def get_vmnx(components):
zlim_sys = ltu.z_from_dv(self.vlim, self.zabs, rel=False)
zmin, zmax = zlim_sys
for component in components:
zlim_comp = ltu.z_from_dv(component.vlim, component.zcomp, rel=False)
zmin = min(zmin, zlim_comp[0])
zmax = max(zmax, zlim_comp[1])
# Convert back to velocities
return ltu.dv_from_z([zmin,zmax], self.zabs, rel=False)
def get_vmnx(components):
zlim_sys = ltu.z_from_dv(self.vlim, self.zabs, rel=False)
zmin, zmax = zlim_sys
for component in components:
zlim_comp = ltu.z_from_dv(component.vlim, component.zcomp, rel=False)
zmin = min(zmin, zlim_comp[0])
zmax = max(zmax, zlim_comp[1])
# Convert back to velocities
return ltu.dv_from_z([zmin,zmax], self.zabs, rel=False)
def update_component_vel(self):
"""Change the velocities of each component to rest frame of zsys
"""
from linetools.analysis.zlimits import zLimits
for i, comp in enumerate(self._components):
dv = ltu.dv_from_z(comp.zcomp, self.zabs)
zmin = ltu.z_from_dv(comp.limits.vlim[0] + dv, self.zabs)
zmax = ltu.z_from_dv(comp.limits.vlim[1] + dv, self.zabs)
newzlim = zLimits(self.zabs, (zmin, zmax))
comp.limits = newzlim
comp.attrib['vel'] = comp.attrib['vel'] + dv
def dla_stat(DLAs, qsos, vprox=None, buff=3000.*u.km/u.s,
zem_min=0., flg_zsrch=0, vmin=0.*u.km/u.s,
LLS_CUT=None, partial=False, prox=False,
zem_tol=0.03):
""" Identify the statistical DLA in a survey
Note that this algorithm ignores any existing mask
Parameters
----------
DLAs : DLASurvey
qsos : Table
keys must include RA, DEC, ZEM, Z_START
vmin : Quantity
vprox
maxdz
zem_min
buff : Quantity
Buffer velocity in Proximate analysis [not ready for this]
NHI_cut
flg_zsrch
dz_toler
partial : bool, optional
Analyze partial LLS? [pLLS]
prox : bool, optional
Proximate LLS? [PLLS]
zem_tol : float, optional
Tolerance in zem
Returns
-------
msk_smpl : bool array
True = statistical
"""
import warnings
from astropy.coordinates import SkyCoord, match_coordinates_sky
# Check for mask
if DLAs.mask is not None:
warnings.warn("Resetting mask to None. Be careful here")
DLAs.mask = None
# DLA
msk_smpl = DLAs.zem != DLAs.zem
#zmax = ltu.z_from_dv(vprox, qsos['ZEM'])
zmin = ltu.z_from_dv(vmin*np.ones(len(qsos)), qsos['Z_START'].data) # vmin must be array-like to be applied to each individual qsos['Z_START']
# Make some lists
qsos_coord = SkyCoord(ra=qsos['RA'], dec=qsos['DEC'])
dla_coord = DLAs.coord
idx, d2d, d3d = match_coordinates_sky(dla_coord, qsos_coord, nthneighbor=1)
close = d2d < 1.*u.arcsec
for qq, idla in enumerate(DLAs._abs_sys):
# In stat?
if close[qq]:
if np.abs(idla.zem-qsos['ZEM'][idx[qq]]) < zem_tol:
if ((idla.zabs >= zmin[idx[qq]]) &
(idla.zabs <= qsos['Z_END'][idx[qq]]) & (qsos[idx[qq]]['FLG_BAL'] != 2)):
msk_smpl[qq] = True
# Return
return msk_smpl
def load_HST_ACS(cls, tau_LL=2, sample='stat'):
""" Load the LLS survey using HST/ACS by O'Meara et al. 2013, ApJ, 765, 137
Parameters
----------
tau_LL : int, optional
Sets sample
sample : str, optional
Returns
-------
lls_survey : IGMSurvey
"""
if tau_LL == 2:
NHI_cut = 17.49
# LLS File
lls_fil = pyigm_path + '/data/LLS/HST/lls_acs_stat_LLS.fits.gz'
lls = Table.read(lls_fil)
# Generate coords
scoords = [
lls['QSO_RA'][ii] + ' ' + lls['QSO_DEC'][ii]
for ii in range(len(lls))
]
coords = SkyCoord(scoords, unit=(u.hourangle, u.deg))
lls['RA'] = coords.ra.value
lls['DEC'] = coords.dec.value
# Read
lls_survey = cls.from_sfits(lls, coords=coords)
lls_survey.ref = 'HST-ACS'
# QSOs file
qsos_fil = pyigm_path + '/data/LLS/HST/lls_acs_qsos_sn1020.fits.gz'
qsos = Table.read(qsos_fil)
lls_survey.sightlines = qsos
# Z_START, Z_END
# Using tau=2
if tau_LL == 2:
lls_survey.sightlines['Z_START'] = np.maximum(
qsos['ZT2'], qsos['ZLLS'][:, 0])
else:
pdb.set_trace()
# zend
zend = ltu.z_from_dv(-3000 * u.km / u.s * np.ones(len(qsos)),
lls_survey.sightlines['ZEM'])
lls_survey.sightlines['Z_END'] = zend
# Stat me
mask = lls_stat(lls_survey, NHI_cut=NHI_cut)
if sample == 'stat':
lls_survey.mask = mask
else:
lls_survey.mask = ~mask
# Return
print('HST-ACS: Loaded')
return lls_survey
def set(self, inp, chk_z=False):#, itype='zlim'):
""" Set (or reset) limits relative to self._z
but does not change self._z
Parameters
----------
inp : tuple, list, or Quantity array
* If floats -> zlim : Redshift limits
* If Quantity array with length units -> wvlim : Wavelength limits
* If Quantity array with speed units -> vlim : Velocity limits
chk_z : bool, optional
Demand that zlim bound z
Often not desired as z can be somewhat arbitrary
Returns
-------
"""
# Checks
if not isinstance(inp, (tuple, list, Quantity)):
raise IOError("Input must be tuple, list or Quantity.")
#if np.isclose(self._z, 0.):
# warnings.warn("Redshift=0. If this is unexpected, set _z and reset limits")
if isinstance(inp[0], float): # assume zlim
self._zlim = inp
elif isinstance(inp[0], Quantity): # may be wvlim or vlim
if inp[0].cgs.unit == u.cm:
self._zlim = (inp/self._wrest).decompose().to(
u.dimensionless_unscaled).value - 1.
elif inp[0].cgs.unit == u.cm/u.s:
self._zlim = ltu.z_from_dv(inp, self._z)
else:
raise IOError("Quantity must be length or speed.")
else:
raise IOError("Input must be floats or Quantities.")
# Check
if chk_z:
if (self._zlim[0] > self._z) or (self._zlim[1] < self._z):
#import pdb; pdb.set_trace()
raise IOError("Invalid input. `zlim` does not bound `z`.")
# Reset
self.reset()
def set(self, inp, chk_z=False):#, itype='zlim'):
""" Over-ride = to re-init values
Parameters
----------
inp : tuple, list, or Quantity array
* If floats -> zlim : Redshift limits
* If Quantity array with length units -> wvlim : Wavelength limits
* If Quantity array with speed units -> vlim : Velocity limits
chk_z : bool, optional
Demand that zlim bound z
Often not desired as z can be somewhat arbitrary
Returns
-------
"""
# Checks
if not isinstance(inp, (tuple, list, Quantity)):
raise IOError("Input must be tuple, list or Quantity.")
if np.isclose(self._z, 0.):
warnings.warn("Redshift=0. If this is unexpected, set _z and reset limits")
if isinstance(inp[0], float): # assume zlim
self._zlim = inp
elif isinstance(inp[0], Quantity): # may be wvlim or vlim
try: # assume wvlim
self._zlim = (inp/self._wrest).decompose().to(
u.dimensionless_unscaled).value - 1.
except UnitConversionError:
try: # assume vlim
self._zlim = ltu.z_from_dv(inp, self._z)
except ValueError:
raise IOError("Quantity must be length or speed.")
else:
raise IOError("Input must be floats or Quantities.")
# Check
if chk_z:
if (self._zlim[0] > self._z) or (self._zlim[1] < self._z):
#import pdb; pdb.set_trace()
raise IOError("Invalid input. `zlim` does not bound `z`.")
# Reset
self.reset()
def test_z_from_dv():
z = ltu.z_from_dv(1000. * u.km / u.s, 2.)
np.testing.assert_allclose(z, 2.0100236684175417)
def __init__(self,
radec,
Zion,
zcomp,
vlim,
Ej=0. / u.cm,
A=None,
Ntup=None,
comment='',
name=None,
stars=None,
reliability='none'):
""" Initiator
Parameters
----------
radec : tuple or SkyCoord
(RA,DEC) in deg or astropy.coordinate.SkyCoord
Zion : tuple
Atomic number, ion -- (int,int)
e.g. (8,1) for OI
Note: (-1, -1) is special and is meant for moleculer (e.g. H2)
This notation will most likely change in the future.
zcomp : float
Absorption component redshift
vlim : Quantity array
Velocity limits of the component w/r to `z`
e.g. [-300,300]*u.km/u.s
A : int, optional
Atomic mass -- used to distinguish isotopes
Ntup : tuple
(int,float,two-element list,tuple or array)
(flag_N, logN, sig_logN)
flag_N : Flag describing N measurement (0: no info; 1: detection; 2: saturated; 3: non-detection)
logN : log10 N column density
sig_logN : Error in log10 N. Two elements are expected but not required
Ej : Quantity, optional
Energy of lower level (1/cm)
stars : str, optional
asterisks to add to name, e.g. '**' for CI**
Required if name=None and Ej>0.
reliability : str, optional
Reliability of AbsComponent
'a' - reliable
'b' - possible
'c' - uncertain
'none' - not defined (default)
comment : str, optional
A comment, default is ``
"""
# Required
self.coord = ltu.radec_to_coord(radec)
self.Zion = Zion
# Limits
zlim = ltu.z_from_dv(vlim, zcomp)
self.limits = zLimits(zcomp, zlim.tolist())
# Attributes
self.attrib = init_attrib.copy()
# Optional
self.A = A
self.Ej = Ej
self.stars = stars
self.comment = comment
if Ntup is not None:
self.attrib['flag_N'] = Ntup[0]
self.attrib['logN'] = Ntup[1]
if isiterable(Ntup[2]):
self.attrib['sig_logN'] = np.array(Ntup[2])
else:
self.attrib['sig_logN'] = np.array([Ntup[2]] * 2)
_, _ = ltaa.linear_clm(self.attrib) # Set linear quantities
# Name
if (name is None) and (self.Zion != (-1, -1)):
iname = ions.ion_to_name(self.Zion, nspace=0)
if self.Ej.value > 0: # Need to put *'s in name
if stars is not None:
iname += stars
else:
warnings.warn(
"No stars provided. Adding one because Ej > 0.")
iname += '*'
self.name = '{:s}_z{:0.5f}'.format(iname, self.zcomp)
elif (name is None) and (self.Zion == (-1, -1)):
self.name = 'mol_z{:0.5f}'.format(self.zcomp)
else:
self.name = name
# reliability
if reliability not in ['a', 'b', 'c', 'none']:
raise ValueError(
"Input reliability `{}` not valid.".format(reliability))
self.reliability = reliability
# AbsLines
self._abslines = []
def load_data(self, **kwargs):
#
#q8file = resource_filename('pyigm', 'data/CGM/QPQ/qpq8_all_measured.dat')
q8file = self.data_file
if self.from_dict:
q8file = self.data_file
qpq8dict = CGMAbsSurvey.from_json(q8file)
ism = LineList('ISM')
qpq8dict.build_systems_from_dict(llist=ism)
self.survey_data = qpq8dict
#self.cgm_abs = qpq8dict.cgm_abs
else:
qpqdata = Table.read(q8file, format='ascii')
#nmax = len(qpqdata) # max number of QSOs
q8filecoord = resource_filename('pyigm',
'data/CGM/QPQ/qpq8_pairs.fits')
qpqdatacoord = Table.read(q8filecoord)
if self.nmax is not None:
nmax = self.nmax
else:
nmax = len(qpqdatacoord) #(qpqdata)
# match names with qpqdatacoord
qnames = []
for i in range(len(qpqdatacoord)):
qname = qpqdatacoord['QSO'][i].strip()
qnames.append(qname[-10:])
qnames2 = []
for i in range(len(qpqdata)):
qname = qpqdata['Pair'][i]
qnames2.append(qname)
for j in range(nmax): # i,j
# match names with qpqdatacoord
i = np.where(np.asarray(qnames2) == qnames[j])[0]
# Instantiate the galaxy
gal = Galaxy((qpqdatacoord['RAD'][j], qpqdatacoord['DECD'][j]),
z=qpqdatacoord['Z_FG'][j])
gal.L_BOL = qpqdatacoord['L_BOL'][j]
gal.L_912 = qpqdatacoord['L_912'][j]
gal.G_UV = qpqdatacoord['G_UV'][j]
gal.zsig = qpqdatacoord['Z_FSIG'][j] * u.km / u.s
# Instantiate the IGM System
igm_sys = IGMSystem(
(qpqdatacoord['RAD_BG'][j], qpqdatacoord['DECD_BG'][j]),
qpqdatacoord['Z_FG'][j], [-5500, 5500.] * u.km / u.s,
abs_type='CGM')
# Redshifts: QSO emission redshifts
igm_sys.zem = qpqdatacoord['Z_BG'][j]
igm_sys.NHI = qpqdata['HIcol'][i]
igm_sys.sig_NHI = [
qpqdata['HIcolhierr'][i], qpqdata['HIcolloerr'][i]
]
igm_sys.s2n_lya = qpqdatacoord['S2N_LYA'][j]
iname = qpqdata['Pair'][i][0] #+'_'+qpqdata['subsys'][i]
# Instantiate
rho = qpqdatacoord['R_PHYS'][j] * u.kpc
cgabs = CGMAbsSys(gal, igm_sys, name=iname, rho=rho, **kwargs)
### add metal lines
### not included CII*, SiII*
lines = [
['CII 1334'], ## ['CII* 1335'],
['CIV 1548', 'CIV 1550'],
['NI 1134', 'NI 1199'],
['NII 1083'],
['NV 1238', 'NV 1242'],
['OI 1302'],
['OVI 1037'],
['MgI 2852'],
['MgII 2796', 'MgII 2803'],
['AlII 1670'],
['AlIII 1854', 'AlIII 1862'],
[
'SiII 1190', 'SiII 1193', 'SiII 1304', 'SiII 1260',
'SiII 1526', 'SiII 1808'
], ## ['SiII* 1264'],
['SiIII 1206'],
['SiIV 1393', 'SiIV 1402'],
[
'FeII 1608', 'FeII 2344', 'FeII 2374', 'FeII 2382',
'FeII 2586', 'FeII 2600'
],
['FeIII 1122']
]
for kk in i:
for icmp in range(len(lines)):
abslines = []
for ii in range(len(lines[icmp])):
wave0 = float(lines[icmp][ii].split(' ')[1])
ewstr = str(lines[icmp][ii].split(' ')[1]) + 'EW'
ewerrstr = str(
lines[icmp][ii].split(' ')[1]) + 'EWerr'
if ewstr == '1808EW':
ewstr = '1808E'
if ewerrstr == '1122EWerr':
ewerrstr = '122EWerr'
if qpqdata[ewstr][kk] != '/':
# find z
v0 = 0.5 * (
qpqdata['v_lobound'][kk] +
qpqdata['v_upbound'][kk]) * u.km / u.s
dv = v0
zref = igm_sys.zabs
z_cmp = ltu.z_from_dv(dv, zref)
## vlim
v1 = qpqdata['v_lobound'][kk] * u.km / u.s
z1 = ltu.z_from_dv(v1, zref)
v1_cmp = ltu.dv_from_z(z1, z_cmp)
v2 = qpqdata['v_upbound'][kk] * u.km / u.s
z2 = ltu.z_from_dv(v2, zref)
v2_cmp = ltu.dv_from_z(z2, z_cmp)
# iline
iline = AbsLine(wave0 * u.AA,
closest=True,
z=z_cmp)
iline.attrib['coord'] = igm_sys.coord
## EW
iline.attrib['EW'] = float(
qpqdata[ewstr][kk]) * u.AA # Rest EW
iline.attrib['sig_EW'] = float(
qpqdata[ewerrstr][kk]) * u.AA
flgew = 1
if iline.attrib[
'EW'] < 3. * iline.attrib['sig_EW']:
flgew = 3
iline.attrib['flag_EW'] = flgew
## column densities
colstr = str(
lines[icmp][ii].split(' ')[0]) + 'col'
colerrstr = str(
lines[icmp][ii].split(' ')[0]) + 'colerr'
iline.attrib['logN'] = qpqdata[colstr][kk]
iline.attrib['sig_logN'] = qpqdata[colerrstr][
kk]
abslines.append(iline)
if len(abslines) > 0:
comp = AbsComponent.from_abslines(abslines,
chk_vel=False)
comp.limits._vlim = [v1_cmp.value, v2_cmp.value
] * u.km / u.s
cgabs.igm_sys.add_component(comp)
# add ang_sep
qsocoord = SkyCoord(ra=qpqdatacoord['RAD'][j],
dec=qpqdatacoord['DECD'][j],
unit='deg')
bgcoord = SkyCoord(ra=qpqdatacoord['RAD_BG'][j],
dec=qpqdatacoord['DECD_BG'][j],
unit='deg')
cgabs.ang_sep = qsocoord.separation(bgcoord).to('arcsec')
self.cgm_abs.append(cgabs)
def cgmabssys_from_sightline_field(field,
sightline,
rho_max=300. * u.kpc,
minz=0.001,
maxz=None,
dv_max=400. * u.km / u.s,
embuffer=None,
dummysys=True,
dummyspec=None,
linelist=None,
debug=False,
**kwargs):
"""Instantiate list of CgmAbsSys objects from IgmgGalaxyField and IGMSightline.
Parameters
----------
field : IgmGalaxyField
sightline : IGMSightline
rho_max : Quantity, optional
Maximum impact parameter for associated galaxies
minz : float, optional
Minimum redshift for galaxy/absorber search
maxz : float, optional
Maximum redshift for galaxy/absorber search
dv_max : Quantity, optional
Maximum galaxy-absorber velocity separation
embuffer : Quantity, optional
Velocity buffer between background source (e.g., QSO) and CGMAbsSys
dummysys : bool, optional
Passed on to 'cgm_from_galaxy_igmsystems()'. If True, create CGMAbsSyS
even if no matching IGMSystem is found in any sightline for some galaxy.
dummyspec : XSpectrum1D, optional
Spectrum object to attach to dummy AbsLine/AbsComponent objects when
adding IGMSystems if dummysys is True
linelist : LineList, optional
ListList from which to add dummy line in case of no IGMSystem match
Returns
-------
cgmabslist : list
List of CgmAbsSys objects
"""
if dummyspec is None:
dummyspec = sightline._abssystems[0]._components[0]._abslines[0].analy[
'spec']
if linelist is None:
from linetools.spectralline import AbsLine
linelist = LineList('ISM')
if embuffer is not None:
try:
bufmax = ltu.z_from_dv(-embuffer, field.zem)
if maxz is not None:
zmax = np.max(bufmax, maxz)
else:
zmax = bufmax
except:
zmax = maxz
else:
zmax = maxz
closegals = get_close_galaxies(field, rho_max, minz, zmax)
if debug:
closegals = closegals[0:10]
cgmabslist = []
for i, gal in enumerate(closegals):
#print('i={:d}'.format(i))
galobj = Galaxy((gal['RA'], gal['DEC']), z=gal['Z'])
cgmobj = cgm_from_galaxy_igmsystems(galobj,
sightline._abssystems,
dv_max=dv_max,
dummysys=dummysys,
dummyspec=dummyspec,
rho_max=rho_max,
linelist=linelist,
**kwargs)
cgmabslist.extend(cgmobj)
return cgmabslist
def cgm_from_galaxy_igmsystems(galaxy,
igmsystems,
rho_max=300 * u.kpc,
dv_max=400 * u.km / u.s,
cosmo=None,
dummysys=False,
dummyspec=None,
verbose=True,
**kwargs):
""" Generate a list of CGMAbsSys objects given an input galaxy and a list of IGMSystems
Parameters
----------
galaxy : Galaxy
igmsystems : list
list of IGMSystems
rho_max : Quantity
Maximum projected separation from sightline to galaxy
dv_max
Maximum velocity offset between system and galaxy
dummysys: bool, optional
If True, instantiate CGMAbsSys even if no match is found in igmsystems
dummyspec : XSpectrum1D, optional
Spectrum object to attach to dummy AbsLine/AbsComponent objects when
adding IGMSystems if dummysys is True.
Returns
-------
cgm_list : list
list of CGM objects generated
"""
from pyigm.cgm.cgm import CGMAbsSys
# Cosmology
if cosmo is None:
cosmo = cosmology.Planck15
if dummysys is True:
if dummyspec is None:
dummyspec = igmsystems[0]._components[0]._abslines[0].analy['spec']
dummycoords = igmsystems[0].coord
# R -- speed things up
rho, angles = calc_cgm_rho(galaxy, igmsystems, cosmo, **kwargs)
if len(igmsystems) == 1: # Kludge
rho = u.Quantity([rho])
angles = u.Quantity([angles])
# dv
igm_z = np.array([igmsystem.zabs for igmsystem in igmsystems])
dv = ltu.dv_from_z(igm_z, galaxy.z)
# Rules
match = np.where((rho < rho_max) & (np.abs(dv) < dv_max))[0]
### If none, see if some system has a component that's actually within dv_max
if (len(match) == 0) & (rho[0] < rho_max):
zcomps = []
sysidxs = []
for i, csys in enumerate(igmsystems):
thesezs = [comp.zcomp for comp in csys._components]
sysidxs.extend([i] * len(thesezs))
zcomps.extend(thesezs)
zcomps = np.array(zcomps)
sysidxs = np.array(sysidxs)
dv_comps = ltu.dv_from_z(zcomps, galaxy.z)
match = np.unique(sysidxs[np.where(np.abs(dv_comps) < dv_max)[0]])
if len(match) == 0:
if dummysys is False:
print(
"No IGMSystem paired to this galaxy. CGM object not created.")
return []
else:
if verbose:
print("No IGMSystem match found. Attaching dummy IGMSystem.")
dummysystem = IGMSystem(dummycoords, galaxy.z, vlim=None)
dummycomp = AbsComponent(dummycoords, (1, 1), galaxy.z,
[-100., 100.] * u.km / u.s)
dummycomp.flag_N = 3
dummyline = AbsLine(
'HI 1215',
**kwargs) # Need an actual transition for comp check
dummyline.analy['spec'] = dummyspec
dummyline.attrib['coord'] = dummycoords
dummycomp.add_absline(dummyline, chk_vel=False, chk_sep=False)
dummysystem.add_component(dummycomp, chk_vel=False, chk_sep=False)
cgm = CGMAbsSys(galaxy, dummysystem, cosmo=cosmo, **kwargs)
cgm_list = [cgm]
else:
# Loop to generate
cgm_list = []
for imatch in match:
# Instantiate new IGMSystem
# Otherwise, updates to the IGMSystem cross-pollinate other CGMs
sysmatch = igmsystems[imatch]
newisys = sysmatch.copy()
# Handle z limits
zlim = ltu.z_from_dv((-dv_max.value, dv_max.value) * u.km / u.s,
galaxy.z)
newlims = zLimits(galaxy.z, zlim.tolist())
newisys.limits = newlims
# Allow for components extending beyond dv_max
newisys.update_vlim()
newisys.update_component_vel()
# Finish
cgm = CGMAbsSys(galaxy,
newisys,
cosmo=cosmo,
rho=rho[imatch],
ang_sep=angles[imatch],
**kwargs)
cgm_list.append(cgm)
# Return
return cgm_list
def writelinepars(fitpars,
fiterrors,
parinfo,
specfile,
outfilename,
linecmts=None):
'''
Write fit parameters out to file.
Parameters
----------
fitpars : list of lists
Parameters for fit ready for fitter!
fiterrors : array of numpy vectors
Error array for the fitting initialized to '0' for each param
parinfo : array of arrays
Flags to be used in fit
specfile : str
Name of the input file containing the spectrum
outfilename : str
Parameter output filename
linecmts : list of lists, optional
Reliability flags and comments, e.g., from igmguesses
'''
import os
### Set outputs and open files
bigfiletowrite = cfg.largeVPparfile
filetowrite = outfilename
if os.path.isfile(filetowrite):
VPparfile = open(filetowrite, 'wb')
bigparfile = open(bigfiletowrite, 'ab') # Append to the running list
else:
VPparfile = open(filetowrite, 'wb')
bigparfile = open(bigfiletowrite, 'wb')
### Prep header of line parameter file
if linecmts is not None:
header = b'specfile|restwave|zsys|col|sigcol|bval|sigbval|vel|sigvel|nflag|bflag|vflag|vlim1|vlim2|wobs1|wobs2|pix1|pix2|z_comp|trans|rely|comment \n'
else:
header = b'specfile|restwave|zsys|col|sigcol|bval|sigbval|vel|sigvel|nflag|bflag|vflag|vlim1|vlim2|wobs1|wobs2|pix1|pix2|z_comp|trans \n'
VPparfile.write(header)
bigparfile.write(header)
### Grab parameters/info for each line
for i in range(len(fitpars[0])):
zline = fitpars[3][i]
vlim1 = fitpars[5][i]
vlim2 = fitpars[6][i]
restwave = fitpars[0][i]
wobs1 = restwave * (1 + zline + vlim1 / 299792.458)
wobs2 = restwave * (1 + zline + vlim2 / 299792.458)
pix1 = jbg.closest(cfg.wave, wobs1)
pix2 = jbg.closest(cfg.wave, wobs2)
trans = atomicdata.lam2ion(fitpars[0][i])
z_comp = ltu.z_from_dv(fitpars[4][i] * u.km / u.s, zline)
if linecmts is not None:
towrite = jbg.pipedelimrow([
specfile, restwave,
round(zline, 5),
round(fitpars[1][i], 3),
round(fiterrors[1][i], 3),
round(fitpars[2][i], 3),
round(fiterrors[2][i], 3),
round(fitpars[4][i], 3),
round(fiterrors[4][i], 3), parinfo[1][i], parinfo[2][i],
parinfo[4][i], vlim1, vlim2, wobs1, wobs2, pix1, pix2,
round(z_comp, 5), trans, linecmts[0][i], linecmts[1][i]
])
else:
towrite = jbg.pipedelimrow([
specfile, restwave,
round(zline, 5),
round(fitpars[1][i], 3),
round(fiterrors[1][i], 3),
round(fitpars[2][i], 3),
round(fiterrors[2][i], 3),
round(fitpars[4][i], 3),
round(fiterrors[4][i], 3), parinfo[1][i], parinfo[2][i],
parinfo[4][i], vlim1, vlim2, wobs1, wobs2, pix1, pix2,
round(z_comp, 5), trans
])
VPparfile.write(towrite.encode())
bigparfile.write(towrite.encode())
VPparfile.close()
bigparfile.close()
print('Line parameters written to:')
print(filetowrite)
def writelinepars(fitpars,fiterrors,parinfo, specfile, outfilename, linecmts=None): ''' Write fit parameters out to file. Parameters ---------- fitpars : list of lists Parameters for fit ready for fitter! fiterrors : array of numpy vectors Error array for the fitting initialized to '0' for each param parinfo : array of arrays Flags to be used in fit specfile : str Name of the input file containing the spectrum outfilename : str Parameter output filename linecmts : list of lists, optional Reliability flags and comments, e.g., from igmguesses ''' import os ### Set outputs and open files bigfiletowrite = cfg.largeVPparfile filetowrite = outfilename if os.path.isfile(filetowrite): VPparfile = open(filetowrite, 'wb') bigparfile = open(bigfiletowrite, 'ab') # Append to the running list else: VPparfile = open(filetowrite, 'wb') bigparfile = open(bigfiletowrite, 'wb') ### Prep header of line parameter file if linecmts is not None: header = 'specfile|restwave|zsys|col|sigcol|bval|sigbval|vel|sigvel|nflag|bflag|vflag|vlim1|vlim2|wobs1|wobs2|pix1|pix2|z_comp|trans|rely|comment \n' else: header = 'specfile|restwave|zsys|col|sigcol|bval|sigbval|vel|sigvel|nflag|bflag|vflag|vlim1|vlim2|wobs1|wobs2|pix1|pix2|z_comp|trans \n' VPparfile.write(header) bigparfile.write(header) ### Grab parameters/info for each line for i in range(len(fitpars[0])): zline = fitpars[3][i] vlim1 = fitpars[5][i] vlim2 = fitpars[6][i] restwave = fitpars[0][i] wobs1 = restwave * (1 + zline + vlim1 / 299792.458) wobs2 = restwave * (1 + zline + vlim2 / 299792.458) pix1 = jbg.closest(cfg.wave, wobs1) pix2 = jbg.closest(cfg.wave, wobs2) trans = atomicdata.lam2ion(fitpars[0][i]) z_comp = ltu.z_from_dv(fitpars[4][i]*u.km/u.s, zline) if linecmts is not None: towrite = jbg.pipedelimrow( [specfile, restwave, round(zline, 5), round(fitpars[1][i], 3), round(fiterrors[1][i], 3), round(fitpars[2][i], 3), round(fiterrors[2][i], 3), round(fitpars[4][i], 3), round(fiterrors[4][i], 3), parinfo[1][i], parinfo[2][i], parinfo[4][i], vlim1, vlim2, wobs1, wobs2, pix1, pix2,round(z_comp, 5), trans, linecmts[0][i],linecmts[1][i]]) else: towrite = jbg.pipedelimrow( [specfile, restwave, round(zline, 5), round(fitpars[1][i], 3), round(fiterrors[1][i], 3), round(fitpars[2][i], 3), round(fiterrors[2][i], 3), round(fitpars[4][i], 3), round(fiterrors[4][i], 3), parinfo[1][i], parinfo[2][i], parinfo[4][i], vlim1, vlim2, wobs1, wobs2, pix1, pix2, round(z_comp, 5),trans]) VPparfile.write(towrite) bigparfile.write(towrite) VPparfile.close() bigparfile.close() print 'Line parameters written to:' print filetowrite
def lls_stat(LLSs,
qsos,
vprox=3000. * u.km / u.s,
maxdz=99.99,
zem_min=0.,
NHI_cut=17.5,
flg_zsrch=0,
dz_toler=0.04,
LLS_CUT=None,
partial=False,
prox=False):
""" Identify the statistical LLS in a survey
Parameters
----------
vprox
maxdz
zem_min
NHI_cut
flg_zsrch
dz_toler
partial : bool, optional
Analyze partial LLS? [pLLS]
prox : bool, optional
Proximate LLS? [PLLS]
Returns
-------
msk_smpl : bool array
True = statistical
"""
# Search redshift
if flg_zsrch == 0:
zsrch = qsos['ZT2']
elif flg_zsrch == 1:
zsrch = qsos['ZT1']
elif flg_zsrch == 2:
zsrch = qsos['ZT0']
# Modify by LLS along QSO sightline as required
if LLS_CUT is not None:
pdb.set_trace()
#zsrch = zsrch > qsos.zlls[LLS_CUT]
# LLS
msk_smpl = LLSs.zem != LLSs.zem
zmax = ltu.z_from_dv(
vprox * np.ones(len(qsos)), qsos['ZEM'].data
) # vprox must be array-like to be applied to each individual qsos['ZEM']
# Make some lists
lls_coord = LLSs.coord
lls_zem = LLSs.zem
lls_zabs = LLSs.zabs
qsos_coord = SkyCoord(ra=qsos['RA'] * u.deg, dec=qsos['DEC'] * u.deg)
for qq, ills in enumerate(LLSs._abs_sys):
# Two LLS on one sightline?
small_sep = ills.coord.separation(lls_coord) < 3.6 * u.arcsec
close_zem = np.abs(ills.zem - lls_zem) < 0.03
close_zabs = np.abs(ills.zabs - lls_zabs) < dz_toler
if np.sum(small_sep & close_zem & close_zabs) != 1:
raise ValueError("LLS are probably too close in z")
# Cut on NHI
if partial & (ills.NHI > NHI_cut):
continue
if ~partial & (ills.NHI <= NHI_cut):
continue
# Match to QSO RA, DEC
idx = np.where((ills.coord.separation(qsos_coord) < 3.6 * u.arcsec)
& (np.abs(qsos['ZEM'] - ills.zem) < 0.03))[0]
if len(idx) != 1:
raise ValueError("Problem with matches")
# Query redshift
if ((zsrch[idx] > 0.) &
(ills.zabs > max(zsrch[idx], qsos['ZEM'][idx] - maxdz) - 1e-4) &
(qsos['ZEM'][idx] > zem_min)):
if (~prox) & (ills.zabs < zmax[idx]): # Intervening
msk_smpl[qq] = True
if prox & (ills.zabs >= zmax[idx]): # Proximate
msk_smpl[qq] = True
# Return
return msk_smpl
def load_SDSS_DR7(cls, sample='stat'):
""" Load the LLS from the SDSS-DR7 survey (Prochaska+10, ApJ, 718, 391)
Parameters
----------
sample : str, optional
LLS sample
stat : Statistical sample
all : All LLS
nonstat : Non-statistical sample
Returns
-------
lls_survey : IGMSurvey
"""
# LLS File
lls_fil = pyigm_path + '/data/LLS/SDSS/lls_dr7_stat_LLS.fits.gz'
print('SDSS-DR7: Loading LLS file {:s}'.format(lls_fil))
lls = Table.read(lls_fil)
# Rename some columns?
lls.rename_column('QSO_RA', 'RA')
lls.rename_column('QSO_DEC', 'DEC')
# Instantiate
scoords = [
lls['RA'][ii] + ' ' + lls['DEC'][ii] for ii in range(len(lls))
]
coords = SkyCoord(scoords, unit=(u.hourangle, u.deg))
lls_survey = cls.from_sfits(lls, coords=coords)
lls_survey.ref = 'SDSS-DR7'
# QSOs file
qsos_fil = pyigm_path + '/data/LLS/SDSS/lls_dr7_qsos_sn2050.fits.gz'
print('SDSS-DR7: Loading QSOs file {:s}'.format(qsos_fil))
qsos = Table.read(qsos_fil)
lls_survey.sightlines = qsos
# All?
if sample == 'all':
return lls_survey
# Stat
# z_em cut
zem_min = 3.6
lowz_q = qsos['ZEM'] < zem_min
qsos['ZT2'][lowz_q] = 99.99
dz_start = 0.4
# Survey path
# Using tau=2
lls_survey.sightlines['Z_START'] = np.maximum(qsos['ZT2'],
qsos['ZLLS'])
# Maximum search
lls_survey.sightlines['Z_START'] = np.maximum(qsos['Z_START'],
qsos['ZEM'] - dz_start)
# Trim bad ones
bad_s = np.any([
lls_survey.sightlines['Z_START'] <= 0.,
lls_survey.sightlines['FLG_QSO'] != 0
],
axis=0)
lls_survey.sightlines['Z_START'][bad_s] = 99.99
# zend
zend = ltu.z_from_dv(-3000 * u.km / u.s * np.ones(len(qsos)),
lls_survey.sightlines['ZEM'])
lls_survey.sightlines['Z_END'] = zend
# Generate mask
print('SDSS-DR7: Performing stats')
mask = lls_stat(lls_survey)
if sample == 'stat':
lls_survey.mask = mask
else:
lls_survey.mask = ~mask
# Return
print('SDSS-DR7: Loaded')
return lls_survey
def read_joebvp_to_components(filename,
coord,
llist=None,
specfile=None,
chk_vel=False):
""" Generate a list of AbsComponent objects from a JoeB VP output file
Parameters
----------
filename : str
joeB VP filename
coord : SkyCoord
QSO sightline
llist : LineList, optional
Used to construct AbsLine objects
specfile : str, optional
chk_vel : bool, optional
Demand that the velocities of a given ion all be the same
Returns
-------
comps : list
list of AbsComponent objects
"""
# init
if llist is None:
llist = LineList('ISM')
comps = []
# Read
vp_data = Table.read(filename, format='ascii')
# Subset by zsys + trans
lbls = []
for izsys, itrans in zip(vp_data['zsys'], vp_data['trans']):
lbls.append('{:.6f}_{:s}'.format(izsys, itrans))
lbls = np.array(lbls)
ulbls = np.unique(lbls)
# Subset by nflag; Build components
for lbl in ulbls:
mt_lines = np.where(lbls == lbl)[0]
if chk_vel:
if len(np.unique(vp_data['vel'][mt_lines])) != 1:
pdb.set_trace()
z_fit = ltu.z_from_dv(vp_data['vel'][mt_lines[0]] * u.km / u.s,
vp_data['zsys'][mt_lines[0]])
# Loop on abs lines
alines = []
for idx in mt_lines:
zlim = [
vp_data['zsys'][idx] + vp_data[vkey][idx] *
(1 + vp_data['zsys'][idx]) / ckms
for vkey in ['vlim1', 'vlim2']
]
absline = AbsLine(vp_data['restwave'][idx] * u.AA,
z=z_fit,
zlim=zlim,
linelist=llist)
# Add measurements [JB -- Want to capture anything else??]
absline.attrib['coord'] = coord
absline.attrib['flag_N'] = 1
absline.attrib['logN'] = vp_data['col'][idx]
absline.attrib['sig_logN'] = vp_data['sigcol'][idx]
absline.attrib['b'] = vp_data['bval'][idx]
absline.attrib['sig_b'] = vp_data['sigbval'][idx]
absline.attrib['z'] = z_fit
absline.attrib['sig_z'] = ltu.dz_from_dv(
vp_data['sigvel'][idx] * u.km / u.s, vp_data['z_comp'][idx])
if specfile is None:
absline.attrib['specfile'] = vp_data['specfile'][idx]
else:
absline.attrib['specfile'] = specfile
# Fill N, sig_N
_, _, = linear_clm(absline.attrib)
alines.append(absline)
# AbsComponent
stars = '*' * alines[0].ion_name.count('*')
if 'comment' in vp_data.keys():
comment = vp_data['comment'][mt_lines[0]]
else:
comment = ''
if 'rely' in vp_data.keys():
reliability = vp_data['rely'][mt_lines[0]]
else:
reliability = 'none'
abscomp = AbsComponent.from_abslines(alines,
stars=stars,
comment=comment,
reliability=reliability)
# Add measurements [JB -- Want to capture anything else??]
abscomp.attrib = alines[0].attrib.copy()
# Remove undesired keys
for key in ['EW', 'sig_EW', 'flag_EW', 'N', 'sig_N']:
abscomp.attrib.pop(key)
# And more required
for key in ['flag_N', 'logN', 'sig_logN']:
setattr(abscomp, key, abscomp.attrib[key])
# Errors must be in first line!
assert abscomp.sig_logN > 0.
comps.append(abscomp)
# Finish
return comps
def test_z_from_dv():
z = ltu.z_from_dv(1000. * u.km / u.s, 2.)
np.testing.assert_allclose(z, 2.0100236684175417)
def __init__(self, radec, Zion, zcomp, vlim, Ej=0./u.cm, A=None,
Ntup=None, comment='', name=None, stars=None, reliability='none'):
""" Initiator
Parameters
----------
radec : tuple or SkyCoord
(RA,DEC) in deg or astropy.coordinate.SkyCoord
Zion : tuple
Atomic number, ion -- (int,int)
e.g. (8,1) for OI
Note: (-1, -1) is special and is meant for moleculer (e.g. H2)
This notation will most likely change in the future.
zcomp : float
Absorption component redshift
vlim : Quantity array
Velocity limits of the component w/r to `z`
e.g. [-300,300]*u.km/u.s
A : int, optional
Atomic mass -- used to distinguish isotopes
Ntup : tuple
(int,float,two-element list,tuple or array)
(flag_N, logN, sig_logN)
flag_N : Flag describing N measurement (0: no info; 1: detection; 2: saturated; 3: non-detection)
logN : log10 N column density
sig_logN : Error in log10 N. Two elements are expected but not required
Ej : Quantity, optional
Energy of lower level (1/cm)
stars : str, optional
asterisks to add to name, e.g. '**' for CI**
Required if name=None and Ej>0.
reliability : str, optional
Reliability of AbsComponent
'a' - reliable
'b' - possible
'c' - uncertain
'none' - not defined (default)
comment : str, optional
A comment, default is ``
"""
# Required
self.coord = ltu.radec_to_coord(radec)
self.Zion = Zion
# Limits
zlim = ltu.z_from_dv(vlim, zcomp)
self.limits = zLimits(zcomp, zlim.tolist())
# Attributes
self.attrib = init_attrib.copy()
# Optional
self.A = A
self.Ej = Ej
self.stars = stars
self.comment = comment
if Ntup is not None:
self.attrib['flag_N'] = Ntup[0]
self.attrib['logN'] = Ntup[1]
if isiterable(Ntup[2]):
self.attrib['sig_logN'] = np.array(Ntup[2])
else:
self.attrib['sig_logN'] = np.array([Ntup[2]]*2)
_, _ = ltaa.linear_clm(self.attrib) # Set linear quantities
# Name
if (name is None) and (self.Zion != (-1, -1)):
iname = ions.ion_to_name(self.Zion, nspace=0)
if self.Ej.value > 0: # Need to put *'s in name
if stars is not None:
iname += stars
else:
warnings.warn("No stars provided. Adding one because Ej > 0.")
iname += '*'
self.name = '{:s}_z{:0.5f}'.format(iname, self.zcomp)
elif (name is None) and (self.Zion == (-1, -1)):
self.name = 'mol_z{:0.5f}'.format(self.zcomp)
else:
self.name = name
# reliability
if reliability not in ['a', 'b', 'c', 'none']:
raise ValueError("Input reliability `{}` not valid.".format(reliability))
self.reliability = reliability
# AbsLines
self._abslines = []
def __init__(self,
radec,
zabs,
vlim,
zem=0.,
abs_type=None,
NHI=0.,
sig_NHI=np.zeros(2),
flag_NHI=None,
name=None,
**kwargs):
self.zem = zem
# Limits
zlim = ltu.z_from_dv(vlim, zabs)
self.limits = zLimits(zabs, zlim.tolist())
# NHI
self.NHI = NHI
self.sig_NHI = sig_NHI
# Special handling for the flag as this is often not input with NHI
if flag_NHI is None:
if NHI > 0.:
self.flag_NHI = 1
else:
self.flag_NHI = 0
else:
self.flag_NHI = flag_NHI
self.coord = ltu.radec_to_coord(radec)
if name is None:
self.name = 'J{:s}{:s}_z{:.6f}'.format( # Should be unique
self.coord.icrs.ra.to_string(unit=u.hour, sep='', pad=True),
self.coord.icrs.dec.to_string(sep='',
pad=True,
alwayssign=True), self.zabs)
else:
self.name = name
# Abs type
if abs_type is None:
self.abs_type = 'NONE'
else:
self.abs_type = abs_type
# Components
self._components = [] # List of AbsComponent objects
# Kinematics
self.kin = {}
# Metallicity
self.ZH = 0.
self.sig_ZH = 0.
self.flag_ZH = 0
# Abundances and Tables
self._EW = Table()
self._ionN = None # Needs to be None for fill_ion
self._trans = Table()
self._ionstate = {}
self._abund = Table()
# Refs (list of references)
self.Refs = []
