def get_best_2comp_residual_cnv(reg, masked=True, window_hwidth=3.5, res_snr_cut=5):
# return convolved residual cube. If masked is True, only convolve over where 'excessive' residual
# above a peak SNR value of res_snr_cut masked
# need a mechanism to make sure reg.ucube.pcubes['1'], reg.ucube.pcubes['2'] exists
res_cube = get_best_2comp_residual(reg)
best_res = res_cube._data
cube_res = SpectralCube(data=best_res, wcs=reg.ucube.pcubes['2'].wcs.copy(),
header=reg.ucube.pcubes['2'].header.copy())
if masked:
best_rms = UCube.get_rms(res_cube._data)
# calculate the peak SNR value of the best-fit residual over the main hyperfine components
vmap = reg.ucube.pcubes['1'].parcube[0]
# make want to double check that masked cube always masks out nan values
res_main_hf = mmg.vmask_cube(res_cube, vmap, window_hwidth=window_hwidth)
if res_main_hf.size > 1e7:
# to avoid loading entire cube and stress the memory
how = 'slice'
else:
# note: 'auto' currently returns slice for n > 1e8
how = 'auto'
# enable huge operations (note: not needed when "how" is chosen wisely, which it should be)
res_main_hf.allow_huge_operations = True
res_main_hf_snr = res_main_hf.max(axis=0, how=how).value / best_rms
res_main_hf.allow_huge_operations = False
# mask out residual with SNR values over the cut threshold
mask_res = res_main_hf_snr > res_snr_cut
mask_res = dilation(mask_res)
cube_res_masked = cube_res.with_mask(~mask_res)
else:
cube_res_masked = cube_res
cube_res_cnv = cnvtool.convolve_sky_byfactor(cube_res_masked, factor=reg.cnv_factor, edgetrim_width=None,
snrmasked=False, iterrefine=False)
cube_res_cnv = cube_res_cnv.with_spectral_unit(u.km / u.s, velocity_convention='radio')
return cube_res_cnv
def get_best_2comp_snr_mod(reg):
modbest = get_best_2comp_model(reg)
res_cube = get_best_2comp_residual(reg)
best_rms = UCube.get_rms(res_cube._data)
return np.nanmax(modbest, axis=0)/best_rms