for i, name in enumerate(("U", "V", "W")):
self.Umean[i, s] = self.f0["Average/"+name][s]
self.Pmean[s] = self.f0["Average/P"][s]
for i, name in enumerate(("UU", "VV", "WW", "UV", "UW", "VW")):
self.UU[i, s] = self.f0["Reynolds Stress/"+name][s]
if __name__ == "__main__":
config.update(
{
'solver': 'IPCS',
'nu': 1./180., # Viscosity
'Re_tau': 180.,
'dt': 0.001, # Time step
'T': 100., # End time
'L': [2, 4*pi, 4.*pi/3.],
'M': [6, 6, 5]
}, "Shen"
)
config.Shen.add_argument("--compute_energy", type=int, default=100)
config.Shen.add_argument("--plot_result", type=int, default=100)
config.Shen.add_argument("--sample_stats", type=int, default=100)
solver = get_solver(update=update, family="Shen")
initialize(**vars(solver))
#init_from_file("IPCSRR.h5", **vars(solver))
set_Source(**vars(solver))
solver.stats = Stats(solver.U, solver.comm, filename="MKMstats")
solver.hdf5file.fname = "IPCSRR.h5"
solver.solve()
s = solver.stats.get_stats()
print t, float(kk), float(ww)
def regression_test(t, tstep, comm, U, curl, float64, dx, L, sum, rank, **kw):
k = comm.reduce(sum(U.astype(float64)*U.astype(float64))*dx[0]*dx[1]*dx[2]/L[0]/L[1]/L[2]/2) # Compute energy with double precision
if config.solver == 'NS':
w = comm.reduce(sum(curl.astype(float64)*curl.astype(float64))*dx[0]*dx[1]*dx[2]/L[0]/L[1]/L[2]/2)
elif config.solver == 'VV':
w = comm.reduce(sum(kw['W'].astype(float64)*kw['W'].astype(float64))*dx[0]*dx[1]*dx[2]/L[0]/L[1]/L[2]/2)
if rank == 0:
assert round(k - 0.124953117517, 7) == 0
assert round(w - 0.375249930801, 7) == 0
if __name__ == "__main__":
config.update(
{
'nu': 0.00625, # Viscosity
'dt': 0.01, # Time step
'T': 0.1, # End time
'L': [2*pi, 4*pi, 2*pi],
'M': [5, 5, 5]
}, "Isotropic"
)
config.Isotropic.add_argument("--compute_energy", type=int, default=2)
solver = get_solver(update=update)
solver.hdf5file.fname = "NS7.h5"
solver.hdf5file.components["W0"] = solver.curl[0]
solver.hdf5file.components["W1"] = solver.curl[1]
solver.hdf5file.components["W2"] = solver.curl[2]
initialize(**vars(solver))
solver.solve()
comm.Gather(u0, uall, root=0)
if rank == 0:
uall = uall.reshape((N[0],))
#x = points
#pc = zeros(len(x))
#pc = ST.fct(uall, pc) # Cheb transform of result
#solution at x = 0
#u = n_cheb.chebval(0, pc)
#u_exact = reference(config.Re, config.t)
u_exact = exact(points, config.Re, config.t)
print "Computed error = %2.8e %2.8e " %(sqrt(sum((uall-u_exact)**2)/N[0]), config.dt)
if __name__ == "__main__":
config.update(
{
'solver': 'IPCS',
'Re': 800.,
'nu': 1./800., # Viscosity
'dt': 0.5, # Time step
'T': 50., # End time
'L': [2, 2*pi, 4*pi/3.],
'M': [6, 5, 1]
}, "Shen"
)
config.Shen.add_argument("--compute_energy", type=int, default=5)
config.Shen.add_argument("--plot_step", type=int, default=10)
solver = get_solver(update=update, regression_test=regression_test, family="Shen")
initialize(**vars(solver))
set_Source(**vars(solver))
solver.solve()
#e1 = 0.5*energy(pert, N, comm, rank, L)
#exact = exp(2*imag(OS.eigval)*config.t)
#if rank == 0:
#print "Computed error = %2.8e %2.8e " %(sqrt(abs(e1/e0-exact)), config.dt)
initOS(OS, U0, U_hat0, X, FST, ST, t=config.t)
pert = (U[0] - U0[0])**2 + (U[1]-U0[1])**2
e1 = 0.5*energy(pert, N, comm, rank, L)
#exact = exp(2*imag(OS.eigval)*config.t)
if rank == 0:
print "Computed error = %2.8e %2.8e " %(sqrt(e1), config.dt)
if __name__ == "__main__":
config.update(
{
'solver': 'IPCS_GeneralBCs',
'Re': 8000.,
'nu': 1./8000., # Viscosity
'dt': 0.01, # Time step
'T': 0.02, # End time
'L': [2, 2*pi, 4*pi/3.],
'M': [7, 6, 1]
}, "ShenGeneralBCs"
)
config.ShenGeneralBCs.add_argument("--compute_energy", type=int, default=1)
config.ShenGeneralBCs.add_argument("--plot_step", type=int, default=10)
solver = get_solver(update=update, regression_test=regression_test, family="ShenGeneralBCs")
vars(solver).update(initialize(**vars(solver)))
set_Source(**vars(solver))
solver.solve()
plt.draw()
if tstep % config.write_result == 0:
P = ifft2_mpi(P_hat*1j, P)
curl = ifft2_mpi(1j*K[0]*U_hat[1]-1j*K[1]*U_hat[0], curl)
hdf5file.write(tstep)
if tstep % config.plot_result == 0 and config.plot_result > 0:
curl = ifft2_mpi(1j*K[0]*U_hat[1]-1j*K[1]*U_hat[0], curl)
im.set_data(curl[:, :])
im.autoscale()
plt.pause(1e-6)
if __name__ == '__main__':
config.update(
{
'solver': 'NS2D',
'nu': 0.001,
'dt': 0.005,
'T': 50,
'write_result': 100,
'M': [6, 6]}
)
config.Isotropic.add_argument("--plot_result", type=int, default=10) # required to allow overloading through commandline
solver = get_solver(update=update, regression_test=regression_test)
solver.hdf5file.components["curl"] = solver.curl
initialize(**vars(solver))
solver.solve()
if tstep % config.write_result == 0:
P = ifft2_mpi(P_hat*1j, P)
curl = ifft2_mpi(1j*K[0]*U_hat[1]-1j*K[1]*U_hat[0], curl)
hdf5file.write(tstep)
if tstep % config.plot_result == 0 and config.plot_result > 0:
curl = ifft2_mpi(1j*K[0]*U_hat[1]-1j*K[1]*U_hat[0], curl)
im.set_data(curl[:, :])
im.autoscale()
plt.pause(1e-6)
if __name__ == '__main__':
from cbcdns import config, get_solver
config.update(
{
'nu': 0.001,
'dt': 0.005,
'T': 50,
'write_result': 100}
)
config.parser.add_argument("--plot_result", type=int, default=10) # required to allow overloading through commandline
solver = get_solver()
solver.hdf5file.components["curl"] = solver.curl
initialize(**vars(solver))
solver.update = update
solver.regression_test = regression_test
solver.solve()
