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Total project reorganization, master now includes Python wrappers
Intermediate work in getting serial FFT's.
Finished building serial FFT version.
Fixed issue with MPI + serial HDF5 compiles + MPI disabled run. Mainly it was due to not setting cart_size on the domain when MPI was disabled at runtime.
Updated Python wrappers to allow for serial FFT's
Fixed a bug introduced in last commit, which broke MPI proc_sizes
Fixed a bug in the sampling behavior

The sampling procedure previously enforced periodic BC's on the input
coordinates. This turned out to be problematic when the sample was very
near the domain boundary, causing the result of indexatposition to be
Nx_global + 2*Ng - 1 instead of Ng, which is way out of bounds.

This commit changes the logic of the setsamplecoords function to reject
a set of samples containing an off-bounds point, having a null effect on
the data structure and returning an error code other than zero.
Adds a histogram getname method to the cow C API
Cleanup

Removes unnecessary calls in the C API histogram_populate function. Also
removes the VectorField3d.hist_magnitude function accidentally added
prematurely in the previous commit.
Adds dot3 and cross transforms
Fixes a problem in the C programs, they forgot to call seal
Introduces the srhdpack source file

Contains a more general version of the pair-wise relative Lorentz factor
procedure. The srhdpack source should end up as its own Python module as
part of cowpy.
Project reorganization

This commit introduces an additional C extension just for SRHD
analysis. It reorganizes the python directory to adhere better to Python
package standard layouts. Shared object files go in the cowpy.capi
module.
Fixes a missing printf parameter in srhdpack.c
Building real test for sampling

The sampling procedure acts strangely when run in parallel. There is a
new tests directory, and a program called sample.py which is carefully
looking at what might cause the problem.
Added a cow_domain_barrier
Improvements to pair sampling tests
Adds a totcounts member to histogram and a unit test
MAJOR FIX: Pair sampling mystery solved

Bins at large spatial separation are left severely under populated when
the output list of coordinates is sampled sequentially. This is due to
the fact that the point sampling routine returns the input coordinates
organized by subgrid, and thus adjacent points in the list are at close
proximity. Any correct usage of the sampling function must randomize its
selection of points from the output list.