(1-np.exp(-(10**row['logh2column']/1e24)))),
gmc=gmc)
print("Chemical equilbrium temperature: ",T1)
cool1 = gmc.dEdt(PsiUser=turb_heating_generator(lengthscale))
print("CO cooling: ",cool1['LambdaLine']['co'])
print("O cooling: ",cool1['LambdaLine']['o'])
print("C cooling: ",cool1['LambdaLine']['c'])
print("C+ cooling: ",cool1['LambdaLine']['c+'])
print("oH2 cooling: ",cool1['LambdaLine']['oh2'])
print("pH2 cooling: ",cool1['LambdaLine']['ph2'])
print("HD cooling: ",cool1['LambdaLine']['hd'])
if __name__ == "__main__":
import matplotlib
matplotlib.rc_file(paths.pcpath('pubfiguresrc'))
densities = np.logspace(3,7,20)
tem = [tkin_all(n*u.cm**-3, 10*u.km/u.s, lengthscale=5*u.pc,
gradient=5*u.km/u.s/u.pc, tdust=25*u.K,
crir=1e-17*u.s**-1) for n in ProgressBar(densities)]
pl.figure(1)
pl.clf()
pl.plot(densities, tem, 'k--', label='CRIR=1e-17, $\sigma=10$ km/s')
pl.xlabel(r'$\log\,N_{\rm H}$')
pl.ylabel('Temperature (K)')
pl.xscale('log')
pl.legend(loc='best')
pl.savefig(paths.fpath("despotic/TvsN.png"))
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.")
execfile(paths.pcpath('parameter_comparisons.py'))
pl.show()
from paths import pcpath
execfile(pcpath('parameter_comparisons.py'))
execfile(pcpath('dendrotem_plots.py'))
execfile(pcpath('figure_ratio_maps.py'))
execfile(pcpath('individual_full_spectra.py'))
execfile(pcpath('integrated_data_figures.py'))
execfile(pcpath('tmap_pv.py'))
execfile(pcpath('t_vs_r.py'))
# not included in pub: execfile(pcpath('tmap_compare.py'))
# not included in publication (Jan 17):
#execfile(pcpath('pyspeckit_region_figures.py'))
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'))
pl.show()
from spectral_cube import SpectralCube, BooleanArrayMask, Projection
import aplpy
import pylab as pl
import matplotlib
import copy
from paths import mpath,apath,fpath,molpath,hpath
from astropy import units as u
from astropy import coordinates
from astropy.io import ascii, fits
from astropy import log
from astropy.wcs import WCS
from astropy import wcs
from piecewise_rtotem import pwtem
import paths
import matplotlib
matplotlib.rc_file(paths.pcpath('pubfiguresrc'))
# obsolete x,y = np.loadtxt(apath('orbit_K14.dat')).T
table = ascii.read(apath('orbit_K14_2.dat'), format='basic', comment="#", guess=False)
coords = coordinates.SkyCoord(table['l']*u.deg, table['b']*u.deg, frame='galactic')
P = pvextractor.Path(coords, width=300*u.arcsec)
dl = (table['l'][1:]-table['l'][:-1])
db = (table['b'][1:]-table['b'][:-1])
dist = (dl**2+db**2)**0.5
cdist = np.zeros(dist.size+1)
cdist[1:] = dist.cumsum()
reftime = -2
bricktime = 0.3
time = table['t']
import matplotlib
from paths import hpath, apath, fpath, pcpath
matplotlib.rc_file(pcpath("pubfiguresrc"))
import numpy as np
import pylab as pl
from astropy.table import Table, Column
from astropy import log
from astropy import units as u
from scipy.interpolate import PiecewisePolynomial
from h2co_modeling.temperature_mapper import ph2cogrid, TemperatureMapper
from dendrograms import catalog, catalog_sm, dend, dendsm
import heating
import gaussian_correction
import lte_model
if "tm" not in locals():
tm = TemperatureMapper(logdensities=[3, 4, 5], abundances=(1.2e-9,))
tm2 = TemperatureMapper(logdensities=[4], deltav=20.0)
tm3 = TemperatureMapper(logdensities=[4], deltav=1.0)
tm4 = TemperatureMapper(logdensities=[4], abundances=(1e-8, 1e-10))
segmentdata = {
"alpha": [(0.0, 1.0, 1.0), (0.5, 1.0, 1.0), (1.0, 1.0, 1.0)],
"blue": [(0.0, 1.0, 1.0), (0.5, 0.0, 0.0), (1.0, 0.0, 0.0)],
"green": [(0.0, 0.0, 0.0), (0.5, 0.75, 0.75), (1.0, 0.0, 0.0)],
"red": [(0.0, 0.0, 0.0), (0.5, 0.0, 0.0), (1.0, 1.0, 1.0)],
