mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-28 05:43:26 +08:00
Rowan Cockett
44 lines
1.0 KiB
Python
44 lines
1.0 KiB
Python
# from scipy.sparse import linalg
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from numpy import *
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#from numpy.linalg import *
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from numpy.random import randn
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from utils import *
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from getDiffOps import getCurlMatrix, getNodalGradient
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from sputils import *
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from meshUtils import *
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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 spsolve
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from scipy.sparse.linalg import *
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from pylab import *
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n1 = 14
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n2 = 14
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n3 = 15
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X, Y, Z = ndgrid(linspace(0, 1, n1), linspace(0, 1, n2), linspace(0, 1, n3))
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sigma = 1e-2*ones([n1-1, n2-1, n3-1])
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sigma[:, :, (n3-1)/2:] = 1e-6
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mu = 4*pi*1e-7*ones([n1-1, n2-1, n3-1])
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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 = shape(A)
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b = 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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