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Let imshow handle float128 data. #8447

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Merged
merged 1 commit into from
Apr 14, 2017
Merged

Let imshow handle float128 data. #8447

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7 changes: 6 additions & 1 deletion lib/matplotlib/colors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -188,7 +188,7 @@ def _to_rgba_no_colorcycle(c, alpha=None):
raise ValueError("Invalid RGBA argument: {!r}".format(orig_c))
# tuple color.
c = np.array(c)
if not np.can_cast(c.dtype, float) or c.ndim != 1:
if not np.can_cast(c.dtype, float, "same_kind") or c.ndim != 1:
# Test the dtype explicitly as `map(float, ...)`, `np.array(...,
# float)` and `np.array(...).astype(float)` all convert "0.5" to 0.5.
# Test dimensionality to reject single floats.
Expand Down Expand Up @@ -934,6 +934,11 @@ def __call__(self, value, clip=None):
resdat -= vmin
resdat /= (vmax - vmin)
result = np.ma.array(resdat, mask=result.mask, copy=False)
# Agg cannot handle float128. We actually only need 32-bit of
# precision, but on Windows, `np.dtype(np.longdouble) == np.float64`,
# so casting to float32 would lose precision on float64s as well.
if result.dtype == np.longdouble:
result = result.astype(np.float64)
if is_scalar:
result = result[0]
return result
Expand Down
16 changes: 8 additions & 8 deletions lib/matplotlib/image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -299,9 +299,9 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
space.
"""
if A is None:
raise RuntimeError('You must first set the image'
' array or the image attribute')
if any(s == 0 for s in A.shape):
raise RuntimeError('You must first set the image '
'array or the image attribute')
if A.size == 0:
raise RuntimeError("_make_image must get a non-empty image. "
"Your Artist's draw method must filter before "
"this method is called.")
Expand Down Expand Up @@ -359,7 +359,7 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
created_rgba_mask = False

if A.ndim not in (2, 3):
raise ValueError("Invalid dimensions, got %s" % (A.shape,))
raise ValueError("Invalid dimensions, got {}".format(A.shape))

if A.ndim == 2:
A = self.norm(A)
Expand Down Expand Up @@ -589,11 +589,11 @@ def set_data(self, A):
self._A = cbook.safe_masked_invalid(A, copy=True)

if (self._A.dtype != np.uint8 and
not np.can_cast(self._A.dtype, float)):
raise TypeError("Image data can not convert to float")
not np.can_cast(self._A.dtype, float, "same_kind")):
raise TypeError("Image data cannot be converted to float")

if (self._A.ndim not in (2, 3) or
(self._A.ndim == 3 and self._A.shape[-1] not in (3, 4))):
if not (self._A.ndim == 2
or self._A.ndim == 3 and self._A.shape[-1] in [3, 4]):
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I think that the not should not have been dropped?

I am partial towards leaving in (), even if they are not strictly needed when they help clarity.

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the boolean structure looks correct to me
i think the newline already helps with priority

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Ah, I missed the leading not when I read this before 🐑

raise TypeError("Invalid dimensions for image data")

self._imcache = None
Expand Down
21 changes: 13 additions & 8 deletions lib/matplotlib/tests/test_image.py
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Expand Up @@ -505,9 +505,9 @@ def test_jpeg_alpha():
def test_nonuniformimage_setdata():
ax = plt.gca()
im = NonUniformImage(ax)
x = np.arange(3, dtype=np.float64)
y = np.arange(4, dtype=np.float64)
z = np.arange(12, dtype=np.float64).reshape((4, 3))
x = np.arange(3, dtype=float)
y = np.arange(4, dtype=float)
z = np.arange(12, dtype=float).reshape((4, 3))
im.set_data(x, y, z)
x[0] = y[0] = z[0, 0] = 9.9
assert im._A[0, 0] == im._Ax[0] == im._Ay[0] == 0, 'value changed'
Expand All @@ -516,7 +516,7 @@ def test_nonuniformimage_setdata():
def test_axesimage_setdata():
ax = plt.gca()
im = AxesImage(ax)
z = np.arange(12, dtype=np.float64).reshape((4, 3))
z = np.arange(12, dtype=float).reshape((4, 3))
im.set_data(z)
z[0, 0] = 9.9
assert im._A[0, 0] == 0, 'value changed'
Expand All @@ -525,7 +525,7 @@ def test_axesimage_setdata():
def test_figureimage_setdata():
fig = plt.gcf()
im = FigureImage(fig)
z = np.arange(12, dtype=np.float64).reshape((4, 3))
z = np.arange(12, dtype=float).reshape((4, 3))
im.set_data(z)
z[0, 0] = 9.9
assert im._A[0, 0] == 0, 'value changed'
Expand All @@ -534,9 +534,9 @@ def test_figureimage_setdata():
def test_pcolorimage_setdata():
ax = plt.gca()
im = PcolorImage(ax)
x = np.arange(3, dtype=np.float64)
y = np.arange(4, dtype=np.float64)
z = np.arange(6, dtype=np.float64).reshape((3, 2))
x = np.arange(3, dtype=float)
y = np.arange(4, dtype=float)
z = np.arange(6, dtype=float).reshape((3, 2))
im.set_data(x, y, z)
x[0] = y[0] = z[0, 0] = 9.9
assert im._A[0, 0] == im._Ax[0] == im._Ay[0] == 0, 'value changed'
Expand Down Expand Up @@ -778,3 +778,8 @@ def test_empty_imshow():

with pytest.raises(RuntimeError):
im.make_image(fig._cachedRenderer)


def test_imshow_float128():
fig, ax = plt.subplots()
ax.imshow(np.zeros((3, 3), dtype=np.longdouble))