Merge pull request matplotlib#29931 from guillermodotn/imsave-seq-fix

Allow Python native sequences in Matplotlib `imsave()`.

Author: ksunden

lib/matplotlib/image.py

@@ -1544,7 +1544,8 @@ def imsave(fname, arr, vmin=None, vmax=None, cmap=None, format=None,
         extension of *fname*, if any, and from :rc:`savefig.format` otherwise.
         If *format* is set, it determines the output format.
     arr : array-like
-        The image data. The shape can be one of
+        The image data. Accepts NumPy arrays or sequences
+        (e.g., lists or tuples). The shape can be one of
         MxN (luminance), MxNx3 (RGB) or MxNx4 (RGBA).
     vmin, vmax : float, optional
         *vmin* and *vmax* set the color scaling for the image by fixing the
@@ -1575,6 +1576,10 @@ def imsave(fname, arr, vmin=None, vmax=None, cmap=None, format=None,
         default 'Software' key.
     """
     from matplotlib.figure import Figure
+
+    # Normalizing input (e.g., list or tuples) to NumPy array if needed
+    arr = np.asanyarray(arr)
+
     if isinstance(fname, os.PathLike):
         fname = os.fspath(fname)
     if format is None:

lib/matplotlib/tests/test_image.py

@@ -184,6 +184,27 @@ def test_imsave(fmt):
     assert_array_equal(arr_dpi1, arr_dpi100)
 
 
+def test_imsave_python_sequences():
+    # Tests saving an image with data passed using Python sequence types
+    # such as lists or tuples.
+
+    # RGB image: 3 rows × 2 columns, with float values in [0.0, 1.0]
+    img_data = [
+        [(1.0, 0.0, 0.0), (0.0, 1.0, 0.0)],
+        [(0.0, 0.0, 1.0), (1.0, 1.0, 0.0)],
+        [(0.0, 1.0, 1.0), (1.0, 0.0, 1.0)],
+    ]
+
+    buff = io.BytesIO()
+    plt.imsave(buff, img_data, format="png")
+    buff.seek(0)
+    read_img = plt.imread(buff)
+
+    assert_array_equal(
+        np.array(img_data),
+        read_img[:, :, :3]  # Drop alpha if present
+    )
+
 @pytest.mark.parametrize("origin", ["upper", "lower"])
 def test_imsave_rgba_origin(origin):
     # test that imsave always passes c-contiguous arrays down to pillow