def outputs(self, output_func=None):
"""This function print the coefficients computed in the inprod_analytic module"""
if output_func is None:
self.values.clear()
tfunc = self.save_ip
else:
tfunc = output_func
pars = QgParams()
pars.set_atmospheric_channel_fourier_modes(6, 6)
pars.set_oceanic_basin_fourier_modes(6, 6)
# Setting MAOOAM default parameters
pars.set_params({'kd': 0.04, 'kdp': 0.04, 'n': 1.5})
aip = analytic.AtmosphericAnalyticInnerProducts(pars)
oip = analytic.OceanicAnalyticInnerProducts(pars)
aip.connect_to_ocean(oip)
natm = pars.nmod[0]
noc = pars.nmod[1]
for i in range(natm):
for j in range(natm):
_ip_string_format(tfunc, "a", [i, j], aip.a(i, j))
_ip_string_format(tfunc, "c", [i, j], aip.c(i, j))
for k in range(natm):
_ip_string_format(tfunc, "b", [i, j, k], aip.b(i, j, k))
_ip_string_format(tfunc, "g", [i, j, k], aip.g(i, j, k))
for j in range(noc):
_ip_string_format(tfunc, "d", [i, j], aip.d(i, j))
_ip_string_format(tfunc, "s", [i, j], aip.s(i, j))
for i in range(noc):
for j in range(noc):
_ip_string_format(tfunc, "M", [i, j], oip.M(i, j))
_ip_string_format(tfunc, "N", [i, j], oip.N(i, j))
for k in range(noc):
_ip_string_format(tfunc, "O", [i, j, k], oip.O(i, j, k))
_ip_string_format(tfunc, "C", [i, j, k], oip.C(i, j, k))
for j in range(natm):
_ip_string_format(tfunc, "K", [i, j], oip.K(i, j))
_ip_string_format(tfunc, "W", [i, j], oip.W(i, j))
def outputs(self, output_func=None):
"""This function print the coefficients computed in the aotensor module"""
if output_func is None:
self.values.clear()
tfunc = self.save_ip
else:
tfunc = output_func
pars = QgParams({'rr': 287.e0, 'sb': 5.6e-8})
pars.set_atmospheric_channel_fourier_modes(6, 6)
pars.set_oceanic_basin_fourier_modes(6, 6)
# Setting MAOOAM default parameters
pars.set_params({'kd': 0.04, 'kdp': 0.04, 'n': 1.5})
aip = analytic.AtmosphericAnalyticInnerProducts(pars)
oip = analytic.OceanicAnalyticInnerProducts(pars)
aip.connect_to_ocean(oip)
aotensor = QgsTensor(pars, aip, oip)
for coo, val in zip(aotensor.tensor.coords.T, aotensor.tensor.data):
_ip_string_format(tfunc, 'aotensor', coo, val)
# Time parameters
dt = 0.1
# Saving the model state n steps
write_steps = 100
# transient time to attractor
transient_time = 3.e6
# integration time on the attractor
integration_time = 5.e5
# file where to write the output
filename = "evol_fields.dat"
T = time.process_time()
# Setting some model parameters
# Model parameters instantiation with default specs
model_parameters = QgParams()
# Mode truncation at the wavenumber 2 in both x and y spatial coordinate
model_parameters.set_atmospheric_channel_fourier_modes(2, 2)
# Mode truncation at the wavenumber 2 in the x and at the
# wavenumber 4 in the y spatial coordinates for the ocean
model_parameters.set_oceanic_basin_fourier_modes(2, 4)
# Setting MAOOAM parameters according to the publication linked above
model_parameters.set_params({
'kd': 0.0290,
'kdp': 0.0290,
'n': 1.5,
'r': 1.e-7,
'h': 136.5,
'd': 1.1e-7
})
Keyword arguments to pass to the :mod:`pickle` module method.
"""
f = open(filename, 'rb')
tmp_dict = pickle.load(f, **kwargs)
f.close()
self.__dict__.clear()
self.__dict__.update(tmp_dict)
def _kronecker_delta(i, j):
if i == j:
return 1
else:
return 0
if __name__ == '__main__':
from qgs.params.params import QgParams
from qgs.inner_products.analytic import AtmosphericAnalyticInnerProducts, OceanicAnalyticInnerProducts
params = QgParams()
params.set_atmospheric_channel_fourier_modes(2, 2)
params.set_oceanic_basin_fourier_modes(2, 4)
aip = AtmosphericAnalyticInnerProducts(params)
oip = OceanicAnalyticInnerProducts(params)
aip.connect_to_ocean(oip)
agotensor = QgsTensor(params, aip, oip)
--------
Not defined and not used."""
return 0
def W(self, i, j):
"""Function to compute the short-wave radiative forcing of the ocean: :math:`W_{i,j} = (\phi_i, F_j)`."""
if self.connected_to_atmosphere:
if not self.stored:
res = self.iip.symbolic_inner_product(self._phi(i), self._F(j))
return float(
res.subs(self.subs).subs(
self.atmospheric_basis.substitutions).subs(
self.ground_basis.substitutions))
else:
return self._W[i, j]
else:
return 0
def _apply(ls):
return ls[0], ls[1](*ls[2])
if __name__ == '__main__':
from qgs.params.params import QgParams
pars = QgParams()
pars.set_atmospheric_channel_fourier_modes(2, 2, mode='symbolic')
pars.set_oceanic_basin_fourier_modes(2, 4, mode='symbolic')
aip = AtmosphericSymbolicInnerProducts(pars)
oip = OceanicSymbolicInnerProducts(pars)
else:
return 1.
def _S1(Pj, Pk, Mj, Hk):
return -(Pk * Mj + Pj * Hk) / 2.
def _S2(Pj, Pk, Mj, Hk):
return (Pk * Mj - Pj * Hk) / 2.
def _S3(Pj, Pk, Hj, Hk):
return (Pk * Hj + Pj * Hk) / 2.
def _S4(Pj, Pk, Hj, Hk):
return (Pk * Hj - Pj * Hk) / 2.
if __name__ == '__main__':
from qgs.params.params import QgParams
pars = QgParams()
pars._set_atmospheric_analytic_fourier_modes(2, 2)
pars._set_oceanic_analytic_fourier_modes(2, 4)
aip = AtmosphericAnalyticInnerProducts(pars)
oip = OceanicAnalyticInnerProducts(pars)
aip.connect_to_ocean(oip)
# Time parameters
dt = 0.1
# Saving the model state n steps
write_steps = 5
# transient time to attractor
transient_time = 1.e5
# integration time on the attractor
integration_time = 1.e4
# file where to write the output
filename = "evol_fields.dat"
T = time.process_time()
# Setting some model parameters
# Model parameters instantiation with some non-default specs
model_parameters = QgParams({'phi0_npi': np.deg2rad(50.)/np.pi, 'hd': 0.1})
# Mode truncation at the wavenumber 2 in both x and y spatial coordinate
model_parameters.set_atmospheric_channel_fourier_modes(2, 2)
# Changing (increasing) the orography depth and the meridional temperature gradient
model_parameters.ground_params.set_orography(0.2, 1)
model_parameters.atemperature_params.set_thetas(0.2, 0)
if print_parameters:
print("")
# Printing the model's parameters
model_parameters.print_params()
# Creating the tendencies functions
f, Df = create_tendencies(model_parameters)