def read_transitions(filename, atomdat):
print 'Reading transitions from', filename
with open(filename) as fh:
linelist = []
for tr in fh:
tr = tr.strip()
if tr and not tr.startswith('#'):
name, t = findtrans(tr, atomdat=atomdat))
temp.append(dict(name=name, wa=t['wa'], )
return linelist
def read_transitions(fh, atomdat):
""" Read transitions from a file
Parameters
----------
fh : str or file object
atomdat : atom.dat object
Read with `barak.absorb.readatom()`
Returns
-------
linelist : list of atom.dat entries
Atom.dat entry for each transition
Notes
-----
Example file format:
HI 1215
CIV 1549
CIV 1550
MgII 2796
MgII 2803
"""
if isinstance(fh, basestring):
print 'Reading transitions from', fh
fh = open(fh, 'rt')
linelist = []
for tr in fh:
tr = tr.strip()
if tr and not tr.startswith('#'):
name, t = findtrans(tr, atomdat=atomdat)
linelist.append((name, t))
fh.close()
return linelist
def process_options(args):
opt = adict()
filename = os.path.abspath(__file__).rsplit('/', 1)[0] + '/default.cfg'
opt = parse_config(filename)
if os.path.lexists('./plot.cfg'):
opt = parse_config('./plot.cfg', opt)
opt.atom = readatom(molecules=True)
if opt.Rfwhm is not None:
if isinstance(opt.Rfwhm, basestring):
if opt.Rfwhm == 'convolve_with_COS_FOS':
if convolve_with_COS_FOS is None:
raise ValueError('convolve_with_COS_FOS() not available')
print('Using tailored FWHM for COS/FOS data')
opt.Rfwhm = 'convolve_with_COS_FOS'
elif opt.Rfwhm.endswith('fits'):
print('Reading Resolution FWHM from', opt.Rfwhm)
res = readtabfits(opt.Rfwhm)
opt.Rfwhm = res.res / 2.354
else:
print('Reading Resolution FWHM from', opt.Rfwhm)
fh = open(opt.Rfwhm)
opt.Rfwhm = 1 / 2.354 * np.array([float(r) for r in fh])
fh.close()
else:
opt.Rfwhm = float(opt.Rfwhm)
if opt.features is not None:
print('Reading feature list from', opt.features)
opt.features = readtabfits(opt.features)
if opt.f26 is not None:
name = opt.f26
print('Reading ions and fitting regions from', name)
opt.f26 = readf26(name)
opt.f26.filename = name
if opt.transitions is not None:
print('Reading transitions from', opt.transitions)
fh = open(opt.transitions)
trans = list(fh)
fh.close()
temp = []
for tr in trans:
tr = tr.strip()
if tr and not tr.startswith('#'):
junk = tr.split()
tr = junk[0] + ' ' + junk[1]
t = findtrans(tr, atomdat=opt.atom)
temp.append(dict(name=t[0], wa=t[1][0], tr=t[1]))
opt.linelist = temp
else:
opt.linelist = readtxt(get_data_path() + 'linelists/qsoabs_lines',
names='wa,name,select')
if opt.f26 is None and opt.taulines is not None:
print('Reading ions from', opt.taulines)
fh = open(opt.taulines)
lines = []
for row in fh:
if row.lstrip().startswith('#'):
continue
items = row.split()
lines.append([items[0]] + list(map(float, items[1:])))
fh.close()
opt.lines = lines
if opt.show_regions is None:
opt.show_regions = True
if hasattr(opt, 'aodname'):
opt.aod = Table.read(opt.aodname)
return opt
def plot_model(pars):
"""
`regions`, `x` must be defined in the model.py module namespace
"""
from run_emcee.plot_mcmc import get_fig_axes, get_nrows_ncols
linepars = pars
dz = 0
if options['wa_vary']:
linepars, regpars = pars[:-len(regions)], pars[-len(regions):]
lines = copy_par_to_lines(linepars, lines_vary)
nrows, ncols = get_nrows_ncols(len(regions))
fig, axes = get_fig_axes(nrows, ncols, len(regions), width=8.2)
fig.subplots_adjust(wspace=1e-6, hspace=1e-6, right=1, top=1,
left=0.07, bottom=0.06)
z0 = lines.z[1]
zp1 = lines.z.mean()
colours = dict(J0='purple',J1='g',J2='r',J3='b')
for ind, (wa, tau0, sp, (i, j), tname) in enumerate(regions):
tau = tau0.copy()
for l in lines:
if options['wa_vary']:
#import pdb; pdb.set_trace()
dz = regpars[ind] / wa[len(wa)//2] * (l.z + 1)
#print l.z, dz, l.logN
trans = atom[l.name.strip()]
tau += calc_iontau(wa, trans, l.z+1 + dz, l.logN, l.b)
dwpix = wa[1] - wa[0]
flmodel0 = convolve_with_COS_FOS(np.exp(-tau), wa, dwpix)
ymod = np.interp(sp.wa[i:j], wa, flmodel0)
ax = axes[ind]
i1 = max(i-50, 0)
j1 = min(j+50, len(sp.wa)-1)
nfl = sp.fl[i1:j1] / sp.co[i1:j1]
ner = sp.er[i1:j1] / sp.co[i1:j1]
tstr, t = findtrans(tname, atom)
obswa = t.wa * (1 + z0)
dv = c_kms * (sp.wa[i:j] / obswa - 1)
dv1 = c_kms * (sp.wa[i1:j1] / obswa - 1)
tstr = tstr[2:]
ax.axhline(0, color='0.5',lw=0.5)
ax.axhline(1, color='k', lw=0.5, ls='--')
ax.fill_between([-150, 150], -0.35, -0.15, color='0.9')
ax.axhline(-0.25, color='k', lw=0.25)
ax.plot(dv1, nfl, color='0.7', lw=0.5, drawstyle='steps-mid')
ax.plot(dv, sp.fl[i:j]/sp.co[i:j], 'k', lw=0.5, drawstyle='steps-mid')
ax.plot(dv, ymod, color='0.3')
#ax.axvline(0, color='0.5', lw=0.5)
ax.plot([-23]*2, [1.1, 1.4], '0.5')
ax.plot([0]*2, [1.1, 1.4], '0.5')
puttext(0.95, 0.95, tstr, ax, fontsize=9, va='top', ha='right',
color=colours[tstr[:2]])
resid = (sp.fl[i:j]/sp.co[i:j] - ymod) / sp.er[i:j] * sp.co[i:j]
ax.plot(dv, -0.25 + resid*0.1, '.', color='0.3', ms=2)
ax.set_ylim(-0.5, 1.9)
ax.set_xlim(-120, 120)
ax.set_yticks([0, 0.5, 1, 1.5])
ax.set_yticklabels(['0.0', '0.5', '1.0', '1.5'])
ax.set_xticks([-100, -50, 0, 50, 100])
ax.set_xticklabels(['', '-50', '0', '50', ''])
if ind+1 < (ncols*(nrows-1)):
ax.set_xticklabels([])
if ind % ncols:
ax.set_yticklabels([])
fig.text(0.5, 0.00, 'Velocity offset (km/s)', fontsize=12, ha='center',va='bottom')
fig.text(0.015, 0.5, 'Transmission', fontsize=12, rotation=90,va='center')
ndf = len(ydata) - len(pars)
print (((ydata - ymodel(x, pars))/ ysigma) **2).sum() / ndf
pl.savefig('fig/model.pdf')
pl.savefig('fig/model.png',dpi=300)
return fig
def process_options(args):
opt = adict()
filename = os.path.abspath(__file__).rsplit('/', 1)[0] + '/default.cfg'
opt = parse_config(filename)
if os.path.lexists('./plot.cfg'):
opt = parse_config('./plot.cfg', opt)
opt.atom = readatom(molecules=True)
if opt.Rfwhm is not None:
if isinstance(opt.Rfwhm, basestring):
if opt.Rfwhm == 'convolve_with_COS_FOS':
if convolve_with_COS_FOS is None:
raise ValueError('convolve_with_COS_FOS() not available')
print('Using tailored FWHM for COS/FOS data')
opt.Rfwhm = 'convolve_with_COS_FOS'
elif opt.Rfwhm.endswith('fits'):
print('Reading Resolution FWHM from', opt.Rfwhm)
res = readtabfits(opt.Rfwhm)
opt.Rfwhm = res.res / 2.354
else:
print('Reading Resolution FWHM from', opt.Rfwhm)
fh = open(opt.Rfwhm)
opt.Rfwhm = 1 / 2.354 * np.array([float(r) for r in fh])
fh.close()
else:
opt.Rfwhm = float(opt.Rfwhm)
if opt.features is not None:
print('Reading feature list from', opt.features)
opt.features = readtabfits(opt.features)
if opt.f26 is not None:
name = opt.f26
print('Reading ions and fitting regions from', name)
opt.f26 = readf26(name)
opt.f26.filename = name
if opt.transitions is not None:
print('Reading transitions from', opt.transitions)
fh = open(opt.transitions)
trans = list(fh)
fh.close()
temp = []
for tr in trans:
tr = tr.strip()
if tr and not tr.startswith('#'):
junk = tr.split()
tr = junk[0] + ' ' + junk[1]
t = findtrans(tr, atomdat=opt.atom)
temp.append(dict(name=t[0], wa=t[1][0], tr=t[1]))
opt.linelist = temp
else:
opt.linelist = readtxt(get_data_path() + 'linelists/qsoabs_lines',
names='wa,name,select')
if opt.f26 is None and opt.taulines is not None:
print('Reading ions from', opt.taulines)
fh = open(opt.taulines)
lines = []
for row in fh:
if row.lstrip().startswith('#'):
continue
items = row.split()
lines.append([items[0]] + list(map(float, items[1:])))
fh.close()
opt.lines = lines
if opt.show_regions is None:
opt.show_regions = True
if hasattr(opt, 'aodname'):
opt.aod = Table.read(opt.aodname)
return opt
