def burning_limiter(eps_filename, results_base):
"""Plot the effects of both burning timestep limiters (castro.dtnuc_e and castro.dtnuc_X)."""
if (os.path.isfile(eps_filename)):
return
results_dir = results_base + 'burning_limiter_e/'
# Get the list of parameter values we have tried
dtnuc_list = wdmerger.get_parameter_list(results_dir)
ni56_arr = get_ni56(results_dir)
dtnuc_list = [dtnuc[len('dt'):] for dtnuc in dtnuc_list]
plt.plot(np.array(dtnuc_list),
np.array(ni56_arr),
linestyle=linestyles[0],
lw=4.0,
label=r'$\Delta t_{be}$')
results_dir = results_base + 'burning_limiter_X/'
# Get the list of parameter values we have tried
dtnuc_list = wdmerger.get_parameter_list(results_dir)
ni56_arr = get_ni56(results_dir)
dtnuc_list = [dtnuc[len('dt'):] for dtnuc in dtnuc_list]
plt.plot(np.array(dtnuc_list),
np.array(ni56_arr),
linestyle=linestyles[1],
lw=4.0,
label=r'$\Delta t_{bX}$')
plt.xscale('log')
plt.xlabel(r"Nuclear burning timestep factor", fontsize=20)
plt.ylabel(r"$^{56}$Ni generated (M$_{\odot}$)", fontsize=20)
plt.tick_params(labelsize=16)
plt.legend(loc='best')
plt.tight_layout()
plt.savefig(eps_filename)
wdmerger.insert_commits_into_eps(eps_filename, get_diagfile(results_dir),
'diag')
plt.close()
def c_fraction(out_filename, results_base):
"""Create a table with the nickel generation as a function of the C/O fraction."""
if (os.path.isfile(out_filename)):
return
# Get the list of parameter values we have tried
results_dir = results_base + '/co'
param_list = wdmerger.get_parameter_list(results_dir)
c_list = [param.split('c')[1].split('o')[0] for param in param_list]
ni56_list = get_ni56(results_dir)
comment = '%\n' + \
'% Summary of the effect of C/O mass fraction \n' + \
'% on 56Ni yield in a 2D white dwarf collision.\n' + \
'% The first column is the initial carbon mass \n' + \
'% fraction and the second is the final nickel \n' + \
'% mass produced, in solar masses.\n' + \
'%\n'
caption = ' Maximum $^{56}Ni$ mass ($M_{\odot}) produced as a function of the ' + \
'initial mass fraction $C$. Since the white dwarfs are purely ' + \
'carbon/oxygen the initial oxygen fraction is $1 - C$.'
col1title = '$C$'
label = 'co'
write_ni56_table(results_dir, out_filename, c_list, ni56_list, comment,
caption, col1title, label)
def eta3(out_filename, results_base):
"""Create a table with the nickel generation as a function of the dual energy eta3 parameter."""
if (os.path.isfile(out_filename)):
return
# Get the list of parameter values we have tried
results_dir = results_base + '/eta3'
param_list = wdmerger.get_parameter_list(results_dir)
eta_list = [param[3:] for param in param_list]
ni56_list = get_ni56(results_dir)
comment = '%\n' + \
'% Summary of the effect of the dual energy parameter \n' + \
'% castro.dual_energy_eta3 on 56Ni yield in a 2D white \n' + \
'% dwarf collision.\n' + \
'% The first column is the value of eta3 and the second \n' + \
'% is the final nickel mass produced, in solar masses.\n' + \
'%\n'
caption = 'Maximum $^{56}Ni$ mass ($M_{\odot}) produced as a function of the ' + \
'dual energy formalism parameter $\\eta_3$.'
col1title = '$\\eta_3$'
label = 'eta3'
write_ni56_table(results_dir, out_filename, eta_list, ni56_list, comment,
caption, col1title, label)
def get_ni56(results_dir, prefix=''):
"""Return a list of maximum 56Ni production from all completed sub-directories in results_dir."""
import numpy as np
ni56_arr = []
dir_list = wdmerger.get_parameter_list(results_dir)
# Strip out those directories that don't match the prefix.
if (prefix != ''):
dir_list = [dir for dir in dir_list if dir[0:len(prefix)] == prefix]
if (dir_list == []):
return ni56_arr
diag_filename_list = [
results_dir + '/' + directory + '/output/species_diag.out'
for directory in dir_list
]
# Ensure all of the output files are there.
for diag_file in diag_filename_list:
if not os.path.isfile(diag_file):
return ni56_arr
ni56_arr = [
np.amax(wdmerger.get_column('Mass ni56', diag_filename)) -
np.amin(wdmerger.get_column('Mass ni56', diag_filename))
for diag_filename in diag_filename_list
]
return ni56_arr
def get_e_release(results_dir):
"""Return a list of energy generation from all completed sub-directories in results_dir."""
import wdmerger_grid_diag_analysis as grid_diag
import numpy as np
dir_list = wdmerger.get_parameter_list(results_dir)
if (dir_list == []):
return
diag_filename_list = [
results_dir + '/' + directory + '/output/grid_diag.out'
for directory in dir_list
]
e_arr = [
np.amax(wdmerger.get_column('TOTAL ENERGY', diag_filename)) -
np.amin(wdmerger.get_column('TOTAL ENERGY', diag_filename))
for diag_filename in diag_filename_list
]
# Divide by 10**51
e_arr = [e / 1.0e51 for e in e_arr]
return e_arr
def small_temp(out_filename, results_base):
"""Create a table with the nickel generation as a function of the temperature floor."""
if (os.path.isfile(out_filename)):
return
# Get the list of parameter values we have tried
results_dir = results_base + '/small_temp'
param_list = wdmerger.get_parameter_list(results_dir)
temp_list = [param[1:] for param in param_list]
ni56_list = get_ni56(results_dir)
comment = '%\n' + \
'% Summary of the effect of the temperature floor \n' + \
'% castro.small_temp on 56Ni yield in a 2D white \n' + \
'% dwarf collision.\n' + \
'% The first column is the temperature floor and the \n' + \
'% second is the final nickel mass produced, in solar masses.\n' + \
'%\n'
caption = 'Maximum $^{56}Ni$ mass ($M_{\odot}) produced as a function of the ' + \
'temperature floor.'
col1title = '$T_{\\text{floor}}$'
label = 'smalltemp'
write_ni56_table(results_dir, out_filename, temp_list, ni56_list, comment,
caption, col1title, label)
def rho_min(out_filename, results_base):
"""Create a table with the nickel generation as a function of the minimum density for reactions."""
if (os.path.isfile(out_filename)):
return
# Get the list of parameter values we have tried
results_dir = results_base + '/rho_min'
param_list = wdmerger.get_parameter_list(results_dir)
temp_list = [param[3:] for param in param_list]
ni56_list = get_ni56(results_dir)
comment = '%\n' + \
'% Summary of the effect of the minimum density\n' + \
'% for reactions on 56Ni yield in a 2D white \n' + \
'% dwarf collision.\n' + \
'% The first column is the density minimum and the \n' + \
'% second is the final nickel mass produced, in solar masses.\n' + \
'%\n'
caption = 'Maximum $^{56}Ni$ mass ($M_{\odot}) produced as a function of the ' + \
'minimum density for allowing nuclear reactions.'
col1title = '$\\rho_{\\text{min}}$'
label = 'tmin'
write_ni56_table(results_dir, out_filename, temp_list, ni56_list, comment,
caption, col1title, label)
def get_abar(results_dir, prefix=''):
"""Return a list of maximum 56Ni production from all completed sub-directories in results_dir."""
import numpy as np
abar_arr = []
dir_list = wdmerger.get_parameter_list(results_dir)
# Strip out those directories that don't match the prefix.
if (prefix != ''):
dir_list = [dir for dir in dir_list if dir[0:len(prefix)] == prefix]
if (dir_list == []):
return abar_arr
diag_filename_list = [
results_dir + '/' + directory + '/output/species_diag.out'
for directory in dir_list
]
# Ensure all of the output files are there.
for diag_file in diag_filename_list:
if not os.path.isfile(diag_file):
return abar_arr
abar_arr = []
for diag_filename in diag_filename_list:
col_names, col_data = wdmerger.get_column_data(diag_filename)
# The only thing we need is the last row, and we can
# skip the first two columns (timestep, simulation time).
spec_names = col_names[2:]
spec_data = col_data[-1, 2:]
# Normalize the species by the total mass.
spec_data /= sum(spec_data)
# Get the atomic masses of each element by stripping out
# only the digits from each column header.
spec_masses = [
int(''.join(c for c in s if c.isdigit())) for s in spec_names
]
# Now compute abar.
abar = sum(spec_masses * spec_data)
abar_arr.append(abar)
return abar_arr
def burning_limiter_X(eps_filename, results_base, do_ni56=True):
"""Plot the effect of the burning timestep limiter castro.dtnuc_X."""
if (os.path.isfile(eps_filename)):
return
else:
print("Generating file %s" % eps_filename)
results_dir = results_base + 'burning_limiter_X/'
if not os.path.isdir(results_dir):
return
# Get the list of parameter values we have tried
dtnuc_list = wdmerger.get_parameter_list(results_dir)
if (dtnuc_list == []):
return
if (do_ni56):
result_arr = np.array(get_ni56(results_dir))
else:
result_arr = np.array(get_abar(results_dir))
# Don't make the plot if we have fewer than two data points.
if len(result_arr) < 2:
return
dtnuc_list = np.array([float(dtnuc[len('dt'):]) for dtnuc in dtnuc_list])
# Sort the lists
result_arr = np.array([x for _, x in sorted(zip(dtnuc_list, result_arr))])
dtnuc_list = sorted(dtnuc_list)
plt.plot(dtnuc_list,
result_arr,
linestyle=linestyles[0],
lw=4.0,
color=colors[0])
plt.xscale('log')
plt.xlabel(r"Nuclear burning timestep factor $f_{bX}$", fontsize=20)
if (do_ni56):
plt.ylabel(r"$^{56}$Ni generated (M$_{\odot}$)", fontsize=20)
else:
plt.ylabel(r"$\overline{A}$", fontsize=20)
plt.tick_params(labelsize=16)
plt.tight_layout()
plt.savefig(eps_filename)
wdmerger.insert_commits_into_eps(eps_filename, get_diagfile(results_dir),
'diag')
png_filename = eps_filename[0:-3] + "png"
plt.savefig(png_filename)
plt.close()
def rho_min(out_filename, results_base):
"""Create a table with the nickel generation as a function of the minimum density for reactions."""
if (os.path.isfile(out_filename)):
return
else:
print("Generating file %s" % out_filename)
# Get the list of parameter values we have tried
results_dir = results_base + '/rho_min'
if not os.path.isdir(results_dir):
return
param_list = wdmerger.get_parameter_list(results_dir)
if (param_list == []):
return
temp_list = [float(param[3:]) for param in param_list]
ni56_list = get_ni56(results_dir)
# Sort the lists
ni56_list = np.array([x for _, x in sorted(zip(temp_list, ni56_list))])
temp_list = sorted(temp_list)
# Return temp_list to scientific notation
temp_list = np.array(["{:.1e}".format(t) for t in temp_list])
comment = '%\n' + \
'% Summary of the effect of the minimum density\n' + \
'% for reactions on 56Ni yield in a white \n' + \
'% dwarf collision.\n' + \
'% The first column is the density minimum and the \n' + \
'% second is the final nickel mass produced, in solar masses.\n' + \
'%\n'
title = 'Effect of the density floor for reactions'
col1title = '$\\rho_{\\text{min}}$'
label = 'tmin'
write_ni56_table(results_dir,
out_filename,
temp_list,
ni56_list,
comment,
col1title,
label,
title=title)
def burning_limiter_mode(out_filename, results_base):
"""Create a table with the nickel generation as a function of the mode used for timestep limiting."""
import os
if os.path.isfile(out_filename):
return
else:
print("Generating file %s" % out_filename)
# Get the list of parameter values we have tried
results_dir = results_base + '/burning_limiter_mode'
if not os.path.isdir(results_dir):
return
param_list = wdmerger.get_parameter_list(results_dir)
if (param_list == []):
return
mode_list = [param[4:] for param in param_list]
ni56_list = get_ni56(results_dir)
comment = '%\n' + \
'% Summary of the effect of the timestep limiting mode \n' + \
'% on 56Ni yield in a white dwarf collision.\n' + \
'% The first column is the limiter mode \n' + \
'% and the second is the final nickel \n' + \
'% mass produced, in solar masses.\n' + \
'%\n'
caption = 'The burning limiter modes are explained in \\autoref{sec:hydrocoupling}.'
col1title = 'Mode'
title = 'Burning Limiter Mode'
label = 'burninglimitermode'
write_ni56_table(results_dir,
out_filename,
mode_list,
ni56_list,
comment,
col1title,
label,
title=title,
caption=caption)
def stellar_masses(eps_filename, results_base):
"""Plot the WD masses as a function of time."""
if not is_root():
return
import os
if not os.path.exists(results_base):
return
import matplotlib.pyplot as plt
import numpy as np
res_list = wdmerger.get_parameter_list(results_base)
directory_list = [results_base + '/' + res for res in res_list]
for i, directory in enumerate(directory_list):
eps_filename_curr = eps_filename.replace('.eps', '_n_' + res_list[i][1:] + '.eps')
if os.path.isfile(eps_filename_curr):
continue
p_diag = directory + '/output/primary_diag.out'
s_diag = directory + '/output/secondary_diag.out'
p_time = wdmerger.get_column('TIME', p_diag)
p_mass = wdmerger.get_column('PRIMARY MASS', p_diag)
s_time = wdmerger.get_column('TIME', s_diag)
s_mass = wdmerger.get_column('SECONDARY MASS', s_diag)
p_mask = np.where(p_time <= 100.0)
s_mask = np.where(s_time <= 100.0)
plt.plot(np.array(p_time)[p_mask], np.array(p_mass)[p_mask] / np.array(p_mass)[0], lw = 4.0, linestyle = linestyles[0], markersize = 12.0, markevery = 2000, label = 'Primary')
plt.plot(np.array(s_time)[s_mask], np.array(s_mass)[s_mask] / np.array(s_mass)[0], lw = 4.0, linestyle = linestyles[1], markersize = 12.0, markevery = 2000, label = 'Secondary')
plt.tick_params(labelsize = 20)
plt.xlabel('Time (s)', fontsize = 24)
plt.ylabel('WD Mass / Initial Mass', fontsize = 24)
plt.legend(loc = 'best', prop = {'size':20}, fancybox = True, framealpha = 0.5)
plt.tight_layout()
plt.savefig(eps_filename_curr)
plt.close()
def get_diagfile(results_dir):
"""Return the name of a diagnostics file in results_dir that is completed.
Useful for the functions that insert git commits into files and need a
representative diagnostic file to get the git commits from. We arbitrarily
pick the last directory."""
dir_list = wdmerger.get_parameter_list(results_dir)
diag_filename_list = [
results_dir + '/' + directory + '/output/species_diag.out'
for directory in dir_list
]
diag_filename = diag_filename_list[-1]
return diag_filename
def get_ni56(results_dir):
"""Return a list of maximum 56Ni production from all completed sub-directories in results_dir."""
import numpy as np
dir_list = sorted(wdmerger.get_parameter_list(results_dir))
diag_filename_list = [
results_dir + '/' + directory + '/output/species_diag.out'
for directory in dir_list
]
ni56_arr = [
np.amax(wdmerger.get_column('Mass ni56', diag_filename))
for diag_filename in diag_filename_list
]
return ni56_arr
def stellar_distance(eps_filename, results_base):
"""Plot the WD distance as a function of time."""
if not is_root():
return
import os
if os.path.isfile(eps_filename):
return
if not os.path.exists(results_base):
return
import matplotlib.pyplot as plt
import numpy as np
res_list = wdmerger.get_parameter_list(results_base)
res_list = sorted([int(res[1:]) for res in res_list])
diag_list = [results_base + '/n' + str(res) + '/output/star_diag.out' for res in res_list]
for i, diag in enumerate(diag_list):
eps_filename_curr = eps_filename.replace('.eps', '_n_' + str(res_list[i]) + '.eps')
if os.path.isfile(eps_filename_curr):
return
time = np.array(wdmerger.get_column('TIME', diag))
dist = np.array(wdmerger.get_column('WD DISTANCE', diag))
mask = np.where(dist > 0.0)
plt.plot(time[mask], dist[mask] / dist[0], lw = 4.0, linestyle = linestyles[0])
plt.tick_params(labelsize = 20)
plt.xlabel('Time (s)', fontsize = 24)
plt.ylabel('WD Distance / Initial Distance', fontsize = 24)
plt.tight_layout()
plt.savefig(eps_filename_curr)
plt.close()
def stellar_distance_convergence(eps_filename, results_base):
"""Plot the WD distance as a function of resolution."""
if not is_root():
return
import os
if os.path.isfile(eps_filename):
return
if not os.path.exists(results_base):
return
import matplotlib.pyplot as plt
import numpy as np
res_list = wdmerger.get_parameter_list(results_base)
res_list = sorted([int(res[1:]) for res in res_list])
diag_list = [results_base + '/n' + str(res) + '/output/star_diag.out' for res in res_list]
for i, diag in enumerate(diag_list):
time = wdmerger.get_column('TIME', diag)
dist = wdmerger.get_column('WD DISTANCE', diag)
mask = np.where(time <= 50.0)
plt.plot(np.array(time)[mask], np.array(dist)[mask] / np.array(dist)[0], lw = 4.0, linestyle = linestyles[i],
marker = markers[i], markersize = 12.0, markevery = 2000, label = 'n = ' + str(res_list[i]))
plt.tick_params(labelsize = 20)
plt.xlabel('Time (s)', fontsize = 24)
plt.ylabel('WD Distance / Initial Distance', fontsize = 24)
plt.legend(loc = 'best', prop = {'size':20}, fancybox = True, framealpha = 0.5)
plt.tight_layout()
plt.savefig(eps_filename)
plt.close()
def impact_parameter(eps_filename, results_dir):
"""Plot the effect of the impact parameter."""
import os
if os.path.isfile(eps_filename):
return
import numpy as np
from matplotlib import pyplot as plt
# Get the list of parameter values we have tried
dtnuc_list = wdmerger.get_parameter_list(results_dir)
ni56_arr = get_ni56(results_dir)
b_list = [dtnuc[len('b'):] for dtnuc in dtnuc_list]
b_list = sorted(b_list)
plt.plot(np.array(b_list), np.array(ni56_arr), markers[0], markersize=12.0)
xaxis_buffer = 0.025
plt.xlim(
[float(b_list[0]) - xaxis_buffer,
float(b_list[-1]) + xaxis_buffer])
plt.xlabel(r"Impact parameter $b$", fontsize=24)
plt.ylabel(r"$^{56}$Ni generated (M$_{\odot}$)", fontsize=24)
plt.tick_params(labelsize=20)
plt.tight_layout()
plt.savefig(eps_filename)
wdmerger.insert_commits_into_eps(eps_filename, get_diagfile(results_dir),
'diag')
plt.close()
def burning_mode(out_filename, results_base):
"""Create a table with the nickel generation as a function of the burning_mode parameter."""
if (os.path.isfile(out_filename)):
return
# Get the list of parameter values we have tried
results_dir = results_base + '/burning_mode'
param_list = wdmerger.get_parameter_list(results_dir)
mode_list = [param for param in param_list]
ni56_list = get_ni56(results_dir)
comment = '%\n' + \
'% Summary of the effect of the burning mode \n' + \
'% for reactions on 56Ni yield in a 2D white \n' + \
'% dwarf collision.\n' + \
'% The first column is the density minimum and the \n' + \
'% second is the final nickel mass produced, in solar masses.\n' + \
'%\n'
caption = 'Maximum $^{56}Ni$ mass ($M_{\odot}) produced as a function of the ' + \
'burning mode for allowing nuclear reactions. Burning mode 0 is a ' + \
'hydrostatic burn, mode 1 is a self-heating burn, mode 2 is a hybrid ' + \
'burn, and mode 3 is a suppressed burn. The meaning of these burning ' + \
'modes is explained in the text.'
col1title = 'Burning Mode'
label = 'burningmode'
write_ni56_table(results_dir, out_filename, mode_list, ni56_list, comment,
caption, col1title, label)
def amr_detonation(eps_filename, results_base):
"""Plot the effect of the refinement based on the nuclear burning rate on the detonation conditions."""
import os
if os.path.isfile(eps_filename):
return
else:
print("Generating file %s" % eps_filename)
import math
import numpy as np
from matplotlib import pyplot as plt
if not os.path.isdir(results_base):
return
diag_file = None
# First, generate a plot of nickel production.
ncell_list = sorted([int(n[1:]) for n in os.listdir(results_base)])
# Now, generate a plot of the distance from the center of the ignition point.
i = 0
for ncell in ncell_list:
results_dir = results_base + 'n' + str(ncell) + '/self-heat/dxnuc/'
if not os.path.isdir(results_dir):
continue
# Get the list of parameter values we have tried
r_list = wdmerger.get_parameter_list(results_dir)
# Strip out the non-refinement directories
r_list = [r for r in r_list if r[0] == 'r']
if (r_list == []):
continue
# Sort them numerically.
r_list = ['r' + str(r) for r in sorted([int(r[1:]) for r in r_list])]
# Cycle through the plot files.
# Get the maximum value of t_sound_t_enuc, and its distance from the origin.
# Stop if we hit a detonation (t_sound_t_enuc > 1).
for r in r_list:
results_dir = results_base + 'n' + str(
ncell) + '/self-heat/dxnuc/' + r
prefix = 'smallplt'
plt_list = [
results_dir + '/output/' + plt
for plt in wdmerger.get_plotfiles(results_dir, prefix=prefix)
]
for plt in plt_list:
[ts_te_max, x, y,
z] = wdmerger.get_maxloc(plt, 't_sound_t_enuc')
if ts_te_max > 1.0:
[rho_max, x, y, z] = wdmerger.get_maxloc(plt, 'density')
dist = np.sqrt(x**2 + y**2)
time = wdmerger.get_time_from_plotfile(plt)
print(ncell, r, time, rho_max, ts_te_max, dist.v / 1.e5)
break
i += 1
def rho_T_sliceplots(output_base,
results_base,
smallplt=True,
prefix="",
domain_frac=1.0,
x_ticks=[2.0e9, 4.0e9],
y_ticks=[2.0e9, 4.0e9],
scale_exp=9):
"""Create a rho/T sliceplot for every plotfile in a given directory."""
import os
if not os.path.isdir(output_base):
os.makedirs(output_base)
from PIL import Image
if (smallplt):
plt_prefix = 'smallplt'
r_list = wdmerger.get_parameter_list(results_base)
# Strip out the non-refinement directories
r_list = [r for r in r_list if r[0] == 'r']
if (r_list == []):
return
dir_list = [results_base + r + '/output/' for r in r_list]
for param, directory in zip(r_list, dir_list):
output_dir = output_base + param
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
plt_list = wdmerger.get_plotfiles(directory, plt_prefix)
eps_list = [
output_dir + "/rho_T_slice" + prefix + "_" + param + "_t_" +
str("%.2f" % wdmerger.get_time_from_plotfile(directory + pltfile))
+ '.eps' for pltfile in plt_list
]
# Generate the plot
for eps_file, pltfile in zip(eps_list, plt_list):
if os.path.isfile(eps_file):
continue
print("Generating plot with filename " + eps_file)
wdmerger.rho_T_sliceplot(eps_file,
directory + pltfile,
domain_frac=domain_frac,
x_ticks=x_ticks,
y_ticks=y_ticks,
scale_exp=scale_exp)
jpg_list = [eps.replace('eps', 'jpg') for eps in eps_list]
mpg_filename = output_dir + "/rho_T_slice" + prefix + "_" + param + ".mpg"
if not os.path.isfile(mpg_filename):
print("Generating file %s" % mpg_filename)
wdmerger.make_movie(output_dir, jpg_list, mpg_filename)
def ode_tolerances(eps_filename, results_base):
"""Plot the effects of all ODE tolerance options."""
if (os.path.isfile(eps_filename)):
return
else:
print("Generating file %s" % eps_filename)
results_dir = results_base + 'spec_tol/'
if not os.path.isdir(results_dir):
return
# Get the list of parameter values we have tried
s_tol_list = wdmerger.get_parameter_list(results_dir)
if (s_tol_list == []):
return
ni56_s_arr = np.array(get_ni56(results_dir))
tol_s_list = [tol[len('tol'):] for tol in tol_s_list]
tol_s_list = np.array([float(tol.replace('d', 'e')) for tol in tol_s_list])
# Sort the lists
ni56_s_arr = np.array([x for _, x in sorted(zip(tol_s_list, ni56_s_arr))])
tol_s_list = sorted(tol_s_list)
results_dir = results_base + 'temp_tol/'
if not os.path.isdir(results_dir):
return
# Get the list of parameter values we have tried
tol_t_list = wdmerger.get_parameter_list(results_dir)
if (tol_t_list == []):
return
ni56_t_arr = np.array(get_ni56(results_dir))
tol_t_list = [tol[len('tol'):] for tol in tol_t_list]
tol_t_list = np.array([float(tol.replace('d', 'e')) for tol in tol_t_list])
# Sort the lists
ni56_t_arr = np.array([x for _, x in sorted(zip(tol_t_list, ni56_t_arr))])
tol_t_list = sorted(tol_t_list)
results_dir = results_base + 'enuc_tol/'
if not os.path.isdir(results_dir):
return
# Get the list of parameter values we have tried
tol_e_list = wdmerger.get_parameter_list(results_dir)
if (tol_e_list == []):
return
ni56_e_arr = np.array(get_ni56(results_dir))
tol_e_list = [tol[len('tol'):] for tol in tol_e_list]
tol_e_list = np.array([float(tol.replace('d', 'e')) for tol in tol_e_list])
# Sort the lists
ni56_e_arr = np.array([x for _, x in sorted(zip(tol_e_list, ni56_e_arr))])
tol_e_list = sorted(tol_e_list)
plt.plot(tol_s_list,
ni56_s_arr,
linestyle=linestyles[0],
lw=4.0,
label=r'Species Tolerance')
plt.plot(tol_t_list,
ni56_t_arr,
linestyle=linestyles[1],
lw=4.0,
label=r'Temperature Tolerance')
plt.plot(tol_e_list,
ni56_e_arr,
linestyle=linestyles[2],
lw=4.0,
label=r'Energy Tolerance')
plt.xscale('log')
plt.xlabel(r"ODE Error Tolerance", fontsize=20)
plt.ylabel(r"$^{56}$Ni generated (M$_{\odot}$)", fontsize=20)
plt.tick_params(labelsize=16)
plt.legend(loc='best')
plt.tight_layout()
plt.savefig(eps_filename)
wdmerger.insert_commits_into_eps(eps_filename, get_diagfile(results_dir),
'diag')
png_filename = eps_filename[0:-3] + "png"
plt.savefig(png_filename)
plt.close()
def amr_nickel(eps_filename, results_base):
"""Plot the effect of the refinement based on the nuclear burning rate on the nickel generation."""
import os
if os.path.isfile(eps_filename):
return
else:
print("Generating file %s" % eps_filename)
import math
import numpy as np
from matplotlib import pyplot as plt
if not os.path.isdir(results_base):
return
diag_file = None
# First, generate a plot of nickel production.
ncell_list = sorted([int(n[1:]) for n in os.listdir(results_base)])
i = 0
for ncell in ncell_list:
results_dir = results_base + 'n' + str(ncell) + '/self-heat/dxnuc/'
if not os.path.isdir(results_dir):
continue
# Get the list of parameter values we have tried
r_list = wdmerger.get_parameter_list(results_dir)
# Strip out the non-refinement directories
r_list = [r for r in r_list if r[0] == 'r']
if (r_list == []):
continue
r_list = [float(r[1:]) for r in r_list]
ni56_arr = get_ni56(results_dir, 'r')
if ni56_arr == []:
continue
if diag_file == None and get_diagfile(results_dir) != None:
diag_file = get_diagfile(results_dir)
# Sort the lists
ni56_arr = np.array([x for _, x in sorted(zip(r_list, ni56_arr))])
r_list = np.array(sorted(r_list))
zonesPerDim = [ncell * int(r) for r in r_list]
plt.plot(zonesPerDim,
ni56_arr,
markers[i],
markersize=12,
linestyle=linestyles[i],
lw=4.0,
label='n = ' + str(ncell))
i += 1
plt.tick_params(axis='both', which='major', pad=10)
plt.xscale('log', basex=2)
plt.ylim([0.0, 0.6])
plt.xlabel(r"Effective zones/dimension", fontsize=24)
plt.ylabel(r"$^{56}$Ni generated (M$_{\odot}$)", fontsize=24)
plt.tick_params(labelsize=16)
plt.legend(loc='best', prop={'size': 20})
plt.tight_layout()
plt.savefig(eps_filename)
wdmerger.insert_commits_into_eps(eps_filename, diag_file, 'diag')
png_filename = eps_filename[0:-3] + "png"
plt.savefig(png_filename)
plt.close()
def amr_ignition(file_base, results_base, do_amr=True):
"""Plot the effect of the resolution on the detonation conditions."""
if not os.path.isdir(results_base):
return
size = 1.6384e9
ncell_list = sorted([int(n[1:]) for n in os.listdir(results_base)])
res_lists = [[]] * len(ncell_list)
dist_lists = [[]] * len(ncell_list)
time_lists = [[]] * len(ncell_list)
base_res_list = []
for i, ncell in enumerate(ncell_list):
base_res_list.append(size / ncell / 1.e5)
dir = results_base + '/n' + str(ncell)
if not os.path.isdir(dir):
continue
# Generate a plot of the distance from the center of the ignition point,
# and also the time of the ignition.
# Get the list of refinement values we have tried.
r_list = wdmerger.get_parameter_list(dir)
if (r_list == []):
continue
# Sort them numerically.
r_list = ['r' + str(r) for r in sorted([int(r[1:]) for r in r_list])]
# Cycle through the plot files.
# Get the distance from the origin of the point where T > 4e9 K, if it exists.
zonesPerDim = []
res_list = []
dist_list = []
time_list = []
for r in r_list:
results_dir = results_base + '/n' + str(ncell) + '/' + r
if not os.path.isdir(results_dir):
continue
print('Searching in directory ' + results_dir)
prefix = 'det_x_plt'
plot_list = [
results_dir + '/output/' + plot
for plot in wdmerger.get_plotfiles(results_dir, prefix=prefix)
]
# Since we'll have stopped after the ignition has occurred,
# we'll search through the plotfiles backward.
T_max = -1.0
T_last = -1.0
for plot in reversed(plot_list):
[T_max, x, y, z] = wdmerger.get_maxloc(plot, 'Temp')
if (T_max < 4.0e9 and T_last >= 4.0e9) or (T_max >= 4.0e9
and T_last < 0.0):
dist = abs(x.v) / 1.0e5
time = wdmerger.get_time_from_plotfile(plot)
zonesPerDim.append(ncell * int(r[1:]))
ds = yt.load(plot)
problo = ds.domain_left_edge.v
probhi = ds.domain_right_edge.v
size = probhi[0] - problo[0]
res_list.append(size / (ncell * int(r[1:])) / 1.0e5)
dist_list.append(dist)
time_list.append(time)
break
else:
T_last = T_max
res_lists[i] = res_list
dist_lists[i] = dist_list
time_lists[i] = time_list
# Plot location of the ignition and time on the same axis.
# We want to combine data at low resolution using their coarse
# grid runs, with the AMR data at the highest resolution.
res_list = []
dist_list = []
time_list = []
for i in range(len(ncell_list) - 1):
res_list.append(res_lists[i][0])
dist_list.append(dist_lists[i][0])
time_list.append(time_lists[i][0])
for res in res_lists[-1]:
res_list.append(res)
for dist in dist_lists[-1]:
dist_list.append(dist)
for time in time_lists[-1]:
time_list.append(time)
fig, ax1 = plt.subplots()
ax1.plot(res_list,
dist_list,
linestyle=linestyles[0],
marker=markers[0],
color=colors[0],
lw=2.0,
label='Ignition location')
ax1.set_xscale('log', basex=10)
ax1.set_xlabel(r"Finest resolution (km)", fontsize=24)
ax1.set_ylabel(r"Ignition location (km)", fontsize=24, color=colors[0])
ax1.tick_params(axis='y', labelcolor=colors[0], labelsize=16)
ax1.tick_params(axis='x', labelsize=16)
ax1.set_ylim(bottom=0.0)
ax2 = ax1.twinx()
ax2.plot(res_list,
time_list,
linestyle=linestyles[1],
marker=markers[1],
color=colors[1],
lw=2.0,
label='Ignition time')
ax2.set_ylabel(r"Ignition time (s)", fontsize=24, color=colors[1])
ax2.tick_params(axis='y', labelcolor=colors[1], labelsize=16)
ax2.set_ylim(bottom=0.0)
fig.set_size_inches(11, 8.5)
fig.tight_layout()
plt.savefig(file_base + '.eps')
plt.savefig(file_base + '.png')
plt.close()
def burning_mode(out_filename, results_base):
"""Create a table with the nickel generation as a function of the burning_mode parameter."""
if (os.path.isfile(out_filename)):
return
else:
print("Generating file %s" % out_filename)
# Get the list of parameter values we have tried
results_dir = results_base + '/burning_mode'
if not os.path.isdir(results_dir):
return
param_list = wdmerger.get_parameter_list(results_dir)
if (param_list == []):
return
mode_list = [param for param in param_list]
ni56_list = get_ni56(results_dir)
# Sort the lists
ni56_list = np.array([x for _, x in sorted(zip(mode_list, ni56_list))])
mode_list = sorted(mode_list)
# Replace the burning mode numbers with names for output purposes
try:
mode_list[mode_list.index('0')] = 'Hydrostatic'
except:
pass
try:
mode_list[mode_list.index('1')] = 'Self-heating'
except:
pass
try:
mode_list[mode_list.index('2')] = 'Hybrid'
except:
pass
try:
mode_list[mode_list.index('3')] = 'Suppressed'
except:
pass
comment = '%\n' + \
'% Summary of the effect of the burning mode \n' + \
'% for reactions on 56Ni yield in a white \n' + \
'% dwarf collision.\n' + \
'% The first column is the density minimum and the \n' + \
'% second is the final nickel mass produced, in solar masses.\n' + \
'%\n'
caption = 'The burning modes are explained in \\autoref{sec:burner}.'
col1title = 'Burning Mode'
title = 'Burning Mode'
label = 'burningmode'
precision = 5 # Because the suppressed burning mode creates so little nickel
write_ni56_table(results_dir,
out_filename,
mode_list,
ni56_list,
comment,
col1title,
label,
precision=precision,
title=title,
caption=caption)
