[Numpy-discussion] ANN: scipy 0.17.0 release

[Evgeni Burovski]

Hi,

On behalf of the Scipy development team I am pleased to announce the
availability of Scipy 0.17.0. This release contains several new features,
detailed in the release notes below. 101 people contributed to this
release over the course of six months.

This release requires Python 2.6, 2.7 or 3.2-3.4 and NumPy 1.6.2 or
greater. Source tarballs and release notes can be found at
https://github.com/scipy/scipy/releases/tag/v0.17.0.

Thanks to everyone who contributed to this release.

Cheers,

Evgeni


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Hash: SHA1

==
SciPy 0.17.0 Release Notes
==

.. contents::

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`.


New features


`scipy.cluster` improvements
- 

A new function `scipy.cluster.hierarchy.cut_tree`, which determines a cut tree
from a linkage matrix, was added.

`scipy.io` improvements
- ---

`scipy.io.mmwrite` gained support for symmetric sparse matrices.

`scipy.io.netcdf` gained support for masking and scaling data based on data
attributes.

`scipy.optimize` improvements
- -

Linear assignment problem solver


`scipy.optimize.linear_sum_assignment` is a new function for solving the
linear sum assignment problem.  It uses the Hungarian algorithm (Kuhn-Munkres).

Least squares optimization
~~

A new function for *nonlinear* least squares optimization with constraints was
added: `scipy.optimize.least_squares`.  It provides several methods:
Levenberg-Marquardt for unconstrained problems, and two trust-region methods
for constrained ones.  Furthermore it provides different loss functions.
New trust-region methods also handle sparse Jacobians.

A new function for *linear* least squares optimization with constraints was
added: `scipy.optimize.lsq_linear`.  It provides a trust-region method as well
as an implementation of the Bounded-Variable Least-Squares (BVLS) algorithm.

`scipy.optimize.curve_fit` now supports fitting with bounds.

`scipy.signal` improvements
- ---

A ``mode`` keyword was added to `scipy.signal.spectrogram`, to let it return
other spectrograms than power spectral density.

`scipy.stats` improvements
- --

Many functions in `scipy.stats` have gained a ``nan_policy`` keyword, which
allows specifying how to treat input with NaNs in them: propagate the NaNs,
raise an error, or omit the NaNs.

Many functions in `scipy.stats` have been improved to correctly handle input
arrays that are empty or contain infs/nans.

A number of functions with the same name in `scipy.stats` and
`scipy.stats.mstats` were changed to have matching signature and behavior.
See `gh-5474 `__ for details.

`scipy.stats.binom_test` and `scipy.stats.mannwhitneyu` gained a keyword
``alternative``, which allows specifying the hypothesis to test for.
Eventually all hypothesis testing functions will get this keyword.

For methods of many continuous distributions, complex input is now accepted.

Matrix normal distribution has been implemented as `scipy.stats.matrix_normal`.

`scipy.sparse` improvements
- ---

The `axis` keyword was added to sparse norms, `scipy.sparse.linalg.norm`.

`scipy.spatial` improvements
- 

`scipy.spatial.cKDTree` was partly rewritten for improved performance and
several new features were added to it:

- - the ``query_ball_point`` method became significantly faster
- - ``query`` and ``query_ball_point`` gained an ``n_jobs`` keyword for parallel
  execution
- - build and query methods now release the GIL
- - full pickling support
- - support for periodic spaces
- - the ``sparse_distance_matrix`` method can 

Re: [Numpy-discussion] ANN: scipy 0.17.0 release

[Evgeni Burovski]

23.01.2016 22:12 пользователь "Kiko"  написал:
>
> is it python3.5 compatible? your message and github don't say the same.

It is indeed --- thanks for catching it. My typo, my bad.

Evgeni

> 2016-01-23 19:12 GMT+01:00, Charles R Harris :
> > 
> >
> > Congratulations.
> >
> > Chuck
> >
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Re: [Numpy-discussion] ANN: scipy 0.17.0 release

[Charles R Harris]

Congratulations.

Chuck
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Re: [Numpy-discussion] ANN: scipy 0.17.0 release

[Kiko]

is it python3.5 compatible? your message and github don't say the same.

2016-01-23 19:12 GMT+01:00, Charles R Harris :
> 
>
> Congratulations.
>
> Chuck
>
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Re: [Numpy-discussion] ANN: scipy 0.17.0 release

[Kiko]

BTW, congratulations and thanks for the hard work

2016-01-23 20:12 GMT+01:00, Kiko :
> is it python3.5 compatible? your message and github don't say the same.
>
> 2016-01-23 19:12 GMT+01:00, Charles R Harris :
>> 
>>
>> Congratulations.
>>
>> Chuck
>>
>
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