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

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Branch: CURRENT, Version: 1.5.2nb1, Package name: py37-scipy-1.5.2nb1, 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:
[math/fftw] [math/lapack] [math/blas] [math/py-numpy] [devel/py-cython] [lang/gcc7] [lang/python37]

Required to build:
[pkgtools/cwrappers]

Master sites:

SHA1: d921aa98f73ea5bc533536df7fa681df52d8b9e2
RMD160: 84d89d666191a1a2270a03bf4b45b40195615e42
Filesize: 24828.07 KB

Version history: (Expand)


CVS history: (Expand)


   2020-10-12 23:52:05 by Jason Bacon | Files touched by this commit (87) | Package updated
Log message:
math/blas, math/lapack: Install interchangeable BLAS system

Install the new interchangeable BLAS system created by Thomas Orgis,
currently supporting Netlib BLAS/LAPACK, OpenBLAS, cblas, lapacke, and
Apple's Accelerate.framework.  This system allows the user to select any
BLAS implementation without modifying packages or using package options, by
setting PKGSRC_BLAS_TYPES in mk.conf. See mk/blas.buildlink3.mk for details.

This commit should not alter behavior of existing packages as the system
defaults to Netlib BLAS/LAPACK, which until now has been the only supported
implementation.

Details:

Add new mk/blas.buildlink3.mk for inclusion in dependent packages
Install compatible Netlib math/blas and math/lapack packages
Update math/blas and math/lapack MAINTAINER approved by adam@
OpenBLAS, cblas, and lapacke will follow in separate commits
Update direct dependents to use mk/blas.buildlink3.mk
Perform recursive revbump
   2020-08-04 03:16:19 by Tobias Nygren | Files touched by this commit (3) | Package updated
Log message:
py-scipy: update to 1.5.2

Done to fix build w/ gfortran 10. "make test" was mostly OK except for
three tests that returned nan where inf was expected ...

Highlights of this release:
  wrappers for more than a dozen new LAPACK routines are now available
  in scipy.linalg.lapack
  Improved support for leveraging 64-bit integer size from linear algebra
  backends
  addition of the probability distribution for two-sided one-sample
  Kolmogorov-Smirnov tests

New features:
  Too many; see release notes at github.

Backwards incompatible changes:
  The output signatures of ?syevr, ?heevr have been changed from
  w, v, info to w, v, m, isuppz, info
  The order of output arguments w, v of <sy/he>{gv, gvd, gvx} is
  swapped.
  The output length of scipy.signal.upfirdn has been corrected, resulting
  outputs may now be shorter for some combinations of up/down ratios and
  input signal and filter lengths.
  scipy.signal.resample now supports a domain keyword argument for
  specification of time or frequency domain input.
   2020-04-28 11:45:27 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-scipy: updated to 1.4.1

SciPy 1.4.1 is a bug-fix release with no new features
compared to 1.4.0. Importantly, it aims to fix a problem
where an older version of pybind11 may cause a segmentation
fault when imported alongside incompatible libraries.

SciPy 1.4.0 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
1.4.x branch, and on adding new features on the master branch.
   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.