2.4.2 Heterogeneous boundary conditions

This example implements a diffusion equation with a boundary condition specified by a function, which can in principle depend on time.

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import numpy as np

from pde import CartesianGrid, DiffusionPDE, ScalarField

# define grid and an initial state
grid = CartesianGrid([[-5, 5], [-5, 5]], 32)
field = ScalarField(grid)


# define the boundary conditions, which here are calculated from a function
def bc_value(adjacent_value, dx, x, y, t):
    """Return boundary value."""
    return np.sign(x)


# define and solve a simple diffusion equation
eq = DiffusionPDE(bc={"*": {"derivative": 0}, "y+": {"value_expression": bc_value}})
res = eq.solve(field, t_range=10, dt=0.01, backend="numpy")
res.plot()