From: Ralf Gommers ralf.gommers@gmail.com

Subject: [Numpy-discussion] ANN: second SciPy 1.0.0 release candidate

Date: October 18, 2017 at 03:04:40 PDT

To: SciPy Developers List scipy-dev@python.org, SciPy Users List scipy-user@python.org, Discussion of Numerical Python numpy-discussion@python.org

Reply-To: Discussion of Numerical Python numpy-discussion@python.orgHi all,

I’m excited to be able to announce the availability of the second (and hopefully last) release candidate of Scipy 1.0. This is a big release, and a version number that has been 16 years in the making. It contains a few more deprecations and backwards incompatible changes than an average release. Therefore please do test it on your own code, and report any issues on the Github issue tracker or on the scipy-dev mailing list.

Sources and binary wheels can be found at https://pypi.python.org/pypi/scipy https://pypi.python.org/pypi/scipy and https://github.com/scipy/scipy/releases/tag/v1.0.0rc2 https://github.com/scipy/scipy/releases/tag/v1.0.0rc2. To install with pip:

`pip install --pre --upgrade scipy`

The most important issues fixed after v1.0.0rc1 is https://github.com/scipy/scipy/issues/7969 https://github.com/scipy/scipy/issues/7969 (missing DLL in Windows wheel).

Pull requests merged after v1.0.0rc1:

`#7948 <https://github.com/scipy/scipy/pull/7948 <https://github.com/scipy/scipy/pull/7948>>`

__: DOC: add note on checking for deprecations before upgrade to…`#7952 <https://github.com/scipy/scipy/pull/7952 <https://github.com/scipy/scipy/pull/7952>>`

__: DOC: update SciPy Roadmap for 1.0 release and recent discussions.`#7960 <https://github.com/scipy/scipy/pull/7960 <https://github.com/scipy/scipy/pull/7960>>`

__: BUG: optimize: revert changes to bfgs in gh-7165`#7962 <https://github.com/scipy/scipy/pull/7962 <https://github.com/scipy/scipy/pull/7962>>`

__: TST: special: mark a failing hyp2f1 test as xfail`#7973 <https://github.com/scipy/scipy/pull/7973 <https://github.com/scipy/scipy/pull/7973>>`

__: BUG: fixed keyword in ‘info’ in`_get_mem_available`

utility`#7986 <https://github.com/scipy/scipy/pull/7986 <https://github.com/scipy/scipy/pull/7986>>`

__: TST: Relax test_trsm precision to 5 decimals`#8001 <https://github.com/scipy/scipy/pull/8001 <https://github.com/scipy/scipy/pull/8001>>`

__: TST: fix test failures from Matplotlib 2.1 update`#8010 <https://github.com/scipy/scipy/pull/8010 <https://github.com/scipy/scipy/pull/8010>>`

__: BUG: signal: fix crash in lfilter`#8019 <https://github.com/scipy/scipy/pull/8019 <https://github.com/scipy/scipy/pull/8019>>`

__: MAINT: fix test failures with NumPy masterThanks to everyone who contributed to this release!

Ralf

## ==========================

SciPy 1.0.0 Release Notes… note:: Scipy 1.0.0 is not released yet!

… contents::

SciPy 1.0.0 is the culmination of 8 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 1.0.x branch, and on adding

new features on the master branch.Some of the highlights of this release are:

- Major build improvements. Windows wheels are available on PyPI for the

first time, and continuous integration has been set up on Windows and OS X

in addition to Linux.- A set of new ODE solvers and a unified interface to them

(`scipy.integrate.solve_ivp`

).- Two new trust region optimizers and a new linear programming method, with

improved performance compared to what`scipy.optimize`

offered previously.- Many new BLAS and LAPACK functions were wrapped. The BLAS wrappers are now

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

This is also the last release to support LAPACK 3.1.x - 3.3.x. Moving the

lowest supported LAPACK version to >3.2.x was long blocked by Apple Accelerate

providing the LAPACK 3.2.1 API. We have decided that it’s time to either drop

Accelerate or, if there is enough interest, provide shims for functions added

in more recent LAPACK versions so it can still be used.## New features

`scipy.cluster`

improvements

`scipy.cluster.hierarchy.optimal_leaf_ordering`

, a function to reorder a

linkage matrix to minimize distances between adjacent leaves, was added.

`scipy.fftpack`

improvementsN-dimensional versions of the discrete sine and cosine transforms and their

inverses were added as`dctn`

,`idctn`

,`dstn`

and`idstn`

.

`scipy.integrate`

improvementsA set of new ODE solvers have been added to

`scipy.integrate`

. The convenience

function`scipy.integrate.solve_ivp`

allows uniform access to all solvers.

The individual solvers (`RK23`

,`RK45`

,`Radau`

,`BDF`

and`LSODA`

)

can also be used directly.

`scipy.linalg`

improvementsThe BLAS wrappers in

`scipy.linalg.blas`

have been completed. Added functions

are`*gbmv`

,`*hbmv`

,`*hpmv`

,`*hpr`

,`*hpr2`

,`*spmv`

,`*spr`

,

`*tbmv`

,`*tbsv`

,`*tpmv`

,`*tpsv`

,`*trsm`

,`*trsv`

,`*sbmv`

,

`*spr2`

,Wrappers for the LAPACK functions

`*gels`

,`*stev`

,`*sytrd`

,`*hetrd`

,

`*sytf2`

,`*hetrf`

,`*sytrf`

,`*sycon`

,`*hecon`

,`*gglse`

,

`*stebz`

,`*stemr`

,`*sterf`

, and`*stein`

have been added.The function

`scipy.linalg.subspace_angles`

has been added to compute the

subspace angles between two matrices.The function

`scipy.linalg.clarkson_woodruff_transform`

has been added.

It finds low-rank matrix approximation via the Clarkson-Woodruff Transform.The functions

`scipy.linalg.eigh_tridiagonal`

and

`scipy.linalg.eigvalsh_tridiagonal`

, which find the eigenvalues and

eigenvectors of tridiagonal hermitian/symmetric matrices, were added.

`scipy.ndimage`

improvementsSupport for homogeneous coordinate transforms has been added to

`scipy.ndimage.affine_transform`

.The

`ndimage`

C code underwent a significant refactoring, and is now

a lot easier to understand and maintain.

`scipy.optimize`

improvementsThe methods

`trust-region-exact`

and`trust-krylov`

have been added to the

function`scipy.optimize.minimize`

. These new trust-region methods solve the

subproblem with higher accuracy at the cost of more Hessian factorizations

(compared to dogleg) or more matrix vector products (compared to ncg) but

usually require less nonlinear iterations and are able to deal with indefinite

Hessians. They seem very competitive against the other Newton methods

implemented in scipy.

`scipy.optimize.linprog`

gained an interior point method. Its performance is

superior (both in accuracy and speed) to the older simplex method.

`scipy.signal`

improvementsAn argument

`fs`

(sampling frequency) was added to the following functions:

`firwin`

,`firwin2`

,`firls`

, and`remez`

. This makes these functions

consistent with many other functions in`scipy.signal`

in which the sampling

frequency can be specified.

`scipy.signal.freqz`

has been sped up significantly for FIR filters.

`scipy.sparse`

improvementsIterating over and slicing of CSC and CSR matrices is now faster by up to ~35%.

The

`tocsr`

method of COO matrices is now several times faster.The

`diagonal`

method of sparse matrices now takes a parameter, indicating

which diagonal to return.

`scipy.sparse.linalg`

improvementsA new iterative solver for large-scale nonsymmetric sparse linear systems,

`scipy.sparse.linalg.gcrotmk`

, was added. It implements`GCROT(m,k)`

, a

flexible variant of`GCROT`

.

`scipy.sparse.linalg.lsmr`

now accepts an initial guess, yielding potentially

faster convergence.SuperLU was updated to version 5.2.1.

`scipy.spatial`

improvementsMany distance metrics in

`scipy.spatial.distance`

gained support for weights.The signatures of

`scipy.spatial.distance.pdist`

and

`scipy.spatial.distance.cdist`

were changed to`*args, **kwargs`

in order to

support a wider range of metrics (e.g. string-based metrics that need extra

keywords). Also, an optional`out`

parameter was added to`pdist`

and

`cdist`

allowing the user to specify where the resulting distance matrix is

to be stored

`scipy.stats`

improvementsThe methods

`cdf`

and`logcdf`

were added to

`scipy.stats.multivariate_normal`

, providing the cumulative distribution

function of the multivariate normal distribution.New statistical distance functions were added, namely

`scipy.stats.wasserstein_distance`

for the first Wasserstein distance and

`scipy.stats.energy_distance`

for the energy distance.## Deprecated features

The following functions in

`scipy.misc`

are deprecated:`bytescale`

,

`fromimage`

,`imfilter`

,`imread`

,`imresize`

,`imrotate`

,

`imsave`

,`imshow`

and`toimage`

. Most of those functions have unexpected

behavior (like rescaling and type casting image data without the user asking

for that). Other functions simply have better alternatives.

`scipy.interpolate.interpolate_wrapper`

and all functions in that submodule

are deprecated. This was a never finished set of wrapper functions which is

not relevant anymore.The

`fillvalue`

of`scipy.signal.convolve2d`

will be cast directly to the

dtypes of the input arrays in the future and checked that it is a scalar or

an array with a single element.

`scipy.spatial.distance.matching`

is deprecated. It is an alias of

`scipy.spatial.distance.hamming`

, which should be used instead.Implementation of

`scipy.spatial.distance.wminkowski`

was based on a wrong

interpretation of the metric definition. In scipy 1.0 it has been just

deprecated in the documentation to keep retro-compatibility but is recommended

to use the new version of`scipy.spatial.distance.minkowski`

that implements

the correct behaviour.Positional arguments of

`scipy.spatial.distance.pdist`

and

`scipy.spatial.distance.cdist`

should be replaced with their keyword version.## Backwards incompatible changes

The following deprecated functions have been removed from

`scipy.stats`

:

`betai`

,`chisqprob`

,`f_value`

,`histogram`

,`histogram2`

,

`pdf_fromgamma`

,`signaltonoise`

,`square_of_sums`

,`ss`

and

`threshold`

.The following deprecated functions have been removed from

`scipy.stats.mstats`

:

`betai`

,`f_value_wilks_lambda`

,`signaltonoise`

and`threshold`

.The deprecated

`a`

and`reta`

keywords have been removed from

`scipy.stats.shapiro`

.The deprecated functions

`sparse.csgraph.cs_graph_components`

and

`sparse.linalg.symeig`

have been removed from`scipy.sparse`

.The following deprecated keywords have been removed in

`scipy.sparse.linalg`

:

`drop_tol`

from`splu`

, and`xtype`

from`bicg`

,`bicgstab`

,`cg`

,

`cgs`

,`gmres`

,`qmr`

and`minres`

.The deprecated functions

`expm2`

and`expm3`

have been removed from

`scipy.linalg`

. The deprecated keyword`q`

was removed from

`scipy.linalg.expm`

. And the deprecated submodule`linalg.calc_lwork`

was

removed.The deprecated functions

`C2K`

,`K2C`

,`F2C`

,`C2F`

,`F2K`

and

`K2F`

have been removed from`scipy.constants`

.The deprecated

`ppform`

class was removed from`scipy.interpolate`

.The deprecated keyword

`iprint`

was removed from`scipy.optimize.fmin_cobyla`

.The default value for the

`zero_phase`

keyword of`scipy.signal.decimate`

has been changed to True.The

`kmeans`

and`kmeans2`

functions in`scipy.cluster.vq`

changed the

method used for random initialization, so using a fixed random seed will

not necessarily produce the same results as in previous versions.

`scipy.special.gammaln`

does not accept complex arguments anymore.The deprecated functions

`sph_jn`

,`sph_yn`

,`sph_jnyn`

,`sph_in`

,

`sph_kn`

, and`sph_inkn`

have been removed. Users should instead use

the functions`spherical_jn`

,`spherical_yn`

,`spherical_in`

, and

`spherical_kn`

. Be aware that the new functions have different

signatures.The cross-class properties of

`scipy.signal.lti`

systems have been removed.

The following properties/setters have been removed:Name - (accessing/setting has been removed) - (setting has been removed)

- StateSpace - (
`num`

,`den`

,`gain`

) - (`zeros`

,`poles`

)- TransferFunction (
`A`

,`B`

,`C`

,`D`

,`gain`

) - (`zeros`

,`poles`

)- ZerosPolesGain (
`A`

,`B`

,`C`

,`D`

,`num`

,`den`

) - ()

`signal.freqz(b, a)`

with`b`

or`a`

>1-D raises a`ValueError`

. This

was a corner case for which it was unclear that the behavior was well-defined.The method

`var`

of`scipy.stats.dirichlet`

now returns a scalar rather than

an ndarray when the length of alpha is 1.## Other changes

SciPy now has a formal governance structure. It consists of a BDFL (Pauli

Virtanen) and a Steering Committee. See`the governance document <https://github.com/scipy/scipy/blob/master/doc/source/dev/governance/governance.rst <https://github.com/scipy/scipy/blob/master/doc/source/dev/governance/governance.rst>>`

_

for details.It is now possible to build SciPy on Windows with MSVC + gfortran! Continuous

integration has been set up for this build configuration on Appveyor, building

against OpenBLAS.Continuous integration for OS X has been set up on TravisCI.

The SciPy test suite has been migrated from

`nose`

to`pytest`

.

`scipy/_distributor_init.py`

was added to allow redistributors of SciPy to

add custom code that needs to run when importing SciPy (e.g. checks for

hardware, DLL search paths, etc.).Support for PEP 518 (specifying build system requirements) was added - see

`pyproject.toml`

in the root of the SciPy repository.In order to have consistent function names, the function

`scipy.linalg.solve_lyapunov`

is renamed to

`scipy.linalg.solve_continuous_lyapunov`

. The old name is kept for

backwards-compatibility.

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# [Numpy-discussion] ANN: second SciPy 1.0.0 release candidate

**christie**(Christie Koehler) #1