fipy: 2D Laplace equation: boundary conditions not taken

user_15294090 0
Viewed 68
from fipy import CellVariable, Grid2D, DiffusionTerm
nx = 20         # grid size on coordinate axes
dx = 1          # grid spacing
ny = nx; dy = dx; L = dx*nx
mesh = Grid2D(dx=dx, dy=dy, nx=nx, ny=ny)
phi = CellVariable(name = "phi", mesh = mesh, value = 0.5)
eq = (0. == DiffusionTerm( coeff=1., var=phi))
valueTopLeft = 0.; valueBottomRight = 1.
phi.constrain(valueTopLeft, where = mesh.facesLeft)
phi.constrain(valueBottomRight, where = mesh.facesRight)
eq.solve(var=phi)
print (phi.value[:])

What's wrong with this code? Code produces zero solution, which is not correct.

fipy
2 Answers

There is a bug in FiPy if you specify the grid spacing as an integer. Changing to dx = 1. results in

[0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575
 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175
 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775
 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375
 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975
 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575
 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175
 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775
 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375
 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975
 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575
 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175
 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775
 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375
 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975
 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575
 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175
 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775
 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375
 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975
 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575
 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175
 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775
 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375
 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975
 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575
 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175
 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775
 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375
 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975
 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575
 0.625 0.675 0.725 0.775 0.825 0.875 0.925 0.975 0.025 0.075 0.125 0.175
 0.225 0.275 0.325 0.375 0.425 0.475 0.525 0.575 0.625 0.675 0.725 0.775
 0.825 0.875 0.925 0.975]
user_20195420

Thanks a lot. I should have found the problem myself. Now I am ready for more fancy things!

user_152940900
Related