Mailman 3 March 2017 - SciPy-Dev

Re: [SciPy-Dev] SciPy-Dev Digest, Vol 161, Issue 12
by Antonio Ribeiro March 12, 2017

March 12, 2017

I would like to start by thanking both Matt Haberland and Nikolay Mayorov for making themselves avaliable for mentoring me. I would like very much to have the opportunity to be mentored by one or even both of you. About the questions raised about the project: - To have a wrapper for “ipopt” in scipy would be nice and, if the owners give permission, it could be one of the items of the proposal. Nevertheless, the implementation of a solver in native Python/Cython still have it advantages and should not be discarded: i) the code in python is much more readable, furthermore native code make it easier for scipy collaborators to add new features and maintain it; ii) Using the proper Numpy and LAPACK functions for expensive operations and using Cython when needed, our implementation can be as fast as C or FORTRAN implementations; iii) It is easier to maintain coherence of interface with other scipy methods using a native implementation. - About the Nikolay question about the interface to use: my plan is to try to implement the solver inside the “minimize” interface in scipy. If needed I can move to a new interface that gives me more freedom. About what to implement and in what order of priority: 1) Nikolay idea implement a set of benchmarks from the beginning is very good, it would allow to compare my method with other already implemented solvers and to assess the quality of my solver during its development. 2) After having a set of benchmarks my idea is to implement an interior points method. In my opinion interior points methods should be the priority because they are able to handle a large range of problems reasonably well. They are very powerful algorithms for large-scale problems and usually are able to deal with medium/small problems reasonably well too. 3) After that I would like to include different possibilities of Hessian approximation to the method (BFGS, L-BFGS, approximated by finite-differences or provided by the user…) 4) And, if I have time, I would like to also implement a SQP solver. It would probably not be the same as the one used in SLSQP. There are several variations of interior points methods and I am still deciding which one to implement among the several available options. I have seen both line-search and trust-region methods being used in literature and in implemented solvers (for instance "ipopt” uses a line-search approach while “KNITRO” uses a trust-region approach). I have found a good reference about trust-region interior point methods in the Conn, Gould and Toint “Trust-Region methods” book; Nocedal and Wright book also have a small chapter about nonlinear interior point methods that can be useful. Furthermore, I am looking into papers and surveys about the subject. I would much appreciate any recommendation or reference about the subject. Same thing with SQP methods. Best regards, Antônio > On Mar 11, 2017, at 14:01, scipy-dev-request(a)scipy.org wrote: > > 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: SciPy-Dev Digest, Vol 161, Issue 11 (Denis Akhiyarov) > 2. Re: SciPy-Dev Digest, Vol 161, Issue 11 (Matt Haberland) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sat, 11 Mar 2017 09:08:17 -0600 > From: Denis Akhiyarov <denis.akhiyarov(a)gmail.com> > To: scipy-dev(a)scipy.org > Subject: Re: [SciPy-Dev] SciPy-Dev Digest, Vol 161, Issue 11 > Message-ID: > <CALxxJLQhh-e-tM5u0EijBbWaC0etaChxkLt61LEy=EPg0A-J-A(a)mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > I used ipopt for interior-point method from python, are you trying to add > something similar to scipy? if yes, why not just add a wrapper for ipopt, > since the license looks not restrictive? > > On Fri, Mar 10, 2017 at 1:40 PM, <scipy-dev-request(a)scipy.org> wrote: > >> 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: GSoC2017: Constrained Optimisation in Scipy (Matt Haberland) >> 2. Re: GSoC2017: Constrained Optimisation in Scipy (Nikolay Mayorov) >> >> >> ---------------------------------------------------------------------- >> >> Message: 1 >> Date: Fri, 10 Mar 2017 10:01:32 -0800 >> From: Matt Haberland <haberland(a)ucla.edu> >> To: SciPy Developers List <scipy-dev(a)scipy.org> >> Subject: Re: [SciPy-Dev] GSoC2017: Constrained Optimisation in Scipy >> Message-ID: >> <CADuxUiyK_d3BvjinikmG_k8LTh8JczMFPwboNaSerdnsWFp=yQ@ >> mail.gmail.com> >> Content-Type: text/plain; charset="utf-8" >> >> The choice of nonlinear optimization algorithm can have a dramatic impact >> on the speed and quality of the solution, and the best choice for a >> particular problem can be difficult to determine a priori, so it is >> important to have multiple options available. >> >> My work in optimal control leads to problems with (almost entirely) >> nonlinear constraints, and the use of derivative information is essential >> for reasonable performance, leaving SLSQP as the only option in SciPy right >> now. However, the problems are also huge and very sparse with a specific >> structure, so SLSQP is not very effective, and not nearly as effective as a >> nonlinear optimization routine could be. So despite SciPy boasting 14 >> options for minimization of a nonlinear objective, it wasn't suitable for >> this work (without the use of an external solver). >> >> I think SciPy is in need of at least one solver designed to handle large, >> fully nonlinear problems, and having two would be much better. Interior >> point and SQP are good, complementary options. >> >> On Thu, Mar 9, 2017 at 2:38 PM, Antonio Ribeiro <antonior92(a)gmail.com> >> wrote: >> >>> Hello, my name is Antonio and I am a Brazilian electrical engineer >>> currently pursuing my master degree. I have contributed to scipy.optimize >>> and scipy.signal implementing functions "iirnotch", "irrpeak" >>> <https://github.com/scipy/scipy/pull/6404>and the method >>> "trust-region-exact" <https://github.com/scipy/scipy/pull/6919> (under >>> revision). I am interested in applying for the Google Summer of Code 2017 >>> to work with the Scipy optimisation package. >>> >>> My proposal is to improve scipy.optimize adding optimisation methods that >>> are able to deal with non-linear constraints. Currently the only >>> implemented methods able to deal with non-linear constraints are the >>> FORTRAN wrappers SLSQP and COBYLA. >>> >>> SLSQP is a sequential quadratic programming method and COBYLA is a >>> derivative-free optimisation method, they both have its limitations: >>> SLSQP is not able to deal with sparse >>> hessians and jacobians and is unfit for large-scale problems and COBYLA, >>> as other derivative-free methods, is a good choice for optimise noisy >>> objective functions, however usually presents a poorer performance then >>> derivative-based methods when the derivatives are available (or even when >>> they are computed by automatic differentiation or finite differences). >>> >>> My proposal is to implement in Scipy one or more state-of-the-art solvers >>> (interior point and SQP methods) for constrained optimisation problems. I >>> would like to get some feedback about this, discuss the relevance of it >> for >>> Scipy and get some suggestions of possible mentors. >>> >>> _______________________________________________ >>> SciPy-Dev mailing list >>> SciPy-Dev(a)scipy.org >>> https://mail.scipy.org/mailman/listinfo/scipy-dev >>> >>> >> >> >> -- >> Matt Haberland >> Assistant Adjunct Professor in the Program in Computing >> Department of Mathematics >> 7620E Math Sciences Building, UCLA >>

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Fwd: SciPy 2017 Registration Now Open
by Juan Shishido March 12, 2017

March 12, 2017

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GSoC2017: Constrained Optimisation in Scipy
by Antonio Ribeiro March 11, 2017

March 11, 2017

Hello, my name is Antonio and I am a Brazilian electrical engineer currently pursuing my master degree. I have contributed to scipy.optimize and scipy.signal implementing functions "iirnotch", "irrpeak" <https://github.com/scipy/scipy/pull/6404>and the method "trust-region-exact" <https://github.com/scipy/scipy/pull/6919> (under revision). I am interested in applying for the Google Summer of Code 2017 to work with the Scipy optimisation package. My proposal is to improve scipy.optimize adding optimisation methods that are able to deal with non-linear constraints. Currently the only implemented methods able to deal with non-linear constraints are the FORTRAN wrappers SLSQP and COBYLA. SLSQP is a sequential quadratic programming method and COBYLA is a derivative-free optimisation method, they both have its limitations: SLSQP is not able to deal with sparse hessians and jacobians and is unfit for large-scale problems and COBYLA, as other derivative-free methods, is a good choice for optimise noisy objective functions, however usually presents a poorer performance then derivative-based methods when the derivatives are available (or even when they are computed by automatic differentiation or finite differences). My proposal is to implement in Scipy one or more state-of-the-art solvers (interior point and SQP methods) for constrained optimisation problems. I would like to get some feedback about this, discuss the relevance of it for Scipy and get some suggestions of possible mentors.

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Re: [SciPy-Dev] SciPy-Dev Digest, Vol 161, Issue 11
by Denis Akhiyarov March 11, 2017

March 11, 2017

I used ipopt for interior-point method from python, are you trying to add something similar to scipy? if yes, why not just add a wrapper for ipopt, since the license looks not restrictive? On Fri, Mar 10, 2017 at 1:40 PM, <scipy-dev-request(a)scipy.org> wrote: > 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: GSoC2017: Constrained Optimisation in Scipy (Matt Haberland) > 2. Re: GSoC2017: Constrained Optimisation in Scipy (Nikolay Mayorov) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Fri, 10 Mar 2017 10:01:32 -0800 > From: Matt Haberland <haberland(a)ucla.edu> > To: SciPy Developers List <scipy-dev(a)scipy.org> > Subject: Re: [SciPy-Dev] GSoC2017: Constrained Optimisation in Scipy > Message-ID: > <CADuxUiyK_d3BvjinikmG_k8LTh8JczMFPwboNaSerdnsWFp=yQ@ > mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > The choice of nonlinear optimization algorithm can have a dramatic impact > on the speed and quality of the solution, and the best choice for a > particular problem can be difficult to determine a priori, so it is > important to have multiple options available. > > My work in optimal control leads to problems with (almost entirely) > nonlinear constraints, and the use of derivative information is essential > for reasonable performance, leaving SLSQP as the only option in SciPy right > now. However, the problems are also huge and very sparse with a specific > structure, so SLSQP is not very effective, and not nearly as effective as a > nonlinear optimization routine could be. So despite SciPy boasting 14 > options for minimization of a nonlinear objective, it wasn't suitable for > this work (without the use of an external solver). > > I think SciPy is in need of at least one solver designed to handle large, > fully nonlinear problems, and having two would be much better. Interior > point and SQP are good, complementary options. > > On Thu, Mar 9, 2017 at 2:38 PM, Antonio Ribeiro <antonior92(a)gmail.com> > wrote: > > > Hello, my name is Antonio and I am a Brazilian electrical engineer > > currently pursuing my master degree. I have contributed to scipy.optimize > > and scipy.signal implementing functions "iirnotch", "irrpeak" > > <https://github.com/scipy/scipy/pull/6404>and the method > > "trust-region-exact" <https://github.com/scipy/scipy/pull/6919> (under > > revision). I am interested in applying for the Google Summer of Code 2017 > > to work with the Scipy optimisation package. > > > > My proposal is to improve scipy.optimize adding optimisation methods that > > are able to deal with non-linear constraints. Currently the only > > implemented methods able to deal with non-linear constraints are the > > FORTRAN wrappers SLSQP and COBYLA. > > > > SLSQP is a sequential quadratic programming method and COBYLA is a > > derivative-free optimisation method, they both have its limitations: > > SLSQP is not able to deal with sparse > > hessians and jacobians and is unfit for large-scale problems and COBYLA, > > as other derivative-free methods, is a good choice for optimise noisy > > objective functions, however usually presents a poorer performance then > > derivative-based methods when the derivatives are available (or even when > > they are computed by automatic differentiation or finite differences). > > > > My proposal is to implement in Scipy one or more state-of-the-art solvers > > (interior point and SQP methods) for constrained optimisation problems. I > > would like to get some feedback about this, discuss the relevance of it > for > > Scipy and get some suggestions of possible mentors. > > > > _______________________________________________ > > SciPy-Dev mailing list > > SciPy-Dev(a)scipy.org > > https://mail.scipy.org/mailman/listinfo/scipy-dev > > > > > > > -- > Matt Haberland > Assistant Adjunct Professor in the Program in Computing > Department of Mathematics > 7620E Math Sciences Building, UCLA >

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ANN: SciPy 0.19.0
by Evgeni Burovski March 10, 2017

March 10, 2017

On behalf of the Scipy development team I am pleased to announce the availability of Scipy 0.19.0. This release contains several great new features and a large number of bug fixes and various improvements, as detailed in the release notes below. 121 people contributed to this release over the course of seven months. Thanks to everyone who contributed! This release requires Python 2.7 or 3.4-3.6 and NumPy 1.8.2 or greater. Source tarballs and release notes can be found at https://github.com/scipy/scipy/releases/tag/v0.19.0. OS X and Linux wheels are available from PyPI. For security-conscious, the wheels themselves are signed with my GPG key. Additionally, you can checksum the wheels and verify the checksums with those listed below or in the README file at https://github.com/scipy/scipy/releases/tag/v0.19.0. Cheers, Evgeni -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA256 ========================== SciPy 0.19.0 Release Notes ========================== .. contents:: SciPy 0.19.0 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 0.19.x branch, and on adding new features on the master branch. This release requires Python 2.7 or 3.4-3.6 and NumPy 1.8.2 or greater. Highlights of this release include: - - A unified foreign function interface layer, `scipy.LowLevelCallable`. - - Cython API for scalar, typed versions of the universal functions from the `scipy.special` module, via `cimport scipy.special.cython_special`. New features ============ Foreign function interface improvements - --------------------------------------- `scipy.LowLevelCallable` provides a new unified interface for wrapping low-level compiled callback functions in the Python space. It supports Cython imported "api" functions, ctypes function pointers, CFFI function pointers, ``PyCapsules``, Numba jitted functions and more. See `gh-6509 <https://github.com/scipy/scipy/pull/6509>`_ for details. `scipy.linalg` improvements - --------------------------- The function `scipy.linalg.solve` obtained two more keywords ``assume_a`` and ``transposed``. The underlying LAPACK routines are replaced with "expert" versions and now can also be used to solve symmetric, hermitian and positive definite coefficient matrices. Moreover, ill-conditioned matrices now cause a warning to be emitted with the estimated condition number information. Old ``sym_pos`` keyword is kept for backwards compatibility reasons however it is identical to using ``assume_a='pos'``. Moreover, the ``debug`` keyword, which had no function but only printing the ``overwrite_<a, b>`` values, is deprecated. The function `scipy.linalg.matrix_balance` was added to perform the so-called matrix balancing using the LAPACK xGEBAL routine family. This can be used to approximately equate the row and column norms through diagonal similarity transformations. The functions `scipy.linalg.solve_continuous_are` and `scipy.linalg.solve_discrete_are` have numerically more stable algorithms. These functions can also solve generalized algebraic matrix Riccati equations. Moreover, both gained a ``balanced`` keyword to turn balancing on and off. `scipy.spatial` improvements - ---------------------------- `scipy.spatial.SphericalVoronoi.sort_vertices_of_regions` has been re-written in Cython to improve performance. `scipy.spatial.SphericalVoronoi` can handle > 200 k points (at least 10 million) and has improved performance. The function `scipy.spatial.distance.directed_hausdorff` was added to calculate the directed Hausdorff distance. ``count_neighbors`` method of `scipy.spatial.cKDTree` gained an ability to perform weighted pair counting via the new keywords ``weights`` and ``cumulative``. See `gh-5647 <https://github.com/scipy/scipy/pull/5647>`_ for details. `scipy.spatial.distance.pdist` and `scipy.spatial.distance.cdist` now support non-double custom metrics. `scipy.ndimage` improvements - ---------------------------- The callback function C API supports PyCapsules in Python 2.7 Multidimensional filters now allow having different extrapolation modes for different axes. `scipy.optimize` improvements - ----------------------------- The `scipy.optimize.basinhopping` global minimizer obtained a new keyword, `seed`, which can be used to seed the random number generator and obtain repeatable minimizations. The keyword `sigma` in `scipy.optimize.curve_fit` was overloaded to also accept the covariance matrix of errors in the data. `scipy.signal` improvements - --------------------------- The function `scipy.signal.correlate` and `scipy.signal.convolve` have a new optional parameter `method`. The default value of `auto` estimates the fastest of two computation methods, the direct approach and the Fourier transform approach. A new function has been added to choose the convolution/correlation method, `scipy.signal.choose_conv_method` which may be appropriate if convolutions or correlations are performed on many arrays of the same size. New functions have been added to calculate complex short time fourier transforms of an input signal, and to invert the transform to recover the original signal: `scipy.signal.stft` and `scipy.signal.istft`. This implementation also fixes the previously incorrect ouput of `scipy.signal.spectrogram` when complex output data were requested. The function `scipy.signal.sosfreqz` was added to compute the frequency response from second-order sections. The function `scipy.signal.unit_impulse` was added to conveniently generate an impulse function. The function `scipy.signal.iirnotch` was added to design second-order IIR notch filters that can be used to remove a frequency component from a signal. The dual function `scipy.signal.iirpeak` was added to compute the coefficients of a second-order IIR peak (resonant) filter. The function `scipy.signal.minimum_phase` was added to convert linear-phase FIR filters to minimum phase. The functions `scipy.signal.upfirdn` and `scipy.signal.resample_poly` are now substantially faster when operating on some n-dimensional arrays when n > 1. The largest reduction in computation time is realized in cases where the size of the array is small (<1k samples or so) along the axis to be filtered. `scipy.fftpack` improvements - ---------------------------- Fast Fourier transform routines now accept `np.float16` inputs and upcast them to `np.float32`. Previously, they would raise an error. `scipy.cluster` improvements - ---------------------------- Methods ``"centroid"`` and ``"median"`` of `scipy.cluster.hierarchy.linkage` have been significantly sped up. Long-standing issues with using ``linkage`` on large input data (over 16 GB) have been resolved. `scipy.sparse` improvements - --------------------------- The functions `scipy.sparse.save_npz` and `scipy.sparse.load_npz` were added, providing simple serialization for some sparse formats. The `prune` method of classes `bsr_matrix`, `csc_matrix`, and `csr_matrix` was updated to reallocate backing arrays under certain conditions, reducing memory usage. The methods `argmin` and `argmax` were added to classes `coo_matrix`, `csc_matrix`, `csr_matrix`, and `bsr_matrix`. New function `scipy.sparse.csgraph.structural_rank` computes the structural rank of a graph with a given sparsity pattern. New function `scipy.sparse.linalg.spsolve_triangular` solves a sparse linear system with a triangular left hand side matrix. `scipy.special` improvements - ---------------------------- Scalar, typed versions of universal functions from `scipy.special` are available in the Cython space via ``cimport`` from the new module `scipy.special.cython_special`. These scalar functions can be expected to be significantly faster then the universal functions for scalar arguments. See the `scipy.special` tutorial for details. Better control over special-function errors is offered by the functions `scipy.special.geterr` and `scipy.special.seterr` and the context manager `scipy.special.errstate`. The names of orthogonal polynomial root functions have been changed to be consistent with other functions relating to orthogonal polynomials. For example, `scipy.special.j_roots` has been renamed `scipy.special.roots_jacobi` for consistency with the related functions `scipy.special.jacobi` and `scipy.special.eval_jacobi`. To preserve back-compatibility the old names have been left as aliases. Wright Omega function is implemented as `scipy.special.wrightomega`. `scipy.stats` improvements - -------------------------- The function `scipy.stats.weightedtau` was added. It provides a weighted version of Kendall's tau. New class `scipy.stats.multinomial` implements the multinomial distribution. New class `scipy.stats.rv_histogram` constructs a continuous univariate distribution with a piecewise linear CDF from a binned data sample. New class `scipy.stats.argus` implements the Argus distribution. `scipy.interpolate` improvements - -------------------------------- New class `scipy.interpolate.BSpline` represents splines. ``BSpline`` objects contain knots and coefficients and can evaluate the spline. The format is consistent with FITPACK, so that one can do, for example:: >>> t, c, k = splrep(x, y, s=0) >>> spl = BSpline(t, c, k) >>> np.allclose(spl(x), y) ``spl*`` functions, `scipy.interpolate.splev`, `scipy.interpolate.splint`, `scipy.interpolate.splder` and `scipy.interpolate.splantider`, accept both ``BSpline`` objects and ``(t, c, k)`` tuples for backwards compatibility. For multidimensional splines, ``c.ndim > 1``, ``BSpline`` objects are consistent with piecewise polynomials, `scipy.interpolate.PPoly`. This means that ``BSpline`` objects are not immediately consistent with `scipy.interpolate.splprep`, and one *cannot* do ``>>> BSpline(*splprep([x, y])[0])``. Consult the `scipy.interpolate` test suite for examples of the precise equivalence. In new code, prefer using ``scipy.interpolate.BSpline`` objects instead of manipulating ``(t, c, k)`` tuples directly. New function `scipy.interpolate.make_interp_spline` constructs an interpolating spline given data points and boundary conditions. New function `scipy.interpolate.make_lsq_spline` constructs a least-squares spline approximation given data points. `scipy.integrate` improvements - ------------------------------ Now `scipy.integrate.fixed_quad` supports vector-valued functions. Deprecated features =================== `scipy.interpolate.splmake`, `scipy.interpolate.spleval` and `scipy.interpolate.spline` are deprecated. The format used by `splmake/spleval` was inconsistent with `splrep/splev` which was confusing to users. `scipy.special.errprint` is deprecated. Improved functionality is available in `scipy.special.seterr`. calling `scipy.spatial.distance.pdist` or `scipy.spatial.distance.cdist` with arguments not needed by the chosen metric is deprecated. Also, metrics `"old_cosine"` and `"old_cos"` are deprecated. Backwards incompatible changes ============================== The deprecated ``scipy.weave`` submodule was removed. `scipy.spatial.distance.squareform` now returns arrays of the same dtype as the input, instead of always float64. `scipy.special.errprint` now returns a boolean. The function `scipy.signal.find_peaks_cwt` now returns an array instead of a list. `scipy.stats.kendalltau` now computes the correct p-value in case the input contains ties. The p-value is also identical to that computed by `scipy.stats.mstats.kendalltau` and by R. If the input does not contain ties there is no change w.r.t. the previous implementation. The function `scipy.linalg.block_diag` will not ignore zero-sized matrices anymore. Instead it will insert rows or columns of zeros of the appropriate size. See gh-4908 for more details. Other changes ============= SciPy wheels will now report their dependency on ``numpy`` on all platforms. This change was made because Numpy wheels are available, and because the pip upgrade behavior is finally changing for the better (use ``--upgrade-strategy=only-if-needed`` for ``pip >= 8.2``; that behavior will become the default in the next major version of ``pip``). Numerical values returned by `scipy.interpolate.interp1d` with ``kind="cubic"`` and ``"quadratic"`` may change relative to previous scipy versions. If your code depended on specific numeric values (i.e., on implementation details of the interpolators), you may want to double-check your results. Authors ======= * @endolith * Max Argus + * Hervé Audren * Alessandro Pietro Bardelli + * Michael Benfield + * Felix Berkenkamp * Matthew Brett * Per Brodtkorb * Evgeni Burovski * Pierre de Buyl * CJ Carey * Brandon Carter + * Tim Cera * Klesk Chonkin * Christian Häggström + * Luca Citi * Peadar Coyle + * Daniel da Silva + * Greg Dooper + * John Draper + * drlvk + * David Ellis + * Yu Feng * Baptiste Fontaine + * Jed Frey + * Siddhartha Gandhi + * Wim Glenn + * Akash Goel + * Christoph Gohlke * Ralf Gommers * Alexander Goncearenco + * Richard Gowers + * Alex Griffing * Radoslaw Guzinski + * Charles Harris * Callum Jacob Hays + * Ian Henriksen * Randy Heydon + * Lindsey Hiltner + * Gerrit Holl + * Hiroki IKEDA + * jfinkels + * Mher Kazandjian + * Thomas Keck + * keuj6 + * Kornel Kielczewski + * Sergey B Kirpichev + * Vasily Kokorev + * Eric Larson * Denis Laxalde * Gregory R. Lee * Josh Lefler + * Julien Lhermitte + * Evan Limanto + * Jin-Guo Liu + * Nikolay Mayorov * Geordie McBain + * Josue Melka + * Matthieu Melot * michaelvmartin15 + * Surhud More + * Brett M. Morris + * Chris Mutel + * Paul Nation * Andrew Nelson * David Nicholson + * Aaron Nielsen + * Joel Nothman * nrnrk + * Juan Nunez-Iglesias * Mikhail Pak + * Gavin Parnaby + * Thomas Pingel + * Ilhan Polat + * Aman Pratik + * Sebastian Pucilowski * Ted Pudlik * puenka + * Eric Quintero * Tyler Reddy * Joscha Reimer * Antonio Horta Ribeiro + * Edward Richards + * Roman Ring + * Rafael Rossi + * Colm Ryan + * Sami Salonen + * Alvaro Sanchez-Gonzalez + * Johannes Schmitz * Kari Schoonbee * Yurii Shevchuk + * Jonathan Siebert + * Jonathan Tammo Siebert + * Scott Sievert + * Sourav Singh * Byron Smith + * Srikiran + * Samuel St-Jean + * Yoni Teitelbaum + * Bhavika Tekwani * Martin Thoma * timbalam + * Svend Vanderveken + * Sebastiano Vigna + * Aditya Vijaykumar + * Santi Villalba + * Ze Vinicius * Pauli Virtanen * Matteo Visconti * Yusuke Watanabe + * Warren Weckesser * Phillip Weinberg + * Nils Werner * Jakub Wilk * Josh Wilson * wirew0rm + * David Wolever + * Nathan Woods * ybeltukov + * G Young * Evgeny Zhurko + A total of 121 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 0.19.0 - ------------------------ - - `#1767 <https://github.com/scipy/scipy/issues/1767>`__: Function definitions in __fitpack.h should be moved. (Trac #1240) - - `#1774 <https://github.com/scipy/scipy/issues/1774>`__: _kmeans chokes on large thresholds (Trac #1247) - - `#2089 <https://github.com/scipy/scipy/issues/2089>`__: Integer overflows cause segfault in linkage function with large... - - `#2190 <https://github.com/scipy/scipy/issues/2190>`__: Are odd-length window functions supposed to be always symmetrical?... - - `#2251 <https://github.com/scipy/scipy/issues/2251>`__: solve_discrete_are in scipy.linalg does (sometimes) not solve... - - `#2580 <https://github.com/scipy/scipy/issues/2580>`__: scipy.interpolate.UnivariateSpline (or a new superclass of it)... - - `#2592 <https://github.com/scipy/scipy/issues/2592>`__: scipy.stats.anderson assumes gumbel_l - - `#3054 <https://github.com/scipy/scipy/issues/3054>`__: scipy.linalg.eig does not handle infinite eigenvalues - - `#3160 <https://github.com/scipy/scipy/issues/3160>`__: multinomial pmf / logpmf - - `#3904 <https://github.com/scipy/scipy/issues/3904>`__: scipy.special.ellipj dn wrong values at quarter period - - `#4044 <https://github.com/scipy/scipy/issues/4044>`__: Inconsistent code book initialization in kmeans - - `#4234 <https://github.com/scipy/scipy/issues/4234>`__: scipy.signal.flattop documentation doesn't list a source for... - - `#4831 <https://github.com/scipy/scipy/issues/4831>`__: Bugs in C code in __quadpack.h - - `#4908 <https://github.com/scipy/scipy/issues/4908>`__: bug: unnessesary validity check for block dimension in scipy.sparse.block_diag - - `#4917 <https://github.com/scipy/scipy/issues/4917>`__: BUG: indexing error for sparse matrix with ix_ - - `#4938 <https://github.com/scipy/scipy/issues/4938>`__: Docs on extending ndimage need to be updated. - - `#5056 <https://github.com/scipy/scipy/issues/5056>`__: sparse matrix element-wise multiplying dense matrix returns dense... - - `#5337 <https://github.com/scipy/scipy/issues/5337>`__: Formula in documentation for correlate is wrong - - `#5537 <https://github.com/scipy/scipy/issues/5537>`__: use OrderedDict in io.netcdf - - `#5750 <https://github.com/scipy/scipy/issues/5750>`__: [doc] missing data index value in KDTree, cKDTree - - `#5755 <https://github.com/scipy/scipy/issues/5755>`__: p-value computation in scipy.stats.kendalltau() in broken in... - - `#5757 <https://github.com/scipy/scipy/issues/5757>`__: BUG: Incorrect complex output of signal.spectrogram - - `#5964 <https://github.com/scipy/scipy/issues/5964>`__: ENH: expose scalar versions of scipy.special functions to cython - - `#6107 <https://github.com/scipy/scipy/issues/6107>`__: scipy.cluster.hierarchy.single segmentation fault with 2**16... - - `#6278 <https://github.com/scipy/scipy/issues/6278>`__: optimize.basinhopping should take a RandomState object - - `#6296 <https://github.com/scipy/scipy/issues/6296>`__: InterpolatedUnivariateSpline: check_finite fails when w is unspecified - - `#6306 <https://github.com/scipy/scipy/issues/6306>`__: Anderson-Darling bad results - - `#6314 <https://github.com/scipy/scipy/issues/6314>`__: scipy.stats.kendaltau() p value not in agreement with R, SPSS... - - `#6340 <https://github.com/scipy/scipy/issues/6340>`__: Curve_fit bounds and maxfev - - `#6377 <https://github.com/scipy/scipy/issues/6377>`__: expm_multiply, complex matrices not working using start,stop,ect... - - `#6382 <https://github.com/scipy/scipy/issues/6382>`__: optimize.differential_evolution stopping criterion has unintuitive... - - `#6391 <https://github.com/scipy/scipy/issues/6391>`__: Global Benchmarking times out at 600s. - - `#6397 <https://github.com/scipy/scipy/issues/6397>`__: mmwrite errors with large (but still 64-bit) integers - - `#6413 <https://github.com/scipy/scipy/issues/6413>`__: scipy.stats.dirichlet computes multivariate gaussian differential... - - `#6428 <https://github.com/scipy/scipy/issues/6428>`__: scipy.stats.mstats.mode modifies input - - `#6440 <https://github.com/scipy/scipy/issues/6440>`__: Figure out ABI break policy for scipy.special Cython API - - `#6441 <https://github.com/scipy/scipy/issues/6441>`__: Using Qhull for halfspace intersection : segfault - - `#6442 <https://github.com/scipy/scipy/issues/6442>`__: scipy.spatial : In incremental mode volume is not recomputed - - `#6451 <https://github.com/scipy/scipy/issues/6451>`__: Documentation for scipy.cluster.hierarchy.to_tree is confusing... - - `#6490 <https://github.com/scipy/scipy/issues/6490>`__: interp1d (kind=zero) returns wrong value for rightmost interpolation... - - `#6521 <https://github.com/scipy/scipy/issues/6521>`__: scipy.stats.entropy does *not* calculate the KL divergence - - `#6530 <https://github.com/scipy/scipy/issues/6530>`__: scipy.stats.spearmanr unexpected NaN handling - - `#6541 <https://github.com/scipy/scipy/issues/6541>`__: Test runner does not run scipy._lib/tests? - - `#6552 <https://github.com/scipy/scipy/issues/6552>`__: BUG: misc.bytescale returns unexpected results when using cmin/cmax... - - `#6556 <https://github.com/scipy/scipy/issues/6556>`__: RectSphereBivariateSpline(u, v, r) fails if min(v) >= pi - - `#6559 <https://github.com/scipy/scipy/issues/6559>`__: Differential_evolution maxiter causing memory overflow - - `#6565 <https://github.com/scipy/scipy/issues/6565>`__: Coverage of spectral functions could be improved - - `#6628 <https://github.com/scipy/scipy/issues/6628>`__: Incorrect parameter name in binomial documentation - - `#6634 <https://github.com/scipy/scipy/issues/6634>`__: Expose LAPACK's xGESVX family for linalg.solve ill-conditioned... - - `#6657 <https://github.com/scipy/scipy/issues/6657>`__: Confusing documentation for `scipy.special.sph_harm` - - `#6676 <https://github.com/scipy/scipy/issues/6676>`__: optimize: Incorrect size of Jacobian returned by `minimize(...,... - - `#6681 <https://github.com/scipy/scipy/issues/6681>`__: add a new context manager to wrap `scipy.special.seterr` - - `#6700 <https://github.com/scipy/scipy/issues/6700>`__: BUG: scipy.io.wavfile.read stays in infinite loop, warns on wav... - - `#6721 <https://github.com/scipy/scipy/issues/6721>`__: scipy.special.chebyt(N) throw a 'TypeError' when N > 64 - - `#6727 <https://github.com/scipy/scipy/issues/6727>`__: Documentation for scipy.stats.norm.fit is incorrect - - `#6764 <https://github.com/scipy/scipy/issues/6764>`__: Documentation for scipy.spatial.Delaunay is partially incorrect - - `#6811 <https://github.com/scipy/scipy/issues/6811>`__: scipy.spatial.SphericalVoronoi fails for large number of points - - `#6841 <https://github.com/scipy/scipy/issues/6841>`__: spearmanr fails when nan_policy='omit' is set - - `#6869 <https://github.com/scipy/scipy/issues/6869>`__: Currently in gaussian_kde, the logpdf function is calculated... - - `#6875 <https://github.com/scipy/scipy/issues/6875>`__: SLSQP inconsistent handling of invalid bounds - - `#6876 <https://github.com/scipy/scipy/issues/6876>`__: Python stopped working (Segfault?) with minimum/maximum filter... - - `#6889 <https://github.com/scipy/scipy/issues/6889>`__: dblquad gives different results under scipy 0.17.1 and 0.18.1 - - `#6898 <https://github.com/scipy/scipy/issues/6898>`__: BUG: dblquad ignores error tolerances - - `#6901 <https://github.com/scipy/scipy/issues/6901>`__: Solving sparse linear systems in CSR format with complex values - - `#6903 <https://github.com/scipy/scipy/issues/6903>`__: issue in spatial.distance.pdist docstring - - `#6917 <https://github.com/scipy/scipy/issues/6917>`__: Problem in passing drop_rule to scipy.sparse.linalg.spilu - - `#6926 <https://github.com/scipy/scipy/issues/6926>`__: signature mismatches for LowLevelCallable - - `#6961 <https://github.com/scipy/scipy/issues/6961>`__: Scipy contains shebang pointing to /usr/bin/python and /bin/bash... - - `#6972 <https://github.com/scipy/scipy/issues/6972>`__: BUG: special: `generate_ufuncs.py` is broken - - `#6984 <https://github.com/scipy/scipy/issues/6984>`__: Assert raises test failure for test_ill_condition_warning - - `#6990 <https://github.com/scipy/scipy/issues/6990>`__: BUG: sparse: Bad documentation of the `k` argument in `sparse.linalg.eigs` - - `#6991 <https://github.com/scipy/scipy/issues/6991>`__: Division by zero in linregress() - - `#7011 <https://github.com/scipy/scipy/issues/7011>`__: possible speed improvment in rv_continuous.fit() - - `#7015 <https://github.com/scipy/scipy/issues/7015>`__: Test failure with Python 3.5 and numpy master - - `#7055 <https://github.com/scipy/scipy/issues/7055>`__: SciPy 0.19.0rc1 test errors and failures on Windows - - `#7096 <https://github.com/scipy/scipy/issues/7096>`__: macOS test failues for test_solve_continuous_are - - `#7100 <https://github.com/scipy/scipy/issues/7100>`__: test_distance.test_Xdist_deprecated_args test error in 0.19.0rc2 Pull requests for 0.19.0 - ------------------------ - - `#2908 <https://github.com/scipy/scipy/pull/2908>`__: Scipy 1.0 Roadmap - - `#3174 <https://github.com/scipy/scipy/pull/3174>`__: add b-splines - - `#4606 <https://github.com/scipy/scipy/pull/4606>`__: ENH: Add a unit impulse waveform function - - `#5608 <https://github.com/scipy/scipy/pull/5608>`__: Adds keyword argument to choose faster convolution method - - `#5647 <https://github.com/scipy/scipy/pull/5647>`__: ENH: Faster count_neighour in cKDTree / + weighted input data - - `#6021 <https://github.com/scipy/scipy/pull/6021>`__: Netcdf append - - `#6058 <https://github.com/scipy/scipy/pull/6058>`__: ENH: scipy.signal - Add stft and istft - - `#6059 <https://github.com/scipy/scipy/pull/6059>`__: ENH: More accurate signal.freqresp for zpk systems - - `#6195 <https://github.com/scipy/scipy/pull/6195>`__: ENH: Cython interface for special - - `#6234 <https://github.com/scipy/scipy/pull/6234>`__: DOC: Fixed a typo in ward() help - - `#6261 <https://github.com/scipy/scipy/pull/6261>`__: ENH: add docstring and clean up code for signal.normalize - - `#6270 <https://github.com/scipy/scipy/pull/6270>`__: MAINT: special: add tests for cdflib - - `#6271 <https://github.com/scipy/scipy/pull/6271>`__: Fix for scipy.cluster.hierarchy.is_isomorphic - - `#6273 <https://github.com/scipy/scipy/pull/6273>`__: optimize: rewrite while loops as for loops - - `#6279 <https://github.com/scipy/scipy/pull/6279>`__: MAINT: Bessel tweaks - - `#6291 <https://github.com/scipy/scipy/pull/6291>`__: Fixes gh-6219: remove runtime warning from genextreme distribution - - `#6294 <https://github.com/scipy/scipy/pull/6294>`__: STY: Some PEP8 and cleaning up imports in stats/_continuous_distns.py - - `#6297 <https://github.com/scipy/scipy/pull/6297>`__: Clarify docs in misc/__init__.py - - `#6300 <https://github.com/scipy/scipy/pull/6300>`__: ENH: sparse: Loosen input validation for `diags` with empty inputs - - `#6301 <https://github.com/scipy/scipy/pull/6301>`__: BUG: standardizes check_finite behavior re optional weights,... - - `#6303 <https://github.com/scipy/scipy/pull/6303>`__: Fixing example in _lazyselect docstring. - - `#6307 <https://github.com/scipy/scipy/pull/6307>`__: MAINT: more improvements to gammainc/gammaincc - - `#6308 <https://github.com/scipy/scipy/pull/6308>`__: Clarified documentation of hypergeometric distribution. - - `#6309 <https://github.com/scipy/scipy/pull/6309>`__: BUG: stats: Improve calculation of the Anderson-Darling statistic. - - `#6315 <https://github.com/scipy/scipy/pull/6315>`__: ENH: Descending order of x in PPoly - - `#6317 <https://github.com/scipy/scipy/pull/6317>`__: ENH: stats: Add support for nan_policy to stats.median_test - - `#6321 <https://github.com/scipy/scipy/pull/6321>`__: TST: fix a typo in test name - - `#6328 <https://github.com/scipy/scipy/pull/6328>`__: ENH: sosfreqz - - `#6335 <https://github.com/scipy/scipy/pull/6335>`__: Define LinregressResult outside of linregress - - `#6337 <https://github.com/scipy/scipy/pull/6337>`__: In anderson test, added support for right skewed gumbel distribution. - - `#6341 <https://github.com/scipy/scipy/pull/6341>`__: Accept several spellings for the curve_fit max number of function... - - `#6342 <https://github.com/scipy/scipy/pull/6342>`__: DOC: cluster: clarify hierarchy.linkage usage - - `#6352 <https://github.com/scipy/scipy/pull/6352>`__: DOC: removed brentq from its own 'see also' - - `#6362 <https://github.com/scipy/scipy/pull/6362>`__: ENH: stats: Use explicit formulas for sf, logsf, etc in weibull... - - `#6369 <https://github.com/scipy/scipy/pull/6369>`__: MAINT: special: add a comment to hyp0f1_complex - - `#6375 <https://github.com/scipy/scipy/pull/6375>`__: Added the multinomial distribution. - - `#6387 <https://github.com/scipy/scipy/pull/6387>`__: MAINT: special: improve accuracy of ellipj's `dn` at quarter... - - `#6388 <https://github.com/scipy/scipy/pull/6388>`__: BenchmarkGlobal - getting it to work in Python3 - - `#6394 <https://github.com/scipy/scipy/pull/6394>`__: ENH: scipy.sparse: add save and load functions for sparse matrices - - `#6400 <https://github.com/scipy/scipy/pull/6400>`__: MAINT: moves global benchmark run from setup_cache to track_all - - `#6403 <https://github.com/scipy/scipy/pull/6403>`__: ENH: seed kwd for basinhopping. Closes #6278 - - `#6404 <https://github.com/scipy/scipy/pull/6404>`__: ENH: signal: added irrnotch and iirpeak functions. - - `#6406 <https://github.com/scipy/scipy/pull/6406>`__: ENH: special: extend `sici`/`shichi` to complex arguments - - `#6407 <https://github.com/scipy/scipy/pull/6407>`__: ENH: Window functions should not accept non-integer or negative... - - `#6408 <https://github.com/scipy/scipy/pull/6408>`__: MAINT: _differentialevolution now uses _lib._util.check_random_state - - `#6427 <https://github.com/scipy/scipy/pull/6427>`__: MAINT: Fix gmpy build & test that mpmath uses gmpy - - `#6439 <https://github.com/scipy/scipy/pull/6439>`__: MAINT: ndimage: update callback function c api - - `#6443 <https://github.com/scipy/scipy/pull/6443>`__: BUG: Fix volume computation in incremental mode - - `#6447 <https://github.com/scipy/scipy/pull/6447>`__: Fixes issue #6413 - Minor documentation fix in the entropy function... - - `#6448 <https://github.com/scipy/scipy/pull/6448>`__: ENH: Add halfspace mode to Qhull - - `#6449 <https://github.com/scipy/scipy/pull/6449>`__: ENH: rtol and atol for differential_evolution termination fixes... - - `#6453 <https://github.com/scipy/scipy/pull/6453>`__: DOC: Add some See Also links between similar functions - - `#6454 <https://github.com/scipy/scipy/pull/6454>`__: DOC: linalg: clarify callable signature in `ordqz` - - `#6457 <https://github.com/scipy/scipy/pull/6457>`__: ENH: spatial: enable non-double dtypes in squareform - - `#6459 <https://github.com/scipy/scipy/pull/6459>`__: BUG: Complex matrices not handled correctly by expm_multiply... - - `#6465 <https://github.com/scipy/scipy/pull/6465>`__: TST DOC Window docs, tests, etc. - - `#6469 <https://github.com/scipy/scipy/pull/6469>`__: ENH: linalg: better handling of infinite eigenvalues in `eig`/`eigvals` - - `#6475 <https://github.com/scipy/scipy/pull/6475>`__: DOC: calling interp1d/interp2d with NaNs is undefined - - `#6477 <https://github.com/scipy/scipy/pull/6477>`__: Document magic numbers in optimize.py - - `#6481 <https://github.com/scipy/scipy/pull/6481>`__: TST: Supress some warnings from test_windows - - `#6485 <https://github.com/scipy/scipy/pull/6485>`__: DOC: spatial: correct typo in procrustes - - `#6487 <https://github.com/scipy/scipy/pull/6487>`__: Fix Bray-Curtis formula in pdist docstring - - `#6493 <https://github.com/scipy/scipy/pull/6493>`__: ENH: Add covariance functionality to scipy.optimize.curve_fit - - `#6494 <https://github.com/scipy/scipy/pull/6494>`__: ENH: stats: Use log1p() to improve some calculations. - - `#6495 <https://github.com/scipy/scipy/pull/6495>`__: BUG: Use MST algorithm instead of SLINK for single linkage clustering - - `#6497 <https://github.com/scipy/scipy/pull/6497>`__: MRG: Add minimum_phase filter function - - `#6505 <https://github.com/scipy/scipy/pull/6505>`__: reset scipy.signal.resample window shape to 1-D - - `#6507 <https://github.com/scipy/scipy/pull/6507>`__: BUG: linkage: Raise exception if y contains non-finite elements - - `#6509 <https://github.com/scipy/scipy/pull/6509>`__: ENH: _lib: add common machinery for low-level callback functions - - `#6520 <https://github.com/scipy/scipy/pull/6520>`__: scipy.sparse.base.__mul__ non-numpy/scipy objects with 'shape'... - - `#6522 <https://github.com/scipy/scipy/pull/6522>`__: Replace kl_div by rel_entr in entropy - - `#6524 <https://github.com/scipy/scipy/pull/6524>`__: DOC: add next_fast_len to list of functions - - `#6527 <https://github.com/scipy/scipy/pull/6527>`__: DOC: Release notes to reflect the new covariance feature in optimize.curve_fit - - `#6532 <https://github.com/scipy/scipy/pull/6532>`__: ENH: Simplify _cos_win, document it, add symmetric/periodic arg - - `#6535 <https://github.com/scipy/scipy/pull/6535>`__: MAINT: sparse.csgraph: updating old cython loops - - `#6540 <https://github.com/scipy/scipy/pull/6540>`__: DOC: add to documentation of orthogonal polynomials - - `#6544 <https://github.com/scipy/scipy/pull/6544>`__: TST: Ensure tests for scipy._lib are run by scipy.test() - - `#6546 <https://github.com/scipy/scipy/pull/6546>`__: updated docstring of stats.linregress - - `#6553 <https://github.com/scipy/scipy/pull/6553>`__: commited changes that I originally submitted for scipy.signal.cspline… - - `#6561 <https://github.com/scipy/scipy/pull/6561>`__: BUG: modify signal.find_peaks_cwt() to return array and accept... - - `#6562 <https://github.com/scipy/scipy/pull/6562>`__: DOC: Negative binomial distribution clarification - - `#6563 <https://github.com/scipy/scipy/pull/6563>`__: MAINT: be more liberal in requiring numpy - - `#6567 <https://github.com/scipy/scipy/pull/6567>`__: MAINT: use xrange for iteration in differential_evolution fixes... - - `#6572 <https://github.com/scipy/scipy/pull/6572>`__: BUG: "sp.linalg.solve_discrete_are" fails for random data - - `#6578 <https://github.com/scipy/scipy/pull/6578>`__: BUG: misc: allow both cmin/cmax and low/high params in bytescale - - `#6581 <https://github.com/scipy/scipy/pull/6581>`__: Fix some unfortunate typos - - `#6582 <https://github.com/scipy/scipy/pull/6582>`__: MAINT: linalg: make handling of infinite eigenvalues in `ordqz`... - - `#6585 <https://github.com/scipy/scipy/pull/6585>`__: DOC: interpolate: correct seealso links to ndimage - - `#6588 <https://github.com/scipy/scipy/pull/6588>`__: Update docstring of scipy.spatial.distance_matrix - - `#6592 <https://github.com/scipy/scipy/pull/6592>`__: DOC: Replace 'first' by 'smallest' in mode - - `#6593 <https://github.com/scipy/scipy/pull/6593>`__: MAINT: remove scipy.weave submodule - - `#6594 <https://github.com/scipy/scipy/pull/6594>`__: DOC: distance.squareform: fix html docs, add note about dtype... - - `#6598 <https://github.com/scipy/scipy/pull/6598>`__: [DOC] Fix incorrect error message in medfilt2d - - `#6599 <https://github.com/scipy/scipy/pull/6599>`__: MAINT: linalg: turn a `solve_discrete_are` test back on - - `#6600 <https://github.com/scipy/scipy/pull/6600>`__: DOC: Add SOS goals to roadmap - - `#6601 <https://github.com/scipy/scipy/pull/6601>`__: DEP: Raise minimum numpy version to 1.8.2 - - `#6605 <https://github.com/scipy/scipy/pull/6605>`__: MAINT: 'new' module is deprecated, don't use it - - `#6607 <https://github.com/scipy/scipy/pull/6607>`__: DOC: add note on change in wheel dependency on numpy and pip... - - `#6609 <https://github.com/scipy/scipy/pull/6609>`__: Fixes #6602 - Typo in docs - - `#6616 <https://github.com/scipy/scipy/pull/6616>`__: ENH: generalization of continuous and discrete Riccati solvers... - - `#6621 <https://github.com/scipy/scipy/pull/6621>`__: DOC: improve cluster.hierarchy docstrings. - - `#6623 <https://github.com/scipy/scipy/pull/6623>`__: CS matrix prune method should copy data from large unpruned arrays - - `#6625 <https://github.com/scipy/scipy/pull/6625>`__: DOC: special: complete documentation of `eval_*` functions - - `#6626 <https://github.com/scipy/scipy/pull/6626>`__: TST: special: silence some deprecation warnings - - `#6631 <https://github.com/scipy/scipy/pull/6631>`__: fix parameter name doc for discrete distributions - - `#6632 <https://github.com/scipy/scipy/pull/6632>`__: MAINT: stats: change some instances of `special` to `sc` - - `#6633 <https://github.com/scipy/scipy/pull/6633>`__: MAINT: refguide: py2k long integers are equal to py3k integers - - `#6638 <https://github.com/scipy/scipy/pull/6638>`__: MAINT: change type declaration in cluster.linkage, prevent overflow - - `#6640 <https://github.com/scipy/scipy/pull/6640>`__: BUG: fix issue with duplicate values used in cluster.vq.kmeans - - `#6641 <https://github.com/scipy/scipy/pull/6641>`__: BUG: fix corner case in cluster.vq.kmeans for large thresholds - - `#6643 <https://github.com/scipy/scipy/pull/6643>`__: MAINT: clean up truncation modes of dendrogram - - `#6645 <https://github.com/scipy/scipy/pull/6645>`__: MAINT: special: rename `*_roots` functions - - `#6646 <https://github.com/scipy/scipy/pull/6646>`__: MAINT: clean up mpmath imports - - `#6647 <https://github.com/scipy/scipy/pull/6647>`__: DOC: add sqrt to Mahalanobis description for pdist - - `#6648 <https://github.com/scipy/scipy/pull/6648>`__: DOC: special: add a section on `cython_special` to the tutorial - - `#6649 <https://github.com/scipy/scipy/pull/6649>`__: ENH: Added scipy.spatial.distance.directed_hausdorff - - `#6650 <https://github.com/scipy/scipy/pull/6650>`__: DOC: add Sphinx roles for DOI and arXiv links - - `#6651 <https://github.com/scipy/scipy/pull/6651>`__: BUG: mstats: make sure mode(..., None) does not modify its input - - `#6652 <https://github.com/scipy/scipy/pull/6652>`__: DOC: special: add section to tutorial on functions not in special - - `#6653 <https://github.com/scipy/scipy/pull/6653>`__: ENH: special: add the Wright Omega function - - `#6656 <https://github.com/scipy/scipy/pull/6656>`__: ENH: don't coerce input to double with custom metric in cdist... - - `#6658 <https://github.com/scipy/scipy/pull/6658>`__: Faster/shorter code for computation of discordances - - `#6659 <https://github.com/scipy/scipy/pull/6659>`__: DOC: special: make __init__ summaries and html summaries match - - `#6661 <https://github.com/scipy/scipy/pull/6661>`__: general.rst: Fix a typo - - `#6664 <https://github.com/scipy/scipy/pull/6664>`__: TST: Spectral functions' window correction factor - - `#6665 <https://github.com/scipy/scipy/pull/6665>`__: [DOC] Conditions on v in RectSphereBivariateSpline - - `#6668 <https://github.com/scipy/scipy/pull/6668>`__: DOC: Mention negative masses for center of mass - - `#6675 <https://github.com/scipy/scipy/pull/6675>`__: MAINT: special: remove outdated README - - `#6677 <https://github.com/scipy/scipy/pull/6677>`__: BUG: Fixes computation of p-values. - - `#6679 <https://github.com/scipy/scipy/pull/6679>`__: BUG: optimize: return correct Jacobian for method 'SLSQP' in... - - `#6680 <https://github.com/scipy/scipy/pull/6680>`__: ENH: Add structural rank to sparse.csgraph - - `#6686 <https://github.com/scipy/scipy/pull/6686>`__: TST: Added Airspeed Velocity benchmarks for SphericalVoronoi - - `#6687 <https://github.com/scipy/scipy/pull/6687>`__: DOC: add section "deciding on new features" to developer guide. - - `#6691 <https://github.com/scipy/scipy/pull/6691>`__: ENH: Clearer error when fmin_slsqp obj doesn't return scalar - - `#6702 <https://github.com/scipy/scipy/pull/6702>`__: TST: Added airspeed velocity benchmarks for scipy.spatial.distance.cdist - - `#6707 <https://github.com/scipy/scipy/pull/6707>`__: TST: interpolate: test fitpack wrappers, not _impl - - `#6709 <https://github.com/scipy/scipy/pull/6709>`__: TST: fix a number of test failures on 32-bit systems - - `#6711 <https://github.com/scipy/scipy/pull/6711>`__: MAINT: move function definitions from __fitpack.h to _fitpackmodule.c - - `#6712 <https://github.com/scipy/scipy/pull/6712>`__: MAINT: clean up wishlist in stats.morestats, and copyright statement. - - `#6715 <https://github.com/scipy/scipy/pull/6715>`__: DOC: update the release notes with BSpline et al. - - `#6716 <https://github.com/scipy/scipy/pull/6716>`__: MAINT: scipy.io.wavfile: No infinite loop when trying to read... - - `#6717 <https://github.com/scipy/scipy/pull/6717>`__: some style cleanup - - `#6723 <https://github.com/scipy/scipy/pull/6723>`__: BUG: special: cast to float before in-place multiplication in... - - `#6726 <https://github.com/scipy/scipy/pull/6726>`__: address performance regressions in interp1d - - `#6728 <https://github.com/scipy/scipy/pull/6728>`__: DOC: made code examples in `integrate` tutorial copy-pasteable - - `#6731 <https://github.com/scipy/scipy/pull/6731>`__: DOC: scipy.optimize: Added an example for wrapping complex-valued... - - `#6732 <https://github.com/scipy/scipy/pull/6732>`__: MAINT: cython_special: remove `errprint` - - `#6733 <https://github.com/scipy/scipy/pull/6733>`__: MAINT: special: fix some pyflakes warnings - - `#6734 <https://github.com/scipy/scipy/pull/6734>`__: DOC: sparse.linalg: fixed matrix description in `bicgstab` doc - - `#6737 <https://github.com/scipy/scipy/pull/6737>`__: BLD: update `cythonize.py` to detect changes in pxi files - - `#6740 <https://github.com/scipy/scipy/pull/6740>`__: DOC: special: some small fixes to docstrings - - `#6741 <https://github.com/scipy/scipy/pull/6741>`__: MAINT: remove dead code in interpolate.py - - `#6742 <https://github.com/scipy/scipy/pull/6742>`__: BUG: fix ``linalg.block_diag`` to support zero-sized matrices. - - `#6744 <https://github.com/scipy/scipy/pull/6744>`__: ENH: interpolate: make PPoly.from_spline accept BSpline objects - - `#6746 <https://github.com/scipy/scipy/pull/6746>`__: DOC: special: clarify use of Condon-Shortley phase in `sph_harm`/`lpmv` - - `#6750 <https://github.com/scipy/scipy/pull/6750>`__: ENH: sparse: avoid densification on broadcasted elem-wise mult - - `#6751 <https://github.com/scipy/scipy/pull/6751>`__: sinm doc explained cosm - - `#6753 <https://github.com/scipy/scipy/pull/6753>`__: ENH: special: allow for more fine-tuned error handling - - `#6759 <https://github.com/scipy/scipy/pull/6759>`__: Move logsumexp and pade from scipy.misc to scipy.special and... - - `#6761 <https://github.com/scipy/scipy/pull/6761>`__: ENH: argmax and argmin methods for sparse matrices - - `#6762 <https://github.com/scipy/scipy/pull/6762>`__: DOC: Improve docstrings of sparse matrices - - `#6763 <https://github.com/scipy/scipy/pull/6763>`__: ENH: Weighted tau - - `#6768 <https://github.com/scipy/scipy/pull/6768>`__: ENH: cythonized spherical Voronoi region polygon vertex sorting - - `#6770 <https://github.com/scipy/scipy/pull/6770>`__: Correction of Delaunay class' documentation - - `#6775 <https://github.com/scipy/scipy/pull/6775>`__: ENH: Integrating LAPACK "expert" routines with conditioning warnings... - - `#6776 <https://github.com/scipy/scipy/pull/6776>`__: MAINT: Removing the trivial f2py warnings - - `#6777 <https://github.com/scipy/scipy/pull/6777>`__: DOC: Update rv_continuous.fit doc. - - `#6778 <https://github.com/scipy/scipy/pull/6778>`__: MAINT: cluster.hierarchy: Improved wording of error msgs - - `#6786 <https://github.com/scipy/scipy/pull/6786>`__: BLD: increase minimum Cython version to 0.23.4 - - `#6787 <https://github.com/scipy/scipy/pull/6787>`__: DOC: expand on ``linalg.block_diag`` changes in 0.19.0 release... - - `#6789 <https://github.com/scipy/scipy/pull/6789>`__: ENH: Add further documentation for norm.fit - - `#6790 <https://github.com/scipy/scipy/pull/6790>`__: MAINT: Fix a potential problem in nn_chain linkage algorithm - - `#6791 <https://github.com/scipy/scipy/pull/6791>`__: DOC: Add examples to scipy.ndimage.fourier - - `#6792 <https://github.com/scipy/scipy/pull/6792>`__: DOC: fix some numpydoc / Sphinx issues. - - `#6793 <https://github.com/scipy/scipy/pull/6793>`__: MAINT: fix circular import after moving functions out of misc - - `#6796 <https://github.com/scipy/scipy/pull/6796>`__: TST: test importing each submodule. Regression test for gh-6793. - - `#6799 <https://github.com/scipy/scipy/pull/6799>`__: ENH: stats: Argus distribution - - `#6801 <https://github.com/scipy/scipy/pull/6801>`__: ENH: stats: Histogram distribution - - `#6803 <https://github.com/scipy/scipy/pull/6803>`__: TST: make sure tests for ``_build_utils`` are run. - - `#6804 <https://github.com/scipy/scipy/pull/6804>`__: MAINT: more fixes in `loggamma` - - `#6806 <https://github.com/scipy/scipy/pull/6806>`__: ENH: Faster linkage for 'centroid' and 'median' methods - - `#6810 <https://github.com/scipy/scipy/pull/6810>`__: ENH: speed up upfirdn and resample_poly for n-dimensional arrays - - `#6812 <https://github.com/scipy/scipy/pull/6812>`__: TST: Added ConvexHull asv benchmark code - - `#6814 <https://github.com/scipy/scipy/pull/6814>`__: ENH: Different extrapolation modes for different dimensions in... - - `#6826 <https://github.com/scipy/scipy/pull/6826>`__: Signal spectral window default fix - - `#6828 <https://github.com/scipy/scipy/pull/6828>`__: BUG: SphericalVoronoi Space Complexity (Fixes #6811) - - `#6830 <https://github.com/scipy/scipy/pull/6830>`__: RealData docstring correction - - `#6834 <https://github.com/scipy/scipy/pull/6834>`__: DOC: Added reference for skewtest function. See #6829 - - `#6836 <https://github.com/scipy/scipy/pull/6836>`__: DOC: Added mode='mirror' in the docstring for the functions accepting... - - `#6838 <https://github.com/scipy/scipy/pull/6838>`__: MAINT: sparse: start removing old BSR methods - - `#6844 <https://github.com/scipy/scipy/pull/6844>`__: handle incompatible dimensions when input is not an ndarray in... - - `#6847 <https://github.com/scipy/scipy/pull/6847>`__: Added maxiter to golden search. - - `#6850 <https://github.com/scipy/scipy/pull/6850>`__: BUG: added check for optional param scipy.stats.spearmanr - - `#6858 <https://github.com/scipy/scipy/pull/6858>`__: MAINT: Removing redundant tests - - `#6861 <https://github.com/scipy/scipy/pull/6861>`__: DEP: Fix escape sequences deprecated in Python 3.6. - - `#6862 <https://github.com/scipy/scipy/pull/6862>`__: DOC: dx should be float, not int - - `#6863 <https://github.com/scipy/scipy/pull/6863>`__: updated documentation curve_fit - - `#6866 <https://github.com/scipy/scipy/pull/6866>`__: DOC : added some documentation to j1 referring to spherical_jn - - `#6867 <https://github.com/scipy/scipy/pull/6867>`__: DOC: cdist move long examples list into Notes section - - `#6868 <https://github.com/scipy/scipy/pull/6868>`__: BUG: Make stats.mode return a ModeResult namedtuple on empty... - - `#6871 <https://github.com/scipy/scipy/pull/6871>`__: Corrected documentation. - - `#6874 <https://github.com/scipy/scipy/pull/6874>`__: ENH: gaussian_kde.logpdf based on logsumexp - - `#6877 <https://github.com/scipy/scipy/pull/6877>`__: BUG: ndimage: guard against footprints of all zeros - - `#6881 <https://github.com/scipy/scipy/pull/6881>`__: python 3.6 - - `#6885 <https://github.com/scipy/scipy/pull/6885>`__: Vectorized integrate.fixed_quad - - `#6886 <https://github.com/scipy/scipy/pull/6886>`__: fixed typo - - `#6891 <https://github.com/scipy/scipy/pull/6891>`__: TST: fix failures for linalg.dare/care due to tightened test... - - `#6892 <https://github.com/scipy/scipy/pull/6892>`__: DOC: fix a bunch of Sphinx errors. - - `#6894 <https://github.com/scipy/scipy/pull/6894>`__: TST: Added asv benchmarks for scipy.spatial.Voronoi - - `#6908 <https://github.com/scipy/scipy/pull/6908>`__: BUG: Fix return dtype for complex input in spsolve - - `#6909 <https://github.com/scipy/scipy/pull/6909>`__: ENH: fftpack: use float32 routines for float16 inputs. - - `#6911 <https://github.com/scipy/scipy/pull/6911>`__: added min/max support to binned_statistic - - `#6913 <https://github.com/scipy/scipy/pull/6913>`__: Fix 6875: SLSQP raise ValueError for all invalid bounds. - - `#6914 <https://github.com/scipy/scipy/pull/6914>`__: DOCS: GH6903 updating docs of Spatial.distance.pdist - - `#6916 <https://github.com/scipy/scipy/pull/6916>`__: MAINT: fix some issues for 32-bit Python - - `#6924 <https://github.com/scipy/scipy/pull/6924>`__: BLD: update Bento build for scipy.LowLevelCallable - - `#6932 <https://github.com/scipy/scipy/pull/6932>`__: ENH: Use OrderedDict in io.netcdf. Closes gh-5537 - - `#6933 <https://github.com/scipy/scipy/pull/6933>`__: BUG: fix LowLevelCallable issue on 32-bit Python. - - `#6936 <https://github.com/scipy/scipy/pull/6936>`__: BUG: sparse: handle size-1 2D indexes correctly - - `#6938 <https://github.com/scipy/scipy/pull/6938>`__: TST: fix test failures in special on 32-bit Python. - - `#6939 <https://github.com/scipy/scipy/pull/6939>`__: Added attributes list to cKDTree docstring - - `#6940 <https://github.com/scipy/scipy/pull/6940>`__: improve efficiency of dok_matrix.tocoo - - `#6942 <https://github.com/scipy/scipy/pull/6942>`__: DOC: add link to liac-arff package in the io.arff docstring. - - `#6943 <https://github.com/scipy/scipy/pull/6943>`__: MAINT: Docstring fixes and an additional test for linalg.solve - - `#6944 <https://github.com/scipy/scipy/pull/6944>`__: DOC: Add example of odeint with a banded Jacobian to the integrate... - - `#6946 <https://github.com/scipy/scipy/pull/6946>`__: ENH: hypergeom.logpmf in terms of betaln - - `#6947 <https://github.com/scipy/scipy/pull/6947>`__: TST: speedup distance tests - - `#6948 <https://github.com/scipy/scipy/pull/6948>`__: DEP: Deprecate the keyword "debug" from linalg.solve - - `#6950 <https://github.com/scipy/scipy/pull/6950>`__: BUG: Correctly treat large integers in MMIO (fixes #6397) - - `#6952 <https://github.com/scipy/scipy/pull/6952>`__: ENH: Minor user-friendliness cleanup in LowLevelCallable - - `#6956 <https://github.com/scipy/scipy/pull/6956>`__: DOC: improve description of 'output' keyword for convolve - - `#6957 <https://github.com/scipy/scipy/pull/6957>`__: ENH more informative error in sparse.bmat - - `#6962 <https://github.com/scipy/scipy/pull/6962>`__: Shebang fixes - - `#6964 <https://github.com/scipy/scipy/pull/6964>`__: DOC: note argmin/argmax addition - - `#6965 <https://github.com/scipy/scipy/pull/6965>`__: BUG: Fix issues passing error tolerances in dblquad and tplquad. - - `#6971 <https://github.com/scipy/scipy/pull/6971>`__: fix the docstring of signaltools.correlate - - `#6973 <https://github.com/scipy/scipy/pull/6973>`__: Silence expected numpy warnings in scipy.ndimage.interpolation.zoom() - - `#6975 <https://github.com/scipy/scipy/pull/6975>`__: BUG: special: fix regex in `generate_ufuncs.py` - - `#6976 <https://github.com/scipy/scipy/pull/6976>`__: Update docstring for griddata - - `#6978 <https://github.com/scipy/scipy/pull/6978>`__: Avoid division by zero in zoom factor calculation - - `#6979 <https://github.com/scipy/scipy/pull/6979>`__: BUG: ARE solvers did not check the generalized case carefully - - `#6985 <https://github.com/scipy/scipy/pull/6985>`__: ENH: sparse: add scipy.sparse.linalg.spsolve_triangular - - `#6994 <https://github.com/scipy/scipy/pull/6994>`__: MAINT: spatial: updates to plotting utils - - `#6995 <https://github.com/scipy/scipy/pull/6995>`__: DOC: Bad documentation of k in sparse.linalg.eigs See #6990 - - `#6997 <https://github.com/scipy/scipy/pull/6997>`__: TST: Changed the test with a less singular example - - `#7000 <https://github.com/scipy/scipy/pull/7000>`__: DOC: clarify interp1d 'zero' argument - - `#7007 <https://github.com/scipy/scipy/pull/7007>`__: BUG: Fix division by zero in linregress() for 2 data points - - `#7009 <https://github.com/scipy/scipy/pull/7009>`__: BUG: Fix problem in passing drop_rule to scipy.sparse.linalg.spilu - - `#7012 <https://github.com/scipy/scipy/pull/7012>`__: speed improvment in _distn_infrastructure.py - - `#7014 <https://github.com/scipy/scipy/pull/7014>`__: Fix Typo: add a single quotation mark to fix a slight typo - - `#7021 <https://github.com/scipy/scipy/pull/7021>`__: MAINT: stats: use machine constants from np.finfo, not machar - - `#7026 <https://github.com/scipy/scipy/pull/7026>`__: MAINT: update .mailmap - - `#7032 <https://github.com/scipy/scipy/pull/7032>`__: Fix layout of rv_histogram docs - - `#7035 <https://github.com/scipy/scipy/pull/7035>`__: DOC: update 0.19.0 release notes - - `#7036 <https://github.com/scipy/scipy/pull/7036>`__: ENH: Add more boundary options to signal.stft - - `#7040 <https://github.com/scipy/scipy/pull/7040>`__: TST: stats: skip too slow tests - - `#7042 <https://github.com/scipy/scipy/pull/7042>`__: MAINT: sparse: speed up setdiag tests - - `#7043 <https://github.com/scipy/scipy/pull/7043>`__: MAINT: refactory and code cleaning Xdist - - `#7053 <https://github.com/scipy/scipy/pull/7053>`__: Fix msvc 9 and 10 compile errors - - `#7060 <https://github.com/scipy/scipy/pull/7060>`__: DOC: updated release notes with #7043 and #6656 - - `#7062 <https://github.com/scipy/scipy/pull/7062>`__: MAINT: Change defaut STFT boundary kwarg to "zeros" - - `#7064 <https://github.com/scipy/scipy/pull/7064>`__: Fix ValueError: path is on mount 'X:', start on mount 'D:' on... - - `#7067 <https://github.com/scipy/scipy/pull/7067>`__: TST: Fix PermissionError: [Errno 13] Permission denied on Windows - - `#7068 <https://github.com/scipy/scipy/pull/7068>`__: TST: Fix UnboundLocalError: local variable 'data' referenced... - - `#7069 <https://github.com/scipy/scipy/pull/7069>`__: Fix OverflowError: Python int too large to convert to C long... - - `#7071 <https://github.com/scipy/scipy/pull/7071>`__: TST: silence RuntimeWarning for nan test of stats.spearmanr - - `#7072 <https://github.com/scipy/scipy/pull/7072>`__: Fix OverflowError: Python int too large to convert to C long... - - `#7084 <https://github.com/scipy/scipy/pull/7084>`__: TST: linalg: bump tolerance in test_falker - - `#7095 <https://github.com/scipy/scipy/pull/7095>`__: TST: linalg: bump more tolerances in test_falker - - `#7101 <https://github.com/scipy/scipy/pull/7101>`__: TST: Relax solve_continuous_are test case 2 and 12 - - `#7106 <https://github.com/scipy/scipy/pull/7106>`__: BUG: stop cdist "correlation" modifying input - - `#7116 <https://github.com/scipy/scipy/pull/7116>`__: Backports to 0.19.0rc2 Checksums ========= MD5 ~~~ dde4d5d44a0274a5abb01be4a3cd486a scipy-0.19.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 08809612b46e660e567e3272ec11c808 scipy-0.19.0-cp27-cp27m-manylinux1_i686.whl 0e49f7fc8d31c1c79f0a4d63b29e8a1f scipy-0.19.0-cp27-cp27m-manylinux1_x86_64.whl a2669158cf847856d292b8a60cdaa170 scipy-0.19.0-cp27-cp27mu-manylinux1_i686.whl adfa1f5127a789165dfe9ff140ec0d6e scipy-0.19.0-cp27-cp27mu-manylinux1_x86_64.whl d568c9f60683c33b81ebc1c39eea198a scipy-0.19.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl a90148fec477c1950578b40a1197509f scipy-0.19.0-cp34-cp34m-manylinux1_i686.whl ed27be5380e0aaf0229adf747e760f8c scipy-0.19.0-cp34-cp34m-manylinux1_x86_64.whl 4cda63dc7b73bd03bdf9e8ebc6027526 scipy-0.19.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl ff8e652b5e918b276793f1ce542a5959 scipy-0.19.0-cp35-cp35m-manylinux1_i686.whl 60741a900a145eb924ec861ec2743582 scipy-0.19.0-cp35-cp35m-manylinux1_x86_64.whl 81685a961d6118459b7787e8465c8d36 scipy-0.19.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 83f0750862c80a659686797d4ec9bca0 scipy-0.19.0-cp36-cp36m-manylinux1_i686.whl 3cbb30615496fbbf9b52c9a643c6fe5e scipy-0.19.0-cp36-cp36m-manylinux1_x86_64.whl 735cdb6fbfcb9917535749816202d0af scipy-0.19.0.tar.gz b21466e87a642940fb9ba35be74940a3 scipy-0.19.0.tar.xz 91b8396231eec780222a57703d3ec550 scipy-0.19.0.zip SHA256 ~~~~~~ 517a85600d6574fef1a67e6d2001b847c27c8bfd136f7a12879c3f91e7bb291f scipy-0.19.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 3c34987ee52fd98b34f2e4a6d277b452d49056f1383550acc54c5bab408a194c scipy-0.19.0-cp27-cp27m-manylinux1_i686.whl eabdfde8276007e9aec9a400f9528645001a30f7d78b04a0ab215183d9523e2a scipy-0.19.0-cp27-cp27m-manylinux1_x86_64.whl fa67bbb0a3225fcd8610d693e7b2ca08fda107359e48229f7b83593bbb70cc97 scipy-0.19.0-cp27-cp27mu-manylinux1_i686.whl 4147b97709e75822e73d312e4d262410baafa961a7b11649a7b4b7c2d41fb4fe scipy-0.19.0-cp27-cp27mu-manylinux1_x86_64.whl 663e78bfa197376547424aff9fb5009e7b2f26855ee5aaf1a2ddbb2f4dc6af3b scipy-0.19.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 2e70ded029d51f6a48d4b2a154f583b85aa2e3290dfd71e0b6bbcfe9454cffdd scipy-0.19.0-cp34-cp34m-manylinux1_i686.whl 4b2731a191dfa48a05b2f5bc18881595a1418092092ecdd8d3feab80f72adc96 scipy-0.19.0-cp34-cp34m-manylinux1_x86_64.whl 57f7be33f1009ad6199132e8a7e5d4c9727224680d8cbc4596a2a8935a86f96b scipy-0.19.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 0496f2b204a63cde3797e5452bf671ee25afc11bd9489ae69cd4dccee13083a1 scipy-0.19.0-cp35-cp35m-manylinux1_i686.whl 1bcf71f2e534a1aabf9f075700701bf3af434120b1b114dfa4723d02e076ed1f scipy-0.19.0-cp35-cp35m-manylinux1_x86_64.whl e1c45905f550b5f14e1f47697c92bab5c1e6ba77da5a441bd2affa4621c41b26 scipy-0.19.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 47f537214293a5d74b05d217afa49b582b7fd9428ec9ea64be69210cfc56611a scipy-0.19.0-cp36-cp36m-manylinux1_i686.whl f5a3a7dcbeb345c227770029870aeb547a3c207a6cbc0106d6157139fd0c23e9 scipy-0.19.0-cp36-cp36m-manylinux1_x86_64.whl eba12b5f757a8c839b26a06f4936ecb80b65cb3674981ee25449b2a55663abe8 scipy-0.19.0.tar.gz ed52232afb2b321a4978e39040d94bf81af90176ba64f58c4499dc305a024437 scipy-0.19.0.tar.xz 4190d34bf9a09626cd42100bbb12e3d96b2daf1a8a3244e991263eb693732122 scipy-0.19.0.zip -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.11 (GNU/Linux) iQEcBAEBCAAGBQJYwWscAAoJEIp0pQ0zQcu+JG8H+gOy04ecVl+IBisy/Fz5wfuy xrsCT5yhRPQpxKph8g/6Us5Oh7s8ixrVt9gTVccAspmWXQJhMy5kcppC3s5WsvU+ jFOwUnW7c9QvtIf2ZD9Ay/56WojlXg1ui17MqoCbmkEn2QE8KTKu93hIZpVD5wmV 1fhd7u/ieeQ7sfj6gMZzt0AGpVjnGedEzHRY4zI0PkiCY+Ex8sc2W8G2h5Qbnx9r KoqECIuesLQzVbNgPhWaWaiE1TNX0EJYdWQll0T8scI4opUdg6vEaR05aPhxeR1r KaGEnvfASTZ369COkuVB4JINlKQj0dwLBFIr9NGVzX4vU74GMh5TuDfJlA/mvGU= =bOnA -----END PGP SIGNATURE-----

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Running Tests
by ashwin.pathak March 9, 2017

March 9, 2017

Hello all, I was learning about nose and test suites, I am not able to figure out how to run test for particular functions that I changed. Can someone help me know the procedure as to how to run tests for individual functions. Thank you

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Drop i386 part of OSX wheel build?
by Matthew Brett March 8, 2017

March 8, 2017

Hi, We're running into travis-ci time limits when building OSX wheels: https://travis-ci.org/MacPython/scipy-wheels/builds/204105101 The main reason for this is that, for OSX, we are building twice, first for i386, then for x86_64, and then combining these builds into a 'fat' binary to be compatible with either architecture. The builds take a long time, hence the timeout. I believe that the i386 architecture on OSX is pretty much unused now. For example, it looks like south of 0.5% of CPUs running OSX cannot do 64-bit: https://www.adium.im/sparkle/#cpu64bit I propose that we drop the i386 part of the scipy build, but continue to distribute apparently dual-arch wheels (architecture 'intel') so that the wheel installs into the Python.org and System Python builds [1]. This has the added advantage of making the wheel build process a lot simpler. Thoughts? Best, Matthew [1] https://bitbucket.org/pygame/pygame/issues/300/os-x-wheels-dmg-and-zip-buil…

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Fwd: Docathon Day 1 Update: The Doccening
by Ralf Gommers March 7, 2017

March 7, 2017

Hi all, The docathlon has started, and Warren got us off the mark with https://github.com/scipy/scipy/pull/7138 (thanks!). If you want to contribute, an easy way is what Warren did: pick a function with an incomplete docstring (e.g. missing example) and add it. Alternatively, look at one of the issues with the documentation label: https://github.com/scipy/scipy/issues?q=is%3Aopen+is%3Aissue+label%3ADocume… And remember to start your commit message with DOC:. Cheers, Ralf ---------- Forwarded message ---------- From: The Docathon Team <choldgraf(a)berkeley.edu> Date: Tue, Mar 7, 2017 at 3:58 PM Subject: Docathon Day 1 Update: The Doccening To: ralf.gommers(a)gmail.com *To err is human, to document is divine -Docrates* The Docathon is One Day Old! <http://predictablynoisy.us15.list-manage.com/track/click?u=80bb9d960ec9c989…> The docathon just turned one (day old)! Here's a quick update to congratulate everybody on a great first day. Updates - We kicked off the week at BIDS by hosting a half-day of Documentation Tutorials <http://predictablynoisy.us15.list-manage.com/track/click?u=80bb9d960ec9c989…>. These were live-streamed on youtube <http://predictablynoisy.us15.list-manage.com/track/click?u=80bb9d960ec9c989…> for your viewing pleasure! - We also demoed a template repository <http://predictablynoisy.us15.list-manage.com/track/click?u=80bb9d960ec9c989…> to help you get sphinx / numpydoc / sphinx-gallery working with your project. Use that along with this guide repository <http://predictablynoisy.us15.list-manage1.com/track/click?u=80bb9d960ec9c98…> to help you get started! Check out the docboards! My favorite thing about today is that you can totally see a bump in the documentation commits for our projects. You can check that out on our global activity board below: *Global Activity* We should also give a shout out to our docstar projects that showed a big bump in activity today. Here's our docboard for project commits: Three cheers for: - PMagPy <http://predictablynoisy.us15.list-manage1.com/track/click?u=80bb9d960ec9c98…>, a python project for analyzing paleomagnetic data - cottoncandy <http://predictablynoisy.us15.list-manage.com/track/click?u=80bb9d960ec9c989…>, a project for storing and flexibly accessing numpy data on Amazon S3. - Sylius <http://predictablynoisy.us15.list-manage.com/track/click?u=80bb9d960ec9c989…>, a platform for e-commerce using PHP We also got a big bump in commits from individual users! Here's what everybody has been up to: Let's give a shout out to this day's docstars *anwarnunez*, *willingc*, and *swanson-hysell*. Keep it going! We look forward to seeing what comes next tomorrow. The working groups will be holding sessions once again, though we've gotten a lot of great contributions from people all over the country! We're making great progress, so let's keep the momentum through tomorrow! Until then, *The Docathon Team* Docathon website <http://predictablynoisy.us15.list-manage1.com/track/click?u=80bb9d960ec9c98…> Projects page <http://predictablynoisy.us15.list-manage.com/track/click?u=80bb9d960ec9c989…> Hosts page <http://predictablynoisy.us15.list-manage2.com/track/click?u=80bb9d960ec9c98…> Slack channel <http://predictablynoisy.us15.list-manage2.com/track/click?u=80bb9d960ec9c98…> Github repo <http://predictablynoisy.us15.list-manage.com/track/click?u=80bb9d960ec9c989…> all hail the party parrot [image: Email Marketing Powered by MailChimp] <http://www.mailchimp.com/monkey-rewards/?utm_source=freemium_newsletter&utm…> <http://predictablynoisy.us15.list-manage1.com/track/click?u=80bb9d960ec9c98…> <http://bids.github.io/docathon> <http://predictablynoisy.us15.list-manage.com/track/click?u=80bb9d960ec9c989…> All hail the party parrot. <http://predictablynoisy.us15.list-manage1.com/track/click?u=80bb9d960ec9c98…> Want to change how you receive these emails? You can update your preferences <http://predictablynoisy.us15.list-manage.com/profile?u=80bb9d960ec9c9896a0c…> or unsubscribe from this list <http://predictablynoisy.us15.list-manage.com/unsubscribe?u=80bb9d960ec9c989…>

1 0

NumPy pre-release 1.12.1rc1
by Charles R Harris March 7, 2017

March 7, 2017

Hi All, I'm pleased to announce the release of NumPy 1.12.1rc1. NumPy 1.12.1rc1 supports Python 2.7 and 3.4 - 3.6 and fixes bugs and regressions found in NumPy 1.12.0. In particular, the regression in f2py constant parsing is fixed. Wheels for Linux, Windows, and OSX can be found on pypi. Archives can be downloaded from github <https://github.com/numpy/numpy/releases/tag/v1.12.1rc1>. *Contributors* A total of 10 people contributed to this release. People with a "+" by their names contributed a patch for the first time. * Charles Harris * Eric Wieser * Greg Young * Joerg Behrmann + * John Kirkham * Julian Taylor * Marten van Kerkwijk * Matthew Brett * Shota Kawabuchi * Jean Utke + *Fixes Backported* * #8483: BUG: Fix wrong future nat warning and equiv type logic error... * #8489: BUG: Fix wrong masked median for some special cases * #8490: DOC: Place np.average in inline code * #8491: TST: Work around isfinite inconsistency on i386 * #8494: BUG: Guard against replacing constants without `'_'` spec in f2py. * #8524: BUG: Fix mean for float 16 non-array inputs for 1.12 * #8571: BUG: Fix calling python api with error set and minor leaks for... * #8602: BUG: Make iscomplexobj compatible with custom dtypes again * #8618: BUG: Fix undefined behaviour induced by bad `__array_wrap__` * #8648: BUG: Fix `MaskedArray.__setitem__` * #8659: BUG: PPC64el machines are POWER for Fortran in f2py * #8665: BUG: Look up methods on MaskedArray in `_frommethod` * #8674: BUG: Remove extra digit in `binary_repr` at limit * #8704: BUG: Fix deepcopy regression for empty arrays. * #8707: BUG: Fix ma.median for empty ndarrays Cheers, Chuck

1 0

Re: [SciPy-Dev] Owen's T function
by Evgeny Zhurko March 3, 2017

March 3, 2017

Maybe someone have borrowed constants before me but i didn't found it. I included all constant and test data from Boost in last commit. But i have new questions: I implemented T1-T6 methods and tried test function on Boost's test data. All tests passed when i use assert_almost_equal with decimal=1. About 30 of 400 examples have deviation 0.01 from real value, 40 of 400 examples have deviation about 1e-10 and the others less then 1e-18. Boost have improvement for some methods ( http://www.boost.org/doc/libs/1_52_0/boost/math/special_functions/owens_t.h…). Is it enough to insert copyright in source code if i'll implement this algorithm into Scipy? Test data have a very big size(about 100 character per number). I inserted data into test_basic.py . May I move test data into txt or csv file and read it in tests? Is it requires including copyright into file with test data? Test data from Boost not cover all methods(only T2, T4) as a result I want to use Owen, Donald B. "Tables for Computing Bivariate Normal Probabilities." ( http://projecteuclid.org/download/pdf_1/euclid.aoms/1177728074). Pull request: https://github.com/scipy/scipy/pull/7120

2 1