from __future__ import division, print_function, absolute_import
import sys
import numpy as np
import vtk
from vtk.util import numpy_support
from scipy.ndimage import map_coordinates
from fury.colormap import line_colors
[docs]def numpy_to_vtk_points(points):
"""Convert Numpy points array to a vtk points array.
Parameters
----------
points : ndarray
Returns
-------
vtk_points : vtkPoints()
"""
vtk_points = vtk.vtkPoints()
vtk_points.SetData(numpy_support.numpy_to_vtk(np.asarray(points),
deep=True))
return vtk_points
[docs]def numpy_to_vtk_colors(colors):
"""Convert Numpy color array to a vtk color array.
Parameters
----------
colors: ndarray
Returns
-------
vtk_colors : vtkDataArray
Notes
-----
If colors are not already in UNSIGNED_CHAR you may need to multiply by 255.
Examples
--------
>>> import numpy as np
>>> from fury.utils import numpy_to_vtk_colors
>>> rgb_array = np.random.rand(100, 3)
>>> vtk_colors = numpy_to_vtk_colors(255 * rgb_array)
"""
vtk_colors = numpy_support.numpy_to_vtk(np.asarray(colors), deep=True,
array_type=vtk.VTK_UNSIGNED_CHAR)
return vtk_colors
[docs]def map_coordinates_3d_4d(input_array, indices):
"""Evaluate the input_array data at the given indices
using trilinear interpolation.
Parameters
----------
input_array : ndarray,
3D or 4D array
indices : ndarray
Returns
-------
output : ndarray
1D or 2D array
"""
if input_array.ndim <= 2 or input_array.ndim >= 5:
raise ValueError("Input array can only be 3d or 4d")
if input_array.ndim == 3:
return map_coordinates(input_array, indices.T, order=1)
if input_array.ndim == 4:
values_4d = []
for i in range(input_array.shape[-1]):
values_tmp = map_coordinates(input_array[..., i],
indices.T, order=1)
values_4d.append(values_tmp)
return np.ascontiguousarray(np.array(values_4d).T)
[docs]def lines_to_vtk_polydata(lines, colors=None):
"""Create a vtkPolyData with lines and colors.
Parameters
----------
lines : list
list of N curves represented as 2D ndarrays
colors : array (N, 3), list of arrays, tuple (3,), array (K,), None
If None then a standard orientation colormap is used for every line.
If one tuple of color is used. Then all streamlines will have the same
colour.
If an array (N, 3) is given, where N is equal to the number of lines.
Then every line is coloured with a different RGB color.
If a list of RGB arrays is given then every point of every line takes
a different color.
If an array (K, 3) is given, where K is the number of points of all
lines then every point is colored with a different RGB color.
If an array (K,) is given, where K is the number of points of all
lines then these are considered as the values to be used by the
colormap.
If an array (L,) is given, where L is the number of streamlines then
these are considered as the values to be used by the colormap per
streamline.
If an array (X, Y, Z) or (X, Y, Z, 3) is given then the values for the
colormap are interpolated automatically using trilinear interpolation.
Returns
-------
poly_data : vtkPolyData
is_colormap : bool, true if the input color array was a colormap
"""
# Get the 3d points_array
points_array = np.vstack(lines)
nb_lines = len(lines)
nb_points = len(points_array)
lines_range = range(nb_lines)
# Get lines_array in vtk input format
lines_array = []
# Using np.intp (instead of int64), because of a bug in numpy:
# https://github.com/nipy/dipy/pull/789
# https://github.com/numpy/numpy/issues/4384
points_per_line = np.zeros([nb_lines], np.intp)
current_position = 0
for i in lines_range:
current_len = len(lines[i])
points_per_line[i] = current_len
end_position = current_position + current_len
lines_array += [current_len]
lines_array += range(current_position, end_position)
current_position = end_position
lines_array = np.array(lines_array)
# Set Points to vtk array format
vtk_points = numpy_to_vtk_points(points_array)
# Set Lines to vtk array format
vtk_lines = vtk.vtkCellArray()
vtk_lines.GetData().DeepCopy(numpy_support.numpy_to_vtk(lines_array))
vtk_lines.SetNumberOfCells(nb_lines)
is_colormap = False
# Get colors_array (reformat to have colors for each points)
# - if/else tested and work in normal simple case
if colors is None: # set automatic rgb colors
cols_arr = line_colors(lines)
colors_mapper = np.repeat(lines_range, points_per_line, axis=0)
vtk_colors = numpy_to_vtk_colors(255 * cols_arr[colors_mapper])
else:
cols_arr = np.asarray(colors)
if cols_arr.dtype == np.object: # colors is a list of colors
vtk_colors = numpy_to_vtk_colors(255 * np.vstack(colors))
else:
if len(cols_arr) == nb_points:
if cols_arr.ndim == 1: # values for every point
vtk_colors = numpy_support.numpy_to_vtk(cols_arr,
deep=True)
is_colormap = True
elif cols_arr.ndim == 2: # map color to each point
vtk_colors = numpy_to_vtk_colors(255 * cols_arr)
elif cols_arr.ndim == 1:
if len(cols_arr) == nb_lines: # values for every streamline
cols_arrx = []
for (i, value) in enumerate(colors):
cols_arrx += lines[i].shape[0]*[value]
cols_arrx = np.array(cols_arrx)
vtk_colors = numpy_support.numpy_to_vtk(cols_arrx,
deep=True)
is_colormap = True
else: # the same colors for all points
vtk_colors = numpy_to_vtk_colors(
np.tile(255 * cols_arr, (nb_points, 1)))
elif cols_arr.ndim == 2: # map color to each line
colors_mapper = np.repeat(lines_range, points_per_line, axis=0)
vtk_colors = numpy_to_vtk_colors(255 * cols_arr[colors_mapper])
else: # colormap
# get colors for each vertex
cols_arr = map_coordinates_3d_4d(cols_arr, points_array)
vtk_colors = numpy_support.numpy_to_vtk(cols_arr, deep=True)
is_colormap = True
vtk_colors.SetName("Colors")
# Create the poly_data
poly_data = vtk.vtkPolyData()
poly_data.SetPoints(vtk_points)
poly_data.SetLines(vtk_lines)
poly_data.GetPointData().SetScalars(vtk_colors)
return poly_data, is_colormap
[docs]def get_polydata_lines(line_polydata):
"""Convert vtk polydata to a list of lines ndarrays.
Parameters
----------
line_polydata : vtkPolyData
Returns
-------
lines : list
List of N curves represented as 2D ndarrays
"""
lines_vertices = numpy_support.vtk_to_numpy(line_polydata.GetPoints().
GetData())
lines_idx = numpy_support.vtk_to_numpy(line_polydata.GetLines().GetData())
lines = []
current_idx = 0
while current_idx < len(lines_idx):
line_len = lines_idx[current_idx]
next_idx = current_idx + line_len + 1
line_range = lines_idx[current_idx + 1: next_idx]
lines += [lines_vertices[line_range]]
current_idx = next_idx
return lines
[docs]def get_polydata_triangles(polydata):
"""Get triangles (ndarrays Nx3 int) from a vtk polydata.
Parameters
----------
polydata : vtkPolyData
Returns
-------
output : array (N, 3)
triangles
"""
vtk_polys = numpy_support.vtk_to_numpy(polydata.GetPolys().GetData())
# test if its really triangles
if not (vtk_polys[::4] == 3).all():
raise AssertionError("Shape error: this is not triangles")
return np.vstack([vtk_polys[1::4], vtk_polys[2::4], vtk_polys[3::4]]).T
[docs]def get_polydata_vertices(polydata):
"""Get vertices (ndarrays Nx3 int) from a vtk polydata.
Parameters
----------
polydata : vtkPolyData
Returns
-------
output : array (N, 3)
points, represented as 2D ndarrays
"""
return numpy_support.vtk_to_numpy(polydata.GetPoints().GetData())
[docs]def get_polydata_normals(polydata):
"""Get vertices normal (ndarrays Nx3 int) from a vtk polydata.
Parameters
----------
polydata : vtkPolyData
Returns
-------
output : array (N, 3)
Normals, represented as 2D ndarrays (Nx3). None if there are no normals
in the vtk polydata.
"""
vtk_normals = polydata.GetPointData().GetNormals()
if vtk_normals is None:
return None
else:
return numpy_support.vtk_to_numpy(vtk_normals)
[docs]def get_polydata_colors(polydata):
"""Get points color (ndarrays Nx3 int) from a vtk polydata.
Parameters
----------
polydata : vtkPolyData
Returns
-------
output : array (N, 3)
Colors. None if no normals in the vtk polydata.
"""
vtk_colors = polydata.GetPointData().GetScalars()
if vtk_colors is None:
return None
else:
return numpy_support.vtk_to_numpy(vtk_colors)
[docs]def set_polydata_triangles(polydata, triangles):
"""Set polydata triangles with a numpy array (ndarrays Nx3 int).
Parameters
----------
polydata : vtkPolyData
triangles : array (N, 3)
triangles, represented as 2D ndarrays (Nx3)
"""
vtk_triangles = np.hstack(np.c_[np.ones(len(triangles)).astype(np.int) * 3,
triangles])
vtk_triangles = numpy_support.numpy_to_vtkIdTypeArray(vtk_triangles,
deep=True)
vtk_cells = vtk.vtkCellArray()
vtk_cells.SetCells(len(triangles), vtk_triangles)
polydata.SetPolys(vtk_cells)
return polydata
[docs]def set_polydata_vertices(polydata, vertices):
"""Set polydata vertices with a numpy array (ndarrays Nx3 int).
Parameters
----------
polydata : vtkPolyData
vertices : vertices, represented as 2D ndarrays (Nx3)
"""
vtk_points = vtk.vtkPoints()
vtk_points.SetData(numpy_support.numpy_to_vtk(vertices, deep=True))
polydata.SetPoints(vtk_points)
return polydata
[docs]def set_polydata_normals(polydata, normals):
"""Set polydata normals with a numpy array (ndarrays Nx3 int).
Parameters
----------
polydata : vtkPolyData
normals : normals, represented as 2D ndarrays (Nx3) (one per vertex)
"""
vtk_normals = numpy_support.numpy_to_vtk(normals, deep=True)
polydata.GetPointData().SetNormals(vtk_normals)
return polydata
[docs]def set_polydata_colors(polydata, colors):
"""Set polydata colors with a numpy array (ndarrays Nx3 int).
Parameters
----------
polydata : vtkPolyData
colors : colors, represented as 2D ndarrays (Nx3)
colors are uint8 [0,255] RGB for each points
"""
vtk_colors = numpy_support.numpy_to_vtk(colors, deep=True,
array_type=vtk.VTK_UNSIGNED_CHAR)
vtk_colors.SetNumberOfComponents(3)
vtk_colors.SetName("RGB")
polydata.GetPointData().SetScalars(vtk_colors)
return polydata
[docs]def update_polydata_normals(polydata):
"""Generate and update polydata normals.
Parameters
----------
polydata : vtkPolyData
"""
normals_gen = set_input(vtk.vtkPolyDataNormals(), polydata)
normals_gen.ComputePointNormalsOn()
normals_gen.ComputeCellNormalsOn()
normals_gen.SplittingOff()
# normals_gen.FlipNormalsOn()
# normals_gen.ConsistencyOn()
# normals_gen.AutoOrientNormalsOn()
normals_gen.Update()
vtk_normals = normals_gen.GetOutput().GetPointData().GetNormals()
polydata.GetPointData().SetNormals(vtk_normals)
[docs]def get_polymapper_from_polydata(polydata):
"""Get vtkPolyDataMapper from a vtkPolyData.
Parameters
----------
polydata : vtkPolyData
Returns
-------
poly_mapper : vtkPolyDataMapper
"""
poly_mapper = set_input(vtk.vtkPolyDataMapper(), polydata)
poly_mapper.ScalarVisibilityOn()
poly_mapper.InterpolateScalarsBeforeMappingOn()
poly_mapper.Update()
poly_mapper.StaticOn()
return poly_mapper
[docs]def get_actor_from_polymapper(poly_mapper):
"""Get vtkActor from a vtkPolyDataMapper.
Parameters
----------
poly_mapper : vtkPolyDataMapper
Returns
-------
actor : vtkActor
"""
actor = vtk.vtkActor()
actor.SetMapper(poly_mapper)
actor.GetProperty().BackfaceCullingOn()
actor.GetProperty().SetInterpolationToPhong()
return actor
[docs]def get_actor_from_polydata(polydata):
"""Get vtkActor from a vtkPolyData.
Parameters
----------
polydata : vtkPolyData
Returns
-------
actor : vtkActor
"""
poly_mapper = get_polymapper_from_polydata(polydata)
return get_actor_from_polymapper(poly_mapper)
[docs]def apply_affine(aff, pts):
"""Apply affine matrix `aff` to points `pts`.
Returns result of application of `aff` to the *right* of `pts`. The
coordinate dimension of `pts` should be the last.
For the 3D case, `aff` will be shape (4,4) and `pts` will have final axis
length 3 - maybe it will just be N by 3. The return value is the
transformed points, in this case::
res = np.dot(aff[:3,:3], pts.T) + aff[:3,3:4]
transformed_pts = res.T
This routine is more general than 3D, in that `aff` can have any shape
(N,N), and `pts` can have any shape, as long as the last dimension is for
the coordinates, and is therefore length N-1.
Parameters
----------
aff : (N, N) array-like
Homogenous affine, for 3D points, will be 4 by 4. Contrary to first
appearance, the affine will be applied on the left of `pts`.
pts : (..., N-1) array-like
Points, where the last dimension contains the coordinates of each
point. For 3D, the last dimension will be length 3.
Returns
-------
transformed_pts : (..., N-1) array
transformed points
Notes
-----
Copied from nibabel to remove dependency.
Examples
--------
>>> aff = np.array([[0,2,0,10],[3,0,0,11],[0,0,4,12],[0,0,0,1]])
>>> pts = np.array([[1,2,3],[2,3,4],[4,5,6],[6,7,8]])
>>> apply_affine(aff, pts) #doctest: +ELLIPSIS
array([[14, 14, 24],
[16, 17, 28],
[20, 23, 36],
[24, 29, 44]]...)
Just to show that in the simple 3D case, it is equivalent to:
>>> (np.dot(aff[:3,:3], pts.T) + aff[:3,3:4]).T #doctest: +ELLIPSIS
array([[14, 14, 24],
[16, 17, 28],
[20, 23, 36],
[24, 29, 44]]...)
But `pts` can be a more complicated shape:
>>> pts = pts.reshape((2,2,3))
>>> apply_affine(aff, pts) #doctest: +ELLIPSIS
array([[[14, 14, 24],
[16, 17, 28]],
<BLANKLINE>
[[20, 23, 36],
[24, 29, 44]]]...)
"""
aff = np.asarray(aff)
pts = np.asarray(pts)
shape = pts.shape
pts = pts.reshape((-1, shape[-1]))
# rzs == rotations, zooms, shears
rzs = aff[:-1, :-1]
trans = aff[:-1, -1]
res = np.dot(pts, rzs.T) + trans[None, :]
return res.reshape(shape)
[docs]def asbytes(s):
if sys.version_info[0] >= 3:
if isinstance(s, bytes):
return s
return s.encode('latin1')
else:
return str(s)
[docs]def vtk_matrix_to_numpy(matrix):
"""Convert VTK matrix to numpy array."""
if matrix is None:
return None
size = (4, 4)
if isinstance(matrix, vtk.vtkMatrix3x3):
size = (3, 3)
mat = np.zeros(size)
for i in range(mat.shape[0]):
for j in range(mat.shape[1]):
mat[i, j] = matrix.GetElement(i, j)
return mat
[docs]def numpy_to_vtk_matrix(array):
"""Convert a numpy array to a VTK matrix."""
if array is None:
return None
if array.shape == (4, 4):
matrix = vtk.vtkMatrix4x4()
elif array.shape == (3, 3):
matrix = vtk.vtkMatrix3x3()
else:
raise ValueError("Invalid matrix shape: {0}".format(array.shape))
for i in range(array.shape[0]):
for j in range(array.shape[1]):
matrix.SetElement(i, j, array[i, j])
return matrix
[docs]def get_bounding_box_sizes(actor):
"""Get the bounding box sizes of an actor."""
X1, X2, Y1, Y2, Z1, Z2 = actor.GetBounds()
return (X2-X1, Y2-Y1, Z2-Z1)
[docs]def get_grid_cells_position(shapes, aspect_ratio=16/9., dim=None):
"""Construct a XY-grid based on the cells content shape.
This function generates the coordinates of every grid cell. The width and
height of every cell correspond to the largest width and the largest height
respectively. The grid dimensions will automatically be adjusted to respect
the given aspect ratio unless they are explicitly specified.
The grid follows a row-major order with the top left corner being at
coordinates (0,0,0) and the bottom right corner being at coordinates
(nb_cols*cell_width, -nb_rows*cell_height, 0). Note that the X increases
while the Y decreases.
Parameters
----------
shapes : list of tuple of int
The shape (width, height) of every cell content.
aspect_ratio : float (optional)
Aspect ratio of the grid (width/height). Default: 16:9.
dim : tuple of int (optional)
Dimension (nb_rows, nb_cols) of the grid, if provided.
Returns
-------
ndarray
3D coordinates of every grid cell.
"""
cell_shape = np.r_[np.max(shapes, axis=0), 0]
cell_aspect_ratio = cell_shape[0] / cell_shape[1]
count = len(shapes)
if dim is None:
# Compute the number of rows and columns.
n_cols = np.ceil(np.sqrt(count*aspect_ratio / cell_aspect_ratio))
n_rows = np.ceil(count / n_cols)
if n_cols * n_rows <= count:
raise ValueError("Too small")
else:
n_rows, n_cols = dim
if n_cols * n_rows < count:
msg = "Size is too small, it cannot contain at least {} elements."
raise ValueError(msg.format(count))
# Use indexing="xy" so the cells are in row-major (C-order). Also,
# the Y coordinates are negative so the cells are order from top to bottom.
X, Y, Z = np.meshgrid(np.arange(n_cols), -np.arange(n_rows),
[0], indexing="xy")
return cell_shape * np.array([X.flatten(), Y.flatten(), Z.flatten()]).T
[docs]def shallow_copy(vtk_object):
"""Create a shallow copy of a given `vtkObject` object."""
copy = vtk_object.NewInstance()
copy.ShallowCopy(vtk_object)
return copy
[docs]def rotate(actor, rotation=(90, 1, 0, 0)):
"""Rotate actor around axis by angle.
Parameters
----------
actor : vtkActor or other prop
rotation : tuple
Rotate with angle w around axis x, y, z. Needs to be provided
in the form (w, x, y, z).
"""
prop3D = actor
center = np.array(prop3D.GetCenter())
oldMatrix = prop3D.GetMatrix()
orig = np.array(prop3D.GetOrigin())
newTransform = vtk.vtkTransform()
newTransform.PostMultiply()
if prop3D.GetUserMatrix() is not None:
newTransform.SetMatrix(prop3D.GetUserMatrix())
else:
newTransform.SetMatrix(oldMatrix)
newTransform.Translate(*(-center))
newTransform.RotateWXYZ(*rotation)
newTransform.Translate(*center)
# now try to get the composit of translate, rotate, and scale
newTransform.Translate(*(-orig))
newTransform.PreMultiply()
newTransform.Translate(*orig)
if prop3D.GetUserMatrix() is not None:
newTransform.GetMatrix(prop3D.GetUserMatrix())
else:
prop3D.SetPosition(newTransform.GetPosition())
prop3D.SetScale(newTransform.GetScale())
prop3D.SetOrientation(newTransform.GetOrientation())