Hello, I am very new to FiPy and trying to solve a 2D diffusion problem with a random source using a method that requires sampling from a conditional distribution (derived from the associated Fokker-Plank equation) at each time step then evolving the deterministic part of the PDE.
The conditional distribution (it's a combination of Beta/Gamma but doesn't matter for my question) would require field-dependent parameters (for the mean/variance/etc.). For example, the following does NOT work (1D example): mesh=Grid1D(nx=50,dx=1.) phi=CellVariable(name="my field at time 0",mesh=mesh) x=mesh.getCellCenters()[0] from scipy.special import erf phi.setValue(1-erf(x)) noise=ExponentialNoiseVariable(mesh=mesh,mean=phi) #mean depends on phi Do I just have to create a "for" loop across the mesh, extract phi at the cell center, generate the corresponding noise at that cell center (using the phi at that cell center as the parameter for whatever distribution) and somehow re-assemble the noise field? Thanks in advance for any suggestions. -akhil
