Fix Affine matrix multiplication warnings

CONTRIBUTING.rst

@@ -169,3 +169,7 @@ Tips
 To run a subset of tests::
 
 $ pytest test/unit/test_show_versions.py::test_get_main_info
+
+When using NumPy's ``assert_almost_equal`` to compare affine transforms, pass
+``tuple(transform)`` for both operands. This compares all nine coefficients
+with the requested precision and avoids treating Affine 3 objects as scalars.

docs/history.rst

@@ -3,6 +3,7 @@ History
 
 Latest
 ------
+- DEP: Require rasterio>=1.5.1 and affine>=3 for matrix multiplication support (#939)
 
 0.23.0
 ------

pyproject.toml

@@ -34,7 +34,8 @@ classifiers = [
 requires-python = ">=3.12"
 dependencies = [
     "packaging",
-    "rasterio>=1.4.3",
+    "rasterio>=1.5.1",
+    "affine>=3",
     # https://github.com/pydata/xarray/issues/11000
     "xarray>=2026.2",
     "pyproj>=3.3",

rioxarray/_spatial_utils.py

@@ -5,7 +5,7 @@
 import math
 import warnings
 from collections.abc import Hashable
-from typing import Any, Iterable, Optional, Union
+from typing import Any, Iterable, Optional, Union, cast
 
 import numpy
 import rasterio.mask
@@ -114,12 +114,13 @@ def affine_to_coords(
     dict: x and y coordinate arrays.
 
     """
-    transform = affine * affine.translation(0.5, 0.5)
+    # Affine's typed overloads do not cover NumPy coordinate arrays.
+    transform = cast(Any, affine @ affine.translation(0.5, 0.5))
     if affine.is_rectilinear and not _affine_has_rotation(affine):
-        x_coords, _ = transform * (numpy.arange(width), numpy.zeros(width))
-        _, y_coords = transform * (numpy.zeros(height), numpy.arange(height))
+        x_coords, _ = transform @ (numpy.arange(width), numpy.zeros(width))
+        _, y_coords = transform @ (numpy.zeros(height), numpy.arange(height))
     else:
-        x_coords, y_coords = transform * numpy.meshgrid(
+        x_coords, y_coords = transform @ numpy.meshgrid(
             numpy.arange(width),
             numpy.arange(height),
         )

rioxarray/rioxarray.py

@@ -439,7 +439,7 @@ def transform(self, recalc: bool = False) -> Affine:
             src_resolution_x, src_resolution_y = self.resolution(recalc=recalc)
         except (DimensionMissingCoordinateError, DimensionError):
             return Affine.identity() if transform is None else transform
-        return Affine.translation(src_left, src_top) * Affine.scale(
+        return Affine.translation(src_left, src_top) @ Affine.scale(
             src_resolution_x, src_resolution_y
         )
 

test/integration/test_integration_rioxarray.py

@@ -323,7 +323,8 @@ def test_pad_box(modis_clip):
                     assert padded_size == original_size
         else:
             assert_almost_equal(
-                xdi.rio._cached_transform(), padded_ds.rio._cached_transform()
+                tuple(xdi.rio._cached_transform()),
+                tuple(padded_ds.rio._cached_transform()),
             )
             for padded_size, original_size in zip(padded_ds.shape, xdi.shape):
                 assert padded_size == original_size
@@ -353,7 +354,9 @@ def test_clip_box(modis_clip):
         except KeyError:
             xdc_values = xdc.values
         assert_almost_equal(clipped_ds_values, xdc_values)
-        assert_almost_equal(clipped_ds.rio.transform(), xdc.rio.transform())
+        assert_almost_equal(
+            tuple(clipped_ds.rio.transform()), tuple(xdc.rio.transform())
+        )
         # make sure it safely writes to netcdf
         clipped_ds.to_netcdf(modis_clip["output"])
 
@@ -381,7 +384,9 @@ def test_clip_box__auto_expand(modis_clip):
         except KeyError:
             xdc_values = xdc.values
         assert_almost_equal(clipped_ds_values, xdc_values)
-        assert_almost_equal(clipped_ds.rio.transform(), xdc.rio.transform())
+        assert_almost_equal(
+            tuple(clipped_ds.rio.transform()), tuple(xdc.rio.transform())
+        )
         # make sure it safely writes to netcdf
         clipped_ds.to_netcdf(modis_clip["output"])
 
@@ -549,7 +554,9 @@ def test_slice_xy(modis_clip):
         except KeyError:
             xdc_values = xdc.values
         assert_almost_equal(clipped_ds_values, xdc_values)
-        assert_almost_equal(clipped_ds.rio.transform(), xdc.rio.transform())
+        assert_almost_equal(
+            tuple(clipped_ds.rio.transform()), tuple(xdc.rio.transform())
+        )
         # make sure it safely writes to netcdf
         clipped_ds.to_netcdf(modis_clip["output"])
 
@@ -1428,7 +1435,7 @@ def test_make_coords__calc_trans(open_func, modis_reproject):
             dst_height=heightr,
         )
 
-        assert_almost_equal(calculated_transform, calculated_transformr)
+        assert_almost_equal(tuple(calculated_transform), tuple(calculated_transformr))
         # check to see if they all match
         if not isinstance(open_func, partial):
             assert_almost_equal(
@@ -1477,7 +1484,7 @@ def test_make_coords__attr_trans(open_func, modis_reproject):
             dst_width=widthr,
             dst_height=heightr,
         )
-        assert_almost_equal(attr_transform, calculated_transformr)
+        assert_almost_equal(tuple(attr_transform), tuple(calculated_transformr))
         # check to see if they all match
         if not isinstance(open_func, partial):
             assert_almost_equal(

test/unit/test_spatial_utils.py

@@ -0,0 +1,12 @@
+import numpy
+from affine import Affine
+
+from rioxarray._spatial_utils import affine_to_coords
+
+
+def test_affine_to_coords_avoids_deprecated_matrix_multiplication() -> None:
+    transform = Affine(1, 0, 0, 0, -1, 4)
+    coords = affine_to_coords(transform, width=4, height=4)
+
+    numpy.testing.assert_array_equal(coords["x"], [0.5, 1.5, 2.5, 3.5])
+    numpy.testing.assert_array_equal(coords["y"], [3.5, 2.5, 1.5, 0.5])