Fix bilinear interpolation for SegmentedBivarColormap

ayshih · ayshih · commit 9f1bc1e58ef6 · 2025-12-08T13:12:09.000-05:00
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -55,7 +55,7 @@
 
 import matplotlib as mpl
 import numpy as np
-from matplotlib import _api, _cm, cbook, scale, _image
+from matplotlib import _api, _cm, cbook, scale
 from ._color_data import BASE_COLORS, TABLEAU_COLORS, CSS4_COLORS, XKCD_COLORS
 
 
@@ -2211,16 +2211,37 @@ def __init__(self, patch, N=256, shape='square', origin=(0, 0),
         super().__init__(N, N, shape, origin, name=name)
 
     def _init(self):
+        # Perform bilinear interpolation
+
         s = self.patch.shape
-        _patch = np.empty((s[0], s[1], 4))
-        _patch[:, :, :3] = self.patch
-        _patch[:, :, 3] = 1
-        transform = mpl.transforms.Affine2D().translate(-0.5, -0.5)\
-                                .scale(self.N / (s[1] - 1), self.N / (s[0] - 1))
-        self._lut = np.empty((self.N, self.N, 4))
-
-        _image.resample(_patch, self._lut, transform, _image.BILINEAR,
-                        resample=False, alpha=1)
+
+        # Indices (whole and fraction) of the new grid points
+        row = np.linspace(0, s[0] - 1, self.N)[:, np.newaxis]
+        col = np.linspace(0, s[1] - 1, self.N)[np.newaxis, :]
+        left = np.floor(row).astype(int)
+        top = np.floor(col).astype(int)
+        row_frac = (row - left)[:, :, np.newaxis]
+        col_frac = (col - top)[:, :, np.newaxis]
+
+        # Indices of the next edges, clipping where needed
+        right = np.clip(left + 1, 0, s[0] - 1)
+        bottom = np.clip(top + 1, 0, s[1] - 1)
+
+        # Values at the corners
+        tl = self.patch[left, top, :]
+        tr = self.patch[right, top, :]
+        bl = self.patch[left, bottom, :]
+        br = self.patch[right, bottom, :]
+
+        # Interpolate between the corners
+        lut = (tl * (1 - row_frac) * (1 - col_frac) +
+               tr * row_frac * (1 - col_frac) +
+               bl * (1 - row_frac) * col_frac +
+               br * row_frac * col_frac)
+
+        # Add the alpha channel
+        self._lut = np.concatenate([lut, np.ones((self.N, self.N, 1))], axis=2)
+
         self._isinit = True
 
 
diff --git a/lib/matplotlib/tests/test_multivariate_colormaps.py b/lib/matplotlib/tests/test_multivariate_colormaps.py
@@ -212,9 +212,18 @@ def test_multivar_resample():
 
 def test_bivar_cmap_call_tuple():
     cmap = mpl.bivar_colormaps['BiOrangeBlue']
-    assert_allclose(cmap((1.0, 1.0)), (1, 1, 1, 1), atol=0.01)
-    assert_allclose(cmap((0.0, 0.0)), (0, 0, 0, 1), atol=0.1)
-    assert_allclose(cmap((0.0, 0.0), alpha=0.1), (0, 0, 0, 0.1), atol=0.1)
+    assert_allclose(cmap((1.0, 1.0)), (1, 1, 1, 1))
+    assert_allclose(cmap((0.0, 0.0)), (0, 0, 0, 1))
+    assert_allclose(cmap((0.2, 0.8)), (0.2, 0.5, 0.8, 1))
+    assert_allclose(cmap((0.0, 0.0), alpha=0.1), (0, 0, 0, 0.1))
+
+
+def test_bivar_cmap_lut_smooth():
+    cmap = mpl.bivar_colormaps['BiOrangeBlue']
+    assert_allclose(cmap.lut[:, 0, 0], np.linspace(0, 1, 256))
+    assert_allclose(cmap.lut[:, 0, 1], np.linspace(0, 0.5, 256), atol=1e-3)
+    assert_allclose(cmap.lut[0, :, 1], np.linspace(0, 0.5, 256), atol=1e-3)
+    assert_allclose(cmap.lut[0, :, 2], np.linspace(0, 1, 256))
 
 
 def test_bivar_cmap_call():
@@ -312,17 +321,29 @@ def test_bivar_cmap_call():
                        match="only implemented for use with with floats"):
         cs = cmap([(0, 5, 9, 0, 0, 9), (0, 0, 0, 5, 11, 11)])
 
-    # test origin
+
+def test_bivar_cmap_1d_origin():
+    """
+    Test getting 1D colormaps with different origins
+    """
+    cmap = mpl.bivar_colormaps['BiOrangeBlue']
+    assert_allclose(cmap[0](1.), (1., 0.5, 0., 1.))
+    assert_allclose(cmap[1](1.), (0., 0.5, 1., 1.))
+
+    cmap = mpl.bivar_colormaps['BiOrangeBlue'].with_extremes(origin=(0, 1))
+    assert_allclose(cmap[0](1.), (1., 1., 1., 1.))
+    assert_allclose(cmap[1](1.), (0., 0.5, 1., 1.))
+
     cmap = mpl.bivar_colormaps['BiOrangeBlue'].with_extremes(origin=(0.5, 0.5))
     assert_allclose(cmap[0](0.5),
-                    (0.50244140625, 0.5024222412109375, 0.50244140625, 1))
+                    (0.5019607843137255, 0.5019453440984237, 0.5019607843137255, 1))
     assert_allclose(cmap[1](0.5),
-                    (0.50244140625, 0.5024222412109375, 0.50244140625, 1))
+                    (0.5019607843137255, 0.5019453440984237, 0.5019607843137255, 1))
+
     cmap = mpl.bivar_colormaps['BiOrangeBlue'].with_extremes(origin=(1, 1))
-    assert_allclose(cmap[0](1.),
-                    (0.99853515625, 0.9985467529296875, 0.99853515625, 1.0))
-    assert_allclose(cmap[1](1.),
-                    (0.99853515625, 0.9985467529296875, 0.99853515625, 1.0))
+    assert_allclose(cmap[0](1.), (1., 1., 1., 1.))
+    assert_allclose(cmap[1](1.), (1., 1., 1., 1.))
+
     with pytest.raises(KeyError,
                        match="only 0 or 1 are valid keys"):
         cs = cmap[2]
@@ -434,21 +455,21 @@ def test_bivar_cmap_from_image():
 
 def test_bivar_resample():
     cmap = mpl.bivar_colormaps['BiOrangeBlue'].resampled((2, 2))
-    assert_allclose(cmap((0.25, 0.25)), (0, 0, 0, 1), atol=1e-2)
+    assert_allclose(cmap((0.25, 0.25)), (0, 0, 0, 1))
 
     cmap = mpl.bivar_colormaps['BiOrangeBlue'].resampled((-2, 2))
-    assert_allclose(cmap((0.25, 0.25)), (1., 0.5, 0., 1.), atol=1e-2)
+    assert_allclose(cmap((0.25, 0.25)), (1., 0.5, 0., 1.))
 
     cmap = mpl.bivar_colormaps['BiOrangeBlue'].resampled((2, -2))
-    assert_allclose(cmap((0.25, 0.25)), (0., 0.5, 1., 1.), atol=1e-2)
+    assert_allclose(cmap((0.25, 0.25)), (0., 0.5, 1., 1.))
 
     cmap = mpl.bivar_colormaps['BiOrangeBlue'].resampled((-2, -2))
-    assert_allclose(cmap((0.25, 0.25)), (1, 1, 1, 1), atol=1e-2)
+    assert_allclose(cmap((0.25, 0.25)), (1, 1, 1, 1))
 
     cmap = mpl.bivar_colormaps['BiOrangeBlue'].reversed()
-    assert_allclose(cmap((0.25, 0.25)), (0.748535, 0.748547, 0.748535, 1.), atol=1e-2)
+    assert_allclose(cmap((0.25, 0.25)), (0.74902, 0.74902, 0.74902, 1.), atol=1e-5)
     cmap = mpl.bivar_colormaps['BiOrangeBlue'].transposed()
-    assert_allclose(cmap((0.25, 0.25)), (0.252441, 0.252422, 0.252441, 1.), atol=1e-2)
+    assert_allclose(cmap((0.25, 0.25)), (0.25098, 0.25098, 0.25098, 1.), atol=1e-5)
 
     with pytest.raises(ValueError, match="lutshape must be of length"):
         cmap = cmap.resampled(4)
