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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
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
from yt.units import mh, kboltz, G
pi = 3.14159265
WIN10 = True
RAY = True
RAY_C = True
SLICE = False # True
PROF = False # True
TABLE = False
PRESEN = False
extension = 'pdf'
if WIN10:
import matplotlib.font_manager as font_manager
font_dirs = ['/mnt/c/Windows/Fonts', ]
font_files = font_manager.findSystemFonts(fontpaths=font_dirs)
font_list = font_manager.createFontList(font_files)
font_manager.fontManager.ttflist.extend(font_list)
if WIN10:
plt.rcParams['font.family'] = 'Times New Roman'
else:
plt.rcParams['font.family'] = 'P052'
# plt.rcParams['font.family'] = 'stix'
plt.rcParams["mathtext.fontset"] = "stix"
fontsize_suptitle = 32
fontsize_suptitle_s = 18
fontsize_title = 32
fontsize_title_s = 28
fontsize_boxsize = 32
fontsize_label = 32
fontsize_cblabel = 28
fontsize_tick = 28
fontsize_label_s = 22
fontsize_cblabel_s= 22
fontsize_tick_s = 22
fontsize_legend = 20
fontsize_legend_s = 16
indir = 'fig2'
#indir = 'test512-L2_1stP3m_TestB'
HydrogenFractionByMass = 0.76
DeuteriumToHydrogenRatio = 3.4e-5 * 2.0
HeliumToHydrogenRatio = (1.0 - HydrogenFractionByMass) / HydrogenFractionByMass
SolarMetalFractionByMass = 0.01295
SolarIronAbundance = 7.50
def Q_HI(m):
x = np.log10(m)
x2 = x * x
if m > 9 and m <= 500:
return 10.0**(43.61 + 4.9*x - 0.83*x2)
elif m > 5 and m <= 9:
return 10.0**(39.29 + 8.55*x)
else:
return 0
def Q_HeI(m):
x = np.log10(m)
x2 = x * x
if m > 9 and m <= 500:
return 10.0**(42.51 + 5.69*x - 1.01*x2)
elif m > 5 and m <= 9:
return 10.0**(29.24 + 18.49*x)
else:
return 0
def Q_HeII(m):
x = np.log10(m)
x2 = x * x
if m > 9 and m <= 500:
return 10.0**(26.71 + 18.14*x - 3.58*x2)
elif m > 5 and m <= 9:
return 10.0**(26.71 + 18.14*x - 3.58*x2)
else:
return 0
def Q_LW(m):
x = np.log10(m)
x2 = x * x
if m > 9 and m <= 500:
return 10.0**(44.03 + 4.59*x - 0.77*x2)
elif m > 5 and m <= 9:
return 10.0**(44.03 + 4.59*x - 0.77*x2)
else:
return 0
def f_shield_H2I_WH11(NH2I, T):
x = NH2I / 5e14
# print("%13.5e %13.5e" % (NH2I, x))
b_doppler = np.sqrt(2.0 * kboltz.d * T / mh.d) / 1e5
# print("%13.5e %13.5e %13.5e %13.5e" % (kboltz.d, T, mh.d, b_doppler))
f_shield = 0.965 / (1.0 + x/b_doppler)**1.1 + 0.035 * np.exp(-8.5e-4 * np.sqrt(1.0 + x))/np.sqrt(1.0 + x)
return f_shield
def Jeans_length(nH, T):
rho = nH * mh.d / HydrogenFractionByMass
gamma = 5.0/3.0
mu = 1.23 * mh.d
cs2 = gamma * kboltz.d * T / mu
return np.sqrt(pi * cs2 / (G.d * rho))
def t_ff(nH):
rho = nH * mh.d / HydrogenFractionByMass
return np.sqrt(3.0*pi/(32.0*G.d*rho))
def k7(T):
return 3.0e-16 * (T/3.e2)**0.95 * np.exp(-T/9.32e3)
def k8(T):
return 1.35e-9*(T**9.8493e-2 + 3.2852e-1 * T**5.5610e-1 + 2.771e-7 * T**2.1826) \
/ (1. + 6.191e-3 * T**1.0461 + 8.9712e-11 * T**3.0424 + 3.2576e-14 * T**3.7741)
# k7 = 3.0e-16_DKIND * (T/3.e2_DKIND)**0.95_DKIND
# & * exp(-T/9.32e3_DKIND) / kunit
# k8 = 1.35e-9_DKIND*(T**9.8493e-2_DKIND + 3.2852e-1_DKIND
# & * T**5.5610e-1_DKIND + 2.771e-7_DKIND * T**2.1826_DKIND)
# & / (1._DKIND + 6.191e-3_DKIND * T**1.0461_DKIND
# & + 8.9712e-11_DKIND * T**3.0424_DKIND
# & + 3.2576e-14_DKIND * T**3.7741_DKIND) / kunit
# 1.35\E{-9} \frac{T^{9.8493\E{-2}} + 3.2852\E{-1} T^{5.5610\E{-1}} + 2.771\E{-7} T^{2.1826}}
# {1.0 + 6.191\E{-3} T^{1.0461} + 8.9712\E{-11} T^{3.0424} + 3.2576\E{-14} T^{3.7741}}
#def z2t(redshift):
# return 10.3438263 * (141.0 / (redshift + 1.0))**(3.0/2.0) ## Myr
#print(z2t(25.034418454577) - z2t(25.075830449034), t_ff(1e6)/3.1557e13)
TopGridDimension = int(sys.argv[1])
NestedLevel = int(sys.argv[2])
Threshold = sys.argv[3]
Test = sys.argv[4]
Test_name = ['TestA', 'TestB', 'TestC']
Test_text = ['(a) Test A', '(b) Test B', '(c) Test C']
inumber0 = int(sys.argv[5])
inumber1 = int(sys.argv[6])
inumber2 = int(sys.argv[7])
colors = ['red', 'green', 'blue']
if RAY:
i_rad = 0
i_nH = 1
i_Tg = 2
i_yHI = 3
i_yelec = 4
i_yH2I = 5
i_yHM = 6
i_kHI = 7
i_kH2It = 8
i_kH2I0 = 9
i_sH2I = 10
i_NH2I = 11
i_kH2I = 12
i_sH2I1 = 13
i_NH2I1 = 14
i_kH2I1 = 15
i_sH2I3 = 16
i_NH2I3 = 17
i_kH2I3 = 18
i_kHDIt = 19
i_kHDI0 = 20
i_sHDI = 21
i_NHDI = 22
i_kHDI = 23
i_sHDI1 = 24
i_NHDI1 = 25
i_kHDI1 = 26
i_sHDI3 = 27
i_NHDI3 = 28
i_kHDI3 = 29
data_prof = [None] * 3
for inumber in range(inumber0, inumber1+1, inumber2):
# READ DATA
# fn_prof = [
# 'test512-L2_1stP3_TestA/Profile-1d_%04d.dat' % inumber
# , 'test512-L2_1stP3_TestB/Profile-1d_%04d.dat' % inumber
# , 'test512-L2_1stP3_TestC/Profile-1d_%04d.dat' % inumber
# ]
for iTest in range(3):
# for iTest in [1]:
outdir = 'test%d-L%d_%s_%s/' % (TopGridDimension, NestedLevel, Threshold, Test_name[iTest])
fn_prof = outdir + 'Profile-1d_%04d.dat' % (inumber)
print(fn_prof)
data_prof[iTest] = np.loadtxt(fn_prof)
fp_Dfront = open(indir + '/ray_Dfront_test%d-L%d_%s_%04d.dat' % (TopGridDimension, NestedLevel, Threshold, inumber), mode='w')
fp_H2ring = open(indir + '/ray_H2ring_test%d-L%d_%s_%04d.dat' % (TopGridDimension, NestedLevel, Threshold, inumber), mode='w')
# Time
outdir = 'test%d-L%d_%s_%s/' % (TopGridDimension, NestedLevel, Threshold, Test_name[iTest])
fn_star = outdir + 'Stars_PopIII_%04d.dat' % (inumber)
starfp = open(fn_star, 'rb')
nPopIII = struct.unpack('i', starfp.read(4))[0]
xPopIII = np.zeros(nPopIII)
yPopIII = np.zeros(nPopIII)
zPopIII = np.zeros(nPopIII)
cPopIII = np.zeros(nPopIII)
tPopIII = np.zeros(nPopIII)
dPopIII = np.zeros(nPopIII)
MPopIII = np.zeros(nPopIII)
for iPopIII in range(nPopIII):
xPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
yPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
zPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
cPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
dPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
tPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
MPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
starfp.close()
iPopIII0 = np.argmin(cPopIII)
t_SF = tPopIII[iPopIII0]
# maximum nH and yH2
# print("nH max")
x_nHmax = np.zeros(3)
x_Dfront_min = np.zeros(3)
x_Dfront_max = np.zeros(3)
x_H2ring_min = np.zeros(3)
x_H2ring_max = np.zeros(3)
for iTest in range(3):
# for iTest in [1]:
# print("#", Test_name[iTest])
i_nHmax = np.argmax(data_prof[iTest][:, i_nH])
x_nHmax[iTest] = data_prof[iTest][i_nHmax, i_rad]
nH_nHmax = data_prof[iTest][i_nHmax, i_nH]
Tg_nHmax = data_prof[iTest][i_nHmax, i_Tg]
yHI_nHmax = data_prof[iTest][i_nHmax, i_yHI ]
yelec_nHmax = data_prof[iTest][i_nHmax, i_yelec]
yH2I_nHmax = data_prof[iTest][i_nHmax, i_yH2I ]
yHM_nHmax = data_prof[iTest][i_nHmax, i_yHM ]
NH2I0_nHmax = data_prof[iTest][i_nHmax, i_NH2I ]
NH2I1_nHmax = data_prof[iTest][i_nHmax, i_NH2I1]
NH2I3_nHmax = data_prof[iTest][i_nHmax, i_NH2I3]
if iTest == 0:
NH2I_nHmax = data_prof[iTest][i_nHmax, i_NH2I ]
if iTest == 1:
NH2I_nHmax = data_prof[iTest][i_nHmax, i_NH2I1]
if iTest == 2:
NH2I_nHmax = data_prof[iTest][i_nHmax, i_NH2I3]
if iTest == 0:
kH2I_nHmax = data_prof[iTest][i_nHmax, i_kH2I ]
if iTest == 1:
kH2I_nHmax = data_prof[iTest][i_nHmax, i_kH2I1]
if iTest == 2:
kH2I_nHmax = data_prof[iTest][i_nHmax, i_kH2I3]
# shielding fraction
f_shield = f_shield_H2I_WH11(NH2I_nHmax, Tg_nHmax)
# shell width
i_Dfront, = np.where(data_prof[iTest][:, i_nH] > 0.1 * nH_nHmax)
if False:
x_Dfront_min[iTest] = np.min(data_prof[iTest][i_Dfront, i_rad])
x_Dfront_max[iTest] = np.max(data_prof[iTest][i_Dfront, i_rad])
else:
i_Dfront_min = np.min(i_Dfront)
i_Dfront_max = np.max(i_Dfront)
x_Dfront_min[iTest] = 10.0**np.interp(np.log10(0.1 * nH_nHmax)
, np.log10(data_prof[iTest][i_Dfront_min-1:i_Dfront_min+1, i_nH ])
, np.log10(data_prof[iTest][i_Dfront_min-1:i_Dfront_min+1, i_rad]))
x_Dfront_max[iTest] = 10.0**np.interp(np.log10(0.1 * nH_nHmax)
, np.log10(data_prof[iTest][i_Dfront_max+1:i_Dfront_max-1:-1, i_nH ])
, np.log10(data_prof[iTest][i_Dfront_max+1:i_Dfront_max-1:-1, i_rad]))
dx_Dfront = x_Dfront_max[iTest] - x_Dfront_min[iTest]
print("#", Test_name[iTest])
if iTest == 0:
# J_LW
# reference values
E_LW = 1.60184e-12 * 12.8 # erg
x_ref = 100.00 # pc
Q_ref = 8e47 # s^-1
fsh_ref = 1.0
Dnu = 1.60184e-12 * (13.6-11.2) / 6.63e-27
J_LW = (E_LW * Q_ref) / (4.0 * np.pi * (x_ref * 3.0856e18)**2) / Dnu / (4.0*np.pi) * fsh_ref
print("J_LW %13.7e" % J_LW)
if iTest == 0:
# calculate the H2 dissociation/formation timescales
# from simulation
print("%13.5e %13.5e" % (
1.0 / kH2I_nHmax
, yH2I_nHmax / (k8(Tg_nHmax) * yHI_nHmax * yHM_nHmax * nH_nHmax)))
# reference values
x_ref = 0.16 # pc
Q_ref = 8e47 # s^-1
fsh_ref = 0.7
tdiss = (4.0 * np.pi * (x_ref * 3.0856e18)**2) / (Q_ref * 3.71e-18) / fsh_ref
print("tdiss %13.7f %13.7e %13.7f %13.5e" % (
x_ref
, Q_ref
, fsh_ref
, tdiss ))
yH2I_ref = 2e-10
yHI_ref = 1.0
yHM_ref = 5e-14
nH_ref = 1e6
k8_ref = 3e-9
tform = yH2I_ref / (k8_ref * yHI_ref * yHM_ref * nH_ref)
print("tform %13.5e %13.5e %13.5e %13.5e %13.5e %13.5e" % (
yH2I_ref
, yHI_ref
, yHM_ref
, nH_ref
, k8_ref
, tform ))
if iTest == 1:
# calculate the dumping timscale of spikes
gamma = 5.0/3.0
mu = 1.23 * mh.d
Tg_ref = 300
cs = np.sqrt(gamma * kboltz.d * Tg_ref / mu)
length = 3e-3 * 3.0856e18
t_cross = length / cs / 3.1557e13
print("%13.5e" % t_cross)
if iTest == 2:
# calculate the Jeans length
nH_ref = 1e6
Tg_ref = 600
print("%13.5e %13.7f %13.5e" % (nH_ref, Tg_ref, Jeans_length(nH_ref, Tg_ref) / 3.0856e18))
fp_Dfront.write("%13s " % Test_name[iTest])
fp_Dfront.write("%13.7f " % x_nHmax[iTest] )
fp_Dfront.write("%13.5e " % nH_nHmax )
fp_Dfront.write("%13.5e " % Tg_nHmax )
fp_Dfront.write("%13.5e " % yH2I_nHmax )
fp_Dfront.write("%13.5e " % NH2I_nHmax )
#fp_Dfront.write("%13.5e " % NH2I0_nHmax )
#fp_Dfront.write("%13.5e " % NH2I1_nHmax )
#fp_Dfront.write("%13.5e " % NH2I3_nHmax )
fp_Dfront.write("%13.5e " % f_shield )
fp_Dfront.write("%13.5e " % kH2I_nHmax )
fp_Dfront.write("%13.7f " % dx_Dfront )
fp_Dfront.write("\n");
# print("yH2I max")
for iTest in range(3):
# for iTest in [1]:
i_yH2Imax = np.argmax(data_prof[iTest][:, i_yH2I][data_prof[iTest][:, i_rad] < x_nHmax[iTest]])
x_yH2Imax = data_prof[iTest][i_yH2Imax, i_rad ]
nH_yH2Imax = data_prof[iTest][i_yH2Imax, i_nH ]
Tg_yH2Imax = data_prof[iTest][i_yH2Imax, i_Tg ]
yH2I_yH2Imax = data_prof[iTest][i_yH2Imax, i_yH2I]
if iTest == 0:
NH2I_yH2Imax = data_prof[iTest][i_yH2Imax, i_NH2I ]
if iTest == 1:
NH2I_yH2Imax = data_prof[iTest][i_yH2Imax, i_NH2I1]
if iTest == 2:
NH2I_yH2Imax = data_prof[iTest][i_yH2Imax, i_NH2I3]
# shell width
if iTest < 2: factor = 10.0
else: factor = 3.0
i_H2ring, = np.where( (data_prof[iTest][:, i_rad ] < 0.3)
& (data_prof[iTest][:, i_yH2I] > yH2I_yH2Imax / factor))
if False:
x_H2ring_min[iTest] = np.min(data_prof[iTest][i_H2ring, i_rad])
x_H2ring_max[iTest] = np.max(data_prof[iTest][i_H2ring, i_rad])
else:
if np.size(i_H2ring):
i_H2ring_min = np.min(i_H2ring)
i_H2ring_max = np.max(i_H2ring)
x_H2ring_min[iTest] = 10.0**np.interp(np.log10(0.1 * yH2I_yH2Imax)
, np.log10(data_prof[iTest][i_H2ring_min-1:i_H2ring_min+1, i_yH2I])
, np.log10(data_prof[iTest][i_H2ring_min-1:i_H2ring_min+1, i_rad ]))
x_H2ring_max[iTest] = 10.0**np.interp(np.log10(0.1 * yH2I_yH2Imax)
, np.log10(data_prof[iTest][i_H2ring_max+1:i_H2ring_max-1:-1, i_yH2I])
, np.log10(data_prof[iTest][i_H2ring_max+1:i_H2ring_max-1:-1, i_rad ]))
else:
x_H2ring_min[iTest] = 0
x_H2ring_max[iTest] = 0
dx_H2ring = x_H2ring_max[iTest] - x_H2ring_min[iTest]
fp_H2ring.write("%13s " % Test_name[iTest])
fp_H2ring.write("%13.7f " % x_yH2Imax )
fp_H2ring.write("%13.5e " % nH_yH2Imax )
fp_H2ring.write("%13.5e " % Tg_yH2Imax )
fp_H2ring.write("%13.5e " % yH2I_yH2Imax )
fp_H2ring.write("%13.5e " % NH2I_yH2Imax )
fp_H2ring.write("%13.7f " % dx_H2ring )
fp_H2ring.write("\n");
fp_Dfront.close()
fp_H2ring.close()
# fiducial values
# print("NH2 %13.5e" % (1.0e-7*1.0e5 * 0.01*3.0856e18))
# FIGURE
ncols = 2; xfig = 12.0
# nrows = 2; yfig = 9.0
nrows = 3; yfig = 12.0
if str(Threshold) == '1stP3':
label_mass = r'$M_{\rm PopIII,1} = 10.4 {\rm M}_{\bigodot}$'
label_nHth = r'$n_{\rm H, th} = 10^6 \ {\rm cm}^{-3}$'
xmin = -2.0; xmax = 2.0
# xmin = -1.2; xmax = -0.5
if str(Threshold) == '1stP3h':
label_mass = r'$M_{\rm PopIII,1} = 10.4 {\rm M}_{\bigodot}$'
label_nHth = r'$n_{\rm H, th} = 10^8 \ {\rm cm}^{-3}$'
xmin = -3.0; xmax = 1.0
if str(Threshold) == '1stP3m':
label_mass = r'$M_{\rm PopIII,1} = 40.0 {\rm M}_{\bigodot}$'
label_nHth = r'$n_{\rm H, th} = 10^6 \ {\rm cm}^{-3}$'
######### xmin = -2.0; xmax = 2.0
xmin = -1.0; xmax = 0.0
labels = [['(a)', '(b)'], ['(c)', '(d)'], ['(e)', '(f)']]
fig, axs = plt.subplots(nrows=nrows, ncols=ncols, figsize=(xfig,yfig), constrained_layout=True)
fig.subplots_adjust(left=0.12, right=0.98, bottom=0.08, top=0.94, wspace=0.4, hspace=0.0)
fig.align_labels()
label_time = r"$t_{\rm SF} = %0.3f$ kyr" % t_SF
fig.suptitle("%s %s %s" % (label_mass, label_nHth, label_time), fontsize=fontsize_suptitle, y=0.99)
for irow in range(nrows):
for icol in range(ncols):
ax = axs[irow][icol]
ax.tick_params(labelsize=fontsize_tick)
ax.annotate(labels[irow][icol], xy=(0.03, 0.97), xycoords=ax.transAxes, fontsize=fontsize_title, va='top' , ha='left')
ymin = np.zeros(3)
ymax = np.zeros(3)
for iTest in range(3):
# for iTest in [1]:
xx = np.log10(data_prof[iTest][:, i_rad])
if icol == 0:
if irow == 0:
yy = np.log10(data_prof[iTest][:, i_nH])
pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2, label=Test_name[iTest])
ax.legend(fontsize=fontsize_legend, loc='upper right')
if irow == 1:
yy = np.log10(data_prof[iTest][:, i_yelec])
pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2)
# y2 = np.log10(data_prof[iTest][:, i_yHM])
# pl = ax.plot(xx, y2, zorder=2, c=colors[iTest], linewidth=2, linestyle='--')
# ax.annotate(r'e$^-$', xy=(0.6, 0.65), xycoords=ax.transAxes
# , color='black', size=fontsize_legend
# , va='center', ha='center'
# )
# ax.annotate(r'H$^-$', xy=(0.6, 0.25), xycoords=ax.transAxes
# , color='black', size=fontsize_legend
# , va='center', ha='center'
# )
if irow == 2:
if iTest == 0:
yy = np.log10(data_prof[iTest][:, i_NH2I])
pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2, label=r'$\int n({\rm H_2}) {\rm d}s$')
if iTest == 1:
yy = np.log10(data_prof[iTest][:, i_NH2I1])
pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2, label=r'$n({\rm H_2}) \left| \rho / \nabla \rho \right|$')
# yy = np.log10(data_prof[iTest][:, i_NH2I ])
# pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2, linestyle='--')
if iTest == 2:
yy = np.log10(data_prof[iTest][:, i_NH2I3])
pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2, label=r'$n({\rm H_2}) \lambda _{\rm J}$')
# yy = np.log10(data_prof[iTest][:, i_NH2I ])
# pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2, linestyle='--')
ax.legend(fontsize=fontsize_legend, loc='lower right')
if icol == 1:
if irow == 0:
yy = np.log10(data_prof[iTest][:, i_Tg])
pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2)
if irow == 1:
yy = np.log10(data_prof[iTest][:, i_yH2I])
pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2)
if irow == 2:
if iTest == 0:
yy = np.log10(data_prof[iTest][:, i_kH2I])
pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2)
if iTest == 1:
yy = np.log10(data_prof[iTest][:, i_kH2I1])
pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2)
if iTest == 2:
yy = np.log10(data_prof[iTest][:, i_kH2I3])
pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2)
# if irow == 0:
# if iTest == 0:
# yy = np.log10(data_prof[iTest][:, i_sH2I])
# pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2, label=r'$N({\rm H_2}) / n({\rm H_2})$')
# if iTest == 1:
# yy = np.log10(data_prof[iTest][:, i_sH2I1])
# pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2, label=r'$\left| \rho / \nabla \rho \right|$')
# if iTest == 2:
# yy = np.log10(data_prof[iTest][:, i_sH2I3])
# pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2, label=r'$\lambda _{\rm J}$')
# ax.legend(fontsize=fontsize_legend)
# pl = ax.plot(xx, yy, zorder=2, c=colors[iTest], linewidth=2)
ymin[iTest] = np.min(yy[(xx > xmin) & (xx < xmax) & (yy != -np.inf)])
ymax[iTest] = np.max(yy[(xx > xmin) & (xx < xmax) & (yy != -np.inf)])
# if icol == 0 and irow == 1:
# y2min = np.min(y2[(xx > xmin) & (xx < xmax) & (y2 != -np.inf)])
# y2max = np.max(y2[(xx > xmin) & (xx < xmax) & (y2 != -np.inf)])
# ymin[iTest] = np.min([ymin[iTest], y2min])
# ymax[iTest] = np.max([ymax[iTest], y2max])
yminmin = np.min(ymin)
ymaxmax = np.max(ymax)
y0 = (yminmin + ymaxmax) / 2.0
dy = ymaxmax - yminmin
yminmin = y0 - 0.55* dy
ymaxmax = y0 + 0.7 * dy
if str(Threshold) == '1stP3' or str(Threshold) == '1stP3m':
if str(Threshold) == '1stP3' : iTest = 0
if str(Threshold) == '1stP3m': iTest = 1
ax.fill_between([np.log10(x_H2ring_min[iTest]), np.log10(x_H2ring_max[iTest])]
, [yminmin, yminmin], [ymaxmax, ymaxmax], facecolor='none', edgecolor='#e1c3e1', hatch='/' *3)
ax.fill_between([np.log10(x_Dfront_min[iTest]), np.log10(x_Dfront_max[iTest])]
, [yminmin, yminmin], [ymaxmax, ymaxmax], facecolor='none', edgecolor='#ffe5b8', hatch='\\'*3)
if icol == 1 and irow == 0:
xxx = np.log10(x_H2ring_max[iTest])
yyy = yminmin + 0.02 * (ymaxmax - yminmin)
ax.annotate(r'H$_2$-ring', xy=(xxx, yyy), xycoords='data'
, color='purple', size=fontsize_legend, rotation=90
, va='bottom', ha='right'
)
# xxx = (np.log10(x_Dfront_min[iTest]) + np.log10(x_Dfront_max[iTest])) / 2
xxx = np.log10(x_Dfront_max[iTest])
yyy = yminmin + 0.98 * (ymaxmax - yminmin)
ax.annotate(r'D-type front', xy=(xxx, yyy), xycoords='data'
, color='orange', size=fontsize_legend, rotation=90
, va='top', ha='right'
)
if str(Threshold) == '1stP3h':
for iTest in range(3):
pl = ax.plot([np.log10(x_nHmax[iTest]), np.log10(x_nHmax[iTest])]
, [yminmin, ymaxmax], zorder=1, c=colors[iTest], linestyle=':', linewidth=1.5)
if irow < nrows - 1:
ax.set_xlabel('')
ax.tick_params(labelbottom = False)
else:
ax.set_xlabel(r"log [ Distance / pc ]" , fontsize=fontsize_label)
ax.tick_params(labelbottom = True)
if icol == 0:
if irow == 0:
ax.set_ylabel(r"log [ $n_{\rm H}$ / cm$^{-3}$ ]" , fontsize=fontsize_label)
if irow == 1:
# ax.set_ylabel(r"log [ $y({\rm H}^{+})$ ]" , fontsize=fontsize_label)
ax.set_ylabel(r"log [ $y({\rm e}^{-})$ ]" , fontsize=fontsize_label)
# ax.set_ylabel(r"log [ $y({\rm e}^{-}, {\rm H}^{-})$ ]" , fontsize=fontsize_label)
if irow == 2:
ax.set_ylabel(r"log [ $N_{{\rm H}_2}$ / cm$^{-2}$ ]" , fontsize=fontsize_label)
if icol == 1:
if irow == 0:
ax.set_ylabel(r"log [ $T$ / K ]" , fontsize=fontsize_label)
if irow == 1:
ax.set_ylabel(r"log [ $y({\rm H}_{2})$ ]" , fontsize=fontsize_label)
if irow == 2:
ax.set_ylabel(r"log [ $k _{\rm diss}$ / s$^{-1}$ ]" , fontsize=fontsize_label)
# if irow == 1:
# ax.set_ylabel(r"log [ $\lambda _{\rm sh} ({\rm H}_2)$ ]", fontsize=fontsize_label)
if str(Threshold) == '1stP3m':
ax.set_xticks(np.linspace(-1, 0, 3))
# ax.set_xticks(np.linspace(-3, 2, 6))
ax.set_xticklabels([r"$-1$", r"$-0.5$", r"$0$"])
# if inumber >= 31: ax.set_xticks(np.linspace(-3, 2, 51))
else:
ax.set_xticks(np.linspace(-3, 2, 6))
if (icol == 0 and irow == 0) or (icol == 0 and irow == 1):
ax.set_yticks(np.linspace(-8, 8, 9))
ax.set_yticks(np.linspace(-8, 8, 17), minor=True)
if (icol == 0 and irow == 2) or (icol == 1 and irow == 1):
ax.set_yticks(np.linspace(-25, 25, 11))
ax.set_yticks(np.linspace(-25, 25, 51), minor=True)
if (icol == 1 and irow == 2):
ax.set_yticks(np.linspace(-20, 0, 11))
ax.set_yticks(np.linspace(-20, 0, 21), minor=True)
ax.set_xlim([xmin, xmax])
ax.set_ylim([yminmin, ymaxmax])
# save figure
fig.savefig(indir + "/rad_%s_%04d.%s" % (Threshold, inumber, extension))
plt.close('all')
if RAY_C:
# column density with the same nH, T, yH2 for TestC
ncols = 1; xfig = 5.0
nrows = 1; yfig = 4.1
if str(Threshold) == '1stP3' or str(Threshold) == '1stP3m':
label_nHth = r'$n_{\rm H, th} = 10^6 \ {\rm cm}^{-3}$'
xmin = -2.0; xmax = 2.0
if str(Threshold) == '1stP3h':
label_nHth = r'$n_{\rm H, th} = 10^8 \ {\rm cm}^{-3}$'
xmin = -3.0; xmax = 1.0
labels = [['(a)', '(b)'], ['(c)', '(d)'], ['(e)', '(f)']]
fig, axs = plt.subplots(nrows=nrows, ncols=ncols, figsize=(xfig,yfig), constrained_layout=True)
fig.subplots_adjust(left=0.2, right=0.9, bottom=0.2, top=0.83, wspace=0.4, hspace=0.0)
fig.align_labels()
label_time = r"$t_{\rm SF} = %0.3f$ kyr" % t_SF
# fig.suptitle("%s %s" % (label_nHth, label_time), fontsize=fontsize_suptitle_s, y=0.99)
fig.suptitle("%s\n%s %s" % (label_mass, label_nHth, label_time), fontsize=fontsize_suptitle_s, y=0.992)
for irow in range(nrows):
for icol in range(ncols):
ax = axs # [irow][icol]
ax.tick_params(labelsize=fontsize_tick_s)
ax.annotate(Test_name[2], xy=(0.03, 0.97), xycoords=ax.transAxes, fontsize=fontsize_title_s, va='top' , ha='left')
ymin = np.zeros(3)
ymax = np.zeros(3)
for iTest in [2]:
xx = np.log10(data_prof[iTest][:, i_rad])
if True:
if True:
if iTest == 2:
# nH2I = data_prof[iTest][:, i_yH2I] * data_prof[iTest][:, i_nH]
yy = np.log10(data_prof[iTest][:, i_NH2I ])
pl = ax.plot(xx, yy, zorder=2, c=colors[0], linewidth=1.5, label=r'$\int n({\rm H_2}) {\rm d}s$')
yy = np.log10(data_prof[iTest][:, i_NH2I1])
pl = ax.plot(xx, yy, zorder=2, c=colors[1], linewidth=1.5, label=r'$n({\rm H_2}) \left| \rho / \nabla \rho \right|$')
yy = np.log10(data_prof[iTest][:, i_NH2I3])
pl = ax.plot(xx, yy, zorder=2, c=colors[2], linewidth=1.5, label=r'$n({\rm H_2}) \lambda _{\rm J}$')
ax.legend(fontsize=fontsize_legend_s)
ymin[iTest] = np.min(yy[(xx > xmin) & (xx < xmax) & (yy != -np.inf)])
ymax[iTest] = np.max(yy[(xx > xmin) & (xx < xmax) & (yy != -np.inf)])
if icol == 0 and irow == 1:
y2min = np.min(y2[(xx > xmin) & (xx < xmax) & (y2 != -np.inf)])
y2max = np.max(y2[(xx > xmin) & (xx < xmax) & (y2 != -np.inf)])
ymin[iTest] = np.min([ymin[iTest], y2min])
ymax[iTest] = np.max([ymax[iTest], y2max])
yminmin = np.min(ymin)
ymaxmax = np.max(ymax)
y0 = (yminmin + ymaxmax) / 2.0
dy = ymaxmax - yminmin
yminmin = y0 - 0.5 * dy
ymaxmax = y0 + 0.7 * dy
if str(Threshold) == '1stP3' or str(Threshold) == '1stP3m':
if str(Threshold) == '1stP3' : iTest = 0
if str(Threshold) == '1stP3m': iTest = 1
ax.fill_between([np.log10(x_H2ring_min[iTest]), np.log10(x_H2ring_max[iTest])]
, [yminmin, yminmin], [ymaxmax, ymaxmax], facecolor='none', edgecolor='#e1c3e1', hatch='/' *3)
ax.fill_between([np.log10(x_Dfront_min[iTest]), np.log10(x_Dfront_max[iTest])]
, [yminmin, yminmin], [ymaxmax, ymaxmax], facecolor='none', edgecolor='#ffe5b8', hatch='\\'*3)
if True:
xxx = np.log10(x_H2ring_max[iTest])
yyy = yminmin + 0.02 * (ymaxmax - yminmin)
ax.annotate(r'H$_2$-ring', xy=(xxx, yyy), xycoords='data'
, color='purple', size=fontsize_legend_s, rotation=90
, va='bottom', ha='right'
)
xxx = (np.log10(x_Dfront_min[iTest]) + np.log10(x_Dfront_max[iTest])) / 2
yyy = yminmin + 0.02 * (ymaxmax - yminmin)
ax.annotate(r'D-type front', xy=(xxx, yyy), xycoords='data'
, color='orange', size=fontsize_legend_s, rotation=90
, va='bottom', ha='center'
)
if str(Threshold) == '1stP3h':
if True:
pl = ax.plot([np.log10(x_nHmax[iTest]), np.log10(x_nHmax[iTest])]
, [yminmin, ymaxmax], zorder=1, c=colors[iTest], linestyle=':', linewidth=1.5)
if irow < nrows - 1:
ax.set_xlabel('')
ax.tick_params(labelbottom = False)
else:
ax.set_xlabel(r"log [ Distance / pc ]", fontsize=fontsize_label_s)
ax.tick_params(labelbottom = True)
if True:
if True:
ax.set_ylabel(r"log [ $N_{{\rm H}_2}$ / cm$^{-2}$ ]", fontsize=fontsize_label_s)
ax.set_xticks(np.linspace(-3, 2, 6))
# ax.set_xticks(np.linspace(-2, 2, 9), minor=True)
if True:
ax.set_yticks(np.linspace(-25, 25, 11))
ax.set_yticks(np.linspace(-25, 25, 51), minor=True)
ax.set_xlim([xmin, xmax])
ax.set_ylim([yminmin, ymaxmax])
# save figure
fig.savefig(indir + "/rad%s_%s_%04d.%s" % (Test, Threshold, inumber, extension))
plt.close('all')
if SLICE:
# TopGridDimension = 512
# NestedLevel = 2
incs = range(inumber0, inumber1+1, inumber2)
# TopGridDimension = 64
# NestedLevel = 2
# incs = [34]
xtime = ''
fields = [
'Hydrogen_number_density'
, 'temperature_corr'
, 'y_H2I'
]
labels = ['(a)', '(b)', '(c)']
nvar = len(fields)
ibox = '0'
# s_box = 0.2
# boxsize = r'0.2 $h^{-1} (1+z)^{-1}$ Mpc'
if str(Threshold) == '1stP3' or str(Threshold) == '1stP3m':
s_box = 2.0
boxsize = r'2 pc'
if str(Threshold) == '1stP3h':
s_box = 0.2
boxsize = r'0.2 pc'
reso = 800
nnc = len(incs)
arrow_length = 0.4
Y, X = np.mgrid[0:reso+1, 0:reso+1]
X = X / float(reso) * s_box
Y = Y / float(reso) * s_box
X = X - 0.5 * s_box
Y = Y - 0.5 * s_box
#print(X)
for iTest in range(3):
# for iTest in [1]:
for iinc in range(nnc):
inc = incs[iinc]
xfig = 18.0
yfig = 6.0
fig, axs = plt.subplots(nrows=1, ncols=len(fields), figsize=(xfig,yfig/0.9), constrained_layout=True)
fig.subplots_adjust(left=0.0, right=1.0, bottom=0.0, top=0.9 , wspace=0.0, hspace=0.0)
if TopGridDimension == 64:
outdir = 'test%d-L%d' % (TopGridDimension, NestedLevel)
if TopGridDimension == 512:
outdir = 'test%d-L%d_%s_%s/' % (TopGridDimension, NestedLevel, Threshold, Test_name[iTest])
# stars
starfile = outdir + ('Stars_PopIII_%04d.dat' % (inc))
# print(starfile)
starfp = open(starfile, 'rb')
nPopIII = struct.unpack('i', starfp.read(4))[0]
xPopIII = np.zeros(nPopIII)
yPopIII = np.zeros(nPopIII)
zPopIII = np.zeros(nPopIII)
cPopIII = np.zeros(nPopIII)
tPopIII = np.zeros(nPopIII)
dPopIII = np.zeros(nPopIII)
MPopIII = np.zeros(nPopIII)
for iPopIII in range(nPopIII):
xPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
yPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
zPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
cPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
dPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
tPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
MPopIII[iPopIII] = struct.unpack('d', starfp.read(8))[0]
# print(xPopIII[iPopIII], yPopIII[iPopIII], tPopIII[iPopIII], MPopIII[iPopIII])
starfp.close()
iPopIII0 = np.argmin(cPopIII)
for ivar in range(nvar):
ax = axs[ivar]
# slice data
infile = outdir + ('Slice_z_%s_%04d.dat' % (fields[ivar], inc))
infp = open(infile, 'rb')
outdata = np.fromfile(infp, dtype='d',sep='')
# if str(fields[ivar]) == 'temperature_corr':
# Z = (outdata).reshape(reso,reso)
# else:
# Z = np.log10(outdata).reshape(reso,reso)
Z = np.log10(outdata).reshape(reso,reso)
infp.close()
if str(Threshold) == '1stP3':
label_mass = r'$M_{\rm PopIII,1} = 10.4 {\rm M}_{\bigodot}$'
label_nHth = r'$n_{\rm H, th} = 10^6 \ {\rm cm}^{-3}$'
xmin = -2.0; xmax = 2.0
# xmin = -1.2; xmax = -0.5
if str(Threshold) == '1stP3h':
label_mass = r'$M_{\rm PopIII,1} = 10.4 {\rm M}_{\bigodot}$'
label_nHth = r'$n_{\rm H, th} = 10^8 \ {\rm cm}^{-3}$'
xmin = -3.0; xmax = 1.0
if str(Threshold) == '1stP3m':
label_mass = r'$M_{\rm PopIII,1} = 40.0 {\rm M}_{\bigodot}$'
label_nHth = r'$n_{\rm H, th} = 10^6 \ {\rm cm}^{-3}$'
# if str(Threshold) == '1stP3' or str(Threshold) == '1stP3m':
# label_nHth = r'$n_{\rm H, th} = 10^6 \ {\rm cm}^{-3}$'
# if str(Threshold) == '1stP3h':
# label_nHth = r'$n_{\rm H, th} = 10^8 \ {\rm cm}^{-3}$'
label_time = r'%s $t_{\rm SF} = %.3f$ kyr' % (Test_name[iTest], tPopIII[iPopIII0])
# fig.suptitle(label_time, fontsize=fontsize_suptitle, y=0.98)
fig.suptitle("%s %s %s" % (label_mass, label_nHth, label_time), fontsize=fontsize_suptitle, y=0.99)
##if ivar == 0:
## ax.set_title("%s" % Test_text[iTest], fontsize=fontsize_suptitle, fontweight='bold', loc='left')
# ##fig.align_labels()
if str(fields[ivar]) == 'Hydrogen_number_density':
cmap = 'bds_highcontrast'
if str(fields[ivar]) == 'temperature_corr':
cmap = 'hot'
if str(fields[ivar]) == 'y_H2I':
cmap = 'BLUE'
# slice data
pcolor = ax.pcolormesh(X, Y, Z, cmap=cmap)
# stars
# pscatt = ax.scatter(xPopIII - xPopIII[iPopIII0], yPopIII - yPopIII[iPopIII0]
# , s=300.0, zorder=500, c='cyan', edgecolor='black', marker='*')
pscatt = ax.scatter(xPopIII - xPopIII[iPopIII0], yPopIII - yPopIII[iPopIII0]
, s=10.0*MPopIII, zorder=500, c='cyan', marker='o')
## if ivar == 0:
## if nSN == 1:
## xtime = r'TestC $t_{\rm SF} = %.3f$ kyr' % tPopIII[iPopIII0]
## if nSN == 3:
## xtime = r'$t_{\rm SF} = %.3f$ kyr' % tPopIII[iPopIII0]
### ax.annotate((0.05, 0.05), 't = %.3f kyr' % tPopIII[iPopIII0], coord_system='axis', color='white')
## ax.annotate(xtime, xy=(0.02, 0.98), xycoords=ax.transAxes
## , color='white', size=fontsize_title
## , va='top', ha='left'
## )
# if nSN == 1:
# ax.annotate(labels[ivar], xy=(0.02, 0.98), xycoords=ax.transAxes
# , color='white', size=fontsize_title
# , va='top', ha='left'
# )
ax.set_aspect('equal', adjustable='box')
ax.tick_params(labelbottom=False,
labelleft=False,
labelright=False,
labeltop=False)
ax.tick_params(bottom=False,
left=False,
right=False,
top=False)
# if ivar==0:
# ax.annotate(xtime, xy=(0.03, 0.97), xycoords=ax.transAxes
# , color='white', fontsize=fontsize_title
# , va='top', ha='left'
# )
if str(fields[ivar]) == 'Hydrogen_number_density':
xccolor='white'
if str(fields[ivar]) == 'temperature_corr':
xccolor='white'
if str(fields[ivar]) == 'y_H2I':
xccolor='white'
if ivar==nvar-1:
ax.annotate(boxsize, xy=(0.93, 0.5), xycoords=ax.transAxes
, color=xccolor, fontsize=fontsize_boxsize, rotation=90
, va='center', ha='center'
# , bbox={'facecolor':'black', 'alpha':0.5, 'pad':2}
)
ax.annotate('', xy=(0.93, 0.0), xycoords=ax.transAxes
, xytext=(0.93, arrow_length), textcoords=ax.transAxes
, arrowprops=dict(shrink=0, width=1, headwidth=8,
headlength=10, connectionstyle='arc3',
facecolor=xccolor, edgecolor=xccolor)
)
ax.annotate('', xy=(0.93, 1.0), xycoords=ax.transAxes
, xytext=(0.93, 1.0-arrow_length), textcoords=ax.transAxes
, arrowprops=dict(shrink=0, width=1, headwidth=8,
headlength=10, connectionstyle='arc3',
facecolor=xccolor, edgecolor=xccolor)
)
cmin = Z.min(); cmax = Z.max();
if str(fields[ivar]) == 'Hydrogen_number_density':
pcolor.set_clim(cmin, cmax)
if str(fields[ivar]) == 'temperature_corr':
pcolor.set_clim(cmin, cmax)
if str(fields[ivar]) == 'y_H2I':
pcolor.set_clim(-4, cmax)
#### pcolor.set_clim(-10, 0)
ticks = np.linspace(-10, 10, 21)
##if str(fields[ivar]) == 'Hydrogen_number_density':
## if str(Threshold) == '1stP3' or str(Threshold) == '1stP3m':
## pcolor.set_clim(3.0, 5.8)
## if str(Threshold) == '1stP3h':
## pcolor.set_clim(5.0, 7.8)
## ticks = np.linspace(3, 5, 3)
##if str(fields[ivar]) == 'temperature_corr':
## pcolor.set_clim(2.0, 4.5)
## ticks = np.linspace( 2, 4, 3)
##if str(fields[ivar]) == 'y_H2I':
## pcolor.set_clim(-15, 0)
### ticks = np.linspace(-15, 0, 16)
## ticks = np.linspace(-15, 0, 4)
axins = inset_axes(ax,
width="50%", # width = 5% of parent_bbox width
height="5%", # height : 50%
loc='lower left',
bbox_to_anchor=(0.05, 0.15, 1, 1),
bbox_transform=ax.transAxes,
borderpad=0,
)
colbar = fig.colorbar(pcolor, orientation='horizontal', ax=ax, cax=axins
# ,aspect=10,pad=-0.22 ,shrink=0.50
,ticks=ticks
)
colbar.outline.set_edgecolor(xccolor)
if str(fields[ivar]) == 'Hydrogen_number_density':
xclabel = r'log [ Density / cm$^{-3}$ ]'
if str(fields[ivar]) == 'temperature_corr':
xclabel = r'Temperature [ K ]'
if str(fields[ivar]) == 'y_H2I':
xclabel = r'$y({\rm H_2})$'
colbar.set_label(xclabel, fontsize=fontsize_cblabel, color=xccolor)
colbar.ax.tick_params(labelsize=fontsize_tick, color=xccolor, labelcolor=xccolor)
fig.savefig(indir + "/snapshots_%s_%s_%04d.png" % (Threshold, Test_name[iTest], inc))
print(inc)
plt.close('all')
if PRESEN:
incs = range(inumber0, inumber1+1, inumber2)
xtime = ''
fields = [
'Hydrogen_number_density'
, 'temperature_corr'
, 'y_H2I'
]
nvar = len(fields)
ibox = '0'
# s_box = 0.2
# boxsize = r'0.2 $h^{-1} (1+z)^{-1}$ Mpc'
if str(Threshold) == '1stP3' or str(Threshold) == '1stP3m':
s_box = 2.0
boxsize = r'2 pc'
if str(Threshold) == '1stP3h':
s_box = 0.2
boxsize = r'0.2 pc'
reso = 800
nnc = len(incs)
arrow_length = 0.4
Y, X = np.mgrid[0:reso+1, 0:reso+1]
X = X / float(reso) * s_box
Y = Y / float(reso) * s_box
X = X - 0.5 * s_box
Y = Y - 0.5 * s_box
#print(X)
if TopGridDimension == 64:
nSN = 1
if TopGridDimension == 512:
nSN = 3
for iinc in range(nnc):
inc = incs[iinc]
if str(Test) == 'TestA':
iSN = 0
if str(Test) == 'TestB':
iSN = 1
if str(Test) == 'TestC':
iSN = 2
if TopGridDimension == 64:
outdir = 'test%d-L%d' % (TopGridDimension, NestedLevel)