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get_mesh_triangles

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jaybgager edited this page Sep 30, 2026 · 1 revision

Gets a numpy array of point coordinates for the vertices of each face of a single-resolution legacy-format mesh in a neuroglancer volume. If the volume is bucket-hosted (the default assumption), it requires read access set up through cloudvolume.

Arguments:

  • volume_path (string, mandatory)
    • the absolute path to the directory of the volume that contains the mesh
    • the last directory should be the top-level folder of the volume
    • e.g. /home/username/ng_meshes/image01 would get the image01 volume in the ng_meshes folder
  • mesh_seg_id (int, optional, default=1)
    • the segment ID of the mesh within the neuroglancer volume
  • local (bool, optional, default=False)
    • if set to True, treats volume_path as a file path on your local machine
    • by default, assumes the volume_path is a bucket-hosted file

Returns:

  • triangles ((n,3,3)-shape numpy array of floats)
    • the point coordinates of the face vertices for each triangle

Example

The example below gets the faces of a mesh with a segment ID 1 in a volume called banc_mesh_01 on a remote bucket.

INPUT:

import tracertools as tt

triangles = tt.get_mesh_triangles(
    volume_path = "https://c10s.pni.princeton.edu/tracers/examples/banc_mesh_01|neuroglancer-precomputed:",
)

print(triangles)

OUTPUT (truncated for space):

[
    [
        [108968.75       178911.5          4687.48888889]
        [113279.75       179077.25         4747.48888889]
        [109466.25       180402.75         4687.48888889]
    ],
    ...
    [
        [139306.         182083.25         4317.48888889]
        [139389.         183077.5          4317.48888889]
        [136902.         183740.25         4427.48888889]
    ]
]

Note

Although point coordinates are often stored as integers in most contexts, meshes (particularly those that were programmatically generated) often store them as floats to maintain accuracy.

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