Skip to main content

Scilpy: diffusion MRI tools and utilities

Project description

Scilpy

GitHub release (latest by date) codecov Documentation Status

PyPI version badge PyPI - Downloads

Docker container badge

Scilpy is the main library supporting research and development at the Sherbrooke Connectivity Imaging Lab (SCIL).

Scilpy mainly comprises tools and utilities to quickly work with diffusion MRI. Most of the tools are based on or are wrappers of the DIPY library, and most of them will eventually be migrated to DIPY. Those tools implement the recommended workflows and parameters used in the lab.

The library is now built for Python 3.12 so be sure to create a virtual environnement for Python 3.12. If this version is not installed on your computer:

sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt-get install python3.12 python3.12-dev python3.12-venv python3.12-tk

:warning: We highly suggest to install uv to speedup scilpy installation: https://docs.astral.sh/uv/getting-started/installation/

:point_up: BUT, if you don't want to use uv, scilpy can still be installed by omitting the uv from all the installation command lines below.

Make sure your pip is up-to-date before trying to install:

uv pip install --upgrade pip

The library's structure is mostly aligned on that of DIPY.

We highly encourage to install scilpy in a virtual environnement. Once done and you're in your virtual environnement, the library and scripts can be installed locally by running these commands:

Install scilpy as a user

# If you are using Python3.10 or Python3.11, export this variable before installing
export SETUPTOOLS_USE_DISTUTILS=stdlib

uv pip install scilpy # For the most recent release from PyPi

Install scilpy as a developer

# If you are using Python3.10 or Python3.11, export this variable before installing
export SETUPTOOLS_USE_DISTUTILS=stdlib

uv pip install -e . # Install from source code (for development)

EXTRAS

On Linux, most likely you will have to install libraries for COMMIT/AMICO

sudo apt install libblas-dev liblapack-dev

While on MacOS you will have to use (most likely)

brew install openblas lapack

On Ubuntu >=20.04, you will have to install libraries for matplotlib

sudo apt install libfreetype6-dev

Note that using this technique will make it harder to remove the scripts when changing versions. We highly recommend working in a Python Virtual Environment.

Scilpy documentation is available: https://scilpy.readthedocs.io/en/latest/

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scilpy-2.2.1.tar.gz (79.6 MB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

scilpy-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.7 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

scilpy-2.2.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.6 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

File details

Details for the file scilpy-2.2.1.tar.gz.

File metadata

  • Download URL: scilpy-2.2.1.tar.gz
  • Upload date:
  • Size: 79.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for scilpy-2.2.1.tar.gz
Algorithm Hash digest
SHA256 bb046fafe166737ff00d52bd73ffa513e22a50ff65cd2b1fa6d9a2c69afc9ef4
MD5 66d67b654b8aa6b7fb2faa13e146f5b3
BLAKE2b-256 8300cb2811422d7e1a087053611dba868fed6e7ff82ddc4c4fff5d54ed87ecb6

See more details on using hashes here.

File details

Details for the file scilpy-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for scilpy-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 55cbe64dfde769b7a60dfff1a5a0cd2063e763ff76d0936ce813208833acf0f2
MD5 42bd7105fad9f4235c117c56b1afe555
BLAKE2b-256 5ad227b97f6b4ede325d403c906060decde90081cb7be584d975355f3bb5e0fc

See more details on using hashes here.

File details

Details for the file scilpy-2.2.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for scilpy-2.2.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d60f11f0347dd09f59715fe45089d2cff5e15acf6d4f2a9f59a07ffe4ab6428e
MD5 d28501dfa67d0b6002b7f27b880b3d46
BLAKE2b-256 cb4b72e07672a10fe46e5f5984b0f4822af4874ad364c2485553f8c0f1e5f1a7

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page