def readf26file(filename):
""" Read a f26 style file, and return with regions sorted by
minimum wavelength.
"""
vpin = readf26(filename)
isort = np.argsort([r.wmin for r in vpin.regions])
vpin.regions = vpin.regions[isort]
return vpin
def make_models(opt, path=None):
if opt.f26name is not None:
n = (path + opt.f26name if path is not None else opt.f26name)
f26 = readf26(n)
n = (path + opt.trfilename if path is not None else opt.trfilename)
transitions = read_transitions(n, atomdat)
ntrans = len(transitions)
if isinstance(opt.spfilename, basestring):
n = (path + opt.spfilename if path is not None else opt.spfilename)
sp = barak.spec.read(n)
else:
sp = opt.spfilename
wa = sp.wa
edges = barak.spec.find_bin_edges(wa) # pixel edges
dwa = edges[1:] - edges[:-1] # width per pixel
ticks = []
model = None
models = []
if opt.f26name is not None:
dw = np.median(dwa)
lines = []
for l in f26.lines:
lines.append((l['name'].replace(' ',''),l['z'],l['b'],l['logN']))
if opt.wadiv is not None:
dw1 = dw / opt.wadiv
wa1 = np.arange(wa[0], wa[-1]+0.5*dw1, dw1)
tau, ticks = find_tau(wa1, lines, atomdat)
else:
tau, ticks = find_tau(wa, lines, atomdat)
model = np.exp(-tau)
models = []
#models = [np.exp(-t) for t in taus]
if opt.wadiv is not None:
model, models = process_Rfwhm(opt.Rfwhm, wa1, model, models)
else:
model, models = process_Rfwhm(opt.Rfwhm, wa, model, models)
if opt.wadiv is not None:
model = np.interp(wa, wa1, model)
models = [np.interp(wa, wa1, m) for m in models]
return sp, transitions, model, models, ticks
from barak.pyvpfit import readf26
from astro.io import writetxt
q0107a = readf26('/home/ntejos/catalogs/Q0107/A.f26')
q0107b = readf26('/home/ntejos/catalogs/Q0107/B.f26')
q0107c = readf26('/home/ntejos/catalogs/Q0107/C.f26')
cond = q0107a.lines.name == 'H I '
a = q0107a.lines[cond]
cond = q0107b.lines.name == 'H I '
b = q0107b.lines[cond]
cond = q0107c.lines.name == 'H I '
c = q0107c.lines[cond]
a.name[:] = 'HI'
b.name[:] = 'HI'
c.name[:] = 'HI'
writetxt('/home/ntejos/catalogs/Q0107/A_HI.txt',[a.name,a.z,a.zsig,a.b,a.bsig,a.logN,a.logNsig])
writetxt('/home/ntejos/catalogs/Q0107/B_HI.txt',[b.name,b.z,b.zsig,b.b,b.bsig,b.logN,b.logNsig])
writetxt('/home/ntejos/catalogs/Q0107/C_HI.txt',[c.name,c.z,c.zsig,c.b,c.bsig,c.logN,c.logNsig])
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
from barak.pyvpfit import readf26
from astro.io import writetxt
q1022 = readf26('/home/ntejos/COS/q1022/FUV/q1022_fuv_all.f26')
cond = q1022.lines.name == 'H I '
a = q1022.lines[cond]
a.name[:] = 'HI'
writetxt('/home/ntejos/catalogs/Q1022/HI.txt',
[a.name, a.z, a.zsig, a.b, a.bsig, a.logN, a.logNsig])
def refresh_f26(self):
name = self.opt.f26.filename
print 're-reading from', name
self.opt.f26 = readf26(name)
self.opt.f26.filename = name
'NV 1238': [(90+vzero,200+vzero),(280+vzero, 403+vzero)],
'OVI 1031': [(-500,-360),(-100, -20),(45,200)],
'OVI 1037': [(-500,-290), (-100, +45), (70,200)],
}
cfg = parse_config(config)
transitions = read_transitions(cfg.trfilename, ATOMDAT)
if 1:
sp = barak.spec.read(cfg.spfilename)
ndiv = 4.
wa_dv = make_constant_dv_wa_scale(sp.wa[0], sp.wa[-1], cfg.Rfwhm / ndiv)
expand_cont_adjustment = 5
vp = readf26(cfg.f26name)
lines = vp.lines[vp.lines.name != '<>']
tau, ticks, alltau = find_tau(sp.wa, lines, ATOMDAT, per_trans=1)
model = convolve_constant_dv(sp.wa, np.exp(-tau), wa_dv, ndiv)
models = [convolve_constant_dv(sp.wa, np.exp(-t), wa_dv, ndiv) for t in
alltau]
adjust = [l for l in vp.lines if l['name'].strip() == '<>']
print 'Nadjust', adjust
if len(adjust) > 0:
regions = vp.regions
isort = regions.wmin.argsort()
print 'Applying continuum adjustments for', len(adjust), 'regions'
for val in adjust:
wav0 = ATOMDAT['<>'].wa[0] * (1 + val['z'])
i0 = regions.wmin[isort].searchsorted(wav0)
i1 = regions.wmax[isort].searchsorted(wav0)
from barak.pyvpfit import readf26
from astro.io import writetxt
q1022 = readf26('/home/ntejos/COS/q1022/FUV/q1022_fuv_all.f26')
cond = q1022.lines.name == 'H I '
a = q1022.lines[cond]
a.name[:] = 'HI'
writetxt('/home/ntejos/catalogs/Q1022/HI.txt',[a.name,a.z,a.zsig,a.b,a.bsig,a.logN,a.logNsig])
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 refresh_f26(self):
name = self.opt.f26.filename
print 're-reading from', name
self.opt.f26 = readf26(name)
self.opt.f26.filename = name
from barak.pyvpfit import readf26 from barak.absorb import findtrans, readatom, find_tau from barak.constants import c_kms from barak.spec import make_constant_dv_wa_scale, convolve_constant_dv from barak.convolve import convolve_psf import pylab as pl import numpy as np f26 = readf26(f26name) atomdat = readatom(molecules=1) spfilename = '' trfilename = '' vmin = vmax = 399 wadiv = None Rfwhm = 6.6 osc = False residuals = True redshift = 0.56 unrelated = [] # ( 3863.451, 3865.529), # ( 3855.399, 3859.330), # ( 4075.662, 4076.668), # ( 4079.430, 4082.960), # ( 3906.116, 3908.287), # ( 3898.097, 3899.218), # ( 4509.955, 4512.281), # ( 4503.099, 4507.387), # ( 4532.218, 4544.106), # ( 4314.625, 4315.922),
from barak.pyvpfit import readf26
from astro.io import writetxt
q0107a = readf26('/home/ntejos/catalogs/Q0107/A.f26')
q0107b = readf26('/home/ntejos/catalogs/Q0107/B.f26')
q0107c = readf26('/home/ntejos/catalogs/Q0107/C.f26')
cond = q0107a.lines.name == 'H I '
a = q0107a.lines[cond]
cond = q0107b.lines.name == 'H I '
b = q0107b.lines[cond]
cond = q0107c.lines.name == 'H I '
c = q0107c.lines[cond]
a.name[:] = 'HI'
b.name[:] = 'HI'
c.name[:] = 'HI'
writetxt('/home/ntejos/catalogs/Q0107/A_HI.txt',
[a.name, a.z, a.zsig, a.b, a.bsig, a.logN, a.logNsig])
writetxt('/home/ntejos/catalogs/Q0107/B_HI.txt',
[b.name, b.z, b.zsig, b.b, b.bsig, b.logN, b.logNsig])
writetxt('/home/ntejos/catalogs/Q0107/C_HI.txt',
[c.name, c.z, c.zsig, c.b, c.bsig, c.logN, c.logNsig])
'NV 1238': [(90 + vzero, 200 + vzero), (280 + vzero, 403 + vzero)],
'OVI 1031': [(-500, -360), (-100, -20), (45, 200)],
'OVI 1037': [(-500, -290), (-100, +45), (70, 200)],
}
cfg = parse_config(config)
transitions = read_transitions(cfg.trfilename, ATOMDAT)
if 1:
sp = barak.spec.read(cfg.spfilename)
ndiv = 4.
wa_dv = make_constant_dv_wa_scale(sp.wa[0], sp.wa[-1], cfg.Rfwhm / ndiv)
expand_cont_adjustment = 5
vp = readf26(cfg.f26name)
lines = vp.lines[vp.lines.name != '<>']
tau, ticks, alltau = find_tau(sp.wa, lines, ATOMDAT, per_trans=1)
model = convolve_constant_dv(sp.wa, np.exp(-tau), wa_dv, ndiv)
models = [
convolve_constant_dv(sp.wa, np.exp(-t), wa_dv, ndiv) for t in alltau
]
adjust = [l for l in vp.lines if l['name'].strip() == '<>']
print 'Nadjust', adjust
if len(adjust) > 0:
regions = vp.regions
isort = regions.wmin.argsort()
print 'Applying continuum adjustments for', len(adjust), 'regions'
for val in adjust:
wav0 = ATOMDAT['<>'].wa[0] * (1 + val['z'])
i0 = regions.wmin[isort].searchsorted(wav0)
