Changelog History
Page 2

v1.4.0.rc2 Changes
December 08, 2019π SciPy 1.4.0 Release Notes
Note : Scipy
1.4.0
is not released yet!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 NumPy 1.15.0 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,

v1.4.0.rc1 Changes
November 22, 2019π SciPy 1.4.0 Release Notes
Note : SciPy 1.4.0 is not released yet!
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 Python 3.5, 3.6),
>=1.14.5
(for Python 3.7),>= 1.17.3
(for Python 3.8)For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 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
reproducibilityscipy.stats.multiscale_graphcorr
has been added for calculation of the
β multiscale graph correlation (MGC) test statisticπ
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.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.scipy.spatial
changes0οΈβ£ The default behavior of the
match_vectors
method of
scipy.spatial.transform.Rotation
was changed for input vectors
that are not normalized and not of equal lengths.
Previously, such vectors would be normalized within the method.
Now, the calculated rotation takes the vector length into account, longer
π vectors will have a larger weight. For more details, see
#10968.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
 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 141 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,

v1.3.3 Changes
November 23, 2019π SciPy 1.3.3 Release Notes
π SciPy
1.3.3
is a bugfix release with no new features
β compared to1.3.2
. In particular, a test suite issue
π involving multiprocessing was fixed for Windows and
π Python3.8
on macOS.β‘οΈ Wheels were also updated to place
msvcp140.dll
at the
appropriate location, which was previously causing issues.Authors
Ilhan Polat
Tyler Reddy
Ralf Gommers 
v1.3.2 Changes
November 09, 2019π SciPy
1.3.2
is a bugfix and maintenance release that adds support for Python3.8
.Authors
 CJ Carey
 Dany Vohl
 Martin Gauch +
 Ralf Gommers
 Matt Haberland
 Eric Larson
 Nikolay Mayorov
 Sam McCormack +
 Andrew Nelson
 Tyler Reddy
 Pauli Virtanen
 Huize Wang +
 Warren Weckesser
 Joseph Weston +
π A total of 14 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. 
v1.3.1 Changes
August 09, 2019π 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. 
v1.3.0 Changes
May 17, 2019π 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

v1.3.0.rc2 Changes
May 09, 2019π SciPy 1.3.0 Release Notes
Note : Scipy 1.3.0 is not released yet!
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).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

v1.3.0.rc1 Changes
April 27, 2019π SciPy 1.3.0 Release Notes
Note : Scipy 1.3.0 is not released yet!
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).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

v1.2.3 Changes
January 21, 2020π SciPy 1.2.3 Release Notes
π SciPy
1.2.3
is a bugfix release with no new features compared to1.2.2
. It is
π part of the longterm support (LTS) release series for Python2.7
.Authors
 Geordie McBain
 Matt Haberland
 David Hagen
 Tyler Reddy
 Pauli Virtanen
 Eric Larson
 Yu Feng
 ananyashreyjain
 Nikolay Mayorov
 Evgeni Burovski
 Warren Weckesser

v1.2.2 Changes
June 07, 2019π SciPy 1.2.2 Release Notes
π SciPy
1.2.2
is a bugfix release with no new features compared to1.2.1
.
Importantly, the SciPy 1.2.2 wheels are built with OpenBLAS0.3.7.dev
to
alleviate issues with SkylakeX AVX512 kernels.Authors
 CJ Carey
 Tyler Dawson +
 Ralf Gommers
 Kai Striega
 Andrew Nelson
 Tyler Reddy
 Kevin Sheppard +
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.