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Revision 1.73 / (download) - annotate - [select for diffs], Sun Nov 19 17:06:18 2023 UTC (12 days, 11 hours ago) by adam
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py-scipy: updated to 1.11.4 Issues closed for 1.11.4 Contradiction in \`pyproject.toml\` requirements? Doc build fails with Python 3.11 BUG: upcasting of indices dtype from DIA to COO/CSR/BSR arrays BUG: Regression in 1.11.3 can still fail for \`optimize.least_squares\`... BUG: build failure with Xcode 15 linker BUG: DiscreteAliasUrn construction fails with UNURANError for... BUG: problem importing libgfortran.5.dylib on macOS Sonoma BUG: scipy.sparse.lil_matrix division by complex number leads... BUG: can't install scipy on mac m1 with poetry due to incompatible... DOC: doc build failing BUG: Python version constraints in releases causes issues for... Pull requests for 1.11.4 DOC, MAINT: workaround for py311 docs set idx_dtype in sparse dia_array.tocoo MAINT: Prep 1.11.4 BLD: fix up version parsing issue in cythonize.py for setup.py... DOC: stats.chisquare: result object contains attribute 'statistic' BUG: fix pow method for sparrays with power zero MAINT, BUG: stats: update the UNU.RAN submodule with DAU fix BUG: Restore the original behavior of 'trf' from least_squares... BLD: use classic linker on macOS 14 (Sonoma), the new linker... BUG: Fix typecasting problem in scipy.sparse.lil_matrix truediv DOC, MAINT: Bump CircleCI Python version to 3.11 MAINT, REL: unpin Python 1.11.x branch MAINT, BLD: poetry loongarch shims
Revision 1.72 / (download) - annotate - [select for diffs], Sat Oct 28 19:57:11 2023 UTC (4 weeks, 6 days ago) by wiz
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python/wheel.mk: simplify a lot, and switch to 'installer' for installation This follows the recommended bootstrap method (flit_core, build, installer). However, installer installs different files than pip, so update PLISTs for all packages using wheel.mk and bump their PKGREVISIONs.
Revision 1.71 / (download) - annotate - [select for diffs], Sun Oct 15 00:11:19 2023 UTC (6 weeks, 6 days ago) by gutteridge
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py-scipy: fix minimum meson dependency pattern We need to force a minimum with the most recent Python multi-version patching.
Revision 1.70 / (download) - annotate - [select for diffs], Thu Sep 28 15:46:30 2023 UTC (2 months ago) by adam
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py-scipy: updated to 1.11.3 Issues closed for 1.11.3 ------------------------ * BUG: scipy.optimize's trust-constr algorithm hangs when keep-feasible... * freqz: suboptimal performance for worN=2\*\*n+1, include_nyquist=True... * Bug in scipy.sparse.csgraph.min_weight_full_bipartite_matching * BUG: Different results between numpy.fft.rfft and scipy.signal.freqz * Buffer dtype mismatch, expected 'ITYPE_t' but got 'long' * BUG: johnsonsu distribution no longer accepts integer \`b\` parameter * BUG: dev.py has \`distutils\` usage * BUG: mesonpy embeds random path in .pyx files * BUG: Regression in 1.11.2: optimize.least_squares with method='trf'... * BUG: Build fails on latest commit * BUG: scipy.sparse.csgraph.laplacian raises AttributeError on... * BUG: Incorrect sampling from zero rank covariance Pull requests for 1.11.3 ------------------------ * BUG: add infeasibility checks to min_weight_full_bipartite_matching * BUG: Allow johnsonsu parameters to be floats * BUG: sparse.csgraph: Support int64 indices in traversal.pyx * BUG: Fix python3.12 distutils dev.py build * BUG: trust-constr Bounds exclusive * MAINT: should not be using np.float64() on arrays * REL, MAINT: prep for 1.11.3 * BUG: Fixes 19103 by adding back make_strictly_feasible to lsq... * BLD: Avoid absolute pathnames in .pyx files * MAINT: signal: Remove the cval parameter from the private function... * BLD: revert to using published wheels [wheel build] * BUG: Support sparse arrays in scipy.sparse.csgraph.laplacian * MAINT: stats.CovViaEigendecomposition: fix \`_LA\` attribute... * TST: fix \`TestODR.test_implicit\` test failure with tolerance... * BUG: freqz rfft grid fix * MAINT: newton, make sure x0 is an inexact type * BUG: stats: fix build failure due to incorrect Boost policies... * BLD: add float.h include to \`_fpumode.c\`, fixes Clang on Windows... * MAINT: fix libquadmath licence
Revision 1.69 / (download) - annotate - [select for diffs], Sat Sep 2 21:52:49 2023 UTC (2 months, 4 weeks ago) by gutteridge
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py-scipy: reflect meson >= 1.1 tool dependency This looks unorthodox, but this package directly expresses a meson minimum, irrespective of meson_python.
Revision 1.68 / (download) - annotate - [select for diffs], Fri Aug 25 15:19:19 2023 UTC (3 months, 1 week ago) by adam
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py-scipy: updated to 1.11.2 SciPy 1.11.2 Issues closed for 1.11.2 special.jn_zeros(281, 6) hangs Complex matrix square root of positive semi-definite matrix BUG: \`loadmat\` fails to load matlab structures with anonymous... BUG: Floating point CSC with int64 indices doesn't work with... BUG: \`scipy.optimize.minimize\` fails when \`dtype=float32\`... DOC: Broken link to installation instructions in README.rst BUG: Build failure with Cython 3.0.0b3 if scipy is already installed BUG: optimize.least_squares with method='trf' yields wrong result... BUG: cKDtree.query no longer accepts DataFrame as input Spalde error with scipy 1.10: 0-th dimension must be fixed BUG: <Compilation of scipy 1.11 falls with python3.12> BUG: Compilation of scipy 1.10.1 and 1.11.1 fails with Python... Pull requests for 1.11.2 BUG: Fix error in linalg/_matfuncs_sqrtm.py BUG: sparse.linalg: Cast index arrays to intc before calling... Allow johnsonsu parameters to be floats MAINT: stats: fix NumPy DeprecationWarnings REL, MAINT: prep for 1.11.2 DOC: Fix broken link to installation guide in README BUG: Ensure cKDtree.query does not pass Pandas DataFrame to np.isfinite CI, MAINT: 32-bit Pillow pin BLD: copy \`cython_optimize.pxd\` to build dir BUG: make \`L-BFGS-B\` optimizer work with single precision gradient BUG: io/matlab: Fix loading of mat files containing fn handles... BUG: make Bessel-roots function not hang and not skip roots DOC: linking interp1d docstring to tutorial BUG: lsq trf gives x=1e-10 if x0 is near a bound CI/BLD: create cp312 wheels DOC: Fix installation instructions using venv/pip CI: move the musllinux Cirrus job to GHA, optimize other jobs CI: reduce Cirrus CI usage during wheel builds BUG: interpolate: fix spalde with len(c) < len(t) BUG: pass unused xrtol in fmin_bfgs to _minimize_bfgs BLD: rename \`setup.py\` to \`_setup.py\` to signal it should... MAINT: NumPy 1.25.x deprecations MAINT: ensure cobyla objective returns scalar
Revision 1.67 / (download) - annotate - [select for diffs], Wed Jul 12 16:26:29 2023 UTC (4 months, 2 weeks ago) by adam
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py-scipy: updated to 1.11.1 SciPy 1.11.1 Issues closed for 1.11.1 BUG: run method of scipy.odr.ODR class fails when delta0 parameter... BUG: segfault in \`scipy.linalg.lu\` on x86_64 windows and macos... BUG: factorial return type inconsistent for 0-dim arrays determinant of a 1x1 matrix returns an array, not a scalar Licensing concern Pull requests for 1.11.1 BUG: Fix work array construction for various weight shapes. REL, MAINT: prep for 1.11.1 BUG: fix handling for \`factorial(..., exact=False)\` for 0-dim... FIX:linalg.lu:Guard against permute_l out of bound behavior MAINT:linalg.det:Return scalars for singleton inputs MAINT: fix unuran licensing 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`.
Revision 1.66 / (download) - annotate - [select for diffs], Sat Jul 1 08:37:41 2023 UTC (5 months ago) by wiz
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*: restrict py-numpy users to 3.9+ in preparation for update
Revision 1.65 / (download) - annotate - [select for diffs], Fri May 5 14:59:25 2023 UTC (6 months, 4 weeks ago) by adam
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py-scipy: updated to 1.10.1
SciPy 1.10.1 is a bug-fix release with no new features
compared to 1.10.0.
SciPy 1.10.0 Release Notes
==========================
SciPy 1.10.0 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
1.10.x branch, and on adding new features on the main branch.
This release requires Python 3.8+ and NumPy 1.19.5 or greater.
For running on PyPy, PyPy3 6.0+ is required.
**************************
Highlights of this release
**************************
- A new dedicated datasets submodule (`scipy.datasets`) has been added, and is
now preferred over usage of `scipy.misc` for dataset retrieval.
- A new `scipy.interpolate.make_smoothing_spline` function was added. This
function constructs a smoothing cubic spline from noisy data, using the
generalized cross-validation (GCV) criterion to find the tradeoff between
smoothness and proximity to data points.
- `scipy.stats` has three new distributions, two new hypothesis tests, three
new sample statistics, a class for greater control over calculations
involving covariance matrices, and many other enhancements.
************
New features
************
`scipy.datasets` introduction
=============================
- A new dedicated ``datasets`` submodule has been added. The submodules
is meant for datasets that are relevant to other SciPy submodules ands
content (tutorials, examples, tests), as well as contain a curated
set of datasets that are of wider interest. As of this release, all
the datasets from `scipy.misc` have been added to `scipy.datasets`
(and deprecated in `scipy.misc`).
- The submodule is based on [Pooch](https://www.fatiando.org/pooch/latest/)
(a new optional dependency for SciPy), a Python package to simplify fetching
data files. This move will, in a subsequent release, facilitate SciPy
to trim down the sdist/wheel sizes, by decoupling the data files and
moving them out of the SciPy repository, hosting them externally and
downloading them when requested. After downloading the datasets once,
the files are cached to avoid network dependence and repeated usage.
- Added datasets from ``scipy.misc``: `scipy.datasets.face`,
`scipy.datasets.ascent`, `scipy.datasets.electrocardiogram`
- Added download and caching functionality:
- `scipy.datasets.download_all`: a function to download all the `scipy.datasets`
associated files at once.
- `scipy.datasets.clear_cache`: a simple utility function to clear cached dataset
files from the file system.
- ``scipy/datasets/_download_all.py`` can be run as a standalone script for
packaging purposes to avoid any external dependency at build or test time.
This can be used by SciPy packagers (e.g., for Linux distros) which may
have to adhere to rules that forbid downloading sources from external
repositories at package build time.
`scipy.integrate` improvements
==============================
- Added parameter ``complex_func`` to `scipy.integrate.quad`, which can be set
``True`` to integrate a complex integrand.
`scipy.interpolate` improvements
================================
- `scipy.interpolate.interpn` now supports tensor-product interpolation methods
(``slinear``, ``cubic``, ``quintic`` and ``pchip``)
- Tensor-product interpolation methods (``slinear``, ``cubic``, ``quintic`` and
``pchip``) in `scipy.interpolate.interpn` and
`scipy.interpolate.RegularGridInterpolator` now allow values with trailing
dimensions.
- `scipy.interpolate.RegularGridInterpolator` has a new fast path for
``method="linear"`` with 2D data, and ``RegularGridInterpolator`` is now
easier to subclass
- `scipy.interpolate.interp1d` now can take a single value for non-spline
methods.
- A new ``extrapolate`` argument is available to `scipy.interpolate.BSpline.design_matrix`,
allowing extrapolation based on the first and last intervals.
- A new function `scipy.interpolate.make_smoothing_spline` has been added. It is an
implementation of the generalized cross-validation spline smoothing
algorithm. The ``lam=None`` (default) mode of this function is a clean-room
reimplementation of the classic ``gcvspl.f`` Fortran algorithm for
constructing GCV splines.
- A new ``method="pchip"`` mode was aded to
`scipy.interpolate.RegularGridInterpolator`. This mode constructs an
interpolator using tensor products of C1-continuous monotone splines
(essentially, a `scipy.interpolate.PchipInterpolator` instance per
dimension).
`scipy.sparse.linalg` improvements
==================================
- The spectral 2-norm is now available in `scipy.sparse.linalg.norm`.
- The performance of `scipy.sparse.linalg.norm` for the default case (Frobenius
norm) has been improved.
- LAPACK wrappers were added for ``trexc`` and ``trsen``.
- The `scipy.sparse.linalg.lobpcg` algorithm was rewritten, yielding
the following improvements:
- a simple tunable restart potentially increases the attainable
accuracy for edge cases,
- internal postprocessing runs one final exact Rayleigh-Ritz method
giving more accurate and orthonormal eigenvectors,
- output the computed iterate with the smallest max norm of the residual
and drop the history of subsequent iterations,
- remove the check for ``LinearOperator`` format input and thus allow
a simple function handle of a callable object as an input,
- better handling of common user errors with input data, rather
than letting the algorithm fail.
`scipy.linalg` improvements
===========================
- `scipy.linalg.lu_factor` now accepts rectangular arrays instead of being restricted
to square arrays.
`scipy.ndimage` improvements
============================
- The new `scipy.ndimage.value_indices` function provides a time-efficient method to
search for the locations of individual values with an array of image data.
- A new ``radius`` argument is supported by `scipy.ndimage.gaussian_filter1d` and
`scipy.ndimage.gaussian_filter` for adjusting the kernel size of the filter.
`scipy.optimize` improvements
=============================
- `scipy.optimize.brute` now coerces non-iterable/single-value ``args`` into a
tuple.
- `scipy.optimize.least_squares` and `scipy.optimize.curve_fit` now accept
`scipy.optimize.Bounds` for bounds constraints.
- Added a tutorial for `scipy.optimize.milp`.
- Improved the pretty-printing of `scipy.optimize.OptimizeResult` objects.
- Additional options (``parallel``, ``threads``, ``mip_rel_gap``) can now
be passed to `scipy.optimize.linprog` with ``method='highs'``.
`scipy.signal` improvements
===========================
- The new window function `scipy.signal.windows.lanczos` was added to compute a
Lanczos window, also known as a sinc window.
`scipy.sparse.csgraph` improvements
===================================
- the performance of `scipy.sparse.csgraph.dijkstra` has been improved, and
star graphs in particular see a marked performance improvement
`scipy.special` improvements
============================
- The new function `scipy.special.powm1`, a ufunc with signature
``powm1(x, y)``, computes ``x**y - 1``. The function avoids the loss of
precision that can result when ``y`` is close to 0 or when ``x`` is close to
1.
- `scipy.special.erfinv` is now more accurate as it leverages the Boost equivalent under
the hood.
`scipy.stats` improvements
==========================
- Added `scipy.stats.goodness_of_fit`, a generalized goodness-of-fit test for
use with any univariate distribution, any combination of known and unknown
parameters, and several choices of test statistic (Kolmogorov-Smirnov,
Cramer-von Mises, and Anderson-Darling).
- Improved `scipy.stats.bootstrap`: Default method ``'BCa'`` now supports
multi-sample statistics. Also, the bootstrap distribution is returned in the
result object, and the result object can be passed into the function as
parameter ``bootstrap_result`` to add additional resamples or change the
confidence interval level and type.
- Added maximum spacing estimation to `scipy.stats.fit`.
- Added the Poisson means test ("E-test") as `scipy.stats.poisson_means_test`.
- Added new sample statistics.
- Added `scipy.stats.contingency.odds_ratio` to compute both the conditional
and unconditional odds ratios and corresponding confidence intervals for
2x2 contingency tables.
- Added `scipy.stats.directional_stats` to compute sample statistics of
n-dimensional directional data.
- Added `scipy.stats.expectile`, which generalizes the expected value in the
same way as quantiles are a generalization of the median.
- Added new statistical distributions.
- Added `scipy.stats.uniform_direction`, a multivariate distribution to
sample uniformly from the surface of a hypersphere.
- Added `scipy.stats.random_table`, a multivariate distribution to sample
uniformly from m x n contingency tables with provided marginals.
- Added `scipy.stats.truncpareto`, the truncated Pareto distribution.
- Improved the ``fit`` method of several distributions.
- `scipy.stats.skewnorm` and `scipy.stats.weibull_min` now use an analytical
solution when ``method='mm'``, which also serves a starting guess to
improve the performance of ``method='mle'``.
- `scipy.stats.gumbel_r` and `scipy.stats.gumbel_l`: analytical maximum
likelihood estimates have been extended to the cases in which location or
scale are fixed by the user.
- Analytical maximum likelihood estimates have been added for
`scipy.stats.powerlaw`.
- Improved random variate sampling of several distributions.
- Drawing multiple samples from `scipy.stats.matrix_normal`,
`scipy.stats.ortho_group`, `scipy.stats.special_ortho_group`, and
`scipy.stats.unitary_group` is faster.
- The ``rvs`` method of `scipy.stats.vonmises` now wraps to the interval
``[-np.pi, np.pi]``.
- Improved the reliability of `scipy.stats.loggamma` ``rvs`` method for small
values of the shape parameter.
- Improved the speed and/or accuracy of functions of several statistical
distributions.
- Added `scipy.stats.Covariance` for better speed, accuracy, and user control
in multivariate normal calculations.
- `scipy.stats.skewnorm` methods ``cdf``, ``sf``, ``ppf``, and ``isf``
methods now use the implementations from Boost, improving speed while
maintaining accuracy. The calculation of higher-order moments is also
faster and more accurate.
- `scipy.stats.invgauss` methods ``ppf`` and ``isf`` methods now use the
implementations from Boost, improving speed and accuracy.
- `scipy.stats.invweibull` methods ``sf`` and ``isf`` are more accurate for
small probability masses.
- `scipy.stats.nct` and `scipy.stats.ncx2` now rely on the implementations
from Boost, improving speed and accuracy.
- Implemented the ``logpdf`` method of `scipy.stats.vonmises` for reliability
in extreme tails.
- Implemented the ``isf`` method of `scipy.stats.levy` for speed and
accuracy.
- Improved the robustness of `scipy.stats.studentized_range` for large ``df``
by adding an infinite degree-of-freedom approximation.
- Added a parameter ``lower_limit`` to `scipy.stats.multivariate_normal`,
allowing the user to change the integration limit from -inf to a desired
value.
- Improved the robustness of ``entropy`` of `scipy.stats.vonmises` for large
concentration values.
- Enhanced `scipy.stats.gaussian_kde`.
- Added `scipy.stats.gaussian_kde.marginal`, which returns the desired
marginal distribution of the original kernel density estimate distribution.
- The ``cdf`` method of `scipy.stats.gaussian_kde` now accepts a
``lower_limit`` parameter for integrating the PDF over a rectangular region.
- Moved calculations for `scipy.stats.gaussian_kde.logpdf` to Cython,
improving speed.
- The global interpreter lock is released by the ``pdf`` method of
`scipy.stats.gaussian_kde` for improved multithreading performance.
- Replaced explicit matrix inversion with Cholesky decomposition for speed
and accuracy.
- Enhanced the result objects returned by many `scipy.stats` functions
- Added a ``confidence_interval`` method to the result object returned by
`scipy.stats.ttest_1samp` and `scipy.stats.ttest_rel`.
- The `scipy.stats` functions ``combine_pvalues``, ``fisher_exact``,
``chi2_contingency``, ``median_test`` and ``mood`` now return
bunch objects rather than plain tuples, allowing attributes to be
accessed by name.
- Attributes of the result objects returned by ``multiscale_graphcorr``,
``anderson_ksamp``, ``binomtest``, ``crosstab``, ``pointbiserialr``,
``spearmanr``, ``kendalltau``, and ``weightedtau`` have been renamed to
``statistic`` and ``pvalue`` for consistency throughout `scipy.stats`.
Old attribute names are still allowed for backward compatibility.
- `scipy.stats.anderson` now returns the parameters of the fitted
distribution in a `scipy.stats._result_classes.FitResult` object.
- The ``plot`` method of `scipy.stats._result_classes.FitResult` now accepts
a ``plot_type`` parameter; the options are ``'hist'`` (histogram, default),
``'qq'`` (Q-Q plot), ``'pp'`` (P-P plot), and ``'cdf'`` (empirical CDF
plot).
- Kolmogorov-Smirnov tests (e.g. `scipy.stats.kstest`) now return the
location (argmax) at which the statistic is calculated and the variant
of the statistic used.
- Improved the performance of several `scipy.stats` functions.
- Improved the performance of `scipy.stats.cramervonmises_2samp` and
`scipy.stats.ks_2samp` with ``method='exact'``.
- Improved the performance of `scipy.stats.siegelslopes`.
- Improved the performance of `scipy.stats.mstats.hdquantile_sd`.
- Improved the performance of `scipy.stats.binned_statistic_dd` for several
NumPy statistics, and binned statistics methods now support complex data.
- Added the ``scramble`` optional argument to `scipy.stats.qmc.LatinHypercube`.
It replaces ``centered``, which is now deprecated.
- Added a parameter ``optimization`` to all `scipy.stats.qmc.QMCEngine`
subclasses to improve characteristics of the quasi-random variates.
- Added tie correction to `scipy.stats.mood`.
- Added tutorials for resampling methods in `scipy.stats`.
- `scipy.stats.bootstrap`, `scipy.stats.permutation_test`, and
`scipy.stats.monte_carlo_test` now automatically detect whether the provided
``statistic`` is vectorized, so passing the ``vectorized`` argument
explicitly is no longer required to take advantage of vectorized statistics.
- Improved the speed of `scipy.stats.permutation_test` for permutation types
``'samples'`` and ``'pairings'``.
- Added ``axis``, ``nan_policy``, and masked array support to
`scipy.stats.jarque_bera`.
- Added the ``nan_policy`` optional argument to `scipy.stats.rankdata`.
*******************
Deprecated features
*******************
- `scipy.misc` module and all the methods in ``misc`` are deprecated in v1.10
and will be completely removed in SciPy v2.0.0. Users are suggested to
utilize the `scipy.datasets` module instead for the dataset methods.
- `scipy.stats.qmc.LatinHypercube` parameter ``centered`` has been deprecated.
It is replaced by the ``scramble`` argument for more consistency with other
QMC engines.
- `scipy.interpolate.interp2d` class has been deprecated. The docstring of the
deprecated routine lists recommended replacements.
********************
Expired Deprecations
********************
- There is an ongoing effort to follow through on long-standing deprecations.
- The following previously deprecated features are affected:
- Removed ``cond`` & ``rcond`` kwargs in ``linalg.pinv``
- Removed wrappers ``scipy.linalg.blas.{clapack, flapack}``
- Removed ``scipy.stats.NumericalInverseHermite`` and removed ``tol`` & ``max_intervals`` kwargs from ``scipy.stats.sampling.NumericalInverseHermite``
- Removed ``local_search_options`` kwarg frrom ``scipy.optimize.dual_annealing``.
*************
Other changes
*************
- `scipy.stats.bootstrap`, `scipy.stats.permutation_test`, and
`scipy.stats.monte_carlo_test` now automatically detect whether the provided
``statistic`` is vectorized by looking for an ``axis`` parameter in the
signature of ``statistic``. If an ``axis`` parameter is present in
``statistic`` but should not be relied on for vectorized calls, users must
pass option ``vectorized==False`` explicitly.
- `scipy.stats.multivariate_normal` will now raise a ``ValueError`` when the
covariance matrix is not positive semidefinite, regardless of which method
is called.
Revision 1.64 / (download) - annotate - [select for diffs], Wed Jan 25 09:08:20 2023 UTC (10 months ago) by wiz
Branch: MAIN
CVS Tags: pkgsrc-2023Q1-base,
pkgsrc-2023Q1
Changes since 1.63: +1 -3
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py-scipy: remove reference to non-existent file
Revision 1.63 / (download) - annotate - [select for diffs], Mon Oct 24 18:18:15 2022 UTC (13 months, 1 week ago) by adam
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CVS Tags: pkgsrc-2022Q4-base,
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py-scipy: updated to 1.9.3
Issues closed for 1.9.3
scipy.interpolate.UnivariateSpline segfault
BUG: multivariate_normal returns a pdf for values outside its...
BUG: stats: inconsistency in docs and behavior of gmean and hmean
running scipy.interpolate.tests.test_fitpack::test_bisplev_integer_overflow...
test_bisplev_integer_overflow: Segmentation fault (core dumped)
Bug: setting iprint=0 hides all output from fmin_l_bfgs_b, but...
\`scipy.stats.mood\` does not correct for ties
ks_2samp throws \`RuntimeWarning: overflow encountered in double_scalars\`
\`shgo\` error since scipy 1.8.0.dev0+1529.803e52d
Input data validation for RectSphereBivariateSpline
BUG: binom.pmf - RuntimeWarning: divide by zero
BUG: scipy.optimize.minimize: Powell's method function evaluated...
BUG: lombscargle fails if argument is a view
BUG: Possible bug when using winsorize on pandas data instead...
BUG: stats.ttest_ind returns wrong p-values with permutations
odr.Model default meta value fails with __getattr__
BUG: Error in error message for incorrect sample dimension in...
BUG: dimension of isuppz in syevr is mistranslated
BUG: \`KDTree\`'s optional argument \`eps\` seems to have no...
dtype not preserved with operations on sparse arrays
BUG: \`stats.fit\` on \`boltzmann\` expects \`bound\` for \`lambda\`,...
BUG: Small oversight in sparse.linalg.lsmr?
BUG: Build failure due to problems with shebang line in cythoner.py
BUG: stats.rayleigh.fit: returns \`loc\` that is inconsistent...
BUG? Incorrect branch in \`LAMV\` / \`_specfunc.lamv\`
DOC: keepdims in stats.mode is incorrectly documented
Pull requests for 1.9.3
BUG: multivariate_normal returns a pdf for values outside its...
Bug: setting iprint=0 hides all output from fmin_l_bfgs_b, but...
BUG: stats: Reformulate loggamma._rvs to handle c << 1.
BUG: fix out-of-bound evaluations in optimize.minimize, powell...
BUG: fix powell evaluated outside limits
BUG: fix stats.rv_histogram for non-uniform bins
stats.mood: correct for when ties are present
BUG: fix a crash in \`fpknot\`
MAINT: stats: fix _contains_nan on Pandas Series
Fix ttest permutations
MAINT: fix SHGO extra arguments
BUG: Fix error in error message for incorrect sample dimension...
MAINT: stats.ks_2samp: always emit warning when exact method...
BUG: fix syevr series segfault by explicitly specifying operator...
BUG: optimize: Fix differential_evolution error message.
FIX: \`odr.Model\` error with default \`meta\` value
FIX: stats: ignore divide-by-zero warnings from Boost binom impl
MAINT: stats.vonmises: wrap rvs to -pi, pi interval
BUG: eps param no effect fixed
MAINT: Ensure Pythran input for lombscargle are contiguous
Detect integer overflow in bivariate splines in fitpackmodule.c,...
BUG: sparse: Fix indexing sparse matrix with empty index arguments.
FIX: spurious divide error with \`gmean\`
BUG: fix mutable data types as default arguments in \`ord.{Data,RealData}\`
MAINT: stats.boltzmann: correct _shape_info typo
BUG: interpolate: sanity check x and y in make_interp_spline(x,...
MAINT: avoid \`func_data\`, it conflicts with system header on...
BUG: interpolate: work array sizes for RectSphereBivariateSpline
BUG: linalg: Fix the XSLOW test test_sgesdd_lwork_bug_workaround()
MAINT: fix small LSMR problem
MAINT: stats.rayleigh: enforce constraint on location
FIX: special: use intended branching for \`lamv\` implementation
MAINT: stats.rv_discrete.pmf: should be zero at non-integer argument
REL: Prep for SciPy 1.9.3
BUG: special: Fix two XSLOW test failures.
MAINT: update meson.build to make it work on IBM i system
BLD: fix issue with incomplete threads dependency handling
Keepdims incorrectly documneted fix
MAINT: Handle numpy's deprecation of accepting out-of-bound integers.
BLD: fix invalid shebang for build helper script
Revision 1.62 / (download) - annotate - [select for diffs], Mon Oct 10 08:46:13 2022 UTC (13 months, 3 weeks ago) by adam
Branch: MAIN
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py-scipy: updated to 1.9.2 Issues closed for 1.9.2 BUG: 1.9.0rc1: \`OptimizeResult\` not populated when \`optimize.milp\`... BUG: \`sparse.hstack\` returns incorrect result when the stack... BUG: optimize.minimize backwards compatability in scipy 1.9 BUG: using msvc + meson to build scipy --> cl cannot be used... BUG: error from \`scipy.stats.mode\` with \`NaN\`s, \`axis !=... BUG: scipy 1.7.3 wheels on PyPI require numpy<1.23 in contradiction... BUG: ncf_gen::ppf(..) causes segfault Pearson3 PPF does not function properly with negative skew. BUG: OSX-64 Test failure test_ppf_against_tables getting NaN Pull requests for 1.9.2 FIX: Updated dtype resolution in \`_stack_along_minor_axis\` FIX: milp: return feasible solutions if available on time out ENH: cibuildwheel infrastructure MAINT: minimize, restore squeezed ((1.0)) addresses 16898 REL: prep for SciPy 1.9.2 DOC: update version switcher for 1.9.1 and pin theme to 0.9 MAINT: cast \`linear_sum_assignment\` to PyCFunction BLD: use compiler flags in a more portable way MAINT: stats.mode: fix bug with \`axis!=1\`, \`nan_policy='omit'\`,... MAINT: fix NumPy upper bound BLD: fix usage of \`get_install_data\`, which defaults to purelib DOC: Update numpy supported versions for 1.9.2 BLD: fixes for building with MSVC and Intel Fortran Rudimentary test for manylinux_aarch64 with cibuildwheel BLD: make MKL detection a little more robust, add notes on TODOs CI: Update cibuildwheel to 2.10.1 MAINT: stats.pearson3: fix ppf for negative skew BUG: Fix numerical precision error of \`truncnorm.logcdf\` when... FIX: ensure a hold on GIL before raising warnings/errors TST: stats.studentized_range: fix incorrect test MAINT: pyproject.toml: Update build system requirements MAINT: 1.9.2 backports
Revision 1.61 / (download) - annotate - [select for diffs], Wed Oct 5 20:54:31 2022 UTC (13 months, 3 weeks ago) by adam
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py-scipy: updated to 1.9.1 SciPy 1.9.1 is a bug-fix release with no new features compared to 1.9.0. Notably, some important meson build fixes are included. SciPy 1.9.0 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 1.9.x branch, and on adding new features on the main branch. This release requires Python 3.8-3.11 and NumPy 1.18.5 or greater. For running on PyPy, PyPy3 6.0+ is required.
Revision 1.60 / (download) - annotate - [select for diffs], Sat Jul 30 16:13:47 2022 UTC (16 months ago) by he
Branch: MAIN
CVS Tags: pkgsrc-2022Q3-base,
pkgsrc-2022Q3
Changes since 1.59: +2 -2
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math/py-scipy: fix build on NetBSD/powerpc (at least!) In the unuran part, omit defining _ISOC99_SOURCE. I am told that the ieeefp.h header should not be used with _ISOC99_SOURCE. (Its use comes from pyport.h.) Lately I've seen this package fail to build also for aarch64, have not verified that this fixes it, though it's not entirely impossible. Fixes what triggered PR#56892. Bump PKGREVISION.
Revision 1.59 / (download) - annotate - [select for diffs], Tue Jun 28 11:34:45 2022 UTC (17 months ago) by wiz
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*: recursive bump for perl 5.36
Revision 1.58 / (download) - annotate - [select for diffs], Fri May 27 16:59:50 2022 UTC (18 months ago) by tnn
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CVS Tags: pkgsrc-2022Q2-base,
pkgsrc-2022Q2
Changes since 1.57: +2 -1
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py-scipy: disable __builtin_prefetch completely for now It failed with GCC too. There is some bad interaction with py-numpy, probably related to patch-numpy_core_include_numpy_npy__common.h. Unbreak the build until I have time to investigate this.
Revision 1.57 / (download) - annotate - [select for diffs], Fri May 20 12:09:01 2022 UTC (18 months, 1 week ago) by adam
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py-scipy: updated to 1.8.1 SciPy 1.8.1 is a bug-fix release with no new features compared to 1.8.0. Notably, usage of Pythran has been restored for Windows builds/binaries.
Revision 1.56 / (download) - annotate - [select for diffs], Tue May 3 15:14:54 2022 UTC (18 months, 4 weeks ago) by tnn
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py-scipy: work around undefined PLT symbol "log1pl" on NetBSD. Bump.
Revision 1.55 / (download) - annotate - [select for diffs], Sat Apr 9 12:15:31 2022 UTC (19 months, 3 weeks ago) by adam
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py-scipy: updated to 1.8.0 SciPy 1.8.0 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 1.8.x branch, and on adding new features on the master branch. This release requires Python 3.8+ and NumPy 1.17.3 or greater. For running on PyPy, PyPy3 6.0+ is required. ************************** Highlights of this release ************************** - A sparse array API has been added for early testing and feedback; this work is ongoing, and users should expect minor API refinements over the next few releases. - The sparse SVD library PROPACK is now vendored with SciPy, and an interface is exposed via `scipy.sparse.svds` with ``solver='PROPACK'``. It is currently default-off due to potential issues on Windows that we aim to resolve in the next release, but can be optionally enabled at runtime for friendly testing with an environment variable setting of ``USE_PROPACK=1``. - A new `scipy.stats.sampling` submodule that leverages the ``UNU.RAN`` C library to sample from arbitrary univariate non-uniform continuous and discrete distributions - All namespaces that were private but happened to miss underscores in their names have been deprecated.
Revision 1.54 / (download) - annotate - [select for diffs], Tue Jan 4 20:54:17 2022 UTC (22 months, 3 weeks ago) by wiz
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pkgsrc-2022Q1
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*: bump PKGREVISION for egg.mk users They now have a tool dependency on py-setuptools instead of a DEPENDS
Revision 1.53 / (download) - annotate - [select for diffs], Thu Dec 30 13:05:39 2021 UTC (23 months ago) by adam
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Forget about Python 3.6
Revision 1.52 / (download) - annotate - [select for diffs], Tue Nov 30 17:00:44 2021 UTC (2 years ago) by adam
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CVS Tags: pkgsrc-2021Q4-base,
pkgsrc-2021Q4
Changes since 1.51: +3 -2
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py-scipy: updated to 1.7.3 SciPy 1.7.3 is a bug-fix release that provides binary wheels for MacOS arm64 with Python 3.8, 3.9, and 3.10. The MacOS arm64 wheels are only available for MacOS version 12.0 and greater, as explained in Issue 14688, linked below. Issues closed for 1.7.3 ----------------------- * Segmentation fault on import of scipy.integrate on Apple M1 ARM... * BUG: ARPACK's eigsh & OpenBLAS from Apple Silicon M1 (arm64)... * four CI failures on pre-release job * Remaining test failures for macOS arm64 wheel * BUG: Segmentation fault caused by scipy.stats.qmc.qmc.update_discrepancy Pull requests for 1.7.3 ----------------------- * BLD: update pyproject.toml for Python 3.10 changes * BUG: out of bounds indexing in stats.qmc.update_discrepancy * MAINT: skip a few failing tests in \`1.7.x\` for macOS arm64
Revision 1.51 / (download) - annotate - [select for diffs], Sat Nov 6 11:53:13 2021 UTC (2 years ago) by adam
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py-scipy: updated to 1.7.2 SciPy 1.7.2 is a bug-fix release with no new features compared to 1.7.1. Notably, the release includes wheels for Python 3.10, and wheels are now built with a newer version of OpenBLAS, 0.3.17. Python 3.10 wheels are provided for MacOS x86_64 (thin, not universal2 or arm64 at this time), and Windows/Linux 64-bit. Many wheels are now built with newer versions of manylinux, which may require newer versions of pip.
Revision 1.50 / (download) - annotate - [select for diffs], Tue Nov 2 18:51:02 2021 UTC (2 years ago) by adam
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py-scipy: updated to 1.7.1 SciPy 1.7.1 is a bug-fix release with no new features compared to 1.7.0. 1.7.0: A new submodule for quasi-Monte Carlo, scipy.stats.qmc, was added The documentation design was updated to use the same PyData-Sphinx theme as NumPy and other ecosystem libraries. We now vendor and leverage the Boost C++ library to enable numerous improvements for long-standing weaknesses in scipy.stats scipy.stats has six new distributions, eight new (or overhauled) hypothesis tests, a new function for bootstrapping, a class that enables fast random variate sampling and percentile point function evaluation, and many other enhancements. cdist and pdist distance calculations are faster for several metrics, especially weighted cases, thanks to a rewrite to a new C++ backend framework A new class for radial basis function interpolation, RBFInterpolator, was added to address issues with the Rbf class.
Revision 1.49 / (download) - annotate - [select for diffs], Mon May 3 17:55:01 2021 UTC (2 years, 6 months ago) by adam
Branch: MAIN
CVS Tags: pkgsrc-2021Q3-base,
pkgsrc-2021Q3,
pkgsrc-2021Q2-base,
pkgsrc-2021Q2
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py-scipy: updated to 1.6.3 Issues closed for 1.6.3 ----------------------- * Divide by zero in distance.yule * prerelease_deps failures * spatial rotation failure in (1.6.3) wheels repo (ARM64) Pull requests for 1.6.3 ----------------------- * fix the matplotlib warning emitted during builing docs * Divide by zero in yule dissimilarity of constant vectors * deprecated np.typeDict * substitute np.math.factorial with math.factorial * add random seeds in Rotation module
Revision 1.48 / (download) - annotate - [select for diffs], Tue Apr 20 21:39:25 2021 UTC (2 years, 7 months ago) by thor
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math/py-scipy: drop direct BLAS dependency, used via math/py-numpy
Revision 1.47 / (download) - annotate - [select for diffs], Fri Apr 9 14:41:35 2021 UTC (2 years, 7 months ago) by tnn
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revert wrong fix for py-scipy python 3.6 deprecation, fix properly
Revision 1.46 / (download) - annotate - [select for diffs], Tue Apr 6 13:11:17 2021 UTC (2 years, 7 months ago) by nia
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py-scipy: unbreak bulk builds if you mark a package incompatible with python version X, you also need to mark any dependent packages incompatible with version X
Revision 1.45 / (download) - annotate - [select for diffs], Tue Apr 6 09:00:42 2021 UTC (2 years, 7 months ago) by prlw1
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py-scipy: ride update and chmod some files to avoid PKG_DEVELOPER warnings
Revision 1.44 / (download) - annotate - [select for diffs], Mon Apr 5 19:26:07 2021 UTC (2 years, 7 months ago) by tnn
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py-scipy: update to 1.6.2 Highlights of this release scipy.ndimage improvements: Fixes and ehancements to boundary extension modes for interpolation functions. Support for complex-valued inputs in many filtering and interpolation functions. New grid_mode option for scipy.ndimage.zoom to enable results consistent with scikit-image's rescale. scipy.optimize.linprog has fast, new methods for large, sparse problems from the HiGHS library. scipy.stats improvements including new distributions, a new test, and enhancements to existing distributions and tests Deprecated features scipy.spatial changes Calling KDTree.query with k=None to find all neighbours is deprecated. Use KDTree.query_ball_point instead. distance.wminkowski was deprecated; use distance.minkowski and supply weights with the w keyword instead. Backwards incompatible changes Using scipy.fft as a function aliasing numpy.fft.fft was removed after being deprecated in SciPy 1.4.0. As a result, the scipy.fft submodule must be explicitly imported now, in line with other SciPy subpackages. scipy.signal changes The output of decimate, lfilter_zi, lfiltic, sos2tf, and sosfilt_zi have been changed to match numpy.result_type of their inputs. The window function slepian was removed. The frechet_l and frechet_r distributions were removed.
Revision 1.43 / (download) - annotate - [select for diffs], Mon Oct 12 21:52:04 2020 UTC (3 years, 1 month ago) by bacon
Branch: MAIN
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pkgsrc-2021Q1,
pkgsrc-2020Q4-base,
pkgsrc-2020Q4
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math/blas, math/lapack: Install interchangeable BLAS system Install the new interchangeable BLAS system created by Thomas Orgis, currently supporting Netlib BLAS/LAPACK, OpenBLAS, cblas, lapacke, and Apple's Accelerate.framework. This system allows the user to select any BLAS implementation without modifying packages or using package options, by setting PKGSRC_BLAS_TYPES in mk.conf. See mk/blas.buildlink3.mk for details. This commit should not alter behavior of existing packages as the system defaults to Netlib BLAS/LAPACK, which until now has been the only supported implementation. Details: Add new mk/blas.buildlink3.mk for inclusion in dependent packages Install compatible Netlib math/blas and math/lapack packages Update math/blas and math/lapack MAINTAINER approved by adam@ OpenBLAS, cblas, and lapacke will follow in separate commits Update direct dependents to use mk/blas.buildlink3.mk Perform recursive revbump
Revision 1.42 / (download) - annotate - [select for diffs], Tue Aug 4 01:16:19 2020 UTC (3 years, 3 months ago) by tnn
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py-scipy: update to 1.5.2
Done to fix build w/ gfortran 10. "make test" was mostly OK except for
three tests that returned nan where inf was expected ...
Highlights of this release:
wrappers for more than a dozen new LAPACK routines are now available
in scipy.linalg.lapack
Improved support for leveraging 64-bit integer size from linear algebra
backends
addition of the probability distribution for two-sided one-sample
Kolmogorov-Smirnov tests
New features:
Too many; see release notes at github.
Backwards incompatible changes:
The output signatures of ?syevr, ?heevr have been changed from
w, v, info to w, v, m, isuppz, info
The order of output arguments w, v of <sy/he>{gv, gvd, gvx} is
swapped.
The output length of scipy.signal.upfirdn has been corrected, resulting
outputs may now be shorter for some combinations of up/down ratios and
input signal and filter lengths.
scipy.signal.resample now supports a domain keyword argument for
specification of time or frequency domain input.
Revision 1.41 / (download) - annotate - [select for diffs], Tue Apr 28 09:45:27 2020 UTC (3 years, 7 months ago) by adam
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py-scipy: updated to 1.4.1 SciPy 1.4.1 is a bug-fix release with no new features compared to 1.4.0. Importantly, it aims to fix a problem where an older version of pybind11 may cause a segmentation fault when imported alongside incompatible libraries. SciPy 1.4.0 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 1.4.x branch, and on adding new features on the master branch.
Revision 1.40 / (download) - annotate - [select for diffs], Mon Nov 4 17:47:30 2019 UTC (4 years ago) by rillig
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pkgsrc-2019Q4-base,
pkgsrc-2019Q4
Changes since 1.39: +2 -2
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mk: make BROKEN a list of lines, like PKG_FAIL_REASON Packages defined the variable BROKEN inconsistently. Some added quotes, like they are required in PKG_FAIL_REASON, some omitted them. Now all packages behave the same, and pkglint will flag future mistakes.
Revision 1.39 / (download) - annotate - [select for diffs], Sat Nov 2 16:16:22 2019 UTC (4 years, 1 month ago) by rillig
Branch: MAIN
Changes since 1.38: +2 -2
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Diff to previous 1.38 (colored)
math: align variable assignments pkglint -Wall -F --only aligned -r Manual correction in R/Makefile.extension for the MASTER_SITES continuation line.
Revision 1.38 / (download) - annotate - [select for diffs], Fri Jun 14 14:53:29 2019 UTC (4 years, 5 months ago) by adam
Branch: MAIN
CVS Tags: pkgsrc-2019Q3-base,
pkgsrc-2019Q3,
pkgsrc-2019Q2-base,
pkgsrc-2019Q2
Changes since 1.37: +10 -55
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Diff to previous 1.37 (colored)
py-scipy: updated to 1.3.0 SciPy 1.3.0 Release Notes SciPy 1.3.0 is the culmination of 5 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been some 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 1.3.x branch, and on adding new features on the master branch. 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. Highlights of this release - Three new stats functions, a rewrite of pearsonr, and an exact computation of the Kolmogorov-Smirnov two-sample test - A new Cython API for bounded scalar-function root-finders in scipy.optimize - Substantial CSR and CSC sparse matrix indexing performance improvements - Added support for interpolation of rotations with continuous angular rate and acceleration in RotationSpline SciPy 1.2.0 Release Notes SciPy 1.2.0 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 1.2.x branch, and on adding new features on the master branch. This release requires Python 2.7 or 3.4+ and NumPy 1.8.2 or greater. This will be the last SciPy release to support Python 2.7. Consequently, the 1.2.x series will be a long term support (LTS) release; we will backport bug fixes until 1 Jan 2020. For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required. Highlights of this release - 1-D root finding improvements with a new solver, toms748, and a new unified interface, root_scalar - New dual_annealing optimization method that combines stochastic and local deterministic searching - A new optimization algorithm, shgo (simplicial homology global optimization) for derivative free optimization problems - A new category of quaternion-based transformations are available in scipy.spatial.transform
Revision 1.37 / (download) - annotate - [select for diffs], Mon Sep 3 08:36:44 2018 UTC (5 years, 2 months ago) by wiz
Branch: MAIN
CVS Tags: pkgsrc-2019Q1-base,
pkgsrc-2019Q1,
pkgsrc-2018Q4-base,
pkgsrc-2018Q4,
pkgsrc-2018Q3-base,
pkgsrc-2018Q3
Changes since 1.36: +1 -2
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Diff to previous 1.36 (colored)
py-scipy: remove reference to non-existent file
Revision 1.36 / (download) - annotate - [select for diffs], Fri Aug 31 08:09:19 2018 UTC (5 years, 3 months ago) by wiz
Branch: MAIN
Changes since 1.35: +5 -5
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py-scipy: add missing test dependency Update comment about upstream bug reports about test failures.
Revision 1.35 / (download) - annotate - [select for diffs], Mon Aug 20 22:36:21 2018 UTC (5 years, 3 months ago) by szptvlfn
Branch: MAIN
Changes since 1.34: +2 -3
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Diff to previous 1.34 (colored)
BUILD_DEPENDS+= -> TEST_DEPENDS+=
Revision 1.34 / (download) - annotate - [select for diffs], Thu Jul 5 04:31:05 2018 UTC (5 years, 4 months ago) by minskim
Branch: MAIN
Changes since 1.33: +3 -1
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Diff to previous 1.33 (colored)
math/py-scipy: Add -headerpad_max_install_names in linking on Darwin Without the link option, install_name_tool may cause an error.
Revision 1.33 / (download) - annotate - [select for diffs], Mon May 14 06:39:32 2018 UTC (5 years, 6 months ago) by adam
Branch: MAIN
CVS Tags: pkgsrc-2018Q2-base,
pkgsrc-2018Q2
Changes since 1.32: +2 -9
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Diff to previous 1.32 (colored)
py-scipy: updated to 1.1.0 SciPy 1.1.0 is the culmination of 7 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 1.1.x branch, and on adding new features on the master branch.
Revision 1.32 / (download) - annotate - [select for diffs], Sat May 12 21:21:46 2018 UTC (5 years, 6 months ago) by jperkin
Branch: MAIN
Changes since 1.31: +2 -2
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py-scipy: GFORTRAN_VERSION might not be defined. Fixes bulk builds.
Revision 1.31 / (download) - annotate - [select for diffs], Fri May 11 14:18:47 2018 UTC (5 years, 6 months ago) by minskim
Branch: MAIN
Changes since 1.30: +9 -2
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math/py-scipy: Fix PLIST on Darwin with gfortran7
Revision 1.30 / (download) - annotate - [select for diffs], Mon Apr 2 19:52:53 2018 UTC (5 years, 8 months ago) by adam
Branch: MAIN
Changes since 1.29: +2 -2
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py-scipy: updated to 1.0.1 SciPy 1.0.1 is a bug-fix release with no new features compared to 1.0.0. Probably the most important change is a fix for an incompatibility between SciPy 1.0.0 and numpy.f2py in the NumPy master branch.
Revision 1.29 / (download) - annotate - [select for diffs], Thu Nov 2 09:40:29 2017 UTC (6 years, 1 month ago) by adam
Branch: MAIN
CVS Tags: pkgsrc-2018Q1-base,
pkgsrc-2018Q1,
pkgsrc-2017Q4-base,
pkgsrc-2017Q4
Changes since 1.28: +2 -3
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Diff to previous 1.28 (colored)
py-scipy: updated to 1.0.0 Some of the highlights of this release are: * Major build improvements. Windows wheels are available on PyPI for the first time, and continuous integration has been set up on Windows and OS X in addition to Linux. * A set of new ODE solvers and a unified interface to them (scipy.integrate.solve_ivp). * Two new trust region optimizers and a new linear programming method, with improved performance compared to what scipy.optimize offered previously. Many new BLAS and LAPACK functions were wrapped. The BLAS wrappers are now complete.
Revision 1.28 / (download) - annotate - [select for diffs], Thu Sep 28 13:49:19 2017 UTC (6 years, 2 months ago) by wiz
Branch: MAIN
Changes since 1.27: +1 -7
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py-scipy: Remove references to non-existent files
Revision 1.27 / (download) - annotate - [select for diffs], Mon Sep 4 18:08:25 2017 UTC (6 years, 2 months ago) by wiz
Branch: MAIN
CVS Tags: pkgsrc-2017Q3-base,
pkgsrc-2017Q3
Changes since 1.26: +2 -2
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Diff to previous 1.26 (colored)
Follow some redirects.
Revision 1.25.2.1 / (download) - annotate - [select for diffs], Mon Aug 28 19:03:29 2017 UTC (6 years, 3 months ago) by bsiegert
Branch: pkgsrc-2017Q2
Changes since 1.25: +2 -1
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Diff to previous 1.25 (colored) next main 1.26 (colored)
Pullup ticket #5535 - requested by he math/py-scipy: powerpc build fix Revisions pulled up: - math/py-scipy/Makefile 1.26 - math/py-scipy/distinfo 1.13 - math/py-scipy/patches/patch-scipy_special___round.h 1.1 --- Module Name: pkgsrc Committed By: he Date: Tue Aug 22 21:37:28 UTC 2017 Modified Files: pkgsrc/math/py-scipy: Makefile distinfo Added Files: pkgsrc/math/py-scipy/patches: patch-scipy_special___round.h Log Message: Add a patch which fixes an obviously bogus preprocessor conditional; in our case, __STDC_VERSION__ isn't defined when built as C++. The fix isn't completeely right, it insists on <fenv.h> if built as C++. Not entirely unreasonable, and makes this build on NetBSD/powerpc as well, which doesn't like the redefinition of fegetround() and fesetround(). Bump PKGREVISION.
Revision 1.26 / (download) - annotate - [select for diffs], Tue Aug 22 21:37:27 2017 UTC (6 years, 3 months ago) by he
Branch: MAIN
Changes since 1.25: +2 -1
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Diff to previous 1.25 (colored)
Add a patch which fixes an obviously bogus preprocessor conditional; in our case, __STDC_VERSION__ isn't defined when built as C++. The fix isn't completeely right, it insists on <fenv.h> if built as C++. Not entirely unreasonable, and makes this build on NetBSD/powerpc as well, which doesn't like the redefinition of fegetround() and fesetround(). Bump PKGREVISION.
Revision 1.25 / (download) - annotate - [select for diffs], Sat Jun 24 08:19:40 2017 UTC (6 years, 5 months ago) by adam
Branch: MAIN
CVS Tags: pkgsrc-2017Q2-base
Branch point for: pkgsrc-2017Q2
Changes since 1.24: +2 -3
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Diff to previous 1.24 (colored)
SciPy 0.19.1 is a bug-fix release with no new features compared to 0.19.0. The most important change is a fix for a severe memory leak in integrate.quad.
Revision 1.24 / (download) - annotate - [select for diffs], Mon Mar 13 19:42:22 2017 UTC (6 years, 8 months ago) by adam
Branch: MAIN
CVS Tags: pkgsrc-2017Q1-base,
pkgsrc-2017Q1
Changes since 1.23: +4 -3
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Diff to previous 1.23 (colored)
SciPy 0.19.0 is the culmination of 7 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. Moreover, our development attention will now shift to bug-fix releases on the 0.19.x branch, and on adding new features on the master branch.
Revision 1.23 / (download) - annotate - [select for diffs], Wed Jan 25 19:48:50 2017 UTC (6 years, 10 months ago) by adam
Branch: MAIN
Changes since 1.22: +2 -2
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SciPy 0.18.1 is a bug-fix release with no new features compared to 0.18.0.
Revision 1.22 / (download) - annotate - [select for diffs], Sun Jan 8 10:39:47 2017 UTC (6 years, 10 months ago) by maya
Branch: MAIN
Changes since 1.21: +3 -2
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Diff to previous 1.21 (colored)
scipy: correct the test target. this is a temporary workaround, upstream will likely fix it so the previous target works - it is mentioned in their documentation. (scipy issue #6498)
Revision 1.21 / (download) - annotate - [select for diffs], Fri Aug 19 10:54:12 2016 UTC (7 years, 3 months ago) by wiz
Branch: MAIN
CVS Tags: pkgsrc-2016Q4-base,
pkgsrc-2016Q4,
pkgsrc-2016Q3-base,
pkgsrc-2016Q3
Changes since 1.20: +14 -6
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Updated py-scipy to 0.18.0. Test failures reported upstream. ========================== SciPy 0.18.0 Release Notes ========================== .. contents:: SciPy 0.18.0 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. Moreover, our development attention will now shift to bug-fix releases on the 0.19.x branch, and on adding new features on the master branch. This release requires Python 2.7 or 3.4-3.5 and NumPy 1.7.1 or greater. Highlights of this release include: - A new ODE solver for two-point boundary value problems, `scipy.optimize.solve_bvp`. - A new class, `CubicSpline`, for cubic spline interpolation of data. - N-dimensional tensor product polynomials, `scipy.interpolate.NdPPoly`. - Spherical Voronoi diagrams, `scipy.spatial.SphericalVoronoi`. - Support for discrete-time linear systems, `scipy.signal.dlti`. New features ============ `scipy.integrate` improvements ------------------------------ A solver of two-point boundary value problems for ODE systems has been implemented in `scipy.integrate.solve_bvp`. The solver allows for non-separated boundary conditions, unknown parameters and certain singular terms. It finds a C1 continious solution using a fourth-order collocation algorithm. `scipy.interpolate` improvements -------------------------------- Cubic spline interpolation is now available via `scipy.interpolate.CubicSpline`. This class represents a piecewise cubic polynomial passing through given points and C2 continuous. It is represented in the standard polynomial basis on each segment. A representation of n-dimensional tensor product piecewise polynomials is available as the `scipy.interpolate.NdPPoly` class. Univariate piecewise polynomial classes, `PPoly` and `Bpoly`, can now be evaluated on periodic domains. Use ``extrapolate="periodic"`` keyword argument for this. `scipy.fftpack` improvements
Revision 1.20 / (download) - annotate - [select for diffs], Sat Apr 23 22:51:57 2016 UTC (7 years, 7 months ago) by markd
Branch: MAIN
CVS Tags: pkgsrc-2016Q2-base,
pkgsrc-2016Q2
Changes since 1.19: +7 -4
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Diff to previous 1.19 (colored)
Update py-scipy to 0.17.0 SciPy 0.17.0 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. Moreover, our development attention will now shift to bug-fix releases on the 0.17.x branch, and on adding new features on the master branch. This release requires Python 2.6, 2.7 or 3.2-3.5 and NumPy 1.6.2 or greater. Release highlights: * New functions for linear and nonlinear least squares optimization with constraints: scipy.optimize.lsq_linear and scipy.optimize.least_squares * Support for fitting with bounds in scipy.optimize.curve_fit. * Significant improvements to scipy.stats, providing many functions with better handing of inputs which have NaNs or are empty, improved documentation, and consistent behavior between scipy.stats and scipy.stats.mstats. * Significant performance improvements and new functionality in scipy.spatial.cKDTree. SciPy 0.16.0 is the culmination of 7 months of hard work. Highlights of this release include: * A Cython API for BLAS/LAPACK in scipy.linalg * A new benchmark suite. ItãàÑÔ now straightforward to add new benchmarks, and theyãàÑÓe routinely included with performance enhancement PRs. * Support for the second order sections (SOS) format in scipy.signal.
Revision 1.19 / (download) - annotate - [select for diffs], Fri Mar 18 12:54:57 2016 UTC (7 years, 8 months ago) by wiedi
Branch: MAIN
CVS Tags: pkgsrc-2016Q1-base,
pkgsrc-2016Q1
Changes since 1.18: +14 -1
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Diff to previous 1.18 (colored)
Fix "relative library path" on Darwin
Revision 1.18 / (download) - annotate - [select for diffs], Thu Feb 25 15:26:55 2016 UTC (7 years, 9 months ago) by jperkin
Branch: MAIN
Changes since 1.17: +4 -6
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Diff to previous 1.17 (colored)
Use OPSYSVARS.
Revision 1.17 / (download) - annotate - [select for diffs], Fri Apr 17 00:49:50 2015 UTC (8 years, 7 months ago) by wen
Branch: MAIN
CVS Tags: pkgsrc-2015Q4-base,
pkgsrc-2015Q4,
pkgsrc-2015Q3-base,
pkgsrc-2015Q3,
pkgsrc-2015Q2-base,
pkgsrc-2015Q2
Changes since 1.16: +4 -37
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Diff to previous 1.16 (colored)
Update to 0.15.1 Upstream changes: SciPy 0.15.1 is a bug-fix release with no new features compared to 0.15.0. Issues fixed - ------------ * `#4413 <https://github.com/scipy/scipy/pull/4413>`__: BUG: Tests too strict, f2py doesn't have to overwrite this array * `#4417 <https://github.com/scipy/scipy/pull/4417>`__: BLD: avoid using NPY_API_VERSION to check not using deprecated... * `#4418 <https://github.com/scipy/scipy/pull/4418>`__: Restore and deprecate scipy.linalg.calc_work SciPy 0.15.0 Release Notes ========================== .. contents:: SciPy 0.15.0 is the culmination of 6 months of hard work. It contains several 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. Moreover, our development attention will now shift to bug-fix releases on the 0.16.x branch, and on adding new features on the master branch. This release requires Python 2.6, 2.7 or 3.2-3.4 and NumPy 1.5.1 or greater. New features ============ Linear Programming Interface - ---------------------------- The new function `scipy.optimize.linprog` provides a generic linear programming similar to the way `scipy.optimize.minimize` provides a generic interface to nonlinear programming optimizers. Currently the only method supported is *simplex* which provides a two-phase, dense-matrix-based simplex algorithm. Callbacks functions are supported, allowing the user to monitor the progress of the algorithm. Differential evolution, a global optimizer - ------------------------------------------ A new `scipy.optimize.differential_evolution` function has been added to the ``optimize`` module. Differential Evolution is an algorithm used for finding the global minimum of multivariate functions. It is stochastic in nature (does not use gradient methods), and can search large areas of candidate space, but often requires larger numbers of function evaluations than conventional gradient based techniques. ``scipy.signal`` improvements - ----------------------------- The function `scipy.signal.max_len_seq` was added, which computes a Maximum Length Sequence (MLS) signal. ``scipy.integrate`` improvements - -------------------------------- It is now possible to use `scipy.integrate` routines to integrate multivariate ctypes functions, thus avoiding callbacks to Python and providing better performance. ``scipy.linalg`` improvements - ----------------------------- The function `scipy.linalg.orthogonal_procrustes` for solving the procrustes linear algebra problem was added. BLAS level 2 functions ``her``, ``syr``, ``her2`` and ``syr2`` are now wrapped in ``scipy.linalg``. ``scipy.sparse`` improvements - ----------------------------- `scipy.sparse.linalg.svds` can now take a ``LinearOperator`` as its main input. ``scipy.special`` improvements - ------------------------------ Values of ellipsoidal harmonic (i.e. Lame) functions and associated normalization constants can be now computed using ``ellip_harm``, ``ellip_harm_2``, and ``ellip_normal``. New convenience functions ``entr``, ``rel_entr`` ``kl_div``, ``huber``, and ``pseudo_huber`` were added. ``scipy.sparse.csgraph`` improvements - ------------------------------------- Routines ``reverse_cuthill_mckee`` and ``maximum_bipartite_matching`` for computing reorderings of sparse graphs were added. ``scipy.stats`` improvements - ---------------------------- Added a Dirichlet multivariate distribution, `scipy.stats.dirichlet`. The new function `scipy.stats.median_test` computes Mood's median test. The new function `scipy.stats.combine_pvalues` implements Fisher's and Stouffer's methods for combining p-values. `scipy.stats.describe` returns a namedtuple rather than a tuple, allowing users to access results by index or by name. Deprecated features =================== The `scipy.weave` module is deprecated. It was the only module never ported to Python 3.x, and is not recommended to be used for new code - use Cython instead. In order to support existing code, ``scipy.weave`` has been packaged separately: https://github.com/scipy/weave. It is a pure Python package, and can easily be installed with ``pip install weave``. `scipy.special.bessel_diff_formula` is deprecated. It is a private function, and therefore will be removed from the public API in a following release. ``scipy.stats.nanmean``, ``nanmedian`` and ``nanstd`` functions are deprecated in favor of their numpy equivalents. Backwards incompatible changes ============================== scipy.ndimage - ------------- The functions `scipy.ndimage.minimum_positions`, `scipy.ndimage.maximum_positions`` and `scipy.ndimage.extrema` return positions as ints instead of floats. scipy.integrate - --------------- The format of banded Jacobians in `scipy.integrate.ode` solvers is changed. Note that the previous documentation of this feature was erroneous. SciPy 0.14.1 Release Notes ========================== SciPy 0.14.1 is a bug-fix release with no new features compared to 0.14.0. Issues closed - ------------- - - `#3630 <https://github.com/scipy/scipy/issues/3630>`__: NetCDF reading results in a segfault - - `#3631 <https://github.com/scipy/scipy/issues/3631>`__: SuperLU object not working as expected for complex matrices - - `#3733 <https://github.com/scipy/scipy/issues/3733>`__: segfault from map_coordinates - - `#3780 <https://github.com/scipy/scipy/issues/3780>`__: Segfault when using CSR/CSC matrix and uint32/uint64 - - `#3781 <https://github.com/scipy/scipy/pull/3781>`__: BUG: sparse: fix omitted types in sparsetools typemaps - - `#3802 <https://github.com/scipy/scipy/issues/3802>`__: 0.14.0 API breakage: _gen generators are missing from scipy.stats.distributions API - - `#3805 <https://github.com/scipy/scipy/issues/3805>`__: ndimage test failures with numpy 1.10 - - `#3812 <https://github.com/scipy/scipy/issues/3812>`__: == sometimes wrong on csr_matrix - - `#3853 <https://github.com/scipy/scipy/issues/3853>`__: Many scipy.sparse test errors/failures with numpy 1.9.0b2 - - `#4084 <https://github.com/scipy/scipy/pull/4084>`__: fix exception declarations for Cython 0.21.1 compatibility - - `#4093 <https://github.com/scipy/scipy/pull/4093>`__: BUG: fitpack: avoid a memory error in splev(x, tck, der=k) - - `#4104 <https://github.com/scipy/scipy/pull/4104>`__: BUG: Workaround SGEMV segfault in Accelerate (maintenance 0.14.x) - - `#4143 <https://github.com/scipy/scipy/pull/4143>`__: BUG: fix ndimage functions for large data - - `#4149 <https://github.com/scipy/scipy/issues/4149>`__: Bug in expm for integer arrays - - `#4154 <https://github.com/scipy/scipy/issues/4154>`__: Backport gh-4041 for 0.14.1 (Ensure that the 'size' argument of PIL's 'resize' method is a tuple) - - `#4163 <https://github.com/scipy/scipy/issues/4163>`__: Backport #4142 (ZeroDivisionError in scipy.sparse.linalg.lsqr) - - `#4164 <https://github.com/scipy/scipy/issues/4164>`__: Backport gh-4153 (remove use of deprecated numpy API in lib/lapack/ f2py wrapper) - - `#4180 <https://github.com/scipy/scipy/pull/4180>`__: backport pil resize support tuple fix - - `#4168 <https://github.com/scipy/scipy/issues/4168>`__: Lots of arpack test failures on windows 32 bits with numpy 1.9.1 - - `#4203 <https://github.com/scipy/scipy/issues/4203>`__: Matrix multiplication in 0.14.x is more than 10x slower compared... - - `#4218 <https://github.com/scipy/scipy/pull/4218>`__: attempt to make ndimage interpolation compatible with numpy relaxed... - - `#4225 <https://github.com/scipy/scipy/pull/4225>`__: BUG: off-by-one error in PPoly shape checks - - `#4248 <https://github.com/scipy/scipy/pull/4248>`__: BUG: optimize: fix issue with incorrect use of closure for slsqp. SciPy 0.14.0 Release Notes ========================== .. contents:: SciPy 0.14.0 is the culmination of 8 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. Moreover, our development attention will now shift to bug-fix releases on the 0.14.x branch, and on adding new features on the master branch. This release requires Python 2.6, 2.7 or 3.2-3.4 and NumPy 1.5.1 or greater. New features ============ ``scipy.interpolate`` improvements ---------------------------------- A new wrapper function `scipy.interpolate.interpn` for interpolation on regular grids has been added. `interpn` supports linear and nearest-neighbor interpolation in arbitrary dimensions and spline interpolation in two dimensions. Faster implementations of piecewise polynomials in power and Bernstein polynomial bases have been added as `scipy.interpolate.PPoly` and `scipy.interpolate.BPoly`. New users should use these in favor of `scipy.interpolate.PiecewisePolynomial`. `scipy.interpolate.interp1d` now accepts non-monotonic inputs and sorts them. If performance is critical, sorting can be turned off by using the new ``assume_sorted`` keyword. Functionality for evaluation of bivariate spline derivatives in ``scipy.interpolate`` has been added. The new class `scipy.interpolate.Akima1DInterpolator` implements the piecewise cubic polynomial interpolation scheme devised by H. Akima. Functionality for fast interpolation on regular, unevenly spaced grids in arbitrary dimensions has been added as `scipy.interpolate.RegularGridInterpolator` . ``scipy.linalg`` improvements ----------------------------- The new function `scipy.linalg.dft` computes the matrix of the discrete Fourier transform. A condition number estimation function for matrix exponential, `scipy.linalg.expm_cond`, has been added. ``scipy.optimize`` improvements ------------------------------- A set of benchmarks for optimize, which can be run with ``optimize.bench()``, has been added. `scipy.optimize.curve_fit` now has more controllable error estimation via the ``absolute_sigma`` keyword. Support for passing custom minimization methods to ``optimize.minimize()`` and ``optimize.minimize_scalar()`` has been added, currently useful especially for combining ``optimize.basinhopping()`` with custom local optimizer routines. ``scipy.stats`` improvements
Revision 1.16 / (download) - annotate - [select for diffs], Tue Jan 27 06:36:27 2015 UTC (8 years, 10 months ago) by dbj
Branch: MAIN
CVS Tags: pkgsrc-2015Q1-base,
pkgsrc-2015Q1
Changes since 1.15: +4 -1
lines
Diff to previous 1.15 (colored)
specifiy -undefined dynamic-lookup with PKGSRC_FORTRAN=gfortran on Darwin
Revision 1.15 / (download) - annotate - [select for diffs], Wed Feb 12 12:53:56 2014 UTC (9 years, 9 months ago) by obache
Branch: MAIN
CVS Tags: pkgsrc-2014Q4-base,
pkgsrc-2014Q4,
pkgsrc-2014Q3-base,
pkgsrc-2014Q3,
pkgsrc-2014Q2-base,
pkgsrc-2014Q2,
pkgsrc-2014Q1-base,
pkgsrc-2014Q1
Changes since 1.14: +3 -3
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Diff to previous 1.14 (colored)
Using distutils. Bump PKGREVISION.
Revision 1.14 / (download) - annotate - [select for diffs], Sat Jan 25 10:30:13 2014 UTC (9 years, 10 months ago) by wiz
Branch: MAIN
Changes since 1.13: +1 -2
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Diff to previous 1.13 (colored)
Mark packages as not ready for python-3.x where applicable; either because they themselves are not ready or because a dependency isn't. This is annotated by PYTHON_VERSIONS_INCOMPATIBLE= 33 # not yet ported as of x.y.z or PYTHON_VERSIONS_INCOMPATIBLE= 33 # py-foo, py-bar respectively, please use the same style for other packages, and check during updates. Use versioned_dependencies.mk where applicable. Use REPLACE_PYTHON instead of handcoded alternatives, where applicable. Reorder Makefile sections into standard order, where applicable. Remove PYTHON_VERSIONS_INCLUDE_3X lines since that will be default with the next commit. Whitespace cleanups and other nits corrected, where necessary.
Revision 1.13 / (download) - annotate - [select for diffs], Wed Oct 16 19:35:40 2013 UTC (10 years, 1 month ago) by markd
Branch: MAIN
CVS Tags: pkgsrc-2013Q4-base,
pkgsrc-2013Q4
Changes since 1.12: +3 -3
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Diff to previous 1.12 (colored)
Update to 0.12.1 SciPy 0.12.1 is a bug-fix release with no new features compared to 0.12.0. The single issue fixed by this release is a security issue in ``scipy.weave``, which was previously using temporary directories in an insecure manner under certain circumstances.
Revision 1.12 / (download) - annotate - [select for diffs], Sun Apr 14 00:28:53 2013 UTC (10 years, 7 months ago) by markd
Branch: MAIN
CVS Tags: pkgsrc-2013Q3-base,
pkgsrc-2013Q3,
pkgsrc-2013Q2-base,
pkgsrc-2013Q2
Changes since 1.11: +16 -15
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Diff to previous 1.11 (colored)
Update to 0.12.0 Changes many - see doc/release/ in the source tarball for details
Revision 1.11 / (download) - annotate - [select for diffs], Tue Oct 16 08:00:27 2012 UTC (11 years, 1 month ago) by wiz
Branch: MAIN
CVS Tags: pkgsrc-2013Q1-base,
pkgsrc-2013Q1,
pkgsrc-2012Q4-base,
pkgsrc-2012Q4
Changes since 1.10: +93 -1
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Diff to previous 1.10 (colored)
Use REPLACE_PYTHON extensively. Bump PKGREVISION.
Revision 1.10 / (download) - annotate - [select for diffs], Tue Sep 11 23:04:32 2012 UTC (11 years, 2 months ago) by asau
Branch: MAIN
CVS Tags: pkgsrc-2012Q3-base,
pkgsrc-2012Q3
Changes since 1.9: +1 -3
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Diff to previous 1.9 (colored)
"user-destdir" is default these days
Revision 1.9 / (download) - annotate - [select for diffs], Tue Aug 14 20:20:55 2012 UTC (11 years, 3 months ago) by fhajny
Branch: MAIN
Changes since 1.8: +2 -1
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Diff to previous 1.8 (colored)
Fortran objects need -fPIC handling (fixes at least SmartOS)
Revision 1.8 / (download) - annotate - [select for diffs], Thu Dec 22 16:32:04 2011 UTC (11 years, 11 months ago) by joerg
Branch: MAIN
CVS Tags: pkgsrc-2012Q2-base,
pkgsrc-2012Q2,
pkgsrc-2012Q1-base,
pkgsrc-2012Q1,
pkgsrc-2011Q4-base,
pkgsrc-2011Q4
Changes since 1.7: +3 -1
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Diff to previous 1.7 (colored)
Make sure that printf format specifiers are defined for C++ code
Revision 1.7 / (download) - annotate - [select for diffs], Sun Jun 6 02:37:08 2010 UTC (13 years, 5 months ago) by markd
Branch: MAIN
CVS Tags: pkgsrc-2011Q3-base,
pkgsrc-2011Q3,
pkgsrc-2011Q2-base,
pkgsrc-2011Q2,
pkgsrc-2011Q1-base,
pkgsrc-2011Q1,
pkgsrc-2010Q4-base,
pkgsrc-2010Q4,
pkgsrc-2010Q3-base,
pkgsrc-2010Q3,
pkgsrc-2010Q2-base,
pkgsrc-2010Q2
Changes since 1.6: +14 -4
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Diff to previous 1.6 (colored)
Update to scipy 0.7.2 SciPy 0.7.2 is a bug-fix release with no new features compared to 0.7.1. The only change is that all C sources from Cython code have been regenerated with Cython 0.12.1. This fixes the incompatibility between binaries of SciPy 0.7.1 and NumPy 1.4. SciPy 0.7.1 is a bug-fix release with no new features compared to 0.7.0.
Revision 1.6 / (download) - annotate - [select for diffs], Sun Feb 21 15:13:42 2010 UTC (13 years, 9 months ago) by wiz
Branch: MAIN
CVS Tags: pkgsrc-2010Q1-base,
pkgsrc-2010Q1
Changes since 1.5: +2 -1
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Diff to previous 1.5 (colored)
Set LICENSE to modified-bsd.
Revision 1.5 / (download) - annotate - [select for diffs], Thu Dec 3 13:06:55 2009 UTC (14 years ago) by asau
Branch: MAIN
CVS Tags: pkgsrc-2009Q4-base,
pkgsrc-2009Q4
Changes since 1.4: +2 -1
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Diff to previous 1.4 (colored)
Follow f2c/libf2c split: bump revision of all packages that list Fortran in used languages.
Revision 1.4 / (download) - annotate - [select for diffs], Wed Sep 23 09:54:45 2009 UTC (14 years, 2 months ago) by tron
Branch: MAIN
CVS Tags: pkgsrc-2009Q3-base,
pkgsrc-2009Q3
Changes since 1.3: +1 -2
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Diff to previous 1.3 (colored)
Remove "PYTHON_VERSIONS_ACCEPTED= 26 25 24" which is unnecessary after Python 2.3 has been removed from "pkgsrc". Approved by Thomas Klausner.
Revision 1.3 / (download) - annotate - [select for diffs], Sat Jul 25 12:16:45 2009 UTC (14 years, 4 months ago) by markd
Branch: MAIN
Changes since 1.2: +4 -4
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Diff to previous 1.2 (colored)
Update SciPy to 0.7.0 SciPy 0.7.0 is the culmination of 16 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.
Revision 1.2 / (download) - annotate - [select for diffs], Wed Feb 11 22:50:09 2009 UTC (14 years, 9 months ago) by joerg
Branch: MAIN
CVS Tags: pkgsrc-2009Q2-base,
pkgsrc-2009Q2,
pkgsrc-2009Q1-base,
pkgsrc-2009Q1
Changes since 1.1: +2 -2
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Diff to previous 1.1 (colored)
Python 2.3 doesn't work, so remove it.
Revision 1.1.1.1 / (download) - annotate - [select for diffs] (vendor branch), Fri Dec 19 22:14:28 2008 UTC (14 years, 11 months ago) by markd
Branch: TNF
CVS Tags: pkgsrc-base,
pkgsrc-2008Q4-base,
pkgsrc-2008Q4
Changes since 1.1: +0 -0
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Diff to previous 1.1 (colored)
Initial import of py-scipy 0.6.0 SciPy is an open source library of scientific tools for Python. SciPy supplements the popular Numeric module, gathering a variety of high level science and engineering modules together as a single package. SciPy includes modules for graphics and plotting, optimization, integration, special functions, signal and image processing, genetic algorithms, ODE solvers, and others.
Revision 1.1 / (download) - annotate - [select for diffs], Fri Dec 19 22:14:28 2008 UTC (14 years, 11 months ago) by markd
Branch: MAIN
Initial revision