Source code for fury.utils

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 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
[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 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) 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
[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,) 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 == 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) 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
[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 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 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_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.hstack( np.c_[np.ones(len(triangles), dtype=req_dtype) * 3, triangles.astype(req_dtype)]) vtk_triangles = numpy_support.numpy_to_vtkIdTypeArray(all_triangles, deep=True) 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, 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
[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 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
[docs]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
[docs]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
[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 =[: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: >>> ([: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 =, rzs.T) + trans[None, :] return res.reshape(shape)
[docs]def asbytes(s): if isinstance(s, bytes): return s return s.encode('latin1')
[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) 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 : 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())
[docs]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
[docs]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
[docs]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
[docs]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]] # 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)
[docs]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]])
[docs]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): """Access to vertices from actor. Parameters ---------- actor : actor Returns ------- vertices : ndarray """ return numpy_support.vtk_to_numpy(actor.GetMapper().GetInput(). GetPoints().GetData())
[docs]def colors_from_actor(actor, array_name='colors'): """Access colors from actor which uses polydata. Parameters ---------- actor : actor Returns ------- output : array (N, 3) Colors """ vtk_colors = \ actor.GetMapper().GetInput().GetPointData().GetArray(array_name) if vtk_colors is None: return None return numpy_support.vtk_to_numpy(vtk_colors)
[docs]def compute_bounds(actor): """Compute Bounds of actor. Parameters ---------- actor : actor """ actor.GetMapper().GetInput().ComputeBounds()
[docs]def update_actor(actor): """Update actor. Parameters ---------- actor : actor """ actor.GetMapper().GetInput().GetPoints().GetData().Modified()
[docs]def get_bounds(actor): """Return Bounds of actor. Parameters ---------- actor : actor Returns ------- vertices : ndarray """ return actor.GetMapper().GetInput().GetBounds()