import numpy as np
import vtk
from vtk.util import numpy_support
from scipy.ndimage import map_coordinates
from fury.colormap import line_colors
def set_input(vtk_object, inp):
"""Set Generic input function which takes into account VTK 5 or 6.
Parameters
----------
vtk_object: vtk object
inp: vtkPolyData or vtkImageData or vtkAlgorithmOutput
Returns
-------
vtk_object
Notes
-------
This can be used in the following way::
from fury.utils import set_input
poly_mapper = set_input(vtk.vtkPolyDataMapper(), poly_data)
"""
if isinstance(inp, (vtk.vtkPolyData, vtk.vtkImageData)):
vtk_object.SetInputData(inp)
elif isinstance(inp, vtk.vtkAlgorithmOutput):
vtk_object.SetInputConnection(inp)
vtk_object.Update()
return vtk_object
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
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
def numpy_to_vtk_cells(data, is_coords=True):
"""Convert numpy array to a vtk cell array.
Parameters
----------
data : ndarray
points coordinate or connectivity array (e.g triangles).
is_coords : ndarray
Select the type of array. default: True.
Returns
-------
vtk_cell : vtkCellArray
connectivity + offset information
"""
data = np.array(data, dtype=object)
nb_cells = len(data)
# Get lines_array in vtk input format
connectivity = data.flatten() if not is_coords else []
offset = [0, ]
current_position = 0
cell_array = vtk.vtkCellArray()
if vtk.vtkVersion.GetVTKMajorVersion() >= 9:
for i in range(nb_cells):
current_len = len(data[i])
offset.append(offset[-1] + current_len)
if is_coords:
end_position = current_position + current_len
connectivity += list(range(current_position, end_position))
current_position = end_position
connectivity = np.array(connectivity, np.intp)
offset = np.array(offset, dtype=connectivity.dtype)
vtk_array_type = numpy_support.get_vtk_array_type(connectivity.dtype)
cell_array.SetData(
numpy_support.numpy_to_vtk(offset, deep=True,
array_type=vtk_array_type),
numpy_support.numpy_to_vtk(connectivity, deep=True,
array_type=vtk_array_type))
else:
for i in range(nb_cells):
current_len = len(data[i])
end_position = current_position + current_len
connectivity += [current_len]
connectivity += list(range(current_position, end_position))
current_position = end_position
connectivity = np.array(connectivity)
cell_array.GetData().DeepCopy(numpy_support.numpy_to_vtk(connectivity))
cell_array.SetNumberOfCells(nb_cells)
return cell_array
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)
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,)
If None or False, 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
color_is_scalar : bool, true if the color array is a single scalar
Scalar array could be used with a colormap lut
None if no color was used
"""
# Get the 3d points_array
points_array = np.vstack(lines)
# Set Points to vtk array format
vtk_points = numpy_to_vtk_points(points_array)
# Set Lines to vtk array format
vtk_cell_array = numpy_to_vtk_cells(lines)
# Create the poly_data
poly_data = vtk.vtkPolyData()
poly_data.SetPoints(vtk_points)
poly_data.SetLines(vtk_cell_array)
# Get colors_array (reformat to have colors for each points)
# - if/else tested and work in normal simple case
nb_points = len(points_array)
nb_lines = len(lines)
lines_range = range(nb_lines)
points_per_line = [len(lines[i]) for i in lines_range]
points_per_line = np.array(points_per_line, np.intp)
color_is_scalar = False
if colors is None or colors is False:
# 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 == 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)
color_is_scalar = 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)
color_is_scalar = 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)
color_is_scalar = True
vtk_colors.SetName("colors")
poly_data.GetPointData().SetScalars(vtk_colors)
return poly_data, color_is_scalar
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
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
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())
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
return numpy_support.vtk_to_numpy(vtk_normals)
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
return numpy_support.vtk_to_numpy(vtk_colors)
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_cells = vtk.vtkCellArray()
if vtk.vtkVersion.GetVTKMajorVersion() >= 9:
vtk_cells = numpy_to_vtk_cells(triangles, is_coords=False)
else:
isize = vtk.vtkIdTypeArray().GetDataTypeSize()
req_dtype = np.int32 if isize == 4 else np.int64
all_triangles =\
np.insert(triangles, 0, 3, axis=1).astype(req_dtype).flatten()
vtk_triangles = numpy_support.numpy_to_vtkIdTypeArray(all_triangles,
deep=True)
vtk_cells.SetCells(len(triangles), vtk_triangles)
polydata.SetPolys(vtk_cells)
return polydata
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
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
def set_polydata_colors(polydata, colors, array_name="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)
nb_components = colors.shape[1]
vtk_colors.SetNumberOfComponents(nb_components)
vtk_colors.SetName(array_name)
polydata.GetPointData().SetScalars(vtk_colors)
return polydata
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)
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
def get_actor_from_polymapper(poly_mapper):
"""Get actor from a vtkPolyDataMapper.
Parameters
----------
poly_mapper : vtkPolyDataMapper
Returns
-------
actor : actor
"""
actor = vtk.vtkActor()
actor.SetMapper(poly_mapper)
actor.GetProperty().BackfaceCullingOn()
actor.GetProperty().SetInterpolationToPhong()
return actor
def get_actor_from_polydata(polydata):
"""Get actor from a vtkPolyData.
Parameters
----------
polydata : vtkPolyData
Returns
-------
actor : actor
"""
poly_mapper = get_polymapper_from_polydata(polydata)
return get_actor_from_polymapper(poly_mapper)
[docs]def get_actor_from_primitive(vertices, triangles, colors=None,
normals=None, backface_culling=True):
"""Get actor from a vtkPolyData.
Parameters
----------
vertices : (Mx3) ndarray
XYZ coordinates of the object
triangles: (Nx3) ndarray
Indices into vertices; forms triangular faces.
colors: (Nx3) or (Nx4) ndarray
RGB or RGBA (for opacity) R, G, B and A should be at the range [0, 1]
N is equal to the number of vertices.
normals: (Nx3) ndarray
normals, represented as 2D ndarrays (Nx3) (one per vertex)
backface_culling: bool
culling of polygons based on orientation of normal with respect to
camera. If backface culling is True, polygons facing away from camera
are not drawn. Default: True
Returns
-------
actor : actor
"""
# Create a Polydata
pd = vtk.vtkPolyData()
set_polydata_vertices(pd, vertices)
set_polydata_triangles(pd, triangles)
if isinstance(colors, np.ndarray):
if len(colors) != len(vertices):
msg = "Vertices and Colors should have the same size."
msg += " Please, update your color array or use the function "
msg += "``fury.primitive.repeat_primitives`` to normalize your "
msg += "color array before calling this function. e.g."
raise ValueError(msg)
set_polydata_colors(pd, colors, array_name="colors")
if isinstance(normals, np.ndarray):
set_polydata_normals(pd, normals)
current_actor = get_actor_from_polydata(pd)
current_actor.GetProperty().SetBackfaceCulling(backface_culling)
return current_actor
def repeat_sources(centers, colors, active_scalars=1., directions=None,
source=None, vertices=None, faces=None):
"""Transform a vtksource to glyph.
"""
if source is None and faces is None:
raise IOError("A source or faces should be defined")
if np.array(colors).ndim == 1:
colors = np.tile(colors, (len(centers), 1))
pts = numpy_to_vtk_points(np.ascontiguousarray(centers))
cols = numpy_to_vtk_colors(255 * np.ascontiguousarray(colors))
cols.SetName('colors')
if isinstance(active_scalars, (float, int)):
active_scalars = np.tile(active_scalars, (len(centers), 1))
if isinstance(active_scalars, np.ndarray):
ascalars = numpy_support.numpy_to_vtk(np.asarray(active_scalars),
deep=True,
array_type=vtk.VTK_DOUBLE)
ascalars.SetName('active_scalars')
if directions is not None:
directions_fa = numpy_support.numpy_to_vtk(np.asarray(directions),
deep=True,
array_type=vtk.VTK_DOUBLE)
directions_fa.SetName('directions')
polydata_centers = vtk.vtkPolyData()
polydata_geom = vtk.vtkPolyData()
if faces is not None:
set_polydata_vertices(polydata_geom, vertices.astype(np.int8))
set_polydata_triangles(polydata_geom, faces)
polydata_centers.SetPoints(pts)
polydata_centers.GetPointData().AddArray(cols)
if directions is not None:
polydata_centers.GetPointData().AddArray(directions_fa)
polydata_centers.GetPointData().SetActiveVectors('directions')
if isinstance(active_scalars, np.ndarray):
polydata_centers.GetPointData().AddArray(ascalars)
polydata_centers.GetPointData().SetActiveScalars('active_scalars')
glyph = vtk.vtkGlyph3D()
if faces is None:
glyph.SetSourceConnection(source.GetOutputPort())
else:
glyph.SetSourceData(polydata_geom)
glyph.SetInputData(polydata_centers)
glyph.SetOrient(True)
glyph.SetScaleModeToScaleByScalar()
glyph.SetVectorModeToUseVector()
glyph.Update()
mapper = vtk.vtkPolyDataMapper()
mapper.SetInputData(glyph.GetOutput())
mapper.SetScalarModeToUsePointFieldData()
mapper.SelectColorArray('colors')
actor = vtk.vtkActor()
actor.SetMapper(mapper)
return actor
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)
def asbytes(s):
if isinstance(s, bytes):
return s
return s.encode('latin1')
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
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
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)
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)
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
def shallow_copy(vtk_object):
"""Create a shallow copy of a given `vtkObject` object."""
copy = vtk_object.NewInstance()
copy.ShallowCopy(vtk_object)
return copy
def rotate(actor, rotation=(90, 1, 0, 0)):
"""Rotate actor around axis by angle.
Parameters
----------
actor : actor 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())
def rgb_to_vtk(data):
"""RGB or RGBA images to VTK arrays.
Parameters
----------
data : ndarray
Shape can be (X, Y, 3) or (X, Y, 4)
Returns
-------
vtkImageData
"""
grid = vtk.vtkImageData()
grid.SetDimensions(data.shape[1], data.shape[0], 1)
nd = data.shape[-1]
vtkarr = numpy_support.numpy_to_vtk(
np.flip(data.swapaxes(0, 1), axis=1).reshape((-1, nd), order='F'))
vtkarr.SetName('Image')
grid.GetPointData().AddArray(vtkarr)
grid.GetPointData().SetActiveScalars('Image')
grid.GetPointData().Update()
return grid
def normalize_v3(arr):
"""Normalize a numpy array of 3 component vectors shape=(N, 3).
Parameters
-----------
array : ndarray
Shape (N, 3)
Returns
-------
norm_array
"""
lens = np.sqrt(arr[:, 0] ** 2 + arr[:, 1] ** 2 + arr[:, 2] ** 2)
arr[:, 0] /= lens
arr[:, 1] /= lens
arr[:, 2] /= lens
return arr
def normals_from_v_f(vertices, faces):
"""Calculate normals from vertices and faces.
Parameters
----------
verices : ndarray
faces : ndarray
Returns
-------
normals : ndarray
Shape same as vertices
"""
norm = np.zeros(vertices.shape, dtype=vertices.dtype)
tris = vertices[faces]
n = np.cross(tris[::, 1] - tris[::, 0], tris[::, 2] - tris[::, 0])
normalize_v3(n)
norm[faces[:, 0]] += n
norm[faces[:, 1]] += n
norm[faces[:, 2]] += n
normalize_v3(norm)
return norm
def triangle_order(vertices, faces):
"""Determine the winding order of a given set of vertices and a triangle.
Parameters
----------
vertices : ndarray
array of vertices making up a shape
faces : ndarray
array of triangles
Returns
-------
order : int
If the order is counter clockwise (CCW), returns True.
Otherwise, returns False.
"""
v1 = vertices[faces[0]]
v2 = vertices[faces[1]]
v3 = vertices[faces[2]]
# https://stackoverflow.com/questions/40454789/computing-face-normals-and-winding
m_orient = np.ones((4, 4))
m_orient[0, :3] = v1
m_orient[1, :3] = v2
m_orient[2, :3] = v3
m_orient[3, :3] = 0
val = np.linalg.det(m_orient)
return bool(val > 0)
def change_vertices_order(triangle):
"""Change the vertices order of a given triangle.
Parameters
----------
triangle : ndarray, shape(1, 3)
array of 3 vertices making up a triangle
Returns
-------
new_triangle : ndarray, shape(1, 3)
new array of vertices making up a triangle in the opposite winding
order of the given parameter
"""
return np.array([triangle[2], triangle[1], triangle[0]])
def fix_winding_order(vertices, triangles, clockwise=False):
"""Return corrected triangles.
Given an ordering of the triangle's three vertices, a triangle can appear
to have a clockwise winding or counter-clockwise winding.
Clockwise means that the three vertices, in order, rotate clockwise around
the triangle's center.
Parameters
----------
vertices : ndarray
array of vertices corresponding to a shape
triangles : ndarray
array of triangles corresponding to a shape
clockwise : bool
triangle order type: clockwise (default) or counter-clockwise.
Returns
-------
corrected_triangles : ndarray
The corrected order of the vert parameter
"""
corrected_triangles = triangles.copy()
desired_order = clockwise
for nb, face in enumerate(triangles):
current_order = triangle_order(vertices, face)
if desired_order != current_order:
corrected_triangles[nb] = change_vertices_order(face)
return corrected_triangles
[docs]def vertices_from_actor(actor, as_vtk=False):
"""Access to vertices from actor.
Parameters
----------
actor : actor
as_vtk: bool, optional
by default, ndarray is returned.
Returns
-------
vertices : ndarray
"""
vtk_array = actor.GetMapper().GetInput().GetPoints().GetData()
if as_vtk:
return vtk_array
return numpy_support.vtk_to_numpy(vtk_array)
def colors_from_actor(actor, array_name='colors', as_vtk=False):
"""Access colors from actor which uses polydata.
Parameters
----------
actor : actor
array_name: str
as_vtk: bool, optional
by default, numpy array is returned.
Returns
-------
output : array (N, 3)
Colors
"""
return array_from_actor(actor, array_name=array_name,
as_vtk=as_vtk)
[docs]def array_from_actor(actor, array_name, as_vtk=False):
"""Access array from actor which uses polydata.
Parameters
----------
actor : actor
array_name: str
as_vtk_type: bool, optional
by default, ndarray is returned.
Returns
-------
output : array (N, 3)
"""
vtk_array = \
actor.GetMapper().GetInput().GetPointData().GetArray(array_name)
if vtk_array is None:
return None
if as_vtk:
return vtk_array
return numpy_support.vtk_to_numpy(vtk_array)
def compute_bounds(actor):
"""Compute Bounds of actor.
Parameters
----------
actor : actor
"""
actor.GetMapper().GetInput().ComputeBounds()
[docs]def update_actor(actor, all_arrays=True):
"""Update actor.
Parameters
----------
actor : actor
all_arrays: bool, optional
if False, only vertices are updated
if True, all arrays associated to the actor are updated
Default: True
"""
pd = actor.GetMapper().GetInput()
pd.GetPoints().GetData().Modified()
if all_arrays:
nb_array = pd.GetPointData().GetNumberOfArrays()
for i in range(nb_array):
pd.GetPointData().GetArray(i).Modified()
def get_bounds(actor):
"""Return Bounds of actor.
Parameters
----------
actor : actor
Returns
-------
vertices : ndarray
"""
return actor.GetMapper().GetInput().GetBounds()