def setUp(self):
self.m = CoupledModel.Model(use_filter=False,nu4=1e14,nu4w=0.)
self.m.tmax = 10*self.m.dt
k, l = 2*np.pi*5/self.m.L, 2*np.pi*9/self.m.L
self.qi = np.sin(k*self.m.x + l*self.m.y)
self.m.set_q(self.qi)
self.m.set_phi(self.qi*0)
def setUp(self):
U0 = 0.05
self.m = CoupledModel.Model(use_filter=False, U=-U0, tdiags=1)
k0 = 10 * (2 * np.pi / self.m.L)
q = ic.LambDipole(self.m, U=U0, R=2 * np.pi / k0)
phi = (np.ones_like(q) + 1j) * 5 * U0 / np.sqrt(2)
self.m.set_q(q)
self.m.set_phi(phi)
self.m.run()
#dt = .0025*Te
dt = .001 * Te
tmax = 10 * Te
## setup model class
model = Model.Model(L=L,
nx=nx,
tmax=tmax,
dt=dt,
m=m,
N=N,
f=f0,
twrite=int(0.1 * Te / dt),
nu4=nu4,
nu4w=nu4w,
nu=0,
nuw=0,
mu=0,
muw=0,
use_filter=False,
U=0,
tdiags=10,
save_to_disk=True,
tsave_snapshots=100,
path=patho,
use_mkl=True,
nthreads=2)
#model = Model.Model(L=L,nx=nx, tmax = tmax,dt = dt,
# twrite=int(0.1*Te/dt),
# nu4=nu4, use_filter=True,
# U =0, tdiags=10,
def setUp(self):
self.m = CoupledModel.Model(use_filter=False)
self.qi = randn(self.m.ny, self.m.nx)
self.phii = randn(self.m.ny,
self.m.nx) + 1j * randn(self.m.ny, self.m.nx)
def Run_CoupledModel(lambdaz=400):
""" Run the model given vertical wavelength m, which the dispersivity, and
fixed initial NIW velocity """
Uw = 0.1
m = 2 * np.pi / lambdaz
patho = "outputs/decaying_turbulence/parameter_exploration/"
patho_qgniw = patho + "Uw" + str(
round(Uw * 10) / 10) + "/lambdaz" + str(lambdaz) + "/"
dt = .0025 * Te / 2
tmax = 150 * Te
# choose nu4w based on vertical wavelength
if lambdaz <= 200:
nu4w_ = nu4w / 10
if lambdaz <= 285:
nu4w_ = nu4w / 5.
elif lambdaz <= 400:
nu4w_ = nu4w
elif lambdaz <= 600:
nu4w_ = 5 * nu4w
elif lambdaz <= 800:
nu4w_ = 10 * nu4w
else:
nu4w_ = nu4w
model = CoupledModel.Model(
L=L,
nx=nx,
tmax=tmax,
dt=dt,
m=m,
N=N,
f=f0,
twrite=int(0.1 * Te / dt),
nu4=nu4,
nu4w=nu4w_,
nu=0,
nuw=0,
mu=0,
muw=0,
use_filter=False,
U=0.,
tdiags=10,
save_to_disk=True,
tsave_snapshots=25,
path=patho_qgniw,
)
## initial conditions
model.set_q(q)
phi = (np.ones_like(q) + 1j) * Uw / np.sqrt(2)
model.set_phi(phi)
# save parameters
SaveParams(model=model, patho=patho_qgniw, m=m, Uw=Uw)
# run the model
model.run()
# simulation parameters
dt = .0025 * Te
tmax = 0.75 * Te
## setup model class
model = Model.Model(L=L,
nx=nx,
tmax=tmax,
dt=dt,
m=m,
N=N,
f=f0,
twrite=int(0.1 * Te / dt),
nu4=nu4 * 0,
nu4w=nu4w * 0,
nu=0,
nuw=0,
mu=0,
muw=0,
use_filter=True,
U=-Ue,
tdiags=10,
save_to_disk=True,
tsave_snapshots=25,
path=patho)
# a quasi-straining flow
psi = -np.sin(2 * np.pi * model.x / model.L) * np.sin(
2 * np.pi * model.y / model.L)
psi_hat = np.fft.fft2(psi)
q = np.fft.ifft2(-model.wv2 * psi_hat).real / (Ue * ke)
#
## initial conditions
#q = ic.McWilliams1984(qgmodel, E=(Ue**2)/2,k0=ke)
#qgmodel.set_q(q)
#
#qgmodel.run()
dt = .0025*Te
tmax = 150*Te
#
# setup model classes
#
coupledmodel = CoupledModel.Model(L=L,nx=nx, tmax = tmax,dt = dt,
m=m,N=N,f=f0, twrite=int(0.1*Te/dt),
nu4=nu4,nu4w=nu4w,nu=0, nuw=0, mu=0, muw=0, use_filter=False,
U = 0., tdiags=10, save_to_disk=True,tsave_snapshots=25, path=patho+"coupled/",)
coupledmodel.logger.info(" ")
#
# initial conditions
#
qinit = np.load("q_init_512.npz")
q = qinit['q']
phi = (np.ones_like(q) + 1j)*Uw/np.sqrt(2)
#model.set_q(qgmodel.q)
coupledmodel.set_q(q)
coupledmodel.set_phi(phi)
def setUp(self):
self.m = CoupledModel.Model(use_filter=False)
k, l = 2*np.pi*5/self.m.L, 2*np.pi*9/self.m.L
self.m.set_q(np.sin(k*self.m.x + l*self.m.y))
self.m.set_phi(np.sin(k*self.m.x + l*self.m.y))
Te = (U0 * k0)**-1 # eddy turn-over time scale
Tf = 2 * np.pi / f0
dt = .025 * Te
tmax = 10 * Te
m = Model.Model(
L=L,
nx=nx,
tmax=tmax,
dt=dt,
m=m,
N=N,
f=f0,
twrite=int(1 * Tf / dt),
nu4=5e11,
nu4w=0e10,
nu=20,
nuw=50e0,
mu=0.e-7,
muw=0e-7,
use_filter=False,
U=-U,
tdiags=1,
save_to_disk=False,
dealias=False,
)
# initial conditions
q = ic.LambDipole(m, U=U, R=2 * np.pi / k0)
phi = (np.ones_like(q) + 1j) * u0 / np.sqrt(2)