Sep 17, 2020 · Sep 17, 2020
diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
                # do not run the vmin/vmax through the same pipeline we can
                # have values close or equal to the boundaries end up on the
                # wrong side.
                vrange = np.array([self.norm.vmin, self.norm.vmax],
                                  dtype=scaled_dtype)
                vmin, vmax = self.norm.vmin, self.norm.vmax
                if vmin is np.ma.masked:
                    vmin, vmax = a_min, a_max
                vrange = np.array([vmin, vmax], dtype=scaled_dtype)

                A_scaled -= a_min
                vrange -= a_min
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
    ax2.imshow(A, interpolation='nearest')


 def test_mask_image_all():
    # Test behavior with an image that is entirely masked does not warn
    data = np.full((2, 2), np.nan)
    fig, ax = plt.subplots()
    ax.imshow(data)
    fig.canvas.draw_idle()  # would emit a warning


 @image_comparison(['imshow_endianess.png'], remove_text=True)
 def test_imshow_endianess():
    x = np.arange(10)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -474,8 +474,10 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
		# do not run the vmin/vmax through the same pipeline we can
		# have values close or equal to the boundaries end up on the
		# wrong side.
		vrange = np.array([self.norm.vmin, self.norm.vmax],
		dtype=scaled_dtype)
		vmin, vmax = self.norm.vmin, self.norm.vmax
		if vmin is np.ma.masked:
		vmin, vmax = a_min, a_max
		vrange = np.array([vmin, vmax], dtype=scaled_dtype)

		A_scaled -= a_min
		vrange -= a_min
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -846,6 +846,14 @@ def test_mask_image():
		ax2.imshow(A, interpolation='nearest')


		def test_mask_image_all():
		# Test behavior with an image that is entirely masked does not warn
		data = np.full((2, 2), np.nan)
		fig, ax = plt.subplots()
		ax.imshow(data)
		fig.canvas.draw_idle() # would emit a warning


		@image_comparison(['imshow_endianess.png'], remove_text=True)
		def test_imshow_endianess():
		x = np.arange(10)
Expand Down