GeezerVison is showing github.com — MultivarColormap and BivarColormap by trygvrad · Pull Request #28454 · matplotlib/matplotlib
MultivarColormap and BivarColormap
#28454
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c803091
MultivarColormap and BivarColormap
trygvrad Jun 25, 2024
f09791c
__getitem__ for colors.BivarColormap
trygvrad Jul 2, 2024
8c848aa
Better descriptors for 'Add' and 'Sub' in colors.MultivarColormap
trygvrad Jul 2, 2024
2213a88
minor fixes for MultivarColormap and BivarColormap
trygvrad Jul 3, 2024
446e1bd
Allows one to not clip to 0...1 in colors.MultivarColormap.__call__()
trygvrad Jul 3, 2024
04228c7
Multivariate and bivariate resampling of colormaps
trygvrad Jul 5, 2024
2911933
Corrected stubs for mutlivariate and bivariate colormaps
trygvrad Jul 6, 2024
e7d884c
minor fixes to colors.py
trygvrad Jul 9, 2024
d365483
Rename 'Add' to 'sRGB_add'
trygvrad Jul 18, 2024
77da937
name as keyword variable and additional tests to multivariate colormaps
trygvrad Jul 25, 2024
e688f03
Apply suggestions from code review
trygvrad Aug 5, 2024
69f9977
Fixes based on feedback on review
trygvrad Aug 5, 2024
8e3f393
removed exposure of multivariate and bivariate colormaps in cm.globals()
trygvrad Aug 7, 2024
a35bc29
improved docstring for MultivarColormap
trygvrad Aug 12, 2024
b73adcf
Apply suggestions from code review
trygvrad Aug 19, 2024
438923f
test _repr_png_() for MultivarColormap
trygvrad Aug 19, 2024
dcf6f8a
improved docstring for SegmentedBivarColormap()
trygvrad Aug 19, 2024
f2f2d71
updated default arguments in docs for multivar and bivar colormaps
trygvrad Aug 22, 2024
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@@ -129,6 +129,8 @@
"interactive",
"is_interactive",
"colormaps",
"multivar_colormaps",
"bivar_colormaps",
"color_sequences",
]
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@@ -1543,4 +1545,6 @@ def validate_backend(s):
# workaround: we must defer colormaps import to after loading rcParams, because
# colormap creation depends on rcParams
from matplotlib.cm import _colormaps as colormaps # noqa: E402
from matplotlib.cm import _multivar_colormaps as multivar_colormaps # noqa: E402
from matplotlib.cm import _bivar_colormaps as bivar_colormaps # noqa: E402
from matplotlib.colors import _color_sequences as color_sequences # noqa: E402
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@@ -116,4 +116,6 @@ def _preprocess_data(
) -> Callable: ...
from matplotlib.cm import _colormaps as colormaps # noqa: E402
from matplotlib.cm import _multivar_colormaps as multivar_colormaps # noqa: E402
from matplotlib.cm import _bivar_colormaps as bivar_colormaps # noqa: E402
from matplotlib.colors import _color_sequences as color_sequences # noqa: E402
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@@ -0,0 +1,166 @@
# auto-generated by https://github.com/trygvrad/multivariate_colormaps
# date: 2024-05-28
from .colors import LinearSegmentedColormap, MultivarColormap
import matplotlib as mpl
_LUTSIZE = mpl.rcParams['image.lut']
_2VarAddA0_data = [[0.000, 0.000, 0.000],
[0.020, 0.026, 0.031],
[0.049, 0.068, 0.085],
[0.075, 0.107, 0.135],
[0.097, 0.144, 0.183],
[0.116, 0.178, 0.231],
[0.133, 0.212, 0.279],
[0.148, 0.244, 0.326],
[0.161, 0.276, 0.374],
[0.173, 0.308, 0.422],
[0.182, 0.339, 0.471],
[0.190, 0.370, 0.521],
[0.197, 0.400, 0.572],
[0.201, 0.431, 0.623],
[0.204, 0.461, 0.675],
[0.204, 0.491, 0.728],
[0.202, 0.520, 0.783],
[0.197, 0.549, 0.838],
[0.187, 0.577, 0.895]]
_2VarAddA1_data = [[0.000, 0.000, 0.000],
[0.030, 0.023, 0.018],
[0.079, 0.060, 0.043],
[0.125, 0.093, 0.065],
[0.170, 0.123, 0.083],
[0.213, 0.151, 0.098],
[0.255, 0.177, 0.110],
[0.298, 0.202, 0.120],
[0.341, 0.226, 0.128],
[0.384, 0.249, 0.134],
[0.427, 0.271, 0.138],
[0.472, 0.292, 0.141],
[0.517, 0.313, 0.142],
[0.563, 0.333, 0.141],
[0.610, 0.353, 0.139],
[0.658, 0.372, 0.134],
[0.708, 0.390, 0.127],
[0.759, 0.407, 0.118],
[0.813, 0.423, 0.105]]
_2VarSubA0_data = [[1.000, 1.000, 1.000],
[0.959, 0.973, 0.986],
[0.916, 0.948, 0.974],
[0.874, 0.923, 0.965],
[0.832, 0.899, 0.956],
[0.790, 0.875, 0.948],
[0.748, 0.852, 0.940],
[0.707, 0.829, 0.934],
[0.665, 0.806, 0.927],
[0.624, 0.784, 0.921],
[0.583, 0.762, 0.916],
[0.541, 0.740, 0.910],
[0.500, 0.718, 0.905],
[0.457, 0.697, 0.901],
[0.414, 0.675, 0.896],
[0.369, 0.652, 0.892],
[0.320, 0.629, 0.888],
[0.266, 0.604, 0.884],
[0.199, 0.574, 0.881]]
_2VarSubA1_data = [[1.000, 1.000, 1.000],
[0.982, 0.967, 0.955],
[0.966, 0.935, 0.908],
[0.951, 0.902, 0.860],
[0.937, 0.870, 0.813],
[0.923, 0.838, 0.765],
[0.910, 0.807, 0.718],
[0.898, 0.776, 0.671],
[0.886, 0.745, 0.624],
[0.874, 0.714, 0.577],
[0.862, 0.683, 0.530],
[0.851, 0.653, 0.483],
[0.841, 0.622, 0.435],
[0.831, 0.592, 0.388],
[0.822, 0.561, 0.340],
[0.813, 0.530, 0.290],
[0.806, 0.498, 0.239],
[0.802, 0.464, 0.184],
[0.801, 0.426, 0.119]]
_3VarAddA0_data = [[0.000, 0.000, 0.000],
[0.018, 0.023, 0.028],
[0.040, 0.056, 0.071],
[0.059, 0.087, 0.110],
[0.074, 0.114, 0.147],
[0.086, 0.139, 0.183],
[0.095, 0.163, 0.219],
[0.101, 0.187, 0.255],
[0.105, 0.209, 0.290],
[0.107, 0.230, 0.326],
[0.105, 0.251, 0.362],
[0.101, 0.271, 0.398],
[0.091, 0.291, 0.434],
[0.075, 0.309, 0.471],
[0.046, 0.325, 0.507],
[0.021, 0.341, 0.546],
[0.021, 0.363, 0.584],
[0.022, 0.385, 0.622],
[0.023, 0.408, 0.661]]
_3VarAddA1_data = [[0.000, 0.000, 0.000],
[0.020, 0.024, 0.016],
[0.047, 0.058, 0.034],
[0.072, 0.088, 0.048],
[0.093, 0.116, 0.059],
[0.113, 0.142, 0.067],
[0.131, 0.167, 0.071],
[0.149, 0.190, 0.074],
[0.166, 0.213, 0.074],
[0.182, 0.235, 0.072],
[0.198, 0.256, 0.068],
[0.215, 0.276, 0.061],
[0.232, 0.296, 0.051],
[0.249, 0.314, 0.037],
[0.270, 0.330, 0.018],
[0.288, 0.347, 0.000],
[0.302, 0.369, 0.000],
[0.315, 0.391, 0.000],
[0.328, 0.414, 0.000]]
_3VarAddA2_data = [[0.000, 0.000, 0.000],
[0.029, 0.020, 0.023],
[0.072, 0.045, 0.055],
[0.111, 0.067, 0.084],
[0.148, 0.085, 0.109],
[0.184, 0.101, 0.133],
[0.219, 0.115, 0.155],
[0.254, 0.127, 0.176],
[0.289, 0.138, 0.195],
[0.323, 0.147, 0.214],
[0.358, 0.155, 0.232],
[0.393, 0.161, 0.250],
[0.429, 0.166, 0.267],
[0.467, 0.169, 0.283],
[0.507, 0.168, 0.298],
[0.546, 0.168, 0.313],
[0.580, 0.172, 0.328],
[0.615, 0.175, 0.341],
[0.649, 0.178, 0.355]]
cmaps = {
name: LinearSegmentedColormap.from_list(name, data, _LUTSIZE) for name, data in [
('2VarAddA0', _2VarAddA0_data),
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These are pretty esoteric names; are they documented somewhere? Might even need a comment here as well.
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@QuLogic thanks for all the comments#28428 (comment)
I wrote a blogpost about their design here: https://trygvrad.github.io/multivariate-colormaps-for-n-dimensions/
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So one of the reasons I suggested we maybe pull these in as dark mode cmaps #28454 (comment) , and I'm okay w/ that happening in a later PR, is that we could then probably have more semantically meaningful names based on the individual maps.
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('2VarAddA1', _2VarAddA1_data),
('2VarSubA0', _2VarSubA0_data),
('2VarSubA1', _2VarSubA1_data),
('3VarAddA0', _3VarAddA0_data),
('3VarAddA1', _3VarAddA1_data),
('3VarAddA2', _3VarAddA2_data),
]}
cmap_families = {
'2VarAddA': MultivarColormap([cmaps[f'2VarAddA{i}'] for i in range(2)],
'sRGB_add', name='2VarAddA'),
'2VarSubA': MultivarColormap([cmaps[f'2VarSubA{i}'] for i in range(2)],
'sRGB_sub', name='2VarSubA'),
'3VarAddA': MultivarColormap([cmaps[f'3VarAddA{i}'] for i in range(3)],
'sRGB_add', name='3VarAddA'),
}
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@@ -24,6 +24,8 @@
from matplotlib import _api, colors, cbook, scale
from matplotlib._cm import datad
from matplotlib._cm_listed import cmaps as cmaps_listed
from matplotlib._cm_multivar import cmap_families as multivar_cmaps
from matplotlib._cm_bivar import cmaps as bivar_cmaps
_LUTSIZE = mpl.rcParams['image.lut']
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@@ -238,6 +240,10 @@ def get_cmap(self, cmap):
_colormaps = ColormapRegistry(_gen_cmap_registry())
globals().update(_colormaps)
_multivar_colormaps = ColormapRegistry(multivar_cmaps)
_bivar_colormaps = ColormapRegistry(bivar_cmaps)
# This is an exact copy of pyplot.get_cmap(). It was removed in 3.9, but apparently
# caused more user trouble than expected. Re-added for 3.9.1 and extended the
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@@ -18,6 +18,8 @@ class ColormapRegistry(Mapping[str, colors.Colormap]):
def get_cmap(self, cmap: str | colors.Colormap) -> colors.Colormap: ...
_colormaps: ColormapRegistry = ...
_multivar_colormaps: ColormapRegistry = ...
_bivar_colormaps: ColormapRegistry = ...
def get_cmap(name: str | colors.Colormap | None = ..., lut: int | None = ...) -> colors.Colormap: ...
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