mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-27 23:08:55 +08:00
Dave Marchant
37 lines
902 B
Python
37 lines
902 B
Python
import numpy as np
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from numpy.random import randn
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from utils import ndgrid
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from getDiffOps import getCurlMatrix, getNodalGradient
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from getFaceInnerProduct import getFaceInnerProduct
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from getEdgeInnerProduct import getEdgeInnerProduct
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from scipy.sparse.linalg import dsolve
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from pylab import norm
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n = np.array([14, 14, 15])
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X, Y, Z = ndgrid(*[np.linspace(0, 1, x) for x in n])
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sigma = 1e-2*np.ones(n-1)
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sigma[:, :, (n[2]-1)/2:] = 1e-6
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mu = 4*np.pi*1e-7*np.ones(n-1)
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w = 10
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CURL = getCurlMatrix(X, Y, Z)
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GRAD = getNodalGradient(X, Y, Z)
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Mf = getFaceInnerProduct(X, Y, Z, 1/mu)
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Me = getEdgeInnerProduct(X, Y, Z, sigma)
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A = CURL.T * Mf * CURL + 1j * w * Me
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ne = np.shape(A)
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b = np.matrix(randn(ne[0])).T
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# clean b
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DIVb = GRAD.T*b
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p = dsolve.spsolve(GRAD.T*GRAD, DIVb, use_umfpack=True).T
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b = b - GRAD*p
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#x = spsolve(A, b)
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x = dsolve.spsolve(A, b, use_umfpack=True).T
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t = norm(A*x-b)/norm(b)
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print t
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