./math/py-numpy, Array processing for numbers, strings, records, and objects

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Branch: CURRENT, Version: 1.14.1, Package name: py27-numpy-1.14.1, Maintainer: pkgsrc-users

NumPy is a general-purpose array-processing package designed to
efficiently manipulate large multi-dimensional arrays of arbitrary
records without sacrificing too much speed for small multi-dimensional
arrays. NumPy is built on the Numeric code base and adds features
introduced by numarray as well as an extended C-API and the ability to
create arrays of arbitrary type.

There are also basic facilities for discrete fourier transform,
basic linear algebra and random number generation.


Required to run:
[lang/g95] [math/lapack] [math/blas] [devel/py-setuptools] [devel/py-cython] [lang/python27]

Required to build:
[devel/py-nose] [pkgtools/cwrappers]

Master sites:

SHA1: cf5ee7c523ba025df780dc44bbb0280ad006cbc9
RMD160: c774ee8dfdbe0281f5104b5af3d4607593bc3752
Filesize: 4176.02 KB

Version history: (Expand)


CVS history: (Expand)


   2018-02-22 11:50:47 by Adam Ciarcinski | Files touched by this commit (2) | Package updated
Log message:
py-numpy: updated to 1.14.1

NumPy 1.14.1 Release Notes

This is a bugfix release for some problems reported following the 1.14.0 \ 
release. The major
problems fixed are the following.

Problems with the new array printing, particularly the printing of complex
values, Please report any additional problems that may turn up.
Problems with np.einsum due to the new optimized=True default. Some
fixes for optimization have been applied and optimize=False is now the
default.
The sort order in np.unique when axis=<some-number> will now always
be lexicographic in the subarray elements. In previous NumPy versions there
was an optimization that could result in sorting the subarrays as unsigned
byte strings.
The change in 1.14.0 that multi-field indexing of structured arrays returns a
view instead of a copy has been reverted but remains on track for NumPy 1.15.
Affected users should read the 1.14.1 Numpy User Guide section
"basics/structured arrays/accessing multiple fields" for advice on how to
manage this transition.
   2018-01-10 09:31:24 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-numpy: updated to 1.14.0

NumPy 1.14.0 Release Notes

Numpy 1.14.0 is the result of seven months of work and contains a large number
of bug fixes and new features, along with several changes with potential
compatibility issues. The major change that users will notice are the
stylistic changes in the way numpy arrays and scalars are printed, a change
that will affect doctests. See below for details on how to preserve the
old style printing when needed.

A major decision affecting future development concerns the schedule for
dropping Python 2.7 support in the runup to 2020. The decision has been made to
support 2.7 for all releases made in 2018, with the last release being
designated a long term release with support for bug fixes extending through
2019. In 2019 support for 2.7 will be dropped in all new releases. More details
can be found in the relevant NEP_.

This release supports Python 2.7 and 3.4 - 3.6.
   2017-10-05 10:21:27 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-numpy: update to 1.13.3

NumPy 1.13.3:
This is a bugfix release for some problems found since 1.13.1. The most
important fixes are for CVE-2017-12852 and temporary elision. Users of earlier
versions of 1.13 should upgrade.
   2017-07-07 06:21:10 by Adam Ciarcinski | Files touched by this commit (3)
Log message:
1.13.1:
Bug fixes.
   2017-06-15 09:02:53 by Adam Ciarcinski | Files touched by this commit (5)
Log message:
NumPy 1.13.0

Highlights
* Operations like a + b + c will reuse temporaries on some platforms,
  resulting in less memory use and faster execution.
* Inplace operations check if inputs overlap outputs and create temporaries
  to avoid problems.
* New __array_ufunc__ attribute provides improved ability for classes to
  override default ufunc behavior.
* New np.block function for creating blocked arrays.

New functions
* New np.positive ufunc.
* New np.divmod ufunc provides more efficient divmod.
* New np.isnat ufunc tests for NaT special values.
* New np.heaviside ufunc computes the Heaviside function.
* New np.isin function, improves on in1d.
* New np.block function for creating blocked arrays.
* New PyArray_MapIterArrayCopyIfOverlap added to NumPy C-API.
   2017-03-24 20:22:28 by Joerg Sonnenberger | Files touched by this commit (3)
Log message:
Check the version number part of the matched string and not the whole
string, otherwise the result is somewhat random. Bump revision again.
   2017-03-24 16:12:30 by Joerg Sonnenberger | Files touched by this commit (3)
Log message:
Restore basic g95 support. Bump revision.
   2017-03-20 14:50:01 by Thomas Klausner | Files touched by this commit (3) | Package updated
Log message:
Updated py-numpy to 1.12.1.

NumPy 1.12.1 supports Python 2.7 and 3.4 - 3.6 and fixes bugs and regressions
found in NumPy 1.12.0. In particular, the regression in f2py constant parsing
is fixed.