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authormarkd <markd>2016-04-23 22:51:57 +0000
committermarkd <markd>2016-04-23 22:51:57 +0000
commit16d58739fd32ec1365ad9529a4d82838cf67a6aa (patch)
tree26d46338f878aa1a9ff398185486533ffa144986 /security/p5-IO-Socket-SSL/distinfo
parent906a7bea57397b971ee9f8035b9b9f28b958d4c1 (diff)
downloadpkgsrc-16d58739fd32ec1365ad9529a4d82838cf67a6aa.tar.gz
Update py-scipy to 0.17.0
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.
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