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plot.py
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plot.py
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import yt
import math
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import AxesGrid
from yt.data_objects.particle_filters import add_particle_filter
#from yt.analysis_modules.halo_finding.api import HaloFinder
from yt.utilities.physical_constants import \
gravitational_constant_cgs as G
from yt.units import mp
import numpy as np
import struct
import os
import sys
from yt.visualization.api import get_multi_plot
from matplotlib.colors import LogNorm
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import matplotlib.cm as cm
pi = 3.14159265
ANALYTIC = False
DUST_PROPERTIES = False
THERMAL_HISTORY = True
MASS_HISTORY = False
C_FE = False
SNAPSHOTS_INI = False
SNAPSHOTS_RAD = False # UNUSED
SNAPSHOTS_EXP = False
SNAPSHOTS_COL = False
SNAPSHOTS_FIN = False
PROFILE_METAL = False
PROFILE_COL = False
plt.rcParams['font.family'] = 'Times New Roman'
plt.rcParams["mathtext.fontset"] = "stix"
fontsize_suptitle = 28
fontsize_title = 24
fontsize_boxsize = 24
fontsize_label = 24
fontsize_cblabel = 24
fontsize_tick = 24
fontsize_label_s = 16
fontsize_cblabel_s= 16
fontsize_tick_s = 16
fontsize_legend = 16
fontsize_legend_s = 12
cm.register_cmap(name='cmap_dens',
data={'red': [[0.0 , 0.0, 0.0],
[0.333333, 0.0, 0.0],
[0.666667, 0.0, 0.0],
[1.0 , 1.0, 1.0]],
'green': [[0.0 , 0.0, 0.0],
[0.333333, 0.0, 0.0],
[0.666667, 1.0, 1.0],
[1.0 , 1.0, 1.0]],
'blue': [[0.0 , 0.0, 0.0],
[0.333333, 1.0, 1.0],
[0.666667, 1.0, 1.0],
[1.0 , 1.0, 1.0]]})
cm.register_cmap(name='cmap_temp',
data={'red': [[0.0 , 0.0, 0.0],
[0.333333, 1.0, 1.0],
[0.666667, 1.0, 1.0],
[1.0 , 1.0, 1.0]],
'green': [[0.0 , 0.0, 0.0],
[0.333333, 0.0, 0.0],
[0.666667, 1.0, 1.0],
[1.0 , 1.0, 1.0]],
'blue': [[0.0 , 0.0, 0.0],
[0.333333, 0.0, 0.0],
[0.666667, 0.0, 0.0],
[1.0 , 1.0, 1.0]]})
outdir = 'fig'
HydrogenFractionByMass = 0.76
DeuteriumToHydrogenRatio = 3.4e-5 * 2.0
HeliumToHydrogenRatio = (1.0 - HydrogenFractionByMass) / HydrogenFractionByMass
SolarMetalFractionByMass = 0.01295
SolarIronAbundance = 7.50
progmass = [
r"$M_{\rm PopIII} = 13 \ {\rm M}_{\bigodot}$"
, r"$M_{\rm PopIII} = 50 \ {\rm M}_{\bigodot}$"
, r"$M_{\rm PopIII} = 80 \ {\rm M}_{\bigodot}$"
]
Fe_H = [
-9.24989440533554
, -7.937489132198783
, -8.279791819037703
]
A_C = [
3.7951320313852737
, 5.058492609804371
, 4.904347239142647
]
if ANALYTIC:
mu_C = 12.0
mu_Fe = 56.0
# C13 ######################
# Mmet = 1.0 # Msun
# M_C = 0.3 # Msun
# M_Fe = 0.1 # Msun
# N_cl = 3
Mmet = 1.5 # Msun
M_C = 0.5 # Msun
M_Fe = 0.2 # Msun
N_cl = 1
R_cl = 6 # pc
D_cl = 50 # pc
M_cloud = 2000.0 # Msun
f_ret = N_cl * (pi*R_cl**2) / (4*pi*D_cl**2)
Zmet_pred = f_ret * Mmet / M_cloud / SolarMetalFractionByMass
A_C_pred = 12.0 + np.log10(f_ret * M_C / mu_C / HydrogenFractionByMass / M_cloud)
Fe_H_pred = 12.0 + np.log10(f_ret * M_Fe/ mu_Fe/ HydrogenFractionByMass / M_cloud) - SolarIronAbundance
print("C13 Mmet %11.5f M_C %11.5f M_Fe %11.5f R_cl %11.5f D_cl %11.5f f_ret %11.5f M_cloud %11.1f A_C %7.1f Fe_H %7.1f Zmet %7.1e"
% (Mmet, M_C, M_Fe, R_cl, D_cl, f_ret, M_cloud, A_C_pred, Fe_H_pred, Zmet_pred) )
# F13 ######################
M_C = 0.08 # Msun
M_Fe = 1.0e-6 # Msun
N_cl = 1
R_cl = 6 # pc
D_cl = 50 # pc
M_cloud = 4000.0 # Msun
f_ret = N_cl * (pi*R_cl**2) / (4*pi*D_cl**2)
Zmet_pred = f_ret * Mmet / M_cloud / SolarMetalFractionByMass
A_C_pred = 12.0 + np.log10(f_ret * M_C / mu_C / HydrogenFractionByMass / M_cloud)
Fe_H_pred = 12.0 + np.log10(f_ret * M_Fe/ mu_Fe/ HydrogenFractionByMass / M_cloud) - SolarIronAbundance
print("F13 Mmet %11.5f M_C %11.5f M_Fe %11.3e R_cl %11.5f D_cl %11.5f f_ret %11.5f M_cloud %11.1f A_C %7.1f Fe_H %7.1f Zmet %7.1e"
% (Mmet, M_C, M_Fe, R_cl, D_cl, f_ret, M_cloud, A_C_pred, Fe_H_pred, Zmet_pred) )
# F80 ######################
M_C = 1.0 # Msun
M_Fe = 1.0e-5 # Msun
N_cl = 1
R_cl = 7 # pc
D_cl = 100 # pc
M_cloud = 1000.0 # Msun
f_ret = N_cl * (pi*R_cl**2) / (4*pi*D_cl**2)
Zmet_pred = f_ret * Mmet / M_cloud / SolarMetalFractionByMass
A_C_pred = 12.0 + np.log10(f_ret * M_C / mu_C / HydrogenFractionByMass / M_cloud)
Fe_H_pred = 12.0 + np.log10(f_ret * M_Fe/ mu_Fe/ HydrogenFractionByMass / M_cloud) - SolarIronAbundance
print("F80 Mmet %11.5f M_C %11.5f M_Fe %11.3e R_cl %11.5f D_cl %11.5f f_ret %11.5f M_cloud %11.1f A_C %7.1f Fe_H %7.1f Zmet %7.1e"
% (Mmet, M_C, M_Fe, R_cl, D_cl, f_ret, M_cloud, A_C_pred, Fe_H_pred, Zmet_pred) )
if DUST_PROPERTIES:
fn_abund = [
'/home/genchiaki/grackle_md/input/metaldustPopIII_M14_mix_M13_rev2.dat'
, '/home/genchiaki/grackle_md/input/metaldustPopIII_M14_mix_M50_rev2.dat'
, '/home/genchiaki/grackle_md/input/metaldustPopIII_M14_mix_M80_rev2.dat'
]
fn_dist = [
'/home/genchiaki/dust/ic/data/dist_Km_13_rev2.dat'
, '/home/genchiaki/dust/ic/data/dist_Km_50_rev2.dat'
, '/home/genchiaki/dust/ic/data/dist_Km_80_rev2.dat'
]
data_dist = [None] * 3
i_rad = 0
i_SiM = 1
i_FeM = 2
i_Mg2SiO4= 3
i_MgSiO3 = 4
i_Fe3O4 = 5
i_AC = 6
i_SiO2D = 7
i_MgO = 8
i_FeS = 9
i_Al2O3 = 10
r0_dust = [0.0]*51
dr0_dust = [0.0]*51
for irad in range(51):
r0_dust[irad] = 10.0**(-8.0+irad*0.1)
dr0_dust[irad] = 10.0**(-7.95+irad*0.1) - 10.0**(-8.05+irad*0.1)
s_AC = 2.23 # g/cc
n_AC = [0.0]*3
delta_r = [0.0]*3
for iSN in range(3):
# FROM INITIAL DATA
fp = open(fn_abund[iSN], 'rb')
Mfrac_C = struct.unpack('d', fp.read(8))[0]
Mfrac_O = struct.unpack('d', fp.read(8))[0]
Mfrac_Mg = struct.unpack('d', fp.read(8))[0]
Mfrac_Al = struct.unpack('d', fp.read(8))[0]
Mfrac_Si = struct.unpack('d', fp.read(8))[0]
Mfrac_S = struct.unpack('d', fp.read(8))[0]
Mfrac_Fe = struct.unpack('d', fp.read(8))[0]
print("%13.5e %13.5e %13.5e " % (Mfrac_C, Mfrac_O, Mfrac_Fe))
fcondC = struct.unpack('d', fp.read(8))[0]
fcondO = struct.unpack('d', fp.read(8))[0]
fcondMg = struct.unpack('d', fp.read(8))[0]
fcondAl = struct.unpack('d', fp.read(8))[0]
fcondSi = struct.unpack('d', fp.read(8))[0]
fcondS = struct.unpack('d', fp.read(8))[0]
fcondFe = struct.unpack('d', fp.read(8))[0]
# print("fcond_ini %13.5e %13.5e %13.5e %13.5e " % (fcondC, fcondO, fcondMg, fcondAl))
fp.close()
C_H = A_C[iSN] - 8.43
A_O = A_C[iSN] - np.log10(Mfrac_C / 12.0) + np.log10(Mfrac_O / 16.0)
O_H = A_O - 8.69
Dtrans = np.log10(10.0**C_H + 0.9 * 10.0**O_H)
print("Dtrans %13.7f C_H %13.7f O_H %13.7f" % (Dtrans, C_H, O_H))
data_dist[iSN] = np.loadtxt(fn_dist[iSN])
sum_r1df0 = 0.0
sum_r2df0 = 0.0
sum_r3df0 = 0.0
for irad in range(51):
sum_r1df0 += data_dist[iSN][irad, i_AC] * dr0_dust[irad] * r0_dust[irad]
sum_r2df0 += data_dist[iSN][irad, i_AC] * dr0_dust[irad] * r0_dust[irad] * r0_dust[irad]
sum_r3df0 += data_dist[iSN][irad, i_AC] * dr0_dust[irad] * r0_dust[irad] * r0_dust[irad] * r0_dust[irad]
rho_AC = fcondC * 10.0**(A_C[iSN]-12.0) * 12.0 * mp # with nH = 1 /cc
n_AC[iSN] = rho_AC / (4.0*pi/3.0 * s_AC * sum_r3df0)
# print("%13.5e %13.5e %13.5e" % (10.0**(A_C[iSN]-12.0), rho_AC, n_AC[iSN]))
# FROM SIMULATION
if iSN==0: fcondC1 = 6.28099e-01
if iSN==1: fcondC1 = 4.32772e-04
if iSN==2: fcondC1 = 3.68941e-02
print("fcondC %13.5e -> %13.5e " % (fcondC, fcondC1))
roots = np.roots([1.0, 3.0*sum_r1df0, 3.0*sum_r2df0, (1.0 - fcondC1 / fcondC)*sum_r3df0])
for iroot in range(3):
if roots[iroot].imag == 0.0:
delta_r[iSN] = roots[iroot].real
# print(delta_r[iSN])
rho_AC1 = fcondC1 * 10.0**(A_C[iSN]-12.0) * 12.0 * mp
# Dust density when all C is condensed ###################
fcondC2 = 1.0
rho_AC2 = fcondC2 * 10.0**(A_C[iSN]-12.0) * 12.0 * mp
log_yAC0 = np.log10(rho_AC /(12.0*mp))
log_yAC1 = np.log10(rho_AC1/(12.0*mp))
log_yAC2 = np.log10(rho_AC2/(12.0*mp))
##########################################################
print("D(AC) %13.5e -> %13.5e" % (rho_AC/(mp/0.76), rho_AC1/(mp/0.76)))
print("y(AC) %13.7f -> %13.7f (-> %13.7f)" % (log_yAC0, log_yAC1, log_yAC2))
sum_r2df1 = sum_r2df0 + 2.0*sum_r1df0*delta_r[iSN] + delta_r[iSN]**2
sum_r3df1 = sum_r3df0 + 3.0*sum_r2df0*delta_r[iSN] + 3.0*sum_r1df0*delta_r[iSN]**2 + delta_r[iSN]**3
n_AC1 = rho_AC1 / (4.0*pi/3.0 * s_AC * sum_r3df1)
print("n(AC) %13.5e -> %13.5e" % (n_AC[iSN], n_AC1))
print("r(AC) %13.5e -> %13.5e" % (sum_r3df0/sum_r2df0*1.0e4, sum_r3df1/sum_r2df1*1.0e4))
# PLOT
fig, ax = plt.subplots(figsize=(6.4,4.8), constrained_layout=True)
ax.tick_params(labelsize=fontsize_tick)
ax.set_xlabel(r"log [ Grain radius / ${\rm \mu m}$ ]", fontsize=fontsize_label)
ax.set_ylabel(r"log [ Number fraction / ${\rm \mu m ^{-1}}$ ]" , fontsize=fontsize_label)
ax.set_xlim([-3, 0])
ax.set_ylim([-21, -13])
ax.set_xticks(np.linspace(-3, 0, 4))
ax.set_xticks(np.linspace(-3, 0, 16), minor=True)
ax.set_yticks(np.linspace(-20,-14, 4))
ax.set_yticks(np.linspace(-21,-13, 9), minor=True)
ax.annotate(r'Amorphous carbon', xy=( 0.02, 0.98), xycoords=ax.transAxes, color='black', fontsize=fontsize_title, va='top' , ha='left')
ax.annotate(r'before grain growth', xy=(-1.1, -14.0), xycoords='data', color='black', fontsize=fontsize_legend, va='center' , ha='left')
ax.annotate(r'after grain growth' , xy=(-1.1, -14.5), xycoords='data', color='black', fontsize=fontsize_legend, va='center' , ha='left')
plot = ax.plot(
np.log10((data_dist[0][:, i_rad] + delta_r[0])*1.0e4), np.log10(n_AC[0] * data_dist[0][:, i_AC]/1.0e4)
, np.log10((data_dist[1][:, i_rad] + delta_r[1])*1.0e4), np.log10(n_AC[1] * data_dist[1][:, i_AC]/1.0e4)
, np.log10((data_dist[2][:, i_rad] + delta_r[2])*1.0e4), np.log10(n_AC[2] * data_dist[2][:, i_AC]/1.0e4)
, np.log10((data_dist[0][:, i_rad] )*1.0e4), np.log10(n_AC[0] * data_dist[0][:, i_AC]/1.0e4)
, np.log10((data_dist[1][:, i_rad] )*1.0e4), np.log10(n_AC[1] * data_dist[1][:, i_AC]/1.0e4)
, np.log10((data_dist[2][:, i_rad] )*1.0e4), np.log10(n_AC[2] * data_dist[2][:, i_AC]/1.0e4)
, [-1.5,-1.2], [-14.0, -14.0] # legend
, [-1.5,-1.2], [-14.5, -14.5] # legend
)
plot[0].set_linestyle("-"); plot[0].set_color("orange"); plot[0].set_linewidth(2)
plot[1].set_linestyle("-"); plot[1].set_color("purple"); plot[1].set_linewidth(2)
plot[2].set_linestyle("-"); plot[2].set_color("green") ; plot[2].set_linewidth(2)
plot[3].set_linestyle("--"); plot[3].set_color("orange"); plot[3].set_linewidth(2)
plot[4].set_linestyle("--"); plot[4].set_color("purple"); plot[4].set_linewidth(2)
plot[5].set_linestyle("--"); plot[5].set_color("green") ; plot[5].set_linewidth(2)
plot[6].set_linestyle("--"); plot[6].set_color("black") ; plot[6].set_linewidth(2) # legend
plot[7].set_linestyle("-"); plot[7].set_color("black") ; plot[7].set_linewidth(2) # legend
plt.legend(labelspacing=0.0, loc='lower right')
ax.legend(progmass, ncol=1, fontsize=fontsize_legend)
fig.savefig("%s/dist.pdf" % outdir)
if THERMAL_HISTORY:
i_time = 0
i_nH = 1
i_Tg = 2
i_elec = 3
i_HI = 4
i_HII = 5
i_HeI = 6
i_HeII = 7
i_HeIII = 8
i_HM = 9
i_H2I = 10
i_H2II = 11
i_DI = 12
i_DII = 13
i_HDI = 14
i_HeHII = 15
i_HDII = 16
i_DM = 17
i_CI = 18
i_CII = 19
i_CO = 20
i_CO2 = 21
i_OI = 22
i_OH = 23
i_H2O = 24
i_O2 = 25
i_SiI = 26
i_SiOI = 27
i_SiO2I = 28
i_CH = 29
i_CH2 = 30
i_COII = 31
i_OII = 32
i_OHII = 33
i_H2OII = 34
i_H3OII = 35
i_O2II = 36
i_Mg = 37
i_Al = 38
i_S = 39
i_Fe = 40
i_SiM = 41
i_FeM = 42
i_Mg2SiO4= 43
i_MgSiO3 = 44
i_Fe3O4 = 45
i_AC = 46
i_SiO2D = 47
i_MgO = 48
i_FeS = 49
i_Al2O3 = 50
i_edot_adia = 51
i_sigv = 52
i_cs = 53
i_axis0 = 54
i_axis1 = 55
i_axis2 = 56
i_edot_comp = 57
i_edot_brem = 58
i_edot_ion_H = 59
i_edot_rec_H = 60
i_edot_line_H = 61
i_edot_ion_He = 62
i_edot_rec_He = 63
i_edot_line_He = 64
i_edot_CIline = 65
i_edot_CIIline = 66
i_edot_OIline = 67
i_edot_H2line = 68
i_edot_H2cont = 69
i_edot_H2form = 70
i_edot_HDline = 71
i_edot_H2Oline = 72
i_edot_OHline = 73
i_edot_COline = 74
i_edot_dst_rad = 75
i_tau_cont = 76
progmass = [
r"$M_{\rm PopIII} = 13 \ {\rm M}_{\bigodot}$"
, r"$M_{\rm PopIII} = 50 \ {\rm M}_{\bigodot}$"
, r"$M_{\rm PopIII} = 80 \ {\rm M}_{\bigodot}$"
]
trace3D = [None] * 3
indir = "/home/genchiaki/scratch/enzo-dev/run/CosmologySimulation/TestPop3-L2_M14_M13"
pdir = indir + '/time_series'
fn_traceM13 = pdir + '/time_series_cool.dat'
trace3D[0] = np.loadtxt(fn_traceM13)
indir = "/home/genchiaki/scratch/enzo-dev/run/CosmologySimulation/TestPop3-L2_M14_M50"
pdir = indir + '/time_series'
fn_traceM50 = pdir + '/time_series_cool.dat'
trace3D[1] = np.loadtxt(fn_traceM50)
indir = "/home/genchiaki/scratch/enzo-dev/run/CosmologySimulation/TestPop3-L2_M14_M80"
pdir = indir + '/time_series'
fn_traceM80 = pdir + '/time_series_cool.dat'
trace3D[2] = np.loadtxt(fn_traceM80)
# Jeans mass
nH_J = [-1, 16]
M_J_p6 = [0.0]*2
M_J_p4 = [0.0]*2
M_J_p2 = [0.0]*2
M_J_p0 = [0.0]*2
M_J_m2 = [0.0]*2
M_J_m4 = [0.0]*2
for i in range(2):
M_J_p6[i] = np.log10( 200.0*(1.0e+6/(1.69e3*(1.23/1.23)**(-1.5)*(10.0**nH_J[i]/1.0e4)**(-0.5)))**(2.0/3.0) )
M_J_p4[i] = np.log10( 200.0*(1.0e+4/(1.69e3*(1.23/1.23)**(-1.5)*(10.0**nH_J[i]/1.0e4)**(-0.5)))**(2.0/3.0) )
M_J_p2[i] = np.log10( 200.0*(1.0e+2/(1.69e3*(1.23/1.23)**(-1.5)*(10.0**nH_J[i]/1.0e4)**(-0.5)))**(2.0/3.0) )
M_J_p0[i] = np.log10( 200.0*(1.0e+0/(1.69e3*(2.31/1.23)**(-1.5)*(10.0**nH_J[i]/1.0e4)**(-0.5)))**(2.0/3.0) )
M_J_m2[i] = np.log10( 200.0*(1.0e-2/(1.69e3*(2.31/1.23)**(-1.5)*(10.0**nH_J[i]/1.0e4)**(-0.5)))**(2.0/3.0) )
M_J_m4[i] = np.log10( 200.0*(1.0e-4/(1.69e3*(2.31/1.23)**(-1.5)*(10.0**nH_J[i]/1.0e4)**(-0.5)))**(2.0/3.0) )
# Density-Temperature/gamma/ellipticity
# nvar = 1
nvar = 3
if nvar==1: ysize = 4.8
if nvar==3: ysize =12.0
fig, axs = plt.subplots(nrows=nvar, ncols=1, figsize=(6.4,ysize), constrained_layout=True)
for ivar in range(nvar):
if nvar==1: ax = axs
else: ax = axs[ivar]
ax.tick_params(labelsize=fontsize_tick)
ax.set_xlim([0, 16])
if ivar==nvar-1: ax.set_xlabel(r"log [ Density / cm$^{-3}$ ]", fontsize=fontsize_label)
if nvar==1:
ax.set_ylabel(r"log [ Temperature / K ]", fontsize=fontsize_label)
else:
if ivar==0: ax.set_ylabel(r"log [ T / K ]" , fontsize=fontsize_label)
if ivar==1: ax.set_ylabel(r"$\gamma$" , fontsize=fontsize_label)
if ivar==2: ax.set_ylabel(r"log [ e ]" , fontsize=fontsize_label)
if ivar==0: ax.set_ylim([ 1.0, 3.5])
if ivar==1: ax.set_ylim([ 0.5, 1.5])
if ivar==2: ax.set_ylim([-0.5, 1.1])
if ivar<nvar-1: ax.tick_params(labelbottom=False, labelleft=True, labelright=False, labeltop=False)
ax.set_xticks(np.linspace( 0, 16, 5))
ax.set_xticks(np.linspace( 0, 16, 17), minor=True)
if nvar==1:
ax.set_yticks(np.linspace( 1.0, 3.0, 3))
ax.set_yticks(np.linspace( 1.0, 3.5, 7), minor=True)
if ivar==0:
xvar0 = np.log10(trace3D[0][:, i_nH])
yvar0 = np.log10(trace3D[0][:, i_Tg])
xvar1 = np.log10(trace3D[1][:, i_nH])
yvar1 = np.log10(trace3D[1][:, i_Tg])
xvar2 = np.log10(trace3D[2][:, i_nH])
yvar2 = np.log10(trace3D[2][:, i_Tg])
if ivar==1:
for iSN in range(3):
nnc = trace3D[iSN][:, i_time].size
xvar = [0.0]*(nnc-1); yvar = [0.0]*(nnc-1)
for inc in range(nnc-1):
log_x0 = np.log10(trace3D[iSN][inc , i_nH]); log_y0 = np.log10(trace3D[iSN][inc , i_Tg])
log_x1 = np.log10(trace3D[iSN][inc+1, i_nH]); log_y1 = np.log10(trace3D[iSN][inc+1, i_Tg])
xvar[inc] = (log_x1 + log_x0) / 2.0
yvar[inc] = (log_y1 - log_y0) / (log_x1 - log_x0) + 1.0
if iSN==0: xvar0 = xvar; yvar0 = yvar
if iSN==1: xvar1 = xvar; yvar1 = yvar
if iSN==2: xvar2 = xvar; yvar2 = yvar
if ivar==2:
xvar0 = np.log10(trace3D[0][:, i_nH])
yvar0 = np.log10(trace3D[0][:, i_axis0] / trace3D[0][:, i_axis2] - 1.0)
xvar1 = np.log10(trace3D[1][:, i_nH])
yvar1 = np.log10(trace3D[1][:, i_axis0] / trace3D[1][:, i_axis2] - 1.0)
xvar2 = np.log10(trace3D[2][:, i_nH])
yvar2 = np.log10(trace3D[2][:, i_axis0] / trace3D[2][:, i_axis2] - 1.0)
plot = ax.plot(
xvar0, yvar0
, xvar1, yvar1
, xvar2, yvar2
)
plot[0].set_linestyle("-"); plot[0].set_color("orange"); plot[0].set_linewidth(2)
plot[1].set_linestyle("-"); plot[1].set_color("purple"); plot[1].set_linewidth(2)
plot[2].set_linestyle("-"); plot[2].set_color("green") ; plot[2].set_linewidth(2)
if ivar==0:
plot_MJ = ax.plot(
nH_J[:], M_J_p6[:]
, nH_J[:], M_J_p4[:]
, nH_J[:], M_J_p2[:]
, nH_J[:], M_J_p0[:]
, nH_J[:], M_J_m2[:]
, nH_J[:], M_J_m4[:]
)
plot_MJ[0].set_linestyle(":"); plot_MJ[0].set_color("black") ; plot_MJ[0].set_linewidth(1)
plot_MJ[1].set_linestyle(":"); plot_MJ[1].set_color("black") ; plot_MJ[1].set_linewidth(1)
plot_MJ[2].set_linestyle(":"); plot_MJ[2].set_color("black") ; plot_MJ[2].set_linewidth(1)
plot_MJ[3].set_linestyle(":"); plot_MJ[3].set_color("black") ; plot_MJ[3].set_linewidth(1)
plot_MJ[4].set_linestyle(":"); plot_MJ[4].set_color("black") ; plot_MJ[4].set_linewidth(1)
plot_MJ[5].set_linestyle(":"); plot_MJ[5].set_color("black") ; plot_MJ[5].set_linewidth(1)
ax.annotate(r'$M_{\rm J} = 10^6 \ {\rm M}_{\bigodot}$', xy=( 0.0, 3.48), xycoords='data', color='black', fontsize=fontsize_legend, va='top' , ha='left' )
ax.annotate( r'$10^4 \ {\rm M}_{\bigodot}$', xy=( 6.0, 3.48), xycoords='data', color='black', fontsize=fontsize_legend, va='top' , ha='center')
ax.annotate( r'$10^2 \ {\rm M}_{\bigodot}$', xy=(10.0, 3.48), xycoords='data', color='black', fontsize=fontsize_legend, va='top' , ha='center')
ax.annotate( r'$1 \ {\rm M}_{\bigodot}$', xy=(13.0, 3.48), xycoords='data', color='black', fontsize=fontsize_legend, va='top' , ha='center')
ax.annotate( r'$10^{-2} \ {\rm M}_{\bigodot}$', xy=(16.0, 2.50), xycoords='data', color='black', fontsize=fontsize_legend, va='center', ha='right' )
if ivar==0:
plt.legend(labelspacing=0.0, loc='lower right')
ax.legend(progmass, ncol=1, fontsize=fontsize_legend)
if nvar == 1:
fig.savefig("%s/nT.pdf" % outdir)
if nvar == 3:
fig.savefig("%s/nTge.pdf" % outdir)
plt.close('all')
# Density-Abundance
progmass = [
r"(a) $M_{\rm PopIII} = 13 \ {\rm M}_{\bigodot}$"
, r"(b) $M_{\rm PopIII} = 50 \ {\rm M}_{\bigodot}$"
, r"(c) $M_{\rm PopIII} = 80 \ {\rm M}_{\bigodot}$"
]
fig, axs = plt.subplots(nrows=4, ncols=3, figsize=(18.0,16.0), constrained_layout=True, sharex='all')
## fig.suptitle(progmass[iSN], fontsize=fontsize_suptitle, fontweight='bold')
for iSN in range(3):
# H-baring species
ax=axs[0][iSN]
ax.annotate(progmass[iSN], xy=(0.03, 1.10), xycoords=ax.transAxes, color='black', fontsize=fontsize_title, va='top', ha='left')
if iSN==0: ax.set_ylabel(r"log [ Abundance ]" , fontsize=fontsize_label)
ax.set_xlim(0, 16)
ax.set_ylim(-12, 2)
ax.set_xticks(np.linspace( 0, 16, 5))
ax.set_xticks(np.linspace( 0, 16, 17), minor=True)
ax.set_yticks(np.linspace(-10, 0, 3))
ax.set_yticks(np.linspace(-12, 2, 15), minor=True)
ax.tick_params(labelsize=fontsize_tick)
if iSN>0: ax.tick_params(labelleft=False)
plot = ax.plot(
np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_elec])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_HI ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_HII ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_H2I ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_HM ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_H2II])
)
plot[0].set_linestyle("-"); plot[0].set_color("orange"); plot[0].set_linewidth(2)
plot[1].set_linestyle("-"); plot[1].set_color("black") ; plot[1].set_linewidth(2)
plot[2].set_linestyle("-"); plot[2].set_color("red") ; plot[2].set_linewidth(2)
plot[3].set_linestyle("-"); plot[3].set_color("blue") ; plot[3].set_linewidth(2)
plot[4].set_linestyle("--"); plot[4].set_color("purple"); plot[4].set_linewidth(2)
plot[5].set_linestyle("--"); plot[5].set_color("green") ; plot[5].set_linewidth(2)
if iSN == 0:
plt.legend(labelspacing=0.0, loc='lower right')
ax.legend([
r"e"
, r"H"
, r"H$^+$"
, r"H$_2$"
, r"H$^-$"
, r"H$_2^+$"
], ncol=2, fontsize=fontsize_legend)
# D-baring species
ax=axs[1][iSN]
if iSN==0: ax.set_ylabel(r"log [ Abundance ]" , fontsize=fontsize_label)
ax.set_xlim(0, 16)
ax.set_ylim(-17.5, -3.5)
ax.set_xticks(np.linspace( 0, 16, 5))
ax.set_xticks(np.linspace( 0, 16, 17), minor=True)
ax.set_yticks(np.linspace(-15, -5, 3))
ax.set_yticks(np.linspace(-17, -4, 14), minor=True)
ax.tick_params(labelsize=fontsize_tick)
if iSN>0: ax.tick_params(labelleft=False)
plot = ax.plot(
np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_DI ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_DII ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_HDI ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_DM ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_HDII])
)
plot[0].set_linestyle("-"); plot[0].set_color("black") ; plot[0].set_linewidth(2)
plot[1].set_linestyle("-"); plot[1].set_color("red") ; plot[1].set_linewidth(2)
plot[2].set_linestyle("-"); plot[2].set_color("blue") ; plot[2].set_linewidth(2)
plot[3].set_linestyle("--"); plot[3].set_color("purple"); plot[3].set_linewidth(2)
plot[4].set_linestyle("--"); plot[4].set_color("green") ; plot[4].set_linewidth(2)
if iSN == 0:
plt.legend(labelspacing=0.0, loc='lower right')
ax.legend([
r"D"
, r"D$^+$"
, r"HD"
, r"D$^-$"
, r"HD$^+$"
], ncol=2, fontsize=fontsize_legend)
# C-baring species
ax=axs[2][iSN]
if iSN==0: ax.set_ylabel(r"log [ Abundance ]" , fontsize=fontsize_label)
ax.set_xlim(0, 16)
ax.set_ylim(-19, -5)
ax.set_xticks(np.linspace( 0, 16, 5))
ax.set_xticks(np.linspace( 0, 16, 17), minor=True)
ax.set_yticks(np.linspace(-15, -5, 3))
ax.set_yticks(np.linspace(-19, -5, 15), minor=True)
ax.tick_params(labelsize=fontsize_tick)
if iSN>0: ax.tick_params(labelleft=False)
plot = ax.plot(
np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_CI ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_CII ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_CO ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_CO2 ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_AC ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_CH ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_CH2 ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_COII])
)
plot[0].set_linestyle("-"); plot[0].set_color("black") ; plot[0].set_linewidth(2)
plot[1].set_linestyle("-"); plot[1].set_color("red") ; plot[1].set_linewidth(2)
plot[2].set_linestyle("-"); plot[2].set_color("orange") ; plot[2].set_linewidth(2)
plot[3].set_linestyle("-"); plot[3].set_color("green") ; plot[3].set_linewidth(2)
plot[4].set_linestyle(":"); plot[4].set_color("black") ; plot[4].set_linewidth(2)
plot[5].set_linestyle("--"); plot[5].set_color("blue") ; plot[5].set_linewidth(2)
plot[6].set_linestyle("--"); plot[6].set_color("purple") ; plot[6].set_linewidth(2)
plot[7].set_linestyle("--"); plot[7].set_color("orange") ; plot[7].set_linewidth(2)
plt.legend(labelspacing=0.0, loc='lower right')
if iSN == 0:
ax.legend([
r"C"
, r"C$^+$"
, r"CO"
, r"CO$_2$"
, r"C (dust)"
, r"CH"
, r"CH$_2$"
, r"CO$^+$"
], ncol=2, fontsize=fontsize_legend)
# O-baring species
ax=axs[3][iSN]
ax.set_xlabel(r"log [ Density / cm$^{-3}$ ]", fontsize=fontsize_label)
if iSN==0: ax.set_ylabel(r"log [ Abundance ]" , fontsize=fontsize_label)
ax.set_xlim(0, 16)
ax.set_ylim(-19, -5)
ax.set_xticks(np.linspace( 0, 16, 5))
ax.set_xticks(np.linspace( 0, 16, 17), minor=True)
ax.set_yticks(np.linspace(-15, -5, 3))
ax.set_yticks(np.linspace(-19, -5, 15), minor=True)
ax.tick_params(labelsize=fontsize_tick)
if iSN>0: ax.tick_params(labelleft=False)
plot = ax.plot(
np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_OI ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_OH ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_H2O ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_O2 ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_OII ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_OHII ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_H2OII])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_H3OII])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(trace3D[iSN][:, i_O2II ])
)
plot[0].set_linestyle("-"); plot[0].set_color("black") ; plot[0].set_linewidth(2)
plot[1].set_linestyle("-"); plot[1].set_color("green") ; plot[1].set_linewidth(2)
plot[2].set_linestyle("-"); plot[2].set_color("blue") ; plot[2].set_linewidth(2)
plot[3].set_linestyle("-"); plot[3].set_color("orange"); plot[3].set_linewidth(2)
plot[4].set_linestyle(":"); plot[4].set_color("black") ; plot[4].set_linewidth(2)
plot[5].set_linestyle(":"); plot[5].set_color("green") ; plot[5].set_linewidth(2)
plot[6].set_linestyle(":"); plot[6].set_color("blue") ; plot[6].set_linewidth(2)
plot[7].set_linestyle(":"); plot[7].set_color("purple"); plot[7].set_linewidth(2)
plot[8].set_linestyle(":"); plot[8].set_color("orange"); plot[8].set_linewidth(2)
plt.legend(labelspacing=0.0, loc='lower right')
if iSN == 0:
ax.legend(["O"
, "OH"
, "H$_{2}$O"
, "O$_{2}$"
, "O$^{+}$"
, "OH$^{+}$"
, "H$_{2}$O$^{+}$"
, "H$_{3}$O$^{+}$"
, "O$_{2}$$^{+}$"
], ncol=2, fontsize=fontsize_legend)
plt.subplots_adjust(left = 0.07
, right = 0.98
, bottom = 0.07
, top = 0.96
, wspace = 0.08
, hspace = 0.00
)
fig.savefig("%s/ny.pdf" % (outdir))
plt.close('all')
# Cooling functions
fig, axs = plt.subplots(nrows=1, ncols=3, figsize=(18.0,5.0), constrained_layout=True, sharex='all')
## fig.suptitle(progmass[iSN], fontsize=fontsize_suptitle, fontweight='bold')
for iSN in range(3):
# H-baring species
ax=axs[iSN]
ax.annotate(progmass[iSN], xy=(0.03, 1.10), xycoords=ax.transAxes, color='black', fontsize=fontsize_title, va='top', ha='left')
ax.set_xlabel(r"log [ Density / cm$^{-3}$ ]", fontsize=fontsize_label)
if iSN==0: ax.set_ylabel(r"log [ Cooling rates / erg g$^{-1}$ s$^{-1}$ ]", fontsize=fontsize_label)
ax.set_xlim(0, 16)
ax.set_ylim(-6, 4)
ax.set_xticks(np.linspace( 0, 16, 5))
ax.set_xticks(np.linspace( 0, 16, 17), minor=True)
ax.set_yticks(np.linspace(-6, 4, 6))
ax.set_yticks(np.linspace(-6, 4, 11), minor=True)
ax.tick_params(labelsize=fontsize_tick)
if iSN>0: ax.tick_params(labelleft=False)
plot = ax.plot(
np.log10(trace3D[iSN][:, i_nH]), np.log10( trace3D[iSN][:, i_edot_adia ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_H2line ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10( trace3D[iSN][:, i_edot_H2form ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_H2form ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_HDline ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_CIline ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_CIIline])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_OIline ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_H2Oline])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_OHline ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_COline ])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_dst_rad])
, np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_H2cont ])
#### , np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_comp ])
#### , np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_brem ])
#### , np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_ion_H ])
#### , np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_rec_H ])
#### , np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_line_H ])
#### , np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_ion_He ])
#### , np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_rec_He ])
#### , np.log10(trace3D[iSN][:, i_nH]), np.log10(-trace3D[iSN][:, i_edot_line_He])
)
plot[ 0].set_linestyle("-"); plot[ 0].set_color("red"); plot[ 0].set_linewidth(2)
plot[ 1].set_linestyle("-"); plot[ 1].set_color("blue") ; plot[ 1].set_linewidth(2)
plot[ 2].set_linestyle("-"); plot[ 2].set_color("purple"); plot[ 2].set_linewidth(2)
plot[ 3].set_linestyle(":"); plot[ 3].set_color("purple"); plot[ 3].set_linewidth(2)
plot[ 4].set_linestyle("-"); plot[ 4].set_color("green"); plot[ 4].set_linewidth(2)
plot[ 5].set_linestyle(":"); plot[ 5].set_color("black"); plot[ 5].set_linewidth(2)
plot[ 6].set_linestyle(":"); plot[ 6].set_color("red"); plot[ 6].set_linewidth(2)
plot[ 7].set_linestyle(":"); plot[ 7].set_color("orange"); plot[ 7].set_linewidth(2)
plot[ 8].set_linestyle("--"); plot[ 8].set_color("dodgerblue"); plot[ 8].set_linewidth(2)
plot[ 9].set_linestyle("--"); plot[ 9].set_color("green") ; plot[ 9].set_linewidth(2)
plot[10].set_linestyle("--"); plot[10].set_color("orange"); plot[10].set_linewidth(2)
plot[11].set_linestyle("-"); plot[11].set_color("grey"); plot[11].set_linewidth(2)
plot[12].set_linestyle(":"); plot[12].set_color("blue"); plot[12].set_linewidth(2)
if iSN==0:
ax.annotate(r"adia" , xy=( 5.0,-1.5), xycoords='data', color="red" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"H$_2$" , xy=( 2.0,-3.0), xycoords='data', color="blue" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"form" , xy=(11.0, 3.0), xycoords='data', color="purple" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"diss" , xy=(15.0,-8.0), xycoords='data', color="purple" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"HD" , xy=( 4.0,-2.3), xycoords='data', color="green" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"CI" , xy=( 3.0,-5.5), xycoords='data', color="black" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"CII" , xy=( 3.0,-8.0), xycoords='data', color="red" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"OI" , xy=( 5.5,-3.7), xycoords='data', color="orange" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"H$_2$O" , xy=( 8.0, 0.5), xycoords='data', color="dodgerblue", fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"OH" , xy=(11.0,-4.0), xycoords='data', color="green" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"CO" , xy=(10.2,-2.8), xycoords='data', color="orange" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"dust" , xy=(13.5, 3.2), xycoords='data', color="grey" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
ax.annotate(r"CIE" , xy=(15.0, 0.5), xycoords='data', color="blue" , fontsize=fontsize_legend, va='center' , ha='center', zorder=4)
plt.subplots_adjust(left = 0.07
, right = 0.98
, bottom = 0.20
, top = 0.92
, wspace = 0.08
, hspace = 0.00
)
fig.savefig("%s/nL.pdf" % (outdir))
plt.close('all')
if MASS_HISTORY:
i_redshift = 0
i_time = 1
i_Rvir = 2
i_Mvir_dm = 3
i_halo_Mgas = 4
i_halo_Mmet = 5
i_halo_MC = 6
i_halo_MO = 7
i_halo_MFe = 8
i_enr_Mgas = 9
i_enr_Mmet = 10
i_enr_MC = 11
i_enr_MO = 12
i_enr_MFe = 13
i_ljeans = 14
i_nHmax = 15
i_cloud_Mgas = 16
i_cloud_Mmet = 17
i_cloud_MC = 18
i_cloud_MO = 19
i_cloud_MFe = 20
i_core_MC = 21
i_core_MCdust = 22
progmass = [
r"$M_{\rm PopIII} = 13 \ {\rm M}_{\bigodot}$"
, r"$M_{\rm PopIII} = 50 \ {\rm M}_{\bigodot}$"
, r"$M_{\rm PopIII} = 80 \ {\rm M}_{\bigodot}$"
]
trace3D = [None] * 4
indir = "/home/genchiaki/scratch/enzo-dev/run/CosmologySimulation/TestPop3-L2_M14_M13"
pdir = indir + '/time_series'
fn_traceM13 = pdir + '/time_series_mass.dat'
trace3D[0] = np.loadtxt(fn_traceM13)
indir = "/home/genchiaki/scratch/enzo-dev/run/CosmologySimulation/TestPop3-L2_M14_M50"
pdir = indir + '/time_series'
fn_traceM50 = pdir + '/time_series_mass.dat'
trace3D[1] = np.loadtxt(fn_traceM50)
indir = "/home/genchiaki/scratch/enzo-dev/run/CosmologySimulation/TestPop3-L2_M14_M80"
pdir = indir + '/time_series'
fn_traceM80 = pdir + '/time_series_mass.dat'
trace3D[2] = np.loadtxt(fn_traceM80)
indir = "/home/genchiaki/scratch/enzo-dev/run/CosmologySimulation/TestPop3-L2_cgrackle_HR2"
pdir = indir + '/time_series'
fn_traceC13 = pdir + '/time_series_mass.dat'
trace3D[3] = np.loadtxt(fn_traceC13)
# trace3D[0][trace3D[0] <= 1.0e-8] = None
# trace3D[1][trace3D[1] <= 1.0e-8] = None
# trace3D[2][trace3D[2] <= 1.0e-8] = None
# trace3D[3][trace3D[3] <= 1.0e-8] = None
time_sf = 364.3
time_life = [11.8, 3.49, 3.03]
nvar = 1
if nvar==1: ysize = 5.2
if nvar==3: ysize =12.0
# fig, axs = plt.subplots(nrows=nvar, ncols=1, figsize=(6.4,ysize), constrained_layout=True)
# for ivar in range(nvar):
# if nvar==1: ax = axs
# else: ax = axs[ivar]
# ax.tick_params(labelsize=fontsize_tick)
# if ivar==nvar-1: ax.set_xlabel(r"log [ Time from star formation / Myr ]", fontsize=fontsize_label)
# if nvar==1:
# ax.set_ylabel(r"log [ Mass / M$_{\bigodot}$ ]", fontsize=fontsize_label)
# t_max = max(trace3D[2][:, i_time]) - time_sf
# ax.set_xlim([np.log10(1.0), np.log10(t_max)])
# # Plot data ###
# plot_dm = ax.plot(
# np.log10(trace3D[0][:, i_time] - time_sf), np.log10(trace3D[0][:, i_Mvir_dm])
# , np.log10(trace3D[1][:, i_time] - time_sf), np.log10(trace3D[1][:, i_Mvir_dm])
# , np.log10(trace3D[2][:, i_time] - time_sf), np.log10(trace3D[2][:, i_Mvir_dm])
# )
# plot_dm[0].set_linestyle("-"); plot_dm[0].set_color("orange"); plot_dm[0].set_linewidth(2)
# plot_dm[1].set_linestyle("-"); plot_dm[1].set_color("purple"); plot_dm[1].set_linewidth(2)
# plot_dm[2].set_linestyle("-"); plot_dm[2].set_color("green" ); plot_dm[2].set_linewidth(2)
# plot_ba = ax.plot(
# np.log10(trace3D[0][:, i_time] - time_sf), np.log10(trace3D[0][:, i_halo_Mgas])
# , np.log10(trace3D[1][:, i_time] - time_sf), np.log10(trace3D[1][:, i_halo_Mgas])
# , np.log10(trace3D[2][:, i_time] - time_sf), np.log10(trace3D[2][:, i_halo_Mgas])
# )
# plot_ba[0].set_linestyle("--"); plot_ba[0].set_color("orange"); plot_ba[0].set_linewidth(2)
# plot_ba[1].set_linestyle("--"); plot_ba[1].set_color("purple"); plot_ba[1].set_linewidth(2)
# plot_ba[2].set_linestyle("--"); plot_ba[2].set_color("green" ); plot_ba[2].set_linewidth(2)
# X_exp0 = [time_life[0], time_life[0]]; Y_exp0 = [4.0, 7.0]
# X_exp1 = [time_life[1], time_life[1]]; Y_exp1 = [4.0, 7.0]
# X_exp2 = [time_life[2], time_life[2]]; Y_exp2 = [4.0, 7.0]
# plot_ba = ax.plot(
# np.log10(X_exp0), Y_exp0
# , np.log10(X_exp1), Y_exp1
# , np.log10(X_exp2), Y_exp2
# )
# plot_ba[0].set_linestyle(":"); plot_ba[0].set_color("orange"); plot_ba[0].set_linewidth(2)
# plot_ba[1].set_linestyle(":"); plot_ba[1].set_color("purple"); plot_ba[1].set_linewidth(2)
# plot_ba[2].set_linestyle(":"); plot_ba[2].set_color("green" ); plot_ba[2].set_linewidth(2)
# ax.set_ylim(4.0, 7.0)
# if ivar==0:
# plt.legend(labelspacing=0.0, loc='lower right')
# ax.legend(progmass, ncol=1, fontsize=fontsize_legend)
# # Redshift ticks ###
# redshift_ticks = [12, 11, 10, 9, 8, 7]
# time_ticks = [0.0]*6
# redshift_list = np.flip(trace3D[2][:, i_redshift], axis=0)
# time_list = np.flip(trace3D[2][:, i_time] , axis=0)
# for itime in range(6):
# time_ticks[itime] = np.interp(redshift_ticks[itime], redshift_list, time_list)
# time_ticks[itime] = np.log10(time_ticks[itime] - time_sf)
# ax2 = ax.twiny()
# ax2.set_xlim(ax.get_xlim())
# ax2.set_xticks(time_ticks)
# ax2.set_xticklabels(redshift_ticks)
# ax2.tick_params(labelsize=fontsize_tick)
# ax2.set_xlabel(r"Redshift", fontsize=fontsize_label)
# fig.savefig("%s/tm.pdf" % outdir)
# metal mass
### in halo
for ivar in range(6):
if ivar == 0: var = 'gas'
if ivar == 1: var = 'met'
if ivar == 2: var = 'fmet'
if ivar == 3: var = 'Zmet'
if ivar == 4: var = 'AC'
if ivar == 5: var = 'FeH'
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(6.4, 5.2), constrained_layout=True)
ax.tick_params(labelsize=fontsize_tick)
##### if iregion == 0: ax.set_xlabel(r"log [ Time from star formation / Myr ]", fontsize=fontsize_label)
##### if iregion == 1: ax.set_xlabel(r"log [ Density / cm$^{-3}$ ]", fontsize=fontsize_label)
ax.set_xlabel(r"log [ Density / cm$^{-3}$ ]", fontsize=fontsize_label)
for iregion in range(2):
if iregion == 0: region = 'halo'
if iregion == 1: region = 'cloud'
if ivar == 0: ax.set_ylabel(r"Gas mass in %s [ M$_{\bigodot}$ ]" % region, fontsize=fontsize_label)
if ivar == 1: ax.set_ylabel(r"Metal mass in %s [ M$_{\bigodot}$ ]" % region, fontsize=fontsize_label)
if ivar == 2: ax.set_ylabel(r"Metal mass frac. in %s" % region, fontsize=fontsize_label)
if ivar == 3: ax.set_ylabel(r"Metallicity in %s [ Z$_{\bigodot}$ ]" % region, fontsize=fontsize_label)
if ivar == 4: ax.set_ylabel(r"$A$(C) in %s" % region, fontsize=fontsize_label)
if ivar == 5: ax.set_ylabel(r"[Fe/H] in %s" % region, fontsize=fontsize_label)
##### if iregion == 0:
##### t_max = max(trace3D[2][:, i_time]) - time_sf
##### ax.set_xlim([np.log10(1.0), np.log10(t_max)])
# Plot data ###
for iSN in range(4):
##### if iregion == 0: XX = np.log10(trace3D[iSN][:, i_time] - time_sf)
##### if iregion == 1: XX = np.log10(trace3D[iSN][:, i_nHmax])
XX = np.log10(trace3D[iSN][:, i_nHmax])
if ivar == 0:
if iregion == 0:
YY = trace3D[iSN][:, i_halo_Mgas ]
if iregion == 1:
YY = trace3D[iSN][:, i_cloud_Mgas]
if ivar == 1:
if iregion == 0:
YY = trace3D[iSN][:, i_halo_Mmet ]
if iregion == 1:
YY = trace3D[iSN][:, i_cloud_Mmet]
if ivar == 2:
if iregion == 0:
YY = trace3D[iSN][:, i_halo_Mmet ]/trace3D[iSN][:, i_enr_Mmet]
## print("f_Z halo")
## for iY in range (YY.size):
## print(" %11.5f %11.5f" % (XX[iY], YY[iY]))
if iregion == 1:
YY = trace3D[iSN][:, i_cloud_Mmet]/trace3D[iSN][:, i_enr_Mmet]
## print("enr_MC")
## if iSN == 0: print(6.69235e-01*trace3D[iSN][:, i_enr_Mmet])
## if iSN == 1: print(2.79167e-01*trace3D[iSN][:, i_enr_Mmet])
## if iSN == 2: print(2.52563e-01*trace3D[iSN][:, i_enr_Mmet])
## if iSN == 3: print(2.65314e-01*trace3D[iSN][:, i_enr_Mmet])
## print("enr_MFe")
## if iSN == 0: print(8.90341e-06*trace3D[iSN][:, i_enr_Mmet])
## if iSN == 1: print(4.15804e-06*trace3D[iSN][:, i_enr_Mmet])
## if iSN == 2: print(2.43915e-06*trace3D[iSN][:, i_enr_Mmet])
## if iSN == 3: print(9.62448e-02*trace3D[iSN][:, i_enr_Mmet])
if ivar == 3:
if iregion == 0:
YY = trace3D[iSN][:, i_halo_Mmet] /trace3D[iSN][:, i_halo_Mgas] /SolarMetalFractionByMass
if iregion == 1:
YY = trace3D[iSN][:, i_cloud_Mmet]/trace3D[iSN][:, i_cloud_Mgas] /SolarMetalFractionByMass
print("Z cloud")
for iY in range (YY.size):
print(" %11.3e %11.3e" % (trace3D[iSN][iY, i_cloud_Mmet]/trace3D[iSN][iY, i_cloud_Mgas], YY[iY]))
if ivar == 4:
if iregion == 0:
if iSN == 0: YY = 12.0 + np.log10(6.69235e-01*trace3D[iSN][:, i_halo_Mmet ]/12.0/HydrogenFractionByMass/trace3D[iSN][:, i_halo_Mgas ])
if iSN == 1: YY = 12.0 + np.log10(2.79167e-01*trace3D[iSN][:, i_halo_Mmet ]/12.0/HydrogenFractionByMass/trace3D[iSN][:, i_halo_Mgas ])
if iSN == 2: YY = 12.0 + np.log10(2.52563e-01*trace3D[iSN][:, i_halo_Mmet ]/12.0/HydrogenFractionByMass/trace3D[iSN][:, i_halo_Mgas ])
if iSN == 3: YY = 12.0 + np.log10(2.65314e-01*trace3D[iSN][:, i_halo_Mmet ]/12.0/HydrogenFractionByMass/trace3D[iSN][:, i_halo_Mgas ])
YY = 12.0 + np.log10(trace3D[iSN][:, i_halo_MC ]/12.0/HydrogenFractionByMass/trace3D[iSN][:, i_halo_Mgas])
if iregion == 1:
if iSN == 0: YY = 12.0 + np.log10(6.69235e-01*trace3D[iSN][:, i_cloud_Mmet]/12.0/HydrogenFractionByMass/trace3D[iSN][:, i_cloud_Mgas])
if iSN == 1: YY = 12.0 + np.log10(2.79167e-01*trace3D[iSN][:, i_cloud_Mmet]/12.0/HydrogenFractionByMass/trace3D[iSN][:, i_cloud_Mgas])
if iSN == 2: YY = 12.0 + np.log10(2.52563e-01*trace3D[iSN][:, i_cloud_Mmet]/12.0/HydrogenFractionByMass/trace3D[iSN][:, i_cloud_Mgas])
if iSN == 3: YY = 12.0 + np.log10(2.65314e-01*trace3D[iSN][:, i_cloud_Mmet]/12.0/HydrogenFractionByMass/trace3D[iSN][:, i_cloud_Mgas])
## YY2 = 12.0 + np.log10(trace3D[iSN][:, i_cloud_MC]/12.0/HydrogenFractionByMass/trace3D[iSN][:, i_cloud_Mgas])
## print("A(C)")
## for iY in range (YY.size):
## print(" %7.2f %7.2f" % (YY[iY], YY2[iY]))
if ivar == 5:
if iregion == 0:
if iSN == 0: YY = 12.0 + np.log10(8.90341e-06*trace3D[iSN][:, i_halo_Mmet ] /56.0/HydrogenFractionByMass/trace3D[iSN][:, i_halo_Mgas ]) - SolarIronAbundance
if iSN == 1: YY = 12.0 + np.log10(4.15804e-06*trace3D[iSN][:, i_halo_Mmet ] /56.0/HydrogenFractionByMass/trace3D[iSN][:, i_halo_Mgas ]) - SolarIronAbundance
if iSN == 2: YY = 12.0 + np.log10(2.43915e-06*trace3D[iSN][:, i_halo_Mmet ] /56.0/HydrogenFractionByMass/trace3D[iSN][:, i_halo_Mgas ]) - SolarIronAbundance
if iSN == 3: YY = 12.0 + np.log10(9.62448e-02*trace3D[iSN][:, i_halo_Mmet ] /56.0/HydrogenFractionByMass/trace3D[iSN][:, i_halo_Mgas ]) - SolarIronAbundance
YY2 = 12.0 + np.log10(trace3D[iSN][:, i_halo_MFe] /56.0/HydrogenFractionByMass/trace3D[iSN][:, i_halo_Mgas]) - SolarIronAbundance
if iregion == 1:
if iSN == 0: YY = 12.0 + np.log10(8.90341e-06*trace3D[iSN][:, i_cloud_Mmet] /56.0/HydrogenFractionByMass/trace3D[iSN][:, i_cloud_Mgas]) - SolarIronAbundance
if iSN == 1: YY = 12.0 + np.log10(4.15804e-06*trace3D[iSN][:, i_cloud_Mmet] /56.0/HydrogenFractionByMass/trace3D[iSN][:, i_cloud_Mgas]) - SolarIronAbundance
if iSN == 2: YY = 12.0 + np.log10(2.43915e-06*trace3D[iSN][:, i_cloud_Mmet] /56.0/HydrogenFractionByMass/trace3D[iSN][:, i_cloud_Mgas]) - SolarIronAbundance
if iSN == 3: YY = 12.0 + np.log10(9.62448e-02*trace3D[iSN][:, i_cloud_Mmet] /56.0/HydrogenFractionByMass/trace3D[iSN][:, i_cloud_Mgas]) - SolarIronAbundance
## YY2 = 12.0 + np.log10(trace3D[iSN][:, i_cloud_MFe]/56.0/HydrogenFractionByMass/trace3D[iSN][:, i_cloud_Mgas]) - SolarIronAbundance
## print("[Fe/H]")
## for iY in range (YY.size):
## print(" %7.2f %7.2f" % (YY[iY], YY2[iY]))
if ivar < 4:
YY[YY <= 1.0e-8] = None
plot_tm = ax.semilogy(XX[:], YY[:])
else:
if ivar == 4: YY[YY <= 0.0] = None
if ivar == 5: YY[YY <= -12.0] = None
plot_tm = ax.plot(XX[:], YY[:])
if iregion == 0:
if iSN == 0: plot_tm[0].set_linestyle("--"); plot_tm[0].set_color("orange"); plot_tm[0].set_linewidth(2)