mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-27 23:23:37 +08:00
rowanc1
86 lines
2.8 KiB
Python
86 lines
2.8 KiB
Python
# import numpy as np
|
|
# import unittest
|
|
# from SimPEG.mesh import TensorMesh
|
|
# from SimPEG.Utils import ModelBuilder, sdiag
|
|
# from SimPEG.forward import Problem
|
|
# from SimPEG.examples.DC import *
|
|
# from TestUtils import checkDerivative
|
|
# from scipy.sparse.linalg import dsolve
|
|
# from SimPEG import inverse
|
|
|
|
|
|
# class DCProblemTests(unittest.TestCase):
|
|
|
|
# def setUp(self):
|
|
# # Create the mesh
|
|
# h1 = np.ones(20)
|
|
# h2 = np.ones(20)
|
|
# mesh = TensorMesh([h1,h2])
|
|
|
|
# # Create some parameters for the model
|
|
# sig1 = 1
|
|
# sig2 = 0.01
|
|
|
|
# # Create a synthetic model from a block in a half-space
|
|
# p0 = [2, 2]
|
|
# p1 = [5, 5]
|
|
# condVals = [sig1, sig2]
|
|
# mSynth = ModelBuilder.defineBlockConductivity(p0,p1,mesh.gridCC,condVals)
|
|
|
|
# # Set up the projection
|
|
# nelec = 10
|
|
# spacelec = 2
|
|
# surfloc = 0.5
|
|
# elecini = 0.5
|
|
# elecend = 0.5+spacelec*(nelec-1)
|
|
# elecLocR = np.linspace(elecini, elecend, nelec)
|
|
# rxmidLoc = (elecLocR[0:nelec-1]+elecLocR[1:nelec])*0.5
|
|
# q, Q, rxmidloc = genTxRxmat(nelec, spacelec, surfloc, elecini, mesh)
|
|
# P = Q.T
|
|
|
|
# # Create some data
|
|
|
|
# problem = DCProblem(mesh)
|
|
# problem.P = P
|
|
# problem.RHS = q
|
|
# data = problem.createSyntheticData(mSynth, std=0.05)
|
|
|
|
# # Now set up the problem to do some minimization
|
|
# opt = inverse.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
|
|
# reg = inverse.Regularization(mesh)
|
|
# inv = inverse.Inversion(problem, reg, opt, data, beta0=1e4)
|
|
|
|
# self.inv = inv
|
|
# self.reg = reg
|
|
# self.p = problem
|
|
# self.mesh = mesh
|
|
# self.m0 = mSynth
|
|
# self.data = data
|
|
|
|
# def test_misfit(self):
|
|
# derChk = lambda m: [self.p.dpred(m), lambda mx: self.p.J(self.m0, mx)]
|
|
# passed = checkDerivative(derChk, self.m0, plotIt=False)
|
|
# self.assertTrue(passed)
|
|
|
|
# def test_adjoint(self):
|
|
# # Adjoint Test
|
|
# u = np.random.rand(self.mesh.nC*self.p.RHS.shape[1])
|
|
# v = np.random.rand(self.mesh.nC)
|
|
# w = np.random.rand(self.data.dobs.shape[0])
|
|
# wtJv = w.dot(self.p.J(self.m0, v, u=u))
|
|
# vtJtw = v.dot(self.p.Jt(self.m0, w, u=u))
|
|
# passed = (wtJv - vtJtw) < 1e-10
|
|
# self.assertTrue(passed)
|
|
|
|
# def test_dataObj(self):
|
|
# derChk = lambda m: [self.inv.dataObj(m), self.inv.dataObjDeriv(m)]
|
|
# checkDerivative(derChk, self.m0, plotIt=False)
|
|
|
|
# def test_modelObj(self):
|
|
# derChk = lambda m: [self.reg.modelObj(m), self.reg.modelObjDeriv(m)]
|
|
# checkDerivative(derChk, self.m0, plotIt=False)
|
|
|
|
|
|
# if __name__ == '__main__':
|
|
# unittest.main()
|