Clean up imports in DC, move data to forward folder. clean up init statements.

SimPEG/examples/DC.py

@@ -1,13 +1,6 @@
-from SimPEG.mesh import TensorMesh
-from SimPEG.forward import Problem, ModelTransforms
-from SimPEG.tests import checkDerivative
-from SimPEG.utils import ModelBuilder, sdiag, mkvc
-from SimPEG import Solver
-import numpy as np
-import scipy.sparse as sp
+from SimPEG import *
 
-
-class DCProblem(ModelTransforms.LogModel, Problem):
+class DCProblem(forward.ModelTransforms.LogModel, forward.Problem):
     """
         **DCProblem**
 
@@ -15,7 +8,7 @@ class DCProblem(ModelTransforms.LogModel, Problem):
 
     """
     def __init__(self, mesh):
-        Problem.__init__(self, mesh)
+        forward.Problem.__init__(self, mesh)
         self.mesh.setCellGradBC('neumann')
 
     def reshapeFields(self, u):
@@ -55,13 +48,13 @@ class DCProblem(ModelTransforms.LogModel, Problem):
 
         u = self.reshapeFields(u)
 
-        return mkvc(self.P*u)
+        return utils.mkvc(self.P*u)
 
     def field(self, m):
         A = self.createMatrix(m)
         solve = Solver(A)
         phi = solve.solve(self.RHS)
-        return mkvc(phi)
+        return utils.mkvc(phi)
 
     def J(self, m, v, u=None):
         """
@@ -101,11 +94,11 @@ class DCProblem(ModelTransforms.LogModel, Problem):
 
         dCdm = np.empty_like(u)
         for i, ui in enumerate(u.T):  # loop over each column
-            dCdm[:, i] = D * ( sdiag( G * ui ) * ( Av_dm * ( mT_dm * v ) ) )
+            dCdm[:, i] = D * ( utils.sdiag( G * ui ) * ( Av_dm * ( mT_dm * v ) ) )
 
         solve = Solver(dCdu)
         Jv = - P * solve.solve(dCdm)
-        return mkvc(Jv)
+        return utils.mkvc(Jv)
 
     def Jt(self, m, v, u=None):
         """Takes data, turns it into a model..ish"""
@@ -130,7 +123,7 @@ class DCProblem(ModelTransforms.LogModel, Problem):
 
         Jtv = 0
         for i, ui in enumerate(u.T):  # loop over each column
-            Jtv += sdiag( G * ui ) * ( D.T * w[:,i] )
+            Jtv += utils.sdiag( G * ui ) * ( D.T * w[:,i] )
 
         Jtv = - mT_dm.T * ( Av_dm.T * Jtv )
         return Jtv
@@ -165,16 +158,13 @@ def genTxRxmat(nelec, spacelec, surfloc, elecini, mesh):
     return q, Q, rxmidLoc
 
 
-
 if __name__ == '__main__':
-
-    from SimPEG import inverse
     import matplotlib.pyplot as plt
 
     # Create the mesh
     h1 = np.ones(20)
     h2 = np.ones(100)
-    mesh = TensorMesh([h1,h2])
+    M = mesh.TensorMesh([h1,h2])
 
     # Create some parameters for the model
     sig1 = np.log(1)
@@ -184,8 +174,8 @@ if __name__ == '__main__':
     p0 = [5, 10]
     p1 = [15, 50]
     condVals = [sig1, sig2]
-    mSynth = ModelBuilder.defineBlockConductivity(p0,p1,mesh.gridCC,condVals)
-    plt.colorbar(mesh.plotImage(mSynth))
+    mSynth = utils.ModelBuilder.defineBlockConductivity(p0,p1,M.gridCC,condVals)
+    plt.colorbar(M.plotImage(mSynth))
     plt.show()
 
     # Set up the projection
@@ -196,32 +186,32 @@ if __name__ == '__main__':
     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)
+    q, Q, rxmidloc = genTxRxmat(nelec, spacelec, surfloc, elecini, M)
     P = Q.T
 
     # Create some data
-    problem = DCProblem(mesh)
+    problem = DCProblem(M)
     problem.P = P
     problem.RHS = q
     data = problem.createSyntheticData(mSynth, std=0.05)
 
     u = problem.field(mSynth)
     u = problem.reshapeFields(u)
-    mesh.plotImage(u[:,10])
+    M.plotImage(u[:,10])
     # plt.show()
 
     # Now set up the problem to do some minimization
     # problem.dobs = dobs
     # problem.std = dobs*0 + 0.05
-    m0 = mesh.gridCC[:,0]*0+sig2
+    m0 = M.gridCC[:,0]*0+sig2
 
-    opt = inverse.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
-    reg = inverse.Regularization(mesh)
+    opt = inverse.InexactGaussNewton(maxIterLS=20, maxIter=3, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
+    reg = inverse.Regularization(M)
     inv = inverse.Inversion(problem, reg, opt, data, beta0=1e4)
 
     # Check Derivative
     derChk = lambda m: [inv.dataObj(m), inv.dataObjDeriv(m)]
-    checkDerivative(derChk, mSynth)
+    tests.checkDerivative(derChk, mSynth)
 
 
 
@@ -230,7 +220,7 @@ if __name__ == '__main__':
 
     m = inv.run(m0)
 
-    plt.colorbar(mesh.plotImage(m))
+    plt.colorbar(M.plotImage(m))
     print m
     plt.show()