mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-27 21:53:41 +08:00
Rowan Cockett
69 lines
2.5 KiB
Python
69 lines
2.5 KiB
Python
from SimPEG import *
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import SimPEG.EM.Static.DC as DC
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def run(plotIt=True):
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cs = 25.
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hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
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hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
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hz = [(cs,7, -1.3),(cs,20)]
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mesh = Mesh.TensorMesh([hx, hy, hz], 'CCN')
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sighalf = 1e-2
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sigma = np.ones(mesh.nC)*sighalf
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xtemp = np.linspace(-150, 150, 21)
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ytemp = np.linspace(-150, 150, 21)
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xyz_rxP = Utils.ndgrid(xtemp-10., ytemp, np.r_[0.])
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xyz_rxN = Utils.ndgrid(xtemp+10., ytemp, np.r_[0.])
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xyz_rxM = Utils.ndgrid(xtemp, ytemp, np.r_[0.])
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# if plotIt:
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# fig, ax = plt.subplots(1,1, figsize = (5,5))
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# mesh.plotSlice(sigma, grid=True, ax = ax)
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# ax.plot(xyz_rxP[:,0],xyz_rxP[:,1], 'w.')
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# ax.plot(xyz_rxN[:,0],xyz_rxN[:,1], 'r.', ms = 3)
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rx = DC.Rx.Dipole(xyz_rxP, xyz_rxN)
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src = DC.Src.Dipole([rx], np.r_[-200, 0, -12.5], np.r_[+200, 0, -12.5])
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survey = DC.Survey([src])
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problem = DC.Problem3D_CC(mesh)
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problem.pair(survey)
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try:
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from pymatsolver import MumpsSolver
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problem.Solver = MumpsSolver
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except Exception, e:
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pass
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data = survey.dpred(sigma)
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def DChalf(srclocP, srclocN, rxloc, sigma, I=1.):
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rp = (srclocP.reshape([1,-1])).repeat(rxloc.shape[0], axis = 0)
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rn = (srclocN.reshape([1,-1])).repeat(rxloc.shape[0], axis = 0)
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rP = np.sqrt(((rxloc-rp)**2).sum(axis=1))
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rN = np.sqrt(((rxloc-rn)**2).sum(axis=1))
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return I/(sigma*2.*np.pi)*(1/rP-1/rN)
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data_anaP = DChalf(np.r_[-200, 0, 0.],np.r_[+200, 0, 0.], xyz_rxP, sighalf)
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data_anaN = DChalf(np.r_[-200, 0, 0.],np.r_[+200, 0, 0.], xyz_rxN, sighalf)
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data_ana = data_anaP-data_anaN
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Data_ana = data_ana.reshape((21, 21), order = 'F')
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Data = data.reshape((21, 21), order = 'F')
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X = xyz_rxM[:,0].reshape((21, 21), order = 'F')
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Y = xyz_rxM[:,1].reshape((21, 21), order = 'F')
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if plotIt:
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots(1,2, figsize = (12, 5))
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vmin = np.r_[data, data_ana].min()
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vmax = np.r_[data, data_ana].max()
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dat1 = ax[1].contourf(X, Y, Data, 60, vmin = vmin, vmax = vmax)
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dat0 = ax[0].contourf(X, Y, Data_ana, 60, vmin = vmin, vmax = vmax)
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cb0 = plt.colorbar(dat1, orientation = 'horizontal', ax = ax[0])
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cb1 = plt.colorbar(dat1, orientation = 'horizontal', ax = ax[1])
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ax[1].set_title('Analytic')
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ax[0].set_title('Computed')
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plt.show()
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return np.linalg.norm(data-data_ana)/np.linalg.norm(data_ana)
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if __name__ == '__main__':
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print run()
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