# This file is part of xrayutilities.
#
# xrayutilities is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, see <http://www.gnu.org/licenses/>.
#
# Copyright (C) 2012 Dominik Kriegner <dominik.kriegner@gmail.com>
# Copyright (C) 2012 Tanja Etzelstorfer <tanja.etzelstorfer@jku.at>

import matplotlib as mpl
import matplotlib.pyplot as plt
import xrayutilities as xu

# plot settings for matplotlib
mpl.rcParams['font.family'] = 'serif'
mpl.rcParams['font.size'] = 20.0
mpl.rcParams['axes.labelsize'] = 'large'
mpl.rcParams['figure.subplot.bottom'] = 0.16
mpl.rcParams['figure.subplot.left'] = 0.17
mpl.rcParams['savefig.dpi'] = 200
mpl.rcParams['axes.grid'] = False


# global setting for the experiment
sample = "rsm" # sample name used also as file name for the data file

# substrate material used for Bragg peak calculation to correct for experimental offsets
Si = xu.materials.Si
Ge = xu.materials.Ge
SiGe = xu.materials.SiGe(1) # parameter x_Ge = 1

hxrd = xu.HXRD(Si.Q(1,1,0),Si.Q(0,0,1))

#################################
# Si/SiGe (004) reciprocal space map
omalign = 34.3046 # experimental aligned values
ttalign = 69.1283
[omnominal,dummy,dummy,ttnominal] = hxrd.Q2Ang(Si.Q(0,0,4)) # nominal values of the substrate peak

# read the data from the xrdml files
om,tt,psd = xu.io.getxrdml_map(sample+'_%d.xrdml',[1,2,3,4,5],path='data')

# determine offset of substrate peak from experimental values (optional)
omalign,ttalign,p,cov = xu.analysis.fit_bragg_peak(om,tt,psd,omalign,ttalign,hxrd,plot=False)

# convert angular coordinates to reciprocal space + correct for offsets
[qx,qy,qz] = hxrd.Ang2Q(om,tt,delta=[omalign-omnominal, ttalign-ttnominal])

# calculate data on a regular grid of 200x201 points
gridder = xu.Gridder2D(200,600)
gridder(qy,qz,psd)
INT = xu.maplog(gridder.gdata.transpose(),6,0)

# plot the intensity as contour plot
plt.figure(); plt.clf()
cf = plt.contourf(gridder.xaxis, gridder.yaxis,INT,100,extend='min')
plt.xlabel(r'$Q_{[110]}$ ($\AA^{-1}$)')
plt.ylabel(r'$Q_{[001]}$ ($\AA^{-1}$)')
cb = plt.colorbar(cf)
cb.set_label(r"$\log($Int$)$ (cps)")

tr = SiGe.RelaxationTriangle([0,0,4], Si, hxrd)
plt.plot(tr[0],tr[1], 'ko')