| Name | meshparty JSON |
| Version |
2.0.3
JSON |
| download |
| home_page | None |
| Summary | a service to work with meshes |
| upload_time | 2025-07-10 18:36:17 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | MIT |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
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| coveralls test coverage |
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.. image:: https://readthedocs.org/projects/meshparty/badge/?version=latest
:target: https://meshparty.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: https://travis-ci.com/sdorkenw/MeshParty.svg?branch=master
:target: https://travis-ci.com/sdorkenw/MeshParty
.. image:: https://codecov.io/gh/sdorkenw/MeshParty/branch/master/graph/badge.svg
:target: https://codecov.io/gh/sdorkenw/MeshParty
.. image:: https://zenodo.org/badge/148393516.svg
:target: https://zenodo.org/badge/latestdoi/148393516
MeshParty
#########
A package to work with meshes, designed around use cases for analyzing neuronal morphology.
documentation https://meshparty.readthedocs.io/
############
From pypi:
::
pip install meshparty
Note: Version 2.0.0 or higher requires Python 3.10 or higher and offers reduced features for mesh analysis and visualization.
Projects like pyvista are now easier and more powerful for work that was previously done in MeshParty.
This package is still intended to be used for the Skeleton and MeshWork classes, but with reduced support for mesh analysis.
To install the git version do:
::
git clone https://github.com/sdorkenw/MeshParty.git
cd MeshParty
pip install . --upgrade
to make optional features of ray tracing and interaction with the PyChunkedGraph work properly you need to install the optional dependencies
::
conda install pyembree
pip install caveclient
Usage example
#################
::
from meshparty import trimesh_io
meshmeta = trimesh_io.MeshMeta()
mesh = meshmeta.mesh(path_to_mesh) # mesh gets cached
local_vertices = mesh.get_local_view(n_points, pc_align=True, method="kdtree")
Downloading meshes
##################
Meshes can be downloaded in parallel using
::
trimesh_io.download_meshes(seg_ids, target_dir, cv_path)
where `cv_path` points to the cloudvolume bucket. For downloading proofread meshes one needs to
specify the `mesh_endpoint` of the chunkedgraph server:
::
trimesh_io.download_meshes(seg_ids, target_dir, cv_path, mesh_endpoint="https://...")
Extracting mesh information
###########################
The mesh needs to be `watertight` In order to compute reliable information. To
test whether a mesh is watertight, run
::
mesh.is_watertight
Since trimesh_io.Mesh() inherits from trimesh.Trimesh all trimesh functionality
is available to mesh, e.g.:
::
mesh.volume
mesh.area
mesh.center_mass
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"description": ".. image:: https://readthedocs.org/projects/meshparty/badge/?version=latest\n :target: https://meshparty.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n.. image:: https://travis-ci.com/sdorkenw/MeshParty.svg?branch=master\n :target: https://travis-ci.com/sdorkenw/MeshParty\n.. image:: https://codecov.io/gh/sdorkenw/MeshParty/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/sdorkenw/MeshParty\n.. image:: https://zenodo.org/badge/148393516.svg\n :target: https://zenodo.org/badge/latestdoi/148393516\n \nMeshParty\n#########\nA package to work with meshes, designed around use cases for analyzing neuronal morphology.\n\ndocumentation https://meshparty.readthedocs.io/\n \n############\n\nFrom pypi:\n::\n\n pip install meshparty\n\nNote: Version 2.0.0 or higher requires Python 3.10 or higher and offers reduced features for mesh analysis and visualization.\nProjects like pyvista are now easier and more powerful for work that was previously done in MeshParty.\nThis package is still intended to be used for the Skeleton and MeshWork classes, but with reduced support for mesh analysis.\n\n\nTo install the git version do:\n\n:: \n\n git clone https://github.com/sdorkenw/MeshParty.git\n cd MeshParty\n pip install . --upgrade\n\n\nto make optional features of ray tracing and interaction with the PyChunkedGraph work properly you need to install the optional dependencies\n\n::\n\n conda install pyembree\n pip install caveclient\n \n\n\nUsage example\n#################\n\n::\n\n from meshparty import trimesh_io\n\n meshmeta = trimesh_io.MeshMeta()\n mesh = meshmeta.mesh(path_to_mesh) # mesh gets cached\n\n local_vertices = mesh.get_local_view(n_points, pc_align=True, method=\"kdtree\")\n\n\nDownloading meshes\n##################\n\nMeshes can be downloaded in parallel using \n\n::\n\n trimesh_io.download_meshes(seg_ids, target_dir, cv_path)\n\n\nwhere `cv_path` points to the cloudvolume bucket. For downloading proofread meshes one needs to \nspecify the `mesh_endpoint` of the chunkedgraph server:\n\n::\n\n trimesh_io.download_meshes(seg_ids, target_dir, cv_path, mesh_endpoint=\"https://...\")\n\n\n\nExtracting mesh information\n###########################\n\nThe mesh needs to be `watertight` In order to compute reliable information. To\ntest whether a mesh is watertight, run\n\n::\n\n mesh.is_watertight\n\n\n\nSince trimesh_io.Mesh() inherits from trimesh.Trimesh all trimesh functionality \nis available to mesh, e.g.:\n::\n\n mesh.volume\n mesh.area\n mesh.center_mass\n\n",
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