profitroll/PhotosAPI
profitroll/PhotosAPI
1
0
Fork 0
Code Issues 4 Pull Requests Releases 7 Wiki Activity

Update dependency scipy to ~=1.11.0 #17

Merged
profitroll merged 1 commits from renovate/scipy-1.x into dev 2023-06-26 11:49:40 +03:00
Conversation 0 Commits 1 Files Changed 1 +1 -1
Renovate commented 2023-06-25 21:47:09 +03:00
Collaborator
Copy Link

This PR contains the following updates:

Package Update Change
scipy (source) minor ~=1.10.1 -> ~=1.11.0

Release Notes

scipy/scipy

v1.11.0: SciPy 1.11.0

Compare Source

SciPy 1.11.0 Release Notes

SciPy 1.11.0 is the culmination of 6 months of hard work. It contains
many new features, numerous bug-fixes, improved test coverage and better
documentation. There have been a number of deprecations and API changes
in this release, which are documented below. All users are encouraged to
upgrade to this release, as there are a large number of bug-fixes and
optimizations. Before upgrading, we recommend that users check that
their own code does not use deprecated SciPy functionality (to do so,
run your code with python -Wd and check for DeprecationWarning s).
Our development attention will now shift to bug-fix releases on the
1.11.x branch, and on adding new features on the main branch.

This release requires Python 3.9+ and NumPy 1.21.6 or greater.

For running on PyPy, PyPy3 6.0+ is required.

Highlights of this release

  • Several scipy.sparse array API improvements, including sparse.sparray, a new
    public base class distinct from the older sparse.spmatrix class,
    proper 64-bit index support, and numerous deprecations paving the way to a
    modern sparse array experience.
  • scipy.stats added tools for survival analysis, multiple hypothesis testing,
    sensitivity analysis, and working with censored data.
  • A new function was added for quasi-Monte Carlo integration, and linear
    algebra functions det and lu now accept nD-arrays.
  • An axes argument was added broadly to ndimage functions, facilitating
    analysis of stacked image data.

New features

scipy.integrate improvements

  • Added scipy.integrate.qmc_quad for quasi-Monte Carlo integration.
  • For an even number of points, scipy.integrate.simpson now calculates
    a parabolic segment over the last three points which gives improved
    accuracy over the previous implementation.

scipy.cluster improvements

  • disjoint_set has a new method subset_size for providing the size
    of a particular subset.

scipy.constants improvements

  • The quetta, ronna, ronto, and quecto SI prefixes were added.

scipy.linalg improvements

  • scipy.linalg.det is improved and now accepts nD-arrays.
  • scipy.linalg.lu is improved and now accepts nD-arrays. With the new
    p_indices switch the output permutation argument can be 1D (n,)
    permutation index instead of the full (n, n) array.

scipy.ndimage improvements

  • axes argument was added to rank_filter, percentile_filter,
    median_filter, uniform_filter, minimum_filter,
    maximum_filter, and gaussian_filter, which can be useful for
    processing stacks of image data.

scipy.optimize improvements

  • scipy.optimize.linprog now passes unrecognized options directly to HiGHS.
  • scipy.optimize.root_scalar now uses Newton's method to be used without
    providing fprime and the secant method to be used without a second
    guess.
  • scipy.optimize.lsq_linear now accepts bounds arguments of type
    scipy.optimize.Bounds.
  • scipy.optimize.minimize method='cobyla' now supports simple bound
    constraints.
  • Users can opt into a new callback interface for most methods of
    scipy.optimize.minimize: If the provided callback callable accepts
    a single keyword argument, intermediate_result, scipy.optimize.minimize
    now passes both the current solution and the optimal value of the objective
    function to the callback as an instance of scipy.optimize.OptimizeResult.
    It also allows the user to terminate optimization by raising a
    StopIteration exception from the callback function.
    scipy.optimize.minimize will return normally, and the latest solution
    information is provided in the result object.
  • scipy.optimize.curve_fit now supports an optional nan_policy argument.
  • scipy.optimize.shgo now has parallelization with the workers argument,
    symmetry arguments that can improve performance, class-based design to
    improve usability, and generally improved performance.

scipy.signal improvements

  • istft has an improved warning message when the NOLA condition fails.

scipy.sparse improvements

  • A new public base class scipy.sparse.sparray was introduced, allowing further
    extension of the sparse array API (such as the support for 1-dimensional
    sparse arrays) without breaking backwards compatibility.
    isinstance(x, scipy.sparse.sparray) to select the new sparse array classes,
    while isinstance(x, scipy.sparse.spmatrix) selects only the old sparse
    matrix classes.
  • Division of sparse arrays by a dense array now returns sparse arrays.
  • scipy.sparse.isspmatrix now only returns True for the sparse matrices instances.
    scipy.sparse.issparse now has to be used instead to check for instances of sparse
    arrays or instances of sparse matrices.
  • Sparse arrays constructed with int64 indices will no longer automatically
    downcast to int32.
  • The argmin and argmax methods now return the correct result when explicit
    zeros are present.

scipy.sparse.linalg improvements

  • dividing LinearOperator by a number now returns a
    _ScaledLinearOperator
  • LinearOperator now supports right multiplication by arrays
  • lobpcg should be more efficient following removal of an extraneous
    QR decomposition.

scipy.spatial improvements

  • Usage of new C++ backend for additional distance metrics, the majority of
    which will see substantial performance improvements, though a few minor
    regressions are known. These are focused on distances between boolean
    arrays.

scipy.special improvements

  • The factorial functions factorial, factorial2 and factorialk
    were made consistent in their behavior (in terms of dimensionality,
    errors etc.). Additionally, factorial2 can now handle arrays with
    exact=True, and factorialk can handle arrays.

scipy.stats improvements

New Features

  • scipy.stats.sobol_indices, a method to compute Sobol' sensitivity indices.
  • scipy.stats.dunnett, which performs Dunnett's test of the means of multiple
    experimental groups against the mean of a control group.
  • scipy.stats.ecdf for computing the empirical CDF and complementary
    CDF (survival function / SF) from uncensored or right-censored data. This
    function is also useful for survival analysis / Kaplan-Meier estimation.
  • scipy.stats.logrank to compare survival functions underlying samples.
  • scipy.stats.false_discovery_control for adjusting p-values to control the
    false discovery rate of multiple hypothesis tests using the
    Benjamini-Hochberg or Benjamini-Yekutieli procedures.
  • scipy.stats.CensoredData to represent censored data. It can be used as
    input to the fit method of univariate distributions and to the new
    ecdf function.
  • Filliben's goodness of fit test as method='Filliben' of
    scipy.stats.goodness_of_fit.
  • scipy.stats.ttest_ind has a new method, confidence_interval for
    computing a confidence interval of the difference between means.
  • scipy.stats.MonteCarloMethod, scipy.stats.PermutationMethod, and
    scipy.stats.BootstrapMethod are new classes to configure resampling and/or
    Monte Carlo versions of hypothesis tests. They can currently be used with
    scipy.stats.pearsonr.

Statistical Distributions

  • Added the von-Mises Fisher distribution as scipy.stats.vonmises_fisher.
    This distribution is the most common analogue of the normal distribution
    on the unit sphere.

  • Added the relativistic Breit-Wigner distribution as
    scipy.stats.rel_breitwigner.
    It is used in high energy physics to model resonances.

  • Added the Dirichlet multinomial distribution as
    scipy.stats.dirichlet_multinomial.

  • Improved the speed and precision of several univariate statistical
    distributions.

    • scipy.stats.anglit sf
    • scipy.stats.beta entropy
    • scipy.stats.betaprime cdf, sf, ppf
    • scipy.stats.chi entropy
    • scipy.stats.chi2 entropy
    • scipy.stats.dgamma entropy, cdf, sf, ppf, and isf
    • scipy.stats.dweibull entropy, sf, and isf
    • scipy.stats.exponweib sf and isf
    • scipy.stats.f entropy
    • scipy.stats.foldcauchy sf
    • scipy.stats.foldnorm cdf and sf
    • scipy.stats.gamma entropy
    • scipy.stats.genexpon ppf, isf, rvs
    • scipy.stats.gengamma entropy
    • scipy.stats.geom entropy
    • scipy.stats.genlogistic entropy, logcdf, sf, ppf,
      and isf
    • scipy.stats.genhyperbolic cdf and sf
    • scipy.stats.gibrat sf and isf
    • scipy.stats.gompertz entropy, sf. and isf
    • scipy.stats.halflogistic sf, and isf
    • scipy.stats.halfcauchy sf and isf
    • scipy.stats.halfnorm cdf, sf, and isf
    • scipy.stats.invgamma entropy
    • scipy.stats.invgauss entropy
    • scipy.stats.johnsonsb pdf, cdf, sf, ppf, and isf
    • scipy.stats.johnsonsu pdf, sf, isf, and stats
    • scipy.stats.lognorm fit
    • scipy.stats.loguniform entropy, logpdf, pdf, cdf, ppf,
      and stats
    • scipy.stats.maxwell sf and isf
    • scipy.stats.nakagami entropy
    • scipy.stats.powerlaw sf
    • scipy.stats.powerlognorm logpdf, logsf, sf, and isf
    • scipy.stats.powernorm sf and isf
    • scipy.stats.t entropy, logpdf, and pdf
    • scipy.stats.truncexpon sf, and isf
    • scipy.stats.truncnorm entropy
    • scipy.stats.truncpareto fit
    • scipy.stats.vonmises fit

  • scipy.stats.multivariate_t now has cdf and entropy methods.

  • scipy.stats.multivariate_normal, scipy.stats.matrix_normal, and
    scipy.stats.invwishart now have an entropy method.

Other Improvements

  • scipy.stats.monte_carlo_test now supports multi-sample statistics.
  • scipy.stats.bootstrap can now produce one-sided confidence intervals.
  • scipy.stats.rankdata performance was improved for method=ordinal and
    method=dense.
  • scipy.stats.moment now supports non-central moment calculation.
  • scipy.stats.anderson now supports the weibull_min distribution.
  • scipy.stats.sem and scipy.stats.iqr now support axis, nan_policy,
    and masked array input.

Deprecated features

  • Multi-Ellipsis sparse matrix indexing has been deprecated and will
    be removed in SciPy 1.13.
  • Several methods were deprecated for sparse arrays: asfptype, getrow,
    getcol, get_shape, getmaxprint, set_shape,
    getnnz, and getformat. Additionally, the .A and .H
    attributes were deprecated. Sparse matrix types are not affected.
  • The scipy.linalg functions tri, triu & tril are deprecated and
    will be removed in SciPy 1.13. Users are recommended to use the NumPy
    versions of these functions with identical names.
  • The scipy.signal functions bspline, quadratic & cubic are
    deprecated and will be removed in SciPy 1.13. Users are recommended to use
    scipy.interpolate.BSpline instead.
  • The even keyword of scipy.integrate.simpson is deprecated and will be
    removed in SciPy 1.13.0. Users should leave this as the default as this
    gives improved accuracy compared to the other methods.
  • Using exact=True when passing integers in a float array to factorial
    is deprecated and will be removed in SciPy 1.13.0.
  • float128 and object dtypes are deprecated for scipy.signal.medfilt and
    scipy.signal.order_filter
  • The functions scipy.signal.{lsim2, impulse2, step2} had long been
    deprecated in documentation only. They now raise a DeprecationWarning and
    will be removed in SciPy 1.13.0.
  • Importing window functions directly from scipy.window has been soft
    deprecated since SciPy 1.1.0. They now raise a DeprecationWarning and
    will be removed in SciPy 1.13.0. Users should instead import them from
    scipy.signal.window or use the convenience function
    scipy.signal.get_window.

Backwards incompatible changes

  • The default for the legacy keyword of scipy.special.comb has changed
    from True to False, as announced since its introduction.

Expired Deprecations

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

  • The n keyword has been removed from scipy.stats.moment.
  • The alpha keyword has been removed from scipy.stats.interval.
  • The misspelt gilbrat distribution has been removed (use
    scipy.stats.gibrat).
  • The deprecated spelling of the kulsinski distance metric has been
    removed (use scipy.spatial.distance.kulczynski1).
  • The vertices keyword of scipy.spatial.Delauney.qhull has been removed
    (use simplices).
  • The residual property of scipy.sparse.csgraph.maximum_flow has been
    removed (use flow).
  • The extradoc keyword of scipy.stats.rv_continuous,
    scipy.stats.rv_discrete and scipy.stats.rv_sample has been removed.
  • The sym_pos keyword of scipy.linalg.solve has been removed.
  • The scipy.optimize.minimize function now raises an error for x0 with
    x0.ndim > 1.
  • In scipy.stats.mode, the default value of keepdims is now False,
    and support for non-numeric input has been removed.
  • The function scipy.signal.lsim does not support non-uniform time steps
    anymore.

Other changes

  • Rewrote the source build docs and restructured the contributor guide.
  • Improved support for cross-compiling with meson build system.
  • MyST-NB notebook infrastructure has been added to our documentation.

Authors

  • h-vetinari (69)
  • Oriol Abril-Pla (1) +
  • Tom Adamczewski (1) +
  • Anton Akhmerov (13)
  • Andrey Akinshin (1) +
  • alice (1) +
  • Oren Amsalem (1)
  • Ross Barnowski (13)
  • Christoph Baumgarten (2)
  • Dawson Beatty (1) +
  • Doron Behar (1) +
  • Peter Bell (1)
  • John Belmonte (1) +
  • boeleman (1) +
  • Jack Borchanian (1) +
  • Matt Borland (3) +
  • Jake Bowhay (41)
  • Larry Bradley (1) +
  • Sienna Brent (1) +
  • Matthew Brett (1)
  • Evgeni Burovski (39)
  • Matthias Bussonnier (2)
  • Maria Cann (1) +
  • Alfredo Carella (1) +
  • CJ Carey (34)
  • Hood Chatham (2)
  • Anirudh Dagar (3)
  • Alberto Defendi (1) +
  • Pol del Aguila (1) +
  • Hans Dembinski (1)
  • Dennis (1) +
  • Vinayak Dev (1) +
  • Thomas Duvernay (1)
  • DWesl (4)
  • Stefan Endres (66)
  • Evandro (1) +
  • Tom Eversdijk (2) +
  • Isuru Fernando (1)
  • Franz Forstmayr (4)
  • Joseph Fox-Rabinovitz (1)
  • Stefano Frazzetto (1) +
  • Neil Girdhar (1)
  • Caden Gobat (1) +
  • Ralf Gommers (153)
  • GonVas (1) +
  • Marco Gorelli (1)
  • Brett Graham (2) +
  • Matt Haberland (388)
  • harshvardhan2707 (1) +
  • Alex Herbert (1) +
  • Guillaume Horel (1)
  • Geert-Jan Huizing (1) +
  • Jakob Jakobson (2)
  • Julien Jerphanion (10)
  • jyuv (2)
  • Rajarshi Karmakar (1) +
  • Ganesh Kathiresan (3) +
  • Robert Kern (4)
  • Andrew Knyazev (4)
  • Sergey Koposov (1)
  • Rishi Kulkarni (2) +
  • Eric Larson (1)
  • Zoufiné Lauer-Bare (2) +
  • Antony Lee (3)
  • Gregory R. Lee (8)
  • Guillaume Lemaitre (2) +
  • lilinjie (2) +
  • Yannis Linardos (1) +
  • Christian Lorentzen (5)
  • Loïc Estève (1)
  • Adam Lugowski (1) +
  • Charlie Marsh (2) +
  • Boris Martin (1) +
  • Nicholas McKibben (11)
  • Melissa Weber Mendonça (58)
  • Michał Górny (1) +
  • Jarrod Millman (5)
  • Stefanie Molin (2) +
  • Mark W. Mueller (1) +
  • mustafacevik (1) +
  • Takumasa N (1) +
  • nboudrie (1)
  • Andrew Nelson (112)
  • Nico Schlömer (4)
  • Lysandros Nikolaou (2) +
  • Kyle Oman (1)
  • OmarManzoor (2) +
  • Simon Ott (1) +
  • Geoffrey Oxberry (1) +
  • Geoffrey M. Oxberry (2) +
  • Sravya papaganti (1) +
  • Tirth Patel (2)
  • Ilhan Polat (32)
  • Quentin Barthélemy (1)
  • Matteo Raso (12) +
  • Tyler Reddy (143)
  • Lucas Roberts (1)
  • Pamphile Roy (225)
  • Jordan Rupprecht (1) +
  • Atsushi Sakai (11)
  • Omar Salman (7) +
  • Leo Sandler (1) +
  • Ujjwal Sarswat (3) +
  • Saumya (1) +
  • Daniel Schmitz (79)
  • Henry Schreiner (2) +
  • Dan Schult (8) +
  • Eli Schwartz (6)
  • Tomer Sery (2) +
  • Scott Shambaugh (10) +
  • Gagandeep Singh (1)
  • Ethan Steinberg (6) +
  • stepeos (2) +
  • Albert Steppi (3)
  • Strahinja Lukić (1)
  • Kai Striega (4)
  • suen-bit (1) +
  • Tartopohm (2)
  • Logan Thomas (2) +
  • Jacopo Tissino (1) +
  • Matus Valo (12) +
  • Jacob Vanderplas (2)
  • Christian Veenhuis (1) +
  • Isaac Virshup (3)
  • Stefan van der Walt (14)
  • Warren Weckesser (63)
  • windows-server-2003 (1)
  • Levi John Wolf (3)
  • Nobel Wong (1) +
  • Benjamin Yeh (1) +
  • Rory Yorke (1)
  • Younes (2) +
  • Zaikun ZHANG (1) +
  • Alex Zverianskii (1) +

A total of 134 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 | `~=1.10.1` -> `~=1.11.0` | --- ### Release Notes <details> <summary>scipy/scipy</summary> ### [`v1.11.0`](https://github.com/scipy/scipy/releases/tag/v1.11.0): SciPy 1.11.0 [Compare Source](https://github.com/scipy/scipy/compare/v1.10.1...v1.11.0) # SciPy 1.11.0 Release Notes SciPy `1.11.0` is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with `python -Wd` and check for `DeprecationWarning` s). Our development attention will now shift to bug-fix releases on the 1.11.x branch, and on adding new features on the main branch. This release requires Python `3.9+` and NumPy `1.21.6` or greater. For running on PyPy, PyPy3 `6.0+` is required. # Highlights of this release - Several `scipy.sparse` array API improvements, including `sparse.sparray`, a new public base class distinct from the older `sparse.spmatrix` class, proper 64-bit index support, and numerous deprecations paving the way to a modern sparse array experience. - `scipy.stats` added tools for survival analysis, multiple hypothesis testing, sensitivity analysis, and working with censored data. - A new function was added for quasi-Monte Carlo integration, and linear algebra functions `det` and `lu` now accept nD-arrays. - An `axes` argument was added broadly to `ndimage` functions, facilitating analysis of stacked image data. # New features # `scipy.integrate` improvements - Added `scipy.integrate.qmc_quad` for quasi-Monte Carlo integration. - For an even number of points, `scipy.integrate.simpson` now calculates a parabolic segment over the last three points which gives improved accuracy over the previous implementation. # `scipy.cluster` improvements - `disjoint_set` has a new method `subset_size` for providing the size of a particular subset. # `scipy.constants` improvements - The `quetta`, `ronna`, `ronto`, and `quecto` SI prefixes were added. # `scipy.linalg` improvements - `scipy.linalg.det` is improved and now accepts nD-arrays. - `scipy.linalg.lu` is improved and now accepts nD-arrays. With the new `p_indices` switch the output permutation argument can be 1D `(n,)` permutation index instead of the full `(n, n)` array. # `scipy.ndimage` improvements - `axes` argument was added to `rank_filter`, `percentile_filter`, `median_filter`, `uniform_filter`, `minimum_filter`, `maximum_filter`, and `gaussian_filter`, which can be useful for processing stacks of image data. # `scipy.optimize` improvements - `scipy.optimize.linprog` now passes unrecognized options directly to HiGHS. - `scipy.optimize.root_scalar` now uses Newton's method to be used without providing `fprime` and the `secant` method to be used without a second guess. - `scipy.optimize.lsq_linear` now accepts `bounds` arguments of type `scipy.optimize.Bounds`. - `scipy.optimize.minimize` `method='cobyla'` now supports simple bound constraints. - Users can opt into a new callback interface for most methods of `scipy.optimize.minimize`: If the provided callback callable accepts a single keyword argument, `intermediate_result`, `scipy.optimize.minimize` now passes both the current solution and the optimal value of the objective function to the callback as an instance of `scipy.optimize.OptimizeResult`. It also allows the user to terminate optimization by raising a `StopIteration` exception from the callback function. `scipy.optimize.minimize` will return normally, and the latest solution information is provided in the result object. - `scipy.optimize.curve_fit` now supports an optional `nan_policy` argument. - `scipy.optimize.shgo` now has parallelization with the `workers` argument, symmetry arguments that can improve performance, class-based design to improve usability, and generally improved performance. # `scipy.signal` improvements - `istft` has an improved warning message when the NOLA condition fails. # `scipy.sparse` improvements - A new public base class `scipy.sparse.sparray` was introduced, allowing further extension of the sparse array API (such as the support for 1-dimensional sparse arrays) without breaking backwards compatibility. `isinstance(x, scipy.sparse.sparray)` to select the new sparse array classes, while `isinstance(x, scipy.sparse.spmatrix)` selects only the old sparse matrix classes. - Division of sparse arrays by a dense array now returns sparse arrays. - `scipy.sparse.isspmatrix` now only returns `True` for the sparse matrices instances. `scipy.sparse.issparse` now has to be used instead to check for instances of sparse arrays or instances of sparse matrices. - Sparse arrays constructed with int64 indices will no longer automatically downcast to int32. - The `argmin` and `argmax` methods now return the correct result when explicit zeros are present. # `scipy.sparse.linalg` improvements - dividing `LinearOperator` by a number now returns a `_ScaledLinearOperator` - `LinearOperator` now supports right multiplication by arrays - `lobpcg` should be more efficient following removal of an extraneous QR decomposition. # `scipy.spatial` improvements - Usage of new C++ backend for additional distance metrics, the majority of which will see substantial performance improvements, though a few minor regressions are known. These are focused on distances between boolean arrays. # `scipy.special` improvements - The factorial functions `factorial`, `factorial2` and `factorialk` were made consistent in their behavior (in terms of dimensionality, errors etc.). Additionally, `factorial2` can now handle arrays with `exact=True`, and `factorialk` can handle arrays. # `scipy.stats` improvements ## New Features - `scipy.stats.sobol_indices`, a method to compute Sobol' sensitivity indices. - `scipy.stats.dunnett`, which performs Dunnett's test of the means of multiple experimental groups against the mean of a control group. - `scipy.stats.ecdf` for computing the empirical CDF and complementary CDF (survival function / SF) from uncensored or right-censored data. This function is also useful for survival analysis / Kaplan-Meier estimation. - `scipy.stats.logrank` to compare survival functions underlying samples. - `scipy.stats.false_discovery_control` for adjusting p-values to control the false discovery rate of multiple hypothesis tests using the Benjamini-Hochberg or Benjamini-Yekutieli procedures. - `scipy.stats.CensoredData` to represent censored data. It can be used as input to the `fit` method of univariate distributions and to the new `ecdf` function. - Filliben's goodness of fit test as `method='Filliben'` of `scipy.stats.goodness_of_fit`. - `scipy.stats.ttest_ind` has a new method, `confidence_interval` for computing a confidence interval of the difference between means. - `scipy.stats.MonteCarloMethod`, `scipy.stats.PermutationMethod`, and `scipy.stats.BootstrapMethod` are new classes to configure resampling and/or Monte Carlo versions of hypothesis tests. They can currently be used with `scipy.stats.pearsonr`. ## Statistical Distributions - Added the von-Mises Fisher distribution as `scipy.stats.vonmises_fisher`. This distribution is the most common analogue of the normal distribution on the unit sphere. - Added the relativistic Breit-Wigner distribution as `scipy.stats.rel_breitwigner`. It is used in high energy physics to model resonances. - Added the Dirichlet multinomial distribution as `scipy.stats.dirichlet_multinomial`. - Improved the speed and precision of several univariate statistical distributions. - `scipy.stats.anglit` `sf` - `scipy.stats.beta` `entropy` - `scipy.stats.betaprime` `cdf`, `sf`, `ppf` - `scipy.stats.chi` `entropy` - `scipy.stats.chi2` `entropy` - `scipy.stats.dgamma` `entropy`, `cdf`, `sf`, `ppf`, and `isf` - `scipy.stats.dweibull` `entropy`, `sf`, and `isf` - `scipy.stats.exponweib` `sf` and `isf` - `scipy.stats.f` `entropy` - `scipy.stats.foldcauchy` `sf` - `scipy.stats.foldnorm` `cdf` and `sf` - `scipy.stats.gamma` `entropy` - `scipy.stats.genexpon` `ppf`, `isf`, `rvs` - `scipy.stats.gengamma` `entropy` - `scipy.stats.geom` `entropy` - `scipy.stats.genlogistic` `entropy`, `logcdf`, `sf`, `ppf`, and `isf` - `scipy.stats.genhyperbolic` `cdf` and `sf` - `scipy.stats.gibrat` `sf` and `isf` - `scipy.stats.gompertz` `entropy`, `sf`. and `isf` - `scipy.stats.halflogistic` `sf`, and `isf` - `scipy.stats.halfcauchy` `sf` and `isf` - `scipy.stats.halfnorm` `cdf`, `sf`, and `isf` - `scipy.stats.invgamma` `entropy` - `scipy.stats.invgauss` `entropy` - `scipy.stats.johnsonsb` `pdf`, `cdf`, `sf`, `ppf`, and `isf` - `scipy.stats.johnsonsu` `pdf`, `sf`, `isf`, and `stats` - `scipy.stats.lognorm` `fit` - `scipy.stats.loguniform` `entropy`, `logpdf`, `pdf`, `cdf`, `ppf`, and `stats` - `scipy.stats.maxwell` `sf` and `isf` - `scipy.stats.nakagami` `entropy` - `scipy.stats.powerlaw` `sf` - `scipy.stats.powerlognorm` `logpdf`, `logsf`, `sf`, and `isf` - `scipy.stats.powernorm` `sf` and `isf` - `scipy.stats.t` `entropy`, `logpdf`, and `pdf` - `scipy.stats.truncexpon` `sf`, and `isf` - `scipy.stats.truncnorm` `entropy` - `scipy.stats.truncpareto` `fit` - `scipy.stats.vonmises` `fit` - `scipy.stats.multivariate_t` now has `cdf` and `entropy` methods. - `scipy.stats.multivariate_normal`, `scipy.stats.matrix_normal`, and `scipy.stats.invwishart` now have an `entropy` method. ## Other Improvements - `scipy.stats.monte_carlo_test` now supports multi-sample statistics. - `scipy.stats.bootstrap` can now produce one-sided confidence intervals. - `scipy.stats.rankdata` performance was improved for `method=ordinal` and `method=dense`. - `scipy.stats.moment` now supports non-central moment calculation. - `scipy.stats.anderson` now supports the `weibull_min` distribution. - `scipy.stats.sem` and `scipy.stats.iqr` now support `axis`, `nan_policy`, and masked array input. # Deprecated features - Multi-Ellipsis sparse matrix indexing has been deprecated and will be removed in SciPy 1.13. - Several methods were deprecated for sparse arrays: `asfptype`, `getrow`, `getcol`, `get_shape`, `getmaxprint`, `set_shape`, `getnnz`, and `getformat`. Additionally, the `.A` and `.H` attributes were deprecated. Sparse matrix types are not affected. - The `scipy.linalg` functions `tri`, `triu` & `tril` are deprecated and will be removed in SciPy 1.13. Users are recommended to use the NumPy versions of these functions with identical names. - The `scipy.signal` functions `bspline`, `quadratic` & `cubic` are deprecated and will be removed in SciPy 1.13. Users are recommended to use `scipy.interpolate.BSpline` instead. - The `even` keyword of `scipy.integrate.simpson` is deprecated and will be removed in SciPy 1.13.0. Users should leave this as the default as this gives improved accuracy compared to the other methods. - Using `exact=True` when passing integers in a float array to `factorial` is deprecated and will be removed in SciPy 1.13.0. - float128 and object dtypes are deprecated for `scipy.signal.medfilt` and `scipy.signal.order_filter` - The functions `scipy.signal.{lsim2, impulse2, step2}` had long been deprecated in documentation only. They now raise a DeprecationWarning and will be removed in SciPy 1.13.0. - Importing window functions directly from `scipy.window` has been soft deprecated since SciPy 1.1.0. They now raise a `DeprecationWarning` and will be removed in SciPy 1.13.0. Users should instead import them from `scipy.signal.window` or use the convenience function `scipy.signal.get_window`. # Backwards incompatible changes - The default for the `legacy` keyword of `scipy.special.comb` has changed from `True` to `False`, as announced since its introduction. # Expired Deprecations There is an ongoing effort to follow through on long-standing deprecations. The following previously deprecated features are affected: - The `n` keyword has been removed from `scipy.stats.moment`. - The `alpha` keyword has been removed from `scipy.stats.interval`. - The misspelt `gilbrat` distribution has been removed (use `scipy.stats.gibrat`). - The deprecated spelling of the `kulsinski` distance metric has been removed (use `scipy.spatial.distance.kulczynski1`). - The `vertices` keyword of `scipy.spatial.Delauney.qhull` has been removed (use simplices). - The `residual` property of `scipy.sparse.csgraph.maximum_flow` has been removed (use `flow`). - The `extradoc` keyword of `scipy.stats.rv_continuous`, `scipy.stats.rv_discrete` and `scipy.stats.rv_sample` has been removed. - The `sym_pos` keyword of `scipy.linalg.solve` has been removed. - The `scipy.optimize.minimize` function now raises an error for `x0` with `x0.ndim > 1`. - In `scipy.stats.mode`, the default value of `keepdims` is now `False`, and support for non-numeric input has been removed. - The function `scipy.signal.lsim` does not support non-uniform time steps anymore. # Other changes - Rewrote the source build docs and restructured the contributor guide. - Improved support for cross-compiling with meson build system. - MyST-NB notebook infrastructure has been added to our documentation. # Authors - h-vetinari (69) - Oriol Abril-Pla (1) + - Tom Adamczewski (1) + - Anton Akhmerov (13) - Andrey Akinshin (1) + - alice (1) + - Oren Amsalem (1) - Ross Barnowski (13) - Christoph Baumgarten (2) - Dawson Beatty (1) + - Doron Behar (1) + - Peter Bell (1) - John Belmonte (1) + - boeleman (1) + - Jack Borchanian (1) + - Matt Borland (3) + - Jake Bowhay (41) - Larry Bradley (1) + - Sienna Brent (1) + - Matthew Brett (1) - Evgeni Burovski (39) - Matthias Bussonnier (2) - Maria Cann (1) + - Alfredo Carella (1) + - CJ Carey (34) - Hood Chatham (2) - Anirudh Dagar (3) - Alberto Defendi (1) + - Pol del Aguila (1) + - Hans Dembinski (1) - Dennis (1) + - Vinayak Dev (1) + - Thomas Duvernay (1) - DWesl (4) - Stefan Endres (66) - Evandro (1) + - Tom Eversdijk (2) + - Isuru Fernando (1) - Franz Forstmayr (4) - Joseph Fox-Rabinovitz (1) - Stefano Frazzetto (1) + - Neil Girdhar (1) - Caden Gobat (1) + - Ralf Gommers (153) - GonVas (1) + - Marco Gorelli (1) - Brett Graham (2) + - Matt Haberland (388) - harshvardhan2707 (1) + - Alex Herbert (1) + - Guillaume Horel (1) - Geert-Jan Huizing (1) + - Jakob Jakobson (2) - Julien Jerphanion (10) - jyuv (2) - Rajarshi Karmakar (1) + - Ganesh Kathiresan (3) + - Robert Kern (4) - Andrew Knyazev (4) - Sergey Koposov (1) - Rishi Kulkarni (2) + - Eric Larson (1) - Zoufiné Lauer-Bare (2) + - Antony Lee (3) - Gregory R. Lee (8) - Guillaume Lemaitre (2) + - lilinjie (2) + - Yannis Linardos (1) + - Christian Lorentzen (5) - Loïc Estève (1) - Adam Lugowski (1) + - Charlie Marsh (2) + - Boris Martin (1) + - Nicholas McKibben (11) - Melissa Weber Mendonça (58) - Michał Górny (1) + - Jarrod Millman (5) - Stefanie Molin (2) + - Mark W. Mueller (1) + - mustafacevik (1) + - Takumasa N (1) + - nboudrie (1) - Andrew Nelson (112) - Nico Schlömer (4) - Lysandros Nikolaou (2) + - Kyle Oman (1) - OmarManzoor (2) + - Simon Ott (1) + - Geoffrey Oxberry (1) + - Geoffrey M. Oxberry (2) + - Sravya papaganti (1) + - Tirth Patel (2) - Ilhan Polat (32) - Quentin Barthélemy (1) - Matteo Raso (12) + - Tyler Reddy (143) - Lucas Roberts (1) - Pamphile Roy (225) - Jordan Rupprecht (1) + - Atsushi Sakai (11) - Omar Salman (7) + - Leo Sandler (1) + - Ujjwal Sarswat (3) + - Saumya (1) + - Daniel Schmitz (79) - Henry Schreiner (2) + - Dan Schult (8) + - Eli Schwartz (6) - Tomer Sery (2) + - Scott Shambaugh (10) + - Gagandeep Singh (1) - Ethan Steinberg (6) + - stepeos (2) + - Albert Steppi (3) - Strahinja Lukić (1) - Kai Striega (4) - suen-bit (1) + - Tartopohm (2) - Logan Thomas (2) + - Jacopo Tissino (1) + - Matus Valo (12) + - Jacob Vanderplas (2) - Christian Veenhuis (1) + - Isaac Virshup (3) - Stefan van der Walt (14) - Warren Weckesser (63) - windows-server-2003 (1) - Levi John Wolf (3) - Nobel Wong (1) + - Benjamin Yeh (1) + - Rory Yorke (1) - Younes (2) + - Zaikun ZHANG (1) + - Alex Zverianskii (1) + A total of 134 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. --- - [ ] <!-- rebase-check -->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-debug:eyJjcmVhdGVkSW5WZXIiOiIzNS41NC4wIiwidXBkYXRlZEluVmVyIjoiMzUuNTQuMCJ9-->
Renovate added 1 commit 2023-06-25 21:47:10 +03:00
profitroll merged commit 2ff4623d5f into dev 2023-06-26 11:49:40 +03:00
profitroll deleted branch renovate/scipy-1.x 2023-06-26 11:49:40 +03:00
Sign in to join this conversation.
Reviewers
No reviewers
Labels
Clear labels   
Kind/Breaking

Breaking change that won't be backward compatible

  
Kind/Bug

Something is not working

  
Kind/Documentation

Documentation changes

  
Kind/Enhancement

Improve existing functionality

  
Kind/Feature

New functionality

  
Kind/Security

This is security issue

  
Kind/Testing

Issue or pull request related to testing

  
Priority
Critical
The priority is critical

  
Priority
High
The priority is high

  
Priority
Low
The priority is low

  
Priority
Medium
The priority is medium

  
Reviewed
Confirmed
Issue has been confirmed

  
Reviewed
Duplicate
This issue or pull request already exists

  
Reviewed
Invalid
Invalid issue

  
Reviewed
Won't Fix
This issue won't be fixed

  
Status
Abandoned
Somebody has started to work on this but abandoned work

  
Status
Blocked
Something is blocking this issue or pull request

  
Status
Need More Info
Feedback is required to reproduce issue or to continue work

No Label
Kind/Breaking
Kind/Bug
Kind/Documentation
Kind/Enhancement
Kind/Feature
Kind/Security
Kind/Testing
Priority
Critical
Priority
High
Priority
Low
Priority
Medium
Reviewed
Confirmed
Reviewed
Duplicate
Reviewed
Invalid
Reviewed
Won't Fix
Status
Abandoned
Status
Blocked
Status
Need More Info
Milestone
Clear milestone
No items
No Milestone
Assignees
Clear assignees
No Assignees
1 Participants
Notifications
Due Date
The due date is invalid or out of range. Please use the format 'yyyy-mm-dd'.

No due date set.

Dependencies

No dependencies set.

Reference: profitroll/PhotosAPI#17
No description provided.
Delete Branch "renovate/scipy-1.x"

Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?