- Update to version 1.8.0
* https://scipy.github.io/devdocs/release.1.8.0.html
* 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. 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).
* 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.
* Backwards incompatible changes
- SciPy has raised the minimum compiler versions to GCC 6.3 on
linux and VS2019 on windows. In particular, this means that
SciPy may now use C99 and C++14 features. For more details
see here.
- The result for empty bins for scipy.stats.binned_statistic
with the builtin 'std' metric is now nan, for consistency
with np.std.
- The function scipy.spatial.distance.wminkowski has been
removed. To achieve the same results as before, please use
the minkowski distance function with the (optional) w=
keyword-argument for the given weight.