From 2ace1d78c6f33a16d8aa7de2028307254d3a0001 Mon Sep 17 00:00:00 2001
From: "Albert Y. Shih" <ayshih@gmail.com>
Date: Wed, 14 May 2025 13:34:10 -0400
Subject: [PATCH 1/2] Fix an off-by-half-pixel bug when resampling under a
 nonaffine transform

---
 lib/matplotlib/tests/test_image.py | 39 ++++++++++++++++++++++++++++--
 src/_image_wrapper.cpp             |  8 +++---
 2 files changed, 42 insertions(+), 5 deletions(-)

diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
index cededdb1b83c..c12a79bc2011 100644
--- a/lib/matplotlib/tests/test_image.py
+++ b/lib/matplotlib/tests/test_image.py
@@ -9,7 +9,7 @@
 import urllib.request
 
 import numpy as np
-from numpy.testing import assert_array_equal
+from numpy.testing import assert_allclose, assert_array_equal
 from PIL import Image
 
 import matplotlib as mpl
@@ -18,7 +18,7 @@
 from matplotlib.image import (AxesImage, BboxImage, FigureImage,
                               NonUniformImage, PcolorImage)
 from matplotlib.testing.decorators import check_figures_equal, image_comparison
-from matplotlib.transforms import Bbox, Affine2D, TransformedBbox
+from matplotlib.transforms import Bbox, Affine2D, Transform, TransformedBbox
 import matplotlib.ticker as mticker
 
 import pytest
@@ -1641,6 +1641,41 @@ def test__resample_valid_output():
         resample(np.zeros((9, 9)), out)
 
 
+@pytest.mark.parametrize("data, interpolation, expected",
+    [(np.array([[0.1, 0.3, 0.2]]), mimage.NEAREST,
+      np.array([[0.1, 0.1, 0.1, 0.3, 0.3, 0.3, 0.3, 0.2, 0.2, 0.2]])),
+     (np.array([[0.1, 0.3, 0.2]]), mimage.BILINEAR,
+      np.array([[0.1, 0.1, 0.15078125, 0.21096191, 0.27033691,
+                 0.28476562, 0.2546875, 0.22460938, 0.20002441, 0.20002441]])),
+    ]
+)
+def test_resample_nonaffine(data, interpolation, expected):
+    # Test that equivalent affine and nonaffine transforms resample the same
+
+    # Create a simple affine transform for scaling the input array
+    affine_transform = Affine2D().scale(sx=expected.shape[1] / data.shape[1], sy=1)
+
+    affine_result = np.empty_like(expected)
+    mimage.resample(data, affine_result, affine_transform,
+                        interpolation=interpolation)
+    assert_allclose(affine_result, expected)
+
+    # Create a nonaffine version of the same transform
+    # by compositing with a nonaffine identity transform
+    class NonAffineIdentityTransform(Transform):
+        input_dims = 2
+        output_dims = 2
+
+        def inverted(self):
+           return self
+    nonaffine_transform = NonAffineIdentityTransform() + affine_transform
+
+    nonaffine_result = np.empty_like(expected)
+    mimage.resample(data, nonaffine_result, nonaffine_transform,
+                        interpolation=interpolation)
+    assert_allclose(nonaffine_result, expected, atol=5e-3)
+
+
 def test_axesimage_get_shape():
     # generate dummy image to test get_shape method
     ax = plt.gca()
diff --git a/src/_image_wrapper.cpp b/src/_image_wrapper.cpp
index 0f7b0da88de8..87d2b3b288ec 100644
--- a/src/_image_wrapper.cpp
+++ b/src/_image_wrapper.cpp
@@ -54,7 +54,7 @@ _get_transform_mesh(const py::object& transform, const py::ssize_t *dims)
     /* TODO: Could we get away with float, rather than double, arrays here? */
 
     /* Given a non-affine transform object, create a mesh that maps
-    every pixel in the output image to the input image.  This is used
+    every pixel center in the output image to the input image.  This is used
     as a lookup table during the actual resampling. */
 
     // If attribute doesn't exist, raises Python AttributeError
@@ -66,8 +66,10 @@ _get_transform_mesh(const py::object& transform, const py::ssize_t *dims)
 
     for (auto y = 0; y < dims[0]; ++y) {
         for (auto x = 0; x < dims[1]; ++x) {
-            *p++ = (double)x;
-            *p++ = (double)y;
+            // The convention for the supplied transform is that pixel centers
+	    // are at 0.5, 1.5, 2.5, etc.
+            *p++ = (double)x + 0.5;
+            *p++ = (double)y + 0.5;
         }
     }
 

From 77bdca4c5148ac6ccf55acc6635ebf147ec28213 Mon Sep 17 00:00:00 2001
From: "Albert Y. Shih" <ayshih@gmail.com>
Date: Wed, 14 May 2025 21:05:39 -0400
Subject: [PATCH 2/2] Updated affected baseline images

---
 .../test_image/log_scale_image.pdf            | Bin 3780 -> 3776 bytes
 .../test_image/log_scale_image.png            | Bin 7914 -> 7942 bytes
 .../test_image/log_scale_image.svg            | 163 ++++++++++--------
 3 files changed, 87 insertions(+), 76 deletions(-)

diff --git a/lib/matplotlib/tests/baseline_images/test_image/log_scale_image.pdf b/lib/matplotlib/tests/baseline_images/test_image/log_scale_image.pdf
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index 6c958cc79592..259eb2c9c7f3 100644
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+++ b/lib/matplotlib/tests/baseline_images/test_image/log_scale_image.svg
@@ -1,12 +1,23 @@
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