def test2(self):
instance = QGmodel(redirection="none")
instance.grid[0, 0, 0].psi
self.assertEquals(instance.get_name_of_current_state(), 'EDIT')
instance.initialize_grid()
self.assertEquals(instance.get_name_of_current_state(), 'RUN')
instance.stop()
def high_level():
qg = QGmodel(redirection="none")
qg.initialize_code()
Nx = 128
Ny = 128
qg.parameters.Lx = 1.e6 | units.m
qg.parameters.Ly = 1.e6 | units.m
qg.parameters.dx = qg.parameters.Lx / Nx
qg.parameters.dy = qg.parameters.Ly / Ny
qg.parameters.ocean_depth = 600 | units.m
qg.parameters.tau = 0.15 | units.Pa
qg.parameters.beta0 = 1.6e-11 | (units.m * units.s)**-1
qg.parameters.dt = 1800 / 10 | units.s
rho0 = qg.parameters.rho
beta0 = qg.parameters.beta0
H = qg.parameters.ocean_depth
L = qg.parameters.Lx
T = qg.parameters.tau
U_dijkstra = 1.6e-2 | units.m / units.s
U = (T / (beta0 * rho0 * H * L))
print "actual, target U:", U.in_(units.m / units.s), U_dijkstra
Reynolds_number = 1.
A_H = U * L / Reynolds_number
qg.parameters.A_H = A_H
timescale = 1 / (beta0 * L)
print "timescale:", timescale.in_(units.s)
print qg.parameters
qg.commit_parameters()
# qg.grid.psi=(qg.grid.x/L ) | units.m**2/units.s
qg.initialize_grid()
pyplot.ion()
f = pyplot.figure()
pyplot.show()
for i in range(101):
tend = i * 12. | units.hour
qg.evolve_model(tend)
psi = qg.grid.psi[:, :, 0]
print qg.model_time.in_(units.day), psi.max(), psi.min()
pyplot.imshow(psi.transpose() / psi.max(),
vmin=0,
vmax=1,
origin="lower")
pyplot.draw()
raw_input()
def sample_run(Nx=128,
Ny=128,
Reynolds_number=50.,
wind_sigma=1.,
dtplot=24. | units.hour,
nstep=10):
qg = QGmodel(redirection="none")
qg.initialize_code()
L = 1.e6 | units.m
qg.parameters.Lx = L
qg.parameters.Ly = L
qg.parameters.dx = qg.parameters.Lx / Nx
qg.parameters.dy = qg.parameters.Ly / Ny
qg.parameters.ocean_depth = 600 | units.m
qg.parameters.tau = 0.15 | units.Pa
qg.parameters.beta0 = 1.6e-11 | (units.m * units.s)**-1
qg.parameters.dt = 900 | units.s
rho0 = qg.parameters.rho
beta0 = qg.parameters.beta0
H = qg.parameters.ocean_depth
L = qg.parameters.Lx
T = qg.parameters.tau
U_dijkstra = 1.6e-2 | units.m / units.s # mentioned in paper
U = (T / (beta0 * rho0 * H * L)) # actual derived from parameters
print("actual, target U:", U.in_(units.m / units.s), U_dijkstra)
A_H = U * L / Reynolds_number
qg.parameters.A_H = A_H
qg.parameters.wind_sigma = wind_sigma
timescale = 1 / (beta0 * L)
print("timescale:", timescale.in_(units.s))
print()
print(qg.parameters)
raw_input()
qg.commit_parameters()
# qg.grid.psi=(qg.grid.x/L ) | units.m**2/units.s
qg.initialize_grid()
pyplot.ion()
f = pyplot.figure()
pyplot.show()
for i in range(nstep + 1):
tend = i * dtplot
qg.evolve_model(tend)
psi = qg.grid.psi[:, :, 0]
print(qg.model_time.in_(units.day),(psi.max()/L).in_(units.km/units.hour), \
(psi.min()/L).in_(units.km/units.hour))
f.clf()
extent = [0, L.value_in(units.km), 0, L.value_in(units.km)]
pyplot.imshow(psi.transpose() / max(psi.max(), -psi.min()),
vmin=-1,
vmax=1,
origin="lower",
extent=extent)
pyplot.xlabel("km")
pyplot.title(str(qg.model_time.in_(units.day)))
pyplot.draw()
raw_input()
