This updates the test infrastructure to store a git hash of the reference
code, instead of generated .h5 files.  The test infrastructure creates a
cache of the reference .h5 files from the specified git hash if it doesn't
already exist, and then compares against that cache.

This gets rid of the need for git-lfs and the cached .h5 files, requiring
instead the code is checked out from git.

Use overlaid dashes for the head traces.

Also do comparison in preferred IFO order.

since it's not needed for most operations

This allows for specifying an order that makes sense without too much loss
of ease of expandability (just need to add an entry to a list).

This finally gets rid of the whole precompIFO function.  It does this
by breaking up precomp into various smaller functions, moving them
into the common IFO noise definition module, and using them
appropriately when needed.  This does result in some of the functions
being called multiple times in the full budget calculation for the
aLIGO-like budgets, but the cost should be minor given the convenience
of getting rid of the whole precomp thing, thereby opening up
everything to non-aLIGO-like configurations.

Even though some functions are calculated multiple times, we're still
orders of magnitude faster than matgwinc, so...  Should still revisit
down the line though.

closes #40

Drop specific comparison to MATGWINC output and move to comparisons to
cached hdf5 traces.  Comparisons to all cached IFO traces will be done by
default.  A PDF report of all discrepancies for all IFOs will be
generated if requested.  inspiral ranges will be calculated if the
inspiral_range package is available.

This adds trace caches (in git-lfs) for all currently supported IFOs,
effectively snap-shotting the current state of the repo.

gitlab CI also updated to use new tests

eliminate need for separate sub-module

This replaces load_ifo(), and returns only the Budget class.

Any ifo.yaml found in a budget package is loaded as ifo attribute.  other
stuff can just be assumed to be provided as class attributes as well.

This patch provides a new nb sub-module that defines classes for managing
and calculating noise budgets.  It provides the following overridable
classes:

nb.Calibration  A noise calibration
nb.Noise        A noise source
nb.Budget       A budget of noises

The Budget class includes a calc_trace() method that will return a traces
dictionary that includes data and trace plot styling for every noise term
in the budget recursively.

The existing included interferometers are updated to define their budgets
using this new interface, and the plot_noises function is updated to
accept the new traces dictionary.

An HDF5_SCHEMA describes how trace dictionaries are encoded into HDF5 files.
The new io module includes functions for writing traces to HDF5 files, and
for reading traces stored in this format.

The command line interface is updated to handle this new structure.

With this tweak, most noises agree within 1 ppb.  Exceptions are
seismic and substrate TE (which still have open bugs in matgwinc).

Arguments added to gwinc.test for setting a tolerance level, and a
list of noises to skip in the comparison.

The CI pipeline will now fail when tests fail.

Use the new CBCWaveform interface in the insprial_range package for specifying
the waveform and parameters, both in the CLI and test.

better titles, calc Total difference, and show max fractional error in plots
and in log, and other log cleanup

The hashes are stored in the pickeled MATLAB results, and uses them to check
if new results need to be calculated based on changes to IFO or gwinc data.

This directly compares the output of gwinc() and gwinc_matlab().  Any
noises that differ by more than 1% are noted and the return value of the
test is non-zero.  Differences can be plotted with the -p option.

This is now commensurate with what matlab gwinc does, and makes the IFO
structures directly comparable without any hacky conversions.

This utilizes matlab.engine to run MATLAB gwinc on it's default IFOModel.
The resultant data (ifo and noises) are saved to gwinc.mat file, which is
then loaded by the test command.  The loaded ifo parameters are used to
create a pygwinc ifo model, from which pygwinc noises are calculated.

The difference between the matgwinc and pygwinc noises are then plotted
and displayed.b