./math/py-scipy, Scientific Algorithms Library for Python

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Branch: CURRENT, Version: 1.3.0, Package name: py37-scipy-1.3.0, Maintainer: markd

SciPy is an open source library of scientific tools for Python. SciPy
supplements the popular Numeric module, gathering a variety of high level
science and engineering modules together as a single package.

SciPy includes modules for graphics and plotting, optimization, integration,
special functions, signal and image processing, genetic algorithms, ODE
solvers, and others.


Required to run:
[lang/g95] [math/fftw] [math/lapack] [math/blas] [math/py-numpy] [devel/py-cython] [lang/python37]

Required to build:
[pkgtools/cwrappers]

Master sites:

SHA1: 6c1896c3e2738e940f8be132eb7caef48d85f1dc
RMD160: deff9efa7ad5807548c53f6ad32f4a0ecf12e07b
Filesize: 23066.959 KB

Version history: (Expand)


CVS history: (Expand)


   2019-11-04 18:47:31 by Roland Illig | Files touched by this commit (14)
Log message:
mk: make BROKEN a list of lines, like PKG_FAIL_REASON

Packages defined the variable BROKEN inconsistently. Some added quotes,
like they are required in PKG_FAIL_REASON, some omitted them.

Now all packages behave the same, and pkglint will flag future mistakes.
   2019-11-02 17:16:23 by Roland Illig | Files touched by this commit (47)
Log message:
math: align variable assignments

pkglint -Wall -F --only aligned -r

Manual correction in R/Makefile.extension for the MASTER_SITES
continuation line.
   2019-06-14 16:53:29 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-scipy: updated to 1.3.0

SciPy 1.3.0 Release Notes

SciPy 1.3.0 is the culmination of 5 months of hard work. It contains
many new features, numerous bug-fixes, improved test coverage and better
documentation. There have been some 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. Before upgrading, we recommend that users check that
their own code does not use deprecated SciPy functionality (to do so,
run your code with python -Wd and check for DeprecationWarning s).
Our development attention will now shift to bug-fix releases on the
1.3.x branch, and on adding new features on the master branch.

This release requires Python 3.5+ and NumPy 1.13.3 or greater.

For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required.

Highlights of this release
- Three new stats functions, a rewrite of pearsonr, and an exact
  computation of the Kolmogorov-Smirnov two-sample test
- A new Cython API for bounded scalar-function root-finders in scipy.optimize
- Substantial CSR and CSC sparse matrix indexing performance
  improvements
- Added support for interpolation of rotations with continuous angular
  rate and acceleration in RotationSpline

SciPy 1.2.0 Release Notes

SciPy 1.2.0 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. Before upgrading, we recommend that users check that
their own code does not use deprecated SciPy functionality (to do so,
run your code with python -Wd and check for DeprecationWarning s).
Our development attention will now shift to bug-fix releases on the
1.2.x branch, and on adding new features on the master branch.

This release requires Python 2.7 or 3.4+ and NumPy 1.8.2 or greater.

This will be the last SciPy release to support Python 2.7.
Consequently, the 1.2.x series will be a long term support (LTS)
release; we will backport bug fixes until 1 Jan 2020.

For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required.

Highlights of this release
- 1-D root finding improvements with a new solver, toms748, and a new
  unified interface, root_scalar
- New dual_annealing optimization method that combines stochastic and
  local deterministic searching
- A new optimization algorithm, shgo (simplicial homology
  global optimization) for derivative free optimization problems
- A new category of quaternion-based transformations are available in
  scipy.spatial.transform
   2018-09-03 11:04:24 by Thomas Klausner | Files touched by this commit (2)
Log message:
py-scipy: add upstream bug reports
   2018-09-03 10:57:24 by Thomas Klausner | Files touched by this commit (2)
Log message:
py-scipy: remove obsolete patch; HAVE_OPEN_MEMSTREAM is defined to 1 nowadays.
   2018-09-03 10:36:44 by Thomas Klausner | Files touched by this commit (1)
Log message:
py-scipy: remove reference to non-existent file
   2018-08-31 10:09:20 by Thomas Klausner | Files touched by this commit (1) | Package updated
Log message:
py-scipy: add missing test dependency

Update comment about upstream bug reports about test failures.
   2018-08-21 00:36:21 by Ryosuke Moro | Files touched by this commit (6)
Log message:
BUILD_DEPENDS+=  ->  TEST_DEPENDS+=