def plot_analytic(r0, prof, pop=0):
if gp.investigate == 'gaia':
if prof=="rho":
analytic = ga.rhogaiatot_3D(r0)
elif prof=="nr":
analytic = ga.nrgaiatot_3D(r0)
elif prof=="beta":
analytic = ga.betagaia(r0)
elif prof=="betastar":
b = ga.betagaia(r0)
analytic = b/(2.-b)
elif prof=="nu":
analytic_3D = ga.nugaiatot_3D(r0)
analytic = rho_INT_Rho(r0, analytic_3D)
elif prof=="sig":
analytic = 0.*r0 # TODO
elif gp.investigate == 'walk':
if prof=='rho':
analytic = ga.rhowalk_3D(r0)[pop]
elif prof=='nr':
analytic = ga.rhowalk_3D(r0)[pop] # TODO
elif prof=='beta':
analytic = ga.walker_delta(pop, r0) # TODO
elif prof=='betastar': # TODO
b = ga.walker_delta(pop, r0)
analytic = b/(2.-b)
elif prof=='nu': # TODO: mass ratio M_tracer/M_DM
pdb.set_trace()
analytic_3D = ga.rhowalk_3D(r0)[pop]
analytic = rho_INT_Rho(r0, analytic_3D)
elif prof=='sig':
analytic = 0.*r0 # TODO
gpl.plot(r0, analytic, 'b')
return analytic
def plotGraph():
fig = figure()
xlabel(r'$r\quad[\mathrm{pc}]$')
if prof == 'M':
ylabel(r'$M\quad[\mathrm{M}_{\odot}]$') #[10^5 M_{\odot}]')
elif prof == 'rho':
ylabel(r'$\rho\quad[\mathrm{M}_{\odot}/\mathrm{pc}^3]$') #[10^5 M_{\odot}]')
elif prof=='delta1' or prof == 'delta2':
ylabel(r'$\beta$') #[10^5 M_{\odot}]')
elif prof == 'nu1':
ylabel(r'$\nu_1$')
elif prof == 'sig1':
ylabel(r'$\sigma_1$')
fill_between(radsc, M95lo*Msc, M95hi*Msc, color='black',alpha=0.2,lw=1)
fill_between(radsc, M68lo*Msc, M68hi*Msc, color='black',alpha=0.4,lw=1)
plot(radsc,Mmedi*Msc,'r',lw=1)
r1 = halflightradius(gp.case)
if prof == 'rho' or prof == 'M' or prof=='beta1' or prof=='nu1' or prof=='sig1':
axvline(x=r1, visible=True)
# theoretical model
if prof == 'M':
plot(radsc,Msc*Mwalkertot(radsc),'--',color='black',lw=1)
elif prof == 'rho':
plot(radsc,Msc*rhogaiatot_3D(radsc),'--',color='black',lw=1) # 7 co
# plot lowest profile as well
# plot(radsc,Msc*profs[0],'.',color='orange',lw=1)
elif prof == 'beta1':
plot(radsc, betagaia(radsc), color='black')
elif prof == 'sig1':
rad, dummy, dummy, sig1, sigerr1 = gh.readcol5(gp.files.sigfiles[1])
rad *= gp.Rscale[1]
sig1*=gp.maxvlos[1]
sigerr1*=gp.maxvlos[1]
# plot(rad, sig1, '--', color='b', lw=2)
# plot(rad, sig1-sigerr1, '--', color='b', lw=1)
# plot(rad, sig1+sigerr1, '--', color='b', lw=1)
fill_between(rad, sig1-sigerr1, sig1+sigerr1, color='blue', alpha=0.3,lw=0)
elif prof == 'nu1':
rad, dummy, dummy, nu1, nuerr1 = gh.readcol5(gp.files.nufiles[1])
rad *= gp.Rscale[1]
# TODO: missing factor 10 somewhere..
pdb.set_trace()
nu1 *= gp.Nu0pc[1]; nuerr1 *= gp.Nu0pc[1]
fill_between(rad, nu1-nuerr1, nu1+nuerr1, color='blue', alpha=0.3,lw=0)
if prof!='delta1' and prof!='delta2' and prof != 'sig1' and prof != 'nu1':
# xscale('log')
yscale('log')
if prof == 'nu1':
yscale('log')
if prof == "M" or prof == 'rho':
xscale('log')
#xlim([100.,1200.]); ylim([0.005,1.5])
# if prof == 'delta1':
# xlim([100.,1200.]); ylim([-0.15,0.9])
return fig