Merge branch 'auto_resolution' of gitlab.eps.surrey.ac.uk:ri0005/binary_c-python into auto_resolution

add modulo cost in tpr calculation: if modulo is 10, we underestimate the cost by ~ a factor 10, so we should multiply by the modulo

also prevented the Moecache from being freed on grid exit: we can have nested grid objects, and in that case it is required to remain

attempted to harmoize the Moe and di Stefano (2017) variable names so they all use Moe2017 (or MOE2017)

added options to the Moe loader so we can change the JSON data and reload it after clearing the cache

the period distribution renormalization now gets the low and high limits from the loaded data

update_dicts() now copies the type of dict_1 for the new dict, rather than using OrderedDict (maybe merge_dicts should do this too?)

I've fixed the _boxed formatting to strip ANSI codes when calculating string lengths (so you can use ANSI colours properly)

changed the colours for the "failed systems" warning so it's absolutely obvious

wrapped the JSON ensemble output in a write_ensemble() function which automatically gzips or bzips depending on the filename extension (or this can be explictly set in grid_options['compress_ensemble'] ).

make gridcode filename blue

cleaned up some of the verbosity to be more like binary_grid and less annoying

Merge branch 'auto_resolution' of gitlab.eps.surrey.ac.uk:ri0005/binary_c-python into auto_resolution

implemented binary_grid-style statistics over last n_logging_stats verbose outputs (50 by default)

added ANSI colour to output if in a terminal (i.e. with a tty)

fixed the cmd-line parser to work in the form x=y as intended (downside: no help output, but that just said how to use the old parser which doesn't exist now)

updated the internal API for how grids are constructed to simplify the code

add option such that when resolution==0, the resolution is calculated automatically from the sample list.

add delete_grid_variable function

In my CEMP simulations, I use the above with something like this to zoom in around 0.8Msun in M1:

emp_population.update_grid_variable(
    name="lnm1",
    spacingfunc="gaussian_zoom(np.log(0.4),np.log(6.0),np.log(0.8),0.05,0.99,100)",
    resolution=0
)