SciPy 1.18.0 Release Notes#
Note
SciPy 1.18.0 is not released yet!
SciPy 1.18.0 is the culmination of X 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
1.17.x branch, and on adding new features on the main branch.
This release requires Python 3.12-3.14 and NumPy 1.26.4 or greater.
Highlights of this release#
New features#
scipy.cluster improvements#
scipy.interpolate improvements#
scipy.linalg improvements#
scipy.ndimage improvements#
scipy.optimize improvements#
scipy.signal improvements#
The new
whittaker_hendersonimplements Whittaker-Henderson smoothing of a discrete signal. It offers different penalties to control the smoothness as well as automatic selection of the penalty strength via optimization of the restricted maximum likelihood (REML) criterion. It is a valuable alternative for the Savitzky-Golay filtersavgol_filter. In econometrics, Whittaker-Henderson graduation of penalty order 2 is also known as Hodrick-Prescott filter.