SciPy 0.12.0 Release Notes

Note

Scipy 0.12.0 is not released yet!

SciPy 0.12.0 is the culmination of XXX months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Moreover, our development attention will now shift to bug-fix releases on the 0.12.x branch, and on adding new features on the master branch.

This release requires Python 2.4-2.7 or 3.1- and NumPy 1.X.X or greater.

New features

scipy.sparse.linalg features

  • In scipy.sparse.linalg.spsolve, the b argument can now be either a vector or a matrix.
  • scipy.sparse.linalg.inv was added. This uses spsolve to compute a sparse matrix inverse.
  • scipy.sparse.linalg.expm was added. This computes the exponential of a sparse matrix using a similar algorithm to the existing dense array implementation in scipy.linalg.expm.

cKDTRee improvements

scipy.spatial: Cython version of KDTree, cKDTree, is now feature-complete. Most operations (construction, query, query_ball_point, query_pairs, count_neighbors and sparse_distance_matrix) are between 200 and 1000 times faster in cKDTree than in KDTree. With very minor caveats, cKDTree has exactly the same interface as KDTree, and can be used as a drop-in replacement.

Authors

  • Anthony Scopatz (sparse linear algebra)
  • Jake Vanderplas (sparse linear algebra)