def calc_chi2(profs, nuparstore):
chi2 = 0.
off = 0
for pop in np.arange(gp.pops)+1:
# nu with normalization to 1 in first bin
nuparams = nuparstore[pop-1]
Numodel = rho_param_INT_Rho(gp.xepol, nuparams) # [Msun/pc^2], on nipol bins
# Numodel = rho_INT_Rho(gp.xipol, profs.get_nu(pop)) # [Msun/pc^2]
Nudata = compare_nu(pop,True,False) # [Msun/pc^2]
Nuerr = compare_nu(pop,True,True) # [Msun/pc^2]
chi2_nu = chi2red(Numodel, Nudata, Nuerr, gp.dof) # [1]
chi2 += chi2_nu # [1]
sigdat = gp.dat.sigdat[pop] # [km/s]
sigerr = gp.dat.sigerr[pop] # [km/s]
chi2_sig = chi2red(profs.get_sig(pop), sigdat, sigerr, gp.dof) # [1]
chi2 += chi2_sig # [1]
print('profs: ', profs.get_nu(pop)[0],', data: ', Nudata[0])
print('chi2_nu, chi2_sig = ',chi2_nu,' ',chi2_sig)
# TODO: check huge offset of Numodel (1000s Msun/pc^2) and Nudata (0.3 Msun/pc^2)
if gp.usekappa:
kapdat = gp.dat.kapdat[pop] # [1]
kaperr = gp.dat.kaperr[pop] # [1]
chi2_kap = chi2red(profs.get_kap(pop), kapdat, kaperr, gp.dof) # [1]
chi2 += chi2_kap # [1]
return chi2
def sig_kap_los(r0, pop, rho_param, nu_param, beta_param):
surfden = rho_param_INT_Rho(r0, rho_param) # total surface density
siglos2surf,kaplos4surf = ant_sigkaplos2surf(r0, beta_param,\
rho_param, nu_param)
# takes [pc], [1*pc], [munit], [munit/pc^3], returns [(km/s)^2], [1]
siglos2 = siglos2surf[:-3]/surfden # [(km/s)^2]
siglos = np.sqrt(siglos2) # [km/s]
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.*np.ones(len(siglos))
return siglos, kaplos # [km/s], [1]