAAAAADARgRfAAAAAAAAbETwBQAAAAAAwEYEXwAAAAAAAGxE8AUAAAAAAMBGBF8AAAAAAABsRPAFAAAAAADARgRfAAAAAAAAbETwBQAAAAAAwEYEXwAAAAAAAGxE8AUAAAAAAMBGBF8AAAAAAABsRPAFAAAAAADARgRfAAAAAAAAbETwBQAAAAAAwEYEXwAAAAAAAGxE8AUAAAAAAMBGBF8AAAAAAABsRPAFAAAAAADARgRfAAAAAAAAbETwBQAAAAAAwEYEXwAAAAAAAGxE8AUAAAAAAMBGBF8AAAAAAABsRPAFAAAAAADARgRfAAAAAAAAbETwBQAAAAAAwEYEXwAAAAAAAGxE8AUAAAAAAMBGBF8AAAAAAABsRPAFAAAAAADARgRfAAAAAAAAbETwBQAAAAAAwEYEXwAAAAAAAGxE8AUAAAAAAMBGBF8AAAAAAABsRPAFAAAAAADARgRfAAAAAAAAbETwBQAAAAAAwEYOY4y53I2wg8PhuNxNAC65v+jmfEWjr8HVhn7m8qCvwdWGvgbAX81fNvgCAAAAAABwJeCyIwAAAAAAABsRfAEAAAAAALARwRcAAAAAAAAbEXwBAAAAAACwEcEXAAAAAAAAGxF8AQAAAAAAsBHBFwAAAAAAABsRfAEAAAAAALARwRcAAAAAAAAbEXwBAAAAAACwEcEXAAAAAAAAGxF8AQAAAAAAsBHBFwAAAAAAABsRfAEAAAAAALARwRcAAAAAAAAbEXwBAAAAAACwEcEXAAAAAAAAGxF8AQAAAAAAsBHBFwAAAAAAABsRfAEAAAAAALARwRcAAAAAAAAbEXwBAAAAAACwEcEXAAAAAAAAGxF8AQAAAAAAsBHBFwAAAAAAABsRfAEAAAAAALARwRcAAAAAAAAbEXwBAAAAAACwEcEXAAAAAAAAGxF8AQAAAAAAsBHBFwAAAAAAABsRfAEAAAAAALDR/wcw0wu7ooX6NQAAAABJRU5ErkJggg==' style='max-width:100%; margin: auto; display: block; '/>
12503 </div>
12504
12505 </div>
12506
12507 </div>
12508 </div>
12509
12510 </div>
12511 <div class="cell border-box-sizing text_cell rendered">
12512 <div class="prompt input_prompt">
12513 </div>
12514 <div class="inner_cell">
12515 <div class="text_cell_render border-box-sizing rendered_html">
12516 <h2 id="Testing-perceptual-uniformity">Testing perceptual uniformity<a class="anchor-link" href="#Testing-perceptual-uniformity">&#182;</a></h2><p>Peter Kovesi created a test image with a sine grating modulation of intensity, where modulation gain decreases from top to bottom, which helps evaluate perceptual uniformity of a colormap at a glance. The matplotlib maintainers use different definitions of perceptually uniform (uniformity in a different color space), but the new matplotlib perceptually uniform colormaps do well at Peter's test image:</p>
12517
12518 </div>
12519 </div>
12520 </div>
12521 <div class="cell border-box-sizing code_cell rendered">
12522 <div class="input">
12523 <div class="prompt input_prompt">In&nbsp;[7]:</div>
12524 <div class="inner_cell">
12525 <div class="input_area">
12526 <div class=" highlight hl-ipython2"><pre><span class="o">%</span><span class="k">output</span> size=200
12527 <span class="o">%</span><span class="k">opts</span> Image [xaxis=&#39;bare&#39; yaxis=&#39;bare&#39; sublabel_format=None aspect=4 fontsize=10]
12528 <span class="n">sine</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="s2">&quot;colourmaptest.npy&quot;</span><span class="p">)</span>
12529 </pre></div>
12530
12531 </div>
12532 </div>
12533 </div>
12534
12535 </div>
12536 <div class="cell border-box-sizing code_cell rendered">
12537 <div class="input">
12538 <div class="prompt input_prompt">In&nbsp;[8]:</div>
12539 <div class="inner_cell">
12540 <div class="input_area">
12541 <div class=" highlight hl-ipython2"><pre><span class="n">colormaps</span><span class="p">([[</span><span class="s2">&quot;viridis&quot;</span><span class="p">]</span><span class="o">*</span><span class="mi">2</span><span class="p">,[</span><span class="s2">&quot;inferno&quot;</span><span class="p">]</span><span class="o">*</span><span class="mi">2</span><span class="p">],</span><span class="n">cols</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span><span class="n">array</span><span class="o">=</span><span class="n">sine</span><span class="p">)</span>
12542 </pre></div>
12543
12544 </div>
12545 </div>
12546 </div>
12547
12548 <div class="output_wrapper">
12549 <div class="output">
12550
12551
12552 <div class="output_area"><div class="prompt output_prompt">Out[8]:</div>
12553
12554 <div class="output_html rendered_html output_subarea output_execute_result">
12555 <img 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' style='max-width:100%; margin: auto; display: block; '/>
12556 </div>
12557
12558 </div>
12559
12560 </div>
12561 </div>
12562
12563 </div>
12564 <div class="cell border-box-sizing text_cell rendered">
12565 <div class="prompt input_prompt">
12566 </div>
12567 <div class="inner_cell">
12568 <div class="text_cell_render border-box-sizing rendered_html">
12569 <p>Here the sine grating for a uniform colormap should be visible as a fine-toothed comb with teeth that gradually become less visible from top to bottom. The further down the comb these teeth are visible, the higher the discriminability of magnitudes at that location in the colormap. Thus a perceptually uniform colormap, like the two above, should have teeth that visible at the same length for all colors.</p>
12570 <p>You can also use these images to evaluate the overall level of discriminability provided by a given colormap -- the longer the visible area of teeth, the better this colormap allows you to discriminate fine differences in magnitude. Here the <code>inferno</code> map seems to have better discriminability than the <code>viridis</code> map, despite both being perceptually uniform.</p>
12571 <p>The default colormaps that have traditionally been used with Matlab, Matplotlib, and HoloViews are clearly not perceptually uniform -- all the green and yellow areas are nearly indistinguishable:</p>
12572
12573 </div>
12574 </div>
12575 </div>
12576 <div class="cell border-box-sizing code_cell rendered">
12577 <div class="input">
12578 <div class="prompt input_prompt">In&nbsp;[9]:</div>
12579 <div class="inner_cell">
12580 <div class="input_area">
12581 <div class=" highlight hl-ipython2"><pre><span class="n">colormaps</span><span class="p">([[</span><span class="s2">&quot;hot&quot;</span><span class="p">]</span><span class="o">*</span><span class="mi">2</span><span class="p">,[</span><span class="s2">&quot;jet&quot;</span><span class="p">]</span><span class="o">*</span><span class="mi">2</span><span class="p">],</span><span class="n">cols</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span><span class="n">array</span><span class="o">=</span><span class="n">sine</span><span class="p">)</span>
12582 </pre></div>
12583
12584 </div>
12585 </div>
12586 </div>
12587
12588 <div class="output_wrapper">
12589 <div class="output">
12590
12591
12592 <div class="output_area"><div class="prompt output_prompt">Out[9]:</div>
12593
12594 <div class="output_html rendered_html output_subarea output_execute_result">
12595 <img 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' style='max-width:100%; margin: auto; display: block; '/>
12596 </div>
12597
12598 </div>
12599
12600 </div>
12601 </div>
12602
12603 </div>
12604 <div class="cell border-box-sizing text_cell rendered">
12605 <div class="prompt input_prompt">
12606 </div>
12607 <div class="inner_cell">
12608 <div class="text_cell_render border-box-sizing rendered_html">
12609 <p>Thus those colormaps should be avoided if at all possible, to avoid generating misleading visualizations. Compare these two to the perceptually uniform versions provided by this package:</p>
12610
12611 </div>
12612 </div>
12613 </div>
12614 <div class="cell border-box-sizing code_cell rendered">
12615 <div class="input">
12616 <div class="prompt input_prompt">In&nbsp;[10]:</div>
12617 <div class="inner_cell">
12618 <div class="input_area">
12619 <div class=" highlight hl-ipython2"><pre><span class="n">colormaps</span><span class="p">([(</span><span class="s2">&quot;fire&quot;</span><span class="p">,</span><span class="n">cc</span><span class="o">.</span><span class="n">m_fire</span><span class="p">),(</span><span class="s2">&quot;rainbow&quot;</span><span class="p">,</span><span class="n">cc</span><span class="o">.</span><span class="n">m_rainbow</span><span class="p">)],</span><span class="n">cols</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span><span class="n">array</span><span class="o">=</span><span class="n">sine</span><span class="p">)</span>
12620 </pre></div>
12621
12622 </div>
12623 </div>
12624 </div>
12625
12626 <div class="output_wrapper">
12627 <div class="output">
12628
12629
12630 <div class="output_area"><div class="prompt output_prompt">Out[10]:</div>
12631
12632 <div class="output_html rendered_html output_subarea output_execute_result">
12633 <img 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' 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12637
12638 </div>
12639 </div>
12640
12641 </div>
12642 <div class="cell border-box-sizing text_cell rendered">
12643 <div class="prompt input_prompt">
12644 </div>
12645 <div class="inner_cell">
12646 <div class="text_cell_render border-box-sizing rendered_html">
12647 <p>We can see the results for all the <code>cetcolors</code> colormaps below, which can be summarized as:</p>
12648 <ul>
12649 <li>"linear" colormaps all work well by this criterion</li>
12650 <li>"diverging" colormaps typically have discontinuities in perceptual discriminability around the central value</li>
12651 <li>"cyclic" colormaps with repeating colors tend to have discontinuities at 1/4 and 3/4 of the way through the cycle, or at other locations if shifted.</li>
12652 <li>"isoluminant" colormaps typically show no visible modulation, because without luminance cues humans can only discriminate low spatial-frequency modulations (i.e., much wider teeth would be needed for evaluating such colormaps)</li>
12653 <li>Some of the "rainbow" colormaps seem to have a perceptual discontinuity around the color red, the reasons for which are not yet clear.</li>
12654 </ul>
12655
12656 </div>
12657 </div>
12658 </div>
12659 <div class="cell border-box-sizing code_cell rendered">
12660 <div class="input">
12661 <div class="prompt input_prompt">In&nbsp;[11]:</div>
12662 <div class="inner_cell">
12663 <div class="input_area">
12664 <div class=" highlight hl-ipython2"><pre><span class="n">colormaps</span><span class="p">(</span><span class="n">all_cms</span><span class="p">,</span><span class="n">cols</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span><span class="n">array</span><span class="o">=</span><span class="n">sine</span><span class="p">)</span>
12665 </pre></div>
12666
12667 </div>
12668 </div>
12669 </div>
12670
12671 <div class="output_wrapper">
12672 <div class="output">
12673
12674
12675 <div class="output_area"><div class="prompt output_prompt">Out[11]:</div>
12676
12677 <div class="output_html rendered_html output_subarea output_execute_result">
12678 <img 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' 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0 {
1 "cells": [
2 {
3 "cell_type": "markdown",
4 "metadata": {},
5 "source": [
6 "# CET perceptually uniform colormaps\n",
7 "\n",
8 "Peter Kovesi at the Center for Exploration Targeting created a very useful set of [perceptually uniform colormaps](https://arxiv.org/abs/1509.03700), many of which can replace the highly non-uniform colormaps provided with Python plotting programs. Here we will show how to use them via the new [cetcolors](https://github.com/bokeh/cetcolors) python package, listing all the ones available and allowing you to evaluate how perceptually uniform they are for you, your particular monitor, etc. \n",
9 "We will plot them using [matplotlib](http://matplotlib.org) via [holoviews](http://holoviews.org), but identical [bokeh](http://bokeh.pydata.org) palettes are also provided, and both Bokeh palettes and Matplotlib colormaps are usable in [datashader](https://github.com/bokeh/datashader). Thus these colormaps can be used in any of those Python packages, as well as any other package that accepts a Python list of normalized RGB tuples or hex colors. See \n",
10 "[Peter's site](http://peterkovesi.com/projects/colourmaps/) to download versions for other non-Python packages.\n",
11 "\n",
12 "We first make some utilities for sorting and visualizing colormaps:"
13 ]
14 },
15 {
16 "cell_type": "code",
17 "execution_count": null,
18 "metadata": {
19 "collapsed": false
20 },
21 "outputs": [],
22 "source": [
23 "import numpy as np\n",
24 "import holoviews as hv\n",
25 "import cetcolors as cc\n",
26 "\n",
27 "hv.notebook_extension()\n",
28 "\n",
29 "import param\n",
30 "with param.logging_level('CRITICAL'):\n",
31 " hv.plotting.mpl.LayoutPlot.v17_layout_format = True"
32 ]
33 },
34 {
35 "cell_type": "code",
36 "execution_count": null,
37 "metadata": {
38 "collapsed": false
39 },
40 "outputs": [],
41 "source": [
42 "%opts Image [xaxis='bare' yaxis='bare' sublabel_format=None aspect=3 fontsize=13]\n",
43 "\n",
44 "# Collapse all colormap aliases into a single string, and then sort by it\n",
45 "inverse = {}\n",
46 "for k,v in cc.cm.items():\n",
47 " if not k[-2:] == \"_r\":\n",
48 " inverse[v] = inverse.get(v, [])\n",
49 " inverse[v].insert(0,k)\n",
50 "all_cms = {', '.join(reversed(v)):k for (k,v) in inverse.items()}.items()\n",
51 "all_cms.sort()\n",
52 "\n",
53 "aliased_cms=[(k,v) for (k,v) in all_cms if \",\" in k]\n",
54 "\n",
55 "def lay_out_in_columns(_list, cols, spacer=None):\n",
56 " \"\"\"Given a list, reorder it into the number of columns specified, filling missing items with the given spacer.\"\"\"\n",
57 " rows = int(np.ceil(len(_list)*1.0/cols))\n",
58 " padded = _list + [spacer] * (rows*cols-len(_list))\n",
59 " return list(np.array(padded).reshape(cols,rows).T.flat)\n",
60 "\n",
61 "xs,ys = np.meshgrid(np.linspace(0,1,80), np.linspace(0,1,10))\n",
62 "\n",
63 "def colormaps(named_cms,cols=3,array=xs):\n",
64 " images = [hv.Image(array, group=name)(style=dict(cmap=cm)) \n",
65 " for name,cm in named_cms]\n",
66 " return hv.Layout(lay_out_in_columns(images,cols,hv.Empty())).display('all').cols(cols)\n",
67 "\n",
68 "def colormaps_by_name(names,cols=3,array=xs):\n",
69 " return colormaps({(k,v) for (k,v) in cc.cm.items() if k in names},cols,array)"
70 ]
71 },
72 {
73 "cell_type": "markdown",
74 "metadata": {},
75 "source": [
76 "## Named colormaps\n",
77 "\n",
78 "The full list of colormaps included will be shown below, but a useful subset of these maps that cover the various types have been given more convenient names, and we will focus on those first. \n",
79 "\n",
80 "**For Matplotlib users**: After importing `cetcolors`, all the colormaps shown here will be available by string name prefixed with `cet_`, along with reversed versions suffixed with `_r` (not shown below). For instance, the `cetcolors` version of \"hot\" is available as \"cet_hot\" and \"cet_hot_r\" (as well as the more verbose names \"cet_linear_kryw_0_100_c71\" and \"cet_linear_kryw_0_100_c71_r\" as described below). \n",
81 "\n",
82 "### Linear (sequential) colormaps, for plotting magnitudes:"
83 ]
84 },
85 {
86 "cell_type": "code",
87 "execution_count": null,
88 "metadata": {
89 "collapsed": false
90 },
91 "outputs": [],
92 "source": [
93 "colormaps([i for i in aliased_cms if \"linear\" in i[0] and \"diverging\" not in i[0]])"
94 ]
95 },
96 {
97 "cell_type": "markdown",
98 "metadata": {},
99 "source": [
100 "### Diverging colormaps, for plotting magnitudes increasing or decreasing from a central point:"
101 ]
102 },
103 {
104 "cell_type": "code",
105 "execution_count": null,
106 "metadata": {
107 "collapsed": false
108 },
109 "outputs": [],
110 "source": [
111 "colormaps([i for i in aliased_cms if \"diverging\" in i[0]])"
112 ]
113 },
114 {
115 "cell_type": "markdown",
116 "metadata": {},
117 "source": [
118 "### Misc colormaps:\n",
119 "\n",
120 "* cyclic: for cyclic quantities like orientation or phase (where the highest and lowest values need the same color)\n",
121 "* isoluminant: to highlight low spatial-frequency information\n",
122 "* rainbow: to highlight local differences in sequential data"
123 ]
124 },
125 {
126 "cell_type": "code",
127 "execution_count": null,
128 "metadata": {
129 "collapsed": false
130 },
131 "outputs": [],
132 "source": [
133 "colormaps([i for i in aliased_cms if \"cyclic\" in i[0] or \"rainbow\" in i[0] or \"isoluminant\" in i[0]])"
134 ]
135 },
136 {
137 "cell_type": "markdown",
138 "metadata": {},
139 "source": [
140 "## Full list of available colormaps\n",
141 "\n",
142 "This list includes all those above, plus other variants and alternatives. Each colormap has a name in the form:\n",
143 "\n",
144 "*category*`_`*huesequence*`_`*lightnessrange*`_c`*meanchroma*`[_`s*colorshift*`_[`r*ifreversed*`]]`\n",
145 "\n",
146 "along with any shorter alias that may be defined above."
147 ]
148 },
149 {
150 "cell_type": "code",
151 "execution_count": null,
152 "metadata": {
153 "collapsed": false
154 },
155 "outputs": [],
156 "source": [
157 "colormaps(all_cms, cols=4)"
158 ]
159 },
160 {
161 "cell_type": "markdown",
162 "metadata": {},
163 "source": [
164 "## Testing perceptual uniformity\n",
165 "\n",
166 "Peter Kovesi created a test image with a sine grating modulation of intensity, where modulation gain decreases from top to bottom, which helps evaluate perceptual uniformity of a colormap at a glance. The matplotlib maintainers use different definitions of perceptually uniform (uniformity in a different color space), but the new matplotlib perceptually uniform colormaps do well at Peter's test image:"
167 ]
168 },
169 {
170 "cell_type": "code",
171 "execution_count": null,
172 "metadata": {
173 "collapsed": false
174 },
175 "outputs": [],
176 "source": [
177 "%output size=200\n",
178 "%opts Image [xaxis='bare' yaxis='bare' sublabel_format=None aspect=4 fontsize=10]\n",
179 "sine=np.load(\"colourmaptest.npy\")"
180 ]
181 },
182 {
183 "cell_type": "code",
184 "execution_count": null,
185 "metadata": {
186 "collapsed": false
187 },
188 "outputs": [],
189 "source": [
190 "colormaps([[\"viridis\"]*2,[\"inferno\"]*2],cols=1,array=sine)"
191 ]
192 },
193 {
194 "cell_type": "markdown",
195 "metadata": {},
196 "source": [
197 "Here the sine grating for a uniform colormap should be visible as a fine-toothed comb with teeth that gradually become less visible from top to bottom. The further down the comb these teeth are visible, the higher the discriminability of magnitudes at that location in the colormap. Thus a perceptually uniform colormap, like the two above, should have teeth that visible at the same length for all colors. \n",
198 "\n",
199 "You can also use these images to evaluate the overall level of discriminability provided by a given colormap -- the longer the visible area of teeth, the better this colormap allows you to discriminate fine differences in magnitude. Here the `inferno` map seems to have better discriminability than the `viridis` map, despite both being perceptually uniform.\n",
200 "\n",
201 "The default colormaps that have traditionally been used with Matlab, Matplotlib, and HoloViews are clearly not perceptually uniform -- all the green and yellow areas are nearly indistinguishable:"
202 ]
203 },
204 {
205 "cell_type": "code",
206 "execution_count": null,
207 "metadata": {
208 "collapsed": false
209 },
210 "outputs": [],
211 "source": [
212 "colormaps([[\"hot\"]*2,[\"jet\"]*2],cols=1,array=sine)"
213 ]
214 },
215 {
216 "cell_type": "markdown",
217 "metadata": {},
218 "source": [
219 "Thus those colormaps should be avoided if at all possible, to avoid generating misleading visualizations. Compare these two to the perceptually uniform versions provided by this package: "
220 ]
221 },
222 {
223 "cell_type": "code",
224 "execution_count": null,
225 "metadata": {
226 "collapsed": false
227 },
228 "outputs": [],
229 "source": [
230 "colormaps([(\"fire\",cc.m_fire),(\"rainbow\",cc.m_rainbow)],cols=1,array=sine)"
231 ]
232 },
233 {
234 "cell_type": "markdown",
235 "metadata": {},
236 "source": [
237 "We can see the results for all the `cetcolors` colormaps below, which can be summarized as:\n",
238 "\n",
239 "* \"linear\" colormaps all work well by this criterion\n",
240 "* \"diverging\" colormaps typically have discontinuities in perceptual discriminability around the central value\n",
241 "* \"cyclic\" colormaps with repeating colors tend to have discontinuities at 1/4 and 3/4 of the way through the cycle, or at other locations if shifted.\n",
242 "* \"isoluminant\" colormaps typically show no visible modulation, because without luminance cues humans can only discriminate low spatial-frequency modulations (i.e., much wider teeth would be needed for evaluating such colormaps)\n",
243 "* Some of the \"rainbow\" colormaps seem to have a perceptual discontinuity around the color red, the reasons for which are not yet clear."
244 ]
245 },
246 {
247 "cell_type": "code",
248 "execution_count": null,
249 "metadata": {
250 "collapsed": false
251 },
252 "outputs": [],
253 "source": [
254 "colormaps(all_cms,cols=1,array=sine)"
255 ]
256 }
257 ],
258 "metadata": {
259 "kernelspec": {
260 "display_name": "Python 2",
261 "language": "python",
262 "name": "python2"
263 },
264 "language_info": {
265 "codemirror_mode": {
266 "name": "ipython",
267 "version": 2
268 },
269 "file_extension": ".py",
270 "mimetype": "text/x-python",
271 "name": "python",
272 "nbconvert_exporter": "python",
273 "pygments_lexer": "ipython2",
274 "version": "2.7.11"
275 }
276 },
277 "nbformat": 4,
278 "nbformat_minor": 0
279 }
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setup.cfg less more
0 [metadata]
1 description-file = README.md
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setup.py less more
0 from setuptools import setup
1
2 setup(name='cetcolors',
3 version='0.9.0',
4 description='Collection of perceptually uniform colormaps',
5 url='http://github.com/bokeh/cetcolors',
6 maintainer='James A. Bednar',
7 maintainer_email='jbednar@continuum.io',
8 packages=['cetcolors'])