A heartfelt Thank you Tyler!
On Wed, Jan 4, 2023 at 6:11 AM Tyler Reddy wrote:
>
> Hi all,
>
> On behalf of the SciPy development team, I'm pleased to announce the release
> of SciPy 1.10.0.
>
> Sources and binary wheels can be found at:
> https://pypi.org/project/scipy/
> and at: https://github.com/scipy/scipy/releases/tag/v1.10.0
>
> One of a few ways to install this release with pip:
>
> pip install scipy==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_smoothi
