def saturationB(Bguess0=1e-19,
nzs=100,
zmin=15, zmax=35,
thetak=0.1,phik=0.83,
val_nk=f.FFTT_nk,
val_Ts=rf.Ts_21cmfast_interp,
val_Tk=rf.Tk_21cmfast_interp,
val_Jlya=rf.Jlya_21cmfast_interp,
val_Tg=rf.Tg_21cmfast_interp,
phin=0., thetan=np.pi/2.,
make_plot=False,
**rootkwargs):
"""This computes the mag. field strength at saturation, at a given z.
"""
zs = np.linspace(zmin, zmax,nzs)
Bevol = np.zeros(nzs)
Bsat = np.zeros(nzs)
Gref = np.zeros(nzs)
Gref_Binf = np.zeros(nzs)
for i,z in enumerate(zs):
H_z = cf.H( z )
Ts = val_Ts( z )
Tg = val_Tg( z )
Tk = val_Tk( z )
Jlya = val_Jlya( z )
Salpha = cf.val_Salpha(Ts, Tk, z, 1., 0)
xalpha = rf.val_xalpha( Salpha=Salpha, Jlya=Jlya, Tg=Tg )
xc = rf.val_xc(z, Tk=Tk, Tg=Tg)
xBcoeff = ge * muB * Tstar / ( 2.*hbar * A * Tg )
xB=xBcoeff*Bguess0
Gref[i] = pt.calc_G(thetak=thetak, phik=phik,
thetan=thetan, phin=phin,
Ts=Ts, Tg=Tg, z=z,
verbose=False,
xalpha=xalpha, xc=xc, xB=xB, x1s=1.)
Gref_Binf[i] = pt.calc_G_Binfinity(thetak=thetak, phik=phik,
thetan=thetan, phin=phin,
Ts=Ts, Tg=Tg, z=z,
verbose=False,
xalpha=xalpha, xc=xc,
x1s=1.)
res = root(evaluate_GminusGinf, Bguess0, args=(Gref_Binf[i],xBcoeff,thetak,phik,thetan,phin,Ts,Tg,z,xalpha,xc,x1s),method='lm',options=dict(ftol=1e-13, eps=1e-6))
Bsat[i] = res.x[0]/(1+z)**2
if make_plot:
plt.figure()
plt.semilogy(zs,Bsat,lw=4,color='blue')
plt.xlabel('z',fontsize=22)
plt.ylabel('saturation B [Gauss]',fontsize=22)
return zs,Bsat
def saturationB_simple(zs=None,nzs=100,
zmin=15, zmax=35,
val_nk=f.FFTT_nk,
val_Ts=rf.Ts_21cmfast_interp,
val_Tk=rf.Tk_21cmfast_interp,
val_Jlya=rf.Jlya_21cmfast_interp,
val_Tg=rf.Tg_21cmfast_interp,
make_plot=False,
fontsize=24):
"""This computes the mag. field strength at saturation, at a given z, in a simplified way, as Bsaturation = (xc + xalpha +1) / xBcoeff.
"""
if zs is None:
zs = np.linspace(zmin, zmax,nzs)
Bsat = np.zeros(len(zs))
for i,z in enumerate(zs):
H_z = cf.H( z )
Ts = val_Ts( z )
Tg = val_Tg( z )
Tk = val_Tk( z )
Jlya = val_Jlya( z )
Salpha = cf.val_Salpha(Ts, Tk, z, 1., 0)
xalpha = rf.val_xalpha( Salpha=Salpha, Jlya=Jlya, Tg=Tg )
xc = rf.val_xc(z, Tk=Tk, Tg=Tg)
xBcoeff = ge * muB * Tstar / ( 2.*hbar * A * Tg )
Bsat[i] = (1+xalpha+xc)/xBcoeff/(1+z)**2
if make_plot:
plt.figure()
#fig = plt.gcf()
ax = plt.gca()
ylabel = ax.set_ylabel('Saturation [Gauss]',fontsize=fontsize)
xlabel = ax.set_xlabel('z',fontsize=fontsize)
plt.semilogy(zs,Bsat,lw=4,color='b')
plt.grid(b=True,which='major')
plt.savefig(RESULTS_PATH+'Bsaturation.pdf',
bbox_extra_artists=[xlabel, ylabel],
bbox_inches='tight')
return zs,Bsat
def saturationB_simple(zs=None,
nzs=100,
zmin=15,
zmax=35,
val_nk=f.FFTT_nk,
val_Ts=rf.Ts_21cmfast_interp,
val_Tk=rf.Tk_21cmfast_interp,
val_Jlya=rf.Jlya_21cmfast_interp,
val_Tg=rf.Tg_21cmfast_interp,
make_plot=False,
fontsize=24):
"""This computes the mag. field strength at saturation, at a given z, in a simplified way, as Bsaturation = (xc + xalpha +1) / xBcoeff.
"""
if zs is None:
zs = np.linspace(zmin, zmax, nzs)
Bsat = np.zeros(len(zs))
for i, z in enumerate(zs):
H_z = cf.H(z)
Ts = val_Ts(z)
Tg = val_Tg(z)
Tk = val_Tk(z)
Jlya = val_Jlya(z)
Salpha = cf.val_Salpha(Ts, Tk, z, 1., 0)
xalpha = rf.val_xalpha(Salpha=Salpha, Jlya=Jlya, Tg=Tg)
xc = rf.val_xc(z, Tk=Tk, Tg=Tg)
xBcoeff = ge * muB * Tstar / (2. * hbar * A * Tg)
Bsat[i] = (1 + xalpha + xc) / xBcoeff / (1 + z)**2
if make_plot:
plt.figure()
#fig = plt.gcf()
ax = plt.gca()
ylabel = ax.set_ylabel('Saturation [Gauss]', fontsize=fontsize)
xlabel = ax.set_xlabel('z', fontsize=fontsize)
plt.semilogy(zs, Bsat, lw=4, color='b')
plt.grid(b=True, which='major')
plt.savefig(RESULTS_PATH + 'Bsaturation.pdf',
bbox_extra_artists=[xlabel, ylabel],
bbox_inches='tight')
return zs, Bsat
def visualize_hp(thetak=np.pi / 2.,
phik=np.pi / 2.,
nside=64,
npix=None,
fileroot=RESULTS_PATH,
z=21,
fontsize=24):
"""This produces healpy visualization of the quadrupole pattern,
in the frame of the atom.
"""
Bs = np.array([0., 1e-18, 1e-17, 1e-16])
Ts = val_Ts(z)
Tg = val_Tg(z)
Tk = val_Tk(z)
Jlya = val_Jlya(z)
Salpha = cf.val_Salpha(Ts, Tk, z, 1., 0)
xalpha = rf.val_xalpha(Salpha=Salpha, Jlya=Jlya, Tg=Tg)
xc = rf.val_xc(z, Tk=Tk, Tg=Tg)
xBcoeff = ge * muB * Tstar / (2. * hbar * A * Tg)
if npix is None:
npix = hp.nside2npix(nside)
for B in Bs:
filename = fileroot + 'hp_B_{:.0}G.pdf'.format(B)
mapa = np.zeros(npix)
for ipix in np.arange(npix):
thetan, phin = hp.pix2ang(nside, ipix)
mapa[ipix] = pt.pattern_Tb(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
xalpha=xalpha,
xc=xc,
xB=xBcoeff * B)
if B > 0.:
Bexponent = np.log10(B / (1 + z)**2)
title = r'$10^{{{:.0f}}}$ Gauss'.format(Bexponent)
else:
title = 'no magnetic field'
hp.mollview(mapa, title='', cbar=False)
plt.title(title, fontsize=fontsize)
plt.savefig(filename)
def visualize_hp(thetak=np.pi/2.,phik=np.pi/2.,
nside=64, npix=None,
fileroot=RESULTS_PATH, z=21,
fontsize=24):
"""This produces healpy visualization of the quadrupole pattern,
in the frame of the atom.
"""
Bs = np.array([0.,1e-18,1e-17, 1e-16])
Ts = val_Ts( z )
Tg = val_Tg( z )
Tk = val_Tk( z )
Jlya = val_Jlya( z )
Salpha = cf.val_Salpha(Ts, Tk, z, 1., 0)
xalpha = rf.val_xalpha( Salpha=Salpha, Jlya=Jlya, Tg=Tg )
xc = rf.val_xc(z, Tk=Tk, Tg=Tg)
xBcoeff = ge * muB * Tstar / ( 2.*hbar * A * Tg )
if npix is None:
npix = hp.nside2npix(nside)
for B in Bs:
filename = fileroot + 'hp_B_{:.0}G.pdf'.format(B)
mapa = np.zeros(npix)
for ipix in np.arange(npix):
thetan, phin = hp.pix2ang(nside, ipix)
mapa[ipix] = pt.pattern_Tb(thetak=thetak, phik=phik,
thetan=thetan, phin=phin,
xalpha=xalpha, xc=xc, xB=xBcoeff*B)
if B > 0.:
Bexponent = np.log10(B / (1+z)**2)
title = r'$10^{{{:.0f}}}$ Gauss'.format(Bexponent)
else:
title = 'no magnetic field'
hp.mollview(mapa, title='', cbar=False)
plt.title(title, fontsize=fontsize)
plt.savefig(filename)
def integrand_PBi(x,
t_yr=1.,
Omega_survey=1.,
DeltaL_km=2.,
val_nk=FFTT_nk,
val_Ts=rf.Ts_21cmfast_interp,
val_Tk=rf.Tk_21cmfast_interp,
val_Jlya=rf.Jlya_21cmfast_interp,
val_x1s=rf.ones_x1s,
val_Tsys=Tsys_Mao2008,
val_Tg=rf.Tg_21cmfast_interp,
phin=0.,
thetan=np.pi / 2.,
debug=False):
"""Calculates value of the integrand for noise per component
of a stochastic mag. field vector B (eq 51 of detectability notes).
This is called by :func:`calc_SNR` that integrates it over k, theta, phi.
:param x:
Array of the following form: x = z, k_Mpc, thetak, phik
:type x: ``array``
:param t_yr:
The total observation time in years.
The time spent on a single field of view (=1sr for FFTT) is t_yr / Omega_survey. ???
:type t_yr: ``float``
:param DeltaL_km:
The size of the FFTT coverage on a side in kilometers.
:type DeltaL_km: ``float``
:param Omega_survey:
The survey area (on the sky) in steradians.
:type Omega_survey: ``float``
:params thetan,phin:
These define direction of the LOS in the frame where
mag. field vector B is along the z axis.
Do not change these unless you know exactly what you're getting into.
:type thetan,phin: ``float``
:params val_*:
Helper functions, like the calulators for various temperatures etc.
:type val_*: ``function``
"""
z = x[0]
k_Mpc = x[1]
thetak = x[2]
phik = x[3]
thetak_n = np.arccos(
np.sin(thetak) * np.cos(phik) * np.sin(thetan) * np.cos(phin) +
np.sin(thetak) * np.sin(phik) * np.sin(thetan) * np.sin(phin) +
np.cos(thetak) * np.cos(thetan))
sint = np.sin(thetak_n)
if np.isclose(sint, 0.):
if debug:
return 0, 0, 0
return 0.
DeltaL_cm = DeltaL_km * 1e5 # cm
lambda_z = lambda21 * (1. + z) # cm
dA = cf.val_dA(z) # cm
kmin = 2. * np.pi / (dA * sint / Mpc_in_cm) # 1/Mpc comoving
kmax = kmin * DeltaL_cm / lambda_z # 1/Mpc comoving
if k_Mpc > kmax or k_Mpc < kmin:
if debug:
return 0, 0, 0
return 0.
t_sec = 365. * 86400 * t_yr # sec
k_cm = k_Mpc / Mpc_in_cm # cm
N_ants = (DeltaL_cm / lambda_z)**2
Ntot = N_ants * (N_ants + 1.) / 2.
nk = val_nk(k_cm,
Ntot=Ntot,
lambda_z=lambda_z,
dA=dA,
sin_thetak_n=sint,
Lmax=DeltaL_cm,
Lmin=lambda_z,
DeltaL=DeltaL_cm)
t1 = t_sec
if Omega_survey > 1.:
t1 = t_sec / Omega_survey
H_z = cf.H(z)
Tsys = val_Tsys(z)
Ts = val_Ts(z)
Tg = val_Tg(z)
Tk = val_Tk(z)
Jlya = val_Jlya(z)
Salpha = cf.val_Salpha(Ts, Tk, z, 1., 0)
xalpha = rf.val_xalpha(Salpha=Salpha, Jlya=Jlya, Tg=Tg)
xc = rf.val_xc(z, Tk=Tk, Tg=Tg)
xBcoeff = ge * muB * Tstar / (2. * hbar * A * Tg)
Pnoise = P21_N(dA=dA,
H_z=H_z,
z=z,
Tsys=Tsys,
t1=t1,
Ae=lambda_z**2,
Lmax=DeltaL_cm,
Lmin=lambda_z,
lambda_z=lambda_z,
nk=nk)
if np.isnan(Pnoise):
raise ValueError('Pnoise is nan.')
Pdelta = cf.val_Pdelta(z, k_Mpc)
G = pt.calc_G(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
xB=0.,
x1s=1.)
dGdB = pt.calc_dGdB(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
xBcoeff=xBcoeff,
x1s=1.)
Psignal = Pdelta * G**2
Numerator = (2. * G * dGdB * (1. + z)**2 * Pdelta)**2
Denominator = 2. * (2. * np.pi)**3 * (
Psignal + Pnoise)**2 ###is 2pi factor right? check!
res = k_Mpc**2 * np.sin(thetak) * Numerator / Denominator
if debug:
return res, Pnoise, nk, Numerator, G, dGdB
return res
def integrand(x,
mode='B0',
t_yr=1.,
Omega_patch=1.,
DeltaL_km=2.,
val_nk=FFTT_nk,
val_Ts=rf.Ts_21cmfast_interp,
val_Tk=rf.Tk_21cmfast_interp,
val_Jlya=rf.Jlya_21cmfast_interp,
val_x1s=rf.ones_x1s,
val_Tsys=Tsys_Mao2008,
val_Tg=rf.Tg_21cmfast_interp,
phin=0.,
thetan=np.pi / 2.,
print_klims=False,
debug=False):
"""Calculates value of the integrand for sensitivity to uniform mag. field vector B (eqs 37,40 of detectability_notes).
This is called by :func:`rand_integrator` that integrates it over z, k, theta, phi.
:param x:
Array of the following form: x = z, k_Mpc, thetak, phik
:type x: ``array``
:param t_yr:
The total observation time in years.
The time spent on a single field of view (=1sr for FFTT) is t_yr / Omega_survey. ???
:type t_yr: ``float``
:param mode:
The mode of calculation; if mode == 'B0', returns sensitivity to measuring uniform mag. field B0
if mode == 'xi', returns 1 sigma sensitivity to distinguishing saturated from unsaturated case,
where xi is unitless and between 0 and 1.
:type mode: ``str``
:param DeltaL_km:
The size of the FFTT coverage on a side in kilometers.
:type DeltaL_km: ``float``
:param Omega_patch:
The area of a small (approx. flat, < 1sr) patch the sky in steradians.
:type Omega_patch: ``float``
:params thetan,phin:
These define direction of the LOS in the frame where
mag. field vector B is along the z axis.
Do not change these unless you know exactly what you're getting into.
:type thetan,phin: ``float``
:params val_*:
Helper functions, like the calulators for various temperatures etc.
:type val_*: ``function``
"""
z = x[0]
k_Mpc = x[1]
thetak = x[2]
phik = x[3]
thetak_n = np.arccos(
np.sin(thetak) * np.cos(phik) * np.sin(thetan) * np.cos(phin) +
np.sin(thetak) * np.sin(phik) * np.sin(thetan) * np.sin(phin) +
np.cos(thetak) * np.cos(thetan))
sint = np.sin(thetak_n)
if np.isclose(sint, 0.):
if debug:
return 0, 0, 0
return 0.
DeltaL_cm = DeltaL_km * 1e5 # cm
lambda_z = lambda21 * (1. + z) # cm
dA = cf.val_dA(z) # cm comov.
kmin = 2. * np.pi / (dA * sint / Mpc_in_cm) # 1/Mpc comoving
kmax = kmin * DeltaL_cm / lambda_z # 1/Mpc comoving
if print_klims:
print('kmax={}, kmin={}'.format(kmax, kmin))
if k_Mpc > kmax or k_Mpc < kmin:
if debug:
return 0, 0, 0
return 0.
t_sec = 365. * 86400 * t_yr # sec
k_cm = k_Mpc / Mpc_in_cm # cm
N_ants = (DeltaL_cm / lambda_z)**2
Ntot = N_ants * (N_ants + 1.) / 2.
nk = val_nk(k_cm,
Ntot=Ntot,
lambda_z=lambda_z,
dA=dA,
sin_thetak_n=sint,
Lmax=DeltaL_cm,
Lmin=lambda_z,
DeltaL=DeltaL_cm)
t1 = t_sec
if Omega_patch > 1.:
t1 = t_sec / Omega_patch
H_z = cf.H(z)
Tsys = val_Tsys(z)
Ts = val_Ts(z)
Tg = val_Tg(z)
Tk = val_Tk(z)
Jlya = val_Jlya(z)
Salpha = cf.val_Salpha(Ts, Tk, z, 1., 0)
xalpha = rf.val_xalpha(Salpha=Salpha, Jlya=Jlya, Tg=Tg)
xc = rf.val_xc(z, Tk=Tk, Tg=Tg)
xBcoeff = ge * muB * Tstar / (2. * hbar * A * Tg)
Vpatch = Vpatch_factor(z, dA=dA, H_z=H_z, Omega_patch=Omega_patch)
Pnoise = P21_N(dA=dA,
H_z=H_z,
z=z,
Tsys=Tsys,
t1=t1,
Ae=lambda_z**2,
Lmax=DeltaL_cm,
Lmin=lambda_z,
lambda_z=lambda_z,
nk=nk)
if np.isnan(Pnoise):
raise ValueError('Pnoise is nan.')
Pdelta = cf.val_Pdelta(z, k_Mpc)
if mode == 'B0':
G = pt.calc_G(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
xB=0.,
x1s=1.)
dGdB = pt.calc_dGdB(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
xBcoeff=xBcoeff,
x1s=1.)
Psignal = Pdelta * G**2
Numerator = (2. * G * dGdB * (1 + z)**2 * Pdelta)**2
Denominator = (Psignal + Pnoise)**2
res = k_Mpc**2 * np.sin(thetak) * Vpatch * Numerator / Denominator / (
2. * np.pi)**3
if mode == 'xi':
G_Bzero = pt.calc_G(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
x1s=1.,
xB=0.)
G_Binfinity = pt.calc_G_Binfinity(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
x1s=1.)
Psignal_Bzero = Pdelta * G_Bzero**2
Psignal_Binfinity = Pdelta * G_Binfinity**2
Numerator = (Psignal_Binfinity - Psignal_Bzero)**2
Denominator = 2. * (Psignal_Bzero + Pnoise)**2
res = k_Mpc**2 * np.sin(thetak) * Vpatch * Numerator / Denominator / (
2. * np.pi)**3
if mode == 'Bi':
G = pt.calc_G(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
xB=0.,
x1s=1.)
dGdB = pt.calc_dGdB(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
xBcoeff=xBcoeff,
x1s=1.) #/ (1.+z)**2 #!!! VG: check
Psignal = Pdelta * G**2
Numerator = (2. * G * dGdB * (1 + z)**2 * Pdelta)**2
Denominator = 2. * (Psignal + Pnoise)**2
res = k_Mpc**2 * np.sin(thetak) * Numerator / Denominator
if debug:
dGdB, summ, xs = pt.calc_dGdB(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
xBcoeff=xBcoeff,
x1s=1.,
debug=True)
return res, Numerator, Denominator, Psignal, Pnoise, G, dGdB, Pdelta, Ts, Tg, summ, xs
return res
def GvsB(zs=[20, 22, 25, 28, 31],
nBs=100,
Bmin=1e-22,
Bmax=1e-18,
thetak=0.1,
phik=0.83,
val_nk=f.FFTT_nk,
val_Ts=rf.Ts_21cmfast_interp,
val_Tk=rf.Tk_21cmfast_interp,
val_Jlya=rf.Jlya_21cmfast_interp,
val_Tg=rf.Tg_21cmfast_interp,
phin=0.,
thetan=np.pi / 2.,
fontsize=24,
make_plot=False,
root=RESULTS_PATH,
ymax=1e-5,
ymin=1e-14):
"""This plots deltaG(B), at a given z.
"""
Bref = 0.
plt.figure()
ax = plt.gca()
colors = ['Violet', 'DarkBlue', 'Maroon', 'r', 'Orange', 'gray']
zs, Bsat = saturationB_simple(zs=zs)
Bs = np.logspace(np.log10(Bmin), np.log10(Bmax), nBs)
deltaG = np.zeros(len(Bs))
for j, z in enumerate(zs):
H_z = cf.H(z)
Ts = val_Ts(z)
Tg = val_Tg(z)
Tk = val_Tk(z)
Jlya = val_Jlya(z)
Salpha = cf.val_Salpha(Ts, Tk, z, 1., 0)
xalpha = rf.val_xalpha(Salpha=Salpha, Jlya=Jlya, Tg=Tg)
xc = rf.val_xc(z, Tk=Tk, Tg=Tg)
xBcoeff = ge * muB * Tstar / (2. * hbar * A * Tg)
x1s = 1.
deltaG = np.zeros(len(Bs))
Gref = pt.calc_G(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
xB=xBcoeff * Bref,
x1s=1.)
for i, B in enumerate(Bs):
xB = xBcoeff * B
G = pt.calc_G(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
xB=xB,
x1s=1.)
deltaG[i] = np.abs((G - Gref) / Gref)
ax.loglog(Bs, deltaG, lw=4, color=colors[j])
ax.loglog(np.array([Bsat[j], Bsat[j]]),
np.array([ymin, ymax]),
'--',
lw=2,
color=colors[j])
xlabel = ax.set_xlabel('B [Gauss]', fontsize=fontsize)
ylabel = ax.set_ylabel(r'$\Delta G / G$', fontsize=fontsize)
plt.savefig(root + 'G_vs_B.pdf',
bbox_extra_artists=[xlabel, ylabel],
bbox_inches='tight')
def saturationB(Bguess0=1e-19,
nzs=100,
zmin=15,
zmax=35,
thetak=0.1,
phik=0.83,
val_nk=f.FFTT_nk,
val_Ts=rf.Ts_21cmfast_interp,
val_Tk=rf.Tk_21cmfast_interp,
val_Jlya=rf.Jlya_21cmfast_interp,
val_Tg=rf.Tg_21cmfast_interp,
phin=0.,
thetan=np.pi / 2.,
make_plot=False,
**rootkwargs):
"""This computes the mag. field strength at saturation, at a given z.
"""
zs = np.linspace(zmin, zmax, nzs)
Bevol = np.zeros(nzs)
Bsat = np.zeros(nzs)
Gref = np.zeros(nzs)
Gref_Binf = np.zeros(nzs)
for i, z in enumerate(zs):
H_z = cf.H(z)
Ts = val_Ts(z)
Tg = val_Tg(z)
Tk = val_Tk(z)
Jlya = val_Jlya(z)
Salpha = cf.val_Salpha(Ts, Tk, z, 1., 0)
xalpha = rf.val_xalpha(Salpha=Salpha, Jlya=Jlya, Tg=Tg)
xc = rf.val_xc(z, Tk=Tk, Tg=Tg)
xBcoeff = ge * muB * Tstar / (2. * hbar * A * Tg)
xB = xBcoeff * Bguess0
Gref[i] = pt.calc_G(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
xB=xB,
x1s=1.)
Gref_Binf[i] = pt.calc_G_Binfinity(thetak=thetak,
phik=phik,
thetan=thetan,
phin=phin,
Ts=Ts,
Tg=Tg,
z=z,
verbose=False,
xalpha=xalpha,
xc=xc,
x1s=1.)
res = root(evaluate_GminusGinf,
Bguess0,
args=(Gref_Binf[i], xBcoeff, thetak, phik, thetan, phin, Ts,
Tg, z, xalpha, xc, x1s),
method='lm',
options=dict(ftol=1e-13, eps=1e-6))
Bsat[i] = res.x[0] / (1 + z)**2
if make_plot:
plt.figure()
plt.semilogy(zs, Bsat, lw=4, color='blue')
plt.xlabel('z', fontsize=22)
plt.ylabel('saturation B [Gauss]', fontsize=22)
return zs, Bsat
def arb_xT(
zmin=15,
zmax=30,
nzs=100,
fontsize=24,
root=RESULTS_PATH,
filename='global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__midFSTAR',
filenames_uncertainty=[
'global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__loFSTAR',
'global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__hiFSTAR'
],
label='',
B0=1e-22,
ymax_T=100,
ymin_x=1e-6):
"""Takes filenames_uncertainty as a list of 2 filenames, no root,
e.g. ['global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__loFSTAR','global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__hiFSTAR']
"""
file_21cmfast = np.loadtxt(INPUTS_PATH + filename)
Tks_21cmfast = file_21cmfast[:, 2][::-1]
Tgs_21cmfast = file_21cmfast[:, 5][::-1]
Tss_21cmfast = file_21cmfast[:, 4][::-1]
Jlyas_21cmfast = file_21cmfast[:, 6][::-1]
zs_21cmfast = file_21cmfast[:, 0][::-1]
xH_21cmfast = file_21cmfast[:, 1][::-1]
if filenames_uncertainty is not None:
file_21cmfast_lo = np.loadtxt(INPUTS_PATH + filenames_uncertainty[0])
Tks_21cmfast_lo = file_21cmfast_lo[:, 2][::-1]
Tgs_21cmfast_lo = file_21cmfast_lo[:, 5][::-1]
Tss_21cmfast_lo = file_21cmfast_lo[:, 4][::-1]
Jlyas_21cmfast_lo = file_21cmfast_lo[:, 6][::-1]
zs_21cmfast_lo = file_21cmfast_lo[:, 0][::-1]
xH_21cmfast_lo = file_21cmfast_lo[:, 1][::-1]
file_21cmfast_hi = np.loadtxt(INPUTS_PATH + filenames_uncertainty[1])
Tks_21cmfast_hi = file_21cmfast_hi[:, 2][::-1]
Tgs_21cmfast_hi = file_21cmfast_hi[:, 5][::-1]
Tss_21cmfast_hi = file_21cmfast_hi[:, 4][::-1]
Jlyas_21cmfast_hi = file_21cmfast_hi[:, 6][::-1]
zs_21cmfast_hi = file_21cmfast_hi[:, 0][::-1]
xH_21cmfast_hi = file_21cmfast_hi[:, 1][::-1]
# plot J_Lya
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z', fontsize=fontsize)
ylabel = ax.set_ylabel(
r'$J_{Ly\alpha}$ [$cm^{-2} sec^{-1} Hz^{-1}sr^{-1}$]',
fontsize=fontsize)
ax.semilogy(zs_21cmfast, Jlyas_21cmfast, lw=4, color='Black')
# if uncertainty files given, plot band around Jlya
if filenames_uncertainty is not None:
maxind = min(len(Jlyas_21cmfast_lo), len(Jlyas_21cmfast_hi)) - 1
ax.fill_between(zs_21cmfast_lo[:maxind],
Jlyas_21cmfast_lo[:maxind],
Jlyas_21cmfast_hi[:maxind],
facecolor='gray',
interpolate=True,
alpha=0.4,
lw=0)
ax.set_xlim(xmin=zmin, xmax=27)
plt.savefig(RESULTS_PATH + 'Jlya{}.pdf'.format(label),
bbox_extra_artists=[xlabel, ylabel],
bbox_inches='tight')
# compute x's and write to file, then plot
xc = []
xB = []
xalpha = []
fout = open(RESULTS_PATH + 'xs_table.txt', 'w')
fout.write('z x_alpha x_c xBcoeff\n')
for i, z in enumerate(zs_21cmfast):
B = B0 * (1 + z)**2
Salpha = cf.val_Salpha(Tss_21cmfast[i], Tks_21cmfast[i], z,
xH_21cmfast[i], 0)
xalpha.append(
rf.val_xalpha(Salpha=Salpha,
Jlya=Jlyas_21cmfast[i],
Tg=Tgs_21cmfast[i]))
xc.append(rf.val_xc(z, Tk=Tks_21cmfast[i], Tg=Tgs_21cmfast[i]))
xBcoeff = ge * muB * Tstar / (2. * hbar * A * Tgs_21cmfast[i])
xB.append(B * xBcoeff)
fout.write('{} {} {} {}\n'.format(z, xalpha[i], xc[i], xBcoeff))
fout.close()
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z', fontsize=fontsize)
ylabel = ax.set_ylabel('')
plt.semilogy(zs_21cmfast,
xc,
'--',
dashes=(15, 5),
lw=4,
color='b',
label=r'$x_{c,(2)}$')
plt.semilogy(zs_21cmfast,
xalpha,
lw=4,
color='k',
label=r'$x_{\alpha,(2)}$')
plt.semilogy(zs_21cmfast,
xB,
'-.',
lw=4,
color='r',
label=r'$x_B$ ($10^{{{:.0f}}}$ G)'.format(np.log10(B0)))
plt.legend(fontsize=fontsize, frameon=False, loc='lower right')
plt.xlim(xmin=zmin, xmax=zmax)
plt.ylim(ymin=ymin_x)
plt.savefig(RESULTS_PATH + 'xs{}.pdf'.format(label),
bbox_extra_artists=[xlabel, ylabel],
bbox_inches='tight')
# plot ionization history
#plt.figure()
#ax = plt.gca()
#xlabel = ax.set_xlabel('z',fontsize=fontsize)
#ylabel = ax.set_ylabel('$x_H$',fontsize=fontsize)
#plt.plot(zs_21cmfast,xH_21cmfast,lw=4,color='red')
#plt.savefig(RESULTS_PATH+'xion{}.pdf'.format(label),
# bbox_extra_artists=[xlabel, ylabel],
# bbox_inches='tight')
# plot T's
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z', fontsize=fontsize)
ylabel = ax.set_ylabel('T [K]', fontsize=fontsize)
plt.plot(zs_21cmfast, Tss_21cmfast, lw=4, color='k', label='$T_s$')
plt.plot(zs_21cmfast,
Tgs_21cmfast,
'--',
lw=4,
color='g',
label=r'$T_{\gamma}$')
plt.plot(zs_21cmfast,
Tks_21cmfast,
'--',
dashes=(15, 5),
lw=4,
color='b',
label='$T_k$')
plt.legend(fontsize=fontsize, frameon=False, loc='upper left')
plt.xlim(xmin=zmin, xmax=zmax)
plt.ylim(ymax=ymax_T)
#if filenames_uncertainty is not None:
# maxind = min(len(Tss_21cmfast_lo),len(Tss_21cmfast_hi))-1
# ax.fill_between(zs_21cmfast_lo[:maxind], Tss_21cmfast_lo[:maxind], Tss_21cmfast_hi[:maxind],
# facecolor='gray', interpolate=True, alpha=0.4, lw=0)
plt.savefig(RESULTS_PATH + 'Ts{}.pdf'.format(label),
bbox_extra_artists=[xlabel, ylabel],
bbox_inches='tight')
def arb_reion_models(
zmin=15,
zmax=27,
nzs=100,
fontsize=24,
root=RESULTS_PATH,
filenames=[
'global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__midFSTAR',
'global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__hiFSTAR',
'global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__loFSTAR',
'global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__fesc-ok',
'global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX5.0e+55_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__low-zetax',
'global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX2.0e+55_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc'
],
labels=[
'mid f*', 'hi f*', 'lo f*', 'fesc ok', 'zetax 0.5', 'zetax 0.2'
]):
"""
"""
if labels is None:
labels = np.arange(len(filenames))
Tks = {}
Tgs = {}
Tss = {}
Jlyas = {}
zs = {}
for i, fn in enumerate(filenames):
file_21cmfast = np.loadtxt(INPUTS_PATH + fn)
Tks[labels[i]] = file_21cmfast[:, 2][::-1]
Tgs[labels[i]] = file_21cmfast[:, 5][::-1]
Tss[labels[i]] = file_21cmfast[:, 4][::-1]
Jlyas[labels[i]] = file_21cmfast[:, 6][::-1]
zs[labels[i]] = file_21cmfast[:, 0][::-1]
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z', fontsize=fontsize)
ylabel = ax.set_ylabel(
r'$J_{Ly\alpha}$ [$cm^{-2} sec^{-1} Hz^{-1}sr^{-1}$]',
fontsize=fontsize)
for l in labels:
ax.semilogy(zs[l], Jlyas[l], lw=4, label='{}'.format(l))
ax.set_xlim(xmin=zmin, xmax=zmax)
plt.legend(loc='lower left')
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z', fontsize=fontsize)
ylabel = ax.set_ylabel(r'$T_S$ [K]', fontsize=fontsize)
for l in labels:
plt.plot(zs[l], Tss[l], lw=4, label='{}'.format(l))
plt.legend(loc='upper left', fontsize=fontsize)
plt.xlim(xmin=zmin, xmax=zmax)
plt.ylim(ymax=100)
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z', fontsize=fontsize)
ylabel = ax.set_ylabel(r'$T_K$ [K]', fontsize=fontsize)
for l in labels:
plt.plot(zs[l], Tks[l], lw=4, label='{}'.format(l))
plt.legend(loc='upper left', fontsize=fontsize)
plt.xlim(xmin=zmin, xmax=zmax)
plt.ylim(ymax=100)
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z', fontsize=fontsize)
ylabel = ax.set_ylabel(r'$x_c$', fontsize=fontsize)
for l in labels:
xc = []
for i, z in enumerate(zs[l]):
xc.append(rf.val_xc(z, Tk=Tks[l][i], Tg=Tgs[l][i]))
plt.semilogy(zs[l], xc, lw=4, label='{}'.format(l))
plt.legend(loc='lower right', fontsize=fontsize)
plt.xlim(xmin=zmin, xmax=zmax)
plt.ylim(ymin=1e-6)
def GvsB(zs=[20,22,25,28,31],
nBs=100, Bmin=1e-22,Bmax=1e-18,
thetak=0.1,phik=0.83,
val_nk=f.FFTT_nk,
val_Ts=rf.Ts_21cmfast_interp,
val_Tk=rf.Tk_21cmfast_interp,
val_Jlya=rf.Jlya_21cmfast_interp,
val_Tg=rf.Tg_21cmfast_interp,
phin=0., thetan=np.pi/2.,
fontsize=24,
make_plot=False,
root=RESULTS_PATH,
ymax=1e-5,
ymin=1e-14):
"""This plots deltaG(B), at a given z.
"""
Bref = 0.
plt.figure()
ax = plt.gca()
colors = ['Violet','DarkBlue','Maroon','r','Orange','gray']
zs, Bsat = saturationB_simple(zs=zs)
Bs = np.logspace(np.log10(Bmin),np.log10(Bmax),nBs)
deltaG = np.zeros(len(Bs))
for j,z in enumerate(zs):
H_z = cf.H( z )
Ts = val_Ts( z )
Tg = val_Tg( z )
Tk = val_Tk( z )
Jlya = val_Jlya( z )
Salpha = cf.val_Salpha(Ts, Tk, z, 1., 0)
xalpha = rf.val_xalpha( Salpha=Salpha, Jlya=Jlya, Tg=Tg )
xc = rf.val_xc(z, Tk=Tk, Tg=Tg)
xBcoeff = ge * muB * Tstar / ( 2.*hbar * A * Tg )
x1s = 1.
deltaG = np.zeros(len(Bs))
Gref = pt.calc_G(thetak=thetak, phik=phik,
thetan=thetan, phin=phin,
Ts=Ts, Tg=Tg, z=z,
verbose=False,
xalpha=xalpha, xc=xc, xB=xBcoeff*Bref, x1s=1.)
for i,B in enumerate(Bs):
xB = xBcoeff*B
G = pt.calc_G(thetak=thetak, phik=phik,
thetan=thetan, phin=phin,
Ts=Ts, Tg=Tg, z=z,
verbose=False,
xalpha=xalpha, xc=xc, xB=xB, x1s=1.)
deltaG[i] = np.abs((G - Gref) / Gref)
ax.loglog(Bs,deltaG,lw=4,color=colors[j])
ax.loglog(np.array([Bsat[j],Bsat[j]]),np.array([ymin,ymax]),'--',lw=2,color=colors[j])
xlabel = ax.set_xlabel('B [Gauss]',fontsize=fontsize)
ylabel = ax.set_ylabel(r'$\Delta G / G$',fontsize=fontsize)
plt.savefig(root+'G_vs_B.pdf',
bbox_extra_artists=[xlabel, ylabel],
bbox_inches='tight')
def arb_xT(zmin=15,zmax=30, nzs=100,
fontsize=24,root=RESULTS_PATH,
filename='global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__midFSTAR',
filenames_uncertainty=['global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__loFSTAR','global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__hiFSTAR'],
label='',B0=1e-22,
ymax_T=100,ymin_x=1e-6):
"""Takes filenames_uncertainty as a list of 2 filenames, no root,
e.g. ['global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__loFSTAR','global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__hiFSTAR']
"""
file_21cmfast = np.loadtxt(INPUTS_PATH+filename)
Tks_21cmfast = file_21cmfast[:,2][::-1]
Tgs_21cmfast = file_21cmfast[:,5][::-1]
Tss_21cmfast = file_21cmfast[:,4][::-1]
Jlyas_21cmfast = file_21cmfast[:,6][::-1]
zs_21cmfast = file_21cmfast[:,0][::-1]
xH_21cmfast = file_21cmfast[:,1][::-1]
if filenames_uncertainty is not None:
file_21cmfast_lo = np.loadtxt(INPUTS_PATH+filenames_uncertainty[0])
Tks_21cmfast_lo = file_21cmfast_lo [:,2][::-1]
Tgs_21cmfast_lo = file_21cmfast_lo [:,5][::-1]
Tss_21cmfast_lo = file_21cmfast_lo [:,4][::-1]
Jlyas_21cmfast_lo = file_21cmfast_lo [:,6][::-1]
zs_21cmfast_lo = file_21cmfast_lo [:,0][::-1]
xH_21cmfast_lo = file_21cmfast_lo [:,1][::-1]
file_21cmfast_hi = np.loadtxt(INPUTS_PATH+filenames_uncertainty[1])
Tks_21cmfast_hi = file_21cmfast_hi [:,2][::-1]
Tgs_21cmfast_hi = file_21cmfast_hi [:,5][::-1]
Tss_21cmfast_hi = file_21cmfast_hi [:,4][::-1]
Jlyas_21cmfast_hi = file_21cmfast_hi[:,6][::-1]
zs_21cmfast_hi = file_21cmfast_hi[:,0][::-1]
xH_21cmfast_hi = file_21cmfast_hi [:,1][::-1]
# plot J_Lya
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z',fontsize=fontsize)
ylabel = ax.set_ylabel(r'$J_{Ly\alpha}$ [$cm^{-2} sec^{-1} Hz^{-1}sr^{-1}$]',fontsize=fontsize)
ax.semilogy(zs_21cmfast,Jlyas_21cmfast,lw=4,color='Black')
# if uncertainty files given, plot band around Jlya
if filenames_uncertainty is not None:
maxind = min(len(Jlyas_21cmfast_lo),len(Jlyas_21cmfast_hi))-1
ax.fill_between(zs_21cmfast_lo[:maxind], Jlyas_21cmfast_lo[:maxind], Jlyas_21cmfast_hi[:maxind],
facecolor='gray', interpolate=True, alpha=0.4, lw=0)
ax.set_xlim(xmin=zmin,xmax=27)
plt.savefig(RESULTS_PATH+'Jlya{}.pdf'.format(label),
bbox_extra_artists=[xlabel, ylabel],
bbox_inches='tight')
# compute x's and write to file, then plot
xc = []; xB = []; xalpha = []
fout = open(RESULTS_PATH + 'xs_table.txt', 'w')
fout.write('z x_alpha x_c xBcoeff\n')
for i,z in enumerate(zs_21cmfast):
B = B0*(1+z)**2
Salpha = cf.val_Salpha(Tss_21cmfast[i], Tks_21cmfast[i], z, xH_21cmfast[i], 0)
xalpha.append(rf.val_xalpha( Salpha=Salpha, Jlya=Jlyas_21cmfast[i], Tg=Tgs_21cmfast[i] ))
xc.append(rf.val_xc(z, Tk=Tks_21cmfast[i], Tg=Tgs_21cmfast[i]))
xBcoeff = ge * muB * Tstar / ( 2.*hbar * A * Tgs_21cmfast[i] )
xB.append(B*xBcoeff)
fout.write('{} {} {} {}\n'.format(z, xalpha[i], xc[i], xBcoeff ))
fout.close()
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z',fontsize=fontsize)
ylabel = ax.set_ylabel('')
plt.semilogy(zs_21cmfast,xc,'--',dashes=(15,5),lw=4,color='b',label=r'$x_{c,(2)}$')
plt.semilogy(zs_21cmfast,xalpha,lw=4,color='k',label=r'$x_{\alpha,(2)}$')
plt.semilogy(zs_21cmfast,xB,'-.',lw=4,color='r',label=r'$x_B$ ($10^{{{:.0f}}}$ G)'.format(np.log10(B0)))
plt.legend(fontsize=fontsize,frameon=False,loc='lower right')
plt.xlim(xmin=zmin,xmax=zmax)
plt.ylim(ymin=ymin_x)
plt.savefig(RESULTS_PATH+'xs{}.pdf'.format(label),
bbox_extra_artists=[xlabel, ylabel],
bbox_inches='tight')
# plot ionization history
#plt.figure()
#ax = plt.gca()
#xlabel = ax.set_xlabel('z',fontsize=fontsize)
#ylabel = ax.set_ylabel('$x_H$',fontsize=fontsize)
#plt.plot(zs_21cmfast,xH_21cmfast,lw=4,color='red')
#plt.savefig(RESULTS_PATH+'xion{}.pdf'.format(label),
# bbox_extra_artists=[xlabel, ylabel],
# bbox_inches='tight')
# plot T's
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z',fontsize=fontsize)
ylabel = ax.set_ylabel('T [K]',fontsize=fontsize)
plt.plot(zs_21cmfast,Tss_21cmfast,lw=4,color='k',label='$T_s$')
plt.plot(zs_21cmfast,Tgs_21cmfast,'--',lw=4,color='g',label=r'$T_{\gamma}$')
plt.plot(zs_21cmfast,Tks_21cmfast,'--',dashes=(15,5),lw=4,color='b',label='$T_k$')
plt.legend(fontsize=fontsize,frameon=False,loc='upper left')
plt.xlim(xmin=zmin,xmax=zmax)
plt.ylim(ymax=ymax_T)
#if filenames_uncertainty is not None:
# maxind = min(len(Tss_21cmfast_lo),len(Tss_21cmfast_hi))-1
# ax.fill_between(zs_21cmfast_lo[:maxind], Tss_21cmfast_lo[:maxind], Tss_21cmfast_hi[:maxind],
# facecolor='gray', interpolate=True, alpha=0.4, lw=0)
plt.savefig(RESULTS_PATH+'Ts{}.pdf'.format(label),
bbox_extra_artists=[xlabel, ylabel],
bbox_inches='tight')
def arb_reion_models(zmin=15,zmax=27, nzs=100,
fontsize=24,root=RESULTS_PATH,
filenames=['global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__midFSTAR','global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__hiFSTAR','global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__loFSTAR','global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX1.0e+56_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__fesc-ok','global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX5.0e+55_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc__low-zetax','global_evolution_zetaIon31.50_Nsteps40_zprimestepfactor1.020_zetaX2.0e+55_alphaX1.2_TvirminX1.0e+04_Pop3_300_200Mpc'],
labels=['mid f*','hi f*','lo f*','fesc ok','zetax 0.5', 'zetax 0.2']):
"""
"""
if labels is None:
labels = np.arange(len(filenames))
Tks = {}
Tgs = {}
Tss = {}
Jlyas = {}
zs = {}
for i,fn in enumerate(filenames):
file_21cmfast = np.loadtxt(INPUTS_PATH+fn)
Tks[labels[i]] = file_21cmfast[:,2][::-1]
Tgs[labels[i]] = file_21cmfast[:,5][::-1]
Tss[labels[i]] = file_21cmfast[:,4][::-1]
Jlyas[labels[i]] = file_21cmfast[:,6][::-1]
zs[labels[i]] = file_21cmfast[:,0][::-1]
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z',fontsize=fontsize)
ylabel = ax.set_ylabel(r'$J_{Ly\alpha}$ [$cm^{-2} sec^{-1} Hz^{-1}sr^{-1}$]',fontsize=fontsize)
for l in labels:
ax.semilogy(zs[l],Jlyas[l],lw=4,label='{}'.format(l))
ax.set_xlim(xmin=zmin,xmax=zmax)
plt.legend(loc='lower left')
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z',fontsize=fontsize)
ylabel = ax.set_ylabel(r'$T_S$ [K]',fontsize=fontsize)
for l in labels:
plt.plot(zs[l],Tss[l],lw=4,label='{}'.format(l))
plt.legend(loc='upper left',fontsize=fontsize)
plt.xlim(xmin=zmin,xmax=zmax)
plt.ylim(ymax=100)
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z',fontsize=fontsize)
ylabel = ax.set_ylabel(r'$T_K$ [K]',fontsize=fontsize)
for l in labels:
plt.plot(zs[l],Tks[l],lw=4,label='{}'.format(l))
plt.legend(loc='upper left',fontsize=fontsize)
plt.xlim(xmin=zmin,xmax=zmax)
plt.ylim(ymax=100)
plt.figure()
ax = plt.gca()
xlabel = ax.set_xlabel('z',fontsize=fontsize)
ylabel = ax.set_ylabel(r'$x_c$',fontsize=fontsize)
for l in labels:
xc = []
for i,z in enumerate(zs[l]):
xc.append(rf.val_xc(z, Tk=Tks[l][i], Tg=Tgs[l][i]))
plt.semilogy(zs[l],xc,lw=4,label='{}'.format(l))
plt.legend(loc='lower right',fontsize=fontsize)
plt.xlim(xmin=zmin,xmax=zmax)
plt.ylim(ymin=1e-6)