if 'DespoticTem' not in catalog.colnames:
from despotic_heating import tkin_all
print("Adding DESPOTIC-derived temperatures to dendrograms.")
from astropy import units as u
import gaussian_correction
gcorfactor = gaussian_correction.gaussian_correction(catalog['Smin303']/catalog['Smax303'])
# use 2*reff because we care about diameter, not radius
# then deconvolve out the beam
# (see paper: 28" -> 30" beam because of gridding_
beam_pc = (30/(np.sqrt(8*np.log(2)))*u.arcsec*8.5*u.kpc).to(u.pc, u.dimensionless_angles())
dtems = [tkin_all(density=10**row['density_chi2']*u.cm**-3,
sigma=row['v_rms']*u.km/u.s*gf,
lengthscale=2*((row['reff']*u.pc*gf)**2-(beam_pc)**2)**0.5,
gradient=5*u.km/u.s/u.pc, #min(5,row['v_rms']/row['reff'])*u.km/u.s/u.pc,
tdust=row['higaldusttem']*u.K,
crir=1e-17*u.s**-1,
ISRF=1,
tdust_rad=(row['higaldusttem']*u.K *
(1-np.exp(-(10**row['logh2column']/1e24)))))
for row,gf in ProgressBar(zip(catalog, gcorfactor))]
catalog.add_column(Column(name='DespoticTem', data=dtems))
catalog.add_column(Column(name='gausscorrfactor', data=gcorfactor))
# time estimate: 30m-1h
dctems = [tkin_all(density=10**row['density_chi2']*u.cm**-3,
sigma=row['v_rms']*u.km/u.s*gf,
lengthscale=2*((row['reff']*u.pc*gf)**2-(beam_pc)**2)**0.5,
gradient=5*u.km/u.s/u.pc, #min(5,row['v_rms']/row['reff'])*u.km/u.s/u.pc,
tdust=row['higaldusttem']*u.K,
crir=1e-17*u.s**-1,
pl.subplots_adjust(hspace=0.45)
outf = paths.fpath('param_fits/{name}_oneD_{num}_parameter_constraints.pdf'.format(name=row['Source_Name'],
num=num))
pl.savefig(outf, bbox_inches='tight')
row_data = mf.get_parconstraints()
for key,value in row_data.iteritems():
row[key] = value
width = row['width']*u.km/u.s
row['reff_pc'] = reff.to(u.pc).value
row['tkin_turb'] = heating.tkin_all(density=10**row['density_chi2']*u.cm**-3,
sigma=width,
lengthscale=reff,
gradient=width/reff,
tdust=row['higaldusttem']*u.K,
crir=0./u.s)
#if row_data['temperature_chi2'] == 10:
# import ipdb; ipdb.set_trace()
log.info("Completed source loop.")
fittable.write(tpath('fitted_line_parameters_Chi2Constraints.ipac'),
format='ascii.ipac')
log.info("Wrote table file. Continuing to parameter plots.")
from astropy import units as u
import gaussian_correction
gcorfactor = gaussian_correction.gaussian_correction(catalog['Smin303'] /
catalog['Smax303'])
# use 2*reff because we care about diameter, not radius
# then deconvolve out the beam
# (see paper: 28" -> 30" beam because of gridding_
beam_pc = (30 / (np.sqrt(8 * np.log(2))) * u.arcsec * 8.5 * u.kpc).to(
u.pc, u.dimensionless_angles())
dtems = [
tkin_all(
density=10**row['density_chi2'] * u.cm**-3,
sigma=row['v_rms'] * u.km / u.s * gf,
lengthscale=2 * ((row['reff'] * u.pc * gf)**2 - (beam_pc)**2)**0.5,
gradient=5 * u.km / u.s /
u.pc, #min(5,row['v_rms']/row['reff'])*u.km/u.s/u.pc,
tdust=row['higaldusttem'] * u.K,
crir=1e-17 * u.s**-1,
ISRF=1,
tdust_rad=(row['higaldusttem'] * u.K *
(1 - np.exp(-(10**row['logh2column'] / 1e24)))))
for row, gf in ProgressBar(zip(catalog, gcorfactor))
]
catalog.add_column(Column(name='DespoticTem', data=dtems))
catalog.add_column(Column(name='gausscorrfactor', data=gcorfactor))
# time estimate: 30m-1h
dctems = [
tkin_all(
density=10**row['density_chi2'] * u.cm**-3,
sigma=row['v_rms'] * u.km / u.s * gf,
outf = paths.fpath(
'param_fits/{name}_oneD_{num}_parameter_constraints.pdf'.format(
name=row['Source_Name'], num=num))
pl.savefig(outf, bbox_inches='tight')
row_data = mf.get_parconstraints()
for key, value in row_data.items():
row[key] = value
width = row['width'] * u.km / u.s
row['reff_pc'] = reff.to(u.pc).value
row['tkin_turb'] = heating.tkin_all(density=10**row['density_chi2'] *
u.cm**-3,
sigma=width,
lengthscale=reff,
gradient=width / reff,
tdust=row['higaldusttem'] * u.K,
crir=0. / u.s)
#if row_data['temperature_chi2'] == 10:
# import ipdb; ipdb.set_trace()
log.info("Completed source loop.")
fittable.write(tpath('fitted_line_parameters_Chi2Constraints.ipac'),
format='ascii.ipac')
log.info("Wrote table file. Continuing to parameter plots.")
execfile(paths.pcpath('parameter_comparisons.py'))
