[Mne_analysis] DIPY 0.11.0 is now available for download

Eleftherios Garyfallidis garyfallidis at gmail.com
Tue Feb 23 11:08:28 EST 2016
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Dear all,

We are excited to announce a new public release of Diffusion Imaging in
Python (DIPY).

The 0.11 release follows closely on the heels of the 0.10 release,
resolving issues that existed in that release on the Windows 64 bit
platform. New features of the 0.11 and 0.10 release cycles include many
additional fixes and new frameworks. Here are some of the highlights:

DIPY 0.11.0 (Monday, 21 February 2016):

- New framework for contextual enhancement of ODFs.

- Compatibility with new version of numpy (1.11).

- Compatibility with VTK 7.0 which supports Python 3.x.

- Faster PIESNO for noise estimation.

- Reorient gradient directions according to motion correction parameters.

- Supporting Python 3.3+ but not 3.2.

- Reduced memory usage in DTI prediction.

- DSI now can use datasets with multiple b0s.

- Fixed different issues with Windows 64bit and Python 3.5.

DIPY 0.10.1 (Friday, 4 December 2015):

- Compatibility with new versions of scipy (0.16) and numpy (1.10).

- New cleaner visualization API, including compatibility with VTK 6, and
functions to create your own interactive visualizations.

- Diffusion Kurtosis Imaging (DKI): Google Summer of Code work by Rafael

- Mean Apparent Propagator (MAP) MRI for tissue microstructure estimation.

- Anisotropic Power Maps from spherical harmonic coefficients.

- A new framework for affine registration of images.

Detailed release notes can be found here:



To upgrade, run the following command in your terminal:

pip install --upgrade dipy

For the complete installation guide look here:


For any questions go to http://dipy.org, or https://neurostars.org or send
an e-mail to neuroimaging at python.org

We also have a new instant messaging service and chat room available at

On behalf of the DIPY developers,

Eleftherios Garyfallidis & Ariel Rokem

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