def display_extent(self, x1, x2, y1, y2, z1, z2):
tmp_mask = np.zeros(grid_shape, dtype=np.bool)
tmp_mask[x1:x2 + 1, y1:y2 + 1, z1:z2 + 1] = True
tmp_mask = np.bitwise_and(tmp_mask, mask)
ijk = np.ascontiguousarray(np.array(np.nonzero(tmp_mask)).T)
if len(ijk) == 0:
self.SetMapper(None)
return
if affine is not None:
ijk_trans = np.ascontiguousarray(apply_affine(affine, ijk))
list_dirs = []
for index, center in enumerate(ijk):
# center = tuple(center)
if affine is None:
xyz = center[:, None]
else:
xyz = ijk_trans[index][:, None]
xyz = xyz.T
for i in range(peaks_dirs[tuple(center)].shape[-2]):
if peaks_values is not None:
pv = peaks_values[tuple(center)][i]
else:
pv = 1.
symm = np.vstack((-peaks_dirs[tuple(center)][i] * pv + xyz,
peaks_dirs[tuple(center)][i] * pv + xyz))
list_dirs.append(symm)
self.mapper = line(list_dirs, colors=colors,
opacity=opacity, linewidth=linewidth,
lod=lod, lod_points=lod_points,
lod_points_size=lod_points_size).GetMapper()
self.SetMapper(self.mapper)
def __init__(self,
odfs,
vertices,
faces,
indices,
scale,
norm,
radial_scale,
shape,
global_cm,
colormap,
opacity,
affine=None,
B=None):
self.vertices = vertices
self.faces = faces
self.odfs = odfs
self.indices = indices
self.B = B
self.radial_scale = radial_scale
self.colormap = colormap
self.grid_shape = shape
self.global_cm = global_cm
# declare a mask to be instantiated in slice_along_axis
self.mask = None
# If a B matrix is given, odfs are expected to
# be in SH basis coefficients.
if self.B is not None:
# In that case, we need to save our normalisation and scale
# to apply them after conversion from SH to SF.
self.norm = norm
self.scale = scale
else:
# If our input is in SF coefficients, we can normalise and
# scale it only once, here.
if norm:
self.odfs /= np.abs(self.odfs).max(axis=-1, keepdims=True)
self.odfs *= scale
# Compute world coordinates of an affine is supplied
self.affine = affine
if self.affine is not None:
self.w_verts = self.vertices.dot(affine[:3, :3])
self.w_pos = apply_affine(affine, np.asarray(self.indices).T)
# Initialize mapper and slice to the
# middle of the volume along Z axis
self.mapper = PolyDataMapper()
self.SetMapper(self.mapper)
self.slice_along_axis(self.grid_shape[-1] // 2)
self.set_opacity(opacity)
def __init__(self,
directions,
indices,
values=None,
affine=None,
colors=None,
lookup_colormap=None,
linewidth=1):
if affine is not None:
w_pos = apply_affine(affine, np.asarray(indices).T)
valid_dirs = directions[indices]
num_dirs = len(np.nonzero(np.abs(valid_dirs).max(axis=-1) > 0)[0])
pnts_per_line = 2
points_array = np.empty((num_dirs * pnts_per_line, 3))
centers_array = np.empty_like(points_array, dtype=int)
diffs_array = np.empty_like(points_array)
line_count = 0
for idx, center in enumerate(zip(indices[0], indices[1], indices[2])):
if affine is None:
xyz = np.asarray(center)
else:
xyz = w_pos[idx, :]
valid_peaks = np.nonzero(
np.abs(valid_dirs[idx, :, :]).max(axis=-1) > 0.)[0]
for direction in valid_peaks:
if values is not None:
pv = values[center][direction]
else:
pv = 1.
point_i = directions[center][direction] * pv + xyz
point_e = -directions[center][direction] * pv + xyz
diff = point_e - point_i
points_array[line_count * pnts_per_line, :] = point_e
points_array[line_count * pnts_per_line + 1, :] = point_i
centers_array[line_count * pnts_per_line, :] = center
centers_array[line_count * pnts_per_line + 1, :] = center
diffs_array[line_count * pnts_per_line, :] = diff
diffs_array[line_count * pnts_per_line + 1, :] = diff
line_count += 1
vtk_points = numpy_to_vtk_points(points_array)
vtk_cells = _points_to_vtk_cells(points_array)
colors_tuple = _peaks_colors_from_points(points_array, colors=colors)
vtk_colors, colors_are_scalars, self.__global_opacity = colors_tuple
poly_data = vtk.vtkPolyData()
poly_data.SetPoints(vtk_points)
poly_data.SetLines(vtk_cells)
poly_data.GetPointData().SetScalars(vtk_colors)
self.__mapper = vtk.vtkPolyDataMapper()
self.__mapper.SetInputData(poly_data)
self.__mapper.ScalarVisibilityOn()
self.__mapper.SetScalarModeToUsePointFieldData()
self.__mapper.SelectColorArray('colors')
self.__mapper.Update()
self.SetMapper(self.__mapper)
attribute_to_actor(self, centers_array, 'center')
attribute_to_actor(self, diffs_array, 'diff')
vs_dec_code = load('peak_dec.vert')
vs_impl_code = load('peak_impl.vert')
fs_dec_code = load('peak_dec.frag')
fs_impl_code = load('peak_impl.frag')
shader_to_actor(self,
'vertex',
decl_code=vs_dec_code,
impl_code=vs_impl_code)
shader_to_actor(self, 'fragment', decl_code=fs_dec_code)
shader_to_actor(self,
'fragment',
impl_code=fs_impl_code,
block='light')
# Color scale with a lookup table
if colors_are_scalars:
if lookup_colormap is None:
lookup_colormap = colormap_lookup_table()
self.__mapper.SetLookupTable(lookup_colormap)
self.__mapper.UseLookupTableScalarRangeOn()
self.__mapper.Update()
self.__lw = linewidth
self.GetProperty().SetLineWidth(self.__lw)
if self.__global_opacity >= 0:
self.GetProperty().SetOpacity(self.__global_opacity)
self.__min_centers = np.min(indices, axis=1)
self.__max_centers = np.max(indices, axis=1)
self.__is_range = True
self.__low_ranges = self.__min_centers
self.__high_ranges = self.__max_centers
self.__cross_section = self.__high_ranges // 2
self.__mapper.AddObserver(vtk.vtkCommand.UpdateShaderEvent,
self.__display_peaks_vtk_callback)
def _tensor_slicer_mapper(evals,
evecs,
affine=None,
mask=None,
sphere=None,
scale=2.2,
norm=True,
opacity=1.,
scalar_colors=None):
"""Helper function for slicing tensor fields
Parameters
----------
evals : (3,) or (X, 3) or (X, Y, 3) or (X, Y, Z, 3) ndarray
eigenvalues
evecs : (3, 3) or (X, 3, 3) or (X, Y, 3, 3) or (X, Y, Z, 3, 3) ndarray
eigenvectors
affine : array
4x4 transformation array from native coordinates to world coordinates
mask : ndarray
3D mask
sphere : Sphere
a sphere
scale : float
Distance between spheres.
norm : bool
Normalize `sphere_values`.
opacity : float
Takes values from 0 (fully transparent) to 1 (opaque)
scalar_colors : (3,) or (X, 3) or (X, Y, 3) or (X, Y, Z, 3) ndarray
RGB colors used to show the tensors
Default None, color the ellipsoids using ``color_fa``
Returns
---------
mapper : vtkPolyDataMapper
Ellipsoid mapper
"""
if mask is None:
mask = np.ones(evals.shape[:3])
ijk = np.ascontiguousarray(np.array(np.nonzero(mask)).T)
if len(ijk) == 0:
return None
if affine is not None:
ijk = np.ascontiguousarray(apply_affine(affine, ijk))
faces = np.asarray(sphere.faces, dtype=int)
vertices = sphere.vertices
if scalar_colors is None:
from dipy.reconst.dti import color_fa, fractional_anisotropy
cfa = color_fa(fractional_anisotropy(evals), evecs)
else:
cfa = _makeNd(scalar_colors, 4)
cols = np.zeros((ijk.shape[0], ) + sphere.vertices.shape, dtype='f4')
all_xyz = []
all_faces = []
for (k, center) in enumerate(ijk):
ea = evals[tuple(center.astype(np.int))]
if norm:
ea /= ea.max()
ea = np.diag(ea.copy())
ev = evecs[tuple(center.astype(np.int))].copy()
xyz = np.dot(ev, np.dot(ea, vertices.T))
xyz = xyz.T
all_xyz.append(scale * xyz + center)
all_faces.append(faces + k * xyz.shape[0])
cols[k, ...] = np.interp(cfa[tuple(center.astype(np.int))], [0, 1],
[0, 255]).astype('ubyte')
all_xyz = np.ascontiguousarray(np.concatenate(all_xyz))
all_xyz_vtk = numpy_support.numpy_to_vtk(all_xyz, deep=True)
all_faces = np.concatenate(all_faces)
all_faces = np.hstack((3 * np.ones((len(all_faces), 1)), all_faces))
ncells = len(all_faces)
all_faces = np.ascontiguousarray(all_faces.ravel(), dtype='i8')
all_faces_vtk = numpy_support.numpy_to_vtkIdTypeArray(all_faces, deep=True)
points = vtk.vtkPoints()
points.SetData(all_xyz_vtk)
cells = vtk.vtkCellArray()
cells.SetCells(ncells, all_faces_vtk)
cols = np.ascontiguousarray(np.reshape(
cols, (cols.shape[0] * cols.shape[1], cols.shape[2])),
dtype='f4')
vtk_colors = numpy_support.numpy_to_vtk(cols,
deep=True,
array_type=vtk.VTK_UNSIGNED_CHAR)
vtk_colors.SetName("Colors")
polydata = vtk.vtkPolyData()
polydata.SetPoints(points)
polydata.SetPolys(cells)
polydata.GetPointData().SetScalars(vtk_colors)
mapper = vtk.vtkPolyDataMapper()
mapper.SetInputData(polydata)
return mapper
def _odf_slicer_mapper(odfs,
affine=None,
mask=None,
sphere=None,
scale=2.2,
norm=True,
radial_scale=True,
opacity=1.,
colormap='plasma',
global_cm=False):
""" Helper function for slicing spherical fields
Parameters
----------
odfs : ndarray
4D array of spherical functions
affine : array
4x4 transformation array from native coordinates to world coordinates
mask : ndarray
3D mask
sphere : Sphere
a sphere
scale : float
Distance between spheres.
norm : bool
Normalize `sphere_values`.
radial_scale : bool
Scale sphere points according to odf values.
opacity : float
Takes values from 0 (fully transparent) to 1 (opaque)
colormap : None or str
If None then white color is used. Otherwise the name of colormap is
given. Matplotlib colormaps are supported (e.g., 'inferno').
global_cm : bool
If True the colormap will be applied in all ODFs. If False
it will be applied individually at each voxel (default False).
Returns
---------
mapper : vtkPolyDataMapper
Spheres mapper
"""
if mask is None:
mask = np.ones(odfs.shape[:3])
ijk = np.ascontiguousarray(np.array(np.nonzero(mask)).T)
if len(ijk) == 0:
return None
if affine is not None:
ijk = np.ascontiguousarray(apply_affine(affine, ijk))
faces = np.asarray(sphere.faces, dtype=int)
vertices = sphere.vertices
all_xyz = []
all_faces = []
all_ms = []
for (k, center) in enumerate(ijk):
m = odfs[tuple(center.astype(np.int))].copy()
if norm:
m /= np.abs(m).max()
if radial_scale:
xyz = vertices * m[:, None]
else:
xyz = vertices.copy()
all_xyz.append(scale * xyz + center)
all_faces.append(faces + k * xyz.shape[0])
all_ms.append(m)
all_xyz = np.ascontiguousarray(np.concatenate(all_xyz))
all_xyz_vtk = numpy_support.numpy_to_vtk(all_xyz, deep=True)
all_faces = np.concatenate(all_faces)
all_faces = np.hstack((3 * np.ones((len(all_faces), 1)), all_faces))
ncells = len(all_faces)
all_faces = np.ascontiguousarray(all_faces.ravel(), dtype='i8')
all_faces_vtk = numpy_support.numpy_to_vtkIdTypeArray(all_faces, deep=True)
if global_cm:
all_ms = np.ascontiguousarray(np.concatenate(all_ms), dtype='f4')
points = vtk.vtkPoints()
points.SetData(all_xyz_vtk)
cells = vtk.vtkCellArray()
cells.SetCells(ncells, all_faces_vtk)
if colormap is not None:
if global_cm:
cols = create_colormap(all_ms.ravel(), colormap)
else:
cols = np.zeros((ijk.shape[0], ) + sphere.vertices.shape,
dtype='f4')
for k in range(ijk.shape[0]):
tmp = create_colormap(all_ms[k].ravel(), colormap)
cols[k] = tmp.copy()
cols = np.ascontiguousarray(np.reshape(
cols, (cols.shape[0] * cols.shape[1], cols.shape[2])),
dtype='f4')
vtk_colors = numpy_support.numpy_to_vtk(
np.asarray(255 * cols),
deep=True,
array_type=vtk.VTK_UNSIGNED_CHAR)
vtk_colors.SetName("Colors")
polydata = vtk.vtkPolyData()
polydata.SetPoints(points)
polydata.SetPolys(cells)
if colormap is not None:
polydata.GetPointData().SetScalars(vtk_colors)
mapper = vtk.vtkPolyDataMapper()
mapper.SetInputData(polydata)
return mapper
