Changelog History
Page 1

v1.6.0.rc1 Changes
December 11, 2020π SciPy 1.6.0 Release Notes
Note : Scipy
1.6.0
is not released yet!SciPy
1.6.0
is the culmination of 6 months of hard work. It contains
β many new features, numerous bugfixes, improved test coverage and better
π documentation. There have been a number of deprecations and 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
1.6.x branch, and on adding new features on the master branch.π This release requires Python
3.7
+ and NumPy1.16.5
or greater.For running on PyPy, PyPy3
6.0
+ is required.π Highlights of this release
 π
scipy.ndimage
improvements: Fixes and ehancements to boundary extension
π modes for interpolation functions. Support for complexvalued inputs in many
filtering and interpolation functions. Newgrid_mode
option for
scipy.ndimage.zoom
to enable results consistent with scikitimage's
rescale
.  β‘οΈ
scipy.optimize.linprog
has fast, new methods for large, sparse problems
from theHiGHS
library.  β
scipy.stats
improvements including new distributions, a new test, and
β¨ enhancements to existing distributions and tests
π New features
scipy.special
improvementsπ
scipy.special
now has improved support for 64bitLAPACK
backendscipy.odr
improvementsπ
scipy.odr
now has support for 64bit integerBLAS
scipy.odr.ODR
has gained an optionaloverwrite
argument so that existing
files may be overwritten.scipy.integrate
improvementsSome renames of functions with poor names were done, with the old names
retained without being in the reference guide for backwards compatibility
reasons:integrate.simps
was renamed tointegrate.simpson
integrate.trapz
was renamed tointegrate.trapezoid
integrate.cumtrapz
was renamed tointegrate.cumulative_trapezoid
scipy.cluster
improvementsscipy.cluster.hierarchy.DisjointSet
has been added for incremental
connectivity queries.scipy.cluster.hierarchy.dendrogram
return value now also includes leaf color
information inleaves_color_list
.scipy.interpolate
improvementsscipy.interpolate.interp1d
has a new methodnearestup
, similar to the
existing methodnearest
but rounds halfintegers up instead of down.scipy.io
improvementsπ Support has been added for reading arbitrary bit depth integer PCM WAV files
from 1 to 32bit, including the commonlyrequested 24bit depth.scipy.linalg
improvementsThe new function
scipy.linalg.matmul_toeplitz
uses the FFT to compute the
product of a Toeplitz matrix with another matrix.π
scipy.linalg.sqrtm
andscipy.linalg.logm
have performance improvements
thanks to additional Cython code.Python
LAPACK
wrappers have been added forpptrf
,pptrs
,ppsv
,
pptri
, andppcon
.scipy.linalg.norm
and thesvd
family of functions will now use 64bit
integer backends when available.scipy.ndimage
improvementsscipy.ndimage.convolve
,scipy.ndimage.correlate
and their 1d counterparts
now accept both complexvalued images and/or complexvalued filter kernels. All
convolutionbased filters also now accept complexvalued inputs
(e.g.gaussian_filter
,uniform_filter
, etc.).π Multiple fixes and enhancements to boundary handling were introduced to
scipy.ndimage
interpolation functions (i.e.affine_transform
,
geometric_transform
,map_coordinates
,rotate
,shift
,zoom
).A new boundary mode,
gridwrap
was added which wraps images periodically,
using a period equal to the shape of the input image grid. This is in contrast
to the existingwrap
mode which uses a period that is one sample smaller
π¦ than the original signal extent along each dimension.π A longstanding bug in the
reflect
boundary condition has been fixed and
the modegridmirror
was introduced as a synonym forreflect
.A new boundary mode,
gridconstant
is now available. This is similar to
the existing ndimageconstant
mode, but interpolation will still performed
at coordinate values outside of the original image extent. This
gridconstant
mode is consistent with OpenCV'sBORDER_CONSTANT
mode
and scikitimage'sconstant
mode.Spline prefiltering (used internally by
ndimage
interpolation functions
π whenorder >= 2
), now supports all boundary modes rather than always
0οΈβ£ defaulting to mirror boundary conditions. The standalone functions
spline_filter
andspline_filter1d
have analytical boundary conditions
that match modesmirror
,gridwrap
andreflect
.scipy.ndimage
interpolation functions now accept complexvalued inputs. In
this case, the interpolation is applied independently to the real and
imaginary components.The
ndimage
tutorials
π (https://docs.scipy.org/doc/scipy/reference/tutorial/ndimage.html) have been
β‘οΈ updated with new figures to better clarify the exact behavior of all of the
interpolation boundary modes.scipy.ndimage.zoom
now has agrid_mode
option that changes the coordinate
of the center of the first pixel along an axis from 0 to 0.5. This allows
resizing in a manner that is consistent with the behavior of scikitimage's
resize
andrescale
functions (and OpenCV'scv2.resize
).β‘οΈ
scipy.optimize
improvementsβ‘οΈ
scipy.optimize.linprog
has fast, new methods for large, sparse problems from
π theHiGHS
C++ library.method='highsds'
uses a high performance dual
revised simplex implementation (HSOL),method='highsipm'
uses an
interiorpoint method with crossover, andmethod='highs'
chooses between
the two automatically. These methods are typically much faster and often exceed
the accuracy of otherlinprog
methods, so we recommend explicitly
specifying one of these three method values when usinglinprog
.β‘οΈ
scipy.optimize.quadratic_assignment
has been added for approximate solution
of the quadratic assignment problem.scipy.optimize.linear_sum_assignment
now has a substantially reduced overhead
for small cost matrix sizesπ
scipy.optimize.least_squares
has improved performance when the user provides
π the jacobian as a sparse jacobian already incsr_matrix
formatβ‘οΈ
scipy.optimize.linprog
now has anrr_method
argument for specification
of the method used for redundancy handling, and a new method for this purpose
is available based on the interpolative decomposition approach.π¦
scipy.signal
improvementsπ¦
scipy.signal.gammatone
has been added to design FIR or IIR filters that
model the human auditory system.π¦
scipy.signal.iircomb
has been added to design IIR peaking/notching comb
π¦ filters that can boost/attenuate a frequency from a signal.π
scipy.signal.sosfilt
performance has been improved to avoid some previously
observed slowdownsπ
scipy.signal.windows.taylor
has been addedthe Taylor window function is
π¦ commonly used in radar digital signal processingπ¦
scipy.signal.gauss_spline
now supportslist
type input for consistency
with other related SciPy functionsπ¦
scipy.signal.correlation_lags
has been added to allow calculation of the lag/
displacement indices array for 1D crosscorrelation.π
scipy.sparse
improvementsA solver for the minimum weight full matching problem for bipartite graphs,
also known as the linear assignment problem, has been added in
scipy.sparse.csgraph.min_weight_full_bipartite_matching
. In particular, this
provides functionality analogous to that of
scipy.optimize.linear_sum_assignment
, but with improved performance for sparse
inputs, and the ability to handle inputs whose dense representations would not
fit in memory.π The time complexity of
scipy.sparse.block_diag
has been improved dramatically
from quadratic to linear.π
scipy.sparse.linalg
improvementsβ‘οΈ The vendored version of
SuperLU
has been updatedscipy.fft
improvementsπ The vendored
pocketfft
library now supports compiling with ARM neon vector
extensions and has improved thread pool behavior.scipy.spatial
improvementsThe python implementation of
KDTree
has been dropped andKDTree
is now
implemented in terms ofcKDTree
. You can now expectcKDTree
like
π performance by default. This also meanssys.setrecursionlimit
no longer
needs to be increased for querying large trees.β‘οΈ
transform.Rotation
has been updated with support for Modified Rodrigues
Parameters alongside the existing rotation representations (PR gh12667).scipy.spatial.transform.Rotation
has been partially cythonized, with some
π performance improvements observedπ
scipy.spatial.distance.cdist
has improved performance with theminkowski
metric, especially for pnorm values of 1 or 2.scipy.stats
improvementsπ New distributions have been added to
scipy.stats
: The asymmetric Laplace continuous distribution has been added as
scipy.stats.laplace_asymmetric
.  The negative hypergeometric distribution has been added as
scipy.stats.nhypergeom
.  The multivariate t distribution has been added as
scipy.stats.multivariate_t
.  The multivariate hypergeometric distribution has been added as
scipy.stats.multivariate_hypergeom
.
The
fit
method has been overridden for several distributions (laplace
,
pareto
,rayleigh
,invgauss
,logistic
,gumbel_l
,
gumbel_r
); they now use analytical, distributionspecific maximum
likelihood estimation results for greater speed and accuracy than the generic
(numerical optimization) implementation.β The onesample CramΓ©rvon Mises test has been added as
scipy.stats.cramervonmises
.β An option to compute onesided pvalues was added to
scipy.stats.ttest_1samp
,
scipy.stats.ttest_ind_from_stats
,scipy.stats.ttest_ind
and
βscipy.stats.ttest_rel
.The function
scipy.stats.kendalltau
now has an option to compute Kendall's
π tauc (also known as Stuart's tauc), and support has been added for exact
pvalue calculations for sample sizes> 171
.stats.trapz
was renamed tostats.trapezoid
, with the former name retained
as an alias for backwards compatibility reasons.The function
scipy.stats.linregress
now includes the standard error of the
intercept in its return value.The
_logpdf
,_sf
, and_isf
methods have been added to
scipy.stats.nakagami
;_sf
and_isf
methods also added to
scipy.stats.gumbel_r
The
sf
method has been added toscipy.stats.levy
andscipy.stats.levy_l
for improved precision.scipy.stats.binned_statistic_dd
performance improvements for the following
computed statistics:max
,min
,median
, andstd
.We gratefully acknowledge the ChanZuckerberg Initiative Essential Open Source
π Software for Science program for supporting many of these improvements to
scipy.stats
.π Deprecated features
scipy.spatial
changesπ Calling
KDTree.query
withk=None
to find all neighbours is deprecated.
UseKDTree.query_ball_point
instead.π
distance.wminkowski
was deprecated; usedistance.minkowski
and supply
weights with thew
keyword instead.Backwards incompatible changes
scipy
changesπ Using
scipy.fft
as a function aliasingnumpy.fft.fft
was removed after
π being deprecated in SciPy1.4.0
. As a result, thescipy.fft
submodule
π¦ must be explicitly imported now, in line with other SciPy subpackages.π¦
scipy.signal
changesThe output of
decimate
,lfilter_zi
,lfiltic
,sos2tf
, and
sosfilt_zi
have been changed to matchnumpy.result_type
of their inputs.π The window function
slepian
was removed. It had been deprecated since SciPy
1.1
.scipy.spatial
changesπ
cKDTree.query
now returns 64bit rather than 32bit integers on Windows,
making behaviour consistent between platforms (PR gh12673).scipy.stats
changesThe
frechet_l
andfrechet_r
distributions were removed. They were
π deprecated since SciPy1.0
.Other changes
π
setup_requires
was removed fromsetup.py
. This means that users
invokingpython setup.py install
without having numpy already installed
will now get an error, rather than having numpy installed for them via
easy_install
. This install method was always fragile and problematic, users
are encouraged to usepip
when installing from source. Fixed a bug in
scipy.optimize.dual_annealing
accept_reject
calculation
that caused uphill jumps to be accepted less frequently.  The time required for (un)pickling of
scipy.stats.rv_continuous
,
scipy.stats.rv_discrete
, andscipy.stats.rv_frozen
has been significantly
reduced (gh12550). Inheriting subclasses should note that__setstate__
no
longer calls__init__
upon unpickling.
Authors
 @endolith
 @vkk800
 aditya +
 George Bateman +
 Christoph Baumgarten
 Peter Bell
 Tobias Biester +
 Keaton J. Burns +
 Evgeni Burovski
 RΓΌdiger Busche +
 Matthias Bussonnier
 Dominic C +
 Corallus Caninus +
 CJ Carey
 Thomas A Caswell
 chapochn +
 LucΓa Cheung
 Zach Colbert +
 Coloquinte +
 Yannick Copin +
 Devin Crowley +
 Terry Davis +
 MichaΓ«l Defferrard +
 devonwp +
 Didier +
 divenex +
 Thomas Duvernay +
 Eoghan O'Connell +
 GΓΆkΓ§en Eraslan
 Kristian Eschenburg +
 Ralf Gommers
 Thomas Grainger +
 GreatV +
 Gregory Gundersen +
 hvetinari +
 Matt Haberland
 Mark Harfouche +
 He He +
 Alex Henrie
 ChunMing Huang +
 Martin James McHugh III +
 Alex Izvorski +
 Joey +
 ST John +
 Jonas Jonker +
 Julius Bier Kirkegaard
 Marcin Konowalczyk +
 Konrad0
 Sam Van Kooten +
 Sergey Koposov +
 Peter Mahler Larsen
 Eric Larson
 Antony Lee
 Gregory R. Lee
 LoΓ―c EstΓ¨ve
 JeanLuc Margot +
 MarkusKoebis +
 Nikolay Mayorov
 G. D. McBain
 Andrew McCluskey +
 Nicholas McKibben
 Sturla Molden
 Denali Molitor +
 Eric Moore
 Shashaank N +
 Prashanth Nadukandi +
 nbelakovski +
 Andrew Nelson
 Nick +
 Nikola ForrΓ³ +
 odidev
 ofirr +
 Sambit Panda
 Dima Pasechnik
 Tirth Patel +
 PaweΕ RedzyΕski +
 Vladimir Philipenko +
 Philipp ThΓΆlke +
 Ilhan Polat
 Eugene Prilepin +
 Vladyslav Rachek
 Ram Rachum +
 Tyler Reddy
 Martin Reinecke +
 Simon Segerblom Rex +
 Lucas Roberts
 Benjamin Rowell +
 Eli Rykoff +
 Atsushi Sakai
 Moritz Schulte +
 Daniel B. Smith
 Steve Smith +
 Jan Soedingrekso +
 Victor Stinner +
 Jose Storopoli +
 Diana Sukhoverkhova +
 SΓΈren Fuglede JΓΈrgensen
 taoky +
 Mike Taves +
 Ian Thomas +
 Will Tirone +
 Frank Torres +
 Seth Troisi
 Ronald van Elburg +
 Hugo van Kemenade
 Paul van Mulbregt
 Saul Ivan Rivas Vega +
 Pauli Virtanen
 Jan Vleeshouwers
 Samuel Wallan
 Warren Weckesser
 Ben West +
 Eric Wieser
 WillTirone +
 Levi John Wolf +
 Zhiqing Xiao
 Rory Yorke +
 Yun Wang (Maigo) +
 Egor Zemlyanoy +
 ZhihuiChen0903 +
 Jacob Zhong +
π 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.  π

v1.5.4 Changes
November 05, 2020π SciPy 1.5.4 Release Notes
π SciPy
1.5.4
is a bugfix release with no new features
compared to1.5.3
. Importantly, wheels are now available
for Python3.9
and a more complete fix has been applied for
π issues building with XCode12
.Authors
 Peter Bell
 CJ Carey
 Andrew McCluskey +
 Andrew Nelson
 Tyler Reddy
 Eli Rykoff +
 Ian Thomas +
π A total of 7 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. 
v1.5.3 Changes
October 17, 2020π SciPy 1.5.3 Release Notes
π SciPy
1.5.3
is a bugfix release with no new features
π§ compared to1.5.2
. In particular, Linux ARM64 wheels are now
available and a compatibility issue with XCode 12 has
π been fixed.Authors
 Peter Bell
 CJ Carey
 Thomas Duvernay +
 Gregory Lee
 Eric Moore
 odidev
 Dima Pasechnik
 Tyler Reddy
 Simon Segerblom Rex +
 Daniel B. Smith
 Will Tirone +
 Warren Weckesser
π A total of 12 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. 
v1.5.2 Changes
July 24, 2020π SciPy 1.5.2 Release Notes
π SciPy
1.5.2
is a bugfix release with no new features
compared to1.5.1
.Authors
 Peter Bell
 Tobias Biester +
 Evgeni Burovski
 Thomas A Caswell
 Ralf Gommers
 Sturla Molden
 Andrew Nelson
 ofirr +
 Sambit Panda
 Ilhan Polat
 Tyler Reddy
 Atsushi Sakai
 Pauli Virtanen
π A total of 13 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. 
v1.5.1 Changes
July 04, 2020π SciPy 1.5.1 Release Notes
π SciPy
1.5.1
is a bugfix release with no new features
compared to1.5.0
. In particular, an issue where DLL loading
π can fail for SciPy wheels on Windows with Python3.6
has been
π fixed.Authors
 Peter Bell
 LoΓ―c EstΓ¨ve
 Philipp ThΓΆlke +
 Tyler Reddy
 Paul van Mulbregt
 Pauli Virtanen
 Warren Weckesser
π A total of 7 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. 
v1.5.0 Changes
June 21, 2020π SciPy 1.5.0 Release Notes
SciPy
1.5.0
is the culmination of 6 months of hard work. It contains
β many new features, numerous bugfixes, improved test coverage and better
π documentation. There have been a number of deprecations and 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
1.5.x branch, and on adding new features on the master branch.π This release requires Python
3.6+
and NumPy1.14.5
or greater.For running on PyPy, PyPy3
6.0+
and NumPy1.15.0
are required.π Highlights of this release
 wrappers for more than a dozen new
LAPACK
routines are now available
inscipy.linalg.lapack
 π Improved support for leveraging 64bit integer size from linear algebra
backends  β addition of the probability distribution for twosided onesample
β KolmogorovSmirnov tests
π New features
scipy.cluster
improvementsπ Initialization of
scipy.cluster.vq.kmeans2
usingminit="++"
had a
quadratic complexity in the number of samples. It has been improved, resulting
in a much faster initialization with quasilinear complexity.scipy.cluster.hierarchy.dendrogram
now respects thematplotlib
color
palettescipy.fft
improvementsA new keywordonly argument
plan
is added to all FFT functions in this
module. It is reserved for passing in a precomputed plan from libraries
providing a FFT backend (such asPyFFTW
andmklfft
), and it is
currently not used in SciPy.scipy.integrate
improvementsscipy.interpolate
improvementsscipy.io
improvementsscipy.io.wavfile
error messages are more explicit about what's wrong, and
extraneous bytes at the ends of files are ignored instead of raising an error
when the data has successfully been read.scipy.io.loadmat
gained asimplify_cells
parameter, which if set to
True
simplifies the structure of the return value if the.mat
file
contains cell arrays.π
pathlib.Path
objects are now supported inscipy.io
Matrix Market I/O
functionsscipy.linalg
improvementsscipy.linalg.eigh
has been improved. Now variousLAPACK
drivers can be
selected at will and also subsets of eigenvalues can be requested via
subset_by_value
keyword. Another keywordsubset_by_index
is introduced.
π Keywordsturbo
andeigvals
are deprecated.Similarly, standard and generalized Hermitian eigenvalue
LAPACK
routines
?<sy/he>evx
are added and existing ones now have full_lwork
counterparts.Wrappers for the following
LAPACK
routines have been added to
scipy.linalg.lapack
:?getc2
: computes the LU factorization of a general matrix with complete
pivoting?gesc2
: solves a linear system given an LU factorization from?getc2
?gejsv
: computes the singular value decomposition of a general matrix
with higher accuracy calculation of tiny singular values and their
corresponding singular vectors?geqrfp
: computes the QR factorization of a general matrix with
nonnegative elements on the diagonal of R?gtsvx
: solves a linear system with general tridiagonal matrix?gttrf
: computes the LU factorization of a tridiagonal matrix?gttrs
: solves a linear system given an LU factorization from?gttrf
?ptsvx
: solves a linear system with symmetric positive definite
tridiagonal matrix?pttrf
: computes the LU factorization of a symmetric positive definite
tridiagonal matrix?pttrs
: solves a linear system given an LU factorization from?pttrf
?pteqr
: computes the eigenvectors and eigenvalues of a positive definite
tridiagonal matrix?tbtrs
: solves a linear system with a triangular banded matrix?csd
: computes the Cosine Sine decomposition of an orthogonal/unitary
matrix
Generalized QR factorization routines (
?geqrf
) now have full_lwork
counterparts.scipy.linalg.cossin
Cosine Sine decomposition of unitary matrices has been
β added.The function
scipy.linalg.khatri_rao
, which computes the KhatriRao product,
was added.The new function
scipy.linalg.convolution_matrix
constructs the Toeplitz
matrix representing onedimensional convolution.scipy.ndimage
improvementsβ‘οΈ
scipy.optimize
improvementsThe finite difference numerical differentiation used in various
minimize
methods that use gradients has several new features: 2point, 3point, or complex step finite differences can be used. Previously
only a 2step finite difference was available.  There is now the possibility to use a relative step size, previously only an
absolute step size was available.  If the
minimize
method uses bounds the numerical differentiation strictly
obeys those limits.  The numerical differentiation machinery now makes use of a simple cache,
which in some cases can reduce the number of function evaluations.  π
minimize
'smethod= 'powell'
now supports simple bound constraints
β‘οΈ There have been several improvements to
scipy.optimize.linprog
: The
linprog
benchmark suite has been expanded considerably.  π
linprog
's dense pivotbased redundancy removal routine and sparse
presolve are faster  π When
scikitsparse
is available, solving sparse problems with
method='interiorpoint'
is faster
β‘οΈ The caching of values when optimizing a function returning both value and
gradient together has been improved, avoiding repeated function evaluations
when using aHessianApproximation
such asBFGS
.differential_evolution
can now use the modernnp.random.Generator
as
π well as the legacynp.random.RandomState
as a seed.π¦
scipy.signal
improvementsA new optional argument
include_nyquist
is added tofreqz
functions in
this module. It is used for including the last frequency (Nyquist frequency).scipy.signal.find_peaks_cwt
now accepts awindow_size
parameter for the
size of the window used to calculate the noise floor.π
scipy.sparse
improvementsOuter indexing is now faster when using a 2d column vector to select column
indices.π
scipy.sparse.lil.tocsr
is fasterπ Fixed/improved comparisons between pydata sparse arrays and sparse matrices
π BSR format sparse multiplication performance has been improved.
π
scipy.sparse.linalg.LinearOperator
has gained the newndim
class
attributescipy.spatial
improvementsscipy.spatial.geometric_slerp
has been added to enable geometric
spherical linear interpolation on an nsphereπ
scipy.spatial.SphericalVoronoi
now supports calculation of region areas in 2D
and 3D casesπ The tree building algorithm used by
cKDTree
has improved from quadratic
worst case time complexity to loglinear. Benchmarks are also now available for
π building and querying of balanced/unbalanced kdtrees.scipy.special
improvementsThe following functions now have Cython interfaces in
cython_special
:scipy.special.erfinv
scipy.special.erfcinv
scipy.special.spherical_jn
scipy.special.spherical_yn
scipy.special.spherical_in
scipy.special.spherical_kn
scipy.special.log_softmax
has been added to calculate the logarithm of softmax
π² function. It provides better accuracy thanlog(scipy.special.softmax(x))
for
inputs that make softmax saturate.scipy.stats
improvementsThe function for generating random samples in
scipy.stats.dlaplace
has been
π improved. The new function is approximately twice as fast with a memory
π footprint reduction between 25 % and 60 % (see gh11069).π
scipy.stats
functions that accept a seed for reproducible calculations using
random number generation (e.g. random variates from distributions) can now use
the modernnp.random.Generator
as well as the legacy
πnp.random.RandomState
as a seed.The
axis
parameter was added toscipy.stats.rankdata
. This allows slices
of an array along the given axis to be ranked independently.The
axis
parameter was added toscipy.stats.f_oneway
, allowing it to
β compute multiple oneway ANOVA tests for data stored in ndimensional
π arrays. The performance off_oneway
was also improved for some cases.The PDF and CDF methods for
stats.geninvgauss
are now significantly faster
as the numerical integration to calculate the CDF uses a Cython based
LowLevelCallable
.Moments of the normal distribution (
scipy.stats.norm
) are now calculated using
analytical formulas instead of numerical integration for greater speed and
accuracyMoments and entropy trapezoidal distribution (
scipy.stats.trapz
) are now
calculated using analytical formulas instead of numerical integration for
greater speed and accuracyMethods of the truncated normal distribution (
scipy.stats.truncnorm
),
especially_rvs
, are significantly faster after a complete rewrite.The
fit
method of the Laplace distribution,scipy.stats.laplace
, now uses
the analytical formulas for the maximum likelihood estimates of the parameters.Generation of random variates is now thread safe for all SciPy distributions.
3rdparty distributions may need to modify the signature of the_rvs()
method to conform to_rvs(self, ..., size=None, random_state=None)
. (A
π onetime VisibleDeprecationWarning is emitted when using nonconformant
distributions.)β The KolmogorovSmirnov twosided test statistic distribution
(scipy.stats.kstwo
) was added. Calculates the distribution of the KS
twosided statisticD_n
for a sample of size n, using a mixture of exact
and asymptotic algorithms.The new function
median_abs_deviation
replaces the deprecated
median_absolute_deviation
.The
wilcoxon
function now computes the pvalue for Wilcoxon's signed rank
β test using the exact distribution for inputs up to length 25. The function has
a newmode
parameter to specify how the pvalue is to be computed. The
0οΈβ£ default is"auto"
, which uses the exact distribution for inputs up to length
25 and the normal approximation for larger inputs.β Added a new Cythonbased implementation to evaluate guassian kernel estimates,
π which should improve the performance ofgaussian_kde
The
winsorize
function now has anan_policy
argument for refined
handling ofnan
input values.The
binned_statistic_dd
function withstatistic="std"
performance was
π improved by ~4x.β
scipy.stats.kstest(rvs, cdf,...)
now handles both onesample and
β twosample testing. The onesample variation usesscipy.stats.ksone
(orscipy.stats.kstwo
with back off toscipy.stats.kstwobign
) to calculate
the pvalue. The twosample variation, invoked ifcdf
is array_like, uses
an algorithm described by Hodges to compute the probability directly, only
backing off toscipy.stats.kstwo
in case of overflow. The result in both
β cases is more accurate pvalues, especially for twosample testing with
smaller (or quite different) sizes.π
scipy.stats.maxwell
performance improvements include a 20 % speed up for
fit()
and 5 % forpdf()
`scipy.stats.shapiro
andscipy.stats.jarque_bera
now return a named tuple
for greater consistency with otherstats
functionsπ Deprecated features
π
scipy
deprecationsscipy.special
changesπ The
bdtr
,bdtrc
, andbdtri
functions are deprecating nonnegative
nonintegraln
arguments.scipy.stats
changesThe function
median_absolute_deviation
is deprecated. Use
median_abs_deviation
instead.The use of the string
"raw"
with thescale
parameter ofiqr
is
π deprecated. Usescale=1
instead.Backwards incompatible changes
scipy.interpolate
changesscipy.linalg
changesThe output signatures of
?syevr
,?heevr
have been changed from
w, v, info
tow, v, m, isuppz, info
The order of output arguments
w
,v
of<sy/he>{gv, gvd, gvx}
is
swapped.π¦
scipy.signal
changesπ¦ The output length of
scipy.signal.upfirdn
has been corrected, resulting
outputs may now be shorter for some combinations of up/down ratios and input
π¦ signal and filter lengths.π¦
scipy.signal.resample
now supports adomain
keyword argument for
specification of time or frequency domain input.scipy.stats
changesOther changes
π Improved support for leveraging 64bit integer size from linear algebra backends
in several parts of the SciPy codebase.Shims designed to ensure the compatibility of SciPy with Python 2.7 have now
π been removed.β Many warnings due to unused imports and unused assignments have been addressed.
π Many usage examples were added to function docstrings, and many input
π» validations and intuitive exception messages have been added throughout the
codebase.Early stage adoption of type annotations in a few parts of the codebase
Authors
 @endolith
 Hameer Abbasi
 ADmitri +
 Wesley Alves +
 Berkay Antmen +
 Sylwester Arabas +
 Arne KΓΌderle +
 Christoph Baumgarten
 Peter Bell
 Felix Berkenkamp
 JordΓ£o Bragantini +
 Clemens Brunner +
 Evgeni Burovski
 Matthias Bussonnier +
 CJ Carey
 Derrick Chambers +
 Leander Claes +
 Christian Clauss
 Luigi F. Cruz +
 dankleeman
 Andras Deak
 Milad Sadeghi DM +
 jeremie du boisberranger +
 Stefan Endres
 Malte Esders +
 Leo Fang +
 felixhekhorn +
 Isuru Fernando
 Andrew Fowlie
 Lakshay Garg +
 Gaurav Gijare +
 Ralf Gommers
 Emmanuelle Gouillart +
 Kevin Green +
 Martin Grignard +
 Maja Gwozdz
 Sturla Molden
 gyudon +
 Matt Haberland
 hakeemo +
 Charles Harris
 Alex Henrie
 Santi Hernandez +
 William Hickman +
 Till Hoffmann +
 Joseph T. Iosue +
 Anany Shrey Jain
 Jakob Jakobson
 Charles Jekel +
 Julien Jerphanion +
 JiachengLiu +
 Christoph Kecht +
 Paul Kienzle +
 Reidar Kind +
 Dmitry E. Kislov +
 Konrad +
 Konrad0
 Takuya KOUMURA +
 Krzysztof PiΓ³ro
 Peter Mahler Larsen
 Eric Larson
 Antony Lee
 Gregory Lee +
 Gregory R. Lee
 Chelsea Liu
 Cong Ma +
 Kevin Mader +
 Maja GwΓ³ΕΊdΕΊ +
 Alex Marvin +
 Matthias KΓΌmmerer
 Nikolay Mayorov
 Mazay0 +
 G. D. McBain
 Nicholas McKibben +
 Sabrina J. Mielke +
 Sebastian J. Mielke +
 MiloΕ‘ KomarΔeviΔ +
 Shubham Mishra +
 Santiago M. Mola +
 Grzegorz Mrukwa +
 Peyton Murray
 Andrew Nelson
 Nico SchlΓΆmer
 nwjenkins +
 odidev +
 Sambit Panda
 Vikas Pandey +
 Rick Paris +
 Harshal Prakash Patankar +
 π Balint Pato +
 Matti Picus
 Ilhan Polat
 poom +
 Siddhesh Poyarekar
 Vladyslav Rachek +
 Bharat Raghunathan
 Manu Rajput +
 Tyler Reddy
 Andrew Reed +
 Lucas Roberts
 Ariel Rokem
 Heshy Roskes
 Matt Ruffalo
 Atsushi Sakai +
 Benjamin Santos +
 Christoph Schock +
 Lisa Schwetlick +
 Chris Simpson +
 Leo Singer
 Kai Striega
 SΓΈren Fuglede JΓΈrgensen
 Kaleab Tessera +
 Seth Troisi +
 Robert Uhl +
 Paul van Mulbregt
 Vasiliy +
 Isaac Virshup +
 Pauli Virtanen
 Shakthi Visagan +
 Jan Vleeshouwers +
 Sam Wallan +
 Lijun Wang +
 Warren Weckesser
 Richard Weiss +
 wenhuiprudencemed +
 Eric Wieser
 Josh Wilson
 James Wright +
 Ruslan Yevdokymov +
 Ziyao Zhang +
π A total of 129 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.  wrappers for more than a dozen new

v1.5.0.rc2 Changes
June 14, 2020π SciPy 1.5.0 Release Notes
Note Scipy
1.5.0
is not released yet!SciPy
1.5.0
is the culmination of 6 months of hard work. It contains
β many new features, numerous bugfixes, improved test coverage and better
π documentation. There have been a number of deprecations and 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
1.5.x branch, and on adding new features on the master branch.π This release requires Python
3.6+
and NumPy1.14.5
or greater.For running on PyPy, PyPy3
6.0+
and NumPy1.15.0
are required.π Highlights of this release
 wrappers for more than a dozen new
LAPACK
routines are now available
inscipy.linalg.lapack
 π Improved support for leveraging 64bit integer size from linear algebra
backends  β addition of the probability distribution for twosided onesample
β KolmogorovSmirnov tests
π New features
scipy.cluster
improvementsπ Initialization of
scipy.cluster.vq.kmeans2
usingminit="++"
had a
quadratic complexity in the number of samples. It has been improved, resulting
in a much faster initialization with quasilinear complexity.scipy.cluster.hierarchy.dendrogram
now respects thematplotlib
color
palettescipy.fft
improvementsA new keywordonly argument
plan
is added to all FFT functions in this
module. It is reserved for passing in a precomputed plan from libraries
providing a FFT backend (such asPyFFTW
andmklfft
), and it is
currently not used in SciPy.scipy.integrate
improvementsscipy.interpolate
improvementsscipy.io
improvementsscipy.io.wavfile
error messages are more explicit about what's wrong, and
extraneous bytes at the ends of files are ignored instead of raising an error
when the data has successfully been read.scipy.io.loadmat
gained asimplify_cells
parameter, which if set to
True
simplifies the structure of the return value if the.mat
file
contains cell arrays.π
pathlib.Path
objects are now supported inscipy.io
Matrix Market I/O
functionsscipy.linalg
improvementsscipy.linalg.eigh
has been improved. Now variousLAPACK
drivers can be
selected at will and also subsets of eigenvalues can be requested via
subset_by_value
keyword. Another keywordsubset_by_index
is introduced.
π Keywordsturbo
andeigvals
are deprecated.Similarly, standard and generalized Hermitian eigenvalue
LAPACK
routines
?<sy/he>evx
are added and existing ones now have full_lwork
counterparts.Wrappers for the following
LAPACK
routines have been added to
scipy.linalg.lapack
:?getc2
: computes the LU factorization of a general matrix with complete
pivoting?gesc2
: solves a linear system given an LU factorization from?getc2
?gejsv
: computes the singular value decomposition of a general matrix
with higher accuracy calculation of tiny singular values and their
corresponding singular vectors?geqrfp
: computes the QR factorization of a general matrix with
nonnegative elements on the diagonal of R?gtsvx
: solves a linear system with general tridiagonal matrix?gttrf
: computes the LU factorization of a tridiagonal matrix?gttrs
: solves a linear system given an LU factorization from?gttrf
?ptsvx
: solves a linear system with symmetric positive definite
tridiagonal matrix?pttrf
: computes the LU factorization of a symmetric positive definite
tridiagonal matrix?pttrs
: solves a linear system given an LU factorization from?pttrf
?pteqr
: computes the eigenvectors and eigenvalues of a positive definite
tridiagonal matrix?tbtrs
: solves a linear system with a triangular banded matrix?csd
: computes the Cosine Sine decomposition of an orthogonal/unitary
matrix
Generalized QR factorization routines (
?geqrf
) now have full_lwork
counterparts.scipy.linalg.cossin
Cosine Sine decomposition of unitary matrices has been
β added.The function
scipy.linalg.khatri_rao
, which computes the KhatriRao product,
was added.The new function
scipy.linalg.convolution_matrix
constructs the Toeplitz
matrix representing onedimensional convolution.scipy.ndimage
improvementsβ‘οΈ
scipy.optimize
improvementsThe finite difference numerical differentiation used in various
minimize
methods that use gradients has several new features: 2point, 3point, or complex step finite differences can be used. Previously
only a 2step finite difference was available.  There is now the possibility to use a relative step size, previously only an
absolute step size was available.  If the
minimize
method uses bounds the numerical differentiation strictly
obeys those limits.  The numerical differentiation machinery now makes use of a simple cache,
which in some cases can reduce the number of function evaluations.  π
minimize
'smethod= 'powell'
now supports simple bound constraints
β‘οΈ There have been several improvements to
scipy.optimize.linprog
: The
linprog
benchmark suite has been expanded considerably.  π
linprog
's dense pivotbased redundancy removal routine and sparse
presolve are faster  π When
scikitsparse
is available, solving sparse problems with
method='interiorpoint'
is faster
β‘οΈ The caching of values when optimizing a function returning both value and
gradient together has been improved, avoiding repeated function evaluations
when using aHessianApproximation
such asBFGS
.differential_evolution
can now use the modernnp.random.Generator
as
π well as the legacynp.random.RandomState
as a seed.π¦
scipy.signal
improvementsA new optional argument
include_nyquist
is added tofreqz
functions in
this module. It is used for including the last frequency (Nyquist frequency).scipy.signal.find_peaks_cwt
now accepts awindow_size
parameter for the
size of the window used to calculate the noise floor.π
scipy.sparse
improvementsOuter indexing is now faster when using a 2d column vector to select column
indices.π
scipy.sparse.lil.tocsr
is fasterπ Fixed/improved comparisons between pydata sparse arrays and sparse matrices
π BSR format sparse multiplication performance has been improved.
π
scipy.sparse.linalg.LinearOperator
has gained the newndim
class
attributescipy.spatial
improvementsscipy.spatial.geometric_slerp
has been added to enable geometric
spherical linear interpolation on an nsphereπ
scipy.spatial.SphericalVoronoi
now supports calculation of region areas in 2D
and 3D casesπ The tree building algorithm used by
cKDTree
has improved from quadratic
worst case time complexity to loglinear. Benchmarks are also now available for
π building and querying of balanced/unbalanced kdtrees.scipy.special
improvementsThe following functions now have Cython interfaces in
cython_special
:scipy.special.erfinv
scipy.special.erfcinv
scipy.special.spherical_jn
scipy.special.spherical_yn
scipy.special.spherical_in
scipy.special.spherical_kn
scipy.special.log_softmax
has been added to calculate the logarithm of softmax
π² function. It provides better accuracy thanlog(scipy.special.softmax(x))
for
inputs that make softmax saturate.scipy.stats
improvementsThe function for generating random samples in
scipy.stats.dlaplace
has been
π improved. The new function is approximately twice as fast with a memory
π footprint reduction between 25 % and 60 % (see gh11069).π
scipy.stats
functions that accept a seed for reproducible calculations using
random number generation (e.g. random variates from distributions) can now use
the modernnp.random.Generator
as well as the legacy
πnp.random.RandomState
as a seed.The
axis
parameter was added toscipy.stats.rankdata
. This allows slices
of an array along the given axis to be ranked independently.The
axis
parameter was added toscipy.stats.f_oneway
, allowing it to
β compute multiple oneway ANOVA tests for data stored in ndimensional
π arrays. The performance off_oneway
was also improved for some cases.The PDF and CDF methods for
stats.geninvgauss
are now significantly faster
as the numerical integration to calculate the CDF uses a Cython based
LowLevelCallable
.Moments of the normal distribution (
scipy.stats.norm
) are now calculated using
analytical formulas instead of numerical integration for greater speed and
accuracyMoments and entropy trapezoidal distribution (
scipy.stats.trapz
) are now
calculated using analytical formulas instead of numerical integration for
greater speed and accuracyMethods of the truncated normal distribution (
scipy.stats.truncnorm
),
especially_rvs
, are significantly faster after a complete rewrite.The
fit
method of the Laplace distribution,scipy.stats.laplace
, now uses
the analytical formulas for the maximum likelihood estimates of the parameters.Generation of random variates is now thread safe for all SciPy distributions.
3rdparty distributions may need to modify the signature of the_rvs()
method to conform to_rvs(self, ..., size=None, random_state=None)
. (A
π onetime VisibleDeprecationWarning is emitted when using nonconformant
distributions.)β The KolmogorovSmirnov twosided test statistic distribution
(scipy.stats.kstwo
) was added. Calculates the distribution of the KS
twosided statisticD_n
for a sample of size n, using a mixture of exact
and asymptotic algorithms.The new function
median_abs_deviation
replaces the deprecated
median_absolute_deviation
.The
wilcoxon
function now computes the pvalue for Wilcoxon's signed rank
β test using the exact distribution for inputs up to length 25. The function has
a newmode
parameter to specify how the pvalue is to be computed. The
0οΈβ£ default is"auto"
, which uses the exact distribution for inputs up to length
25 and the normal approximation for larger inputs.β Added a new Cythonbased implementation to evaluate guassian kernel estimates,
π which should improve the performance ofgaussian_kde
The
winsorize
function now has anan_policy
argument for refined
handling ofnan
input values.The
binned_statistic_dd
function withstatistic="std"
performance was
π improved by ~4x.β
scipy.stats.kstest(rvs, cdf,...)
now handles both onesample and
β twosample testing. The onesample variation usesscipy.stats.ksone
(orscipy.stats.kstwo
with back off toscipy.stats.kstwobign
) to calculate
the pvalue. The twosample variation, invoked ifcdf
is array_like, uses
an algorithm described by Hodges to compute the probability directly, only
backing off toscipy.stats.kstwo
in case of overflow. The result in both
β cases is more accurate pvalues, especially for twosample testing with
smaller (or quite different) sizes.π
scipy.stats.maxwell
performance improvements include a 20 % speed up for
fit()
and 5 % forpdf()
`scipy.stats.shapiro
andscipy.stats.jarque_bera
now return a named tuple
for greater consistency with otherstats
functionsπ Deprecated features
π
scipy
deprecationsscipy.special
changesπ The
bdtr
,bdtrc
, andbdtri
functions are deprecating nonnegative
nonintegraln
arguments.scipy.stats
changesThe function
median_absolute_deviation
is deprecated. Use
median_abs_deviation
instead.The use of the string
"raw"
with thescale
parameter ofiqr
is
π deprecated. Usescale=1
instead.Backwards incompatible changes
scipy.interpolate
changesscipy.linalg
changesThe output signatures of
?syevr
,?heevr
have been changed from
w, v, info
tow, v, m, isuppz, info
The order of output arguments
w
,v
of<sy/he>{gv, gvd, gvx}
is
swapped.π¦
scipy.signal
changesπ¦ The output length of
scipy.signal.upfirdn
has been corrected, resulting
outputs may now be shorter for some combinations of up/down ratios and input
π¦ signal and filter lengths.π¦
scipy.signal.resample
now supports adomain
keyword argument for
specification of time or frequency domain input.scipy.stats
changesOther changes
π Improved support for leveraging 64bit integer size from linear algebra backends
in several parts of the SciPy codebase.Shims designed to ensure the compatibility of SciPy with Python 2.7 have now
π been removed.β Many warnings due to unused imports and unused assignments have been addressed.
π Many usage examples were added to function docstrings, and many input
π» validations and intuitive exception messages have been added throughout the
codebase.Early stage adoption of type annotations in a few parts of the codebase
Authors
 @endolith
 Hameer Abbasi
 ADmitri +
 Wesley Alves +
 Berkay Antmen +
 Sylwester Arabas +
 Arne KΓΌderle +
 Christoph Baumgarten
 Peter Bell
 Felix Berkenkamp
 JordΓ£o Bragantini +
 Clemens Brunner +
 Evgeni Burovski
 Matthias Bussonnier +
 CJ Carey
 Derrick Chambers +
 Leander Claes +
 Christian Clauss
 Luigi F. Cruz +
 dankleeman
 Andras Deak
 Milad Sadeghi DM +
 jeremie du boisberranger +
 Stefan Endres
 Malte Esders +
 Leo Fang +
 felixhekhorn +
 Isuru Fernando
 Andrew Fowlie
 Lakshay Garg +
 Gaurav Gijare +
 Ralf Gommers
 Emmanuelle Gouillart +
 Kevin Green +
 Martin Grignard +
 Maja Gwozdz
 Sturla Molden
 gyudon +
 Matt Haberland
 hakeemo +
 Charles Harris
 Alex Henrie
 Santi Hernandez +
 William Hickman +
 Till Hoffmann +
 Joseph T. Iosue +
 Anany Shrey Jain
 Jakob Jakobson
 Charles Jekel +
 Julien Jerphanion +
 JiachengLiu +
 Christoph Kecht +
 Paul Kienzle +
 Reidar Kind +
 Dmitry E. Kislov +
 Konrad +
 Konrad0
 Takuya KOUMURA +
 Krzysztof PiΓ³ro
 Peter Mahler Larsen
 Eric Larson
 Antony Lee
 Gregory Lee +
 Gregory R. Lee
 Chelsea Liu
 Cong Ma +
 Kevin Mader +
 Maja GwΓ³ΕΊdΕΊ +
 Alex Marvin +
 Matthias KΓΌmmerer
 Nikolay Mayorov
 Mazay0 +
 G. D. McBain
 Nicholas McKibben +
 Sabrina J. Mielke +
 Sebastian J. Mielke +
 MiloΕ‘ KomarΔeviΔ +
 Shubham Mishra +
 Santiago M. Mola +
 Grzegorz Mrukwa +
 Peyton Murray
 Andrew Nelson
 Nico SchlΓΆmer
 nwjenkins +
 odidev +
 Sambit Panda
 Vikas Pandey +
 Rick Paris +
 Harshal Prakash Patankar +
 π Balint Pato +
 Matti Picus
 Ilhan Polat
 poom +
 Siddhesh Poyarekar
 Vladyslav Rachek +
 Bharat Raghunathan
 Manu Rajput +
 Tyler Reddy
 Andrew Reed +
 Lucas Roberts
 Ariel Rokem
 Heshy Roskes
 Matt Ruffalo
 Atsushi Sakai +
 Benjamin Santos +
 Christoph Schock +
 Lisa Schwetlick +
 Chris Simpson +
 Leo Singer
 Kai Striega
 SΓΈren Fuglede JΓΈrgensen
 Kaleab Tessera +
 Seth Troisi +
 Robert Uhl +
 Paul van Mulbregt
 Vasiliy +
 Isaac Virshup +
 Pauli Virtanen
 Shakthi Visagan +
 Jan Vleeshouwers +
 Sam Wallan +
 Lijun Wang +
 Warren Weckesser
 Richard Weiss +
 wenhuiprudencemed +
 Eric Wieser
 Josh Wilson
 James Wright +
 Ruslan Yevdokymov +
 Ziyao Zhang +
π A total of 129 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.  wrappers for more than a dozen new

v1.5.0.rc1 Changes
May 30, 2020π SciPy 1.5.0 Release Notes
Note : Scipy
1.5.0
is not released yet!SciPy
1.5.0
is the culmination of 6 months of hard work. It contains
β many new features, numerous bugfixes, improved test coverage and better
π documentation. There have been a number of deprecations and 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
1.5.x branch, and on adding new features on the master branch.π This release requires Python
3.6+
and NumPy1.14.5
or greater.For running on PyPy, PyPy3
6.0+
and NumPy1.15.0
are required.π Highlights of this release
 wrappers for more than a dozen new
LAPACK
routines are now available
inscipy.linalg.lapack
 π Improved support for leveraging 64bit integer size from linear algebra
backends  β addition of the probability distribution for twosided onesample
β KolmogorovSmirnov tests
π New features
scipy.cluster
improvementsπ Initialization of
scipy.cluster.vq.kmeans2
usingminit="++"
had a
quadratic complexity in the number of samples. It has been improved, resulting
in a much faster initialization with quasilinear complexity.scipy.cluster.hierarchy.dendrogram
now respects thematplotlib
color
palettescipy.fft
improvementsA new keywordonly argument
plan
is added to all FFT functions in this
module. It is reserved for passing in a precomputed plan from libraries
providing a FFT backend (such asPyFFTW
andmklfft
), and it is
currently not used in SciPy.scipy.integrate
improvementsscipy.interpolate
improvementsscipy.io
improvementsscipy.io.wavfile
error messages are more explicit about what's wrong, and
extraneous bytes at the ends of files are ignored instead of raising an error
when the data has successfully been read.scipy.io.loadmat
gained asimplify_cells
parameter, which if set to
True
simplifies the structure of the return value if the.mat
file
contains cell arrays.π
pathlib.Path
objects are now supported inscipy.io
Matrix Market I/O
functionsscipy.linalg
improvementsscipy.linalg.eigh
has been improved. Now variousLAPACK
drivers can be
selected at will and also subsets of eigenvalues can be requested via
subset_by_value
keyword. Another keywordsubset_by_index
is introduced.
π Keywordsturbo
andeigvals
are deprecated.Similarly, standard and generalized Hermitian eigenvalue
LAPACK
routines
?<sy/he>evx
are added and existing ones now have full_lwork
counterparts.Wrappers for the following
LAPACK
routines have been added to
scipy.linalg.lapack
:?getc2
: computes the LU factorization of a general matrix with complete
pivoting?gesc2
: solves a linear system given an LU factorization from?getc2
?gejsv
: computes the singular value decomposition of a general matrix
with higher accuracy calculation of tiny singular values and their
corresponding singular vectors?geqrfp
: computes the QR factorization of a general matrix with
nonnegative elements on the diagonal of R?gtsvx
: solves a linear system with general tridiagonal matrix?gttrf
: computes the LU factorization of a tridiagonal matrix?gttrs
: solves a linear system given an LU factorization from?gttrf
?ptsvx
: solves a linear system with symmetric positive definite
tridiagonal matrix?pttrf
: computes the LU factorization of a symmetric positive definite
tridiagonal matrix?pttrs
: solves a linear system given an LU factorization from?pttrf
?pteqr
: computes the eigenvectors and eigenvalues of a positive definite
tridiagonal matrix?tbtrs
: solves a linear system with a triangular banded matrix?csd
: computes the Cosine Sine decomposition of an orthogonal/unitary
matrix
Generalized QR factorization routines (
?geqrf
) now have full_lwork
counterparts.scipy.linalg.cossin
Cosine Sine decomposition of unitary matrices has been
β added.The function
scipy.linalg.khatri_rao
, which computes the KhatriRao product,
was added.The new function
scipy.linalg.convolution_matrix
constructs the Toeplitz
matrix representing onedimensional convolution.scipy.ndimage
improvementsβ‘οΈ
scipy.optimize
improvementsThe finite difference numerical differentiation used in various
minimize
methods that use gradients has several new features: 2point, 3point, or complex step finite differences can be used. Previously
only a 2step finite difference was available.  There is now the possibility to use a relative step size, previously only an
absolute step size was available.  If the
minimize
method uses bounds the numerical differentiation strictly
obeys those limits.  The numerical differentiation machinery now makes use of a simple cache,
which in some cases can reduce the number of function evaluations.  π
minimize
'smethod= 'powell'
now supports simple bound constraints
β‘οΈ There have been several improvements to
scipy.optimize.linprog
: The
linprog
benchmark suite has been expanded considerably.  π
linprog
's dense pivotbased redundancy removal routine and sparse
presolve are faster  π When
scikitsparse
is available, solving sparse problems with
method='interiorpoint'
is faster
β‘οΈ The caching of values when optimizing a function returning both value and
gradient together has been improved, avoiding repeated function evaluations
when using aHessianApproximation
such asBFGS
.differential_evolution
can now use the modernnp.random.Generator
as
π well as the legacynp.random.RandomState
as a seed.π¦
scipy.signal
improvementsA new optional argument
include_nyquist
is added tofreqz
functions in
this module. It is used for including the last frequency (Nyquist frequency).scipy.signal.find_peaks_cwt
now accepts awindow_size
parameter for the
size of the window used to calculate the noise floor.π
scipy.sparse
improvementsOuter indexing is now faster when using a 2d column vector to select column
indices.π
scipy.sparse.lil.tocsr
is fasterπ Fixed/improved comparisons between pydata sparse arrays and sparse matrices
π BSR format sparse multiplication performance has been improved.
π
scipy.sparse.linalg.LinearOperator
has gained the newndim
class
attributescipy.spatial
improvementsscipy.spatial.geometric_slerp
has been added to enable geometric
spherical linear interpolation on an nsphereπ
scipy.spatial.SphericalVoronoi
now supports calculation of region areas in 2D
and 3D casesπ The tree building algorithm used by
cKDTree
has improved from quadratic
worst case time complexity to loglinear. Benchmarks are also now available for
π building and querying of balanced/unbalanced kdtrees.scipy.special
improvementsThe following functions now have Cython interfaces in
cython_special
:scipy.special.erfinv
scipy.special.erfcinv
scipy.special.spherical_jn
scipy.special.spherical_yn
scipy.special.spherical_in
scipy.special.spherical_kn
scipy.special.log_softmax
has been added to calculate the logarithm of softmax
π² function. It provides better accuracy thanlog(scipy.special.softmax(x))
for
inputs that make softmax saturate.scipy.stats
improvementsThe function for generating random samples in
scipy.stats.dlaplace
has been
π improved. The new function is approximately twice as fast with a memory
π footprint reduction between 25 % and 60 % (see gh11069).π
scipy.stats
functions that accept a seed for reproducible calculations using
random number generation (e.g. random variates from distributions) can now use
the modernnp.random.Generator
as well as the legacy
πnp.random.RandomState
as a seed.The
axis
parameter was added toscipy.stats.rankdata
. This allows slices
of an array along the given axis to be ranked independently.The
axis
parameter was added toscipy.stats.f_oneway
, allowing it to
β compute multiple oneway ANOVA tests for data stored in ndimensional
π arrays. The performance off_oneway
was also improved for some cases.The PDF and CDF methods for
stats.geninvgauss
are now significantly faster
as the numerical integration to calculate the CDF uses a Cython based
LowLevelCallable
.Moments of the normal distribution (
scipy.stats.norm
) are now calculated using
analytical formulas instead of numerical integration for greater speed and
accuracyMoments and entropy trapezoidal distribution (
scipy.stats.trapz
) are now
calculated using analytical formulas instead of numerical integration for
greater speed and accuracyMethods of the truncated normal distribution (
scipy.stats.truncnorm
),
especially_rvs
, are significantly faster after a complete rewrite.The
fit
method of the Laplace distribution,scipy.stats.laplace
, now uses
the analytical formulas for the maximum likelihood estimates of the parameters.Generation of random variates is now thread safe for all SciPy distributions.
3rdparty distributions may need to modify the signature of the_rvs()
method to conform to_rvs(self, ..., size=None, random_state=None)
. (A
π onetime VisibleDeprecationWarning is emitted when using nonconformant
distributions.)β The KolmogorovSmirnov twosided test statistic distribution
(scipy.stats.kstwo
) was added. Calculates the distribution of the KS
twosided statisticD_n
for a sample of size n, using a mixture of exact
and asymptotic algorithms.The new function
median_abs_deviation
replaces the deprecated
median_absolute_deviation
.The
wilcoxon
function now computes the pvalue for Wilcoxon's signed rank
β test using the exact distribution for inputs up to length 25. The function has
a newmode
parameter to specify how the pvalue is to be computed. The
0οΈβ£ default is"auto"
, which uses the exact distribution for inputs up to length
25 and the normal approximation for larger inputs.β Added a new Cythonbased implementation to evaluate guassian kernel estimates,
π which should improve the performance ofgaussian_kde
The
winsorize
function now has anan_policy
argument for refined
handling ofnan
input values.The
binned_statistic_dd
function withstatistic="std"
performance was
π improved by ~4x.β
scipy.stats.kstest(rvs, cdf,...)
now handles both onesample and
β twosample testing. The onesample variation usesscipy.stats.ksone
(orscipy.stats.kstwo
with back off toscipy.stats.kstwobign
) to calculate
the pvalue. The twosample variation, invoked ifcdf
is array_like, uses
an algorithm described by Hodges to compute the probability directly, only
backing off toscipy.stats.kstwo
in case of overflow. The result in both
β cases is more accurate pvalues, especially for twosample testing with
smaller (or quite different) sizes.π
scipy.stats.maxwell
performance improvements include a 20 % speed up for
fit()
and 5 % forpdf()
`scipy.stats.shapiro
andscipy.stats.jarque_bera
now return a named tuple
for greater consistency with otherstats
functionsπ Deprecated features
π
scipy
deprecationsscipy.special
changesπ The
bdtr
,bdtrc
, andbdtri
functions are deprecating nonnegative
nonintegraln
arguments.scipy.stats
changesThe function
median_absolute_deviation
is deprecated. Use
median_abs_deviation
instead.The use of the string
"raw"
with thescale
parameter ofiqr
is
π deprecated. Usescale=1
instead.Backwards incompatible changes
scipy.interpolate
changesscipy.linalg
changesThe output signatures of
?syevr
,?heevr
have been changed from
w, v, info
tow, v, m, isuppz, info
The order of output arguments
w
,v
of<sy/he>{gv, gvd, gvx}
is
swapped.π¦
scipy.signal
changesπ¦ The output length of
scipy.signal.upfirdn
has been corrected, resulting
outputs may now be shorter for some combinations of up/down ratios and input
π¦ signal and filter lengths.π¦
scipy.signal.resample
now supports adomain
keyword argument for
specification of time or frequency domain input.scipy.stats
changesOther changes
π Improved support for leveraging 64bit integer size from linear algebra backends
in several parts of the SciPy codebase.Shims designed to ensure the compatibility of SciPy with Python 2.7 have now
π been removed.β Many warnings due to unused imports and unused assignments have been addressed.
π Many usage examples were added to function docstrings, and many input
π» validations and intuitive exception messages have been added throughout the
codebase.Early stage adoption of type annotations in a few parts of the codebase
Authors
 @endolith
 Hameer Abbasi
 ADmitri +
 Wesley Alves +
 Berkay Antmen +
 Sylwester Arabas +
 Arne KΓΒΌderle +
 Christoph Baumgarten
 Peter Bell
 Felix Berkenkamp
 JordΓΒ£o Bragantini +
 Clemens Brunner +
 Evgeni Burovski
 Matthias Bussonnier +
 CJ Carey
 Derrick Chambers +
 Leander Claes +
 Christian Clauss
 Luigi F. Cruz +
 dankleeman
 Andras Deak
 Milad Sadeghi DM +
 jeremie du boisberranger +
 Stefan Endres
 Malte Esders +
 Leo Fang +
 felixhekhorn +
 Isuru Fernando
 Andrew Fowlie
 Lakshay Garg +
 Gaurav Gijare +
 Ralf Gommers
 Emmanuelle Gouillart +
 Kevin Green +
 Martin Grignard +
 Maja Gwozdz
 gyudon +
 Matt Haberland
 hakeemo +
 Charles Harris
 Alex Henrie
 Santi Hernandez +
 William Hickman +
 Till Hoffmann +
 Joseph T. Iosue +
 Anany Shrey Jain
 Jakob Jakobson
 Charles Jekel +
 Julien Jerphanion +
 JiachengLiu +
 Christoph Kecht +
 Paul Kienzle +
 Reidar Kind +
 Dmitry E. Kislov +
 Konrad +
 Konrad0
 Takuya KOUMURA +
 Krzysztof PiΓΒ³ro
 Peter Mahler Larsen
 Eric Larson
 Antony Lee
 Gregory Lee +
 Gregory R. Lee
 Chelsea Liu
 Cong Ma +
 Kevin Mader +
 Maja GwΓΒ³Γ ΒΊdΓ ΒΊ +
 Alex Marvin +
 Matthias KΓΒΌmmerer
 Nikolay Mayorov
 Mazay0 +
 G. D. McBain
 Nicholas McKibben +
 Sabrina J. Mielke +
 Sebastian J. Mielke +
 MiloΓ Β‘ KomarΓοΏ½eviΓβ‘ +
 Shubham Mishra +
 Santiago M. Mola +
 Grzegorz Mrukwa +
 Peyton Murray
 Andrew Nelson
 Nico SchlΓΒΆmer
 nwjenkins +
 odidev +
 Sambit Panda
 Vikas Pandey +
 Rick Paris +
 Harshal Prakash Patankar +
 π Balint Pato +
 Matti Picus
 Ilhan Polat
 poom +
 Siddhesh Poyarekar
 Vladyslav Rachek +
 Bharat Raghunathan
 Manu Rajput +
 Tyler Reddy
 Andrew Reed +
 Lucas Roberts
 Ariel Rokem
 Heshy Roskes
 Matt Ruffalo
 Atsushi Sakai +
 Benjamin Santos +
 Christoph Schock +
 Lisa Schwetlick +
 Chris Simpson +
 Leo Singer
 Kai Striega
 SΓΒΈren Fuglede JΓΒΈrgensen
 Kaleab Tessera +
 Seth Troisi +
 Robert Uhl +
 Paul van Mulbregt
 Vasiliy +
 Isaac Virshup +
 Pauli Virtanen
 Shakthi Visagan +
 Jan Vleeshouwers +
 Sam Wallan +
 Lijun Wang +
 Warren Weckesser
 Richard Weiss +
 wenhuiprudencemed +
 Eric Wieser
 Josh Wilson
 James Wright +
 Ruslan Yevdokymov +
 Ziyao Zhang +
π A total of 129 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.  wrappers for more than a dozen new

v1.4.1 Changes
December 19, 2019π SciPy 1.4.1 Release Notes
π SciPy
1.4.1
is a bugfix release with no new features
compared to1.4.0
. Importantly, it aims to fix a problem
where an older version ofpybind11
may cause a segmentation
fault when imported alongside incompatible libraries.Authors
 Ralf Gommers
 Tyler Reddy

v1.4.0 Changes
December 16, 2019π SciPy 1.4.0 Release Notes
SciPy
1.4.0
is the culmination of 6 months of hard work. It contains
β many new features, numerous bugfixes, improved test coverage and better
π documentation. There have been a number of deprecations and 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
1.4.x branch, and on adding new features on the master branch.π This release requires Python
3.5+
and NumPy>=1.13.3
(for Python3.5
,3.6
),
>=1.14.5
(for Python3.7
),>= 1.17.3
(for Python3.8
)For running on PyPy, PyPy3
6.0+
and NumPy1.15.0
are required.π Highlights of this release
 a new submodule,
scipy.fft
, now supersedesscipy.fftpack
; this
π means support forlong double
transforms, faster multidimensional
π transforms, improved algorithm time complexity, release of the global
π intepreter lock, and control over threading behavior  π support for
pydata/sparse
arrays inscipy.sparse.linalg
 π substantial improvement to the documentation and functionality of
severalscipy.special
functions, and some new additions  the generalized inverse Gaussian distribution has been added to
scipy.stats
 an implementation of the EdmondsKarp algorithm in
πscipy.sparse.csgraph.maximum_flow
 π
scipy.spatial.SphericalVoronoi
now supports ndimensional input,
π has linear memory complexity, improved performance, and
π supports singlehemisphere generators
π New features
Infrastructure
π Documentation can now be built with
runtests.py doc
π³ A
Dockerfile
is now available in thescipy/scipydev
repository to
facilitate getting started with SciPy development.scipy.constants
improvementsβ‘οΈ
scipy.constants
has been updated with the CODATA 2018 constants.scipy.fft
addedscipy.fft
is a new submodule that supersedes thescipy.fftpack
submodule.
For the most part, this is a dropin replacement fornumpy.fft
and
scipy.fftpack
alike. With some important differences,scipy.fft
: π uses NumPy's conventions for real transforms (
rfft
). This means the
return value is a complex array, half the size of the fullfft
output.
This is different from the output offftpack
which returned a real array
representing complex components packed together.  the inverse real to real transforms (
idct
andidst
) are normalized
fornorm=None
in thesame way asifft
. This means the identity
idct(dct(x)) == x
is nowTrue
for all norm modes.  does not include the convolutions or pseudodifferential operators
fromfftpack
.
This submodule is based on the
pypocketfft
library, developed by the
author ofpocketfft
which was recently adopted by NumPy as well.
pypocketfft
offers a number of advantages over fortranFFTPACK
: π support for long double (
np.longfloat
) precision transforms.  faster multidimensional transforms using vectorisation
 π Bluesteinβs algorithm removes the worstcase
O(n^2)
complexity of
FFTPACK
 π the global interpreter lock (
GIL
) is released during transforms  π· optional multithreading of multidimensional transforms via the
workers
argument
π Note that
scipy.fftpack
has not been deprecated and will continue to be
maintained but is now considered legacy. New code is recommended to use
scipy.fft
instead, where possible.scipy.fftpack
improvementsscipy.fftpack
now uses pypocketfft to perform its FFTs, offering the same
speed and accuracy benefits listed for scipy.fft above but without the
π improved API.scipy.integrate
improvementsThe function
scipy.integrate.solve_ivp
now has anargs
argument.
This allows the userdefined functions passed to the function to have
β additional parameters without having to create wrapper functions or
lambda expressions for them.scipy.integrate.solve_ivp
can now return ay_events
attribute
representing the solution of the ODE at event timesπ New
OdeSolver
is implemented DOP853
. This is a highorder explicit
β RungeKutta method originally implemented in Fortran. Now we provide a pure
Python implementation usable throughsolve_ivp
with all its features.π
scipy.integrate.quad
provides better user feedback when break points are
specified with a weighted integrand.scipy.integrate.quad_vec
is now available for general purpose integration
of vectorvalued functionsscipy.interpolate
improvementsscipy.interpolate.pade
now handles complex input data gracefullyscipy.interpolate.Rbf
can now interpolate multidimensional functionsscipy.io
improvementsscipy.io.wavfile.read
can now read data from aWAV
file that has a
π malformed header, similar to other modernWAV
file parsersπ»
scipy.io.FortranFile
now has an expanded set of availableException
classes for handling poorlyformatted filesscipy.linalg
improvementsThe function
scipy.linalg.subspace_angles(A, B)
now gives correct
results for complexvalued matrices. Before this, the function only returned
correct values for realvalued matrices.π New boolean keyword argument
check_finite
forscipy.linalg.norm
; whether
to check that the input matrix contains only finite numbers. Disabling may
π give a performance gain, but may result in problems (crashes, nontermination)
if the inputs do contain infinities or NaNs.π
scipy.linalg.solve_triangular
has improved performance for a Cordered
triangular matrixLAPACK
wrappers have been added for?geequ
,?geequb
,?syequb
,
and?heequb
π Some performance improvements may be observed due to an internal optimization
in operations involving LAPACK routines via_compute_lwork
. This is
particularly true for operations on small arrays.Block
QR
wrappers are now available inscipy.linalg.lapack
scipy.ndimage
improvementsβ‘οΈ
scipy.optimize
improvementsIt is now possible to use linear and nonlinear constraints with
β‘οΈscipy.optimize.differential_evolution
.scipy.optimize.linear_sum_assignment
has been rewritten in C++ to improve
π performance, and now allows input costs to be infinite.A
ScalarFunction.fun_and_grad
method was added for convenient simultaneous
retrieval of a function and gradient evaluationπ
scipy.optimize.minimize
BFGS
method has improved performance by avoiding
duplicate evaluations in some casesπ Better user feedback is provided when an objective function returns an array
instead of a scalar.π¦
scipy.signal
improvementsβ Added a new function to calculate convolution using the overlapadd method,
π¦ namedscipy.signal.oaconvolve
. Likescipy.signal.fftconvolve
, this
π function supports specifying dimensions along which to do the convolution.π¦
scipy.signal.cwt
now supports complex wavelets.The implementation of
choose_conv_method
has been updated to reflect the
π new FFT implementation. In addition, the performance has been significantly
π improved (with rather drastic improvements in edge cases).The function
upfirdn
now has amode
keyword argument that can be used
π¦ to select the signal extension mode used at the signal boundaries. These modes
are also available for use inresample_poly
via a newly addedpadtype
argument.π
scipy.signal.sosfilt
now benefits from Cython code for improved performanceπ¦
scipy.signal.resample
should be more efficient by leveragingrfft
when
possibleπ
scipy.sparse
improvementsπ It is now possible to use the LOBPCG method in
scipy.sparse.linalg.svds
.π
scipy.sparse.linalg.LinearOperator
now supports the operationrmatmat
for adjoint matrixmatrix multiplication, in addition tormatvec
.β‘οΈ Multiple stability updates enable float32 support in the LOBPCG eigenvalue
solver for symmetric and Hermitian eigenvalues problems in
πscipy.sparse.linalg.lobpcg
.A solver for the maximum flow problem has been added as
πscipy.sparse.csgraph.maximum_flow
.scipy.sparse.csgraph.maximum_bipartite_matching
now allows nonsquare inputs,
π no longer requires a perfect matching to exist, and has improved performance.π
scipy.sparse.lil_matrix
conversions now perform better in some scenariosπ Basic support is available for
pydata/sparse
arrays in
πscipy.sparse.linalg
π
scipy.sparse.linalg.spsolve_triangular
now supports theunit_diagonal
argument to improve call signature similarity with its dense counterpart,
scipy.linalg.solve_triangular
π
assertAlmostEqual
may now be used with sparse matrices, which have added
support for__round__
scipy.spatial
improvementsβ¬οΈ The bundled Qhull library was upgraded to version 2019.1, fixing several
issues. Scipyspecific patches are no longer applied to it.scipy.spatial.SphericalVoronoi
now has linear memory complexity, improved
π performance, and supports singlehemisphere generators. Support has also been
β added for handling generators that lie on a great circle arc (geodesic input)
and for generators in ndimensions.scipy.spatial.transform.Rotation
now includes functions for calculation of a
mean rotation, generation of the 3D rotation groups, and reduction of rotations
with rotational symmetries.scipy.spatial.transform.Slerp
is now callable with a scalar argumentscipy.spatial.voronoi_plot_2d
now supports furthest site Voronoi diagramsscipy.spatial.Delaunay
andscipy.spatial.Voronoi
now have attributes
for tracking whether they are furthest site diagramsscipy.special
improvementsThe Voigt profile has been added as
scipy.special.voigt_profile
.A real dispatch has been added for the Wright Omega function
(scipy.special.wrightomega
).The analytic continuation of the Riemann zeta function has been added. (The
Riemann zeta function is the oneargument variant ofscipy.special.zeta
.)The complete elliptic integral of the first kind (
scipy.special.ellipk
) is
now available inscipy.special.cython_special
.The accuracy of
scipy.special.hyp1f1
for real arguments has been improved.π The documentation of many functions has been improved.
scipy.stats
improvementsβ
scipy.stats.multiscale_graphcorr
added as an independence test that
operates on high dimensional and nonlinear data sets. It has higher statistical
β power than otherscipy.stats
tests while being the only one that operates on
multivariate data.The generalized inverse Gaussian distribution (
scipy.stats.geninvgauss
) has
been added.It is now possible to efficiently reuse
scipy.stats.binned_statistic_dd
with new values by providing the result of a previous call to the function.scipy.stats.hmean
now handles input with zeros more gracefully.The betabinomial distribution is now available in
scipy.stats.betabinom
.scipy.stats.zscore
,scipy.stats.circmean
,scipy.stats.circstd
, and
πscipy.stats.circvar
now support thenan_policy
argument for enhanced
handling ofNaN
valuesscipy.stats.entropy
now accepts anaxis
argumentπ
scipy.stats.gaussian_kde.resample
now accepts aseed
argument to empower
reproducibilityπ
scipy.stats.kendalltau
performance has improved, especially for large inputs,
due to improved cache usageπ
scipy.stats.truncnorm
distribution has been rewritten to support much wider
tailsπ Deprecated features
π
scipy
deprecationsπ Support for NumPy functions exposed via the root SciPy namespace is deprecated
π and will be removed in 2.0.0. For example, if you usescipy.rand
or
scipy.diag
, you should change your code to directly use
0οΈβ£numpy.random.default_rng
ornumpy.diag
, respectively.
π They remain available in the currently continuing Scipy 1.x release series.π» The exception to this rule is using
scipy.fft
as a function 
:mod:scipy.fft
is now meant to be used only as a module, so the ability to
π callscipy.fft(...)
will be removed in SciPy 1.5.0.In
scipy.spatial.Rotation
methodsfrom_dcm
,as_dcm
were renamed to
from_matrix
,as_matrix
respectively. The old names will be removed in
SciPy 1.6.0.π Method
Rotation.match_vectors
was deprecated in favor of
Rotation.align_vectors
, which provides a more logical and
general API to the same functionality. The old method
π will be removed in SciPy 1.6.0.Backwards incompatible changes
scipy.special
changesπ The deprecated functions
hyp2f0
,hyp1f2
, andhyp3f0
have been
β removed.The deprecated function
bessel_diff_formula
has been removed.The function
i0
is no longer registered withnumpy.dual
, so that
numpy.dual.i0
will unconditionally refer to the NumPy version regardless
of whetherscipy.special
is imported.The function
expn
has been changed to returnnan
outside of its
domain of definition (x, n < 0
) instead ofinf
.π
scipy.sparse
changesπ Sparse matrix reshape now raises an error if shape is not twodimensional,
rather than guessing what was meant. The behavior is now the same as before
SciPy 1.1.0.π
CSR
andCSC
sparse matrix classes should now return empty matrices
of the same type when indexed out of bounds. Previously, for some versions
of SciPy, this would raise anIndexError
. The change is largely motivated
by greater consistency withndarray
andnumpy.matrix
semantics.π¦
scipy.signal
changesπ¦
scipy.signal.resample
behavior for length1 signal inputs has been
π fixed to output a constant (DC) value rather than an impulse, consistent with
π¦ the assumption of signal periodicity in the FFT method.π¦
scipy.signal.cwt
now performs complex conjugation and timereversal of
π wavelet data, which is a backwardsincompatible bugfix for
timeasymmetric wavelets.scipy.stats
changesπ
scipy.stats.loguniform
added with better documentation as (an alias for
scipy.stats.reciprocal
).loguniform
generates random variables
π² that are equally likely in the log space; e.g.,1
,10
and100
are all equally likely ifloguniform(10 **0, 10** 2).rvs()
is used.Other changes
The
LSODA
method ofscipy.integrate.solve_ivp
now correctly detects stiff
problems.scipy.spatial.cKDTree
now accepts and correctly handles empty input datascipy.stats.binned_statistic_dd
now calculates the standard deviation
statistic in a numerically stable way.scipy.stats.binned_statistic_dd
now throws an error if the input data
contains eithernp.nan
ornp.inf
. Similarly, inscipy.stats
now all
continuous distributions'.fit()
methods throw an error if the input data
contain any instance of eithernp.nan
ornp.inf
.Authors
 @endolith
 @wenhuiprudencemed +
 Abhinav +
 Anne Archibald
 ashwinpathak20nov1996 +
 Danilo Augusto +
 Nelson Auner +
 aypiggott +
 Christoph Baumgarten
 Peter Bell
 Sebastian Berg
 Arman Bilge +
 Benedikt Boecking +
 Christoph Boeddeker +
 Daniel Bunting
 Evgeni Burovski
 Angeline Burrell +
 Angeline G. Burrell +
 CJ Carey
 Carlos Ramos CarreΓ±o +
 Mak Sze Chun +
 Malayaja Chutani +
 Christian Clauss +
 Jonathan Conroy +
 Stephen P Cook +
 Dylan Cutler +
 Anirudh Dagar +
 Aidan Dang +
 dankleeman +
 Brandon David +
 Tyler Dawson +
 Dieter WerthmΓΌller
 Joe Driscoll +
 Jakub Dyczek +
 DΓ‘vid BodnΓ‘r
 Fletcher Easton +
 Stefan Endres
 etienne +
 Johann Faouzi
 Yu Feng
 Isuru Fernando +
 Matthew H Flamm
 Martin Gauch +
 Gabriel Gerlero +
 Ralf Gommers
 Chris Gorgolewski +
 Domen Gorjup +
 Edouard Goudenhoofdt +
 Jan Gwinner +
 Maja Gwozdz +
 Matt Haberland
 hadshirt +
 Pierre Haessig +
 David Hagen
 Charles Harris
 Gina Helfrich +
 Alex Henrie +
 Francisco J. Hernandez Heras +
 Andreas Hilboll
 Lindsey Hiltner
 Thomas Hisch
 Min ho Kim +
 GertLudwig Ingold
 jakobjakobson13 +
 Todd Jennings
 He Jia
 Muhammad Firmansyah Kasim +
 Andrew Knyazev +
 Holger Kohr +
 Mateusz Konieczny +
 Krzysztof PiΓ³ro +
 Philipp Lang +
 Peter Mahler Larsen +
 Eric Larson
 Antony Lee
 Gregory R. Lee
 Chelsea Liu +
 Jesse Livezey
 Peter Lysakovski +
 Jason Manley +
 Michael Marien +
 Nikolay Mayorov
 G. D. McBain +
 Sam McCormack +
 Melissa Weber MendonΓ§a +
 Kevin Michel +
 mikeWShef +
 Sturla Molden
 Eric Moore
 Peyton Murray +
 Andrew Nelson
 Clement Ng +
 Juan NunezIglesias
 Renee Otten +
 Kellie Ottoboni +
 Ayappan P
 Sambit Panda +
 Tapasweni Pathak +
 Oleksandr Pavlyk
 Fabian Pedregosa
 Petar MlinariΔ
 Matti Picus
 Marcel Plch +
 Christoph Pohl +
 Ilhan Polat
 Siddhesh Poyarekar +
 Ioannis Prapas +
 James Alan Preiss +
 Yisheng Qiu +
 Eric Quintero
 Bharat Raghunathan +
 Tyler Reddy
 Joscha Reimer
 Antonio Horta Ribeiro
 Lucas Roberts
 rtshort +
 Josua Sassen
 Kevin Sheppard
 Scott Sievert
 Leo Singer
 Kai Striega
 SΓΈren Fuglede JΓΈrgensen
 tborisow +
 Γtienne Tremblay +
 tuxcell +
 Miguel de ValBorro
 Andrew Valentine +
 Hugo van Kemenade
 Paul van Mulbregt
 Sebastiano Vigna
 Pauli Virtanen
 Dany Vohl +
 Ben Walsh +
 Huize Wang +
 Warren Weckesser
 Anreas Weh +
 Joseph Weston +
 Adrian Wijaya +
 Timothy Willard +
 Josh Wilson
 Kentaro Yamamoto +
 Dave Zbarsky +
π A total of 142 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.  a new submodule,