Mailman 3 January 2016 - SciPy-Dev

dense output option in integrate.ode
by Evgeni Burovski Feb. 20, 2017

Feb. 20, 2017

Hi David, Hi Jim, > I am new to SciPy-dev. Will the dense output option in scipy.integrate.ode > become available in 0.17.0? This is a feature already available in the > original FORTAN, but wasn't implemented in the wrapper. If the feature is sent as a pull request against the scipy master branch, the PR is reviewed by the maintainers of the integrate package and merged into master before the release split, then yes, it would be available in 0.17.0. So far I do not see any progress towards it. > I wrote these dense output extensions that you listed: > > https://github.com/jddmartin/scipy/tree/dense_output_from_dopri5_and_dop853 > https://github.com/jddmartin/dense_output_example_usage > > but I didn't issue any pull request to scipy. I sent this message to the > scipy developers list: > http://article.gmane.org/gmane.comp.python.scientific.devel/19635/ > explaining the changes. I was hoping for some feedback before issuing a > pull request. Ah, I see that the email likely fell through the cracks back in April. Sorry about that. You might want to ping that email thread once more or send a pull request on github (or both). <snip> Cheers, Evgeni

3 5

ANN: scipy 0.17.0 release
by Evgeni Burovski Feb. 15, 2016

Feb. 15, 2016

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 -----BEGIN PGP SIGNED MESSAGE----- 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 <https://github.com/scipy/scipy/issues/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 now return and sparse matrix type `scipy.interpolate` improvements - -------------------------------- Out-of-bounds behavior of `scipy.interpolate.interp1d` has been improved. Use a two-element tuple for the ``fill_value`` argument to specify separate fill values for input below and above the interpolation range. Linear and nearest interpolation kinds of `scipy.interpolate.interp1d` support extrapolation via the ``fill_value="extrapolate"`` keyword. ``fill_value`` can also be set to an array-like (or a two-element tuple of array-likes for separate below and above values) so long as it broadcasts properly to the non-interpolated dimensions of an array. This was implicitly supported by previous versions of scipy, but support has now been formalized and gets compatibility-checked before use. For example, a set of ``y`` values to interpolate with shape ``(2, 3, 5)`` interpolated along the last axis (2) could accept a ``fill_value`` array with shape ``()`` (singleton), ``(1,)``, ``(2, 1)``, ``(1, 3)``, ``(3,)``, or ``(2, 3)``; or it can be a 2-element tuple to specify separate below and above bounds, where each of the two tuple elements obeys proper broadcasting rules. `scipy.linalg` improvements - --------------------------- The default algorithm for `scipy.linalg.leastsq` has been changed to use LAPACK's function ``*gelsd``. Users wanting to get the previous behavior can use a new keyword ``lapack_driver="gelss"`` (allowed values are "gelss", "gelsd" and "gelsy"). ``scipy.sparse`` matrices and linear operators now support the matmul (``@``) operator when available (Python 3.5+). See [PEP 465](http://legacy.python.org/dev/peps/pep-0465/) A new function `scipy.linalg.ordqz`, for QZ decomposition with reordering, has been added. Deprecated features =================== ``scipy.stats.histogram`` is deprecated in favor of ``np.histogram``, which is faster and provides the same functionality. ``scipy.stats.threshold`` and ``scipy.mstats.threshold`` are deprecated in favor of ``np.clip``. See issue #617 for details. ``scipy.stats.ss`` is deprecated. This is a support function, not meant to be exposed to the user. Also, the name is unclear. See issue #663 for details. ``scipy.stats.square_of_sums`` is deprecated. This too is a support function not meant to be exposed to the user. See issues #665 and #663 for details. ``scipy.stats.f_value``, ``scipy.stats.f_value_multivariate``, ``scipy.stats.f_value_wilks_lambda``, and ``scipy.mstats.f_value_wilks_lambda`` are deprecated. These are related to ANOVA, for which ``scipy.stats`` provides quite limited functionality and these functions are not very useful standalone. See issues #660 and #650 for details. ``scipy.stats.chisqprob`` is deprecated. This is an alias. ``stats.chi2.sf`` should be used instead. ``scipy.stats.betai`` is deprecated. This is an alias for ``special.betainc`` which should be used instead. Backwards incompatible changes ============================== The functions ``stats.trim1`` and ``stats.trimboth`` now make sure the elements trimmed are the lowest and/or highest, depending on the case. Slicing without at least partial sorting was previously done, but didn't make sense for unsorted input. When ``variable_names`` is set to an empty list, ``scipy.io.loadmat`` now correctly returns no values instead of all the contents of the MAT file. Element-wise multiplication of sparse matrices now returns a sparse result in all cases. Previously, multiplying a sparse matrix with a dense matrix or array would return a dense matrix. The function ``misc.lena`` has been removed due to license incompatibility. The constructor for ``sparse.coo_matrix`` no longer accepts ``(None, (m,n))`` to construct an all-zero matrix of shape ``(m,n)``. This functionality was deprecated since at least 2007 and was already broken in the previous SciPy release. Use ``coo_matrix((m,n))`` instead. The Cython wrappers in ``linalg.cython_lapack`` for the LAPACK routines ``*gegs``, ``*gegv``, ``*gelsx``, ``*geqpf``, ``*ggsvd``, ``*ggsvp``, ``*lahrd``, ``*latzm``, ``*tzrqf`` have been removed since these routines are not present in the new LAPACK 3.6.0 release. With the exception of the routines ``*ggsvd`` and ``*ggsvp``, these were all deprecated in favor of routines that are currently present in our Cython LAPACK wrappers. Because the LAPACK ``*gegv`` routines were removed in LAPACK 3.6.0. The corresponding Python wrappers in ``scipy.linalg.lapack`` are now deprecated and will be removed in a future release. The source files for these routines have been temporarily included as a part of ``scipy.linalg`` so that SciPy can be built against LAPACK versions that do not provide these deprecated routines. Other changes ============= Html and pdf documentation of development versions of Scipy is now automatically rebuilt after every merged pull request. `scipy.constants` is updated to the CODATA 2014 recommended values. Usage of `scipy.fftpack` functions within Scipy has been changed in such a way that `PyFFTW <http://hgomersall.github.io/pyFFTW/>`__ can easily replace `scipy.fftpack` functions (with improved performance). See `gh-5295 <https://github.com/scipy/scipy/pull/5295>`__ for details. The ``imread`` functions in `scipy.misc` and `scipy.ndimage` were unified, for which a ``mode`` argument was added to `scipy.misc.imread`. Also, bugs for 1-bit and indexed RGB image formats were fixed. ``runtests.py``, the development script to build and test Scipy, now allows building in parallel with ``--parallel``. Authors ======= * @cel4 + * @chemelnucfin + * @endolith * @mamrehn + * @tosh1ki + * Joshua L. Adelman + * Anne Archibald * Hervé Audren + * Vincent Barrielle + * Bruno Beltran + * Sumit Binnani + * Joseph Jon Booker * Olga Botvinnik + * Michael Boyle + * Matthew Brett * Zaz Brown + * Lars Buitinck * Pete Bunch + * Evgeni Burovski * CJ Carey * Ien Cheng + * Cody + * Jaime Fernandez del Rio * Ales Erjavec + * Abraham Escalante * Yves-Rémi Van Eycke + * Yu Feng + * Eric Firing * Francis T. O'Donovan + * André Gaul * Christoph Gohlke * Ralf Gommers * Alex Griffing * Alexander Grigorievskiy * Charles Harris * Jörn Hees + * Ian Henriksen * Derek Homeier + * David Menéndez Hurtado * Gert-Ludwig Ingold * Aakash Jain + * Rohit Jamuar + * Jan Schlüter * Johannes Ballé * Luke Zoltan Kelley + * Jason King + * Andreas Kopecky + * Eric Larson * Denis Laxalde * Antony Lee * Gregory R. Lee * Josh Levy-Kramer + * Sam Lewis + * François Magimel + * Martín Gaitán + * Sam Mason + * Andreas Mayer * Nikolay Mayorov * Damon McDougall + * Robert McGibbon * Sturla Molden * Will Monroe + * Eric Moore * Maniteja Nandana * Vikram Natarajan + * Andrew Nelson * Marti Nito + * Behzad Nouri + * Daisuke Oyama + * Giorgio Patrini + * Fabian Paul + * Christoph Paulik + * Mad Physicist + * Irvin Probst * Sebastian Pucilowski + * Ted Pudlik + * Eric Quintero * Yoav Ram + * Joscha Reimer + * Juha Remes * Frederik Rietdijk + * Rémy Léone + * Christian Sachs + * Skipper Seabold * Sebastian Skoupý + * Alex Seewald + * Andreas Sorge + * Bernardo Sulzbach + * Julian Taylor * Louis Tiao + * Utkarsh Upadhyay + * Jacob Vanderplas * Gael Varoquaux + * Pauli Virtanen * Fredrik Wallner + * Stefan van der Walt * James Webber + * Warren Weckesser * Raphael Wettinger + * Josh Wilson + * Nat Wilson + * Peter Yin + A total of 101 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. Issues closed for 0.17.0 - ------------------------ - - `#1923 <https://github.com/scipy/scipy/issues/1923>`__: problem with numpy 0's in stats.poisson.rvs (Trac #1398) - - `#2138 <https://github.com/scipy/scipy/issues/2138>`__: scipy.misc.imread segfaults on 1 bit png (Trac #1613) - - `#2237 <https://github.com/scipy/scipy/issues/2237>`__: distributions do not accept complex arguments (Trac #1718) - - `#2282 <https://github.com/scipy/scipy/issues/2282>`__: scipy.special.hyp1f1(0.5, 1.5, -1000) fails (Trac #1763) - - `#2618 <https://github.com/scipy/scipy/issues/2618>`__: poisson.pmf returns NaN if mu is 0 - - `#2957 <https://github.com/scipy/scipy/issues/2957>`__: hyp1f1 precision issue - - `#2997 <https://github.com/scipy/scipy/issues/2997>`__: FAIL: test_qhull.TestUtilities.test_more_barycentric_transforms - - `#3129 <https://github.com/scipy/scipy/issues/3129>`__: No way to set ranges for fitting parameters in Optimize functions - - `#3191 <https://github.com/scipy/scipy/issues/3191>`__: interp1d should contain a fill_value_below and a fill_value_above... - - `#3453 <https://github.com/scipy/scipy/issues/3453>`__: PchipInterpolator sets slopes at edges differently than Matlab's... - - `#4106 <https://github.com/scipy/scipy/issues/4106>`__: ndimage._ni_support._normalize_sequence() fails with numpy.int64 - - `#4118 <https://github.com/scipy/scipy/issues/4118>`__: `scipy.integrate.ode.set_solout` called after `scipy.integrate.ode.set_initial_value` fails silently - - `#4233 <https://github.com/scipy/scipy/issues/4233>`__: 1D scipy.interpolate.griddata using method=nearest produces nans... - - `#4375 <https://github.com/scipy/scipy/issues/4375>`__: All tests fail due to bad file permissions - - `#4580 <https://github.com/scipy/scipy/issues/4580>`__: scipy.ndimage.filters.convolve documenation is incorrect - - `#4627 <https://github.com/scipy/scipy/issues/4627>`__: logsumexp with sign indicator - enable calculation with negative... - - `#4702 <https://github.com/scipy/scipy/issues/4702>`__: logsumexp with zero scaling factor - - `#4834 <https://github.com/scipy/scipy/issues/4834>`__: gammainc should return 1.0 instead of NaN for infinite x - - `#4838 <https://github.com/scipy/scipy/issues/4838>`__: enh: exprel special function - - `#4862 <https://github.com/scipy/scipy/issues/4862>`__: the scipy.special.boxcox function is inaccurate for denormal... - - `#4887 <https://github.com/scipy/scipy/issues/4887>`__: Spherical harmonic incongruences - - `#4895 <https://github.com/scipy/scipy/issues/4895>`__: some scipy ufuncs have inconsistent output dtypes? - - `#4923 <https://github.com/scipy/scipy/issues/4923>`__: logm does not aggressively convert complex outputs to float - - `#4932 <https://github.com/scipy/scipy/issues/4932>`__: BUG: stats: The `fit` method of the distributions silently ignores... - - `#4956 <https://github.com/scipy/scipy/issues/4956>`__: Documentation error in `scipy.special.bi_zeros` - - `#4957 <https://github.com/scipy/scipy/issues/4957>`__: Docstring for `pbvv_seq` is wrong - - `#4967 <https://github.com/scipy/scipy/issues/4967>`__: block_diag should look at dtypes of all arguments, not only the... - - `#5037 <https://github.com/scipy/scipy/issues/5037>`__: scipy.optimize.minimize error messages are printed to stdout... - - `#5039 <https://github.com/scipy/scipy/issues/5039>`__: Cubic interpolation: On entry to DGESDD parameter number 12 had... - - `#5163 <https://github.com/scipy/scipy/issues/5163>`__: Base case example of Hierarchical Clustering (offer) - - `#5181 <https://github.com/scipy/scipy/issues/5181>`__: BUG: stats.genextreme.entropy should use the explicit formula - - `#5184 <https://github.com/scipy/scipy/issues/5184>`__: Some? wheels don't express a numpy dependency - - `#5197 <https://github.com/scipy/scipy/issues/5197>`__: mstats: test_kurtosis fails (ULP max is 2) - - `#5260 <https://github.com/scipy/scipy/issues/5260>`__: Typo causing an error in splrep - - `#5263 <https://github.com/scipy/scipy/issues/5263>`__: Default epsilon in rbf.py fails for colinear points - - `#5276 <https://github.com/scipy/scipy/issues/5276>`__: Reading empty (no data) arff file fails - - `#5280 <https://github.com/scipy/scipy/issues/5280>`__: 1d scipy.signal.convolve much slower than numpy.convolve - - `#5326 <https://github.com/scipy/scipy/issues/5326>`__: Implementation error in scipy.interpolate.PchipInterpolator - - `#5370 <https://github.com/scipy/scipy/issues/5370>`__: Test issue with test_quadpack and libm.so as a linker script - - `#5426 <https://github.com/scipy/scipy/issues/5426>`__: ERROR: test_stats.test_chisquare_masked_arrays - - `#5427 <https://github.com/scipy/scipy/issues/5427>`__: Automate installing correct numpy versions in numpy-vendor image - - `#5430 <https://github.com/scipy/scipy/issues/5430>`__: Python3 : Numpy scalar types "not iterable"; specific instance... - - `#5450 <https://github.com/scipy/scipy/issues/5450>`__: BUG: spatial.ConvexHull triggers a seg. fault when given nans. - - `#5478 <https://github.com/scipy/scipy/issues/5478>`__: clarify the relation between matrix normal distribution and `multivariate_normal` - - `#5539 <https://github.com/scipy/scipy/issues/5539>`__: lstsq related test failures on windows binaries from numpy-vendor - - `#5560 <https://github.com/scipy/scipy/issues/5560>`__: doc: scipy.stats.burr pdf issue - - `#5571 <https://github.com/scipy/scipy/issues/5571>`__: lstsq test failure after lapack_driver change - - `#5577 <https://github.com/scipy/scipy/issues/5577>`__: ordqz segfault on Python 3.4 in Wine - - `#5578 <https://github.com/scipy/scipy/issues/5578>`__: scipy.linalg test failures on python 3 in Wine - - `#5607 <https://github.com/scipy/scipy/issues/5607>`__: Overloaded ‘isnan(double&)’ is ambiguous when compiling with... - - `#5629 <https://github.com/scipy/scipy/issues/5629>`__: Test for lstsq randomly failed - - `#5630 <https://github.com/scipy/scipy/issues/5630>`__: memory leak with scipy 0.16 spatial cKDEtree - - `#5689 <https://github.com/scipy/scipy/issues/5689>`__: isnan errors compiling scipy/special/Faddeeva.cc with clang++ - - `#5694 <https://github.com/scipy/scipy/issues/5694>`__: fftpack test failure in test_import - - `#5719 <https://github.com/scipy/scipy/issues/5719>`__: curve_fit(method!="lm") ignores initial guess Pull requests for 0.17.0 - ------------------------ - - `#3022 <https://github.com/scipy/scipy/pull/3022>`__: hyp1f1: better handling of large negative arguments - - `#3107 <https://github.com/scipy/scipy/pull/3107>`__: ENH: Add ordered QZ decomposition - - `#4390 <https://github.com/scipy/scipy/pull/4390>`__: ENH: Allow axis and keepdims arguments to be passed to scipy.linalg.norm. - - `#4671 <https://github.com/scipy/scipy/pull/4671>`__: ENH: add axis to sparse norms - - `#4796 <https://github.com/scipy/scipy/pull/4796>`__: ENH: Add cut tree function to scipy.cluster.hierarchy - - `#4809 <https://github.com/scipy/scipy/pull/4809>`__: MAINT: cauchy moments are undefined - - `#4821 <https://github.com/scipy/scipy/pull/4821>`__: ENH: stats: make distribution instances picklable - - `#4839 <https://github.com/scipy/scipy/pull/4839>`__: ENH: Add scipy.special.exprel relative error exponential ufunc - - `#4859 <https://github.com/scipy/scipy/pull/4859>`__: Logsumexp fixes - allows sign flags and b==0 - - `#4865 <https://github.com/scipy/scipy/pull/4865>`__: BUG: scipy.io.mmio.write: error with big indices and low precision - - `#4869 <https://github.com/scipy/scipy/pull/4869>`__: add as_inexact option to _lib._util._asarray_validated - - `#4884 <https://github.com/scipy/scipy/pull/4884>`__: ENH: Finite difference approximation of Jacobian matrix - - `#4890 <https://github.com/scipy/scipy/pull/4890>`__: ENH: Port cKDTree query methods to C++, allow pickling on Python... - - `#4892 <https://github.com/scipy/scipy/pull/4892>`__: how much doctesting is too much? - - `#4896 <https://github.com/scipy/scipy/pull/4896>`__: MAINT: work around a possible numpy ufunc loop selection bug - - `#4898 <https://github.com/scipy/scipy/pull/4898>`__: MAINT: A bit of pyflakes-driven cleanup. - - `#4899 <https://github.com/scipy/scipy/pull/4899>`__: ENH: add 'alternative' keyword to hypothesis tests in stats - - `#4903 <https://github.com/scipy/scipy/pull/4903>`__: BENCH: Benchmarks for interpolate module - - `#4905 <https://github.com/scipy/scipy/pull/4905>`__: MAINT: prepend underscore to mask_to_limits; delete masked_var. - - `#4906 <https://github.com/scipy/scipy/pull/4906>`__: MAINT: Benchmarks for optimize.leastsq - - `#4910 <https://github.com/scipy/scipy/pull/4910>`__: WIP: Trimmed statistics functions have inconsistent API. - - `#4912 <https://github.com/scipy/scipy/pull/4912>`__: MAINT: fix typo in stats tutorial. Closes gh-4911. - - `#4914 <https://github.com/scipy/scipy/pull/4914>`__: DEP: deprecate `scipy.stats.ss` and `scipy.stats.square_of_sums`. - - `#4924 <https://github.com/scipy/scipy/pull/4924>`__: MAINT: if the imaginary part of logm of a real matrix is small,... - - `#4930 <https://github.com/scipy/scipy/pull/4930>`__: BENCH: Benchmarks for signal module - - `#4941 <https://github.com/scipy/scipy/pull/4941>`__: ENH: update `find_repeats`. - - `#4942 <https://github.com/scipy/scipy/pull/4942>`__: MAINT: use np.float64_t instead of np.float_t in cKDTree - - `#4944 <https://github.com/scipy/scipy/pull/4944>`__: BUG: integer overflow in correlate_nd - - `#4951 <https://github.com/scipy/scipy/pull/4951>`__: do not ignore invalid kwargs in distributions fit method - - `#4958 <https://github.com/scipy/scipy/pull/4958>`__: Add some detail to docstrings for special functions - - `#4961 <https://github.com/scipy/scipy/pull/4961>`__: ENH: stats.describe: add bias kw and empty array handling - - `#4963 <https://github.com/scipy/scipy/pull/4963>`__: ENH: scipy.sparse.coo.coo_matrix.__init__: less memory needed - - `#4968 <https://github.com/scipy/scipy/pull/4968>`__: DEP: deprecate ``stats.f_value*`` and ``mstats.f_value*`` functions. - - `#4969 <https://github.com/scipy/scipy/pull/4969>`__: ENH: review `stats.relfreq` and `stats.cumfreq`; fixes to `stats.histogram` - - `#4971 <https://github.com/scipy/scipy/pull/4971>`__: Extend github source links to line ranges - - `#4972 <https://github.com/scipy/scipy/pull/4972>`__: MAINT: impove the error message in validate_runtests_log - - `#4976 <https://github.com/scipy/scipy/pull/4976>`__: DEP: deprecate `scipy.stats.threshold` - - `#4977 <https://github.com/scipy/scipy/pull/4977>`__: MAINT: more careful dtype treatment in block diagonal matrix... - - `#4979 <https://github.com/scipy/scipy/pull/4979>`__: ENH: distributions, complex arguments - - `#4984 <https://github.com/scipy/scipy/pull/4984>`__: clarify dirichlet distribution error handling - - `#4992 <https://github.com/scipy/scipy/pull/4992>`__: ENH: `stats.fligner` and `stats.bartlett` empty input handling. - - `#4996 <https://github.com/scipy/scipy/pull/4996>`__: DOC: fix stats.spearmanr docs - - `#4997 <https://github.com/scipy/scipy/pull/4997>`__: Fix up boxcox for underflow / loss of precision - - `#4998 <https://github.com/scipy/scipy/pull/4998>`__: DOC: improved documentation for `stats.ppcc_max` - - `#5000 <https://github.com/scipy/scipy/pull/5000>`__: ENH: added empty input handling `scipy.moment`; doc enhancements - - `#5003 <https://github.com/scipy/scipy/pull/5003>`__: ENH: improves rankdata algorithm - - `#5005 <https://github.com/scipy/scipy/pull/5005>`__: scipy.stats: numerical stability improvement - - `#5007 <https://github.com/scipy/scipy/pull/5007>`__: ENH: nan handling in functions that use `stats._chk_asarray` - - `#5009 <https://github.com/scipy/scipy/pull/5009>`__: remove coveralls.io - - `#5010 <https://github.com/scipy/scipy/pull/5010>`__: Hypergeometric distribution log survival function - - `#5014 <https://github.com/scipy/scipy/pull/5014>`__: Patch to compute the volume and area of convex hulls - - `#5015 <https://github.com/scipy/scipy/pull/5015>`__: DOC: Fix mistaken variable name in sawtooth - - `#5016 <https://github.com/scipy/scipy/pull/5016>`__: DOC: resample example - - `#5017 <https://github.com/scipy/scipy/pull/5017>`__: DEP: deprecate `stats.betai` and `stats.chisqprob` - - `#5018 <https://github.com/scipy/scipy/pull/5018>`__: ENH: Add test on random inpu to volume computations - - `#5026 <https://github.com/scipy/scipy/pull/5026>`__: BUG: Fix return dtype of lil_matrix.getnnz(axis=0) - - `#5030 <https://github.com/scipy/scipy/pull/5030>`__: DOC: resample slow for prime output too - - `#5033 <https://github.com/scipy/scipy/pull/5033>`__: MAINT: integrate, special: remove unused R1MACH and Makefile - - `#5034 <https://github.com/scipy/scipy/pull/5034>`__: MAINT: signal: lift max_len_seq validation out of Cython - - `#5035 <https://github.com/scipy/scipy/pull/5035>`__: DOC/MAINT: refguide / doctest drudgery - - `#5041 <https://github.com/scipy/scipy/pull/5041>`__: BUG: fixing some small memory leaks detected by cppcheck - - `#5044 <https://github.com/scipy/scipy/pull/5044>`__: [GSoC] ENH: New least-squares algorithms - - `#5050 <https://github.com/scipy/scipy/pull/5050>`__: MAINT: C fixes, trimmed a lot of dead code from Cephes - - `#5057 <https://github.com/scipy/scipy/pull/5057>`__: ENH: sparse: avoid densifying on sparse/dense elementwise mult - - `#5058 <https://github.com/scipy/scipy/pull/5058>`__: TST: stats: add a sample distribution to the test loop - - `#5061 <https://github.com/scipy/scipy/pull/5061>`__: ENH: spatial: faster 2D Voronoi and Convex Hull plotting - - `#5065 <https://github.com/scipy/scipy/pull/5065>`__: TST: improve test coverage for `stats.mvsdist` and `stats.bayes_mvs` - - `#5066 <https://github.com/scipy/scipy/pull/5066>`__: MAINT: fitpack: remove a noop - - `#5067 <https://github.com/scipy/scipy/pull/5067>`__: ENH: empty and nan input handling for `stats.kstat` and `stats.kstatvar` - - `#5071 <https://github.com/scipy/scipy/pull/5071>`__: DOC: optimize: Correct paper reference, add doi - - `#5072 <https://github.com/scipy/scipy/pull/5072>`__: MAINT: scipy.sparse cleanup - - `#5073 <https://github.com/scipy/scipy/pull/5073>`__: DOC: special: Add an example showing the relation of diric to... - - `#5075 <https://github.com/scipy/scipy/pull/5075>`__: DOC: clarified parameterization of stats.lognorm - - `#5076 <https://github.com/scipy/scipy/pull/5076>`__: use int, float, bool instead of np.int, np.float, np.bool - - `#5078 <https://github.com/scipy/scipy/pull/5078>`__: DOC: Rename fftpack docs to README - - `#5081 <https://github.com/scipy/scipy/pull/5081>`__: BUG: Correct handling of scalar 'b' in lsmr and lsqr - - `#5082 <https://github.com/scipy/scipy/pull/5082>`__: loadmat variable_names: don't confuse [] and None. - - `#5083 <https://github.com/scipy/scipy/pull/5083>`__: Fix integrate.fixed_quad docstring to indicate None return value - - `#5086 <https://github.com/scipy/scipy/pull/5086>`__: Use solve() instead of inv() for gaussian_kde - - `#5090 <https://github.com/scipy/scipy/pull/5090>`__: MAINT: stats: add explicit _sf, _isf to gengamma distribution - - `#5094 <https://github.com/scipy/scipy/pull/5094>`__: ENH: scipy.interpolate.NearestNDInterpolator: cKDTree configurable - - `#5098 <https://github.com/scipy/scipy/pull/5098>`__: DOC: special: fix typesetting in ``*_roots quadrature`` functions - - `#5099 <https://github.com/scipy/scipy/pull/5099>`__: DOC: make the docstring of stats.moment raw - - `#5104 <https://github.com/scipy/scipy/pull/5104>`__: DOC/ENH fixes and micro-optimizations for scipy.linalg - - `#5105 <https://github.com/scipy/scipy/pull/5105>`__: enh: made l-bfgs-b parameter for the maximum number of line search... - - `#5106 <https://github.com/scipy/scipy/pull/5106>`__: TST: add NIST test cases to `stats.f_oneway` - - `#5110 <https://github.com/scipy/scipy/pull/5110>`__: [GSoC]: Bounded linear least squares - - `#5111 <https://github.com/scipy/scipy/pull/5111>`__: MAINT: special: Cephes cleanup - - `#5118 <https://github.com/scipy/scipy/pull/5118>`__: BUG: FIR path failed if len(x) < len(b) in lfilter. - - `#5124 <https://github.com/scipy/scipy/pull/5124>`__: ENH: move the filliben approximation to a publicly visible function - - `#5126 <https://github.com/scipy/scipy/pull/5126>`__: StatisticsCleanup: `stats.kruskal` review - - `#5130 <https://github.com/scipy/scipy/pull/5130>`__: DOC: update PyPi trove classifiers. Beta -> Stable. Add license. - - `#5131 <https://github.com/scipy/scipy/pull/5131>`__: DOC: differential_evolution, improve docstring for mutation and... - - `#5132 <https://github.com/scipy/scipy/pull/5132>`__: MAINT: differential_evolution improve init_population_lhs comments... - - `#5133 <https://github.com/scipy/scipy/pull/5133>`__: MRG: rebased mmio refactoring - - `#5135 <https://github.com/scipy/scipy/pull/5135>`__: MAINT: `stats.mstats` consistency with `stats.stats` - - `#5139 <https://github.com/scipy/scipy/pull/5139>`__: TST: linalg: add a smoke test for gh-5039 - - `#5140 <https://github.com/scipy/scipy/pull/5140>`__: EHN: Update constants.codata to CODATA 2014 - - `#5145 <https://github.com/scipy/scipy/pull/5145>`__: added ValueError to docstring as possible error raised - - `#5146 <https://github.com/scipy/scipy/pull/5146>`__: MAINT: Improve implementation details and doc in `stats.shapiro` - - `#5147 <https://github.com/scipy/scipy/pull/5147>`__: [GSoC] ENH: Upgrades to curve_fit - - `#5150 <https://github.com/scipy/scipy/pull/5150>`__: Fix misleading wavelets/cwt example - - `#5152 <https://github.com/scipy/scipy/pull/5152>`__: BUG: cluster.hierarchy.dendrogram: missing font size doesn't... - - `#5153 <https://github.com/scipy/scipy/pull/5153>`__: add keywords to control the summation in discrete distributions... - - `#5156 <https://github.com/scipy/scipy/pull/5156>`__: DOC: added comments on algorithms used in Legendre function - - `#5158 <https://github.com/scipy/scipy/pull/5158>`__: ENH: optimize: add the Hungarian algorithm - - `#5162 <https://github.com/scipy/scipy/pull/5162>`__: FIX: Remove lena - - `#5164 <https://github.com/scipy/scipy/pull/5164>`__: MAINT: fix cluster.hierarchy.dendrogram issues and docs - - `#5166 <https://github.com/scipy/scipy/pull/5166>`__: MAINT: changed `stats.pointbiserialr` to delegate to `stats.pearsonr` - - `#5167 <https://github.com/scipy/scipy/pull/5167>`__: ENH: add nan_policy to `stats.kendalltau`. - - `#5168 <https://github.com/scipy/scipy/pull/5168>`__: TST: added nist test case (Norris) to `stats.linregress`. - - `#5169 <https://github.com/scipy/scipy/pull/5169>`__: update lpmv docstring - - `#5171 <https://github.com/scipy/scipy/pull/5171>`__: Clarify metric parameter in linkage docstring - - `#5172 <https://github.com/scipy/scipy/pull/5172>`__: ENH: add mode keyword to signal.spectrogram - - `#5177 <https://github.com/scipy/scipy/pull/5177>`__: DOC: graphical example for KDTree.query_ball_point - - `#5179 <https://github.com/scipy/scipy/pull/5179>`__: MAINT: stats: tweak the formula for ncx2.pdf - - `#5188 <https://github.com/scipy/scipy/pull/5188>`__: MAINT: linalg: A bit of clean up. - - `#5189 <https://github.com/scipy/scipy/pull/5189>`__: BUG: stats: Use the explicit formula in stats.genextreme.entropy - - `#5193 <https://github.com/scipy/scipy/pull/5193>`__: BUG: fix uninitialized use in lartg - - `#5194 <https://github.com/scipy/scipy/pull/5194>`__: BUG: properly return error to fortran from ode_jacobian_function - - `#5198 <https://github.com/scipy/scipy/pull/5198>`__: TST: Fix TestCtypesQuad failure on Python 3.5 for Windows - - `#5201 <https://github.com/scipy/scipy/pull/5201>`__: allow extrapolation in interp1d - - `#5209 <https://github.com/scipy/scipy/pull/5209>`__: MAINT: Change complex parameter to boolean in Y_() - - `#5213 <https://github.com/scipy/scipy/pull/5213>`__: BUG: sparse: fix logical comparison dtype conflicts - - `#5216 <https://github.com/scipy/scipy/pull/5216>`__: BUG: sparse: fixing unbound local error - - `#5218 <https://github.com/scipy/scipy/pull/5218>`__: DOC and BUG: Bessel function docstring improvements, fix array_like,... - - `#5222 <https://github.com/scipy/scipy/pull/5222>`__: MAINT: sparse: fix COO ctor - - `#5224 <https://github.com/scipy/scipy/pull/5224>`__: DOC: optimize: type of OptimizeResult.hess_inv varies - - `#5228 <https://github.com/scipy/scipy/pull/5228>`__: ENH: Add maskandscale support to netcdf; based on pupynere and... - - `#5229 <https://github.com/scipy/scipy/pull/5229>`__: DOC: sparse.linalg.svds doc typo fixed - - `#5234 <https://github.com/scipy/scipy/pull/5234>`__: MAINT: sparse: simplify COO ctor - - `#5235 <https://github.com/scipy/scipy/pull/5235>`__: MAINT: sparse: warn on todia() with many diagonals - - `#5236 <https://github.com/scipy/scipy/pull/5236>`__: MAINT: ndimage: simplify thread handling/recursion + constness - - `#5239 <https://github.com/scipy/scipy/pull/5239>`__: BUG: integrate: Fixed issue 4118 - - `#5241 <https://github.com/scipy/scipy/pull/5241>`__: qr_insert fixes, closes #5149 - - `#5246 <https://github.com/scipy/scipy/pull/5246>`__: Doctest tutorial files - - `#5247 <https://github.com/scipy/scipy/pull/5247>`__: DOC: optimize: typo/import fix in linear_sum_assignment - - `#5248 <https://github.com/scipy/scipy/pull/5248>`__: remove inspect.getargspec and test python 3.5 on Travis CI - - `#5250 <https://github.com/scipy/scipy/pull/5250>`__: BUG: Fix sparse multiply by single-element zero - - `#5261 <https://github.com/scipy/scipy/pull/5261>`__: Fix bug causing a TypeError in splrep when a runtime warning... - - `#5262 <https://github.com/scipy/scipy/pull/5262>`__: Follow up to 4489 (Addition LAPACK routines in linalg.lstsq) - - `#5264 <https://github.com/scipy/scipy/pull/5264>`__: ignore zero-length edges for default epsilon - - `#5269 <https://github.com/scipy/scipy/pull/5269>`__: DOC: Typos and spell-checking - - `#5272 <https://github.com/scipy/scipy/pull/5272>`__: MAINT: signal: Convert array syntax to memoryviews - - `#5273 <https://github.com/scipy/scipy/pull/5273>`__: DOC: raw strings for docstrings with math - - `#5274 <https://github.com/scipy/scipy/pull/5274>`__: MAINT: sparse: update cython code for MST - - `#5278 <https://github.com/scipy/scipy/pull/5278>`__: BUG: io: Stop guessing the data delimiter in ARFF files. - - `#5289 <https://github.com/scipy/scipy/pull/5289>`__: BUG: misc: Fix the Pillow work-around for 1-bit images. - - `#5291 <https://github.com/scipy/scipy/pull/5291>`__: ENH: call np.correlate for 1d in scipy.signal.correlate - - `#5294 <https://github.com/scipy/scipy/pull/5294>`__: DOC: special: Remove a potentially misleading example from the... - - `#5295 <https://github.com/scipy/scipy/pull/5295>`__: Simplify replacement of fftpack by pyfftw - - `#5296 <https://github.com/scipy/scipy/pull/5296>`__: ENH: Add matrix normal distribution to stats - - `#5297 <https://github.com/scipy/scipy/pull/5297>`__: Fixed leaf_rotation and leaf_font_size in Python 3 - - `#5303 <https://github.com/scipy/scipy/pull/5303>`__: MAINT: stats: rewrite find_repeats - - `#5307 <https://github.com/scipy/scipy/pull/5307>`__: MAINT: stats: remove unused Fortran routine - - `#5313 <https://github.com/scipy/scipy/pull/5313>`__: BUG: sparse: fix diags for nonsquare matrices - - `#5315 <https://github.com/scipy/scipy/pull/5315>`__: MAINT: special: Cephes cleanup - - `#5316 <https://github.com/scipy/scipy/pull/5316>`__: fix input check for sparse.linalg.svds - - `#5319 <https://github.com/scipy/scipy/pull/5319>`__: MAINT: Cython code maintenance - - `#5328 <https://github.com/scipy/scipy/pull/5328>`__: BUG: Fix place_poles return values - - `#5329 <https://github.com/scipy/scipy/pull/5329>`__: avoid a spurious divide-by-zero in Student t stats - - `#5334 <https://github.com/scipy/scipy/pull/5334>`__: MAINT: integrate: miscellaneous cleanup - - `#5340 <https://github.com/scipy/scipy/pull/5340>`__: MAINT: Printing Error Msg to STDERR and Removing iterate.dat - - `#5347 <https://github.com/scipy/scipy/pull/5347>`__: ENH: add Py3.5-style matmul operator (e.g. A @ B) to sparse linear... - - `#5350 <https://github.com/scipy/scipy/pull/5350>`__: FIX error, when reading 32-bit float wav files - - `#5351 <https://github.com/scipy/scipy/pull/5351>`__: refactor the PCHIP interpolant's algorithm - - `#5354 <https://github.com/scipy/scipy/pull/5354>`__: MAINT: construct csr and csc matrices from integer lists - - `#5359 <https://github.com/scipy/scipy/pull/5359>`__: add a fast path to interp1d - - `#5364 <https://github.com/scipy/scipy/pull/5364>`__: Add two fill_values to interp1d. - - `#5365 <https://github.com/scipy/scipy/pull/5365>`__: ABCD docstrings - - `#5366 <https://github.com/scipy/scipy/pull/5366>`__: Fixed typo in the documentation for scipy.signal.cwt() per #5290. - - `#5367 <https://github.com/scipy/scipy/pull/5367>`__: DOC updated scipy.spatial.Delaunay example - - `#5368 <https://github.com/scipy/scipy/pull/5368>`__: ENH: Do not create a throwaway class at every function call - - `#5372 <https://github.com/scipy/scipy/pull/5372>`__: DOC: spectral: fix reference formatting - - `#5375 <https://github.com/scipy/scipy/pull/5375>`__: PEP8 amendments to ffpack_basic.py - - `#5377 <https://github.com/scipy/scipy/pull/5377>`__: BUG: integrate: builtin name no longer shadowed - - `#5381 <https://github.com/scipy/scipy/pull/5381>`__: PEP8ified fftpack_pseudo_diffs.py - - `#5385 <https://github.com/scipy/scipy/pull/5385>`__: BLD: fix Bento build for changes to optimize and spatial - - `#5386 <https://github.com/scipy/scipy/pull/5386>`__: STY: PEP8 amendments to interpolate.py - - `#5387 <https://github.com/scipy/scipy/pull/5387>`__: DEP: deprecate stats.histogram - - `#5388 <https://github.com/scipy/scipy/pull/5388>`__: REL: add "make upload" command to doc/Makefile. - - `#5389 <https://github.com/scipy/scipy/pull/5389>`__: DOC: updated origin param of scipy.ndimage.filters.convolve - - `#5395 <https://github.com/scipy/scipy/pull/5395>`__: BUG: special: fix a number of edge cases related to `x = np.inf`. - - `#5398 <https://github.com/scipy/scipy/pull/5398>`__: MAINT: stats: avoid spurious warnings in lognorm.pdf(0, s) - - `#5407 <https://github.com/scipy/scipy/pull/5407>`__: ENH: stats: Handle mu=0 in stats.poisson - - `#5409 <https://github.com/scipy/scipy/pull/5409>`__: Fix the behavior of discrete distributions at the right-hand... - - `#5412 <https://github.com/scipy/scipy/pull/5412>`__: TST: stats: skip a test to avoid a spurious log(0) warning - - `#5413 <https://github.com/scipy/scipy/pull/5413>`__: BUG: linalg: work around LAPACK single-precision lwork computation... - - `#5414 <https://github.com/scipy/scipy/pull/5414>`__: MAINT: stats: move creation of namedtuples outside of function... - - `#5415 <https://github.com/scipy/scipy/pull/5415>`__: DOC: fix up sections in ToC in the pdf reference guide - - `#5416 <https://github.com/scipy/scipy/pull/5416>`__: TST: fix issue with a ctypes test for integrate on Fedora. - - `#5418 <https://github.com/scipy/scipy/pull/5418>`__: DOC: fix bugs in signal.TransferFunction docstring. Closes gh-5287. - - `#5419 <https://github.com/scipy/scipy/pull/5419>`__: MAINT: sparse: fix usage of NotImplementedError - - `#5420 <https://github.com/scipy/scipy/pull/5420>`__: Raise proper error if maxiter < 1 - - `#5422 <https://github.com/scipy/scipy/pull/5422>`__: DOC: changed documentation of brent to be consistent with bracket - - `#5444 <https://github.com/scipy/scipy/pull/5444>`__: BUG: gaussian_filter, BPoly.from_derivatives fail on numpy int... - - `#5445 <https://github.com/scipy/scipy/pull/5445>`__: MAINT: stats: fix incorrect deprecation warnings and test noise - - `#5446 <https://github.com/scipy/scipy/pull/5446>`__: DOC: add note about PyFFTW in fftpack tutorial. - - `#5459 <https://github.com/scipy/scipy/pull/5459>`__: DOC: integrate: Some improvements to the differential equation... - - `#5465 <https://github.com/scipy/scipy/pull/5465>`__: BUG: Relax mstats kurtosis test tolerance by a few ulp - - `#5471 <https://github.com/scipy/scipy/pull/5471>`__: ConvexHull should raise ValueError for NaNs. - - `#5473 <https://github.com/scipy/scipy/pull/5473>`__: MAINT: update decorators.py module to version 4.0.5 - - `#5476 <https://github.com/scipy/scipy/pull/5476>`__: BUG: imsave searches for wrong channel axis if image has 3 or... - - `#5477 <https://github.com/scipy/scipy/pull/5477>`__: BLD: add numpy to setup/install_requires for OS X wheels - - `#5479 <https://github.com/scipy/scipy/pull/5479>`__: ENH: return Jacobian/Hessian from BasinHopping - - `#5484 <https://github.com/scipy/scipy/pull/5484>`__: BUG: fix ttest zero division handling - - `#5486 <https://github.com/scipy/scipy/pull/5486>`__: Fix crash on kmeans2 - - `#5491 <https://github.com/scipy/scipy/pull/5491>`__: MAINT: Expose parallel build option to runtests.py - - `#5494 <https://github.com/scipy/scipy/pull/5494>`__: Sort OptimizeResult.__repr__ by key - - `#5496 <https://github.com/scipy/scipy/pull/5496>`__: DOC: update the author name mapping - - `#5497 <https://github.com/scipy/scipy/pull/5497>`__: Enhancement to binned_statistic: option to unraveled returned... - - `#5498 <https://github.com/scipy/scipy/pull/5498>`__: BUG: sparse: fix a bug in sparsetools input dtype resolution - - `#5500 <https://github.com/scipy/scipy/pull/5500>`__: DOC: detect unprintable characters in docstrings - - `#5505 <https://github.com/scipy/scipy/pull/5505>`__: BUG: misc: Ensure fromimage converts mode 'P' to 'RGB' or 'RGBA'. - - `#5514 <https://github.com/scipy/scipy/pull/5514>`__: DOC: further update the release notes - - `#5515 <https://github.com/scipy/scipy/pull/5515>`__: ENH: optionally disable fixed-point acceleration - - `#5517 <https://github.com/scipy/scipy/pull/5517>`__: DOC: Improvements and additions to the matrix_normal doc - - `#5518 <https://github.com/scipy/scipy/pull/5518>`__: Remove wrappers for LAPACK deprecated routines - - `#5521 <https://github.com/scipy/scipy/pull/5521>`__: TST: skip a linalg.orth memory test on 32-bit platforms. - - `#5523 <https://github.com/scipy/scipy/pull/5523>`__: DOC: change a few floats to integers in docstring examples - - `#5524 <https://github.com/scipy/scipy/pull/5524>`__: DOC: more updates to 0.17.0 release notes. - - `#5525 <https://github.com/scipy/scipy/pull/5525>`__: Fix to minor typo in documentation for scipy.integrate.ode - - `#5527 <https://github.com/scipy/scipy/pull/5527>`__: TST: bump arccosh tolerance to allow for inaccurate numpy or... - - `#5535 <https://github.com/scipy/scipy/pull/5535>`__: DOC: signal: minor clarification to docstring of TransferFunction. - - `#5538 <https://github.com/scipy/scipy/pull/5538>`__: DOC: signal: fix find_peaks_cwt documentation - - `#5545 <https://github.com/scipy/scipy/pull/5545>`__: MAINT: Fix typo in linalg/basic.py - - `#5547 <https://github.com/scipy/scipy/pull/5547>`__: TST: mark TestEig.test_singular as knownfail in master. - - `#5550 <https://github.com/scipy/scipy/pull/5550>`__: MAINT: work around lstsq driver selection issue - - `#5556 <https://github.com/scipy/scipy/pull/5556>`__: BUG: Fixed broken dogbox trust-region radius update - - `#5561 <https://github.com/scipy/scipy/pull/5561>`__: BUG: eliminate warnings, exception (on Win) in test_maskandscale;... - - `#5567 <https://github.com/scipy/scipy/pull/5567>`__: TST: a few cleanups in the test suite; run_module_suite and clearer... - - `#5568 <https://github.com/scipy/scipy/pull/5568>`__: MAINT: simplify poisson's _argcheck - - `#5569 <https://github.com/scipy/scipy/pull/5569>`__: TST: bump GMean test tolerance to make it pass on Wine - - `#5572 <https://github.com/scipy/scipy/pull/5572>`__: TST: lstsq: bump test tolerance for TravisCI - - `#5573 <https://github.com/scipy/scipy/pull/5573>`__: TST: remove use of np.fromfile from cluster.vq tests - - `#5576 <https://github.com/scipy/scipy/pull/5576>`__: Lapack deprecations - - `#5579 <https://github.com/scipy/scipy/pull/5579>`__: TST: skip tests of linalg.norm axis keyword on numpy <= 1.7.x - - `#5582 <https://github.com/scipy/scipy/pull/5582>`__: Clarify language of survival function documentation - - `#5583 <https://github.com/scipy/scipy/pull/5583>`__: MAINT: stats/tests: A bit of clean up. - - `#5588 <https://github.com/scipy/scipy/pull/5588>`__: DOC: stats: Add a note that stats.burr is the Type III Burr distribution. - - `#5595 <https://github.com/scipy/scipy/pull/5595>`__: TST: fix test_lamch failures on Python 3 - - `#5600 <https://github.com/scipy/scipy/pull/5600>`__: MAINT: Ignore spatial/ckdtree.cxx and .h - - `#5602 <https://github.com/scipy/scipy/pull/5602>`__: Explicitly numbered replacement fields for maintainability - - `#5605 <https://github.com/scipy/scipy/pull/5605>`__: MAINT: collection of small fixes to test suite - - `#5614 <https://github.com/scipy/scipy/pull/5614>`__: Minor doc change. - - `#5624 <https://github.com/scipy/scipy/pull/5624>`__: FIX: Fix interpolate - - `#5625 <https://github.com/scipy/scipy/pull/5625>`__: BUG: msvc9 binaries crash when indexing std::vector of size 0 - - `#5635 <https://github.com/scipy/scipy/pull/5635>`__: BUG: misspelled __dealloc__ in cKDTree. - - `#5642 <https://github.com/scipy/scipy/pull/5642>`__: STY: minor fixup of formatting of 0.17.0 release notes. - - `#5643 <https://github.com/scipy/scipy/pull/5643>`__: BLD: fix a build issue in special/Faddeeva.cc with isnan. - - `#5661 <https://github.com/scipy/scipy/pull/5661>`__: TST: linalg tests used stdlib random instead of numpy.random. - - `#5682 <https://github.com/scipy/scipy/pull/5682>`__: backports for 0.17.0 - - `#5696 <https://github.com/scipy/scipy/pull/5696>`__: Minor improvements to least_squares' docstring. - - `#5697 <https://github.com/scipy/scipy/pull/5697>`__: BLD: fix for isnan/isinf issues in special/Faddeeva.cc - - `#5720 <https://github.com/scipy/scipy/pull/5720>`__: TST: fix for file opening error in fftpack test_import.py - - `#5722 <https://github.com/scipy/scipy/pull/5722>`__: BUG: Make curve_fit respect an initial guess with bounds - - `#5726 <https://github.com/scipy/scipy/pull/5726>`__: Backports for v0.17.0rc2 - - `#5727 <https://github.com/scipy/scipy/pull/5727>`__: API: Changes to least_squares API Checksums ========= MD5 ~~~ 5ff2971e1ce90e762c59d2cd84837224 scipy-0.17.0.tar.gz ef0949640ee73f845dde6dd7f84d7691 scipy-0.17.0.tar.xz 28a4fe29e980804db162524f10873211 scipy-0.17.0.zip SHA256 ~~~~~~ f600b755fb69437d0f70361f9e560ab4d304b1b66987ed5a28bdd9dd7793e089 scipy-0.17.0.tar.gz 2bc03ea36cd55bfd80869d87f690334b4cad240373e05857ddfa7a4d1e2f9a7a scipy-0.17.0.tar.xz ede6820030b2e5796126aa1571d86738b14bbd670d68c83378877b1d9eb9894d scipy-0.17.0.zip -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.11 (GNU/Linux) iQEcBAEBAgAGBQJWokWbAAoJEIp0pQ0zQcu+JUgH/16Qqurptl3jUU11+4pl+8ji 3AFZN+dgzGLyiMz9s+V+OyL4hcdZY4++WM2QizF5uD3hDDFNi+aJRHAYySMAZeIZ O8y//v+DXDVOLZpKwcPFq5E5ZebTDh1jO4zZzpuyi1PnKgTAEKZeSyBSMd0RMx/p kZ0URTcAa/tPgkNZz3+i8By9b/zBWOlbI+v6fCVwV8E20YWfGBSp2s0KAtQk787D Q88ylnc3Zfv4IR1hgCFZz6oJA0RgmpH4USKi7guyg+fIKjf1nFe64zIuV3C2r/Uj y9Qbs/8x/HTteDp5owkRiSwnpTZHOtx/jqeh2z/w9aQe0i8Nag5Ere6JZ2kixG4= =jZUn -----END PGP SIGNATURE-----

2 2

win32 binaries and scipy 0.17.0 release
by Evgeni Burovski Feb. 14, 2016

Feb. 14, 2016

Hi, Here's a proposal to follow the numpy lead (https://mail.scipy.org/pipermail/numpy-discussion/2015-December/074422.html) and stop providing the official binaries for 32-bit windows. The reasons are basically the same as for numpy: these binaries contain BLAS/LAPACK which is necessarily lower quality than what's available from Christoph Gohlke/Canopy/Anaconda; they do not and cannot support python 3.5; the build toolchain is currently broken and to the best of my knowledge nobody knows how to fix it. With regards to the scipy 0.17.0 release, win32 problems are responsible for delaying the release for almost a month (OK, the original schedule was too optimistic, but still). The alternatives, as I see them, are: * stop providing the windows binaries (until a MinGW-64 based toolchain is ready, but this is separate) and make the release. * release 0.17.0 with only python 3.4 binaries available (this is the only python version I can build the binaries which do not segfault immediately :-)) * delay the release with no ETA and no clear path forward. Thoughts? Evgeni

11 45

ode and odeint callable parameters
by Irvin Probst Jan. 29, 2016

Jan. 29, 2016

Hi, maybe my question has been asked a thousand times but why are the callable's parameters in ode and odeint reversed ? From scipy.integrate.ode: http://docs.scipy.org/doc/scipy-0.16.0/reference/generated/scipy.integrate.… f : callable f(t, y, *f_args) From scipy.integrate.odeint: http://docs.scipy.org/doc/scipy-0.16.0/reference/generated/scipy.integrate.… func : callable(y, t0, ...) Admittedly one will usually choose ode or odeint depending on what has to be done, but from an educational point of view this is really annoying. Say you want to show how to use ode or odeint to simulate something ? You have to define twice the same dynamics: def f_odeint(y,t): return y[1], -np.sin(y[0]) def f_ode(t,y): return [[y[1], -np.sin(y[0])]] Then come the usual questions: - why do I have to reverse y and t ? => Err... you see... because... - why can't I return a tuple in f_ode as in f_odeint ? => see ticket #1187 So I know that reversing the callable's parameters will break half the code using ode or odeint in the world and this is out of question, but couldn't it be possible to make it a bit more clear somewhere in the doc that the parameters are indeed reversed ? Or maybe am I missing some obvious explanation ? Regards.

5 22

Numpy 1.11.0b2 released
by Charles R Harris Jan. 28, 2016

Jan. 28, 2016

Hi All, I hope I am pleased to announce the Numpy 1.11.0b2 release. The first beta was a damp squib due to missing files in the released source files, this release fixes that. The new source filese may be downloaded from sourceforge, no binaries will be released until the mingw tool chain problems are sorted. Please test and report any problem. Chuck

2 1

Numpy 1.11.0b1 is out
by Charles R Harris Jan. 26, 2016

Jan. 26, 2016

Hi All, I'm pleased to announce that Numpy 1.11.0b1 <http://sourceforge.net/projects/numpy/files/NumPy/1.11.0b1/> is now available on sourceforge. This is a source release as the mingw32 toolchain is broken. Please test it out and report any errors that you discover. Hopefully we can do better with 1.11.0 than we did with 1.10.0 ;) Chuck

1 0

Resampling using polyphase filtering
by Eric Larson Jan. 26, 2016

Jan. 26, 2016

Hey all, I have made a PR to scipy to add signal resampling using polyphase filtering (via upfirdn) to complement the existing FFT-based resampling method currently available via resample(...). Feel free to take a look and leave comments if interested: https://github.com/scipy/scipy/pull/5749 Eric

1 0

Re: [SciPy-Dev] SciPy-Dev Digest, Vol 147, Issue 20
by The Helmbolds Jan. 26, 2016

Jan. 26, 2016

However, if the inputs were a dictionary ---- "You won't find the right answers if you don't ask the right questions!" (Robert Helmbold, 2013) From: "scipy-dev-request(a)scipy.org" <scipy-dev-request(a)scipy.org> To: scipy-dev(a)scipy.org Sent: Tuesday, January 26, 2016 3:43 AM Subject: SciPy-Dev Digest, Vol 147, Issue 20 Send SciPy-Dev mailing list submissions to scipy-dev(a)scipy.org To subscribe or unsubscribe via the World Wide Web, visit https://mail.scipy.org/mailman/listinfo/scipy-dev or, via email, send a message with subject or body 'help' to scipy-dev-request(a)scipy.org You can reach the person managing the list at scipy-dev-owner(a)scipy.org When replying, please edit your Subject line so it is more specific than "Re: Contents of SciPy-Dev digest..." Today's Topics: 1. Re: ode and odeint callable parameters (Marcel Oliver) 2. Re: ode and odeint callable parameters (Benny Malengier) 3. Re: ode and odeint callable parameters (Marcel Oliver) ---------------------------------------------------------------------- Message: 1 Date: Mon, 25 Jan 2016 14:29:20 +0100 From: Marcel Oliver <m.oliver(a)jacobs-university.de> To: SciPy Developers List <scipy-dev(a)scipy.org> Subject: Re: [SciPy-Dev] ode and odeint callable parameters Message-ID: <22182.9008.344108.842230(a)xps13.localdomain> Content-Type: text/plain; charset="us-ascii" Anne Archibald writes: > There is periodically discussion of the mess of interfaces and > solvers for ODEs in scipy (see the archives about six months ago, > for example). One of the concerns is that people want to do very > different things, so settling on a good interface is not at all > easy. I don't just mean the underlying algorithms, but also the > calling interface. It's easy to support someone who drops in an RHS > and asks for the solution at a hundred predefined points. It's also > clear that a general toolkit shouldn't support my use case: a > 22-dimensional solver with a compiled RHS generated by a symbolic > algebra package, with internal precision switchable between 80 and > 128 bits, with a root-finder attached to the output to define > stopping places, that needs to all run with compiled speed. So > where along that scale do you aim scipy's interface? I have my own > ideas (see aforementioned archive thread) but don't have the energy > to implement it myself. And anyway, some people need very different > things from their ODE solvers (for example, solution objects > evaluable anywhere). > > Anne Thanks for all the comments. I had not been aware of the existence of scikits odes - the additional capabilities are very nice, but API-wise it just adds to the mess... Being unsure what has previously been discussed, I'd just like to share some random thoughts, as I don't claim to understand the problem domain completely. Basically, the API should make simple thing simple and natural, and complicated things possible. So I think your requirements stated above should not be completely out of reach - in principle - even though high precision arithmetic would require completely new backends and whether one can get close to compiled speed is probably very problem dependent. So, here an unordered list of thoughts: 1. I don't think there is a big difference in practice between the ode, odes, and odeint interfaces. Personally, think that odeint (f, y0, t) is just fine. But the object oriented approach of ode/odes is good, too; however, the various parameters should be controlled by (keyword) arguments as a statement like r.set_initial_value(y0, t0).set_f_params(2.0).set_jac_params(2.0) is just not pretty. So I like the odes approach best, with a basic object oriented structure, but the parameters set as arguments, not via methods. Not sure if odes allows to set an initial time different from zero, that is essential. I also dislike that specifying the solver is mandatory and first in the argument list; I think this is specialist territory as many of the existing solvers perform sufficiently well over a large range of problems so that changing the solver is more of an exception. If the interface is object oriented (as in ode or odes), then at least the default solver should be reentrant, otherwise the API raises false expectations. I would also suggest that, independent of the rest of the API, the final time t can be an array or a scalar; the result is either returned as a vector of shape y0 when t is scalar and as an array with one additional axis for time when t is a 1-d-array. 2. It would be very nice to control output time intervals or exit times. Mathematica has a fairly rich "WhenEvent" API, although it seems to me it may also be no more than a fancy wrapper around a standard solver. The Mathematica API feels almost a bit too general, but there are certainly two independent ways triggers could be implemented, both seem useful to me: (a) Simple Boolean trigger for "output event" and "termination event" based on the evaluation of some function of (y,t,p) which is passed to the solver and which is evaluated after each time step. (b) Trigger for "output event" and/or "termination" based on finding the root of a scalar function of the (y,t,p). This needs either a separate root finder or a modification to the implicit solver (the latter may be hard as that would require nontrivial modification of the embedded solver code). (odes "rootfn" may be doing just that, but there seems to be no detailed documentation...) 3. Returning interpolating function objects as, e.g., Mathematica does, seems a bit of overkill to me. It would be easier to set up an independent general interpolating function library (as possibly even exists already) and pass a discrete time series to it. It is likely that by deriving the interpolation function directly from the interpolation on which the solver is based one could gain some efficiency and give better control of the interpolation accuracy, but to me that seems to require a lot of effort for relatively little improvement. 4. odes includes DAE solvers. I wonder if it would not be more natural to pass the algebraic part of the equation as a separate keyword argument and let the solver wrapper decide, based on the presence or absence of this argument, whether to call a DAE backend. 5. As I wrote before, the API should deal transparently with d-dimensional vector fields. Just a question about solver backends: it seems that the SUNDIALS solvers are particularly strong for large stiff systems which come from parabolic PDEs? (And of course the ability to propagate sensitivities, is that ability made available through odes, too?) On smaller system of ODEs, I have found that ode "dop853" is extremely accurate and seems capable of dealing with rather stiff problems even though I have no clue how it does it. (E.g., for the Van der Pol oscillator with large stiffness parameter where other explicit solvers either blow up or grind to a halt, dop853 and also dopri5 are doing just fine while Matlab's dopri5 solver fails as expected. It's a mystery to me.) In any case, it would be very nice to develop a clear plan for cleaning up ODE solver backend in Scipy. Once there is a clear target, it might be easier to see what is easy to do and what is missing on the backend side. Regards, Marcel ------------------------------ Message: 2 Date: Mon, 25 Jan 2016 15:22:09 +0100 From: Benny Malengier <benny.malengier(a)gmail.com> To: SciPy Developers List <scipy-dev(a)scipy.org> Subject: Re: [SciPy-Dev] ode and odeint callable parameters Message-ID: <CAOyNq8qd-4FrS4QDn861F0bSwsOaEwx9sHs0oAwCENLOhYQTGA(a)mail.gmail.com> Content-Type: text/plain; charset="utf-8" 2016-01-25 14:29 GMT+01:00 Marcel Oliver <m.oliver(a)jacobs-university.de>: > Anne Archibald writes: > > <snip> > > to implement it myself. And anyway, some people need very different > > things from their ODE solvers (for example, solution objects > > evaluable anywhere). > > > > Anne > > <snip> > > 2. It would be very nice to control output time intervals or exit > times. Mathematica has a fairly rich "WhenEvent" API, although it > seems to me it may also be no more than a fancy wrapper around a > standard solver. > > The Mathematica API feels almost a bit too general, but there are > certainly two independent ways triggers could be implemented, both > seem useful to me: > > (a) Simple Boolean trigger for "output event" and "termination > event" based on the evaluation of some function of (y,t,p) > which is passed to the solver and which is evaluated after each > time step. > > (b) Trigger for "output event" and/or "termination" based on > finding the root of a scalar function of the (y,t,p). This > needs either a separate root finder or a modification to the > implicit solver (the latter may be hard as that would require > nontrivial modification of the embedded solver code). > > (odes "rootfn" may be doing just that, but there seems to be no > detailed documentation...) > Yes rootfn does that. A nicer interface with onroot functionality to that was added by a contributor to CVODE, I just extended it to the IDA solver. Only available through the solve method of the solvers (as STEP methods just stop), example: https://github.com/bmcage/odes/blob/master/docs/src/examples/ode/freefall.py Same with fixed tstop added in a list of output times: https://github.com/bmcage/odes/blob/master/docs/src/examples/ode/freefall_t… > > 3. Returning interpolating function objects as, e.g., Mathematica > does, seems a bit of overkill to me. It would be easier to set up > an independent general interpolating function library (as possibly > even exists already) and pass a discrete time series to it. It is > likely that by deriving the interpolation function directly from > the interpolation on which the solver is based one could gain some > efficiency and give better control of the interpolation accuracy, > but to me that seems to require a lot of effort for relatively > little improvement. > agree. Also, just reinit the solver and solve again from closest start time is an option too if for some reason interpolation error must be avoided. CVODE can actually give you output backward if you have jumped too far ahead, but that requires you to know where you want interpolation output immediately after doing a STEP. All very problem depending. > > 4. odes includes DAE solvers. I wonder if it would not be more > natural to pass the algebraic part of the equation as a separate > keyword argument and let the solver wrapper decide, based on the > presence or absence of this argument, whether to call a DAE > backend. > These things all require a lot of boilerplate code. In the end, my experience is that the documentation of the original solvers is the best to learn the details, so keeping variable names the same in options is more important than something that is more pythonic. Eg, the rootfn above is a bad name, but fits the original documentation at https://computation.llnl.gov/casc/sundials/documentation/documentation.html CVODE doc is 164 pages, in the end, for problems you want to optimize you will grab that documentation to learn what options you want to tweak. About transparant algebraic part. The backends need a lot of info on the algebraic part. You also need to structure your variables specifically if you eg want banded Jacobian. And the calling sequence of all functions becomes different with an extra parameter in and out (ydot). Quite a lot of boilerplate that slows your wrapper down will be needed I'm afraid. > 5. As I wrote before, the API should deal transparently with > d-dimensional vector fields. > I'm not really following. You mean unwrap and wrap again like the complex_ode solver does now in scipy? http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.integrate.… Writing your own wrapper for your problem does not seem like a big task to me. > > Just a question about solver backends: it seems that the SUNDIALS > solvers are particularly strong for large stiff systems which come > from parabolic PDEs? (And of course the ability to propagate > sensitivities, is that ability made available through odes, too?) > They are used for that too, but it is not the core. Large complex kinetic systems with different time scales seems like the largest use case on the mailing list, see also as first example in the example doc. Sensitivities are not present in odes at the moment, but I think some wrappers have that covered already. Let's say it is asked once or twice a year to add. > On smaller system of ODEs, I have found that ode "dop853" is extremely > accurate and seems capable of dealing with rather stiff problems even > though I have no clue how it does it. (E.g., for the Van der Pol > oscillator with large stiffness parameter where other explicit solvers > either blow up or grind to a halt, dop853 and also dopri5 are doing > just fine while Matlab's dopri5 solver fails as expected. It's a > mystery to me.) > Some extra tests seem in order. How does method=adams in ode succeed? Should you be able to quickly make an ipython notebook ... > In any case, it would be very nice to develop a clear plan for > cleaning up ODE solver backend in Scipy. Once there is a clear > target, it might be easier to see what is easy to do and what is > missing on the backend side. > Yes. We don't have our own backends, we only wrap backends. In the end, those backends with continued development will win out. Wrapping solvers is a tricky business, as it is very hard to avoid design of the solver to not slip through > > Regards, > Marcel > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev(a)scipy.org > https://mail.scipy.org/mailman/listinfo/scipy-dev >

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ANN: second release candidate for scipy 0.17.0
by Evgeni Burovski Jan. 12, 2016

Jan. 12, 2016

Hi, I'm pleased to announce the availability of the second release candidate for Scipy 0.17.0. It's two days ahead of the original schedule: based on typical development patterns, I'd like to have two weekends and a full working week before January 17th, when this rc2 is supposed to become the final release. Please try this rc and report any issues on Github tracker or scipy-dev mailing list. Source tarballs and full release notes are available from Github Releases: https://github.com/scipy/scipy/releases/tag/v0.17.0rc2 Compared to rc1, the following PRs were merged: - - `#5624 <https://github.com/scipy/scipy/pull/5624>`__: FIX: Fix interpolate - - `#5625 <https://github.com/scipy/scipy/pull/5625>`__: BUG: msvc9 binaries crash when indexing std::vector of size 0 - - `#5635 <https://github.com/scipy/scipy/pull/5635>`__: BUG: misspelled __dealloc__ in cKDTree. - - `#5642 <https://github.com/scipy/scipy/pull/5642>`__: STY: minor fixup of formatting of 0.17.0 release notes. - - `#5643 <https://github.com/scipy/scipy/pull/5643>`__: BLD: fix a build issue in special/Faddeeva.cc with isnan. - - `#5661 <https://github.com/scipy/scipy/pull/5661>`__: TST: linalg tests used stdlib random instead of numpy.random. There is a bit of an unusual change in this rc. In short, in testing rc1 we found that 1) interpolate.interp1d had an undocumented feature of allowing an array-valued fill_value to be broadcast against the data being interpolated, and 2) we broke it in 0.17.0rc1. (See PR 5624 for details.) We now *think* we fixed it so that no existing code is broken. Nevertheless, I would like to encourage everyone to test their code against this rc2, especially all code which uses interp1d. Cheers, Evgeni

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differential_evolution enhancement
by Niklas K. Jan. 10, 2016

Jan. 10, 2016

Hi, I would like to use the differential_evolution algorithm but extend it with a few functionalities: 1. I would like to use the args arguments also in the callback method so that artificial arguments can be passed to that method as well as to the objective itself. 2. I would like to use a convex hull as an alternative to the bounds parameter. The type could be checked and the code could behave accordingly. Here the change is a little more difficult since the methods init_population_lhs and init_population_random need to be adopted to the appropriate bounds type. A first approach could be to sample in the designated way (LHS or random) as long as enough samples for the population are present in space defined by the convex hull. I think that both alterations create a backwards compatible code and can be done with a minimal changes. I hope a lead developer could give some feedback on my ideas. Best Regards

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