Update dependency scipy to ~=1.13.0 #52

2024-04-02T23:47:17+02:00

Renovate commented

2024-04-02 23:47:17 +02:00

This PR contains the following updates:

Package	Update	Change
scipy (source)	minor	`~=1.12.0` -> `~=1.13.0`

Release Notes

scipy/scipy (scipy)

`v1.13.0`: SciPy 1.13.0

Compare Source

SciPy 1.13.0 Release Notes

SciPy 1.13.0 is the culmination of 3 months of hard work. This
out-of-band release aims to support NumPy 2.0.0, and is backwards
compatible to NumPy 1.22.4. The version of OpenBLAS used to build
the 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

Support for NumPy 2.0.0.
Interactive examples have been added to the documentation, allowing users
to run the examples locally on embedded Jupyterlite notebooks in their
browser.
Preliminary 1D array support for the COO and DOK sparse formats.
Several scipy.stats functions have gained support for additional
axis, nan_policy, and keepdims arguments. scipy.stats also
has several performance and accuracy improvements.

New features

`scipy.integrate` improvements

The terminal attribute of scipy.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 registered
event.

`scipy.io` improvements

scipy.io.wavfile.write has improved dtype input validation.

`scipy.interpolate` improvements

The Modified Akima Interpolation has been added to
interpolate.Akima1DInterpolator, available via the new method
argument.
New method BSpline.insert_knot inserts a knot into a BSpline 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 derivatives
in 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 at xi.
Performance characteristics of tensor-product spline methods of
RegularGridInterpolator have been changed: evaluations should be
significantly faster, while construction might be slower. If you experience
issues with construction times, you may need to experiment with optional
keyword arguments solver and solver_args. Previous behavior (fast
construction, slow evaluations) can be obtained via "*_legacy" methods:
method="cubic_legacy" is exactly equivalent to method="cubic" in
previous releases. See gh-19633 for details.

`scipy.signal` improvements

Many filter design functions now have improved input validation for the
sampling frequency (fs).

`scipy.sparse` improvements

coo_array now supports 1D shapes, and has additional 1D support for
min, max, argmin, and argmax. The DOK format now has
preliminary 1D support as well, though only supports simple integer indices
at the time of writing.
Experimental support has been added for pydata/sparse array inputs to
scipy.sparse.csgraph.
dok_array and dok_matrix now have proper implementations of
fromkeys.
csr and csc formats now have improved setdiag performance.

`scipy.spatial` improvements

voronoi_plot_2d now draws Voronoi edges to infinity more clearly
when the aspect ratio is skewed.

`scipy.special` improvements

All Fortran code, namely, AMOS, specfun, and cdflib libraries
that the majority of special functions depend on, is ported to Cython/C.
The function factorialk now also supports faster, approximate
calculation using exact=False.

`scipy.stats` improvements

scipy.stats.rankdata and scipy.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 statistic
calculation, improved caching, improved exploitation of symmetry, and a
memory reduction. PermutationMethod support was also added.
scipy.stats.mood now has nan_policy and keepdims support.
scipy.stats.brunnermunzel now has axis and keepdims 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, and
scipy.stats.kstest have gained axis, nan_policy and
keepdims support.
scipy.stats.boxcox_normmax has gained a ymax parameter to allow user
specification of the maximum value of the transformed data.
scipy.stats.vonmises pdf method has been extended to support
kappa=0. The fit method is also more performant due to the use of
non-trivial bounds to solve for kappa.
High order moment calculations for scipy.stats.powerlaw are now more
accurate.
The fit methods of scipy.stats.gamma (with method='mm') and
scipy.stats.loglaplace are faster and more reliable.
scipy.stats.goodness_of_fit now supports the use of a custom statistic
provided by the user.
scipy.stats.wilcoxon now supports PermutationMethod, enabling
calculation of accurate p-values in the presence of ties and zeros.
scipy.stats.monte_carlo_test now has improved robustness in the face of
numerical noise.
scipy.stats.wasserstein_distance_nd was introduced to compute the
Wasserstein-1 distance between two N-D discrete distributions.

Deprecated features

Complex dtypes in PchipInterpolator and Akima1DInterpolator have
been 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 on y.
Non-integer values of n together with exact=True are deprecated for
scipy.special.factorial.

Expired Deprecations

There is an ongoing effort to follow through on long-standing deprecations.
The following previously deprecated features are affected:

scipy.signal.{lsim2,impulse2,step2} have been removed in favour of
scipy.signal.{lsim,impulse,step}.
Window functions can no longer be imported from the scipy.signal namespace and
instead should be accessed through either scipy.signal.windows or
scipy.signal.get_window.
scipy.sparse no longer supports multi-Ellipsis indexing
scipy.signal.{bspline,quadratic,cubic} have been removed in favour of alternatives
in scipy.interpolate.
scipy.linalg.tri{,u,l} have been removed in favour of numpy.tri{,u,l}.
Non-integer arrays in scipy.special.factorial with exact=True now raise an
error.
Functions from NumPy's main namespace which were exposed in SciPy's main
namespace, such as numpy.histogram exposed by scipy.histogram, have
been removed from SciPy's main namespace. Please use the functions directly
from numpy. This was originally performed for SciPy 1.12.0 however was missed from
the release notes so is included here for completeness.

Backwards incompatible changes

Other changes

The second argument of scipy.stats.moment has been renamed to order
while maintaining backward compatibility.

Authors

Name (commits)
h-vetinari (50)
acceptacross (1) +
Petteri Aimonen (1) +
Francis Allanah (2) +
Jonas Kock am Brink (1) +
anupriyakkumari (12) +
Aman Atman (2) +
Aaditya Bansal (1) +
Christoph Baumgarten (2)
Sebastian Berg (4)
Nicolas Bloyet (2) +
Matt Borland (1)
Jonas Bosse (1) +
Jake Bowhay (25)
Matthew Brett (1)
Dietrich Brunn (7)
Evgeni Burovski (65)
Matthias Bussonnier (4)
Tim Butters (1) +
Cale (1) +
CJ Carey (5)
Thomas A Caswell (1)
Sean Cheah (44) +
Lucas Colley (97)
com3dian (1)
Gianluca Detommaso (1) +
Thomas Duvernay (1)
DWesl (2)
f380cedric (1) +
fancidev (13) +
Daniel Garcia (1) +
Lukas Geiger (3)
Ralf Gommers (147)
Matt Haberland (81)
Tessa van der Heiden (2) +
Shawn Hsu (1) +
inky (3) +
Jannes Münchmeyer (2) +
Aditya Vidyadhar Kamath (2) +
Agriya Khetarpal (1) +
Andrew Landau (1) +
Eric Larson (7)
Zhen-Qi Liu (1) +
Christian Lorentzen (2)
Adam Lugowski (4)
m-maggi (6) +
Chethin Manage (1) +
Ben Mares (1)
Chris Markiewicz (1) +
Mateusz Sokół (3)
Daniel McCloy (1) +
Melissa Weber Mendonça (6)
Josue Melka (1)
Michał Górny (4)
Juan Montesinos (1) +
Juan F. Montesinos (1) +
Takumasa Nakamura (1)
Andrew Nelson (27)
Praveer Nidamaluri (1)
Yagiz Olmez (5) +
Dimitri Papadopoulos Orfanos (1)
Drew Parsons (1) +
Tirth Patel (7)
Pearu Peterson (1)
Matti Picus (3)
Rambaud Pierrick (1) +
Ilhan Polat (30)
Quentin Barthélemy (1)
Tyler Reddy (117)
Pamphile Roy (10)
Atsushi Sakai (8)
Daniel Schmitz (10)
Dan Schult (17)
Eli Schwartz (4)
Stefanie Senger (1) +
Scott Shambaugh (2)
Kevin Sheppard (2)
sidsrinivasan (4) +
Samuel St-Jean (1)
Albert Steppi (31)
Adam J. Stewart (4)
Kai Striega (3)
Ruikang Sun (1) +
Mike Taves (1)
Nicolas Tessore (3)
Benedict T Thekkel (1) +
Will Tirone (4)
Jacob Vanderplas (2)
Christian Veenhuis (1)
Isaac Virshup (2)
Ben Wallace (1) +
Xuefeng Xu (3)
Xiao Yuan (5)
Irwin Zaid (8)
Elmar Zander (1) +
Mathias Zechmeister (1) +

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

📅 Schedule: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined).

🚦 Automerge: Enabled.

♻ Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.

🔕 Ignore: Close this PR and you won't be reminded about this update again.

If you want to rebase/retry this PR, check this box

This PR has been generated by Renovate Bot.

This PR contains the following updates: | Package | Update | Change | |---|---|---| | [scipy](https://scipy.org/) ([source](https://github.com/scipy/scipy)) | minor | `~=1.12.0` -> `~=1.13.0` | --- ### Release Notes <details> <summary>scipy/scipy (scipy)</summary> ### [`v1.13.0`](https://github.com/scipy/scipy/releases/tag/v1.13.0): SciPy 1.13.0 [Compare Source](https://github.com/scipy/scipy/compare/v1.12.0...v1.13.0) # SciPy 1.13.0 Release Notes SciPy `1.13.0` is the culmination of 3 months of hard work. This out-of-band release aims to support NumPy `2.0.0`, and is backwards compatible to NumPy `1.22.4`. The version of OpenBLAS used to build the 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 - Support for NumPy `2.0.0`. - Interactive examples have been added to the documentation, allowing users to run the examples locally on embedded Jupyterlite notebooks in their browser. - Preliminary 1D array support for the COO and DOK sparse formats. - Several `scipy.stats` functions have gained support for additional `axis`, `nan_policy`, and `keepdims` arguments. `scipy.stats` also has several performance and accuracy improvements. # New features # `scipy.integrate` improvements - The `terminal` attribute of `scipy.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 registered event. # `scipy.io` improvements - `scipy.io.wavfile.write` has improved `dtype` input validation. # `scipy.interpolate` improvements - The Modified Akima Interpolation has been added to `interpolate.Akima1DInterpolator`, available via the new `method` argument. - New method `BSpline.insert_knot` inserts a knot into a `BSpline` 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 derivatives in 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` at `xi`. - Performance characteristics of tensor-product spline methods of `RegularGridInterpolator` have been changed: evaluations should be significantly faster, while construction might be slower. If you experience issues with construction times, you may need to experiment with optional keyword arguments `solver` and `solver_args`. Previous behavior (fast construction, slow evaluations) can be obtained via `"*_legacy"` methods: `method="cubic_legacy"` is exactly equivalent to `method="cubic"` in previous releases. See `gh-19633` for details. # `scipy.signal` improvements - Many filter design functions now have improved input validation for the sampling frequency (`fs`). # `scipy.sparse` improvements - `coo_array` now supports 1D shapes, and has additional 1D support for `min`, `max`, `argmin`, and `argmax`. The DOK format now has preliminary 1D support as well, though only supports simple integer indices at the time of writing. - Experimental support has been added for `pydata/sparse` array inputs to `scipy.sparse.csgraph`. - `dok_array` and `dok_matrix` now have proper implementations of `fromkeys`. - `csr` and `csc` formats now have improved `setdiag` performance. # `scipy.spatial` improvements - `voronoi_plot_2d` now draws Voronoi edges to infinity more clearly when the aspect ratio is skewed. # `scipy.special` improvements - All Fortran code, namely, `AMOS`, `specfun`, and `cdflib` libraries that the majority of special functions depend on, is ported to Cython/C. - The function `factorialk` now also supports faster, approximate calculation using `exact=False`. # `scipy.stats` improvements - `scipy.stats.rankdata` and `scipy.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 statistic calculation, improved caching, improved exploitation of symmetry, and a memory reduction. `PermutationMethod` support was also added. - `scipy.stats.mood` now has `nan_policy` and `keepdims` support. - `scipy.stats.brunnermunzel` now has `axis` and `keepdims` 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`, and `scipy.stats.kstest` have gained `axis`, `nan_policy` and `keepdims` support. - `scipy.stats.boxcox_normmax` has gained a `ymax` parameter to allow user specification of the maximum value of the transformed data. - `scipy.stats.vonmises` `pdf` method has been extended to support `kappa=0`. The `fit` method is also more performant due to the use of non-trivial bounds to solve for `kappa`. - High order `moment` calculations for `scipy.stats.powerlaw` are now more accurate. - The `fit` methods of `scipy.stats.gamma` (with `method='mm'`) and `scipy.stats.loglaplace` are faster and more reliable. - `scipy.stats.goodness_of_fit` now supports the use of a custom `statistic` provided by the user. - `scipy.stats.wilcoxon` now supports `PermutationMethod`, enabling calculation of accurate p-values in the presence of ties and zeros. - `scipy.stats.monte_carlo_test` now has improved robustness in the face of numerical noise. - `scipy.stats.wasserstein_distance_nd` was introduced to compute the Wasserstein-1 distance between two N-D discrete distributions. # Deprecated features - Complex dtypes in `PchipInterpolator` and `Akima1DInterpolator` have been 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` on `y`. - Non-integer values of `n` together with `exact=True` are deprecated for `scipy.special.factorial`. # Expired Deprecations There is an ongoing effort to follow through on long-standing deprecations. The following previously deprecated features are affected: - `scipy.signal.{lsim2,impulse2,step2}` have been removed in favour of `scipy.signal.{lsim,impulse,step}`. - Window functions can no longer be imported from the `scipy.signal` namespace and instead should be accessed through either `scipy.signal.windows` or `scipy.signal.get_window`. - `scipy.sparse` no longer supports multi-Ellipsis indexing - `scipy.signal.{bspline,quadratic,cubic}` have been removed in favour of alternatives in `scipy.interpolate`. - `scipy.linalg.tri{,u,l}` have been removed in favour of `numpy.tri{,u,l}`. - Non-integer arrays in `scipy.special.factorial` with `exact=True` now raise an error. - Functions from NumPy's main namespace which were exposed in SciPy's main namespace, such as `numpy.histogram` exposed by `scipy.histogram`, have been removed from SciPy's main namespace. Please use the functions directly from `numpy`. This was originally performed for SciPy 1.12.0 however was missed from the release notes so is included here for completeness. # Backwards incompatible changes # Other changes - The second argument of `scipy.stats.moment` has been renamed to `order` while maintaining backward compatibility. # Authors - Name (commits) - h-vetinari (50) - acceptacross (1) + - Petteri Aimonen (1) + - Francis Allanah (2) + - Jonas Kock am Brink (1) + - anupriyakkumari (12) + - Aman Atman (2) + - Aaditya Bansal (1) + - Christoph Baumgarten (2) - Sebastian Berg (4) - Nicolas Bloyet (2) + - Matt Borland (1) - Jonas Bosse (1) + - Jake Bowhay (25) - Matthew Brett (1) - Dietrich Brunn (7) - Evgeni Burovski (65) - Matthias Bussonnier (4) - Tim Butters (1) + - Cale (1) + - CJ Carey (5) - Thomas A Caswell (1) - Sean Cheah (44) + - Lucas Colley (97) - com3dian (1) - Gianluca Detommaso (1) + - Thomas Duvernay (1) - DWesl (2) - f380cedric (1) + - fancidev (13) + - Daniel Garcia (1) + - Lukas Geiger (3) - Ralf Gommers (147) - Matt Haberland (81) - Tessa van der Heiden (2) + - Shawn Hsu (1) + - inky (3) + - Jannes Münchmeyer (2) + - Aditya Vidyadhar Kamath (2) + - Agriya Khetarpal (1) + - Andrew Landau (1) + - Eric Larson (7) - Zhen-Qi Liu (1) + - Christian Lorentzen (2) - Adam Lugowski (4) - m-maggi (6) + - Chethin Manage (1) + - Ben Mares (1) - Chris Markiewicz (1) + - Mateusz Sokół (3) - Daniel McCloy (1) + - Melissa Weber Mendonça (6) - Josue Melka (1) - Michał Górny (4) - Juan Montesinos (1) + - Juan F. Montesinos (1) + - Takumasa Nakamura (1) - Andrew Nelson (27) - Praveer Nidamaluri (1) - Yagiz Olmez (5) + - Dimitri Papadopoulos Orfanos (1) - Drew Parsons (1) + - Tirth Patel (7) - Pearu Peterson (1) - Matti Picus (3) - Rambaud Pierrick (1) + - Ilhan Polat (30) - Quentin Barthélemy (1) - Tyler Reddy (117) - Pamphile Roy (10) - Atsushi Sakai (8) - Daniel Schmitz (10) - Dan Schult (17) - Eli Schwartz (4) - Stefanie Senger (1) + - Scott Shambaugh (2) - Kevin Sheppard (2) - sidsrinivasan (4) + - Samuel St-Jean (1) - Albert Steppi (31) - Adam J. Stewart (4) - Kai Striega (3) - Ruikang Sun (1) + - Mike Taves (1) - Nicolas Tessore (3) - Benedict T Thekkel (1) + - Will Tirone (4) - Jacob Vanderplas (2) - Christian Veenhuis (1) - Isaac Virshup (2) - Ben Wallace (1) + - Xuefeng Xu (3) - Xiao Yuan (5) - Irwin Zaid (8) - Elmar Zander (1) + - Mathias Zechmeister (1) + 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. </details> --- ### Configuration 📅 **Schedule**: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined). 🚦 **Automerge**: Enabled. ♻ **Rebasing**: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox. 🔕 **Ignore**: Close this PR and you won't be reminded about this update again. --- - [ ] If you want to rebase/retry this PR, check this box --- This PR has been generated by [Renovate Bot](https://github.com/renovatebot/renovate).

Renovate scheduled this pull request to auto merge when all checks succeed 2024-04-02 23:47:18 +02:00

profitroll commented

2024-04-03 22:27:23 +02:00

Further testing is required, as this new version may contain breaking changes.

profitroll added the

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Need More Info

label 2024-04-03 22:27:52 +02:00

Renovate force-pushed renovate/scipy-1.x from 9c66b3cefa to 508984442b

2024-04-19 21:09:03 +02:00

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profitroll merged commit adcf25ff15 into dev

2024-04-21 16:17:17 +02:00

profitroll deleted branch renovate/scipy-1.x

2024-04-21 16:17:18 +02:00

profitroll referenced this issue from a commit

2024-04-21 16:17:18 +02:00

Merge pull request 'Update dependency scipy to ~=1.13.0' (#52) from renovate/scipy-1.x into dev

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Reference: profitroll/PhotosAPI#52

Update dependency scipy to ~=1.13.0 #52

Release Notes

v1.13.0: SciPy 1.13.0

SciPy 1.13.0 Release Notes

Highlights of this release

New features

scipy.integrate improvements

scipy.io improvements

scipy.interpolate improvements

scipy.signal improvements

scipy.sparse improvements

scipy.spatial improvements

scipy.special improvements

scipy.stats improvements