Candidates¶

class ipctk.Candidates¶

Bases: pybind11_object

Public Data Attributes:

`vv_candidates`
`ev_candidates`
`ee_candidates`
`fv_candidates`

Public Methods:

`__init__`(self)
`build`(args, *kwargs)	Overloaded function.
`__len__`(self)
`empty`(self)
`clear`(self)
`__getitem__`(self, arg0)
`is_step_collision_free`(self, mesh, ...)	Determine if the step is collision free from the set of candidates.
`compute_collision_free_stepsize`(self, mesh, ...)	Computes a maximal step size that is collision free using the set of collision candidates.
`compute_noncandidate_conservative_stepsize`(...)	Computes a conservative bound on the largest-feasible step size for surface primitives not in collision.
`compute_cfl_stepsize`(self, mesh, ...)	Computes a CFL-inspired CCD maximum step step size.
`save_obj`(self, filename, vertices, edges, faces)

Inherited from pybind11_object

__annotations__ = {}¶

__getitem__(self, arg0: int) → ipc::CollisionStencil¶

__init__(self)¶

__len__(self) → int¶

__module__ = 'ipctk'¶

build(*args, **kwargs)¶

Overloaded function.

build(self: ipctk.Candidates, mesh: ipc::CollisionMesh, vertices: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], inflation_radius: float = 0, broad_phase: ipctk.BroadPhase = <ipctk.HashGrid object at 0x7fd2aad71f70>) -> None

Initialize the set of discrete collision detection candidates.

Parameters:
mesh: The surface of the collision mesh. vertices: Surface vertex positions (rowwise). inflation_radius: Amount to inflate the bounding boxes. broad_phase: Broad phase to use.
build(self: ipctk.Candidates, mesh: ipc::CollisionMesh, vertices_t0: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], vertices_t1: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], inflation_radius: float = 0, broad_phase: ipctk.BroadPhase = <ipctk.HashGrid object at 0x7fd2aad720f0>) -> None

Initialize the set of continuous collision detection candidates.

Note:
Assumes the trajectory is linear.

Parameters:
mesh: The surface of the collision mesh. vertices_t0: Surface vertex starting positions (rowwise). vertices_t1: Surface vertex ending positions (rowwise). inflation_radius: Amount to inflate the bounding boxes. broad_phase: Broad phase to use.

clear(self) → None¶

compute_cfl_stepsize(self: ipctk.Candidates, mesh: ipc::CollisionMesh, vertices_t0: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], vertices_t1: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], dhat: float, min_distance: float = 0.0, broad_phase: ipctk.BroadPhase = <ipctk.HashGrid object at 0x7fd2aad727b0>, narrow_phase_ccd: ipctk.NarrowPhaseCCD = <ipctk.TightInclusionCCD object at 0x7fd2aad6a1b0>) → float¶

Computes a CFL-inspired CCD maximum step step size.

Parameters:¶

mesh: The collision mesh.
vertices_t0: Surface vertex starting positions (rowwise).
vertices_t1: Surface vertex ending positions (rowwise).
dhat: Barrier activation distance.
min_distance: Minimum distance allowable between any two elements.
broad_phase: Broad phase algorithm to use.
narrow_phase_ccd: Narrow phase CCD algorithm to use.

compute_collision_free_stepsize(self: ipctk.Candidates, mesh: ipc::CollisionMesh, vertices_t0: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], vertices_t1: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], min_distance: float = 0.0, narrow_phase_ccd: ipctk.NarrowPhaseCCD = <ipctk.TightInclusionCCD object at 0x7fd2aad72570>) → float¶

Computes a maximal step size that is collision free using the set of collision candidates.

Note

Assumes the trajectory is linear.

Parameters:¶

mesh: The collision mesh.
vertices_t0: Surface vertex starting positions (rowwise). Assumed to be intersection free.
vertices_t1: Surface vertex ending positions (rowwise).
min_distance: The minimum distance allowable between any two elements.
narrow_phase_ccd: The narrow phase CCD algorithm to use.

Returns:¶

A step-size \(\in [0, 1]\) that is collision free. A value of 1.0 if a full step and 0.0 is no step.

compute_noncandidate_conservative_stepsize(self: ipctk.Candidates, mesh: ipc::CollisionMesh, displacements: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], dhat: float) → float¶

Computes a conservative bound on the largest-feasible step size for surface primitives not in collision.

Parameters:¶

mesh: The collision mesh.
displacements: Surface vertex displacements (rowwise).
dhat: Barrier activation distance.

property ee_candidates : list[ipc::EdgeEdgeCandidate]¶

empty(self) → bool¶

property ev_candidates : list[ipc::EdgeVertexCandidate]¶

property fv_candidates : list[ipc::FaceVertexCandidate]¶

is_step_collision_free(self: ipctk.Candidates, mesh: ipc::CollisionMesh, vertices_t0: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], vertices_t1: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], min_distance: float = 0.0, narrow_phase_ccd: ipctk.NarrowPhaseCCD = <ipctk.TightInclusionCCD object at 0x7fd2aad72470>) → bool¶

Determine if the step is collision free from the set of candidates.

Note

Assumes the trajectory is linear.

Parameters:¶

mesh: The collision mesh.
vertices_t0: Surface vertex starting positions (rowwise).
vertices_t1: Surface vertex ending positions (rowwise).
min_distance: The minimum distance allowable between any two elements.
narrow_phase_ccd: The narrow phase CCD algorithm to use.

Returns:¶

True if <b>any</b> collisions occur.

save_obj(self, filename: str, vertices: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], edges: numpy.ndarray[numpy.int32[m, n], flags.f_contiguous], faces: numpy.ndarray[numpy.int32[m, n], flags.f_contiguous]) → bool¶

property vv_candidates : list[ipc::VertexVertexCandidate]¶

Collision Stencil¶

Error

This autoclass is not working. I don’t know why. I have to investigate.

Vertex-Vertex Candidate¶

class ipctk.VertexVertexCandidate¶

Bases: CollisionStencil

Public Data Attributes:

`vertex0_id`	ID of the first vertex
`vertex1_id`	ID of the second vertex

Public Methods:

`__init__`(args, *kwargs)	Overloaded function.
`__str__`(self)
`__repr__`(self)
`__eq__`(self, other)
`__ne__`(self, other)
`__lt__`(self, other)	Compare EdgeVertexCandidates for sorting.

Inherited from CollisionStencil

`__init__`(args, *kwargs)
`num_vertices`(self)	Get the number of vertices in the collision stencil.
`dim`(self, ndof)	Get the dimension of the collision stencil.
`vertex_ids`(self, edges, faces)	Get the vertex IDs of the collision stencil.
`vertices`(self, vertices, edges, faces)	Get the vertex attributes of the collision stencil.
`dof`(self, X, edges, faces)	Select this stencil's DOF from the full matrix of DOF.
`compute_distance`(args, *kwargs)	Overloaded function.
`compute_distance_gradient`(args, *kwargs)	Overloaded function.
`compute_distance_hessian`(args, *kwargs)	Overloaded function.
`ccd`(self, vertices_t0, 1]], vertices_t1, ...)	Perform narrow-phase CCD on the candidate.
`print_ccd_query`(self, vertices_t0, vertices_t1)	Print the CCD query to cout.

Inherited from pybind11_object

__annotations__ = {}¶

__eq__(self, other: ipctk.VertexVertexCandidate) → bool¶

__hash__ = None¶

__init__(*args, **kwargs)¶

Overloaded function.

__init__(self: ipctk.VertexVertexCandidate, vertex0_id: int, vertex1_id: int) -> None
__init__(self: ipctk.VertexVertexCandidate, vertex_ids: tuple[int, int]) -> None

__lt__(self, other: ipctk.VertexVertexCandidate) → bool¶: Compare EdgeVertexCandidates for sorting.

__module__ = 'ipctk'¶

__ne__(self, other: ipctk.VertexVertexCandidate) → bool¶

__repr__(self) → str¶

__str__(self) → str¶

property vertex0_id : int¶: ID of the first vertex

property vertex1_id : int¶: ID of the second vertex

Edge-Vertex Candidate¶

class ipctk.EdgeVertexCandidate¶

Bases: CollisionStencil

Public Data Attributes:

`edge_id`	ID of the edge
`vertex_id`	ID of the vertex

Public Methods:

`__init__`(args, *kwargs)	Overloaded function.
`known_dtype`(self)
`__str__`(self)
`__repr__`(self)
`__eq__`(self, other)
`__ne__`(self, other)
`__lt__`(self, other)	Compare EdgeVertexCandidates for sorting.

Inherited from CollisionStencil

`__init__`(args, *kwargs)
`num_vertices`(self)	Get the number of vertices in the collision stencil.
`dim`(self, ndof)	Get the dimension of the collision stencil.
`vertex_ids`(self, edges, faces)	Get the vertex IDs of the collision stencil.
`vertices`(self, vertices, edges, faces)	Get the vertex attributes of the collision stencil.
`dof`(self, X, edges, faces)	Select this stencil's DOF from the full matrix of DOF.
`compute_distance`(args, *kwargs)	Overloaded function.
`compute_distance_gradient`(args, *kwargs)	Overloaded function.
`compute_distance_hessian`(args, *kwargs)	Overloaded function.
`ccd`(self, vertices_t0, 1]], vertices_t1, ...)	Perform narrow-phase CCD on the candidate.
`print_ccd_query`(self, vertices_t0, vertices_t1)	Print the CCD query to cout.

Inherited from pybind11_object

__annotations__ = {}¶

__eq__(self, other: ipctk.EdgeVertexCandidate) → bool¶

__hash__ = None¶

__init__(*args, **kwargs)¶

Overloaded function.

__init__(self: ipctk.EdgeVertexCandidate, edge_id: int, vertex_id: int) -> None
__init__(self: ipctk.EdgeVertexCandidate, edge_and_vertex_id: tuple[int, int]) -> None

__lt__(self, other: ipctk.EdgeVertexCandidate) → bool¶: Compare EdgeVertexCandidates for sorting.

__module__ = 'ipctk'¶

__ne__(self, other: ipctk.EdgeVertexCandidate) → bool¶

__repr__(self) → str¶

__str__(self) → str¶

property edge_id : int¶: ID of the edge

known_dtype(self) → ipc::PointEdgeDistanceType¶

property vertex_id : int¶: ID of the vertex

Edge-Edge Candidate¶

class ipctk.EdgeEdgeCandidate¶

Bases: CollisionStencil

Public Data Attributes:

`edge0_id`	ID of the first edge.
`edge1_id`	ID of the second edge.

Public Methods:

`__init__`(args, *kwargs)	Overloaded function.
`known_dtype`(self)
`__str__`(self)
`__repr__`(self)
`__eq__`(self, other)
`__ne__`(self, other)
`__lt__`(self, other)	Compare EdgeEdgeCandidates for sorting.

Inherited from CollisionStencil

`__init__`(args, *kwargs)
`num_vertices`(self)	Get the number of vertices in the collision stencil.
`dim`(self, ndof)	Get the dimension of the collision stencil.
`vertex_ids`(self, edges, faces)	Get the vertex IDs of the collision stencil.
`vertices`(self, vertices, edges, faces)	Get the vertex attributes of the collision stencil.
`dof`(self, X, edges, faces)	Select this stencil's DOF from the full matrix of DOF.
`compute_distance`(args, *kwargs)	Overloaded function.
`compute_distance_gradient`(args, *kwargs)	Overloaded function.
`compute_distance_hessian`(args, *kwargs)	Overloaded function.
`ccd`(self, vertices_t0, 1]], vertices_t1, ...)	Perform narrow-phase CCD on the candidate.
`print_ccd_query`(self, vertices_t0, vertices_t1)	Print the CCD query to cout.

Inherited from pybind11_object

__annotations__ = {}¶

__eq__(self, other: ipctk.EdgeEdgeCandidate) → bool¶

__hash__ = None¶

__init__(*args, **kwargs)¶

Overloaded function.

__init__(self: ipctk.EdgeEdgeCandidate, edge0_id: int, edge1_id: int) -> None
__init__(self: ipctk.EdgeEdgeCandidate, edge_ids: tuple[int, int]) -> None

__lt__(self, other: ipctk.EdgeEdgeCandidate) → bool¶: Compare EdgeEdgeCandidates for sorting.

__module__ = 'ipctk'¶

__ne__(self, other: ipctk.EdgeEdgeCandidate) → bool¶

__repr__(self) → str¶

__str__(self) → str¶

property edge0_id : int¶: ID of the first edge.

property edge1_id : int¶: ID of the second edge.

known_dtype(self) → ipc::EdgeEdgeDistanceType¶

Edge-Face Candidate¶

class ipctk.EdgeFaceCandidate¶

Bases: pybind11_object

Public Data Attributes:

`edge_id`	ID of the edge
`face_id`	ID of the face

Public Methods:

`__init__`(args, *kwargs)	Overloaded function.
`__str__`(self)
`__repr__`(self)
`__eq__`(self, other)
`__ne__`(self, other)
`__lt__`(self, other)	Compare EdgeFaceCandidate for sorting.

Inherited from pybind11_object

__annotations__ = {}¶

__eq__(self, other: ipctk.EdgeFaceCandidate) → bool¶

__hash__ = None¶

__init__(*args, **kwargs)¶

Overloaded function.

__init__(self: ipctk.EdgeFaceCandidate, edge_id: int, face_id: int) -> None
__init__(self: ipctk.EdgeFaceCandidate, edge_and_face_id: tuple[int, int]) -> None

__lt__(self, other: ipctk.EdgeFaceCandidate) → bool¶: Compare EdgeFaceCandidate for sorting.

__module__ = 'ipctk'¶

__ne__(self, other: ipctk.EdgeFaceCandidate) → bool¶

__repr__(self) → str¶

__str__(self) → str¶

property edge_id : int¶: ID of the edge

property face_id : int¶: ID of the face

Face-Vertex Candidate¶

class ipctk.FaceVertexCandidate¶

Bases: CollisionStencil

Public Data Attributes:

`face_id`	ID of the face
`vertex_id`	ID of the vertex

Public Methods:

`__init__`(args, *kwargs)	Overloaded function.
`known_dtype`(self)
`__str__`(self)
`__repr__`(self)
`__eq__`(self, other)
`__ne__`(self, other)
`__lt__`(self, other)	Compare FaceVertexCandidate for sorting.

Inherited from CollisionStencil

`__init__`(args, *kwargs)
`num_vertices`(self)	Get the number of vertices in the collision stencil.
`dim`(self, ndof)	Get the dimension of the collision stencil.
`vertex_ids`(self, edges, faces)	Get the vertex IDs of the collision stencil.
`vertices`(self, vertices, edges, faces)	Get the vertex attributes of the collision stencil.
`dof`(self, X, edges, faces)	Select this stencil's DOF from the full matrix of DOF.
`compute_distance`(args, *kwargs)	Overloaded function.
`compute_distance_gradient`(args, *kwargs)	Overloaded function.
`compute_distance_hessian`(args, *kwargs)	Overloaded function.
`ccd`(self, vertices_t0, 1]], vertices_t1, ...)	Perform narrow-phase CCD on the candidate.
`print_ccd_query`(self, vertices_t0, vertices_t1)	Print the CCD query to cout.

Inherited from pybind11_object

__annotations__ = {}¶

__eq__(self, other: ipctk.FaceVertexCandidate) → bool¶

__hash__ = None¶

__init__(*args, **kwargs)¶

Overloaded function.

__init__(self: ipctk.FaceVertexCandidate, face_id: int, vertex_id: int) -> None
__init__(self: ipctk.FaceVertexCandidate, face_and_vertex_id: tuple[int, int]) -> None

__lt__(self, other: ipctk.FaceVertexCandidate) → bool¶: Compare FaceVertexCandidate for sorting.

__module__ = 'ipctk'¶

__ne__(self, other: ipctk.FaceVertexCandidate) → bool¶

__repr__(self) → str¶

__str__(self) → str¶

property face_id : int¶: ID of the face

known_dtype(self) → ipc::PointTriangleDistanceType¶

property vertex_id : int¶: ID of the vertex