A library of musculoskeletal modelling tools.
Project description
A Python library for tools used in musculoskeletal modelling. Includes tools for parametric meshing, registration, image analysis, statistical shape modelling, and 3-D visualisation using Mayavi.
Optional dependencies
VTK and VTK Python bindings (for mesh processing)
Mayavi (for 3-D visualisation, requires Numpy, VTK, wxPython, configobj)
PyCSG (for generating constructive solids)
pydicom (for reading DICOM images)
Cython (speeds up active shape model and random forest segmentation)
matplotlib for some inbuilt plotting functions
Installation
Linux
If you would like to use in-built visualisation modules, first install Mayavi for you distribution, else you can skip this step.
Install VTK and VTK python bindings (e.g. through your package manager). VTK 5.10 is the most stable in my experience with Mayavi.
Install mayavi through your package manager (e.g. sudo apt-get install mayavi2) or pip (e.g. pip install –user mayavi)
Download the wheel and
pip install --user [path/to/wheel]
Windows
The most painless way to install the python dependencies required by GIAS2 is to install the umbrella package Anaconda.
If you would like to use in-built visualisation modules, install Mayavi. In you installed Anaconda, from the Anaconda commandline,
conda install mayavi
Download the wheel and from the Anaconda commandline
pip install --user [path/to/wheel]
Examples
Example of some the capabilities of GIAS2 can be found in the gias2/examples/ directory. We are working to add more examples.
Tutorials
License
GIAS2 is under the Mozilla Public license 2.0.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
File details
Details for the file gias2-0.7.14-py3-none-any.whl
.
File metadata
- Download URL: gias2-0.7.14-py3-none-any.whl
- Upload date:
- Size: 7.5 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c02db804f05f6bcd79c7dea3cc80c7315b4754657b836881e42686bd1a0be622 |
|
MD5 | 02b40e2b9283bbf5401af400be918a68 |
|
BLAKE2b-256 | 75983f4a010db5e69ed3c4ec7f6177056930f25c088ff8d63a0345ffaa567b6b |