v0.6.0

Dependencies

• PyCOMPSs >= 2.7
• Scikit-learn >= 0.19.2
• NumPy >= 1.15.4
• Scipy >= 1.0.0
• cvxpy>=1.1.5

Upgrade Steps

If using docker, just use the new image.

If you have a local installation, upgrade to COMPSs 2.7 (see COMPSs doc) before upgrading to dislib 0.6.0. Also, install the Python cvxpy module in order to use the regression algorithms: pip install cvxpy.

Breaking Changes

• ds-array doesn't accept a chunk_size bigger than the array.
• Moved data loading routines to a different file as array.py was getting too big.
• apply_along_axis for sparse data now returns sparse ds-arrays.
• Some PyCOMPSs log messages have changed.

New Features

• User guide and glossary
• Method to read from npy files
• Support for one-dimensional data in ds-array
• Parametrized ds-array tests
• identity, full and zeros methods that generate ds-arrays filled with a value
• ds-array operators: subtraction, division, conjugate, transpose, item setting, etc.
• matmul, kronecker product and rechunk methods for of ds-arrays
• Automatic deletion of ds-arrays when the GC is called.
• Multivariate linear regression.
• SVD (Singular Value Decomposition)
• PCA using SVD
• ADMM Lasso algorithm
• Daura clustering algorithm

Bug Fixes

• Some bugs in the ds-array
• Internal inconsistencies in transformed_array of PCA

Improvements

• Improved performance testing scripts and added new tests
• Allow executing applications with params using dislib exec
• Extended and improved the tutorial notebook
• Updated dislib-base docker image
• Replaced COLLECTION_INOUT parameters with COLLECTION_OUT when possible for improving performance