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warp.volume_sample_index#

warp.volume_sample_index(
id: uint64,
uvw: vec3f,
sampling_mode: int32,
voxel_data: Array[Any],
background: Any,
) → Any#

  • Kernel

  • Differentiable

Sample the volume given by id at the index-space point uvw, reading voxel values from a separate voxel_data array.

On NanoVDB OnIndex and OnIndexMask grids, each active voxel maps to a linear index into voxel_data and background supplies inactive voxels. On Index and IndexMask grids and on classical value grids, every slot in an allocated leaf maps to voxel_data regardless of its active mask; background is used outside allocated leaves. This lets several fields share one topology. See warp.Volume.allocate_by_voxels() and volume_lookup_index().

uvw is in index space (voxel coordinates) and may be fractional. Sampling modes and boundary conventions match volume_sample(); use CLOSEST for integer data. For floating-point scalar and vector data, LINEAR is differentiable with respect to uvw, voxel_data, and background. See the Volume sampling user-guide examples.

Parameters:

  • id – The id of a warp.Volume providing the topology and voxel indices.

  • uvw – Sampling location in index space (voxel coordinates); may be fractional.

  • sampling_mode – warp.Volume.CLOSEST or warp.Volume.LINEAR; use CLOSEST for integer data.

  • voxel_data – Per-voxel values indexed by each voxel’s linear index. For volumes whose indexable count fits in int32, must hold at least volume_voxel_count() entries. warp.Volume.get_voxel_count() returns a host-side capacity that is safe for allocation but may exceed the live indexable count for rebuildable volumes. The array’s dtype must match background.

  • background – Value used for inactive voxels on OnIndex and OnIndexMask grids and outside allocated leaves on Index and IndexMask grids and classical value grids; its dtype must match voxel_data.

Returns:

The sampled value, of the same dtype as voxel_data.

Example

@wp.kernel
def fill(vid: wp.uint64, d: wp.array[wp.float32]):
    i, j, k = wp.tid()
    idx = wp.volume_lookup_index(vid, i, j, k)
    if idx >= 0:
        d[idx] = wp.float32(i) * 10.0

@wp.kernel
def sample(vid: wp.uint64, d: wp.array[wp.float32], out: wp.array[wp.float32]):
    out[0] = wp.volume_sample_index(vid, wp.vec3(0.5, 0.0, 0.0), wp.Volume.LINEAR, d, 0.0)

voxels = wp.array([[0, 0, 0], [1, 0, 0]], dtype=wp.vec3i)
volume = wp.Volume.allocate_by_voxels(voxels, voxel_size=1.0)
data = wp.zeros(volume.get_voxel_count(), dtype=wp.float32)
out = wp.zeros(1, dtype=wp.float32)
wp.launch(fill, dim=(2, 1, 1), inputs=[volume.id, data])
wp.launch(sample, dim=1, inputs=[volume.id, data], outputs=[out])
print(round(float(out.numpy()[0]), 1))

5.0