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Speedup LinearSegmentedColormap.from_list. #19287

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Merged
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Jan 18, 2021
Merged

Speedup LinearSegmentedColormap.from_list. #19287

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31 changes: 20 additions & 11 deletions lib/matplotlib/colors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -361,11 +361,20 @@ def to_rgba_array(c, alpha=None):

if len(c) == 0:
return np.zeros((0, 4), float)

# Quick path if the whole sequence can be directly converted to a numpy
# array in one shot.
lens = {len(cc) if isinstance(cc, (list, tuple)) else -1 for cc in c}
if lens == {3}:
rgba = np.column_stack([c, np.ones(len(c))])
elif lens == {4}:
rgba = np.array(c)
else:
if np.iterable(alpha):
return np.array([to_rgba(cc, aa) for cc, aa in zip(c, alpha)])
else:
return np.array([to_rgba(cc, alpha) for cc in c])
rgba = np.array([to_rgba(cc) for cc in c])

if alpha is not None:
rgba[:, 3] = alpha
return rgba


def to_rgb(c):
Expand Down Expand Up @@ -914,13 +923,13 @@ def from_list(name, colors, N=256, gamma=1.0):
else:
vals = np.linspace(0, 1, len(colors))

cdict = dict(red=[], green=[], blue=[], alpha=[])
for val, color in zip(vals, colors):
r, g, b, a = to_rgba(color)
cdict['red'].append((val, r, r))
cdict['green'].append((val, g, g))
cdict['blue'].append((val, b, b))
cdict['alpha'].append((val, a, a))
r, g, b, a = to_rgba_array(colors).T
cdict = {
"red": np.column_stack([vals, r, r]),
"green": np.column_stack([vals, g, g]),
"blue": np.column_stack([vals, b, b]),
"alpha": np.column_stack([vals, a, a]),
}

return LinearSegmentedColormap(name, cdict, N, gamma)

Expand Down