calc_skeleton_mesh_intersect - jaybgager/tracertools GitHub Wiki

This function calculates all the points at which a skeleton intersects a mesh. The point coordinates for bones and mesh triangles must be in the same voxel resolution.

Arguments:

  • bones ((n,2,3)-shape numpy array of floats, mandatory)
    • an array of pairs of point coordinates that define the edges ("bones") of the skeleton
  • mesh_triangles ((n,3,3)-shape numpy array of floats)
    • an array of trios of point coordinates for the vertices of the triangles of the mesh

Returns:

  • intersections (varies, see description)
    • a list of the intersection points between the skeleton and the mesh as a (3)-shape numpy arrays of floats if any were found
    • if no intersections were found, returns None instead

Example

Since this code requires a skeleton's bones and a mesh's triangles, here's an example of how you could get those using other tracertools functions.

INPUT:

import tracertools as tt

# this part gets the skeleton for a given segment
skel = tt.get_seg_skeletons(
    datastack = "brain_and_nerve_cord",
    seg_ids = [720575941526718564],
)[0]

# this part gets the list of individual skeleton edges, or "bones", from the skeleton
bone_list = tt.get_bones(
    datastack = "brain_and_nerve_cord", 
    skeleton = skel,
)

# this part gets a list of all the mesh's faces, or "triangles"
triangles = tt.get_mesh_triangles(
    volume_path = "https://c10s.pni.princeton.edu/tracers/examples/banc_mesh_01|neuroglancer-precomputed:"
)

Now that you have a list of bones and triangles, you can use the following code to check if any of the bones intersect any of the triangles:

INPUT:

intersections = tt.calc_skeleton_mesh_intersect(
    bones = bone_list, 
    mesh_triangles = triangles,
)

print(intersections)

OUTPUT:

[array([121305., 181906.,   4627.]),
 array([123200., 172384.,   4720.]),
 array([124027., 174945.,   5243.]),
 array([124240., 176101.,   5346.]),
 array([123934., 175092.,   5244.]),
 array([127158., 175525.,   4693.]),
 array([125175., 175250.,   5344.]),
 array([125127., 174504.,   5263.]),
 array([125315., 175057.,   5311.]),
 array([122142., 175971.,   4855.])]

[!NOTE] This function uses the Numba Python package to bypass the Python interpreter and compile directly to machine code using the JIT compiler to dramatically speed up the calculation time for segments/meshes with large numbers of bones/faces. Although no issues with this have yet been encountered, there are anecdotal reports online of occasional memory leakage with Numba. If you encounter this, please let us know by submitting an Issue.