def get_rel_LInf_errors(target_dirs):
d_list = []
for outdir in target_dirs:
r = ASCIIReader(outdir)
__, d = r.get_time_and_detonation_velocity()
d_list.append(d)
errors_LInf = [float('NaN')]
for i, d in enumerate(d_list):
if i == 0:
continue
d_1 = d_list[i - 1]
d_2 = d_list[i]
error = linalg.norm(d_1 - d_2, np.Inf) / linalg.norm(d_2, np.Inf)
errors_LInf.append(error)
assert len(target_dirs) == len(errors_LInf)
errors_LInf_array = np.asarray(errors_LInf)
return errors_LInf_array
def get_modes_list(target_dirs):
modes_list = []
for outdir in target_dirs:
r = ASCIIReader(outdir)
modes = r.get_stability_info()
modes_list.append(modes)
return modes_list
def plot_time_series(E_act):
r = ASCIIReader('_output/q=050.00-e_act=0{:4.2f}/n12=0160/'.format(E_act))
t, d = r.get_time_and_detonation_velocity()
plt.figure()
plt.plot(t, d, '-')
plt.xlabel('time')
plt.ylabel(r"$\psi '$")
plt.tight_layout(pad=0.1)
savefig('time-series-e_act={:4.2f}.pdf'.format(E_act))
def znd_read_data():
output_dir = '_output'
dirs = os.listdir(output_dir)
dirs.sort()
x = []
rho = []
u = []
p = []
lamda = []
for d in dirs:
dirname = os.path.join(output_dir, d)
r = ASCIIReader(dirname)
znd_data = r.get_znd_data()
x.append(znd_data['x'])
rho.append((d, znd_data['rho']))
u.append((d, znd_data['u_lab']))
p.append((d, znd_data['p']))
lamda.append((d, znd_data['lamda']))
return x, rho, u, p, lamda
return outdir
if __name__ == '__main__':
q = 50.0
n12_list = [20, 40, 80, 160, 320, 640, 1280, 2560]
tasks = [(q, n12) for n12 in n12_list]
with mp.Pool(processes=12) as pool:
results = pool.map(_run_solver, tasks)
assert results == sorted(results)
sim_results = []
for r in results:
reader = ASCIIReader(r)
__, d = reader.get_time_and_detonation_velocity()
sim_results.append(d)
for i, n12 in enumerate(n12_list[:-1]):
print('*** Difference between N12={} and N12={}'.format(
n12_list[i], n12_list[i + 1]))
d_1 = sim_results[i]
d_2 = sim_results[i + 1]
print(' L2-norm of difference: {}'.format(linalg.norm(d_1 - d_2,
2)))
print(' LInf-norm of difference: {}'.format(
linalg.norm(d_1 - d_2, np.Inf)))
#!/usr/bin/env python
import os
import matplotlib.pyplot as plt
from saf.euler1d.linear.asciireader import ASCIIReader
from matplotlib.ticker import FormatStrFormatter
from helpers import FIGSIZE_TWO_SUBPLOTS_TWO_ROWS as figsize
r_35 = ASCIIReader('_output/q=050.00-e_act=035.00/n12=0640')
r_40 = ASCIIReader('_output/q=050.00-e_act=040.00/n12=0640')
t_35, d_35 = r_35.get_time_and_detonation_velocity()
t_40, d_40 = r_40.get_time_and_detonation_velocity()
fig, ax = plt.subplots(nrows=2, ncols=1, figsize=figsize)
ax[0].plot(t_35, d_35, '-')
ax[0].set_xlim((0, 50))
ax[0].set_ylim((-0.1, 0.85))
#ax[0].set_ylim((-1e-4, 1e-4))
ax[0].set_xlabel(r'$t$')
ax[0].set_ylabel(r"$\psi '$")
f_1_x = FormatStrFormatter('%6.1f')
ax[0].yaxis.set_major_formatter(f_1_x)
ax[0].text(0.9, 0.85, '(a)', transform=ax[0].transAxes)
ax[1].plot(t_40, d_40, '-')
ax[1].set_ylim((-100, 2000))
ax[1].set_ylabel(r"$\psi '$")
ax[1].set_xlabel(r'$t$')