"""
Copied from apex_cmz_h2co then cropped to just get the grids
"""
from astropy import log
from astropy.io import fits
from pyspeckit.spectrum import models
from pyspeckit.spectrum.models.model import SpectralModel
from paths import gpath
try:
# create the Formaldehyde Radex fitter
# This step cannot be easily generalized: the user needs to read in their own grids
texgrid303 = fits.getdata(gpath('fjdu_pH2CO_303_tex_1kms.fits'))
taugrid303 = fits.getdata(gpath('fjdu_pH2CO_303_tau_1kms.fits'))
texgrid321 = fits.getdata(gpath('fjdu_pH2CO_321_tex_1kms.fits'))
taugrid321 = fits.getdata(gpath('fjdu_pH2CO_321_tau_1kms.fits'))
texgrid322 = fits.getdata(gpath('fjdu_pH2CO_322_tex_1kms.fits'))
taugrid322 = fits.getdata(gpath('fjdu_pH2CO_322_tau_1kms.fits'))
hdr = hdrb = fits.getheader(gpath('fjdu_pH2CO_303_tex_1kms.fits'))
# # this deserves a lot of explanation:
# # models.formaldehyde.formaldehyde_radex is the MODEL that we are going to fit
# # models.model.SpectralModel is a wrapper to deal with parinfo, multiple peaks,
# # and annotations
# # all of the parameters after the first are passed to the model function
h2co_radex_fitter = SpectralModel(
models.formaldehyde_mm.formaldehyde_mm_radex,
5,
parnames=['temperature', 'column', 'density', 'center', 'width'],
parvalues=[50, 12, 4.5, 0, 1],
bt = re.compile("tex|tau|flux")
(fTI, fpars, fbad_pars) = compute_grid(Radex=pyradex.fjdu.Fjdu,
run_kwargs={})
for pn in fpars:
btype = bt.search(pn).group()
ff = makefits(fpars[pn],
btype,
densities=densities,
temperatures=temperatures,
columns=columns)
outfile = 'fjdu_pH2CO_{line}_{type}_{dv}.fits'.format(line=pn[-3:],
type=btype,
dv='1kms')
ff.writeto(gpath(outfile), clobber=True)
print(outfile)
ff = makefits(fpars['fluxgrid_321'] / fpars['fluxgrid_303'],
'ratio',
densities=densities,
temperatures=temperatures,
columns=columns)
outfile = 'fjdu_pH2CO_{line}_{type}_{dv}.fits'.format(line='321to303',
type='ratio',
dv='1kms')
ff.writeto(gpath(outfile), clobber=True)
(TI, pars, bad_pars) = compute_grid()
for pn in pars:
import pyspeckit
import numpy as np
from astropy import log
from astropy.io import fits
from pyspeckit.spectrum import models
from pyspeckit.spectrum.models.model import SpectralModel
import FITS_tools
from paths import h2copath, mergepath, figurepath, gpath
from make_ratiotem_cubesims import tm
import os
try:
# create the Formaldehyde Radex fitter
# This step cannot be easily generalized: the user needs to read in their own grids
texgrid303 = fits.getdata(gpath('fjdu_pH2CO_303_tex_5kms.fits'))
taugrid303 = fits.getdata(gpath('fjdu_pH2CO_303_tau_5kms.fits'))
texgrid321 = fits.getdata(gpath('fjdu_pH2CO_321_tex_5kms.fits'))
taugrid321 = fits.getdata(gpath('fjdu_pH2CO_321_tau_5kms.fits'))
texgrid322 = fits.getdata(gpath('fjdu_pH2CO_322_tex_5kms.fits'))
taugrid322 = fits.getdata(gpath('fjdu_pH2CO_322_tau_5kms.fits'))
hdr = hdrb = fits.getheader(gpath('fjdu_pH2CO_303_tex_5kms.fits'))
# # this deserves a lot of explanation:
# # models.formaldehyde.formaldehyde_radex is the MODEL that we are going to fit
# # models.model.SpectralModel is a wrapper to deal with parinfo, multiple peaks,
# # and annotations
# # all of the parameters after the first are passed to the model function
h2co_radex_fitter = SpectralModel(models.formaldehyde_mm.formaldehyde_mm_radex,
5,
parnames=['temperature','column','density','center','width'],
from paths import gpath
except ImportError:
gpath = lambda x: x
bt = re.compile("tex|tau|flux")
(fTI, fpars, fbad_pars) = compute_grid(Radex=pyradex.fjdu.Fjdu,
run_kwargs={})
for pn in fpars:
btype = bt.search(pn).group()
ff = makefits(fpars[pn], btype, densities=densities,
temperatures=temperatures, columns=columns)
outfile = 'fjdu_pH2CO_{line}_{type}_{dv}.fits'.format(line=pn[-3:],
type=btype,
dv='5kms')
ff.writeto(gpath(outfile),
clobber=True)
print(outfile)
ff = makefits(fpars['fluxgrid_321']/fpars['fluxgrid_303'], 'ratio',
densities=densities, temperatures=temperatures,
columns=columns)
outfile = 'fjdu_pH2CO_{line}_{type}_{dv}.fits'.format(line='321to303',
type='ratio',
dv='5kms')
ff.writeto(gpath(outfile), clobber=True)
(TI, pars, bad_pars) = compute_grid()
for pn in pars:
btype = bt.search(pn).group()
newfile.header.update('CRVAL3' , (min(temperatures)) )
newfile.header.update('CRPIX3' , 1 )
if len(np.unique(temperatures)) == 1:
newfile.header.update('CTYPE3' , 'ONE-TEMP' )
newfile.header.update('CDELT3' , temperatures[0])
else:
newfile.header.update('CTYPE3' , 'LIN-TEMP' )
newfile.header.update('CDELT3' , (np.unique(temperatures)[1]) - (np.unique(temperatures)[0]) )
return newfile
if __name__ == "__main__":
import re
from paths import gpath
import os
if not os.path.isdir(gpath('')):
os.mkdir(gpath(''))
bt = re.compile("tex|tau|flux")
(fTI, fpars, fbad_pars) = compute_grid(Radex=pyradex.fjdu.Fjdu,
run_kwargs={})
for pn in fpars:
btype = bt.search(pn).group()
ff = makefits(fpars[pn], btype, densities=densities,
temperatures=temperatures, columns=columns)
outfile = 'fjdu_hc3n_{line}_{type}_{dv}.fits'.format(line=pn.split("_")[-1],
type=btype,
dv='5kms')
ff.writeto(gpath(outfile),
clobber=True)
