mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-28 03:35:09 +08:00
Dave Marchant
37 lines
902 B
Python
37 lines
902 B
Python
import numpy as np
|
|
from numpy.random import randn
|
|
from utils import ndgrid
|
|
from getDiffOps import getCurlMatrix, getNodalGradient
|
|
from getFaceInnerProduct import getFaceInnerProduct
|
|
from getEdgeInnerProduct import getEdgeInnerProduct
|
|
from scipy.sparse.linalg import dsolve
|
|
from pylab import norm
|
|
|
|
n = np.array([14, 14, 15])
|
|
|
|
X, Y, Z = ndgrid(*[np.linspace(0, 1, x) for x in n])
|
|
sigma = 1e-2*np.ones(n-1)
|
|
sigma[:, :, (n[2]-1)/2:] = 1e-6
|
|
mu = 4*np.pi*1e-7*np.ones(n-1)
|
|
w = 10
|
|
|
|
CURL = getCurlMatrix(X, Y, Z)
|
|
GRAD = getNodalGradient(X, Y, Z)
|
|
Mf = getFaceInnerProduct(X, Y, Z, 1/mu)
|
|
Me = getEdgeInnerProduct(X, Y, Z, sigma)
|
|
|
|
A = CURL.T * Mf * CURL + 1j * w * Me
|
|
|
|
ne = np.shape(A)
|
|
b = np.matrix(randn(ne[0])).T
|
|
# clean b
|
|
DIVb = GRAD.T*b
|
|
p = dsolve.spsolve(GRAD.T*GRAD, DIVb, use_umfpack=True).T
|
|
b = b - GRAD*p
|
|
|
|
#x = spsolve(A, b)
|
|
x = dsolve.spsolve(A, b, use_umfpack=True).T
|
|
|
|
t = norm(A*x-b)/norm(b)
|
|
print t
|