SciPy v1.3.1 Release Notes
Release Date: 20190809 // 13 days ago
π SciPy
1.3.1
is a bugfix release with no new features compared to1.3.0
.Authors
 Matt Haberland
 Geordie McBain
 Yu Feng
 Evgeni Burovski
 Sturla Molden
 Tapasweni Pathak
 Eric Larson
 Peter Bell
 Carlos Ramos CarreΓ±o +
 Ralf Gommers
 David Hagen
 Antony Lee
 Ayappan P
 Tyler Reddy
 Pauli Virtanen
π A total of 15 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.
Previous changes from v1.3.0

π SciPy 1.3.0 Release Notes
SciPy 1.3.0 is the culmination of 5 months of hard work. It contains
β many new features, numerous bugfixes, improved test coverage and better
π documentation. There have been some API changes
π in this release, which are documented below. All users are encouraged to
π upgrade to this release, as there are a large number of bugfixes and
β¬οΈ optimizations. Before upgrading, we recommend that users check that
π their own code does not use deprecated SciPy functionality (to do so,
π run your code withpython Wd
and check forDeprecationWarning
s).
π Our development attention will now shift to bugfix releases on the
1.3.x branch, and on adding new features on the master branch.π 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.
π Highlights of this release
 Three new
stats
functions, a rewrite ofpearsonr
, and an exact
β computation of the KolmogorovSmirnov twosample test  β‘οΈ A new Cython API for bounded scalarfunction rootfinders in
scipy.optimize
 π Substantial
CSR
andCSC
sparse matrix indexing performance
π improvements  β Added support for interpolation of rotations with continuous angular
rate and acceleration inRotationSpline
π New features
scipy.interpolate
improvementsA new class
CubicHermiteSpline
is introduced. It is a piecewisecubic
interpolator which matches observed values and first derivatives. Existing
cubic interpolatorsCubicSpline
,PchipInterpolator
and
Akima1DInterpolator
were made subclasses ofCubicHermiteSpline
.scipy.io
improvementsFor the AttributeRelation File Format (ARFF)
scipy.io.arff.loadarff
π now supports relational attributes.π
scipy.io.mmread
can now parse Matrix Market format files with empty lines.scipy.linalg
improvementsβ 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 6090 percent speedup for dense input matrices.
π Truly sparse input matrices should also benefit from the improved sketch
algorithm, which now correctly runs inO(nnz(A))
time.β Added new functions to calculate symmetric Fiedler matrices and
Fiedler companion matrices, namedscipy.linalg.fiedler
and
scipy.linalg.fiedler_companion
, respectively. These may be used
for root finding.scipy.ndimage
improvementsπ Gaussian filter performances may improve by an order of magnitude in
some cases, thanks to removal of a dependence onnp.polynomial
. This
may impactscipy.ndimage.gaussian_filter
for example.β‘οΈ
scipy.optimize
improvementsβ‘οΈ The
scipy.optimize.brute
minimizer obtained a new keywordworkers
, which
can be used to parallelize computation.β‘οΈ A Cython API for bounded scalarfunction rootfinders in
scipy.optimize
β‘οΈ is available in a new modulescipy.optimize.cython_optimize
viacimport
.
This API may be used withnogil
andprange
to loop
over an array of function arguments to solve for an array of roots more
quickly than with pure Python.0οΈβ£
'interiorpoint'
is now the default method forlinprog
, and
π'interiorpoint'
now uses SuiteSparse for sparse problems when the
π required scikits (scikitumfpack and scikitsparse) are available.
On benchmark problems (gh10026), execution time reductions by factors of 23
were typical. Also, a newmethod='revised simplex'
has been added.
It is not as fast or robust asmethod='interiorpoint'
, but it is a faster,
more robust, and equally accurate substitute for the legacy
method='simplex'
.differential_evolution
can now use aBounds
class to specify the
β‘οΈ bounds for the optimizing argument of a function.π
scipy.optimize.dual_annealing
performance improvements related to
vectorisation of some internal code.π¦
scipy.signal
improvementsπ Two additional methods of discretization are now supported by
π¦scipy.signal.cont2discrete
:impulse
andfoh
.π¦
scipy.signal.firls
now uses faster solversπ¦
scipy.signal.detrend
now has a lower physical memory footprint in some
cases, which may be leveraged using the newoverwrite_data
keyword argumentπ¦
scipy.signal.firwin
pass_zero
argument now accepts new string arguments
that allow specification of the desired filter type:'bandpass'
,
'lowpass'
,'highpass'
, and'bandstop'
π
scipy.signal.sosfilt
may have improved performance due to lower retention
π of the global interpreter lock (GIL) in algorithmπ
scipy.sparse
improvementsA new keyword was added to
csgraph.dijsktra
that
π allows users to query the shortest path to ANY of the passed in indices,
β as opposed to the shortest path to EVERY passed index.π
scipy.sparse.linalg.lsmr
performance has been improved by roughly 10 percent
on large problemsπ Improved performance and reduced physical memory footprint of the algorithm
π used byscipy.sparse.linalg.lobpcg
π
CSR
andCSC
sparse matrix fancy indexing performance has been
π improved substantiallyscipy.spatial
improvementsscipy.spatial.ConvexHull
now has agood
attribute that can be used
alongsize theQGn
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
π Cython features, including GIL handling and exception translation. An issue
π withreturn_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 accelerationscipy.stats
improvementsβ Added a new function to compute the EppsSingleton test statistic,
scipy.stats.epps_singleton_2samp
, which can be applied to continuous and
discrete distributions.New functions
scipy.stats.median_absolute_deviation
andscipy.stats.gstd
(geometric standard deviation) were added. Thescipy.stats.combine_pvalues
π method now supportspearson
,tippett
andmudholkar_george
pvalue
combination methods.The
scipy.stats.ortho_group
andscipy.stats.special_ortho_group
β‘οΈrvs(dim)
functions' algorithms were updated from aO(dim^4)
implementation to aO(dim^3)
which gives large speed improvements
fordim>100
.A rewrite of
scipy.stats.pearsonr
to use a more robust algorithm,
β provide meaningful exceptions and warnings on potentially pathological input,
and fix at least five separate reported issues in the original implementation.π Improved the precision of
hypergeom.logcdf
andhypergeom.logsf
.β Added exact computation for KolmogorovSmirnov (KS) twosample test, replacing
β the previously approximate computation for the twosided teststats.ks_2samp
.
β Also added a onesided, twosample KS test, and a keywordalternative
to
stats.ks_2samp
.Backwards incompatible changes
scipy.interpolate
changesFunctions from
scipy.interpolate
(spleval
,spline
,splmake
,
andspltopp
) and functions fromscipy.misc
(bytescale
,
fromimage
,imfilter
,imread
,imresize
,imrotate
,
πimsave
,imshow
,toimage
) have been removed. The former set has
π been deprecated since v0.19.0 and the latter has been deprecated since v1.0.0.
Similarly, aliases fromscipy.misc
(comb
,factorial
,
πfactorial2
,factorialk
,logsumexp
,pade
,info
,source
,
πwho
) which have been deprecated since v1.0.0 are removed.
SciPy documentation for v1.1.0 <https://docs.scipy.org/doc/scipy1.1.0/reference/misc.html>
__
can be used to track the new import locations for the relocated functions.scipy.linalg
changes0οΈβ£ For
pinv
,pinv2
, andpinvh
, the default cutoff values are changed
π for consistency (see the docs for the actual values).β‘οΈ
scipy.optimize
changes0οΈβ£ The default method for
linprog
is now'interiorpoint'
. 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
βͺ by the constraints. To revert to the original simplex method,
include the argumentmethod='simplex'
.scipy.stats
changesβ Previously,
ks_2samp(data1, data2)
would run a twosided test and return
β the approximated pvalue. The new signature,ks_2samp(data1, data2, alternative="twosided", method="auto")
, still runs the twosided test by
0οΈβ£ default but returns the exact pvalue for small samples and the approximated
value for large samples.method="asymp"
would be equivalent to the
π old version butauto
is the better choice.Other changes
β‘οΈ Our tutorial has been expanded with a new section on global optimizers
There has been a rework of the
stats.distributions
tutorials.β‘οΈ
scipy.optimize
now correctly sets the convergence flag of the result to
CONVERR
, a convergence error, for bounded scalarfunction rootfinders
if the maximum iterations has been exceeded,disp
is false, and
full_output
is true.β‘οΈ
scipy.optimize.curve_fit
no longer fails ifxdata
andydata
dtypes
differ; they are both now automatically cast tofloat64
.scipy.ndimage
functions includingbinary_erosion
,binary_closing
, and
binary_dilation
now require an integer value for the number of iterations,
which alleviates a number of reported issues.π Fixed normal approximation in case
zero_method == "pratt"
in
scipy.stats.wilcoxon
.π Fixes for incorrect probabilities, broadcasting issues and threadsafety
related to stats distributions setting member variables inside_argcheck()
.β‘οΈ
scipy.optimize.newton
now correctly raises aRuntimeError
, when default
arguments are used, in the case that 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.Authors
 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 WerthmΓΌller
 Conner DiPaolo +
 Dowon
 Michael Dunphy +
 Peter Andreas Entschev +
 GΓΆkΓ§en 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 MlinariΔ +
 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
π 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.  Three new