dipy · PyPI

Diffusion MRI Imaging in Python

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Maintainers

arokem garyfallidis matthew.brett skoudoro

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Project description

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DIPY [DIPYREF] is a python library for the analysis of MR diffusion imaging.

DIPY is for research only; please contact admins@dipy.org if you plan to deploy in clinical settings.

Website

Current information can always be found from the DIPY website - http://dipy.org

Mailing Lists

Please see the DIPY community list at https://mail.python.org/mailman3/lists/dipy.python.org/

Please see the users’ forum at https://github.com/dipy/dipy/discussions

Please join the gitter chatroom here.

Code

You can find our sources and single-click downloads:

Main repository on Github.
Documentation for all releases and current development tree.
Download as a tar/zip file the current trunk.

Installing DIPY

DIPY can be installed using pip:

pip install dipy

or using conda:

conda install -c conda-forge dipy

For detailed installation instructions, including instructions for installing from source, please read our installation documentation.

Python versions and dependencies

DIPY follows the Scientific Python SPEC 0 — Minimum Supported Versions recommendation as closely as possible, including the supported Python and dependencies versions.

Further information can be found in Toolchain Roadmap.

License

DIPY is licensed under the terms of the BSD license. Please see the LICENSE file.

Contributing

We welcome contributions from the community. Please read our Contributing guidelines.

Reference

[DIPYREF]

E. Garyfallidis, M. Brett, B. Amirbekian, A. Rokem, S. Van Der Walt, M. Descoteaux, I. Nimmo-Smith and DIPY contributors, “DIPY, a library for the analysis of diffusion MRI data”, Frontiers in Neuroinformatics, vol. 8, p. 8, Frontiers, 2014.

Project details

These details have been verified by PyPI

Maintainers

arokem garyfallidis matthew.brett skoudoro

These details have not been verified by PyPI

Project links

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Release history Release notifications | RSS feed

This version

1.9.0

Mar 8, 2024

1.8.0

Dec 14, 2023

1.7.0

Apr 23, 2023

1.6.0

Jan 16, 2023

1.5.0

Mar 11, 2022

1.4.1

May 6, 2021

1.4.0

Mar 14, 2021

1.3.0

Nov 5, 2020

1.2.0

Sep 8, 2020

1.1.1

Jan 11, 2020

1.1.0

Jan 7, 2020

1.0.0

Aug 6, 2019

0.16.0

Mar 11, 2019

0.15.0

Dec 12, 2018

0.14.0

May 1, 2018

0.13.0

Oct 24, 2017

0.12.0

Jun 27, 2017

0.11.0

Feb 21, 2016

0.10.1

Dec 4, 2015

0.9.2

Mar 18, 2015

0.9.1

Mar 18, 2015

0.9.0

Mar 18, 2015

0.8.0

Jan 6, 2015

0.7.1

Jan 16, 2014

0.7.0

Dec 24, 2013

0.6.0

Mar 30, 2013

0.5.0

Feb 13, 2011

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Hashes for dipy-1.9.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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Hashes for dipy-1.9.0-cp310-cp310-win_amd64.whl
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Hashes for dipy-1.9.0-1-cp310-cp310-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`2e4f6f25455b5600fbfa256120bfe486044585d8d769ac69ce489c47f90f5a54`
MD5	`dbc3835909840e262b553ea6fad048d8`
BLAKE2b-256	`afa97a0f58ca512f70b64bb648e7bcfceed19b45eb115e0cd905cc18c829137c`

Hashes for dipy-1.9.0-1-cp310-cp310-macosx_10_9_x86_64.whl

Hashes for dipy-1.9.0-1-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`4114959d291eea4b79ff0a0044cfb9ea78d584d1ff303e18c9ee08dbf1c2bcbd`
MD5	`e32990edc22f4924b3264c6ccd9a3711`
BLAKE2b-256	`8727c3e6032cbbe3d0d8c8612f09fa93107a066cb651dccc170a92ae964d5330`

Hashes for dipy-1.9.0-1-cp39-cp39-macosx_11_0_arm64.whl

Hashes for dipy-1.9.0-1-cp39-cp39-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`9f1bfdd31ca2e7ff55f99aa80396b84303c354f1c468ba1eb0306a2a504cbc22`
MD5	`80c0e1f5fcae249b555fd573fdebabca`
BLAKE2b-256	`b3eb3149388f74975c4f6ee862638f7c170506718362629f6771e002a3e625dc`

Hashes for dipy-1.9.0-1-cp39-cp39-macosx_10_9_x86_64.whl

Hashes for dipy-1.9.0-1-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`8819ffa79acc79832982ef6adb33bd00dac44e82ee42c51f5a25a5d0e929ec3d`
MD5	`9bc29c238dcd7c123f88d9b1087831aa`
BLAKE2b-256	`af7b12d9a0c545c92df995c7461b258522979e64e98a3b4e514ba16fe9b4a0db`