I was unaware of this package, and had to look it up. It's my opinion that his package is only relevant to a likely small subset of users engaged in computational neuroanatomy. I am not sure updates really belong on this list...

Andrew

<~~~~~~~~~~~~~~~~~~~~~~~~~~~>
J. Andrew Howe, PhD
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I live to learn, so I can learn to live. - me
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On Sat, Jan 18, 2020 at 1:12 PM Joel Nothman <joel.nothman@gmail.com> wrote:
If the Scikit-learn mailing list is going to include announcements of related package releases, could we please get a line or two describing that package? I expect most readers here don't know of DIPY, or of its relevance to Scikit-learn users. (I'm still not sure why it's generally relevant to scikit-learn users.)

Thanks

On Fri, 17 Jan 2020 at 04:04, Eleftherios Garyfallidis <garyfallidis@gmail.com> wrote:

We are excited to announce a new release of DIPY:


DIPY 1.1.1 is out! In addition:


a) A new 5 day workshop available during March 16-20 to learn the theory and applications of the hundreds of methods available in DIPY 1.1.1  Intense!

See the exquisite program here.


b) Given the need for a myriad of new DIPY derivative projects, DIPY moved to its own organization in GitHub. Long live DIPY! 
And therefore, https://github.com/dipy/dipy supersedes https://github.com/nipy/dipy The old link will be available as a redirect link for the next 6 months.

c) Please support us by citing DIPY in your papers using the following DOI: 10.3389/fninf.2014.00008 otherwise the DIPY citation police will find you. ;) 


DIPY 1.1.1 (Friday, 10 January 2020)

This release received contributions from 11 developers (the full release notes are at: https://dipy.org/documentation/1.1.1./release_notes/release1.1/). Thank you all for your contributions and feedback!


Please click here to check API changes. 


Highlights of this release include:

  • New module for deep learning DIPY.NN (uses TensorFlow 2.0).

  • Improved DKI performance and increased utilities.

  • Non-linear and RESTORE fits from DTI compatible now with DKI.

  • Numerical solutions for estimating axial, radial and mean kurtosis.

  • Added Kurtosis Fractional Anisotropy by Glenn et al. 2015.

  • Added Mean Kurtosis Tensor by Hansen et al. 2013.

  • Nibabel minimum version is 3.0.0.

  • Azure CI added and Appveyor CI removed.

  • New command line interfaces for LPCA, MPPCA and Gibbs Unringing.

  • New MTMS CSD tutorial added.

  • Horizon refactored and updated to support StatefulTractograms.

  • Speeded up all cython modules by using a smarter configuration setting.

  • All tutorials updated to API changes and 2 new tutorials added.

  • Large documentation update.

  • Closed 126 issues and merged 50 pull requests.

Note:

  • Have in mind that DIPY stopped supporting Python 2 after version 0.16.0. All major Python projects have switched to Python 3. It is time that you switch too. 



To upgrade or install DIPY


Run the following command in your terminal: 


pip install --upgrade dipy


or


conda install -c conda-forge dipy


This version of DIPY depends on nibabel (3.0.0+). 

For visualization you need FURY (0.4.0+).


Questions or suggestions?

 

For any questions go to http://dipy.org, or send an e-mail to dipy@python.org  

We also have an instant messaging service and chat room available at https://gitter.im/nipy/dipy


On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

https://dipy.org/contributors


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