View page source

warp.fem.AdaptiveNanogrid#

class warp.fem.AdaptiveNanogrid(
cell_grid,
cell_level,
level_count,
temporary_store,
scalar_type=warp.float32,
)[source]#

Adaptive sparse grid.

Parameters:
__init__(
cell_grid,
cell_level,
level_count,
temporary_store,
scalar_type=warp.float32,
)[source]#

Construct an adaptive sparse grid geometry from an in-memory NanoVDB volume and a list of levels.

It is not recommended to use this constructor directly; see the helper functions warp.fem.adaptive_nanogrid_from_field() and warp.fem.adaptive_nanogrid_from_hierarchy().

Parameters:

  • cell_grid (Volume) – A warp volume (ideally backed by an index grid) whose voxels coordinates correspond to the lowest fine-resolution voxel of each cell. The cell’s extent is then given by the cell_level array. For instance, a voxel at coordinates ijk and level 0 corresponds to a fine cell at the same coordinates, a voxel at coordinates 2*ijk and level 1 corresponds to a cell spanning 2^3 voxels from 2*ijk to 2*ijk + (1,1,1), etc.

  • cell_level (array) – Refinement level for each voxel of the volume. Level 0 is the finest, level level_count-1 is the coarsest.

  • level_count (int) – Number of levels in the grid

  • scalar_type (type) – Scalar type for coordinate and weight computations (warp.float32 or warp.float64)

  • temporary_store (TemporaryStore)

Methods

__init__(cell_grid, cell_level, level_count, ...)

Construct an adaptive sparse grid geometry from an in-memory NanoVDB volume and a list of levels.

boundary_side_count()

build_bvh([device])

Rebuild the geometry's Bounding Volume Hierarchy (BVH) for device from scratch.

bvh_id(device)

Return the BVH identifier for the given device, or 0 if unavailable.

cell_arg_value(device)

cell_count()

fill_cell_arg(arg, device)

fill_side_arg(arg, device)

fill_side_index_arg(arg, device)

make_filtered_cell_lookup([filter_func])

reference_cell()

reference_side()

side_arg_value(device)

side_count()

side_deformation_gradient(args, s)

Device function returning the gradient of world position with respect to reference side

side_index_arg_value(device)

side_normal(args, s)

Device function returning the element normal at a sample point

stacked_edge_count()

stacked_face_count()

supports_cell_lookup(device)

update_bvh([device])

Refit the geometry's BVH if it exists on device, or build it from scratch otherwise.

vertex_count()

Attributes

FACE_AXIS_MASK

FACE_INNER_OFFSET_BIT

FACE_OUTER_OFFSET_BIT

GRID_AXIS_FLAG

SideIndexArg

Structure containing arguments to be passed to device functions for indexing sides.

base

Return the base geometry from which this geometry derives its topology.

boundary_side_index

cell_closest_point

cell_coordinates

cell_deformation_gradient

cell_dimension

Manifold dimension of the geometry cells

cell_grid

cell_inverse_deformation_gradient

cell_lookup

Device function for looking up the closest cell to a position.

cell_measure

cell_measure_ratio

cell_normal

cell_position

coarse_ijk

coords_type

Warp vector type for element coordinates matching this geometry's scalar precision.

dimension

Dimension of the embedding space.

encode_axis_and_level

face_grid

find_cell

fine_ijk

name

Name of the geometry, including scalar type suffix for non-default precision.

sample_type

Warp struct type for samples matching this geometry's scalar precision.

scalar_type

side_closest_point

side_coordinates

side_from_cell_coords

side_inner_cell_coords

side_inner_cell_index

side_inner_inverse_deformation_gradient

side_measure

side_measure_ratio

side_outer_cell_coords

side_outer_cell_index

side_outer_inverse_deformation_gradient

side_position

side_to_cell_arg

stacked_edge_grid

stacked_face_grid

transform

Transform matrix mapping index to world space.

vertex_grid

CellArg

Structure containing arguments to be passed to device functions evaluating cell-related quantities.

SideArg

Structure containing arguments to be passed to device functions evaluating side-related quantities.
dimension: int = 3#

Dimension of the embedding space.

property stacked_face_grid: Volume[source]#
stacked_face_count()[source]#
property stacked_edge_grid: Volume[source]#
stacked_edge_count()[source]#
fill_cell_arg(arg, device)[source]#
fill_side_arg(arg, device)[source]#
supports_cell_lookup(device)[source]#
cell_position = <Function AdaptiveNanogrid__cell_position(args: Any, s: Any)>#
Parameters:
cell_deformation_gradient = <Function AdaptiveNanogrid__cell_deformation_gradient(args: Any, s: Any)>#
Parameters:
cell_inverse_deformation_gradient = <Function AdaptiveNanogrid__cell_inverse_deformation_gradient(args: Any, s: Any)>#
Parameters:
cell_measure = <Function AdaptiveNanogrid__cell_measure(args: Any, s: Any)>#
Parameters:
cell_normal = <Function AdaptiveNanogrid__cell_normal(args: Any, s: Any)>#
Parameters:
cell_coordinates = <Function AdaptiveNanogrid__cell_coordinates(args: Any, cell_index: int, pos: Any)>#
Parameters:
cell_closest_point = <Function AdaptiveNanogrid__cell_closest_point(args: Any, cell_index: int, pos: Any)>#
Parameters:
side_position = <Function AdaptiveNanogrid__side_position(args: Any, s: Any)>#
Parameters:
side_inner_inverse_deformation_gradient = <Function AdaptiveNanogrid__side_inner_inverse_deformation_gradient(args: Any, s: Any)>#
Parameters:
side_outer_inverse_deformation_gradient = <Function AdaptiveNanogrid__side_outer_inverse_deformation_gradient(args: Any, s: Any)>#
Parameters:
side_measure = <Function AdaptiveNanogrid__side_measure(args: Any, s: Any)>#
Parameters:
side_measure_ratio = <Function AdaptiveNanogrid__side_measure_ratio(args: Any, s: Any)>#
Parameters:
side_inner_cell_index = <Function AdaptiveNanogrid__side_inner_cell_index(args: Any, side_index: int)>#
Parameters:
side_outer_cell_index = <Function AdaptiveNanogrid__side_outer_cell_index(args: Any, side_index: int)>#
Parameters:
side_inner_cell_coords = <Function AdaptiveNanogrid__side_inner_cell_coords(args: Any, side_index: int, side_coords: Any)>#
Parameters:

  • args (Any)

  • side_index (int)

  • side_coords (Any)

side_outer_cell_coords = <Function AdaptiveNanogrid__side_outer_cell_coords(args: Any, side_index: int, side_coords: Any)>#
Parameters:

  • args (Any)

  • side_index (int)

  • side_coords (Any)

side_from_cell_coords = <Function AdaptiveNanogrid__side_from_cell_coords(args: Any, side_index: int, element_index: int, element_coords: Any)>#
Parameters:

  • args (Any)

  • side_index (int)

  • element_index (int)

  • element_coords (Any)

side_to_cell_arg = <Function AdaptiveNanogrid__side_to_cell_arg(side_arg: Any)>#
Parameters:

side_arg (Any)

side_coordinates = <Function AdaptiveNanogrid__side_coordinates(args: Any, side_index: int, pos: Any)>#
Parameters:
side_closest_point = <Function AdaptiveNanogrid__side_closest_point(args: Any, side_index: int, pos: Any)>#
Parameters:
coarse_ijk = <Function AdaptiveNanogrid__coarse_ijk(ijk: vec3i, level: int)>#
Parameters:
fine_ijk = <Function AdaptiveNanogrid__fine_ijk(ijk: vec3i, level: int)>#
Parameters:
encode_axis_and_level = <Function AdaptiveNanogrid__encode_axis_and_level(ijk: vec3i, axis: int, level: int)>#
Parameters:
find_cell = <Function AdaptiveNanogrid__find_cell(cell_grid: uint64, ijk: vec3i, level_count: int, cell_level: array(ndim=1, dtype=uint8))>#
Parameters: