def __init__( self, theta=power_angles(), \
scatm=ss.Scatmodel(), \
rad=0.1, ener=1.0, nx=1000 ):
# Theta automatically sampled in log space.
# If I don't do it this way, linear interpolation easily fails
# for small angles (between theta[0] and theta[1]). Since
# most of my plots are in log-space, it makes more sense to
# sample logarithmically.
if np.size(theta) < 2:
print('Error: Must give more than one theta value')
self.theta = None
self.rad = None
self.ener = None
self.scatm = None
self.theta = theta
self.rad = rad
self.ener = ener
self.scatm = scatm
dxi = 1.0 / np.float(nx)
xi = np.arange( 0, 1.0, dxi ) + dxi
itemp = np.array([])
for th in self.theta:
thscat = th / xi
dsig = ss.Diffscat( theta=thscat, scatm=self.scatm, E=self.ener, a=self.rad ).dsig
itemp = np.append( itemp, \
c.intz( xi, dsig/(xi**2) ) )
self.itemp = itemp * c.arcs2rad**2
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 ScreenIGM(halo, zs=2.0, zg=1.0, md=1.5e-5, cosm=cosmo.Cosmology()):
"""
FUNCTION ScreenIGM( halo, zs=2.0, zg=1.0, md=1.5e-5, cosm=cosmo.Cosmology() )
MODIFIES halo.htype, halo.dist, halo.intensity, halo.taux
--------------------------------------------------------------------
halo : Halo object
zs : float : redshift of source
zg : float : redshift of screen
md : float : mass density of dust to use in screen [g cm^-2]
cosm : cosmo.Cosmology
"""
if zg >= zs:
print "%% STOP: zg must be < zs"
E0 = halo.energy
alpha = halo.alpha
scatm = halo.scatm
# Store information about this halo calculation
halo.htype = CosmHalo(zs=zs, zg=zg, cosm=cosm, igmtype="Screen")
halo.dist = dust.Dustspectrum(rad=halo.rad, md=md)
X = cosmo.DChi(zs, zp=zg, cosm=cosm) / cosmo.DChi(zs, cosm=cosm) # Single value
thscat = alpha / X # Scattering angle required
Eg = E0 * (1 + zg) # Photon energy at the screen
## Single grain size case
if type(halo.rad) == dust.Grain:
dsig = ss.Diffscat(theta=thscat, a=halo.dist.a, E=Eg, scatm=scatm).dsig
intensity = halo.dist.nd / np.power(X, 2) * dsig
## Distribution of grain sizes
elif type(halo.rad) == dust.Dustdist:
avals = halo.dist.a
dsig = np.zeros(shape=(np.size(avals), np.size(thscat)))
for i in range(np.size(avals)):
dsig[i, :] = ss.Diffscat(theta=thscat, a=avals[i], E=Eg, scatm=scatm).dsig
intensity = np.array([])
for j in range(np.size(thscat)):
itemp = halo.dist.nd * dsig[:, j] / np.power(X, 2)
intensity = np.append(intensity, c.intz(avals, itemp))
else:
print "%% Must input type dust.Grain or dust.Dustdist"
intensity = np.zeros(np.size(zpvals))
halo.intensity = intensity * np.power(c.arcs2rad(), 2) # arcsec^-2
halo.taux = cosmo.CosmTauScreen(zg, E=halo.energy, dist=halo.dist, scatm=halo.scatm)
def __init__( self, E=1.0, scatm=Scatmodel(), dist=dust.Dustspectrum() ):
self.scatm = scatm
self.E = E
self.dist = dist
if scatm.stype == 'RG':
print 'Rayleigh-Gans cross-section not currently supported for Kappaext'
self.kappa = None
return
cm = scatm.cmodel
scat = scatm.smodel
cgeo = np.pi * np.power( dist.a * c.micron2cm(), 2 )
qext = np.zeros( shape=( np.size(E),np.size(dist.a) ) )
qext_pe = np.zeros( shape=( np.size(E),np.size(dist.a) ) )
qext_pa = np.zeros( shape=( np.size(E),np.size(dist.a) ) )
# Test for graphite case
if cm.cmtype == 'Graphite':
cmGraphitePerp = cmi.CmGraphite(size=cm.size, orient='perp')
cmGraphitePara = cmi.CmGraphite(size=cm.size, orient='para')
if np.size(dist.a) > 1:
for i in range( np.size(dist.a) ):
qext_pe[:,i] = scat.Qext( E, a=dist.a[i], cm=cmGraphitePerp )
qext_pa[:,i] = scat.Qext( E, a=dist.a[i], cm=cmGraphitePara )
else:
qext_pe = scat.Qext( E, a=dist.a, cm=cmGraphitePerp )
qext_pa = scat.Qext( E, a=dist.a, cm=cmGraphitePara )
qext = ( qext_pa + 2.0 * qext_pe ) / 3.0
else:
if np.size(dist.a) > 1:
for i in range( np.size(dist.a) ):
qext[:,i] = scat.Qext( E, a=dist.a[i], cm=cm )
else:
qext = scat.Qext( E, a=dist.a, cm=cm )
if np.size(dist.a) == 1:
kappa = dist.nd * qext * cgeo / dist.md
else:
kappa = np.array([])
for j in range( np.size(E) ):
kappa = np.append( kappa, \
c.intz( dist.a, dist.nd * qext[j,:] * cgeo ) / dist.md )
self.kappa = kappa
def CosmTauX( z, E=1.0, dist=dust.Powerlaw(), scatm=ss.Scatmodel(), cosm=Cosmology(), nz=100 ):
"""
FUNCTION CosmTauX( z, E=1.0, dist=dust.Powerlaw(), scatm=ss.Scatmodel(), cosm=Cosmology(), nz=100
---------------------------------
INPUT
z : redshift of source
E : scalar or np.array [keV]
dist : dust.Powerlaw 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 ecf( self, theta, nth=500 ):
NE, NA = len(self.energy), len(self.alpha)
result = np.zeros( NE ) # NE x NA
taux = self.taux
tharray = np.linspace( min(self.alpha), theta, nth )
if self.taux == None:
print('ERROR: No taux is specified. Need to run halo calculation')
return result
for i in range(NE):
interpH = interp1d( self.alpha, self.intensity[i,:] )
result[i] = c.intz( tharray, interpH(tharray) * 2.0*np.pi*tharray ) / taux[i]
return result
def ecf(self, theta, nth=500):
"""
Returns the enclosed fraction for the halo surface brightness
profile, via integral(theta,2pi*theta*halo)/tau.
theta : float : Value for which to compute enclosed fraction (arcseconds)
nth : int (500) : Number of angles to use in calculation
"""
if self.htype == None:
print "Error: Halo has not yet beein calculated."
return
interpH = interp1d(self.alpha, self.intensity)
tharray = np.linspace(min(self.alpha), theta, nth)
try:
return c.intz(tharray, interpH(tharray) * 2.0 * np.pi * tharray) / self.taux
except:
print "Error: ECF calculation failed. Theta is likely out of bounds."
return
def __init__( self, E=1.0, scatm=Scatmodel(), dist=dust.Dustspectrum() ):
self.scatm = scatm
self.E = E
self.dist = dist
cm = scatm.cmodel
scat = scatm.smodel
cgeo = np.pi * np.power( dist.a * c.micron2cm(), 2 )
qsca = np.zeros( shape=( np.size(E),np.size(dist.a) ) )
qsca_pe = np.zeros( shape=( np.size(E),np.size(dist.a) ) )
qsca_pa = np.zeros( shape=( np.size(E),np.size(dist.a) ) )
# Test for graphite case
if cm.cmtype == 'Graphite':
cmGraphitePerp = cmi.CmGraphite(size=cm.size, orient='perp')
cmGraphitePara = cmi.CmGraphite(size=cm.size, orient='para')
if np.size(dist.a) > 1:
for i in range( np.size(dist.a) ):
qsca_pe[:,i] = scat.Qsca( E, a=dist.a[i], cm=cmGraphitePerp )
qsca_pa[:,i] = scat.Qsca( E, a=dist.a[i], cm=cmGraphitePara )
else:
qsca_pe = scat.Qsca( E, a=dist.a, cm=cmGraphitePerp )
qsca_pa = scat.Qsca( E, a=dist.a, cm=cmGraphitePara )
qsca = ( qsca_pa + 2.0 * qsca_pe ) / 3.0
else:
if np.size(dist.a) > 1:
for i in range( np.size(dist.a) ):
qsca[:,i] = scat.Qsca( E, a=dist.a[i], cm=cm )
else:
qsca = scat.Qsca( E, a=dist.a, cm=cm )
if np.size(dist.a) == 1:
kappa = dist.nd * qsca * cgeo / dist.md
else:
kappa = np.array([])
for j in range( np.size(E) ):
kappa = np.append( kappa, \
c.intz( dist.a, dist.nd * qsca[j,:] * cgeo ) / dist.md )
self.kappa = kappa
def DiscreteISM( halo, xg=0.5, NH=1.0e20, d2g=0.009 ):
"""
Calculate the X-ray scattering intensity for dust in an
infinitesimally thin wall somewhere on the line of sight.
| **MODIFIES**
| halo.htype, halo.dist, halo.taux, halo.intensity
| **INPUTS**
| halo : Halo object
| xg : float : distance FROM source / distance between source and observer
| NH : float : column density [cm^-2]
| d2g : float : dust-to-gass mass ratio
"""
E0 = halo.energy
alpha = halo.alpha
scatm = halo.scatm
md = NH * c.m_p * d2g
halo.htype = GalHalo( xg=xg, NH=NH, d2g=d2g, ismtype='Screen' )
halo.dist = dust.Dustspectrum( rad=halo.rad, md=md )
thscat = alpha / xg
if type(halo.rad) == dust.Grain:
dsig = ss.Diffscat( theta=thscat, a=halo.dist.a, E=E0, scatm=scatm ).dsig
intensity = np.power( xg, -2.0 ) * dsig * halo.dist.nd
elif type(halo.rad) == dust.Dustdist:
avals = halo.dist.a
intensity = []
for i in range( len(alpha) ):
iatemp = np.zeros( shape=( len(avals),len(alpha) ) )
for j in range( len(avals) ):
dsig = ss.Diffscat( theta=thscat, a=avals[j], E=E0, scatm=scatm ).dsig
iatemp[j,:] = np.power(xg,-2.0) * dsig
intensity.append( c.intz( avals, iatemp[:,i] * halo.dist.nd ) )
intensity = np.array( intensity )
else:
print('%% Must input type dust.Grain or dust.Dustdist')
intensity = np.zeros( np.size(xvals) )
halo.intensity = intensity * np.power( c.arcs2rad, 2 ) # arcsec^-2
halo.taux = ss.Kappascat( E=halo.energy, scatm=halo.scatm, dist=halo.dist ).kappa * md
def DiscreteISM( halo, xg=0.5, NH=1.0e20, d2g=0.009 ):
"""
FUNCTION DiscreteISM( halo, xg=0.5, NH=1.0e20, d2g=0.009 )
MODIFIES halo.htype, halo.dist, halo.taux, halo.intensity
----------------------------------------------------------------------------
halo : Halo object
xg : float : distance FROM source / distance between source and observer
NH : float : column density [cm^-2]
d2g : float : dust-to-gass mass ratio
"""
E0 = halo.energy
alpha = halo.alpha
scatm = halo.scatm
md = NH * c.mp() * d2g
halo.htype = GalHalo( xg=xg, NH=NH, d2g=d2g, ismtype='Screen' )
halo.dist = dust.Dustspectrum( rad=halo.rad, md=md )
thscat = alpha / xg
if type(halo.rad) == dust.Grain:
dsig = ss.Diffscat( theta=thscat, a=halo.dist.a, E=E0, scatm=scatm ).dsig
intensity = np.power( xg, -2.0 ) * dsig * halo.dist.nd
elif type(halo.rad) == dust.Dustdist:
avals = halo.dist.a
intensity = []
for i in range( len(alpha) ):
iatemp = np.zeros( shape=( len(avals),len(alpha) ) )
for j in range( len(avals) ):
dsig = ss.Diffscat( theta=thscat, a=avals[j], E=E0, scatm=scatm ).dsig
iatemp[j,:] = np.power(xg,-2.0) * dsig
intensity.append( c.intz( avals, iatemp[:,i] * halo.dist.nd ) )
intensity = np.array( intensity )
else:
print '%% Must input type dust.Grain or dust.Dustdist'
intensity = np.zeros( np.size(xvals) )
halo.intensity = intensity * np.power( c.arcs2rad(), 2 ) # arcsec^-2
halo.taux = ss.Kappascat( E=halo.energy, scatm=halo.scatm, dist=halo.dist ).kappa * md
def __call__(self, with_mp=False):
cm = self.scatm.cmodel
scat = self.scatm.smodel
cgeo = np.pi * np.power( self.dist.a * c.micron2cm(), 2 )
# Test for graphite case
if cm.cmtype == 'Graphite':
if np.size(self.dist.a) > 1:
for i in range( np.size(self.dist.a) ):
self.qsca_pe[:,i] = scat.Qsca( self.E, a=self.dist.a[i], cm=cmi.CmGraphite(size=cm.size, orient='perp') )
self.qsca_pa[:,i] = scat.Qsca( self.E, a=self.dist.a[i], cm=cmi.CmGraphite(size=cm.size, orient='para') )
else:
self.qsca_pe = scat.Qsca( self.E, a=self.dist.a, cm=cmi.CmGraphite(size=cm.size, orient='perp') )
self.qsca_pa = scat.Qsca( self.E, a=self.dist.a, cm=cmi.CmGraphite(size=cm.size, orient='para') )
self.qsca = ( self.qsca_pa + 2.0 * self.qsca_pe ) / 3.0
else:
if np.size(self.dist.a) > 1:
if with_mp:
pool = Pool(processes=2)
self.qsca = np.array(pool.map(self._one_scatter,self.dist.a)).T
else:
for i in range( np.size(self.dist.a) ):
self.qsca[:,i] = self._one_scatter(self.dist.a[i])
else:
self.qsca = scat.Qsca( self.E, a=self.dist.a, cm=cm )
if np.size(self.dist.a) == 1:
kappa = self.dist.nd * self.qsca * cgeo / self.dist.md
else:
kappa = np.array([])
for j in range( np.size(self.E) ):
kappa = np.append( kappa, \
c.intz( self.dist.a, self.dist.nd * self.qsca[j,:] * cgeo ) / self.dist.md )
self.kappa = kappa
def ecf( self, theta, nth=500 ):
"""
Returns the enclosed fraction for the halo surface brightness
profile, as a function of energy via
integral(theta,2pi*theta*halo)/total_halo_counts
-------------------------------------------------------------------------
theta : float : Value for which to compute enclosed fraction (arcseconds)
nth : int (500) : Number of angles to use in calculation
"""
NE, NA = len(self.energy), len(self.alpha)
result = np.zeros( NE ) # NE x NA
taux = self.taux
tharray = np.linspace( min(self.alpha), theta, nth )
if self.taux == None:
print 'ERROR: No taux is specified. Need to run halo calculation'
return result
for i in range(NE):
interpH = interp1d( self.alpha, self.intensity[i,:] )
result[i] = c.intz( tharray, interpH(tharray) * 2.0*np.pi*tharray ) / taux[i]
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)
def ndens(self, md=MDUST):
adep = np.power( self.a, -self.p ) # um^-p
dmda = adep * 4./3. * np.pi * self.rho * np.power( self.a*c.micron2cm, 3 ) # g um^-p
const = md / c.intz( self.a, dmda ) # cm^-? um^p-1
return const * adep # cm^-? um^-1
def dnda(self, md=1.5e-5):
adep = np.power( self.a, -self.p ) # um^-p
dmda = adep * 4./3. * np.pi * self.rho * np.power( self.a*c.micron2cm(), 3 ) # g um^-p
const = md / c.intz( self.a, dmda ) # cm^-? um^p-1
return const * adep # cm^-? um^-1
def make_WD01_Dustspectrum( R_V=3.1, bc=0.0, rad=DEFAULT_RAD, type='Graphite', gal='MW', verbose=True ):
"""
make_WD01_Dustspectrum(
R_V [float],
bc [float],
rad [np.array : grain sizes (um)],
type [string : 'Graphite' or 'Silicate'] )
gal [string : 'MW', 'LMC', or 'SMC'],
-------------------------------------------
Returns a dust.Dustspectrum object containing a
(grain sizes), nd (dn/da), and md (total mass density of dust)
>>> wd01_sil = make_WD01_Dustspectrum(type='Silicate')
>>> (dust._integrate_dust_mass(wd01_sil)/wd01_sil.md) - 1.0 < 0.01
>>> wd01_gra = make_WD01_Dustspectrum(type='Graphite')
>>> (dust._integrate_dust_mass(wd01_gra)/wd01_gra.md) - 1.0 < 0.01
"""
if type == 'Graphite':
rho_d = 2.2 #g cm^-3
elif type == 'Silicate':
rho_d = 3.8
else:
print('Error: Dust type not recognized')
return
ANGS2MICRON = 1.e-10 * 1.e6
a = rad # Easier than changing variable names further down
a_cm = rad * c.micron2cm
NA = np.size( a )
(alpha, beta, a_t, a_c, C) = get_dist_params( R_V=R_V, bc=bc, type=type, gal=gal, verbose=verbose )
if type == 'Graphite':
mc = 12. * 1.67e-24 # Mass of carbon atom in grams (12 m_p)
rho = 2.24 # g cm^-3
sig = 0.4
a_01 = 3.5*ANGS2MICRON # 3.5 angstroms in units of microns
a_01_cm = a_01 * c.micron2cm
bc1 = 0.75 * bc * 1.e-5
B_1 = (3.0/(2*np.pi)**1.5) * np.exp(-4.5 * 0.4**2) / (rho*a_01_cm**3 * 0.4) \
* bc1 * mc / (1 + special.erf( 3*0.4/np.sqrt(2) + np.log(a_01/3.5e-4)/(0.4*np.sqrt(2)) ) )
a_02 = 30.0*ANGS2MICRON # 30 angtroms in units of microns
a_02_cm = a_02 * c.micron2cm
bc2 = 0.25 * bc * 1.e-5
B_2 = (3.0/(2*np.pi)**1.5) * np.exp(-4.5 * 0.4**2) / (rho*a_02_cm**3 * 0.4) \
* bc2 * mc / (1 + special.erf( 3*0.4/np.sqrt(2) + np.log(a_02/3.5e-4)/(0.4*np.sqrt(2)) ) )
D = (B_1/a_cm) * np.exp( -0.5*( np.log(a/a_01)/sig )**2 ) + \
(B_2/a_cm) * np.exp( -0.5*( np.log(a/a_02)/sig )**2 )
Case_vsg = np.where( a < 3.5*ANGS2MICRON )
if np.size(Case_vsg) != 0:
D[Case_vsg] = 0.0
Case_g = np.zeros( NA )
case1g = np.where( np.logical_and(a > 3.5*ANGS2MICRON, a < a_t ) )
case2g = np.where( a >= a_t )
if np.size(case1g) != 0:
Case_g[case1g] = 1.0
if np.size(case2g) != 0:
Case_g[case2g] = np.exp( -( (a[case2g]-a_t) / a_c )**3 )
if beta >= 0:
F_g = 1 + beta * a / a_t
if beta < 0:
F_g = 1.0 / (1 - beta * a / a_t)
Dist_WD01 = D + C/a_cm * (a/a_t)**alpha * F_g * Case_g #cm^-4 per n_H
if type == 'Silicate':
Case_s = np.zeros( NA )
case1s = np.where( np.logical_and( a > 3.5*ANGS2MICRON, a < a_t ) )
case2s = np.where( a >= a_t )
if np.size(case1s) != 0:
Case_s[case1s] = 1.0
if np.size(case2s) != 0:
Case_s[case2s] = np.exp( -( (a[case2s]-a_t)/a_c )**3 )
F_s = np.zeros( NA )
if beta >= 0:
F_s = 1 + beta * a / a_t
if beta < 0:
F_s = 1. / (1 - beta * a / a_t)
Dist_WD01 = C/a_cm * (a/a_t)**alpha * F_s * Case_s #cm^-4 per n_H
mg = 4.0/3.0*np.pi*a_cm**3 * rho_d # mass of each dust grain
Md = c.intz( a_cm, Dist_WD01 * mg )
result = dust.Dustspectrum()
result.a = a
result.rho = rho_d
result.nd = Dist_WD01 * c.micron2cm # cm^-3 per um per n_H
result.md = Md
return result
def make_WD01_Dustspectrum( R_V=3.1, bc=0.0, rad=dust.adist(), type='Graphite', gal='MW' ):
"""
make_WD01_Dustspectrum(
R_V [float],
bc [float],
rad [np.array : grain sizes (um)],
type [string : 'Graphite' or 'Silicate'] )
gal [string : 'MW', 'LMC', or 'SMC'],
-------------------------------------------
Returns a dust.Dustspectrum object containing a (grain sizes), nd (dn/da), and md (total mass density of dust)
"""
if type == 'Graphite':
rho_d = 2.2 #g cm^-3
elif type == 'Silicate':
rho_d = 3.8
else:
print 'Error: Dust type not recognized'
return
dist = dust.Dustdist( rad=rad, rho=rho_d, p=4 )
result = dust.Dustspectrum( rad=dist )
ANGS2MICRON = 1.e-10 * 1.e6
a = dist.a
a_cm = dist.a * c.micron2cm()
NA = np.size( a )
(alpha, beta, a_t, a_c, C) = get_dist_params( R_V=R_V, bc=bc, type=type, gal=gal )
if type == 'Graphite':
mc = 12. * 1.67e-24 # Mass of carbon atom in grams (12 m_p)
rho = 2.24 # g cm^-3
sig = 0.4
a_01 = 3.5*ANGS2MICRON # 3.5 angstroms in units of microns
a_01_cm = a_01 * c.micron2cm()
bc1 = 0.75 * bc * 1.e-5
B_1 = (3.0/(2*np.pi)**1.5) * np.exp(-4.5 * 0.4**2) / (rho*a_01_cm**3 * 0.4) \
* bc1 * mc / (1 + special.erf( 3*0.4/np.sqrt(2) + np.log(a_01/3.5e-4)/(0.4*np.sqrt(2)) ) )
a_02 = 30.0*ANGS2MICRON # 30 angtroms in units of microns
a_02_cm = a_02 * c.micron2cm()
bc2 = 0.25 * bc * 1.e-5
B_2 = (3.0/(2*np.pi)**1.5) * np.exp(-4.5 * 0.4**2) / (rho*a_02_cm**3 * 0.4) \
* bc2 * mc / (1 + special.erf( 3*0.4/np.sqrt(2) + np.log(a_02/3.5e-4)/(0.4*np.sqrt(2)) ) )
D = (B_1/a_cm) * np.exp( -0.5*( np.log(a/a_01)/sig )**2 ) + \
(B_2/a_cm) * np.exp( -0.5*( np.log(a/a_02)/sig )**2 )
Case_vsg = np.where( a < 3.5*ANGS2MICRON )
if np.size(Case_vsg) != 0:
D[Case_vsg] = 0.0
Case_g = np.zeros( NA )
case1g = np.where( np.logical_and(a > 3.5*ANGS2MICRON, a < a_t ) )
case2g = np.where( a >= a_t )
if np.size(case1g) != 0:
Case_g[case1g] = 1.0
if np.size(case2g) != 0:
Case_g[case2g] = np.exp( -( (a[case2g]-a_t) / a_c )**3 )
if beta >= 0:
F_g = 1 + beta * a / a_t
if beta < 0:
F_g = 1.0 / (1 - beta * a / a_t)
Dist_WD01 = D + C/a_cm * (a/a_t)**alpha * F_g * Case_g #cm^-4 per n_H
if type == 'Silicate':
Case_s = np.zeros( NA )
case1s = np.where( np.logical_and( a > 3.5*ANGS2MICRON, a < a_t ) )
case2s = np.where( a >= a_t )
if np.size(case1s) != 0:
Case_s[case1s] = 1.0
if np.size(case2s) != 0:
Case_s[case2s] = np.exp( -( (a[case2s]-a_t)/a_c )**3 )
F_s = np.zeros( NA )
if beta >= 0:
F_s = 1 + beta * a / a_t
if beta < 0:
F_s = 1. / (1 - beta * a / a_t)
Dist_WD01 = C/a_cm * (a/a_t)**alpha * F_s * Case_s #cm^-4 per n_H
## Modify result Dustspectrum so we get a proper WD01 dist!
mg = 4.0/3.0*np.pi*a_cm**3 * rho_d # mass of each dust grain
Md = c.intz( a_cm, Dist_WD01 * mg )
result.nd = Dist_WD01 * c.micron2cm() # cm^-3 per um per n_H
result.md = Md
return result
def UniformISM( halo, NH=1.0e20, d2g=0.009, nx=1000, usepathdiff=False ):
"""
Calculate the X-ray scattering intensity for dust distributed
uniformly along the line of sight
| **MODIFIES**
| halo.htype, halo.dist, halo.taux, halo.intensity
| **INPUTS**
| halo : Halo object
| NH : float : column density [cm^-2]
| d2g : float : dust-to-gass mass ratio
| nx : int : number of values to use in integration
| usepathdiff : boolean : True = use extinction due to path difference e^(-tau*path_diff)
"""
E0 = halo.energy
alpha = halo.alpha
scatm = halo.scatm
md = NH * c.m_p * d2g
halo.htype = GalHalo( NH=NH, d2g=d2g, ismtype='Uniform' )
halo.dist = dust.Dustspectrum( rad=halo.rad, md=md )
halo.taux = ss.Kappascat( E=halo.energy, scatm=halo.scatm, dist=halo.dist ).kappa * md
dx = 1.0 / nx
xvals = np.arange( 0.0, 1.0, dx ) + dx
#--- Single grain case ---
if type( halo.rad ) == dust.Grain:
intensity = np.array([])
for al in alpha:
thscat = al / xvals # np.size(thscat) = nx
dsig = ss.Diffscat( theta=thscat, a=halo.dist.a, E=E0, scatm=scatm ).dsig
delta_tau = 0.0
if usepathdiff:
print('Using path difference')
delta_x = path_diff( al, xvals )
delta_tau = halo.taux * delta_x
print(np.max( delta_x ))
itemp = np.power( xvals, -2.0 ) * dsig * halo.dist.nd * np.exp( -delta_tau )
intensity = np.append( intensity, c.intz( xvals, itemp ) )
#--- Dust distribution case ---
elif type( halo.rad ) == dust.Dustdist:
avals = halo.dist.a
intensity = np.array([])
for al in alpha:
thscat = al / xvals # np.size(thscat) = nx
iatemp = np.array([])
for aa in avals:
dsig = ss.Diffscat( theta=thscat, a=aa, E=E0, scatm=scatm ).dsig
delta_tau = 0.0
if usepathdiff:
print('Using path difference')
delta_x = path_diff( al, xvals )
delta_tau = halo.taux * delta_x
print(max( delta_x ))
dtemp = np.power( xvals, -2.0 ) * dsig * np.exp( -delta_tau )
iatemp = np.append( iatemp, c.intz( xvals, dtemp ) )
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(xvals) )
# Set the halo intensity
halo.intensity = intensity * np.power( c.arcs2rad, 2 ) # arcsec^-2
