def DChi( z, zp=0.0, cosm=Cosmology(), nz=100 ):
"""
Calculates co-moving radial distance [Gpc] from zp to z using dx = cdt/a
z : float : redshift
zp ; float (0) : starting redshift
cosm : Cosmology
nz : int (100) : number of z-values to use in calculation
"""
zvals = zvalues( zs=z, z0=zp, nz=nz )
integrand = c.cperh0() * ( c.h0()/cosm.h0 ) / np.sqrt( cosm.m * np.power(1+zvals,3) + cosm.l )
return c.intz( zvals, integrand ) / (1e9 * c.pc2cm() ) # Gpc, in comoving coordinates
def CosmTauX( z, E=1.0, dist=dust.Dustdist(), scatm=ss.Scatmodel(), cosm=Cosmology(), nz=100 ):
"""
FUNCTION CosmTauX( z, E=1.0, dist=dust.Dustdist(), scatm=ss.Scatmodel(), cosm=Cosmology(), nz=100
---------------------------------
INPUT
z : redshift of source
E : scalar or np.array [keV]
dist : dust.Dustdist or dust.Grain
scatm : ss.Scatmodel
cosm : cosm.Cosmology
---------------------------------
OUTPUT
tauX : scalar or np.array [optical depth to X-ray scattering]
= kappa( dn/da da ) cosmdens (1+z)^2 cdz/hfac
"""
zvals = zvalues( zs=z, nz=nz )
md = Cosmdens( cosm=cosm ).md
spec = dust.Dustspectrum( rad=dist, md=md )
if np.size(E) > 1:
result = np.array([])
for ener in E:
Evals = ener * (1+zvals)
kappa = ss.Kappascat( E=Evals, scatm=scatm, dist=spec ).kappa
hfac = np.sqrt( cosm.m * np.power( 1+zvals, 3 ) + cosm.l )
integrand = kappa * md * np.power( 1+zvals, 2 ) * \
c.cperh0() * ( c.h0()/cosm.h0 ) / hfac
result = np.append( result, c.intz( zvals, integrand ) )
else:
Evals = E * (1 + zvals)
kappa = ss.Kappascat( E=Evals, scatm=scatm, dist=spec ).kappa
hfac = np.sqrt( cosm.m * np.power( 1+zvals, 3 ) + cosm.l )
integrand = kappa * md * np.power( 1+zvals, 2 ) * c.cperh0() * ( c.h0()/cosm.h0 ) / hfac
result = c.intz( zvals, integrand )
return result
def UniformIGM(halo, zs=4.0, cosm=cosmo.Cosmology(), nz=500):
"""
FUNCTION UniformIGM( halo, zs=4.0, cosm=cosmo.Cosmology(), nz=500 )
MODIFIES halo.htype, halo.dist, halo.intensity, halo.taux
--------------------------------------------------------------------
halo : Halo object
zs : float : redshift of source
cosm : cosmo.Cosmology
nz : int : number of z-values to use in integration
"""
E0 = halo.energy
alpha = halo.alpha
scatm = halo.scatm
halo.htype = CosmHalo(zs=zs, cosm=cosm, igmtype="Uniform") # Stores information about this halo calc
halo.dist = dust.Dustspectrum(rad=halo.rad, md=cosmo.Cosmdens(cosm=cosm).md)
Dtot = cosmo.DChi(zs, cosm=cosm, nz=nz)
zpvals = cosmo.zvalues(zs=zs - zs / nz, z0=0, nz=nz)
DP = np.array([])
for zp in zpvals:
DP = np.append(DP, cosmo.DChi(zs, zp=zp, cosm=cosm))
X = DP / Dtot
c_H0_cm = c.cperh0() * (c.h0() / cosm.h0) # cm
hfac = np.sqrt(cosm.m * np.power(1 + zpvals, 3) + cosm.l)
Evals = E0 * (1 + zpvals)
## Single grain case
if type(halo.rad) == dust.Grain:
intensity = np.array([])
f = 0.0
cnt = 0.0
na = np.size(alpha)
for al in alpha:
cnt += 1
thscat = al / X # np.size(thscat) = nz
dsig = ss.Diffscat(theta=thscat, a=halo.dist.a, E=Evals, scatm=scatm).dsig
itemp = c_H0_cm / hfac * np.power((1 + zpvals) / X, 2) * halo.dist.nd * dsig
intensity = np.append(intensity, c.intz(zpvals, itemp))
## Dust distribution case
elif type(halo.rad) == dust.Dustdist:
avals = halo.dist.a
intensity = np.array([])
for al in alpha:
thscat = al / X # np.size(thscat) = nz
iatemp = np.array([])
for aa in avals:
dsig = ss.Diffscat(theta=thscat, a=aa, E=Evals, scatm=scatm).dsig
dtmp = c_H0_cm / hfac * np.power((1 + zpvals) / X, 2) * dsig
iatemp = np.append(iatemp, c.intz(zpvals, dtmp))
intensity = np.append(intensity, c.intz(avals, halo.dist.nd * iatemp))
else:
print "%% Must input type dust.Grain or dust.Dustdist"
intensity = np.zeros(np.size(zpvals))
# ----- Finally, set the halo intensity --------
halo.intensity = intensity * np.power(c.arcs2rad(), 2) # arcsec^-2
halo.taux = cosmo.CosmTauX(zs, E=halo.energy, dist=halo.rad, scatm=halo.scatm, cosm=halo.htype.cosm)