.. -*- mode: rst -*-
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.. _changelog:

Dipy Development Changelog
-----------------------------

Dipy is a diffusion MR imaging library written in Python

'Close gh-' statements refer to GitHub issues that are available at::

  http://github.com/nipy/dipy/issues

The full VCS changelog is available here:

  http://github.com/nipy/dipy/commits/master

Releases
~~~~~~~~

Dipy
++++

The code found in Dipy was created by the following people: Eleftherios Garyfallidis, Matthew Brett, Bago Amirbekian, Ian Nimmo-Smith, Ariel Rokem, Stefan van der Walt, Christopher Nguyen, Maxime Descoteaux, Yaroslav Halchenko, Emanuele Olivetti, Michael Paquette, Samuel St-Jean, Endolith and Maria Luisa Mandelli.


* 0.6.0 (Sunday, 24 Mar 2013)

* Cython 0.17+ enforced
* New reconstruction models API 
* Diffusion Spectrum Imaging (DSI) 
* DSI with deconvolution
* Generalized Q-sampling Imaging 2 (GQI2)
* Modular fiber tracking 
  * deterministic
  * probabilistic
* Fast volume indexing (a faster ndindex)
* Spherical Harmonic Models
  * Opdt (Tristan-Vega et. al)
  * CSA odf (Aganj et. al)
  * Analytical Q-ball (Descoteuax et. al)
  * Tuch's Q-ball (Tuch et. al)
* Visualization of spherical functions
* Peak finding in odfs
* Non-linear peak finding
* Sphere Object
* Gradients Object
* 2D sphere plotting
* MultiTensor and Ball & Sticks voxel simulations
* Fetch/Download data for examples
* Software phantom generation
* Angular similarity for comparisons between multiple peaks
* SingleVoxelModel to MultiVoxelModel decorator
* Mrtrix and fibernavigator SH bases
* More Benchmarks
* More Tests
* Color FA and other Tensor metrics added
* Scripts for the ISBI 2013 competition
* Fit_tensor script added
* Radial basis function interpolation on the sphere
* New examples/tutorials


* 0.5.0 (Friday, 11 Feb 2011)

  * Initial release.

    * Reconstruction algorithms e.g. GQI, DTI
    * Tractography generation algorithms e.g. EuDX
    * Intelligent downsampling of tracks
    * Ultra fast tractography clustering
    * Resampling datasets with anisotropic voxels to isotropic
    * Visualizing multiple brains simultaneously
    * Finding track correspondence between different brains
    * Reading many different file formats e.g. Trackvis or Nifti
    * Dealing with huge tractographies without memory restrictions
    * Playing with datasets interactively without storing
    * And much more and even more to come in next releases
