Vegas

=============================
Fixes problem when integrating multiple integrands
simultaneously that are very different in magnitude.
Also adds new functionality to vegas.ravg().

==============
- Adds new keywords save and saveall for Integrators. These allow
the integrator to save results in a file automatically at the end of
each iteration. See "Saving Results Automatically" in the tutorial
for more details and examples.

- Pickled integrators now include information about the adaptive
stratified sampling as well as the adaptive importance sampling
(integ.map). This makes for larger files but now captures the
complete state of the integrator. The AdaptiveMap integ.map can
be pickled by itself, in a smaller file, if that is all that is
neeeded.

- Adds new function ravg for manipulating vegas results.

- Added extend method to results returned by vegas Integrators
that allow results from different runs to be merged.

- Bug fixes for pickling of integrators and integration results.
Can nnow use either pickle.dump/load or gvar.dump/load.

- Fixed pickling of Integrator so it handles nstrat properly.

======================
- New implementation for using multiple processors to evaluate expensive
integrands. This new implementation is simpler than using MPI (which is
still supported) and is based on Python's standard multiprocessing library
(so, unlike MPI, does not require additional software beyond what comes
standard with Python). New keyword nproc specifies the number of
processes/processors that are used in parallel to evaluate the integrand.
Assumes Python 3.3 or later.

- Improvements to PDFIntegrator. Can now be pickled which allows it to work
with nproc > 1.

- Multiple processors also supported for AdaptiveMap.adapt_to_samples. This
is useful for very high dimensions or large number of samples.

- Forces Cython to regenerate *.c files when using Python 3.11 or later (deals
with incompatibilities introduced by 3.11).

=======================
Adds a new keyword uses_jac that causes vegas to supply
the vegas map's Jacobian to the integrand. A sample
application is given in the "vegas Jacobian" section of the
Tutorial in the documentation.

==========================
- Fixes installation issue with Python 3.10.

- Bug fix when using very large number of stratifications
per axis (> ninc per axis). The algorithm was operating
sub-optimally in some such situations. Not usually an
issue except for low-dimension integrals.

========================
New implementation of PDFIntegrator which is slightly
incompatible with the previous implementation but
significantly more capable. In particular,
it can now be used with non-Gaussian PDFs. It
also now works with batch integrands, which
lead to big speed increases.

Also includes a further bug fix
when max_nhcube=1.