Verification plot

docs/api_DC.rst

@@ -129,6 +129,7 @@ where
 
 Here \\(\\bm\\) indicates model parameters in discretized space.
 
+.. plot :: ../simpegDC/Examples/Verification.py
 
 .. automodule:: simpegDC.DC
     :show-inheritance:

simpegDC/Examples/Verification.py

@@ -0,0 +1,51 @@
+from SimPEG import *
+import simpegDC as DC
+import matplotlib.pyplot as plt
+cs = 25.
+hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
+hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
+hz = [(cs,7, -1.3),(cs,20)]
+mesh = Mesh.TensorMesh([hx, hy, hz], 'CCN')
+sighalf = 1e-2
+sigma = np.ones(mesh.nC)*sighalf
+xtemp = np.linspace(-150, 150, 21)
+ytemp = np.linspace(-150, 150, 21)
+xyz_rxP = Utils.ndgrid(xtemp-10., ytemp, np.r_[0.])
+xyz_rxN = Utils.ndgrid(xtemp+10., ytemp, np.r_[0.])
+xyz_rxM = Utils.ndgrid(xtemp, ytemp, np.r_[0.])
+fig, ax = plt.subplots(1,1, figsize = (5,5))
+mesh.plotSlice(sigma, grid=True, ax = ax)
+ax.plot(xyz_rxP[:,0],xyz_rxP[:,1], 'w.')
+ax.plot(xyz_rxN[:,0],xyz_rxN[:,1], 'r.', ms = 3)
+rx = DC.DipoleRx(xyz_rxP, xyz_rxN)
+tx = DC.DipoleTx([-200, 0, -12.5],[+200, 0, -12.5], [rx])
+survey = DC.SurveyDC([tx])
+problem = DC.ProblemDC(mesh)
+problem.pair(survey)
+data = survey.dpred(sigma)
+
+def DChalf(txlocP, txlocN, rxloc, sigma, I=1.):
+    rp = (txlocP.reshape([1,-1])).repeat(rxloc.shape[0], axis = 0)
+    rn = (txlocN.reshape([1,-1])).repeat(rxloc.shape[0], axis = 0)
+    rP = np.sqrt(((rxloc-rp)**2).sum(axis=1))
+    rN = np.sqrt(((rxloc-rn)**2).sum(axis=1))
+    return I/(sigma*2.*np.pi)*(1/rP-1/rN)
+
+data_analP = DChalf(np.r_[-200, 0, 0.],np.r_[+200, 0, 0.], xyz_rxP, sighalf)
+data_analN = DChalf(np.r_[-200, 0, 0.],np.r_[+200, 0, 0.], xyz_rxN, sighalf)
+data_anal = data_analP-data_analN
+Data_anal = data_anal.reshape((21, 21), order = 'F')
+Data = data.reshape((21, 21), order = 'F')
+X = xyz_rxM[:,0].reshape((21, 21), order = 'F')
+Y = xyz_rxM[:,1].reshape((21, 21), order = 'F')
+
+fig, ax = plt.subplots(1,2, figsize = (12, 5))
+vmin = np.r_[data, data_anal].min()
+vmax = np.r_[data, data_anal].max()
+dat1 = ax[1].contourf(X, Y, Data, 60, vmin = vmin, vmax = vmax)
+dat0 = ax[0].contourf(X, Y, Data_anal, 60, vmin = vmin, vmax = vmax)
+cb0 = plt.colorbar(dat1, orientation = 'horizontal', ax = ax[0])
+cb1 = plt.colorbar(dat1, orientation = 'horizontal', ax = ax[1])
+ax[1].set_title('Analytic')
+ax[0].set_title('Computed')
+plt.show()