def test_numpy_share_memory(self):
# TODO: do pytest parametarize once we move to pytest
np_img = np.arange(4 * 5 * 3, dtype=np.uint8).reshape(4, 5, 3)
vital_img = Image(np_img)
assert np.all(np_img == vital_img.asarray()), (
'must be initially the same')
np_img += 1
assert np.all(np_img != vital_img.asarray()), (
'we do not share memory yet')
def test_numpy_share_memory(self):
# TODO: do pytest parametarize once we move to pytest
np_img = np.arange(4 * 5 * 3, dtype=np.uint8).reshape(4, 5, 3)
vital_img = Image(np_img)
assert np.all(np_img == vital_img.asarray()), (
'must be initially the same')
np_img += 1
assert np.all(np_img != vital_img.asarray()), (
'we do not share memory yet')
def _test_numpy(dtype_name, nchannels, order='c'):
if nchannels is None:
shape = (5, 4)
else:
shape = (5, 4, nchannels)
size = np.prod(shape)
dtype = np.dtype(dtype_name)
if dtype_name == 'bool':
np_img = np.zeros(size, dtype=dtype).reshape(shape)
np_img[0::2] = 1
else:
np_img = np.arange(size, dtype=dtype).reshape(shape)
if order.startswith('c'):
np_img = np.ascontiguousarray(np_img)
elif order.startswith('fortran'):
np_img = np.asfortranarray(np_img)
else:
raise KeyError(order)
if order.endswith('-reverse'):
np_img = np_img[::-1, ::-1]
vital_img = Image(np_img)
recast = vital_img.asarray()
if nchannels is None:
# asarray always returns 3 channels
np_img = np_img[..., None]
pixel_type_name = vital_img.pixel_type_name()
if dtype_name == 'float16':
want = 'float16'
if dtype_name == 'float32':
want = 'float'
elif dtype_name == 'float64':
want = 'double'
else:
want = dtype_name
assert pixel_type_name == want, 'want={} but got={}'.format(
want, pixel_type_name)
if not np.all(np_img == recast):
raise AssertionError(
'Failed dtype={}, nchannels={}, order={}'.format(
dtype_name, nchannels, order))
def _test_numpy(dtype_name, nchannels, order='c'):
if nchannels is None:
shape = (5, 4)
else:
shape = (5, 4, nchannels)
size = np.prod(shape)
dtype = np.dtype(dtype_name)
if dtype_name == 'bool':
np_img = np.zeros(size, dtype=dtype).reshape(shape)
np_img[0::2] = 1
else:
np_img = np.arange(size, dtype=dtype).reshape(shape)
if order.startswith('c'):
np_img = np.ascontiguousarray(np_img)
elif order.startswith('fortran'):
np_img = np.asfortranarray(np_img)
else:
raise KeyError(order)
if order.endswith('-reverse'):
np_img = np_img[::-1, ::-1]
vital_img = Image(np_img)
recast = vital_img.asarray()
if nchannels is None:
# asarray always returns 3 channels
np_img = np_img[..., None]
pixel_type_name = vital_img.pixel_type_name()
if dtype_name == 'float16':
want = 'float16'
if dtype_name == 'float32':
want = 'float'
elif dtype_name == 'float64':
want = 'double'
else:
want = dtype_name
assert pixel_type_name == want, 'want={} but got={}'.format(
want, pixel_type_name)
if not np.all(np_img == recast):
raise AssertionError(
'Failed dtype={}, nchannels={}, order={}'.format(
dtype_name, nchannels, order))
def _test_numpy(dtype_name, nchannels, order='c'):
np_img = create_numpy_image(dtype_name, nchannels, order)
vital_img = Image(np_img)
recast = vital_img.asarray()
# asarray always returns 3 channels
np_img = np.atleast_3d(np_img)
pixel_type_name = vital_img.pixel_type_name()
want = map_dtype_name_to_pixel_type(dtype_name)
assert pixel_type_name == want, 'want={} but got={}'.format(
want, pixel_type_name)
if not np.all(np_img == recast):
raise AssertionError(
'Failed dtype={}, nchannels={}, order={}'.format(
dtype_name, nchannels, order))
