New Upstream Snapshot - colorspacious
Ready changes
Summary
Merged new upstream version: 1.1.2+git20190817.1.5894892 (was: 1.1.2).
Resulting package
Built on 2022-12-20T09:20 (took 3m23s)
The resulting binary packages can be installed (if you have the apt repository enabled) by running one of:
apt install -t fresh-snapshots python3-colorspacious
Lintian Result
Diff
diff --git a/PKG-INFO b/PKG-INFO
index 1400cf0..ebd0e06 100644
--- a/PKG-INFO
+++ b/PKG-INFO
@@ -1,101 +1,101 @@
-Metadata-Version: 1.1
+Metadata-Version: 2.1
Name: colorspacious
-Version: 1.1.2
+Version: 1.1.2+dev
Summary: A powerful, accurate, and easy-to-use Python library for doing colorspace conversions
Home-page: https://github.com/njsmith/colorspacious
Author: Nathaniel J. Smith
Author-email: njs@pobox.com
License: MIT
-Description: colorspacious
- =============
-
- .. image:: https://travis-ci.org/njsmith/colorspacious.svg?branch=master
- :target: https://travis-ci.org/njsmith/colorspacious
- :alt: Automated test status
-
- .. image:: https://codecov.io/gh/njsmith/colorspacious/branch/master/graph/badge.svg
- :target: https://codecov.io/gh/njsmith/colorspacious
- :alt: Test coverage
-
- .. image:: https://readthedocs.org/projects/colorspacious/badge/?version=latest
- :target: http://colorspacious.readthedocs.io/en/latest/?badge=latest
- :alt: Documentation Status
-
- .. image:: https://zenodo.org/badge/38525000.svg
- :target: https://zenodo.org/badge/latestdoi/38525000
-
- Colorspacious is a powerful, accurate, and easy-to-use library for
- performing colorspace conversions.
-
- In addition to the most common standard colorspaces (sRGB, XYZ, xyY,
- CIELab, CIELCh), we also include: color vision deficiency ("color
- blindness") simulations using the approach of Machado et al (2009); a
- complete implementation of `CIECAM02
- <https://en.wikipedia.org/wiki/CIECAM02>`_; and the perceptually
- uniform CAM02-UCS / CAM02-LCD / CAM02-SCD spaces proposed by Luo et al
- (2006).
-
- To get started, simply write::
-
- from colorspacious import cspace_convert
-
- Jp, ap, bp = cspace_convert([64, 128, 255], "sRGB255", "CAM02-UCS")
-
- This converts an sRGB value (represented as integers between 0-255) to
- CAM02-UCS `J'a'b'` coordinates (assuming standard sRGB viewing
- conditions by default). This requires passing through 4 intermediate
- colorspaces; ``cspace_convert`` automatically finds the optimal route
- and applies all conversions in sequence:
-
- This function also of course accepts arbitrary NumPy arrays, so
- converting a whole image is just as easy as converting a single value.
-
- Documentation:
- http://colorspacious.readthedocs.org/
-
- Installation:
- ``pip install colorspacious``
-
- Downloads:
- https://pypi.python.org/pypi/colorspacious/
-
- Code and bug tracker:
- https://github.com/njsmith/colorspacious
-
- Contact:
- Nathaniel J. Smith <njs@pobox.com>
-
- Dependencies:
- * Python 2.6+, or 3.3+
- * NumPy
-
- Developer dependencies (only needed for hacking on source):
- * nose: needed to run tests
-
- License:
- MIT, see LICENSE.txt for details.
-
- References for algorithms we implement:
- * Luo, M. R., Cui, G., & Li, C. (2006). Uniform colour spaces based on
- CIECAM02 colour appearance model. Color Research & Application, 31(4),
- 320–330. doi:10.1002/col.20227
- * Machado, G. M., Oliveira, M. M., & Fernandes, L. A. (2009). A
- physiologically-based model for simulation of color vision
- deficiency. Visualization and Computer Graphics, IEEE Transactions on,
- 15(6), 1291–1298. http://www.inf.ufrgs.br/~oliveira/pubs_files/CVD_Simulation/CVD_Simulation.html
-
- Other Python packages with similar functionality that you might want
- to check out as well or instead:
-
- * ``colour``: http://colour-science.org/
- * ``colormath``: http://python-colormath.readthedocs.org/
- * ``ciecam02``: https://pypi.python.org/pypi/ciecam02/
- * ``ColorPy``: http://markkness.net/colorpy/ColorPy.html
-
-Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
+License-File: LICENSE.txt
+
+colorspacious
+=============
+
+.. image:: https://travis-ci.org/njsmith/colorspacious.svg?branch=master
+ :target: https://travis-ci.org/njsmith/colorspacious
+ :alt: Automated test status
+
+.. image:: https://codecov.io/gh/njsmith/colorspacious/branch/master/graph/badge.svg
+ :target: https://codecov.io/gh/njsmith/colorspacious
+ :alt: Test coverage
+
+.. image:: https://readthedocs.org/projects/colorspacious/badge/?version=latest
+ :target: http://colorspacious.readthedocs.io/en/latest/?badge=latest
+ :alt: Documentation Status
+
+.. image:: https://zenodo.org/badge/38525000.svg
+ :target: https://zenodo.org/badge/latestdoi/38525000
+
+Colorspacious is a powerful, accurate, and easy-to-use library for
+performing colorspace conversions.
+
+In addition to the most common standard colorspaces (sRGB, XYZ, xyY,
+CIELab, CIELCh), we also include: color vision deficiency ("color
+blindness") simulations using the approach of Machado et al (2009); a
+complete implementation of `CIECAM02
+<https://en.wikipedia.org/wiki/CIECAM02>`_; and the perceptually
+uniform CAM02-UCS / CAM02-LCD / CAM02-SCD spaces proposed by Luo et al
+(2006).
+
+To get started, simply write::
+
+ from colorspacious import cspace_convert
+
+ Jp, ap, bp = cspace_convert([64, 128, 255], "sRGB255", "CAM02-UCS")
+
+This converts an sRGB value (represented as integers between 0-255) to
+CAM02-UCS `J'a'b'` coordinates (assuming standard sRGB viewing
+conditions by default). This requires passing through 4 intermediate
+colorspaces; ``cspace_convert`` automatically finds the optimal route
+and applies all conversions in sequence:
+
+This function also of course accepts arbitrary NumPy arrays, so
+converting a whole image is just as easy as converting a single value.
+
+Documentation:
+ http://colorspacious.readthedocs.org/
+
+Installation:
+ ``pip install colorspacious``
+
+Downloads:
+ https://pypi.python.org/pypi/colorspacious/
+
+Code and bug tracker:
+ https://github.com/njsmith/colorspacious
+
+Contact:
+ Nathaniel J. Smith <njs@pobox.com>
+
+Dependencies:
+ * Python 2.6+, or 3.3+
+ * NumPy
+
+Developer dependencies (only needed for hacking on source):
+ * nose: needed to run tests
+
+License:
+ MIT, see LICENSE.txt for details.
+
+References for algorithms we implement:
+ * Luo, M. R., Cui, G., & Li, C. (2006). Uniform colour spaces based on
+ CIECAM02 colour appearance model. Color Research & Application, 31(4),
+ 320–330. doi:10.1002/col.20227
+ * Machado, G. M., Oliveira, M. M., & Fernandes, L. A. (2009). A
+ physiologically-based model for simulation of color vision
+ deficiency. Visualization and Computer Graphics, IEEE Transactions on,
+ 15(6), 1291–1298. http://www.inf.ufrgs.br/~oliveira/pubs_files/CVD_Simulation/CVD_Simulation.html
+
+Other Python packages with similar functionality that you might want
+to check out as well or instead:
+
+* ``colour``: http://colour-science.org/
+* ``colormath``: http://python-colormath.readthedocs.org/
+* ``ciecam02``: https://pypi.python.org/pypi/ciecam02/
+* ``ColorPy``: http://markkness.net/colorpy/ColorPy.html
diff --git a/colorspacious.egg-info/PKG-INFO b/colorspacious.egg-info/PKG-INFO
index 1400cf0..ebd0e06 100644
--- a/colorspacious.egg-info/PKG-INFO
+++ b/colorspacious.egg-info/PKG-INFO
@@ -1,101 +1,101 @@
-Metadata-Version: 1.1
+Metadata-Version: 2.1
Name: colorspacious
-Version: 1.1.2
+Version: 1.1.2+dev
Summary: A powerful, accurate, and easy-to-use Python library for doing colorspace conversions
Home-page: https://github.com/njsmith/colorspacious
Author: Nathaniel J. Smith
Author-email: njs@pobox.com
License: MIT
-Description: colorspacious
- =============
-
- .. image:: https://travis-ci.org/njsmith/colorspacious.svg?branch=master
- :target: https://travis-ci.org/njsmith/colorspacious
- :alt: Automated test status
-
- .. image:: https://codecov.io/gh/njsmith/colorspacious/branch/master/graph/badge.svg
- :target: https://codecov.io/gh/njsmith/colorspacious
- :alt: Test coverage
-
- .. image:: https://readthedocs.org/projects/colorspacious/badge/?version=latest
- :target: http://colorspacious.readthedocs.io/en/latest/?badge=latest
- :alt: Documentation Status
-
- .. image:: https://zenodo.org/badge/38525000.svg
- :target: https://zenodo.org/badge/latestdoi/38525000
-
- Colorspacious is a powerful, accurate, and easy-to-use library for
- performing colorspace conversions.
-
- In addition to the most common standard colorspaces (sRGB, XYZ, xyY,
- CIELab, CIELCh), we also include: color vision deficiency ("color
- blindness") simulations using the approach of Machado et al (2009); a
- complete implementation of `CIECAM02
- <https://en.wikipedia.org/wiki/CIECAM02>`_; and the perceptually
- uniform CAM02-UCS / CAM02-LCD / CAM02-SCD spaces proposed by Luo et al
- (2006).
-
- To get started, simply write::
-
- from colorspacious import cspace_convert
-
- Jp, ap, bp = cspace_convert([64, 128, 255], "sRGB255", "CAM02-UCS")
-
- This converts an sRGB value (represented as integers between 0-255) to
- CAM02-UCS `J'a'b'` coordinates (assuming standard sRGB viewing
- conditions by default). This requires passing through 4 intermediate
- colorspaces; ``cspace_convert`` automatically finds the optimal route
- and applies all conversions in sequence:
-
- This function also of course accepts arbitrary NumPy arrays, so
- converting a whole image is just as easy as converting a single value.
-
- Documentation:
- http://colorspacious.readthedocs.org/
-
- Installation:
- ``pip install colorspacious``
-
- Downloads:
- https://pypi.python.org/pypi/colorspacious/
-
- Code and bug tracker:
- https://github.com/njsmith/colorspacious
-
- Contact:
- Nathaniel J. Smith <njs@pobox.com>
-
- Dependencies:
- * Python 2.6+, or 3.3+
- * NumPy
-
- Developer dependencies (only needed for hacking on source):
- * nose: needed to run tests
-
- License:
- MIT, see LICENSE.txt for details.
-
- References for algorithms we implement:
- * Luo, M. R., Cui, G., & Li, C. (2006). Uniform colour spaces based on
- CIECAM02 colour appearance model. Color Research & Application, 31(4),
- 320–330. doi:10.1002/col.20227
- * Machado, G. M., Oliveira, M. M., & Fernandes, L. A. (2009). A
- physiologically-based model for simulation of color vision
- deficiency. Visualization and Computer Graphics, IEEE Transactions on,
- 15(6), 1291–1298. http://www.inf.ufrgs.br/~oliveira/pubs_files/CVD_Simulation/CVD_Simulation.html
-
- Other Python packages with similar functionality that you might want
- to check out as well or instead:
-
- * ``colour``: http://colour-science.org/
- * ``colormath``: http://python-colormath.readthedocs.org/
- * ``ciecam02``: https://pypi.python.org/pypi/ciecam02/
- * ``ColorPy``: http://markkness.net/colorpy/ColorPy.html
-
-Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
+License-File: LICENSE.txt
+
+colorspacious
+=============
+
+.. image:: https://travis-ci.org/njsmith/colorspacious.svg?branch=master
+ :target: https://travis-ci.org/njsmith/colorspacious
+ :alt: Automated test status
+
+.. image:: https://codecov.io/gh/njsmith/colorspacious/branch/master/graph/badge.svg
+ :target: https://codecov.io/gh/njsmith/colorspacious
+ :alt: Test coverage
+
+.. image:: https://readthedocs.org/projects/colorspacious/badge/?version=latest
+ :target: http://colorspacious.readthedocs.io/en/latest/?badge=latest
+ :alt: Documentation Status
+
+.. image:: https://zenodo.org/badge/38525000.svg
+ :target: https://zenodo.org/badge/latestdoi/38525000
+
+Colorspacious is a powerful, accurate, and easy-to-use library for
+performing colorspace conversions.
+
+In addition to the most common standard colorspaces (sRGB, XYZ, xyY,
+CIELab, CIELCh), we also include: color vision deficiency ("color
+blindness") simulations using the approach of Machado et al (2009); a
+complete implementation of `CIECAM02
+<https://en.wikipedia.org/wiki/CIECAM02>`_; and the perceptually
+uniform CAM02-UCS / CAM02-LCD / CAM02-SCD spaces proposed by Luo et al
+(2006).
+
+To get started, simply write::
+
+ from colorspacious import cspace_convert
+
+ Jp, ap, bp = cspace_convert([64, 128, 255], "sRGB255", "CAM02-UCS")
+
+This converts an sRGB value (represented as integers between 0-255) to
+CAM02-UCS `J'a'b'` coordinates (assuming standard sRGB viewing
+conditions by default). This requires passing through 4 intermediate
+colorspaces; ``cspace_convert`` automatically finds the optimal route
+and applies all conversions in sequence:
+
+This function also of course accepts arbitrary NumPy arrays, so
+converting a whole image is just as easy as converting a single value.
+
+Documentation:
+ http://colorspacious.readthedocs.org/
+
+Installation:
+ ``pip install colorspacious``
+
+Downloads:
+ https://pypi.python.org/pypi/colorspacious/
+
+Code and bug tracker:
+ https://github.com/njsmith/colorspacious
+
+Contact:
+ Nathaniel J. Smith <njs@pobox.com>
+
+Dependencies:
+ * Python 2.6+, or 3.3+
+ * NumPy
+
+Developer dependencies (only needed for hacking on source):
+ * nose: needed to run tests
+
+License:
+ MIT, see LICENSE.txt for details.
+
+References for algorithms we implement:
+ * Luo, M. R., Cui, G., & Li, C. (2006). Uniform colour spaces based on
+ CIECAM02 colour appearance model. Color Research & Application, 31(4),
+ 320–330. doi:10.1002/col.20227
+ * Machado, G. M., Oliveira, M. M., & Fernandes, L. A. (2009). A
+ physiologically-based model for simulation of color vision
+ deficiency. Visualization and Computer Graphics, IEEE Transactions on,
+ 15(6), 1291–1298. http://www.inf.ufrgs.br/~oliveira/pubs_files/CVD_Simulation/CVD_Simulation.html
+
+Other Python packages with similar functionality that you might want
+to check out as well or instead:
+
+* ``colour``: http://colour-science.org/
+* ``colormath``: http://python-colormath.readthedocs.org/
+* ``ciecam02``: https://pypi.python.org/pypi/ciecam02/
+* ``ColorPy``: http://markkness.net/colorpy/ColorPy.html
diff --git a/colorspacious/version.py b/colorspacious/version.py
index 7f6a288..b610577 100644
--- a/colorspacious/version.py
+++ b/colorspacious/version.py
@@ -18,4 +18,4 @@
# want. (Contrast with the special suffix 1.0.0.dev, which sorts *before*
# 1.0.0.)
-__version__ = "1.1.2"
+__version__ = "1.1.2+dev"
diff --git a/debian/changelog b/debian/changelog
index fa3bb77..90d89d6 100644
--- a/debian/changelog
+++ b/debian/changelog
@@ -1,3 +1,9 @@
+colorspacious (1.1.2+git20190817.1.5894892-1) UNRELEASED; urgency=low
+
+ * New upstream snapshot.
+
+ -- Debian Janitor <janitor@jelmer.uk> Tue, 20 Dec 2022 09:18:19 -0000
+
colorspacious (1.1.2-3) unstable; urgency=medium
[ Ondřej Nový ]
diff --git a/doc/changes.rst b/doc/changes.rst
index 550ef14..7feb931 100644
--- a/doc/changes.rst
+++ b/doc/changes.rst
@@ -4,6 +4,9 @@ Changes
v1.1.2
------
+.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.1214904.svg
+ :target: https://doi.org/10.5281/zenodo.1214904
+
* **BUG AFFECTING CALCULATIONS:** As a result of the scrutiny
triggered by the v1.1.1 release, we discovered that the reference
article that colorspacious (and other libraries) was using as a
diff --git a/doc/reference.rst b/doc/reference.rst
index 4cbc142..06c5081 100644
--- a/doc/reference.rst
+++ b/doc/reference.rst
@@ -148,9 +148,11 @@ and use ``xyY1`` if you have or want a Y value that falls between 0
and 1.
**CIELab**: The standard `CIE 1976 L*a*b* color space
-<https://en.wikipedia.org/wiki/Lab_color_space>`_. L* is scaled to
-vary from 0 to 100; a* and b* are likewise scaled to roughly the
-range -50 to 50. This space takes a parameter, *XYZ100_w*, which sets
+<https://en.wikipedia.org/wiki/Lab_color_space>`_.
+``L*`` is scaled to vary from 0 to 100,
+and in most settings the values of ``a*`` and ``b*`` will be roughly in the range -100 to 100,
+though you can certainly get larger values if your inputs are sufficiently extreme.
+This space takes a parameter, *XYZ100_w*, which sets
the reference white point, and may be specified either directly as a
tristimulus value or as a string naming one of the well-known standard
illuminants like ``"D65"``.
Debdiff
[The following lists of changes regard files as different if they have different names, permissions or owners.]
Files in second set of .debs but not in first
-rw-r--r-- root/root /usr/lib/python3/dist-packages/colorspacious-1.1.2+dev.egg-info/PKG-INFO -rw-r--r-- root/root /usr/lib/python3/dist-packages/colorspacious-1.1.2+dev.egg-info/dependency_links.txt -rw-r--r-- root/root /usr/lib/python3/dist-packages/colorspacious-1.1.2+dev.egg-info/requires.txt -rw-r--r-- root/root /usr/lib/python3/dist-packages/colorspacious-1.1.2+dev.egg-info/top_level.txt
Files in first set of .debs but not in second
-rw-r--r-- root/root /usr/lib/python3/dist-packages/colorspacious-1.1.2.egg-info/PKG-INFO -rw-r--r-- root/root /usr/lib/python3/dist-packages/colorspacious-1.1.2.egg-info/dependency_links.txt -rw-r--r-- root/root /usr/lib/python3/dist-packages/colorspacious-1.1.2.egg-info/requires.txt -rw-r--r-- root/root /usr/lib/python3/dist-packages/colorspacious-1.1.2.egg-info/top_level.txt
No differences were encountered in the control files