def plotPriorSurf(plotfilename):
#Calculate the surface density profile for each trial potential, then plot the range
if '.png' in plotfilename:
savefilename= plotfilename.replace('.png','.sav')
elif '.ps' in plotfilename:
savefilename= plotfilename.replace('.ps','.sav')
if not os.path.exists(savefilename):
options= setup_options(None)
options.potential= 'dpdiskplhalofixbulgeflatwgasalt'
options.fitdvt= False
rs= numpy.linspace(4.2,9.8,101)
rds= numpy.linspace(2.,3.4,8)
fhs= numpy.linspace(0.,1.,16)
surfz= numpy.zeros((len(rs),len(rds)*len(fhs)))+numpy.nan
ro= 1.
vo= 230./220.
dlnvcdlnr= 0.
zh= 400.
for jj in range(len(rds)):
for kk in range(len(fhs)):
#Setup potential to calculate stuff
potparams= numpy.array([numpy.log(rds[jj]/8.),vo,numpy.log(zh/8000.),fhs[kk],dlnvcdlnr])
try:
pot= setup_potential(potparams,options,0,returnrawpot=True)
except RuntimeError:
continue
for ii in range(len(rs)):
surfz[ii,jj*len(fhs)+kk]= 2.*integrate.quad((lambda zz: potential.evaluateDensities(rs[ii]/8.,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
#Find minimum and maximum curves
minsurfz= numpy.nanmin(surfz,axis=1)
maxsurfz= numpy.nanmax(surfz,axis=1)
#Save
save_pickles(savefilename,rs,minsurfz,maxsurfz)
else:
savefile= open(savefilename,'rb')
rs= pickle.load(savefile)
minsurfz= pickle.load(savefile)
maxsurfz= pickle.load(savefile)
savefile.close()
#Plot
bovy_plot.bovy_print()
bovy_plot.bovy_plot([numpy.nan],[numpy.nan],'ko',
xlabel=r'$R\ (\mathrm{kpc})$',
ylabel=r'$\Sigma(R,|Z| \leq 1.1\,\mathrm{kpc})\ (M_\odot\,\mathrm{pc}^{-2})$',
xrange=[4.,10.],
yrange=[10,1050.],
semilogy=True)
pyplot.fill_between(rs,minsurfz,maxsurfz,
color='0.50')
bovy_plot.bovy_text(8.,68.,r'$\odot$',size=16.,verticalalignment='center',
horizontalalignment='center')
bovy_plot.bovy_end_print(plotfilename)
return None
def plot_forces():
potparams= numpy.array([numpy.log(2.15/_REFR0),
1.,
numpy.log(0.3/_REFR0),
0.307169914244,
-1.79107550983])
options= setup_options(None)
options.potential= 'dpdiskplhalofixcutbulgeflatwgasalt'
pot= setup_potential(potparams,options,0,returnrawpot=True)
bovy_plot.bovy_print(fig_width=8.,fig_height=5.)
potential.plotDensities(pot,rmin=-15./8.,rmax=15./8.,nrs=100,
zmin=-10./8,zmax=10./8.,nzs=101,ncontours=10,
aspect=5./5.,log=True)
bovy_plot.bovy_end_print('/home/bovy/Desktop/test.png')
pass
def illustrateBestR(options,args):
if options.sample.lower() == 'g':
npops= 62
elif options.sample.lower() == 'k':
npops= 54
if options.sample.lower() == 'g':
savefile= open('binmapping_g.sav','rb')
elif options.sample.lower() == 'k':
savefile= open('binmapping_k.sav','rb')
fehs= pickle.load(savefile)
afes= pickle.load(savefile)
savefile.close()
#For bin 10, calculate the correlation between sigma and Rd
bin= options.index
derivProps= calcAllSurfErr(bin,options,args)
#rs= numpy.linspace(4.5,9.,101)
#derivProps= numpy.zeros((101,6))
rs= derivProps[:,0]
#also calculate the full surface density profile for each Rd's best fh
if _NOTDONEYET:
spl= options.restart.split('.')
else:
spl= args[0].split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % bin
newname+= spl[-1]
options.potential= 'dpdiskplhalofixbulgeflatwgasalt'
options.fitdvt= False
savefile= open(newname,'rb')
try:
if not _NOTDONEYET:
params= pickle.load(savefile)
mlogl= pickle.load(savefile)
logl= pickle.load(savefile)
except:
raise
finally:
savefile.close()
if _NOTDONEYET:
logl[(logl == 0.)]= -numpy.finfo(numpy.dtype(numpy.float64)).max
logl[numpy.isnan(logl)]= -numpy.finfo(numpy.dtype(numpy.float64)).max
marglogl= numpy.zeros((logl.shape[0],logl.shape[3]))
sigs= numpy.zeros((logl.shape[0],len(rs)))
rds= numpy.linspace(2.,3.4,8)
fhs= numpy.linspace(0.,1.,16)
hiresfhs= numpy.linspace(0.,1.,101)
ro= 1.
vo= options.fixvc/_REFV0
for jj in range(logl.shape[0]):
for kk in range(logl.shape[3]):
marglogl[jj,kk]= misc.logsumexp(logl[jj,0,0,kk,:,:,:,0].flatten())
#interpolate
tindx= marglogl[jj,:] > -1000000000.
intp= interpolate.InterpolatedUnivariateSpline(fhs[tindx],marglogl[jj,tindx],
k=3)
ml= intp(hiresfhs)
indx= numpy.argmax(ml)
indx2= numpy.argmax(marglogl[jj,:])
#Setup potential to calculate stuff
potparams= numpy.array([numpy.log(rds[jj]/8.),vo,numpy.log(options.fixzh/8000.),hiresfhs[indx],options.dlnvcdlnr])
try:
pot= setup_potential(potparams,options,0,returnrawpot=True)
except RuntimeError:
continue
#Total surface density
for ll in range(len(rs)):
surfz= 2.*integrate.quad((lambda zz: potential.evaluateDensities(rs[ll]/_REFR0,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
sigs[jj,ll]= surfz
#Now plot sigs
bovy_plot.bovy_print(fig_height=7.,fig_width=5.)
left, bottom, width, height= 0.1, 0.35, 0.8, 0.4
axTop= pyplot.axes([left,bottom,width,height])
fig= pyplot.gcf()
fig.sca(axTop)
ii= 0
bovy_plot.bovy_plot(rs,sigs[ii,:],'k-',
xlabel=r'$R\ (\mathrm{kpc})$',
ylabel=r'$\Sigma(R,|Z| \leq 1.1\,\mathrm{kpc})\ (M_\odot\,\mathrm{pc}^{-2})$',
xrange=[4.,10.],
yrange=[10,1050.],
semilogy=True,overplot=True)
for ii in range(1,logl.shape[0]):
bovy_plot.bovy_plot(rs,sigs[ii,:],'k-',overplot=True)
thisax= pyplot.gca()
thisax.set_yscale('log')
nullfmt = NullFormatter() # no labels
thisax.xaxis.set_major_formatter(nullfmt)
thisax.set_ylim(10.,1050.)
thisax.set_xlim(4.,10.)
pyplot.ylabel(r'$\Sigma_{1.1}(R)\ (M_\odot\,\mathrm{pc}^{-2})$')
bovy_plot._add_ticks(yticks=False)
bovy_plot.bovy_text(r'$[\mathrm{Fe/H}] = %.2f$' % (fehs[bin])
+'\n'
r'$[\alpha/\mathrm{Fe}] = %.3f$' % (afes[bin]),
size=16.,top_right=True)
left, bottom, width, height= 0.1, 0.1, 0.8, 0.25
ax2= pyplot.axes([left,bottom,width,height])
fig= pyplot.gcf()
fig.sca(ax2)
bovy_plot.bovy_plot(rs,derivProps[:,2],'k-',lw=2.,
xrange=[4.,10.],
overplot=True)
indx= numpy.argmin(numpy.fabs(derivProps[:,2]))
bovy_plot.bovy_plot([4.,10.],[0.,0.],'-',color='0.5',overplot=True)
bovy_plot.bovy_plot([rs[indx],rs[indx]],[derivProps[indx,2],1000.],
'k--',overplot=True)
thisax= pyplot.gca()
pyplot.ylabel(r'$\mathrm{Correlation\ between}$'+'\n'+r'$\!\!\!\!\!\!\!\!R_d\ \&\ \Sigma_{1.1}(R)$')
pyplot.xlabel(r'$R\ (\mathrm{kpc})$')
pyplot.xlim(4.,10.)
pyplot.ylim(-.5,.5)
bovy_plot._add_ticks()
pyplot.sca(axTop)
bovy_plot.bovy_plot([rs[indx],rs[indx]],[0.01,sigs[3,indx]],
'k--',overplot=True)
bovy_plot.bovy_end_print(options.outfilename)
def plot_hrhrvshr(options,args):
"""Plot hr^out/hr^in as a function of hr for various sr"""
if len(args) == 0.:
print "Must provide a savefilename ..."
print "Returning ..."
return None
if os.path.exists(args[0]):
#Load
savefile= open(args[0],'rb')
plotthis= pickle.load(savefile)
hrs= pickle.load(savefile)
srs= pickle.load(savefile)
savefile.close()
else:
#Grid of models to test
hrs= numpy.linspace(options.hrmin,options.hrmax,options.nhr)
srs= numpy.linspace(options.srmin,options.srmax,options.nsr)
#Tile
hrs= numpy.tile(hrs,(options.nsr,1)).T
srs= numpy.tile(srs,(options.nhr,1))
plotthis= numpy.zeros((options.nhr,options.nsr))
#Setup potential and aA
poptions= setup_options(None)
#poptions.potential= 'dpdiskplhalofixbulgeflatwgasalt'
#params= [0.,0.,0.,0.,0.,0.,-1.16315,1.,-3.,0.4,0.]
poptions.potential= 'btii'
params= None
#pot= MWPotential
pot= setup_potential(params,poptions,1)
if options.aAmethod.lower() == 'staeckel':
aA= actionAngleStaeckel(pot=pot,delta=0.45,c=True)
else:
aA=actionAngleAdiabaticGrid(pot=pot,nR=16,nEz=16,nEr=31,nLz=31,
zmax=1.,Rmax=5.)
for ii in range(options.nhr):
for jj in range(options.nsr):
qdf= quasiisothermaldf(hrs[ii,jj]/8.,srs[ii,jj]/220.,
srs[ii,jj]/numpy.sqrt(3.)/220.,
7./8.,1.,
pot=pot,aA=aA)
plotthis[ii,jj]= qdf.estimate_hr(1.,z=0.8/8.,
dR=0.33,
gl=True)/hrs[ii,jj]*8.
print ii*options.nsr+jj+1, options.nsr*options.nhr, \
hrs[ii,jj], srs[ii,jj], plotthis[ii,jj]
#Save
save_pickles(args[0],plotthis,hrs,srs)
#Now plot
bovy_plot.bovy_print(fig_width=6.,
text_fontsize=20.,
legend_fontsize=24.,
xtick_labelsize=18.,
ytick_labelsize=18.,
axes_labelsize=24.)
indx= 0
lines= []
colors= [cm.jet(ii/float(options.nsr-1.)*1.+0.) for ii in range(options.nsr)]
lss= ['-' for ii in range(options.nsr)]#,'--','-.','..']
labels= []
lines.append(bovy_plot.bovy_plot(hrs[:,indx],plotthis[:,indx],
color=colors[indx],ls=lss[indx],
xrange=[0.5,5.5],
yrange=[0.,2.],
xlabel=r'$h^{\mathrm{in}}_R\ \mathrm{at}\ 8\,\mathrm{kpc}$',
ylabel=r'$h^{\mathrm{out}}_R / h^{\mathrm{in}}_R$'))
labels.append(r'$\sigma_R = %.0f \,\mathrm{km\,s}^{-1}$' % srs[0,indx])
for indx in range(1,options.nsr):
lines.append(bovy_plot.bovy_plot(hrs[:,indx],plotthis[:,indx],
color=colors[indx],ls=lss[indx],
overplot=True))
labels.append(r'$\sigma_R = %.0f \,\mathrm{km\,s}^{-1}$' % srs[0,indx])
"""
#Legend
pyplot.legend(lines,#(line1[0],line2[0],line3[0],line4[0]),
labels,#(r'$v_{bc} = 0$',
# r'$v_{bc} = 1\,\sigma_{bc}$',
# r'$v_{bc} = 2\,\sigma_{bc}$',
# r'$v_{bc} = 3\,\sigma_{bc}$'),
loc='lower right',#bbox_to_anchor=(.91,.375),
numpoints=2,
prop={'size':14},
frameon=False)
"""
#Add colorbar
map = cm.ScalarMappable(cmap=cm.jet)
map.set_array(srs[0,:])
map.set_clim(vmin=numpy.amin(srs[0,:]),vmax=numpy.amax(srs[0,:]))
cbar= pyplot.colorbar(map,fraction=0.15)
cbar.set_clim(numpy.amin(srs[0,:]),numpy.amax(srs[0,:]))
cbar.set_label(r'$\sigma_R \,(\mathrm{km\,s}^{-1})$')
bovy_plot.bovy_end_print(options.plotfilename)
def plot_szszvssz(options,args):
"""Plot sz^out/sz^in as a function of sz for various hr"""
if len(args) == 0.:
print "Must provide a savefilename ..."
print "Returning ..."
return None
if os.path.exists(args[0]):
#Load
savefile= open(args[0],'rb')
plotthis= pickle.load(savefile)
szs= pickle.load(savefile)
hrs= pickle.load(savefile)
savefile.close()
else:
#Grid of models to test
if options.subtype.lower() == 'sr':
szs= numpy.linspace(options.srmin,options.srmax,options.nsz)
else:
szs= numpy.linspace(options.szmin,options.szmax,options.nsz)
hrs= numpy.linspace(options.hrmin,options.hrmax,options.nhr)
#Tile
szs= numpy.tile(szs,(options.nhr,1)).T
hrs= numpy.tile(hrs,(options.nsz,1))
plotthis= numpy.zeros((options.nsz,options.nhr))
#Setup potential and aA
poptions= setup_options(None)
#poptions.potential= 'dpdiskplhalofixbulgeflatwgasalt'
#params= [0.,0.,0.,0.,0.,0.,-1.16315,1.,-3.,0.4,0.]
poptions.potential= 'btii'
params= None
#pot= MWPotential
pot= setup_potential(params,poptions,1)
if options.aAmethod.lower() == 'staeckel':
aA= actionAngleStaeckel(pot=pot,delta=0.45,c=True)
else:
aA=actionAngleAdiabaticGrid(pot=pot,nR=16,nEz=16,nEr=31,nLz=31,
zmax=1.,Rmax=5.)
for ii in range(options.nsz):
for jj in range(options.nhr):
if options.subtype.lower() == 'sr':
qdf= quasiisothermaldf(hrs[ii,jj]/8.,
szs[ii,jj]/220.,
szs[ii,jj]/220./numpy.sqrt(3.),
7./8.,1.,
pot=pot,aA=aA)
else:
qdf= quasiisothermaldf(hrs[ii,jj]/8.,
szs[ii,jj]/220.*numpy.sqrt(3.),
szs[ii,jj]/220.,
7./8.,1.,
pot=pot,aA=aA)
if options.subtype.lower() == 'sr':
plotthis[ii,jj]= numpy.sqrt(qdf.sigmaR2(1.,0.8/8.,
gl=True))/szs[ii,jj]*220.
else:
plotthis[ii,jj]= numpy.sqrt(qdf.sigmaz2(1.,0.8/8.,
gl=True))/szs[ii,jj]*220.
print ii*options.nhr+jj+1, options.nhr*options.nsz, \
szs[ii,jj], hrs[ii,jj], plotthis[ii,jj]
#Save
save_pickles(args[0],plotthis,szs,hrs)
#Now plot
bovy_plot.bovy_print(fig_width=6.,
text_fontsize=20.,
legend_fontsize=24.,
xtick_labelsize=18.,
ytick_labelsize=18.,
axes_labelsize=24.)
indx= 0
lines= []
colors= [cm.jet(ii/float(options.nhr-1.)*1.+0.) for ii in range(options.nhr)]
lss= ['-' for ii in range(options.nhr)]#,'--','-.','..']
labels= []
if options.subtype.lower() == 'sr':
lines.append(bovy_plot.bovy_plot(szs[:,indx],plotthis[:,indx],
color=colors[indx],ls=lss[indx],
xrange=[10.,85.],
yrange=[0.8,1.5],
xlabel=r'$\sigma^{\mathrm{in}}_R\ \mathrm{at}\ R = 8\,\mathrm{kpc}$',
ylabel=r'$\sigma^{\mathrm{out}}_R / \sigma^{\mathrm{in}}_R$'))
else:
lines.append(bovy_plot.bovy_plot(szs[:,indx],plotthis[:,indx],
color=colors[indx],ls=lss[indx],
xrange=[10.,115.],
yrange=[0.5,1.2],
xlabel=r'$\sigma^{\mathrm{in}}_Z\ \mathrm{at}\ R = 8\,\mathrm{kpc}$',
ylabel=r'$\sigma^{\mathrm{out}}_Z / \sigma^{\mathrm{in}}_Z$'))
for indx in range(1,options.nhr):
lines.append(bovy_plot.bovy_plot(szs[:,indx],plotthis[:,indx],
color=colors[indx],ls=lss[indx],
overplot=True))
#Add colorbar
map = cm.ScalarMappable(cmap=cm.jet)
map.set_array(hrs[0,:])
map.set_clim(vmin=numpy.amin(hrs[0,:]),vmax=numpy.amax(hrs[0,:]))
cbar= pyplot.colorbar(map,fraction=0.15)
cbar.set_clim(numpy.amin(hrs[0,:]),numpy.amax(hrs[0,:]))
cbar.set_label(r'$h_R\, (\mathrm{kpc})$')
bovy_plot.bovy_end_print(options.plotfilename)
def plotSurfRdfh(plotfilename):
#Calculate the surface density profile for each trial potential, then plot in 2D
if '.png' in plotfilename:
savefilename= plotfilename.replace('.png','.sav')
elif '.ps' in plotfilename:
savefilename= plotfilename.replace('.ps','.sav')
if not os.path.exists(savefilename):
options= setup_options(None)
options.potential= 'dpdiskplhalofixbulgeflatwgasalt'
options.fitdvt= False
rs= numpy.array([5.,8.,11.])
rds= numpy.linspace(2.,3.4,_NRDS)
fhs= numpy.linspace(0.,1.,_NFHS)
surfz= numpy.zeros((len(rs),len(rds),len(fhs)))+numpy.nan
ro= 1.
vo= _VC/ _REFV0
dlnvcdlnr= _DLNVCDLNR
zh= _ZH
for jj in range(len(rds)):
for kk in range(len(fhs)):
#Setup potential to calculate stuff
potparams= numpy.array([numpy.log(rds[jj]/8.),vo,numpy.log(zh/8000.),fhs[kk],dlnvcdlnr])
try:
pot= setup_potential(potparams,options,0,returnrawpot=True)
except RuntimeError:
continue
for ii in range(len(rs)):
if False:
surfz[ii,jj,kk]= -potential.evaluatezforces(rs[ii]/_REFR0,options.height/_REFR0/ro,pot)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro/2./numpy.pi
else:
surfz[ii,jj,kk]= 2.*integrate.quad((lambda zz: potential.evaluateDensities(rs[ii]/8.,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
#Save
save_pickles(savefilename,rs,rds,fhs,surfz)
else:
savefile= open(savefilename,'rb')
rs= pickle.load(savefile)
rds= pickle.load(savefile)
fhs= pickle.load(savefile)
surfz= pickle.load(savefile)
savefile.close()
#Now plot
bovy_plot.bovy_print()
data = numpy.ma.masked_invalid(surfz[1,:,:])
bovy_plot.bovy_dens2d(data.filled(data.mean()).T,
origin='lower',
cmap='jet',
colorbar=True,
shrink=0.775,
xlabel=r'$\mathrm{disk\ scale\ length}\,(\mathrm{kpc})$',
ylabel=r'$\mathrm{relative\ halo\ contribution\ to}\ V^2_c(R_0)$',
zlabel=r'$\Sigma(R_0,|Z| \leq 1.1\,\mathrm{kpc})\, (M_\odot\,\mathrm{pc}^{-2})$',
xrange=[rds[0]-(rds[1]-rds[0])/2.,
rds[-1]+(rds[1]-rds[0])/2.],
yrange=[fhs[0]-(fhs[1]-fhs[0])/2.,
fhs[-1]+(fhs[1]-fhs[0])/2.])
#Fix bad data
bad_data = numpy.ma.masked_where(~data.mask, data.mask)
bovy_plot.bovy_dens2d(bad_data.T,
origin='lower',
interpolation='nearest',
cmap=cm.gray_r,
overplot=True,
xrange=[rds[0]-(rds[1]-rds[0])/2.,
rds[-1]+(rds[1]-rds[0])/2.],
yrange=[fhs[0]-(fhs[1]-fhs[0])/2.,
fhs[-1]+(fhs[1]-fhs[0])/2.])
#Overlay contours of sigma at other R
bovy_plot.bovy_dens2d(surfz[0,:,:].T,origin='lower',
xrange=[rds[0]-(rds[1]-rds[0])/2.,
rds[-1]+(rds[1]-rds[0])/2.],
yrange=[fhs[0]-(fhs[1]-fhs[0])/2.,
fhs[-1]+(fhs[1]-fhs[0])/2.],
overplot=True,
justcontours=True,
contours=True,
cntrcolors='k',
cntrls='-')
bovy_plot.bovy_dens2d(surfz[2,:,:].T,origin='lower',
xrange=[rds[0]-(rds[1]-rds[0])/2.,
rds[-1]+(rds[1]-rds[0])/2.],
yrange=[fhs[0]-(fhs[1]-fhs[0])/2.,
fhs[-1]+(fhs[1]-fhs[0])/2.],
overplot=True,
justcontours=True,
contours=True,
cntrcolors='w',
# cntrlabel=True,
cntrls='--')
#Add labels
bovy_plot.bovy_text(r'$\Sigma(R=5\,\mathrm{kpc})$'
+'\n'
+r'$\Sigma(R=11\,\mathrm{kpc})$',
bottom_left=True,size=14.)
bovy_plot.bovy_plot([2.575,2.8],[0.15,0.31],'-',color='0.5',overplot=True)
bovy_plot.bovy_plot([2.625,2.95],[0.06,0.1525],'-',color='0.5',overplot=True)
#overplot actual gridpoints
gridrds= numpy.linspace(2.,3.4,8)
gridfhs= numpy.linspace(0.,1.,16)
for ii in range(len(gridrds)):
bovy_plot.bovy_plot(gridrds[ii]+numpy.zeros(len(gridfhs)),
gridfhs,
's',
color='w',ms=3.,overplot=True,
markeredgecolor='none')
bovy_plot.bovy_end_print(plotfilename)
return None
def plot_DFRotcurves(options,args):
raw= read_rawdata(options)
#Bin the data
binned= pixelAfeFeh(raw,dfeh=options.dfeh,dafe=options.dafe)
if options.tighten:
tightbinned= pixelAfeFeh(raw,dfeh=options.dfeh,dafe=options.dafe,
fehmin=-1.6,fehmax=0.5,afemin=-0.05,
afemax=0.55)
else:
tightbinned= binned
#Map the bins with ndata > minndata in 1D
fehs, afes= [], []
counter= 0
abindx= numpy.zeros((len(binned.fehedges)-1,len(binned.afeedges)-1),
dtype='int')
for ii in range(len(binned.fehedges)-1):
for jj in range(len(binned.afeedges)-1):
data= binned(binned.feh(ii),binned.afe(jj))
if len(data) < options.minndata:
continue
#print binned.feh(ii), binned.afe(jj), len(data)
fehs.append(binned.feh(ii))
afes.append(binned.afe(jj))
abindx[ii,jj]= counter
counter+= 1
nabundancebins= len(fehs)
fehs= numpy.array(fehs)
afes= numpy.array(afes)
#Load each solutions
sols= []
savename= args[0]
initname= options.init
for ii in range(nabundancebins):
spl= savename.split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % ii
newname+= spl[-1]
savefilename= newname
#Read savefile
try:
savefile= open(savefilename,'rb')
except IOError:
print "WARNING: MISSING ABUNDANCE BIN"
sols.append(None)
else:
sols.append(pickle.load(savefile))
savefile.close()
#Load samples as well
if options.mcsample:
#Do the same for init
spl= initname.split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % ii
newname+= spl[-1]
options.init= newname
mapfehs= monoAbundanceMW.fehs()
mapafes= monoAbundanceMW.afes()
#Now plot
#Run through the pixels and plot rotation curves
if options.type == 'afe':
vmin, vmax= 0.0,.5
zlabel=r'$[\alpha/\mathrm{Fe}]$'
elif options.type == 'feh':
vmin, vmax= -1.6,0.4
zlabel=r'$[\mathrm{Fe/H}]$'
overplot= False
if options.subtype is None or options.subtype.lower() != 'median':
bovy_plot.bovy_print(fig_height=3.87,fig_width=5.)
medianvc= []
medianvc_disk= []
medianvc_halo= []
medianvc_bulge= []
medianrs= numpy.linspace(0.001,2.,1001)
for ii in range(tightbinned.npixfeh()):
for jj in range(tightbinned.npixafe()):
data= binned(tightbinned.feh(ii),tightbinned.afe(jj))
if len(data) < options.minndata:
if options.type.lower() == 'afe' or options.type.lower() == 'feh' or options.type.lower() == 'fehafe' \
or options.type.lower() == 'afefeh':
continue
else:
plotthis[ii,jj]= numpy.nan
continue
#Find abundance indx
fehindx= binned.fehindx(tightbinned.feh(ii))#Map onto regular binning
afeindx= binned.afeindx(tightbinned.afe(jj))
solindx= abindx[fehindx,afeindx]
monoabindx= numpy.argmin((tightbinned.feh(ii)-mapfehs)**2./0.01 \
+(tightbinned.afe(jj)-mapafes)**2./0.0025)
if sols[solindx] is None:
if options.type.lower() == 'afe' or options.type.lower() == 'feh' or options.type.lower() == 'fehafe' \
or options.type.lower() == 'afefeh':
continue
else:
plotthis[ii,jj]= numpy.nan
continue
s= get_potparams(sols[solindx],options,1)
#Setup potential
pot= setup_potential(sols[solindx],options,1,returnrawpot=True)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.type.lower() == 'afe':
plotc= tightbinned.afe(jj)
elif options.type.lower() == 'feh':
plotc= tightbinned.feh(jj)
colormap = cm.jet
if options.subtype is None or options.subtype.lower() == 'full':
potential.plotRotcurve(pot,Rrange=[0.001,2.],
overplot=overplot,ls='-',
color=colormap(_squeeze(plotc,vmin,vmax)),
yrange=[0.,1.29],
ylabel= r"$V_c(R)/V_c(R_0)$",
zorder=int(numpy.random.uniform()*100))
elif options.subtype.lower() == 'disk':
if 'mwpotential' in options.potential.lower():
diskpot= pot[0]
elif 'wgas' in options.potential.lower():
diskpot= [pot[0],pot[-1]]
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
diskpot= pot[0]
elif 'dpdisk' in options.potential.lower():
diskpot= pot[0]
potential.plotRotcurve(diskpot,Rrange=[0.001,2.],
yrange=[0.,1.29],
overplot=overplot,ls='-',
color=colormap(_squeeze(plotc,vmin,vmax)),
ylabel= r"$V_c(R)/V_c(R_0)$",
zorder=int(numpy.random.uniform()*100))
elif options.subtype.lower() == 'halo':
halopot= pot[1]
potential.plotRotcurve(halopot,Rrange=[0.001,2.],
overplot=overplot,ls='-',
yrange=[0.,1.29],
ylabel= r"$V_c(R)/V_c(R_0)$",
color=colormap(_squeeze(plotc,vmin,vmax)),
zorder=int(numpy.random.uniform()*100))
elif options.subtype.lower() == 'bulge':
bulgepot= pot[2]
potential.plotRotcurve(bulgepot,Rrange=[0.001,2.],
overplot=overplot,ls='-',
ylabel= r"$V_c(R)/V_c(R_0)$",
yrange=[0.,1.29],
color=colormap(_squeeze(plotc,vmin,vmax)),
zorder=int(numpy.random.uniform()*100))
elif options.subtype.lower() == 'median':
if 'mwpotential' in options.potential.lower():
diskpot= pot[0]
elif 'wgas' in options.potential.lower():
diskpot= [pot[0],pot[-1]]
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
diskpot= pot[0]
elif 'dpdisk' in options.potential.lower():
diskpot= pot[0]
halopot= pot[1]
bulgepot= pot[2]
vo= get_vo(sols[solindx],options,1)
medianvc.append(vo*potential.calcRotcurve(pot,medianrs))
medianvc_disk.append(vo*potential.calcRotcurve(diskpot,medianrs))
medianvc_halo.append(vo*potential.calcRotcurve(halopot,medianrs))
medianvc_bulge.append(vo*potential.calcRotcurve(bulgepot,medianrs))
overplot=True
if options.subtype is None or options.subtype.lower() != 'median':
#Add colorbar
m = cm.ScalarMappable(cmap=cm.jet)
m.set_array(plotc)
m.set_clim(vmin=vmin,vmax=vmax)
cbar= pyplot.colorbar(m,fraction=0.15)
cbar.set_clim((vmin,vmax))
cbar.set_label(zlabel)
if options.subtype is None:
pass
elif options.subtype.lower() == 'disk':
bovy_plot.bovy_text(r'$\mathrm{Disk}$',bottom_right=True,size=_legendsize)
elif options.subtype.lower() == 'halo':
bovy_plot.bovy_text(r'$\mathrm{Halo}$',bottom_right=True,size=_legendsize)
elif options.subtype.lower() == 'bulge':
bovy_plot.bovy_text(r'$\mathrm{Bulge}$',bottom_right=True,size=_legendsize)
else:
#Calc medians
nbins= len(medianvc)
vc= numpy.empty((len(medianrs),nbins))
vc_disk= numpy.empty((len(medianrs),nbins))
vc_bulge= numpy.empty((len(medianrs),nbins))
vc_halo= numpy.empty((len(medianrs),nbins))
for ii in range(nbins):
vc[:,ii]= medianvc[ii]
vc_disk[:,ii]= medianvc_disk[ii]
vc_halo[:,ii]= medianvc_halo[ii]
vc_bulge[:,ii]= medianvc_bulge[ii]
vc= numpy.median(vc,axis=1)*_REFV0
#vcro= vc[numpy.argmin(numpy.fabs(medianrs-1.))]
#vc/= vcro
vc_disk= numpy.median(vc_disk,axis=1)*_REFV0
vc_halo= numpy.median(vc_halo,axis=1)*_REFV0
vc_bulge= numpy.median(vc_bulge,axis=1)*_REFV0
bovy_plot.bovy_print(fig_height=3.87,fig_width=5.)
bovy_plot.bovy_plot(medianrs,vc,'k-',
xlabel=r"$R/R_0$",
ylabel= r"$V_c(R)\ [\mathrm{km\,s}^{-1}]$",
yrange=[0.,1.29*_REFV0],
xrange=[0.,2.])
linedisk= bovy_plot.bovy_plot(medianrs,vc_disk,'k--',
overplot=True)
linedisk[0].set_dashes([5,5])
bovy_plot.bovy_plot(medianrs,vc_halo,'k:',
overplot=True)
linebulge= bovy_plot.bovy_plot(medianrs,vc_bulge,'k--',
overplot=True)
linebulge[0].set_dashes([10,4])
bovy_plot.bovy_text(1.95,120.,r'$\mathrm{Disk}$',size=_legendsize,
horizontalalignment='right')
bovy_plot.bovy_text(1.95,193.,r'$\mathrm{Halo}$',size=_legendsize,
horizontalalignment='right')
bovy_plot.bovy_text(1.95,28.,r'$\mathrm{Bulge}$',size=_legendsize,
horizontalalignment='right')
bovy_plot.bovy_end_print(options.outfilename)
def generate_fakeDFData(options,args):
#Check whether the savefile already exists
if os.path.exists(args[0]):
savefile= open(args[0],'rb')
print "Savefile already exists, not re-sampling and overwriting ..."
return None
#Read the data
print "Reading the data ..."
if options.sample.lower() == 'g':
if options.select.lower() == 'program':
raw= read_gdwarfs(_GDWARFFILE,logg=True,ebv=True,sn=options.snmin,nosolar=True,nocoords=True)
else:
raw= read_gdwarfs(logg=True,ebv=True,sn=options.snmin,nosolar=True,nocoords=True)
elif options.sample.lower() == 'k':
if options.select.lower() == 'program':
raw= read_kdwarfs(_KDWARFFILE,logg=True,ebv=True,sn=options.snmin,nosolar=True,nocoords=True)
else:
raw= read_kdwarfs(logg=True,ebv=True,sn=options.snmin,nosolar=True,
nocoords=True)
if not options.bmin is None:
#Cut on |b|
raw= raw[(numpy.fabs(raw.b) > options.bmin)]
if not options.fehmin is None:
raw= raw[(raw.feh >= options.fehmin)]
if not options.fehmax is None:
raw= raw[(raw.feh < options.fehmax)]
if not options.afemin is None:
raw= raw[(raw.afe >= options.afemin)]
if not options.afemax is None:
raw= raw[(raw.afe < options.afemax)]
if not options.plate is None and not options.loo:
raw= raw[(raw.plate == options.plate)]
elif not options.plate is None:
raw= raw[(raw.plate != options.plate)]
#Bin the data
binned= pixelAfeFeh(raw,dfeh=options.dfeh,dafe=options.dafe)
#Map the bins with ndata > minndata in 1D
fehs, afes= [], []
for ii in range(len(binned.fehedges)-1):
for jj in range(len(binned.afeedges)-1):
data= binned(binned.feh(ii),binned.afe(jj))
if len(data) < options.minndata:
continue
fehs.append(binned.feh(ii))
afes.append(binned.afe(jj))
nabundancebins= len(fehs)
fehs= numpy.array(fehs)
afes= numpy.array(afes)
if not options.singlefeh is None:
if options.loo:
pass
else:
#Set up single feh
indx= binned.callIndx(options.singlefeh,options.singleafe)
if numpy.sum(indx) == 0:
raise IOError("Bin corresponding to singlefeh and singleafe is empty ...")
data= copy.copy(binned.data[indx])
print "Using %i data points ..." % (len(data))
#Bin again
binned= pixelAfeFeh(data,dfeh=options.dfeh,dafe=options.dafe)
fehs, afes= [], []
for ii in range(len(binned.fehedges)-1):
for jj in range(len(binned.afeedges)-1):
data= binned(binned.feh(ii),binned.afe(jj))
if len(data) < options.minndata:
continue
fehs.append(binned.feh(ii))
afes.append(binned.afe(jj))
nabundancebins= len(fehs)
fehs= numpy.array(fehs)
afes= numpy.array(afes)
#Setup the selection function
#Load selection function
plates= numpy.array(list(set(list(raw.plate))),dtype='int') #Only load plates that we use
print "Using %i plates, %i stars ..." %(len(plates),len(raw))
sf= segueSelect(plates=plates,type_faint='tanhrcut',
sample=options.sample,type_bright='tanhrcut',
sn=options.snmin,select=options.select,
indiv_brightlims=options.indiv_brightlims)
platelb= bovy_coords.radec_to_lb(sf.platestr.ra,sf.platestr.dec,
degree=True)
if options.sample.lower() == 'g':
grmin, grmax= 0.48, 0.55
rmin,rmax= 14.50001, 20.199999 #so we don't go out of the range
if options.sample.lower() == 'k':
grmin, grmax= 0.55, 0.75
rmin,rmax= 14.50001, 18.999999
colorrange=[grmin,grmax]
mapfehs= monoAbundanceMW.fehs()
mapafes= monoAbundanceMW.afes()
#Setup params
if not options.init is None:
#Load initial parameters from file
savefile= open(options.init,'rb')
tparams= pickle.load(savefile)
savefile.close()
#Setup the correct form
params= initialize(options,fehs,afes)
params[0:6]= get_dfparams(tparams,options.index,options,log=True)
params[6:11]= tparams[-5:len(tparams)]
else:
params= initialize(options,fehs,afes)
#Setup potential
if (options.potential.lower() == 'flatlog' or options.potential.lower() == 'flatlogdisk') \
and not options.flatten is None:
#Set flattening
potparams= list(get_potparams(params,options,len(fehs)))
potparams[0]= options.flatten
params= set_potparams(potparams,params,options,len(fehs))
pot= setup_potential(params,options,len(fehs))
aA= setup_aA(pot,options)
if not options.multi is None:
binned= fakeDFData_abundance_singles(binned,options,args,fehs,afes)
else:
for ii in range(len(fehs)):
print "Working on population %i / %i ..." % (ii+1,len(fehs))
#Setup qdf
dfparams= get_dfparams(params,ii,options,log=False)
vo= get_vo(params,options,len(fehs))
ro= get_ro(params,options)
if options.dfmodel.lower() == 'qdf':
#Normalize
hr= dfparams[0]/ro
sr= dfparams[1]/vo
sz= dfparams[2]/vo
hsr= dfparams[3]/ro
hsz= dfparams[4]/ro
print hr, sr, sz, hsr, hsz
qdf= quasiisothermaldf(hr,sr,sz,hsr,hsz,pot=pot,aA=aA,cutcounter=True)
#Some more selection stuff
data= binned(fehs[ii],afes[ii])
#feh and color
feh= fehs[ii]
fehrange= [feh-options.dfeh/2.,feh+options.dfeh/2.]
#FeH
fehdist= DistSpline(*numpy.histogram(data.feh,bins=5,
range=fehrange),
xrange=fehrange,dontcuttorange=False)
#Color
colordist= DistSpline(*numpy.histogram(data.dered_g\
-data.dered_r,
bins=9,range=colorrange),
xrange=colorrange)
#Re-sample
binned= fakeDFData(binned,qdf,ii,params,fehs,afes,options,
rmin,rmax,
platelb,
grmin,grmax,
fehrange,
colordist,
fehdist,feh,sf,
mapfehs,mapafes,
ro=None,vo=None)
#Save to new file
fitsio.write(args[0],binned.data)
return None
def plot_DFsingles(options,args):
raw= read_rawdata(options)
#Bin the data
binned= pixelAfeFeh(raw,dfeh=options.dfeh,dafe=options.dafe)
if options.tighten:
tightbinned= pixelAfeFeh(raw,dfeh=options.dfeh,dafe=options.dafe,
fehmin=-1.6,fehmax=0.5,afemin=-0.05,
afemax=0.55)
else:
tightbinned= binned
#Map the bins with ndata > minndata in 1D
fehs, afes= [], []
counter= 0
abindx= numpy.zeros((len(binned.fehedges)-1,len(binned.afeedges)-1),
dtype='int')
for ii in range(len(binned.fehedges)-1):
for jj in range(len(binned.afeedges)-1):
data= binned(binned.feh(ii),binned.afe(jj))
if len(data) < options.minndata:
continue
#print binned.feh(ii), binned.afe(jj), len(data)
fehs.append(binned.feh(ii))
afes.append(binned.afe(jj))
abindx[ii,jj]= counter
counter+= 1
nabundancebins= len(fehs)
fehs= numpy.array(fehs)
afes= numpy.array(afes)
#Load each solutions
sols= []
savename= args[0]
initname= options.init
for ii in range(nabundancebins):
spl= savename.split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % ii
newname+= spl[-1]
savefilename= newname
#Read savefile
try:
savefile= open(savefilename,'rb')
except IOError:
print "WARNING: MISSING ABUNDANCE BIN"
sols.append(None)
else:
sols.append(pickle.load(savefile))
savefile.close()
#Load samples as well
if options.mcsample:
#Do the same for init
spl= initname.split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % ii
newname+= spl[-1]
options.init= newname
mapfehs= monoAbundanceMW.fehs()
mapafes= monoAbundanceMW.afes()
#Now plot
#Run through the pixels and gather
if options.type.lower() == 'afe' or options.type.lower() == 'feh' \
or options.type.lower() == 'fehafe' \
or options.type.lower() == 'afefeh':
plotthis= []
errors= []
else:
plotthis= numpy.zeros((tightbinned.npixfeh(),tightbinned.npixafe()))
for ii in range(tightbinned.npixfeh()):
for jj in range(tightbinned.npixafe()):
data= binned(tightbinned.feh(ii),tightbinned.afe(jj))
if len(data) < options.minndata:
if options.type.lower() == 'afe' or options.type.lower() == 'feh' or options.type.lower() == 'fehafe' \
or options.type.lower() == 'afefeh':
continue
else:
plotthis[ii,jj]= numpy.nan
continue
#Find abundance indx
fehindx= binned.fehindx(tightbinned.feh(ii))#Map onto regular binning
afeindx= binned.afeindx(tightbinned.afe(jj))
solindx= abindx[fehindx,afeindx]
monoabindx= numpy.argmin((tightbinned.feh(ii)-mapfehs)**2./0.01 \
+(tightbinned.afe(jj)-mapafes)**2./0.0025)
if sols[solindx] is None:
if options.type.lower() == 'afe' or options.type.lower() == 'feh' or options.type.lower() == 'fehafe' \
or options.type.lower() == 'afefeh':
continue
else:
plotthis[ii,jj]= numpy.nan
continue
if options.type.lower() == 'q':
s= get_potparams(sols[solindx],options,1)
plotthis[ii,jj]= s[0]
if not options.flatten is None:
plotthis[ii,jj]/= options.flatten
elif options.type.lower() == 'vc':
if options.fixvo:
plotthis[ii,jj]= 1.
else:
s= get_potparams(sols[solindx],options,1)
plotthis[ii,jj]= s[1]
elif options.type.lower() == 'rd':
s= get_potparams(sols[solindx],options,1)
plotthis[ii,jj]= numpy.exp(s[0])
elif options.type.lower() == 'zh':
s= get_potparams(sols[solindx],options,1)
plotthis[ii,jj]= numpy.exp(s[2-(1-(options.fixvo is None))])
elif options.type.lower() == 'ndata':
plotthis[ii,jj]= len(data)
elif options.type.lower() == 'hr':
s= get_dfparams(sols[solindx],0,options)
plotthis[ii,jj]= s[0]*_REFR0
if options.relative:
thishr= monoAbundanceMW.hr(mapfehs[monoabindx],mapafes[monoabindx])
plotthis[ii,jj]/= thishr
elif options.type.lower() == 'sz':
s= get_dfparams(sols[solindx],0,options)
plotthis[ii,jj]= s[2]*_REFV0
if options.relative:
thissz= monoAbundanceMW.sigmaz(mapfehs[monoabindx],mapafes[monoabindx])
plotthis[ii,jj]/= thissz
elif options.type.lower() == 'sr':
s= get_dfparams(sols[solindx],0,options)
plotthis[ii,jj]= s[1]*_REFV0
if options.relative:
thissr= monoAbundanceMW.sigmaz(mapfehs[monoabindx],mapafes[monoabindx])*2.
plotthis[ii,jj]/= thissr
elif options.type.lower() == 'srsz':
#Setup everything
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
aA= setup_aA(pot,options)
dfparams= get_dfparams(sols[solindx],0,options,log=False)
if options.dfmodel.lower() == 'qdf':
#Normalize
hr= dfparams[0]/ro
sr= dfparams[1]/vo
sz= dfparams[2]/vo
hsr= dfparams[3]/ro
hsz= dfparams[4]/ro
#Setup
qdf= quasiisothermaldf(hr,sr,sz,hsr,hsz,pot=pot,
aA=aA,cutcounter=True)
plotthis[ii,jj]= numpy.sqrt(qdf.sigmaR2(1.,1./_REFR0/ro,
ngl=options.ngl,gl=True)\
/qdf.sigmaz2(1.,1./_REFR0/ro,
ngl=options.ngl,gl=True))
elif options.type.lower() == 'outfrac':
s= get_dfparams(sols[solindx],0,options)
plotthis[ii,jj]= s[5]
elif options.type.lower() == 'rhodm':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mwpotential' in options.potential.lower():
plotthis[ii,jj]= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
plotthis[ii,jj]= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskflplhalofixplfixbulgeflat':
plotthis[ii,jj]= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.type.lower() == 'rhoo':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
plotthis[ii,jj]= potential.evaluateDensities(1.,0.,pot)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.type.lower() == 'surfz':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
plotthis[ii,jj]= 2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
elif options.type.lower() == 'surfzdisk':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mpdisk' in options.potential.lower() or 'mwpotential' in options.potential.lower():
plotthis[ii,jj]= 2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot[0])),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
elif options.type.lower() == 'kz':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
plotthis[ii,jj]= numpy.fabs(potential.evaluatezforces(1.,options.height/ro/_REFR0,pot)/2./numpy.pi/4.302*_REFV0**2.*vo**2./_REFR0/ro)
elif options.type.lower() == 'plhalo':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
plotthis[ii,jj]= pot[1].alpha
elif options.type.lower() == 'qhalo':
#Setup potential
s= get_potparams(sols[solindx],options,1)
if options.potential.lower() == 'mpdiskflplhalofixplfixbulgeflat':
plotthis[ii,jj]= s[4]
elif options.type.lower() == 'dlnvcdlnr':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
plotthis[ii,jj]= potential.dvcircdR(pot,1.)
elif options.type.lower() == 'fd':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mwpotential' in options.potential.lower():
plotthis[ii,jj]= (pot[0].vcirc(1.))**2.
elif options.type.lower() == 'fh':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mwpotential' in options.potential.lower():
plotthis[ii,jj]= (pot[1].vcirc(1.))**2.
elif options.type.lower() == 'fb':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mwpotential' in options.potential.lower():
plotthis[ii,jj]= (pot[2].vcirc(1.))**2.
elif options.type.lower() == 'afe' or options.type.lower() == 'feh' or options.type.lower() == 'fehafe' \
or options.type.lower() == 'afefeh':
thisplot=[tightbinned.feh(ii),
tightbinned.afe(jj),
len(data)]
if options.subtype.lower() == 'qvc':
s= get_potparams(sols[solindx],options,1)
thisq= s[0]
if not options.flatten is None:
thisq/= options.flatten
thisvc= s[1]
thisplot.extend([thisq,thisvc])
elif options.subtype.lower() == 'rdzh':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
thisplot.extend([thisrd,thiszh])
elif options.subtype.lower() == 'zhvc':
s= get_potparams(sols[solindx],options,1)
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
thisvc= s[1]*_REFV0
thisplot.extend([thiszh,thisvc])
elif options.subtype.lower() == 'dlnvcdlnrvc':
s= get_potparams(sols[solindx],options,1)
thisslope= s[3-(1-(options.fixvo is None))]/30.
thisvc= s[1]*_REFV0
thisplot.extend([thisslope,thisvc])
elif options.subtype.lower() == 'rdvc':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
thisvc= s[1]*_REFV0
thisplot.extend([thisrd,thisvc])
elif options.subtype.lower() == 'rdplhalo':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
thisplot.extend([thisrd,thisplhalo])
elif options.subtype.lower() == 'dlnvcdlnrplhalo':
s= get_potparams(sols[solindx],options,1)
thisslope= s[3-(1-(options.fixvo is None))]/30.
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
thisplot.extend([thisslope,thisplhalo])
elif options.subtype.lower() == 'dlnvcdlnrzh':
s= get_potparams(sols[solindx],options,1)
thisslope= s[3-(1-(options.fixvo is None))]/30.
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
thisplot.extend([thisslope,thiszh])
elif options.subtype.lower() == 'vc14plhalo':
s= get_potparams(sols[solindx],options,1)
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
thisvc14= potential.vcirc(pot,14./_REFR0/ro)*_REFV0*vo
thisplot.extend([thisplhalo,thisvc14])
elif options.subtype.lower() == 'plhalovc':
s= get_potparams(sols[solindx],options,1)
thisvc= s[1]*_REFV0
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
thisplot.extend([thisplhalo,thisvc])
elif options.subtype.lower() == 'zhplhalo':
s= get_potparams(sols[solindx],options,1)
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
thisplot.extend([thiszh,thisplhalo])
elif options.subtype.lower() == 'rhodmzh':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
if 'mwpotential' in options.potential.lower():
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhodm,thiszh])
elif options.subtype.lower() == 'rhodmsurfz':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
thissurfz= 2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
if 'mwpotential' in options.potential.lower():
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhodm,thissurfz])
elif options.subtype.lower() == 'surfzzh':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
thissurfz= 2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
thisplot.extend([thissurfz,thiszh])
elif options.subtype.lower() == 'rhoozh':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
thisrhoo= potential.evaluateDensities(1.,0.,pot)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhoo,thiszh])
elif options.subtype.lower() == 'rhodmvc':
s= get_potparams(sols[solindx],options,1)
thisvc= s[1]*_REFV0
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mwpotential' in options.potential.lower():
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhodm,thisvc])
elif options.subtype.lower() == 'rhodmrd':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
thisrdh= numpy.exp(s[0])
if 'mwpotential' in options.potential.lower():
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhodm,thisrd])
elif options.subtype.lower() == 'rhodmplhalo':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
if 'mwpotential' in options.potential.lower():
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhodm,thisplhalo])
plotthis.append(thisplot)
#Set up plot
if options.type.lower() == 'q':
if not options.flatten is None:
vmin, vmax= 0.9, 1.1
zlabel=r'$\mathrm{flattening}\ q / %.1f$' % options.flatten
elif 'real' in options.outfilename.lower():
vmin, vmax= 0.9, 1.1
medianq= numpy.median(plotthis[numpy.isfinite(plotthis)])
plotthis/= medianq
zlabel=r'$\mathrm{flattening}\ q / %.2f$' % medianq
else:
vmin, vmax= 0.5, 1.2
zlabel=r'$\mathrm{flattening}\ q$'
elif options.type.lower() == 'vc':
vmin, vmax= 0.95, 1.05
zlabel=r'$V_c / %i\ \mathrm{km\,s}^{-1}$' % int(_REFV0)
if 'real' in options.outfilename.lower():
medianvc= numpy.median(plotthis[numpy.isfinite(plotthis)])
plotthis/= medianvc
zlabel=r'$V_c / %i\ \mathrm{km\,s}^{-1}$' % int(_REFV0*medianvc)
elif options.type.lower() == 'rhodm':
vmin, vmax= 0.00, 0.02
zlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.type.lower() == 'rhoo':
vmin, vmax= 0.00, 0.2
zlabel=r'$\rho(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.type.lower() == 'surfz':
vmin, vmax= 50.,120.
zlabel=r'$\Sigma(%.1f\,\mathrm{kpc};R_0)\ [M_\odot\,\mathrm{pc}^{-2}]$' % options.height
elif options.type.lower() == 'surfzdisk':
vmin, vmax= 20.,90.
zlabel=r'$\Sigma_{\mathrm{disk}}(%.1f\,\mathrm{kpc};R_0)\ [M_\odot\,\mathrm{pc}^{-2}]$' % options.height
elif options.type.lower() == 'kz':
vmin, vmax= 50.,120.
zlabel=r'$K_Z(%.1f\,\mathrm{kpc};R_0)\ [M_\odot\,\mathrm{pc}^{-2}]$' % options.height
elif options.type.lower() == 'dlnvcdlnr':
vmin, vmax= -0.3,0.2
zlabel=r'$\frac{\mathrm{d} \ln V_c}{\mathrm{d} \ln R}$'
elif options.type.lower() == 'fd':
vmin, vmax= 0.00, 1.
zlabel=r'$V_{c,\mathrm{disk}} / V_c\,(R_0)$'
elif options.type.lower() == 'fh':
vmin, vmax= 0.00, 1.
zlabel=r'$V_{c,\mathrm{halo}} / V_c\,(R_0)$'
elif options.type.lower() == 'fb':
vmin, vmax= 0.00, .1
zlabel=r'$V_{c,\mathrm{halo}} / V_c\,(R_0)$'
elif options.type.lower() == 'rd':
vmin, vmax= 0.2, 0.6
zlabel=r'$R_d / R_0$'
elif options.type.lower() == 'zh':
vmin, vmax= 0.0125, 0.075
zlabel=r'$z_h / R_0$'
elif options.type.lower() == 'plhalo':
vmin, vmax= 0.0, 2.
zlabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
elif options.type.lower() == 'qhalo':
vmin, vmax= 0.4, 1.15
zlabel=r'$q_\Phi^{\mathrm{halo}}$'
elif options.type.lower() == 'ndata':
vmin, vmax= numpy.nanmin(plotthis), numpy.nanmax(plotthis)
zlabel=r'$N_\mathrm{data}$'
elif options.type == 'hr':
if options.relative:
vmin, vmax= 0.8, 1.2
zlabel=r'$\mathrm{input / output\ radial\ scale\ length}$'
else:
vmin, vmax= 1.35,4.5
zlabel=r'$\mathrm{model\ radial\ scale\ length\ [kpc]}$'
elif options.type == 'sz':
if options.relative:
vmin, vmax= 0.8, 1.2
zlabel= r'$\mathrm{input / output\ model}\ \sigma_z$'
else:
vmin, vmax= 10.,60.
zlabel= r'$\mathrm{model}\ \sigma_z\ [\mathrm{km\ s}^{-1}]$'
elif options.type == 'sr':
if options.relative:
vmin, vmax= 0.8, 1.2
zlabel= r'$\mathrm{input/output\ model}\ \sigma_R$'
else:
vmin, vmax= 10.,60.
zlabel= r'$\mathrm{model}\ \sigma_R\ [\mathrm{km\ s}^{-1}]$'
elif options.type == 'srsz':
vmin, vmax= 0.5,2.
zlabel= r'$\sigma_R/\sigma_z\ (R_0,1\,\mathrm{kpc})$'
elif options.type == 'outfrac':
vmin, vmax= 0., 1.
zlabel= r'$\mathrm{relative\ number\ of\ outliers}$'
elif options.type == 'afe':
vmin, vmax= 0.0,.5
zlabel=r'$[\alpha/\mathrm{Fe}]$'
elif options.type == 'feh':
vmin, vmax= -1.6,0.4
zlabel=r'$[\mathrm{Fe/H}]$'
elif options.type == 'fehafe':
vmin, vmax= -.7,.7
zlabel=r'$[\mathrm{Fe/H}]-[\mathrm{Fe/H}]_{1/2}([\alpha/\mathrm{Fe}])$'
elif options.type == 'afefeh':
vmin, vmax= -.15,.15
zlabel=r'$[\alpha/\mathrm{Fe}]-[\alpha/\mathrm{Fe}]_{1/2}([\mathrm{Fe/H}])$'
if options.tighten:
xrange=[-1.6,0.5]
yrange=[-0.05,0.55]
else:
xrange=[-2.,0.5]
yrange=[-0.2,0.6]
#Now plot
if options.type.lower() == 'afe' or options.type.lower() == 'feh' \
or options.type.lower() == 'fehafe':
#Gather everything
afe, feh, ndata, x, y= [], [], [], [], []
for ii in range(len(plotthis)):
afe.append(plotthis[ii][1])
feh.append(plotthis[ii][0])
ndata.append(plotthis[ii][2])
x.append(plotthis[ii][3])
y.append(plotthis[ii][4])
afe= numpy.array(afe)
feh= numpy.array(feh)
ndata= numpy.array(ndata)
x= numpy.array(x)
y= numpy.array(y)
#Process ndata
ndata= ndata**.5
ndata= ndata/numpy.median(ndata)*35.
if options.type.lower() == 'afe':
plotc= afe
elif options.type.lower() == 'feh':
plotc= feh
elif options.type.lower() == 'afefeh':
#Go through the bins to determine whether feh is high or low for this alpha
plotc= numpy.zeros(len(afe))
for ii in range(tightbinned.npixfeh()):
fehbin= ii
data= tightbinned.data[(tightbinned.data.feh > tightbinned.fehedges[fehbin])\
*(tightbinned.data.feh <= tightbinned.fehedges[fehbin+1])]
medianafe= numpy.median(data.afe)
for jj in range(len(afe)):
if feh[jj] == tightbinned.feh(ii):
plotc[jj]= afe[jj]-medianafe
else:
#Go through the bins to determine whether feh is high or low for this alpha
plotc= numpy.zeros(len(feh))
for ii in range(tightbinned.npixafe()):
afebin= ii
data= tightbinned.data[(tightbinned.data.afe > tightbinned.afeedges[afebin])\
*(tightbinned.data.afe <= tightbinned.afeedges[afebin+1])]
medianfeh= numpy.median(data.feh)
for jj in range(len(feh)):
if afe[jj] == tightbinned.afe(ii):
plotc[jj]= feh[jj]-medianfeh
onedhists=False
if options.subtype.lower() == 'qvc':
if not options.flatten is None:
xrange= [0.9,1.1]
xlabel=r'$\mathrm{flattening}\ q / %.1f$' % options.flatten
elif 'real' in options.outfilename.lower():
xrange= [0.9,1.1]
medianq= numpy.median(x[numpy.isfinite(x)])
x/= medianq
xlabel=r'$\mathrm{flattening}\ q / %.2f$' % medianq
else:
xrange= [0.5, 1.2]
xlabel=r'$\mathrm{flattening}\ q$'
yrange= [0.95, 1.05]
ylabel=r'$V_c / %i\ \mathrm{km\,s}^{-1}$' % int(_REFV0)
if 'real' in options.outfilename.lower():
medianvc= numpy.median(y[numpy.isfinite(y)])
y/= medianvc
ylabel=r'$V_c / %i\ \mathrm{km\,s}^{-1}$' % int(_REFV0*medianvc)
elif options.subtype.lower() == 'rdzh':
yrange= [0.0125,0.1]
xrange= [0.2,0.8]
xlabel=r'$R_d / R_0$'
ylabel=r'$z_h / R_0$'
elif options.subtype.lower() == 'rdplhalo':
yrange= [0.,2.]
xrange= [0.2,0.8]
xlabel=r'$R_d / R_0$'
ylabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
elif options.subtype.lower() == 'vc14plhalo':
yrange= [210.,280.]
xrange= [0.,2.]
xlabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
ylabel=r'$V_c (R=14\,\mathrm{kpc})\ [\mathrm{km\,s}^{-1}$]'
elif options.subtype.lower() == 'zhplhalo':
yrange= [0.,2.]
xrange= [0.0125,0.1]
ylabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
xlabel=r'$z_h / R_0$'
elif options.subtype.lower() == 'rhodmplhalo':
xrange= [0.,0.02]
yrange= [0.,2.]
ylabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
xlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'rhodmzh':
yrange= [0.0125,0.1]
xrange= [0.,0.02]
ylabel=r'$z_h / R_0$'
xlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'rhoozh':
yrange= [0.0125,0.1]
xrange= [0.,0.2]
ylabel=r'$z_h / R_0$'
xlabel=r'$\rho(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'surfzzh':
yrange= [0.0125,0.1]
xrange= [50.+20.*(options.height-1.1),120.+20.*(options.height-1.1)]
ylabel=r'$z_h / R_0$'
xlabel=r'$\Sigma(%.1f\,\mathrm{kpc};R_0)\ [M_\odot\,\mathrm{pc}^{-2}]$' % options.height
elif options.subtype.lower() == 'rhodmsurfz':
yrange= [50.+20.*(options.height-1.1),120.+20.*(options.height-1.1)]
xrange= [0.,0.02]
ylabel=r'$\Sigma(%.1f\,\mathrm{kpc};R_0)\ [M_\odot\,\mathrm{pc}^{-2}]$' % options.height
xlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'rhodmrd':
yrange= [0.2,0.8]
xrange= [0.,0.02]
ylabel=r'$R_d / R_0$'
xlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'rdvc':
yrange= [210.,250.]
xrange= [0.2,0.8]
xlabel=r'$R_d / R_0$'
ylabel=r'$V_c\ [\mathrm{km\,s}^{-1}]$'
elif options.subtype.lower() == 'zhvc':
yrange= [210.,250.]
xrange= [0.0125,0.1]
xlabel=r'$z_h / R_0$'
ylabel=r'$V_c\ [\mathrm{km\,s}^{-1}]$'
elif options.subtype.lower() == 'dlnvcdlnrvc':
yrange= [210.,250.]
xrange= [-0.2,0.07]
xlabel=r'$\mathrm{d}\ln V_c / \mathrm{d}\ln R\, (R_0)$'
ylabel=r'$V_c\ [\mathrm{km\,s}^{-1}]$'
onedhists=True
elif options.subtype.lower() == 'dlnvcdlnrplhalo':
yrange= [0.,2.]
ylabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
xrange= [-0.2,0.07]
xlabel=r'$\mathrm{d}\ln V_c / \mathrm{d}\ln R\, (R_0)$'
elif options.subtype.lower() == 'dlnvcdlnrzh':
yrange= [0.0125,0.1]
ylabel=r'$z_h / R_0$'
xrange= [-0.2,0.07]
xlabel=r'$\mathrm{d}\ln V_c / \mathrm{d}\ln R\, (R_0)$'
elif options.subtype.lower() == 'rhodmvc':
yrange= [210.,250.]
xrange= [0.,0.02]
ylabel=r'$V_c\ [\mathrm{km\,s}^{-1}]$'
xlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'plhalovc':
yrange= [210.,250.]
xrange= [0.,2.]
xlabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
ylabel=r'$V_c\ [\mathrm{km\,s}^{-1}$]'
bovy_plot.bovy_print(fig_height=3.87,fig_width=5.)
ax= bovy_plot.bovy_plot(x,y,
s=ndata,c=plotc,
cmap='jet',
xlabel=xlabel,ylabel=ylabel,
clabel=zlabel,
xrange=xrange,yrange=yrange,
vmin=vmin,vmax=vmax,
scatter=True,edgecolors='none',
colorbar=True-onedhists,
onedhists=onedhists,
onedhistxnormed=onedhists,
onedhistynormed=onedhists,
bins=15)
if onedhists:
axS, axx, axy= ax
if options.subtype.lower() == 'dlnvcdlnrvc':
#Plot prior on one-d axes
sb= numpy.linspace(-0.2,0.0399,1001)
fsb= numpy.exp(numpy.log((0.04-sb)/0.04)-(0.04-sb)/0.04)
fsb/= numpy.sum(fsb)*(sb[1]-sb[0])
axx.plot(sb,fsb,'-',color='0.65')
tvc= numpy.linspace(150.,350.,1001)
fvc= numpy.exp(-(tvc-225.)**2./2./15.**2.)
fvc/= numpy.sum(fvc)*(tvc[1]-tvc[0])
axy.plot(fvc,tvc,'-',color='0.65')
else:
bovy_plot.bovy_print()
bovy_plot.bovy_dens2d(plotthis.T,origin='lower',cmap='jet',
interpolation='nearest',
xlabel=r'$[\mathrm{Fe/H}]$',
ylabel=r'$[\alpha/\mathrm{Fe}]$',
zlabel=zlabel,
xrange=xrange,yrange=yrange,
vmin=vmin,vmax=vmax,
contours=False,
colorbar=True,shrink=0.78)
if options.type.lower() == 'q' or options.type.lower() == 'vc' \
or options.relative or options.type.lower() == 'rd' \
or options.type.lower() == 'fd' \
or options.type.lower() == 'fh' \
or options.type.lower() == 'fb' \
or options.type.lower() == 'plhalo' \
or options.type.lower() == 'surfz' \
or options.type.lower() == 'surfzdisk' \
or options.type.lower() == 'rhoo' \
or options.type.lower() == 'qhalo' \
or options.type.lower() == 'kz':
bovy_plot.bovy_text(r'$\mathrm{median} = %.2f \pm %.2f$' % (numpy.median(plotthis[numpy.isfinite(plotthis)]),
1.4826*numpy.median(numpy.fabs(plotthis[numpy.isfinite(plotthis)]-numpy.median(plotthis[numpy.isfinite(plotthis)])))),
bottom_left=True,size=14.)
if options.type.lower() == 'zh' or options.type.lower() == 'rhodm':
bovy_plot.bovy_text(r'$\mathrm{median} = %.4f \pm %.4f$' % (numpy.median(plotthis[numpy.isfinite(plotthis)]),
1.4826*numpy.median(numpy.fabs(plotthis[numpy.isfinite(plotthis)]-numpy.median(plotthis[numpy.isfinite(plotthis)])))),
bottom_left=True,size=14.)
bovy_plot.bovy_end_print(options.outfilename)
return None
def calcDFResults(options,args,boot=True,nomedian=False):
if len(args) == 2 and options.sample == 'gk':
toptions= copy.copy(options)
toptions.sample= 'g'
toptions.select= 'all'
outg= calcDFResults(toptions,[args[0]],boot=boot,nomedian=True)
toptions.sample= 'k'
toptions.select= 'program'
outk= calcDFResults(toptions,[args[1]],boot=boot,nomedian=True)
#Combine
out= {}
for k in outg.keys():
valg= outg[k]
valk= outk[k]
val= numpy.zeros(len(valg)+len(valk))
val[0:len(valg)]= valg
val[len(valg):len(valg)+len(valk)]= valk
out[k]= val
if nomedian: return out
else: return add_median(out,boot=boot)
raw= read_rawdata(options)
#Bin the data
binned= pixelAfeFeh(raw,dfeh=options.dfeh,dafe=options.dafe)
tightbinned= binned
#Map the bins with ndata > minndata in 1D
fehs, afes= [], []
counter= 0
abindx= numpy.zeros((len(binned.fehedges)-1,len(binned.afeedges)-1),
dtype='int')
for ii in range(len(binned.fehedges)-1):
for jj in range(len(binned.afeedges)-1):
data= binned(binned.feh(ii),binned.afe(jj))
if len(data) < options.minndata:
continue
#print binned.feh(ii), binned.afe(jj), len(data)
fehs.append(binned.feh(ii))
afes.append(binned.afe(jj))
abindx[ii,jj]= counter
counter+= 1
nabundancebins= len(fehs)
fehs= numpy.array(fehs)
afes= numpy.array(afes)
#Load each of the solutions
sols= []
chi2s= []
savename= args[0]
initname= options.init
for ii in range(nabundancebins):
spl= savename.split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % ii
newname+= spl[-1]
savefilename= newname
#Read savefile
try:
savefile= open(savefilename,'rb')
except IOError:
print "WARNING: MISSING ABUNDANCE BIN"
sols.append(None)
chi2s.append(None)
else:
sols.append(pickle.load(savefile))
chi2s.append(pickle.load(savefile))
savefile.close()
#Load samples as well
if options.mcsample:
#Do the same for init
spl= initname.split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % ii
newname+= spl[-1]
options.init= newname
mapfehs= monoAbundanceMW.fehs()
mapafes= monoAbundanceMW.afes()
#Now plot
#Run through the pixels and gather
fehs= []
afes= []
ndatas= []
zmedians= []
#Basic parameters
hrs= []
srs= []
szs= []
hsrs= []
hszs= []
outfracs= []
rds= []
rdexps= []
vcs= []
zhs= []
zhexps= []
dlnvcdlnrs= []
plhalos= []
rorss= []
dvts= []
#derived parameters
surfzs= []
surfz800s= []
surfzdisks= []
massdisks= []
rhoos= []
rhooalts= []
rhodms= []
vcdvcros= []
vcdvcs= []
vescs= []
mloglikemins= []
for ii in range(tightbinned.npixfeh()):
for jj in range(tightbinned.npixafe()):
data= binned(tightbinned.feh(ii),tightbinned.afe(jj))
if len(data) < options.minndata:
continue
#Find abundance indx
fehindx= binned.fehindx(tightbinned.feh(ii))#Map onto regular binning
afeindx= binned.afeindx(tightbinned.afe(jj))
solindx= abindx[fehindx,afeindx]
monoabindx= numpy.argmin((tightbinned.feh(ii)-mapfehs)**2./0.01 \
+(tightbinned.afe(jj)-mapafes)**2./0.0025)
if sols[solindx] is None:
continue
try:
pot= setup_potential(sols[solindx],options,1,interpDens=True,
interpdvcircdr=True,returnrawpot=True)
except RuntimeError:
print "A bin has an unphysical potential ..."
continue
# if 'dpdisk' in options.potential.lower():
# try:
# rawpot= setup_potential(sols[solindx],options,1,
# returnrawpot=True)
# except RuntimeError:
# print "A bin has an unphysical potential ..."
# continue
fehs.append(tightbinned.feh(ii))
afes.append(tightbinned.afe(jj))
zmedians.append(numpy.median(numpy.fabs(data.zc+_ZSUN)))
#vc
s= get_potparams(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.fixvo:
vcs.append(options.fixvo*_REFV0)
else:
vcs.append(s[1]*_REFV0)
#rd
rds.append(numpy.exp(s[0]))
#zh
zhs.append(numpy.exp(s[2-(1-(options.fixvo is None))]))
#rdexp & zhexp
if options.sample == 'g': tz= 1.1/_REFR0/ro
elif options.sample == 'k': tz= 0.84/_REFR0/ro
if 'mpdisk' in options.potential.lower() or 'mwpotential' in options.potential.lower():
mp= potential.MiyamotoNagaiPotential(a=rds[-1],b=zhs[-1])
#rdexp
f= mp.dens(1.,0.125)
dr= 10.**-3.
df= (mp.dens(1.+dr/2.,0.125)-mp.dens(1.-dr/2.,0.125))/dr
rdexps.append(-f/df)
#zhexp
f= mp.dens(1.,tz)
dz= 10.**-3.
df= (mp.dens(1.,tz+dz/2.)-mp.dens(1.,tz-dz/2.))/dz
zhexps.append(-f/df)
elif 'dpdisk' in options.potential.lower():
rdexps.append(numpy.exp(s[0]))
zhexps.append(numpy.exp(s[2-(1-(options.fixvo is None))]))
#ndata
ndatas.append(len(data))
#hr
dfparams= get_dfparams(sols[solindx],0,options)
if options.relative:
thishr= monoAbundanceMW.hr(mapfehs[monoabindx],mapafes[monoabindx])
hrs.append(dfparams[0]*_REFR0/thishr)
else:
hrs.append(dfparams[0]*_REFR0)
#sz
if options.relative:
thissz= monoAbundanceMW.sigmaz(mapfehs[monoabindx],mapafes[monoabindx])
szs.append(dfparams[2]*_REFV0/thissz)
else:
szs.append(dfparams[2]*_REFV0)
#sr
if options.relative:
thissr= monoAbundanceMW.sigmaz(mapfehs[monoabindx],mapafes[monoabindx])*2.#BOVY: UPDATE
srs.append(dfparams[1]*_REFV0/thissr)
else:
srs.append(dfparams[1]*_REFV0)
#hsr
hsrs.append(dfparams[3]*_REFR0)
#hsz
hszs.append(dfparams[4]*_REFR0)
#outfrac
outfracs.append(dfparams[5])
#rhodm
#Setup potential
vo= get_vo(sols[solindx],options,1)
if 'mwpotential' in options.potential.lower():
rhodms.append(pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.)
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
rhodms.append(pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.)
elif options.potential.lower() == 'mpdiskflplhalofixplfixbulgeflat':
rhodms.append(pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.)
elif options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
rhodms.append(pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.)
#rhoo
rhoos.append(potential.evaluateDensities(1.,0.,pot)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.)
#surfz
surfzs.append(2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro)
#surfz800
surfz800s.append(2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot)),0.,0.8/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro)
#surzdisk
if 'mpdisk' in options.potential.lower() or 'mwpotential' in options.potential.lower():
surfzdisks.append(2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot[0])),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro)
surfzdiskzm= 2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot[0])),0.,tz)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
elif 'dpdisk' in options.potential.lower():
surfzdisks.append(2.*pot[0].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.*zhexps[-1]*ro*_REFR0*1000.)
#rhooalt
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
rhooalts.append(rhoos[-1]-pot[0].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.+surfzdiskzm/2./zhexps[-1]/ro/_REFR0/1000./(1.-numpy.exp(-tz/zhexps[-1])))
elif options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
rhooalts.append(rhoos[-1])
#massdisk
if options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
rhod= pot[0].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
else:
rhod= surfzdiskzm/2./zhexps[-1]/ro/_REFR0/1000./(1.-numpy.exp(-tz/zhexps[-1]))
massdisks.append(rhod*2.*zhexps[-1]*numpy.exp(1./rdexps[-1])*rdexps[-1]**2.*2.*numpy.pi*(ro*_REFR0)**3./10.)
#plhalo
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
plhalos.append(pot[1].alpha)
plhalos.append((1.-pot[1].alpha)/(pot[1].alpha-3.))
elif options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
plhalos.append(pot[1].alpha)
rorss.append((1.-pot[1].alpha)/(pot[1].alpha-3.))
#dlnvcdlnr
if options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
dlnvcdlnrs.append(potential.dvcircdR(pot,1.))
else:
dlnvcdlnrs.append(potential.dvcircdR(pot,1.))
#vcdvc
if options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
vcdvcros.append(pot[0].vcirc(1.)/potential.vcirc(pot,1.))
vcdvcs.append(pot[0].vcirc(2.2*rdexps[-1])/potential.vcirc(pot,2.2*rdexps[-1]))
else:
vcdvcros.append(pot[0].vcirc(1.)/potential.vcirc(pot,1.))
vcdvcs.append(pot[0].vcirc(2.2*rdexps[-1])/potential.vcirc(pot,2.2*rdexps[-1]))
#mloglike
mloglikemins.append(chi2s[solindx])
#escape velocity
vescs.append(potential.vesc(pot,1.)*_REFV0)
if options.fitdvt:
dvts.append(sols[solindx][0])
#Gather
fehs= numpy.array(fehs)
afes= numpy.array(afes)
zmedians= numpy.array(zmedians)
ndatas= numpy.array(ndatas)
#Basic parameters
hrs= numpy.array(hrs)
srs= numpy.array(srs)
szs= numpy.array(szs)
hsrs= numpy.array(hsrs)
hszs= numpy.array(hszs)
outfracs= numpy.array(outfracs)
vcs= numpy.array(vcs)
rds= numpy.array(rds)
zhs= numpy.array(zhs)
rdexps= numpy.array(rdexps)
zhexps= numpy.array(zhexps)
dlnvcdlnrs= numpy.array(dlnvcdlnrs)
plhalos= numpy.array(plhalos)
rorss= numpy.array(rorss)
if options.fitdvt:
dvts= numpy.array(dvts)
#derived parameters
surfzs= numpy.array(surfzs)
surfz800s= numpy.array(surfz800s)
surfzdisks= numpy.array(surfzdisks)
massdisks= numpy.array(massdisks)
rhoos= numpy.array(rhoos)
rhooalts= numpy.array(rhooalts)
rhodms= numpy.array(rhodms)
vcdvcros= numpy.array(vcdvcros)
vcdvcs= numpy.array(vcdvcs)
rexps= numpy.sqrt(2.)*(rds+zhs)/2.2
mloglikemins= numpy.array(mloglikemins)
vescs= numpy.array(vescs)
#Load into dictionary
out= {}
out['feh']= fehs
out['afe']= afes
out['zmedian']= zmedians
out['ndata']= ndatas
out['hr']= hrs
out['sr']= srs
out['sz']= szs
out['hsr']= hsrs
out['hsz']= hszs
out['outfrac']= outfracs
out['vc']= vcs
out['rd']= rds
out['zh']= zhs
out['rdexp']= rdexps
out['zhexp']= zhexps
out['dlnvcdlnr']= dlnvcdlnrs
out['plhalo']= plhalos
out['rors']= rorss
out['surfz']= surfzs
out['surfz800']= surfz800s
out['surfzdisk']= surfzdisks
out['massdisk']= massdisks
out['rhoo']= rhoos
out['rhooalt']= rhooalts
out['rhodm']= rhodms
out['vcdvc']= vcdvcs
out['vcdvcro']= vcdvcros
out['rexp']= rexps
out['mloglikemin']= mloglikemins
out['vesc']= vescs
if options.fitdvt:
out['dvt']= dvts
if nomedian: return out
else: return add_median(out,boot=boot)
