/
galEvol.py
461 lines (431 loc) · 21.6 KB
/
galEvol.py
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import volumeAnalysis
import bhanalysis
import matplotlib.colors as pltcolors
import matplotlib.pyplot as plt
import numpy as np
import pickle
import pynbody
import matplotlib.patches as mpatches
import gc
import readcol
plt.ion()
plt.rc('xtick',labelsize=15)
plt.rc('ytick',labelsize=15)
plt.rc('font', weight='medium')
plt.rc('axes', linewidth=2)
plt.rc('xtick.major',width=2)
plt.rc('ytick.major',width=2)
def colorcolor(halos=[1,2],average=False,simdirs=['romulus8.256gst3.bwBH'],dodust=True,dustfile = 'dust.pkl',magfile = 'mags.pkl',hcol=['red','blue'],hcmap=['Reds','Blues'],simmark=['o'],msize=100,plotData=True,simlabels=['Romulus'],hlabels=['halo 1','halo 2'],overplot=False,cbar=True):
simcnt = 0
for dir in simdirs:
print "getting data for ", dir
magf = open(dir+'/'+magfile,'rb')
mags = pickle.load(magf)
magf.close()
zmax = mags['z'].max()
zmin = mags['z'].min()
red = mags['z']
print zmax, zmin
redcNorm = pltcolors.Normalize(1./zmax,1./zmin)
if dodust:
dustf = open(dir+'/'+dustfile,'rb')
dust = pickle.load(dustf)
dustf.close()
hcnt = 0
color1 = np.zeros((len(halos),len(mags['v'][0])))
color2 = np.zeros((len(halos),len(mags['v'][0])))
for h in halos:
u, = np.where(np.array(mags['halos'])==h)
if len(u) > 1:
print "WARNING more than one entry in magnitudes file for halo", h, "using first entry..."
if len(u) == 0:
print "Halo", h, " not found in magnitudes file... skipping..."
continue
color1[hcnt,:] = mags['v'][u[0]] - mags['j'][u[0]]
color2[hcnt,:] = mags['u'][u[0]] - mags['v'][u[0]]
if dodust==True:
ud, = np.where(np.array(dust['halos'])==h)
if len(u) > 1: print "WARNING more than one entry in dust file for halo", h, "using first entry..."
if len(u) == 0:
print "Halo", h, " not found in dust file... skipping..."
continue
reddening1 = dust['v'][ud[0]] - dust['j'][ud[0]]
reddening2 = dust['u'][ud[0]] - dust['v'][ud[0]]
color1[hcnt,:] += reddening1
color2[hcnt,:] += reddening2
# print len(color1), len(color2), len(red), len(1./red)
# print hcol[hcnt],hcmap[hcnt],1/red
if average==False:
labelstr = False
if hlabels[hcnt] or simlabels[simcnt]: labelstr = simlabels[simcnt]+" "+hlabels[hcnt]
plt.scatter(color1[hcnt,:],color2[hcnt,:],c=1./red,norm=redcNorm,cmap=hcmap[hcnt],marker=simmark[simcnt],s=msize,label=labelstr,color=hcol[hcnt])
hcnt += 1
if average==True:
labelstr=False
if hlabels[0] or simlabels[0] : labelstr = simlabels[0]+" "+hlabels[0]
plt.scatter(color1.mean(axis=0),color2.mean(axis=0),c=1./red,norm=redcNorm,cmap=hcmap[0],marker=simmark[simcnt],s=msize,label=labelstr,color=hcol[0])
plt.errorbar(color1.mean(axis=0),color2.mean(axis=0),xerr=color1.std(axis=0),yerr=color2.std(axis=0),fmt='o',color=hcol[0],markersize=0,linewidth=2,elinewidth=0.75)
simcnt += 1
if plotData==True:
plt.errorbar(volumeAnalysis.CANDELS_MW['VJ'],volumeAnalysis.CANDELS_MW['UV'],xerr=[volumeAnalysis.CANDELS_MW['VJ-'],volumeAnalysis.CANDELS_MW['VJ+']],yerr=[volumeAnalysis.CANDELS_MW['UV-'],volumeAnalysis.CANDELS_MW['UV+']],fmt='o-',color='grey',markersize=0,elinewidth=.75,linewidth=2)
plt.errorbar(volumeAnalysis.CANDELS_M31['VJ'],volumeAnalysis.CANDELS_M31['UV'],xerr=[volumeAnalysis.CANDELS_M31['VJ-'],volumeAnalysis.CANDELS_M31['VJ+']],yerr=[volumeAnalysis.CANDELS_M31['UV-'],volumeAnalysis.CANDELS_M31['UV+']],fmt='o-',color='k',markersize=0,elinewidth=.75,linewidth=2)
plt.scatter(volumeAnalysis.CANDELS_MW['VJ'],volumeAnalysis.CANDELS_MW['UV'],c=1./np.array(volumeAnalysis.CANDELS_MW['redshift']),norm=redcNorm,cmap='Greys',s=150,marker='D',label='CANDELS MW',linewidth=1.5,color='k')
plt.scatter(volumeAnalysis.CANDELS_M31['VJ'],volumeAnalysis.CANDELS_M31['UV'],c=1./np.array(volumeAnalysis.CANDELS_M31['redshift']),norm=redcNorm,cmap='Greys',s=150,marker='^',label='CANDELS M31',linewidth=1.5,color='k')
if cbar==True:
cbar = plt.colorbar(ticks=[0.25,0.5,1,1.5,2.0])
cbar.set_label('Redshift',fontsize=30)
cbar.set_ticklabels(['4','2','1','0.667','0.5'])
if overplot==False:
plt.plot([1.5,1.5],[1.9,2.7],'k--',linewidth=1.5)
plt.plot([1.0,1.5],[1.3,1.9],'k--',linewidth=1.5)
plt.plot([-0.5,1.0],[1.3,1.3],'k--',linewidth=1.5)
plt.xlim(-0.5,2.1)
plt.ylim(-0.2,2.3)
plt.ylabel('U-V color',fontsize=40)
plt.xlabel('V-J color',fontsize=40)
plt.xticks(fontsize=20)
plt.legend(loc='upper left',fontsize=30)
return
def colortime(halos=[1,2],average=False,shade=False,simdirs=['romulus8.256gst3.bwBH'],dodust=True,dustfile = 'dust.pkl',magfile = 'mags.pkl',hcol=['red','blue'],simstyle=['solid','solid'],plotData=True,simlabels=['Romulus'],hlabels=['halo 1','halo 2'],overplot=False):
simcnt = 0
print "number of halos", len(halos)
for dir in simdirs:
print "getting data for ", dir
magf = open(dir+'/'+magfile,'rb')
mags = pickle.load(magf)
magf.close()
zmax = mags['z'].max()
zmin = mags['z'].min()
red = mags['z']
if dodust:
dustf = open(dir+'/'+dustfile,'rb')
dust = pickle.load(dustf)
dustf.close()
hcnt = 0
f = open(dir+'/files.list')
files = f.readlines()
f.close()
s = pynbody.load(dir+'/'+files[0].strip('\n'))
time = [bhanalysis.getTime(z,s) for z in red]
color = np.zeros((len(halos),len(mags['v'][0])))
for h in halos:
u, = np.where(np.array(mags['halos'])==h)
if len(u) > 1:
print "WARNING more than one entry in magnitudes file for halo", h, "using first entry..."
if len(u) == 0:
print "Halo", h, " not found in magnitudes file... skipping..."
continue
if average==True:
color[hcnt,:] = mags['u'][u[0]] - mags['v'][u[0]]
else:
color[hcnt,:] = mags['u'][u[0]] - mags['v'][u[0]]
if dodust==True:
ud, = np.where(np.array(dust['halos'])==h)
if len(u) > 1: print "WARNING more than one entry in dust file for halo", h, "using first entry..."
if len(u) == 0:
print "Halo", h, " not found in dust file... skipping..."
continue
reddening = dust['u'][ud[0]] - dust['v'][ud[0]]
color[hcnt,:] += reddening
if average==False and shade==False:
labelstr = None
if hlabels[hcnt] or simlabels[simcnt]: labelstr = simlabels[simcnt]+" "+hlabels[hcnt]
plt.plot(time,color[hcnt,:],color=hcol[hcnt],linewidth=2,linestyle=simstyle[simcnt],label=labelstr)
hcnt += 1
if average==True and shade==False:
labelstr = None
if hlabels[0] or simlabels[0]: labelstr = simlabels[0]+" "+hlabels[0]
plt.errorbar(time,color.mean(axis=0),color=hcol[0],yerr=color.std(axis=0),linewidth=2,linestyle=simstyle[simcnt],label=labelstr)
if shade==True and average==False:
labelstr = None
if hlabels[0] or simlabels[0]: labelstr = simlabels[0]+" "+hlabels[0]
plt.fill_between(time,color.min(axis=0),color.max(axis=0),facecolor=hcol[0],alpha=0.5)
if shade==True and average==True:
labelstr = None
if hlabels[0] or simlabels[0]: labelstr = simlabels[0]+" "+hlabels[0]
print labelstr
plt.plot(time,color.mean(axis=0),color=hcol[0],label=labelstr,linestyle=simstyle[simcnt],linewidth=2)
plt.fill_between(time,color.mean(axis=0)-color.std(axis=0),color.mean(axis=0)+color.std(axis=0),facecolor=hcol[0],alpha=0.5,label=labelstr)
simcnt += 1
if plotData == True:
volumeAnalysis.CANDELS_M31['Time'] = [bhanalysis.getTime(z,s) for z in volumeAnalysis.CANDELS_M31['redshift']]
volumeAnalysis.CANDELS_MW['Time'] = [bhanalysis.getTime(z,s) for z in volumeAnalysis.CANDELS_MW['redshift']]
plt.errorbar(volumeAnalysis.CANDELS_M31['Time'],volumeAnalysis.CANDELS_M31['UV'],yerr=[volumeAnalysis.CANDELS_M31['UV-'],volumeAnalysis.CANDELS_M31['UV+']],fmt='^',color='k',markersize=10,label='CANDELS M31')
plt.errorbar(volumeAnalysis.CANDELS_MW['Time'],volumeAnalysis.CANDELS_MW['UV'],yerr=[volumeAnalysis.CANDELS_MW['UV-'],volumeAnalysis.CANDELS_MW['UV+']],fmt='D',color='grey',markersize=10,label='CANDELS MW')
if overplot==False:
plt.xticks(fontsize=20)
plt.ylabel('U-V color',fontsize=40)
plt.xlabel('Time (Gyr)',fontsize=40)
plt.plot([0,9],[1.3,1.3],'k--')
plt.legend(loc='upper left',fontsize=22)
return
def plotStarGrowth(stars,type='Total',halo=1,color='blue',linestyle='solid',label=None,plotData=True,error=True,datacolor=['grey','k']):
if plotData==True:
f = open('/nobackupp8/mtremmel/DATA/Morishita15/Morishita15.pkl','rb')
data = pickle.load(f)
f.close()
if type == 'Total':
plt.plot(stars['z'],stars['Total'][halo-1,:],color=color,linestyle=linestyle,label=label)
if plotData==True:
if error == False:
plt.plot(data['z'],data['totMW'],color=datacolor[0],marker='D',label='CANDELS MW',markersize=10,linestyle='')
# plt.plot(data['z'],data['totMG'],color=datacolor[1],marker='^',label='CANDELS M31',markersize=10,linestyle='')
if error == True:
plt.errorbar(data['z'],data['totMW'],color=datacolor[0],yerr=[data['totMWerrMinus'],data['totMWerrPlus']],fmt='D',label='CANDELS MW',markersize=10)
# plt.errorbar(data['z'],data['totMG'],color=datacolor[1],yerr=[data['totMGerrMinus'],data['totMGerrPlus']],fmt='^',label='CANDELS M31',markersize=10)
if type == 'Inner':
plt.plot(stars['z'],stars['M <2.5 kpc'][halo-1,:],color=color,linestyle=linestyle,label=label)
if plotData==True:
if error == False:
plt.plot(data['z'],data['innerMW'],color=datacolor[0],marker='D',label='CANDELS MW',markersize=10,linestyle='')
# plt.plot(data['z'],data['innerMG'],color=datacolor[1],marker='^',label='CANDELS M31',markersize=10,linestyle='')
if error == True:
plt.errorbar(data['z'],data['innerMW'],color=datacolor[0],yerr=[data['innerMWerrMinus'],data['innerMWerrPlus']],fmt='D',label='CANDELS MW',markersize=10)
# plt.errorbar(data['z'],data['innerMG'],color=datacolor[1],yerr=[data['innerMGerrMinus'],data['innerMGerrPlus']],fmt='^',label='CANDELS M31',markersize=10)
if type == 'Outer':
plt.plot(stars['z'],stars['M >2.5 kpc'][halo-1,:],color=color,linestyle=linestyle,label=label)
if plotData==True:
if error == False:
plt.plot(data['z'],data['outerMW'],color=datacolor[0],marker='D',label='CANDELS MW',markersize=10,linestyle='')
# plt.plot(data['z'],data['outerMG'],color=datacolor[1],marker='^',label='CANDELS M31',markersize=10,linestyle='')
if error == True:
plt.errorbar(data['z'],data['outerMW'],color=datacolor[0],yerr=[data['outerMWerrMinus'],data['outerMWerrPlus']],fmt='D',label='CANDELS MW',markersize=10)
# plt.errorbar(data['z'],data['outerMG'],color=datacolor[1],yerr=[data['outerMGerrMinus'],data['outerMGerrPlus']],fmt='^',label='CANDELS M31',markersize=10)
plt.ylabel(r'M$_{*}$ [M$_{\odot}$]',fontsize=30)
plt.xlabel(r'Redshift',fontsize=30)
plt.legend(fontsize=20)
return
def MStarGrowth(lowz,catfiles,Rth='2.5 kpc',halonum=[1],filename='MstarGrowth.pkl'):
f = open(catfiles,'r')
files = f.readlines()
slz = pynbody.load(lowz)
lz = str(round(slz.properties['a']**-1 -1,3))
Stars = {'Total':pynbody.array.SimArray(np.zeros((len(halonum),len(files)+1)),'Msol'),
'Rhalf':pynbody.array.SimArray(np.zeros((len(halonum),len(files)+1)),'kpc'),
'M <'+Rth:pynbody.array.SimArray(np.zeros((len(halonum),len(files)+1)),'Msol'),
'M >'+Rth:pynbody.array.SimArray(np.zeros((len(halonum),len(files)+1)),'Msol'),
'z':np.zeros(len(files)+1),
'halos':halonum}
catend = '.cat.z'+lz+'\n'
for i in range(len(files)):
print "calculating stellar buildup for halos in ", files[i].strip('\n')
xx = files[i].find(catend)
simname=files[i][0:xx]
s = pynbody.load(simname)
h = s.halos()
Stars['z'][i] = s.properties['a']**-1 -1
s.physical_units()
catf = open(files[i].strip('\n'))
cat = pickle.load(catf)
catf.close()
amigastat = readcol.readcol(simname+'.amiga.stat',asdict=True)
for j in range(len(halonum)):
print "halo", halonum[j]
progs, = np.where(cat==halonum[j])
if len(progs)==0:
print "no progenitors found in this step!"
continue
curhalos, = np.where(np.in1d(amigastat['Grp'],progs))
main = amigastat['Grp'][curhalos][np.argmax(amigastat['StarMass(M_sol)'][curhalos])]
print "progenitor", main
h1 = h[main]
try:
pynbody.analysis.halo.center(h1,mode='hyb',wrap=True)
except:
pynbody.analysis.halo.center(h1,mode='hyb',wrap=True,vel=False)
Stars['Total'][j,i] = h1.stars['mass'].in_units('Msol').sum()
Stars['M <'+Rth][j,i] = h1.stars['mass'][(h1.stars['r'].in_units(Rth) <= 1)].in_units('Msol').sum()
Stars['M >'+Rth][j,i] = h1.stars['mass'][(h1.stars['r'].in_units(Rth) > 1)].in_units('Msol').sum()
order = np.argsort(h1.stars['r'])
Mcum = np.cumsum(h1.stars['mass'][order].in_units('Msol'))
o, = np.where(Mcum >= Stars['Total'][j,i]/2.)
Stars['Rhalf'][j,i] = h1.stars['r'].in_units('kpc')[order[o[0]]]
del(Mcum)
del(order)
del(o)
gc.collect()
del(s)
del(h)
del(cat)
gc.collect()
h = slz.halos()
slz.physical_units()
print "calculating stellar buildup for halos in ",lowz
Stars['z'][i+1] = slz.properties['a']**-1 -1
for j in range(len(halonum)):
h1 = h[halonum[j]]
try:
pynbody.analysis.halo.center(h1,mode='hyb',wrap=True)
except:
pynbody.analysis.halo.center(h1,mode='hyb',wrap=True,vel=False)
Stars['Total'][j,i+1] = h1.stars['mass'].in_units('Msol').sum()
Stars['M <'+Rth][j,i+1] = h1.stars['mass'][(h1.stars['r'].in_units(Rth) <= 1)].in_units('Msol').sum()
Stars['M >'+Rth][j,i+1] = h1.stars['mass'][(h1.stars['r'].in_units(Rth) > 1)].in_units('Msol').sum()
order = np.argsort(h1.stars['r'])
Mcum = np.cumsum(h1.stars['mass'][order].in_units('Msol'))
o, = np.where(Mcum >= Stars['Total'][j,i+1]/2.)
Stars['Rhalf'][j,i+1] = h1.stars['r'].in_units('kpc')[order[o[0]]]
if filename:
print "saving data..."
f = open(filename,'wb')
pickle.dump(Stars,f)
f.close()
return Stars
def BrightBHGal(bhhalo,bhorbit,filelist='files.list',stepfile='steps.list',dt='100 Myr',lcut=1e43,filename='brightBHgal.pkl'):
f = open(stepfile,'r')
steps = np.array(f.readlines()).astype('int')
f.close()
f = open(filelist,'r')
files = f.readlines()
f.close()
dtunits = pynbody.units.Unit(dt)
dt = pynbody.array.SimArray(1.0,dtunits)
init = np.array([])
data = {'halonum':init,'step':init,'time':init,'z':init,'sfr':init,'starmass':init,'dmmass':init,'gasmass':init,'metalicity':init,'HIfrac':init,'BHmass':init,'BHlum':init,'interact':init,'offset':init,'otheroffset':init,'otherBHmass':init,'otherBHlum':init,'BHiord':init,'otherBHiord':init,'BHmdot':init,'otherBHmdot':init}
for i in range(len(files)):
print "gettign data for for ", files[i].strip('\n')
s = pynbody.load(files[i].strip('\n'))
if len(bhhalo['mass'][(bhhalo['mass'][:,i]>0)])==0:
print "no BHs this step! moving on"
continue
# if len(s.stars[(s.stars['tform']<0)]) == 0:
# print "no BHs this step! moving on"
# continue
h = s.halos()
s.physical_units()
simtime = s.properties['time'].in_units(dtunits)
iords = bhhalo['iord'][(np.in1d(bhhalo['iord'],s.stars['iord'][(s.stars['tform']<0)]))]
halos = init
lummean = init
dist = init
time = init
mass = init
interact = init
iord = init
acc = init
starM = init
dmM = init
gasM = init
for id in iords:
curbh, = np.where(bhorbit['iord']==id)
curbh2, = np.where(bhhalo['iord']==id)
curbh = curbh[0]
curbh2 = curbh2[0]
if bhhalo['haloID'][curbh2,i]==0: continue
tt, = np.where((bhorbit['data'][curbh]['Time'].in_units(dtunits) <= simtime)&(bhorbit['data'][curbh]['Time'].in_units(dtunits) >= simtime - dt)&(bhorbit['data'][curbh]['mass'].in_units('Msol')-bhorbit['data'][curbh]['dM'].in_units('Msol')>=1e6))
lum = bhorbit['data'][curbh]['mdot'][tt].in_units('g s**-1')*0.1*3e10*3e10
mdot = bhorbit['data'][curbh]['mdot'][tt].in_units('Msol yr**-1')
tstep = bhorbit['data'][curbh]['dt'][tt].in_units(dtunits)
lmean = np.sum(lum*tstep)/dt
mdotmean = np.sum(mdot*tstep)/dt
if lmean > lcut:
halos = np.append(halos,bhhalo['haloID'][curbh2,i])
lummean = np.append(lummean,lmean)
if bhhalo['distcen'][curbh2,i]>0:
dist = np.append(dist, bhhalo['distcen'][curbh2,i])
else:
dist = np.append(dist, bhhalo['dist'][curbh2,i])
interact = np.append(interact,bhhalo['interact'][curbh2,i])
mass = np.append(mass,bhhalo['mass'][curbh2,i])
iord = np.append(iord,id)
acc = np.append(acc,mdotmean)
starM = np.append(starM,bhhalo['halostarmass'][curbh2,i])
gasM = np.append(gasM,bhhalo['halogasmass'][curbh2,i])
dmM = np.append(dmM,bhhalo['halodarkmass'][curbh2,i])
print len(lummean)
uhalos,invind = np.unique(halos,return_inverse=True)
data['halonum'] = np.append(data['halonum'],uhalos)
data['step'] = np.append(data['step'],np.ones(len(uhalos))*steps[i])
data['time'] = np.append(data['time'],np.ones(len(uhalos))*s.properties['time'].in_units('Gyr'))
data['z'] = np.append(data['z'],np.ones(len(uhalos))*(s.properties['a']**-1 -1))
for hh in uhalos:
print "getting BH info for halo ", hh
o, = np.where(halos==hh)
ltmp = lummean[o]
dtmp = dist[o]
mtmp = mass[o]
itmp = iord[o]
atmp = acc[o]
smtmp = starM[o]
gmtmp = gasM[o]
dmMtmp = dmM[o]
inttmp = interact[o]
print ltmp
lsrt = np.argsort(ltmp)
data['BHlum'] = np.append(data['BHlum'],ltmp[lsrt[-1]])
data['offset'] = np.append(data['offset'],dtmp[lsrt[-1]])
data['BHmass'] = np.append(data['BHmass'],mtmp[lsrt[-1]])
data['BHiord'] = np.append(data['BHiord'],itmp[lsrt[-1]])
data['BHmdot'] = np.append(data['BHmdot'],atmp[lsrt[-1]])
data['starmass'] = np.append(data['starmass'],smtmp[lsrt[-1]])
data['dmmass'] = np.append(data['dmmass'],dmMtmp[lsrt[-1]])
data['gasmass'] = np.append(data['gasmass'],gmtmp[lsrt[-1]])
data['interact'] = np.append(data['interact'],inttmp[lsrt[-1]])
if len(ltmp) > 1:
data['otherBHlum'] = np.append(data['otherBHlum'],ltmp[lsrt[-2]])
data['otheroffset'] = np.append(data['otheroffset'],dtmp[lsrt[-2]])
data['otherBHmass'] = np.append(data['otherBHmass'],mtmp[lsrt[-2]])
data['otherBHiord'] = np.append(data['otherBHiord'],itmp[lsrt[-2]])
data['otherBHmdot'] = np.append(data['otherBHmdot'],atmp[lsrt[-2]])
else:
data['otherBHlum'] = np.append(data['otherBHlum'],0)
data['otheroffset'] = np.append(data['otheroffset'],0)
data['otherBHmass'] = np.append(data['otherBHmass'],0)
data['otherBHiord'] = np.append(data['otherBHiord'],0)
data['otherBHmdot'] = np.append(data['otherBHmdot'],0)
if len(h[hh].s)>0:
newstars, = np.where(h[hh].s['tform'].in_units(dtunits)>=simtime-dt)
s.read_starlog()
sfr = h[hh].s['massform'][newstars].in_units('Msol').sum()/dt.in_units('yr')
else:
sfr = 0
if len(h[hh].g) > 0:
metalicity = np.sum(h[hh].g['metals']*h[hh].g['mass'])/np.sum(h[hh].g['mass'])
HI = np.sum(h[hh].g['HI']*h[hh].g['mass'])/np.sum(h[hh].g['mass'])
else:
metalicity = 0
HI = 0
data['sfr']=np.append(data['sfr'],sfr)
data['metalicity']=np.append(data['metalicity'],metalicity)
data['HIfrac'] = np.append(data['HIfrac'],HI)
del(s)
del(h)
gc.collect()
if filename:
f = open(filename,'wb')
pickle.dump(data,f)
f.close()
return data
def MulaneyBHSFR(sfr):
#Mulaney+ 2012
return 1e-3 * sfr
def ChenBHSFR(sfr):
#Chen+ 2013
return 10**-3.72 * sfr**1.05
def TotalIRto60micron(LIR):
'''based on figure 3 of Chary and Elbaz 2001'''
return LIR/2.
def SFRtoIR(SFR):
'''based on Daddi+ 2007'''
return SFR / 1.73e-10 * 3.846e33
def RosarioBHSFR(sfr):
#Rosario+ 2012
LIR = SFRtoIR(sfr)
L60 = TotalIRto60micron(LIR)
logL60norm = np.log10(L60/1e44)
logLBH = np.log10(L60/1e44)**(1.0/0.78) + np.log10(6.3e44)
LBH = 10**logLBH
mdot = pynbody.array.SimArray(LBH/(0.1*3e10*3e10),'g s**-1')
return mdot.in_units('Msol yr**-1')
def plotBHSFRdata():
sfrline = 10**np.arange(-4,4,0.1)
mdotM12 = MulaneyBHSFR(sfrline)
mdotC13 = ChenBHSFR(sfrline)
# mdotR12 = RosarioBHSFR(sfrline)
plt.plot(sfrline,mdotM12,'b-',label='Mulaney+ 12',linewidth=2)
plt.plot(sfrline,mdotC13,'b--',label='Chen+ 13',linewidth=2)
# plt.plot(sfrline,mdotR12,'g-',label='Rosario+ 12',linewidth=2)
plt.legend(fontsize=20)
plt.ylabel(r'$\dot{\mathrm{M}_{BH}}$ [M$_{odot}$ yr$^{-1}$]',fontsize=30)
plt.xlabel(r'SFR [M$_{odot}$ yr$^{-1}$]',fontsize=30)
return