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slam

Surface anaLysis And Modeling

Build Status Coverage Status

slam is a pure Python library for analysing and modeling surfaces represented as a triangular mesh. It is an extension of Trimesh, which is an open source python module dedicated to general mesh processing: https://github.com/mikedh/trimesh

The present module will consist of extensions to adapt Trimesh for the purpose of surface analysis of brain MRI data.

Installation:

  1. install the lastest version of trimesh in easy (minimal dependency) mode:

    pip install trimesh[easy]

  2. install pyglet:

    conda install -c conda-forge pyglet

  3. install nibabel

    pip install nibabel

  4. install matplotlib

    conda install matplotlib

  5. install gdist

    pip install cython
pip install gdist

  6. clone the current repo

  7. try example scripts located in examples folder

Features (added value compared to Trimesh):

. io: read/write gifti (and nifti) file format

. generate_parametric_surfaces: generation of parametric surfaces with random sampling

. geodesics: geodesic distance computation using gdist and networkx

. differential_geometry: several implementations of graph Laplacian (conformal, authalic, FEM...)

. mapping: several types of mapping between the mesh and a sphere, a disc...

. distortion: distortion measures between two meshes, for quantitative analysis of mapping properties

. remeshing: projection of vertex-level information between two meshes based on their spherical representation

. topology: mesh surgery (boundary indentification, hole closing will be added in the future)

. vertex_voronoi: compute the voronoi of each vertex of a mesh, usefull for numerous applications

. texture: a class to manage properly vertex-level information.

. plot: extension of Trimesh's pyglet viewer to visualize textures with colorbar.

For contributors:

  1. intall flake8 and autopep8

    pip install -U autopep8 flake8

  2. install pytest

    pip install -U pytest