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4 changes: 2 additions & 2 deletions lib/matplotlib/cbook.py
Original file line number Diff line number Diff line change
Expand Up @@ -1340,9 +1340,9 @@ def _to_unmasked_float_array(x):
values are converted to nans.
"""
if hasattr(x, 'mask'):
return np.ma.asarray(x, float).filled(np.nan)
return np.ma.asanyarray(x, float).filled(np.nan)
else:
return np.asarray(x, float)
return np.asanyarray(x, float)


def _check_1d(x):
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16 changes: 8 additions & 8 deletions lib/matplotlib/collections.py
Original file line number Diff line number Diff line change
Expand Up @@ -1242,15 +1242,15 @@ def set_verts(self, verts, closed=True):
return

# Fast path for arrays
if isinstance(verts, np.ndarray) and len(verts.shape) == 3:
if isinstance(verts, np.ndarray) and len(verts.shape) == 3 and verts.size:
verts_pad = np.concatenate((verts, verts[:, :1]), axis=1)
# Creating the codes once is much faster than having Path do it
# separately each time by passing closed=True.
codes = np.empty(verts_pad.shape[1], dtype=mpath.Path.code_type)
codes[:] = mpath.Path.LINETO
codes[0] = mpath.Path.MOVETO
codes[-1] = mpath.Path.CLOSEPOLY
self._paths = [mpath.Path(xy, codes) for xy in verts_pad]
# It's faster to create the codes and internal flags once in a
# template path and reuse them.
template_path = mpath.Path(verts_pad[0], closed=True)
codes = template_path.codes
_make_path = mpath.Path._fast_from_codes_and_verts
self._paths = [_make_path(xy, codes, internals_from=template_path)
for xy in verts_pad]
return

self._paths = []
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1 change: 0 additions & 1 deletion lib/matplotlib/path.py
Original file line number Diff line number Diff line change
Expand Up @@ -76,7 +76,6 @@ class Path:
made up front in the constructor that will not change when the
data changes.
"""

code_type = np.uint8

# Path codes
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6 changes: 0 additions & 6 deletions lib/matplotlib/tests/test_transforms.py
Original file line number Diff line number Diff line change
Expand Up @@ -987,12 +987,6 @@ def test_transformed_path():
[(0, 0), (r2, r2), (0, 2 * r2), (-r2, r2)],
atol=1e-15)

# Changing the path does not change the result (it's cached).
path.points = [(0, 0)] * 4
assert_allclose(trans_path.get_fully_transformed_path().vertices,
[(0, 0), (r2, r2), (0, 2 * r2), (-r2, r2)],
atol=1e-15)


def test_transformed_patch_path():
trans = mtransforms.Affine2D()
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2 changes: 1 addition & 1 deletion lib/mpl_toolkits/mplot3d/art3d.py
Original file line number Diff line number Diff line change
Expand Up @@ -1367,7 +1367,7 @@ def _zalpha(colors, zs):
# Should really normalize against the viewing depth.
if len(colors) == 0 or len(zs) == 0:
return np.zeros((0, 4))
norm = Normalize(min(zs), max(zs))
norm = Normalize(np.min(zs), np.max(zs))
sats = 1 - norm(zs) * 0.7
rgba = np.broadcast_to(mcolors.to_rgba_array(colors), (len(zs), 4))
return np.column_stack([rgba[:, :3], rgba[:, 3] * sats])
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3 changes: 1 addition & 2 deletions lib/mpl_toolkits/mplot3d/proj3d.py
Original file line number Diff line number Diff line change
Expand Up @@ -164,8 +164,7 @@ def _proj_transform_vectors(vecs, M):

def _proj_transform_vec_clip(vec, M, focal_length):
vecw = np.dot(M, vec.data)
w = vecw[3]
txs, tys, tzs = vecw[0] / w, vecw[1] / w, vecw[2] / w
txs, tys, tzs = vecw[0:3] / vecw[3]
if np.isinf(focal_length): # don't clip orthographic projection
tis = np.ones(txs.shape, dtype=bool)
else:
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