DeepSDFStruct.mesh

Functions

create_3D_mesh(sdf, N_base, mesh_type[, ...])
export_abaqus_surf_mesh(surf_mesh, filename)	export a mesh and adds corresponding boundary conditions
export_sdf_grid_vtk(sdf, filename[, N, ...])
export_surface_mesh(filename, mesh[, dSurf])
export_volume_mesh(volume_mesh, filename[, ...])	export a mesh and adds corresponding boundary conditions
generate_2D_surf_mesh(sdf, n_squares[, ...])
get_verts(sdf, samples, constructor, cube_idx, N)
process_N_base_input(N, tiling)
prune_collinear(points[, tol])	Remove nearly collinear points from a polyline (closed loop).
sdf_to_triangle_dict(x, y, sdf[, level, ...])	Convert an SDF array to a PSLG dict for triangle.triangulate.
tetrahedralize_surface(surface_mesh)

Classes

torchSurfMesh(vertices, faces)
torchVolumeMesh(vertices, volumes)

DeepSDFStruct.mesh.create_3D_mesh(sdf, N_base, mesh_type, differentiate=False, device='cpu')

Return type:

Tuple[Union[torchSurfMesh, torchVolumeMesh], Optional[Tensor]]

Parameters:

• sdf (DeepSDFStruct.SDF.SDFBase)

• mesh_type (str)

DeepSDFStruct.mesh.export_abaqus_surf_mesh(surf_mesh, filename)

export a mesh and adds corresponding boundary conditions

Parameters:

• surf_mesh (gustaf.faces.Faces)

• filename (str)

DeepSDFStruct.mesh.export_sdf_grid_vtk(sdf, filename, N=64, bounds=None, device='cpu')

Parameters:

sdf (DeepSDFStruct.SDF.SDFBase)

DeepSDFStruct.mesh.export_surface_mesh(filename, mesh, dSurf=None)

Parameters:

• filename (str | bytes | os.PathLike[str] | os.PathLike[bytes])

• mesh (gustaf.faces.Faces | DeepSDFStruct.mesh.torchSurfMesh)

DeepSDFStruct.mesh.export_volume_mesh(volume_mesh, filename, export_abaqus=False)

export a mesh and adds corresponding boundary conditions

Parameters:

• volume_mesh (gustaf.volumes.Volumes)

• filename (str)

DeepSDFStruct.mesh.generate_2D_surf_mesh(sdf, n_squares, n_elements=50000, bounds=None)

Parameters:

• sdf (DeepSDFStruct.SDF.SDFBase)

• n_squares (int)

• n_elements (int)

DeepSDFStruct.mesh.get_verts(sdf, samples, constructor, cube_idx, N, return_faces=False, output_tetmesh=False)

Parameters:

• sdf (DeepSDFStruct.SDF.SDFBase)

• samples (torch.Tensor)

• constructor (DeepSDFStruct.flexicubes.flexicubes.FlexiCubes)

• cube_idx (torch.Tensor)

DeepSDFStruct.mesh.process_N_base_input(N, tiling)

DeepSDFStruct.mesh.prune_collinear(points, tol=1e-09)

Remove nearly collinear points from a polyline (closed loop). :type points: :param points: Nx2 array of (x,y) vertices. :type points: ndarray :type tol: :param tol: area tolerance. Smaller = stricter (keep more points). :type tol: float

Returns:

pruned Nx2 array of vertices.

Return type:

ndarray

DeepSDFStruct.mesh.sdf_to_triangle_dict(x, y, sdf, level=0.0, pad_value=1.0, collinear_tol=1e-08)

Convert an SDF array to a PSLG dict for triangle.triangulate. Includes domain boundary and hole polygons.

Parameters:

• sdf (np.ndarray) – 2D signed distance field.

• level (float) – Contour level (usually 0 for boundary).

• pad_value (float) – Value outside domain to close boundaries.

Returns:

{“vertices”: …, “segments”: …, “holes”: …}

Return type:

dict

DeepSDFStruct.mesh.tetrahedralize_surface(surface_mesh)

Return type:

tuple[Volumes, ndarray]

Parameters:

surface_mesh (gustaf.faces.Faces)

class DeepSDFStruct.mesh.torchSurfMesh(vertices, faces)

Bases: object

Parameters:

• vertices (torch.Tensor)

• faces (torch.Tensor)

to_gus()

to_trimesh()

class DeepSDFStruct.mesh.torchVolumeMesh(vertices, volumes)

Bases: object

Parameters:

• vertices (torch.Tensor)

• volumes (torch.Tensor)

to_gus()

to_trimesh()