# slicer = (slice(825, 1033), slice(360, 692))
slicer = (slice(None), slice(None))
# Load in the rotation subtracted cubes
hi_cube = SpectralCube.read(fourteenB_HI_data_path(rotsub_cube_name))
co_cube = SpectralCube.read(iram_co21_data_path("m33.co21_iram.rotsub.fits"))
start_vel = - 30 * u.km / u.s
end_vel = 30 * u.km / u.s
del_vel = 3. * u.km / u.s
vels = np.arange(start_vel.value, end_vel.value + del_vel.value,
del_vel.value) * u.km / u.s
# Get the radius array so we can cut to where the CO data is valid
radii = gal.radius(header=hi_cube[0].header)
max_radius = 6.0 * u.kpc
all_dists = []
all_radii = []
all_vals_hi = []
all_vals_co = []
edge_masks = []
skeletons = []
hi_beam = average_beams(hi_cube.beams)
# Estimate the noise level in an equivalent slab
hi_mom0 = hi_cube.spectral_slab(-180 * u.km / u.s, -183 * u.km / u.s).moment0()
sigma = sig_clip(hi_mom0.value, nsig=10) * \
hi_beam.jtok(hi_freq).value
from analysis.galaxy_params import gal
cube = SpectralCube.read(fourteenB_HI_data_path(cube_name))
mask = fits.open(fourteenB_HI_data_path(mask_name))[0]
# Apply the source mask
cube = cube.with_mask((mask.data > 0))
# Now cut to the elliptical region to remove all bkg regions
# region = pyregion.open(c_hi_analysispath("rotation_curves/mom1_rotcurve_mask.reg"))
# subcube = cube.subcube_from_ds9region(region)
# Since the parameters of M33 are already well constrained, use a radius
# cut-off based on previous values. The fitting is done out to 10 kpc. A
# small bit is added here to account for small changes in the fit parameters.
radius = gal.radius(header=cube.header)
max_radius = 10.25 * u.kpc
subcube = cube.with_mask(radius < max_radius).minimal_subcube()
# Now create the moment 1 and save it. Make a linewidth one too.
# DISKFIT has issues with float64, so convert to float32 then save
moment0_name = "M33_14B-088_HI.clean.image.pbcov_gt_{}.ellip_mask.mom0.fits".format(pb_lim)
moment0 = subcube.moment0()
moment0.write(fourteenB_HI_data_path(moment0_name, no_check=True),
overwrite=True)
moment1_name = "M33_14B-088_HI.clean.image.pbcov_gt_{}.ellip_mask.mom1.fits".format(pb_lim)
moment1 = subcube.moment1().astype(np.float32)
moment1.header["BITPIX"] = -32
moment1.write(fourteenB_HI_data_path(moment1_name, no_check=True),
co21_mass_conversion, hi_freq)
from analysis.galaxy_params import gal
'''
Create profiles of HI and CO after rotation subtraction.
'''
co_cube = SpectralCube.read(iram_co21_data_path("m33.co21_iram.rotsub.fits"))
# mask = fits.getdata(iram_co21_data_path("m33.co21_new_assign_clfind.fits"))
# co_cube = co_cube.with_mask(mask.astype(bool))
hi_cube = SpectralCube.read(fourteenB_HI_data_path(rotsub_cube_name))
hi_mask = fits.open(fourteenB_HI_data_path(rotsub_mask_name))[0]
hi_cube = hi_cube.with_mask(hi_mask.data > 0)
hi_radius = gal.radius(header=hi_cube.header)
co_radius = gal.radius(header=co_cube.header)
# Perform the same analysis split up into radial bins
dr = 500 * u.pc
max_radius = (6.0 * u.kpc).to(u.pc)
nbins = np.int(np.floor(max_radius / dr))
inneredge = np.linspace(0, max_radius - dr, nbins)
outeredge = np.linspace(dr, max_radius, nbins)
total_spectrum_hi_radial = np.zeros((inneredge.size, hi_cube.shape[0]))
total_spectrum_co_radial = np.zeros((inneredge.size, co_cube.shape[0]))
