warp.bvh_query_next#

warp.bvh_query_next(
query: _BvhQueryAabb,
index: int32,
max_dist: float32,
) → bool#

  • Kernel

Advance a BVH query to the next overlapping item and report whether one was found.

Writes the index of the current item to index and returns True; returns False once the query is exhausted (index is then left unchanged). The reported index is the item’s index into the lowers/uppers arrays passed to warp.Bvh. Used in a while loop together with bvh_query_aabb(), bvh_query_ray(), bvh_query_capsule(), or bvh_query_sphere().

For plain ray queries (bvh_query_ray()), max_dist bounds how far along the ray to look for intersections, measured in multiples of dir’s length (so it is a distance only if dir was normalized). For capsule queries (bvh_query_capsule()), pass dir = p1 - p0 (unnormalized) together with max_dist = 1.0 to sweep from p0 to p1. max_dist has no effect on AABB or sphere queries.

Note that increasing max_dist may miss intersections: a subtree already rejected for being beyond max_dist is never revisited, even if a later, larger max_dist would reach it. It is therefore only safe to monotonically reduce max_dist during a query.

Parameters:

  • query – The query to advance, from bvh_query_aabb(), bvh_query_ray(), bvh_query_capsule(), or bvh_query_sphere()

  • index – Output; receives the index of the current overlapping item

  • max_dist – For ray queries, the maximum distance along the ray to check for intersections (in multiples of dir’s length). Has no effect on AABB or sphere queries.

Returns:

True if another overlapping item was found (its index written to index), False if the query is exhausted.

Example

@wp.kernel
def query_region(bvh_id: wp.uint64, lowers: wp.array[wp.vec3], uppers: wp.array[wp.vec3],
                 lo: wp.vec3, hi: wp.vec3, centers: wp.array[wp.vec3]):
    query = wp.bvh_query_aabb(bvh_id, lo, hi)
    item = int(0)
    while wp.bvh_query_next(query, item):
        centers[item] = 0.5 * (lowers[item] + uppers[item])

lowers = wp.array([[0, 0, 0], [2, 0, 0], [4, 0, 0]], dtype=wp.vec3)
uppers = wp.array([[1, 1, 1], [3, 1, 1], [5, 1, 1]], dtype=wp.vec3)
bvh = wp.Bvh(lowers=lowers, uppers=uppers)

centers = wp.zeros(3, dtype=wp.vec3)  # center of each object whose box overlaps the region
wp.launch(query_region, dim=1, inputs=[bvh.id, lowers, uppers, wp.vec3(0.5, 0.5, 0.5), wp.vec3(2.5, 0.5, 0.5)], outputs=[centers])
print(centers.numpy().tolist())

[[0.5, 0.5, 0.5], [2.5, 0.5, 0.5], [0.0, 0.0, 0.0]]
warp.bvh_query_next(
query: _BvhQueryRay,
index: int32,
max_dist: float32,
) → bool

  • Kernel

Advance a bvh_query_ray() query to the next intersected item.

warp.bvh_query_next(
query: _BvhQueryCapsule,
index: int32,
max_dist: float32,
) → bool

  • Kernel

Advance a bvh_query_capsule() query to the next intersected item.

warp.bvh_query_next(
query: _BvhQuerySphere,
index: int32,
max_dist: float32,
) → bool

  • Kernel

Advance a bvh_query_sphere() query to the next intersected item.

warp.bvh_query_next(
query: BvhQuery,
index: int32,
max_dist: float32,
) → bool

  • Kernel

Advance a BVH query whose kind is selected at runtime to the next overlapping item.