Simplify handling of out-of-bound values Colormap.__call__.

anntzer · anntzer · commit 04e708882065 · 2023-01-14T17:39:02.000+01:00
Mostly, we don't need to manually handle/clip out of bounds float values
if we compute the masks early enough (note that these masks are always
computed at some point anyways, so there's no cost of doing that a bit
earlier).
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -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
@@ -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)
