- add a test to transform a buffer and compare to numpy's matrix-matrix
  multiply

gstlal_inspiral_pipe: fix broken calc likelihood dag nodes when there are multiple combinations of detector livetime

- generalization to multiple output documents was missed in part of the
  likelihood ratio branch

this patch folds the joint SNR PDFs into the ranking statistic.  in doing
so, it breaks the current technique for building the ranking statistic
histograms and therefore also introduces a new technique for constructing
those histograms based on stochastic sampling.

this patch also fully reworks the FAP and FAR machinery.  it introduces new
on-disk file formats, combines all instrument categories into a single
experiment with a single FAP, redesigns the FAR normalization around a
single total event count (removing the trials table machinery, using the
coinc parameter histogram data instead).

some steps in the pipeline become more costly.
gstlal_inspiral_calc_likelihoods now requires several CPU cores to run the
stochastic sampling in the background while assigning likelihood ratios in
the main thread.  other steps become less costly.
gstlal_inspiral_marginalize_likelihood is reduced to little more than file
I/O.

all the machinery is now in place for this to work, i.e., the background
and signal probabilities are being calculated correctly.  with this patch
we have a ranking statistic that can be used to rank all coincs together on
a single scale regardless of instrument combination.

match argument order in inspiral.Data() creation

rename keyword argument wherever it appears

it's still broken, though.  just collected into one place so it'll be easier to fix.