def calculate_rf_lens_magnitudes(lens_redshift, velocity_dispersion,
filters_dict):
"""Calculates the reference-frame lens magnitudes in multiple filters
Parameters
----------
lens_redshift : float
Redshift of the lens
velocity_dispersion : float
Velocity dispersion of the lens
filters_dict : dict
(See output of `get_sdss_filters` for details)
Throughputs of various filters
Returns
-------
dict
Each key is one of string characters 'u', 'g', 'r', 'i', 'z'
representing the filter
Each value is the reference-frame apparent magnitude of the quasar
in the 'key' filter, of type float
"""
from stellarpop import tools
from lenspop import population_functions, distances
from astropy.cosmology import FlatLambdaCDM
# Instantiate Distance
distance = distances.Distance() #TODO: necessary?
# Instantiate LensPopulation
lenspop = population_functions.LensPopulation_()
# Instantiate FlatLambdaCDM cosmology with reasonable parameters
cosmology = FlatLambdaCDM(H0=70.0, Om0=0.3)
lens_sed = tools.getSED('BC_Z=1.0_age=9.000gyr')
velocity_dispersion = np.atleast_1d(velocity_dispersion)
# Absolute --> apparent magnitude conversion in the R-band
lens_abmag_r = tools.ABFilterMagnitude(filters_dict['r'], lens_sed,
lens_redshift)
distance_modulus = cosmology.distmod(lens_redshift).value
lens_appmag_r = lens_abmag_r + distance_modulus
# [Reference frame] Absolute --> apparent magnitude conversion in the R-band
rf_lens_abmag_r, _ = lenspop.EarlyTypeRelations(velocity_dispersion)
rf_lens_appmag = {}
rf_lens_appmag['r'] = rf_lens_abmag_r + distance_modulus
# Quantity which is added to ~magnitude to convert it into reference-frame ~magnitude
offset_rf = rf_lens_abmag_r - lens_abmag_r
# Converting absolute magnitude to reference-frame apparent magnitude
for band in 'ugiz':
rf_lens_appmag[band] = tools.ABFilterMagnitude(
filters_dict[band], lens_sed,
lens_redshift) + offset_rf + distance_modulus
return rf_lens_appmag
def __init__(self,D=None,reset=False,zlmax=2,sigfloor=100,
bands=['F814W_ACS','g_SDSS','r_SDSS','i_SDSS','z_SDSS','Y_UKIRT'],cosmo=[0.3,0.7,0.7],sourcepop="lsst"
):
self.sourcepopulation=sourcepop
if D==None:
D=distances.Distance(cosmo=cosmo)
self.L = lenspop.LensPopulation(reset=reset, sigfloor=sigfloor,
zlmax=zlmax, bands=bands, D=D)
self.S = lenspop.SourcePopulation(reset=reset, bands=bands, D=D, population=sourcepop)
self.E = lenspop.EinsteinRadiusTools(D=D)
def beginRedshiftDependentRelation(self,
D,
reset,
zmax=10,
cosmo=[0.3, 0.7, 0.7]):
self.zmax = zmax
self.zbins, self.dz = numpy.linspace(0, self.zmax, 401, retstep=True)
self.z2bins, self.dz2 = numpy.linspace(0, self.zmax, 201, retstep=True)
if D == None:
D = distances.Distance(cosmo=cosmo)
self.D = D
if reset != True:
try:
#load useful redshift splines
splinedump = open("redshiftsplines.pkl", "rb")
self.Da_spline, self.Dmod_spline, self.volume_spline, self.Da_bispline = pickle.load(
splinedump)
except IOError or EOFError:
self.redshiftfunctions()
else:
self.redshiftfunctions()
def paint(self, Nmax=None, verbose=False,
lrg_input_cat='$OM10_DIR/data/LRGo.txt',
qso_input_cat='$OM10_DIR/data/QSOo.txt',
synthetic=False):
"""
Add new columns to the table, for the magnitudes in various filters.
Parameters
----------
synthetic : boolean
Use `lenspop` to make synthetic magnitudes in various filters
target : string
Paint lenses ('lens') or sources ('source')
lrg_input_cat : string
Name of LRG catalog, if not using synthetic paint
qso_input_cat : string
Name of QSO catalog, if not using synthetic paint
verbose : boolean
print progress to stdout
Notes
-----
* Synthetic painting is very slow, as we loop over each object.
* The treatment of QSOs may be flawed: the offset calculation has not
been tested.
"""
if synthetic==False:
# read data from SDSS
f=open(os.path.expandvars(lrg_input_cat),'r')
lrg=loadtxt(f)
f.close()
g=open(os.path.expandvars(qso_input_cat),'r')
qso=loadtxt(g)
g.close()
###MY OWN REDSHIFT ONLY MATCHING HERE:
lens_props = ['MAGG_LENS','MAGR_LENS','MAGI_LENS','MAGZ_LENS', \
'MAGW1_LENS','MAGW2_LENS','MAGW3_LENS','MAGW4_LENS', 'SDSS_FLAG_LENS']
src_props = ['MAGG_SRC','MAGR_SRC','MAGI_SRC','MAGZ_SRC', \
'MAGW1_SRC','MAGW2_SRC','MAGW3_SRC','MAGW4_SRC', 'SDSS_FLAG_SRC']
tmp_lens = Table(np.zeros((len(self.sample),len(lens_props)),dtype='f8'),names=lens_props)
tmp_src = Table(np.zeros((len(self.sample),len(src_props)),dtype='f8'),names=src_props)
if verbose: print('setup done')
lrg_sort = lrg[np.argsort(lrg[:,0]),:]
qso_sort = qso[np.argsort(qso[:,0]),:]
lens_count = 0
for lens in self.sample:
#paint lens
ind = np.searchsorted(lrg_sort[:,0],lens['ZLENS'])
if ind >= len(lrg_sort): ind = len(lrg_sort) - 1
tmp_lens[lens_count] = lrg_sort[ind,6:] - lrg_sort[ind,8] + lens['APMAG_I'] #assign colors, not mags
#paint source
qso_ind = np.searchsorted(qso_sort[:,0],lens['ZSRC'])
if qso_ind >= len(qso_sort): qso_ind = len(qso_sort) - 1
tmp_src[lens_count] = qso_sort[qso_ind,1:] - qso_sort[qso_ind,3] + lens['MAGI']
lens_count += 1
self.sample = hstack([self.sample,tmp_lens,tmp_src])
if synthetic==True:
lens_count = 0
total = len(self.sample)
Rfilter = tools.filterfromfile('r_SDSS')
Ufilter = tools.filterfromfile('u_SDSS')
# sort the Ufilter array
Ufilterarg=np.sort(Ufilter[1])
Ufilter = (Ufilter[0], Ufilterarg, 1)
Gfilter = tools.filterfromfile('g_SDSS')
Ifilter = tools.filterfromfile('i_SDSS')
Zfilter = tools.filterfromfile('z_SDSS')
self.Nlenses=len(self.sample)
bands = ('r_SDSS_lens', 'g_SDSS_lens', 'i_SDSS_lens', 'z_SDSS_lens', 'u_SDSS_lens','r_SDSS_quasar', 'g_SDSS_quasar', 'i_SDSS_quasar', 'z_SDSS_quasar', 'u_SDSS_quasar')
if verbose: print('OM10: computing synthetic magnitudes in the following bands: ', bands)
# call a distance class constructor
d = distances.Distance()
# number of data in the table of calculated magnitude
totalEntrees = self.Nlenses*10.0
t = Table(np.arange(totalEntrees).reshape(self.Nlenses, 10),
names=bands)
Lsed = tools.getSED('BC_Z=1.0_age=9.000gyr')
Qsed = tools.getSED('agn')
from astropy.cosmology import FlatLambdaCDM
cosmo = FlatLambdaCDM(H0=70, Om0=0.3)
lenspop_constructor = population_functions.LensPopulation_()
for lens in self.sample:
# calculate the quasar magnitude
redshift = lens['ZSRC']
RF_Imag_app_q = lens['MAGI_IN']
Qoffset = RF_Imag_app_q - tools.ABFilterMagnitude(Ifilter, Qsed, redshift)
RF_Rmag_app_q = tools.ABFilterMagnitude(Rfilter, Qsed, redshift) + Qoffset
RF_Gmag_app_q = tools.ABFilterMagnitude(Gfilter, Qsed, redshift) + Qoffset
RF_Zmag_app_q = tools.ABFilterMagnitude(Zfilter, Qsed, redshift) + Qoffset
if(redshift<3.9):
RF_Umag_app_q = tools.ABFilterMagnitude(Ufilter, Qsed, redshift) + Qoffset
elif(redshift>=3.9):
RF_Umag_app_q = 99
# calculate the lens magnitude
veldisp = np.atleast_1d(lens['VELDISP'])
redshift = lens['ZLENS']
# Reference Frame Absolute R magnitude
RF_RMag_abs, _ = lenspop_constructor.EarlyTypeRelations(veldisp)
RMag_abs = tools.ABFilterMagnitude(Rfilter, Lsed, redshift)
distMod = cosmo.distmod(redshift).value
Rmag_app = RMag_abs + distMod
offset_abs_app = RMag_abs - Rmag_app
offset_RF_abs = RF_RMag_abs - RMag_abs
RF_Rmag_app = RF_RMag_abs - offset_abs_app
# Get filters and calculate magnitudes for each filter:
RF_Umag_app = tools.ABFilterMagnitude(Ufilter, Lsed, redshift) + offset_RF_abs + distMod
RF_Gmag_app = tools.ABFilterMagnitude(Gfilter, Lsed, redshift) + offset_RF_abs + distMod
RF_Imag_app = tools.ABFilterMagnitude(Ifilter, Lsed, redshift) + offset_RF_abs + distMod
RF_Zmag_app = tools.ABFilterMagnitude(Zfilter, Lsed, redshift) + offset_RF_abs + distMod
t['u_SDSS_lens'][lens_count] = RF_Umag_app
t['r_SDSS_lens'][lens_count] = RF_Rmag_app
t['g_SDSS_lens'][lens_count] = RF_Gmag_app
t['i_SDSS_lens'][lens_count] = RF_Imag_app
t['z_SDSS_lens'][lens_count] = RF_Zmag_app
t['u_SDSS_quasar'][lens_count] = RF_Umag_app_q
t['r_SDSS_quasar'][lens_count] = RF_Rmag_app_q
t['g_SDSS_quasar'][lens_count] = RF_Gmag_app_q
t['i_SDSS_quasar'][lens_count] = RF_Imag_app_q
t['z_SDSS_quasar'][lens_count] = RF_Zmag_app_q
lens_count = lens_count + 1
dot = np.mod(lens_count, total/np.min([79,total])) == 0
if verbose and dot:
print('.', end="")
# Update the sample by adding the table of calculated magnitude
self.sample.add_columns(t.columns.values())
self.lenses = self.sample.copy()
return