def jwstfig_z3(simIa=None,
simIbc=None,
simII=None,
contours=True,
redshiftcircle=True,
clobber=False,
nsim=2000,
**plotargs):
from pytools import plotsetup
from matplotlib import pyplot as pl
fig = plotsetup.fullpaperfig([8, 4])
simIa, simIbc, simII = doublecircle('jwst3',
simIa,
simIbc,
simII,
clobber=clobber,
circle1bands=['f182m', 'f300m'],
circle2bands=['f210m', 'f300m'],
contours=contours,
redshiftcircle=redshiftcircle,
filterset='jwst_z3',
nsim=nsim,
**plotargs)
ax1, ax2 = fig.axes
fig.subplots_adjust(left=0.1,
bottom=0.18,
right=0.89,
top=0.95,
wspace=0.1)
ax2.yaxis.labelpad = 20
pl.draw()
return simIa, simIbc, simII
def bushfig(simIa=None,
simIbc=None,
simII=None,
contours=True,
redshiftcircle=False,
clobber=False,
**plotargs):
from pytools import plotsetup
from matplotlib import pyplot as pl, ticker
fig = plotsetup.fullpaperfig([8, 4])
simIa, simIbc, simII = doublecircle('bush',
simIa,
simIbc,
simII,
clobber=clobber,
circle1bands=['f098m', 'f153m'],
circle2bands=['f127m', 'f139m'],
contours=contours,
redshiftcircle=redshiftcircle,
**plotargs)
fig = pl.gcf()
ax1, ax2 = fig.axes
fig.subplots_adjust(left=0.1,
bottom=0.18,
right=0.89,
top=0.95,
wspace=0.1)
ax1.set_xlim(-0.6, 0.95)
ax1.set_ylim(-0.9, 0.5)
ax2.set_xlim(-0.6, 0.6)
ax2.set_ylim(-0.8, 0.6)
ax2.yaxis.labelpad = 20
for ax in [ax1, ax2]:
ax.xaxis.set_major_locator(ticker.MultipleLocator(0.2))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.1))
ax.yaxis.set_major_locator(ticker.MultipleLocator(0.2))
ax.yaxis.set_minor_locator(ticker.MultipleLocator(0.1))
#ax.text( 0.1, 0.1, 'SN Ia', color=color1,
# ha='left',va='top')#,transform=ax1.transAxes,fontsize=14)
#ax.text( 0., -0.05, 'CC SN', color=color2,
# ha='center',va='top')#,transform=ax1.transAxes,fontsize=14)
ax2.text(
0.95,
0.95,
'GSD11Bus',
transform=ax2.transAxes,
ha='right',
va='top',
color='k',
fontsize=15,
)
pl.draw()
return simIa, simIbc, simII
def plotzpoints(sn, simIa, dz=0.05):
""" plot the
:param sn:
:param simIa:
:param dz:
:return:
"""
from matplotlib import cm
import mpltools
from pytools import plotsetup
if 'FLT' not in simIa.__dict__:
simIa.getLightCurves()
zbins, c7Ipts, c8Ipts, cPNpts = get_colors_binned_by_z(sn, simIa, dz)
plotsetup.fullpaperfig(1, [5, 5])
pl.clf()
ax1 = pl.gca()
# ax1.plot(QH,PN, ls=' ', marker='o',color='k', alpha=0.3 )
mpltools.color.cycle_cmap(len(zbins), cmap=cm.gist_rainbow_r, ax=ax1)
for iz in range(len(zbins) - 1):
z0, z1 = zbins[iz], zbins[iz + 1]
#if dz>=0.1 : zmid = round(np.mean([z0,z1]),1)
#elif dz>=0.01 : zmid = round(np.mean([z0,z1]),2)
ax1.plot(c7Ipts[iz],
cPNpts[iz],
marker='o',
alpha=0.3,
ls=' ',
mew=0,
label='%.2f-%.2f' % (z0, z1))
ax1.legend(loc='upper left',
ncol=2,
numpoints=1,
frameon=False,
handletextpad=0.3,
handlelength=0.2)
ax1.set_xlabel('F763M-F814W')
ax1.set_ylabel('F139M-F140W')
# plotPhot(label=True)
ax1.set_xlim(-0.8, 0.8)
ax1.set_ylim(-0.8, 0.8)
fig = pl.gcf()
fig.subplots_adjust(bottom=0.12, left=0.16, right=0.95, top=0.95)
pl.draw()
def plotzpoints(sn,simIa,dz=0.1):
""" plot the
:param sn:
:param simIa:
:param dz:
:return:
"""
from matplotlib import cm
from mpltools import color
from pytools import plotsetup
if 'FLT' not in simIa.__dict__ :
simIa.getLightCurves()
zbins = np.arange( sn.z - sn.zerr, sn.z + sn.zerr + dz, dz )
izbinarg = np.digitize( simIa.z, zbins, right=True )-1
iQ = np.where( simIa.FLT=='Q' )
iH = np.where( simIa.FLT=='H' )
iP = np.where( simIa.FLT=='P' )
iN = np.where( simIa.FLT=='N' )
Q,H,P,N = simIa.MAG[iQ],simIa.MAG[iH],simIa.MAG[iP],simIa.MAG[iN]
QH = Q-H
PN = P-N
plotsetup.fullpaperfig( 1, [5,5] )
pl.clf()
ax1 = pl.gca()
# ax1.plot(QH,PN, ls=' ', marker='o',color='k', alpha=0.3 )
color.cycle_cmap( len(zbins), cmap=cm.gist_rainbow_r, ax=ax1)
for iz in range(len(zbins)-1) :
z0, z1 = zbins[iz],zbins[iz+1]
QHz = QH[izbinarg==iz]
PNz = PN[izbinarg==iz]
if dz>=0.1 : zmid = round(np.mean([z0,z1]),1)
elif dz>=0.01 : zmid = round(np.mean([z0,z1]),2)
ax1.plot(QHz,PNz, marker='o', alpha=0.3, ls=' ',mew=0,label='%.1f-%.1f'%(z0,z1) )
ax1.legend(loc='upper left', ncol=2, numpoints=1, frameon=False,
handletextpad=0.3, handlelength=0.2 )
ax1.set_xlabel('F153M-F160W')
ax1.set_ylabel('F139M-F140W')
plotPhot(label=True)
ax1.set_xlim(-0.35,0.53)
ax1.set_ylim(-0.35,0.53)
fig = pl.gcf()
fig.subplots_adjust(bottom=0.12,left=0.16,right=0.95,top=0.95)
pl.draw()
def colfaxfig(simIa=None,
simIbc=None,
simII=None,
contours=True,
redshiftcircle=True,
clobber=False,
**plotargs):
from pytools import plotsetup
from matplotlib import pyplot as pl
from mpltools import color
from matplotlib import cm
fig = plotsetup.fullpaperfig([8, 4])
simIa, simIbc, simII = doublecircle('colfax',
simIa,
simIbc,
simII,
clobber=clobber,
circle1bands=['f139m', 'f127m'],
circle2bands=['f139m', 'f153m'],
contours=contours,
redshiftcircle=redshiftcircle,
**plotargs)
fig = pl.gcf()
ax1, ax2 = fig.axes
fig.subplots_adjust(left=0.1,
bottom=0.18,
right=0.89,
top=0.95,
wspace=0.1)
ax1.set_xlim(-0.5, 0.4)
ax1.set_ylim(-0.7, 0.4)
ax2.set_xlim(-0.5, 0.4)
ax2.set_ylim(-0.4, 0.4)
ax2.text(
0.95,
0.95,
'GND12Col',
transform=ax2.transAxes,
ha='right',
va='top',
color='k',
fontsize=15,
)
ax2.yaxis.labelpad = 20
colorlist = color.colors_from_cmap(2, cm.jet)
ax1.text(0.15, 0.17, 'z=1.9', ha='left', va='top', color=colorlist[0])
ax1.text(-0.23, 0.32, 'z=2.4', ha='left', va='top', color=colorlist[1])
pl.draw()
return simIa, simIbc, simII
def plotzpoints(sn,simIa,dz=0.05):
""" plot the
:param sn:
:param simIa:
:param dz:
:return:
"""
from matplotlib import cm
import mpltools
from pytools import plotsetup
if 'FLT' not in simIa.__dict__ :
simIa.getLightCurves()
zbins, c7Ipts, c8Ipts, cPNpts = get_colors_binned_by_z(sn,simIa,dz)
plotsetup.fullpaperfig( 1, [5,5] )
pl.clf()
ax1 = pl.gca()
# ax1.plot(QH,PN, ls=' ', marker='o',color='k', alpha=0.3 )
mpltools.color.cycle_cmap( len(zbins), cmap=cm.gist_rainbow_r, ax=ax1)
for iz in range(len(zbins)-1) :
z0, z1 = zbins[iz],zbins[iz+1]
#if dz>=0.1 : zmid = round(np.mean([z0,z1]),1)
#elif dz>=0.01 : zmid = round(np.mean([z0,z1]),2)
ax1.plot(c7Ipts[iz],cPNpts[iz], marker='o', alpha=0.3, ls=' ',
mew=0,label='%.2f-%.2f'%(z0,z1) )
ax1.legend(loc='upper left', ncol=2, numpoints=1, frameon=False,
handletextpad=0.3, handlelength=0.2 )
ax1.set_xlabel('F763M-F814W')
ax1.set_ylabel('F139M-F140W')
# plotPhot(label=True)
ax1.set_xlim(-0.8,0.8)
ax1.set_ylim(-0.8,0.8)
fig = pl.gcf()
fig.subplots_adjust(bottom=0.12,left=0.16,right=0.95,top=0.95)
pl.draw()
def mkfig3d( simdata, dz=0.05, snanadatfile=_SNANADATFILE, ):
""" Plot the results of a SNANA monte carlo simulation as a 3-D circle
diagram.
:param simdata:
:param dz:
:param snanadatfile:
:return:
"""
from mpl_toolkits.mplot3d.axes3d import Axes3D
from matplotlib import cm
import mpltools
from pytools import plotsetup
fig = plotsetup.fullpaperfig( 1, [10,10] )
sn = stardust.SuperNova(snanadatfile)
simIa, simIbc, simII = simdata
ax1 = fig.add_axes( [0.12,0.12,0.85,0.85], projection='3d')
c7I,c8I, cPN = get_colors( simII )
ax1.plot3D(c7I,c8I,cPN, marker='o', color='k',
alpha=1, ls=' ', mew=0,label='Type II' )
c7I,c8I, cPN = get_colors( simIbc )
ax1.plot3D(c7I,c8I,cPN, marker='o', color='sienna',
alpha=1, ls=' ', mew=0,label='Type Ibc' )
zbins, c7I,c8I, cPN = get_colors_binned_by_z( sn, simIa, dz=dz )
mpltools.color.cycle_cmap( len(zbins), cmap=cm.gist_rainbow_r, ax=ax1)
for iz in range(len(zbins)-1) :
z0, z1 = zbins[iz],zbins[iz+1]
#if dz>=0.1 : zmid = round(np.mean([z0,z1]),1)
#elif dz>=0.01 : zmid = round(np.mean([z0,z1]),2)
ax1.plot3D(c7I[iz],c8I[iz],cPN[iz], marker='o', alpha=1, ls=' ',
mew=0,label='%.2f-%.2f'%(z0,z1) )
ax1.set_xlim(-0.1,0.5)
ax1.set_ylim(-0.4,0.2)
ax1.set_zlim(-0.3,0.3)
ax1.legend(loc='upper left', ncol=2, numpoints=1, frameon=False,
handletextpad=0.3, handlelength=0.2 )
ax1.set_xlabel('F763M-F814W')
ax1.set_ylabel('F845M-F140W')
ax1.set_zlabel('F139M-F140W')
def mk_multisurvey_fig():
fig1 = plotsetup.fullpaperfig(figsize=[12,6])
fig1.clf()
for survey, zbins, mfc, mec in zip(
['Deep','Med','Wide'],
[np.arange(0.8,2.51,0.25),np.arange(0.3,1.25,0.2),
np.arange(0.01,0.62,0.2)],
[cp.lightred, cp.teal, cp.lightblue],
[cp.darkred, cp.darkgreen, cp.darkblue]):
mk_class_fig('%s_class.dat' % survey.lower(), zbins=zbins,
mfc=mfc, mec=mec, color=mec, marker='D')
ax = fig1.add_subplot(2,4,1)
txt = ax.text(0.4, 0.7, 'Wide', ha='right', va='top',
fontsize=15, color=cp.darkblue)
txt = ax.text(0.6, 0.65, 'Med', ha='left', va='top',
fontsize=15, color=cp.teal)
txt = ax.text(1.5, 0.55, 'Deep', ha='center', va='top',
fontsize=15, color=cp.darkred)
pl.savefig(os.path.expanduser("~/Desktop/wfirst_classification_test.pdf"))
def sncosmo_circlefig( simIa=None, simCC=None,
simIapkl='colfax_SncosmoSim_Ia.pkl',
simCCpkl='colfax_SncosmoSim_CC.pkl',
z_range=[1.9,2.35], nsim=1000,
verbose=True, clobber=False ):
""" Construct a color-color circle figure for SN Colfax, with observed
photometry included.
:param simIa:
:param simCC:
:param simIapkl:
:param simCCpkl:
:param z_range:
:param nsim:
:param verbose:
:param clobber:
:return:
"""
import medband_classtest
import os
import cPickle
from matplotlib import pyplot as pl
# from matplotlib import patheffects as pe
import numpy as np
from pytools import plotsetup
fig = plotsetup.fullpaperfig( 1, figsize=[8,4])
pl.ioff()
mjdpk = 56078
mjdmedband = 56084
t0_range = [ mjdmedband-mjdpk-3,mjdmedband-mjdpk+3 ]
t0 = mjdmedband-mjdpk
if simIa is not None :
pass
elif os.path.isfile( simIapkl ) and not clobber>1 :
if verbose: print("Loading Ia simulation from pickle : %s"%simIapkl)
fin = open( simIapkl, 'rb' )
simIa = cPickle.load( fin )
fin.close()
else :
if verbose: print("Running a new Ia simulation, then saving to pickle : %s"%simIapkl)
simIa = medband_classtest.SncosmoSim( 'Ia' , z_range=z_range, t0_range=t0_range, nsim=nsim )
fout = open( simIapkl, 'wb' )
cPickle.dump( simIa, fout, protocol=-1 )
fout.close()
if simCC is not None :
pass
elif os.path.isfile( simCCpkl ) and not clobber>1 :
if verbose: print("Loading CC simulation from pickle : %s"%simCCpkl)
fin = open( simCCpkl, 'rb' )
simCC = cPickle.load(fin)
fin.close()
else :
if verbose: print("Running a new CC simulation, then saving to pickle : %s"%simCCpkl)
simCC = medband_classtest.SncosmoSim( 'CC' , z_range=z_range, t0_range=t0_range, nsim=nsim )
fout = open( simCCpkl, 'wb' )
cPickle.dump( simCC, fout, protocol=-1 )
fout.close()
import getredshift
plotcontours( simIa, simCC, plotstyle='points' )
fig = pl.gcf()
ax1 = fig.add_subplot(1,2,1)
mkcirclepoints(zrange=z_range, t0=t0, colorselect=[1,0], coloredaxislabels=False, marker='o' )
ax2 = fig.add_subplot(1,2,2, sharex=ax1)
mkcirclepoints(zrange=z_range, t0=t0, colorselect=[1,2], coloredaxislabels=False, marker='o' )
mag4 = { # using the multi-epoch stack for the psf model
'f127m':25.6728,
'f125w':26.1096,
'f139m':25.5964,
'f140w':25.7223,
'f153m':25.7903,
'f160w':25.9248,
}
magerr = { # using the drop-and-recover psf fitting err method
'f125w':0.126760,
'f127m':0.102688,
'f139m':0.132692,
'f140w':0.043144,
'f153m':0.170073,
'f160w':0.117535,
}
mag2 = { # Using steve's 0.3"-aperture photometry
'f127m':25.668,
'f125w':26.172,
'f139m':25.601,
'f140w':25.747,
'f153m':25.769,
'f160w':25.958,
}
magerr2 = { # Using steve's 0.3"-aperture photometry
'f127m':0.095,
'f125w':0.118,
'f139m':0.096,
'f140w':0.063,
'f153m':0.125,
'f160w':0.129,
}
mag = mag6
f25 = {}
ferr25 = {}
for k in mag.keys() :
f25[k] = 10**(-0.4*(mag[k]-25.))
ferr25[k] = magerr[k] * f25[k] / 2.5*np.log10(np.e)
deltamag = { 'f127m':mag['f127m']-mag['f125w'],
'f139m':mag['f139m']-mag['f140w'],
'f153m':mag['f153m']-mag['f160w'],
}
deltamagerr = { 'f127m':np.sqrt(magerr['f127m']**2+magerr['f125w']**2),
'f139m':np.sqrt(magerr['f139m']**2+magerr['f140w']**2),
'f153m':np.sqrt(magerr['f153m']**2+magerr['f160w']**2),
}
ax1.errorbar( deltamag['f139m'], deltamag['f127m'],
deltamagerr['f127m'], deltamagerr['f139m'],
marker='D', ms=10, elinewidth=2, capsize=0, color='darkorange' )
ax2.errorbar( deltamag['f139m'], deltamag['f153m'],
deltamagerr['f153m'], deltamagerr['f139m'],
marker='D', ms=10, elinewidth=2, capsize=0, color='darkorange' )
ax1.set_xlim( -0.35, 0.3 )
ax1.set_ylim( -0.7, 0.22 )
ax2.set_ylim( -0.4, 0.3 )
ax2.text( deltamag['f139m']+0.05, deltamag['f153m']-0.05, 'GND12Col' ,
ha='left',va='top', color='darkorange',fontsize=15,)
# path_effects=[pe.withStroke( linewidth=3,foreground='k')] )
# pl.legend( loc='upper right', numpoints=2, handlelength=0.3)
pl.draw()
pl.ion()
return( simIa, simCC )
def sncosmo_circlefig(simIa=None,
simCC=None,
simIapkl='colfax_SncosmoSim_Ia.pkl',
simCCpkl='colfax_SncosmoSim_CC.pkl',
z_range=[1.9, 2.35],
nsim=1000,
verbose=True,
clobber=False):
""" Construct a color-color circle figure for SN Colfax, with observed
photometry included.
:param simIa:
:param simCC:
:param simIapkl:
:param simCCpkl:
:param z_range:
:param nsim:
:param verbose:
:param clobber:
:return:
"""
import medband_classtest
import os
import cPickle
from matplotlib import pyplot as pl
# from matplotlib import patheffects as pe
import numpy as np
from pytools import plotsetup
fig = plotsetup.fullpaperfig(1, figsize=[8, 4])
pl.ioff()
mjdpk = 56078
mjdmedband = 56084
t0_range = [mjdmedband - mjdpk - 3, mjdmedband - mjdpk + 3]
t0 = mjdmedband - mjdpk
if simIa is not None:
pass
elif os.path.isfile(simIapkl) and not clobber > 1:
if verbose: print("Loading Ia simulation from pickle : %s" % simIapkl)
fin = open(simIapkl, 'rb')
simIa = cPickle.load(fin)
fin.close()
else:
if verbose:
print("Running a new Ia simulation, then saving to pickle : %s" %
simIapkl)
simIa = medband_classtest.SncosmoSim('Ia',
z_range=z_range,
t0_range=t0_range,
nsim=nsim)
fout = open(simIapkl, 'wb')
cPickle.dump(simIa, fout, protocol=-1)
fout.close()
if simCC is not None:
pass
elif os.path.isfile(simCCpkl) and not clobber > 1:
if verbose: print("Loading CC simulation from pickle : %s" % simCCpkl)
fin = open(simCCpkl, 'rb')
simCC = cPickle.load(fin)
fin.close()
else:
if verbose:
print("Running a new CC simulation, then saving to pickle : %s" %
simCCpkl)
simCC = medband_classtest.SncosmoSim('CC',
z_range=z_range,
t0_range=t0_range,
nsim=nsim)
fout = open(simCCpkl, 'wb')
cPickle.dump(simCC, fout, protocol=-1)
fout.close()
import getredshift
plotcontours(simIa, simCC, plotstyle='points')
fig = pl.gcf()
ax1 = fig.add_subplot(1, 2, 1)
mkcirclepoints(zrange=z_range,
t0=t0,
colorselect=[1, 0],
coloredaxislabels=False,
marker='o')
ax2 = fig.add_subplot(1, 2, 2, sharex=ax1)
mkcirclepoints(zrange=z_range,
t0=t0,
colorselect=[1, 2],
coloredaxislabels=False,
marker='o')
mag4 = { # using the multi-epoch stack for the psf model
'f127m':25.6728,
'f125w':26.1096,
'f139m':25.5964,
'f140w':25.7223,
'f153m':25.7903,
'f160w':25.9248,
}
magerr = { # using the drop-and-recover psf fitting err method
'f125w':0.126760,
'f127m':0.102688,
'f139m':0.132692,
'f140w':0.043144,
'f153m':0.170073,
'f160w':0.117535,
}
mag2 = { # Using steve's 0.3"-aperture photometry
'f127m':25.668,
'f125w':26.172,
'f139m':25.601,
'f140w':25.747,
'f153m':25.769,
'f160w':25.958,
}
magerr2 = { # Using steve's 0.3"-aperture photometry
'f127m':0.095,
'f125w':0.118,
'f139m':0.096,
'f140w':0.063,
'f153m':0.125,
'f160w':0.129,
}
mag = mag6
f25 = {}
ferr25 = {}
for k in mag.keys():
f25[k] = 10**(-0.4 * (mag[k] - 25.))
ferr25[k] = magerr[k] * f25[k] / 2.5 * np.log10(np.e)
deltamag = {
'f127m': mag['f127m'] - mag['f125w'],
'f139m': mag['f139m'] - mag['f140w'],
'f153m': mag['f153m'] - mag['f160w'],
}
deltamagerr = {
'f127m': np.sqrt(magerr['f127m']**2 + magerr['f125w']**2),
'f139m': np.sqrt(magerr['f139m']**2 + magerr['f140w']**2),
'f153m': np.sqrt(magerr['f153m']**2 + magerr['f160w']**2),
}
ax1.errorbar(deltamag['f139m'],
deltamag['f127m'],
deltamagerr['f127m'],
deltamagerr['f139m'],
marker='D',
ms=10,
elinewidth=2,
capsize=0,
color='darkorange')
ax2.errorbar(deltamag['f139m'],
deltamag['f153m'],
deltamagerr['f153m'],
deltamagerr['f139m'],
marker='D',
ms=10,
elinewidth=2,
capsize=0,
color='darkorange')
ax1.set_xlim(-0.35, 0.3)
ax1.set_ylim(-0.7, 0.22)
ax2.set_ylim(-0.4, 0.3)
ax2.text(
deltamag['f139m'] + 0.05,
deltamag['f153m'] - 0.05,
'GND12Col',
ha='left',
va='top',
color='darkorange',
fontsize=15,
)
# path_effects=[pe.withStroke( linewidth=3,foreground='k')] )
# pl.legend( loc='upper right', numpoints=2, handlelength=0.3)
pl.draw()
pl.ion()
return (simIa, simCC)
def mkresidplot(datfile='ps1union.dat',
ageaxis=True,
highz='Malmquist',
highzlabels=True,
lensfactor=0.093,
presfig=False,
bigtext=False):
""" construct the hubble residual plot
"""
from pytools import plotsetup, cosmo, colorpalette as cp
from matplotlib import patches
import numpy as np
from matplotlib import pyplot as pl
from scipy.interpolate import interp1d
if presfig:
plotsetup.presfig(wide=True)
else:
plotsetup.fullpaperfig([8.5, 4.5], bigtext=bigtext)
clf()
highz = highz.lower()
if highz == 'malmquist':
zlim = [0, 2.78]
elif highz == 'rodney':
zlim = [0, 3.49]
if presfig: zlim = [0, 3.78]
else:
zlim = [0, 2.45]
fig = gcf()
if presfig:
bottomAxeslim = [0.13, 0.18, 0.85, 0.65]
else:
bottomAxeslim = [0.09, 0.12, 0.88, 0.75]
ax1 = fig.add_axes(bottomAxeslim, frameon=True, alpha=0.0, label='axes1')
ax1top = ax1.twiny()
# read in redshifts and distances
hubbledat, H0, Om, MB = gethubbledat(datfile)
if lensfactor:
# muerr = 0.093z : Holz & Linder, 2005
# muerr = 0.055z : Jonsson+ 2012
hubbledat['muerr'] = np.sqrt(hubbledat['muerr']**2 +
(lensfactor * hubbledat['z'])**2)
# plot ground data
colordict = {
'low-z': cp.purple,
'sdss': cp.lightblue,
'ps1': cp.darkblue,
'snls': cp.darkgreen,
'hstacs': cp.darkorange,
'hstwfc3': cp.medred,
'hstwfc3a': cp.medred,
'hstwfc3b': cp.darkred,
'jwst': cp.darkgrey,
}
elw = 0.75
cs = 0
for survey in ['low-z', 'sdss', 'snls', 'ps1', 'hstacs']:
isurvey = where((hubbledat['survey'] == survey)
& (hubbledat['spec'] > 0))
ax1.errorbar(hubbledat['z'][isurvey],
hubbledat['mures'][isurvey],
hubbledat['muerr'][isurvey],
hubbledat['zerr'][isurvey],
marker='o',
ls=' ',
mew=0.01,
markersize=5,
color=colordict[survey],
mfc=colordict[survey],
ecolor=colordict[survey],
elinewidth=elw,
capsize=cs,
alpha=0.7)
if highz:
# get the high-z SN fits from Dan
labeldict = {#'primo':'Rodney+ 2012',
#'wilson':'Jones, Rodney+ 2013',
'stone':'GND13Sto',
'colfax':'GND12Col',
}
if highz == 'rodney':
labeldict = {
'primo': 'Rodney+ 2012',
'wilson': 'Jones, Rodney+ 2013',
'stone': 'Rodney+ in prep',
'colfax': 'Rodney+ in prep',
}
for survey, namelist in zip(
['hstwfc3a', 'hstwfc3b'],
[['primo', 'wilson'], ['stone', 'colfax']]):
color = colordict[survey]
for name in namelist:
if name not in hubbledat['name']: continue
iname = np.where(hubbledat['name'] == name)[0][0]
z, zerr = hubbledat['z'][iname], hubbledat['zerr'][iname]
mu, muerr = hubbledat['mures'][iname], hubbledat['muerr'][
iname]
if name == 'colfax':
# Not applying a lensing correction for mu=1.04 +-0.03 : 0.0426 +- 0.031 mag
icol = np.where(
[n.startswith('col') for n in hubbledat['name']])[0]
mucol = interp1d(hubbledat['z'][icol],
hubbledat['mures'][icol])
ax1.plot([2.16, 2.19, 2.21, 2.24, 2.26, 2.28],
mucol([2.16, 2.19, 2.21, 2.24, 2.26, 2.28]),
color=color,
lw=0.75,
ls='-')
ax1.errorbar(2.26,
mucol(2.26),
muerr,
marker='D',
ls=' ',
mew=0.01,
markersize=8,
color=color,
mfc=color,
ecolor=color,
elinewidth=elw,
capsize=cs,
alpha=1)
z = 2.26
mu = mucol(2.26)
elif name == 'stone':
# not applying a lensing correction for stone:
# mu = mu + 0.0215; muerr = np.sqrt( muerr**2 + 0.02**2 )
isto = np.where(
[n.startswith('stone') for n in hubbledat['name']])[0]
musto = interp1d(hubbledat['z'][isto],
hubbledat['mures'][isto])
ax1.plot(np.arange(1.66, 2.01, 0.02),
musto(np.arange(1.66, 2.01, 0.02)),
color=color,
lw=0.75,
ls='--')
ax1.errorbar(1.80,
musto(1.80),
muerr,
zerr,
marker='D',
ls=' ',
mew=0.01,
markersize=8,
color=color,
mfc=color,
ecolor=color,
elinewidth=elw,
capsize=cs,
alpha=1)
z = 1.80
mu = musto(1.80)
else:
ax1.errorbar(z,
mu,
muerr,
zerr,
marker='D',
ls=' ',
mew=0.01,
markersize=8,
color=color,
mfc=color,
ecolor=color,
elinewidth=elw,
capsize=cs,
alpha=1)
if highzlabels and name in labeldict:
# ax1.text( z-0.035, mu+0.07, labeldict[name],
if name == 'primo':
ax1.text(
z - 0.05,
mu + 0.035,
labeldict[name],
color=color, # backgroundcolor='w',
va='bottom',
ha='center',
rotation=90)
else:
ax1.text(
z,
mu + muerr + 0.07,
labeldict[name],
color=color, # backgroundcolor='w',
va='bottom',
ha='center',
rotation=90)
# plot the lcdm cosmology
ax1.axhline(0, color='0.4', ls='-')
# plot extreme w'
zLCDM = np.arange(0.01, 5, 0.05)
muLCDM = cosmo.mu(zLCDM, H0=H0, Om=Om, Ode=(1 - Om), w0=-1., wa=0)
#muextremeDE = cosmo.mu( z, H0=_H0, Om=_Om, Ode=(1-_Om), w0=-0.7, wa=-2)
mu1 = cosmo.mu(zLCDM,
H0=H0,
Om=Om - 0.015,
Ode=(1 - Om + 0.015),
w0=-1.2,
wa=0.7)
mu2 = cosmo.mu(zLCDM,
H0=H0,
Om=Om + 0.055,
Ode=(1 - Om - 0.055),
w0=-0.65,
wa=-2.2)
ax1.fill_between(zLCDM,
mu1 - muLCDM,
mu2 - muLCDM,
color='k',
alpha=0.2,
lw=0.01,
zorder=10)
if not presfig:
ax1.text(0.08,
-0.8,
'low-z',
fontsize=(presfig and 'small') or 10.5,
ha='center',
color=colordict['low-z'])
ax1.text(0.25,
-0.85,
'SDSS',
fontsize=(presfig and 'small') or 10.5,
ha='center',
color=colordict['sdss'])
ax1.text(0.5,
-0.9,
'PS1',
fontsize=(presfig and 'small') or 10.5,
ha='center',
color=colordict['ps1'])
ax1.text(0.75,
-0.95,
'SNLS',
fontsize=(presfig and 'small') or 10.5,
ha='center',
color=colordict['snls'])
ax1.text(1.25,
-0.8,
'HST+ACS',
fontsize=(presfig and 'small') or 10.5,
ha='center',
color=colordict['hstacs'])
ax1.text(1.95,
-0.95,
'HST+WFC3',
fontsize=(presfig and 'small') or 10.5,
ha='center',
color=colordict['hstwfc3b'])
lowzRect = patches.Rectangle([0.0, -0.85],
0.08,
0.03,
fill=True,
lw=0,
alpha=0.3,
color=colordict['low-z'])
sdssRect = patches.Rectangle([0.06, -0.9],
0.34,
0.03,
fill=True,
lw=0,
alpha=0.3,
color=colordict['sdss'])
ps1Rect = patches.Rectangle([0.1, -0.95],
0.5,
0.03,
fill=True,
lw=0,
alpha=0.3,
color=colordict['ps1'])
snlsRect = patches.Rectangle([0.15, -1.0],
0.9,
0.03,
fill=True,
lw=0,
alpha=0.3,
color=colordict['snls'])
acsRect = patches.Rectangle([0.60, -0.85],
1.15,
0.03,
fill=True,
lw=0,
alpha=0.3,
color=colordict['hstacs'])
wfc3Rect = patches.Rectangle([1.20, -1.0],
1.1,
0.03,
fill=True,
lw=0,
alpha=0.3,
color=colordict['hstwfc3b'])
ax1.add_patch(lowzRect)
ax1.add_patch(sdssRect)
ax1.add_patch(ps1Rect)
ax1.add_patch(snlsRect)
ax1.add_patch(acsRect)
ax1.add_patch(wfc3Rect)
if highz == 'rodney':
if not presfig:
#ffsnRect = patches.Rectangle( [2.30,-1.0], 0.7, 0.03, fill=False,lw=1, alpha=1.0, color=colordict['hstwfc3b'] )
jwstRect = patches.Rectangle([2.00, -0.85],
2.0,
0.03,
fill=False,
lw=1,
alpha=1.0,
color=colordict['jwst'])
#ax1.add_patch( ffsnRect )
ax1.add_patch(jwstRect)
#ax1.text( 2.5, -0.95, '+ lensing',fontsize=10.5, ha='center', color=colordict['hstwfc3b'] )
ax1.text(3.0,
-0.78,
'JWST',
fontsize=(presfig and 'medium') or 10.5,
ha='center',
color=colordict['jwst'])
color = cp.bluegray
ax1.arrow(2.5,
0.15,
0.3,
0.0,
fc=color,
ec=color,
head_width=0.05,
head_length=0.0,
overhang=0.0)
ax1.plot(2.5, 0.15, marker='o', mfc='w', mec=color)
ax1.text(2.49, 0.19, '0.3 Gyr', ha='left', va='bottom', color=color)
ax1.text(2.82, 0.15, 'z=2.8', ha='left', va='center', color=color)
color = cp.teal
ax1.arrow(2.5,
0.45,
0.55,
0.0,
fc=color,
ec=color,
head_width=0.05,
head_length=0.08,
overhang=0.25,
length_includes_head=True)
ax1.plot(2.5, 0.45, marker='o', mfc='w', mec=color)
ax1.text(2.6, 0.48, '1 Gyr', ha='left', va='bottom', color=color)
ax1.text(3.08, 0.45, 'z=3.8', ha='left', va='center', color=color)
color = cp.coral
ax1.arrow(2.5,
0.7,
0.75,
0.0,
fc=color,
ec=color,
head_width=0.05,
head_length=0.08,
overhang=0.25,
length_includes_head=True)
ax1.plot(2.5, 0.7, marker='o', mfc='w', mec=color)
ax1.text(2.7, 0.72, '2 Gyr', ha='left', va='bottom', color=color)
ax1.text(3.28, 0.7, 'z=8.3', ha='left', va='center', color=color)
if not presfig:
ax1.text(2.5, 0.7, 'z=2.5', ha='center', va='bottom', color='0.4')
ax1.text(2.5,
0.8,
'explosion',
ha='center',
va='bottom',
color='0.3') #, fontsize=10.5 )
ax1.text(2.85, 0.8, 'delay', ha='center', va='bottom',
color='0.3') #, fontsize=10.5 )
ax1.text(3.15,
0.8,
'formation',
ha='left',
va='bottom',
color='0.3') #, fontsize=10.5 )
if presfig:
ax1.text(
0.82,
0.46,
'flat $\Lambda$CDM',
color='0.1',
ha='right',
va='top',
transform=ax1.transAxes) # , fontsize=10.5, backgroundcolor='w' )
else:
ax1.text(
0.99,
0.56,
'flat $\Lambda$CDM',
color='0.1',
ha='right',
va='top',
transform=ax1.transAxes) # , fontsize=10.5, backgroundcolor='w' )
ax1.text(0.99,
0.46,
'$\pm$95\% conf. \non $w_0 , w_a$',
color='0.4',
ha='right',
va='top',
transform=ax1.transAxes) # , fontsize=10.5,backgroundcolor='w' )
# ax1.text( 0.95, 0.95, 'Open Symbols:\n no spec. confirmation', color='0.5', transform=ax1.transAxes, ha='right',va='top' )
ax1.set_xlabel('Redshift', fontsize='large')
# ax1.set_ylabel('$\mu_{observed}$ - $\mu_{\Lambda CDM}$')
if highz == 'rodney':
ax1.set_ylabel(r'$m_B^{\prime} - m_{\Lambda CDM}$', fontsize='large')
else:
ax1.set_ylabel(r'$m_B + \alpha x_1 - \beta c - m_{\Lambda CDM}$',
fontsize='large')
if presfig:
ax1.yaxis.set_label_coords(-0.08, 0.65)
# mulim = array( [33,46.5] )
muresidlim = array([-1.05, 1.05])
# zlim = array( [0.0,3.49] )
ax1.xaxis.set_ticks([
0.1,
] + np.arange(0.5, zlim[-1], 0.5).tolist())
ax1.set_xlim(zlim)
ax1.set_ylim(muresidlim)
from pytools import colorpalette as cp
if highz.lower() == 'malmquist':
# z, dm, tvis = get_visibility_time_grid( 0.5, x1=0., c=0. )
# contourlevels = [50]
# ax1.contour( z, dm, tvis, levels=contourlevels, colors=cp.darkbluegray, linestyles='dashed' )
z5050, dm5050 = get_visibility_time_line(tvislim=50,
deteff_threshold=0.5,
x1=0,
c=0,
zrange=[1.0, 3.0])
ax1.fill_between(z5050,
dm5050,
np.ones(len(z5050)) * muresidlim[1] + 0.05,
color=cp.bluegray,
zorder=-200,
alpha=0.3)
# ax1.plot( z5050, dm5050, color='0.8')
z050, dm050 = get_visibility_time_line(tvislim=0.01,
deteff_threshold=0.5,
x1=0,
c=0,
zrange=[1.7, 3.0])
ax1.fill_between(z050,
dm050,
np.ones(len(z050)) * muresidlim[1] + 0.05,
color=cp.darkbluegray,
zorder=-100,
alpha=0.3)
ax1.text(1.53,
0.92,
't$_{\\rm vis}<$50 days',
ha='left',
va='top',
color=cp.darkgrey)
ax1.text(2.75,
0.92,
'undetectable',
ha='right',
va='top',
color=cp.darkgrey)
if highz == 'evolution':
# plot SNIa evolution
minmassdict = progenitorMinMassLines(zform=11)
z = minmassdict['z']
for key, color in zip(['mm25', 'mm15', 'mm04'], ['r', 'g', 'b']):
minmass = minmassdict[key]
mavez = Mave(_MAXMASS, minmass)
ax1.plot(z, (mavez - mavez[0]) * _DMUDMASS, ls='-', color=color)
ax1.text(2.5,
-0.95,
'+ lensing',
fontsize=10.5,
ha='center',
color=colordict['hstwfc3b'])
ax1.text(3.0,
-0.78,
'JWST',
fontsize=10.5,
ha='center',
color=colordict['jwst'])
color = cp.bluegray
ax1.arrow(2.5,
0.25,
0.3,
0.0,
fc=color,
ec=color,
head_width=0.05,
head_length=0.0,
overhang=0.0)
ax1.plot(2.5, 0.25, marker='o', mfc='w', mec=color)
ax1.text(2.55, 0.27, '0.3 Gyr', ha='left', va='bottom', color=color)
ax1.text(2.82, 0.25, 'z=2.8', ha='left', va='center', color=color)
color = cp.teal
ax1.arrow(2.5,
0.45,
0.55,
0.0,
fc=color,
ec=color,
head_width=0.05,
head_length=0.08,
overhang=0.25,
length_includes_head=True)
ax1.plot(2.5, 0.45, marker='o', mfc='w', mec=color)
ax1.text(2.65, 0.47, '1 Gyr', ha='left', va='bottom', color=color)
ax1.text(3.08, 0.45, 'z=3.8', ha='left', va='center', color=color)
color = cp.coral
ax1.arrow(2.5,
0.65,
0.75,
0.0,
fc=color,
ec=color,
head_width=0.05,
head_length=0.08,
overhang=0.25,
length_includes_head=True)
ax1.plot(2.5, 0.65, marker='o', mfc='w', mec=color)
ax1.text(2.75, 0.67, '2 Gyr', ha='left', va='bottom', color=color)
ax1.text(3.28, 0.65, 'z=8.3', ha='left', va='center', color=color)
ax1.text(2.5, 0.7, 'z=2.5', ha='center', va='bottom', color='0.4')
ax1.text(2.5,
0.8,
'explosion',
ha='center',
va='bottom',
color='0.3',
fontsize=10.5)
ax1.text(2.85,
0.8,
'delay',
ha='center',
va='bottom',
color='0.3',
fontsize=10.5)
ax1.text(3.15,
0.8,
'formation',
ha='left',
va='bottom',
color='0.3',
fontsize=10.5)
if ageaxis:
if highz == 'rodney':
# ax1top.set_xlabel( 'age of Universe (Gyr)',fontsize='large',x=0.15,ha='left')
ageticks = np.array([13, 9, 6, 4, 3, 2])
else:
ageticks = np.array([13, 9, 6, 4, 3])
ax1top.set_xlabel('Age of Universe (Gyr)', fontsize='large')
ax1top.set_xlim(zlim)
ztickloctop = cosmo.zfromt(ageticks)
ax1top.xaxis.set_ticks(ztickloctop)
ax1top.xaxis.set_ticklabels(ageticks)
pl.draw()
def plot_light_curve_fit_from_SNANA(snid='colfax', plotmags=False):
""" make a plot showing the light curve fit, extracted from a SNANA
output .TEXT file generated by D.Scolnic"""
from pytools import plotsetup, colorpalette as cp
from astropy.io import ascii
import numpy as np
from matplotlib import pyplot as pl
from scipy.interpolate import interp1d
from matplotlib import ticker
import os
import sys
from hstphot import hstzpt
alpha2filter = {
'H': 'f160w',
'N': 'f140w',
'J': 'f125w',
'Y': 'f105w',
'Z': 'f850l',
'I': 'f814w',
'V': 'f606w',
'L': 'f098m',
'O': 'f127m',
'P': 'f139m',
'Q': 'f153m',
}
colordict = {
'H': 'k',
'J': cp.darkgold,
'Y': cp.cadetblue,
'N': cp.darkgreen,
'V': cp.coral
}
fluxdat = ascii.read('CANDELs-%s.LCPLOT.TEXT' % snid)
name = fluxdat['col1']
mjd = fluxdat['col2']
tobs = fluxdat['col3']
fluxcal = fluxdat['col4']
fluxcalerr = fluxdat['col5']
obsflag = fluxdat['col6']
bandletter = fluxdat['col7']
flux = fluxcal * 0.1
fluxerr = fluxcalerr * 0.1
# mag = np.where( flux>0, -2.5*np.log10( flux ) + 25, 35 )
# magerr = np.where( flux>0, 1.0857 * fluxerr / flux, 0.2 )
# medbanddict = {'f105w':'f098m','f125w':'f127m', 'f140w':'f139m', 'f160w':'f153m'}
colors = [cp.purple, cp.bluegray, cp.darkgreen, cp.red]
plotsetup.fullpaperfig([8, 3])
pl.clf()
fig = pl.gcf()
mjdmin = mjd.min() - 10
mjdmax = mjd.max() + 25
mjdmod = np.arange(mjdmin, mjdmax, 1)
if snid == 'colfax':
ymax = 0.7
ymaxMB = 0.3
mjdmin = 56025
mjdmax = 56220
z, mjdpeak = 2.1, 56080.
snlabel = 'GND12Col'
elif snid == 'stone':
ymax = 1.2
ymaxMB = 0.35
mjdmin = 56430
mjdmax = 56600
z, mjdpeak = 1.8, 56485.
snlabel = 'GND13Sto'
trestmin = (mjdmin - mjdpeak) / (1 + z)
trestmax = (mjdmax - mjdpeak) / (1 + z)
ax1w = pl.subplot2grid([4, 3], [0, 0], rowspan=3)
ax2w = pl.subplot2grid([4, 3], [0, 1], rowspan=3, sharex=ax1w, sharey=ax1w)
ax3w = pl.subplot2grid([4, 3], [0, 2], rowspan=3, sharex=ax1w, sharey=ax1w)
ax1m = pl.subplot2grid([4, 3], [3, 0], sharex=ax1w)
ax2m = pl.subplot2grid([4, 3], [3, 1], sharex=ax1w, sharey=ax1m)
ax3m = pl.subplot2grid([4, 3], [3, 2], sharex=ax1w, sharey=ax1m)
iax = 0
for bbl, mbl, color in zip(['Y', 'J', 'N', 'H'], ['L', 'O', 'P', 'Q'],
colors):
if bbl not in bandletter: continue
iax += 1
filternamew = alpha2filter[bbl].upper()
filternamem = alpha2filter[mbl].upper()
if iax == 1:
axw = ax1w
axm = ax1m
axw.text(0.05,
0.92,
snlabel,
color='k',
fontsize='large',
fontweight='heavy',
ha='left',
va='top',
transform=axw.transAxes)
# axw.text( -0.28, 1.2, snlabel, backgroundcolor='w', color='k', fontsize='large', fontweight='heavy', ha='left',va='top', transform=axw.transAxes, zorder=1000 )
axw.set_ylabel('flux (zp$_{AB}$=25)')
axm.set_ylabel('$\Delta$f$_{25}$')
elif iax == 2:
axw = ax2w
axm = ax2m
else:
axw = ax3w
axm = ax3m
axw.yaxis.set_ticks_position('right')
axw.yaxis.set_ticks_position('both')
axm.yaxis.set_ticks_position('right')
axm.yaxis.set_ticks_position('both')
axtop = axw.twiny()
axtop.set_xlim(trestmin, trestmax)
if iax == 2:
axtop.set_xlabel('rest frame time (days from peak)')
axm.set_xlabel('observer frame time (MJD)')
pl.setp(axw.get_yticklabels(), visible=False)
pl.setp(axm.get_yticklabels(), visible=False)
pl.setp(axw.get_xticklabels(), visible=False)
axw.text(0.95,
0.92,
filternamew,
ha='right',
va='top',
color=color,
transform=axw.transAxes)
iobs = np.where((bandletter == bbl) & (obsflag > 0))[0]
imod = np.where((bandletter == bbl) & (obsflag == 0))[0]
# import pdb; pdb.set_trace()
axw.errorbar(mjd[iobs],
flux[iobs],
fluxerr[iobs],
color=color,
marker='D',
ls=' ',
zorder=-100)
axw.plot(mjd[imod],
flux[imod],
color=color,
marker=' ',
ls='-',
zorder=-100)
axw.fill_between(mjd[imod],
flux[imod] + fluxerr[imod],
flux[imod] - fluxerr[imod],
color=color,
alpha=0.3,
zorder=-1000)
if mbl not in bandletter: continue
axm.text(0.95,
0.5,
filternamem,
ha='right',
va='center',
backgroundcolor='w',
color=color,
transform=axm.transAxes)
iobsmb = np.where((bandletter == mbl) & (obsflag > 0))[0]
imodmb = np.where((bandletter == mbl) & (obsflag == 0))[0]
mbfluxinterp = interp1d(mjd[imodmb],
flux[imodmb],
fill_value=0,
bounds_error=False)
mbfluxdiff = flux[iobsmb] - mbfluxinterp(mjd[iobsmb])
axm.errorbar(mjd[iobsmb],
mbfluxdiff,
fluxerr[iobsmb],
color=color,
marker='o',
mfc='w',
ls=' ')
axm.fill_between(mjd[imodmb],
fluxerr[imodmb],
-fluxerr[imodmb],
color=color,
alpha=0.3,
zorder=-1000)
axm.axhline(0, color=color, lw=0.8, ls='--')
ax1w.set_xlim(mjdmin, mjdmax)
ax1w.set_ylim(-0.08, ymax)
ax1m.set_ylim(-ymaxMB, ymaxMB)
ax1w.xaxis.set_major_locator(ticker.MultipleLocator(100))
ax1w.xaxis.set_minor_locator(ticker.MultipleLocator(25))
ax1w.yaxis.set_major_locator(ticker.MultipleLocator(0.2))
ax1w.yaxis.set_minor_locator(ticker.MultipleLocator(0.1))
ax1m.xaxis.set_major_locator(ticker.MultipleLocator(100))
ax1m.xaxis.set_minor_locator(ticker.MultipleLocator(25))
ax1m.yaxis.set_major_locator(ticker.MultipleLocator(0.2))
ax1m.yaxis.set_minor_locator(ticker.MultipleLocator(0.1))
fig.subplots_adjust(left=0.1,
bottom=0.18,
right=0.95,
top=0.82,
wspace=0.,
hspace=0)
pl.draw()
def sncosmo_circlefig(simIa=None,
simCC=None,
simIapkl='bush_SncosmoSim_Ia.pkl',
simCCpkl='bush_SncosmoSim_CC.pkl',
z_range=[1.16, 2.36],
nsim=1000,
verbose=True,
clobber=False):
""" Construct a color-color circle figure for SN Colfax, with observed
photometry included.
:param simIa:
:param simCC:
:param simIapkl:
:param simCCpkl:
:param z_range:
:param nsim:
:param verbose:
:param clobber:
:return:
"""
import medband_classtest
import os
import cPickle
from matplotlib import pyplot as pl
# from matplotlib import patheffects as pe
import numpy as np
from pytools import plotsetup
fig = plotsetup.fullpaperfig(1, figsize=[8, 4])
pl.ioff()
mjdpk = 55797.
mjdmedband = 55804.
t0_range = [mjdmedband - mjdpk - 3, mjdmedband - mjdpk + 3]
t0 = mjdmedband - mjdpk
if simIa is not None:
pass
elif os.path.isfile(simIapkl) and not clobber > 1:
if verbose: print("Loading Ia simulation from pickle : %s" % simIapkl)
fin = open(simIapkl, 'rb')
simIa = cPickle.load(fin)
fin.close()
else:
if verbose:
print("Running a new Ia simulation, then saving to pickle : %s" %
simIapkl)
simIa = medband_classtest.SncosmoSim('Ia',
z_range=z_range,
t0_range=t0_range,
nsim=nsim)
fout = open(simIapkl, 'wb')
cPickle.dump(simIa, fout, protocol=-1)
fout.close()
if simCC is not None:
pass
elif os.path.isfile(simCCpkl) and not clobber > 1:
if verbose: print("Loading CC simulation from pickle : %s" % simCCpkl)
fin = open(simCCpkl, 'rb')
simCC = cPickle.load(fin)
fin.close()
else:
if verbose:
print("Running a new CC simulation, then saving to pickle : %s" %
simCCpkl)
simCC = medband_classtest.SncosmoSim('CC',
z_range=z_range,
t0_range=t0_range,
nsim=nsim)
fout = open(simCCpkl, 'wb')
cPickle.dump(simCC, fout, protocol=-1)
fout.close()
import getredshift
# classify.plotcontours( simIa, simCC, plotstyle='points' )
fig = pl.gcf()
ax1 = fig.add_subplot(1, 2, 1)
mkcirclepoints(zrange=z_range,
t0=t0,
colorselect=[1, 0],
coloredaxislabels=False,
marker='o')
ax2 = fig.add_subplot(1, 2, 2, sharex=ax1)
mkcirclepoints(zrange=z_range,
t0=t0,
colorselect=[0, 2],
coloredaxislabels=False,
marker='o')
mag4 = { # from psf model based on the multi-epoch stack
'f125w':25.9432,
'f127m':25.9555,
'f139m':25.5784,
'f140w':26.2892,
'f153m':25.3580,
'f160w':25.9067,
}
mag6 = { # from psf model based on the multi-epoch stack
'f125w':25.9464,
'f127m':25.9610,
'f139m':25.6361,
'f140w':26.2892,
'f153m':25.3578,
'f160w':25.9097,
}
magerr = { # from drop method
'f125w':0.106712,
'f127m':0.184979,
'f139m':0.214549,
'f140w':0.1162 ,
'f153m':0.160024,
'f160w':0.138843,
}
mag = mag6
f25 = {}
ferr25 = {}
for k in mag.keys():
f25[k] = 10**(-0.4 * (mag[k] - 25.))
ferr25[k] = magerr[k] * f25[k] / 2.5 * np.log10(np.e)
deltamag = {
'f127m': mag['f127m'] - mag['f125w'],
'f139m': mag['f139m'] - mag['f140w'],
'f153m': mag['f153m'] - mag['f160w'],
}
deltamagerr = {
'f127m': np.sqrt(magerr['f127m']**2 + magerr['f125w']**2),
'f139m': np.sqrt(magerr['f139m']**2 + magerr['f140w']**2),
'f153m': np.sqrt(magerr['f153m']**2 + magerr['f160w']**2),
}
ax1.errorbar(deltamag['f139m'],
deltamag['f127m'],
deltamagerr['f127m'],
deltamagerr['f139m'],
marker='D',
ms=10,
elinewidth=2,
capsize=0,
color='darkorange')
ax2.errorbar(deltamag['f127m'],
deltamag['f153m'],
deltamagerr['f153m'],
deltamagerr['f127m'],
marker='D',
ms=10,
elinewidth=2,
capsize=0,
color='darkorange')
ax1.set_xlim(-0.35, 0.3)
ax1.set_ylim(-0.7, 0.22)
ax2.set_ylim(-0.4, 0.3)
ax2.text(
deltamag['f139m'] + 0.05,
deltamag['f153m'] - 0.05,
'GND12Bus',
ha='left',
va='top',
color='darkorange',
fontsize=15,
)
# path_effects=[pe.withStroke( linewidth=3,foreground='k')] )
# pl.legend( loc='upper right', numpoints=2, handlelength=0.3)
pl.draw()
pl.ion()
return (simIa, simCC)
def mkresidplot( datfile='ps1union.dat', ageaxis=True,
highz='Malmquist', highzlabels=True,
lensfactor=0.093, presfig=False, bigtext=False ) :
""" construct the hubble residual plot
"""
from pytools import plotsetup, cosmo, colorpalette as cp
from matplotlib import patches
import numpy as np
from matplotlib import pyplot as pl
from scipy.interpolate import interp1d
if presfig :
plotsetup.presfig( wide=True )
else :
plotsetup.fullpaperfig( [8.5,4.5], bigtext=bigtext)
clf()
highz= highz.lower()
if highz=='malmquist':
zlim=[0,2.78]
elif highz=='rodney':
zlim=[0,3.49]
if presfig : zlim=[0,3.78]
else :
zlim=[0,2.45]
fig = gcf()
if presfig :
bottomAxeslim = [ 0.13, 0.18, 0.85, 0.65 ]
else :
bottomAxeslim = [ 0.09, 0.12, 0.88, 0.75 ]
ax1 = fig.add_axes( bottomAxeslim, frameon=True, alpha=0.0, label='axes1')
ax1top = ax1.twiny()
# read in redshifts and distances
hubbledat, H0, Om, MB = gethubbledat( datfile )
if lensfactor :
# muerr = 0.093z : Holz & Linder, 2005
# muerr = 0.055z : Jonsson+ 2012
hubbledat['muerr'] = np.sqrt( hubbledat['muerr']**2 + (lensfactor*hubbledat['z'])**2 )
# plot ground data
colordict = {'low-z':cp.purple,
'sdss':cp.lightblue,
'ps1':cp.darkblue,
'snls':cp.darkgreen,
'hstacs':cp.darkorange,
'hstwfc3':cp.medred,
'hstwfc3a':cp.medred,
'hstwfc3b':cp.darkred,
'jwst':cp.darkgrey,
}
elw=0.75
cs=0
for survey in ['low-z','sdss','snls','ps1','hstacs']:
isurvey = where( (hubbledat['survey']==survey) & (hubbledat['spec']>0) )
ax1.errorbar( hubbledat['z'][isurvey], hubbledat['mures'][isurvey],
hubbledat['muerr'][isurvey], hubbledat['zerr'][isurvey],
marker='o', ls=' ',mew=0.01, markersize=5,
color=colordict[survey], mfc=colordict[survey],
ecolor=colordict[survey],
elinewidth=elw, capsize=cs, alpha=0.7 )
if highz :
# get the high-z SN fits from Dan
labeldict = {#'primo':'Rodney+ 2012',
#'wilson':'Jones, Rodney+ 2013',
'stone':'GND13Sto',
'colfax':'GND12Col',
}
if highz=='rodney':
labeldict = {'primo':'Rodney+ 2012',
'wilson':'Jones, Rodney+ 2013',
'stone':'Rodney+ in prep',
'colfax':'Rodney+ in prep',
}
for survey, namelist in zip( ['hstwfc3a','hstwfc3b'],
[['primo','wilson'],['stone','colfax']] ):
color=colordict[survey]
for name in namelist :
if name not in hubbledat['name'] : continue
iname = np.where( hubbledat['name'] == name )[0][0]
z,zerr = hubbledat['z'][iname], hubbledat['zerr'][iname]
mu,muerr = hubbledat['mures'][iname],hubbledat['muerr'][iname]
if name=='colfax' :
# Not applying a lensing correction for mu=1.04 +-0.03 : 0.0426 +- 0.031 mag
icol = np.where( [n.startswith('col') for n in hubbledat['name']] )[0]
mucol = interp1d( hubbledat['z'][icol], hubbledat['mures'][icol] )
ax1.plot( [2.16,2.19,2.21,2.24,2.26,2.28],
mucol([2.16,2.19,2.21,2.24,2.26,2.28]),
color=color, lw=0.75, ls='-' )
ax1.errorbar( 2.26, mucol(2.26), muerr,
marker='D', ls=' ',mew=0.01, markersize=8,
color=color, mfc=color, ecolor=color,
elinewidth=elw, capsize=cs, alpha=1 )
z = 2.26
mu = mucol(2.26)
elif name=='stone' :
# not applying a lensing correction for stone:
# mu = mu + 0.0215; muerr = np.sqrt( muerr**2 + 0.02**2 )
isto = np.where( [n.startswith('stone') for n in hubbledat['name']] )[0]
musto = interp1d( hubbledat['z'][isto], hubbledat['mures'][isto] )
ax1.plot( np.arange(1.66,2.01,0.02),
musto(np.arange(1.66,2.01,0.02)),
color=color, lw=0.75, ls='--' )
ax1.errorbar( 1.80, musto(1.80), muerr, zerr,
marker='D', ls=' ',mew=0.01, markersize=8,
color=color, mfc=color, ecolor=color,
elinewidth=elw, capsize=cs, alpha=1 )
z = 1.80
mu = musto(1.80)
else :
ax1.errorbar( z, mu, muerr, zerr,
marker='D', ls=' ',mew=0.01, markersize=8,
color=color, mfc=color, ecolor=color,
elinewidth=elw, capsize=cs, alpha=1 )
if highzlabels and name in labeldict :
# ax1.text( z-0.035, mu+0.07, labeldict[name],
if name=='primo':
ax1.text( z-0.05, mu+0.035, labeldict[name],
color=color, # backgroundcolor='w',
va='bottom', ha='center', rotation=90 )
else :
ax1.text( z, mu+muerr+0.07, labeldict[name],
color=color, # backgroundcolor='w',
va='bottom', ha='center', rotation=90 )
# plot the lcdm cosmology
ax1.axhline( 0, color='0.4', ls='-' )
# plot extreme w'
zLCDM = np.arange( 0.01, 5, 0.05)
muLCDM = cosmo.mu( zLCDM, H0=H0, Om=Om, Ode=(1-Om), w0=-1., wa=0)
#muextremeDE = cosmo.mu( z, H0=_H0, Om=_Om, Ode=(1-_Om), w0=-0.7, wa=-2)
mu1 = cosmo.mu( zLCDM, H0=H0, Om=Om-0.015, Ode=(1-Om+0.015), w0=-1.2, wa=0.7)
mu2 = cosmo.mu( zLCDM, H0=H0, Om=Om+0.055, Ode=(1-Om-0.055), w0=-0.65, wa=-2.2)
ax1.fill_between( zLCDM, mu1-muLCDM, mu2-muLCDM, color='k', alpha=0.2, lw=0.01, zorder=10 )
if not presfig :
ax1.text( 0.08, -0.8, 'low-z', fontsize=(presfig and 'small') or 10.5, ha='center', color=colordict['low-z'] )
ax1.text( 0.25, -0.85, 'SDSS', fontsize=(presfig and 'small') or 10.5, ha='center', color=colordict['sdss'] )
ax1.text( 0.5 , -0.9, 'PS1', fontsize=(presfig and 'small') or 10.5, ha='center', color=colordict['ps1'] )
ax1.text( 0.75, -0.95, 'SNLS', fontsize=(presfig and 'small') or 10.5, ha='center', color=colordict['snls'] )
ax1.text( 1.25, -0.8, 'HST+ACS', fontsize=(presfig and 'small') or 10.5, ha='center', color=colordict['hstacs'] )
ax1.text( 1.95, -0.95, 'HST+WFC3', fontsize=(presfig and 'small') or 10.5, ha='center', color=colordict['hstwfc3b'] )
lowzRect = patches.Rectangle( [0.0,-0.85], 0.08, 0.03, fill=True, lw=0, alpha=0.3, color=colordict['low-z'] )
sdssRect = patches.Rectangle( [0.06,-0.9], 0.34, 0.03, fill=True, lw=0, alpha=0.3, color=colordict['sdss'] )
ps1Rect = patches.Rectangle( [0.1,-0.95], 0.5, 0.03, fill=True, lw=0, alpha=0.3, color=colordict['ps1'] )
snlsRect = patches.Rectangle( [0.15,-1.0], 0.9, 0.03, fill=True, lw=0, alpha=0.3, color=colordict['snls'] )
acsRect = patches.Rectangle( [0.60,-0.85], 1.15, 0.03, fill=True, lw=0, alpha=0.3, color=colordict['hstacs'] )
wfc3Rect = patches.Rectangle( [1.20,-1.0], 1.1, 0.03, fill=True, lw=0, alpha=0.3, color=colordict['hstwfc3b'] )
ax1.add_patch( lowzRect )
ax1.add_patch( sdssRect )
ax1.add_patch( ps1Rect )
ax1.add_patch( snlsRect )
ax1.add_patch( acsRect )
ax1.add_patch( wfc3Rect )
if highz=='rodney':
if not presfig :
#ffsnRect = patches.Rectangle( [2.30,-1.0], 0.7, 0.03, fill=False,lw=1, alpha=1.0, color=colordict['hstwfc3b'] )
jwstRect = patches.Rectangle( [2.00,-0.85],2.0, 0.03, fill=False,lw=1, alpha=1.0, color=colordict['jwst'] )
#ax1.add_patch( ffsnRect )
ax1.add_patch( jwstRect )
#ax1.text( 2.5, -0.95, '+ lensing',fontsize=10.5, ha='center', color=colordict['hstwfc3b'] )
ax1.text( 3.0, -0.78, 'JWST', fontsize=(presfig and 'medium') or 10.5, ha='center', color=colordict['jwst'] )
color = cp.bluegray
ax1.arrow( 2.5, 0.15, 0.3, 0.0, fc=color, ec=color, head_width=0.05, head_length=0.0, overhang=0.0 )
ax1.plot( 2.5, 0.15, marker='o', mfc='w', mec=color )
ax1.text( 2.49, 0.19, '0.3 Gyr', ha='left', va='bottom', color=color)
ax1.text( 2.82, 0.15, 'z=2.8', ha='left', va='center', color=color)
color = cp.teal
ax1.arrow( 2.5, 0.45, 0.55, 0.0, fc=color, ec=color, head_width=0.05, head_length=0.08, overhang=0.25, length_includes_head=True )
ax1.plot( 2.5, 0.45, marker='o', mfc='w', mec=color )
ax1.text( 2.6, 0.48, '1 Gyr', ha='left', va='bottom', color=color)
ax1.text( 3.08, 0.45, 'z=3.8', ha='left', va='center', color=color)
color = cp.coral
ax1.arrow( 2.5, 0.7, 0.75, 0.0, fc=color, ec=color, head_width=0.05, head_length=0.08, overhang=0.25, length_includes_head=True )
ax1.plot( 2.5, 0.7, marker='o', mfc='w', mec=color )
ax1.text( 2.7, 0.72, '2 Gyr', ha='left', va='bottom', color=color)
ax1.text( 3.28, 0.7, 'z=8.3', ha='left', va='center', color=color)
if not presfig :
ax1.text( 2.5, 0.7, 'z=2.5', ha='center', va='bottom', color='0.4' )
ax1.text( 2.5, 0.8, 'explosion', ha='center', va='bottom', color='0.3' )#, fontsize=10.5 )
ax1.text( 2.85, 0.8, 'delay', ha='center', va='bottom', color='0.3' )#, fontsize=10.5 )
ax1.text( 3.15, 0.8, 'formation', ha='left', va='bottom', color='0.3' )#, fontsize=10.5 )
if presfig :
ax1.text( 0.82, 0.46, 'flat $\Lambda$CDM',
color='0.1', ha='right', va='top',
transform=ax1.transAxes )# , fontsize=10.5, backgroundcolor='w' )
else :
ax1.text( 0.99, 0.56, 'flat $\Lambda$CDM',
color='0.1', ha='right', va='top',
transform=ax1.transAxes )# , fontsize=10.5, backgroundcolor='w' )
ax1.text( 0.99, 0.46, '$\pm$95\% conf. \non $w_0 , w_a$',
color='0.4', ha='right', va='top',
transform=ax1.transAxes )# , fontsize=10.5,backgroundcolor='w' )
# ax1.text( 0.95, 0.95, 'Open Symbols:\n no spec. confirmation', color='0.5', transform=ax1.transAxes, ha='right',va='top' )
ax1.set_xlabel('Redshift',fontsize='large')
# ax1.set_ylabel('$\mu_{observed}$ - $\mu_{\Lambda CDM}$')
if highz=='rodney' :
ax1.set_ylabel(r'$m_B^{\prime} - m_{\Lambda CDM}$', fontsize='large')
else :
ax1.set_ylabel(r'$m_B + \alpha x_1 - \beta c - m_{\Lambda CDM}$', fontsize='large')
if presfig :
ax1.yaxis.set_label_coords( -0.08, 0.65 )
# mulim = array( [33,46.5] )
muresidlim = array( [-1.05,1.05] )
# zlim = array( [0.0,3.49] )
ax1.xaxis.set_ticks( [0.1,] + np.arange(0.5,zlim[-1],0.5).tolist() )
ax1.set_xlim( zlim )
ax1.set_ylim( muresidlim )
from pytools import colorpalette as cp
if highz.lower()=='malmquist' :
# z, dm, tvis = get_visibility_time_grid( 0.5, x1=0., c=0. )
# contourlevels = [50]
# ax1.contour( z, dm, tvis, levels=contourlevels, colors=cp.darkbluegray, linestyles='dashed' )
z5050, dm5050 = get_visibility_time_line( tvislim=50, deteff_threshold=0.5, x1=0, c=0, zrange=[1.0,3.0] )
ax1.fill_between( z5050, dm5050, np.ones(len(z5050))*muresidlim[1]+0.05, color=cp.bluegray, zorder=-200, alpha=0.3)
# ax1.plot( z5050, dm5050, color='0.8')
z050, dm050 = get_visibility_time_line( tvislim=0.01, deteff_threshold=0.5, x1=0, c=0, zrange=[1.7,3.0] )
ax1.fill_between( z050, dm050, np.ones(len(z050))*muresidlim[1]+0.05, color=cp.darkbluegray, zorder=-100, alpha=0.3)
ax1.text( 1.53, 0.92, 't$_{\\rm vis}<$50 days', ha='left', va='top', color=cp.darkgrey )
ax1.text( 2.75, 0.92, 'undetectable', ha='right', va='top', color=cp.darkgrey )
if highz=='evolution' :
# plot SNIa evolution
minmassdict = progenitorMinMassLines( zform=11 )
z = minmassdict['z']
for key,color in zip( ['mm25','mm15','mm04'], ['r','g','b'] ):
minmass = minmassdict[key]
mavez = Mave( _MAXMASS, minmass )
ax1.plot( z, (mavez-mavez[0]) * _DMUDMASS, ls='-', color=color )
ax1.text( 2.5, -0.95, '+ lensing',fontsize=10.5, ha='center', color=colordict['hstwfc3b'] )
ax1.text( 3.0, -0.78, 'JWST', fontsize=10.5, ha='center', color=colordict['jwst'] )
color = cp.bluegray
ax1.arrow( 2.5, 0.25, 0.3, 0.0, fc=color, ec=color, head_width=0.05, head_length=0.0, overhang=0.0 )
ax1.plot( 2.5, 0.25, marker='o', mfc='w', mec=color )
ax1.text( 2.55, 0.27, '0.3 Gyr', ha='left', va='bottom', color=color)
ax1.text( 2.82, 0.25, 'z=2.8', ha='left', va='center', color=color)
color = cp.teal
ax1.arrow( 2.5, 0.45, 0.55, 0.0, fc=color, ec=color, head_width=0.05, head_length=0.08, overhang=0.25, length_includes_head=True )
ax1.plot( 2.5, 0.45, marker='o', mfc='w', mec=color )
ax1.text( 2.65, 0.47, '1 Gyr', ha='left', va='bottom', color=color)
ax1.text( 3.08, 0.45, 'z=3.8', ha='left', va='center', color=color)
color = cp.coral
ax1.arrow( 2.5, 0.65, 0.75, 0.0, fc=color, ec=color, head_width=0.05, head_length=0.08, overhang=0.25, length_includes_head=True )
ax1.plot( 2.5, 0.65, marker='o', mfc='w', mec=color )
ax1.text( 2.75, 0.67, '2 Gyr', ha='left', va='bottom', color=color)
ax1.text( 3.28, 0.65, 'z=8.3', ha='left', va='center', color=color)
ax1.text( 2.5, 0.7, 'z=2.5', ha='center', va='bottom', color='0.4' )
ax1.text( 2.5, 0.8, 'explosion', ha='center', va='bottom', color='0.3', fontsize=10.5 )
ax1.text( 2.85, 0.8, 'delay', ha='center', va='bottom', color='0.3', fontsize=10.5 )
ax1.text( 3.15, 0.8, 'formation', ha='left', va='bottom', color='0.3', fontsize=10.5 )
if ageaxis :
if highz=='rodney':
# ax1top.set_xlabel( 'age of Universe (Gyr)',fontsize='large',x=0.15,ha='left')
ageticks = np.array( [13, 9, 6, 4, 3, 2 ] )
else :
ageticks = np.array( [13, 9, 6, 4, 3 ] )
ax1top.set_xlabel( 'Age of Universe (Gyr)',fontsize='large')
ax1top.set_xlim( zlim )
ztickloctop = cosmo.zfromt( ageticks )
ax1top.xaxis.set_ticks( ztickloctop )
ax1top.xaxis.set_ticklabels( ageticks )
pl.draw()
def plotSNRtest02(datfileIa='colorColorClassify_Ia.dat',
datfileCC='colorColorClassify_CC.dat'):
""" Plot the results of a classification validation test.
:return:
"""
from matplotlib import pyplot as pl
from pytools import plotsetup
import numpy as np
from astropy.io import ascii
datIa = ascii.read(datfileIa,
format='commented_header',
header_start=-1,
data_start=0)
datCC = ascii.read(datfileCC,
format='commented_header',
header_start=-1,
data_start=0)
pIaIa = datIa['P(Ia|D)']
zIa = datIa['z']
SNRIa = datIa['S/N']
pIaCC = datCC['P(Ia|D)']
zCC = datCC['z']
SNRCC = datCC['S/N']
fig2 = plotsetup.fullpaperfig(2, figsize=[8, 3])
def purity(nTrue, nFalse, W=3):
return (float(nTrue) / (float(nTrue) + float(W * nFalse)))
def efficiency(nTrue, nTot):
return (float(nTrue) / float(nTot))
SNRlist = np.unique(SNRIa)
ncol = len(SNRlist)
icol = 0
axlist = []
for SNR in SNRlist:
icol += 1
irow = -1
iSNRIa = np.where(SNRIa == SNR)[0]
iSNRCC = np.where(SNRCC == SNR)[0]
zIaSNR = zIa[iSNRIa]
zCCSNR = zCC[iSNRCC]
for threshold in [0.5, 0.75]:
irow += 1
if icol == 1:
ax1 = pl.subplot(2, ncol, icol + irow * ncol)
ax = ax1
else:
ax = pl.subplot(2,
ncol,
icol + irow * ncol,
sharex=ax1,
sharey=ax1)
axlist.append(ax)
nIaTrue = np.count_nonzero(pIaIa[iSNRIa] > threshold)
nIaFalse = np.count_nonzero(pIaCC[iSNRCC] > threshold)
nIaTot = len(iSNRIa)
ppIa = purity(nIaTrue, nIaFalse, W=3)
pIa = purity(nIaTrue, nIaFalse, W=1)
eIa = efficiency(nIaTrue, nIaTot)
print('SNR=%i, Thresh=%.2f, Purity = %.2f, Pseudo-Purity = %.2f' %
(SNR, threshold, pIa, ppIa))
zbinmin = np.arange(1.8, 2.2, 0.05)
ppIaz, pIaz, eIaz = [], [], []
zbinmid = []
for zmin in zbinmin:
zmax = zmin + 0.05
izthisbinIa = np.where((zIaSNR >= zmin) & (zIaSNR < zmax))[0]
izthisbinCC = np.where((zCCSNR >= zmin) & (zCCSNR < zmax))[0]
if not len(izthisbinCC): continue
if not len(izthisbinIa): continue
nIaTrue = np.count_nonzero(
pIaIa[iSNRIa][izthisbinIa] > threshold)
nIaFalse = np.count_nonzero(
pIaCC[iSNRCC][izthisbinCC] > threshold)
nIaTot = len(izthisbinIa)
if nIaTrue == 0 and nIaFalse == 0: continue
ppIaz.append(purity(nIaTrue, nIaFalse, W=3))
pIaz.append(purity(nIaTrue, nIaFalse, W=1))
eIaz.append(efficiency(nIaTrue, nIaTot))
zbinmid.append(zmin + 0.025)
ax.plot(zbinmid,
ppIaz,
color='darkorange',
marker='d',
ls='--',
lw=1)
ax.plot(zbinmid, pIaz, color='darkcyan', marker='o', ls='-', lw=1)
ax.plot(zbinmid, eIaz, color='0.5', marker='^', ls=':', lw=1)
ax.set_xlim(1.75, 2.25)
ax.set_ylim(-0.1, 1.1)
if icol == 2:
pl.setp(ax.get_yticklabels(), visible=False)
if icol == 3:
ax.yaxis.set_ticks_position('right')
ax.yaxis.set_ticks_position('both')
ax.yaxis.set_label_position('right')
if irow == 0:
pl.setp(ax.get_xticklabels(), visible=False)
ax.set_title('S/N=%i' % SNR, fontsize=12, color='0.5')
#if irow==1 and icol==2 :
# ax.set_xlabel('Redshift')
#if icol==1 :
# ax.set_ylabel('Ia Sample Purity')
if icol == 2:
ax.text(0.5,
0.05,
'thresh=%0.2f' % (threshold),
ha='center',
va='bottom',
transform=ax.transAxes,
fontsize=12,
color='0.5')
if irow == 0 and icol == ncol:
ax.text(0.85,
0.05,
'true\npurity',
ha='center',
va='bottom',
color='darkcyan',
fontsize=10,
transform=ax.transAxes)
ax.text(0.5,
0.05,
'pseudo\npurity',
ha='center',
va='bottom',
color='darkorange',
fontsize=10,
transform=ax.transAxes)
ax.text(0.05,
0.05,
'efficiency',
ha='left',
va='bottom',
color='0.3',
fontsize=10,
transform=ax.transAxes)
# make a background axis frame for x and y axis labels
bgAxes = pl.axes([0.05, 0.1, 0.9, 0.85], frameon=False)
bgAxes.set_xticks([])
bgAxes.set_yticks([])
bgAxes.set_xlabel('Redshift')
bgAxes.set_ylabel('Ia Sample Purity')
pl.subplots_adjust(wspace=0,
hspace=0,
left=0.08,
bottom=0.18,
right=0.92,
top=0.9)
pl.draw()
def stonefig(simIa=None,
simIbc=None,
simII=None,
contours=True,
redshiftcircle=True,
clobber=False,
**plotargs):
from pytools import plotsetup
from mpltools import color
from matplotlib import cm
fig = plotsetup.fullpaperfig(figsize=[7.5, 3.5])
fig.clf()
ax1 = fig.add_subplot(1, 2, 1)
simIa, simIbc, simII = singlecircle(
'stone',
simIa,
simIbc,
simII,
clobber=clobber,
medbandx='f139m',
medbandy='f153m',
contours=contours,
redshiftcircle=False, #redshiftcircle,
**plotargs)
fig.subplots_adjust(left=0.10,
bottom=0.15,
right=0.92,
top=0.98,
wspace=0.0)
ax1 = pl.gca()
ax1.text(
0.05,
0.95,
'GND13Sto',
transform=ax1.transAxes,
ha='left',
va='top',
color='k',
fontsize=15,
)
ax2 = fig.add_subplot(1, 2, 2, sharex=ax1, sharey=ax1)
singlecircle('stone',
medbandx='f139m',
medbandy='f153m',
contours=False,
points=False,
redshiftcircle=True,
**plotargs)
#plot_redshift_circle(z_range=STONE.z_range, tobs=STONE.tobs,
# medbandx='f139m', medbandy='f153m',
# source='salt2', coloredaxislabels=False, marker='o' )
ax2.yaxis.set_label_position('right')
ax2.yaxis.set_ticks_position('right')
ax2.yaxis.set_ticks_position('both')
pl.setp(ax2.yaxis.get_label(), rotation=-90)
colorlist = color.colors_from_cmap(9, cm.jet)
ax2.text(0.1, -0.15, 'z=1.6', ha='left', va='top', color=colorlist[0])
ax2.text(-0.06, -0.18, '1.7', ha='left', va='top', color=colorlist[1])
ax2.text(0.26, 0.06, '1.8', ha='left', va='top', color=colorlist[2])
ax2.text(0.14, 0.0, '1.9', ha='left', va='top', color='darkcyan')
ax2.text(-0.1, -0.19, '2.0', ha='right', va='top', color='limegreen')
ax2.text(-0.09,
0.23,
'2.1',
ha='right',
va='bottom',
color='darkolivegreen')
ax2.text(0.13, 0.27, '2.2', ha='left', va='top', color=colorlist[6])
ax2.text(-0.1, -0.07, '2.3', ha='center', va='center', color=colorlist[7])
ax2.text(-0.23,
-0.14,
'z=2.4',
ha='right',
va='bottom',
color=colorlist[8])
ax1.set_xlim(-0.35, 0.35)
ax1.set_ylim(-0.3, 0.45)
pl.draw()
return simIa, simIbc, simII
def mk_histogram_figure(sndatfile='candels_sn_hostphot2.txt',
galdata=None,
galdatfilelist=[
'CANDELS.GOODSS.F160W.v1.PHOTOZ.CAT',
'CANDELS.GOODSN.F160W.v1.PHOTOZ.CAT',
'CANDELS.UDS.F160W.v1.photoz.cat',
],
insetstamps=False):
fig = plotsetup.fullpaperfig()
cwd = os.path.abspath('.')
sndata = ascii.read(sndatfile,
format='commented_header',
header_start=-1,
data_start=0)
igot160 = np.where(sndata['sb_f160w'] > 0)[0]
sb160 = sndata['sb_f160w'][igot160]
pIa = sndata['PIa'][igot160]
pl.clf()
ax = pl.axes([0.06, 0.12, 0.9, 0.6])
ax.hist(sb160,
bins=np.arange(20, 28, 0.5),
weights=pIa,
color=cp.darkred,
alpha=0.5,
normed=True)
ax.hist(sb160,
bins=np.arange(20, 28, 0.5),
weights=(1 - pIa),
color=cp.darkblue,
alpha=0.5,
normed=True)
if galdata is None:
galdatalist = [ascii.read(galdatfile) for galdatfile in galdatfilelist]
galdata = vstack(galdatalist, join_type='outer')
m160 = galdata['mag_f160w']
zphot = galdata['Photo_z']
iz12 = np.where((zphot > 1) & (zphot < 2.5))[0]
m160 = m160[iz12]
ax.hist(m160,
bins=np.arange(20, 28, 0.2),
color=cp.black,
alpha=0.3,
normed=True,
zorder=-1000)
fig.subplots_adjust(left=0.06, bottom=0.12, right=0.97, top=0.97)
ax.set_xlabel('SN Host Galaxy Surface Brightness (mag arcsec$^{-2}$)')
ax.set_ylabel('Normalized Count')
ax.set_yticks([])
ax.text(0.7,
0.92, '\\noindent Magnitude from total flux,\n'
'all galaxies with $1<z<2.5$',
transform=ax.transAxes,
ha='left',
va='top',
color=cp.darkgrey)
ax.text(0.3,
0.92, '\\noindent CANDELS SN Host galaxies,\n'
'with $1<z<2.5$',
transform=ax.transAxes,
ha='left',
va='top',
color=cp.darkgrey)
ax.text(0.15,
0.52,
'Type Ia SN',
transform=ax.transAxes,
ha='right',
va='top',
color=cp.darkred)
ax.text(0.35,
0.62,
'CC SN',
transform=ax.transAxes,
ha='left',
va='top',
color=cp.darkblue)
ax.plot([22.25, 22.75], [0.2, 0.3],
marker=' ',
ls='-',
color=cp.darkblue,
lw=1)
ax.plot([21.75, 20.75], [0.13, 0.24],
marker=' ',
ls='-',
color=cp.darkred,
lw=1)
pl.draw()
if insetstamps:
ax1 = pl.axes([0.1, 0.76, 0.18, 0.2])
show_sn_on_image('camille', 'camille_f160w_e00_reg_drz_sci.fits')
ax2 = pl.axes([0.42, 0.76, 0.18, 0.2])
show_sn_on_image('gore', 'gore_f160w_e00_reg_drz_sci.fits')
ax3 = pl.axes([0.72, 0.76, 0.18, 0.2])
show_sn_on_image('fairbanks', 'fairbanks_f160w_e00_reg_drz_sci.fits')
#ax1.set_xticks([])
#ax2.set_xticks([])
#ax3.set_xticks([])
#ax1.set_yticks([])
#ax2.set_yticks([])
#ax3.set_yticks([])
imdat = pyfits.getdata('camille/camille_f160w_e00_reg_drz_sci.fits')
h, w = imdat.shape
#ax1.imshow( imdat[h/2-15:h/2+15,w/2-15:w/2+15], vmin=-0.05, vmax=0.15,
# cmap=cm.Greys_r, aspect='equal', interpolation='nearest')
return galdata
def plot_light_curve_fit( fitter='mlcs2k2', plotmags=True,
compare=False ) :
""" make the SN Tomas light curve fit figure"""
from pytools import plotsetup, colorpalette as cp
from astropy.io import ascii
import numpy as np
from matplotlib import pyplot as pl
from matplotlib import ticker, gridspec
import os
import sys
from hstphot import hstzpt
thisfile = sys.argv[0]
if 'ipython' in thisfile :
thisfile = __file__
thisdir = os.path.abspath( os.path.dirname(thisfile))
sn = ascii.read(os.path.join(thisdir,'data/HST_FFSN_tomas.dat'),
format='commented_header', header_start=-1, data_start=0)
alpha2filter = { 'H':'F160W','N':'F140W','J':'F125W',
'Y':'F105W','I':'F814W','V':'F606W','B':'F435W' }
colordict = { 'H':'k', 'N':cp.darkred,
'J':cp.darkgold, 'Y':cp.cadetblue,
'I':cp.darkgreen, 'V':cp.coral,
'B':cp.purple}
if fitter=='both' :
plotsetup.fullpaperfig([8,4])
gs = gridspec.GridSpec( 2,5 )
rowdict = {'salt2':1,'mlcs2k2':0}
fitterlist=['mlcs2k2','salt2']
else :
plotsetup.fullpaperfig([8,4])
gs = gridspec.GridSpec(1,5)
rowdict = {fitter:0}
fitterlist = [fitter]
fig = pl.gcf()
pl.clf()
for fitter in fitterlist :
axdict = {
'B':fig.add_subplot(gs[rowdict[fitter],0]),
'Y':fig.add_subplot(gs[rowdict[fitter],1]),
'J':fig.add_subplot(gs[rowdict[fitter],2]),
'N':fig.add_subplot(gs[rowdict[fitter],3]),
'H':fig.add_subplot(gs[rowdict[fitter],4]),
}
axdict['V'] = axdict['B']
axdict['I'] = axdict['B']
for band in ['V','I','Y','J','N','H'] :
ax = axdict[band.upper()]
filtname = alpha2filter[band]
color = colordict[band]
if band=='B':
ax.text(0.85,0.45,'%s'%filtname.upper(), color=color,
fontsize='small',ha='right',va='top',
transform=ax.transAxes)
if band=='V':
ax.text(0.85,0.55,'%s'%filtname.upper(), color=color,
fontsize='small',ha='right',va='top',
transform=ax.transAxes)
if plotmags :
ifilt = np.where((sn['filter']==filtname) &
(sn['magerr']>0))[0]
y,yerr = sn['mag'][ifilt], sn['magerr'][ifilt]
else :
ifilt = np.where((sn['filter']==filtname))[0]
f,ferr = sn['flux'][ifilt], sn['fluxerr'][ifilt]
y = f*10**(-0.4*(sn['zpt'][ifilt]-25))
yerr = ferr*10**(-0.4*(sn['zpt'][ifilt]-25))
ax.errorbar( sn['mjd'][ifilt], y, yerr, color=color,
marker='D', ls=' ', zorder=-100)
# ax.errorbar( mjd[iobs], y[iobs], yerr[iobs], color=color,
# marker='D', ls=' ', zorder=-100 )
fluxfile = os.path.join(
thisdir,'data/%s_fit/HST_FFSN_tomas-1101-%s.flux'%(fitter,band) )
if not os.path.isfile(fluxfile): continue
fluxdat = ascii.read(fluxfile)
mjd = fluxdat['col2']
tobs = fluxdat['col3']
fluxcal = fluxdat['col4']
fluxcalerr = fluxdat['col5']
if filtname.lower().startswith('f1'):
zptvega = hstzpt.getzptWFC3IR(filtname,'vega')
zptab = hstzpt.getzptWFC3IR(filtname,'ab')
else :
zptvega = hstzpt.getzptACS(filtname,'vega')
zptab = hstzpt.getzptACS(filtname,'ab')
flux = fluxcal * 10**(-0.4*(27.5-zptvega))
fluxab25 = flux * 10**(-0.4*(zptab-25))
fluxerr = fluxcalerr * 10**(-0.4*(27.5-zptvega))
fluxerrab25 = fluxerr * 10**(-0.4*(zptab-25))
modkey = fluxdat['col6']
mag = np.where( fluxab25>0, -2.5*np.log10( fluxab25 ) + 25, 35 )
magerr = np.where( fluxab25>0, 1.0857 * fluxerrab25 / fluxab25, 0.2 )
if plotmags :
y,yerr = mag, magerr
else :
y,yerr = fluxab25, fluxerrab25
iobs = np.where( modkey>0 )[0]
imod = np.where( modkey==0 )[0]
ax.plot( mjd[imod], y[imod], color=color, marker=' ', ls='-', zorder=-100 )
ax.fill_between( mjd[imod], y[imod]+yerr[imod], y[imod]-yerr[imod],
color=color, alpha=0.3, zorder=-1000 )
ax.set_xlim( 56780,56950 )
ax.xaxis.set_major_locator( ticker.MultipleLocator( 100 ) )
ax.xaxis.set_minor_locator( ticker.MultipleLocator( 20 ) )
if plotmags :
ax.set_ylim( 27.9, 22.25 )
else :
ax.set_ylim( -0.2, 2.9 )
ax.yaxis.set_major_locator( ticker.MultipleLocator( 1 ) )
ax.yaxis.set_minor_locator( ticker.MultipleLocator( 0.5 ) )
ax.text(0.85,0.65,'%s'%filtname.upper(), color=color,
fontsize='small',ha='right',va='top',
transform=ax.transAxes)
if band=='H':
ax.text(0.9,0.9,'%s'%fitter.upper(), color='k',
fontsize='large',ha='right',va='top',
transform=ax.transAxes)
if rowdict[fitter]==0:
axtop = ax.twiny()
z=1.31
mjdpk=56816.3
axtop.set_xlim( (ax.get_xlim()[0]-mjdpk)/(1+z), (ax.get_xlim()[1]-mjdpk)/(1+z) )
axtop.xaxis.set_major_locator( ticker.MultipleLocator( 20 ) )
axtop.xaxis.set_minor_locator( ticker.MultipleLocator( 10 ) )
axtop.xaxis.set_label_coords( -0.03, 1.01)
axtop.tick_params( pad=2)
if band=='I':
axtop.set_xlabel( "t$_{\\rm rest}$ : ")
if ax != axdict['B']:
pl.setp( ax.get_yticklabels(),visible=False)
if plotmags :
axdict['B'].set_ylabel( r"AB mag")#, fontsize='x-large')
else :
axdict['B'].set_ylabel( r"Flux (zp$_{\rm AB}$=25)")#, fontsize='x-large')
# fig.suptitle( 'SN HFF14tom at $z=1.33\pm0.02$' )
axdict['B'].set_xlabel( "MJD : ")#, fontsize='x-large')
axdict['B'].xaxis.set_label_coords( -0.22, -0.06)
#ax.yaxis.set_major_locator( ticker.MultipleLocator( 1 ) )
#ax.yaxis.set_minor_locator( ticker.MultipleLocator( 0.5 ) )
fig.subplots_adjust( left=0.08, bottom=0.12, right=0.98, top=0.91,
hspace=0, wspace=0)
pl.draw()
def mkfig3d(
simdata,
dz=0.05,
snanadatfile=_SNANADATFILE,
):
""" Plot the results of a SNANA monte carlo simulation as a 3-D circle
diagram.
:param simdata:
:param dz:
:param snanadatfile:
:return:
"""
from mpl_toolkits.mplot3d.axes3d import Axes3D
from matplotlib import cm
import mpltools
from pytools import plotsetup
fig = plotsetup.fullpaperfig(1, [10, 10])
sn = stardust.SuperNova(snanadatfile)
simIa, simIbc, simII = simdata
ax1 = fig.add_axes([0.12, 0.12, 0.85, 0.85], projection='3d')
c7I, c8I, cPN = get_colors(simII)
ax1.plot3D(c7I,
c8I,
cPN,
marker='o',
color='k',
alpha=1,
ls=' ',
mew=0,
label='Type II')
c7I, c8I, cPN = get_colors(simIbc)
ax1.plot3D(c7I,
c8I,
cPN,
marker='o',
color='sienna',
alpha=1,
ls=' ',
mew=0,
label='Type Ibc')
zbins, c7I, c8I, cPN = get_colors_binned_by_z(sn, simIa, dz=dz)
mpltools.color.cycle_cmap(len(zbins), cmap=cm.gist_rainbow_r, ax=ax1)
for iz in range(len(zbins) - 1):
z0, z1 = zbins[iz], zbins[iz + 1]
#if dz>=0.1 : zmid = round(np.mean([z0,z1]),1)
#elif dz>=0.01 : zmid = round(np.mean([z0,z1]),2)
ax1.plot3D(c7I[iz],
c8I[iz],
cPN[iz],
marker='o',
alpha=1,
ls=' ',
mew=0,
label='%.2f-%.2f' % (z0, z1))
ax1.set_xlim(-0.1, 0.5)
ax1.set_ylim(-0.4, 0.2)
ax1.set_zlim(-0.3, 0.3)
ax1.legend(loc='upper left',
ncol=2,
numpoints=1,
frameon=False,
handletextpad=0.3,
handlelength=0.2)
ax1.set_xlabel('F763M-F814W')
ax1.set_ylabel('F845M-F140W')
ax1.set_zlabel('F139M-F140W')
def mk_bush_lc_plot(snfitres=None):
from astropy.io import ascii
import numpy as np
from scipy.interpolate import interp1d
from matplotlib import pyplot as pl, ticker
from pytools import plotsetup, colorpalette as cp
import time
start = time.time()
if snfitres is not None:
sn, fit, res = snfitres
else:
sn, fit, res = dofit(
'/Users/rodney/Dropbox/MEDBAND/DATFILES/HST_CANDELS4_bushALL.sncosmo.dat',
z=1.15,
dz=0.001,
t0=55803.1,
dt0=25.0,
model='s11-2006fo',
noUV=True)
snid = 'GSD11Bus'
ymax = 0.8
# optbands = ['f350lp','f606w','f814w','f850lp']
allbands = np.unique(sn['filter'])
broadbands = [
band for band in allbands
if band in ['f814w', 'f105w', 'f125w', 'f140w', 'f160w']
]
nax = 5
medbanddict = {
'f105w': 'f098m',
'f125w': 'f127m',
'f140w': 'f139m',
'f160w': 'f153m'
}
bands = sn['filter']
mjd = sn['mjd']
flux = sn['flux'] * 10**(-0.4 * (sn['zpt'] - 25))
fluxerr = sn['fluxerr'] * 10**(-0.4 * (sn['zpt'] - 25))
alpha2filter = {
'H': 'f160w',
'N': 'f140w',
'J': 'f125w',
'Y': 'f105w',
'Z': 'f850l',
'I': 'f814w',
'V': 'f606w',
'L': 'f098m',
'O': 'f127m',
'P': 'f139m',
'Q': 'f153m',
}
plotsetup.fullpaperfig([8, 3])
pl.clf()
fig = pl.gcf()
#mjdmin = mjd.min()-10
#mjdmax = mjd.max()+25
ymax = 0.7
ymaxMB = 0.39
mjdmin = 55701
mjdmax = 55995
mjdmod = np.arange(mjdmin, mjdmax, 1)
z, mjdpeak = 1.15, 55802.
snlabel = 'GSD11Bus'
trestmin = (mjdmin - mjdpeak) / (1 + z)
trestmax = (mjdmax - mjdpeak) / (1 + z)
ax1w = pl.subplot2grid([4, 4], [0, 0], rowspan=3)
ax2w = pl.subplot2grid([4, 4], [0, 1], rowspan=3, sharex=ax1w, sharey=ax1w)
ax3w = pl.subplot2grid([4, 4], [0, 2], rowspan=3, sharex=ax1w, sharey=ax1w)
ax4w = pl.subplot2grid([4, 4], [0, 3], rowspan=3, sharex=ax1w, sharey=ax1w)
#ax5w = pl.subplot2grid( [4,5], [0,4], rowspan=3, sharex=ax1w, sharey=ax1w )
ax1m = pl.subplot2grid([4, 4], [3, 0], sharex=ax1w)
ax2m = pl.subplot2grid([4, 4], [3, 1], sharex=ax1w, sharey=ax1m)
ax3m = pl.subplot2grid([4, 4], [3, 2], sharex=ax1w, sharey=ax1m)
ax4m = pl.subplot2grid([4, 4], [3, 3], sharex=ax1w, sharey=ax1m)
#ax5m = pl.subplot2grid( [4,5], [3,4], sharex=ax1w, sharey=ax1m )
iax = 0
for bb, mb in zip(['f105w', 'f125w', 'f140w', 'f160w'],
['f098m', 'f127m', 'f139m', 'f153m']):
iax += 1
ibb = np.where(bands == bb)
imb = np.where(bands == mb)
yval = flux
yerr = fluxerr
ymod_bb = fit.bandflux(bb, mjdmod, zp=25, zpsys='ab')
if iax == 1:
axw = ax1w
axm = ax1m
axw.text(0.05,
0.92,
snlabel,
color='k',
fontsize='large',
fontweight='heavy',
ha='left',
va='top',
transform=axw.transAxes)
# axw.text( -0.28, 1.2, snlabel, backgroundcolor='w', color='k', fontsize='large', fontweight='heavy', ha='left',va='top', transform=axw.transAxes, zorder=1000 )
axw.set_ylabel('flux (zp$_{AB}$=25)')
axm.set_ylabel('$\Delta$f$_{25}$')
elif iax == 2:
axw = ax2w
axm = ax2m
elif iax == 3:
axw = ax3w
axm = ax3m
elif iax == 4:
axw = ax4w
axm = ax4m
axw.yaxis.set_ticks_position('right')
axw.yaxis.set_ticks_position('both')
axm.yaxis.set_ticks_position('right')
axm.yaxis.set_ticks_position('both')
axtop = axw.twiny()
axtop.set_xlim(trestmin, trestmax)
if iax in [2, 3]:
pl.setp(axw.get_yticklabels(), visible=False)
pl.setp(axm.get_yticklabels(), visible=False)
if iax == 2:
axtop.set_xlabel('rest frame time (days from peak)')
axm.set_xlabel('observer frame time (MJD)')
pl.setp(axw.get_xticklabels(), visible=False)
axw.text(0.95,
0.92,
bb.upper(),
ha='right',
va='top',
color='k',
transform=axw.transAxes)
color = 'k'
axw.plot(mjdmod, ymod_bb, marker=None, color='0.5', ls='-', zorder=-10)
axw.errorbar(mjd[ibb],
yval[ibb],
yerr[ibb],
ms=8,
marker='o',
color=color,
mfc=color,
mec=color,
capsize=0,
ls=' ',
zorder=10)
if not mb: continue
axm.text(0.95,
0.5,
mb.upper(),
ha='right',
va='center',
backgroundcolor='w',
color=color,
transform=axm.transAxes)
mbfluxdiff = yval[imb] - fit.bandflux(mb, mjd[imb], zp=25, zpsys='ab')
axm.errorbar(mjd[imb],
mbfluxdiff,
fluxerr[imb],
color='k',
marker='o',
mfc='w',
ls=' ')
# axm.fill_between( mjdmod, fluxerr[imodmb], -fluxerr[imodmb],
# color=color, alpha=0.3, zorder=-1000 )
axm.axhline(0, color='k', lw=0.8, ls='--')
ax1w.set_xlim(mjdmin, mjdmax)
ax1w.set_ylim(-0.08, ymax)
ax1m.set_ylim(-ymaxMB, ymaxMB)
ax1w.xaxis.set_major_locator(ticker.MultipleLocator(100))
ax1w.xaxis.set_minor_locator(ticker.MultipleLocator(25))
ax1w.yaxis.set_major_locator(ticker.MultipleLocator(0.2))
ax1w.yaxis.set_minor_locator(ticker.MultipleLocator(0.1))
ax1m.xaxis.set_major_locator(ticker.MultipleLocator(100))
ax1m.xaxis.set_minor_locator(ticker.MultipleLocator(25))
ax1m.yaxis.set_major_locator(ticker.MultipleLocator(0.2))
ax1m.yaxis.set_minor_locator(ticker.MultipleLocator(0.1))
fig.subplots_adjust(left=0.1,
bottom=0.18,
right=0.95,
top=0.82,
wspace=0.,
hspace=0)
pl.draw()
def lcplot(snid='colfax', yunits='flux', snfitres=None):
from matplotlib import pyplot as pl, ticker
from pytools import plotsetup, colorpalette as cp
import time
start = time.time()
if snfitres is not None:
sn, fit, res = snfitres
else:
sn, fit, res = dofitIa(snid)
if snid == 'bush':
snid = 'GSD11Bus'
ymax = 0.8
labelcorner = 'upper right'
elif snid == 'colfax':
snid = 'GND12Col'
ymax = 0.7
labelcorner = 'upper right'
elif snid == 'stone':
snid = 'GND13Sto'
ymax = 1.2
labelcorner = 'upper right'
else:
ymax = 1.2
labelcorner = 'upper right'
# optbands = ['f350lp','f606w','f814w','f850lp']
allbands = np.unique(sn['filter'])
broadbands = [
band for band in allbands
if band in ['f105w', 'f125w', 'f140w', 'f160w']
]
nax = len(broadbands)
medbanddict = {
'f105w': 'f098m',
'f125w': 'f127m',
'f140w': 'f139m',
'f160w': 'f153m'
}
bands = sn['filter']
markers = ['^', 'o', 's', 'd']
colors = [cp.purple, cp.bluegray, cp.darkgreen, cp.red]
mjd = sn['mjd']
mag = sn['mag']
magerr = sn['magerr']
flux = sn['flux'] * 10**(-0.4 * (sn['zpt'] - 25))
fluxerr = sn['fluxerr'] * 10**(-0.4 * (sn['zpt'] - 25))
plotsetup.fullpaperfig(2, [8, 3])
pl.clf()
fig = pl.gcf()
mjdmin = mjd.min() - 10
mjdmax = mjd.max() + 25
mjdmod = np.arange(mjdmin, mjdmax, 1)
z = res['parameters'][res['param_names'].index('z')]
mjdpeak = res['parameters'][res['param_names'].index('t0')]
trestmin = (mjdmin - mjdpeak) / (1 + z)
trestmax = (mjdmax - mjdpeak) / (1 + z)
iax = 0
for bb, marker, color in zip(broadbands, markers, colors):
t1 = time.time()
iax += 1
ibb = np.where(bands == bb)
mb = medbanddict[bb]
imb = np.where(bands == mb)
if iax == 1:
ax = fig.add_subplot(1, nax, iax)
ax1 = ax
axtop = ax.twiny()
ax1.text(-0.3,
1.22,
snid,
color='k',
fontsize='large',
fontweight='heavy',
ha='left',
va='top',
transform=ax.transAxes)
elif iax == 2:
ax = fig.add_subplot(1, nax, iax, sharex=ax1, sharey=ax1)
axtop = ax.twiny()
axtop.set_xlabel('rest frame time (days from peak)')
ax.set_xlabel('observer frame time (MJD)')
pl.setp(ax.get_yticklabels(), visible=False)
elif iax == nax:
ax = fig.add_subplot(1, nax, iax, sharex=ax1, sharey=ax1)
axtop = ax.twiny()
ax.yaxis.set_ticks_position('right')
ax.yaxis.set_ticks_position('both')
else:
ax = fig.add_subplot(1, nax, iax, sharex=ax1, sharey=ax1)
axtop = ax.twiny()
pl.setp(ax.get_yticklabels(), visible=False)
if yunits == 'mag':
yval = mag
yerr = magerr
ymod_bb = fit.bandmag(bb, 'ab', mjdmod)
ymod_mb = fit.bandmag(mb, 'ab', mjdmod)
if iax == 1:
ax.set_ylabel('AB mag')
# ax.set_ylim( 30.6, 25.2 )
else:
yval = flux
yerr = fluxerr
ymod_bb = fit.bandflux(bb, mjdmod, zp=25, zpsys='ab')
ymod_mb = fit.bandflux(mb, mjdmod, zp=25, zpsys='ab')
if iax == 1:
ax.set_ylabel('flux (zp$_{AB}$=25)')
ax.set_ylim(-0.09, ymax)
ax.plot(mjdmod, ymod_bb, marker=None, color='0.5', ls='-', zorder=-10)
ax.errorbar(mjd[ibb],
yval[ibb],
yerr[ibb],
ms=8,
marker='o',
color=color,
mfc=color,
mec=color,
capsize=0,
ls=' ',
zorder=10)
if mb in allbands:
ax.plot(mjdmod,
ymod_mb,
marker=None,
color='0.5',
ls='--',
zorder=-10)
ax.errorbar(mjd[imb],
yval[imb],
yerr[imb],
ms=9,
marker='o',
color='k',
mfc='w',
mec='k',
capsize=0,
ls=' ',
alpha=0.5,
zorder=20)
if labelcorner == 'lower right':
ax.text(0.92,
0.42,
'%s' % (bb.upper()),
color=color,
fontsize='medium',
fontweight='heavy',
ha='right',
va='top',
transform=ax.transAxes)
if mb in allbands:
ax.text(0.92,
0.32,
'%s' % (mb.upper()),
color='k',
fontsize='medium',
fontweight='heavy',
ha='right',
va='top',
transform=ax.transAxes)
elif labelcorner == 'upper left':
ax.text(0.08,
0.92,
'%s' % (bb.upper()),
color=color,
fontsize='medium',
fontweight='heavy',
ha='left',
va='top',
transform=ax.transAxes)
if mb in allbands:
ax.text(0.08,
0.82,
'%s' % (mb.upper()),
color='k',
fontsize='medium',
fontweight='heavy',
ha='left',
va='top',
transform=ax.transAxes)
if labelcorner == 'upper right':
ax.text(0.92,
0.92,
'%s' % (bb.upper()),
color=color,
fontsize='medium',
fontweight='heavy',
ha='right',
va='top',
transform=ax.transAxes)
if mb in allbands:
ax.text(0.92,
0.82,
'%s' % (mb.upper()),
color='k',
fontsize='medium',
fontweight='heavy',
ha='right',
va='top',
transform=ax.transAxes)
ax.set_xlim(mjdmin, mjdmax)
axtop.set_xlim(trestmin, trestmax)
ax.xaxis.set_major_locator(ticker.MultipleLocator(100))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(20))
axtop.xaxis.set_major_locator(ticker.MultipleLocator(20))
axtop.xaxis.set_minor_locator(ticker.MultipleLocator(5))
ax.yaxis.set_major_locator(ticker.MultipleLocator(0.2))
ax.yaxis.set_minor_locator(ticker.MultipleLocator(0.1))
for tick in axtop.get_xaxis().get_major_ticks():
tick.set_pad(5.)
tick.label1 = tick._get_text1()
t2 = time.time()
print("%s %.1f %.1f " % (bb.upper(), t2 - start, t2 - t1))
fig.subplots_adjust(left=0.1,
bottom=0.18,
right=0.95,
top=0.82,
wspace=0.,
hspace=0.15)
pl.draw()
t3 = time.time()
print("All %.1f" % (t3 - start))
def mkExtinctionDemoFig():
""" Make a demo figure that shows how the pseudo-colors
do not change much even under extreme host galaxy extinction
:return:
"""
from matplotlib import pyplot as pl
from matplotlib import ticker
from pytools import plotsetup
plotsetup.fullpaperfig(figsize=[8, 4])
pl.clf()
ax1 = pl.subplot(3, 2, 1)
mksedplot(z=2.0, Av=0.0, color='darkblue')
ax2 = pl.subplot(3, 2, 3, sharex=ax1, sharey=ax1)
mksedplot(z=2.0, Av=1.0, color='green')
ax3 = pl.subplot(3, 2, 5, sharex=ax1, sharey=ax1)
mksedplot(z=2.0, Av=2.0, color='darkred')
pl.setp(ax1.get_xticklabels(), visible=False)
pl.setp(ax2.get_xticklabels(), visible=False)
ax3.set_xlim(1.12, 1.69)
ax3.set_ylim(0.0, 0.7)
ax3.set_yticklabels([])
#ax3.set_xticks([1.1,1.3,1.5,1.7])
ax3.set_xlabel('wavelength ($\mu$m)')
ax2.set_ylabel('SN Flux or Filter Transmission\n (arbitrary units)')
ax1.text(1.27,
0.6,
'F127M',
color='darkmagenta',
fontsize=9,
ha='center',
va='center')
ax1.text(1.39,
0.6,
'F139M',
color='teal',
fontsize=9,
ha='center',
va='center')
ax1.text(1.53,
0.6,
'F153M',
color='darkorange',
fontsize=9,
ha='center',
va='center')
ax1.text(0.95,
0.45,
'A$_V$=0.0',
color='darkblue',
transform=ax1.transAxes,
ha='right',
va='top')
ax2.text(0.95,
0.65,
'A$_V$=1.0',
color='green',
transform=ax2.transAxes,
ha='right',
va='top')
ax3.text(0.95,
0.75,
'A$_V$=2.0',
color='darkred',
transform=ax3.transAxes,
ha='right',
va='top')
ax4 = pl.subplot(2, 2, 2)
mkcirclepoints(colorselect=[1, 0],
source='hsiao',
marker='o',
ls=' ',
mew=0)
pl.setp(ax4.get_xticklabels(), visible=False)
ax4.yaxis.set_ticks_position('right')
ax4.yaxis.set_ticks_position('both')
ax4.yaxis.set_label_position('right')
ax5 = pl.subplot(2, 2, 4, sharex=ax4)
mkcirclepoints(colorselect=[1, 2],
source='hsiao',
marker='o',
ls=' ',
mew=0)
ax5.yaxis.set_ticks_position('right')
ax5.yaxis.set_ticks_position('both')
ax5.yaxis.set_label_position('right')
ax5.set_xlim(-0.2, 0.25)
ax4.set_ylim(-0.39, 0.19)
ax5.set_ylim(-0.15, 0.29)
pl.setp(ax5.yaxis.get_label(), rotation=-90)
pl.setp(ax4.yaxis.get_label(), rotation=-90)
ax4.yaxis.labelpad = 20
ax5.yaxis.labelpad = 20
ax1.xaxis.set_major_locator(ticker.MultipleLocator(0.1))
ax1.xaxis.set_minor_locator(ticker.MultipleLocator(0.05))
ax5.xaxis.set_major_locator(ticker.MultipleLocator(0.1))
ax5.xaxis.set_minor_locator(ticker.MultipleLocator(0.05))
ax4.yaxis.set_major_locator(ticker.MultipleLocator(0.1))
ax4.yaxis.set_minor_locator(ticker.MultipleLocator(0.05))
ax5.yaxis.set_major_locator(ticker.MultipleLocator(0.1))
ax5.yaxis.set_minor_locator(ticker.MultipleLocator(0.05))
fig = pl.gcf()
fig.subplots_adjust(left=0.08,
right=0.88,
bottom=0.15,
top=0.97,
hspace=0,
wspace=0.08)
def mkExtinctionDemoFigSmall(z=2.0):
""" make a set of plots showing the SN Ia SED (Hsiao template)
at three extinction values, with bandpasses overlaid.
:return:
"""
import numpy as np
import sncosmo
# from sncosmost import hstbandpasses, ccsnmodels
from matplotlib import rc
rc('text', usetex=True)
rc('text.latex', preamble='\usepackage[usenames]{xcolor}')
from matplotlib import pyplot as pl
from matplotlib import ticker
from pytools import plotsetup
from scipy import interpolate as scint
fig = plotsetup.fullpaperfig(1, [8, 3])
# load the O'Donnell 1994 dust model
dust = sncosmo.OD94Dust()
snIa = sncosmo.Model(source='hsiao',
effects=[dust],
effect_names=['host'],
effect_frames=['rest'])
ax1 = pl.gca()
f127m = sncosmo.get_bandpass('f127m')
f139m = sncosmo.get_bandpass('f139m')
f153m = sncosmo.get_bandpass('f153m')
f125w = sncosmo.get_bandpass('f125w')
f140w = sncosmo.get_bandpass('f140w')
f160w = sncosmo.get_bandpass('f160w')
wf127m = f127m.wave / 10000.
wf139m = f139m.wave / 10000.
wf153m = f153m.wave / 10000.
wf125w = f125w.wave / 10000.
wf140w = f140w.wave / 10000.
wf160w = f160w.wave / 10000.
# ax2 = ax1.twinx()
ax2 = ax1
ax2.plot(wf127m, f127m.trans, color='darkmagenta', ls='-', lw=2)
ax2.plot(wf153m, f153m.trans, color='darkorange', ls='-', lw=2)
ax2.plot(wf125w, f125w.trans, color='darkmagenta', ls='--', lw=2)
ax2.plot(wf160w, f160w.trans, color='darkorange', ls='--', lw=2)
intf127m = scint.interp1d(wf127m,
f127m.trans,
bounds_error=False,
fill_value=0)
intf153m = scint.interp1d(wf153m,
f153m.trans,
bounds_error=False,
fill_value=0)
colorlist1, colorlist2 = [], []
for Av, ls, alpha in zip([2, 1, 0], [':', '--', '-'], [0.1, 0.3, 0.5]):
snIa.set(z=z, t0=0, hostr_v=3.1, hostebv=Av / 3.1)
colorlist1.append(
snIa.bandmag('f127m', 'ab', 0) - snIa.bandmag('f125w', 'ab', 0))
colorlist2.append(
snIa.bandmag('f153m', 'ab', 0) - snIa.bandmag('f160w', 'ab', 0))
snwave = np.arange(6000., 20000., 10.)
snflux = snIa.flux(0, snwave)
snwave = snwave / 10000.
snflux = 0.12 * snflux / snflux[400]
ax1.plot(snwave, snflux, color='k', ls=ls, lw=1, label='%.1f' % Av)
overlap127 = np.min([snflux, intf127m(snwave)], axis=0)
ax2.fill_between(snwave,
np.zeros(len(snwave)),
overlap127,
color='darkmagenta',
alpha=alpha)
overlap153 = np.min([snflux, intf153m(snwave)], axis=0)
pl.fill_between(snwave,
np.zeros(len(snwave)),
overlap153,
color='darkorange',
alpha=alpha)
ax1.legend(loc='upper left',
bbox_to_anchor=(0.0, 0.9),
frameon=False,
fontsize=11)
ax1.text(0.08,
0.88,
'A$_V$',
transform=ax1.transAxes,
ha='left',
va='bottom',
fontsize=11)
ax1.text(0.13,
0.88,
'$\Delta$m$_{127}$',
color='darkmagenta',
transform=ax1.transAxes,
ha='left',
va='bottom',
fontsize=11)
ax1.text(0.23,
0.88,
'$\Delta$m$_{153}$',
color='darkorange',
transform=ax1.transAxes,
ha='left',
va='bottom',
fontsize=11)
ax1.text(0.14,
0.78,
'%.3f' % colorlist1[0],
color='darkmagenta',
transform=ax1.transAxes,
ha='left',
va='bottom',
fontsize=11)
ax1.text(0.23,
0.78,
'%.3f' % colorlist2[0],
color='darkorange',
transform=ax1.transAxes,
ha='left',
va='bottom',
fontsize=11)
ax1.text(0.14,
0.68,
'%.3f' % colorlist1[1],
color='darkmagenta',
transform=ax1.transAxes,
ha='left',
va='bottom',
fontsize=11)
ax1.text(0.23,
0.68,
'%.3f' % colorlist2[1],
color='darkorange',
transform=ax1.transAxes,
ha='left',
va='bottom',
fontsize=11)
ax1.text(0.14,
0.58,
'%.3f' % colorlist1[2],
color='darkmagenta',
transform=ax1.transAxes,
ha='left',
va='bottom',
fontsize=11)
ax1.text(0.23,
0.58,
'%.3f' % colorlist2[2],
color='darkorange',
transform=ax1.transAxes,
ha='left',
va='bottom',
fontsize=11)
# title=+
# '\\textcolor{DarlMagenta}{W}' +
# '\\textcolor{F153M-F160W')#, handlelength=0.5, numpoints=3)
# ax1.text( 0.15,0.95,,ha='left',va='bottom')
ax1.yaxis.set_major_locator(ticker.MultipleLocator(0.1))
ax1.yaxis.set_minor_locator(ticker.MultipleLocator(0.05))
ax1.xaxis.set_major_locator(ticker.MultipleLocator(0.2))
ax1.xaxis.set_minor_locator(ticker.MultipleLocator(0.1))
ax1.set_xlabel('wavelength ($\mu$m)')
ax1.set_ylabel('SN Flux or Filter Transmission\n (arbitrary units)')
ax1.set_xlim(0.6, 2.0)
ax1.set_ylim(0.0, 0.7)
ax1.set_yticklabels([])
ax1.text(1.27,
0.6,
'F127M,F125W',
color='darkmagenta',
fontsize=9,
ha='center',
va='center')
ax1.text(1.53,
0.6,
'F153M,F160W',
color='darkorange',
fontsize=9,
ha='center',
va='center')
fig.subplots_adjust(left=0.12, right=0.95, bottom=0.18, top=0.92)
def sncosmo_circlefig( simIa=None, simCC=None,
simIapkl='stone_SncosmoSim_Ia.pkl',
simCCpkl='stone_SncosmoSim_CC.pkl',
z_range=[1.6,2.0], nsim=1000,
verbose=True, clobber=False ):
""" Construct a color-color circle figure for SN Colfax, with observed
photometry included.
:param simIa:
:param simCC:
:param simIapkl:
:param simCCpkl:
:param z_range:
:param nsim:
:param verbose:
:param clobber:
:return:
"""
import medband_classtest
import os
import cPickle
from matplotlib import pyplot as pl
# from matplotlib import patheffects as pe
import numpy as np
from pytools import plotsetup
fig = plotsetup.fullpaperfig( 1, figsize=[8,4])
pl.ioff()
mjdpk = 56482.
mjdmedband = 56475.
t0_range = [ mjdmedband-mjdpk-3,mjdmedband-mjdpk+3 ]
t0 = mjdmedband-mjdpk
if simIa is not None :
pass
elif os.path.isfile( simIapkl ) and not clobber>1 :
if verbose: print("Loading Ia simulation from pickle : %s"%simIapkl)
fin = open( simIapkl, 'rb' )
simIa = cPickle.load( fin )
fin.close()
else :
if verbose: print("Running a new Ia simulation, then saving to pickle : %s"%simIapkl)
simIa = medband_classtest.SncosmoSim( 'Ia' , z_range=z_range, t0_range=t0_range, nsim=nsim )
fout = open( simIapkl, 'wb' )
cPickle.dump( simIa, fout, protocol=-1 )
fout.close()
if simCC is not None :
pass
elif os.path.isfile( simCCpkl ) and not clobber>1 :
if verbose: print("Loading CC simulation from pickle : %s"%simCCpkl)
fin = open( simCCpkl, 'rb' )
simCC = cPickle.load(fin)
fin.close()
else :
if verbose: print("Running a new CC simulation, then saving to pickle : %s"%simCCpkl)
simCC = medband_classtest.SncosmoSim( 'CC' , z_range=z_range, t0_range=t0_range, nsim=nsim )
fout = open( simCCpkl, 'wb' )
cPickle.dump( simCC, fout, protocol=-1 )
fout.close()
import getredshift
plotcontours( simIa, simCC, plotstyle='points' )
fig = pl.gcf()
ax1 = fig.add_subplot(1,2,1)
mkcirclepoints(zrange=z_range, t0=t0, colorselect=[1,0], coloredaxislabels=False, marker='o' )
ax2 = fig.add_subplot(1,2,2, sharex=ax1)
mkcirclepoints(zrange=z_range, t0=t0, colorselect=[1,2], coloredaxislabels=False, marker='o' )
magerr = { # from drop method
'f139m':0.182164 ,
'f140w':0.0920638,
'f153m':0.185014 ,
'f160w':0.0731440,
}
mag = { # from idl5 psf fitting
'f139m':25.4198,
'f140w':25.3622,
'f153m':25.5056,
'f160w':25.2278,
}
f25 = {}
ferr25 = {}
for k in mag.keys() :
f25[k] = 10**(-0.4*(mag[k]-25.))
ferr25[k] = magerr[k] * f25[k] / 2.5*np.log10(np.e)
deltamag = {
'f139m':mag['f139m']-mag['f140w'],
'f153m':mag['f153m']-mag['f160w'],
}
deltamagerr = {
'f139m':np.sqrt(magerr['f139m']**2+magerr['f140w']**2),
'f153m':np.sqrt(magerr['f153m']**2+magerr['f160w']**2),
}
# ax1.errorbar( deltamag['f139m'], deltamag['f127m'],
# deltamagerr['f127m'], deltamagerr['f139m'],
# marker='D', ms=10, elinewidth=2, capsize=0, color='darkorange' )
ax2.errorbar( deltamag['f139m'], deltamag['f153m'],
deltamagerr['f153m'], deltamagerr['f139m'],
marker='D', ms=10, elinewidth=2, capsize=0, color='darkorange' )
ax1.set_xlim( -0.35, 0.3 )
ax1.set_ylim( -0.7, 0.22 )
ax2.set_ylim( -0.4, 0.3 )
ax2.text( deltamag['f139m']+0.05, deltamag['f153m']-0.05, 'GND13Sto' ,
ha='left',va='top', color='darkorange',fontsize=15,)
# path_effects=[pe.withStroke( linewidth=3,foreground='k')] )
# pl.legend( loc='upper right', numpoints=2, handlelength=0.3)
pl.draw()
pl.ion()
return( simIa, simCC )
def mk_histogram_figure(sndatfile='candels_sn_hostphot2.txt',
galdata=None,
galdatfilelist=['CANDELS.GOODSS.F160W.v1.PHOTOZ.CAT',
'CANDELS.GOODSN.F160W.v1.PHOTOZ.CAT',
'CANDELS.UDS.F160W.v1.photoz.cat',
],
insetstamps=False):
fig = plotsetup.fullpaperfig()
cwd = os.path.abspath('.')
sndata = ascii.read(sndatfile, format='commented_header',
header_start=-1, data_start=0)
igot160 = np.where(sndata['sb_f160w']>0)[0]
sb160 = sndata['sb_f160w'][igot160]
pIa = sndata['PIa'][igot160]
pl.clf()
ax = pl.axes([0.06,0.12,0.9,0.6])
ax.hist( sb160, bins=np.arange(20,28,0.5), weights=pIa,
color=cp.darkred, alpha=0.5, normed=True )
ax.hist( sb160, bins=np.arange(20,28,0.5), weights=(1-pIa),
color=cp.darkblue, alpha=0.5, normed=True )
if galdata is None:
galdatalist = [ascii.read(galdatfile) for galdatfile in galdatfilelist]
galdata = vstack(galdatalist, join_type='outer')
m160 = galdata['mag_f160w']
zphot = galdata['Photo_z']
iz12 = np.where((zphot>1) & (zphot<2.5) )[0]
m160 = m160[iz12]
ax.hist( m160, bins=np.arange(20,28,0.2), color=cp.black,
alpha=0.3, normed=True, zorder=-1000 )
fig.subplots_adjust(left=0.06, bottom=0.12, right=0.97, top=0.97)
ax.set_xlabel('SN Host Galaxy Surface Brightness (mag arcsec$^{-2}$)')
ax.set_ylabel('Normalized Count')
ax.set_yticks([])
ax.text(0.7, 0.92, '\\noindent Magnitude from total flux,\n'
'all galaxies with $1<z<2.5$',
transform=ax.transAxes, ha='left', va='top', color=cp.darkgrey)
ax.text(0.3, 0.92, '\\noindent CANDELS SN Host galaxies,\n'
'with $1<z<2.5$',
transform=ax.transAxes, ha='left', va='top', color=cp.darkgrey)
ax.text(0.15, 0.52, 'Type Ia SN',
transform=ax.transAxes, ha='right', va='top', color=cp.darkred)
ax.text(0.35, 0.62, 'CC SN',
transform=ax.transAxes, ha='left', va='top', color=cp.darkblue)
ax.plot([22.25, 22.75], [0.2, 0.3], marker=' ', ls='-', color=cp.darkblue,
lw=1)
ax.plot([21.75, 20.75], [0.13, 0.24], marker=' ', ls='-', color=cp.darkred,
lw=1)
pl.draw()
if insetstamps:
ax1 = pl.axes([0.1,0.76,0.18,0.2])
show_sn_on_image('camille','camille_f160w_e00_reg_drz_sci.fits')
ax2 = pl.axes([0.42,0.76,0.18,0.2])
show_sn_on_image('gore','gore_f160w_e00_reg_drz_sci.fits')
ax3 = pl.axes([0.72,0.76,0.18,0.2])
show_sn_on_image('fairbanks','fairbanks_f160w_e00_reg_drz_sci.fits')
#ax1.set_xticks([])
#ax2.set_xticks([])
#ax3.set_xticks([])
#ax1.set_yticks([])
#ax2.set_yticks([])
#ax3.set_yticks([])
imdat = pyfits.getdata('camille/camille_f160w_e00_reg_drz_sci.fits')
h,w = imdat.shape
#ax1.imshow( imdat[h/2-15:h/2+15,w/2-15:w/2+15], vmin=-0.05, vmax=0.15,
# cmap=cm.Greys_r, aspect='equal', interpolation='nearest')
return galdata
def plotSNRtest01(datfileIa='colorColorClassify_Ia.dat',
datfileCC='colorColorClassify_CC.dat'):
""" Plot the results of a classification validation test.
:return:
"""
from matplotlib import pyplot as pl
from pytools import plotsetup
import numpy as np
from astropy.io import ascii
datIa = ascii.read(datfileIa,
format='commented_header',
header_start=-1,
data_start=0)
datCC = ascii.read(datfileCC,
format='commented_header',
header_start=-1,
data_start=0)
pIaIa = datIa['P(Ia|D)']
zIa = datIa['z']
SNRIa = datIa['S/N']
pIaCC = datCC['P(Ia|D)']
zCC = datCC['z']
SNRCC = datCC['S/N']
fig1 = plotsetup.fullpaperfig(figsize=[8, 3])
SNRlist = np.unique(SNRIa)
ncol = len(SNRlist)
icol = 0
axlist = []
for SNR in SNRlist:
icol += 1
if icol == 1:
ax1 = pl.subplot(1, ncol, icol)
ax = ax1
else:
ax = pl.subplot(1, ncol, icol, sharex=ax1, sharey=ax1)
axlist.append(ax)
out1 = ax.hist(pIaIa[np.where(SNRIa == SNR)[0]],
bins=np.arange(0, 1.01, 0.05),
color='darkmagenta',
alpha=0.3)
out2 = ax.hist(pIaCC[np.where(SNRCC == SNR)[0]],
bins=np.arange(0, 1.01, 0.05),
color='teal',
alpha=0.3)
ax1.set_xlim(0.0, 1.05)
ax1.set_xticks([0.2, 0.4, 0.6, 0.8, 1.0])
ax1 = axlist[0]
imid = int(round(len(axlist) / 2))
ax2 = axlist[imid]
ax3 = axlist[-1]
ax2.set_xlabel('P(Ia$|$D)')
ax1.set_ylabel('Number of Test SN')
pl.setp(ax2.get_yticklabels(), visible=False)
pl.setp(ax2.get_ylabel(), visible=False)
ax3.yaxis.set_ticks_position('right')
ax3.yaxis.set_ticks_position('both')
ax3.yaxis.set_label_position('right')
ax1.set_title('S/N=%i' % SNRlist[0], color='0.3')
ax2.set_title('S/N=%i' % SNRlist[imid], color='0.3')
ax3.set_title('S/N=%i' % SNRlist[-1], color='0.3')
ax3.text(0.1,
0.95,
'CCSN\nTest\nSet',
color='teal',
ha='left',
va='top',
transform=ax3.transAxes)
ax3.text(0.88,
0.95,
'SN Ia\nTest\nSet',
color='darkmagenta',
ha='right',
va='top',
transform=ax3.transAxes)
pl.subplots_adjust(wspace=0,
hspace=0,
left=0.09,
bottom=0.18,
right=0.92,
top=0.9)
pl.draw()
def plot_light_curve_fit_from_SNANA( snid='colfax', plotmags=False ) :
""" make a plot showing the light curve fit, extracted from a SNANA
output .TEXT file generated by D.Scolnic"""
from pytools import plotsetup, colorpalette as cp
from astropy.io import ascii
import numpy as np
from matplotlib import pyplot as pl
from scipy.interpolate import interp1d
from matplotlib import ticker
import os
import sys
from hstphot import hstzpt
alpha2filter = { 'H':'f160w','N':'f140w','J':'f125w','Y':'f105w',
'Z':'f850l','I':'f814w','V':'f606w',
'L':'f098m','O':'f127m','P':'f139m','Q':'f153m',
}
colordict = { 'H':'k', 'J':cp.darkgold, 'Y':cp.cadetblue,
'N':cp.darkgreen, 'V':cp.coral }
fluxdat = ascii.read( 'CANDELs-%s.LCPLOT.TEXT'%snid )
name = fluxdat['col1']
mjd = fluxdat['col2']
tobs = fluxdat['col3']
fluxcal = fluxdat['col4']
fluxcalerr = fluxdat['col5']
obsflag = fluxdat['col6']
bandletter = fluxdat['col7']
flux = fluxcal * 0.1
fluxerr = fluxcalerr * 0.1
# mag = np.where( flux>0, -2.5*np.log10( flux ) + 25, 35 )
# magerr = np.where( flux>0, 1.0857 * fluxerr / flux, 0.2 )
# medbanddict = {'f105w':'f098m','f125w':'f127m', 'f140w':'f139m', 'f160w':'f153m'}
colors = [cp.purple, cp.bluegray,cp.darkgreen,cp.red]
plotsetup.fullpaperfig( [8,3] )
pl.clf()
fig = pl.gcf()
mjdmin = mjd.min()-10
mjdmax = mjd.max()+25
mjdmod = np.arange( mjdmin, mjdmax, 1 )
if snid=='colfax' :
ymax=0.7
ymaxMB=0.3
mjdmin= 56025
mjdmax = 56220
z, mjdpeak = 2.1, 56080.
snlabel='GND12Col'
elif snid=='stone' :
ymax=1.2
ymaxMB=0.35
mjdmin= 56430
mjdmax = 56600
z,mjdpeak = 1.8, 56485.
snlabel='GND13Sto'
trestmin = (mjdmin - mjdpeak)/(1+z)
trestmax = (mjdmax - mjdpeak)/(1+z)
ax1w = pl.subplot2grid( [4,3], [0,0], rowspan=3 )
ax2w = pl.subplot2grid( [4,3], [0,1], rowspan=3, sharex=ax1w, sharey=ax1w )
ax3w = pl.subplot2grid( [4,3], [0,2], rowspan=3, sharex=ax1w, sharey=ax1w )
ax1m = pl.subplot2grid( [4,3], [3,0], sharex=ax1w )
ax2m = pl.subplot2grid( [4,3], [3,1], sharex=ax1w, sharey=ax1m )
ax3m = pl.subplot2grid( [4,3], [3,2], sharex=ax1w, sharey=ax1m )
iax = 0
for bbl, mbl, color in zip( ['Y','J','N','H'], ['L','O','P','Q'], colors ) :
if bbl not in bandletter : continue
iax += 1
filternamew = alpha2filter[ bbl ].upper()
filternamem = alpha2filter[ mbl ].upper()
if iax==1 :
axw = ax1w
axm = ax1m
axw.text( 0.05, 0.92, snlabel, color='k', fontsize='large', fontweight='heavy', ha='left',va='top', transform=axw.transAxes )
# axw.text( -0.28, 1.2, snlabel, backgroundcolor='w', color='k', fontsize='large', fontweight='heavy', ha='left',va='top', transform=axw.transAxes, zorder=1000 )
axw.set_ylabel( 'flux (zp$_{AB}$=25)' )
axm.set_ylabel( '$\Delta$f$_{25}$' )
elif iax==2 :
axw = ax2w
axm = ax2m
else :
axw = ax3w
axm = ax3m
axw.yaxis.set_ticks_position('right')
axw.yaxis.set_ticks_position('both')
axm.yaxis.set_ticks_position('right')
axm.yaxis.set_ticks_position('both')
axtop = axw.twiny()
axtop.set_xlim( trestmin, trestmax )
if iax==2 :
axtop.set_xlabel( 'rest frame time (days from peak)')
axm.set_xlabel( 'observer frame time (MJD)')
pl.setp( axw.get_yticklabels(), visible=False )
pl.setp( axm.get_yticklabels(), visible=False )
pl.setp( axw.get_xticklabels(), visible=False )
axw.text( 0.95,0.92, filternamew, ha='right', va='top', color=color, transform=axw.transAxes )
iobs = np.where( (bandletter==bbl) & (obsflag>0) )[0]
imod = np.where( (bandletter==bbl) & (obsflag==0) )[0]
# import pdb; pdb.set_trace()
axw.errorbar( mjd[iobs], flux[iobs], fluxerr[iobs], color=color, marker='D', ls=' ', zorder=-100 )
axw.plot( mjd[imod], flux[imod], color=color, marker=' ', ls='-', zorder=-100 )
axw.fill_between( mjd[imod], flux[imod]+fluxerr[imod], flux[imod]-fluxerr[imod],
color=color, alpha=0.3, zorder=-1000 )
if mbl not in bandletter : continue
axm.text( 0.95,0.5, filternamem, ha='right', va='center', backgroundcolor='w', color=color, transform=axm.transAxes )
iobsmb = np.where( (bandletter==mbl) & (obsflag>0) )[0]
imodmb = np.where( (bandletter==mbl) & (obsflag==0) )[0]
mbfluxinterp = interp1d( mjd[imodmb], flux[imodmb], fill_value=0, bounds_error=False )
mbfluxdiff = flux[iobsmb] - mbfluxinterp( mjd[iobsmb] )
axm.errorbar( mjd[iobsmb], mbfluxdiff, fluxerr[iobsmb], color=color, marker='o', mfc='w', ls=' ' )
axm.fill_between( mjd[imodmb], fluxerr[imodmb], -fluxerr[imodmb],
color=color, alpha=0.3, zorder=-1000 )
axm.axhline( 0, color=color, lw=0.8, ls='--')
ax1w.set_xlim( mjdmin, mjdmax )
ax1w.set_ylim( -0.08, ymax )
ax1m.set_ylim( -ymaxMB, ymaxMB )
ax1w.xaxis.set_major_locator( ticker.MultipleLocator( 100 ) )
ax1w.xaxis.set_minor_locator( ticker.MultipleLocator( 25 ) )
ax1w.yaxis.set_major_locator( ticker.MultipleLocator( 0.2 ) )
ax1w.yaxis.set_minor_locator( ticker.MultipleLocator( 0.1 ) )
ax1m.xaxis.set_major_locator( ticker.MultipleLocator( 100 ) )
ax1m.xaxis.set_minor_locator( ticker.MultipleLocator( 25 ) )
ax1m.yaxis.set_major_locator( ticker.MultipleLocator( 0.2 ) )
ax1m.yaxis.set_minor_locator( ticker.MultipleLocator( 0.1 ) )
fig.subplots_adjust( left=0.1, bottom=0.18, right=0.95, top=0.82, wspace=0., hspace=0 )
pl.draw()
def mkdemofig():
""" Construct a demonstration figure showing how the medium band filters
pick out features in the Type Ia SN spectrum and how pseudo-colors can
provide redshift information. (This is Figure 1 in the paper)
"""
from matplotlib import ticker
from pytools import plotsetup
plotsetup.fullpaperfig(figsize=[8, 4])
pl.clf()
ax1 = pl.subplot(3, 2, 1)
mksedplot(1.8, color='darkblue')
ax2 = pl.subplot(3, 2, 3, sharex=ax1, sharey=ax1)
mksedplot(2.0, color='green')
ax3 = pl.subplot(3, 2, 5, sharex=ax1, sharey=ax1)
mksedplot(2.2, color='darkred')
pl.setp(ax1.get_xticklabels(), visible=False)
pl.setp(ax2.get_xticklabels(), visible=False)
ax3.set_xlim(1.12, 1.69)
ax3.set_ylim(0.0, 0.7)
ax3.set_yticklabels([])
ax3.set_xlabel('wavelength ($\mu$m)')
ax2.set_ylabel('SN Flux or Filter Transmission\n (arbitrary units)')
ax1.text(1.27,
0.6,
'F127M',
color='darkmagenta',
fontsize=9,
ha='center',
va='center')
ax1.text(1.39,
0.6,
'F139M',
color='teal',
fontsize=9,
ha='center',
va='center')
ax1.text(1.53,
0.6,
'F153M',
color='darkorange',
fontsize=9,
ha='center',
va='center')
ax1.text(0.95,
0.45,
'z=1.8',
color='darkblue',
transform=ax1.transAxes,
ha='right',
va='top')
ax2.text(0.95,
0.45,
'z=2.0',
color='green',
transform=ax2.transAxes,
ha='right',
va='top')
ax3.text(0.95,
0.55,
'z=2.2',
color='darkred',
transform=ax3.transAxes,
ha='right',
va='top')
ax4 = pl.subplot(2, 2, 2)
mkcirclepoints(zrange=[1.8, 2.2],
colorselect=[1, 0],
source='hsiao',
marker='o',
ls=' ',
mew=0.1,
mec='w')
ax4.text(0.19,
-0.13,
'z=1.8',
color='darkblue',
ha='right',
va='center',
rotation=0)
ax4.text(-0.06,
0.02,
'z=2.0',
color='green',
ha='center',
va='center',
rotation=0)
ax4.text(0.15,
-0.34,
'z=2.2',
color='darkred',
ha='left',
va='center',
rotation=0)
pl.setp(ax4.get_xticklabels(), visible=False)
ax4.yaxis.set_ticks_position('right')
ax4.yaxis.set_ticks_position('both')
ax4.yaxis.set_label_position('right')
ax5 = pl.subplot(2, 2, 4, sharex=ax4)
mkcirclepoints(zrange=[1.8, 2.2],
colorselect=[1, 2],
source='hsiao',
marker='o',
ls=' ',
mew=0.1,
mec='w')
ax5.yaxis.set_ticks_position('right')
ax5.yaxis.set_ticks_position('both')
ax5.yaxis.set_label_position('right')
ax5.text(0.2,
0.02,
'z=1.8',
color='darkblue',
ha='center',
va='center',
rotation=0)
ax5.text(-0.07,
-0.09,
'z=2.0',
color='green',
ha='center',
va='center',
rotation=0)
ax5.text(0.11,
0.13,
'z=2.2',
color='darkred',
ha='center',
va='center',
rotation=0)
ax5.set_xlim(-0.2, 0.25)
ax4.set_ylim(-0.39, 0.19)
ax5.set_ylim(-0.15, 0.29)
pl.setp(ax5.yaxis.get_label(), rotation=-90)
pl.setp(ax4.yaxis.get_label(), rotation=-90)
ax4.yaxis.labelpad = 20
ax5.yaxis.labelpad = 20
ax1.xaxis.set_major_locator(ticker.MultipleLocator(0.1))
ax1.xaxis.set_minor_locator(ticker.MultipleLocator(0.05))
ax5.xaxis.set_major_locator(ticker.MultipleLocator(0.1))
ax5.xaxis.set_minor_locator(ticker.MultipleLocator(0.05))
ax4.yaxis.set_major_locator(ticker.MultipleLocator(0.1))
ax4.yaxis.set_minor_locator(ticker.MultipleLocator(0.05))
ax5.yaxis.set_major_locator(ticker.MultipleLocator(0.1))
ax5.yaxis.set_minor_locator(ticker.MultipleLocator(0.05))
fig = pl.gcf()
fig.subplots_adjust(left=0.08,
right=0.88,
bottom=0.15,
top=0.97,
hspace=0,
wspace=0.08)
def keck_proposal_plot(sn, fit, res):
from pytools import plotsetup
from matplotlib import rcParams, pyplot as pl
plotsetup.fullpaperfig()
pl.clf()
tplot = np.arange(57525, 57720, 1)
for bandname, color, offset in zip(['f105w', 'f125w', 'f140w', 'f160w'],
['b', 'g', 'darkorange', 'k'],
[+1.5, +1, +0.5, 0]):
mag = fit.bandmag(bandname, 'ab', tplot)
pl.plot(tplot, mag + offset, color=color)
snmjd = sn['MJD']
snmag = sn['MAG']
snmagerr = sn['MAGERR']
snband = sn['FILTER']
isn = np.where(snband == bandname.upper())
pl.errorbar(snmjd[isn],
snmag[isn] + offset,
snmagerr[isn],
marker='o',
ls=' ',
ms=8,
capsize=0.1,
color=color)
ax = pl.gca()
ax.invert_yaxis()
ax.set_ylim(27.4, 23.8)
ax.set_xlim(57540, 57690)
ax.text(57585,
27.0,
'Y+1.5 (F105W)',
ha='right',
color='b',
fontsize='large',
va='top')
ax.text(57597,
25.8,
'J+1 (F125W)',
ha='right',
color='g',
fontsize='large',
va='bottom')
ax.text(57650,
26.5,
'JH+0.5 (F140W)',
ha='left',
color='darkorange',
fontsize='large',
va='top')
ax.text(57642,
25.4,
'H (F160W)',
ha='left',
color='k',
fontsize='large',
va='bottom')
ax.set_xlabel('Observed Time (MJD)')
ax.set_ylabel('AB magnitude')
fig = pl.gcf()
fig.subplots_adjust(left=0.12, bottom=0.14, right=0.97, top=0.97)
pl.draw()
def mk_bush_lc_plot( snfitres=None ):
from astropy.io import ascii
import numpy as np
from scipy.interpolate import interp1d
from matplotlib import pyplot as pl, ticker
from pytools import plotsetup, colorpalette as cp
import time
start = time.time()
if snfitres is not None :
sn,fit,res = snfitres
else :
sn,fit,res = dofit('/Users/rodney/Dropbox/MEDBAND/DATFILES/HST_CANDELS4_bushALL.sncosmo.dat',
z=1.15, dz=0.001, t0=55803.1, dt0=25.0,
model='s11-2006fo', noUV=True )
snid = 'GSD11Bus'
ymax=0.8
# optbands = ['f350lp','f606w','f814w','f850lp']
allbands = np.unique( sn['filter'] )
broadbands = [ band for band in allbands if band in ['f814w','f105w','f125w','f140w','f160w'] ]
nax = 5
medbanddict = {'f105w':'f098m','f125w':'f127m', 'f140w':'f139m', 'f160w':'f153m'}
bands = sn['filter']
mjd = sn['mjd']
flux = sn['flux'] * 10**(-0.4*(sn['zpt']-25))
fluxerr = sn['fluxerr'] * 10**(-0.4*(sn['zpt']-25))
alpha2filter = { 'H':'f160w','N':'f140w','J':'f125w','Y':'f105w',
'Z':'f850l','I':'f814w','V':'f606w',
'L':'f098m','O':'f127m','P':'f139m','Q':'f153m',
}
plotsetup.fullpaperfig( [8,3] )
pl.clf()
fig = pl.gcf()
#mjdmin = mjd.min()-10
#mjdmax = mjd.max()+25
ymax=0.7
ymaxMB=0.39
mjdmin= 55701
mjdmax = 55995
mjdmod = np.arange( mjdmin, mjdmax, 1 )
z, mjdpeak = 1.15, 55802.
snlabel='GSD11Bus'
trestmin = (mjdmin - mjdpeak)/(1+z)
trestmax = (mjdmax - mjdpeak)/(1+z)
ax1w = pl.subplot2grid( [4,4], [0,0], rowspan=3 )
ax2w = pl.subplot2grid( [4,4], [0,1], rowspan=3, sharex=ax1w, sharey=ax1w )
ax3w = pl.subplot2grid( [4,4], [0,2], rowspan=3, sharex=ax1w, sharey=ax1w )
ax4w = pl.subplot2grid( [4,4], [0,3], rowspan=3, sharex=ax1w, sharey=ax1w )
#ax5w = pl.subplot2grid( [4,5], [0,4], rowspan=3, sharex=ax1w, sharey=ax1w )
ax1m = pl.subplot2grid( [4,4], [3,0], sharex=ax1w )
ax2m = pl.subplot2grid( [4,4], [3,1], sharex=ax1w, sharey=ax1m )
ax3m = pl.subplot2grid( [4,4], [3,2], sharex=ax1w, sharey=ax1m )
ax4m = pl.subplot2grid( [4,4], [3,3], sharex=ax1w, sharey=ax1m )
#ax5m = pl.subplot2grid( [4,5], [3,4], sharex=ax1w, sharey=ax1m )
iax = 0
for bb, mb in zip( ['f105w','f125w','f140w','f160w'], ['f098m','f127m','f139m','f153m'] ) :
iax += 1
ibb = np.where( bands == bb )
imb = np.where( bands == mb )
yval = flux
yerr = fluxerr
ymod_bb = fit.bandflux( bb, mjdmod , zp=25, zpsys='ab' )
if iax==1 :
axw = ax1w
axm = ax1m
axw.text( 0.05, 0.92, snlabel, color='k', fontsize='large', fontweight='heavy', ha='left',va='top', transform=axw.transAxes )
# axw.text( -0.28, 1.2, snlabel, backgroundcolor='w', color='k', fontsize='large', fontweight='heavy', ha='left',va='top', transform=axw.transAxes, zorder=1000 )
axw.set_ylabel( 'flux (zp$_{AB}$=25)' )
axm.set_ylabel( '$\Delta$f$_{25}$' )
elif iax==2 :
axw = ax2w
axm = ax2m
elif iax==3 :
axw = ax3w
axm = ax3m
elif iax==4 :
axw = ax4w
axm = ax4m
axw.yaxis.set_ticks_position('right')
axw.yaxis.set_ticks_position('both')
axm.yaxis.set_ticks_position('right')
axm.yaxis.set_ticks_position('both')
axtop = axw.twiny()
axtop.set_xlim( trestmin, trestmax )
if iax in [2,3] :
pl.setp( axw.get_yticklabels(), visible=False )
pl.setp( axm.get_yticklabels(), visible=False )
if iax == 2 :
axtop.set_xlabel( 'rest frame time (days from peak)')
axm.set_xlabel( 'observer frame time (MJD)')
pl.setp( axw.get_xticklabels(), visible=False )
axw.text( 0.95,0.92, bb.upper(), ha='right', va='top', color='k', transform=axw.transAxes )
color='k'
axw.plot( mjdmod, ymod_bb, marker=None, color='0.5', ls='-' , zorder=-10 )
axw.errorbar( mjd[ibb], yval[ibb], yerr[ibb], ms=8, marker='o', color=color, mfc=color, mec=color, capsize=0, ls=' ' , zorder=10 )
if not mb : continue
axm.text( 0.95,0.5, mb.upper(), ha='right', va='center', backgroundcolor='w', color=color, transform=axm.transAxes )
mbfluxdiff = yval[imb] - fit.bandflux( mb, mjd[imb], zp=25, zpsys='ab' )
axm.errorbar( mjd[imb], mbfluxdiff, fluxerr[imb], color='k', marker='o', mfc='w', ls=' ' )
# axm.fill_between( mjdmod, fluxerr[imodmb], -fluxerr[imodmb],
# color=color, alpha=0.3, zorder=-1000 )
axm.axhline( 0, color='k', lw=0.8, ls='--')
ax1w.set_xlim( mjdmin, mjdmax )
ax1w.set_ylim( -0.08, ymax )
ax1m.set_ylim( -ymaxMB, ymaxMB )
ax1w.xaxis.set_major_locator( ticker.MultipleLocator( 100 ) )
ax1w.xaxis.set_minor_locator( ticker.MultipleLocator( 25 ) )
ax1w.yaxis.set_major_locator( ticker.MultipleLocator( 0.2 ) )
ax1w.yaxis.set_minor_locator( ticker.MultipleLocator( 0.1 ) )
ax1m.xaxis.set_major_locator( ticker.MultipleLocator( 100 ) )
ax1m.xaxis.set_minor_locator( ticker.MultipleLocator( 25 ) )
ax1m.yaxis.set_major_locator( ticker.MultipleLocator( 0.2 ) )
ax1m.yaxis.set_minor_locator( ticker.MultipleLocator( 0.1 ) )
fig.subplots_adjust( left=0.1, bottom=0.18, right=0.95, top=0.82, wspace=0., hspace=0 )
pl.draw()
def sncosmoplot(sn, fit, res):
from pytools import plotsetup
from matplotlib import rcParams
plotsetup.fullpaperfig()
rcParams['text.usetex'] = False
sncosmo.plot_lc(sn, model=fit, errors=res.errors)
def classdemofig(sim1=None,
sim2=None,
sim3=None,
contours=True,
clobber=False,
**plotargs):
""" Make a circle figure demonstrating the segregation of SN types
in pseudo-color space for classification.
:param sim1:
:param sim2:
:param sim3:
:param contours:
:param clobber:
:param plotargs:
:return:
"""
from pytools import plotsetup
fig = plotsetup.fullpaperfig(figsize=[8, 4])
sim1, sim2, sim3 = doublecircle(None,
sim1,
sim2,
sim3,
clobber=clobber,
contours=contours,
redshiftcircle=False,
**plotargs)
ax1 = fig.add_subplot(1, 2, 1)
ax2 = fig.add_subplot(1, 2, 2, sharex=ax1)
if contours:
ax1.text(-0.25,
-0.3,
'SN Ia',
color=_COLOR1,
ha='right',
va='top',
fontsize=14)
ax1.text(0.0, -0.08, 'SN II', color=_COLOR2, ha='center', va='center')
ax1.text(-0.2, 0.25, 'SN Ib/c', color=_COLOR3, ha='right', va='top')
else:
ax1.text(-0.25,
-0.3,
'SN Ia',
color=_COLOR1,
ha='right',
va='top',
fontsize=14)
ax1.text(-0.25, -0.08, 'SN II', color=_COLOR2, ha='right', va='center')
ax1.text(-0.25, 0.25, 'SN Ib/c', color=_COLOR3, ha='right', va='top')
fig.subplots_adjust(left=0.12,
bottom=0.14,
right=0.88,
top=0.95,
wspace=0.1)
ax1.set_xlim(-0.45, 0.4)
ax1.set_ylim(-0.45, 0.3)
ax2.set_ylim(-0.25, 0.3)
return (sim1, sim2, sim3)
def mkdemofig():
""" Construct a demonstration figure showing how the medium band filters
pick out features in the Type Ia SN spectrum and how pseudo-colors can
provide redshift information. (This is Figure 1 in the paper)
"""
from matplotlib import ticker
from pytools import plotsetup
plotsetup.fullpaperfig(figsize=[8,4])
pl.clf()
ax1 = pl.subplot( 3, 2, 1 )
mksedplot( 1.8, color='darkblue' )
ax2 = pl.subplot( 3, 2, 3, sharex=ax1, sharey=ax1 )
mksedplot( 2.0, color='green')
ax3 = pl.subplot( 3, 2, 5, sharex=ax1, sharey=ax1 )
mksedplot( 2.2, color='darkred' )
pl.setp( ax1.get_xticklabels(), visible=False )
pl.setp( ax2.get_xticklabels(), visible=False )
ax3.set_xlim( 1.12, 1.69 )
ax3.set_ylim( 0.0, 0.7 )
ax3.set_yticklabels([])
ax3.set_xlabel('wavelength ($\mu$m)')
ax2.set_ylabel('SN Flux or Filter Transmission\n (arbitrary units)')
ax1.text(1.27,0.6,'F127M',color='darkmagenta',fontsize=9, ha='center',va='center')
ax1.text(1.39,0.6,'F139M',color='teal',fontsize=9, ha='center',va='center')
ax1.text(1.53,0.6,'F153M',color='darkorange',fontsize=9, ha='center',va='center')
ax1.text(0.95,0.45,'z=1.8', color='darkblue', transform=ax1.transAxes,ha='right',va='top')
ax2.text(0.95,0.45,'z=2.0', color='green', transform=ax2.transAxes,ha='right',va='top')
ax3.text(0.95,0.55,'z=2.2', color='darkred', transform=ax3.transAxes,ha='right',va='top')
ax4 = pl.subplot( 2, 2, 2 )
mkcirclepoints(zrange=[1.8,2.2], colorselect=[1,0], source='hsiao',
marker='o', ls=' ', mew=0.1, mec='w' )
ax4.text( 0.19, -0.13, 'z=1.8', color='darkblue', ha='right', va='center', rotation=0)
ax4.text( -0.06, 0.02, 'z=2.0', color='green', ha='center', va='center', rotation=0)
ax4.text( 0.15, -0.34, 'z=2.2', color='darkred', ha='left', va='center', rotation=0)
pl.setp( ax4.get_xticklabels(), visible=False )
ax4.yaxis.set_ticks_position( 'right')
ax4.yaxis.set_ticks_position( 'both')
ax4.yaxis.set_label_position( 'right')
ax5 = pl.subplot( 2, 2, 4, sharex=ax4 )
mkcirclepoints(zrange=[1.8,2.2], colorselect=[1,2], source='hsiao',
marker='o', ls=' ', mew=0.1, mec='w' )
ax5.yaxis.set_ticks_position( 'right')
ax5.yaxis.set_ticks_position( 'both')
ax5.yaxis.set_label_position( 'right')
ax5.text( 0.2, 0.02, 'z=1.8', color='darkblue', ha='center', va='center', rotation=0)
ax5.text( -0.07,-0.09, 'z=2.0', color='green', ha='center', va='center', rotation=0)
ax5.text( 0.11, 0.13, 'z=2.2', color='darkred', ha='center', va='center', rotation=0)
ax5.set_xlim( -0.2, 0.25 )
ax4.set_ylim( -0.39, 0.19 )
ax5.set_ylim( -0.15, 0.29 )
pl.setp( ax5.yaxis.get_label(), rotation=-90 )
pl.setp( ax4.yaxis.get_label(), rotation=-90 )
ax4.yaxis.labelpad= 20
ax5.yaxis.labelpad= 20
ax1.xaxis.set_major_locator( ticker.MultipleLocator( 0.1 ) )
ax1.xaxis.set_minor_locator( ticker.MultipleLocator( 0.05 ) )
ax5.xaxis.set_major_locator( ticker.MultipleLocator( 0.1 ) )
ax5.xaxis.set_minor_locator( ticker.MultipleLocator( 0.05 ) )
ax4.yaxis.set_major_locator( ticker.MultipleLocator( 0.1 ) )
ax4.yaxis.set_minor_locator( ticker.MultipleLocator( 0.05 ) )
ax5.yaxis.set_major_locator( ticker.MultipleLocator( 0.1 ) )
ax5.yaxis.set_minor_locator( ticker.MultipleLocator( 0.05 ) )
fig = pl.gcf()
fig.subplots_adjust( left=0.08, right=0.88, bottom=0.15, top=0.97, hspace=0, wspace=0.08 )
def lcplot( snid='colfax', yunits='flux', snfitres=None ):
from matplotlib import pyplot as pl, ticker
from pytools import plotsetup, colorpalette as cp
import time
start = time.time()
if snfitres is not None :
sn,fit,res = snfitres
else :
sn,fit,res = dofitIa( snid )
if snid=='bush' :
snid = 'GSD11Bus'
ymax=0.8
labelcorner='upper right'
elif snid=='colfax' :
snid = 'GND12Col'
ymax=0.7
labelcorner='upper right'
elif snid=='stone' :
snid = 'GND13Sto'
ymax=1.2
labelcorner='upper right'
else :
ymax=1.2
labelcorner='upper right'
# optbands = ['f350lp','f606w','f814w','f850lp']
allbands = np.unique( sn['filter'] )
broadbands = [ band for band in allbands if band in ['f105w','f125w','f140w','f160w'] ]
nax = len(broadbands)
medbanddict = {'f105w':'f098m','f125w':'f127m', 'f140w':'f139m', 'f160w':'f153m'}
bands = sn['filter']
markers = ['^','o','s','d']
colors = [cp.purple, cp.bluegray,cp.darkgreen,cp.red]
mjd = sn['mjd']
mag = sn['mag']
magerr = sn['magerr']
flux = sn['flux'] * 10**(-0.4*(sn['zpt']-25))
fluxerr = sn['fluxerr'] * 10**(-0.4*(sn['zpt']-25))
plotsetup.fullpaperfig( 2, [8,3] )
pl.clf()
fig = pl.gcf()
mjdmin = mjd.min()-10
mjdmax = mjd.max()+25
mjdmod = np.arange( mjdmin, mjdmax, 1 )
z = res['parameters'][ res['param_names'].index('z') ]
mjdpeak = res['parameters'][ res['param_names'].index('t0') ]
trestmin = (mjdmin - mjdpeak)/(1+z)
trestmax = (mjdmax - mjdpeak)/(1+z)
iax = 0
for bb, marker, color in zip( broadbands, markers, colors ) :
t1 = time.time()
iax += 1
ibb = np.where( bands == bb )
mb = medbanddict[bb]
imb = np.where( bands == mb )
if iax==1 :
ax = fig.add_subplot( 1, nax, iax )
ax1 = ax
axtop = ax.twiny()
ax1.text( -0.3, 1.22, snid, color='k', fontsize='large', fontweight='heavy', ha='left',va='top', transform=ax.transAxes )
elif iax==2 :
ax = fig.add_subplot( 1, nax, iax, sharex=ax1, sharey=ax1 )
axtop = ax.twiny()
axtop.set_xlabel( 'rest frame time (days from peak)')
ax.set_xlabel( 'observer frame time (MJD)')
pl.setp( ax.get_yticklabels(), visible=False )
elif iax==nax :
ax = fig.add_subplot( 1, nax, iax, sharex=ax1, sharey=ax1 )
axtop = ax.twiny()
ax.yaxis.set_ticks_position('right')
ax.yaxis.set_ticks_position('both')
else :
ax = fig.add_subplot( 1, nax, iax, sharex=ax1, sharey=ax1 )
axtop = ax.twiny()
pl.setp( ax.get_yticklabels(), visible=False )
if yunits=='mag' :
yval = mag
yerr = magerr
ymod_bb = fit.bandmag( bb, 'ab', mjdmod )
ymod_mb = fit.bandmag( mb, 'ab', mjdmod )
if iax==1 :
ax.set_ylabel( 'AB mag' )
# ax.set_ylim( 30.6, 25.2 )
else :
yval = flux
yerr = fluxerr
ymod_bb = fit.bandflux( bb, mjdmod , zp=25, zpsys='ab' )
ymod_mb = fit.bandflux( mb, mjdmod , zp=25, zpsys='ab' )
if iax==1 :
ax.set_ylabel( 'flux (zp$_{AB}$=25)' )
ax.set_ylim( -0.09, ymax )
ax.plot( mjdmod, ymod_bb, marker=None, color='0.5', ls='-' , zorder=-10 )
ax.errorbar( mjd[ibb], yval[ibb], yerr[ibb], ms=8, marker='o', color=color, mfc=color, mec=color, capsize=0, ls=' ' , zorder=10 )
if mb in allbands :
ax.plot( mjdmod, ymod_mb, marker=None, color='0.5', ls='--' , zorder=-10 )
ax.errorbar( mjd[imb], yval[imb], yerr[imb], ms=9, marker='o', color='k', mfc='w', mec='k', capsize=0, ls=' ' , alpha=0.5, zorder=20 )
if labelcorner=='lower right' :
ax.text( 0.92,0.42, '%s'%(bb.upper()) , color=color, fontsize='medium', fontweight='heavy', ha='right',va='top', transform=ax.transAxes )
if mb in allbands :
ax.text( 0.92,0.32, '%s'%(mb.upper()) , color='k', fontsize='medium', fontweight='heavy', ha='right',va='top', transform=ax.transAxes )
elif labelcorner=='upper left' :
ax.text( 0.08,0.92, '%s'%(bb.upper()) , color=color, fontsize='medium', fontweight='heavy', ha='left',va='top', transform=ax.transAxes )
if mb in allbands :
ax.text( 0.08,0.82, '%s'%(mb.upper()) , color='k', fontsize='medium', fontweight='heavy', ha='left',va='top', transform=ax.transAxes )
if labelcorner=='upper right' :
ax.text( 0.92,0.92, '%s'%(bb.upper()) , color=color, fontsize='medium', fontweight='heavy', ha='right',va='top', transform=ax.transAxes )
if mb in allbands :
ax.text( 0.92,0.82, '%s'%(mb.upper()) , color='k', fontsize='medium', fontweight='heavy', ha='right',va='top', transform=ax.transAxes )
ax.set_xlim( mjdmin, mjdmax )
axtop.set_xlim( trestmin, trestmax )
ax.xaxis.set_major_locator( ticker.MultipleLocator( 100 ) )
ax.xaxis.set_minor_locator( ticker.MultipleLocator( 20 ) )
axtop.xaxis.set_major_locator( ticker.MultipleLocator( 20 ) )
axtop.xaxis.set_minor_locator( ticker.MultipleLocator( 5 ) )
ax.yaxis.set_major_locator( ticker.MultipleLocator( 0.2 ) )
ax.yaxis.set_minor_locator( ticker.MultipleLocator( 0.1 ) )
for tick in axtop.get_xaxis().get_major_ticks():
tick.set_pad(5.)
tick.label1 = tick._get_text1()
t2 = time.time()
print( "%s %.1f %.1f "%( bb.upper(), t2-start, t2-t1))
fig.subplots_adjust( left=0.1, bottom=0.18, right=0.95, top=0.82, wspace=0., hspace=0.15 )
pl.draw()
t3 = time.time()
print( "All %.1f"%( t3-start) )
