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ListedColormap: repeat colors if necessary #147

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Merged
mathause merged 2 commits into from
Nov 25, 2024
Merged

ListedColormap: repeat colors if necessary #147

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ListedColormap: repeat colors if necessary
mathause Nov 25, 2024
393c4a5
changelog
mathause Nov 25, 2024
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5 changes: 5 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -40,6 +40,11 @@

- Ensure the current axes (`plt.gca()`) is not changed by calling `mpu.colorbar(...)` ([#136](https://github.com/mathause/mplotutils/pull/136)).

### Internal changes

- Align internal usage of `ListedColormaps` with changes in [matplotlib/matplotlib#29135](https://github.com/matplotlib/matplotlib/pull/29135)
([#145](https://github.com/mathause/mplotutils/pull/145), and [#147](https://github.com/mathause/mplotutils/pull/147)).

## v0.5.0 (27.03.2024)

Version v0.5.0 aligns passing multiple axes to `colorbar` with matplotlib.
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5 changes: 4 additions & 1 deletion mplotutils/_colormaps.py
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@@ -1,3 +1,5 @@
import itertools

import matplotlib as mpl
import numpy as np
from matplotlib.colors import from_levels_and_colors
Expand Down Expand Up @@ -54,7 +56,8 @@ def _color_palette(cmap, n_colors):

colors_i = np.linspace(0, 1.0, n_colors)
if isinstance(cmap, (list, tuple)):
# we have a list of colors
# expand or truncate the list of colors to n_colors
cmap = list(itertools.islice(itertools.cycle(cmap), n_colors))
cmap = ListedColormap(cmap)
pal = cmap(colors_i)
elif isinstance(cmap, str):
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19 changes: 18 additions & 1 deletion mplotutils/tests/test_colormap.py
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Expand Up @@ -77,8 +77,25 @@ def test_from_levels_and_cmap_seaborn_cmap():


def test_from_levels_and_cmap_colorstring():
pytest.importorskip("seaborn")

levels = [1, 2, 3]
cmap, norm = mpu.from_levels_and_cmap(levels, "0.1")
assert_cmap_norm(cmap, norm, levels, extend="neither")

np.testing.assert_equal(cmap.colors[0], np.array([0.1, 0.1, 0.1, 1.0]))
np.testing.assert_equal(cmap.colors[1], np.array([0.1, 0.1, 0.1, 1.0]))


def test_from_levels_and_cmap_color_list_explicit():

levels = [1, 2, 3, 4, 5]

# ensure colors are repeated (although that can also be unexpected)
cmap, norm = mpu.from_levels_and_cmap(levels, ["b", "k"])

assert_cmap_norm(cmap, norm, levels, extend="neither")

np.testing.assert_equal(cmap.colors[0], np.array([0.0, 0.0, 1.0, 1.0])) # blue
np.testing.assert_equal(cmap.colors[1], np.array([0.0, 0.0, 0.0, 1.0])) # black
np.testing.assert_equal(cmap.colors[2], np.array([0.0, 0.0, 1.0, 1.0])) # blue
np.testing.assert_equal(cmap.colors[3], np.array([0.0, 0.0, 0.0, 1.0])) # black
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