from solver import Evolve_RG
import numpy as np
import matplotlib.pyplot as plt
from constants import *
from matplotlib import rc
rc('font',**{'family':'serif','serif':['Times'],'size':14})
rc('text', usetex=True)
env=Evolve_RG.load('example-tstop-universal.pickle')
plt.figure(figsize=(12,5.5))
plt.subplot(1,2,1)
nfreq=len(env.freqs)
tv=env.tv
lums=np.zeros_like(env.corrs)
plt.plot(tv/Myr,env.synch,ls='--',color='black',label='150 MHz uncorrected')
for i in range(nfreq):
lums[:,i]=env.synch*(env.freqs[i]/env.nu_ref)**-env.alpha*env.corrs[:,i]
plt.plot(tv/Myr,lums[:,i],label='%.0f MHz' % (env.freqs[i]/1e6))
plt.xscale('log')
plt.yscale('log')
plt.legend(loc=0,fontsize='small')
plt.xlabel('Time (Myr)')
plt.ylabel('Radio luminosity (W Hz$^{-1}$)')
plt.xlim((1,300))
plt.ylim((1e25,3e29))
plt.subplot(1,2,2)
for i in range(1,nfreq):
plt.plot(tv/Myr,-np.log(lums[:,i]/lums[:,i-1])/np.log(env.freqs[i]/env.freqs[i-1]),label='$\\alpha_{%.0f}^{%.0f}$' % (env.freqs[i]/1e6,env.freqs[i-1]/1e6))
naxes = 4
ylabs = ['Length/kpc', 'Axial ratio', 'Mach number', 'L_150/(W/Hz)']
for i in range(naxes):
axes.append(plt.subplot(naxes / 2, naxes / 2, i + 1))
for ax in axes:
ax.set_xscale('log')
ax.set_yscale('log')
tmin = 10**-6
tmax = 300
tv = np.logspace(np.log10(tmin), np.log10(tmax), 100) * Myr
env = Evolve_RG('beta',
kT=0.86e3 * eV,
p0=2e-12,
rc=22 * 1.528714 * kpc,
beta=0.67,
do_adiabatic=False,
q=2.1)
#env=evolve_rg('universal',M500=1e14)
for Q in np.logspace(37.5, 39.5, 5):
print('solving for jet power', Q, 'W')
env.solve(Q, tv)
env.findb()
env.findsynch(150e6)
env.findcorrection((150e6, ))
axes[0].plot(tv / Myr, env.R / kpc, label='Q = %.2g W' % Q)
axes[1].plot(tv / Myr, env.rlobe, label='Q = %.2g W' % Q)
axes[2].plot(tv / Myr, env.m1, label='Q = %.2g W' % Q)
axes[3].plot(env.R / kpc,
axes=[]
naxes=4
for i in range(naxes):
axes.append(plt.subplot(naxes/2,naxes/2,i+1))
for ax in axes:
ax.set_xscale('log')
ax.set_yscale('log')
tmin=0
tmax=300
tv=np.logspace(-6,np.log10(tmax),100)*Myr
#env=evolve_rg('universal',M500=1e14)
Q=10**38.5
for i in range(2):
env=Evolve_RG('beta',kT=0.86e3*eV,p0=2e-12,rc=22*1.528714*kpc,beta=0.67,do_adiabatic=True,q=2.1)
env.solve(Q,tv,tstop=Myr*(tmax-(i*200)))
env.findb()
env.findsynch(150e6)
env.findcorrection((150e6,))
axes[0].plot(tv/Myr,env.R/kpc)
axes[1].plot(tv/Myr,env.rlobe,label='i = %i' % i)
axes[2].plot(tv/Myr,env.m1)
axes[3].plot(env.R/kpc,env.synch*env.corrs[:,0])
env.save('save_tstop_%i.pickle' % i)
#axis1.set_ylim(R/kpc/5,5*R/kpc)
#axis2.set_ylim(enow/5,enow*20)
for ax in axes[0:3]:
ax.set_xlim((tmin,tmax))
# Plot a couple of pressure profiles
from constants import *
from solver import Evolve_RG
import numpy as np
import os.path
xi = 0.4
q = 2.1
labels = ['beta', 'universal']
envs = [
Evolve_RG('beta',
kT=2.27e3 * eV,
p0=4e-12,
rc=30 * kpc,
beta=0.67,
xi=xi,
q=q),
Evolve_RG('universal', M500=1e14, xi=xi, q=q)
]
tmin = 0
tmax = 300
tv = np.logspace(-5, np.log10(tmax), 100) * Myr
Q = 2e39
for env, l in zip(envs, labels):
inname = 'example-' + l + '.pickle'
outname = 'example-' + l + '-highz.pickle'
if os.path.isfile(inname):
env = Evolve_RG.load(inname)
plt.xscale('log')
plt.yscale('log')
plt.figure(4)
plt.xscale('log')
tmin=0
tmax=300
tv=np.logspace(-6,np.log10(tmax),100)*Myr
if highz:
g=glob.glob('highz*.pickle')
else:
g=glob.glob('save_*.pickle')
for f in g:
sdict={}
env=Evolve_RG.load(f)
sdict['color']=cm.gist_rainbow((np.log10(env.Q)-36)/4.0)
sdict['alpha']=((np.log10(env.m500)-11.5)/3.5)**2.0
plt.figure(1)
plt.plot(tv/Myr,env.R/kpc,**sdict)
plt.figure(2)
plt.plot(env.R/kpc,np.sqrt(env.vl/(np.pi*env.R**3.0)),**sdict)
plt.figure(3)
plt.plot(env.R/kpc,env.synch*env.corrs[:,0],zorder=2,**sdict)
plt.figure(4)
plt.plot(env.R/kpc,0.55+np.log(env.corrs[:,0]/env.corrs[:,1])/np.log(1400.0/150.0),**sdict)
#axes[3].plot(env.R/kpc,env.synch)
#axis1.set_ylim(R/kpc/5,5*R/kpc)
#axis2.set_ylim(enow/5,enow*20)
xlabels=['t (Myr)','Lobe length (kpc)','Lobe length (kpc)','Lobe length (kpc)']
rc('font', **{'family': 'serif', 'serif': ['Times'], 'size': 14})
rc('text', usetex=True)
tmin = 0
tmax = 200
tv = np.logspace(-6, np.log10(tmax), 200) * Myr
#env=evolve_rg('universal',M500=1e14)
Q = 2e38
envs = []
for beta in [0.55, 0.75, 0.90]:
for rc in [20, 30, 40]:
outname = 'beta-%.2f-%i.pickle' % (beta, rc)
if os.path.isfile(outname):
envs.append(Evolve_RG.load(outname))
else:
rc *= 2.1 * kpc
envs.append(
Evolve_RG('beta',
kT=2e3 * eV,
p0=5.76e-12,
rc=rc,
beta=beta,
qfactor=0.5 * 25 * 730e3,
Gamma_j=(5.0 / 3.0)))
envs[-1].solve(Q, tv)
envs[-1].save(outname)
for i in range(2):
for env in envs:
naxes=4
plt.figure(figsize=(12,9))
for i in range(naxes):
axes.append(plt.subplot(naxes/2,naxes/2,i+1))
for ax in axes:
ax.set_xscale('log')
axes[0].set_yscale('log')
axes[2].set_yscale('log')
names=['beta','universal']
colours=['blue','orange']
labels=['$\\beta$ model','Universal']
for n,c,l in zip(names,colours,labels):
outname='example-'+n+'.pickle'
env=Evolve_RG.load(outname)
tv=env.tv
axes[0].plot(tv/Myr,env.R/kpc,color=c,label=l+' $R$')
rlobep=np.sqrt(env.vl/(4*np.pi*env.R))
axes[0].plot(tv/Myr,env.Rp/kpc,ls=':',color=c,label=l+' $R_\\perp$')
axes[0].plot(tv/Myr,rlobep/kpc,ls='--',color=c,label=l+' $R_{\\perp, lobe}$')
if n=='universal': axes[0].plot(tv/Myr,40*(tv/Myr)**0.6,ls='-.',color='green',label='$R \propto t^{3/5}$')
axes[1].plot(tv/Myr,env.rlobe,color=c)
axes[2].plot(tv/Myr,env.m1,color=c)
axes[2].plot(tv/Myr,env.mp1,color=c,ls=':')
axial=2*rlobep/env.R
axes[3].plot(tv/Myr,axial,color=c,label=l)
#axis1.set_ylim(R/kpc/5,5*R/kpc)
#axis2.set_ylim(enow/5,enow*20)
import pickle
import os
from constants import *
from solver import Evolve_RG
if __name__ == '__main__':
import sys
number = int(sys.argv[1]) - 1
qnum = number // 10
mnum = number % 10
print qnum, mnum
tmin = 0
tmax = 500
tv = np.logspace(-6, np.log10(tmax), 100) * Myr
Qs = np.logspace(36, 40, 13)
masses = np.logspace(13, 15, 10)
Q = Qs[qnum]
m = masses[mnum]
print 'Doing the run for Q=', Q, 'M=', m
env = Evolve_RG('universal', M500=m, xi=0.40, q=2.1)
outfile = 'save_%.1f_%.1f.pickle' % (np.log10(Q), np.log10(m))
if not os.path.isfile(outfile):
print 'solving for', Q, m
env.solve(Q, tv)
env.findb()
env.findsynch(150e6)
env.findcorrection((150e6, 1400e6), do_adiabatic=True)
env.save(outfile)
import numpy as np
from solver import Evolve_RG
t = Table.read('source-table.txt', format='ascii')
l150 = []
d = []
alpha = []
live = []
remnant = []
u = np.random.uniform(size=len(t))
theta = np.arccos(1 - u)
for i, r in enumerate(t):
inname = 'run-%i.pickle' % i
env = Evolve_RG.load(inname)
synch = env.synch[-1] * env.corrs[-1, 0]
live.append(synch > 0)
l150.append(synch)
d.append(env.R[-1])
if synch > 0:
alpha.append(0.55 + np.log(env.corrs[-1, 1] / env.corrs[-1, 2]) /
np.log(1400.0 / 150.0))
else:
alpha.append(np.nan)
remnant.append((r['lifetime'] + r['Tstart']) < 1000.0)
t['l150'] = l150
t['D'] = d
t['alpha'] = alpha
t['live'] = live
from solver import Evolve_RG
import numpy as np
import matplotlib.pyplot as plt
from constants import *
from matplotlib import rc
rc('font',**{'family':'serif','serif':['Times'],'size':14})
rc('text', usetex=True)
env=Evolve_RG.load('dwarf.pickle')
plt.figure(figsize=(12,10))
plt.subplot(2,2,1)
nfreq=len(env.freqs)
tv=env.tv
lums=np.zeros_like(env.corrs)
plt.plot(tv/Myr,env.synch,ls='--',color='black',label='150 MHz uncorrected')
for i in range(nfreq):
lums[:,i]=env.synch*(env.freqs[i]/env.nu_ref)**-env.alpha*env.corrs[:,i]
plt.plot(tv/Myr,lums[:,i],label='%.0f MHz' % (env.freqs[i]/1e6))
plt.xscale('log')
plt.yscale('log')
plt.legend(loc=0,fontsize='small')
plt.xlabel('Time (Myr)')
plt.ylabel('Radio luminosity (W Hz$^{-1}$)')
plt.subplot(2,2,2)
for i in range(1,nfreq):
plt.plot(tv/Myr,-np.log(lums[:,i]/lums[:,i-1])/np.log(env.freqs[i]/env.freqs[i-1]),label='$\\alpha_{%.0f}^{%.0f}$' % (env.freqs[i]/1e6,env.freqs[i-1]/1e6))
plt.xscale('log')
plt.legend(loc=0,fontsize='small')
import os
from constants import *
from solver import Evolve_RG
if __name__ == '__main__':
import sys
number = int(sys.argv[1]) - 1
qnum = number // 10
mnum = number % 10
print qnum, mnum
tmin = 0
tmax = 500
tv = np.logspace(-6, np.log10(tmax), 100) * Myr
Qs = np.logspace(36, 40, 13)
masses = np.logspace(13, 15, 10)
Q = Qs[qnum]
m = masses[mnum]
print 'Doing the run for Q=', Q, 'M=', m
infile = 'save_%.1f_%.1f.pickle' % (np.log10(Q), np.log10(m))
env = Evolve_RG.load(infile)
outfile = 'highz_%.1f_%.1f.pickle' % (np.log10(Q), np.log10(m))
if not os.path.isfile(outfile):
print 'solving for', Q, m
#env.solve(Q,tv)
#env.findb()
#env.findsynch(150e6)
env.findcorrection((150e6, 1400e6), do_adiabatic=True, z=2)
env.save(outfile)
from matplotlib import rc
import os.path
rc('font', **{'family': 'serif', 'serif': ['Times'], 'size': 14})
rc('text', usetex=True)
i = 0
for beta in [0.55, 0.75, 0.90]:
for rc in [20, 30, 40]:
color = [
'orange', 'red', 'firebrick', 'yellowgreen', 'lime', 'darkgreen',
'dodgerblue', 'royalblue', 'darkblue'
][i]
i += 1
env = Evolve_RG.load('beta-%.2f-%i.pickle' % (beta, rc))
tv = env.tv
plt.plot(tv / Myr, env.vl / (kpc**3.0), color=color, ls='--')
t = np.loadtxt('/home/mjh/PLUTO/results2/bmb-%i-%i-2s' %
(int(beta * 100), rc),
skiprows=1)
stu = 2.9
slu = 2.1
plt.plot(t[:, 0] * stu, (t[:, 14] + t[:, 1]) * 0.5 * slu**3.0,
color=color,
label='$\\beta = %.2f$ $r_c=%.0f$ kpc' %
(env.beta, env.rc / kpc))
plt.xscale('log')
# Plot a couple of pressure profiles
import matplotlib.pyplot as plt
from constants import *
from solver import Evolve_RG
import numpy as np
from matplotlib import rc
rc('font', **{'family': 'serif', 'serif': ['Times'], 'size': 14})
rc('text', usetex=True)
labels = ['$\\beta$ model', 'Universal']
colours = ['blue', 'orange']
envs = [
Evolve_RG('beta', kT=2.27e3 * eV, p0=4e-12, rc=30 * kpc, beta=0.67),
Evolve_RG('universal', M500=1e14)
]
dist = np.logspace(-3, 3.3, 100)
for env, l, c in zip(envs, labels, colours):
plt.plot(dist, env.pr(dist * kpc), label=l, color=c)
plt.xlabel('Distance (kpc)')
plt.ylabel('Pressure (Pa)')
plt.xscale('log')
plt.yscale('log')
plt.legend(loc=0)
plt.tight_layout()
plt.savefig('prprof.pdf')
from constants import *
from matplotlib import rc
rc('font', **{'family': 'serif', 'serif': ['Times'], 'size': 14})
rc('text', usetex=True)
plt.figure(figsize=(12, 5.5))
done_uncorr = False
for name, label in zip(
['example-universal-noad', 'example-universal', 'example-universal-highz'],
[
'Radiative only, $z=0$', 'Radiative + adiabatic, $z=0$',
'Radiative + adiabatic, $z=2$'
]):
env = Evolve_RG.load(name + '.pickle')
plt.subplot(1, 2, 1)
nfreq = len(env.freqs)
tv = env.tv
lums = np.zeros_like(env.corrs)
if not done_uncorr:
plt.plot(tv / Myr,
env.synch,
ls='--',
color='black',
label='150 MHz uncorrected')
for i in range(nfreq):
lums[:, i] = env.synch * (env.freqs[i] /
env.nu_ref)**-env.alpha * env.corrs[:, i]
ploti = 0
# Example dwarf galaxy profile
from constants import *
from solver import Evolve_RG
import numpy as np
import os.path
xi = 0.4
q = 2.1
env = Evolve_RG('beta',
kT=1e4 * boltzmann,
p0=10**0.75 * 3.1e-16,
rc=0.8 * kpc,
beta=0.67,
xi=xi,
q=q)
outname = 'dwarf.pickle'
tmin = 0
tmax = 100
tv = np.logspace(-5, np.log10(tmax), 100) * Myr
Q = 1e35
env.solve(Q, tv)
env.save(outname)
env.findb()
env.findsynch(150e6)
env.findcorrection((150e6, 330e6, 1.4e9, 5e9, 8e9, 15e9), do_adiabatic=True)
env.save(outname)
#!/usr/bin/python
from solver import Evolve_RG
from astropy.table import Table
import sys
from constants import *
import os
t = Table.read('source-table.txt', format='ascii')
lookback = 1000
n = int(sys.argv[1])
r = t[n]
print r
env = Evolve_RG('universal', M500=r['M500'], xi=0.40, q=2.1)
tlimit = lookback - r['Tstart']
tv = np.logspace(-6, np.log10(tlimit), 100) * Myr
outfile = 'run-%i.pickle' % n
if not os.path.isfile(outfile):
env.solve(r['Q'], tv, tstop=r['lifetime'] * Myr)
env.findb()
env.findsynch(150e6)
env.findcorrection((150e6, 150e6 * (1 + r['z']), 1400e6 * (1 + r['z'])),
do_adiabatic=True,
z=r['z'],
timerange=(99, ))
env.save('run-%i.pickle' % n)