ANN: SciPy 0.12.0 release candidate 1

Hi, I am pleased to announce the availability of the first release candidate of SciPy 0.12.0. This is shaping up to be another solid release, with some cool new features (see highlights below) and a large amount of bug fixes and maintenance work under the hood. The number of contributors also keeps rising steadily, we're at 74 so far for this release. Sources and binaries can be found at http://sourceforge.net/projects/scipy/files/scipy/0.12.0rc1/, release notes are copied below. Please try this release and report any problems on the mailing list. If no issues are found, the final release will be in one week. Cheers, Ralf ========================== SciPy 0.12.0 Release Notes ========================== .. note:: Scipy 0.12.0 is not released yet! .. contents:: SciPy 0.12.0 is the culmination of 7 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 0.12.x branch, and on adding new features on the master branch. Some of the highlights of this release are: - Completed QHull wrappers in scipy.spatial. - cKDTree now a drop-in replacement for KDTree. - A new global optimizer, basinhopping. - Support for Python 2 and Python 3 from the same code base (no more 2to3). This release requires Python 2.6, 2.7 or 3.1-3.3 and NumPy 1.5.1 or greater. Support for Python 2.4 and 2.5 has been dropped as of this release. New features ============ ``scipy.spatial`` improvements ------------------------------ cKDTree feature-complete ^^^^^^^^^^^^^^^^^^^^^^^^ Cython version of KDTree, cKDTree, is now feature-complete. Most operations (construction, query, query_ball_point, query_pairs, count_neighbors and sparse_distance_matrix) are between 200 and 1000 times faster in cKDTree than in KDTree. With very minor caveats, cKDTree has exactly the same interface as KDTree, and can be used as a drop-in replacement. Voronoi diagrams and convex hulls ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ `scipy.spatial` now contains functionality for computing Voronoi diagrams and convex hulls using the Qhull library. (Delaunay triangulation was available since Scipy 0.9.0.) Delaunay improvements ^^^^^^^^^^^^^^^^^^^^^ It's now possible to pass in custom Qhull options in Delaunay triangulation. Coplanar points are now also recorded, if present. Incremental construction of Delaunay triangulations is now also possible. Spectral estimators (``scipy.signal``) -------------------------------------- The functions ``scipy.signal.periodogram`` and ``scipy.signal.welch`` were added, providing DFT-based spectral estimators. ``scipy.optimize`` improvements ------------------------------- Callback functions in L-BFGS-B and TNC ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A callback mechanism was added to L-BFGS-B and TNC minimization solvers. Basin hopping global optimization (``scipy.optimize.basinhopping``) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A new global optimization algorithm. Basinhopping is designed to efficiently find the global minimum of a smooth function. ``scipy.special`` improvements ------------------------------ Revised complex error functions ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The computation of special functions related to the error function now uses a new `Faddeeva library from MIT <http://ab-initio.mit.edu/Faddeeva>`__ which increases their numerical precision. The scaled and imaginary error functions ``erfcx`` and ``erfi`` were also added, and the Dawson integral ``dawsn`` can now be evaluated for a complex argument. Faster orthogonal polynomials ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Evaluation of orthogonal polynomials (the ``eval_*`` routines) in now faster in ``scipy.special``, and their ``out=`` argument functions properly. ``scipy.sparse.linalg`` features -------------------------------- - In ``scipy.sparse.linalg.spsolve``, the ``b`` argument can now be either a vector or a matrix. - ``scipy.sparse.linalg.inv`` was added. This uses ``spsolve`` to compute a sparse matrix inverse. - ``scipy.sparse.linalg.expm`` was added. This computes the exponential of a sparse matrix using a similar algorithm to the existing dense array implementation in ``scipy.linalg.expm``. Listing Matlab(R) file contents in ``scipy.io`` ----------------------------------------------- A new function ``whosmat`` is available in ``scipy.io`` for inspecting contents of MAT files without reading them to memory. Documented BLAS and LAPACK low-level interfaces (``scipy.linalg``) ------------------------------------------------------------------ The modules `scipy.linalg.blas` and `scipy.linalg.lapack` can be used to access low-level BLAS and LAPACK functions. Polynomial interpolation improvements (``scipy.interpolate``) ------------------------------------------------------------- The barycentric, Krogh, piecewise and pchip polynomial interpolators in ``scipy.interpolate`` accept now an ``axis`` argument. Deprecated features =================== `scipy.lib.lapack` ------------------ The module `scipy.lib.lapack` is deprecated. You can use `scipy.linalg.lapack` instead. The module `scipy.lib.blas` was deprecated earlier in Scipy 0.10.0. `fblas` and `cblas` ------------------- Accessing the modules `scipy.linalg.fblas`, `cblas`, `flapack`, `clapack` is deprecated. Instead, use the modules `scipy.linalg.lapack` and `scipy.linalg.blas`. Backwards incompatible changes ============================== Removal of ``scipy.io.save_as_module`` -------------------------------------- The function ``scipy.io.save_as_module`` was deprecated in Scipy 0.11.0, and is now removed. Its private support modules ``scipy.io.dumbdbm_patched`` and ``scipy.io.dumb_shelve`` are also removed. Other changes ============= Authors ======= * Anton Akhmerov + * Alexander Eberspächer + * Anne Archibald * Jisk Attema + * K.-Michael Aye + * bemasc + * Sebastian Berg + * François Boulogne + * Matthew Brett * Lars Buitinck * Steven Byrnes + * Tim Cera + * Christian + * Keith Clawson + * David Cournapeau * Nathan Crock + * endolith * Bradley M. Froehle + * Matthew R Goodman * Christoph Gohlke * Ralf Gommers * Robert David Grant + * Yaroslav Halchenko * Charles Harris * Jonathan Helmus * Andreas Hilboll * Hugo + * Oleksandr Huziy * Jeroen Demeyer + * Johannes Schönberger + * Steven G. Johnson + * Chris Jordan-Squire * Jonathan Taylor + * Niklas Kroeger + * Jerome Kieffer + * kingson + * Josh Lawrence * Denis Laxalde * Alex Leach + * Lorenzo Luengo + * Stephen McQuay + * MinRK * Sturla Molden + * Eric Moore + * mszep + * Matt Newville + * Vlad Niculae * Travis Oliphant * David Parker + * Fabian Pedregosa * Josef Perktold * Zach Ploskey + * Alex Reinhart + * Richard Lindsley + * Gilles Rochefort + * Ciro Duran Santillli + * Jan Schlueter + * Jonathan Scholz + * Anthony Scopatz * Skipper Seabold * Fabrice Silva + * Scott Sinclair * Jacob Stevenson + * Sturla Molden + * Julian Taylor + * thorstenkranz + * John Travers + * True Price + * Nicky van Foreest * Jacob Vanderplas * Patrick Varilly * Daniel Velkov + * Pauli Virtanen * Stefan van der Walt * Warren Weckesser A total of 74 people contributed to this release. People with a "+" by their names contributed a patch for the first time.

Hi Ralf, scipy.misc.pilutil.radon is marked as deprecated and to be removed in 0.12, but is still available: https://github.com/scipy/scipy/blob/maintenance/0.12.x/scipy/misc/pilutil.py... Should it be removed before the release? Cheers, Tim On 30 March 2013 23:31, Ralf Gommers <ralf.gommers@gmail.com> wrote:
Hi,
I am pleased to announce the availability of the first release candidate of SciPy 0.12.0. This is shaping up to be another solid release, with some cool new features (see highlights below) and a large amount of bug fixes and maintenance work under the hood. The number of contributors also keeps rising steadily, we're at 74 so far for this release.
Sources and binaries can be found at http://sourceforge.net/projects/scipy/files/scipy/0.12.0rc1/, release notes are copied below.
Please try this release and report any problems on the mailing list. If no issues are found, the final release will be in one week.
Cheers, Ralf
========================== SciPy 0.12.0 Release Notes ==========================
.. note:: Scipy 0.12.0 is not released yet!
.. contents::
SciPy 0.12.0 is the culmination of 7 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 0.12.x branch, and on adding new features on the master branch.
Some of the highlights of this release are:
- Completed QHull wrappers in scipy.spatial. - cKDTree now a drop-in replacement for KDTree. - A new global optimizer, basinhopping. - Support for Python 2 and Python 3 from the same code base (no more 2to3).
This release requires Python 2.6, 2.7 or 3.1-3.3 and NumPy 1.5.1 or greater. Support for Python 2.4 and 2.5 has been dropped as of this release.
New features ============
``scipy.spatial`` improvements ------------------------------
cKDTree feature-complete ^^^^^^^^^^^^^^^^^^^^^^^^ Cython version of KDTree, cKDTree, is now feature-complete. Most operations (construction, query, query_ball_point, query_pairs, count_neighbors and sparse_distance_matrix) are between 200 and 1000 times faster in cKDTree than in KDTree. With very minor caveats, cKDTree has exactly the same interface as KDTree, and can be used as a drop-in replacement.
Voronoi diagrams and convex hulls ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ `scipy.spatial` now contains functionality for computing Voronoi diagrams and convex hulls using the Qhull library. (Delaunay triangulation was available since Scipy 0.9.0.)
Delaunay improvements ^^^^^^^^^^^^^^^^^^^^^ It's now possible to pass in custom Qhull options in Delaunay triangulation. Coplanar points are now also recorded, if present. Incremental construction of Delaunay triangulations is now also possible.
Spectral estimators (``scipy.signal``) -------------------------------------- The functions ``scipy.signal.periodogram`` and ``scipy.signal.welch`` were added, providing DFT-based spectral estimators.
``scipy.optimize`` improvements -------------------------------
Callback functions in L-BFGS-B and TNC ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A callback mechanism was added to L-BFGS-B and TNC minimization solvers.
Basin hopping global optimization (``scipy.optimize.basinhopping``) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A new global optimization algorithm. Basinhopping is designed to efficiently find the global minimum of a smooth function.
``scipy.special`` improvements ------------------------------
Revised complex error functions ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The computation of special functions related to the error function now uses a new `Faddeeva library from MIT <http://ab-initio.mit.edu/Faddeeva>`__ which increases their numerical precision. The scaled and imaginary error functions ``erfcx`` and ``erfi`` were also added, and the Dawson integral ``dawsn`` can now be evaluated for a complex argument.
Faster orthogonal polynomials ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Evaluation of orthogonal polynomials (the ``eval_*`` routines) in now faster in ``scipy.special``, and their ``out=`` argument functions properly.
``scipy.sparse.linalg`` features -------------------------------- - In ``scipy.sparse.linalg.spsolve``, the ``b`` argument can now be either a vector or a matrix. - ``scipy.sparse.linalg.inv`` was added. This uses ``spsolve`` to compute a sparse matrix inverse. - ``scipy.sparse.linalg.expm`` was added. This computes the exponential of a sparse matrix using a similar algorithm to the existing dense array implementation in ``scipy.linalg.expm``.
Listing Matlab(R) file contents in ``scipy.io`` ----------------------------------------------- A new function ``whosmat`` is available in ``scipy.io`` for inspecting contents of MAT files without reading them to memory.
Documented BLAS and LAPACK low-level interfaces (``scipy.linalg``) ------------------------------------------------------------------ The modules `scipy.linalg.blas` and `scipy.linalg.lapack` can be used to access low-level BLAS and LAPACK functions.
Polynomial interpolation improvements (``scipy.interpolate``) ------------------------------------------------------------- The barycentric, Krogh, piecewise and pchip polynomial interpolators in ``scipy.interpolate`` accept now an ``axis`` argument.
Deprecated features ===================
`scipy.lib.lapack` ------------------ The module `scipy.lib.lapack` is deprecated. You can use `scipy.linalg.lapack` instead. The module `scipy.lib.blas` was deprecated earlier in Scipy 0.10.0.
`fblas` and `cblas` ------------------- Accessing the modules `scipy.linalg.fblas`, `cblas`, `flapack`, `clapack` is deprecated. Instead, use the modules `scipy.linalg.lapack` and `scipy.linalg.blas`.
Backwards incompatible changes ==============================
Removal of ``scipy.io.save_as_module`` -------------------------------------- The function ``scipy.io.save_as_module`` was deprecated in Scipy 0.11.0, and is now removed.
Its private support modules ``scipy.io.dumbdbm_patched`` and ``scipy.io.dumb_shelve`` are also removed.
Other changes =============
Authors ======= * Anton Akhmerov + * Alexander Eberspächer + * Anne Archibald * Jisk Attema + * K.-Michael Aye + * bemasc + * Sebastian Berg + * François Boulogne + * Matthew Brett * Lars Buitinck * Steven Byrnes + * Tim Cera + * Christian + * Keith Clawson + * David Cournapeau * Nathan Crock + * endolith * Bradley M. Froehle + * Matthew R Goodman * Christoph Gohlke * Ralf Gommers * Robert David Grant + * Yaroslav Halchenko * Charles Harris * Jonathan Helmus * Andreas Hilboll * Hugo + * Oleksandr Huziy * Jeroen Demeyer + * Johannes Schönberger + * Steven G. Johnson + * Chris Jordan-Squire * Jonathan Taylor + * Niklas Kroeger + * Jerome Kieffer + * kingson + * Josh Lawrence * Denis Laxalde * Alex Leach + * Lorenzo Luengo + * Stephen McQuay + * MinRK * Sturla Molden + * Eric Moore + * mszep + * Matt Newville + * Vlad Niculae * Travis Oliphant * David Parker + * Fabian Pedregosa * Josef Perktold * Zach Ploskey + * Alex Reinhart + * Richard Lindsley + * Gilles Rochefort + * Ciro Duran Santillli + * Jan Schlueter + * Jonathan Scholz + * Anthony Scopatz * Skipper Seabold * Fabrice Silva + * Scott Sinclair * Jacob Stevenson + * Sturla Molden + * Julian Taylor + * thorstenkranz + * John Travers + * True Price + * Nicky van Foreest * Jacob Vanderplas * Patrick Varilly * Daniel Velkov + * Pauli Virtanen * Stefan van der Walt * Warren Weckesser
A total of 74 people contributed to this release. People with a "+" by their names contributed a patch for the first time.
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev

On Sun, Mar 31, 2013 at 4:08 AM, Tim Leslie <tim.leslie@gmail.com> wrote:
Hi Ralf,
scipy.misc.pilutil.radon is marked as deprecated and to be removed in 0.12, but is still available:
https://github.com/scipy/scipy/blob/maintenance/0.12.x/scipy/misc/pilutil.py...
Should it be removed before the release?
Hi Tim, thanks for noticing that. It should have been removed, however after RC1 is out I think it's a bit late. I'd prefer to change the message to 0.13 and remove it in master now. I'll send a PR for that. Ralf
Cheers,
Tim
On 30 March 2013 23:31, Ralf Gommers <ralf.gommers@gmail.com> wrote:
Hi,
I am pleased to announce the availability of the first release candidate of SciPy 0.12.0. This is shaping up to be another solid release, with some cool new features (see highlights below) and a large amount of bug fixes and maintenance work under the hood. The number of contributors also keeps rising steadily, we're at 74 so far for this release.
Sources and binaries can be found at http://sourceforge.net/projects/scipy/files/scipy/0.12.0rc1/, release notes are copied below.
Please try this release and report any problems on the mailing list. If no issues are found, the final release will be in one week.
Cheers, Ralf
========================== SciPy 0.12.0 Release Notes ==========================
.. note:: Scipy 0.12.0 is not released yet!
.. contents::
SciPy 0.12.0 is the culmination of 7 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 0.12.x branch, and on adding new features on the master branch.
Some of the highlights of this release are:
- Completed QHull wrappers in scipy.spatial. - cKDTree now a drop-in replacement for KDTree. - A new global optimizer, basinhopping. - Support for Python 2 and Python 3 from the same code base (no more 2to3).
This release requires Python 2.6, 2.7 or 3.1-3.3 and NumPy 1.5.1 or greater. Support for Python 2.4 and 2.5 has been dropped as of this release.
New features ============
``scipy.spatial`` improvements ------------------------------
cKDTree feature-complete ^^^^^^^^^^^^^^^^^^^^^^^^ Cython version of KDTree, cKDTree, is now feature-complete. Most operations (construction, query, query_ball_point, query_pairs, count_neighbors and sparse_distance_matrix) are between 200 and 1000 times faster in cKDTree than in KDTree. With very minor caveats, cKDTree has exactly the same interface as KDTree, and can be used as a drop-in replacement.
Voronoi diagrams and convex hulls ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ `scipy.spatial` now contains functionality for computing Voronoi diagrams and convex hulls using the Qhull library. (Delaunay triangulation was available since Scipy 0.9.0.)
Delaunay improvements ^^^^^^^^^^^^^^^^^^^^^ It's now possible to pass in custom Qhull options in Delaunay triangulation. Coplanar points are now also recorded, if present. Incremental construction of Delaunay triangulations is now also possible.
Spectral estimators (``scipy.signal``) -------------------------------------- The functions ``scipy.signal.periodogram`` and ``scipy.signal.welch`` were added, providing DFT-based spectral estimators.
``scipy.optimize`` improvements -------------------------------
Callback functions in L-BFGS-B and TNC ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A callback mechanism was added to L-BFGS-B and TNC minimization solvers.
Basin hopping global optimization (``scipy.optimize.basinhopping``) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A new global optimization algorithm. Basinhopping is designed to efficiently find the global minimum of a smooth function.
``scipy.special`` improvements ------------------------------
Revised complex error functions ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The computation of special functions related to the error function now uses a new `Faddeeva library from MIT <http://ab-initio.mit.edu/Faddeeva>`__ which increases their numerical precision. The scaled and imaginary error functions ``erfcx`` and ``erfi`` were also added, and the Dawson integral ``dawsn`` can now be evaluated for a complex argument.
Faster orthogonal polynomials ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Evaluation of orthogonal polynomials (the ``eval_*`` routines) in now faster in ``scipy.special``, and their ``out=`` argument functions properly.
``scipy.sparse.linalg`` features -------------------------------- - In ``scipy.sparse.linalg.spsolve``, the ``b`` argument can now be either a vector or a matrix. - ``scipy.sparse.linalg.inv`` was added. This uses ``spsolve`` to compute a sparse matrix inverse. - ``scipy.sparse.linalg.expm`` was added. This computes the exponential of a sparse matrix using a similar algorithm to the existing dense array implementation in ``scipy.linalg.expm``.
Listing Matlab(R) file contents in ``scipy.io`` ----------------------------------------------- A new function ``whosmat`` is available in ``scipy.io`` for inspecting contents of MAT files without reading them to memory.
Documented BLAS and LAPACK low-level interfaces (``scipy.linalg``) ------------------------------------------------------------------ The modules `scipy.linalg.blas` and `scipy.linalg.lapack` can be used to access low-level BLAS and LAPACK functions.
Polynomial interpolation improvements (``scipy.interpolate``) ------------------------------------------------------------- The barycentric, Krogh, piecewise and pchip polynomial interpolators in ``scipy.interpolate`` accept now an ``axis`` argument.
Deprecated features ===================
`scipy.lib.lapack` ------------------ The module `scipy.lib.lapack` is deprecated. You can use `scipy.linalg.lapack` instead. The module `scipy.lib.blas` was deprecated earlier in Scipy 0.10.0.
`fblas` and `cblas` ------------------- Accessing the modules `scipy.linalg.fblas`, `cblas`, `flapack`, `clapack` is deprecated. Instead, use the modules `scipy.linalg.lapack` and `scipy.linalg.blas`.
Backwards incompatible changes ==============================
Removal of ``scipy.io.save_as_module`` -------------------------------------- The function ``scipy.io.save_as_module`` was deprecated in Scipy 0.11.0, and is now removed.
Its private support modules ``scipy.io.dumbdbm_patched`` and ``scipy.io.dumb_shelve`` are also removed.
Other changes =============
Authors ======= * Anton Akhmerov + * Alexander Eberspächer + * Anne Archibald * Jisk Attema + * K.-Michael Aye + * bemasc + * Sebastian Berg + * François Boulogne + * Matthew Brett * Lars Buitinck * Steven Byrnes + * Tim Cera + * Christian + * Keith Clawson + * David Cournapeau * Nathan Crock + * endolith * Bradley M. Froehle + * Matthew R Goodman * Christoph Gohlke * Ralf Gommers * Robert David Grant + * Yaroslav Halchenko * Charles Harris * Jonathan Helmus * Andreas Hilboll * Hugo + * Oleksandr Huziy * Jeroen Demeyer + * Johannes Schönberger + * Steven G. Johnson + * Chris Jordan-Squire * Jonathan Taylor + * Niklas Kroeger + * Jerome Kieffer + * kingson + * Josh Lawrence * Denis Laxalde * Alex Leach + * Lorenzo Luengo + * Stephen McQuay + * MinRK * Sturla Molden + * Eric Moore + * mszep + * Matt Newville + * Vlad Niculae * Travis Oliphant * David Parker + * Fabian Pedregosa * Josef Perktold * Zach Ploskey + * Alex Reinhart + * Richard Lindsley + * Gilles Rochefort + * Ciro Duran Santillli + * Jan Schlueter + * Jonathan Scholz + * Anthony Scopatz * Skipper Seabold * Fabrice Silva + * Scott Sinclair * Jacob Stevenson + * Sturla Molden + * Julian Taylor + * thorstenkranz + * John Travers + * True Price + * Nicky van Foreest * Jacob Vanderplas * Patrick Varilly * Daniel Velkov + * Pauli Virtanen * Stefan van der Walt * Warren Weckesser
A total of 74 people contributed to this release. People with a "+" by their names contributed a patch for the first time.
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev
_______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org http://mail.scipy.org/mailman/listinfo/scipy-dev

That sounds fine to me, I don't actually use the function, I just noticed that comment while browsing the source. Tim On 31 March 2013 22:35, Ralf Gommers <ralf.gommers@gmail.com> wrote:
On Sun, Mar 31, 2013 at 4:08 AM, Tim Leslie <tim.leslie@gmail.com> wrote:
Hi Ralf,
scipy.misc.pilutil.radon is marked as deprecated and to be removed in 0.12, but is still available:
https://github.com/scipy/scipy/blob/maintenance/0.12.x/scipy/misc/pilutil.py...
Should it be removed before the release?
Hi Tim, thanks for noticing that. It should have been removed, however after RC1 is out I think it's a bit late. I'd prefer to change the message to 0.13 and remove it in master now. I'll send a PR for that.
Ralf
Cheers,
Tim
On 30 March 2013 23:31, Ralf Gommers <ralf.gommers@gmail.com> wrote:
Hi,
I am pleased to announce the availability of the first release candidate of SciPy 0.12.0. This is shaping up to be another solid release, with some cool new features (see highlights below) and a large amount of bug fixes and maintenance work under the hood. The number of contributors also keeps rising steadily, we're at 74 so far for this release.
Sources and binaries can be found at http://sourceforge.net/projects/scipy/files/scipy/0.12.0rc1/, release notes are copied below.
Please try this release and report any problems on the mailing list. If no issues are found, the final release will be in one week.
Cheers, Ralf
========================== SciPy 0.12.0 Release Notes ==========================
.. note:: Scipy 0.12.0 is not released yet!
.. contents::
SciPy 0.12.0 is the culmination of 7 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 0.12.x branch, and on adding new features on the master branch.
Some of the highlights of this release are:
- Completed QHull wrappers in scipy.spatial. - cKDTree now a drop-in replacement for KDTree. - A new global optimizer, basinhopping. - Support for Python 2 and Python 3 from the same code base (no more 2to3).
This release requires Python 2.6, 2.7 or 3.1-3.3 and NumPy 1.5.1 or greater. Support for Python 2.4 and 2.5 has been dropped as of this release.
New features ============
``scipy.spatial`` improvements ------------------------------
cKDTree feature-complete ^^^^^^^^^^^^^^^^^^^^^^^^ Cython version of KDTree, cKDTree, is now feature-complete. Most operations (construction, query, query_ball_point, query_pairs, count_neighbors and sparse_distance_matrix) are between 200 and 1000 times faster in cKDTree than in KDTree. With very minor caveats, cKDTree has exactly the same interface as KDTree, and can be used as a drop-in replacement.
Voronoi diagrams and convex hulls ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ `scipy.spatial` now contains functionality for computing Voronoi diagrams and convex hulls using the Qhull library. (Delaunay triangulation was available since Scipy 0.9.0.)
Delaunay improvements ^^^^^^^^^^^^^^^^^^^^^ It's now possible to pass in custom Qhull options in Delaunay triangulation. Coplanar points are now also recorded, if present. Incremental construction of Delaunay triangulations is now also possible.
Spectral estimators (``scipy.signal``) -------------------------------------- The functions ``scipy.signal.periodogram`` and ``scipy.signal.welch`` were added, providing DFT-based spectral estimators.
``scipy.optimize`` improvements -------------------------------
Callback functions in L-BFGS-B and TNC ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A callback mechanism was added to L-BFGS-B and TNC minimization solvers.
Basin hopping global optimization (``scipy.optimize.basinhopping``) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A new global optimization algorithm. Basinhopping is designed to efficiently find the global minimum of a smooth function.
``scipy.special`` improvements ------------------------------
Revised complex error functions ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The computation of special functions related to the error function now uses a new `Faddeeva library from MIT <http://ab-initio.mit.edu/Faddeeva>`__ which increases their numerical precision. The scaled and imaginary error functions ``erfcx`` and ``erfi`` were also added, and the Dawson integral ``dawsn`` can now be evaluated for a complex argument.
Faster orthogonal polynomials ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Evaluation of orthogonal polynomials (the ``eval_*`` routines) in now faster in ``scipy.special``, and their ``out=`` argument functions properly.
``scipy.sparse.linalg`` features -------------------------------- - In ``scipy.sparse.linalg.spsolve``, the ``b`` argument can now be either a vector or a matrix. - ``scipy.sparse.linalg.inv`` was added. This uses ``spsolve`` to compute a sparse matrix inverse. - ``scipy.sparse.linalg.expm`` was added. This computes the exponential of a sparse matrix using a similar algorithm to the existing dense array implementation in ``scipy.linalg.expm``.
Listing Matlab(R) file contents in ``scipy.io`` ----------------------------------------------- A new function ``whosmat`` is available in ``scipy.io`` for inspecting contents of MAT files without reading them to memory.
Documented BLAS and LAPACK low-level interfaces (``scipy.linalg``) ------------------------------------------------------------------ The modules `scipy.linalg.blas` and `scipy.linalg.lapack` can be used to access low-level BLAS and LAPACK functions.
Polynomial interpolation improvements (``scipy.interpolate``) ------------------------------------------------------------- The barycentric, Krogh, piecewise and pchip polynomial interpolators in ``scipy.interpolate`` accept now an ``axis`` argument.
Deprecated features ===================
`scipy.lib.lapack` ------------------ The module `scipy.lib.lapack` is deprecated. You can use `scipy.linalg.lapack` instead. The module `scipy.lib.blas` was deprecated earlier in Scipy 0.10.0.
`fblas` and `cblas` ------------------- Accessing the modules `scipy.linalg.fblas`, `cblas`, `flapack`, `clapack` is deprecated. Instead, use the modules `scipy.linalg.lapack` and `scipy.linalg.blas`.
Backwards incompatible changes ==============================
Removal of ``scipy.io.save_as_module`` -------------------------------------- The function ``scipy.io.save_as_module`` was deprecated in Scipy 0.11.0, and is now removed.
Its private support modules ``scipy.io.dumbdbm_patched`` and ``scipy.io.dumb_shelve`` are also removed.
Other changes =============
Authors ======= * Anton Akhmerov + * Alexander Eberspächer + * Anne Archibald * Jisk Attema + * K.-Michael Aye + * bemasc + * Sebastian Berg + * François Boulogne + * Matthew Brett * Lars Buitinck * Steven Byrnes + * Tim Cera + * Christian + * Keith Clawson + * David Cournapeau * Nathan Crock + * endolith * Bradley M. Froehle + * Matthew R Goodman * Christoph Gohlke * Ralf Gommers * Robert David Grant + * Yaroslav Halchenko * Charles Harris * Jonathan Helmus * Andreas Hilboll * Hugo + * Oleksandr Huziy * Jeroen Demeyer + * Johannes Schönberger + * Steven G. Johnson + * Chris Jordan-Squire * Jonathan Taylor + * Niklas Kroeger + * Jerome Kieffer + * kingson + * Josh Lawrence * Denis Laxalde * Alex Leach + * Lorenzo Luengo + * Stephen McQuay + * MinRK * Sturla Molden + * Eric Moore + * mszep + * Matt Newville + * Vlad Niculae * Travis Oliphant * David Parker + * Fabian Pedregosa * Josef Perktold * Zach Ploskey + * Alex Reinhart + * Richard Lindsley + * Gilles Rochefort + * Ciro Duran Santillli + * Jan Schlueter + * Jonathan Scholz + * Anthony Scopatz * Skipper Seabold * Fabrice Silva + * Scott Sinclair * Jacob Stevenson + * Sturla Molden + * Julian Taylor + * thorstenkranz + * John Travers + * True Price + * Nicky van Foreest * Jacob Vanderplas * Patrick Varilly * Daniel Velkov + * Pauli Virtanen * Stefan van der Walt * Warren Weckesser
A total of 74 people contributed to this release. People with a "+" by their names contributed a patch for the first time.
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On Sat, Mar 30, 2013 at 1:31 PM, Ralf Gommers <ralf.gommers@gmail.com>wrote:
Hi,
I am pleased to announce the availability of the first release candidate of SciPy 0.12.0. This is shaping up to be another solid release, with some cool new features (see highlights below) and a large amount of bug fixes and maintenance work under the hood. The number of contributors also keeps rising steadily, we're at 74 so far for this release.
Sources and binaries can be found at http://sourceforge.net/projects/scipy/files/scipy/0.12.0rc1/, release notes are copied below.
Please try this release and report any problems on the mailing list. If no issues are found, the final release will be in one week.
Hi, I'm about to cut the final release but am not really sure about how heavily the beta and RC were tested. Normally there are always a few Windows-specific issues for example, this time nothing. A few "I tested this on platform X and it looks good" responses would reassure me. Thanks, Ralf

On 4/6/2013 3:22 AM, Ralf Gommers wrote:
On Sat, Mar 30, 2013 at 1:31 PM, Ralf Gommers <ralf.gommers@gmail.com <mailto:ralf.gommers@gmail.com>> wrote:
Hi,
I am pleased to announce the availability of the first release candidate of SciPy 0.12.0. This is shaping up to be another solid release, with some cool new features (see highlights below) and a large amount of bug fixes and maintenance work under the hood. The number of contributors also keeps rising steadily, we're at 74 so far for this release.
Sources and binaries can be found at http://sourceforge.net/projects/scipy/files/scipy/0.12.0rc1/, release notes are copied below.
Please try this release and report any problems on the mailing list. If no issues are found, the final release will be in one week.
Hi, I'm about to cut the final release but am not really sure about how heavily the beta and RC were tested. Normally there are always a few Windows-specific issues for example, this time nothing. A few "I tested this on platform X and it looks good" responses would reassure me.
Thanks, Ralf
Looks good. It builds and tests OK on Windows with msvc, numpy-MKL 1.7.1rc, Python 2.6 to 3.3, 32 and 64 bit. Occasionally/rarely test_singular fails but that is known (http://projects.scipy.org/scipy/ticket/1735). Christoph

On Sat, Apr 6, 2013 at 12:35 PM, Christoph Gohlke <cgohlke@uci.edu> wrote:
On 4/6/2013 3:22 AM, Ralf Gommers wrote:
On Sat, Mar 30, 2013 at 1:31 PM, Ralf Gommers <ralf.gommers@gmail.com <mailto:ralf.gommers@gmail.com>> wrote:
Hi,
I am pleased to announce the availability of the first release candidate of SciPy 0.12.0. This is shaping up to be another solid release, with some cool new features (see highlights below) and a large amount of bug fixes and maintenance work under the hood. The number of contributors also keeps rising steadily, we're at 74 so far for this release.
Sources and binaries can be found at http://sourceforge.net/projects/scipy/files/scipy/0.12.0rc1/, release notes are copied below.
Please try this release and report any problems on the mailing list. If no issues are found, the final release will be in one week.
Hi, I'm about to cut the final release but am not really sure about how heavily the beta and RC were tested. Normally there are always a few Windows-specific issues for example, this time nothing. A few "I tested this on platform X and it looks good" responses would reassure me.
Thanks, Ralf
Looks good. It builds and tests OK on Windows with msvc, numpy-MKL 1.7.1rc, Python 2.6 to 3.3, 32 and 64 bit.
Thanks Christophe! Looks like we can finish up the release this weekend then.
Occasionally/rarely test_singular fails but that is known (http://projects.scipy.org/scipy/ticket/1735).
Good point, that should be then marked as knownfail for the release. I occasionally see that one on Linux as well. Ralf

On Sat, Apr 6, 2013 at 6:39 AM, Ralf Gommers <ralf.gommers@gmail.com> wrote:
On Sat, Apr 6, 2013 at 12:35 PM, Christoph Gohlke <cgohlke@uci.edu> wrote:
On 4/6/2013 3:22 AM, Ralf Gommers wrote:
On Sat, Mar 30, 2013 at 1:31 PM, Ralf Gommers <ralf.gommers@gmail.com <mailto:ralf.gommers@gmail.com>> wrote:
Hi,
I am pleased to announce the availability of the first release candidate of SciPy 0.12.0. This is shaping up to be another solid release, with some cool new features (see highlights below) and a large amount of bug fixes and maintenance work under the hood. The number of contributors also keeps rising steadily, we're at 74 so far for this release.
Sources and binaries can be found at http://sourceforge.net/projects/scipy/files/scipy/0.12.0rc1/, release notes are copied below.
Please try this release and report any problems on the mailing list. If no issues are found, the final release will be in one week.
Hi, I'm about to cut the final release but am not really sure about how heavily the beta and RC were tested. Normally there are always a few Windows-specific issues for example, this time nothing. A few "I tested this on platform X and it looks good" responses would reassure me.
Thanks, Ralf
Looks good. It builds and tests OK on Windows with msvc, numpy-MKL 1.7.1rc, Python 2.6 to 3.3, 32 and 64 bit.
Thanks Christophe! Looks like we can finish up the release this weekend then.
Occasionally/rarely test_singular fails but that is known (http://projects.scipy.org/scipy/ticket/1735).
Good point, that should be then marked as knownfail for the release. I occasionally see that one on Linux as well.
I tried out the py 2.7, 32bit installer, and I don't see any errors or failures (besides singular). (statsmodels has only one failure related to fsolve, but that's for every version of scipy > 0.9. statsmodels also has one or two random failures in what should be deterministic tests, but they also happen every once in a while independent of scipy version.) Thanks, Josef
Ralf
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On Sat, Apr 6, 2013 at 8:07 PM, <josef.pktd@gmail.com> wrote:
On Sat, Apr 6, 2013 at 6:39 AM, Ralf Gommers <ralf.gommers@gmail.com> wrote:
On Sat, Apr 6, 2013 at 12:35 PM, Christoph Gohlke <cgohlke@uci.edu>
On 4/6/2013 3:22 AM, Ralf Gommers wrote:
On Sat, Mar 30, 2013 at 1:31 PM, Ralf Gommers <ralf.gommers@gmail.com <mailto:ralf.gommers@gmail.com>> wrote:
Hi,
I am pleased to announce the availability of the first release candidate of SciPy 0.12.0. This is shaping up to be another solid release, with some cool new features (see highlights below) and a large amount of bug fixes and maintenance work under the hood. The number of contributors also keeps rising steadily, we're at 74 so far for this release.
Sources and binaries can be found at http://sourceforge.net/projects/scipy/files/scipy/0.12.0rc1/, release notes are copied below.
Please try this release and report any problems on the mailing
wrote: list.
If no issues are found, the final release will be in one week.
Hi, I'm about to cut the final release but am not really sure about
how
heavily the beta and RC were tested. Normally there are always a few Windows-specific issues for example, this time nothing. A few "I tested this on platform X and it looks good" responses would reassure me.
Thanks, Ralf
Looks good. It builds and tests OK on Windows with msvc, numpy-MKL 1.7.1rc, Python 2.6 to 3.3, 32 and 64 bit.
Thanks Christophe! Looks like we can finish up the release this weekend then.
Occasionally/rarely test_singular fails but that is known (http://projects.scipy.org/scipy/ticket/1735).
Good point, that should be then marked as knownfail for the release. I occasionally see that one on Linux as well.
I tried out the py 2.7, 32bit installer, and I don't see any errors or failures (besides singular).
Thanks Josef. I created the release tag, announcement and binaries will follow. Ralf
(statsmodels has only one failure related to fsolve, but that's for every version of scipy > 0.9. statsmodels also has one or two random failures in what should be deterministic tests, but they also happen every once in a while independent of scipy version.)
Thanks,
Josef
Ralf
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participants (4)
-
Christoph Gohlke
-
josef.pktd@gmail.com
-
Ralf Gommers
-
Tim Leslie