tau_approx = Lx * np.pi * m**2 / (2. * Lz * eps * N1 * k)
tau_exact = tau_approx + eps * (Lx / Lz) * (2. * (m * np.pi)**2 -
3.) / (12. * N1 * k * np.pi)
tau_off = Lx * (6 + np.pi**2 * m**2 *
(1. + 3. * eps**2)) / (6. * eps * N1 * k * np.pi * Lz)
energ_normed = vars['tropenergy'][:, 0, 0] / np.max(vars['tropenergy'][:, 0,
0])
energ_theory = np.exp(-(dims['t'] - pulse_len) / tau_exact)
energ_approx = np.exp(-(dims['t'] - pulse_len) / tau_approx)
energ_off = np.exp(-(dims['t'] - pulse_len) / tau_off)
energ_normed_2D = vars['te'][:, 0, :].T / np.max(vars['te'][:, 0, :].T)
dp.make_1D_plot(sim_name + '/energytest.pdf',
dims['t'],
simulation=energ_normed,
theory=energ_theory,
offmode=energ_off)
dp.make_2D_plot(sim_name + '/tetest.pdf', (dims['t'], dims['z'] / 1000.),
energ_normed_2D,
title='Total Energy',
xlabel='time (s)',
ylabel='height (km)')
u_wnd = vars['uu'][-1, :, :].T
b_init = vars['b3d'][2, :, :].T
dp.make_2D_plot(sim_name + '/b_snap.pdf',
(dims['x'] / 1000., dims['z'] / 1000.),
b_init,
title='buoyancy at the beginning',
xlabel='x (km)',
dims = dp.read_dims(data)
data.close()
energ_normed = vars['tropenergy'][:,0,0]/np.max(vars['tropenergy'][:,0,0])
taufit.taufit(energ_normed,dims, m, k, eps, Lx, Lz, archive_list)
#tau_approx = Lx*np.pi*m**2/(2.*Lz*eps*N1*k*2.)
#tau_exact = tau_approx + eps * (Lx/Lz) * (2. * (m*np.pi)**2 - 3.)/(12. * N1 * k * np.pi * 2.)
#tau_off = Lx*(6 + np.pi**2*m**2*(1.+3.*eps**2))/(6.*eps*N1*k*np.p
energ_normed = vars['tropenergy'][:,0,0]/np.max(vars['tropenergy'][:,0,0])
energ_theory = np.exp(-(dims['t'] - pulse_len )/tau_exact)
energ_approx = np.exp(-(dims['t'] - pulse_len )/tau_approx)
#energ_off = np.exp(-(dims['t'] - pulse_len)/tau_off)
dp.make_1D_plot(sim_name+'/energytest.pdf', dims['t'], simulation = energ_normed,
theory = energ_theory, approx = energ_approx)
dp.make_2D_plot(sim_name+'/binit.pdf', (dims['x']/1000., dims['z']/1000.),vars['b3d'][1,:,:].T , title='b initial', xlabel = 'x (km)', ylabel = 'z (km)')
plt.clf()
plt.plot(dims['t'], np.log(energ_normed))
plt.plot(dims['t'], -1./tau_exact*dims['t'], label = 'theory')
plt.legend()
plt.savefig(sim_name + '/regresstest.pdf')
plt.clf()
taufit.plot_taus(archive_list)
import pickle
outfile = open( "eps02_m2.p", "wb" )
pickle.dump(archive_list, outfile)
#dp.make_1D_plot(sim_name+'/energytest.pdf', dims['t'], simulation = energ_normed,
# theory = energ_theory, offmode = energ_off)
data = h5py.File(filepath, "r")
dict_vars = {'te':'total e profile','b3d':'buoyancy', 'tropenergy':'tropo energy'}
vars = dp.read_vars(data, dict_vars)
dims = dp.read_dims(data)
data.close()
#parameters
pulse_len = 300
m = 1.5
k = 10.
N1 = 0.01
eps = 1
Lx, Lz = (2000000, 10000)
tau_approx = Lx*np.pi*m**2/(2.*Lz*eps*N1*k)
tau_exact = tau_approx + eps * (Lx/Lz) * (2. * (m*np.pi)**2 - 3.)/(12. * N1 * k * np.pi)
tau_off = Lx*(6 + np.pi**2*m**2*(1.+3.*eps**2))/(6.*eps*N1*k*np.pi*Lz)
energ_normed = vars['tropenergy'][:,0,0]/np.max(vars['tropenergy'][:,0,0])
energ_theory = np.exp(-(dims['t'] - pulse_len)/tau_exact)
energ_approx = np.exp(-(dims['t'] - pulse_len)/tau_approx)
energ_off = np.exp(-(dims['t'] - pulse_len)/tau_off)
energ_normed_2D = vars['te'][:,0,:].T/np.max(vars['te'][:,0,:].T)
dp.make_1D_plot('energytest.pdf', dims['t'], simulation = energ_normed, theory = energ_theory, off = energ_off)
dp.make_2D_plot('tetest.pdf', (dims['t'], dims['z']/1000.), energ_normed_2D, title = 'Total Energy', xlabel = 'time (s)', ylabel = 'height (km)')
pulse_len = 300
m = 1.5
k = 10.
N1 = 0.01
eps = 1
Lx, Lz = (2000000, 10000)
tau_approx = Lx * np.pi * m**2 / (2. * Lz * eps * N1 * k)
tau_exact = tau_approx + eps * (Lx / Lz) * (2. * (m * np.pi)**2 -
3.) / (12. * N1 * k * np.pi)
tau_off = Lx * (6 + np.pi**2 * m**2 *
(1. + 3. * eps**2)) / (6. * eps * N1 * k * np.pi * Lz)
energ_normed = vars['tropenergy'][:, 0, 0] / np.max(vars['tropenergy'][:, 0,
0])
energ_theory = np.exp(-(dims['t'] - pulse_len) / tau_exact)
energ_approx = np.exp(-(dims['t'] - pulse_len) / tau_approx)
energ_off = np.exp(-(dims['t'] - pulse_len) / tau_off)
energ_normed_2D = vars['te'][:, 0, :].T / np.max(vars['te'][:, 0, :].T)
dp.make_1D_plot('energytest.pdf',
dims['t'],
simulation=energ_normed,
theory=energ_theory,
off=energ_off)
dp.make_2D_plot('tetest.pdf', (dims['t'], dims['z'] / 1000.),
energ_normed_2D,
title='Total Energy',
xlabel='time (s)',
ylabel='height (km)')
# for pulse, base decay timescale based on domain size
if PULSE == True:
k = 4.
tau_approx = Lx*np.pi*m**2/(2.*Lz*eps*N1*k)
tau_exact = tau_approx + eps * (Lx/Lz) * (2. * (m*np.pi)**2 - 3.)/(12. * N1 * k * np.pi)
tau_off = Lx*(6 + np.pi**2*m**2*(1.+3.*eps**2))/(6.*eps*N1*k*np.pi*Lz)
energ_normed = vars['tropenergy'][:,0,0]/np.max(vars['tropenergy'][:,0,0])
energ_theory = np.exp(-(dims['t'] - pulse_len)/tau_exact)
energ_approx = np.exp(-(dims['t'] - pulse_len)/tau_approx)
energ_off = np.exp(-(dims['t'] - pulse_len)/tau_off)
energ_normed_2D = vars['te'][:,0,:].T/np.max(vars['te'][:,0,:].T)
dp.make_1D_plot(sim_name+'/energytest.pdf', dims['t'], simulation = energ_normed,
theory = energ_theory, offmode = energ_off)
dp.make_2D_plot(sim_name+'/tetest.pdf', (dims['t'], dims['z']/1000.), energ_normed_2D,
title = 'Total Energy', xlabel = 'time (s)', ylabel = 'height (km)')
u_wnd = vars['uu'][-1,:,:].T
b_init = vars['b3d'][2,:,:].T
dp.make_2D_plot(sim_name + '/b_snap.pdf', (dims['x']/1000., dims['z']/1000.) , b_init, title='buoyancy at the beginning', xlabel = 'x (km)', ylabel = 'z (km)' )
#
#plt.pcolormesh(t,z, te[:,0,:].T)
#plt.colorbar()
#plt.title('total energy' )
#figpath = sim_name + "/tetest.pdf"
#plt.savefig(figpath)
#plt.clf()