# Load in my huge FITS creator
execfile(os.path.expanduser("~/Dropbox/code_development/ewky_scripts/write_huge_fits.py"))
def find_nearest(array, value):
'''
http://stackoverflow.com/questions/2566412/find-nearest-value-in-numpy-array
'''
idx = (np.abs(array - value)).argmin()
return idx
# Set vsys. Using the fit value from DISKFIT
table_name = fourteenB_HI_data_path("diskfit_noasymm_noradial_nowarp_output/rad.out.csv")
tab = Table.read(table_name)
cube = SpectralCube.read(iram_co21_data_path("m33.co21_iram.fits"))
# Somehow blank keywords are generated when reading the cube in... something
# to do with dropping the Stokes axis is my guess.
del cube._header[""]
# Where's the center?
# center_pixel = find_nearest(cube.spectral_axis, vsys)
# In this case, the remaining difference is a minuscule 3 m/s.
model = return_smooth_model(tab, cube.header, gal)
# Now calculate the spectral shifts needed for each pixel
# Assuming that the array shapes for the same (which they are here)
shifts = np.zeros(model.shape)
posns = np.where(np.isfinite(model))
from astropy.io import fits
# Import from above.
# parentdir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# os.sys.path.insert(0, parentdir)
from paths import (iram_co21_data_path, fourteenB_HI_data_path,
paper1_figures_path)
from constants import lwidth_name
from galaxy_params import gal
from HI_veldisp_profile import radial_profile
# Load data in
cube = SpectralCube.read(iram_co21_data_path("m33.co21_iram.fits"))
del cube._header[""]
# cube = cube.with_mask(cube > 0.1 * u.K)
mask = fits.getdata(iram_co21_data_path("m33.co21_new_assign_clfind.fits"))
cube = cube.with_mask(mask.astype(bool))
lwidth_co = cube.linewidth_sigma()
lwidth_hi = fits.open(fourteenB_HI_data_path(lwidth_name))[0]
lwidth_hi = Projection(lwidth_hi.data, wcs=WCS(lwidth_hi.header),
unit=u.m / u.s)
dr = 250 * u.pc
rs, sd, sd_sigma = radial_profile(gal, lwidth_co, max_rad=6 * u.kpc,
dr=dr)
Create the surface density profile in CO(2-1), assuming a factor to convert
to the H2 mass.
'''
co21_mass_conversion = 6.7 * (u.M_sun / u.pc ** 2) / (u.K * u.km / u.s)
# IRAM beam efficiency
beam_eff = 0.75
# Set the radial disk widths to bin over
# dr = 500 * u.pc
dr = 100 * u.pc
# dr = 300 * u.pc
# Load the moment 0
cube = SpectralCube.read(iram_co21_data_path("m33.co21_iram.fits"))
del cube._header[""]
cube = cube.with_mask(cube > 0.1 * u.K)
mom0_hi = fits.open(fourteenB_HI_data_path(moment0_name))[0]
hi_cube = SpectralCube.read(fourteenB_HI_data_path(cube_name))
mask = fits.open(fourteenB_HI_data_path(mask_name))[0]
hi_cube = hi_cube.with_mask(mask.data > 0)
radii = gal.radius(header=cube.header)
# Edge effects are really awful in this map. Ignore the edges by masking
# beyond 6 kpc. This is really close to the edge of the data anyways, and
# honestly results beyond this point shouldn't be trusted...
cube = cube.with_mask(radii < 6. * u.kpc)
# mom0 = fits.open(os.path.join(direc, "m33.ico.fits"))[0]
