Gvar

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- New setup.py that: a) does not require cython; b) works even if
numpy is not installed (by installing numpy before it is required).
Previous versions of setup.py did not work unless cython and numpy
were already installed. This version uses setuptools to install
numpy and, optionally, cython before they are used to build gvar.
cython is not used by default; to turn it on set USE_CYTHON=True in
setup.py.

- Fixed formatting bug in gvar.fmt_errorbudget().

- Modifications to support hosting documentation by ReadTheDocs.

- Minor bug (error message) in gvar.Histogram.

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Fixes typo in gvar.correlate that makes gvar compilation fail on some
machines.

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json support in gvar.dump, gvar.load, etc was not quite right in v8.3.1 and so
was unreliable. The situation is improved here. Note that these functions are
meant to extend and improve on gvar.BufferDict.dump, etc which functions are
still available but will get limited support going forward.

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A very minor updata:

- gvar.dump, gvar.load, etc can now use json instead of pickle
for serializing collections of GVars. pickle is probably more
robust.

- bug fix in evalcorr to deal with very rare condition that caused
the routine to crash (condition caused by std dev = 0.0 for a GVar).

======================
Bug fixes and a little bit of new functionality.

- A new utility gvar.dataset.svd_diagnosis() analyzes a dataset
containing Monte Carlo results for multiple variables to determine
whether or not an SVD cut is needed for the correlation matrix
describing these variables. The smallest eigenvalues of a correlation
matrix can be badly underestimated when the number of
Monte Carlo samples is insufficiently large. This makes the correlation
matrix more singular than it should be, which can lead to problems,
for example, when trying to fit the correlated data. This utility
estimates the size of the svd cut to use on the correlation matrix.
A new case study illustrates its use.

- Fix plotting by PDFHistogram.make_plot to account for (incompatible)
change introduced in matplotlib-2.0.0's pyplot.bar.

- gvar.dataset.bin_data(xx) returns a gvar.dataset.Dataset ordered
dictionary if xx is a dictionary.

- pickle now works for (the mostly hidden classes) gvar.svec and gvar.smat
and therefore for x.internaldata where x is a GVar. Tricky to use
internaldata, however.

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- Slightly faster memory allocation for GVars.

- Fixed problems in gvar.BufferDict caused by changes in Python's
dictionaries starting at Python 3.5. The new code has been tested
(and should work) with Python 3.4, 3.5 and 3.6.