SciPy 1.3.0 Release Notes#

SciPy 1.3.0 is the culmination of 5 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been some 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. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with python -Wd and check for DeprecationWarning s). Our development attention will now shift to bug-fix releases on the 1.3.x branch, and on adding new features on the master branch.

This release requires Python 3.5+ and NumPy 1.13.3 or greater.

For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required.

Highlights of this release#

  • Three new stats functions, a rewrite of pearsonr, and an exact computation of the Kolmogorov-Smirnov two-sample test.

  • A new Cython API for bounded scalar-function root-finders in scipy.optimize.

  • Substantial CSR and CSC sparse matrix indexing performance improvements.

  • Added support for interpolation of rotations with continuous angular rate and acceleration in RotationSpline.

New features#

scipy.interpolate improvements#

A new class CubicHermiteSpline is introduced. It is a piecewise-cubic interpolator which matches observed values and first derivatives. Existing cubic interpolators CubicSpline, PchipInterpolator and Akima1DInterpolator were made subclasses of CubicHermiteSpline. improvements#

For the Attribute-Relation File Format (ARFF) now supports relational attributes. can now parse Matrix Market format files with empty lines.

scipy.linalg improvements#

Added wrappers for ?syconv routines, which convert a symmetric matrix given by a triangular matrix factorization into two matrices and vice versa.

scipy.linalg.clarkson_woodruff_transform now uses an algorithm that leverages sparsity. This may provide a 60-90 percent speedup for dense input matrices. Truly sparse input matrices should also benefit from the improved sketch algorithm, which now correctly runs in O(nnz(A)) time.

Added new functions to calculate symmetric Fiedler matrices and Fiedler companion matrices, named scipy.linalg.fiedler and scipy.linalg.fiedler_companion, respectively. These may be used for root finding.

scipy.ndimage improvements#

Gaussian filter performances may improve by an order of magnitude in some cases, thanks to the removal of a dependence on np.polynomial. This may impact scipy.ndimage.gaussian_filter for example.

scipy.optimize improvements#

The scipy.optimize.brute minimizer obtained a new keyword workers, which can be used to parallelize computation.

A Cython API for bounded scalar-function root-finders in scipy.optimize is available in a new module scipy.optimize.cython_optimize via cimport. This API may be used with nogil and prange to loop over an array of function arguments to solve for an array of roots more quickly than with pure Python.

'interior-point' is now the default method for linprog, and 'interior-point' now uses SuiteSparse for sparse problems when the required scikits (scikit-umfpack and scikit-sparse) are available. On benchmark problems (gh-10026), execution time reductions by factors of 2-3 were typical. Also, a new method='revised simplex' has been added. It is not as fast or robust as method='interior-point', but it is a faster, more robust, and equally accurate substitute for the legacy method='simplex'.

differential_evolution can now use a Bounds class to specify the bounds for the optimizing argument of a function.

scipy.optimize.dual_annealing performance improvements related to vectorization of some internal code.

scipy.signal improvements#

Two additional methods of discretization are now supported by scipy.signal.cont2discrete: impulse and foh.

scipy.signal.firls now uses faster solvers.

scipy.signal.detrend now has a lower physical memory footprint in some cases, which may be leveraged using the new overwrite_data keyword argument.

scipy.signal.firwin pass_zero argument now accepts new string arguments that allow specification of the desired filter type: 'bandpass', 'lowpass', 'highpass', and 'bandstop'.

scipy.signal.sosfilt may have improved performance due to lower retention of the global interpreter lock (GIL) in the algorithm.

scipy.sparse improvements#

A new keyword was added to csgraph.dijsktra that allows users to query the shortest path to ANY of the passed-in indices, as opposed to the shortest path to EVERY passed index.

scipy.sparse.linalg.lsmr performance has been improved by roughly 10 percent on large problems.

Improved performance and reduced physical memory footprint of the algorithm used by scipy.sparse.linalg.lobpcg.

CSR and CSC sparse matrix fancy indexing performance has been improved substantially.

scipy.spatial improvements#

scipy.spatial.ConvexHull now has a good attribute that can be used alongsize the QGn Qhull options to determine which external facets of a convex hull are visible from an external query point.

scipy.spatial.cKDTree.query_ball_point has been modernized to use some newer Cython features, including GIL handling and exception translation. An issue with return_sorted=True and scalar queries was fixed, and a new mode named return_length was added. return_length only computes the length of the returned indices list instead of allocating the array every time.

scipy.spatial.transform.RotationSpline has been added to enable interpolation of rotations with continuous angular rates and acceleration.

scipy.stats improvements#

Added a new function to compute the Epps-Singleton test statistic, scipy.stats.epps_singleton_2samp, which can be applied to continuous and discrete distributions.

New functions scipy.stats.median_absolute_deviation and scipy.stats.gstd (geometric standard deviation) were added. The scipy.stats.combine_pvalues method now supports pearson, tippett and mudholkar_george pvalue combination methods.

The scipy.stats.ortho_group and scipy.stats.special_ortho_group rvs(dim) functions’ algorithms were updated from a O(dim^4) implementation to a O(dim^3) which gives large speed improvements for dim>100.

A rewrite of scipy.stats.pearsonr to use a more robust algorithm, provide meaningful exceptions and warnings on potentially pathological input, and fix at least five separate reported issues in the original implementation.

Improved the precision of hypergeom.logcdf and hypergeom.logsf.

Added exact computation for Kolmogorov-Smirnov (KS) two-sample test, replacing the previously approximate computation for the two-sided test stats.ks_2samp. Also added a one-sided, two-sample KS test, and a keyword alternative to stats.ks_2samp.

Backwards-incompatible changes#

scipy.interpolate changes#

Functions from scipy.interpolate (spleval, spline, splmake, and spltopp) and functions from scipy.misc (bytescale, fromimage, imfilter, imread, imresize, imrotate, imsave, imshow, toimage) have been removed. The former set has been deprecated since v0.19.0 and the latter has been deprecated since v1.0.0. Similarly, aliases from scipy.misc (comb, factorial, factorial2, factorialk, logsumexp, pade, info, source, who) which have been deprecated since v1.0.0 are removed. SciPy documentation for v1.1.0 can be used to track the new import locations for the relocated functions.

scipy.linalg changes#

For pinv, pinv2, and pinvh, the default cutoff values are changed for consistency (see the docs for the actual values).

scipy.optimize changes#

The default method for linprog is now 'interior-point'. The method’s robustness and speed come at a cost: solutions may not be accurate to machine precision or correspond with a vertex of the polytope defined by the constraints. To revert to the original simplex method, include the argument method='simplex'.

scipy.stats changes#

Previously, ks_2samp(data1, data2) would run a two-sided test and return the approximated p-value. The new signature, ks_2samp(data1, data2, alternative="two-sided", method="auto"), still runs the two-sided test by default but returns the exact p-value for small samples and the approximated value for large samples. method="asymp" would be equivalent to the old version but auto is the better choice.

Other changes#

Our tutorial has been expanded with a new section on global optimizers.

There has been a rework of the stats.distributions tutorials.

scipy.optimize now correctly sets the convergence flag of the result to CONVERR, a convergence error, for bounded scalar-function root-finders if the maximum iterations has been exceeded, disp is false, and full_output is true.

scipy.optimize.curve_fit no longer fails if xdata and ydata dtypes differ; they are both now automatically cast to float64.

scipy.ndimage functions including binary_erosion, binary_closing, and binary_dilation now require an integer value for the number of iterations, which alleviates a number of reported issues.

Fixed normal approximation in case zero_method == "pratt" in scipy.stats.wilcoxon.

Fixes for incorrect probabilities, broadcasting issues and thread-safety related to stats distributions setting member variables inside _argcheck().

scipy.optimize.newton now correctly raises a RuntimeError in the following cases: when default arguments are used and if a derivative of value zero is obtained (which is a special case of failing to converge).

A draft toolchain roadmap is now available, laying out a compatibility plan including Python versions, C standards, and NumPy versions.


  • ananyashreyjain +

  • ApamNapat +

  • Scott Calabrese Barton +

  • Christoph Baumgarten

  • Peter Bell +

  • Jacob Blomgren +

  • Doctor Bob +

  • Mana Borwornpadungkitti +

  • Matthew Brett

  • Evgeni Burovski

  • CJ Carey

  • Vega Theil Carstensen +

  • Robert Cimrman

  • Forrest Collman +

  • Pietro Cottone +

  • David +

  • Idan David +

  • Christoph Deil

  • Dieter Werthmüller

  • Conner DiPaolo +

  • Dowon

  • Michael Dunphy +

  • Peter Andreas Entschev +

  • Gökçen Eraslan +

  • Johann Faouzi +

  • Yu Feng

  • Piotr Figiel +

  • Matthew H Flamm

  • Franz Forstmayr +

  • Christoph Gohlke

  • Richard Janis Goldschmidt +

  • Ralf Gommers

  • Lars Grueter

  • Sylvain Gubian

  • Matt Haberland

  • Yaroslav Halchenko

  • Charles Harris

  • Lindsey Hiltner

  • JakobStruye +

  • He Jia +

  • Jwink3101 +

  • Greg Kiar +

  • Julius Bier Kirkegaard

  • John Kirkham +

  • Thomas Kluyver

  • Vladimir Korolev +

  • Joseph Kuo +

  • Michael Lamparski +

  • Eric Larson

  • Denis Laxalde

  • Katrin Leinweber

  • Jesse Livezey

  • ludcila +

  • Dhruv Madeka +

  • Magnus +

  • Nikolay Mayorov

  • Mark Mikofski

  • Jarrod Millman

  • Markus Mohrhard +

  • Eric Moore

  • Andrew Nelson

  • Aki Nishimura +

  • OGordon100 +

  • Petar Mlinarić +

  • Stefan Peterson

  • Matti Picus +

  • Ilhan Polat

  • Aaron Pries +

  • Matteo Ravasi +

  • Tyler Reddy

  • Ashton Reimer +

  • Joscha Reimer

  • rfezzani +

  • Riadh +

  • Lucas Roberts

  • Heshy Roskes +

  • Mirko Scholz +

  • Taylor D. Scott +

  • Srikrishna Sekhar +

  • Kevin Sheppard +

  • Sourav Singh

  • skjerns +

  • Kai Striega

  • SyedSaifAliAlvi +

  • Gopi Manohar T +

  • Albert Thomas +

  • Timon +

  • Paul van Mulbregt

  • Jacob Vanderplas

  • Daniel Vargas +

  • Pauli Virtanen

  • VNMabus +

  • Stefan van der Walt

  • Warren Weckesser

  • Josh Wilson

  • Nate Yoder +

  • Roman Yurchak

A total of 97 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 1.3.0#

  • #1320: scipy.stats.distribution: problem with self.a, self.b if they…

  • #2002: members set in scipy.stats.distributions.##._argcheck (Trac #1477)

  • #2823: distribution methods add tmp

  • #3220: Scipy.opimize.fmin_powell direc argument syntax unclear

  • #3728: scipy.stats.pearsonr: possible bug with zero variance input

  • #6805: error-in-scipy-wilcoxon-signed-rank-test-for-equal-series

  • #6873: ‘stats.boxcox’ return all same values

  • #7117: Warn users when using float32 input data to curve_fit and friends

  • #7632: it’s not possible to tell the `optimize.least_squares` solver…

  • #7730: stats.pearsonr: Potential division by zero for dataset of length…

  • #7933: stats.truncnorm fails when providing values outside truncation…

  • #8033: Add standard filter types to firwin to set pass_zero intuitively…

  • #8600: lfilter.c.src zfill has erroneous header

  • #8692: Non-negative values of `stats.hypergeom.logcdf`

  • #8734: Enable pip build isolation

  • #8861: scipy.linalg.pinv gives wrong result while scipy.linalg.pinv2…

  • #8915: need to fix macOS build against older numpy versions

  • #8980: scipy.stats.pearsonr overflows with high values of x and y

  • #9226: BUG: signal: SystemError: <built-in function _linear_filter>…

  • #9254: BUG: root finders brentq, etc, flag says “converged” even if…

  • #9308: Test failure - test_initial_constraints_as_canonical

  • #9353: scipy.stats.pearsonr returns r=1 if r_num/r_den = inf

  • #9359: Planck distribution is a geometric distribution

  • #9381: linregress should warn user in 2x2 array case

  • #9406: BUG: stats: In pearsonr, when r is nan, the p-value must also…

  • #9437: Cannot create sparse matrix from size_t indexes

  • #9518: Relational attributes in loadarff

  • #9551: BUG: scipy.optimize.newton says the root of x^2+1 is zero.

  • #9564: rv_sample accepts invalid input in scipy.stats

  • #9565: improper handling of multidimensional input in stats.rv_sample

  • #9581: Least-squares minimization fails silently when x and y data are…

  • #9587: Outdated value for

  • #9611: Overflow error with new way of p-value calculation in kendall…

  • #9645: `scipy.stats.mode` crashes with variable length arrays (`dtype=object`)

  • #9734: PendingDeprecationWarning for np.matrix with pytest

  • #9786: stats.ks_2samp() misleading for small data sets.

  • #9790: Excessive memory usage on detrend

  • #9801: dual_annealing does not set the success attribute in OptimizeResult

  • #9833: IntegrationWarning from mielke.stats() during build of html doc.

  • #9835: scipy.signal.firls seems to be inefficient versus MATLAB firls

  • #9864: Curve_fit does not check for empty input data if called with…

  • #9869: scipy.ndimage.label: Minor documentation issue

  • #9882: format at the wrong paranthesis in scipy.spatial.transform

  • #9889: scipy.signal.find_peaks minor documentation issue

  • #9890: Minkowski p-norm Issues in cKDTree For Values Other Than 2 Or…

  • #9896: scipy.stats._argcheck sets (not just checks) values

  • #9905: Memory error in ndimage.binary_erosion

  • #9909: binary_dilation/erosion/closing crashes when iterations is float

  • #9919: BUG: `coo_matrix` does not validate the `shape` argument.

  • #9982: lsq_linear hangs/infinite loop with ‘trf’ method

  • #10003: exponnorm.pdf returns NAN for small K

  • #10011: Incorrect check for invalid rotation plane in scipy.ndimage.rotate

  • #10024: Fails to build from git

  • #10048: DOC: scipy.optimize.root_scalar

  • #10068: DOC: scipy.interpolate.splev

  • #10074: BUG: `expm` calculates the wrong coefficients in the backward…

Pull requests for 1.3.0#

  • #7827: ENH: sparse: overhaul of sparse matrix indexing

  • #8431: ENH: Cython optimize zeros api

  • #8743: DOC: Updated linalg.pinv, .pinv2, .pinvh docstrings

  • #8744: DOC: added examples to remez docstring

  • #9227: DOC: update description of “direc” parameter of “fmin_powell”

  • #9263: ENH: optimize: added “revised simplex” for scipy.optimize.linprog

  • #9325: DEP: Remove deprecated functions for 1.3.0

  • #9330: Add note on push and pull affine transformations

  • #9423: DOC: Clearly state how 2x2 input arrays are handled in stats.linregress

  • #9428: ENH: parallelised brute

  • #9438: BUG: Initialize coo matrix with size_t indexes

  • #9455: MAINT: Speed up get_(lapack,blas)_func

  • #9465: MAINT: Clean up optimize.zeros C solvers interfaces/code.

  • #9477: DOC: linalg: fix lstsq docstring on residues shape

  • #9478: DOC: Add docstring examples for rosen functions

  • #9479: DOC: Add docstring example for ai_zeros and bi_zeros

  • #9480: MAINT: linalg: lstsq clean up

  • #9489: DOC: roadmap update for changes over the last year.

  • #9492: MAINT: stats: Improve implementation of chi2 ppf method.

  • #9497: DOC: Improve docstrings sparse.linalg.isolve

  • #9499: DOC: Replace “Scipy” with “SciPy” in the .rst doc files for consistency.

  • #9500: DOC: Document the toolchain and its roadmap.

  • #9505: DOC: specify which definition of skewness is used

  • #9511: DEP: interpolate: remove deprecated interpolate_wrapper

  • #9517: BUG: improve error handling in stats.iqr

  • #9522: ENH: Add Fiedler and fiedler companion to special matrices

  • #9526: TST: relax precision requirements in signal.correlate tests

  • #9529: DOC: fix missing random seed in optimize.newton example

  • #9533: MAINT: Use list comprehension when possible

  • #9537: DOC: add a “big picture” roadmap

  • #9538: DOC: Replace “Numpy” with “NumPy” in .py, .rst and .txt doc files…

  • #9539: ENH: add two-sample test (Epps-Singleton) to scipy.stats

  • #9559: DOC: add section on global optimizers to tutorial

  • #9561: ENH: remove noprefix.h, change code appropriately

  • #9562: MAINT: stats: Rewrite pearsonr.

  • #9563: BUG: Minor bug fix Callback in linprog(method=’simplex’)

  • #9568: MAINT: raise runtime error for newton with zeroder if disp true,…

  • #9570: Correct docstring in show_options in optimize. Fixes #9407

  • #9573: BUG fixes range of pk variable pre-check

  • #9577: TST: fix minor issue in a signal.stft test.

  • #9580: Included blank line before list - Fixes #8658

  • #9582: MAINT: drop Python 2.7 and 3.4

  • #9588: MAINT: update `constants.astronomical_unit` to new 2012 value.

  • #9592: TST: Add 32-bit testing to CI

  • #9593: DOC: Replace cumulative density with cumulative distribution

  • #9596: TST: remove VC 9.0 from Azure CI

  • #9599: Hyperlink DOI to preferred resolver

  • #9601: DEV: try to limit GC memory use on PyPy

  • #9603: MAINT: improve logcdf and logsf of hypergeometric distribution

  • #9605: Reference to pylops in LinearOperator notes and ARPACK example

  • #9617: TST: reduce max memory usage for sparse.linalg.lgmres test

  • #9619: FIX: Sparse matrix addition/subtraction eliminates explicit zeros

  • #9621: bugfix in rv_sample in scipy.stats

  • #9622: MAINT: Raise error in directed_hausdorff distance

  • #9623: DOC: Build docs with warnings as errors

  • #9625: Return the number of calls to ‘hessp’ (not just ‘hess’) in trust…

  • #9627: BUG: ignore empty lines in mmio

  • #9637: Function to calculate the MAD of an array

  • #9646: BUG: stats: mode for objects w/ndim > 1

  • #9648: Add `stats.contingency` to refguide-check

  • #9650: ENH: many lobpcg() algorithm improvements

  • #9652: Move misc.doccer to _lib.doccer

  • #9660: ENH: add pearson, tippett, and mudholkar-george to combine_pvalues

  • #9661: BUG: Fix ksone right-hand endpoint, documentation and tests.

  • #9664: ENH: adding multi-target dijsktra performance enhancement

  • #9670: MAINT: link planck and geometric distribution in scipy.stats

  • #9676: ENH: optimize: change default linprog method to interior-point

  • #9685: Added reference to ndimage.filters.median_filter

  • #9705: Fix coefficients in expm helper function

  • #9711: Release the GIL during sosfilt processing for simple types

  • #9721: ENH: Convexhull visiblefacets

  • #9723: BLD: Modify rv_generic._construct_doc to print out failing distribution…

  • #9726: BUG: Fix small issues with `signal.lfilter’

  • #9729: BUG: Typecheck iterations for binary image operations

  • #9730: ENH: reduce sizeof(NI_WatershedElement) by 20%

  • #9731: ENH: remove suspicious sequence of type castings

  • #9739: BUG: qr_updates fails if u is exactly in span Q

  • #9749: BUG: MapWrapper.__exit__ should terminate

  • #9753: ENH: Added exact computation for Kolmogorov-Smirnov two-sample…

  • #9755: DOC: Added example for signal.impulse, copied from impulse2

  • #9756: DOC: Added docstring example for iirdesign

  • #9757: DOC: Added examples for step functions

  • #9759: ENH: Allow pass_zero to act like btype

  • #9760: DOC: Added docstring for lp2bs

  • #9761: DOC: Added docstring and example for lp2bp

  • #9764: BUG: Catch internal warnings for matrix

  • #9766: ENH: Speed up _gaussian_kernel1d by removing dependence on np.polynomial

  • #9769: BUG: Fix Cubic Spline Read Only issues

  • #9773: DOC: Several docstrings

  • #9774: TST: bump Azure CI OpenBLAS version to match wheels

  • #9775: DOC: Improve clarity of cov_x documentation for scipy.optimize.leastsq

  • #9779: ENH: dual_annealing vectorise visit_fn

  • #9788: TST, BUG: f2py-related issues with NumPy < 1.14.0

  • #9791: BUG: fix amax constraint not enforced in scalar_search_wolfe2

  • #9792: ENH: Allow inplace copying in place in “detrend” function

  • #9795: DOC: Fix/update docstring for dstn and dst

  • #9796: MAINT: Allow None tolerances in least_squares

  • #9798: BUG: fixes abort trap 6 error in scipy issue 9785 in unit tests

  • #9807: MAINT: improve doc and add alternative keyword to wilcoxon in…

  • #9808: Fix PPoly integrate and test for CubicSpline

  • #9810: ENH: Add the geometric standard deviation function

  • #9811: MAINT: remove invalid derphi default None value in scalar_search_wolfe2

  • #9813: Adapt hamming distance in C to support weights

  • #9817: DOC: Copy solver description to solver modules

  • #9829: ENH: Add FOH and equivalent impulse response discretizations…

  • #9831: ENH: Implement RotationSpline

  • #9834: DOC: Change mielke distribution default parameters to ensure…

  • #9838: ENH: Use faster solvers for firls

  • #9854: ENH: loadarff now supports relational attributes.

  • #9856: integrate.bvp - improve handling of nonlinear boundary conditions

  • #9862: TST: reduce Appveyor CI load

  • #9874: DOC: Update requirements in release notes

  • #9883: BUG: fixed parenthesis in spatial.rotation

  • #9884: ENH: Use Sparsity in Clarkson-Woodruff Sketch

  • #9888: MAINT: Replace NumPy aliased functions

  • #9892: BUG: Fix 9890 query_ball_point returns wrong result when p is…

  • #9893: BUG: curve_fit doesn’t check for empty input if called with bounds

  • #9894: scipy.signal.find_peaks documentation error

  • #9898: BUG: Set success attribute in OptimizeResult. See #9801

  • #9900: BUG: Restrict rv_generic._argcheck() and its overrides from setting…

  • #9906: fixed a bug in kde logpdf

  • #9911: DOC: replace example for “” with the one from numpy…

  • #9912: BF(DOC): point to instead of plain (python) .select

  • #9914: DOC: change ValueError message in _validate_pad of signaltools.

  • #9915: cKDTree query_ball_point improvements

  • #9918: Update ckdtree.pyx with boxsize argument in docstring

  • #9920: BUG: sparse: Validate explicit shape if given with dense argument…

  • #9924: BLD: add back pyproject.toml

  • #9931: Fix empty constraint

  • #9935: DOC: fix references for stats.f_oneway

  • #9936: Revert gh-9619: “FIX: Sparse matrix addition/subtraction eliminates…

  • #9937: MAINT: fix PEP8 issues and update to pycodestyle 2.5.0

  • #9939: DOC: correct `structure` description in `ndimage.label` docstring

  • #9940: MAINT: remove extraneous distutils copies

  • #9945: ENH: differential_evolution can use Bounds object

  • #9949: Added ‘std’ to add doctstrings since it is a `known_stats`…

  • #9953: DOC: Documentation cleanup for stats tutorials.

  • #9962: __repr__ for Bounds

  • #9971: ENH: Improve performance of lsmr

  • #9987: CI: pin Sphinx version to 1.8.5

  • #9990: ENH: constraint violation

  • #9991: BUG: Avoid inplace modification of input array in newton

  • #9995: MAINT: sparse.csgraph: Add cdef to stop build warning.

  • #9996: BUG: Make minimize_quadratic_1d work with infinite bounds correctly

  • #10004: BUG: Fix unbound local error in linprog - simplex.

  • #10007: BLD: fix Python 3.7 build with build isolation

  • #10009: BUG: Make sure that _binary_erosion only accepts an integer number…

  • #10016: Update link to airspeed-velocity

  • #10017: DOC: Update `interpolate.LSQSphereBivariateSpline` to include…

  • #10018: MAINT: special: Fix a few warnings that occur when compiling…

  • #10019: TST: Azure summarizes test failures

  • #10021: ENH: Introduce CubicHermiteSpline

  • #10022: BENCH: Increase cython version in asv to fix benchmark builds

  • #10023: BUG: Avoid exponnorm producing nan for small K values.

  • #10025: BUG: optimize: tweaked linprog status 4 error message

  • #10026: ENH: optimize: use SuiteSparse in linprog interior-point when…

  • #10027: MAINT: cluster: clean up the use of malloc() in the function…

  • #10028: Fix rotate invalid plane check

  • #10040: MAINT: fix pratt method of wilcox test in scipy.stats

  • #10041: MAINT: special: Fix a warning generated when building the AMOS…

  • #10044: DOC: fix up spatial.transform.Rotation docstrings

  • #10047: MAINT: interpolate: Fix a few build warnings.

  • #10051: Add project_urls to setup

  • #10052: don’t set flag to “converged” if max iter exceeded

  • #10054: MAINT: signal: Fix a few build warnings and modernize some C…

  • #10056: BUG: Ensure factorial is not too large in kendaltau

  • #10058: Small speedup in samping from ortho and special_ortho groups

  • #10059: BUG: optimize: fix #10038 by increasing tol

  • #10061: BLD: DOC: make building docs easier by parsing python version.

  • #10064: ENH: Significant speedup for ortho and special ortho group

  • #10065: DOC: Reword parameter descriptions in `optimize.root_scalar`

  • #10066: BUG: signal: Fix error raised by savgol_coeffs when deriv > polyorder.

  • #10067: MAINT: Fix the cutoff value inconsistency for pinv2 and pinvh

  • #10072: BUG: stats: Fix boxcox_llf to avoid loss of precision.

  • #10075: ENH: Add wrappers for ?syconv routines

  • #10076: BUG: optimize: fix curve_fit for mixed float32/float64 input

  • #10077: DOC: Replace undefined `k` in `interpolate.splev` docstring

  • #10079: DOC: Fixed typo, rearranged some doc of stats.morestats.wilcoxon.

  • #10080: TST: install scikit-sparse for full TravisCI tests

  • #10083: Clean ``_clean_inputs`` in optimize.linprog

  • #10088: ENH: optimize: linprog test CHOLMOD/UMFPACK solvers when available

  • #10090: MAINT: Fix CubicSplinerInterpolator for pandas

  • #10091: MAINT: improve logcdf and logsf of hypergeometric distribution

  • #10095: MAINT: Clean ``_clean_inputs`` in linprog

  • #10116: MAINT: update scipy-sphinx-theme

  • #10135: BUG: fix linprog revised simplex docstring problem failure