SciPy 0.17.0 is the culmination of 6 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 0.17.x branch, and on adding new features on the
master branch.
This release requires Python 2.6, 2.7 or 3.2-3.5 and NumPy 1.6.2 or greater.
Release highlights:
* New functions for linear and nonlinear least squares optimization with
constraints: scipy.optimize.lsq_linear and scipy.optimize.least_squares
* Support for fitting with bounds in scipy.optimize.curve_fit.
* Significant improvements to scipy.stats, providing many functions with
better handing of inputs which have NaNs or are empty, improved
documentation, and consistent behavior between scipy.stats and
scipy.stats.mstats.
* Significant performance improvements and new functionality in
scipy.spatial.cKDTree.
SciPy 0.16.0 is the culmination of 7 months of hard work.
Highlights of this release include:
* A Cython API for BLAS/LAPACK in scipy.linalg
* A new benchmark suite. It’s now straightforward to add new benchmarks,
and they’re routinely included with performance enhancement PRs.
* Support for the second order sections (SOS) format in scipy.signal.
5ddb0c30d1