Update dependency scipy to v1.13.0 #1215
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This PR contains the following updates:
1.12.0
->1.13.0
Release Notes
scipy/scipy (scipy)
v1.13.0
: SciPy 1.13.0Compare Source
SciPy 1.13.0 Release Notes
SciPy
1.13.0
is the culmination of 3 months of hard work. Thisout-of-band release aims to support NumPy
2.0.0
, and is backwardscompatible to NumPy
1.22.4
. The version of OpenBLAS used to buildthe PyPI wheels has been increased to
0.3.26.dev
.This release requires Python 3.9+ and NumPy 1.22.4 or greater.
For running on PyPy, PyPy3 6.0+ is required.
Highlights of this release
2.0.0
.to run the examples locally on embedded Jupyterlite notebooks in their
browser.
scipy.stats
functions have gained support for additionalaxis
,nan_policy
, andkeepdims
arguments.scipy.stats
alsohas several performance and accuracy improvements.
New features
scipy.integrate
improvementsterminal
attribute ofscipy.integrate.solve_ivp
events
callables now additionally accepts integer values to specify a number
of occurrences required for termination, rather than the previous restriction
of only accepting a
bool
value to terminate on the first registeredevent.
scipy.io
improvementsscipy.io.wavfile.write
has improveddtype
input validation.scipy.interpolate
improvementsinterpolate.Akima1DInterpolator
, available via the newmethod
argument.
BSpline.insert_knot
inserts a knot into aBSpline
instance.This routine is similar to the module-level
scipy.interpolate.insert
function, and works with the BSpline objects instead of
tck
tuples.RegularGridInterpolator
gained the functionality to compute derivativesin place. For instance,
RegularGridInterolator((x, y), values, method="cubic")(xi, nu=(1, 1))
evaluates the mixed second derivative,:math:
\partial^2 / \partial x \partial y
atxi
.RegularGridInterpolator
have been changed: evaluations should besignificantly faster, while construction might be slower. If you experience
issues with construction times, you may need to experiment with optional
keyword arguments
solver
andsolver_args
. Previous behavior (fastconstruction, slow evaluations) can be obtained via
"*_legacy"
methods:method="cubic_legacy"
is exactly equivalent tomethod="cubic"
inprevious releases. See
gh-19633
for details.scipy.signal
improvementssampling frequency (
fs
).scipy.sparse
improvementscoo_array
now supports 1D shapes, and has additional 1D support formin
,max
,argmin
, andargmax
. The DOK format now haspreliminary 1D support as well, though only supports simple integer indices
at the time of writing.
pydata/sparse
array inputs toscipy.sparse.csgraph
.dok_array
anddok_matrix
now have proper implementations offromkeys
.csr
andcsc
formats now have improvedsetdiag
performance.scipy.spatial
improvementsvoronoi_plot_2d
now draws Voronoi edges to infinity more clearlywhen the aspect ratio is skewed.
scipy.special
improvementsAMOS
,specfun
, andcdflib
librariesthat the majority of special functions depend on, is ported to Cython/C.
factorialk
now also supports faster, approximatecalculation using
exact=False
.scipy.stats
improvementsscipy.stats.rankdata
andscipy.stats.wilcoxon
have been vectorized,improving their performance and the performance of hypothesis tests that
depend on them.
stats.mannwhitneyu
should now be faster due to a vectorized statisticcalculation, improved caching, improved exploitation of symmetry, and a
memory reduction.
PermutationMethod
support was also added.scipy.stats.mood
now hasnan_policy
andkeepdims
support.scipy.stats.brunnermunzel
now hasaxis
andkeepdims
support.scipy.stats.friedmanchisquare
,scipy.stats.shapiro
,scipy.stats.normaltest
,scipy.stats.skewtest
,scipy.stats.kurtosistest
,scipy.stats.f_oneway
,scipy.stats.alexandergovern
,scipy.stats.combine_pvalues
, andscipy.stats.kstest
have gainedaxis
,nan_policy
andkeepdims
support.scipy.stats.boxcox_normmax
has gained aymax
parameter to allow userspecification of the maximum value of the transformed data.
scipy.stats.vonmises
pdf
method has been extended to supportkappa=0
. Thefit
method is also more performant due to the use ofnon-trivial bounds to solve for
kappa
.moment
calculations forscipy.stats.powerlaw
are now moreaccurate.
fit
methods ofscipy.stats.gamma
(withmethod='mm'
) andscipy.stats.loglaplace
are faster and more reliable.scipy.stats.goodness_of_fit
now supports the use of a customstatistic
provided by the user.
scipy.stats.wilcoxon
now supportsPermutationMethod
, enablingcalculation of accurate p-values in the presence of ties and zeros.
scipy.stats.monte_carlo_test
now has improved robustness in the face ofnumerical noise.
scipy.stats.wasserstein_distance_nd
was introduced to compute theWasserstein-1 distance between two N-D discrete distributions.
Deprecated features
PchipInterpolator
andAkima1DInterpolator
havebeen deprecated and will raise an error in SciPy 1.15.0. If you are trying
to use the real components of the passed array, use
np.real
ony
.Backwards incompatible changes
Other changes
scipy.stats.moment
has been renamed toorder
while maintaining backward compatibility.
Authors
A total of 96 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.
Configuration
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