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lightcone.py
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lightcone.py
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# ===========================================================================
import pangloss
import cPickle
import numpy
import pylab as plt
from math import pi
# ======================================================================
class Lightcone(object):
"""
NAME
Lightcone
PURPOSE
Define a conical region of space containing many galaxies, and
enable mass to be assigned to those galaxies and consequent
useful quantities to be calculated.
COMMENTS
The masses of galaxies in a lightcone are always uncertain.
Methods are provided to characterise this uncertainty by drawing
sample masses for each galaxy, from various specified relations.
INITIALISATION
catalog Filename of the parent galaxy catalog
flavor Is the catalog 'real' or 'simulated'?
position The sky position (J2000 deg) of the cone centre
radius The radius of the lightcone field of view (arcmin)
maglimit The depth of the galaxy selection (magnitudes)
band The band in which the selection is made
METHODS
galaxiesWithin(self,radius,cut=[18.5,24.5],band="F814W",radius_unit="arcsec"):
numberWithin(self,radius,cut=[18.5,24.5],band="F814W",radius_unit="arcsec"):
define_system(self,zl,zs,cosmo=[0.25,0.75,0.73]):
loadGrid(self, Grid):
mimicPhotozError(self,sigma=0.1):
writeColumn(self,string,values):
snapToGrid(self, Grid):
drawMstars(self,model): Needs updating to take SHMR object
drawMhalos(self,modelT):
drawConcentrations(self,errors=False):
makeKappas(self,errors=False,truncationscale=5,profile="BMO1"):
combineKappas(self):
BUGS
AUTHORS
This file is part of the Pangloss project, distributed under the
GPL v2, by Tom Collett (IoA) and Phil Marshall (Oxford).
Please cite: Collett et al 2013, http://arxiv.org/abs/1303.6564
HISTORY
2013-03-23 Collett & Marshall (Cambridge)
"""
# ----------------------------------------------------------------------------
def __init__(self,catalog,flavor,position,radius,maglimit=99,band="r"):
self.name = 'Lightcone through the Universe'
self.flavor = flavor # 'real' or 'simulated'
self.catalog = catalog
# Simulated lightcones have "true" (ray-traced) convergence:
self.kappa_hilbert = None # until set!
# Catalog limits:
self.xmax = self.catalog['nRA'].max()
self.xmin = self.catalog['nRA'].min()
self.ymax = self.catalog['Dec'].max()
self.ymin = self.catalog['Dec'].min()
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Cut out a square cone:
self.rmax = radius
self.xc = [position[0],position[1]]
dx = self.rmax*pangloss.arcmin2rad
self.galaxies = self.catalog.where((self.catalog.nRA > (self.xc[0]-dx)) & \
(self.catalog.nRA < (self.xc[0]+dx)) & \
(self.catalog.Dec > (self.xc[1]-dx)) & \
(self.catalog.Dec < (self.xc[1]+dx)) )
# Trim it to a circle:
x = (self.galaxies.nRA - self.xc[0])*pangloss.rad2arcmin
y = (self.galaxies.Dec - self.xc[1])*pangloss.rad2arcmin
r = numpy.sqrt(x*x + y*y)
phi=numpy.arctan(y/x)
self.galaxies.add_column('x',x)
self.galaxies.add_column('y',y)
self.galaxies.add_column('r',r)
self.galaxies.add_column('phi',phi)
self.galaxies = self.galaxies.where(self.galaxies.r < self.rmax)
try:
self.galaxies = self.galaxies.where(self.galaxies.Type != 2)
except AttributeError: pass
self.allgalaxies = self.galaxies
# Now we have a small catalog, just for the requested lightcone.
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Halo parameters, to be varied during sampling analysis:
self.galaxies.add_column('z',self.galaxies.z_obs*1.0)
if self.flavor == 'simulated':
# Take the log of the halo mass, and set up the parameter array:
self.galaxies.add_column('Mh_obs',numpy.log10(self.galaxies.Mhalo_obs))
self.galaxies.add_column('Mh',self.galaxies.Mh_obs*1.0)
# Stellar masses will be added by drawMstars
# Halo masses will be replaced by drawMhalos
elif self.flavor == 'real':
# Mstar is already given as log M...
self.galaxies.add_column('Mstar',self.galaxies.Mstar_obs*1.0)
# Halo masses will be added by drawMhalos
if len(self.galaxies) == 0:
print "Lightcone: WARNING: no galaxies here!"
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Save memory!
del self.catalog
del catalog
return None
# ----------------------------------------------------------------------------
def __str__(self):
return 'Lightcone of radius %.2f arcmin, centred on (%.3f,%.3f) rad' % (self.rmax,self.xc[0],self.xc[1])
# ----------------------------------------------------------------------------
# Tell me the number of galaxies within a certain radius, that pass a
# certain magnitude cut.
def galaxiesWithin(self,radius,cut=[18.5,24.5], band="F814W", radius_unit="arcmin"):
if band == "u" or band == "g" or band == "r" or band == "i" or band == "z":
col = "mag_SDSS_%s" % band
elif band == "F814" or band == "F814W" or band == "814" or band == 814:
col = "mag_F814W"
elif band == "WFC125" or band == "F125W" or band == "F125" or band == "125" or band == 125:
col = "WFC125"
else:
col = "mag_%s" % band
if radius < 0.1:
print "Warning: Default units for radius are arcmin!"
if radius_unit == "arcmin":
radius = radius
if radius_unit == "arcsec":
radius = radius/60.
if col != "warning":
# self.N_cut=self.galaxies.where((self.galaxies.r < radius) & \
# (self.galaxies["%s"%col] < cut[1])& \
# (self.galaxies["%s"%col] > cut[0]))
self.N_cut=self.galaxies.where((self.galaxies.r < radius) & \
(self.galaxies["%s"%col] < cut[1])& \
(self.galaxies["%s"%col] > cut[0]))
return self.N_cut
def numberWithin(self,radius,cut=[18.5,24.5],band="F125W",units="arcmin"):
Ntable = self.galaxiesWithin(radius,cut,band,units)
return len(Ntable.r)
# ----------------------------------------------------------------------------
def defineSystem(self,zl,zs,cosmo=[0.25,0.75,0.73]):
self.zl = zl
self.zs = zs
self.cosmo = cosmo
self.galaxies = self.galaxies.where(self.galaxies.z_obs<zs+0.2)
return
# ----------------------------------------------------------------------------
def loadGrid(self, Grid):
if numpy.abs(self.zl-Grid.zltrue) > 0.05: print "Grid zl != lens zl"
if numpy.abs(self.zs-Grid.zs) > 0.05: print "Grid zs != lens zs"
self.redshifts,self.dz = Grid.redshifts,Grid.dz
self.Da_l,self.Da_s,self.Da_ls = Grid.Da_l,Grid.Da_s,Grid.Da_ls
return
# ----------------------------------------------------------------------------
# Simple model for spectroscopic coverage - to be applied to the
# calibration lightcones to match the observed catalog.
def configureForSurvey(self, experiment):
PR = experiment.parameters['PhotometricRadius']
PD = experiment.parameters['PhotometricDepth']
assert len(PR) == len(PD)
SR = experiment.parameters['SpectroscopicRadius']
SD = experiment.parameters['SpectroscopicDepth']
assert len(SR)==len(SD)
band = experiment.parameters['LightconeDepthBand']
if band == "u" or band == "g" or band == "r" or band == "i" or band == "z":
col = "mag_SDSS_%s" % band
elif band == "F814" or band == "F814W" or band == "814" or band == 814:
col = "mag_F814W" #note that this isn't included atm
elif band == "WFC125" or band == "F125" or band == "F125W" or band == "125" or band == 125:
col = "WFC125" #this was the matching band for BoRG
else:
col = "mag_%s" % band
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Only include galaxies observed by photometry:
self.writeColumn('photo_flag',False)
self.writeColumn('identifier',range(len(self.galaxies.x)))
if PR != ['']:
for i in range(len(PR)):
R=PR[i]*60 # positions are stored in arcseconds
D=PD[i]
goodset = set(self.galaxies.where((self.galaxies.r < R) & \
(self.galaxies["%s"%col] < D)).identifier)
self.galaxies.photo_flag[numpy.array(\
[_ in goodset for _ in self.galaxies.identifier])]=True
self.galaxies = self.galaxies.where(self.galaxies.photo_flag==True)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Set spectroscopic flag of any galaxy that should have
# spectroscopy, according to the given radius and depth:
self.writeColumn('spec_flag',False)
if SR!=['']:
for i in range(len(SR)):
R=SR[i]*60 # positions are stored in arcseconds
D=SD[i]
goodset=set(self.galaxies.where((self.galaxies.r < R) & \
(self.galaxies["%s"%col] < D)).identifier)
self.galaxies.spec_flag[numpy.array(\
[_ in goodset for _ in self.galaxies.identifier])]=True
return
# ----------------------------------------------------------------------------
# The following methods are designed to be run multiple times
# (previous ones are single use per lightcone)
# ----------------------------------------------------------------------------
# Add galaxy property column, overwriting any values that already exist:
def writeColumn(self,string,values):
try:
self.galaxies.add_column('%s'%string,values)
except ValueError:
self.galaxies["%s"%string]=values
# ----------------------------------------------------------------------------
def mimicPhotozError(self,sigma=0.1):
# Start with the original, constant z_obs in the catalog:
z_obs = self.galaxies.z_obs.copy()
# RMS error on this z is either sigma or 0.0:
e = ( self.galaxies.spec_flag == False )*sigma
# Add Gaussian noise to get this realisation's z:
z = z_obs + e*(1+z_obs)*numpy.random.randn(len(z_obs))
# Over-write the z parameter array:
self.writeColumn('z',z)
return
# ----------------------------------------------------------------------------
# Snap the parameters z onto the grid, to speed up calculations:
def snapToGrid(self, Grid):
z = self.galaxies.z
sz,p = Grid.snap(z)
self.writeColumn('Da_p',Grid.Da_p[p])
self.writeColumn('rho_crit',Grid.rho_crit[p])
self.writeColumn('sigma_crit',Grid.sigma_crit[p])
self.writeColumn('beta',Grid.beta[p])
rphys = self.galaxies.r*pangloss.arcmin2rad*self.galaxies.Da_p
self.writeColumn('rphys',rphys)
# ----------------------------------------------------------------------------
# Given Mhalo and z, draw an Mstar, and an identical Mstar_obs:
def drawMstars(self,model):
Mstar = model.drawMstars(self.galaxies.Mh,self.galaxies.z)
self.writeColumn('Mstar',Mstar)
# Copy this to Mstar_obs - mimicMstarError will deal with noise
self.writeColumn('Mstar_obs',Mstar)
return
# ----------------------------------------------------------------------------
# Given an observed Mstar_obs, what could the parameter Mstar be?
def mimicMstarError(self,sigmaP,sigmaS):
Mstar = self.galaxies.Mstar_obs.copy()
# Add offset due to photometric or spectroscopic error:
Mstar[self.galaxies.spec_flag==False] += numpy.random.randn(Mstar[self.galaxies.spec_flag==False].size)*sigmaP
Mstar[self.galaxies.spec_flag==True] += numpy.random.randn(Mstar[self.galaxies.spec_flag==True].size)*sigmaS
# Over-write the Mstar parameter array:
self.writeColumn('Mstar',Mstar)
return
# ----------------------------------------------------------------------------
# Given an Mstar and z, what could the parameter Mh be?
def drawMhalos(self,model):
Mh = model.drawMhalos(self.galaxies.Mstar,self.galaxies.z)
self.writeColumn('Mh',Mh)
return
# ----------------------------------------------------------------------------
# Given an Mh, what could the halo concentration be?
def drawConcentrations(self,errors=False):
M200 = 10**self.galaxies.Mh
r200 = (3*M200/(800*3.14159*self.galaxies.rho_crit))**(1./3)
self.writeColumn("r200",r200)
c200 = pangloss.MCrelation(M200,scatter=errors)
self.writeColumn("c200",c200)
r_s = r200/c200
self.writeColumn('rs',r_s)
x = self.galaxies.rphys/r_s
self.writeColumn('X',x)
return
# ----------------------------------------------------------------------------
# Compute halos' contributions to the convergence:
def makeKappas(self,errors=False,truncationscale=5,profile="BMO1"):
c200 = self.galaxies.c200
r200 = self.galaxies.r200
x = self.galaxies.X
r_s = self.galaxies.rs
rho_s = pangloss.delta_c(c200)*self.galaxies.rho_crit
self.kappa_s = rho_s * r_s /self.galaxies.sigma_crit #kappa slice for each lightcone
r_trunc = truncationscale*r200
xtrunc = r_trunc/r_s
kappaHalo = self.kappa_s*1.0
gammaHalo = self.kappa_s*1.0
if profile=="BMO1":
F=pangloss.BMO1Ffunc(x,xtrunc)
G=pangloss.BMO1Gfunc(x,xtrunc)
if profile=="BMO2":
F=pangloss.BMO2Ffunc(x,xtrunc)
G=pangloss.BMO2Gfunc(x,xtrunc)
kappaHalo *= F
gammaHalo *= (G-F)
phi = self.galaxies.phi
kappa = kappaHalo
gamma = gammaHalo
gamma1 = gamma*numpy.cos(2*phi)
gamma2 = gamma*numpy.sin(2*phi)
mu = 1.0/(((1.0 - kappa)**2.0) - (gamma**2.0))
self.writeColumn('kappa',kappa)
self.writeColumn('gamma',gamma)
self.writeColumn('gamma1',-gamma1)
self.writeColumn('gamma2',-gamma2)
self.writeColumn('mu',mu)
return
# ----------------------------------------------------------------------------
def combineKappas(self):
B=self.galaxies.beta
K=self.galaxies.kappa
G=self.galaxies.gamma
G1=self.galaxies.gamma1
G2=self.galaxies.gamma2
D= K**2-G**2
kappa_keeton = (1.-B) * (K- B*(D)) / ( (1-B*K)**2 - (B*G)**2 )
gamma1_keeton = (1.-B) * (G1) / ( (1-B*K)**2 - (B*G)**2 )
gamma2_keeton = (1.-B) * (G2) / ( (1-B*K)**2 - (B*G)**2 )
kappa_tom = (1.-B) * K
gamma1_tom = (1.-B) * G1
gamma2_tom = (1.-B) * G2
self.writeColumn('kappa_keeton',kappa_keeton)
self.writeColumn('gamma1_keeton',gamma1_keeton)
self.writeColumn('gamma2_keeton',gamma2_keeton)
self.writeColumn('kappa_tom',kappa_tom)
self.writeColumn('gamma1_tom',gamma1_tom)
self.writeColumn('gamma2_tom',gamma2_tom)
self.writeColumn('kappa_add',K)
self.writeColumn('gamma1_add',G1)
self.writeColumn('gamma2_add',G2)
self.kappa_add_total=numpy.sum(self.galaxies.kappa)
self.kappa_keeton_total=numpy.sum(self.galaxies.kappa_keeton)
self.kappa_tom_total=numpy.sum(self.galaxies.kappa_tom)
self.gamma1_add_total=numpy.sum(self.galaxies.gamma1)
self.gamma1_keeton_total=numpy.sum(self.galaxies.gamma1_keeton)
self.gamma1_tom_total=numpy.sum(self.galaxies.gamma1_tom)
self.gamma2_add_total=numpy.sum(self.galaxies.gamma2)
self.gamma2_keeton_total=numpy.sum(self.galaxies.gamma2_keeton)
self.gamma2_tom_total=numpy.sum(self.galaxies.gamma2_tom)
return self.kappa_add_total
# ----------------------------------------------------------------------------
# Calculate magnification along line of sight
def combineMus(self,weakapprox=True):
M=self.galaxies.mu
K=self.galaxies.kappa
G=self.galaxies.gamma
G1=self.galaxies.gamma1
G2=self.galaxies.gamma2
Ksum = self.kappa_add_total #numpy.sum(K)
self.G1sum = numpy.sum(G1)
self.G2sum = numpy.sum(G2)
self.Gsum = numpy.sqrt(self.G1sum**2 + self.G2sum**2)
if weakapprox is True:
Msum = 1.0 + 2.0*Ksum
else:
inverseMsum = (1.0 - Ksum)**2.0 - self.Gsum**2.0
Msum = 1.0/inverseMsum
self.mu_add_total=Msum
return self.mu_add_total
# ----------------------------------------------------------------------------
# Find contribution of various quantities along LoS at given z
# for plotting cumulative sums of parameters with z
def findContributions(self,quantity):
# Point positions:
zmax = self.zs+0.1
zbins = 15
z = numpy.linspace(0.0,zmax,zbins)
# Plot the points:
if quantity == 'mass':
contr = numpy.zeros(zbins)
for i in range(zbins):
galaxies = self.galaxies.where(self.galaxies.z <= z[i])
size = galaxies.Mhalo_obs
contr[i] = numpy.sum(size)
elif quantity == 'kappa':
contr = numpy.zeros(zbins)
for i in range(zbins):
galaxies = self.galaxies.where(self.galaxies.z <= z[i])
size = galaxies.kappa
contr[i] = numpy.sum(size)
elif quantity == 'mu':
contr = numpy.zeros(zbins)
for i in range(zbins):
galaxies = self.galaxies.where(self.galaxies.z <= z[i])
size = galaxies.mu
contr[i] = numpy.sum(size)
elif quantity == 'stellarmass':
contr = numpy.zeros(zbins)
for i in range(zbins):
galaxies = self.galaxies.where(self.galaxies.z <= z[i])
size = galaxies.Mstar_obs
contr[i] = numpy.sum(size)
else:
raise "Lightcone plotting error: unknown quantity "+quantity
return contr
# ----------------------------------------------------------------------------
# Plotting
# ----------------------------------------------------------------------------
def plotFieldOfView(self,quantity,AX):
slicehalfwidth = self.rmax / 6.0
if quantity == 'mass':
self.writeColumn('rtrunc_arcmin',(self.galaxies.r200/ self.galaxies.Da_p) * pangloss.rad2arcmin)
self.writeColumn('rscale_arcmin',(self.galaxies.rs/ self.galaxies.Da_p) * pangloss.rad2arcmin)
for i in range(len(self.galaxies.x)):
trunc = plt.Circle([self.galaxies.x[i], self.galaxies.y[i]],radius=self.galaxies.rtrunc_arcmin[i],fill=True,fc="b",alpha=0.05)
AX.add_patch(trunc)
for i in range(len(self.galaxies.x)):
core = plt.Circle([self.galaxies.x[i], self.galaxies.y[i]],radius=self.galaxies.rscale_arcmin[i],fill=True,fc="r",alpha=0.5)
AX.add_patch(core)
plt.title('Halo Mass')
elif quantity == 'kappa':
plt.scatter(self.galaxies.x, self.galaxies.y, c='r', marker='o', s=(self.galaxies.kappa)*30000)
plt.title('Convergence')
elif quantity == 'mu':
plt.scatter(self.galaxies.x, self.galaxies.y, c='g', marker='o', s=((self.galaxies.mu-1.0)*3E4))
plt.title('Magnification')
elif quantity == 'stellarmass':
plt.scatter(self.galaxies.x, self.galaxies.y, c='y', marker='o', s=(numpy.log(self.galaxies.Mstar)/2),edgecolor = 'none' )
plt.title('Stellar Mass')
elif quantity == 'light':
plt.scatter(self.galaxies.x, self.galaxies.y, c='y', marker='o', s=(2**(25-self.galaxies.mag)),edgecolor = 'none' )
plt.title('Galaxy Light')
else:
raise "Lightcone plotting error: unknown quantity "+quantity
# Lightcone boundary and centroid:
circ = plt.Circle(self.xc,radius=self.rmax,fill=False,linestyle='dotted')
AX.add_patch(circ)
AX.plot([self.xc[0]],[self.xc[1]], c='k', marker='+',markersize=20,markeredgewidth=1)
axlimits = [self.xc[0]-self.rmax-0.1,self.xc[0]+self.rmax+0.1,self.xc[1]-self.rmax-0.1,self.xc[1]+self.rmax+0.1]
AX.axis(axlimits)
# Show slice:
plt.axvline(x=slicehalfwidth, ymin=axlimits[2], ymax=axlimits[3],color='black', ls='dotted')
plt.axvline(x=-slicehalfwidth, ymin=axlimits[2], ymax=axlimits[3],color='black', ls='dotted')
# Labels:
plt.xlabel('x / arcmin')
# plt.ylabel('y / arcmin')
return
# ----------------------------------------------------------------------------
def plotLineOfSight(self,quantity,AX):
# Only plot a subset of points, in a slice down the middle of
# the light cone:
subset = numpy.abs(self.galaxies.x)<0.3
# Point positions:
z = self.galaxies.z[subset]
y = self.galaxies.y[subset]
# Plot the points:
if quantity == 'mass':
size = (10.0**(self.galaxies.Mh[subset]-11.0))
plt.scatter(z, y, c='k', marker='o', s=size, edgecolor='none' )
plt.title('Line-of-sight Halo Mass')
elif quantity == 'kappa':
size = ((self.galaxies.kappa[subset])*30000.0)
plt.scatter(z, y, c='r', marker='o', s=size, edgecolor='k' )
plt.title('Line-of-sight Convergence')
elif quantity == 'mu':
size = ((self.galaxies.mu[subset]-1.0)*3E4)
plt.scatter(z, y, c='g', marker='o', s=size, edgecolor='k' )
plt.title(r'Line-of-sight Magnification $(\mu - 1)$')
elif quantity == 'stellarmass':
size = ((numpy.log(self.galaxies.Mstar[subset]))/2.0)
plt.scatter(z, y, c='y', marker='o', s=size, edgecolor='none' )
plt.title('Line-of-sight Stellar Mass')
elif quantity == 'light':
size = (2**(25-(self.galaxies.mag[subset])))
plt.scatter(z, y, c='y', marker='o', s=size, edgecolor='none' )
plt.title('Line-of-sight Galaxy Light')
else:
raise "Lightcone plotting error: unknown quantity "+quantity
# Axis limits:
zmax = max(self.galaxies.z.max(),self.zs)
AX.axis([0,zmax+0.1,-self.rmax-0.1,self.rmax+0.1])
# Labels:
plt.xlabel('redshift z')
plt.ylabel('y / arcmin')
# Add lines marking source and lens plane, and optical axis:
plt.axvline(x=self.zl, ymin=0, ymax=1,color='black', ls='dotted',label='bla')
plt.axvline(x=self.zs, ymin=0, ymax=1,color='black', ls='dotted')
plt.axhline(y=0.0, xmin=0.0, xmax=zmax, color='black', ls='dashed')
return
# ----------------------------------------------------------------------------
# Plotting cumulative sum of parameters with redshift
def plotContributions(self,quantity,output):
plt.clf()
# Point positions:
zmax = self.zs+0.1
z = numpy.linspace(0.0,zmax,100)
# Plot the points:
if quantity == 'mass':
contr = numpy.zeros(len(z))
for i in range(len(z)):
galaxies = self.galaxies.where(self.galaxies.z <= z[i])
size = galaxies.Mhalo_obs
contr[i] = numpy.sum(size)
plt.plot(z, contr)
plt.title('Cumulative Sum of Halo Mass')
elif quantity == 'kappa':
contr = numpy.zeros(len(z))
for i in range(len(z)):
galaxies = self.galaxies.where(self.galaxies.z <= z[i])
size = galaxies.kappa
contr[i] = numpy.sum(size)
plt.plot(z, contr)
plt.title(r'Cumulative Sum of $\kappa_h$')
elif quantity == 'mu':
contr = numpy.zeros(len(z))
for i in range(len(z)):
galaxies = self.galaxies.where(self.galaxies.z <= z[i])
size = galaxies.mu
contr[i] = numpy.sum(size)
plt.plot(z, contr)
plt.title(r'Cumulative Sum of $\mu_h$')
elif quantity == 'stellarmass':
contr = numpy.zeros(len(z))
for i in range(len(z)):
galaxies = self.galaxies.where(self.galaxies.z <= z[i])
size = galaxies.Mstar_obs
contr[i] = numpy.sum(size)
plt.plot(z, contr)
plt.title('Cumulative Sum of Stellar Mass')
else:
raise "Lightcone plotting error: unknown quantity "+quantity
# Axis limits:
zmax = max(self.galaxies.z.max(),self.zs+0.1)
# Labels:
plt.xlabel('redshift z')
if output != None:
pangloss.rm(output)
plt.savefig(output,dpi=300)
return
# ----------------------------------------------------------------------------
def plot(self,var='kappa',output=None):
plt.clf()
# Panel 1: Galaxy positions:
ax1 = plt.subplot(3,3,(1,4), aspect ='equal')
self.plotFieldOfView('light',ax1)
# Panel 2: Halo mass distributions:
ax2 = plt.subplot(3,3,(2,5), aspect ='equal')
self.plotFieldOfView('mass',ax2)
# Panel 3: Kappa contributions:
ax3 = plt.subplot(3,3,(3,6), aspect ='equal')
self.plotFieldOfView(var,ax3)
# Lower panel: View along redshift axis
ax4 = plt.subplot(3,3,(7,9))
self.plotLineOfSight(var,ax4)
if output != None:
pangloss.rm(output)
plt.savefig(output,dpi=300)
return None
# ----------------------------------------------------------------------------
#=============================================================================