Gvar

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Modified so that it works with numpy>=2.0.

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- Improvements to gvar.PDFStatistics, including new keywords
fits, errorbars for PDFStatistics.plot_histogram.

- gvar.PDFHistogram deprecated.

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- Fixes default arguments for sample and raniter.

- Move gvar.pxd to correct place.

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- gvar.PDF is completely rewritten to increase functionality for use by the
vegas and lsqfit modules. The changes are incompatible with previous versions.

- Substantial extensions to gvar.PDFStatistics for use in lsqfit.vegas_fit. Adds
a fit to a continuous split-normal distribution to the histogram analysis.
Introduces an incompatibility because the attributes of a PDFStatistics
have different names. Adds plotting capability.

- bd = gvar.BufferDict(d, keys=[k1, k2, ...]) copies d[k] into bd[k]
for every k in keys that is also in d. The results are now copied in the
order specified by keys.

- Fixes a bug in gvar.BufferDict.all_keys that in certain situations included
the same key twice.

- Adds BufferDict.lbatch_buf and BufferDict.rbatch_buf for extracting batch buffers
from batch BufferDicts.

- Fixes bug in gvar.BufferDict.all_keys which caused crashes when keys
were not strings.

- Fixes inconsistencies in gvar.SVD when svdcut=0.0.

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- Adds batch capability to gvar.sample and gvar.raniter so samples can
be created in large batches, which is much more efficient if large
numbers of samples are needed. Also adds similar capability to
gvar.BufferDict when making clones. These changes are useful
for (fast) Monte Carlo simulations: see the section on Sampling GVars
in the tutorial.

- Updates use of numpy's random module to conform with changes in
numpy version 1.17. See the documentation for :func:`gvar.ranseed`.

- New case study (on Creating an Integrator) that illustrates how to
repurpose an existing library function to accommodate GVars.

- The import time for gvar is greatly reduced, especially if numpy has
already been loaded.

- Simplifies gvar.__version__ (no longer uses importlib.metadata, which is buggy
and increases gvar's import time significantly).

- Minor fixes to GVar.set, GVar.__format__, evalcov, evalcov_blocks,
evalcov_blocks_dense, and gvar.dataset.avg_data (when median=unbias=True).

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Introduces more modern string formatting for GVars, including support for
the e, f and g formats used to format floats. For more details see the section
on "Formatting GVars for Printing and Display" in the GVar documentation.
The default format is somewhat different from before.