Note
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2.4.7 SDE with Stratonovich interpretation
This example solves a stochastic diffusion equation with Stratonovich interpretation

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from pde import PDE, ScalarField, UnitGrid
class AllenCahnNoisePDE(PDE):
"""Allen–Cahn PDE with custom noise implementation."""
use_noise_variance = True
def make_noise_variance(self, state, *, backend, ret_diff=False):
"""Make function that calculates noise variance."""
noise = float(self.noise)
if ret_diff:
def noise_variance(state_data, t):
return noise * state_data**2, 2 * noise * state_data
else:
def noise_variance(state_data, t):
return noise * state_data**2
return noise_variance
eq = AllenCahnNoisePDE(
rhs={"c": "laplace(c) + c - c**3"}, noise=1.0, noise_interpretation="stratonovich"
)
state = ScalarField.random_uniform(UnitGrid([64, 64]), -1, 1)
result = eq.solve(state, t_range=10, dt=1e-3, solver="milstein")
result.plot()
Total running time of the script: (0 minutes 5.358 seconds)