def compare_nu(pop, dat, err):
# pop \in {1,2} gives population
# if dat == True: return data; else: model (possibly projected)
# if err == True: return data error instead
if (not dat) and err:
print('wrong use of compare_nu, error only given for data, not model')
exit(1)
ret = []
if dat:
if gp.geom == 'disc':
ret = gp.ipol.nudat1 if pop == 1 else gp.dat.nudat2
if err:
ret = gp.ipol.nuerr1 if pop == 1 else gp.ipol.nuerr2
elif gp.geom == 'sphere':
ret = gp.ipol.nudat1_2D if pop == 1 else gp.dat.nudat2_2D
if err:
ret = gp.ipol.nuerr1_2D if pop == 1 else gp.ipol.nuerr2_2D
else: # [model]
if gp.geom == 'disc':
ret = gp.ipol.nudat1 if pop == 1 else gp.ipol.nudat2
if err:
ret = gp.ipol.nuerr1 if pop == 1 else gp.ipol.nuerr2
elif gp.geom == 'sphere':
ret = rho_INT_Rho(gp.xipol,gp.ipol.nudat1) if pop == 1 else\
rho_Int_Rho(gp.ipol.nudat2)
if err:
# TODO: does that make sense? what do we want to compare to here?
ret = rho_INT_Rho(gp.xipol,gp.ipol.nuerr1) if pop == 1 else\
rho_Int_Rho(gp.ipol.nuerr2)
return ret
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 Rhowalk(rad):
rhodm, rhostar1, rhostar2 = rhowalk(rad) # 3* [msun/pc^3]
surfdm = rho_INT_Rho(rad, rhodm) # [msun/pc^2]
surfstar1 = rho_INT_Rho(rad, rhostar1) # [msun/pc^2]
surfstar2 = rho_INT_Rho(rad, rhostar2) # [msun/pc^2]
return surfdm, surfstar1, surfstar2 # 3* [msun/pc^2]
def sig_kap_los(dens_r, nu_r, beta_r):
r0 = gp.xipol[:]
# TODO: fix spline warnings
surfden = rho_INT_Rho(r0, nu_r) # or INTIPOL
# takes [pc], [munit/pc^3], gives back [munit/pc^2]
# gpl.start()
# pdb.set_trace()
# gpl.plot(r0, surfden,'red')
# gpl.plot(r0, Sigma_anf(r0))
# Calculate density and M force:
intbeta = ant_intbeta(r0, beta_r) # [1]
# TODO:pdb.set_trace() get splines correctly
siglos2surf, kaplos4surf = ant_sigkaplos2surf(r0, beta_r, intbeta, dens_r, nu_r)
# takes [pc], [1*pc], [munit], [munit/pc^3], gives back [(km/s)^2], [1]
siglos2 = siglos2surf / surfden # [(km/s)^2]
siglos = np.sqrt(siglos2) # [km/s]
# gpl.start(); pdb.set_trace()
# gpl.plot(r0,sig_los_anf(r0),lw=2)
if gp.usekappa:
kaplos4 = kaplos4surf / surfden
# takes [munit/pc^2 (km/s)^2], gives back [(km/s)^2]
kaplos = kaplos4 / (siglos2 ** 2)
# - 3.0 # subtract 3.0 for Gaussian distribution in Fisher version.
else:
kaplos = 3.0 * np.ones(len(siglos))
return siglos, kaplos # [km/s], [1]
def calc_chi2():
numodel1 = rho_INT_Rho(gp.xipol,gp.nu1_x) if gp.geom=='sphere' else gp.nu1_x
nudata1 = compare_nu(1,True,False)
nuerr1 = compare_nu(1,True,True)
gp.chi2t_nu1 = chi2red(numodel1, nudata1, nuerr1, gp.dof)
gp.chi2t_nu = gp.chi2t_nu1
if gp.analytic:
gp.chi2t_sig1 = chi2red(gp.sig1_x,rho_anf(gp.xipol),\
gp.ipol.sigerr1,gp.dof)
gp.chi2t_kap1 = chi2red(gp.kap1_x,gp.ipol.kapdat1,\
gp.ipol.kaperr1,gp.dof)
else:
gp.chi2t_sig1 = chi2red(gp.sig1_x,gp.ipol.sigdat1,\
gp.ipol.sigerr1,gp.dof)
gp.chi2t_kap1 = chi2red(gp.kap1_x,gp.ipol.kapdat1,\
gp.ipol.kaperr1,gp.dof)
gp.chi2t_sig = gp.chi2t_sig1
gp.chi2t_kap = gp.chi2t_kap1
if not gp.deltaprior and gp.uselike:
sig_Rz = phys.sigma_rz(gp.xipol, gp.xipol, gp.parst.delta1)
prob_t = prob_t + np.sum((sig_Rz - sigRz_dat)**2./sigRz_dat_err**2.)
gp.chi2t1 = gp.chi2t_nu1 + gp.chi2t_sig1 # + gp.chi2t_kap1 # TODO
gp.chi2t = gp.chi2t1
if gp.pops == 2:
numodel2 = rho_INT_Rho(gp.xipol,gp.nu2_x) if gp.geom=='sphere' \
else gp.nu2_x
nudata2 = compare_nu(2,True,False)
nuerr2 = compare_nu(2,True,True)
gp.chi2t_nu2 = chi2red(numodel2, nudata2, nuerr2, gp.dof)
gp.chi2t_nu += gp.chi2t_nu2
gp.chi2t_sig2 = chi2red(gp.sig2_x, gp.ipol.sigdat2,\
gp.ipol.sigerr2,gp.dof)
gp.chi2t_sig += gp.chi2t_sig2
gp.chi2t_kap2 = chi2red(gp.kap2_x, gp.ipol.kapdat2,\
gp.ipol.kaperr2,gp.dof)
gp.chi2t_kap += gp.chi2t_kap2
gp.chi2t2 = gp.chi2t_nu2 + gp.chi2t_sig2 # + gp.chi2t_kap2 # TODO
gp.chi2t += gp.chi2t2
gh.checknan(gp.chi2t)
gp.fnewoverf = np.exp(gp.chi2/2.0-gp.chi2t/2.0)
gh.checknan(gp.fnewoverf)
return gp.fnewoverf
def compare_nu(pop, dat, err):
# if dat == True: return data; else: model (possibly projected)
# if err == True: return data error instead
if (not dat) and err:
print('wrong use of compare_nu, error only given for data, not model')
exit(1)
ret = []
if dat:
if gp.geom == 'sphere':
ret = gp.dat.Nudat[pop] # [Msun/pc^2]
if err:
ret = gp.dat.Nuerr[pop] # [Msun/pc^2]
else: # [model]
if gp.geom == 'sphere':
print('TODO: calculating stupid thing?')
ret = rho_INT_Rho(gp.xipol, gp.dat.nudat[pop]) # [Msun/pc^2]
return ret # [Msun/pc^2]
def physical(r0, prof, pop, tmp_rho, tmp_nu, tmp_beta):
if prof == "rho":
tmp_prof = phys.rho(r0, tmp_rho)
elif prof == 'nr':
tmp_prof = tmp_rho[1:]
elif prof == "nu":
tmp_prof = rho_INT_Rho(r0, phys.rho(r0, tmp_nu))
elif prof == "betastar":
tmp_prof = phys.mapping_beta_star_poly(r0, tmp_beta)
elif prof == "beta":
tmp_prof = phys.beta(r0, tmp_beta)
elif prof == "sig":
tmp_sig, tmp_kap = phys.sig_kap_los(r0, pop, tmp_rho, tmp_nu, tmp_beta)
tmp_prof = tmp_sig
elif prof == "kap":
tmp_sig, tmp_kap = phys.sig_kap_los(r0, pop, tmp_rho, tmp_nu, tmp_beta)
tmp_prof = tmp_kap
return tmp_prof
print('input: ', basename)
M = np.loadtxt(basename+'prof'+prof+str(pop),skiprows=0,unpack=False)
print('len (M) = ',len(M))
radii = M[0]
profs = M[1:] # all saved profiles
#profs = M[-10:]
#profs = M[-10000::10] # only the last 1e5 profiles, thinned by 10
Mprofbins = np.transpose(profs)
newMprofbins = gh.sort_profiles_binwise(Mprofbins)
Mmin, M95lo, M68lo, Mmedi, M68hi, M95hi, Mmax = gh.get_median_1_2_sig(newMprofbins)
if prof == 'nu':
Mmax=rho_INT_Rho(radii, Mmax)
M95hi=rho_INT_Rho(radii, M95hi)
M68hi=rho_INT_Rho(radii, M68hi)
Mmedi=rho_INT_Rho(radii, Mmedi)
M68lo=rho_INT_Rho(radii, M68lo)
M95lo=rho_INT_Rho(radii, M95lo)
Mmin=rho_INT_Rho(radii, Mmin)
# def extralast(rad, prof):
# tck = splrep(rad[:-1],np.log(prof[:-1]),k=2,s=0.1)
# prof = np.hstack([prof[:-1],np.exp(splev(rad[-1],tck))])
# return prof
# M95hi = extralast(radii,M95hi)
# M68hi = extralast(radii,M68hi)
# Mmedi = extralast(radii,Mmedi)