def test_reorder_img_mirror():
affine = np.array([[-1.1, -0., 0., 0.], [-0., -1.2, 0., 0.],
[-0., -0., 1.3, 0.], [0., 0., 0., 1.]])
img = Nifti1Image(np.zeros((4, 6, 8)), affine=affine)
reordered = reorder_img(img)
np.testing.assert_allclose(
get_bounds(reordered.shape, reordered.affine),
get_bounds(img.shape, img.affine),
)
def test_reorder_img_mirror():
affine = np.array([
[-1.1, -0., 0., 0.],
[-0., -1.2, 0., 0.],
[-0., -0., 1.3, 0.],
[0., 0., 0., 1.]
])
img = Nifti1Image(np.zeros((4, 6, 8)), affine=affine)
reordered = reorder_img(img)
np.testing.assert_allclose(
get_bounds(reordered.shape, reordered.affine),
get_bounds(img.shape, img.affine),
)
def get_mask_bounds(mask, affine):
""" Return the world-space bounds occupied by a mask given an affine.
Notes
-----
The mask should have only one connect component.
The affine should be diagonal or diagonal-permuted.
"""
(xmin, xmax), (ymin, ymax), (zmin, zmax) = get_bounds(mask.shape, affine)
slices = ndimage.find_objects(mask)
if len(slices) == 0:
warnings.warn("empty mask", stacklevel=2)
else:
x_slice, y_slice, z_slice = slices[0]
x_width, y_width, z_width = mask.shape
xmin, xmax = (xmin + x_slice.start*(xmax - xmin)/x_width,
xmin + x_slice.stop *(xmax - xmin)/x_width)
ymin, ymax = (ymin + y_slice.start*(ymax - ymin)/y_width,
ymin + y_slice.stop *(ymax - ymin)/y_width)
zmin, zmax = (zmin + z_slice.start*(zmax - zmin)/z_width,
zmin + z_slice.stop *(zmax - zmin)/z_width)
return xmin, xmax, ymin, ymax, zmin, zmax
def reorder_affine(affine, shape):
"""
Modified from nilearn.image.resampling.reorder_img and nilearn.image.resampling.resample_img
:param affine:
:param shape:
:return:
"""
Q, R = np.linalg.qr(affine[:3, :3])
_affine = np.diag(np.abs(np.diag(R))[np.abs(Q).argmax(axis=1)])
target_affine = np.eye(4)
target_affine[:3, :3] = _affine
transform_affine = np.linalg.inv(target_affine).dot(affine)
(xmin, xmax), (ymin, ymax), (zmin,
zmax) = get_bounds(shape[:3],
transform_affine)
offset = target_affine[:3, :3].dot([xmin, ymin, zmin])
target_affine[:3, 3] = offset
return target_affine
def _add_arrows(self, t):
"""Adds arrows using matplotlib.quiver"""
# Format 3D data
data_list = []
extent_list = []
for display_ax in self.display.axes.values():
data = []
for k, direction in enumerate(self._ndvar.space._directions):
vol = self._dir_imgs[k][t]
try:
vol_data = np.squeeze(vol.get_data())
data_2d = display_ax.transform_to_2d(vol_data, vol.affine)
data_2d = np.squeeze(data_2d)
except IndexError:
# We are cutting outside the indices of the data
data_2d = None
data.append(data_2d)
data_list.append(np.array(data))
data_bounds = get_bounds(vol_data.shape, vol.affine)
if display_ax.direction == 'y':
(xmin, xmax), (_, _), (zmin, zmax) = data_bounds
elif display_ax.direction in 'xlr':
(_, _), (xmin, xmax), (zmin, zmax) = data_bounds
elif display_ax.direction == 'z':
(xmin, xmax), (zmin, zmax), (_, _) = data_bounds
extent = (xmin, xmax, zmin, zmax)
extent_list.append(extent)
to_iterate_over = zip(self.display.axes.values(), data_list, extent_list)
# Plotting using quiver
if self.display._black_bg:
color = 'w'
else:
color = 'k'
ims = []
for display_ax, data_2d, extent in to_iterate_over:
if data_2d is not None:
# get data mask
if self.threshold is None:
thr = 0
else:
thr = self.threshold ** 2
data = (data_2d ** 2).sum(axis=0)
not_mask = data > thr
# If data_2d is completely masked, then there is nothing to
# plot. Hence, continued to loop over. This problem came up
# with matplotlib 2.1.0. See issue #9280 in matplotlib.
if not_mask.any():
affine_2d = get_transform(extent, data.shape)
indices = np.where(not_mask)
x, y = coord_transform_2d(indices, affine_2d)
if display_ax.direction == 'y':
dir_data = (data_2d[0][indices], data_2d[2][indices])
elif display_ax.direction == 'l':
dir_data = (-data_2d[1][indices], data_2d[2][indices])
elif display_ax.direction in 'xr':
dir_data = (data_2d[1][indices], data_2d[2][indices])
elif display_ax.direction == 'z':
dir_data = (data_2d[0][indices], data_2d[1][indices])
im = display_ax.ax.quiver(x, y, dir_data[0], dir_data[1],
color=color,
scale=self.arrow_scale)
else:
continue
ims.append(im)
self._quivers = ims
return