return result
def sersic_half_scale_ratio(n):
#half light radius is radius that contains 0.5 of the total light
#scale radius is the radias when the profile intensity drops by 1/e. In this function, r_scale =1.0
r = np.linspace(0, 10, 1000)
tot_light = sersic_inter(r, n)
r_half = r[np.searchsorted(tot_light, 0.5)]
return r_half # = r_half/r_scale = r_half/1.0
redshift = np.linspace(0, 2, 1000)
#mpc_arcsec = interp1d(redshift,cosmo.kpc_proper_per_arcmin(redshift)/1000.0/60)
arcsec_per_mpc = interp1d(redshift,
cosmo.arcsec_per_kpc_proper(redshift).value * 1000.0)
sersic_half_scale_ratio_10 = sersic_half_scale_ratio(1.0)
sersic_half_scale_ratio_15 = sersic_half_scale_ratio(1.5)
sersic_half_scale_ratio_35 = sersic_half_scale_ratio(3.5)
hernquist_half_scale_ratio = 1.8153
size = hfile['redshift'].size
# slct_blue = hfile['magnitude:SDSS_u:observed'].values-hfile['magnitude:SDSS_g:observed'].values<1.36
# slct_red = slct_blue==0
# size = slct_blue.size
# data = np.ndarray(slct_blue.size,dtype=float)
# data[slct_blue]=hfile['spheriodRadius'].values*sersic_half_scale_ratio_15
# data[slct_red] =hfile['spheriodRadius'].values*sersic_half_scale_ratio_35
result = cumtrapz(sersic_r(r,n),x=r,initial=0.0)
result = result/result[-1]
return result
def sersic_half_scale_ratio(n):
#half light radius is radius that contains 0.5 of the total light
#scale radius is the radias when the profile intensity drops by 1/e. In this function, r_scale =1.0
r = np.linspace(0,10,1000)
tot_light = sersic_inter(r,n)
r_half = r[np.searchsorted(tot_light,0.5)]
return r_half # = r_half/r_scale = r_half/1.0
redshift=np.linspace(0,2,1000)
#mpc_arcsec = interp1d(redshift,cosmo.kpc_proper_per_arcmin(redshift)/1000.0/60)
arcsec_per_mpc = interp1d(redshift,cosmo.arcsec_per_kpc_proper(redshift).value*1000.0)
sersic_half_scale_ratio_10 = sersic_half_scale_ratio(1.0)
sersic_half_scale_ratio_15 = sersic_half_scale_ratio(1.5)
sersic_half_scale_ratio_35 = sersic_half_scale_ratio(3.5)
hernquist_half_scale_ratio = 1.8153
size = hfile['blackHoleMass'].size
# slct_blue = hfile['magnitude:SDSS_u:observed'].values-hfile['magnitude:SDSS_g:observed'].values<1.36
# slct_red = slct_blue==0
# size = slct_blue.size
# data = np.ndarray(slct_blue.size,dtype=float)
# data[slct_blue]=hfile['spheriodRadius'].values*sersic_half_scale_ratio_15
# data[slct_red] =hfile['spheriodRadius'].values*sersic_half_scale_ratio_35
