warp.fem.AdaptiveNanogrid#

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

Adaptive sparse grid.

Parameters:

cell_grid (Volume)
cell_level (array)
level_count (int)
temporary_store (TemporaryStore)

__init__( cell_grid, cell_level, level_count, temporary_store, )[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
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`()	Number of boundary sides in the grid.
`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`()	Number of cells in the grid.
`fill_cell_arg`(arg, device)	Fill the arguments to be passed to cell-related device functions.
`fill_side_arg`(arg, device)	Fill the arguments to be passed to side-related device functions.
`fill_side_index_arg`(arg, device)	Fill the arguments to be passed to side-index device functions.
`make_filtered_cell_lookup`([filter_func])	Create a filtered cell lookup function.
`reference_cell`()	Reference element for grid cells.
`reference_side`()	Reference element for grid sides.
`side_arg_value`(device)
`side_count`()	Number of sides in the grid.
`side_index_arg_value`(device)
`stacked_edge_count`()	Number of stacked edges in the grid.
`stacked_face_count`()	Number of stacked faces in the grid.
`supports_cell_lookup`(device)	Return whether cell lookups are supported on the given device.
`update_bvh`([device])	Refit the geometry's BVH if it exists on `device`, or build it from scratch otherwise.
`vertex_count`()	Number of vertices in the grid.

Attributes

`CellArg`	Structure containing arguments to be passed to device functions evaluating cell-related quantities.
`FACE_AXIS_MASK`
`FACE_INNER_OFFSET_BIT`
`FACE_OUTER_OFFSET_BIT`
`GRID_AXIS_FLAG`
`SideArg`	Structure containing arguments to be passed to device functions evaluating side-related quantities.
`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`	NanoVDB volume storing cell voxels.
`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`
`dimension`
`encode_axis_and_level`
`face_grid`	NanoVDB volume storing face voxels.
`find_cell`
`fine_ijk`
`name`	Name of the geometry.
`side_closest_point`
`side_coordinates`
`side_deformation_gradient`
`side_from_cell_coords`
`side_inner_cell_coords`
`side_inner_cell_index`
`side_inner_inverse_deformation_gradient`
`side_measure`
`side_measure_ratio`
`side_normal`
`side_outer_cell_coords`
`side_outer_cell_index`
`side_outer_inverse_deformation_gradient`
`side_position`
`side_to_cell_arg`
`stacked_edge_grid`	NanoVDB volume storing stacked edge voxels.
`stacked_face_grid`	NanoVDB volume storing stacked face voxels.
`transform`	Transform matrix mapping index to world space.
`vertex_grid`	NanoVDB volume storing vertex voxels.

dimension: int = 3#

property stacked_face_grid: Volume[source]#: NanoVDB volume storing stacked face voxels.

stacked_face_count()[source]#: Number of stacked faces in the grid.

property stacked_edge_grid: Volume[source]#: NanoVDB volume storing stacked edge voxels.

stacked_edge_count()[source]#: Number of stacked edges in the grid.

CellArg: Struct = <warp._src.codegen.Struct object>#: Structure containing arguments to be passed to device functions evaluating cell-related quantities.

fill_cell_arg(arg, device)[source]#

Fill the arguments to be passed to cell-related device functions.

Parameters:: arg (AdaptiveNanogridCellArg)

cell_position = <Function AdaptiveNanogrid__cell_position(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridCellArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridCellArg)
s (Sample)

cell_deformation_gradient = <Function AdaptiveNanogrid__cell_deformation_gradient(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridCellArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridCellArg)
s (Sample)

cell_inverse_deformation_gradient = <Function AdaptiveNanogrid__cell_inverse_deformation_gradient(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridCellArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridCellArg)
s (Sample)

supports_cell_lookup(device)[source]#: Return whether cell lookups are supported on the given device.

cell_coordinates = <Function AdaptiveNanogrid__cell_coordinates(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridCellArg, cell_index: int, pos: vec3f)>#

Parameters:

args (AdaptiveNanogridCellArg)
cell_index (int)
pos (vec3f)

cell_closest_point = <Function AdaptiveNanogrid__cell_closest_point(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridCellArg, cell_index: int, pos: vec3f)>#

Parameters:

args (AdaptiveNanogridCellArg)
cell_index (int)
pos (vec3f)

cell_measure = <Function AdaptiveNanogrid__cell_measure(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridCellArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridCellArg)
s (Sample)

cell_normal = <Function AdaptiveNanogrid__cell_normal(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridCellArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridCellArg)
s (Sample)

SideArg: Struct = <warp._src.codegen.Struct object>#: Structure containing arguments to be passed to device functions evaluating side-related quantities.

side_to_cell_arg = <Function AdaptiveNanogrid__side_to_cell_arg(side_arg: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg)>#

Parameters:: side_arg (AdaptiveNanogridSideArg)

fill_side_arg(arg, device)[source]#

Fill the arguments to be passed to side-related device functions.

Parameters:: arg (AdaptiveNanogridSideArg)

side_position = <Function AdaptiveNanogrid__side_position(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridSideArg)
s (Sample)

side_deformation_gradient = <Function AdaptiveNanogrid__side_deformation_gradient(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridSideArg)
s (Sample)

side_inner_inverse_deformation_gradient = <Function AdaptiveNanogrid__side_inner_inverse_deformation_gradient(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridSideArg)
s (Sample)

side_outer_inverse_deformation_gradient = <Function AdaptiveNanogrid__side_outer_inverse_deformation_gradient(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridSideArg)
s (Sample)

side_measure = <Function AdaptiveNanogrid__side_measure(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridSideArg)
s (Sample)

side_measure_ratio = <Function AdaptiveNanogrid__side_measure_ratio(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridSideArg)
s (Sample)

side_normal = <Function AdaptiveNanogrid__side_normal(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, s: warp._src.fem.types.Sample)>#

Parameters:

args (AdaptiveNanogridSideArg)
s (Sample)

side_inner_cell_index = <Function AdaptiveNanogrid__side_inner_cell_index(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, side_index: int)>#

Parameters:

args (AdaptiveNanogridSideArg)
side_index (int)

side_outer_cell_index = <Function AdaptiveNanogrid__side_outer_cell_index(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, side_index: int)>#

Parameters:

args (AdaptiveNanogridSideArg)
side_index (int)

side_inner_cell_coords = <Function AdaptiveNanogrid__side_inner_cell_coords(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, side_index: int, side_coords: vec3f)>#

Parameters:

args (AdaptiveNanogridSideArg)
side_index (int)
side_coords (vec3f)

side_outer_cell_coords = <Function AdaptiveNanogrid__side_outer_cell_coords(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, side_index: int, side_coords: vec3f)>#

Parameters:

args (AdaptiveNanogridSideArg)
side_index (int)
side_coords (vec3f)

side_from_cell_coords = <Function AdaptiveNanogrid__side_from_cell_coords(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, side_index: int, element_index: int, element_coords: vec3f)>#

Parameters:

args (AdaptiveNanogridSideArg)
side_index (int)
element_index (int)
element_coords (vec3f)

side_coordinates = <Function AdaptiveNanogrid__side_coordinates(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, side_index: int, pos: vec3f)>#

Parameters:

args (AdaptiveNanogridSideArg)
side_index (int)
pos (vec3f)

side_closest_point = <Function AdaptiveNanogrid__side_closest_point(args: warp._src.fem.geometry.adaptive_nanogrid.AdaptiveNanogridSideArg, side_index: int, pos: vec3f)>#

Parameters:

args (AdaptiveNanogridSideArg)
side_index (int)
pos (vec3f)

coarse_ijk = <Function AdaptiveNanogrid__coarse_ijk(ijk: vec3i, level: int)>#

Parameters:

ijk (vec3i)
level (int)

fine_ijk = <Function AdaptiveNanogrid__fine_ijk(ijk: vec3i, level: int)>#

Parameters:

ijk (vec3i)
level (int)

encode_axis_and_level = <Function AdaptiveNanogrid__encode_axis_and_level(ijk: vec3i, axis: int, level: int)>#

Parameters:

ijk (vec3i)
axis (int)
level (int)

find_cell = <Function AdaptiveNanogrid__find_cell(cell_grid: uint64, ijk: vec3i, level_count: int, cell_level: array(ndim=1, dtype=uint8))>#

Parameters:

cell_grid (uint64)
ijk (vec3i)
level_count (int)
cell_level (array(ndim=1, dtype=uint8))