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

Ralf Gommers ralf.gommers at gmail.com
Wed Oct 18 06:04:40 EDT 2017

Hi 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
and https://github.com/scipy/scipy/releases/tag/v1.0.0rc2. To install with

    pip install --pre --upgrade scipy

The most important issues fixed after v1.0.0rc1 is
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>`__: DOC: add note on
checking for deprecations before upgrade to...
- `#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>`__: BUG: optimize:
revert changes to bfgs in gh-7165
- `#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>`__: BUG: fixed keyword
in 'info' in ``_get_mem_available`` utility
- `#7986 <https://github.com/scipy/scipy/pull/7986>`__: TST: Relax
test_trsm precision to 5 decimals
- `#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>`__: BUG: signal: fix
crash in lfilter
- `#8019 <https://github.com/scipy/scipy/pull/8019>`__: MAINT: fix test
failures with NumPy master

Thanks to everyone who contributed to this release!


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
- 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

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
providing the LAPACK 3.2.1 API.  We have decided that it's time to either
Accelerate or, if there is enough interest, provide shims for functions
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` improvements

N-dimensional versions of the discrete sine and cosine transforms and their
inverses were added as ``dctn``, ``idctn``, ``dstn`` and ``idstn``.

`scipy.integrate` improvements

A set of new ODE solvers have been added to `scipy.integrate`.  The
function `scipy.integrate.solve_ivp` allows uniform access to all solvers.
The individual solvers (``RK23``, ``RK45``, ``Radau``, ``BDF`` and
can also be used directly.

`scipy.linalg` improvements

The BLAS wrappers in `scipy.linalg.blas` have been completed.  Added
are ``*gbmv``, ``*hbmv``, ``*hpmv``, ``*hpr``, ``*hpr2``, ``*spmv``,
``*tbmv``, ``*tbsv``, ``*tpmv``, ``*tpsv``, ``*trsm``, ``*trsv``, ``*sbmv``,

Wrappers for the LAPACK functions ``*gels``, ``*stev``, ``*sytrd``,
``*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` improvements

Support for homogeneous coordinate transforms has been added to

The ``ndimage`` C code underwent a significant refactoring, and is now
a lot easier to understand and maintain.

`scipy.optimize` improvements

The methods ``trust-region-exact`` and ``trust-krylov`` have been added to
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
Hessians. They seem very competitive against the other Newton methods
implemented in scipy.

`scipy.optimize.linprog` gained an interior point method.  Its performance
superior (both in accuracy and speed) to the older simplex method.

`scipy.signal` improvements

An argument ``fs`` (sampling frequency) was added to the following
``firwin``, ``firwin2``, ``firls``, and ``remez``.  This makes these
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` improvements

Iterating over and slicing of CSC and CSR matrices is now faster by up to

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` improvements

A 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
faster convergence.

SuperLU was updated to version 5.2.1.

`scipy.spatial` improvements

Many distance metrics in `scipy.spatial.distance` gained support for

The signatures of `scipy.spatial.distance.pdist` and
`scipy.spatial.distance.cdist` were changed to ``*args, **kwargs`` in order
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
to be stored

`scipy.stats` improvements

The 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
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
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
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

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

The following deprecated functions have been removed from
``betai``, ``f_value_wilks_lambda``, ``signaltonoise`` and ``threshold``.

The deprecated ``a`` and ``reta`` keywords have been removed from

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
``drop_tol`` from ``splu``, and ``xtype`` from ``bicg``, ``bicgstab``,
``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

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

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

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``,
* ZerosPolesGain (``A``, ``B``, ``C``, ``D``, ``num``, ``den``) - ()

``signal.freqz(b, a)`` with ``b`` or ``a`` >1-D raises a ``ValueError``.
was a corner case for which it was unclear that the behavior was

The method ``var`` of `scipy.stats.dirichlet` now returns a scalar rather
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
for details.

It is now possible to build SciPy on Windows with MSVC + gfortran!
integration has been set up for this build configuration on Appveyor,
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
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