shellprofilear.append(bincount) shellprofilear.append(aGasMassHot) shellprofilear.append(aGasMassO6) shellprofilear.append(aGasMassLowIon) shellprofilear.append(aGasMassCold) shellprofilear.append(aGasFluxHot) shellprofilear.append(aGasFluxO6) shellprofilear.append(aGasFluxLowIon) shellprofilear.append(aGasFluxCold) bincount+=1 foutname = today+'PhaseShells.txt' outline3 = SF.line_to_string(shellprofilear, newline='y') i = open(foutname, 'a') i.write(outline3) i.close() MetalMassHot = np.array(MetalMassHot) MetalMassO6 = np.array(MetalMassO6) MetalMassLowIon = np.array(MetalMassLowIon) MetalMassCold = np.array(MetalMassCold) GasMassHot = np.array(GasMassHot) GasMassO6 = np.array(GasMassO6) GasMassLowIon = np.array(GasMassLowIon) GasMassCold = np.array(GasMassCold)
print 'but please stop at z=',Zs[count], ' N = ',SF.N_for_z(Zs[count])
print 'updating good_halos.txt'
if (os.path.isfile('good_halos.txt')):
f = np.loadtxt('good_halos.txt', ndmin=2)
haloIDs = f[:,3]
if (ID[count] in haloIDs):
print 'this already has an entry in good_halos.txt'
print 'keep going? '
override = raw_input('y/n ')
if (override == 'n'):
print 'ok not including this branch '
good = False
if (good):
g = open('good_halos.txt', 'a')
line = [haloN, fhires[count], nDM[count], ID[count], Zs[0], Zs[count], SF.N_for_z(Zs[0]), SF.N_for_z(Zs[count]), type, nstar[count]]
lala = SF.line_to_string(line)
g.write(lala)
g.close()
else:
print 'do not do this halo!'
print 'updating tried_halos.txt'
g = open('tried_halos.txt', 'a')
line = [haloN, fhires[count], nDM[count], ID[count], Zs[0], Zs[count], SF.N_for_z(Zs[0]), SF.N_for_z(Zs[count]), good, type, nstar[count]]
lala = SF.line_to_string(line)
g.write(lala)
g.close()
if (doplots != 'y'):
print 'skipping plots '
sys.exit()
vesc_order = np.argsort(vesc_ar[count]) mass_sorted_cumsum = np.cumsum(sig_ar[count][vesc_order]) mass_sorted_cumsum /= mass_sorted_cumsum[-1] vesc_med = np.interp(0.5, mass_sorted_cumsum,vesc_ar[count][vesc_order] ) vesc_25 = np.interp(0.25, mass_sorted_cumsum,vesc_ar[count][vesc_order] ) vesc_75 = np.interp(0.75, mass_sorted_cumsum,vesc_ar[count][vesc_order] ) print 'name of ep ',ep_name_ar[count] print 'num of snaps in ep', Neps_ar[count] print 'vesc ',len(vesc_ar[count]) print 'sig ',len(sig_ar[count]) weight_avg_vesc = np.average(vesc_ar[count], weights=sig_ar[count]) print 'weighted average vesc ',weight_avg_vesc print '25th, 50th, 75th percentile vesc ',vesc_25, vesc_med, vesc_75 weighted_avg_sig = np.average(sig_ar[count], weights=sig_ar[count])/area_of_cell print 'weighted average sig ',weighted_avg_sig unweighted_avg_sig = np.mean(sig_ar[count])/area_of_cell print 'unweighted average sig ',unweighted_avg_sig myline = [count, ep_name_ar[count], Neps_ar[count], weight_avg_vesc, vesc_25, vesc_med, vesc_75, weighted_avg_sig, unweighted_avg_sig, maxSF_ar[count], totMass_ar[count], duration_ar[count] ] mystring = SF.line_to_string(myline) f.write(mystring) print count, average_weighted_sig shell_histresults = np.histogram(vesc_ar[count], num_bins, range=(0, 1000), weights=np.array(mass_ar[count])/totalmass) [histx, histy] = ssp.create_plottable_hist(shell_histresults) plt.plot(histx,histy, color=color_ar[count], ls = ls_ar[count], lw=2) count+=1 f.close() plt.legend(my_special_legend, loc='best') plt.savefig(str(today) +'normedeps'+'.pdf')
Gdists = SF.calcdist2(haloX, haloY, haloZ, G['p'][:, 0][Gclose],
G['p'][:, 1][Gclose], G['p'][:, 2][Gclose], boxsize)
Ghalo = Gdists < Rvir
TempCutISM = PhysTemp[Gclose][Ghalo] < TempBound1
TempCutCGMCool = PhysTemp[Gclose][Ghalo] < TempBound2
TempCutCGMWarm = (PhysTemp[Gclose][Ghalo] >=
TempBound2) * (PhysTemp[Gclose][Ghalo] < TempBound3)
TempCutCGMHot = PhysTemp[Gclose][Ghalo] >= TempBound3
ISMDensCut = PhysRho[Gclose][Ghalo] > 0.1
MISM1 = np.sum(G['m'][Gclose][Ghalo][ISMDensCut]) * 1e10 / h
MISM2 = np.sum(G['m'][Gclose][Ghalo][ISMDensCut * TempCutISM]) * 1e10 / h
MCGM1 = np.sum(
G['m'][Gclose][Ghalo][TempCutCGMCool * np.invert(ISMDensCut)]) * 1e10 / h
MCGM2 = np.sum(G['m'][Gclose][Ghalo][TempCutCGMCool * np.invert(
TempCutISM * ISMDensCut)]) * 1e10 / h
MCGM3 = np.sum(G['m'][Gclose][Ghalo][TempCutCGMWarm]) * 1e10 / h
MCGM4 = np.sum(G['m'][Gclose][Ghalo][TempCutCGMHot]) * 1e10 / h
Line = [M / h, Mstar / h, MISM1, MISM2, MCGM1, MCGM2, MCGM3, MCGM4, a, Nsnap]
foutname = today + 'TheramlProfile.txt'
print SF.line_to_string(Line, newline='n')
outline2 = SF.line_to_string(Line, newline='y')
g = open(foutname, 'a')
g.write(outline2)
g.close()
weight_avg_vesc = np.average(vesc_ar[count], weights=sig_ar[count])
print 'weighted average vesc ', weight_avg_vesc
print '25th, 50th, 75th percentile vesc ', vesc_25, vesc_med, vesc_75
weighted_avg_sig = np.average(sig_ar[count],
weights=sig_ar[count]) / area_of_cell
print 'weighted average sig ', weighted_avg_sig
unweighted_avg_sig = np.mean(sig_ar[count]) / area_of_cell
print 'unweighted average sig ', unweighted_avg_sig
myline = [
count, lasta_ar[count], Neps_ar[count], weight_avg_vesc, vesc_25,
vesc_med, vesc_75, weighted_avg_sig, unweighted_avg_sig,
maxSF_ar[count], totMass_ar[count], duration_ar[count]
]
thar.append('z=' + str(lasta_ar[count]))
mystring = SF.line_to_string(myline)
f.write(mystring)
shell_histresults = np.histogram(vesc_ar[count],
num_bins,
range=(0, 1000),
weights=np.array(mass_ar[count]) /
totalmass)
[histx, histy] = ssp.create_plottable_hist(shell_histresults)
plt.plot(histx,
histy,
color=color_ar[count],
ls=ls_ar[count],
lw=2,
alpha=0.5)
count += 1
plt.legend(thar, loc='best')
strang1 = f.readline()
strang2 = f.readline()
dars = f.readlines()
f.close()
gork = open(foutname, 'w')
gork.write(strang1)
gork.write(strang2)
count = 0
for line in dars:
xsd = line.split()
xsd[6] = finalx[count]
xsd[7] = finaly[count]
xsd[8] = finalz[count]
myline = SF.line_to_string(xsd, newline='y', tabs='y')
#print myline
gork.write(myline)
count +=1
if (count >= len(finalx)):
break
gork.close()
OSinddsum = np.fabs(OSinddx) + np.fabs(OSinddy) + np.fabs(OSinddz)
finalddsum = np.fabs(finalddx) + np.fabs(finalddy) + np.fabs(finalddz)
initddsum = np.fabs(ddx) + np.fabs(ddy) + np.fabs(ddz)
fig3 = plt.figure(figsize=(10, 6))
plt.xlabel('z')
plt.ylabel('ddx, ddy, ddz (kpc/h)')
plt.plot(Zs, initddsum, color='r', ls ='-', lw=1)
strang1 = f.readline()
strang2 = f.readline()
dars = f.readlines()
f.close()
gork = open(foutname, 'w')
gork.write(strang1)
gork.write(strang2)
count = 0
for line in dars:
xsd = line.split()
xsd[6] = finalx[count]
xsd[7] = finaly[count]
xsd[8] = finalz[count]
myline = SF.line_to_string(xsd, newline='y', tabs='y')
#print myline
gork.write(myline)
count += 1
if (count >= len(finalx)):
break
gork.close()
OSinddsum = np.fabs(OSinddx) + np.fabs(OSinddy) + np.fabs(OSinddz)
finalddsum = np.fabs(finalddx) + np.fabs(finalddy) + np.fabs(finalddz)
initddsum = np.fabs(ddx) + np.fabs(ddy) + np.fabs(ddz)
fig3 = plt.figure(figsize=(10, 6))
plt.xlabel('z')
plt.ylabel('ddx, ddy, ddz (kpc/h)')
plt.plot(Zs, initddsum, color='r', ls='-', lw=1)
haloIDs = f[:, 3]
if (ID[count] in haloIDs):
print 'this already has an entry in good_halos.txt'
print 'keep going? '
override = raw_input('y/n ')
if (override == 'n'):
print 'ok not including this branch '
good = False
if (good):
g = open('good_halos.txt', 'a')
line = [
haloN, fhires[count], nDM[count], ID[count], Zs[0], Zs[count],
SF.N_for_z(Zs[0]),
SF.N_for_z(Zs[count]), type, nstar[count]
]
lala = SF.line_to_string(line)
g.write(lala)
g.close()
else:
print 'do not do this halo!'
print 'updating tried_halos.txt'
g = open('tried_halos.txt', 'a')
line = [
haloN, fhires[count], nDM[count], ID[count], Zs[0], Zs[count],
SF.N_for_z(Zs[0]),
SF.N_for_z(Zs[count]), good, type, nstar[count]
]
lala = SF.line_to_string(line)
g.write(lala)
g.close()
sys.exit() finname1 = str(sys.argv[1]) f = open(finname1) dars = np.loadtxt(f) f.close() SF_start = dars[:,13] SF_end = dars[:,15] Mstar = dars[:,8] eta = dars[:,17] epN = dars[:,0] cut1 = Mstar > Mstarlowlim cut2 = Mstar < Mstarupperlim cut = cut1*cut2 foutname = today+'relevant_snaps.txt' f = open(foutname, 'w') count = 0 while (count < len(SF_start[cut])): Nstart = N_for_T(SF_start[cut][count]) Nend = N_for_T(SF_end[cut][count]) print epN[cut][count], Mstar[cut][count]/1e10, Nstart, Nend, eta[cut][count] line = [epN[cut][count], Mstar[cut][count]/1e10, Nstart, Nend, eta[cut][count]] thestring = SF.line_to_string(line) f.write(thestring) count+=1 f.close()
count_ar = [] frac_ar = [] cellmass*=1e10/h totalfrac = 0 vesc_cge_ar = potter.calculate_escape_velocity([haloX, haloY, haloZ], [x_cells, y_cells, z_cells], G, S, D, where_do_we_go*h/a) * np.sqrt(2.0) print 'halo is here ',haloX, haloY, haloZ while (count < len(x_cells)): totalfrac+=cellmass[count]/Mnewstars #vesc_cge_beta = potter2.calculate_escape_velocity([haloX, haloY, haloZ], [x_cells[count], y_cells[count], z_cells[count]], G, S, D, where_do_we_go*h/a)*np.sqrt(2.0) print count, x_cells[count], y_cells[count], z_cells[count], vesc_cge_ar[count], cellmass[count], cellmass[count]/Mnewstars, totalfrac frac_ar.append(cellmass[count]/Mnewstars) count_ar.append(count) count +=1 vesc_cge_ar = np.array(vesc_cge_ar) count_ar = np.array(count_ar) frac_ar = np.array(frac_ar) vhist_header = [Nsnap, redshift, where_do_we_go , Rstars*a/h, Mnewstars, SFR_time_range, Nnewstars, the_surface_frac, haloX, haloY, haloZ] vhist_header_string = SF.line_to_string(vhist_header, newline='n') outtable = np.column_stack([count_ar, cellmass, vesc_cge_ar, x_cells, y_cells, z_cells, frac_ar ]) foutname = str(today)+'Xsurface_list'+Nsnapstring+'N'+str(halo_to_do[workcount])+'.txt' np.savetxt(foutname, outtable, fmt='%1.6e', header=vhist_header_string) if (do_graphs): foutname1a = str(today)+'image_stars'+Nsnapstring+'N'+str(halo_to_do[workcount])+'.pdf' foutnameDM = str(today)+'image_DM'+Nsnapstring+'N'+str(halo_to_do[workcount])+'.pdf' GL.pluscuts_2d_desnity_hist(S, Rstars, haloX, haloY, haloZ, foutname1a, dolabel=True, extrapoints = [[x_cells[0], y_cells[0], z_cells[0]]], extrars=[-1]) GL.pluscuts_2d_desnity_hist(D, Rstars, haloX, haloY, haloZ, foutnameDM, dolabel=True) workcount+=1
OutflowingParticlesID_G2_095Rvir[here])
len95in25 = len(OutflowingParticlesID_G2_095Rvir[here])
Particles_G_095_len = len(Particles_G2_095)
here_still = np.in1d(Particles_G2_095, OutflowingParticlesID_025Rvir)
#fraction of particles at shell #2 at later epoch still from first burst of shell#1
len95stillin25 = len(Particles_G2_095[here_still])
#1. halo, 2. Nsnap1, 3. Nsnap2, 4. redshift1, 5. redshift2, 6. len25-number of outflowing particles from epoch1, shell1. 7. len95 - number of outflowing particles at epoch2, shell2. 8. len95in25 number of outflowing particles at epoch2, shell2, that were also outflowing at shell1 at epoch1. 9. len95in25/len95. Fraction of outflowing particles at shell2 epoch2 that were also outflowing in shell1 at epoch1 over the number of outflowing particles in shell2 epoch2. 10. len95in25/len25. Fraction of outflowing particles at shell2 epoch2 that were also outflowing in shell1 at epoch1, over the number of outflowing particles from shell1 epoch1. 11. len95stillin25)/float(len25)- total number of particles in epoch2 shell2 that originated from outflowing particles from epoch1 shell 1. 12. index1. 13. index2. 14. use_v0 (True if vcut =0, False if vcut=vsig) #15 outflowrate1 #16 outflowrate2
print halo_to_do, Nsnap, Nsnap2, redshift1, redshift2, len25, len95, len95in25, len95stillin25, (
float(len95in25) /
float(len95)), (float(len95in25) /
float(len25)), (float(len95stillin25) /
float(len25)), index1, index2, use_v0
BigString = [
halo_to_do, Nsnap, Nsnap2, redshift1,
redshift2, len25, len95, len95in25, len95stillin25,
(float(len95in25) / float(len95)), (float(len95in25) / float(len25)),
(float(len95stillin25) / float(len25)), index1, index2,
int(use_v0), original_outflow_rate, second_outflow_rate
]
thestring = SF.line_to_string(BigString)
foutname = 'entrain_outflow_' + str(Nsnap) + 'halo' + str(halo_to_do) + '.txt'
g = open(foutname, 'a')
g.write(thestring)
g.close()
f = open(finname1)
dars = np.loadtxt(f)
f.close()
SF_start = dars[:, 13]
SF_end = dars[:, 15]
Mstar = dars[:, 8]
eta = dars[:, 17]
epN = dars[:, 0]
cut1 = Mstar > Mstarlowlim
cut2 = Mstar < Mstarupperlim
cut = cut1 * cut2
foutname = today + 'relevant_snaps.txt'
f = open(foutname, 'w')
count = 0
while (count < len(SF_start[cut])):
Nstart = N_for_T(SF_start[cut][count])
Nend = N_for_T(SF_end[cut][count])
print epN[cut][count], Mstar[cut][count] / 1e10, Nstart, Nend, eta[cut][
count]
line = [
epN[cut][count], Mstar[cut][count] / 1e10, Nstart, Nend,
eta[cut][count]
]
thestring = SF.line_to_string(line)
f.write(thestring)
count += 1
f.close()
