0.3.10

New Functionality

• Added new 2-D matrix permutation to correlation_permutation()

Bug Fixes

• Updated MANIFEST to include resources with pypi
• fixed compatibility issues with python 2.7 and joblib. Using older version for now.
• refactored tests to be cleaner with fixtures.

0.3.9

New Functionality

• New regression method for Adjacency objects (univariate and Adjacency decomposition)
• faster t-tests (permutation and standard)
• within cluster mean method for Adjacency objects
• similarity to distance conversion for Adacency objects
• new function to convert ROI values back into brain_data instances

0.3.8

New Functionality

• Brain_Data now has scale method to be consistent with spm and fsl

Bug Fixes

• Big refactor to design_matrix class.
• Updated documentation.

0.3.7

New Functionality

• added labels to Adjacency Class
• refactored regression module (includes robust and AR models)
• updated threshold methds
• refactored design_matrix class. Lots of new functionality
• refactored trim and winsorize into single function
• permutation tests now default to two tailed

Bug Fixes

• plot_mds
• upsample
• importing lists of 4d data.
• transform_pairwise
• Design_matrix many bug fixes
• conflict with matplotlib and nilearn versions

0.3.6

New Functionality

• Added ability to perform hyperalignment using procrustes transform and shared response model.
• Added ability to decompose across space and time
• Added cosine similarity to Brain_Data.similarity

Bug Fixes

• fixed bug with thresholding
• fixed bug with random seed and parallel processing bootstrap and permutations
• fixed bug with naming in design_matrix
• fixed bug with file_reader
• fixed bug with plotting (updated matplotlib and nilearn version)
• moved external code to /external folder

0.3.5

New Functionality
Added ability to decompose Brain_Data objects using PCA, ICA, NNMF.

Bug Fixes
Fixed bug with pypi with requirements file.

0.3.4

This release was lead by @ejolly and added a bunch of new things.

New Functionality

• Added a new Preference class to specify preferences for nltools. The most notable one is which brain mask to implicitly use. For large datasets, 3 x 3 x 3 will dramatically reduce RAM costs and speed up computations. These masks are packaged in resources folder as well as versions that don't include the ventricles.
• ARMA estimator for regress methods
• robust regression for regress methods

API Changes

• Brain_Data.threshold has a new api. Can now accommodate bidirectional thresholding, but must specify an upper and lower bound thresholds

Bug Fixes

• small bug in bootstrap function
• requirements file now synced with setuptools
• rolled back matplotlib to avoid a new plotting bug.
• fixed data type output for Brain_Data.ttest()
• fixed an indexing bug with stats.downsample function

0.3.2

Bugs Fixed

• Brain_Data slicing
• optional imports
• refactored data module

New Functionality

• permutation and bootstraps now run in parallel
• can now concatenate Brain_Data and Adjacency objects

0.3.1

Fixed bugs with:
-ROC (forced choice and balanced accuracy, store gaussian weights)
-create_sphere
-Brain_Data logical indexing
-compatible with scipy 1.0.0
-winsorize

Added new functionality:
-transform_pairwise()

0.3.0

Now compatible with Python3