8000 Simplify handling of out-of-bound values `Colormap.__call__`. by anntzer · Pull Request #24978 · matplotlib/matplotlib · GitHub
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Simplify handling of out-of-bound values Colormap.__call__. #24978

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Merged
merged 1 commit into from
Jan 17, 2023
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Simplify handling of out-of-bound values Colormap.__call__. #24978

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30 changes: 10 additions & 20 deletions lib/matplotlib/colors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -706,30 +706,24 @@ def __call__(self, X, alpha=None, bytes=False):
if not self._isinit:
self._init()

# Take the bad mask from a masked array, or in all other cases defer
# np.isnan() to after we have converted to an array.
mask_bad = X.mask if np.ma.is_masked(X) else None
xa = np.array(X, copy=True)
if mask_bad is None:
mask_bad = np.isnan(xa)
if not xa.dtype.isnative:
xa = xa.byteswap().newbyteorder() # Native byteorder is faster.
if xa.dtype.kind == "f":
xa *= self.N
# Negative values are out of range, but astype(int) would
# truncate them towards zero.
xa[xa < 0] = -1
# xa == 1 (== N after multiplication) is not out of range.
xa[xa == self.N] = self.N - 1
# Avoid converting large positive values to negative integers.
np.clip(xa, -1, self.N, out=xa)
# Pre-compute the masks before casting to int (which can truncate
# negative values to zero or wrap large floats to negative ints).
mask_under = xa < 0
mask_over = xa >= self.N
# If input was masked, get the bad mask from it; else mask out nans.
mask_bad = X.mask if np.ma.is_masked(X) else np.isnan(xa)
with np.errstate(invalid="ignore"):
# We need this cast for unsigned ints as well as floats
xa = xa.astype(int)
# Set the over-range indices before the under-range;
# otherwise the under-range values get converted to over-range.
xa[xa > self.N - 1] = self._i_over
xa[xa < 0] = self._i_under
xa[mask_under] = self._i_under
xa[mask_over] = self._i_over
xa[mask_bad] = self._i_bad

lut = self._lut
Expand All @@ -747,13 +741,9 @@ def __call__(self, X, alpha=None, bytes=False):
f"alpha is array-like but its shape {alpha.shape} does "
f"not match that of X {xa.shape}")
rgba[..., -1] = alpha

# If the "bad" color is all zeros, then ignore alpha input.
if (lut[-1] == 0).all() and np.any(mask_bad):
if np.iterable(mask_bad) and mask_bad.shape == xa.shape:
rgba[mask_bad] = (0, 0, 0, 0)
else:
rgba[..., :] = (0, 0, 0, 0)
if (lut[-1] == 0).all():
rgba[mask_bad] = (0, 0, 0, 0)

if not np.iterable(X):
rgba = tuple(rgba)
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