geomfum.shape package#

Subpackages#

geomfum.shape.convert package
- Module contents

Submodules#

geomfum.shape.hierarchical module#

Hierarchical objects module. An HierarchicalShape is composed of a low-resolution and a high-resolution shape, with methods to transfer functions between the two resolutions.

class geomfum.shape.hierarchical.EigenBasis(vals, vecs, use_k=None)[source]#

Bases: Basis

Basis formed by eigenvectors with dynamic truncation support.

Parameters:

vals (array-like, shape=[full_spectrum_size]) – Eigenvalues.
vecs (array-like, shape=[dim, full_spectrum_size]) – Eigenvectors.
use_k (int) – Number of values to use on computations.

property full_spectrum_size#

Total number of stored eigenvalues/eigenvectors.

Returns:: spectrum_size (int) – Spectrum size.

property nonzero_vals#

Nonzero eigenvalues.

Returns:: vals (array-like, shape=[spectrum_size - n_zeros]) – Eigenvalues.

property nonzero_vecs#

Eigenvectors corresponding to nonzero eigenvalues.

Returns:: vecs (array-like, shape=[dim, spectrum_size - n_zeros]) – Eigenvectors.

property spectrum_size#

Number of eigenvalues/eigenvectors currently in use.

Returns:: spectrum_size (int) – Spectrum size.

truncate(spectrum_size)[source]#

Create new basis with reduced spectrum size.

Parameters:: spectrum_size (int) – Spectrum size.
Returns:: basis (Eigenbasis) – Truncated eigenbasis.

property vals#

Currently used eigenvalues (truncated to use_k).

Returns:: vals (array-like, shape=[spectrum_size]) – Eigenvalues.

property vecs#

Currently used eigenvectors (truncated to use_k).

Returns:: vecs (array-like, shape=[dim, spectrum_size]) – Eigenvectors.

class geomfum.shape.hierarchical.HierarchicalMesh(*args, **kwargs)[source]#

Bases: WhichRegistryMixins, HierarchicalShape

Hierarchical mesh.

Parameters:

low (TriangleMesh) – Low resolution shape.
high (TriangleMesh) – High resolution shape.

class geomfum.shape.hierarchical.HierarchicalMeshRegistry[source]#

Bases: Registry

MAP = {'pyrmt': ('PyrmtHierarchicalMesh', None)}#

default = 'pyrmt'#

class geomfum.shape.hierarchical.HierarchicalShape(low, high)[source]#

Bases: ABC

Hierarchical shape. An HierarchicalShape is composed of a low-resolution and a high-resolution shape, with methods to transfer functions between the two resolutions.

Parameters:

low (Shape) – Low-resolution shape.
high (Shape) – High-resolution shape.

extend_basis(set_as_basis=True)[source]#

Extend basis.

See section 3.3. of [MBMR2023] for details.

Parameters:: set_as_basis (bool) – Whether to set as basis.
Returns:: vecs (array-like, shape=[high.n_vertices, spectrum_size]) – Eigenvectors.

References

[MBMR2023]

Filippo Maggioli, Daniele Baieri, Simone Melzi, and Emanuele Rodolà. “ReMatching: Low-Resolution Representations for Scalable Shape

Correspondence.” arXiv, October 30, 2023. https://doi.org/10.48550/arXiv.2305.09274.

abstractmethod scalar_low_high(scalar)[source]#

Transfer scalar from low-resolution to high.

Parameters:: scalar (array-like, shape=[…, low.n_vertices]) – Scalar map on the low-resolution shape.
Returns:: high_scalar (array-like, shape=[…, high.n_vertices]) – Scalar map on the high-resolution shape.

class geomfum.shape.hierarchical.NestedHierarchicalMesh(hshapes)[source]#

Bases: NestedHierarchicalShape

Nested hierachical mesh.

property hmeshes#

Meshes from low to high resolution.

Remarks#

hshapeslist[HierarchicalMesh]: Hierarchical meshes from low to high resolution.

property meshes#

Meshes from low to high resolution.

Remarks#

mesheslist[Mesh]: List of meshes from low to high resolution.

property n_faces#

Number of faces at each level.

Returns:: n_faces (list[int])

property n_vertices#

Number of vertices at each level.

Returns:: n_vertices (list[int])

class geomfum.shape.hierarchical.NestedHierarchicalShape(hshapes)[source]#

Bases: object

Nested hierachical shape. An object composed of multiple hierarchical shapes from low to high resolution.

Parameters:: hshapes (list[HierarchicalShape]) – Hierarchical shapes from low to high resolution.

extend_basis(set_as_basis=True, n_levels=None)[source]#

Extend basis.

See section 3.3. of [MBMR2023] for details.

Parameters:

set_as_basis (bool) – Whether to set as basis.
n_levels (int) – Number of levels to transfer scalar. If None transfer up to maximum resolution.

Returns:

vecs (list[array-like], shape=[level.n_vertices, spectrum_size]) – Eigenvectors. As many as number of levels.

References

[MBMR2023]

Filippo Maggioli, Daniele Baieri, Simone Melzi, and Emanuele Rodolà. “ReMatching: Low-Resolution Representations for Scalable Shape

Correspondence.” arXiv, October 30, 2023. https://doi.org/10.48550/arXiv.2305.09274.

classmethod from_hierarchical_shape(shape, HierarchicalShape, **kwargs)[source]#

Create nested from hierarchical.

Parameters:

shape (Shape.) – High-resolution shape.
HierarchicalShape (HierarchicalShape object) – Class for the mapping between two resolutions. Signature: `(high_res_shape, **kwargs).
kwargs (dict) – Each must be a list with the proper number of resolution levels.

property highest#

Highest resolution shape.

Returns:: shape (Shape.)

property lowest#

Lowest resolution shape.

Returns:: shape (Shape.)

scalar_low_high(scalar, n_levels=None)[source]#

Transfer scalar from low-resolution to high.

Parameters:

scalar (array-like, shape=[…, low.n_vertices]) – Scalar map on the low-resolution shape.
n_levels (int) – Number of levels to transfer scalar. If None transfer up to maximum resolution.

Returns:

high_scalar (list[array-like], shape=[…, level.n_vertices]) – Scalar map on the shape at corresponding level. As many as number of levels.

property shapes#

Shapes from low to high resolution.

Remarks#

shapeslist[Shape]: List of shapes from low to high resolution.

class geomfum.shape.hierarchical.WhichRegistryMixins(*args, **kwargs)[source]#

Bases: object

Mixin enabling registry-based instantiation via ‘which’ parameter.

classmethod from_registry(*args, which=None, **kwargs)[source]#

Create instance from registered implementation.

Parameters:: which (str) – A registered implementation.
Returns:: obj (BaseHeatKernelSignature) – Instantiated object.

geomfum.shape.mesh module#

Definition of triangle mesh.

class geomfum.shape.mesh.FaceDivergenceOperator(*args, **kwargs)[source]#

Bases: WhichRegistryMixins, VectorFieldOperator

Divergence of a function on a mesh.

class geomfum.shape.mesh.FaceOrientationOperator(*args, **kwargs)[source]#

Bases: WhichRegistryMixins, VectorFieldOperator

Orientation operator associated to a gradient field.

For a given function \(g\) on the vertices, this operator linearly computes \(< \grad(f) x \grad(g)\), n> for each vertex by averaging along the adjacent faces. In practice, we compute \(< n x \grad(f), \grad(g) >\) for simpler computation.

class geomfum.shape.mesh.FaceValuedGradient(*args, **kwargs)[source]#

Bases: WhichRegistryMixins, FunctionalOperator

Gradient of a function on a mesh.

Computes the gradient of a function on f using linear interpolation between vertices.

class geomfum.shape.mesh.HeatDistanceMetric(*args, **kwargs)[source]#

Bases: MeshWhichRegistryMixins

Geodesic distance approximation using the heat method.

References

[CWW2017]

Crane, K., Weischedel, C., Wardetzky, M., 2017. The heat method for distance computation. Commun. ACM 60, 90–99. https://doi.org/10.1145/3131280

class geomfum.shape.mesh.Shape(is_mesh)[source]#

Bases: ABC

Abstract base class for geometric shapes with differential operators.

Parameters:: is_mesh (bool) – Whether the shape is a mesh (True) or point cloud (False).

property basis#

Function basis associated with the shape.

Returns:: basis (Basis) – Basis.

equip_with_operator(name, Operator, allow_overwrite=True, **kwargs)[source]#

Equip shape with a differential or geometric operator.

Parameters:

name (str) – Attribute name for the operator.
Operator (class) – Operator class to instantiate.
allow_overwrite (bool, optional) – Whether to allow overwriting existing attributes (default: True).
**kwargs – Additional arguments passed to the Operator constructor.

Returns:

self (Shape) – The shape instance for method chaining.

set_basis(basis)[source]#

Set function basis associated with the shape.

Parameters:: basis (Basis) – Basis.

set_landmarks(landmark_indices, append=False)[source]#

Set landmarks points on the shape.

Parameters:

landmark_indices (array-like, shape=[n_landmarks]) – Landmarks.
append (bool) – Whether to append landmarks to already-existing ones.

class geomfum.shape.mesh.TriangleMesh(vertices, faces)[source]#

Bases: Shape

Triangulated surface mesh with vertices, faces, and differential operators.

Parameters:

vertices (array-like, shape=[n_vertices, 3]) – Vertices of the mesh.
faces (array-like, shape=[n_faces, 3]) – Faces of the mesh.

property dist_matrix#

Pairwise distances between all vertices using the equipped metric.

Returns:: _dist_matrix (array-like, shape=[n_vertices, n_vertices]) – Metric distance matrix.

property edge_tangent_vectors#

Edge vectors projected onto local tangent planes.

Returns:: edge_tangent_vectors (array-like, shape=[n_edges, 2]) – Tangent vectors of the edges, projected onto the local tangent plane.

property edges#

Edges of the mesh.

Returns:: edges (array-like, shape=[n_edges, 2])

equip_with_metric(metric)[source]#

Equip mesh with a distance metric.

Parameters:: metric (class) – A metric class to use for the mesh.

property face_area_vectors#

Face area vectors (unnormalized normals with magnitude equal to face area).

Returns:: area_vectors (array-like, shape=[n_faces, 3]) – Per-face area vectors.

property face_areas#

Area of each triangular face.

Returns:: face_areas (array-like, shape=[n_faces]) – Per-face areas.

property face_normals#

Unit normal vectors for each face.

Returns:: normals (array-like, shape=[n_faces, 3]) – Per-face normals.

property face_vertex_coords#

Extract vertex coordinates corresponding to each face.

Returns:: vertices (array-like, shape=[{n_faces}, n_per_face_vertex, 3]) – Coordinates of the ith vertex of that face.

classmethod from_file(filename)[source]#

Load mesh from file.

Parameters:: filename (str) – Path to the mesh file.
Returns:: mesh (TriangleMesh) – A triangle mesh.

property n_faces#

Number of faces.

Returns:: n_faces (int)

property n_vertices#

Number of vertices.

Returns:: n_vertices (int)

property vertex_areas#

Area associated with each vertex (one-third of adjacent triangle areas).

Returns:: vertex_areas (array-like, shape=[n_vertices]) – Per-vertex areas.

property vertex_normals#

Unit normal vectors at vertices (area-weighted average of adjacent face normals).

Returns:: normals (array-like, shape=[n_vertices, 3]) – Normalized per-vertex normals.

property vertex_tangent_frames#

Local orthonormal coordinate frames at each vertex.

Returns:: tangent_frame (array-like, shape=[n_vertices, 3, 3]) – Tangent frame of the mesh, where: - [n_vertices, 0, :] are the X basis vectors - [n_vertices, 1, :] are the Y basis vectors - [n_vertices, 2, :] are the vertex normals

geomfum.shape.mesh.compute_edge_tangent_vectors(vertices, edges, tangent_frames)[source]#

Project edge vectors onto local tangent plane coordinates.

Parameters:

vertices (array-like, shape=[n_vertices, 3]) – Vertex coordinates.
edges (array-like, shape=[n_edges, 2]) – Edges of the shape.
tangent_frames (array-like, shape=[n_vertices, 3, 3]) – Tangent frames for each vertex.

Returns:

edge_tangent_vectors (array-like, shape=[n_edges, 2]) – Tangent vectors of the edges, projected onto the local tangent plane.

geomfum.shape.mesh.compute_tangent_frames(vertices, normals)[source]#

Construct local orthonormal frames at each vertex from normal vectors.

Parameters:

vertices (array-like, shape=[n_vertices, 3]) – Vertex coordinates.
normals (array-like, shape=[n_vertices, 3]) – Vertex normals.

Returns:

frames (array-like, shape=[n_vertices, 3, 3]) – Tangent frames.

geomfum.shape.mesh.load_mesh(filename)[source]#

Load a mesh from a file.

Parameters:

filename (str) – File name.

Returns:

vertices (array-like, shape=[n_vertices, 3])
faces (array_like, shape=[n_faces, 3])

geomfum.shape.point_cloud module#

Definition of point cloud.

class geomfum.shape.point_cloud.HeatDistanceMetric(*args, **kwargs)[source]#

Bases: MeshWhichRegistryMixins

Geodesic distance approximation using the heat method.

References

[CWW2017]

Crane, K., Weischedel, C., Wardetzky, M., 2017. The heat method for distance computation. Commun. ACM 60, 90–99. https://doi.org/10.1145/3131280

class geomfum.shape.point_cloud.PointCloud(vertices)[source]#

Bases: Shape

Unstructured point cloud with k-NN connectivity and differential operators.

Parameters:: vertices (array-like, shape=[n_vertices, 3]) – Vertices of the point cloud.

property dist_matrix#

Pairwise distances between all points using the equipped metric.

Returns:: _dist_matrix (array-like, shape=[n_vertices, n_vertices]) – Metric distance matrix.

property edge_tangent_vectors#

Edge vectors projected onto local tangent planes.

Returns:: edge_tangent_vectors (array-like, shape=[n_edges, 2]) – Tangent vectors of the edges, projected onto the local tangent plane.

property edges#: Edge connectivity from k-NN graph.

equip_with_metric(metric)[source]#

Equip point cloud with a distance metric.

Parameters:: metric (class) – A metric class to use for the point cloud.

classmethod from_file(filename)[source]#

Load point cloud from file.

Returns:: mesh (PointCloud) – A point cloud.

property knn_graph#

K-nearest neighbors connectivity graph.

Returns:: knn_info (dict) – Dictionary containing: - ‘indices’: array-like, shape=[n_vertices, k] - neighbor indices for each vertex - ‘distances’: array-like, shape=[n_vertices, k] - distances to neighbors - ‘k’: int - number of neighbors - ‘nbrs_model’: sklearn.neighbors.NearestNeighbors - fitted model for reuse

property n_vertices#

Number of points.

Returns:: n_vertices (int)

property vertex_normals#

Normal vectors estimated from local neighborhoods using PCA.

Returns:: normals (array-like, shape=[n_vertices, 3]) – Normalized per-vertex normals estimated from local neighborhoods using PCA.

property vertex_tangent_frames#

Local orthonormal coordinate frames at each point.

Returns:: tangent_frame (array-like, shape=[n_vertices, 3, 3]) – Tangent frame of the mesh, where: - [n_vertices, 0, :] are the X basis vectors - [n_vertices, 1, :] are the Y basis vectors - [n_vertices, 2, :] are the vertex normals

class geomfum.shape.point_cloud.Shape(is_mesh)[source]#

Bases: ABC

Abstract base class for geometric shapes with differential operators.

Parameters:: is_mesh (bool) – Whether the shape is a mesh (True) or point cloud (False).

property basis#

Function basis associated with the shape.

Returns:: basis (Basis) – Basis.

equip_with_operator(name, Operator, allow_overwrite=True, **kwargs)[source]#

Equip shape with a differential or geometric operator.

Parameters:

name (str) – Attribute name for the operator.
Operator (class) – Operator class to instantiate.
allow_overwrite (bool, optional) – Whether to allow overwriting existing attributes (default: True).
**kwargs – Additional arguments passed to the Operator constructor.

Returns:

self (Shape) – The shape instance for method chaining.

set_basis(basis)[source]#

Set function basis associated with the shape.

Parameters:: basis (Basis) – Basis.

set_landmarks(landmark_indices, append=False)[source]#

Set landmarks points on the shape.

Parameters:

landmark_indices (array-like, shape=[n_landmarks]) – Landmarks.
append (bool) – Whether to append landmarks to already-existing ones.

geomfum.shape.point_cloud.compute_edge_tangent_vectors(vertices, edges, tangent_frames)[source]#

Project edge vectors onto local tangent plane coordinates.

Parameters:

vertices (array-like, shape=[n_vertices, 3]) – Vertex coordinates.
edges (array-like, shape=[n_edges, 2]) – Edges of the shape.
tangent_frames (array-like, shape=[n_vertices, 3, 3]) – Tangent frames for each vertex.

Returns:

edge_tangent_vectors (array-like, shape=[n_edges, 2]) – Tangent vectors of the edges, projected onto the local tangent plane.

geomfum.shape.point_cloud.compute_tangent_frames(vertices, normals)[source]#

Construct local orthonormal frames at each vertex from normal vectors.

Parameters:

vertices (array-like, shape=[n_vertices, 3]) – Vertex coordinates.
normals (array-like, shape=[n_vertices, 3]) – Vertex normals.

Returns:

frames (array-like, shape=[n_vertices, 3, 3]) – Tangent frames.

geomfum.shape.point_cloud.load_pointcloud(filename)[source]#

Load a point cloud from a file.

Parameters:: filename (str) – File name.
Returns:: vertices (array-like, shape=[n_vertices, 3])

geomfum.shape.shape_utils module#

Utility functions for shape computations.

geomfum.shape.shape_utils.compute_edge_tangent_vectors(vertices, edges, tangent_frames)[source]#

Project edge vectors onto local tangent plane coordinates.

Parameters:

vertices (array-like, shape=[n_vertices, 3]) – Vertex coordinates.
edges (array-like, shape=[n_edges, 2]) – Edges of the shape.
tangent_frames (array-like, shape=[n_vertices, 3, 3]) – Tangent frames for each vertex.

Returns:

edge_tangent_vectors (array-like, shape=[n_edges, 2]) – Tangent vectors of the edges, projected onto the local tangent plane.

geomfum.shape.shape_utils.compute_gradient_matrix_fem(vertices, edges, edge_tangent_vectors)[source]#

Construct gradient operator using local least-squares approximation.

Parameters:

vertices (array-like, shape=[n_vertices, 3]) – Vertex coordinates.
edges (array-like, shape=[n_edges, 2]) – Edges of the shape.
edge_tangent_vectors (array-like, shape=[n_edges, 2]) – Tangent vectors of the edges, projected onto the local tangent plane.

Returns:

grad_matrix (array-like, shape=[n_edges, n_vertices]) – Gradient matrix.

geomfum.shape.shape_utils.compute_tangent_frames(vertices, normals)[source]#

Construct local orthonormal frames at each vertex from normal vectors.

Parameters:

vertices (array-like, shape=[n_vertices, 3]) – Vertex coordinates.
normals (array-like, shape=[n_vertices, 3]) – Vertex normals.

Returns:

frames (array-like, shape=[n_vertices, 3, 3]) – Tangent frames.

Module contents#

Shapes Module. This module contains various shape representations used in Geomfum, such as TriangleMesh and PointCloud.

class geomfum.shape.PointCloud(vertices)[source]#

Bases: Shape

Unstructured point cloud with k-NN connectivity and differential operators.

Parameters:: vertices (array-like, shape=[n_vertices, 3]) – Vertices of the point cloud.

property dist_matrix#

Pairwise distances between all points using the equipped metric.

Returns:: _dist_matrix (array-like, shape=[n_vertices, n_vertices]) – Metric distance matrix.

property edge_tangent_vectors#

Edge vectors projected onto local tangent planes.

Returns:: edge_tangent_vectors (array-like, shape=[n_edges, 2]) – Tangent vectors of the edges, projected onto the local tangent plane.

property edges#: Edge connectivity from k-NN graph.

equip_with_metric(metric)[source]#

Equip point cloud with a distance metric.

Parameters:: metric (class) – A metric class to use for the point cloud.

classmethod from_file(filename)[source]#

Load point cloud from file.

Returns:: mesh (PointCloud) – A point cloud.

property knn_graph#

K-nearest neighbors connectivity graph.

Returns:: knn_info (dict) – Dictionary containing: - ‘indices’: array-like, shape=[n_vertices, k] - neighbor indices for each vertex - ‘distances’: array-like, shape=[n_vertices, k] - distances to neighbors - ‘k’: int - number of neighbors - ‘nbrs_model’: sklearn.neighbors.NearestNeighbors - fitted model for reuse

property n_vertices#

Number of points.

Returns:: n_vertices (int)

property vertex_normals#

Normal vectors estimated from local neighborhoods using PCA.

Returns:: normals (array-like, shape=[n_vertices, 3]) – Normalized per-vertex normals estimated from local neighborhoods using PCA.

property vertex_tangent_frames#

Local orthonormal coordinate frames at each point.

Returns:: tangent_frame (array-like, shape=[n_vertices, 3, 3]) – Tangent frame of the mesh, where: - [n_vertices, 0, :] are the X basis vectors - [n_vertices, 1, :] are the Y basis vectors - [n_vertices, 2, :] are the vertex normals

class geomfum.shape.Shape(is_mesh)[source]#

Bases: ABC

Abstract base class for geometric shapes with differential operators.

Parameters:: is_mesh (bool) – Whether the shape is a mesh (True) or point cloud (False).

property basis#

Function basis associated with the shape.

Returns:: basis (Basis) – Basis.

equip_with_operator(name, Operator, allow_overwrite=True, **kwargs)[source]#

Equip shape with a differential or geometric operator.

Parameters:

name (str) – Attribute name for the operator.
Operator (class) – Operator class to instantiate.
allow_overwrite (bool, optional) – Whether to allow overwriting existing attributes (default: True).
**kwargs – Additional arguments passed to the Operator constructor.

Returns:

self (Shape) – The shape instance for method chaining.

set_basis(basis)[source]#

Set function basis associated with the shape.

Parameters:: basis (Basis) – Basis.

set_landmarks(landmark_indices, append=False)[source]#

Set landmarks points on the shape.

Parameters:

landmark_indices (array-like, shape=[n_landmarks]) – Landmarks.
append (bool) – Whether to append landmarks to already-existing ones.

class geomfum.shape.TriangleMesh(vertices, faces)[source]#

Bases: Shape

Triangulated surface mesh with vertices, faces, and differential operators.

Parameters:

vertices (array-like, shape=[n_vertices, 3]) – Vertices of the mesh.
faces (array-like, shape=[n_faces, 3]) – Faces of the mesh.

property dist_matrix#

Pairwise distances between all vertices using the equipped metric.

Returns:: _dist_matrix (array-like, shape=[n_vertices, n_vertices]) – Metric distance matrix.

property edge_tangent_vectors#

Edge vectors projected onto local tangent planes.

Returns:: edge_tangent_vectors (array-like, shape=[n_edges, 2]) – Tangent vectors of the edges, projected onto the local tangent plane.

property edges#

Edges of the mesh.

Returns:: edges (array-like, shape=[n_edges, 2])

equip_with_metric(metric)[source]#

Equip mesh with a distance metric.

Parameters:: metric (class) – A metric class to use for the mesh.

property face_area_vectors#

Face area vectors (unnormalized normals with magnitude equal to face area).

Returns:: area_vectors (array-like, shape=[n_faces, 3]) – Per-face area vectors.

property face_areas#

Area of each triangular face.

Returns:: face_areas (array-like, shape=[n_faces]) – Per-face areas.

property face_normals#

Unit normal vectors for each face.

Returns:: normals (array-like, shape=[n_faces, 3]) – Per-face normals.

property face_vertex_coords#

Extract vertex coordinates corresponding to each face.

Returns:: vertices (array-like, shape=[{n_faces}, n_per_face_vertex, 3]) – Coordinates of the ith vertex of that face.

classmethod from_file(filename)[source]#

Load mesh from file.

Parameters:: filename (str) – Path to the mesh file.
Returns:: mesh (TriangleMesh) – A triangle mesh.

property n_faces#

Number of faces.

Returns:: n_faces (int)

property n_vertices#

Number of vertices.

Returns:: n_vertices (int)

property vertex_areas#

Area associated with each vertex (one-third of adjacent triangle areas).

Returns:: vertex_areas (array-like, shape=[n_vertices]) – Per-vertex areas.

property vertex_normals#

Unit normal vectors at vertices (area-weighted average of adjacent face normals).

Returns:: normals (array-like, shape=[n_vertices, 3]) – Normalized per-vertex normals.

property vertex_tangent_frames#

Local orthonormal coordinate frames at each vertex.

Returns:: tangent_frame (array-like, shape=[n_vertices, 3, 3]) – Tangent frame of the mesh, where: - [n_vertices, 0, :] are the X basis vectors - [n_vertices, 1, :] are the Y basis vectors - [n_vertices, 2, :] are the vertex normals

geomfum.shape package#

Subpackages#

Submodules#

geomfum.shape.hierarchical module#

Remarks#

Remarks#

Remarks#

geomfum.shape.mesh module#

geomfum.shape.point_cloud module#

geomfum.shape.shape_utils module#

Module contents#

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