Statistical learning for neuroimaging in Python
Project description
nilearn
Nilearn is a Python module for fast and easy statistical learning on NeuroImaging data.
It leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis.
This work is made available by a community of people, amongst which the INRIA Parietal Project Team and the scikit-learn folks, in particular P. Gervais, A. Abraham, V. Michel, A. Gramfort, G. Varoquaux, F. Pedregosa, B. Thirion, M. Eickenberg, C. F. Gorgolewski, D. Bzdok, L. Esteve and B. Cipollini.
Important links
Official source code repo: https://github.com/nilearn/nilearn/
HTML documentation (stable release): http://nilearn.github.io/
Dependencies
The required dependencies to use the software are:
Python >= 3.5,
setuptools
Numpy >= 1.11
SciPy >= 0.19
Scikit-learn >= 0.19
Joblib >= 0.11
Nibabel >= 2.0.2
If you are using nilearn plotting functionalities or running the examples, matplotlib >= 1.5.1 is required.
If you want to run the tests, you need pytest >= 3.9 and pytest-cov for coverage reporting.
Install
First make sure you have installed all the dependencies listed above. Then you can install nilearn by running the following command in a command prompt:
pip install -U --user nilearn
More detailed instructions are available at http://nilearn.github.io/introduction.html#installation.
Development
Detailed instructions on how to contribute are available at http://nilearn.github.io/contributing.html
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 Distribution
Built Distribution
File details
Details for the file nilearn-0.6.1.tar.gz
.
File metadata
- Download URL: nilearn-0.6.1.tar.gz
- Upload date:
- Size: 2.4 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/44.0.0.post20200106 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | e18f029e915232450e6d3574a2253d8b6cb2d7bbea521118854a1e2ea67c8242 |
|
MD5 | 396c2defd0dca0bd6d74233ca5a55d33 |
|
BLAKE2b-256 | 2ca6b9b4eea0848c1f67340181732ed237df974d2e0c59cd834284a91f61f307 |
File details
Details for the file nilearn-0.6.1-py3-none-any.whl
.
File metadata
- Download URL: nilearn-0.6.1-py3-none-any.whl
- Upload date:
- Size: 2.5 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/44.0.0.post20200106 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 52e18df737b8e3cfaddd91946190f4f881c8ca38dcb83f3d7b0f3014381c3f12 |
|
MD5 | 37395e7c3271dd83fe831e5dadbe458c |
|
BLAKE2b-256 | 8a33ff38efcb7e41131f093f483f44c477fbaebc43c5445379fefc272a0a97b5 |