"""
This function writes out a list of line luminosities computed by
cloudy from a slug run.
"""
import numpy as np
try:
import astropy.io.fits as fits
except ImportError:
fits = None
import warnings
warnings.warn("Unable to import astropy. FITS funtionality" +
" will not be available.")
[docs]def write_integrated_cloudylines(data, model_name, fmt):
"""
Write out line luminosities computed by cloudy on a slug spectrum
Parameters
data : namedtuple
Integrated cloudy line data to be written; a namedtuple
containing the fields time, cloudy_linelist, cloudy_linewl,
cloudy_linelum
model_name : string
Base file name to give the model to be written. Can include a
directory specification if desired.
fmt : string
Format for the output file. Allowed values are 'ascii', 'bin'
or 'binary, and 'fits'.
Returns
Nothing
"""
# Make sure fmt is valid
if fmt != 'ascii' and fmt != 'bin' and fmt != 'binary' and \
fmt != 'fits':
raise ValueError("fmt must be ascii, bin, binary, or fits")
# Make sure we're not trying to do fits if we don't have astropy
if fmt == 'fits' and fits is None:
raise ValueError("Couldn't import astropy, so fits format "+
"is unavailable.")
if fmt == 'ascii':
# ASCII mode
fp = open(model_name+'_integrated_cloudylines.txt', 'w')
# Write header lines
fp.write(("{:<14s}"*4).
format('Time', 'LineLabel', 'Wavelength',
'Luminosity') + "\n")
fp.write(("{:<14s}"*4).
format('(yr)', '', '(Angstrom)', '(erg/s)') + "\n")
fp.write(("{:<14s}"*4).
format('-----------', '-----------', '-----------',
'-----------')
+ "\n")
# Write data
ntime = data.cloudy_linelum.shape[-2]
ntrial = data.cloudy_linelum.shape[-1]
if len(data.time) > ntime:
random_time = True
else:
random_time = False
nline = len(data.cloudy_linewl)
for i in range(ntrial):
if i != 0:
fp.write("-"*(4*14-3)+"\n")
for j in range(ntime):
if random_time:
t_out = data.time[i]
else:
t_out = data.time[j]
for k in range(nline):
fp.write(("{:11.5e} {:>11s} {:11.5e} " +
"{:11.5e}\n")
.format(t_out,
data.cloudy_linelabel[k],
data.cloudy_linewl[k],
data.cloudy_linelum[k,j,i]))
# Close
fp.close()
elif fmt == 'bin' or fmt == 'binary':
# Binary mode
fp = open(model_name+'_integrated_cloudylines.bin', 'wb')
# Write out number of lines and line labels as ASCII, one per
# line
nlabel = len(data.cloudy_linelabel)
fp.write(str(nlabel)+"\n")
for i in range(nlabel):
fp.write(data.cloudy_linelabel[i]+"\n")
# Write line wavelengths
fp.write(data.cloudy_linewl)
# Write line luminosities
ntime = data.cloudy_linelum.shape[1]
ntrial = data.cloudy_linelum.shape[2]
if len(data.time) > ntime:
random_time = True
else:
random_time = False
for i in range(ntrial):
for j in range(ntime):
fp.write(np.uint(i))
if random_time:
fp.write(data.time[i])
else:
fp.write(data.time[j])
# This next line is needed to put the data into a
# contiguous block before writing
tmp = np.copy(data.cloudy_linelum[:,j,i])
fp.write(tmp)
# Close file
fp.close()
elif fmt == 'fits':
# FITS mode
# Create a first HDU containing the line wavelengths and labels
nl = len(data.cloudy_linewl)
fmtstring = "A4"
wlcols = [fits.Column(name="Line_Label",
format=fmtstring,
array=data.cloudy_linelabel)]
fmtstring = "D"
wlcols.append(fits.Column(name="Wavelength",
format=fmtstring,
unit="Angstrom",
array=data.cloudy_linewl))
wlfits = fits.ColDefs(wlcols)
wlhdu = fits.BinTableHDU.from_columns(wlcols)
# Figure out number of trials, and tile arrays
ntimes = data.cloudy_linelum.shape[1]
ntrial = data.cloudy_linelum.shape[2]
trial = np.transpose(np.tile(
np.arange(ntrial, dtype='int64'), (ntimes,1))).\
flatten()
if len(data.time) > ntimes:
times = data.time
else:
times = np.tile(data.time, ntrial)
# Convert data to FITS columns
cols = []
cols.append(fits.Column(name="Trial", format="1K",
unit="", array=trial))
cols.append(fits.Column(name="Time", format="1D",
unit="yr", array=times))
cols.append(fits.Column(name="Line_Luminosity",
format=str(nl)+"D",
unit="erg/s",
array=np.transpose(data.cloudy_linelum).
reshape(ntimes*ntrial, nl)))
linelum_cols = fits.ColDefs(cols)
linelumhdu = fits.BinTableHDU.from_columns(linelum_cols)
# Create dummy primary HDU
prihdu = fits.PrimaryHDU()
# Create HDU list and write to file
hdulist = fits.HDUList([prihdu, wlhdu, linelumhdu])
hdulist.writeto(model_name+'_integrated_cloudylines.fits',
overwrite=True)