matplotlib
diff --git a/‎lib/matplotlib/colors.py
Copy file name to clipboardExpand all lines: lib/matplotlib/colors.py
+14-24Lines changed: 14 additions & 24 deletions b/‎lib/matplotlib/colors.py
Copy file name to clipboardExpand all lines: lib/matplotlib/colors.py
+14-24Lines changed: 14 additions & 24 deletions
diff --git a/‎lib/matplotlib/tests/test_colors.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_colors.py
+1-2Lines changed: 1 addition & 2 deletions b/‎lib/matplotlib/tests/test_colors.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_colors.py
+1-2Lines changed: 1 addition & 2 deletions
diff --git a/‎lib/mpl_toolkits/tests/test_axes_grid1.py
Copy file name to clipboardExpand all lines: lib/mpl_toolkits/tests/test_axes_grid1.py
+2-3Lines changed: 2 additions & 3 deletions b/‎lib/mpl_toolkits/tests/test_axes_grid1.py
Copy file name to clipboardExpand all lines: lib/mpl_toolkits/tests/test_axes_grid1.py
+2-3Lines changed: 2 additions & 3 deletions
@@ -1317,21 +1317,19 @@ def rgb_to_hsv(arr):
     hsv : (..., 3) ndarray
        Colors converted to hsv values in range [0, 1]
     """
-    # make sure it is an ndarray
     arr = np.asarray(arr)
 
     # check length of the last dimension, should be _some_ sort of rgb
     if arr.shape[-1] != 3:
         raise ValueError("Last dimension of input array must be 3; "
                          "shape {} was found.".format(arr.shape))
 
-    in_ndim = arr.ndim
-    if arr.ndim == 1:
-        arr = np.array(arr, ndmin=2)
-
-    # make sure we don't have an int image
-    arr = arr.astype(np.promote_types(arr.dtype, np.float32))
-
+    in_shape = arr.shape
+    arr = np.array(
+        arr, copy=False,
+        dtype=np.promote_types(arr.dtype, np.float32),  # Don't work on ints.
+        ndmin=2,  # In case input was 1D.
+    )
     out = np.zeros_like(arr)
     arr_max = arr.max(-1)
     ipos = arr_max > 0
@@ -1353,10 +1351,7 @@ def rgb_to_hsv(arr):
     out[..., 1] = s
     out[..., 2] = arr_max
 
-    if in_ndim == 1:
-        out.shape = (3,)
-
-    return out
+    return out.reshape(in_shape)
 
 
 def hsv_to_rgb(hsv):
@@ -1381,14 +1376,12 @@ def hsv_to_rgb(hsv):
         raise ValueError("Last dimension of input array must be 3; "
                          "shape {shp} was found.".format(shp=hsv.shape))
 
-    # if we got passed a 1D array, try to treat as
-    # a single color and reshape as needed
-    in_ndim = hsv.ndim
-    if in_ndim == 1:
-        hsv = np.array(hsv, ndmin=2)
-
-    # make sure we don't have an int image
-    hsv = hsv.astype(np.promote_types(hsv.dtype, np.float32))
+    in_shape = hsv.shape
+    hsv = np.array(
+        hsv, copy=False,
+        dtype=np.promote_types(hsv.dtype, np.float32),  # Don't work on ints.
+        ndmin=2,  # In case input was 1D.
+    )
 
     h = hsv[..., 0]
     s = hsv[..., 1]
@@ -1441,10 +1434,7 @@ def hsv_to_rgb(hsv):
 
     rgb = np.stack([r, g, b], axis=-1)
 
-    if in_ndim == 1:
-        rgb.shape = (3,)
-
-    return rgb
+    return rgb.reshape(in_shape)
 
 
 def _vector_magnitude(arr):
 
@@ -695,8 +695,7 @@ def __isub__(self, other):
         def __add__(self, other):
             raise RuntimeError
 
-    data = np.arange(-10, 10, 1, dtype=float)
-    data.shape = (10, 2)
+    data = np.arange(-10, 10, 1, dtype=float).reshape((10, 2))
     mydata = data.view(MyArray)
 
     for norm in [mcolors.Normalize(), mcolors.LogNorm(),
 
@@ -398,10 +398,9 @@ def test_axes_locatable_position():
                   savefig_kwarg={'bbox_inches': 'tight'})
 def test_image_grid():
     # test that image grid works with bbox_inches=tight.
-    im = np.arange(100)
-    im.shape = 10, 10
+    im = np.arange(100).reshape((10, 10))
 
-    fig = plt.figure(1, (4., 4.))
+    fig = plt.figure(1, (4, 4))
     grid = ImageGrid(fig, 111, nrows_ncols=(2, 2), axes_pad=0.1)
 
     for i in range(4):