def load_from_nh(set_of_dir, nh):
set_of_dir_nh = set_of_dir.filter(nh=nh, f=0)
path = set_of_dir_nh.path_larger_t_start()
sim = solveq2d.create_sim_plot_from_dir(path)
tmin, tmax, tstatio = baseSW1lw.tminmaxstatio_from_sim(sim, VERBOSE=True)
(dico_time_means,
dico_results) = sim.output.spatial_means.compute_time_means(tstatio)
c2 = sim.param['c2']
c = np.sqrt(c2)
EK = dico_time_means['EK']
Fr = np.sqrt(2 * EK / c2)
EA = dico_time_means['EA']
EKr = dico_time_means['EKr']
EKd = EK - EKr
E = EK + EA
epsK = dico_time_means['epsK']
epsA = dico_time_means['epsA']
eps = epsK + epsA
epsK_tot = dico_time_means['epsK_tot']
epsA_tot = dico_time_means['epsA_tot']
Enorm = np.sqrt(eps * Lf * c)
print 'c = {0:8.1f}, Fr = {1:8.3f}, eps = {2:8.2f}'.format(c, Fr, eps)
return locals()
def spectra_from_namedir(nh):
set_of_dir_nh = set_of_dir.filter(nh=nh)
path = set_of_dir_nh.path_larger_t_start()
sim = solveq2d.create_sim_plot_from_dir(path)
tmin, tmax, tstatio = baseSW1lw.tminmaxstatio_from_sim(sim, VERBOSE=True)
dico_results = sim.output.spectra.load1D_mean(tmin=tstatio)
kh = dico_results['kh']
spectEK = (dico_results['spectrum1Dkx_EK'] +
dico_results['spectrum1Dkx_EK']) / 2
spectEA = (dico_results['spectrum1Dkx_EA'] +
dico_results['spectrum1Dkx_EA']) / 2
spectEKr = (dico_results['spectrum1Dkx_EKr'] +
dico_results['spectrum1Dkx_EKr']) / 2
spectEKd = spectEK - spectEKr
spectE = spectEK + spectEA
dico1, dico2 = sim.output.spatial_means.compute_time_means(tstatio=tstatio)
epsK = dico1['epsK']
epsA = dico1['epsA']
eps = epsK + epsA
EK = dico1['EK']
U = np.sqrt(2 * EK)
c = np.sqrt(sim.param['c2'])
return locals()
def print1sim(set_of_dir, f):
"""Print informations on one simulation."""
print('\n\n')
set_of_dir = set_of_dir.filter(f=f)
path = set_of_dir.path_larger_t_start()
sim = solveq2d.create_sim_plot_from_dir(path)
param = sim.param
nx = param['nx']
c = np.sqrt(sim.param['c2'])
nu8 = param['nu_8']
f = sim.param['f']
tmin, tmax, tstatio = baseSW1lw.tminmaxstatio_from_sim(sim, VERBOSE=True)
dico1, dico2 = sim.output.spatial_means.compute_time_means(tstatio=tstatio)
epsK = dico1['epsK']
epsA = dico1['epsA']
eps = epsK + epsA
Ff = eps**(1. / 3) * kf**(-1. / 3) / c
n = 8
kd8 = (eps / nu8**3)**(1. / (3 * n - 2))
kmax = param['coef_dealiasing'] * np.pi * nx / param['Lx']
minh, maxu = minhmaxu_from_sim(sim)
ftable.write('\n')
ftable.write('{0:4d} & {1:4.0f} & '.format(nx, c))
ftable.write('{0:7.1e} & '.format(nu8))
if f > 0:
Ro = eps**(1. / 3) * kf**(2. / 3) / f
Bu = (kf * c / f)**2
print('Ro = {0:.2f}; Bu = {1:.2f}'.format(Ro, Bu))
ftable.write('{0:4.1f} & {1:6.2g} & {2:6.2g} & '.format(f, Ro, Bu))
else:
ftable.write(' 0 & $\infty$ & $\infty$ & ')
ftable.write('{0:4.2f} & '.format(eps))
ftable.write('{0:.2f} & '.format(kmax / kd8))
ftable.write('{0:3.0f} & '.format(kd8 / kf))
ftable.write('{0:6.3f} & '.format(Ff))
ftable.write('{0:4.2f} & {1:4.2f} '.format(minh, maxu / c))
ftable.write('\\\\')
str_resol = repr(resol)
str_to_find_path = (dir_base + '/Pure_standing_waves_' + str_resol +
'*/SE2D*c=' + repr(c)) + '_*'
print(str_to_find_path)
paths = glob.glob(str_to_find_path)
print(paths)
set_of_dir = solveq2d.SetOfDirResults(paths)
path = set_of_dir.path_larger_t_start()
sim = solveq2d.create_sim_plot_from_dir(path)
tmin, tmax, tstatio = baseSW1lw.tminmaxstatio_from_sim(sim, VERBOSE=True)
dico_spectra, dico_results = sim.output.time_sigK.compute_spectra()
omega = dico_spectra['omega']
time_spectra_q = dico_spectra['time_spectra_q']
time_spectra_a = dico_spectra['time_spectra_a']
time_spectra_d = dico_spectra['time_spectra_d']
omega_shell = dico_results['omega_shell']
kh_shell = dico_results['kh_shell']
deltak = baseSW1lw.deltak
print('deltak/k = ', deltak / kh_shell)
print('k/deltak = ', kh_shell / deltak)
