misc fixes

- 2to3 on setup.py to allow python 3 import
- removed uneeded circular import in Maps.py
- added missing old_div o mathutils

.bumpversion.cfg

@@ -1,4 +1,4 @@
 [bumpversion]
-current_version = 0.1.10
+current_version = 0.1.12
 files = setup.py SimPEG/__init__.py docs/conf.py
 

.gitignore

@@ -39,3 +39,5 @@ nosetests.xml
 *.sublime-workspace
 docs/_build/
 Makefile
+docs/warnings.txt
+.DS_Store

.travis.yml

@@ -1,6 +1,7 @@
 language: python
 python:
   - 2.7
+  - 3.4
 
 sudo: false
 
@@ -24,18 +25,25 @@ env:
     - TEST_DIR=tests/examples
     - TEST_DIR=tests/em/fdem/inverse/adjoint
     - TEST_DIR=tests/em/fdem/forward
+    - TEST_DIR=tests/docs;
+      GAE_PYTHONPATH=${HOME}/.cache/google_appengine;
+      PATH=$PATH:${HOME}/google-cloud-sdk/bin;
+      PYTHONPATH=${PYTHONPATH}:${GAE_PYTHONPATH};
+      CLOUDSDK_CORE_DISABLE_PROMPTS=1
 
 # Setup anaconda
 before_install:
-  - if [ ${TRAVIS_PYTHON_VERSION:0:1} == "2" ]; then wget http://repo.continuum.io/miniconda/Miniconda-3.8.3-Linux-x86_64.sh -O miniconda.sh; else wget http://repo.continuum.io/miniconda/Miniconda3-3.8.3-Linux-x86_64.sh -O miniconda.sh; fi
+# Install packages
+  - if [ ${TRAVIS_PYTHON_VERSION:0:1} == "2" ]; then wget http://repo.continuum.io/miniconda/Miniconda-3.8.3-Linux-x86_64.sh
+    -O miniconda.sh; else wget http://repo.continuum.io/miniconda/Miniconda3-3.8.3-Linux-x86_64.sh
+    -O miniconda.sh; fi
   - chmod +x miniconda.sh
   - ./miniconda.sh -b
-  - export PATH=/home/travis/anaconda/bin:/home/travis/miniconda/bin:$PATH
+  - export PATH=/home/travis/anaconda/bin:/home/travis/anaconda3/bin:/home/travis/miniconda/bin:/home/travis/miniconda3/bin:$PATH
   - conda update --yes conda
 
-# Install packages
 install:
-  - conda install --yes pip python=$TRAVIS_PYTHON_VERSION numpy scipy matplotlib cython ipython nose vtk
+  - conda install --yes pip python=$TRAVIS_PYTHON_VERSION numpy scipy matplotlib cython ipython nose vtk sphinx
   - pip install nose-cov python-coveralls
 
   - git clone https://github.com/rowanc1/pymatsolver.git
@@ -46,11 +54,26 @@ install:
 
 # Run test
 script:
+  # test docs
   - nosetests $TEST_DIR --with-cov --cov SimPEG --cov-config .coveragerc -v -s
 
 # Calculate coverage
 after_success:
-  - coveralls --config_file .coveragerc
+  - bash <(curl -s https://codecov.io/bash)
+  - if [ "$TRAVIS_BRANCH" = "master" -a "$TRAVIS_PULL_REQUEST" = "false" ]; then
+      if [ ${TEST_DIR} == "tests/docs" ]; then
+        python scripts/fetch_gae_sdk.py $(dirname "${GAE_PYTHONPATH}");
+        openssl aes-256-cbc -K $encrypted_93066031461c_key -iv $encrypted_93066031461c_iv
+          -in docs/credentials.tar.gz.enc -out credentials.tar.gz -d ;
+        if [ ! -d ${HOME}/google-cloud-sdk ]; then curl https://sdk.cloud.google.com | bash; fi ;
+        tar -xzf credentials.tar.gz ;
+        gcloud auth activate-service-account --key-file client-secret.json ;
+        gcloud config set project simpegdocs;
+        gcloud -q components update gae-python;
+        gcloud -q preview app deploy ./docs/app.yaml --version ${TRAVIS_COMMIT} --promote;
+      fi;
+    fi
+
 
 notifications:
   email:

README.rst

@@ -1,4 +1,4 @@
-.. image:: https://raw.github.com/simpeg/simpeg/master/docs/simpeg-logo.png
+.. image:: https://raw.github.com/simpeg/simpeg/master/docs/images/simpeg-logo.png
     :alt: SimPEG Logo
 
 ======
@@ -25,6 +25,14 @@ SimPEG
     :target: https://coveralls.io/r/simpeg/simpeg?branch=master
     :alt: Coverage status
 
+.. image:: http://img.shields.io/badge/GITTER-JOIN_CHAT-brightgreen.svg?style=flat-square
+    :alt: gitter chat room at https://gitter.im/simpeg/simpeg
+    :target: https://gitter.im/simpeg/simpeg
+
+.. image:: https://codecov.io/gh/simpeg/simpeg/branch/master/graph/badge.svg
+  :target: https://codecov.io/gh/simpeg/simpeg
+
+
 Simulation and Parameter Estimation in Geophysics  -  A python package for simulation and gradient based parameter estimation in the context of geophysical applications.
 
 The vision is to create a package for finite volume simulation with applications to geophysical imaging and subsurface flow. To enable the understanding of the many different components, this package has the following features:

SimPEG/DCIP/BaseDC.py

@@ -1,3 +1,11 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from builtins import super
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
 from SimPEG import *
 
 class FieldsDC_CC(Problem.Fields):
@@ -61,7 +69,7 @@ class SrcDipole(Survey.BaseSrc):
         pts = [self.loc[0], self.loc[1]]
         inds = Utils.closestPoints(prob.mesh, pts)
         q = np.zeros(prob.mesh.nC)
-        q[inds] = - self.current * ( np.r_[1., -1.] / prob.mesh.vol[inds] )
+        q[inds] = - self.current * (np.r_[1., -1.] / prob.mesh.vol[inds])
         # self._rhsDict[mesh] = q
         # return self._rhsDict[mesh]
         return q
@@ -162,8 +170,8 @@ class ProblemDC_CC(Problem.BaseProblem):
         """
             Makes the matrix A(m) for the DC resistivity problem.
 
-            :param numpy.array m: model
-            :rtype: scipy.csc_matrix
+            :param numpy.ndarray m: model
+            :rtype: scipy.sparse.csc_matrix
             :return: A(m)
 
             .. math::
@@ -200,11 +208,11 @@ class ProblemDC_CC(Problem.BaseProblem):
 
         return F
 
-    def Jvec(self, m, v, u=None):
+    def Jvec(self, m, v, f=None):
         """
             :param numpy.array m: model
             :param numpy.array v: vector to multiply
-            :param numpy.array u: fields
+            :param Fields f: fields
             :rtype: numpy.array
             :return: Jv
 
@@ -225,11 +233,10 @@ class ProblemDC_CC(Problem.BaseProblem):
         # Set current model; clear dependent property $\mathbf{A(m)}$
         self.curModel = m
         sigma = self.curModel.transform # $\sigma = \mathcal{M}(\m)$
-        if u is None:
+        if f is None:
             # Run forward simulation if $u$ not provided
-            u = self.fields(self.curModel)[self.survey.srcList, 'phi_sol']
-        else:
-            u = u[self.survey.srcList, 'phi_sol']
+            f = self.fields(self.curModel)
+        u = f[self.survey.srcList, 'phi_sol']
 
         D = self.mesh.faceDiv
         G = self.mesh.cellGrad
@@ -251,19 +258,18 @@ class ProblemDC_CC(Problem.BaseProblem):
         if self.Ainv is None:
             self.Ainv = self.Solver(dA_du, **self.solverOpts)
 
-        P        = self.survey.getP(self.mesh)
+        P     = self.survey.getP(self.mesh)
         Jv    = - P * mkvc( self.Ainv * dCdm_x_v )
         return Jv
 
-    def Jtvec(self, m, v, u=None):
+    def Jtvec(self, m, v, f=None):
 
         self.curModel = m
         sigma = self.curModel.transform # $\sigma = \mathcal{M}(\m)$
-        if u is None:
-            # Run forward simulation if $u$ not provided
-            u = self.fields(self.curModel)[self.survey.srcList, 'phi_sol']
-        else:
-            u = u[self.survey.srcList, 'phi_sol']
+        if f is None:
+            # Run forward simulation if $f$ not provided
+            f = self.fields(self.curModel)
+        u = f[self.survey.srcList, 'phi_sol']
 
         shp = u.shape
         P = self.survey.getP(self.mesh)

SimPEG/DCIP/BaseIP.py

@@ -1,5 +1,12 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
 from SimPEG import *
-from BaseDC import SurveyDC, FieldsDC_CC
+from .BaseDC import SurveyDC, FieldsDC_CC
 
 class SurveyIP(SurveyDC):
     """
@@ -14,12 +21,12 @@ class SurveyIP(SurveyDC):
         Survey.BaseSurvey.__init__(self, **kwargs)
         self._Ps = {}
 
-    def dpred(self, m, u=None):
+    def dpred(self, m, f=None):
         """
             Predicted data.
 
             .. math::
-                d_\\text{pred} = Pu(m)
+                d_\\text{pred} = Pf(m)
         """
 
         return self.prob.forward(m)
@@ -52,7 +59,7 @@ class ProblemIP(Problem.BaseProblem):
             # sigma = self.curModel.transform
             sigma = self.sigma
             Av = self.mesh.aveF2CC
-            self._Msig = Utils.sdiag(1/(self.mesh.dim * Av.T * (1/sigma)))
+            self._Msig = Utils.sdiag(1//(self.mesh.dim * Av.T * (1/sigma)))
         return self._Msig
 
     @property
@@ -71,7 +78,7 @@ class ProblemIP(Problem.BaseProblem):
             Makes the matrix A(m) for the DC resistivity problem.
 
             :param numpy.array m: model
-            :rtype: scipy.csc_matrix
+            :rtype: scipy.sparse.csc_matrix
             :return: A(m)
 
             .. math::
@@ -143,10 +150,10 @@ class ProblemIP(Problem.BaseProblem):
         J_x_v    = - P * mkvc( self.Ainv * dCdm_x_v )
         return -J_x_v
 
-    def Jvec(self, m, v, u=None):
+    def Jvec(self, m, v, f=None):
         return self.forward(v)
 
-    def Jtvec(self, m, v, u=None):
+    def Jtvec(self, m, v, f=None):
 
         self.curModel = m
         # sigma = self.curModel.transform # $\sigma = \mathcal{M}(\m)$

SimPEG/DCIP/DCIPUtils.py

@@ -1,12 +1,26 @@
-from SimPEG import np
-import BaseDC as DC
-import BaseDC as IP
+from __future__ import print_function
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+from builtins import open
+from builtins import int
+from future import standard_library
+standard_library.install_aliases()
+from builtins import map
+from builtins import range
+from SimPEG import np, Utils
+from . import BaseDC as DC
+from . import BaseDC as IP
+import warnings
 
 def getActiveindfromTopo(mesh, topo):
 # def genActiveindfromTopo(mesh, topo):
     """
         Get active indices from topography
     """
+    warnings.warn(
+            "`getActiveindfromTopo` is deprecated and will be removed in future versions. Use `SimPEG.Utils.surface2ind_topo` instead",
+            FutureWarning)
     from scipy.interpolate import NearestNDInterpolator
     if mesh.dim==3:
         nCxy = mesh.nCx*mesh.nCy
@@ -28,6 +42,9 @@ def gettopoCC(mesh, airind):
     """
         Get topography from active indices of mesh.
     """
+    warnings.warn(
+            "`gettopoCC` is deprecated and will be removed in future versions. Use `SimPEG.Utils.surface2ind_topo` instead",
+            FutureWarning)
     mesh2D = Mesh.TensorMesh([mesh.hx, mesh.hy], mesh.x0[:2])
     zc = mesh.gridCC[:,2]
     AIRIND = airind.reshape((mesh.vnC[0]*mesh.vnC[1],mesh.vnC[2]), order='F')
@@ -60,7 +77,7 @@ def readUBC_DC3Dobstopo(filename,mesh,topo,probType="CC"):
         if "!" in line.split(): continue
         elif line == '\n': continue
         elif line == ' \n': continue
-        temp =  map(float, line.split())
+        temp =  list(map(float, line.split()))
         # Read a line for the current electrode
         if len(temp) == 5: # SRC: Only X and Y are provided (assume no topography)
             #TODO consider topography and assign the closest cell center in the earth
@@ -118,34 +135,27 @@ def readUBC_DC3Dobstopo(filename,mesh,topo,probType="CC"):
 
 def readUBC_DC2DModel(fileName):
     """
-        Read UBC GIF 2DTensor model and generate 2D Tensor model in simpeg
+    Read UBC GIF 2DTensor model and generate 2D Tensor model in simpeg
 
-        Input:
-        :param fileName, path to the UBC GIF 2D model file
-
-        Output:
-        :param SimPEG TensorMesh 2D object
-        :return
-
-        Created on Thu Nov 12 13:14:10 2015
-
-        @author: dominiquef
+    :param string fileName: path to the UBC GIF 2D model file
+    :rtype: TensorMesh
+    :return: SimPEG TensorMesh 2D object
 
     """
     from SimPEG import np, mkvc
 
     # Open fileand skip header... assume that we know the mesh already
-    obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
+    obsfile = np.genfromtxt(fileName, delimiter=' \n', dtype=np.str, comments='!')
 
-    dim = np.array(obsfile[0].split(),dtype=float)
+    dim = np.array(obsfile[0].split(), dtype=float)
 
-    temp = np.array(obsfile[1].split(),dtype=float)
+    temp = np.array(obsfile[1].split(), dtype=float)
 
     if len(temp) > 1:
         model = np.zeros(dim)
 
         for ii in range(len(obsfile)-1):
-            mm = np.array(obsfile[ii+1].split(),dtype=float)
+            mm = np.array(obsfile[ii+1].split(), dtype=float)
             model[:,ii] = mm
 
         model = model[:,::-1]
@@ -153,10 +163,10 @@ def readUBC_DC2DModel(fileName):
     else:
 
         if len(obsfile[1:])==1:
-            mm = np.array(obsfile[1:].split(),dtype=float)
+            mm = np.array(obsfile[1:].split(), dtype=float)
 
         else:
-            mm = np.array(obsfile[1:],dtype=float)
+            mm = np.array(obsfile[1:], dtype=float)
 
         # Permute the second dimension to flip the order
         model = mm.reshape(dim[1],dim[0])
@@ -169,32 +179,25 @@ def readUBC_DC2DModel(fileName):
 
     return model
 
-def plot_pseudoSection(DCsurvey, axs, stype):
+
+def plot_pseudoSection(DCsurvey, axs, surveyType='dipole-dipole', unitType='volt', clim=None, cblabel=True, axlabel = True, colorbar = True, contour = None):
     """
-        Read list of 2D tx-rx location and plot a speudo-section of apparent
-        resistivity.
+    Read list of 2D tx-rx location and plot a speudo-section of apparent
+    resistivity.
 
-        Assumes flat topo for now...
+    Assumes flat topo for now...
 
-        Input:
-        :param d2D, z0
-        :switch stype -> Either 'pdp' (pole-dipole) | 'dpdp' (dipole-dipole)
-
-        Output:
-        :figure scatter plot overlayed on image
-
-        Edited Feb 17th, 2016
-
-        @author: dominiquef
+    :param SurveyDC DCsurvey:
+    :param string surveyType: Either 'pole-dipole'  | 'dipole-dipole'
+    :param string unitType: Either 'appResistivity' | 'appConductivity'  | 'volt'
+    :rtype: matplotlib.plt
+    :return: figure scatter plot overlayed on image
 
     """
     from SimPEG import np
     from scipy.interpolate import griddata
     import pylab as plt
 
-    # Set depth to 0 for now
-    z0 = 0.
-
     # Pre-allocate
     midx = []
     midz = []
@@ -221,69 +224,117 @@ def plot_pseudoSection(DCsurvey, axs, stype):
         Cmid = (Tx[0][0] + Tx[1][0])/2
         Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
 
-        # Compute pant leg of apparent rho
-        if stype == 'pdp':
-            leg =  data * 2*np.pi  * MA * ( MA + MN ) / MN
+        # Change output for unitType
+        if unitType == 'volt':
 
-            leg = np.log10(abs(1/leg))
+            rho = np.hstack([rho,data])
 
-        elif stype == 'dpdp':
-            leg = data * 2*np.pi / ( 1/MA - 1/MB - 1/NB + 1/NA )
+        else:
+
+            # Compute pant leg of apparent rho
+            if surveyType == 'pole-dipole':
+
+                leg =  data * 2*np.pi  * MA * ( MA + MN ) / MN
+
+            elif surveyType == 'dipole-dipole':
+
+                leg = data * 2*np.pi / (1/MA - 1/MB - 1/NB + 1/NA)
+
+            else:
+                print("""unitType must be 'pole-dipole' | 'dipole-dipole' """)
+                break
 
 
-        midx = np.hstack([midx, ( Cmid + Pmid )/2 ])
-        midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + z0 ])
-        rho = np.hstack([rho,leg])
+            if unitType == 'appConductivity':
 
+                leg = np.log10(abs(1./leg))
+                rho = np.hstack([rho,leg])
 
-    ax = axs
+            elif unitType == 'appResistivity':
+
+                leg = np.log10(abs(leg))
+                rho = np.hstack([rho,leg])
+
+            else:
+                print("""unitType must be 'appResistivity' | 'appConductivity' | 'volt' """)
+                break
+
+        midx = np.hstack([midx, (Cmid + Pmid)/2])
+        midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + (Tx[0][2] + Tx[1][2])/2])
 
     # Grid points
     grid_x, grid_z = np.mgrid[np.min(midx):np.max(midx), np.min(midz):np.max(midz)]
     grid_rho = griddata(np.c_[midx,midz], rho.T, (grid_x, grid_z), method='linear')
 
+    # Scale the color scheme
+    if clim == None:
+        vmin, vmax = rho.min(), rho.max()
+    else:
+        vmin, vmax = clim[0], clim[1]
 
-    plt.imshow(grid_rho.T, extent = (np.min(midx),np.max(midx),np.min(midz),np.max(midz)), origin='lower', alpha=0.8, vmin = np.min(rho), vmax = np.max(rho))
-    cbar = plt.colorbar(format = '%.2f',fraction=0.04,orientation="horizontal")
+    # Plot data
+    grid_rho = np.ma.masked_where(np.isnan(grid_rho), grid_rho)
 
-    cmin,cmax = cbar.get_clim()
-    ticks = np.linspace(cmin,cmax,3)
-    cbar.set_ticks(ticks)
 
-    # Plot apparent resistivity
-    plt.scatter(midx,midz,s=50,c=rho.T)
 
-    ax.set_xticklabels([])
+    ph = plt.pcolormesh(grid_x[:,0],grid_z[0,:],grid_rho.T, vmin = vmin, vmax = vmax)
+    plt.gca().tick_params(axis='both', which='major', labelsize=8)
+
+    if contour is not None:
+        plt.contour(grid_x,grid_z,grid_rho,levels = contour,colors = 'r', vmin = vmin, vmax = vmax)
+
+    # Add scatter points
+    axs.scatter(midx,midz,s=10,c=rho.T, vmin = vmin, vmax = vmax)
+
+    if colorbar:
+
+        if unitType == 'volt':
+            cbar = plt.colorbar(ph, ax = axs, format="%4.1f",fraction=0.04,orientation="horizontal")
+
+        else:
+            cbar = plt.colorbar(ph, ax = axs, format="$10^{%.1f}$",fraction=0.04,orientation="horizontal")
+
+            cmin,cmax = cbar.get_clim()
+            ticks = np.linspace(cmin,cmax,3)
+            cbar.set_ticks(ticks)
+            cbar.ax.tick_params(labelsize=10)
+
+            if unitType == 'appConductivity':
+                cbar.set_label("App.Cond",size=12)
+            elif unitType == 'appResistivity':
+                cbar.set_label("App.Res.",size=12)
+            elif unitType == 'volt':
+                cbar.set_label("Potential (V)",size=12)
+
+
+    if not axlabel:
+        axs.set_xticklabels([])
+        axs.set_yticklabels([])
 
-    ax.set_ylabel('Z')
-    ax.yaxis.tick_right()
-    ax.yaxis.set_label_position('right')
     plt.gca().set_aspect('equal', adjustable='box')
 
 
-    return ax
 
-def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
+    return ph
+
+def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
     """
-        Load in endpoints and survey specifications to generate Tx, Rx location
-        stations.
+    Load in endpoints and survey specifications to generate Tx, Rx location
+    stations.
 
-        Assumes flat topo for now...
+    Assumes flat topo for now...
 
-        Input:
-        :param endl -> input endpoints [x1, y1, z1, x2, y2, z2]
-        :object mesh -> SimPEG mesh object
-        :switch stype -> "dpdp" (dipole-dipole) | "pdp" (pole-dipole) | 'gradient'
-        : param a, n -> pole seperation, number of rx dipoles per tx
+    :param numpy.array endl: input endpoints [[x1, y1] , [x2, y2]]
+    :param Mesh mesh: SimPEG mesh object
+    :param string surveyType: 'dipole-dipole' | 'pole-dipole' | 'gradient'
+    :param float AM_sep: transmitter (A) - receiver (M) seperation
+    :param float b: receiver dipole seperation
+    :param float nrx: pole seperation, number of rx dipoles per tx
 
-        Output:
-        :param Tx, Rx -> List objects for each tx location
-            Lines: P1x, P1y, P1z, P2x, P2y, P2z
+    :rtype: DC.Survey, Src, Rx
+    :returns: DC survey, Source
 
-        Created on Wed December 9th, 2015
-
-        @author: dominiquef
-        !! Require clean up to deal with DCsurvey
+    !! Require clean up to deal with DCsurvey
     """
 
     from SimPEG import np
@@ -299,17 +350,17 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
     dl_x = ( endl[1,0] - endl[0,0] ) / dl_len
     dl_y = ( endl[1,1] - endl[0,1] ) / dl_len
 
-    nstn = np.floor( dl_len / a )
+    nstn = np.floor(dl_len / AM_sep)
 
     # Compute discrete pole location along line
-    stn_x = endl[0,0] + np.array(range(int(nstn)))*dl_x*a
-    stn_y = endl[0,1] + np.array(range(int(nstn)))*dl_y*a
+    stn_x = endl[0,0] + np.array(list(range(int(nstn))))*dl_x*AM_sep
+    stn_y = endl[0,1] + np.array(list(range(int(nstn))))*dl_y*AM_sep
 
     # Create line of P1 locations
     M = np.c_[stn_x, stn_y, np.ones(nstn).T*mesh.vectorNz[-1]]
 
     # Create line of P2 locations
-    N = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
+    N = np.c_[stn_x+AM_sep*dl_x, stn_y+AM_sep*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
 
     ## Build list of Tx-Rx locations depending on survey type
     # Dipole-dipole: Moving tx with [a] spacing -> [AB a MN1 a MN2 ... a MNn]
@@ -319,14 +370,14 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
     SrcList = []
 
 
-    if stype != 'gradient':
+    if surveyType != 'gradient':
 
         for ii in range(0, int(nstn)-1):
 
 
-            if stype == 'dpdp':
+            if surveyType == 'dipole-dipole':
                 tx = np.c_[M[ii,:],N[ii,:]]
-            elif stype == 'pdp':
+            elif surveyType == 'pole-dipole':
                 tx = np.c_[M[ii,:],M[ii,:]]
 
             # Rx.append(np.c_[M[ii+1:indx,:],N[ii+1:indx,:]])
@@ -335,43 +386,33 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
             AB = xy_2_r(tx[0,1],endl[1,0],tx[1,1],endl[1,1])
 
             # Number of receivers to fit
-            nstn = np.min([np.floor( (AB - b) / a ) , n])
+            nstn = np.min([(AB - MN_sep) // AM_sep, nrx])
 
             # Check if there is enough space, else break the loop
             if nstn <= 0:
                 continue
 
             # Compute discrete pole location along line
-            stn_x = N[ii,0] + dl_x*b + np.array(range(int(nstn)))*dl_x*a
-            stn_y = N[ii,1] + dl_y*b + np.array(range(int(nstn)))*dl_y*a
+            stn_x = N[ii,0] + dl_x*MN_sep + np.array(list(range(int(nstn))))*dl_x*AM_sep
+            stn_y = N[ii,1] + dl_y*MN_sep + np.array(list(range(int(nstn))))*dl_y*AM_sep
 
             # Create receiver poles
             # Create line of P1 locations
             P1 = np.c_[stn_x, stn_y, np.ones(nstn).T*mesh.vectorNz[-1]]
 
             # Create line of P2 locations
-            P2 = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
+            P2 = np.c_[stn_x+AM_sep*dl_x, stn_y+AM_sep*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
 
             Rx.append(np.c_[P1,P2])
             rxClass = DC.RxDipole(P1, P2)
             Tx.append(tx)
-            if stype == 'dpdp':
+            if surveyType == 'dipole-dipole':
                 srcClass = DC.SrcDipole([rxClass], M[ii,:],N[ii,:])
-            elif stype == 'pdp':
+            elif surveyType == 'pole-dipole':
                 srcClass = DC.SrcDipole([rxClass], M[ii,:],M[ii,:])
             SrcList.append(srcClass)
 
-#==============================================================================
-#     elif re.match(stype,'dpdp'):
-#
-#         for ii in range(0, int(nstn)-2):
-#
-#             indx = np.min([ii+n+1,nstn])
-#             Tx.append(np.c_[M[ii,:],N[ii,:]])
-#             Rx.append(np.c_[M[ii+2:indx,:],N[ii+2:indx,:]])
-#==============================================================================
-
-    elif stype == 'gradient':
+    elif surveyType == 'gradient':
 
         # Gradient survey only requires Tx at end of line and creates a square
         # grid of receivers at in the middle at a pre-set minimum distance
@@ -379,24 +420,24 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
         Tx.append(np.c_[M[0,:],N[-1,:]])
 
         # Get the edge limit of survey area
-        min_x = endl[0,0] + dl_x * b
-        min_y = endl[0,1] + dl_y * b
+        min_x = endl[0,0] + dl_x * MN_sep
+        min_y = endl[0,1] + dl_y * MN_sep
 
-        max_x = endl[1,0] - dl_x * b
-        max_y = endl[1,1] - dl_y * b
+        max_x = endl[1,0] - dl_x * MN_sep
+        max_y = endl[1,1] - dl_y * MN_sep
 
         box_l = np.sqrt( (min_x - max_x)**2 + (min_y - max_y)**2 )
         box_w = box_l/2.
 
-        nstn = np.floor( box_l / a )
+        nstn = box_l // AM_sep
 
         # Compute discrete pole location along line
-        stn_x = min_x + np.array(range(int(nstn)))*dl_x*a
-        stn_y = min_y + np.array(range(int(nstn)))*dl_y*a
+        stn_x = min_x + np.array(list(range(int(nstn))))*dl_x*AM_sep
+        stn_y = min_y + np.array(list(range(int(nstn))))*dl_y*AM_sep
 
         # Define number of cross lines
-        nlin = int(np.floor( box_w / a ))
-        lind = range(-nlin,nlin+1)
+        nlin = int(box_w // AM_sep)
+        lind = list(range(-nlin,nlin+1))
 
         ngrad = nstn * len(lind)
 
@@ -404,12 +445,12 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
         for ii in range( len(lind) ):
 
             # Move line in perpendicular direction by dipole spacing
-            lxx = stn_x - lind[ii]*a*dl_y
-            lyy = stn_y + lind[ii]*a*dl_x
+            lxx = stn_x - lind[ii]*AM_sep*dl_y
+            lyy = stn_y + lind[ii]*AM_sep*dl_x
 
 
             M = np.c_[ lxx, lyy , np.ones(nstn).T*mesh.vectorNz[-1]]
-            N = np.c_[ lxx+a*dl_x, lyy+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
+            N = np.c_[ lxx+AM_sep*dl_x, lyy+AM_sep*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
 
             rx[(ii*nstn):((ii+1)*nstn),:] = np.c_[M,N]
 
@@ -418,37 +459,37 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
         srcClass = DC.SrcDipole([rxClass], M[0,:], N[-1,:])
         SrcList.append(srcClass)
     else:
-        print """stype must be either 'pdp', 'dpdp' or 'gradient'. """
+        print("""surveyType must be either 'pole-dipole', 'dipole-dipole' or 'gradient'. """)
 
     survey = DC.SurveyDC(SrcList)
     return survey, Tx, Rx
 
-def writeUBC_DCobs(fileName, DCsurvey, dtype, stype):
+
+def writeUBC_DCobs(fileName, DCsurvey, dim, surveyType, iptype = 0):
     """
         Write UBC GIF DCIP 2D or 3D observation file
 
-        Input:
-        :string fileName -> including path where the file is written out
-        :DCsurvey -> DC survey class object
-        :string dtype ->  either '2D' | '3D'
-        :string  stype ->  either 'SURFACE' | 'GENERAL'
-
-        Output:
-        :param UBC2D-Data file
-        :return
-
-        Last edit: February 16th, 2016
-
-        @author: dominiquef
-
+        :param string fileName: including path where the file is written out
+        :param Survey DCsurvey: DC survey class object
+        :param string dim:  either '2D' | '3D'
+        :param string surveyType:  either 'SURFACE' | 'GENERAL'
+        :rtype: file
+        :return: UBC2D-Data file
     """
+
     from SimPEG import mkvc
 
-    assert (dtype=='2D') | (dtype=='3D'), "Data must be either '2D' | '3D'"
-    assert (stype=='SURFACE') | (stype=='GENERAL') | (stype=='SIMPLE'), "Data must be either 'SURFACE' | 'GENERAL' | 'SIMPLE'"
+    assert (dim=='2D') | (dim=='3D'), "Data must be either '2D' | '3D'"
+    assert (surveyType=='SURFACE') | (surveyType=='GENERAL') | (surveyType=='SIMPLE'), "Data must be either 'SURFACE' | 'GENERAL' | 'SIMPLE'"
 
     fid = open(fileName,'w')
-    fid.write('! ' + stype + ' FORMAT\n')
+    fid.write('! ' + surveyType + ' FORMAT\n')
+
+    if iptype!=0:
+        fid.write('IPTYPE=%i\n'%iptype)
+
+    else:
+        fid.write('! ' + stype + ' FORMAT\n')
 
     count = 0
 
@@ -463,10 +504,10 @@ def writeUBC_DCobs(fileName, DCsurvey, dtype, stype):
         M = rx[0]
         N = rx[1]
 
-        # Adapt source-receiver location for dtype and stype
-        if dtype=='2D':
+        # Adapt source-receiver location for dim and surveyType
+        if dim=='2D':
 
-            if stype == 'SIMPLE':
+            if surveyType == 'SIMPLE':
 
                 #fid.writelines("%e " % ii for ii in mkvc(tx[0,:]))
                 A = np.repeat(tx[0,0],M.shape[0],axis=0)
@@ -479,58 +520,60 @@ def writeUBC_DCobs(fileName, DCsurvey, dtype, stype):
 
             else:
 
-                if stype == 'SURFACE':
+                if surveyType == 'SURFACE':
 
-                    fid.writelines("%e " % ii for ii in mkvc(tx[0,:]))
+                    fid.writelines("%f " % ii for ii in mkvc(tx[0,:]))
                     M = M[:,0]
                     N = N[:,0]
 
-                if stype == 'GENERAL':
+                if surveyType == 'GENERAL':
+
+                    # Flip sign for z-elevation to depth
+                    tx[2::2,:] = -tx[2::2,:]
 
                     fid.writelines("%e " % ii for ii in mkvc(tx[::2,:]))
                     M = M[:,0::2]
                     N = N[:,0::2]
 
+                    # Flip sign for z-elevation to depth
+                    M[:,1::2] = -M[:,1::2]
+                    N[:,1::2] = -N[:,1::2]
+
                 fid.write('%i\n'% nD)
-                np.savetxt(fid, np.c_[ M, N , DCsurvey.dobs[count:count+nD], DCsurvey.std[count:count+nD] ], fmt='%e',delimiter=' ',newline='\n')
+                np.savetxt(fid, np.c_[ M, N , DCsurvey.dobs[count:count+nD], DCsurvey.std[count:count+nD] ], fmt='%f',delimiter=' ',newline='\n')
 
-        if dtype=='3D':
+        if dim=='3D':
 
-            if stype == 'SURFACE':
+            if surveyType == 'SURFACE':
 
                 fid.writelines("%e " % ii for ii in mkvc(tx[0:2,:]))
                 M = M[:,0:2]
                 N = N[:,0:2]
 
-            if stype == 'GENERAL':
+            if surveyType == 'GENERAL':
 
-                fid.writelines("%e " % ii for ii in mkvc(tx))
+                fid.writelines("%e " % ii for ii in mkvc(tx[0:3,:]))
 
             fid.write('%i\n'% nD)
             np.savetxt(fid, np.c_[ M, N , DCsurvey.dobs[count:count+nD], DCsurvey.std[count:count+nD] ], fmt='%e',delimiter=' ',newline='\n')
+            fid.write('\n')
 
         count += nD
 
     fid.close()
 
-def convertObs_DC3D_to_2D(DCsurvey,lineID):
+def convertObs_DC3D_to_2D(DCsurvey, lineID, flag='local'):
     """
-        Read DC survey and data and change
-        coordinate system to distance along line assuming
-        all data is acquired along line.
-        First transmitter pole is assumed to be at the origin
+        Read DC survey and projects the coordinate system
+        according to the flag = 'Xloc' | 'Yloc' | 'local' (default)
+        In the 'local' system, station coordinates are referenced
+        to distance from the first srcLoc[0].loc[0]
 
-        Assumes flat topo for now...
+        The Z value is preserved, but Y coordinates zeroed.
 
-        Input:
-        :param Tx, Rx
-
-        Output:
-        :figure Tx2d, Rx2d
-
-        Edited Feb 17th, 2016
-
-        @author: dominiquef
+        :param DC.Survey survey3D: 3D simpeg DC survey
+        :rtype: DC.Survey
+        :return: survey2D
 
     """
     from SimPEG import np
@@ -570,25 +613,39 @@ def convertObs_DC3D_to_2D(DCsurvey,lineID):
             Rx = DCsurvey.srcList[indx[ii]].rxList[0].locs
             nrx = Rx[0].shape[0]
 
-            # Find A electrode along line
-            vec, r = r_unit(x0,Tx[ii][0,0:2])
-            A = stn_id(vecTx,vec,r)
+            if flag == 'local':
+                # Find A electrode along line
+                vec, r = r_unit(x0,Tx[ii][0,0:2])
+                A = stn_id(vecTx,vec,r)
 
-            # Find B electrode along line
-            vec, r = r_unit(x0,Tx[ii][1,0:2])
-            B = stn_id(vecTx,vec,r)
+                # Find B electrode along line
+                vec, r = r_unit(x0,Tx[ii][1,0:2])
+                B = stn_id(vecTx,vec,r)
 
-            M = np.zeros(nrx)
-            N = np.zeros(nrx)
-            for kk in range(nrx):
+                M = np.zeros(nrx)
+                N = np.zeros(nrx)
+                for kk in range(nrx):
 
-                # Find all M electrodes along line
-                vec, r = r_unit(x0,Rx[0][kk,0:2])
-                M[kk] = stn_id(vecTx,vec,r)
+                    # Find all M electrodes along line
+                    vec, r = r_unit(x0,Rx[0][kk,0:2])
+                    M[kk] = stn_id(vecTx,vec,r)
 
-                # Find all N electrodes along line
-                vec, r = r_unit(x0,Rx[1][kk,0:2])
-                N[kk] = stn_id(vecTx,vec,r)
+                    # Find all N electrodes along line
+                    vec, r = r_unit(x0,Rx[1][kk,0:2])
+                    N[kk] = stn_id(vecTx,vec,r)
+            elif flag == 'Yloc':
+                """ Flip the XY axis locs"""
+                A = Tx[ii][0,1]
+                B = Tx[ii][1,1]
+                M = Rx[0][:,1]
+                N = Rx[1][:,1]
+
+            elif flag == 'Xloc':
+                """ Copy the rx-tx locs"""
+                A = Tx[ii][0,0]
+                B = Tx[ii][1,0]
+                M = Rx[0][:,0]
+                N = Rx[1][:,0]
 
             Rx = DC.RxDipole(np.c_[M,np.zeros(nrx),Rx[0][:,2]],np.c_[N,np.zeros(nrx),Rx[1][:,2]])
 
@@ -602,50 +659,53 @@ def convertObs_DC3D_to_2D(DCsurvey,lineID):
 
     return DCsurvey2D
 
-def readUBC_DC3Dobs(fileName):
+def readUBC_DC3Dobs(fileName, rtype = 'DC'):
     """
-        Read UBC GIF DCIP 3D observation file and generate arrays for tx-rx location
+        Read UBC GIF IP 3D observation file and generate survey
 
-        Input:
-        :param fileName, path to the UBC GIF 3D obs file
-
-        Output:
-        :param rx, tx, d, wd
-        :return
-
-        Created on Mon December 7th, 2015
-
-        @author: dominiquef
+        :param string fileName:, path to the UBC GIF 3D obs file
+        :rtype: Survey
+        :return: DCIPsurvey
 
     """
+    zflag = True # Flag for z value provided
 
     # Load file
-    obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
+    if rtype == 'IP':
+        obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='IPTYPE')
+
+    elif rtype == 'DC':
+        obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
+
+    else:
+        print("rtype must be 'DC'(default) | 'IP'")
 
     # Pre-allocate
     srcLists = []
     Rx = []
     d = []
     wd = []
-    zflag = True # Flag for z value provided
+
 
     # Countdown for number of obs/tx
     count = 0
     for ii in range(obsfile.shape[0]):
 
+        # Skip if blank line
         if not obsfile[ii]:
             continue
 
-        # First line is transmitter with number of receivers
+        # First line or end of a transmitter block, read transmitter info
         if count==0:
-
-            temp = (np.fromstring(obsfile[ii], dtype=float,sep=' ').T)
+            # Read the line
+            temp = (np.fromstring(obsfile[ii], dtype=float, sep=' ').T)
             count = int(temp[-1])
 
             # Check if z value is provided, if False -> nan
             if len(temp)==5:
-                tx = np.r_[temp[0:2],np.nan,temp[0:2],np.nan]
-                zflag = False
+                tx = np.r_[temp[0:2],np.nan,temp[2:4],np.nan]
+
+                zflag = False # Pass on the flag to the receiver loc
 
             else:
                 tx = temp[:-1]
@@ -653,8 +713,16 @@ def readUBC_DC3Dobs(fileName):
             rx = []
             continue
 
-        temp = np.fromstring(obsfile[ii], dtype=float,sep=' ')
+        temp = np.fromstring(obsfile[ii], dtype=float,sep=' ') # Get the string
 
+        # Filter out negative IP
+#        if temp[-2] < 0:
+#            count = count -1
+#            print "Negative!"
+#
+#        else:
+
+        # If the Z-location is provided, otherwise put nan
         if zflag:
 
             rx.append(temp[:-2])
@@ -664,7 +732,7 @@ def readUBC_DC3Dobs(fileName):
                 wd.append(temp[-1])
 
         else:
-            rx.append(np.r_[temp[0:2],np.nan,temp[0:2],np.nan] )
+            rx.append(np.r_[temp[0:2],np.nan,temp[2:4],np.nan] )
             # Check if there is data with the location
             if len(temp)==6:
                 d.append(temp[-2])
@@ -672,7 +740,7 @@ def readUBC_DC3Dobs(fileName):
 
         count = count -1
 
-        # Reach the end of transmitter block
+        # Reach the end of transmitter block, append the src, rx and continue
         if count == 0:
             rx = np.asarray(rx)
             Rx = DC.RxDipole(rx[:,:3],rx[:,3:])
@@ -688,19 +756,12 @@ def readUBC_DC3Dobs(fileName):
 
 def readUBC_DC2Dobs(fileName):
     """
+        ------- NEEDS TO BE UPDATED ------
         Read UBC GIF 2D observation file and generate arrays for tx-rx location
 
-        Input:
-        :param fileName, path to the UBC GIF 2D model file
-
-        Output:
-        :param rx, tx
-        :return
-
-        Created on Thu Nov 12 13:14:10 2015
-
-        @author: dominiquef
-
+        :param string fileName: path to the UBC GIF 2D model file
+        :rtype: (DC.Src, DC.Rx, ??, ??)
+        :return: source_locs, rx_locs, ??, ??
     """
 
     from SimPEG import np
@@ -735,16 +796,78 @@ def readUBC_DC2Dobs(fileName):
 
     return tx, rx, d, wd
 
+def readUBC_DC2Dpre(fileName):
+    """
+        Read UBC GIF DCIP 2D observation file and generate arrays for tx-rx location
+
+        Input:
+        :param string fileName: path to the UBC GIF 3D obs file
+        :rtype: DC.Survey
+        :return: DCsurvey
+
+        Created on Mon March 9th, 2016 << Doug's 70th Birthday !! >>
+
+        @author: dominiquef
+
+    """
+
+    # Load file
+    obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
+
+    # Pre-allocate
+    srcLists = []
+    Rx = []
+    d = []
+    zflag = True # Flag for z value provided
+
+    for ii in range(obsfile.shape[0]):
+
+        if not obsfile[ii]:
+            continue
+
+        # First line is transmitter with number of receivers
+
+
+        temp = (np.fromstring(obsfile[ii], dtype=float,sep=' ').T)
+
+
+        # Check if z value is provided, if False -> nan
+        if len(temp)==5:
+            tx = np.r_[temp[0],np.nan,np.nan,temp[1],np.nan,np.nan]
+            zflag = False
+
+        else:
+            tx = np.r_[temp[0],np.nan,temp[1],temp[2],np.nan,temp[3]]
+
+
+        if zflag:
+            rx = np.c_[temp[4],np.nan,temp[5],temp[6],np.nan,temp[7]]
+
+
+        else:
+            rx = np.c_[temp[2],np.nan,np.nan,temp[3],np.nan,np.nan]
+            # Check if there is data with the location
+
+        d.append(temp[-1])
+
+
+        Rx = DC.RxDipole(rx[:,:3],rx[:,3:])
+        srcLists.append( DC.SrcDipole( [Rx], tx[:3],tx[3:]) )
+
+    # Create survey class
+    survey = DC.SurveyDC(srcLists)
+
+    survey.dobs = np.asarray(d)
+
+    return {'DCsurvey':survey}
+
 def readUBC_DC2DMesh(fileName):
     """
         Read UBC GIF 2DTensor mesh and generate 2D Tensor mesh in simpeg
 
-        Input:
-        :param fileName, path to the UBC GIF mesh file
-
-        Output:
-        :param SimPEG TensorMesh 2D object
-        :return
+        :param string fileName: path to the UBC GIF mesh file
+        :rtype: Mesh.TensorMesh
+        :return: SimPEG TensorMesh 2D object
 
         Created on Thu Nov 12 13:14:10 2015
 
@@ -810,12 +933,9 @@ def xy_2_lineID(DCsurvey):
         they were collected. May need to generalize for random
         point locations, but will be more expensive
 
-        Input:
-        :param DCdict Vectors of station location
-
-        Output:
-        :param LineID Vector of integers
-        :return
+        :param numpy.array DCdict: Vectors of station location
+        :rtype: numpy.array
+        :return: LineID Vector of integers
 
         Created on Thu Feb 11, 2015
 
@@ -928,7 +1048,6 @@ def getSrc_locs(DCsurvey):
 
     srcMat = np.zeros((DCsurvey.nSrc,2,3))
     for ii in range(DCsurvey.nSrc):
-        print np.asarray(DCsurvey.srcList[ii].loc).shape
         srcMat[ii,:,:] =  np.asarray(DCsurvey.srcList[ii].loc)
 
     return srcMat

SimPEG/DCIP/Utils.py

@@ -1,3 +1,10 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
 import numpy as np
 
 def WennerSrcList(nElecs, aSpacing, in2D=False, plotIt=False):
@@ -5,7 +12,7 @@ def WennerSrcList(nElecs, aSpacing, in2D=False, plotIt=False):
     import SimPEG.DCIP as DC
 
     elocs = np.arange(0,aSpacing*nElecs,aSpacing)
-    elocs -= (nElecs*aSpacing - aSpacing)/2
+    elocs -= (nElecs*aSpacing - aSpacing) / 2
     space = 1
     WENNER = np.zeros((0,),dtype=int)
     for ii in range(nElecs):

SimPEG/DCIP/__init__.py

@@ -1,4 +1,10 @@
-from BaseDC import *
-from BaseIP import *
-from DCIPUtils import *
-import Utils
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .BaseDC import *
+from .BaseIP import *
+from .DCIPUtils import *
+from . import Utils

SimPEG/DataMisfit.py

@@ -1,7 +1,16 @@
-import Utils, Survey, Problem, numpy as np, scipy.sparse as sp, gc
+from __future__ import print_function
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import object
+from . import Utils, Survey, Problem
+import numpy as np, scipy.sparse as sp, gc
+from future.utils import with_metaclass
 
 
-class BaseDataMisfit(object):
+class BaseDataMisfit(with_metaclass(Utils.SimPEGMetaClass, object)):
     """BaseDataMisfit
 
         .. note::
@@ -9,8 +18,6 @@ class BaseDataMisfit(object):
             You should inherit from this class to create your own data misfit term.
     """
 
-    __metaclass__ = Utils.SimPEGMetaClass
-
     debug   = False  #: Print debugging information
     counter = None   #: Set this to a SimPEG.Utils.Counter() if you want to count things
 
@@ -22,11 +29,11 @@ class BaseDataMisfit(object):
         Utils.setKwargs(self,**kwargs)
 
     @Utils.timeIt
-    def eval(self, m, u=None):
-        """eval(m, u=None)
+    def eval(self, m, f=None):
+        """eval(m, f=None)
 
             :param numpy.array m: geophysical model
-            :param numpy.array u: fields
+            :param Fields f: fields
             :rtype: float
             :return: data misfit
 
@@ -34,11 +41,11 @@ class BaseDataMisfit(object):
         raise NotImplementedError('This method should be overwritten.')
 
     @Utils.timeIt
-    def evalDeriv(self, m, u=None):
-        """evalDeriv(m, u=None)
+    def evalDeriv(self, m, f=None):
+        """evalDeriv(m, f=None)
 
             :param numpy.array m: geophysical model
-            :param numpy.array u: fields
+            :param Fields f: fields
             :rtype: numpy.array
             :return: data misfit derivative
 
@@ -47,12 +54,12 @@ class BaseDataMisfit(object):
 
 
     @Utils.timeIt
-    def eval2Deriv(self, m, v, u=None):
-        """eval2Deriv(m, v, u=None)
+    def eval2Deriv(self, m, v, f=None):
+        """eval2Deriv(m, v, f=None)
 
             :param numpy.array m: geophysical model
             :param numpy.array v: vector to multiply
-            :param numpy.array u: fields
+            :param Fields f: fields
             :rtype: numpy.array
             :return: data misfit derivative
 
@@ -89,15 +96,15 @@ class l2_DataMisfit(BaseDataMisfit):
         """
 
         if getattr(self, '_Wd', None) is None:
-            
+
             survey = self.survey
 
             if getattr(survey,'std', None) is None:
-                print 'SimPEG.DataMisfit.l2_DataMisfit assigning default std of 5%'
+                print('SimPEG.DataMisfit.l2_DataMisfit assigning default std of 5%')
                 survey.std = 0.05
 
             if getattr(survey, 'eps', None) is None:
-                print 'SimPEG.DataMisfit.l2_DataMisfit assigning default eps of 1e-5 * ||dobs||'
+                print('SimPEG.DataMisfit.l2_DataMisfit assigning default eps of 1e-5 * ||dobs||')
                 survey.eps = np.linalg.norm(Utils.mkvc(survey.dobs),2)*1e-5
 
             self._Wd = Utils.sdiag(1/(abs(survey.dobs)*survey.std+survey.eps))
@@ -108,24 +115,20 @@ class l2_DataMisfit(BaseDataMisfit):
         self._Wd = value
 
     @Utils.timeIt
-    def eval(self, m, u=None):
-        "eval(m, u=None)"
-        prob   = self.prob
-        survey = self.survey
-        R = self.Wd * survey.residual(m, u=u)
+    def eval(self, m, f=None):
+        "eval(m, f=None)"
+        if f is None: f = self.prob.fields(m)
+        R = self.Wd * self.survey.residual(m, f)
         return 0.5*np.vdot(R, R)
 
     @Utils.timeIt
-    def evalDeriv(self, m, u=None):
-        "evalDeriv(m, u=None)"
-        prob   = self.prob
-        survey = self.survey
-        if u is None: u = prob.fields(m)
-        return prob.Jtvec(m, self.Wd * (self.Wd * survey.residual(m, u=u)), u=u)
+    def evalDeriv(self, m, f=None):
+        "evalDeriv(m, f=None)"
+        if f is None: f = self.prob.fields(m)
+        return self.prob.Jtvec(m, self.Wd * (self.Wd * self.survey.residual(m, f=f)), f=f)
 
     @Utils.timeIt
-    def eval2Deriv(self, m, v, u=None):
-        "eval2Deriv(m, v, u=None)"
-        prob   = self.prob
-        if u is None: u = prob.fields(m)
-        return prob.Jtvec_approx(m, self.Wd * (self.Wd * prob.Jvec_approx(m, v, u=u)), u=u)
+    def eval2Deriv(self, m, v, f=None):
+        "eval2Deriv(m, v, f=None)"
+        if f is None: f = self.prob.fields(m)
+        return self.prob.Jtvec_approx(m, self.Wd * (self.Wd * self.prob.Jvec_approx(m, v, f=f)), f=f)

SimPEG/Directives.py

@@ -1,4 +1,15 @@
-import Utils, numpy as np
+from __future__ import print_function
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import absolute_import
+from builtins import open
+from builtins import int
+from future import standard_library
+standard_library.install_aliases()
+from builtins import str
+from builtins import object
+from . import Utils
+import numpy as np
 
 class InversionDirective(object):
     """InversionDirective"""
@@ -15,7 +26,7 @@ class InversionDirective(object):
     @inversion.setter
     def inversion(self, i):
         if getattr(self,'_inversion',None) is not None:
-            print 'Warning: InversionDirective %s has switched to a new inversion.' % self.__name__
+            print('Warning: InversionDirective %s has switched to a new inversion.' % self.__name__)
         self._inversion = i
 
     @property
@@ -68,7 +79,7 @@ class DirectiveList(object):
     def inversion(self, i):
         if self.inversion is i: return
         if getattr(self,'_inversion',None) is not None:
-            print 'Warning: %s has switched to a new inversion.' % self.__name__
+            print('Warning: %s has switched to a new inversion.' % self.__name__)
         for d in self.dList:
             d.inversion = i
         self._inversion = i
@@ -120,13 +131,13 @@ class BetaEstimate_ByEig(InversionDirective):
             :return: beta0
         """
 
-        if self.debug: print 'Calculating the beta0 parameter.'
+        if self.debug: print('Calculating the beta0 parameter.')
 
         m = self.invProb.curModel
-        u = self.invProb.getFields(m, store=True, deleteWarmstart=False)
+        f = self.invProb.getFields(m, store=True, deleteWarmstart=False)
 
         x0 = np.random.rand(*m.shape)
-        t = x0.dot(self.dmisfit.eval2Deriv(m,x0,u=u))
+        t = x0.dot(self.dmisfit.eval2Deriv(m,x0,f=f))
         b = x0.dot(self.reg.eval2Deriv(m, v=x0))
         self.beta0 = self.beta0_ratio*(t/b)
 
@@ -141,15 +152,21 @@ class BetaSchedule(InversionDirective):
 
     def endIter(self):
         if self.opt.iter > 0 and self.opt.iter % self.coolingRate == 0:
-            if self.debug: print 'BetaSchedule is cooling Beta. Iteration: %d' % self.opt.iter
+            if self.debug: print('BetaSchedule is cooling Beta. Iteration: %d' % self.opt.iter)
             self.invProb.beta /= self.coolingFactor
 
+
 class TargetMisfit(InversionDirective):
 
+    chifact = 1.
+    phi_d_star = None
+
     @property
     def target(self):
         if getattr(self, '_target', None) is None:
-            self._target = self.survey.nD*0.5
+            if self.phi_d_star is None:
+                self.phi_d_star = 0.5 * self.survey.nD
+            self._target = self.chifact * self.phi_d_star # the factor of 0.5 is because we do phid = 0.5*|| dpred - dobs||^2
         return self._target
     @target.setter
     def target(self, val):
@@ -161,7 +178,7 @@ class TargetMisfit(InversionDirective):
 
 
 
-class _SaveEveryIteration(InversionDirective):
+class SaveEveryIteration(InversionDirective):
     @property
     def name(self):
         if getattr(self, '_name', None) is None:
@@ -182,21 +199,21 @@ class _SaveEveryIteration(InversionDirective):
         self._fileName = value
 
 
-class SaveModelEveryIteration(_SaveEveryIteration):
+class SaveModelEveryIteration(SaveEveryIteration):
     """SaveModelEveryIteration"""
 
     def initialize(self):
-        print "SimPEG.SaveModelEveryIteration will save your models as: '###-%s.npy'"%self.fileName
+        print("SimPEG.SaveModelEveryIteration will save your models as: '###-%s.npy'"%self.fileName)
 
     def endIter(self):
         np.save('%03d-%s' % (self.opt.iter, self.fileName), self.opt.xc)
 
 
-class SaveOutputEveryIteration(_SaveEveryIteration):
+class SaveOutputEveryIteration(SaveEveryIteration):
     """SaveModelEveryIteration"""
 
     def initialize(self):
-        print "SimPEG.SaveOutputEveryIteration will save your inversion progress as: '###-%s.txt'"%self.fileName
+        print("SimPEG.SaveOutputEveryIteration will save your inversion progress as: '###-%s.txt'"%self.fileName)
         f = open(self.fileName+'.txt', 'w')
         f.write("  #     beta     phi_d     phi_m       f\n")
         f.close()
@@ -206,23 +223,23 @@ class SaveOutputEveryIteration(_SaveEveryIteration):
         f.write(' %3d %1.4e %1.4e %1.4e %1.4e\n'%(self.opt.iter, self.invProb.beta, self.invProb.phi_d, self.invProb.phi_m, self.opt.f))
         f.close()
 
-class SaveOutputDictEveryIteration(_SaveEveryIteration):
+class SaveOutputDictEveryIteration(SaveEveryIteration):
     """SaveOutputDictEveryIteration"""
 
     def initialize(self):
-        print "SimPEG.SaveOutputDictEveryIteration will save your inversion progress as dictionary: '###-%s.npz'"%self.fileName
+        print("SimPEG.SaveOutputDictEveryIteration will save your inversion progress as dictionary: '###-%s.npz'"%self.fileName)
 
     def endIter(self):
         # Save the data.
         ms = self.reg.Ws * ( self.reg.mapping * (self.invProb.curModel - self.reg.mref) )
         phi_ms = 0.5*ms.dot(ms)
-        if self.reg.smoothModel == True:
+        if self.reg.mrefInSmooth == True:
             mref = self.reg.mref
         else:
             mref = 0
         mx = self.reg.Wx * ( self.reg.mapping * (self.invProb.curModel - mref) )
         phi_mx = 0.5 * mx.dot(mx)
-        if self.prob.mesh.dim==2:
+        if self.prob.mesh.dim >= 2:
             my = self.reg.Wy * ( self.reg.mapping * (self.invProb.curModel - mref) )
             phi_my = 0.5 * my.dot(my)
         else:
@@ -237,49 +254,210 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
         # Save the file as a npz
         np.savez('{:03d}-{:s}'.format(self.opt.iter,self.fileName), iter=self.opt.iter, beta=self.invProb.beta, phi_d=self.invProb.phi_d, phi_m=self.invProb.phi_m, phi_ms=phi_ms, phi_mx=phi_mx, phi_my=phi_my, phi_mz=phi_mz,f=self.opt.f, m=self.invProb.curModel,dpred=self.invProb.dpred)
 
-class SaveOutputDictEveryIteration(_SaveEveryIteration):
-    """SaveOutputDictEveryIteration
-    A directive that saves some relevant information from the inversion run to a numpy .npz dictionary file (see numpy.savez function for further info).
-    """
-
-    def initialize(self):
-        print "SimPEG.SaveOutputDictEveryIteration will save your inversion progress as dictionary: '%s-###.npz'"%self.fileName
-
-    def endIter(self):
-        # Save the data.
-        ms = self.reg.Ws * ( self.reg.mapping * (self.invProb.curModel - self.reg.mref) )
-        phi_ms = 0.5*ms.dot(ms)
-        if self.reg.smoothModel == True:
-            mref = self.reg.mref
-        else:
-            mref = 0
-        mx = self.reg.Wx * ( self.reg.mapping * (self.invProb.curModel - mref) )
-        phi_mx = 0.5 * mx.dot(mx)
-        if self.prob.mesh.dim==2:
-            my = self.reg.Wy * ( self.reg.mapping * (self.invProb.curModel - mref) )
-            phi_my = 0.5 * my.dot(my)
-        else:
-            phi_my = 'NaN'
-        if self.prob.mesh.dim==3 and 'CYL' not in self.prob.mesh._meshType:
-            mz = self.reg.Wz * ( self.reg.mapping * (self.invProb.curModel - mref) )
-            phi_mz = 0.5 * mz.dot(mz)
-        else:
-            phi_mz = 'NaN'
-
-
-        # Save the file as a npz
-        np.savez('{:s}-{:03d}'.format(self.fileName,self.opt.iter), iter=self.opt.iter, beta=self.invProb.beta, phi_d=self.invProb.phi_d, phi_m=self.invProb.phi_m, phi_ms=phi_ms, phi_mx=phi_mx, phi_my=phi_my, phi_mz=phi_mz,f=self.opt.f, m=self.invProb.curModel,dpred=self.invProb.dpred)
-
-
-
-# class UpdateReferenceModel(Parameter):
-
-#     mref0 = None
-
-#     def nextIter(self):
 #         mref = getattr(self, 'm_prev', None)
 #         if mref is None:
 #             if self.debug: print 'UpdateReferenceModel is using mref0'
 #             mref = self.mref0
 #         self.m_prev = self.invProb.m_current
 #         return mref
+
+class Update_IRLS(InversionDirective):
+
+    eps_min = None
+    eps = None
+    norms = [2.,2.,2.,2.]
+    factor = None
+    gamma = None
+    phi_m_last = None
+    phi_d_last = None
+    f_old = None
+    f_min_change = 1e-2
+    beta_tol = 5e-2
+    prctile = 95
+
+    # Solving parameter for IRLS (mode:2)
+    IRLSiter   = 0
+    minGNiter = 5
+    maxIRLSiter = 10
+    iterStart = 0
+
+    # Beta schedule
+    coolingFactor = 2.
+    coolingRate = 1
+
+    mode = 1
+
+    @property
+    def target(self):
+        if getattr(self, '_target', None) is None:
+            self._target = self.survey.nD*0.5
+        return self._target
+    @target.setter
+    def target(self, val):
+        self._target = val
+
+    def initialize(self):
+
+        if self.mode == 1:
+            self.reg.norms = [2., 2., 2., 2.]
+
+    def endIter(self):
+
+        # After reaching target misfit with l2-norm, switch to IRLS (mode:2)
+        if self.invProb.phi_d < self.target and self.mode == 1:
+            print("Convergence with smooth l2-norm regularization: Start IRLS steps...")
+
+            self.mode = 2
+
+            # Either use the supplied epsilon, or fix base on distribution of
+            # model values
+            if getattr(self, 'reg.eps', None) is None:
+                self.reg.eps_p = np.percentile(np.abs(self.invProb.curModel),self.prctile)
+            else:
+                self.reg.eps_p = self.eps[0]
+
+            if getattr(self, 'reg.eps', None) is None:
+                self.reg.eps_q = np.percentile(np.abs(self.reg.regmesh.cellDiffxStencil*(self.reg.mapping * self.invProb.curModel)),self.prctile)
+            else:
+                self.reg.eps_q = self.eps[1]
+
+            print("L[p qx qy qz]-norm : " + str(self.reg.norms))
+            print("eps_p: " + str(self.reg.eps_p) + " eps_q: " + str(self.reg.eps_q))
+
+            self.reg.norms = self.norms
+            self.coolingFactor = 1.
+            self.coolingRate = 1
+            self.iterStart = self.opt.iter
+            self.phi_d_last = self.invProb.phi_d
+            self.phi_m_last = self.invProb.phi_m_last
+
+            self.reg.l2model = self.invProb.curModel
+            self.reg.curModel = self.invProb.curModel
+
+            if getattr(self, 'f_old', None) is None:
+                self.f_old = self.reg.eval(self.invProb.curModel)#self.invProb.evalFunction(self.invProb.curModel, return_g=False, return_H=False)
+
+        # Beta Schedule
+        if self.opt.iter > 0 and self.opt.iter % self.coolingRate == 0:
+            if self.debug: print('BetaSchedule is cooling Beta. Iteration: %d' % self.opt.iter)
+            self.invProb.beta /= self.coolingFactor
+
+
+        # Only update after GN iterations
+        if (self.opt.iter-self.iterStart) % self.minGNiter == 0 and self.mode==2:
+
+            self.IRLSiter += 1
+
+            phim_new = self.reg.eval(self.invProb.curModel)
+            self.f_change = np.abs(self.f_old - phim_new) / self.f_old
+
+            print("Regularization decrease: %6.3e" % (self.f_change))
+
+            # Check for maximum number of IRLS cycles
+            if self.IRLSiter == self.maxIRLSiter:
+                print("Reach maximum number of IRLS cycles: %i" % self.maxIRLSiter)
+                self.opt.stopNextIteration = True
+                return
+
+            # Check if the function has changed enough
+            if self.f_change < self.f_min_change and self.IRLSiter > 1:
+                print("Minimum decrease in regularization. End of IRLS")
+                self.opt.stopNextIteration = True
+                return
+            else:
+                self.f_old = phim_new
+
+#            # Cool the threshold parameter if required
+#            if getattr(self, 'factor', None) is not None:
+#                eps = self.reg.eps / self.factor
+#
+#                if getattr(self, 'eps_min', None) is not None:
+#                    self.reg.eps = np.max([self.eps_min,eps])
+#                else:
+#                    self.reg.eps = eps
+
+            # Get phi_m at the end of current iteration
+            self.phi_m_last = self.invProb.phi_m_last
+
+            # Reset the regularization matrices so that it is
+            # recalculated for current model
+            self.reg._Wsmall = None
+            self.reg._Wx = None
+            self.reg._Wy = None
+            self.reg._Wz = None
+
+             # Update the model used for the IRLS weights
+            self.reg.curModel = self.invProb.curModel
+
+            # Temporarely set gamma to 1. to get raw phi_m
+            self.reg.gamma = 1.
+
+            # Compute new model objective function value
+            phim_new = self.reg.eval(self.invProb.curModel)
+
+            # Update gamma to scale the regularization between IRLS iterations
+            self.reg.gamma = self.phi_m_last / phim_new
+
+            # Reset the regularization matrices again for new gamma
+            self.reg._Wsmall = None
+            self.reg._Wx = None
+            self.reg._Wy = None
+            self.reg._Wz = None
+
+            # Check if misfit is within the tolerance, otherwise scale beta
+            val = self.invProb.phi_d / (self.survey.nD*0.5)
+
+            if np.abs(1.-val) > self.beta_tol:
+                self.invProb.beta = self.invProb.beta * self.survey.nD*0.5 / self.invProb.phi_d
+
+class Update_lin_PreCond(InversionDirective):
+    """
+    Create a Jacobi preconditioner for the linear problem
+    """
+    onlyOnStart=False
+
+    def initialize(self):
+
+        if getattr(self.opt, 'approxHinv', None) is None:
+            # Update the pre-conditioner
+            diagA = np.sum(self.prob.G**2.,axis=0) + self.invProb.beta*(self.reg.W.T*self.reg.W).diagonal() #* (self.reg.mapping * np.ones(self.reg.curModel.size))**2.
+            PC     = Utils.sdiag((self.prob.mapping.deriv(None).T *diagA)**-1.)
+            self.opt.approxHinv = PC
+
+    def endIter(self):
+        # Cool the threshold parameter
+        if self.onlyOnStart==True:
+            return
+
+        if getattr(self.opt, 'approxHinv', None) is not None:
+            # Update the pre-conditioner
+            diagA = np.sum(self.prob.G**2.,axis=0) + self.invProb.beta*(self.reg.W.T*self.reg.W).diagonal() #* (self.reg.mapping * np.ones(self.reg.curModel.size))**2.
+            PC     = Utils.sdiag((self.prob.mapping.deriv(None).T *diagA)**-1.)
+            self.opt.approxHinv = PC
+
+
+class Update_Wj(InversionDirective):
+    """
+        Create approx-sensitivity base weighting using the probing method
+    """
+    k = None # Number of probing cycles
+    itr = None # Iteration number to update Wj, or always update if None
+
+    def endIter(self):
+
+        if self.itr is None or self.itr == self.opt.iter:
+
+            m = self.invProb.curModel
+            if self.k is None:
+                self.k = int(self.survey.nD/10)
+
+            def JtJv(v):
+
+                Jv = self.prob.Jvec(m, v)
+
+                return self.prob.Jtvec(m,Jv)
+
+            JtJdiag = Utils.diagEst(JtJv,len(m),k=self.k)
+            JtJdiag = JtJdiag / max(JtJdiag)
+
+            self.reg.wght = JtJdiag

SimPEG/EM/Analytics/DC.py

@@ -0,0 +1,125 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
+import numpy as np
+from scipy.constants import mu_0, pi
+from scipy import special
+
+def DCAnalyticHalf(txloc, rxlocs, sigma, earth_type="wholespace"):
+    """
+        Analytic solution for electric potential from a postive pole
+
+        :param array txloc: a xyz location of A (+) electrode (np.r_[xa, ya, za])
+        :param list rxlocs: xyz locations of M (+) and N (-) electrodes [M, N]
+
+            e.g.
+            rxlocs = [M, N]
+            M: xyz locations of M (+) electrode (np.c_[xmlocs, ymlocs, zmlocs])
+            N: xyz locations of N (-) electrode (np.c_[xnlocs, ynlocs, znlocs])
+
+        :param float or complex sigma: values of conductivity
+        :param string earth_type: values of conductivity ("wholsespace" or "halfspace")
+
+    """
+    M = rxlocs[0]
+    N = rxlocs[1]
+
+    rM = np.sqrt( (M[:,0]-txloc[0])**2 + (M[:,1]-txloc[1])**2 + (M[:,2]-txloc[1])**2 )
+    rN = np.sqrt( (N[:,0]-txloc[0])**2 + (N[:,1]-txloc[1])**2 + (N[:,2]-txloc[1])**2 )
+
+    phiM = 1./(4*np.pi*rM*sigma)
+    phiN = 1./(4*np.pi*rN*sigma)
+    phi = phiM - phiN
+
+    if earth_type == "halfspace":
+        phi *= 2
+
+    return phi
+
+deg2rad  = lambda deg: deg/180.*np.pi
+rad2deg  = lambda rad: rad*180./np.pi
+
+def DCAnalyticSphere(txloc, rxloc, xc, radius, sigma, sigma1, \
+                 field_type = "secondary", order=12, halfspace=False):
+# def DCSpherePointCurrent(txloc, rxloc, xc, radius, rho, rho1, \
+#                  field_type = "secondary", order=12):
+    """
+
+        Parameters:
+
+            :param array txloc: A (+) current electrode location (x,y,z)
+            :param array xc: x center of depressed sphere
+            :param array rxloc: M(+) electrode locations / (Nx3 array, # of electrodes)
+
+            :param float radius: radius (float): radius of the sphere (m)
+            :param float rho: resistivity of the background (ohm-m)
+            :param float rho1: resistivity of the sphere
+            :param string field_type: : "secondary", "total", "primary"
+                  (default="secondary")
+                  "secondary": secondary potential only due to sphere
+                  "primary": primary potential from the point source
+                  "total": "secondary"+"primary"
+            :param float order: maximum order of Legendre polynomial (default=12)
+
+        Written by Seogi Kang (skang@eos.ubc.ca)
+        Ph.D. Candidate of University of British Columbia, Canada
+
+    """
+
+    Pleg = []
+    # Compute Legendre Polynomial
+    for i in range(order):
+        Pleg.append(special.legendre(i, monic=0))
+
+
+    rho = 1./sigma
+    rho1 = 1./sigma1
+
+    # Center of the sphere should be aligned in txloc in y-direction
+    yc = txloc[1]
+    xyz = np.c_[rxloc[:,0]-xc, rxloc[:,1]-yc, rxloc[:,2]]
+    r = np.sqrt( (xyz**2).sum(axis=1) )
+
+    x0 = abs(txloc[0]-xc)
+
+    costheta = xyz[:,0]/r * (txloc[0]-xc)/x0
+    phi = np.zeros_like(r)
+    R = (r**2+x0**2.-2.*r*x0*costheta)**0.5
+    # primary potential in a whole space
+    prim = rho*1./(4*np.pi*R)
+
+    if field_type =="primary":
+        return prim
+
+    sphind = r < radius
+    out = np.zeros_like(r)
+    for n in range(order):
+        An, Bn = AnBnfun(n, radius, x0, rho, rho1)
+        dumout = An*r[~sphind]**(-n-1.)*Pleg[n](costheta[~sphind])
+        out[~sphind] += dumout
+        dumin = Bn*r[sphind]**(n)*Pleg[n](costheta[sphind])
+        out[sphind] += dumin
+
+    out[~sphind] += prim[~sphind]
+
+    if halfspace:
+        scale = 2
+    else:
+        scale = 1
+
+    if field_type == "secondary":
+        return scale*(out-prim)
+    elif field_type == "total":
+        return scale*out
+
+def AnBnfun(n, radius, x0, rho, rho1, I=1.):
+    const = I*rho/(4*np.pi)
+    bunmo = n*rho + (n+1)*rho1
+    An = const * radius**(2*n+1) / x0 ** (n+1.) * n * \
+        (rho1-rho) / bunmo
+    Bn = const * 1. / x0 ** (n+1.) * (2*n+1) * (rho1) / bunmo
+    return An, Bn

SimPEG/EM/Analytics/FDEM.py

@@ -1,4 +1,9 @@
 from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 import numpy as np
 from scipy.constants import mu_0, pi
 from scipy.special import erf

SimPEG/EM/Analytics/FDEMDipolarfields.py

@@ -0,0 +1,307 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+import numpy as np
+from scipy.constants import mu_0, pi, epsilon_0
+from scipy.special import erf
+from SimPEG import Utils
+
+omega = lambda f: 2.*np.pi*f
+# TODO:
+# r = lambda dx, dy, dz: np.sqrt( dx**2. + dy**2. + dz**2.)
+# k = lambda f, mu, epsilon, sig: np.sqrt( omega(f)**2. *mu*epsilon -1j*omega(f)*mu*sig )
+
+def E_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=1., length=1., orientation='X', kappa=0., epsr=1.):
+
+    """
+        Computing Analytic Electric fields from Electrical Dipole in a Wholespace
+        TODO:
+            Add description of parameters
+    """
+    mu = mu_0*(1+kappa)
+    epsilon = epsilon_0*epsr
+    sig_hat = sig + 1j*omega(f)*epsilon
+
+    XYZ = Utils.asArray_N_x_Dim(XYZ, 3)
+    # Check
+    if XYZ.shape[0] > 1 & f.shape[0] > 1:
+        raise Exception("I/O type error: For multiple field locations only a single frequency can be specified.")
+
+    dx = XYZ[:,0]-srcLoc[0]
+    dy = XYZ[:,1]-srcLoc[1]
+    dz = XYZ[:,2]-srcLoc[2]
+
+    r  = np.sqrt( dx**2. + dy**2. + dz**2.)
+    # k  = np.sqrt( -1j*2.*np.pi*f*mu*sig )
+    k  = np.sqrt( omega(f)**2. *mu*epsilon -1j*omega(f)*mu*sig )
+
+    front = current * length / (4.*np.pi*sig_hat* r**3) * np.exp(-1j*k*r)
+    mid   = -k**2 * r**2 + 3*1j*k*r + 3
+
+    if orientation.upper() == 'X':
+        Ex = front*((dx**2 / r**2)*mid + (k**2 * r**2 -1j*k*r-1.))
+        Ey = front*(dx*dy  / r**2)*mid
+        Ez = front*(dx*dz  / r**2)*mid
+        return Ex, Ey, Ez
+
+    elif orientation.upper() == 'Y':
+        #  x--> y, y--> z, z-->x
+        Ey = front*((dy**2 / r**2)*mid + (k**2 * r**2 -1j*k*r-1.))
+        Ez = front*(dy*dz  / r**2)*mid
+        Ex = front*(dy*dx  / r**2)*mid
+        return Ex, Ey, Ez
+
+    elif orientation.upper() == 'Z':
+        # x --> z, y --> x, z --> y
+        Ez = front*((dz**2 / r**2)*mid + (k**2 * r**2 -1j*k*r-1.))
+        Ex = front*(dz*dx  / r**2)*mid
+        Ey = front*(dz*dy  / r**2)*mid
+        return Ex, Ey, Ez
+
+
+def E_galvanic_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=1., length=1., orientation='X', kappa=1., epsr=1.):
+
+    """
+        Computing Galvanic portion of Electric fields from Electrical Dipole in a Wholespace
+        TODO:
+            Add description of parameters
+    """
+    mu = mu_0*(1+kappa)
+    epsilon = epsilon_0*epsr
+    sig_hat = sig + 1j*omega(f)*epsilon
+
+    XYZ = Utils.asArray_N_x_Dim(XYZ, 3)
+    # Check
+    if XYZ.shape[0] > 1 & f.shape[0] > 1:
+        raise Exception("I/O type error: For multiple field locations only a single frequency can be specified.")
+
+    dx = XYZ[:,0]-srcLoc[0]
+    dy = XYZ[:,1]-srcLoc[1]
+    dz = XYZ[:,2]-srcLoc[2]
+
+    r  = np.sqrt( dx**2. + dy**2. + dz**2.)
+    # k  = np.sqrt( -1j*2.*np.pi*f*mu*sig )
+    k  = np.sqrt( omega(f)**2. *mu*epsilon -1j*omega(f)*mu*sig )
+
+    front = current * length / (4.*np.pi*sig_hat* r**3) * np.exp(-1j*k*r)
+    mid   = -k**2 * r**2 + 3*1j*k*r + 3
+
+    if orientation.upper() == 'X':
+        Ex_galvanic = front*((dx**2 / r**2)*mid + (-1j*k*r-1.))
+        Ey_galvanic = front*(dx*dy  / r**2)*mid
+        Ez_galvanic = front*(dx*dz  / r**2)*mid
+        return Ex_galvanic, Ey_galvanic, Ez_galvanic
+
+    elif orientation.upper() == 'Y':
+        #  x--> y, y--> z, z-->x
+        Ey_galvanic = front*((dy**2 / r**2)*mid + (-1j*k*r-1.))
+        Ez_galvanic = front*(dy*dz  / r**2)*mid
+        Ex_galvanic = front*(dy*dx  / r**2)*mid
+        return Ex_galvanic, Ey_galvanic, Ez_galvanic
+
+    elif orientation.upper() == 'Z':
+        # x --> z, y --> x, z --> y
+        Ez_galvanic = front*((dz**2 / r**2)*mid + (-1j*k*r-1.))
+        Ex_galvanic = front*(dz*dx  / r**2)*mid
+        Ey_galvanic = front*(dz*dy  / r**2)*mid
+        return Ex_galvanic, Ey_galvanic, Ez_galvanic
+
+
+def E_inductive_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=1., length=1., orientation='X', kappa=1., epsr=1.):
+
+    """
+        Computing Inductive portion of Electric fields from Electrical Dipole in a Wholespace
+        TODO:
+            Add description of parameters
+    """
+    mu = mu_0*(1+kappa)
+    epsilon = epsilon_0*epsr
+    sig_hat = sig + 1j*omega(f)*epsilon
+
+    XYZ = Utils.asArray_N_x_Dim(XYZ, 3)
+    # Check
+    if XYZ.shape[0] > 1 & f.shape[0] > 1:
+        raise Exception("I/O type error: For multiple field locations only a single frequency can be specified.")
+
+    dx = XYZ[:,0]-srcLoc[0]
+    dy = XYZ[:,1]-srcLoc[1]
+    dz = XYZ[:,2]-srcLoc[2]
+
+    r  = np.sqrt( dx**2. + dy**2. + dz**2.)
+    # k  = np.sqrt( -1j*2.*np.pi*f*mu*sig )
+    k  = np.sqrt( omega(f)**2. *mu*epsilon -1j*omega(f)*mu*sig )
+
+    front = current * length / (4.*np.pi*sig_hat* r**3) * np.exp(-1j*k*r)
+
+    if orientation.upper() == 'X':
+        Ex_inductive = front*(k**2 * r**2)
+        Ey_inductive = np.zeros_like(Ex_inductive)
+        Ez_inductive = np.zeros_like(Ex_inductive)
+        return Ex_inductive, Ey_inductive, Ez_inductive
+
+    elif orientation.upper() == 'Y':
+        #  x--> y, y--> z, z-->x
+        Ey_inductive = front*(k**2 * r**2)
+        Ez_inductive = np.zeros_like(Ey_inductive)
+        Ex_inductive = np.zeros_like(Ey_inductive)
+        return Ex_inductive, Ey_inductive, Ez_inductive
+
+    elif orientation.upper() == 'Z':
+        # x --> z, y --> x, z --> y
+        Ez_inductive = front*(k**2 * r**2)
+        Ex_inductive = np.zeros_like(Ez_inductive)
+        Ey_inductive = np.zeros_like(Ez_inductive)
+        return Ex_inductive, Ey_inductive, Ez_inductive
+
+
+def J_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=1., length=1., orientation='X', kappa=1., epsr=1.):
+
+    """
+        Computing Current densities from Electrical Dipole in a Wholespace
+        TODO:
+            Add description of parameters
+    """
+
+    Ex, Ey, Ez = E_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=current, length=length, orientation=orientation, kappa=kappa, epsr=epsr)
+    Jx = sig*Ex
+    Jy = sig*Ey
+    Jz = sig*Ez
+    return Jx, Jy, Jz
+
+
+def J_galvanic_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=1., length=1., orientation='X', kappa=1., epsr=1.):
+
+    """
+        Computing Galvanic portion of Current densities from Electrical Dipole in a Wholespace
+        TODO:
+            Add description of parameters
+    """
+
+    Ex_galvanic, Ey_galvanic, Ez_galvanic = E_galvanic_from_ElectricDipoleWholeSpaced(XYZ, srcLoc, sig, f, current=current, length=length, orientation=orientation, kappa=kappa, epsr=epsr)
+    Jx_galvanic = sig*Ex_galvanic
+    Jy_galvanic = sig*Ey_galvanic
+    Jz_galvanic = sig*Ez_galvanic
+    return Jx_galvanic, Jy_galvanic, Jz_galvanic
+
+
+def J_inductive_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=1., length=1., orientation='X', kappa=1., epsr=1.):
+
+    """
+        Computing Inductive portion of Current densities from Electrical Dipole in a Wholespace
+        TODO:
+            Add description of parameters
+    """
+
+    Ex_inductive, Ey_inductive, Ez_inductive = E_inductive_from_ElectricDipoleWholeSpaced(XYZ, srcLoc, sig, f, current=current, length=length, orientation=orientation, kappa=kappa, epsr=epsr)
+    Jx_inductive = sig*Ex_inductive
+    Jy_inductive = sig*Ey_inductive
+    Jz_inductive = sig*Ez_inductive
+    return Jx_inductive, Jy_inductive, Jz_inductive
+
+
+def H_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=1., length=1., orientation='X', kappa=1., epsr=1.):
+
+    """
+        Computing Magnetic fields from Electrical Dipole in a Wholespace
+        TODO:
+            Add description of parameters
+    """
+    mu = mu_0*(1+kappa)
+    epsilon = epsilon_0*epsr
+    XYZ = Utils.asArray_N_x_Dim(XYZ, 3)
+    # Check
+    if XYZ.shape[0] > 1 & f.shape[0] > 1:
+        raise Exception("I/O type error: For multiple field locations only a single frequency can be specified.")
+
+    dx = XYZ[:,0]-srcLoc[0]
+    dy = XYZ[:,1]-srcLoc[1]
+    dz = XYZ[:,2]-srcLoc[2]
+
+    r  = np.sqrt( dx**2. + dy**2. + dz**2.)
+    # k  = np.sqrt( -1j*2.*np.pi*f*mu*sig )
+    k  = np.sqrt( omega(f)**2. *mu*epsilon -1j*omega(f)*mu*sig )
+
+    front = current * length / (4.*np.pi* r**2) * (-1j*k*r + 1) * np.exp(-1j*k*r)
+
+    if orientation.upper() == 'X':
+        Hy = front*(-dz  / r)
+        Hz = front*(dy  / r)
+        Hx = np.zeros_like(Hy)
+        return Hx, Hy, Hz
+
+    elif orientation.upper() == 'Y':
+        Hx = front*(dz  / r)
+        Hz = front*(-dx  / r)
+        Hy = np.zeros_like(Hx)
+        return Hx, Hy, Hz
+
+    elif orientation.upper() == 'Z':
+        Hx = front*(-dy / r)
+        Hy = front*(dx  / r)
+        Hz = np.zeros_like(Hx)
+        return Hx, Hy, Hz
+
+
+def B_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=1., length=1., orientation='X', kappa=1., epsr=1.):
+
+    """
+        Computing Magnetic flux densites from Electrical Dipole in a Wholespace
+        TODO:
+            Add description of parameters
+    """
+
+    Hx, Hy, Hz = H_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=current, length=length, orientation=orientation, kappa=kappa, epsr=epsr)
+    Bx = mu*Hx
+    By = mu*Hy
+    Bz = mu*Hz
+    return Bx, By, Bz
+
+
+def A_from_ElectricDipoleWholeSpace(XYZ, srcLoc, sig, f, current=1., length=1., orientation='X', kappa=1., epsr=1.):
+
+    """
+        Computing Electric vector potentials from Electrical Dipole in a Wholespace
+        TODO:
+            Add description of parameters
+    """
+    mu = mu_0*(1+kappa)
+    epsilon = epsilon_0*epsr
+    XYZ = Utils.asArray_N_x_Dim(XYZ, 3)
+    # Check
+    if XYZ.shape[0] > 1 & f.shape[0] > 1:
+        raise Exception("I/O type error: For multiple field locations only a single frequency can be specified.")
+
+    dx = XYZ[:,0]-srcLoc[0]
+    dy = XYZ[:,1]-srcLoc[1]
+    dz = XYZ[:,2]-srcLoc[2]
+
+    r  = np.sqrt( dx**2. + dy**2. + dz**2.)
+    k  = np.sqrt( omega(f)**2. *mu*epsilon -1j*omega(f)*mu*sig )
+
+    front = current * length / (4.*np.pi*r)
+
+    if orientation.upper() == 'X':
+        Ax = front*np.exp(-1j*k*r)
+        Ay = np.zeros_like(Ax)
+        Az = np.zeros_like(Ax)
+        return Ax, Ay, Az
+
+    elif orientation.upper() == 'Y':
+        Ay = front*np.exp(-1j*k*r)
+        Ax = np.zeros_like(Ay)
+        Az = np.zeros_like(Ay)
+        return Ax, Ay, Az
+
+    elif orientation.upper() == 'Z':
+        Az = front*np.exp(-1j*k*r)
+        Ax = np.zeros_like(Ay)
+        Ay = np.zeros_like(Ay)
+        return Ax, Ay, Az
+
+
+
+
+

SimPEG/EM/Analytics/FDEMcasing.py

@@ -1,3 +1,9 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import Utils, np
 from scipy.constants import mu_0, epsilon_0
 from SimPEG.EM.Utils.EMUtils import k
@@ -34,7 +40,7 @@ def _getCasingHertzMagDipoleDeriv_r(srcloc,obsloc,freq,sigma,a,b,mu=mu_0*np.ones
     sqrtr2z2 = np.sqrt(r2 + dxyz[:,2]**2)
     k2 = k(freq,sigma[2],mu[2],eps)
 
-    return -HertzZ * np.sqrt(r2) / sqrtr2z2 * (1j*k2 + 1./ sqrtr2z2)
+    return -HertzZ * np.sqrt(r2) / sqrtr2z2 * (1j*k2 + 1. / sqrtr2z2)
 
 
 def _getCasingHertzMagDipoleDeriv_z(srcloc,obsloc,freq,sigma,a,b,mu=mu_0*np.ones(3),eps=epsilon_0,moment=1.):

SimPEG/EM/Analytics/TDEM.py

@@ -1,3 +1,9 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 import numpy as np
 from scipy.constants import mu_0, pi
 from scipy.special import erf

SimPEG/EM/Analytics/__init__.py

@@ -1,3 +1,11 @@
-from TDEM import hzAnalyticDipoleT
-from FDEM import hzAnalyticDipoleF
-from FDEMcasing import *
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .TDEM import hzAnalyticDipoleT
+from .FDEM import hzAnalyticDipoleF
+from .FDEMcasing import *
+from .DC import DCAnalyticHalf, DCAnalyticSphere
+from .FDEMDipolarfields import *

SimPEG/EM/Base.py

@@ -1,15 +1,22 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import Survey, Problem, Utils, Models, Maps, PropMaps, np, sp, Solver as SimpegSolver
 from scipy.constants import mu_0
 
+
 class EMPropMap(Maps.PropMap):
-    """ 
+    """
         Property Map for EM Problems. The electrical conductivity (\\(\\sigma\\)) is the default inversion property, and the default value of the magnetic permeability is that of free space (\\(\\mu = 4\\pi\\times 10^{-7} \\) H/m)
     """
 
     sigma = Maps.Property("Electrical Conductivity", defaultInvProp = True, propertyLink=('rho',Maps.ReciprocalMap))
     mu = Maps.Property("Inverse Magnetic Permeability", defaultVal = mu_0, propertyLink=('mui',Maps.ReciprocalMap))
 
-    rho = Maps.Property("Electrical Resistivity", propertyLink=('sigma', Maps.ReciprocalMap)) 
+    rho = Maps.Property("Electrical Resistivity", propertyLink=('sigma', Maps.ReciprocalMap))
     mui = Maps.Property("Inverse Magnetic Permeability", defaultVal = 1./mu_0, propertyLink=('mu', Maps.ReciprocalMap))
 
 
@@ -19,10 +26,10 @@ class BaseEMProblem(Problem.BaseProblem):
         Problem.BaseProblem.__init__(self, mesh, **kwargs)
 
 
-    surveyPair = Survey.BaseSurvey
-    dataPair = Survey.Data
-    
-    PropMap = EMPropMap
+    surveyPair = Survey.BaseSurvey #: The survey to pair with.
+    dataPair = Survey.Data #: The data to pair with.
+
+    PropMap = EMPropMap #: The property mapping
 
     Solver = SimpegSolver
     solverOpts = {}
@@ -51,7 +58,7 @@ class BaseEMProblem(Problem.BaseProblem):
         if self.mapping.muMap is not None or self.mapping.muiMap is not None:
             toDelete += ['_MeMu', '_MeMuI','_MfMui','_MfMuiI']
         return toDelete
-    
+
     @property
     def Me(self):
         """
@@ -61,6 +68,15 @@ class BaseEMProblem(Problem.BaseProblem):
             self._Me = self.mesh.getEdgeInnerProduct()
         return self._Me
 
+    @property
+    def MeI(self):
+        """
+            Edge inner product matrix
+        """
+        if getattr(self, '_MeI', None) is None:
+            self._MeI = self.mesh.getEdgeInnerProduct(invMat=True)
+        return self._MeI
+
     @property
     def Mf(self):
         """
@@ -70,8 +86,22 @@ class BaseEMProblem(Problem.BaseProblem):
             self._Mf = self.mesh.getFaceInnerProduct()
         return self._Mf
 
+    @property
+    def MfI(self):
+        """
+            Face inner product matrix
+        """
+        if getattr(self, '_MfI', None) is None:
+            self._MfI = self.mesh.getFaceInnerProduct(invMat=True)
+        return self._MfI
 
-    # ----- Magnetic Permeability ----- # 
+    @property
+    def Vol(self):
+        if getattr(self, '_Vol', None) is None:
+            self._Vol = Utils.sdiag(self.mesh.vol)
+        return self._Vol
+
+    # ----- Magnetic Permeability ----- #
     @property
     def MfMui(self):
         """
@@ -109,7 +139,7 @@ class BaseEMProblem(Problem.BaseProblem):
         return self._MeMuI
 
 
-    # ----- Electrical Conductivity ----- # 
+    # ----- Electrical Conductivity ----- #
     #TODO: hardcoded to sigma as the model
     @property
     def MeSigma(self):
@@ -120,18 +150,17 @@ class BaseEMProblem(Problem.BaseProblem):
             self._MeSigma = self.mesh.getEdgeInnerProduct(self.curModel.sigma)
         return self._MeSigma
 
-    # TODO: This should take a vector 
+    # TODO: This should take a vector
     def MeSigmaDeriv(self, u):
         """
             Derivative of MeSigma with respect to the model
-        """ 
+        """
         return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma)(u) * self.curModel.sigmaDeriv
-    
 
     @property
     def MeSigmaI(self):
         """
-            Inverse of the edge inner product matrix for \\(\\sigma\\). 
+            Inverse of the edge inner product matrix for \\(\\sigma\\).
         """
         if getattr(self, '_MeSigmaI', None) is None:
             self._MeSigmaI = self.mesh.getEdgeInnerProduct(self.curModel.sigma, invMat=True)
@@ -140,16 +169,13 @@ class BaseEMProblem(Problem.BaseProblem):
     # TODO: This should take a vector
     def MeSigmaIDeriv(self, u):
         """
-            Derivative of :code:`MeSigma` with respect to the model 
-        """ 
+            Derivative of :code:`MeSigma` with respect to the model
+        """
         # TODO: only works for diagonal tensors. getEdgeInnerProductDeriv, invMat=True should be implemented in SimPEG
 
         dMeSigmaI_dI = -self.MeSigmaI**2
         dMe_dsig = self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma)(u)
-        dsig_dm = self.curModel.sigmaDeriv
-        return dMeSigmaI_dI * ( dMe_dsig * ( dsig_dm))
-        # return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma, invMat=True)(u)
-
+        return dMeSigmaI_dI * ( dMe_dsig * self.curModel.sigmaDeriv )
 
     @property
     def MfRho(self):
@@ -163,10 +189,9 @@ class BaseEMProblem(Problem.BaseProblem):
     # TODO: This should take a vector
     def MfRhoDeriv(self,u):
         """
-            Derivative of :code:`MfRho` with respect to the model. 
+            Derivative of :code:`MfRho` with respect to the model.
         """
-        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u) * (-Utils.sdiag(self.curModel.rho**2) * self.curModel.sigmaDeriv)
-        # self.curModel.rhoDeriv
+        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u) * self.curModel.rhoDeriv
 
     @property
     def MfRhoI(self):
@@ -181,6 +206,33 @@ class BaseEMProblem(Problem.BaseProblem):
     # TODO: This should take a vector
     def MfRhoIDeriv(self,u):
         """
-            Derivative of :code:`MfRhoI` with respect to the model. 
+            Derivative of :code:`MfRhoI` with respect to the model.
         """
-        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho, invMat=True)(u) * self.curModel.rhoDeriv
+
+        dMfRhoI_dI = -self.MfRhoI**2
+        dMf_drho = self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u)
+        return dMfRhoI_dI * ( dMf_drho * self.curModel.rhoDeriv )
+
+class BaseEMSurvey(Survey.BaseSurvey):
+
+    def __init__(self, srcList, **kwargs):
+        # Sort these by frequency
+        self.srcList = srcList
+        Survey.BaseSurvey.__init__(self, **kwargs)
+
+    def eval(self, f):
+        """
+        Project fields to receiver locations
+
+        :param Fields u: fields object
+        :rtype: numpy.ndarray
+        :return: data
+        """
+        data = Survey.Data(self)
+        for src in self.srcList:
+            for rx in src.rxList:
+                data[src, rx] = rx.eval(src, self.mesh, f)
+        return data
+
+    def evalDeriv(self, f):
+        raise Exception('Use Receivers to project fields deriv.')

SimPEG/EM/FDEM/FieldsFDEM.py

@@ -1,3 +1,10 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from builtins import int
+from future import standard_library
+standard_library.install_aliases()
 import numpy as np
 import scipy.sparse as sp
 import SimPEG
@@ -6,11 +13,11 @@ from SimPEG.EM.Utils import omega
 from SimPEG.Utils import Zero, Identity, sdiag
 
 
-class Fields(SimPEG.Problem.Fields):
+class FieldsFDEM(SimPEG.Problem.Fields):
     """
-    
+
     Fancy Field Storage for a FDEM survey. Only one field type is stored for
-    each problem, the rest are computed. The fields obejct acts like an array and is indexed by
+    each problem, the rest are computed. The fields object acts like an array and is indexed by
 
     .. code-block:: python
 
@@ -34,57 +41,57 @@ class Fields(SimPEG.Problem.Fields):
 
     def _e(self, solution, srcList):
         """
-        Total electric field is sum of primary and secondary 
-        
+        Total electric field is sum of primary and secondary
+
         :param numpy.ndarray solution: field we solved for
         :param list srcList: list of sources
         :rtype: numpy.ndarray
         :return: total electric field
         """
-        if getattr(self, '_ePrimary', None) is None or getattr(self, '_eSecondary', None) is None: 
-            raise NotImplementedError ('Getting e from %s is not implemented' %self.knownFields.keys()[0])
+        if getattr(self, '_ePrimary', None) is None or getattr(self, '_eSecondary', None) is None:
+            raise NotImplementedError ('Getting e from %s is not implemented' %list(self.knownFields.keys())[0])
 
         return self._ePrimary(solution,srcList) + self._eSecondary(solution,srcList)
 
     def _b(self, solution, srcList):
         """
-        Total magnetic flux density is sum of primary and secondary 
-        
+        Total magnetic flux density is sum of primary and secondary
+
         :param numpy.ndarray solution: field we solved for
         :param list srcList: list of sources
         :rtype: numpy.ndarray
-        :return: total magnetic flux density 
+        :return: total magnetic flux density
         """
-        if getattr(self, '_bPrimary', None) is None or getattr(self, '_bSecondary', None) is None: 
-            raise NotImplementedError ('Getting b from %s is not implemented' %self.knownFields.keys()[0])
+        if getattr(self, '_bPrimary', None) is None or getattr(self, '_bSecondary', None) is None:
+            raise NotImplementedError ('Getting b from %s is not implemented' %list(self.knownFields.keys())[0])
 
         return self._bPrimary(solution, srcList) + self._bSecondary(solution, srcList)
 
     def _h(self, solution, srcList):
         """
-        Total magnetic field is sum of primary and secondary 
-        
+        Total magnetic field is sum of primary and secondary
+
         :param numpy.ndarray solution: field we solved for
         :param list srcList: list of sources
         :rtype: numpy.ndarray
         :return: total magnetic field
         """
-        if getattr(self, '_hPrimary', None) is None or getattr(self, '_hSecondary', None) is None: 
-            raise NotImplementedError ('Getting h from %s is not implemented' %self.knownFields.keys()[0])
+        if getattr(self, '_hPrimary', None) is None or getattr(self, '_hSecondary', None) is None:
+            raise NotImplementedError ('Getting h from %s is not implemented' %list(self.knownFields.keys())[0])
 
         return self._hPrimary(solution, srcList) + self._hSecondary(solution, srcList)
 
     def _j(self, solution, srcList):
         """
-        Total current density is sum of primary and secondary 
-        
+        Total current density is sum of primary and secondary
+
         :param numpy.ndarray solution: field we solved for
         :param list srcList: list of sources
         :rtype: numpy.ndarray
-        :return: total current density 
+        :return: total current density
         """
-        if getattr(self, '_jPrimary', None) is None or getattr(self, '_jSecondary', None) is None: 
-            raise NotImplementedError ('Getting j from %s is not implemented' %self.knownFields.keys()[0])
+        if getattr(self, '_jPrimary', None) is None or getattr(self, '_jSecondary', None) is None:
+            raise NotImplementedError ('Getting j from %s is not implemented' %list(self.knownFields.keys())[0])
 
         return self._jPrimary(solution, srcList) + self._jSecondary(solution, srcList)
 
@@ -92,15 +99,15 @@ class Fields(SimPEG.Problem.Fields):
         """
         Total derivative of e with respect to the inversion model. Returns :math:`d\mathbf{e}/d\mathbf{m}` for forward and (:math:`d\mathbf{e}/d\mathbf{u}`, :math:`d\mathb{u}/d\mathbf{m}`) for the adjoint
 
-        :param Src src: sorce
+        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
         :param numpy.ndarray du_dm_v: derivative of the solution vector with respect to the model times a vector (is None for adjoint)
         :param numpy.ndarray v: vector to take sensitivity product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: derivative times a vector (or tuple for adjoint)
         """
-        if getattr(self, '_eDeriv_u', None) is None or getattr(self, '_eDeriv_m', None) is None: 
-            raise NotImplementedError ('Getting eDerivs from %s is not implemented' %self.knownFields.keys()[0])
+        if getattr(self, '_eDeriv_u', None) is None or getattr(self, '_eDeriv_m', None) is None:
+            raise NotImplementedError ('Getting eDerivs from %s is not implemented' %list(self.knownFields.keys())[0])
 
         if adjoint:
             return self._eDeriv_u(src, v, adjoint), self._eDeriv_m(src, v, adjoint)
@@ -110,35 +117,35 @@ class Fields(SimPEG.Problem.Fields):
         """
         Total derivative of b with respect to the inversion model. Returns :math:`d\mathbf{b}/d\mathbf{m}` for forward and (:math:`d\mathbf{b}/d\mathbf{u}`, :math:`d\mathb{u}/d\mathbf{m}`) for the adjoint
 
-        :param Src src: sorce
+        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
         :param numpy.ndarray du_dm_v: derivative of the solution vector with respect to the model times a vector (is None for adjoint)
         :param numpy.ndarray v: vector to take sensitivity product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: derivative times a vector (or tuple for adjoint)
         """
-        if getattr(self, '_bDeriv_u', None) is None or getattr(self, '_bDeriv_m', None) is None: 
-            raise NotImplementedError ('Getting bDerivs from %s is not implemented' %self.knownFields.keys()[0])
+        if getattr(self, '_bDeriv_u', None) is None or getattr(self, '_bDeriv_m', None) is None:
+            raise NotImplementedError ('Getting bDerivs from %s is not implemented' %list(self.knownFields.keys())[0])
 
         if adjoint:
             return self._bDeriv_u(src, v, adjoint), self._bDeriv_m(src, v, adjoint)
-        return np.array(self._bDeriv_u(src, du_dm_v, adjoint) + self._bDeriv_m(src, v, adjoint), dtype = complex) 
+        return np.array(self._bDeriv_u(src, du_dm_v, adjoint) + self._bDeriv_m(src, v, adjoint), dtype = complex)
 
     def _hDeriv(self, src, du_dm_v, v, adjoint = False):
         """
         Total derivative of h with respect to the inversion model. Returns :math:`d\mathbf{h}/d\mathbf{m}` for forward and (:math:`d\mathbf{h}/d\mathbf{u}`, :math:`d\mathb{u}/d\mathbf{m}`) for the adjoint
 
-        :param Src src: sorce
+        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
         :param numpy.ndarray du_dm_v: derivative of the solution vector with respect to the model times a vector (is None for adjoint)
         :param numpy.ndarray v: vector to take sensitivity product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: derivative times a vector (or tuple for adjoint)
         """
-        if getattr(self, '_hDeriv_u', None) is None or getattr(self, '_hDeriv_m', None) is None: 
-            raise NotImplementedError ('Getting hDerivs from %s is not implemented' %self.knownFields.keys()[0])
+        if getattr(self, '_hDeriv_u', None) is None or getattr(self, '_hDeriv_m', None) is None:
+            raise NotImplementedError ('Getting hDerivs from %s is not implemented' %list(self.knownFields.keys())[0])
 
-        if adjoint: 
+        if adjoint:
             return self._hDeriv_u(src, v, adjoint), self._hDeriv_m(src, v, adjoint)
         return np.array(self._hDeriv_u(src, du_dm_v, adjoint) + self._hDeriv_m(src, v, adjoint), dtype = complex)
 
@@ -146,26 +153,26 @@ class Fields(SimPEG.Problem.Fields):
         """
         Total derivative of j with respect to the inversion model. Returns :math:`d\mathbf{j}/d\mathbf{m}` for forward and (:math:`d\mathbf{j}/d\mathbf{u}`, :math:`d\mathb{u}/d\mathbf{m}`) for the adjoint
 
-        :param Src src: sorce
+        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
         :param numpy.ndarray du_dm_v: derivative of the solution vector with respect to the model times a vector (is None for adjoint)
         :param numpy.ndarray v: vector to take sensitivity product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: derivative times a vector (or tuple for adjoint)
         """
-        if getattr(self, '_jDeriv_u', None) is None or getattr(self, '_jDeriv_m', None) is None: 
-            raise NotImplementedError ('Getting jDerivs from %s is not implemented' %self.knownFields.keys()[0])
+        if getattr(self, '_jDeriv_u', None) is None or getattr(self, '_jDeriv_m', None) is None:
+            raise NotImplementedError ('Getting jDerivs from %s is not implemented' %list(self.knownFields.keys())[0])
 
         if adjoint:
             return self._jDeriv_u(src, v, adjoint), self._jDeriv_m(src, v, adjoint)
         return np.array(self._jDeriv_u(src, du_dm_v, adjoint) + self._jDeriv_m(src, v, adjoint), dtype = complex)
 
-class Fields_e(Fields):
+class Fields3D_e(FieldsFDEM):
     """
-    Fields object for Problem_e. 
+    Fields object for Problem3D_e.
 
-    :param Mesh mesh: mesh
-    :param Survey survey: survey 
+    :param BaseMesh mesh: mesh
+    :param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
     """
 
     knownFields = {'eSolution':'E'}
@@ -180,9 +187,6 @@ class Fields_e(Fields):
                     'h' : ['eSolution','CCV','_h'],
                   }
 
-    def __init__(self, mesh, survey, **kwargs):
-        Fields.__init__(self,mesh,survey,**kwargs)
-
     def startup(self):
         self.prob = self.survey.prob
         self._edgeCurl = self.survey.prob.mesh.edgeCurl
@@ -233,9 +237,9 @@ class Fields_e(Fields):
 
     def _eDeriv_u(self, src, v, adjoint = False):
         """
-        Partial derivative of the total electric field with respect to the thing we 
+        Partial derivative of the total electric field with respect to the thing we
         solved for.
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -247,8 +251,8 @@ class Fields_e(Fields):
 
     def _eDeriv_m(self, src, v, adjoint = False):
         """
-        Partial derivative of the total electric field with respect to the inversion model. Here, we assume that the primary does not depend on the model. Note that this also includes derivative contributions from the sources. 
-        
+        Partial derivative of the total electric field with respect to the inversion model. Here, we assume that the primary does not depend on the model. Note that this also includes derivative contributions from the sources.
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -288,15 +292,15 @@ class Fields_e(Fields):
         C = self._edgeCurl
         b = (C * eSolution)
         for i, src in enumerate(srcList):
-            b[:,i] *= - 1./(1j*omega(src.freq))
-            S_m, _ = src.eval(self.prob)
-            b[:,i] = b[:,i]+ 1./(1j*omega(src.freq)) * S_m
+            b[:,i] *= -1./(1j*omega(src.freq))
+            s_m, _ = src.eval(self.prob)
+            b[:,i] = b[:,i]+ 1./(1j*omega(src.freq)) * s_m
         return b
 
     def _bDeriv_u(self, src, du_dm_v, adjoint = False):
         """
         Derivative of the magnetic flux density with respect to the thing we solved for
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
@@ -312,8 +316,8 @@ class Fields_e(Fields):
 
     def _bDeriv_m(self, src, v, adjoint = False):
         """
-        Derivative of the magnetic flux density with respect to the inversion model. 
-        
+        Derivative of the magnetic flux density with respect to the inversion model.
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -321,8 +325,8 @@ class Fields_e(Fields):
         :return: product of the magnetic flux density derivative with respect to the inversion model with a vector
         """
 
-        S_mDeriv, _ = src.evalDeriv(self.prob, v, adjoint)
-        return 1./(1j * omega(src.freq)) * S_mDeriv
+        s_mDeriv, _ = src.evalDeriv(self.prob, v, adjoint)
+        return 1./(1j * omega(src.freq)) * s_mDeriv
 
     def _j(self,  eSolution, srcList):
         """
@@ -341,25 +345,25 @@ class Fields_e(Fields):
     def _jDeriv_u(self, src, du_dm_v, adjoint = False):
         """
         Derivative of the current density with respect to the thing we solved for
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: product of the derivative of the current density with respect to the field we solved for with a vector
         """
-        n = int(self._aveE2CCV.shape[0] / self._nC) # number of components (instead of checking if cyl or not)
+        n = int(self._aveE2CCV.shape[0] // self._nC) # number of components (instead of checking if cyl or not)
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
 
-        if adjoint: 
+        if adjoint:
             return  self._eDeriv_u(src, self._MeSigma.T * (self._aveE2CCV.T * (VI.T * du_dm_v) ), adjoint = adjoint)
         return VI * (self._aveE2CCV * (self._MeSigma * (self._eDeriv_u(src, du_dm_v, adjoint=adjoint) ) ) )
-        
+
 
     def _jDeriv_m(self, src, v, adjoint = False):
         """
-        Derivative of the current density with respect to the inversion model. 
-        
+        Derivative of the current density with respect to the inversion model.
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -373,7 +377,7 @@ class Fields_e(Fields):
         if adjoint:
             return self._MeSigmaDeriv(e).T * (self._aveE2CCV.T * (VI.T * v)) + self._eDeriv_m(src, self._aveE2CCV.T * (VI.T * v), adjoint=adjoint)
         return VI * (self._aveE2CCV * ( self._eDeriv_m(src, v, adjoint=adjoint) + self._MeSigmaDeriv(e) * v))
-        
+
 
 
     def _h(self, eSolution, srcList):
@@ -385,22 +389,22 @@ class Fields_e(Fields):
         :rtype: numpy.ndarray
         :return: magnetic field
         """
-        n = int(self._aveF2CCV.shape[0] / self._nC) # Number of Components
-        VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
+        n = int(self._aveF2CCV.shape[0] // self._nC) # Number of Components
+        VI = sdiag(np.kron(np.ones(n), 1. // self.prob.mesh.vol))
 
         return VI * (self._aveF2CCV * (self._MfMui * self._b(eSolution, srcList)))
 
     def _hDeriv_u(self, src, du_dm_v, adjoint = False):
         """
         Derivative of the magnetic field with respect to the thing we solved for
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: product of the derivative of the magnetic field with respect to the field we solved for with a vector
         """
-        n = int(self._aveF2CCV.shape[0] / self._nC) # Number of Components
+        n = int(self._aveF2CCV.shape[0] // self._nC) # Number of Components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
         if adjoint:
             v =  self._MfMui.T * (self._aveF2CCV.T  * (VI.T * du_dm_v))
@@ -409,15 +413,15 @@ class Fields_e(Fields):
 
     def _hDeriv_m(self, src, v, adjoint = False):
         """
-        Derivative of the magnetic field with respect to the inversion model. 
-        
+        Derivative of the magnetic field with respect to the inversion model.
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: product of the magnetic field derivative with respect to the inversion model with a vector
         """
-        n = int(self._aveF2CCV.shape[0] / self._nC) # Number of Components
+        n = int(self._aveF2CCV.shape[0] // self._nC) # Number of Components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
         if adjoint:
             v =  self._MfMui.T * (self._aveF2CCV.T  * (VI.T * v))
@@ -426,12 +430,12 @@ class Fields_e(Fields):
 
 
 
-class Fields_b(Fields):
+class Fields3D_b(FieldsFDEM):
     """
-    Fields object for Problem_b. 
+    Fields object for Problem3D_b.
 
-    :param Mesh mesh: mesh
-    :param Survey survey: survey 
+    :param BaseMesh mesh: mesh
+    :param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
     """
 
     knownFields = {'bSolution':'F'}
@@ -446,9 +450,6 @@ class Fields_b(Fields):
                     'h' : ['bSolution','CCV','_h'],
                   }
 
-    def __init__(self,mesh,survey,**kwargs):
-        Fields.__init__(self,mesh,survey,**kwargs)
-
     def startup(self):
         self.prob = self.survey.prob
         self._edgeCurl = self.survey.prob.mesh.edgeCurl
@@ -506,9 +507,9 @@ class Fields_b(Fields):
 
     def _bDeriv_u(self, src, du_dm_v, adjoint=False):
         """
-        Partial derivative of the total magnetic flux density with respect to the thing we 
+        Partial derivative of the total magnetic flux density with respect to the thing we
         solved for.
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
@@ -520,8 +521,8 @@ class Fields_b(Fields):
 
     def _bDeriv_m(self, src, v, adjoint=False):
         """
-        Partial derivative of the total magnetic flux density with respect to the inversion model. Here, we assume that the primary does not depend on the model. Note that this also includes derivative contributions from the sources. 
-        
+        Partial derivative of the total magnetic flux density with respect to the inversion model. Here, we assume that the primary does not depend on the model. Note that this also includes derivative contributions from the sources.
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -560,15 +561,15 @@ class Fields_b(Fields):
 
         e = ( self._edgeCurl.T * ( self._MfMui * bSolution))
         for i,src in enumerate(srcList):
-            _,S_e = src.eval(self.prob)
-            e[:,i] = e[:,i] + - S_e
+            _,s_e = src.eval(self.prob)
+            e[:,i] = e[:,i] + - s_e
 
         return self._MeSigmaI * e
 
     def _eDeriv_u(self, src, du_dm_v, adjoint=False):
         """
         Derivative of the electric field with respect to the thing we solved for
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -583,8 +584,8 @@ class Fields_b(Fields):
 
     def _eDeriv_m(self, src, v, adjoint=False):
         """
-        Derivative of the electric field with respect to the inversion model 
-        
+        Derivative of the electric field with respect to the inversion model
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -593,15 +594,15 @@ class Fields_b(Fields):
         """
 
         bSolution = Utils.mkvc(self[src, 'bSolution'])
-        _,S_e = src.eval(self.prob)
+        _,s_e = src.eval(self.prob)
 
-        w = -S_e + self._edgeCurl.T * (self._MfMui * bSolution)
-        _, S_eDeriv = src.evalDeriv(self.prob, v, adjoint)
+        w = -s_e + self._edgeCurl.T * (self._MfMui * bSolution)
+        _, s_eDeriv = src.evalDeriv(self.prob, v, adjoint)
 
 
         if adjoint:
-            return self._MeSigmaIDeriv(w).T * v - self._MeSigmaI.T * S_eDeriv
-        return  self._MeSigmaIDeriv(w) * v - self._MeSigmaI * S_eDeriv
+            return self._MeSigmaIDeriv(w).T * v - self._MeSigmaI.T * s_eDeriv
+        return  self._MeSigmaIDeriv(w) * v - self._MeSigmaI * s_eDeriv
 
     def _j(self, bSolution, srcList):
         """
@@ -613,24 +614,24 @@ class Fields_b(Fields):
         :return: primary current density
         """
 
-        n = int(self._aveE2CCV.shape[0] / self._nC) # number of components
+        n = int(self._aveE2CCV.shape[0] // self._nC) # number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
 
         return VI * (self._aveE2CCV * ( self._MeSigma * self._e(bSolution,srcList ) ) )
-        
+
 
     def _jDeriv_u(self, src, du_dm_v, adjoint=False):
         """
-        Partial derivative of the current density with respect to the thing we 
+        Partial derivative of the current density with respect to the thing we
         solved for.
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: product of the derivative of the current density with respect to the field we solved for with a vector
         """
-        n = int(self._aveE2CCV.shape[0] / self._nC) # number of components
+        n = int(self._aveE2CCV.shape[0] // self._nC) # number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
         if adjoint:
             return self._MfMui.T * ( self._edgeCurl * ( self._aveE2CCV.T * (VI.T * du_dm_v) ) )
@@ -639,8 +640,8 @@ class Fields_b(Fields):
 
     def _jDeriv_m(self, src, v, adjoint=False):
         """
-        Derivative of the current density with respect to the inversion model 
-        
+        Derivative of the current density with respect to the inversion model
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -658,22 +659,22 @@ class Fields_b(Fields):
         :rtype: numpy.ndarray
         :return: magnetic field
         """
-        n = int(self._aveF2CCV.shape[0] / self._nC) #number of components
+        n = int(self._aveF2CCV.shape[0] // self._nC) #number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
         return VI * (self._aveF2CCV * (self._MfMui * self._b(bSolution, srcList)))
 
     def _hDeriv_u(self, src, du_dm_v, adjoint=False):
         """
-        Partial derivative of the magnetic field with respect to the thing we 
+        Partial derivative of the magnetic field with respect to the thing we
         solved for.
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: product of the derivative of the magnetic field with respect to the field we solved for with a vector
         """
-        n = int(self._aveF2CCV.shape[0] / self._nC) #number of components
+        n = int(self._aveF2CCV.shape[0] // self._nC) #number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
 
         if adjoint:
@@ -682,8 +683,8 @@ class Fields_b(Fields):
 
     def _hDeriv_m(self, src, v, adjoint=False):
         """
-        Derivative of the magnetic field with respect to the inversion model 
-        
+        Derivative of the magnetic field with respect to the inversion model
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -693,12 +694,12 @@ class Fields_b(Fields):
         return Zero()
 
 
-class Fields_j(Fields):
+class Fields3D_j(FieldsFDEM):
     """
-    Fields object for Problem_j. 
+    Fields object for Problem3D_j.
 
-    :param Mesh mesh: mesh
-    :param Survey survey: survey 
+    :param BaseMesh mesh: mesh
+    :param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
     """
 
     knownFields = {'jSolution':'F'}
@@ -713,9 +714,6 @@ class Fields_j(Fields):
                     'b' : ['jSolution','CCV','_b'],
                   }
 
-    def __init__(self,mesh,survey,**kwargs):
-        Fields.__init__(self,mesh,survey,**kwargs)
-
     def startup(self):
         self.prob = self.survey.prob
         self._edgeCurl = self.survey.prob.mesh.edgeCurl
@@ -769,12 +767,12 @@ class Fields_j(Fields):
 
     def _j(self, jSolution, srcList):
         """
-        Total current density is sum of primary and secondary 
-        
+        Total current density is sum of primary and secondary
+
         :param numpy.ndarray jSolution: field we solved for
         :param list srcList: list of sources
         :rtype: numpy.ndarray
-        :return: total current density 
+        :return: total current density
         """
 
         return self._jPrimary(jSolution, srcList) + self._jSecondary(jSolution, srcList)
@@ -782,9 +780,9 @@ class Fields_j(Fields):
 
     def _jDeriv_u(self, src, du_dm_v, adjoint=False):
         """
-        Partial derivative of the total current density with respect to the thing we 
+        Partial derivative of the total current density with respect to the thing we
         solved for.
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -797,8 +795,8 @@ class Fields_j(Fields):
 
     def _jDeriv_m(self, src, v, adjoint=False):
         """
-        Partial derivative of the total current density with respect to the inversion model. Here, we assume that the primary does not depend on the model. Note that this also includes derivative contributions from the sources. 
-        
+        Partial derivative of the total current density with respect to the inversion model. Here, we assume that the primary does not depend on the model. Note that this also includes derivative contributions from the sources.
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -837,15 +835,15 @@ class Fields_j(Fields):
         h = (self._edgeCurl.T * (self._MfRho * jSolution) )
         for i, src in enumerate(srcList):
             h[:,i] *= -1./(1j*omega(src.freq))
-            S_m,_ = src.eval(self.prob)
-            h[:,i] = h[:,i] + 1./(1j*omega(src.freq)) * (S_m)
+            s_m,_ = src.eval(self.prob)
+            h[:,i] = h[:,i] + 1./(1j*omega(src.freq)) * (s_m)
         return self._MeMuI * h
 
 
     def _hDeriv_u(self, src, du_dm_v, adjoint=False):
         """
         Derivative of the magnetic field with respect to the thing we solved for
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
@@ -856,13 +854,13 @@ class Fields_j(Fields):
         if adjoint:
             return  -1./(1j*omega(src.freq)) * self._MfRho.T * (self._edgeCurl * ( self._MeMuI.T * du_dm_v))
         return  -1./(1j*omega(src.freq)) * self._MeMuI * (self._edgeCurl.T * (self._MfRho * du_dm_v) )
-        
+
 
 
     def _hDeriv_m(self, src, v, adjoint=False):
         """
-        Derivative of the magnetic field with respect to the inversion model 
-        
+        Derivative of the magnetic field with respect to the inversion model
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -875,19 +873,19 @@ class Fields_j(Fields):
         C = self._edgeCurl
         MfRho = self._MfRho
         MfRhoDeriv = self._MfRhoDeriv
-        S_mDeriv,_ = src.evalDeriv(self.prob, adjoint = adjoint)
+        s_mDeriv,_ = src.evalDeriv(self.prob, adjoint = adjoint)
 
         if not adjoint:
             hDeriv_m =  -1./(1j*omega(src.freq)) * MeMuI * (C.T * (MfRhoDeriv(jSolution)*v ) )
-            S_mDeriv = S_mDeriv(v)
-            hDeriv_m = hDeriv_m + 1./(1j*omega(src.freq)) * MeMuI * ( S_mDeriv)
+            s_mDeriv = s_mDeriv(v)
+            hDeriv_m = hDeriv_m + 1./(1j*omega(src.freq)) * MeMuI * ( s_mDeriv)
 
         elif adjoint:
             hDeriv_m =  -1./(1j*omega(src.freq)) * MfRhoDeriv(jSolution).T * ( C * (MeMuI.T * v ) )
 
-            S_mDeriv = S_mDeriv(MeMuI.T * v)
-            hDeriv_m = hDeriv_m + 1./(1j*omega(src.freq)) * S_mDeriv
-        
+            s_mDeriv = s_mDeriv(MeMuI.T * v)
+            hDeriv_m = hDeriv_m + 1./(1j*omega(src.freq)) * s_mDeriv
+
         return hDeriv_m
 
     def _e(self, jSolution, srcList):
@@ -899,21 +897,21 @@ class Fields_j(Fields):
         :rtype: numpy.ndarray
         :return: electric field
         """
-        n = int(self._aveF2CCV.shape[0] / self._nC) # number of components
+        n = int(self._aveF2CCV.shape[0] // self._nC) # number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
-        return VI * (self._aveF2CCV * (self._MfRho *  self._j(jSolution, srcList))) 
+        return VI * (self._aveF2CCV * (self._MfRho *  self._j(jSolution, srcList)))
 
     def _eDeriv_u(self, src, du_dm_v, adjoint=False):
         """
         Derivative of the electric field with respect to the thing we solved for
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: product of the derivative of the electric field with respect to the field we solved for with a vector
         """
-        n = int(self._aveF2CCV.shape[0] / self._nC) # number of components
+        n = int(self._aveF2CCV.shape[0] // self._nC) # number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
         if adjoint:
             return self._MfRho.T * ( self._aveF2CCV.T * ( VI.T * du_dm_v ) )
@@ -921,8 +919,8 @@ class Fields_j(Fields):
 
     def _eDeriv_m(self, src, v, adjoint=False):
         """
-        Derivative of the electric field with respect to the inversion model 
-        
+        Derivative of the electric field with respect to the inversion model
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -930,7 +928,7 @@ class Fields_j(Fields):
         :return: product of the derivative of the electric field with respect to the model with a vector
         """
         jSolution = Utils.mkvc(self[src,'jSolution'])
-        n = int(self._aveF2CCV.shape[0] / self._nC) # number of components
+        n = int(self._aveF2CCV.shape[0] // self._nC) # number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
         if adjoint:
             return self._MfRhoDeriv(jSolution).T * ( self._aveF2CCV.T * ( VI.T * v ) )
@@ -943,24 +941,24 @@ class Fields_j(Fields):
         :param numpy.ndarray hSolution: field we solved for
         :param list srcList: list of sources
         :rtype: numpy.ndarray
-        :return: secondary magnetic flux density 
+        :return: secondary magnetic flux density
         """
-        n = int(self._aveE2CCV.shape[0] / self._nC) # number of components
+        n = int(self._aveE2CCV.shape[0] // self._nC) # number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
 
-        return VI * (self._aveE2CCV * ( self._MeMu * self._h(jSolution,srcList)) ) 
+        return VI * (self._aveE2CCV * ( self._MeMu * self._h(jSolution,srcList)) )
 
     def _bDeriv_u(self, src, du_dm_v, adjoint=False):
         """
         Derivative of the magnetic flux density with respect to the thing we solved for
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: product of the derivative of the magnetic flux density with respect to the field we solved for with a vector
         """
-        n = int(self._aveF2CCV.shape[0] / self._nC) # number of components
+        n = int(self._aveF2CCV.shape[0] // self._nC) # number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
 
         if adjoint:
@@ -969,8 +967,8 @@ class Fields_j(Fields):
 
     def _bDeriv_m(self, src, v, adjoint=False):
         """
-        Derivative of the magnetic flux density with respect to the inversion model 
-        
+        Derivative of the magnetic flux density with respect to the inversion model
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -978,22 +976,22 @@ class Fields_j(Fields):
         :return: product of the derivative of the magnetic flux density with respect to the model with a vector
         """
         jSolution = self[src,'jSolution']
-        n = int(self._aveE2CCV.shape[0] / self._nC) # number of components
+        n = int(self._aveE2CCV.shape[0] // self._nC) # number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
-        S_mDeriv,_ = src.evalDeriv(self.prob, adjoint = adjoint)
+        s_mDeriv,_ = src.evalDeriv(self.prob, adjoint = adjoint)
 
         if adjoint:
             v = self._aveE2CCV.T * ( VI.T * v)
-            return 1./(1j * omega(src.freq)) * ( S_mDeriv(v) - self._MfRhoDeriv(jSolution).T * (self._edgeCurl * v ))
-        return 1./(1j * omega(src.freq)) * VI * (self._aveE2CCV * ( S_mDeriv(v) - self._edgeCurl.T * ( self._MfRhoDeriv(jSolution) * v ) ) )
+            return 1./(1j * omega(src.freq)) * ( s_mDeriv(v) - self._MfRhoDeriv(jSolution).T * (self._edgeCurl * v ))
+        return 1./(1j * omega(src.freq)) * VI * (self._aveE2CCV * ( s_mDeriv(v) - self._edgeCurl.T * ( self._MfRhoDeriv(jSolution) * v ) ) )
 
 
-class Fields_h(Fields):
+class Fields3D_h(FieldsFDEM):
     """
-    Fields object for Problem_h. 
+    Fields object for Problem3D_h.
 
-    :param Mesh mesh: mesh
-    :param Survey survey: survey 
+    :param BaseMesh mesh: mesh
+    :param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
     """
 
     knownFields = {'hSolution':'E'}
@@ -1008,9 +1006,6 @@ class Fields_h(Fields):
                     'b' : ['hSolution','CCV','_b'],
                   }
 
-    def __init__(self,mesh,survey,**kwargs):
-        Fields.__init__(self,mesh,survey,**kwargs)
-
     def startup(self):
         self.prob = self.survey.prob
         self._edgeCurl = self.survey.prob.mesh.edgeCurl
@@ -1065,9 +1060,9 @@ class Fields_h(Fields):
 
     def _hDeriv_u(self, src, du_dm_v, adjoint=False):
         """
-        Partial derivative of the total magnetic field with respect to the thing we 
+        Partial derivative of the total magnetic field with respect to the thing we
         solved for.
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
@@ -1079,8 +1074,8 @@ class Fields_h(Fields):
 
     def _hDeriv_m(self, src, v, adjoint=False):
         """
-        Partial derivative of the total magnetic field with respect to the inversion model. Here, we assume that the primary does not depend on the model. Note that this also includes derivative contributions from the sources. 
-        
+        Partial derivative of the total magnetic field with respect to the inversion model. Here, we assume that the primary does not depend on the model. Note that this also includes derivative contributions from the sources.
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -1119,14 +1114,14 @@ class Fields_h(Fields):
 
         j = self._edgeCurl*hSolution
         for i, src in enumerate(srcList):
-            _,S_e = src.eval(self.prob)
-            j[:,i] = j[:,i]+ -S_e
+            _,s_e = src.eval(self.prob)
+            j[:,i] = j[:,i]+ -s_e
         return j
 
     def _jDeriv_u(self, src, du_dm_v, adjoint=False):
         """
         Derivative of the current density with respect to the thing we solved for
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
@@ -1142,8 +1137,8 @@ class Fields_h(Fields):
 
     def _jDeriv_m(self, src, v, adjoint=False):
         """
-        Derivative of the current density with respect to the inversion model. 
-        
+        Derivative of the current density with respect to the inversion model.
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -1151,9 +1146,9 @@ class Fields_h(Fields):
         :return: product of the current density derivative with respect to the inversion model with a vector
         """
 
-        _,S_eDeriv = src.evalDeriv(self.prob, v, adjoint)
-        return -S_eDeriv
-    
+        _,s_eDeriv = src.evalDeriv(self.prob, v, adjoint)
+        return -s_eDeriv
+
     def _e(self, hSolution, srcList):
         """
         Electric field from hSolution
@@ -1163,30 +1158,30 @@ class Fields_h(Fields):
         :rtype: numpy.ndarray
         :return: electric field
         """
-        n = int(self._aveF2CCV.shape[0] / self._nC) #number of components
+        n = int(self._aveF2CCV.shape[0] // self._nC) #number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
-        return VI * (self._aveF2CCV * (self._MfRho *  self._j(hSolution, srcList))) 
+        return VI * (self._aveF2CCV * (self._MfRho *  self._j(hSolution, srcList)))
 
     def _eDeriv_u(self, src, du_dm_v, adjoint=False):
         """
         Derivative of the electric field with respect to the thing we solved for
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: product of the derivative of the electric field with respect to the field we solved for with a vector
         """
-        n = int(self._aveF2CCV.shape[0] / self._nC) #number of components
+        n = int(self._aveF2CCV.shape[0] // self._nC) #number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
         if adjoint:
             return self._edgeCurl.T * ( self._MfRho.T * ( self._aveF2CCV.T * ( VI.T * du_dm_v ) ) )
-        return VI * (self._aveF2CCV * (self._MfRho *  self._edgeCurl * du_dm_v )) 
+        return VI * (self._aveF2CCV * (self._MfRho *  self._edgeCurl * du_dm_v ))
 
     def _eDeriv_m(self, src, v, adjoint=False):
         """
-        Derivative of the electric field with respect to the inversion model. 
-        
+        Derivative of the electric field with respect to the inversion model.
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
@@ -1194,9 +1189,9 @@ class Fields_h(Fields):
         :return: product of the electric field derivative with respect to the inversion model with a vector
         """
         hSolution = Utils.mkvc(self[src,'hSolution'])
-        n = int(self._aveF2CCV.shape[0] / self._nC) #number of components
+        n = int(self._aveF2CCV.shape[0] // self._nC) #number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
-        if adjoint: 
+        if adjoint:
             return ( self._MfRhoDeriv(self._edgeCurl * hSolution).T * ( self._aveF2CCV.T * (VI.T * v) ) )
         return VI * (self._aveF2CCV * (self._MfRhoDeriv(self._edgeCurl * hSolution) * v ))
 
@@ -1207,10 +1202,10 @@ class Fields_h(Fields):
         :param numpy.ndarray hSolution: field we solved for
         :param list srcList: list of sources
         :rtype: numpy.ndarray
-        :return: magnetic flux density 
+        :return: magnetic flux density
         """
         h = self._h(hSolution, srcList)
-        n = int(self._aveE2CCV.shape[0] / self._nC) #number of components 
+        n = int(self._aveE2CCV.shape[0] // self._nC) #number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
 
         return VI * (self._aveE2CCV * (self._MeMu * h))
@@ -1218,14 +1213,14 @@ class Fields_h(Fields):
     def _bDeriv_u(self, src, du_dm_v, adjoint=False):
         """
         Derivative of the magnetic flux density with respect to the thing we solved for
-        
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray du_dm_v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: product of the derivative of the magnetic flux density with respect to the field we solved for with a vector
         """
-        n = int(self._aveE2CCV.shape[0] / self._nC) #number of components 
+        n = int(self._aveE2CCV.shape[0] // self._nC) #number of components
         VI = sdiag(np.kron(np.ones(n), 1./self.prob.mesh.vol))
         if adjoint:
             return self._MeMu.T * (self._aveE2CCV.T * ( VI.T * du_dm_v ))
@@ -1233,8 +1228,8 @@ class Fields_h(Fields):
 
     def _bDeriv_m(self, src, v, adjoint=False):
         """
-        Derivative of the magnetic flux density with respect to the inversion model. 
-        
+        Derivative of the magnetic flux density with respect to the inversion model.
+
         :param SimPEG.EM.FDEM.Src src: source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?

SimPEG/EM/FDEM/ProblemFDEM.py

@@ -1,7 +1,13 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import Problem, Utils, np, sp, Solver as SimpegSolver
 from scipy.constants import mu_0
-from SurveyFDEM import Survey as SurveyFDEM
-from FieldsFDEM import Fields, Fields_e, Fields_b, Fields_h, Fields_j
+from .SurveyFDEM import Survey as SurveyFDEM
+from .FieldsFDEM import FieldsFDEM, Fields3D_e, Fields3D_b, Fields3D_h, Fields3D_j
 from SimPEG.EM.Base import BaseEMProblem
 from SimPEG.EM.Utils import omega
 
@@ -17,10 +23,10 @@ class BaseFDEMProblem(BaseEMProblem):
             \mathbf{C} \mathbf{e} + i \omega \mathbf{b} = \mathbf{s_m} \\\\
             {\mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f} \mathbf{b} - \mathbf{M_{\sigma}^e} \mathbf{e} = \mathbf{s_e}}
 
-        if using the E-B formulation (:code:`Problem_e`
-        or :code:`Problem_b`). Note that in this case, :math:`\mathbf{s_e}` is an integrated quantity. 
+        if using the E-B formulation (:code:`Problem3D_e`
+        or :code:`Problem3D_b`). Note that in this case, :math:`\mathbf{s_e}` is an integrated quantity.
 
-        If we write Maxwell's equations in terms of 
+        If we write Maxwell's equations in terms of
         \\\(\\\mathbf{h}\\\) and current density \\\(\\\mathbf{j}\\\)
 
         .. math ::
@@ -28,84 +34,85 @@ class BaseFDEMProblem(BaseEMProblem):
             \mathbf{C}^{\\top} \mathbf{M_{\\rho}^f} \mathbf{j} + i \omega \mathbf{M_{\mu}^e} \mathbf{h} = \mathbf{s_m} \\\\
             \mathbf{C} \mathbf{h} - \mathbf{j} = \mathbf{s_e}
 
-        if using the H-J formulation (:code:`Problem_j` or :code:`Problem_h`). Note that here, :math:`\mathbf{s_m}` is an integrated quantity. 
+        if using the H-J formulation (:code:`Problem3D_j` or :code:`Problem3D_h`). Note that here, :math:`\mathbf{s_m}` is an integrated quantity.
 
         The problem performs the elimination so that we are solving the system for \\\(\\\mathbf{e},\\\mathbf{b},\\\mathbf{j} \\\) or \\\(\\\mathbf{h}\\\)
+
     """
 
     surveyPair = SurveyFDEM
-    fieldsPair = Fields
+    fieldsPair = FieldsFDEM
 
-    def fields(self, m=None):
+    def fields(self, m):
         """
         Solve the forward problem for the fields.
-        
+
         :param numpy.array m: inversion model (nP,)
         :rtype numpy.array:
-        :return F: forward solution
+        :return f: forward solution
         """
 
         self.curModel = m
-        F = self.fieldsPair(self.mesh, self.survey)
+        f = self.fieldsPair(self.mesh, self.survey)
 
         for freq in self.survey.freqs:
             A = self.getA(freq)
             rhs = self.getRHS(freq)
             Ainv = self.Solver(A, **self.solverOpts)
-            sol = Ainv * rhs
+            u = Ainv * rhs
             Srcs = self.survey.getSrcByFreq(freq)
-            F[Srcs, self._solutionType] = sol
+            f[Srcs, self._solutionType] = u
             Ainv.clean()
-        return F
+        return f
 
-    def Jvec(self, m, v, u=None):
+    def Jvec(self, m, v, f=None):
         """
         Sensitivity times a vector.
 
         :param numpy.array m: inversion model (nP,)
         :param numpy.array v: vector which we take sensitivity product with (nP,)
-        :param SimPEG.EM.FDEM.Fields u: fields object 
+        :param SimPEG.EM.FDEM.FieldsFDEM.FieldsFDEM u: fields object
         :rtype numpy.array:
-        :return: Jv (ndata,) 
+        :return: Jv (ndata,)
         """
 
-        if u is None:
-           u = self.fields(m)
+        if f is None:
+           f = self.fields(m)
 
         self.curModel = m
 
         Jv = self.dataPair(self.survey)
 
         for freq in self.survey.freqs:
-            A = self.getA(freq) 
-            Ainv = self.Solver(A, **self.solverOpts)
+            A = self.getA(freq)
+            Ainv = self.Solver(A, **self.solverOpts) # create the concept of Ainv (actually a solve)
 
             for src in self.survey.getSrcByFreq(freq):
-                u_src = u[src, self._solutionType]
+                u_src = f[src, self._solutionType]
                 dA_dm_v = self.getADeriv(freq, u_src, v)
-                dRHS_dm_v = self.getRHSDeriv(freq, src, v) 
+                dRHS_dm_v = self.getRHSDeriv(freq, src, v)
                 du_dm_v = Ainv * ( - dA_dm_v + dRHS_dm_v )
-                
+
                 for rx in src.rxList:
-                    df_dmFun = getattr(u, '_%sDeriv'%rx.projField, None)
+                    df_dmFun = getattr(f, '_{0}Deriv'.format(rx.projField), None)
                     df_dm_v = df_dmFun(src, du_dm_v, v, adjoint=False)
-                    Jv[src, rx] = rx.evalDeriv(src, self.mesh, u, df_dm_v)
+                    Jv[src, rx] = rx.evalDeriv(src, self.mesh, f, df_dm_v)
             Ainv.clean()
         return Utils.mkvc(Jv)
 
-    def Jtvec(self, m, v, u=None):
+    def Jtvec(self, m, v, f=None):
         """
         Sensitivity transpose times a vector
 
         :param numpy.array m: inversion model (nP,)
         :param numpy.array v: vector which we take adjoint product with (nP,)
-        :param SimPEG.EM.FDEM.Fields u: fields object 
+        :param SimPEG.EM.FDEM.FieldsFDEM.FieldsFDEM u: fields object
         :rtype numpy.array:
-        :return: Jv (ndata,) 
+        :return: Jv (ndata,)
         """
 
-        if u is None:
-            u = self.fields(m)
+        if f is None:
+            f = self.fields(m)
 
         self.curModel = m
 
@@ -120,12 +127,12 @@ class BaseFDEMProblem(BaseEMProblem):
             ATinv = self.Solver(AT, **self.solverOpts)
 
             for src in self.survey.getSrcByFreq(freq):
-                u_src = u[src, self._solutionType]
+                u_src = f[src, self._solutionType]
 
                 for rx in src.rxList:
-                    PTv = rx.evalDeriv(src, self.mesh, u, v[src, rx], adjoint=True) # wrt u, need possibility wrt m
+                    PTv = rx.evalDeriv(src, self.mesh, f, v[src, rx], adjoint=True) # wrt f, need possibility wrt m
 
-                    df_duTFun = getattr(u, '_%sDeriv'%rx.projField, None)
+                    df_duTFun = getattr(f, '_{0}Deriv'.format(rx.projField), None)
                     df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
 
                     ATinvdf_duT = ATinv * df_duT
@@ -137,14 +144,13 @@ class BaseFDEMProblem(BaseEMProblem):
                     df_dmT = df_dmT + du_dmT
 
                     # TODO: this should be taken care of by the reciever?
-                    real_or_imag = rx.projComp
-                    if real_or_imag is 'real':
+                    if rx.component is 'real':
                         Jtv +=   np.array(df_dmT, dtype=complex).real
-                    elif real_or_imag is 'imag':
+                    elif rx.component is 'imag':
                         Jtv += - np.array(df_dmT, dtype=complex).real
                     else:
                         raise Exception('Must be real or imag')
-            
+
             ATinv.clean()
 
         return Utils.mkvc(Jtv)
@@ -154,30 +160,31 @@ class BaseFDEMProblem(BaseEMProblem):
         Evaluates the sources for a given frequency and puts them in matrix form
 
         :param float freq: Frequency
-        :rtype: (numpy.ndarray, numpy.ndarray)  
-        :return: S_m, S_e (nE or nF, nSrc)
+        :rtype: tuple
+        :return: (s_m, s_e) (nE or nF, nSrc)
         """
         Srcs = self.survey.getSrcByFreq(freq)
         if self._formulation is 'EB':
-            S_m = np.zeros((self.mesh.nF,len(Srcs)), dtype=complex)
-            S_e = np.zeros((self.mesh.nE,len(Srcs)), dtype=complex)
+            s_m = np.zeros((self.mesh.nF,len(Srcs)), dtype=complex)
+            s_e = np.zeros((self.mesh.nE,len(Srcs)), dtype=complex)
         elif self._formulation is 'HJ':
-            S_m = np.zeros((self.mesh.nE,len(Srcs)), dtype=complex)
-            S_e = np.zeros((self.mesh.nF,len(Srcs)), dtype=complex)
+            s_m = np.zeros((self.mesh.nE,len(Srcs)), dtype=complex)
+            s_e = np.zeros((self.mesh.nF,len(Srcs)), dtype=complex)
 
         for i, src in enumerate(Srcs):
             smi, sei = src.eval(self)
-            S_m[:,i] = S_m[:,i] + smi
-            S_e[:,i] = S_e[:,i] + sei
+            #Why are you adding?
+            s_m[:,i] = s_m[:,i] + smi
+            s_e[:,i] = s_e[:,i] + sei
 
-        return S_m, S_e
+        return s_m, s_e
 
 
 ##########################################################################################
 ################################ E-B Formulation #########################################
 ##########################################################################################
 
-class Problem_e(BaseFDEMProblem):
+class Problem3D_e(BaseFDEMProblem):
     """
     By eliminating the magnetic flux density using
 
@@ -194,12 +201,12 @@ class Problem_e(BaseFDEMProblem):
 
     which we solve for :math:`\mathbf{e}`.
 
-    :param SimPEG.Mesh mesh: mesh
+    :param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
     """
 
     _solutionType = 'eSolution'
     _formulation  = 'EB'
-    fieldsPair    = Fields_e
+    fieldsPair    = Fields3D_e
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -207,7 +214,7 @@ class Problem_e(BaseFDEMProblem):
     def getA(self, freq):
         """
         System matrix
-        
+
         .. math ::
             \mathbf{A} = \mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f} \mathbf{C} + i \omega \mathbf{M^e_{\sigma}}
 
@@ -230,12 +237,12 @@ class Problem_e(BaseFDEMProblem):
         .. math ::
             \\frac{\mathbf{A}(\mathbf{m}) \mathbf{v}}{d \mathbf{m}} = i \omega \\frac{d \mathbf{M^e_{\sigma}}\mathbf{v} }{d\mathbf{m}}
 
-        :param float freq: frequency 
-        :param numpy.ndarray u: solution vector (nE,) 
+        :param float freq: frequency
+        :param numpy.ndarray u: solution vector (nE,)
         :param numpy.ndarray v: vector to take prodct with (nP,) or (nD,) for adjoint
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
-        :return: derivative of the system matrix times a vector (nP,) or adjoint (nD,) 
+        :return: derivative of the system matrix times a vector (nP,) or adjoint (nD,)
         """
 
         dsig_dm = self.curModel.sigmaDeriv
@@ -248,28 +255,28 @@ class Problem_e(BaseFDEMProblem):
 
     def getRHS(self, freq):
         """
-        Right hand side for the system 
+        Right hand side for the system
 
         .. math ::
             \mathbf{RHS} = \mathbf{C}^{\\top} \mathbf{M_{\mu^{-1}}^f}\mathbf{s_m} -i\omega\mathbf{M_e}\mathbf{s_e}
 
         :param float freq: Frequency
-        :rtype: numpy.ndarray 
+        :rtype: numpy.ndarray
         :return: RHS (nE, nSrc)
         """
 
-        S_m, S_e = self.getSourceTerm(freq)
+        s_m, s_e = self.getSourceTerm(freq)
         C = self.mesh.edgeCurl
         MfMui = self.MfMui
 
-        return C.T * (MfMui * S_m) -1j * omega(freq) * S_e
+        return C.T * (MfMui * s_m) -1j * omega(freq) * s_e
 
     def getRHSDeriv(self, freq, src, v, adjoint=False):
         """
-        Derivative of the right hand side with respect to the model 
+        Derivative of the right hand side with respect to the model
 
         :param float freq: frequency
-        :param SimPEG.EM.FDEM.Src src: FDEM source
+        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
@@ -278,17 +285,17 @@ class Problem_e(BaseFDEMProblem):
 
         C = self.mesh.edgeCurl
         MfMui = self.MfMui
-        S_mDeriv, S_eDeriv = src.evalDeriv(self, adjoint=adjoint)
+        s_mDeriv, s_eDeriv = src.evalDeriv(self, adjoint=adjoint)
 
         if adjoint:
             dRHS = MfMui * (C * v)
-            return S_mDeriv(dRHS) - 1j * omega(freq) * S_eDeriv(v)
+            return s_mDeriv(dRHS) - 1j * omega(freq) * s_eDeriv(v)
 
         else:
-            return C.T * (MfMui * S_mDeriv(v)) -1j * omega(freq) * S_eDeriv(v)
+            return C.T * (MfMui * s_mDeriv(v)) -1j * omega(freq) * s_eDeriv(v)
 
 
-class Problem_b(BaseFDEMProblem):
+class Problem3D_b(BaseFDEMProblem):
     """
     We eliminate :math:`\mathbf{e}` using
 
@@ -305,12 +312,12 @@ class Problem_b(BaseFDEMProblem):
     .. note ::
         The inverse problem will not work with full anisotropy
 
-    :param SimPEG.Mesh mesh: mesh
+    :param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
     """
 
     _solutionType = 'bSolution'
     _formulation  = 'EB'
-    fieldsPair    = Fields_b
+    fieldsPair    = Fields3D_b
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -346,12 +353,12 @@ class Problem_b(BaseFDEMProblem):
         .. math ::
             \\frac{\mathbf{A}(\mathbf{m}) \mathbf{v}}{d \mathbf{m}} = \mathbf{C} \\frac{\mathbf{M^e_{\sigma}} \mathbf{v}}{d\mathbf{m}}
 
-        :param float freq: frequency 
-        :param numpy.ndarray u: solution vector (nF,) 
+        :param float freq: frequency
+        :param numpy.ndarray u: solution vector (nF,)
         :param numpy.ndarray v: vector to take prodct with (nP,) or (nD,) for adjoint
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
-        :return: derivative of the system matrix times a vector (nP,) or adjoint (nD,)  
+        :return: derivative of the system matrix times a vector (nP,) or adjoint (nD,)
         """
 
         MfMui = self.MfMui
@@ -373,21 +380,21 @@ class Problem_b(BaseFDEMProblem):
 
     def getRHS(self, freq):
         """
-        Right hand side for the system 
+        Right hand side for the system
 
         .. math ::
             \mathbf{RHS} = \mathbf{s_m} + \mathbf{M^e_{\sigma}}^{-1}\mathbf{s_e}
 
         :param float freq: Frequency
-        :rtype: numpy.ndarray 
+        :rtype: numpy.ndarray
         :return: RHS (nE, nSrc)
         """
 
-        S_m, S_e = self.getSourceTerm(freq)
+        s_m, s_e = self.getSourceTerm(freq)
         C = self.mesh.edgeCurl
         MeSigmaI = self.MeSigmaI
 
-        RHS = S_m + C * ( MeSigmaI * S_e )
+        RHS = s_m + C * ( MeSigmaI * s_e )
 
         if self._makeASymmetric is True:
             MfMui = self.MfMui
@@ -400,7 +407,7 @@ class Problem_b(BaseFDEMProblem):
         Derivative of the right hand side with respect to the model
 
         :param float freq: frequency
-        :param SimPEG.EM.FDEM.Src src: FDEM source
+        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
@@ -408,21 +415,21 @@ class Problem_b(BaseFDEMProblem):
         """
 
         C = self.mesh.edgeCurl
-        S_m, S_e = src.eval(self)
+        s_m, s_e = src.eval(self)
         MfMui = self.MfMui
 
         if self._makeASymmetric and adjoint:
             v = self.MfMui * v
 
-        MeSigmaIDeriv = self.MeSigmaIDeriv(S_e)
-        S_mDeriv, S_eDeriv = src.evalDeriv(self, adjoint=adjoint)
+        MeSigmaIDeriv = self.MeSigmaIDeriv(s_e)
+        s_mDeriv, s_eDeriv = src.evalDeriv(self, adjoint=adjoint)
 
         if not adjoint:
             RHSderiv = C * (MeSigmaIDeriv * v)
-            SrcDeriv = S_mDeriv(v) + C * (self.MeSigmaI * S_eDeriv(v))
+            SrcDeriv = s_mDeriv(v) + C * (self.MeSigmaI * s_eDeriv(v))
         elif adjoint:
             RHSderiv = MeSigmaIDeriv.T * (C.T * v)
-            SrcDeriv = S_mDeriv(v) + self.MeSigmaI.T * (C.T * S_eDeriv(v))
+            SrcDeriv = s_mDeriv(v) + self.MeSigmaI.T * (C.T * s_eDeriv(v))
 
         if self._makeASymmetric is True and not adjoint:
             return MfMui.T * (SrcDeriv + RHSderiv)
@@ -436,7 +443,7 @@ class Problem_b(BaseFDEMProblem):
 ##########################################################################################
 
 
-class Problem_j(BaseFDEMProblem):
+class Problem3D_j(BaseFDEMProblem):
     """
     We eliminate \\\(\\\mathbf{h}\\\) using
 
@@ -444,6 +451,7 @@ class Problem_j(BaseFDEMProblem):
 
         \mathbf{h} = \\frac{1}{i \omega} \mathbf{M_{\mu}^e}^{-1} \\left(-\mathbf{C}^{\\top} \mathbf{M_{\\rho}^f} \mathbf{j}  + \mathbf{M^e} \mathbf{s_m} \\right)
 
+
     and solve for \\\(\\\mathbf{j}\\\) using
 
     .. math ::
@@ -453,12 +461,12 @@ class Problem_j(BaseFDEMProblem):
     .. note::
         This implementation does not yet work with full anisotropy!!
 
-    :param SimPEG.Mesh mesh: mesh
+    :param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
     """
 
     _solutionType = 'jSolution'
     _formulation  = 'HJ'
-    fieldsPair    = Fields_j
+    fieldsPair    = Fields3D_j
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -497,12 +505,12 @@ class Problem_j(BaseFDEMProblem):
 
             \\frac{\mathbf{A(\sigma)} \mathbf{v}}{d \mathbf{m}} = \mathbf{C}  \mathbf{M^e_{mu^{-1}}} \mathbf{C^{\\top}} \\frac{d \mathbf{M^f_{\sigma^{-1}}}\mathbf{v} }{d \mathbf{m}}
 
-        :param float freq: frequency 
-        :param numpy.ndarray u: solution vector (nF,) 
+        :param float freq: frequency
+        :param numpy.ndarray u: solution vector (nF,)
         :param numpy.ndarray v: vector to take prodct with (nP,) or (nD,) for adjoint
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
-        :return: derivative of the system matrix times a vector (nP,) or adjoint (nD,)  
+        :return: derivative of the system matrix times a vector (nP,) or adjoint (nD,)
         """
 
         MeMuI = self.MeMuI
@@ -522,22 +530,22 @@ class Problem_j(BaseFDEMProblem):
 
     def getRHS(self, freq):
         """
-        Right hand side for the system 
+        Right hand side for the system
 
         .. math ::
 
             \mathbf{RHS} = \mathbf{C} \mathbf{M_{\mu}^e}^{-1}\mathbf{s_m} -i\omega \mathbf{s_e}
 
         :param float freq: Frequency
-        :rtype: numpy.ndarray (nE, nSrc)
-        :return: RHS
+        :rtype: numpy.ndarray
+        :return: RHS (nE, nSrc)
         """
 
-        S_m, S_e = self.getSourceTerm(freq)
+        s_m, s_e = self.getSourceTerm(freq)
         C = self.mesh.edgeCurl
         MeMuI = self.MeMuI
 
-        RHS = C * (MeMuI * S_m) - 1j * omega(freq) * S_e
+        RHS = C * (MeMuI * s_m) - 1j * omega(freq) * s_e
         if self._makeASymmetric is True:
             MfRho = self.MfRho
             return MfRho.T*RHS
@@ -546,10 +554,10 @@ class Problem_j(BaseFDEMProblem):
 
     def getRHSDeriv(self, freq, src, v, adjoint=False):
         """
-        Derivative of the right hand side with respect to the model 
+        Derivative of the right hand side with respect to the model
 
         :param float freq: frequency
-        :param SimPEG.EM.FDEM.Src src: FDEM source
+        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
@@ -558,16 +566,16 @@ class Problem_j(BaseFDEMProblem):
 
         C = self.mesh.edgeCurl
         MeMuI = self.MeMuI
-        S_mDeriv, S_eDeriv = src.evalDeriv(self, adjoint=adjoint)
+        s_mDeriv, s_eDeriv = src.evalDeriv(self, adjoint=adjoint)
 
         if adjoint:
             if self._makeASymmetric:
                 MfRho = self.MfRho
                 v = MfRho*v
-            return S_mDeriv(MeMuI.T * (C.T * v)) - 1j * omega(freq) * S_eDeriv(v)
+            return s_mDeriv(MeMuI.T * (C.T * v)) - 1j * omega(freq) * s_eDeriv(v)
 
         else:
-            RHSDeriv = C * (MeMuI * S_mDeriv(v)) - 1j * omega(freq) * S_eDeriv(v)
+            RHSDeriv = C * (MeMuI * s_mDeriv(v)) - 1j * omega(freq) * s_eDeriv(v)
 
             if self._makeASymmetric:
                 MfRho = self.MfRho
@@ -577,7 +585,7 @@ class Problem_j(BaseFDEMProblem):
 
 
 
-class Problem_h(BaseFDEMProblem):
+class Problem3D_h(BaseFDEMProblem):
     """
     We eliminate \\\(\\\mathbf{j}\\\) using
 
@@ -591,12 +599,12 @@ class Problem_h(BaseFDEMProblem):
 
         \\left(\mathbf{C}^{\\top} \mathbf{M_{\\rho}^f} \mathbf{C} + i \omega \mathbf{M_{\mu}^e}\\right) \mathbf{h} = \mathbf{M^e} \mathbf{s_m} + \mathbf{C}^{\\top} \mathbf{M_{\\rho}^f} \mathbf{s_e}
 
-    :param SimPEG.Mesh mesh: mesh
+    :param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
     """
 
     _solutionType = 'hSolution'
     _formulation  = 'HJ'
-    fieldsPair    = Fields_h
+    fieldsPair    = Fields3D_h
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -608,9 +616,11 @@ class Problem_h(BaseFDEMProblem):
         .. math::
             \mathbf{A} = \mathbf{C}^{\\top} \mathbf{M_{\\rho}^f} \mathbf{C} + i \omega \mathbf{M_{\mu}^e}
 
+
         :param float freq: Frequency
         :rtype: scipy.sparse.csr_matrix
         :return: A
+
         """
 
         MeMu = self.MeMu
@@ -626,12 +636,12 @@ class Problem_h(BaseFDEMProblem):
         .. math::
             \\frac{\mathbf{A}(\mathbf{m}) \mathbf{v}}{d \mathbf{m}} = \mathbf{C}^{\\top}\\frac{d \mathbf{M^f_{\\rho}}\mathbf{v} }{d\mathbf{m}}
 
-        :param float freq: frequency 
-        :param numpy.ndarray u: solution vector (nE,) 
+        :param float freq: frequency
+        :param numpy.ndarray u: solution vector (nE,)
         :param numpy.ndarray v: vector to take prodct with (nP,) or (nD,) for adjoint
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
-        :return: derivative of the system matrix times a vector (nP,) or adjoint (nD,)  
+        :return: derivative of the system matrix times a vector (nP,) or adjoint (nD,)
         """
 
         MeMu = self.MeMu
@@ -644,46 +654,47 @@ class Problem_h(BaseFDEMProblem):
 
     def getRHS(self, freq):
         """
-        Right hand side for the system 
+        Right hand side for the system
 
         .. math ::
 
             \mathbf{RHS} = \mathbf{M^e} \mathbf{s_m} + \mathbf{C}^{\\top} \mathbf{M_{\\rho}^f} \mathbf{s_e}
 
         :param float freq: Frequency
-        :rtype: numpy.ndarray 
+        :rtype: numpy.ndarray
         :return: RHS (nE, nSrc)
+
         """
 
-        S_m, S_e = self.getSourceTerm(freq)
+        s_m, s_e = self.getSourceTerm(freq)
         C = self.mesh.edgeCurl
         MfRho  = self.MfRho
 
-        return S_m + C.T * ( MfRho * S_e )
+        return s_m + C.T * ( MfRho * s_e )
 
     def getRHSDeriv(self, freq, src, v, adjoint=False):
         """
-        Derivative of the right hand side with respect to the model 
+        Derivative of the right hand side with respect to the model
 
         :param float freq: frequency
-        :param SimPEG.EM.FDEM.Src src: FDEM source
+        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
         :return: product of rhs deriv with a vector
         """
 
-        _, S_e = src.eval(self)
+        _, s_e = src.eval(self)
         C = self.mesh.edgeCurl
         MfRho  = self.MfRho
 
-        MfRhoDeriv = self.MfRhoDeriv(S_e)
+        MfRhoDeriv = self.MfRhoDeriv(s_e)
         if not adjoint:
             RHSDeriv = C.T * (MfRhoDeriv * v)
         elif adjoint:
             RHSDeriv = MfRhoDeriv.T * (C * v)
 
-        S_mDeriv, S_eDeriv = src.evalDeriv(self, adjoint=adjoint)
+        s_mDeriv, s_eDeriv = src.evalDeriv(self, adjoint=adjoint)
 
-        return RHSDeriv + S_mDeriv(v) + C.T * (MfRho * S_eDeriv(v))
+        return RHSDeriv + s_mDeriv(v) + C.T * (MfRho * s_eDeriv(v))
 

SimPEG/EM/FDEM/RxFDEM.py

@@ -0,0 +1,133 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from builtins import super
+from future import standard_library
+standard_library.install_aliases()
+import SimPEG
+from SimPEG import sp
+
+class BaseRx(SimPEG.Survey.BaseRx):
+    """
+    Frequency domain receiver base class
+
+    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
+    :param string orientation: receiver orientation 'x', 'y' or 'z'
+    :param string component: real or imaginary component 'real' or 'imag'
+    """
+
+    def __init__(self, locs, orientation=None, component=None):
+        assert(orientation in ['x','y','z']), "Orientation %s not known. Orientation must be in 'x', 'y', 'z'. Arbitrary orientations have not yet been implemented."%orientation
+        assert(component in ['real', 'imag']), "'component' must be 'real' or 'imag', not %s"%component
+
+        self.projComp = orientation
+        self.component = component
+
+        SimPEG.Survey.BaseRx.__init__(self, locs, rxType=None) #TODO: remove rxType from baseRx
+
+    def projGLoc(self, u):
+        """Grid Location projection (e.g. Ex Fy ...)"""
+        return u._GLoc(self.projField) + self.projComp
+
+    def eval(self, src, mesh, f):
+        """
+        Project fields to receivers to get data.
+
+        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
+        :param BaseMesh mesh: mesh used
+        :param Fields f: fields object
+        :rtype: numpy.ndarray
+        :return: fields projected to recievers
+        """
+
+        P = self.getP(mesh, self.projGLoc(f))
+        f_part_complex = f[src, self.projField]
+        f_part = getattr(f_part_complex, self.component) # get the real or imag component
+
+        return P*f_part
+
+    def evalDeriv(self, src, mesh, f, v, adjoint=False):
+        """
+        Derivative of projected fields with respect to the inversion model times a vector.
+
+        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
+        :param BaseMesh mesh: mesh used
+        :param Fields f: fields object
+        :param numpy.ndarray v: vector to multiply
+        :rtype: numpy.ndarray
+        :return: fields projected to recievers
+        """
+
+        P = self.getP(mesh, self.projGLoc(f))
+
+        if not adjoint:
+            Pv_complex = P * v
+            Pv = getattr(Pv_complex, self.component)
+        elif adjoint:
+            Pv_real = P.T * v
+
+            if self.component == 'imag':
+                Pv = 1j*Pv_real
+            elif self.component == 'real':
+                Pv = Pv_real.astype(complex)
+            else:
+                raise NotImplementedError('must be real or imag')
+
+        return Pv
+
+
+class Point_e(BaseRx):
+    """
+    Electric field FDEM receiver
+
+    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
+    :param string orientation: receiver orientation 'x', 'y' or 'z'
+    :param string component: real or imaginary component 'real' or 'imag'
+    """
+
+    def __init__(self, locs, orientation=None, component=None):
+        self.projField = 'e'
+        super(Point_e, self).__init__(locs, orientation, component)
+
+
+class Point_b(BaseRx):
+    """
+    Magnetic flux FDEM receiver
+
+    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
+    :param string orientation: receiver orientation 'x', 'y' or 'z'
+    :param string component: real or imaginary component 'real' or 'imag'
+    """
+
+    def __init__(self, locs, orientation=None, component=None):
+        self.projField = 'b'
+        super(Point_b, self).__init__(locs, orientation, component)
+
+
+class Point_h(BaseRx):
+    """
+    Magnetic field FDEM receiver
+
+    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
+    :param string orientation: receiver orientation 'x', 'y' or 'z'
+    :param string component: real or imaginary component 'real' or 'imag'
+    """
+
+    def __init__(self, locs, orientation=None, component=None):
+        self.projField = 'h'
+        super(Point_h, self).__init__(locs, orientation, component)
+
+
+class Point_j(BaseRx):
+    """
+    Current density FDEM receiver
+
+    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
+    :param string orientation: receiver orientation 'x', 'y' or 'z'
+    :param string component: real or imaginary component 'real' or 'imag'
+    """
+
+    def __init__(self, locs, orientation=None, component=None):
+        self.projField = 'j'
+        super(Point_j, self).__init__(locs, orientation, component)

SimPEG/EM/FDEM/SrcFDEM.py

@@ -1,3 +1,9 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import Survey, Problem, Utils, np, sp
 from scipy.constants import mu_0
 from SimPEG.EM.Utils import *
@@ -9,105 +15,118 @@ class BaseSrc(Survey.BaseSrc):
     """
 
     freq = None
-    # rxPair = RxFDEM
-    integrate = True
+    integrate = False
+    _ePrimary = None
+    _bPrimary = None
+    _hPrimary = None
+    _jPrimary = None
+
+    def __init__(self, rxList, **kwargs):
+        Survey.BaseSrc.__init__(self, rxList, **kwargs)
 
     def eval(self, prob):
         """
-        Evaluate the source terms.
-        - :math:`S_m` : magnetic source term
-        - :math:`S_e` : electric source term
+        - :math:`s_m` : magnetic source term
+        - :math:`s_e` : electric source term
 
-        :param Problem prob: FDEM Problem
-        :rtype: (numpy.ndarray, numpy.ndarray)
+        :param BaseFDEMProblem prob: FDEM Problem
+        :rtype: tuple
         :return: tuple with magnetic source term and electric source term
         """
-        S_m = self.S_m(prob)
-        S_e = self.S_e(prob)
-        return S_m, S_e
+        s_m = self.s_m(prob)
+        s_e = self.s_e(prob)
+        return s_m, s_e
 
     def evalDeriv(self, prob, v=None, adjoint=False):
         """
         Derivatives of the source terms with respect to the inversion model
-        - :code:`S_mDeriv` : derivative of the magnetic source term
-        - :code:`S_eDeriv` : derivative of the electric source term
+        - :code:`s_mDeriv` : derivative of the magnetic source term
+        - :code:`s_eDeriv` : derivative of the electric source term
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
-        :rtype: (numpy.ndarray, numpy.ndarray)
+        :rtype: tuple
         :return: tuple with magnetic source term and electric source term derivatives times a vector
         """
         if v is not None:
-            return self.S_mDeriv(prob, v, adjoint), self.S_eDeriv(prob, v, adjoint)
+            return self.s_mDeriv(prob, v, adjoint), self.s_eDeriv(prob, v, adjoint)
         else:
-            return lambda v: self.S_mDeriv(prob, v, adjoint), lambda v: self.S_eDeriv(prob, v, adjoint)
+            return lambda v: self.s_mDeriv(prob, v, adjoint), lambda v: self.s_eDeriv(prob, v, adjoint)
 
     def bPrimary(self, prob):
         """
         Primary magnetic flux density
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: primary magnetic flux density
         """
-        return Zero()
+        if self._bPrimary is None:
+            return Zero()
+        return self._bPrimary
 
     def hPrimary(self, prob):
         """
         Primary magnetic field
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
-        return Zero()
+        if self._hPrimary is None:
+            return Zero()
+        return self._hPrimary
 
     def ePrimary(self, prob):
         """
         Primary electric field
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: primary electric field
         """
-        return Zero()
+        if self._ePrimary is None:
+            return Zero()
+        return self._ePrimary
 
     def jPrimary(self, prob):
         """
         Primary current density
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: primary current density
         """
-        return Zero()
+        if self._jPrimary is None:
+            return Zero()
+        return self._jPrimary
 
-    def S_m(self, prob):
+    def s_m(self, prob):
         """
         Magnetic source term
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: magnetic source term on mesh
         """
         return Zero()
 
-    def S_e(self, prob):
+    def s_e(self, prob):
         """
         Electric source term
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: electric source term on mesh
         """
         return Zero()
 
-    def S_mDeriv(self, prob, v, adjoint = False):
+    def s_mDeriv(self, prob, v, adjoint = False):
         """
         Derivative of magnetic source term with respect to the inversion model
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
@@ -116,11 +135,11 @@ class BaseSrc(Survey.BaseSrc):
 
         return Zero()
 
-    def S_eDeriv(self, prob, v, adjoint = False):
+    def s_eDeriv(self, prob, v, adjoint = False):
         """
         Derivative of electric source term with respect to the inversion model
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
@@ -131,104 +150,101 @@ class BaseSrc(Survey.BaseSrc):
 
 class RawVec_e(BaseSrc):
     """
-    RawVec electric source. It is defined by the user provided vector S_e
+    RawVec electric source. It is defined by the user provided vector s_e
 
     :param list rxList: receiver list
     :param float freq: frequency
-    :param numpy.array S_e: electric source term
-    :param bool integrate: Integrate the source term (multiply by Me) [True]
+    :param numpy.array s_e: electric source term
+    :param bool integrate: Integrate the source term (multiply by Me) [False]
     """
 
-    def __init__(self, rxList, freq, S_e, integrate=True): #, ePrimary=None, bPrimary=None, hPrimary=None, jPrimary=None):
-        self._S_e = np.array(S_e, dtype=complex)
+    def __init__(self, rxList, freq, s_e, **kwargs):
+        self._s_e = np.array(s_e, dtype=complex)
         self.freq = float(freq)
-        self.integrate = integrate
 
-        BaseSrc.__init__(self, rxList)
+        BaseSrc.__init__(self, rxList, **kwargs)
 
-    def S_e(self, prob):
+    def s_e(self, prob):
         """
         Electric source term
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: electric source term on mesh
         """
         if prob._formulation is 'EB' and self.integrate is True:
-            return prob.Me * self._S_e
-        return self._S_e
+            return prob.Me * self._s_e
+        return self._s_e
 
 
 class RawVec_m(BaseSrc):
     """
-    RawVec magnetic source. It is defined by the user provided vector S_m
+    RawVec magnetic source. It is defined by the user provided vector s_m
 
     :param float freq: frequency
     :param rxList: receiver list
-    :param numpy.array S_m: magnetic source term
-    :param bool integrate: Integrate the source term (multiply by Me) [True]
+    :param numpy.array s_m: magnetic source term
+    :param bool integrate: Integrate the source term (multiply by Me) [False]
     """
 
-    def __init__(self, rxList, freq, S_m, integrate=True):  #ePrimary=Zero(), bPrimary=Zero(), hPrimary=Zero(), jPrimary=Zero()):
-        self._S_m = np.array(S_m, dtype=complex)
+    def __init__(self, rxList, freq, s_m, **kwargs):  #ePrimary=Zero(), bPrimary=Zero(), hPrimary=Zero(), jPrimary=Zero()):
+        self._s_m = np.array(s_m, dtype=complex)
         self.freq = float(freq)
-        self.integrate = integrate
 
-        BaseSrc.__init__(self, rxList)
+        BaseSrc.__init__(self, rxList, **kwargs)
 
-    def S_m(self, prob):
+    def s_m(self, prob):
         """
         Magnetic source term
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: magnetic source term on mesh
         """
         if prob._formulation is 'HJ' and self.integrate is True:
-            return prob.Me * self._S_m
-        return self._S_m
+            return prob.Me * self._s_m
+        return self._s_m
 
 
 class RawVec(BaseSrc):
     """
-    RawVec source. It is defined by the user provided vectors S_m, S_e
+    RawVec source. It is defined by the user provided vectors s_m, s_e
 
     :param rxList: receiver list
     :param float freq: frequency
-    :param numpy.array S_m: magnetic source term
-    :param numpy.array S_e: electric source term
-    :param bool integrate: Integrate the source term (multiply by Me) [True]
+    :param numpy.array s_m: magnetic source term
+    :param numpy.array s_e: electric source term
+    :param bool integrate: Integrate the source term (multiply by Me) [False]
     """
-    def __init__(self, rxList, freq, S_m, S_e, integrate=True):
-        self._S_m = np.array(S_m, dtype=complex)
-        self._S_e = np.array(S_e, dtype=complex)
+    def __init__(self, rxList, freq, s_m, s_e, **kwargs):
+        self._s_m = np.array(s_m, dtype=complex)
+        self._s_e = np.array(s_e, dtype=complex)
         self.freq = float(freq)
-        self.integrate = integrate
-        BaseSrc.__init__(self, rxList)
+        BaseSrc.__init__(self, rxList, **kwargs)
 
-    def S_m(self, prob):
+    def s_m(self, prob):
         """
         Magnetic source term
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: magnetic source term on mesh
         """
         if prob._formulation is 'HJ' and self.integrate is True:
-            return prob.Me * self._S_m
-        return self._S_m
+            return prob.Me * self._s_m
+        return self._s_m
 
-    def S_e(self, prob):
+    def s_e(self, prob):
         """
         Electric source term
 
-        :param Problem prob: FDEM Problem
+        :param BaseFDEMProblem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: electric source term on mesh
         """
         if prob._formulation is 'EB' and self.integrate is True:
-            return prob.Me * self._S_e
-        return self._S_e
+            return prob.Me * self._s_e
+        return self._s_e
 
 
 class MagDipole(BaseSrc):
@@ -278,21 +294,20 @@ class MagDipole(BaseSrc):
     :param float mu: background magnetic permeability
     """
 
-    def __init__(self, rxList, freq, loc, orientation='Z', moment=1., mu=mu_0):
+    def __init__(self, rxList, freq, loc, orientation='Z', moment=1., mu=mu_0, **kwargs):
         self.freq = float(freq)
         self.loc = loc
         self.orientation = orientation
         assert orientation in ['X','Y','Z'], "Orientation (right now) doesn't actually do anything! The methods in SrcUtils should take care of this..."
         self.moment = moment
         self.mu = mu
-        self.integrate = False
         BaseSrc.__init__(self, rxList)
 
     def bPrimary(self, prob):
         """
         The primary magnetic flux density from a magnetic vector potential
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -330,32 +345,32 @@ class MagDipole(BaseSrc):
         """
         The primary magnetic field from a magnetic vector potential
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
         b = self.bPrimary(prob)
-        return 1./self.mu * b 
+        return 1./self.mu * b
 
-    def S_m(self, prob):
+    def s_m(self, prob):
         """
         The magnetic source term
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
 
         b_p = self.bPrimary(prob)
         if prob._formulation is 'HJ':
-            b_p = prob.Me * b_p 
+            b_p = prob.Me * b_p
         return -1j*omega(self.freq)*b_p
 
-    def S_e(self, prob):
+    def s_e(self, prob):
         """
         The electric source term
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -407,7 +422,7 @@ class MagDipole_Bfield(BaseSrc):
         """
         The primary magnetic flux density from the analytic solution for magnetic fields from a dipole
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -446,18 +461,18 @@ class MagDipole_Bfield(BaseSrc):
         """
         The primary magnetic field from a magnetic vector potential
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
         b = self.bPrimary(prob)
         return 1/self.mu * b
 
-    def S_m(self, prob):
+    def s_m(self, prob):
         """
         The magnetic source term
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -466,11 +481,11 @@ class MagDipole_Bfield(BaseSrc):
             b = prob.Me * b
         return -1j*omega(self.freq)*b
 
-    def S_e(self, prob):
+    def s_e(self, prob):
         """
         The electric source term
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -521,7 +536,7 @@ class CircularLoop(BaseSrc):
         """
         The primary magnetic flux density from a magnetic vector potential
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -543,7 +558,7 @@ class CircularLoop(BaseSrc):
             if not prob.mesh.isSymmetric:
                 # TODO ?
                 raise NotImplementedError('Non-symmetric cyl mesh not implemented yet!')
-            a = MagneticDipoleVectorPotential(self.loc, gridY, 'y', moment=self.radius, mu=self.mu)
+            a = MagneticLoopVectorPotential(self.loc, gridY, 'y', moment=self.radius, mu=self.mu)
 
         else:
             srcfct = MagneticDipoleVectorPotential
@@ -558,18 +573,18 @@ class CircularLoop(BaseSrc):
         """
         The primary magnetic field from a magnetic vector potential
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
         b = self.bPrimary(prob)
         return 1./self.mu*b
 
-    def S_m(self, prob):
+    def s_m(self, prob):
         """
         The magnetic source term
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -578,11 +593,11 @@ class CircularLoop(BaseSrc):
             b =  prob.Me *  b
         return -1j*omega(self.freq)*b
 
-    def S_e(self, prob):
+    def s_e(self, prob):
         """
         The electric source term
 
-        :param Problem prob: FDEM problem
+        :param BaseFDEMProblem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -604,6 +619,6 @@ class CircularLoop(BaseSrc):
 
             return -C.T * (MMui_s * self.bPrimary(prob))
 
-            
+
 
 

SimPEG/EM/FDEM/SurveyFDEM.py

@@ -1,129 +1,19 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
 import SimPEG
 from SimPEG.EM.Utils import *
+from SimPEG.EM.Base import BaseEMSurvey
 from scipy.constants import mu_0
 from SimPEG.Utils import Zero, Identity
-import SrcFDEM as Src
+from . import SrcFDEM as Src
+from . import RxFDEM as Rx
 from SimPEG import sp
 
-
-####################################################
-# Receivers
-####################################################
-
-class Rx(SimPEG.Survey.BaseRx):
-    """
-    Frequency domain receivers
-
-    :param numpy.ndarray locs: receiver locations (ie. :code:`np.r_[x,y,z]`)
-    :param string rxType: reciever type from knownRxTypes
-    """
-
-    knownRxTypes = {
-                    'exr':['e', 'x', 'real'],
-                    'eyr':['e', 'y', 'real'],
-                    'ezr':['e', 'z', 'real'],
-                    'exi':['e', 'x', 'imag'],
-                    'eyi':['e', 'y', 'imag'],
-                    'ezi':['e', 'z', 'imag'],
-
-                    'bxr':['b', 'x', 'real'],
-                    'byr':['b', 'y', 'real'],
-                    'bzr':['b', 'z', 'real'],
-                    'bxi':['b', 'x', 'imag'],
-                    'byi':['b', 'y', 'imag'],
-                    'bzi':['b', 'z', 'imag'],
-
-                    'jxr':['j', 'x', 'real'],
-                    'jyr':['j', 'y', 'real'],
-                    'jzr':['j', 'z', 'real'],
-                    'jxi':['j', 'x', 'imag'],
-                    'jyi':['j', 'y', 'imag'],
-                    'jzi':['j', 'z', 'imag'],
-
-                    'hxr':['h', 'x', 'real'],
-                    'hyr':['h', 'y', 'real'],
-                    'hzr':['h', 'z', 'real'],
-                    'hxi':['h', 'x', 'imag'],
-                    'hyi':['h', 'y', 'imag'],
-                    'hzi':['h', 'z', 'imag'],
-                   }
-    radius = None
-
-    def __init__(self, locs, rxType):
-        SimPEG.Survey.BaseRx.__init__(self, locs, rxType)
-
-    @property
-    def projField(self):
-        """Field Type projection (e.g. e b ...)"""
-        return self.knownRxTypes[self.rxType][0]
-
-    @property
-    def projComp(self):
-        """Component projection (real/imag)"""
-        return self.knownRxTypes[self.rxType][2]
-
-    def projGLoc(self, u):
-        """Grid Location projection (e.g. Ex Fy ...)"""
-        return u._GLoc(self.rxType[0]) + self.knownRxTypes[self.rxType][1]
-
-    def eval(self, src, mesh, u):
-        """
-        Project fields to recievers to get data.
-
-        :param Source src: FDEM source
-        :param Mesh mesh: mesh used
-        :param Fields f: fields object
-        :rtype: numpy.ndarray
-        :return: fields projected to recievers
-        """
-        # projGLoc = u._GLoc(self.knownRxTypes[self.rxType][0])
-        # projGLoc += self.knownRxTypes[self.rxType][1]
-
-        P = self.getP(mesh, self.projGLoc(u))
-        u_part_complex = u[src, self.projField]
-        # get the real or imag component
-        real_or_imag = self.projComp
-        u_part = getattr(u_part_complex, real_or_imag)
-        
-        return P*u_part
-
-    def evalDeriv(self, src, mesh, u, v, adjoint=False):
-        """
-        Derivative of projected fields with respect to the inversion model times a vector.
-
-        :param Source src: FDEM source
-        :param Mesh mesh: mesh used
-        :param Fields u: fields object
-        :param numpy.ndarray v: vector to multiply
-        :rtype: numpy.ndarray
-        :return: fields projected to recievers
-        """
-
-        P = self.getP(mesh, self.projGLoc(u))
-
-        if not adjoint:
-            Pv_complex = P * v
-            real_or_imag = self.projComp
-            Pv = getattr(Pv_complex, real_or_imag)
-        elif adjoint:
-            Pv_real = P.T * v
-
-            real_or_imag = self.projComp
-            if real_or_imag == 'imag':
-                Pv = 1j*Pv_real
-            elif real_or_imag == 'real':
-                Pv = Pv_real.astype(complex)
-            else:
-                raise NotImplementedError('must be real or imag')
-
-        return Pv
-
-
-####################################################
-# Survey
-####################################################
-
-class Survey(SimPEG.Survey.BaseSurvey):
+class Survey(BaseEMSurvey):
     """
     Frequency domain electromagnetic survey
 
@@ -131,12 +21,12 @@ class Survey(SimPEG.Survey.BaseSurvey):
     """
 
     srcPair = Src.BaseSrc
-    rxPaair = Rx 
+    rxPair = Rx.BaseRx
 
     def __init__(self, srcList, **kwargs):
         # Sort these by frequency
         self.srcList = srcList
-        SimPEG.Survey.BaseSurvey.__init__(self, **kwargs)
+        BaseEMSurvey.__init__(self, srcList, **kwargs)
 
         _freqDict = {}
         for src in srcList:
@@ -171,24 +61,8 @@ class Survey(SimPEG.Survey.BaseSurvey):
         Returns the sources associated with a specific frequency.
         :param float freq: frequency for which we look up sources
         :rtype: dictionary
-        :return: sources at the sepcified frequency 
+        :return: sources at the sepcified frequency
         """
         assert freq in self._freqDict, "The requested frequency is not in this survey."
         return self._freqDict[freq]
 
-    def eval(self, u):
-        """
-        Project fields to receiver locations
-        :param Fields u: fields object
-        :rtype: numpy.ndarray
-        :return: data
-        """
-        data = SimPEG.Survey.Data(self)
-        for src in self.srcList:
-            for rx in src.rxList:
-                data[src, rx] = rx.eval(src, self.mesh, u)
-        return data
-
-    def evalDeriv(self, u):
-        raise Exception('Use Receivers to project fields deriv.')
-

SimPEG/EM/FDEM/__init__.py

@@ -1,3 +1,11 @@
-from SurveyFDEM import Rx, Src, Survey
-from FDEM import BaseFDEMProblem, Problem_e, Problem_b, Problem_j, Problem_h
-from FieldsFDEM import *
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .SurveyFDEM import Survey
+from . import SrcFDEM as Src
+from . import RxFDEM as Rx
+from .ProblemFDEM import Problem3D_e, Problem3D_b, Problem3D_j, Problem3D_h
+from .FieldsFDEM import Fields3D_e, Fields3D_b, Fields3D_j, Fields3D_h

SimPEG/EM/Static/DC/BoundaryUtils.py

@@ -0,0 +1,166 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+import numpy as np
+
+def getxBCyBC_CC(mesh, alpha, beta, gamma):
+# def getxBCyBC(mesh, alpha, beta, gamma):
+    """
+    This is a subfunction generating mixed-boundary condition:
+
+    .. math::
+
+        \nabla \cdot \vec{j} = -\nabla \cdot \vec{j}_s = q
+
+        \rho \vec{j} = -\nabla \phi \phi
+
+        \alpha \phi + \beta \frac{\partial \phi}{\partial r} = \gamma \ at \ r = \partial \Omega
+
+        xBC = f_1(\alpha, \beta, \gamma)
+        yBC = f(\alpha, \beta, \gamma)
+
+    Computes xBC and yBC for cell-centered discretizations
+    """
+    if mesh.dim == 1: #1D
+        if (len(alpha) != 2 or len(beta) != 2 or len(gamma) != 2):
+            raise Exception("Lenght of list, alpha should be 2")
+        fCCxm,fCCxp = mesh.cellBoundaryInd
+        nBC = fCCxm.sum()+fCCxp.sum()
+        h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
+
+        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
+        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
+
+        # h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
+        h_xm, h_xp = mesh.hx[0], mesh.hx[-1]
+
+        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
+        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
+        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
+        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
+
+        xBC_xm = 0.5*a_xm
+        xBC_xp = 0.5*a_xp/b_xp
+        yBC_xm = 0.5*(1.-b_xm)
+        yBC_xp = 0.5*(1.-1./b_xp)
+
+        xBC = np.r_[xBC_xm, xBC_xp]
+        yBC = np.r_[yBC_xm, yBC_xp]
+
+    elif mesh.dim == 2: #2D
+        if (len(alpha) != 4 or len(beta) != 4 or len(gamma) != 4):
+            raise Exception("Lenght of list, alpha should be 4")
+
+        fxm,fxp,fym,fyp = mesh.faceBoundaryInd
+        nBC = fxm.sum()+fxp.sum()+fxm.sum()+fxp.sum()
+
+        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
+        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
+        alpha_ym, beta_ym, gamma_ym = alpha[2], beta[2], gamma[2]
+        alpha_yp, beta_yp, gamma_yp = alpha[3], beta[3], gamma[3]
+
+        # h_xm, h_xp = mesh.gridCC[fCCxm,0], mesh.gridCC[fCCxp,0]
+        # h_ym, h_yp = mesh.gridCC[fCCym,1], mesh.gridCC[fCCyp,1]
+
+        h_xm, h_xp = mesh.hx[0]*np.ones_like(alpha_xm), mesh.hx[-1]*np.ones_like(alpha_xp)
+        h_ym, h_yp = mesh.hy[0]*np.ones_like(alpha_ym), mesh.hy[-1]*np.ones_like(alpha_yp)
+
+        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
+        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
+        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
+        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
+
+        a_ym = gamma_ym/(0.5*alpha_ym-beta_ym/h_ym)
+        b_ym = (0.5*alpha_ym+beta_ym/h_ym)/(0.5*alpha_ym-beta_ym/h_ym)
+        a_yp = gamma_yp/(0.5*alpha_yp-beta_yp/h_yp)
+        b_yp = (0.5*alpha_yp+beta_yp/h_yp)/(0.5*alpha_yp-beta_yp/h_yp)
+
+        xBC_xm = 0.5*a_xm
+        xBC_xp = 0.5*a_xp/b_xp
+        yBC_xm = 0.5*(1.-b_xm)
+        yBC_xp = 0.5*(1.-1./b_xp)
+        xBC_ym = 0.5*a_ym
+        xBC_yp = 0.5*a_yp/b_yp
+        yBC_ym = 0.5*(1.-b_ym)
+        yBC_yp = 0.5*(1.-1./b_yp)
+
+        sortindsfx = np.argsort(np.r_[np.arange(mesh.nFx)[fxm], np.arange(mesh.nFx)[fxp]])
+        sortindsfy = np.argsort(np.r_[np.arange(mesh.nFy)[fym], np.arange(mesh.nFy)[fyp]])
+
+        xBC_x = np.r_[xBC_xm, xBC_xp][sortindsfx]
+        xBC_y = np.r_[xBC_ym, xBC_yp][sortindsfy]
+        yBC_x = np.r_[yBC_xm, yBC_xp][sortindsfx]
+        yBC_y = np.r_[yBC_ym, yBC_yp][sortindsfy]
+
+        xBC = np.r_[xBC_x, xBC_y]
+        yBC = np.r_[yBC_x, yBC_y]
+
+    elif mesh.dim == 3: #3D
+        if (len(alpha) != 6 or len(beta) != 6 or len(gamma) != 6):
+            raise Exception("Lenght of list, alpha should be 6")
+        # fCCxm,fCCxp,fCCym,fCCyp,fCCzm,fCCzp = mesh.cellBoundaryInd
+        fxm,fxp,fym,fyp,fzm,fzp = mesh.faceBoundaryInd
+        nBC = fxm.sum()+fxp.sum()+fxm.sum()+fxp.sum()
+
+        alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
+        alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
+        alpha_ym, beta_ym, gamma_ym = alpha[2], beta[2], gamma[2]
+        alpha_yp, beta_yp, gamma_yp = alpha[3], beta[3], gamma[3]
+        alpha_zm, beta_zm, gamma_zm = alpha[4], beta[4], gamma[4]
+        alpha_zp, beta_zp, gamma_zp = alpha[5], beta[5], gamma[5]
+
+        # h_xm, h_xp = mesh.gridCC[fCCxm,0], mesh.gridCC[fCCxp,0]
+        # h_ym, h_yp = mesh.gridCC[fCCym,1], mesh.gridCC[fCCyp,1]
+        # h_zm, h_zp = mesh.gridCC[fCCzm,2], mesh.gridCC[fCCzp,2]
+
+        h_xm, h_xp = mesh.hx[0]*np.ones_like(alpha_xm), mesh.hx[-1]*np.ones_like(alpha_xp)
+        h_ym, h_yp = mesh.hy[0]*np.ones_like(alpha_ym), mesh.hy[-1]*np.ones_like(alpha_yp)
+        h_zm, h_zp = mesh.hz[0]*np.ones_like(alpha_zm), mesh.hz[-1]*np.ones_like(alpha_zp)
+
+        a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
+        b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
+        a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
+        b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
+
+        a_ym = gamma_ym/(0.5*alpha_ym-beta_ym/h_ym)
+        b_ym = (0.5*alpha_ym+beta_ym/h_ym)/(0.5*alpha_ym-beta_ym/h_ym)
+        a_yp = gamma_yp/(0.5*alpha_yp-beta_yp/h_yp)
+        b_yp = (0.5*alpha_yp+beta_yp/h_yp)/(0.5*alpha_yp-beta_yp/h_yp)
+
+        a_zm = gamma_zm/(0.5*alpha_zm-beta_zm/h_zm)
+        b_zm = (0.5*alpha_zm+beta_zm/h_zm)/(0.5*alpha_zm-beta_zm/h_zm)
+        a_zp = gamma_zp/(0.5*alpha_zp-beta_zp/h_zp)
+        b_zp = (0.5*alpha_zp+beta_zp/h_zp)/(0.5*alpha_zp-beta_zp/h_zp)
+
+        xBC_xm = 0.5*a_xm
+        xBC_xp = 0.5*a_xp/b_xp
+        yBC_xm = 0.5*(1.-b_xm)
+        yBC_xp = 0.5*(1.-1./b_xp)
+        xBC_ym = 0.5*a_ym
+        xBC_yp = 0.5*a_yp/b_yp
+        yBC_ym = 0.5*(1.-b_ym)
+        yBC_yp = 0.5*(1.-1./b_yp)
+        xBC_zm = 0.5*a_zm
+        xBC_zp = 0.5*a_zp/b_zp
+        yBC_zm = 0.5*(1.-b_zm)
+        yBC_zp = 0.5*(1.-1./b_zp)
+
+        sortindsfx = np.argsort(np.r_[np.arange(mesh.nFx)[fxm], np.arange(mesh.nFx)[fxp]])
+        sortindsfy = np.argsort(np.r_[np.arange(mesh.nFy)[fym], np.arange(mesh.nFy)[fyp]])
+        sortindsfz = np.argsort(np.r_[np.arange(mesh.nFz)[fzm], np.arange(mesh.nFz)[fzp]])
+
+        xBC_x = np.r_[xBC_xm, xBC_xp][sortindsfx]
+        xBC_y = np.r_[xBC_ym, xBC_yp][sortindsfy]
+        xBC_z = np.r_[xBC_zm, xBC_zp][sortindsfz]
+
+        yBC_x = np.r_[yBC_xm, yBC_xp][sortindsfx]
+        yBC_y = np.r_[yBC_ym, yBC_yp][sortindsfy]
+        yBC_z = np.r_[yBC_zm, yBC_zp][sortindsfz]
+
+        xBC = np.r_[xBC_x, xBC_y, xBC_z]
+        yBC = np.r_[yBC_x, yBC_y, yBC_z]
+
+    return xBC, yBC

SimPEG/EM/Static/DC/FieldsDC.py

@@ -0,0 +1,154 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+import SimPEG
+from SimPEG.Utils import Identity, Zero
+import numpy as np
+from scipy.constants import epsilon_0
+
+class Fields(SimPEG.Problem.Fields):
+    knownFields = {}
+    dtype = float
+
+    def _phiDeriv(self, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_phiDeriv_u', None) is None or getattr(self, '_phiDeriv_m', None) is None:
+            raise NotImplementedError ('Getting phiDerivs from %s is not implemented' %list(self.knownFields.keys())[0])
+
+        if adjoint:
+            return self._phiDeriv_u(src, v, adjoint=adjoint), self._phiDeriv_m(src, v, adjoint=adjoint)
+
+        return np.array(self._phiDeriv_u(src, du_dm_v, adjoint) + self._phiDeriv_m(src, v, adjoint), dtype = float)
+
+    def _eDeriv(self, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_eDeriv_u', None) is None or getattr(self, '_eDeriv_m', None) is None:
+            raise NotImplementedError ('Getting eDerivs from %s is not implemented' %list(self.knownFields.keys())[0])
+
+        if adjoint:
+            return self._eDeriv_u(src, v, adjoint), self._eDeriv_m(src, v, adjoint)
+        return np.array(self._eDeriv_u(src, du_dm_v, adjoint) + self._eDeriv_m(src, v, adjoint), dtype = float)
+
+    def _jDeriv(self, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_jDeriv_u', None) is None or getattr(self, '_jDeriv_m', None) is None:
+            raise NotImplementedError ('Getting jDerivs from %s is not implemented' %list(self.knownFields.keys())[0])
+
+        if adjoint:
+            return self._jDeriv_u(src, v, adjoint), self._jDeriv_m(src, v, adjoint)
+        return np.array(self._jDeriv_u(src, du_dm_v, adjoint) + self._jDeriv_m(src, v, adjoint), dtype = float)
+
+
+class Fields_CC(Fields):
+    knownFields = {'phiSolution':'CC'}
+    aliasFields = {
+                    'phi': ['phiSolution','CC','_phi'],
+                    'j' : ['phiSolution','F','_j'],
+                    'e' : ['phiSolution','F','_e'],
+                    'charge' : ['phiSolution','CC','_charge'],
+                  }
+                  # primary - secondary
+                  # CC variables
+
+    def __init__(self, mesh, survey, **kwargs):
+        Fields.__init__(self, mesh, survey, **kwargs)
+        mesh.setCellGradBC("neumann")
+        cellGrad = mesh.cellGrad
+    def startup(self):
+        self.prob = self.survey.prob
+
+    def _GLoc(self, fieldType):
+        if fieldType == 'phi':
+            return 'CC'
+        elif fieldType == 'e' or fieldType == 'j':
+            return 'F'
+        else:
+            raise Exception('Field type must be phi, e, j')
+
+    def _phi(self, phiSolution, srcList):
+        return phiSolution
+
+    def _phiDeriv_u(self, src, v, adjoint = False):
+        return Identity()*v
+
+    def _phiDeriv_m(self, src, v, adjoint = False):
+        return Zero()
+
+    def _j(self, phiSolution, srcList):
+        """
+            .. math::
+                \mathbf{j} = \mathbf{M}^{f \ -1}_{\rho} \mathbf{G} \phi
+        """
+        return self.prob.MfRhoI*self.prob.Grad*phiSolution
+
+    def _e(self, phiSolution, srcList):
+        """
+            In HJ formulation e is not well-defined!!
+            .. math::
+                \vec{e} = -\nabla \phi
+        """
+        return -self.mesh.cellGrad*phiSolution
+
+    def _charge(self, phiSolution, srcList):
+        """
+            .. math::
+                \int \nabla \codt \vec{e} =  \int \frac{\rho_v }{\epsillon_0}
+        """
+        return epsilon_0*self.prob.Vol*(self.mesh.faceDiv*self._e(phiSolution, srcList))
+
+class Fields_N(Fields):
+    knownFields = {'phiSolution':'N'}
+    aliasFields = {
+                    'phi': ['phiSolution','N','_phi'],
+                    'j' : ['phiSolution','E','_j'],
+                    'e' : ['phiSolution','E','_e'],
+                    'charge' : ['phiSolution','N','_charge'],
+                  }
+                  # primary - secondary
+                  # N variables
+
+    def __init__(self, mesh, survey, **kwargs):
+        Fields.__init__(self, mesh, survey, **kwargs)
+
+    def startup(self):
+        self.prob = self.survey.prob
+
+    def _GLoc(self, fieldType):
+        if fieldType == 'phi':
+            return 'N'
+        elif fieldType == 'e' or fieldType == 'j':
+            return 'E'
+        else:
+            raise Exception('Field type must be phi, e, j')
+
+    def _phi(self, phiSolution, srcList):
+        return phiSolution
+
+    def _phiDeriv_u(self, src, v, adjoint = False):
+        return Identity()*v
+
+    def _phiDeriv_m(self, src, v, adjoint = False):
+        return Zero()
+
+    def _j(self, phiSolution, srcList):
+        """
+            In EB formulation j is not well-defined!!
+            .. math::
+                \mathbf{j} = - \mathbf{M}^{e}_{\sigma} \mathbf{G} \phi
+        """
+        return self.prob.MeSigma * self._e(phiSolution, srcList)
+
+    def _e(self, phiSolution, srcList):
+        """
+            In HJ formulation e is not well-defined!!
+            .. math::
+                \vec{e} = -\nabla \phi
+        """
+        return -self.mesh.nodalGrad * phiSolution
+
+    def _charge(self, phiSolution, srcList):
+        """
+            .. math::
+                \int \nabla \codt \vec{e} =  \int \frac{\rho_v }{\epsillon_0}
+        """
+        return - epsilon_0*(self.mesh.nodalGrad.T*self.mesh.getEdgeInnerProduct()*self._e(phiSolution, srcList))

SimPEG/EM/Static/DC/FieldsDC_2D.py

@@ -0,0 +1,152 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+import SimPEG
+from SimPEG.Utils import Identity, Zero
+import numpy as np
+
+class Fields_ky(SimPEG.Problem.TimeFields):
+
+    """
+
+    Fancy Field Storage for a 2.5D code.
+
+    u[:,'phi', kyInd] = phi
+    print u[src0,'phi']
+
+    Only one field type is stored for
+    each problem, the rest are computed. The fields obejct acts like an array and is indexed by
+    .. code-block:: python
+        f = problem.fields(m)
+        e = f[srcList,'e']
+        j = f[srcList,'j']
+
+    If accessing all sources for a given field, use the :code:`:`
+    .. code-block:: python
+        f = problem.fields(m)
+        phi = f[:,'phi']
+        e = f[:,'e']
+        b = f[:,'b']
+    The array returned will be size (nE or nF, nSrcs :math:`\\times` nFrequencies)
+    """
+
+    knownFields = {}
+    dtype = float
+
+    def _phiDeriv(self,kyInd, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_phiDeriv_u', None) is None or getattr(self, '_phiDeriv_m', None) is None:
+            raise NotImplementedError ('Getting phiDerivs from %s is not implemented' %list(self.knownFields.keys())[0])
+
+        if adjoint:
+            return self._phiDeriv_u(kyInd, src, v, adjoint=adjoint), self._phiDeriv_m(kyInd, src, v, adjoint=adjoint)
+
+        return np.array(self._phiDeriv_u(kyInd, src, du_dm_v, adjoint) + self._phiDeriv_m(kyInd, src, v, adjoint), dtype = float)
+
+    def _eDeriv(self,kyInd, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_eDeriv_u', None) is None or getattr(self, '_eDeriv_m', None) is None:
+            raise NotImplementedError ('Getting eDerivs from %s is not implemented' %list(self.knownFields.keys())[0])
+
+        if adjoint:
+            return self._eDeriv_u(kyInd, src, v, adjoint), self._eDeriv_m(kyInd, src, v, adjoint)
+        return np.array(self._eDeriv_u(kyInd, src, du_dm_v, adjoint) + self._eDeriv_m(kyInd, src, v, adjoint), dtype = float)
+
+    def _jDeriv(self,kyInd, src, du_dm_v, v, adjoint=False):
+        if getattr(self, '_jDeriv_u', None) is None or getattr(self, '_jDeriv_m', None) is None:
+            raise NotImplementedError ('Getting jDerivs from %s is not implemented' %list(self.knownFields.keys())[0])
+
+        if adjoint:
+            return self._jDeriv_u(kyInd, src, v, adjoint), self._jDeriv_m(kyInd, src, v, adjoint)
+        return np.array(self._jDeriv_u(kyInd, src, du_dm_v, adjoint) + self._jDeriv_m(kyInd, src, v, adjoint), dtype = float)
+
+
+    # def _eDeriv(self, tInd, src, dun_dm_v, v, adjoint=False):
+    #     if adjoint is True:
+    #         return self._eDeriv_u(tInd, src, v, adjoint), self._eDeriv_m(tInd, src, v, adjoint)
+    #     return self._eDeriv_u(tInd, src, dun_dm_v) + self._eDeriv_m(tInd, src, v)
+
+    # def _bDeriv(self, tInd, src, dun_dm_v, v, adjoint=False):
+    #     if adjoint is True:
+    #         return self._bDeriv_u(tInd, src, v, adjoint), self._bDeriv_m(tInd, src, v, adjoint)
+    #     return self._bDeriv_u(tInd, src, dun_dm_v) + self._bDeriv_m(tInd, src, v)
+
+
+class Fields_ky_CC(Fields_ky):
+    knownFields = {'phiSolution':'CC'}
+    aliasFields = {
+                    'phi': ['phiSolution','CC','_phi'],
+                    'j' : ['phiSolution','F','_j'],
+                    'e' : ['phiSolution','F','_e'],
+                  }
+                  # primary - secondary
+                  # CC variables
+
+    def __init__(self, mesh, survey, **kwargs):
+        Fields_ky.__init__(self, mesh, survey, **kwargs)
+
+    def startup(self):
+        self.prob = self.survey.prob
+
+    def _GLoc(self, fieldType):
+        if fieldType == 'phi':
+            return 'CC'
+        elif fieldType == 'e' or fieldType == 'j':
+            return 'F'
+        else:
+            raise Exception('Field type must be phi, e, j')
+
+    def _phi(self, phiSolution, src, kyInd):
+        return phiSolution
+
+    def _phiDeriv_u(self, kyInd, src, v, adjoint = False):
+        return Identity()*v
+
+    def _phiDeriv_m(self, kyInd, src, v, adjoint = False):
+        return Zero()
+
+    def _j(self, phiSolution, srcList):
+        raise NotImplementedError
+
+    def _e(self, phiSolution, srcList):
+        raise NotImplementedError
+
+class Fields_ky_N(Fields_ky):
+    knownFields = {'phiSolution':'N'}
+    aliasFields = {
+                    'phi': ['phiSolution','N','_phi'],
+                    'j' : ['phiSolution','E','_j'],
+                    'e' : ['phiSolution','E','_e'],
+                  }
+                  # primary - secondary
+                  # CC variables
+
+    def __init__(self, mesh, survey, **kwargs):
+        Fields_ky.__init__(self, mesh, survey, **kwargs)
+
+    def startup(self):
+        self.prob = self.survey.prob
+
+    def _GLoc(self, fieldType):
+        if fieldType == 'phi':
+            return 'N'
+        elif fieldType == 'e' or fieldType == 'j':
+            return 'E'
+        else:
+            raise Exception('Field type must be phi, e, j')
+
+    def _phi(self, phiSolution, src, kyInd):
+        return phiSolution
+
+    def _phiDeriv_u(self, kyInd, src, v, adjoint = False):
+        return Identity()*v
+
+    def _phiDeriv_m(self, kyInd, src, v, adjoint = False):
+        return Zero()
+
+    def _j(self, phiSolution, srcList):
+        raise NotImplementedError
+
+    def _e(self, phiSolution, srcList):
+        raise NotImplementedError

SimPEG/EM/Static/DC/ProblemDC.py

@@ -0,0 +1,302 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from SimPEG import Problem, Utils
+from SimPEG.EM.Base import BaseEMProblem
+from .SurveyDC import Survey
+from .FieldsDC import Fields, Fields_CC, Fields_N
+from SimPEG.Utils import sdiag
+import numpy as np
+from SimPEG.Utils import Zero
+from .BoundaryUtils import getxBCyBC_CC
+
+class BaseDCProblem(BaseEMProblem):
+
+    surveyPair = Survey
+    fieldsPair = Fields
+    Ainv = None
+
+    def fields(self, m):
+        self.curModel = m
+
+        if not self.Ainv == None:
+            self.Ainv.clean()
+
+        f = self.fieldsPair(self.mesh, self.survey)
+        A = self.getA()
+        self.Ainv = self.Solver(A, **self.solverOpts)
+        RHS = self.getRHS()
+        u = self.Ainv * RHS
+        Srcs = self.survey.srcList
+        f[Srcs, self._solutionType] = u
+        return f
+
+    def Jvec(self, m, v, f=None):
+
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        Jv = self.dataPair(self.survey) #same size as the data
+
+        A = self.getA()
+
+        for src in self.survey.srcList:
+            u_src = f[src, self._solutionType] # solution vector
+            dA_dm_v = self.getADeriv(u_src, v)
+            dRHS_dm_v = self.getRHSDeriv(src, v)
+            du_dm_v = self.Ainv * ( - dA_dm_v + dRHS_dm_v )
+
+            for rx in src.rxList:
+                df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                df_dm_v = df_dmFun(src, du_dm_v, v, adjoint=False)
+                Jv[src, rx] = rx.evalDeriv(src, self.mesh, f, df_dm_v)
+        return Utils.mkvc(Jv)
+
+    def Jtvec(self, m, v, f=None):
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        # Ensure v is a data object.
+        if not isinstance(v, self.dataPair):
+            v = self.dataPair(self.survey, v)
+
+        Jtv = np.zeros(m.size)
+        AT = self.getA()
+
+
+        for src in self.survey.srcList:
+            u_src = f[src, self._solutionType]
+            for rx in src.rxList:
+                PTv = rx.evalDeriv(src, self.mesh, f, v[src, rx], adjoint=True) # wrt f, need possibility wrt m
+                df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
+
+                ATinvdf_duT = self.Ainv * df_duT
+
+                dA_dmT = self.getADeriv(u_src, ATinvdf_duT, adjoint=True)
+                dRHS_dmT = self.getRHSDeriv(src, ATinvdf_duT, adjoint=True)
+                du_dmT = -dA_dmT + dRHS_dmT
+                Jtv += (df_dmT + du_dmT).astype(float)
+
+        return Utils.mkvc(Jtv)
+
+    def getSourceTerm(self):
+        """
+        takes concept of source and turns it into a matrix
+        """
+        """
+        Evaluates the sources, and puts them in matrix form
+
+        :rtype: (numpy.ndarray, numpy.ndarray)
+        :return: q (nC or nN, nSrc)
+        """
+
+        Srcs = self.survey.srcList
+
+        if self._formulation is 'EB':
+            n = self.mesh.nN
+            # return NotImplementedError
+
+        elif self._formulation is 'HJ':
+            n = self.mesh.nC
+
+        q = np.zeros((n, len(Srcs)))
+
+        for i, src in enumerate(Srcs):
+            q[:,i] = src.eval(self)
+        return q
+
+class Problem3D_CC(BaseDCProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'HJ' # CC potentials means J is on faces
+    fieldsPair    = Fields_CC
+
+    def __init__(self, mesh, **kwargs):
+        BaseDCProblem.__init__(self, mesh, **kwargs)
+        self.setBC()
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI G
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        MfRhoI = self.MfRhoI
+        A = D * MfRhoI * G
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * A
+        return A
+
+    def getADeriv(self, u, v, adjoint= False):
+
+        D = self.Div
+        G = self.Grad
+        MfRhoIDeriv = self.MfRhoIDeriv
+
+        if adjoint:
+            return(MfRhoIDeriv( G * u ).T) * ( D.T * v)
+
+        return D * (MfRhoIDeriv( G * u ) * v)
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+    def setBC(self):
+        if self.mesh.dim==3:
+            fxm,fxp,fym,fyp,fzm,fzp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+            gBFzm = self.mesh.gridFz[fzm,:]
+            gBFzp = self.mesh.gridFz[fzp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+            temp_zm, temp_zp = np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+            alpha_zm, alpha_zp = temp_zm*0., temp_zp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+            beta_zm, beta_zp = temp_zm, temp_zp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+            gamma_zm, gamma_zp = temp_zm*0., temp_zp*0.
+
+            alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp, alpha_zm, alpha_zp]
+            beta =  [beta_xm, beta_xp, beta_ym, beta_yp, beta_zm, beta_zp]
+            gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp, gamma_zm, gamma_zp]
+
+        elif self.mesh.dim==2:
+
+            fxm,fxp,fym,fyp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+
+            alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp]
+            beta =  [beta_xm, beta_xp, beta_ym, beta_yp]
+            gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp]
+
+        x_BC, y_BC = getxBCyBC_CC(self.mesh, alpha, beta, gamma)
+        V = self.Vol
+        self.Div = V * self.mesh.faceDiv
+        P_BC, B = self.mesh.getBCProjWF_simple()
+        M = B*self.mesh.aveCC2F
+        self.Grad = self.Div.T - P_BC*Utils.sdiag(y_BC)*M
+
+
+class Problem3D_N(BaseDCProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'EB' # N potentials means B is on faces
+    fieldsPair    = Fields_N
+
+    def __init__(self, mesh, **kwargs):
+        BaseDCProblem.__init__(self, mesh, **kwargs)
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = G.T MeSigma G
+
+        """
+
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        A = Grad.T * MeSigma * Grad
+
+        # Handling Null space of A
+        A[0,0] = A[0,0] + 1.
+
+        return A
+
+    def getADeriv(self, u, v, adjoint=False):
+        """
+
+        Product of the derivative of our system matrix with respect to the model and a vector
+
+        """
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        if not adjoint:
+            return Grad.T*(self.MeSigmaDeriv(Grad*u)*v)
+        elif adjoint:
+            return self.MeSigmaDeriv(Grad*u).T * (Grad*v)
+
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+
+
+

SimPEG/EM/Static/DC/ProblemDC_2D.py

@@ -0,0 +1,356 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
+from SimPEG import Problem, Utils
+from SimPEG.EM.Base import BaseEMProblem
+from .SurveyDC import Survey, Survey_ky
+from .FieldsDC_2D import Fields_ky, Fields_ky_CC, Fields_ky_N
+from SimPEG.Utils import sdiag
+import numpy as np
+from SimPEG.Utils import Zero
+from .BoundaryUtils import getxBCyBC_CC
+
+class BaseDCProblem_2D(BaseEMProblem):
+
+    surveyPair = Survey_ky
+    fieldsPair = Fields_ky
+    nky = 15
+    kys = np.logspace(-4, 1, nky)
+    Ainv = [None for i in range(nky)]
+    nT = nky # Only for using TimeFields
+
+    def fields(self, m):
+        self.curModel = m
+
+        if not self.Ainv[0] == None:
+            for i in range(self.nky):
+                self.Ainv[i].clean()
+
+        f = self.fieldsPair(self.mesh, self.survey)
+        Srcs = self.survey.srcList
+        for iky in range(self.nky):
+            ky = self.kys[iky]
+            A = self.getA(ky)
+            self.Ainv[iky] = self.Solver(A, **self.solverOpts)
+            RHS = self.getRHS(ky)
+            u = self.Ainv[iky] * RHS
+            f[Srcs, self._solutionType, iky] = u
+        return f
+
+    def Jvec(self, m, v, f=None):
+
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        Jv = self.dataPair(self.survey) #same size as the data
+        Jv0 = self.dataPair(self.survey)
+
+        # Assume y=0.
+        # This needs some thoughts to implement in general when src is dipole
+        dky = np.diff(self.kys)
+        dky = np.r_[dky[0], dky]
+        y = 0.
+
+        #TODO: this loop is pretty slow .. (Parellize)
+        for iky in range(self.nky):
+            ky = self.kys[iky]
+            A = self.getA(ky)
+            for src in self.survey.srcList:
+                u_src = f[src, self._solutionType, iky] # solution vector
+                dA_dm_v = self.getADeriv(ky, u_src, v)
+                dRHS_dm_v = self.getRHSDeriv(ky, src, v)
+                du_dm_v = self.Ainv[iky] * ( - dA_dm_v + dRHS_dm_v )
+                for rx in src.rxList:
+                    df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                    df_dm_v = df_dmFun(iky, src, du_dm_v, v, adjoint=False)
+                    # Trapezoidal intergration
+                    Jv1_temp = 1./np.pi*rx.evalDeriv(ky, src, self.mesh, f, df_dm_v)
+                    if iky==0:
+                        #First assigment
+                        Jv[src, rx] = Jv1_temp*dky[iky]*np.cos(ky*y)
+                    else:
+                        Jv[src, rx] += Jv1_temp*dky[iky]    /2.*np.cos(ky*y)
+                        Jv[src, rx] += Jv0[src, rx]*dky[iky]/2.*np.cos(ky*y)
+                    Jv0[src, rx] = Jv1_temp.copy()
+        return Utils.mkvc(Jv)
+
+    def Jtvec(self, m, v, f=None):
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        # Ensure v is a data object.
+        if not isinstance(v, self.dataPair):
+            v = self.dataPair(self.survey, v)
+
+        Jtv = np.zeros(m.size, dtype=float)
+
+        # Assume y=0.
+        # This needs some thoughts to implement in general when src is dipole
+        dky = np.diff(self.kys)
+        dky = np.r_[dky[0], dky]
+        y = 0.
+
+        for src in self.survey.srcList:
+            for rx in src.rxList:
+                Jtv_temp1 = np.zeros(m.size, dtype=float)
+                Jtv_temp0 = np.zeros(m.size, dtype=float)
+                #TODO: this loop is pretty slow .. (Parellize)
+                for iky in range(self.nky):
+                    u_src = f[src, self._solutionType, iky]
+                    ky = self.kys[iky]
+                    AT = self.getA(ky)
+                    PTv = rx.evalDeriv(ky, src, self.mesh, f, v[src, rx], adjoint=True) # wrt f, need possibility wrt m
+                    df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                    df_duT, df_dmT = df_duTFun(iky, src, None, PTv, adjoint=True)
+
+                    ATinvdf_duT = self.Ainv[iky] * df_duT
+
+                    dA_dmT = self.getADeriv(ky, u_src, ATinvdf_duT, adjoint=True)
+                    dRHS_dmT = self.getRHSDeriv(ky, src, ATinvdf_duT, adjoint=True)
+                    du_dmT = -dA_dmT + dRHS_dmT
+                    Jtv_temp1 = 1./np.pi*(df_dmT + du_dmT).astype(float)
+                    # Trapezoidal intergration
+                    if iky==0:
+                        #First assigment
+                        Jtv += Jtv_temp1*dky[iky]*np.cos(ky*y)
+                    else:
+                        Jtv += Jtv_temp1*dky[iky]/2.*np.cos(ky*y)
+                        Jtv += Jtv_temp0*dky[iky]/2.*np.cos(ky*y)
+                    Jtv_temp0 = Jtv_temp1.copy()
+        return Utils.mkvc(Jtv)
+
+    def getSourceTerm(self, ky):
+        """
+        takes concept of source and turns it into a matrix
+        """
+        """
+        Evaluates the sources, and puts them in matrix form
+
+        :rtype: (numpy.ndarray, numpy.ndarray)
+        :return: q (nC or nN, nSrc)
+        """
+
+        Srcs = self.survey.srcList
+
+        if self._formulation is 'EB':
+            n = self.mesh.nN
+            # return NotImplementedError
+
+        elif self._formulation is 'HJ':
+            n = self.mesh.nC
+
+        q = np.zeros((n, len(Srcs)))
+
+        for i, src in enumerate(Srcs):
+            q[:,i] = src.eval(self)
+        return q
+
+class Problem2D_CC(BaseDCProblem_2D):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'HJ' # CC potentials means J is on faces
+    fieldsPair    = Fields_ky_CC
+
+    def __init__(self, mesh, **kwargs):
+        BaseDCProblem_2D.__init__(self, mesh, **kwargs)
+        self.setBC()
+
+    def getA(self, ky):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI G
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        vol = self.mesh.vol
+        MfRhoI = self.MfRhoI
+        # Get resistivity rho
+        rho = self.curModel.rho
+        A = D * MfRhoI * G + Utils.sdiag(ky**2*vol/rho)
+        return A
+
+    def getADeriv(self, ky, u, v, adjoint= False):
+
+        D = self.Div
+        G = self.Grad
+        vol = self.mesh.vol
+        MfRhoIDeriv = self.MfRhoIDeriv
+        rho = self.curModel.rho
+        if adjoint:
+            return(MfRhoIDeriv( G * u ).T) * ( D.T * v) + ky**2*Utils.sdiag(u.flatten()*vol*(-1./rho**2))*v
+        return D * ((MfRhoIDeriv( G * u )) * v) + ky**2*Utils.sdiag(u.flatten()*vol*(-1./rho**2))*v
+
+    def getRHS(self, ky):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm(ky)
+        return RHS
+
+    def getRHSDeriv(self, ky, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, ky, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+    def setBC(self):
+        if self.mesh.dim==3:
+            fxm,fxp,fym,fyp,fzm,fzp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+            gBFzm = self.mesh.gridFz[fzm,:]
+            gBFzp = self.mesh.gridFz[fzp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+            temp_zm, temp_zp = np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+            alpha_zm, alpha_zp = temp_zm*0., temp_zp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+            beta_zm, beta_zp = temp_zm, temp_zp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+            gamma_zm, gamma_zp = temp_zm*0., temp_zp*0.
+
+            alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp, alpha_zm, alpha_zp]
+            beta =  [beta_xm, beta_xp, beta_ym, beta_yp, beta_zm, beta_zp]
+            gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp, gamma_zm, gamma_zp]
+
+        elif self.mesh.dim==2:
+
+            fxm,fxp,fym,fyp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+
+            alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp]
+            beta =  [beta_xm, beta_xp, beta_ym, beta_yp]
+            gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp]
+
+        x_BC, y_BC = getxBCyBC_CC(self.mesh, alpha, beta, gamma)
+        V = self.Vol
+        self.Div = V * self.mesh.faceDiv
+        P_BC, B = self.mesh.getBCProjWF_simple()
+        M = B*self.mesh.aveCC2F
+        self.Grad = self.Div.T - P_BC*Utils.sdiag(y_BC)*M
+
+class Problem2D_N(BaseDCProblem_2D):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'EB' # CC potentials means J is on faces
+    fieldsPair    = Fields_ky_N
+
+    def __init__(self, mesh, **kwargs):
+        BaseDCProblem_2D.__init__(self, mesh, **kwargs)
+        # self.setBC()
+
+    @property
+    def MnSigma(self):
+        """
+            Node inner product matrix for \\(\\sigma\\). Used in the E-B formulation
+        """
+        # TODO: only works isotropic sigma
+        sigma = self.curModel.sigma
+        vol = self.mesh.vol
+        MnSigma = Utils.sdiag(self.mesh.aveN2CC.T*(Utils.sdiag(vol)*sigma))
+
+        return MnSigma
+
+    def MnSigmaDeriv(self, u):
+        """
+            Derivative of MnSigma with respect to the model
+        """
+        sigma = self.curModel.sigma
+        sigmaderiv = self.curModel.sigmaDeriv
+        vol = self.mesh.vol
+        return Utils.sdiag(u)*self.mesh.aveN2CC.T*Utils.sdiag(vol) * self.curModel.sigmaDeriv
+
+    def getA(self, ky):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI G
+
+        """
+
+        MeSigma = self.MeSigma
+        MnSigma = self.MnSigma
+        Grad = self.mesh.nodalGrad
+        # Get conductivity sigma
+        sigma = self.curModel.sigma
+        A = Grad.T * MeSigma * Grad + ky**2*MnSigma
+
+        # Handling Null space of A
+        A[0,0] = A[0,0] + 1.
+        return A
+
+    def getADeriv(self, ky, u, v, adjoint= False):
+
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        sigma = self.curModel.sigma
+        vol = self.mesh.vol
+
+        if adjoint:
+            return self.MeSigmaDeriv(Grad*u).T * (Grad*v) + ky**2*self.MnSigmaDeriv(u).T*v
+        return Grad.T*(self.MeSigmaDeriv(Grad*u)*v) + ky**2*self.MnSigmaDeriv(u)*v
+
+    def getRHS(self, ky):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm(ky)
+        return RHS
+
+    def getRHSDeriv(self, ky, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, ky, adjoint=adjoint)
+        # return qDeriv
+        return Zero()

SimPEG/EM/Static/DC/RxDC.py

@@ -0,0 +1,136 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
+import SimPEG
+import numpy as np
+from SimPEG.Utils import Zero, closestPoints
+
+class BaseRx(SimPEG.Survey.BaseRx):
+    locs = None
+    rxType = None
+
+    knownRxTypes = {
+                    'phi':['phi',None],
+                    'ex':['e','x'],
+                    'ey':['e','y'],
+                    'ez':['e','z'],
+                    'jx':['j','x'],
+                    'jy':['j','y'],
+                    'jz':['j','z'],
+                    }
+
+    def __init__(self, locs, rxType, **kwargs):
+        SimPEG.Survey.BaseRx.__init__(self, locs, rxType, **kwargs)
+
+
+    @property
+    def projField(self):
+        """Field Type projection (e.g. e b ...)"""
+        return self.knownRxTypes[self.rxType][0]
+
+    def projGLoc(self, f):
+        """Grid Location projection (e.g. Ex Fy ...)"""
+        comp = self.knownRxTypes[self.rxType][1]
+        if comp is not None:
+            return f._GLoc(self.rxType) + comp
+        return f._GLoc(self.rxType)
+
+    def eval(self, src, mesh, f):
+        P = self.getP(mesh, self.projGLoc(f))
+        return P*f[src, self.projField]
+
+    def evalDeriv(self, src, mesh, f, v, adjoint=False):
+        P = self.getP(mesh, self.projGLoc(f))
+        if not adjoint:
+            return P*v
+        elif adjoint:
+            return P.T*v
+
+# DC.Rx.Dipole(locs)
+class Dipole(BaseRx):
+
+    def __init__(self, locsM, locsN, rxType = 'phi', **kwargs):
+        assert locsM.shape == locsN.shape, 'locsM and locsN need to be the same size'
+        locs = [locsM, locsN]
+        # We may not need this ...
+        BaseRx.__init__(self, locs, rxType)
+
+    @property
+    def nD(self):
+        """Number of data in the receiver."""
+        return self.locs[0].shape[0]
+
+        # Not sure why ...
+        # return int(self.locs[0].size / 2)
+
+
+    def getP(self, mesh, Gloc):
+        if mesh in self._Ps:
+            return self._Ps[mesh]
+
+        P0 = mesh.getInterpolationMat(self.locs[0], Gloc)
+        P1 = mesh.getInterpolationMat(self.locs[1], Gloc)
+        P = P0 - P1
+
+        if self.storeProjections:
+            self._Ps[mesh] = P
+
+        return P
+
+
+class Dipole_ky(BaseRx):
+
+    def __init__(self, locsM, locsN, rxType = 'phi', **kwargs):
+        assert locsM.shape == locsN.shape, 'locsM and locsN need to be the same size'
+        locs = [locsM, locsN]
+        # We may not need this ...
+        BaseRx.__init__(self, locs, rxType)
+
+    @property
+    def nD(self):
+        """Number of data in the receiver."""
+        return self.locs[0].shape[0]
+
+        # Not sure why ...
+        # return int(self.locs[0].size / 2)
+
+    def getP(self, mesh, Gloc):
+        if mesh in self._Ps:
+            return self._Ps[mesh]
+
+        P0 = mesh.getInterpolationMat(self.locs[0], Gloc)
+        P1 = mesh.getInterpolationMat(self.locs[1], Gloc)
+        P = P0 - P1
+        if self.storeProjections:
+            self._Ps[mesh] = P
+        return P
+
+    def eval(self, kys, src, mesh, f):
+        P = self.getP(mesh, self.projGLoc(f))
+        Pf = P*f[src, self.projField,:]
+        return self.IntTrapezoidal(kys, Pf, y=0.)
+
+    def evalDeriv(self, ky, src, mesh, f, v, adjoint=False):
+        P = self.getP(mesh, self.projGLoc(f))
+        if not adjoint:
+            return P*v
+        elif adjoint:
+            return P.T*v
+
+    def IntTrapezoidal(self, kys, Pf, y=0.):
+        phi = np.zeros(Pf.shape[0])
+        nky = kys.size
+        dky = np.diff(kys)
+        dky = np.r_[dky[0], dky]
+        phi0 = 1./np.pi*Pf[:,0]
+        for iky in range(nky):
+            phi1 = 1./np.pi*Pf[:,iky]
+            phi += phi1*dky[iky]/2.*np.cos(kys[iky]*y)
+            phi += phi0*dky[iky]/2.*np.cos(kys[iky]*y)
+            phi0 = phi1.copy()
+        return phi
+

SimPEG/EM/Static/DC/SrcDC.py

@@ -0,0 +1,92 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+import SimPEG
+# from SimPEG.EM.Base import BaseEMSurvey
+from SimPEG.Utils import Zero, closestPoints, mkvc
+import numpy as np
+
+class BaseSrc(SimPEG.Survey.BaseSrc):
+
+    current = 1.0
+    loc = None
+
+    def __init__(self, rxList, **kwargs):
+        SimPEG.Survey.BaseSrc.__init__(self, rxList, **kwargs)
+
+    def eval(self, prob):
+        raise NotImplementedError
+
+    def evalDeriv(self, prob):
+        return Zero()
+
+
+class Dipole(BaseSrc):
+
+    def __init__(self, rxList, locA, locB, **kwargs):
+        assert locA.shape == locB.shape, 'Shape of locA and locB should be the same'
+        self.loc = [locA, locB]
+        BaseSrc.__init__(self, rxList, **kwargs)
+
+    def eval(self, prob):
+        if prob._formulation == 'HJ':
+            inds = closestPoints(prob.mesh, self.loc, gridLoc='CC')
+            q = np.zeros(prob.mesh.nC)
+            q[inds] = self.current * np.r_[1., -1.]
+        elif prob._formulation == 'EB':
+            qa = prob.mesh.getInterpolationMat(self.loc[0], locType='N').todense()
+            qb = -prob.mesh.getInterpolationMat(self.loc[1], locType='N').todense()
+            q = self.current * mkvc(qa+qb)
+        return q
+
+class Pole(BaseSrc):
+
+    def __init__(self, rxList, loc, **kwargs):
+        BaseSrc.__init__(self, rxList, loc=loc, **kwargs)
+
+    def eval(self, prob):
+        if prob._formulation == 'HJ':
+            inds = closestPoints(prob.mesh, self.loc)
+            q = np.zeros(prob.mesh.nC)
+            q[inds] = self.current * np.r_[1.]
+        elif prob._formulation == 'EB':
+            q = prob.mesh.getInterpolationMat(self.loc, locType='N').todense()
+            q = self.current * mkvc(q)
+        return q
+
+
+# class Dipole_ky(BaseSrc):
+
+#     def __init__(self, rxList, locA, locB, **kwargs):
+#         assert locA.shape == locB.shape, 'Shape of locA and locB should be the same'
+#         self.loc = [locA[[0,2]], locB[[0,2]]]
+#         BaseSrc.__init__(self, rxList, **kwargs)
+
+#     def eval(self, prob):
+#         if prob._formulation == 'HJ':
+#             inds = closestPoints(prob.mesh, self.loc, gridLoc='CC')
+#             q = np.zeros(prob.mesh.nC)
+#             q[inds] = self.current * np.r_[1., -1.]
+#         elif prob._formulation == 'EB':
+#             qa = prob.mesh.getInterpolationMat(self.loc[0], locType='N').todense()
+#             qb = -prob.mesh.getInterpolationMat(self.loc[1], locType='N').todense()
+#             q = self.current * mkvc(qa+qb)
+#         return q
+
+# class Pole_ky(BaseSrc):
+
+#     def __init__(self, rxList, loc, **kwargs):
+#         BaseSrc.__init__(self, rxList, loc=loc, **kwargs)
+
+#     def eval(self, prob):
+#         if prob._formulation == 'HJ':
+#             inds = closestPoints(prob.mesh, self.loc[[0,2]])
+#             q = np.zeros(prob.mesh.nC)
+#             q[inds] = self.current * np.r_[1.]
+#         elif prob._formulation == 'EB':
+#             q = prob.mesh.getInterpolationMat(self.loc[[0,2]], locType='N').todense()
+#             q = self.current * mkvc(q)
+#         return q

SimPEG/EM/Static/DC/SurveyDC.py

@@ -0,0 +1,44 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+import SimPEG
+from SimPEG.EM.Base import BaseEMSurvey
+from SimPEG import sp, Survey
+from SimPEG.Utils import Zero, Identity
+from .RxDC import BaseRx
+from .SrcDC import BaseSrc
+
+class Survey(BaseEMSurvey):
+    rxPair  = BaseRx
+    srcPair = BaseSrc
+
+    def __init__(self, srcList, **kwargs):
+        self.srcList = srcList
+        BaseEMSurvey.__init__(self, srcList, **kwargs)
+
+class Survey_ky(BaseEMSurvey):
+    rxPair  = BaseRx
+    srcPair = BaseSrc
+
+    def __init__(self, srcList, **kwargs):
+        self.srcList = srcList
+        BaseEMSurvey.__init__(self, srcList, **kwargs)
+
+    def eval(self, f):
+        """
+        Project fields to receiver locations
+        :param Fields u: fields object
+        :rtype: numpy.ndarray
+        :return: data
+        """
+        data = SimPEG.Survey.Data(self)
+        kys = self.prob.kys
+        for src in self.srcList:
+            for rx in src.rxList:
+                data[src, rx] = rx.eval(kys, src, self.mesh, f)
+        return data
+
+

SimPEG/EM/Static/DC/Utils.py

@@ -0,0 +1,45 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
+import numpy as np
+
+def WennerSrcList(nElecs, aSpacing, in2D=False, plotIt=False):
+
+    import SimPEG.EM.Static.DC as DC
+
+    elocs = np.arange(0,aSpacing*nElecs,aSpacing)
+    elocs -= (nElecs*aSpacing - aSpacing)/2
+    space = 1
+    WENNER = np.zeros((0,),dtype=int)
+    for ii in range(nElecs):
+        for jj in range(nElecs):
+            test = np.r_[jj,jj+space,jj+space*2,jj+space*3]
+            if np.any(test >= nElecs):
+                break
+            WENNER = np.r_[WENNER, test]
+        space += 1
+    WENNER = WENNER.reshape((-1,4))
+
+
+    if plotIt:
+        for i, s in enumerate('rbkg'):
+            plt.plot(elocs[WENNER[:,i]],s+'.')
+        plt.show()
+
+    # Create sources and receivers
+    i = 0
+    if in2D:
+        getLoc = lambda ii, abmn: np.r_[elocs[WENNER[ii,abmn]],0]
+    else:
+        getLoc = lambda ii, abmn: np.r_[elocs[WENNER[ii,abmn]],0, 0]
+    srcList = []
+    for i in range(WENNER.shape[0]):
+        rx = DC.Rx.Dipole(getLoc(i,1).reshape([1,-1]),getLoc(i,2).reshape([1,-1]))
+        src = DC.Src.Dipole([rx], getLoc(i,0),getLoc(i,3))
+        srcList += [src]
+
+    return srcList

SimPEG/EM/Static/DC/__init__.py

@@ -0,0 +1,14 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .ProblemDC import Problem3D_CC, Problem3D_N
+from .ProblemDC_2D import Problem2D_CC, Problem2D_N
+from .SurveyDC import Survey, Survey_ky
+from . import SrcDC as Src #Pole
+from . import RxDC as Rx
+from .FieldsDC import Fields_CC
+from .BoundaryUtils import getxBCyBC_CC
+from . import Utils

SimPEG/EM/Static/IP/ProblemIP.py

@@ -0,0 +1,378 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from SimPEG import Problem, Utils, Maps, Mesh
+from SimPEG.EM.Base import BaseEMProblem
+from SimPEG.EM.Static.DC.FieldsDC import Fields, Fields_CC, Fields_N
+from SimPEG.Utils import sdiag
+import numpy as np
+from SimPEG.Utils import Zero
+from SimPEG.EM.Static.DC import getxBCyBC_CC
+from .SurveyIP import Survey
+
+class IPPropMap(Maps.PropMap):
+    """
+        Property Map for IP Problems. The electrical chargeability,
+        (\\(\\eta\\)) is the default inversion property
+    """
+    eta = Maps.Property("Electrical Chargeability", defaultInvProp = True)
+
+class BaseIPProblem(BaseEMProblem):
+
+    surveyPair = Survey
+    fieldsPair = Fields
+    PropMap = IPPropMap
+    Ainv = None
+    sigma = None
+    rho = None
+    f = None
+    Ainv = None
+
+    def fields(self, m):
+        self.curModel = m
+        if self.f is None:
+            self.f = self.fieldsPair(self.mesh, self.survey)
+            if self.Ainv == None:
+                A = self.getA()
+                self.Ainv = self.Solver(A, **self.solverOpts)
+            RHS = self.getRHS()
+            u = self.Ainv * RHS
+            Srcs = self.survey.srcList
+            self.f[Srcs, self._solutionType] = u
+        return self.f
+
+    def Jvec(self, m, v, f=None):
+
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        Jv = self.dataPair(self.survey) #same size as the data
+
+        A = self.getA()
+
+        for src in self.survey.srcList:
+            u_src = f[src, self._solutionType] # solution vector
+            dA_dm_v = self.getADeriv(u_src, v)
+            dRHS_dm_v = self.getRHSDeriv(src, v)
+            du_dm_v = self.Ainv * ( - dA_dm_v + dRHS_dm_v )
+
+            for rx in src.rxList:
+                df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                df_dm_v = df_dmFun(src, du_dm_v, v, adjoint=False)
+                Jv[src, rx] = rx.evalDeriv(src, self.mesh, f, df_dm_v)
+        # Conductivity (d u / d log sigma)
+        if self._formulation is 'EB':
+            return -Utils.mkvc(Jv)
+        # Conductivity (d u / d log rho)
+        if self._formulation is 'HJ':
+            return Utils.mkvc(Jv)
+
+    def Jtvec(self, m, v, f=None):
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        # Ensure v is a data object.
+        if not isinstance(v, self.dataPair):
+            v = self.dataPair(self.survey, v)
+
+        Jtv = np.zeros(m.size)
+        AT = self.getA()
+
+        for src in self.survey.srcList:
+            u_src = f[src, self._solutionType]
+            for rx in src.rxList:
+                PTv = rx.evalDeriv(src, self.mesh, f, v[src, rx], adjoint=True) # wrt f, need possibility wrt m
+                df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
+                ATinvdf_duT = self.Ainv * df_duT
+                dA_dmT = self.getADeriv(u_src, ATinvdf_duT, adjoint=True)
+                dRHS_dmT = self.getRHSDeriv(src, ATinvdf_duT, adjoint=True)
+                du_dmT = -dA_dmT + dRHS_dmT
+                Jtv += (df_dmT + du_dmT).astype(float)
+        # Conductivity ((d u / d log sigma).T)
+        if self._formulation is 'EB':
+            return -Utils.mkvc(Jtv)
+        # Conductivity ((d u / d log rho).T)
+        if self._formulation is 'HJ':
+            return Utils.mkvc(Jtv)
+
+    def getSourceTerm(self):
+        """
+        takes concept of source and turns it into a matrix
+        """
+        """
+        Evaluates the sources, and puts them in matrix form
+
+        :rtype: (numpy.ndarray, numpy.ndarray)
+        :return: q (nC or nN, nSrc)
+        """
+
+        Srcs = self.survey.srcList
+
+        if self._formulation is 'EB':
+            n = self.mesh.nN
+            # return NotImplementedError
+
+        elif self._formulation is 'HJ':
+            n = self.mesh.nC
+
+        q = np.zeros((n, len(Srcs)))
+
+        for i, src in enumerate(Srcs):
+            q[:,i] = src.eval(self)
+        return q
+
+    @property
+    def deleteTheseOnModelUpdate(self):
+        toDelete = []
+        return toDelete
+
+    # assume log rho or log cond
+    @property
+    def MeSigma(self):
+        """
+            Edge inner product matrix for \\(\\sigma\\). Used in the E-B formulation
+        """
+        if getattr(self, '_MeSigma', None) is None:
+            self._MeSigma = self.mesh.getEdgeInnerProduct(self.sigma)
+        return self._MeSigma
+
+    @property
+    def MfRhoI(self):
+        """
+            Inverse of :code:`MfRho`
+        """
+        if getattr(self, '_MfRhoI', None) is None:
+            self._MfRhoI = self.mesh.getFaceInnerProduct(self.rho, invMat=True)
+        return self._MfRhoI
+
+    def MfRhoIDeriv(self,u):
+        """
+            Derivative of :code:`MfRhoI` with respect to the model.
+        """
+
+        dMfRhoI_dI = -self.MfRhoI**2
+        dMf_drho = self.mesh.getFaceInnerProductDeriv(self.rho)(u)
+        drho_dlogrho = Utils.sdiag(self.rho)*self.curModel.etaDeriv
+        return dMfRhoI_dI * ( dMf_drho * ( drho_dlogrho))
+
+    # TODO: This should take a vector
+    def MeSigmaDeriv(self, u):
+        """
+            Derivative of MeSigma with respect to the model
+        """
+        dsigma_dlogsigma = Utils.sdiag(self.sigma)*self.curModel.etaDeriv
+        return self.mesh.getEdgeInnerProductDeriv(self.sigma)(u) * dsigma_dlogsigma
+
+class Problem3D_CC(BaseIPProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'HJ' # CC potentials means J is on faces
+    fieldsPair    = Fields_CC
+
+    def __init__(self, mesh, **kwargs):
+        BaseIPProblem.__init__(self, mesh, **kwargs)
+        self.setBC()
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI G
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        MfRhoI = self.MfRhoI
+        A = D * MfRhoI * G
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * A
+        return A
+
+    def getADeriv(self, u, v, adjoint= False):
+
+        D = self.Div
+        G = self.Grad
+        MfRhoIDeriv = self.MfRhoIDeriv
+
+        if adjoint:
+            # if self._makeASymmetric is True:
+            #     v = V * v
+            return(MfRhoIDeriv( G * u ).T) * ( D.T * v)
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * ( D * ( MfRhoIDeriv( D.T * ( V * u ) ) * v ) )
+        return D * (MfRhoIDeriv( G * u ) * v)
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return self.Vol.T * RHS
+
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+    def setBC(self):
+        if self.mesh.dim==3:
+            fxm,fxp,fym,fyp,fzm,fzp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+            gBFzm = self.mesh.gridFz[fzm,:]
+            gBFzp = self.mesh.gridFz[fzp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+            temp_zm, temp_zp = np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+            alpha_zm, alpha_zp = temp_zm*0., temp_zp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+            beta_zm, beta_zp = temp_zm, temp_zp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+            gamma_zm, gamma_zp = temp_zm*0., temp_zp*0.
+
+            alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp, alpha_zm, alpha_zp]
+            beta =  [beta_xm, beta_xp, beta_ym, beta_yp, beta_zm, beta_zp]
+            gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp, gamma_zm, gamma_zp]
+
+        elif self.mesh.dim==2:
+
+            fxm,fxp,fym,fyp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+
+            alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp]
+            beta =  [beta_xm, beta_xp, beta_ym, beta_yp]
+            gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp]
+
+        x_BC, y_BC = getxBCyBC_CC(self.mesh, alpha, beta, gamma)
+        V = self.Vol
+        self.Div = V * self.mesh.faceDiv
+        P_BC, B = self.mesh.getBCProjWF_simple()
+        M = B*self.mesh.aveCC2F
+        self.Grad = self.Div.T - P_BC*Utils.sdiag(y_BC)*M
+
+
+class Problem3D_N(BaseIPProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'EB' # N potentials means B is on faces
+    fieldsPair    = Fields_N
+
+    def __init__(self, mesh, **kwargs):
+        BaseIPProblem.__init__(self, mesh, **kwargs)
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = G.T MeSigma G
+
+        """
+
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        A = Grad.T * MeSigma * Grad
+
+        # Handling Null space of A
+        A[0,0] = A[0,0] + 1.
+
+        return A
+
+    def getADeriv(self, u, v, adjoint=False):
+        """
+
+        Product of the derivative of our system matrix with respect to the model and a vector
+
+        """
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        if not adjoint:
+            return Grad.T*(self.MeSigmaDeriv(Grad*u)*v)
+        elif adjoint:
+            return self.MeSigmaDeriv(Grad*u).T * (Grad*v)
+
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+if __name__ == '__main__':
+
+
+    cs = 12.5
+    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],x0="CCN")
+    sigma = np.ones(mesh.nC)
+    prob = BaseIPProblem(mesh, sigma=sigma)
+
+

SimPEG/EM/Static/IP/SurveyIP.py

@@ -0,0 +1,29 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+import SimPEG
+from SimPEG.EM.Base import BaseEMSurvey
+from SimPEG import sp, Survey
+from SimPEG.Utils import Zero, Identity
+from SimPEG.EM.Static.DC.SrcDC import BaseSrc
+from SimPEG.EM.Static.DC.RxDC import BaseRx
+
+class Survey(BaseEMSurvey):
+    rxPair  = BaseRx
+    srcPair = BaseSrc
+
+    def __init__(self, srcList, **kwargs):
+        self.srcList = srcList
+        BaseEMSurvey.__init__(self, srcList, **kwargs)
+
+    def dpred(self, m, f=None):
+        """
+            Predicted data.
+
+            .. math::
+                d_\\text{pred} = Pf(m)
+        """
+        return self.prob.Jvec(m, m, f=f)

SimPEG/EM/Static/IP/__init__.py

@@ -0,0 +1,8 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .ProblemIP import Problem3D_CC, Problem3D_N
+from .SurveyIP import Survey

SimPEG/EM/Static/SIP/ProblemSIP.py

@@ -0,0 +1,453 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from builtins import int
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
+from SimPEG import Problem, Utils, Maps, Mesh
+from SimPEG.EM.Base import BaseEMProblem
+from SimPEG.EM.Static.DC.FieldsDC import Fields, Fields_CC, Fields_N
+from SimPEG.Utils import sdiag
+import numpy as np
+from SimPEG.Utils import Zero
+from SimPEG.EM.Static.DC import getxBCyBC_CC
+from .SurveySIP import Survey, Data
+
+class ColeColePropMap(Maps.PropMap):
+    """
+        Property Map for EM Problems. The electrical conductivity (\\(\\sigma\\)) is the default inversion property, and the default value of the magnetic permeability is that of free space (\\(\\mu = 4\\pi\\times 10^{-7} \\) H/m)
+    """
+
+    eta = Maps.Property("Electrical Conductivity", defaultInvProp=True)
+    tau = Maps.Property("Electrical Conductivity", defaultVal=0.1, propertyLink=('taui', Maps.ReciprocalMap))
+    taui   = Maps.Property("Electrical Conductivity", defaultVal=1., propertyLink=('tau', Maps.ReciprocalMap))
+    c   = Maps.Property("Electrical Conductivity", defaultVal=1.)
+
+
+class BaseSIPProblem(BaseEMProblem):
+
+    surveyPair = Survey
+    fieldsPair = Fields
+    dataPair = Data
+    PropMap = ColeColePropMap
+    Ainv = None
+    sigma = None
+    rho = None
+    f = None
+    Ainv = None
+
+    def DebyeTime(self, t):
+        peta = self.curModel.eta*np.exp(-self.curModel.taui*t)
+        return peta
+
+    def EtaDeriv(self, t, v, adjoint=False):
+        v = np.array(v, dtype=float)
+        if adjoint:
+            return self.curModel.etaDeriv.T * (np.exp(-self.curModel.taui*t)*v)
+        else:
+            return np.exp(-self.curModel.taui*t) * (self.curModel.etaDeriv*v)
+
+
+    def TauiDeriv(self, t, v, adjoint=False):
+        v = np.array(v, dtype=float)
+        if adjoint:
+            return -self.curModel.tauiDeriv.T * (self.curModel.eta*t*np.exp(-self.curModel.taui*t)*v)
+        else:
+            return -self.curModel.eta*t*np.exp(-self.curModel.taui*t) * (self.curModel.tauiDeriv*v)
+
+    def fields(self, m):
+        self.curModel = m
+        if self.f is None:
+            self.f = self.fieldsPair(self.mesh, self.survey)
+            if self.Ainv == None:
+                A = self.getA()
+                self.Ainv = self.Solver(A, **self.solverOpts)
+            RHS = self.getRHS()
+            u = self.Ainv * RHS
+            Srcs = self.survey.srcList
+            self.f[Srcs, self._solutionType] = u
+        return self.f
+
+    def forward(self, m, f=None):
+
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+        Jv = self.dataPair(self.survey) #same size as the data
+        # A = self.getA()
+        JvAll = []
+        for tind in range(len(self.survey.times)):
+            #Pseudo-chareability
+            t = self.survey.times[tind]
+            v = self.DebyeTime(t)
+            for src in self.survey.srcList:
+                u_src = f[src, self._solutionType] # solution vector
+                dA_dm_v = self.getADeriv(u_src, v)
+                dRHS_dm_v = self.getRHSDeriv(src, v)
+                du_dm_v = self.Ainv * ( - dA_dm_v + dRHS_dm_v )
+                for rx in src.rxList:
+                    timeindex = rx.getTimeP(self.survey.times)
+                    if timeindex[tind]:
+                        df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                        df_dm_v = df_dmFun(src, du_dm_v, v, adjoint=False)
+                        Jv[src, rx, t] = rx.evalDeriv(src, self.mesh, f, df_dm_v)
+
+        # Conductivity (d u / d log sigma)
+        if self._formulation is 'EB':
+            return -Utils.mkvc(Jv)
+        # Resistivity (d u / d log rho)
+        if self._formulation is 'HJ':
+            return Utils.mkvc(Jv)
+
+    def Jvec(self, m, v, f=None):
+
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+        Jv = self.dataPair(self.survey) #same size as the data
+        # A = self.getA()
+        JvAll = []
+        #Assume only eta and tau (eta first then tau)
+        # v = [2*Mx1]
+        v = v.reshape((v.size//2), 2), order='F')
+
+        for tind in range(len(self.survey.times)):
+            t = self.survey.times[tind]
+            v0 = self.EtaDeriv(t, v[:,0])
+            v1 = self.TauiDeriv(t, v[:,1])
+            for src in self.survey.srcList:
+                u_src = f[src, self._solutionType] # solution vector
+                dA_dm_v0 = self.getADeriv(u_src, v0)
+                dRHS_dm_v0 = self.getRHSDeriv(src, v0)
+                du_dm_v0 = self.Ainv * ( - dA_dm_v0 + dRHS_dm_v0 )
+                dA_dm_v1 = self.getADeriv(u_src, v1)
+                dRHS_dm_v1 = self.getRHSDeriv(src, v1)
+                du_dm_v1 = self.Ainv * ( - dA_dm_v1 + dRHS_dm_v1 )
+                for rx in src.rxList:
+                    timeindex = rx.getTimeP(self.survey.times)
+                    if timeindex[tind]:
+                        df_dmFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                        df_dm_v0 = df_dmFun(src, du_dm_v0, v0, adjoint=False)
+                        df_dm_v1 = df_dmFun(src, du_dm_v1, v1, adjoint=False)
+                        Jv[src, rx, t] = rx.evalDeriv(src, self.mesh, f, df_dm_v0)
+                        Jv[src, rx, t] += rx.evalDeriv(src, self.mesh, f, df_dm_v1)
+        # Conductivity (d u / d log sigma)
+        if self._formulation is 'EB':
+            return -Jv.tovec()
+        # Resistivity (d u / d log rho)
+        if self._formulation is 'HJ':
+            return Jv.tovec()
+
+    def Jtvec(self, m, v, f=None):
+        if f is None:
+            f = self.fields(m)
+
+        self.curModel = m
+
+        # Ensure v is a data object.
+        if not isinstance(v, self.dataPair):
+            v = self.dataPair(self.survey, v)
+
+        Jtv= np.zeros(m.size)
+        for tind in range(len(self.survey.times)):
+            t = self.survey.times[tind]
+            for src in self.survey.srcList:
+                u_src = f[src, self._solutionType]
+                for rx in src.rxList:
+                    timeindex = rx.getTimeP(self.survey.times)
+                    if timeindex[tind]:
+                        PTv = rx.evalDeriv(src, self.mesh, f, v[src, rx, t], adjoint=True) # wrt f, need possibility wrt m
+                        df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
+                        df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
+                        ATinvdf_duT = self.Ainv * df_duT
+                        dA_dmT = self.getADeriv(u_src, ATinvdf_duT, adjoint=True)
+                        dRHS_dmT = self.getRHSDeriv(src, ATinvdf_duT, adjoint=True)
+                        du_dmT = -dA_dmT + dRHS_dmT
+                        Jtv += np.r_[self.EtaDeriv(self.survey.times[tind], du_dmT, adjoint=True), self.TauiDeriv(self.survey.times[tind], du_dmT, adjoint=True)]
+
+        # Conductivity ((d u / d log sigma).T)
+        if self._formulation is 'EB':
+            return -Jtv
+        # Conductivity ((d u / d log rho).T)
+        if self._formulation is 'HJ':
+            return Jtv
+
+    def getSourceTerm(self):
+        """
+        takes concept of source and turns it into a matrix
+        """
+        """
+        Evaluates the sources, and puts them in matrix form
+
+        :rtype: (numpy.ndarray, numpy.ndarray)
+        :return: q (nC or nN, nSrc)
+        """
+
+        Srcs = self.survey.srcList
+
+        if self._formulation is 'EB':
+            n = self.mesh.nN
+            # return NotImplementedError
+
+        elif self._formulation is 'HJ':
+            n = self.mesh.nC
+
+        q = np.zeros((n, len(Srcs)))
+
+        for i, src in enumerate(Srcs):
+            q[:,i] = src.eval(self)
+        return q
+
+    @property
+    def deleteTheseOnModelUpdate(self):
+        toDelete = []
+        return toDelete
+
+    # assume log rho or log cond
+    @property
+    def MeSigma(self):
+        """
+            Edge inner product matrix for \\(\\sigma\\). Used in the E-B formulation
+        """
+        if getattr(self, '_MeSigma', None) is None:
+            self._MeSigma = self.mesh.getEdgeInnerProduct(self.sigma)
+        return self._MeSigma
+
+    @property
+    def MfRhoI(self):
+        """
+            Inverse of :code:`MfRho`
+        """
+        if getattr(self, '_MfRhoI', None) is None:
+            self._MfRhoI = self.mesh.getFaceInnerProduct(self.rho, invMat=True)
+        return self._MfRhoI
+
+    def MfRhoIDeriv(self,u):
+        """
+            Derivative of :code:`MfRhoI` with respect to the model.
+        """
+
+        dMfRhoI_dI = -self.MfRhoI**2
+        dMf_drho = self.mesh.getFaceInnerProductDeriv(self.rho)(u)
+        drho_dlogrho = Utils.sdiag(self.rho)
+        return dMfRhoI_dI * ( dMf_drho * ( drho_dlogrho))
+
+    # TODO: This should take a vector
+    def MeSigmaDeriv(self, u):
+        """
+            Derivative of MeSigma with respect to the model
+        """
+        dsigma_dlogsigma = Utils.sdiag(self.sigma)
+        return self.mesh.getEdgeInnerProductDeriv(self.sigma)(u) * dsigma_dlogsigma
+
+class Problem3D_CC(BaseSIPProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'HJ' # CC potentials means J is on faces
+    fieldsPair    = Fields_CC
+
+    def __init__(self, mesh, **kwargs):
+        BaseSIPProblem.__init__(self, mesh, **kwargs)
+        self.setBC()
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = D MfRhoI G
+
+        """
+
+        D = self.Div
+        G = self.Grad
+        # TODO: this won't work for full anisotropy
+        MfRhoI = self.MfRhoI
+        A = D * MfRhoI * G
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * A
+        return A
+
+    def getADeriv(self, u, v, adjoint= False):
+
+        D = self.Div
+        G = self.Grad
+        MfRhoIDeriv = self.MfRhoIDeriv
+
+        if adjoint:
+            # if self._makeASymmetric is True:
+            #     v = V * v
+            return(MfRhoIDeriv( G * u ).T) * ( D.T * v)
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return V.T * ( D * ( MfRhoIDeriv( D.T * ( V * u ) ) * v ) )
+        return D * (MfRhoIDeriv( G * u ) * v)
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+
+        # I think we should deprecate this for DC problem.
+        # if self._makeASymmetric is True:
+        #     return self.Vol.T * RHS
+
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+    def setBC(self):
+        if self.mesh.dim==3:
+            fxm,fxp,fym,fyp,fzm,fzp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+            gBFzm = self.mesh.gridFz[fzm,:]
+            gBFzp = self.mesh.gridFz[fzp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+            temp_zm, temp_zp = np.ones_like(gBFzm[:,2]), np.ones_like(gBFzp[:,2])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+            alpha_zm, alpha_zp = temp_zm*0., temp_zp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+            beta_zm, beta_zp = temp_zm, temp_zp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+            gamma_zm, gamma_zp = temp_zm*0., temp_zp*0.
+
+            alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp, alpha_zm, alpha_zp]
+            beta =  [beta_xm, beta_xp, beta_ym, beta_yp, beta_zm, beta_zp]
+            gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp, gamma_zm, gamma_zp]
+
+        elif self.mesh.dim==2:
+
+            fxm,fxp,fym,fyp = self.mesh.faceBoundaryInd
+            gBFxm = self.mesh.gridFx[fxm,:]
+            gBFxp = self.mesh.gridFx[fxp,:]
+            gBFym = self.mesh.gridFy[fym,:]
+            gBFyp = self.mesh.gridFy[fyp,:]
+
+            # Setup Mixed B.C (alpha, beta, gamma)
+            temp_xm, temp_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
+            temp_ym, temp_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
+
+            alpha_xm, alpha_xp = temp_xm*0., temp_xp*0.
+            alpha_ym, alpha_yp = temp_ym*0., temp_yp*0.
+
+            beta_xm, beta_xp = temp_xm, temp_xp
+            beta_ym, beta_yp = temp_ym, temp_yp
+
+            gamma_xm, gamma_xp = temp_xm*0., temp_xp*0.
+            gamma_ym, gamma_yp = temp_ym*0., temp_yp*0.
+
+            alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp]
+            beta =  [beta_xm, beta_xp, beta_ym, beta_yp]
+            gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp]
+
+        x_BC, y_BC = getxBCyBC_CC(self.mesh, alpha, beta, gamma)
+        V = self.Vol
+        self.Div = V * self.mesh.faceDiv
+        P_BC, B = self.mesh.getBCProjWF_simple()
+        M = B*self.mesh.aveCC2F
+        self.Grad = self.Div.T - P_BC*Utils.sdiag(y_BC)*M
+
+
+class Problem3D_N(BaseSIPProblem):
+
+    _solutionType = 'phiSolution'
+    _formulation  = 'EB' # N potentials means B is on faces
+    fieldsPair    = Fields_N
+
+    def __init__(self, mesh, **kwargs):
+        BaseSIPProblem.__init__(self, mesh, **kwargs)
+
+    def getA(self):
+        """
+
+        Make the A matrix for the cell centered DC resistivity problem
+
+        A = G.T MeSigma G
+
+        """
+
+        # TODO: this won't work for full anisotropy
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        A = Grad.T * MeSigma * Grad
+
+        # Handling Null space of A
+        A[0,0] = A[0,0] + 1.
+
+        return A
+
+    def getADeriv(self, u, v, adjoint=False):
+        """
+
+        Product of the derivative of our system matrix with respect to the model and a vector
+
+        """
+        MeSigma = self.MeSigma
+        Grad = self.mesh.nodalGrad
+        if not adjoint:
+            return Grad.T*(self.MeSigmaDeriv(Grad*u)*v)
+        elif adjoint:
+            return self.MeSigmaDeriv(Grad*u).T * (Grad*v)
+
+
+    def getRHS(self):
+        """
+        RHS for the DC problem
+
+        q
+        """
+
+        RHS = self.getSourceTerm()
+        return RHS
+
+    def getRHSDeriv(self, src, v, adjoint=False):
+        """
+        Derivative of the right hand side with respect to the model
+        """
+        # TODO: add qDeriv for RHS depending on m
+        # qDeriv = src.evalDeriv(self, adjoint=adjoint)
+        # return qDeriv
+        return Zero()
+
+if __name__ == '__main__':
+
+
+    cs = 12.5
+    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],x0="CCN")
+    sigma = np.ones(mesh.nC)
+    prob = BaseSIPProblem(mesh, sigma=sigma)
+
+

SimPEG/EM/Static/SIP/Regularization.py

@@ -0,0 +1,211 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
+from SimPEG import Utils, Maps, Mesh, sp, np
+from SimPEG.Regularization import BaseRegularization, Simple
+
+class MultiRegularization(Simple):
+    """
+    **MultiRegularization Class**
+
+    This is used to regularize the model space
+    having multiple models [m1, m2, m3, ...] ::
+
+        reg = Regularization(mesh)
+
+    """
+    nModels = None # Number of models
+    ratios = None  # Ratio for different models
+    crossgrad = False # Use cross gradient or not
+    betacross = 1.
+    wx = []
+    wy = []
+    wz = []
+
+    def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
+        BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
+        if self.nModels == None:
+            raise Exception("Put nModels as a initial input!")
+        if self.ratios == None:
+            self.ratios = [1. for imodel in range(self.nModels)]
+
+    @property
+    def Wsmall(self):
+        """Regularization matrix Wsmall"""
+        if getattr(self,'_Wsmall', None) is None:
+            vecs = []
+            for imodel in range(self.nModels):
+                vecs.append((self.regmesh.vol*self.alpha_s*self.wght*self.ratios[imodel])**0.5)
+            self._Wsmall = Utils.sdiag(np.hstack(vecs))
+        return self._Wsmall
+
+    @property
+    def Wx(self):
+        """Regularization matrix Wx"""
+        if getattr(self, '_Wx', None) is None:
+            mats = []
+            for imodel in range(self.nModels):
+                self.wx.append(Utils.sdiag((self.regmesh.aveCC2Fx * self.regmesh.vol*self.alpha_x*self.ratios[imodel]*(self.regmesh.aveCC2Fx*self.wght))**0.5))
+                mats.append(self.wx[imodel]*self.regmesh.cellDiffxStencil)
+            self._Wx = sp.block_diag(mats)
+        return self._Wx
+
+    @property
+    def Wy(self):
+        """Regularization matrix Wy"""
+        if getattr(self, '_Wy', None) is None:
+            mats = []
+            for imodel in range(self.nModels):
+                self.wy.append(Utils.sdiag((self.regmesh.aveCC2Fy * self.regmesh.vol*self.alpha_y*self.ratios[imodel]*(self.regmesh.aveCC2Fy*self.wght))**0.5))
+                mats.append(self.wy[imodel]*self.regmesh.cellDiffyStencil)
+            self._Wy = sp.block_diag(mats)
+        return self._Wy
+
+    @property
+    def Wz(self):
+        """Regularization matrix Wz"""
+        if getattr(self, '_Wz', None) is None:
+            mats = []
+            for imodel in range(self.nModels):
+                self.wz.append(Utils.sdiag((self.regmesh.aveCC2Fz * self.regmesh.vol*self.alpha_z*self.ratios[imodel]*(self.regmesh.aveCC2Fz*self.wght))**0.5))
+                mats.append(self.wz[imodel]*self.regmesh.cellDiffzStencil)
+            self._Wz = sp.block_diag(mats)
+        return self._Wz
+
+    @property
+    def Wsmooth(self):
+        """Full smoothness regularization matrix W"""
+        if getattr(self, '_Wsmooth', None) is None:
+            wlist = (self.Wx,)
+            if self.regmesh.dim > 1:
+                wlist += (self.Wy,)
+            if self.regmesh.dim > 2:
+                wlist += (self.Wz,)
+            self._Wsmooth = sp.vstack(wlist)
+        return self._Wsmooth
+
+    @property
+    def W(self):
+        """Full regularization matrix W"""
+        if getattr(self, '_W', None) is None:
+            wlist = (self.Wsmall, self.Wsmooth)
+            self._W = sp.vstack(wlist)
+        return self._W
+
+
+    @Utils.timeIt
+    def eval(self, m):
+        return self._evalSmall(m) + self._evalSmooth(m)
+
+    @Utils.timeIt
+    def _evalSmall(self, m):
+        r = self.Wsmall * ( self.mapping * (m - self.mref) )
+        return 0.5 * r.dot(r)
+
+    @Utils.timeIt
+    def _evalSmooth(self, m):
+        if self.mrefInSmooth == True:
+            r = self.Wsmooth * ( self.mapping * (m - self.mref) )
+        elif self.mrefInSmooth == False:
+            r = self.Wsmooth * ( self.mapping * m)
+        return 0.5 * r.dot(r)
+
+    def cross(a,b):
+        ax, ay, az = a[0], a[1], a[2]
+        bx, by, bz = b[0], b[1], b[2]
+        cx = ay*bz - az*by
+        cy = az*bx - ax*bz
+        cz = ax*by - ay*bx
+        return [cx, cy, cz]
+
+     # TODO: Implement Cross Gradients..
+    @Utils.timeIt
+    def _evalCross(self, m):
+        if self.crossgrad == False:
+            return 0.
+        elif self.crossgrad == True:
+            M = (self.mapping * m).reshape((self.regmesh.nC, self.nModels), order="F")
+
+            ax = self.regmesh.aveFx2CC*self.regmesh.wx[0]*M[:,0]
+            ay = self.regmesh.aveFy2CC*self.regmesh.wy[0]*M[:,0]
+            az = self.regmesh.aveFz2CC*self.regmesh.wz[0]*M[:,0]
+            bx = self.regmesh.aveFx2CC*self.regmesh.wx[1]*M[:,1]
+            by = self.regmesh.aveFy2CC*self.regmesh.wy[1]*M[:,1]
+            bz = self.regmesh.aveFz2CC*self.regmesh.wz[1]*M[:,1]
+            #ab
+            out_ab = cross([ax, ay, az], [bx, by, bz])
+            r = np.r_[out_ab[0], out_ab[1], out_ab[2]]*np.sqrt(self.betacross)
+
+            if self.nModels == 3:
+                cx = self.regmesh.aveFx2CC*self.regmesh.wx[1]*M[:,1]
+                cy = self.regmesh.aveFy2CC*self.regmesh.wy[1]*M[:,1]
+                cz = self.regmesh.aveFz2CC*self.regmesh.wz[1]*M[:,1]
+                #ac
+                out_ac = cross([ax, ay, az], [cx, cy, cz])
+                #bc
+                out_bc = cross([bx, by, bz], [cx, cy, cz])
+                r = np.r_[r, np.hstack(out_ac)*np.sqrt(self.betacross), np.hstack(out_bc)*np.sqrt(self.betacross)]
+
+            return 0.5 * r.dot(r)
+
+    @Utils.timeIt
+    def evalDeriv(self, m):
+        """
+        The regularization is:
+
+        .. math::
+
+            R(m) = \\frac{1}{2}\mathbf{(m-m_\\text{ref})^\\top W^\\top W(m-m_\\text{ref})}
+
+        So the derivative is straight forward:
+
+        .. math::
+
+            R(m) = \mathbf{W^\\top W (m-m_\\text{ref})}
+
+        """
+        deriv = self._evalSmallDeriv(m) + self._evalSmoothDeriv(m)
+        if self.crossgrad==True:
+            deriv += self._evalCrossDeriv(m)
+        return deriv
+
+    @Utils.timeIt
+    def _evalCrossDeriv(self,m):
+        r = self.Wsmall * ( self.mapping * (m - self.mref) )
+        return r.T * ( self.Wsmall * self.mapping.deriv(m - self.mref) )
+
+    @Utils.timeIt
+    def eval2Deriv(self, m, v=None):
+        """
+        Second derivative
+
+        :param numpy.array m: geophysical model
+        :param numpy.array v: vector to multiply
+        :rtype: scipy.sparse.csr_matrix or numpy.ndarray
+        :return: WtW or WtW*v
+
+        The regularization is:
+
+        .. math::
+
+            R(m) = \\frac{1}{2}\mathbf{(m-m_\\text{ref})^\\top W^\\top W(m-m_\\text{ref})}
+
+        So the second derivative is straight forward:
+
+        .. math::
+
+            R(m) = \mathbf{W^\\top W}
+
+        """
+        mD = self.mapping.deriv(m - self.mref)
+        if v is None:
+            return mD.T * self.W.T * self.W * mD
+
+        return mD.T * ( self.W.T * ( self.W * ( mD * v) ) )
+
+
+

SimPEG/EM/Static/SIP/RxSIP.py

@@ -0,0 +1,94 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+import SimPEG
+import numpy as np
+from SimPEG.Utils import Zero, closestPoints
+
+class BaseRx(SimPEG.Survey.BaseTimeRx):
+    locs = None
+    rxType = None
+
+    knownRxTypes = {
+                    'phi':['phi',None],
+                    'ex':['e','x'],
+                    'ey':['e','y'],
+                    'ez':['e','z'],
+                    'jx':['j','x'],
+                    'jy':['j','y'],
+                    'jz':['j','z'],
+                    }
+
+    def __init__(self, locs, times, rxType, **kwargs):
+        SimPEG.Survey.BaseTimeRx.__init__(self, locs, times, rxType, **kwargs)
+
+    @property
+    def projField(self):
+        """Field Type projection (e.g. e b ...)"""
+        return self.knownRxTypes[self.rxType][0]
+
+    def projGLoc(self, f):
+        """Grid Location projection (e.g. Ex Fy ...)"""
+        comp = self.knownRxTypes[self.rxType][1]
+        if comp is not None:
+            return f._GLoc(self.rxType) + comp
+        return f._GLoc(self.rxType)
+
+    def getTimeP(self, timesall):
+        """
+            Returns the time projection matrix.
+
+            .. note::
+
+                This is not stored in memory, but is created on demand.
+        """
+        time_inds = np.in1d(timesall, self.times)
+        return time_inds
+
+    def evalDeriv(self, src, mesh, f, v, adjoint=False):
+        P = self.getP(mesh, self.projGLoc(f))
+        if not adjoint:
+            return P*v
+        elif adjoint:
+            return P.T*v
+
+
+# DC.Rx.Dipole(locs)
+class Dipole(BaseRx):
+
+    def __init__(self, locsM, locsN, times, rxType = 'phi', **kwargs):
+        assert locsM.shape == locsN.shape, 'locsM and locsN need to be the same size'
+        locs = [locsM, locsN]
+        # We may not need this ...
+        BaseRx.__init__(self, locs, times, rxType)
+
+    @property
+    def nD(self):
+        """Number of data in the receiver."""
+        # return self.locs[0].shape[0] * len(self.times)
+        return self.locs[0].shape[0]
+
+    @property
+    def nRx(self):
+        """Number of data in the receiver."""
+        return self.locs[0].shape[0]
+
+        # Not sure why ...
+        # return int(self.locs[0].size / 2)
+
+
+    def getP(self, mesh, Gloc):
+        if mesh in self._Ps:
+            return self._Ps[mesh]
+
+        P0 = mesh.getInterpolationMat(self.locs[0], Gloc)
+        P1 = mesh.getInterpolationMat(self.locs[1], Gloc)
+        P = P0 - P1
+
+        if self.storeProjections:
+            self._Ps[mesh] = P
+
+        return P

SimPEG/EM/Static/SIP/SrcSIP.py

@@ -0,0 +1,70 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+import SimPEG
+# from SimPEG.EM.Base import BaseEMSurvey
+from SimPEG.Utils import Zero, closestPoints, mkvc
+import numpy as np
+
+class BaseSrc(SimPEG.Survey.BaseSrc):
+
+    current = 1.0
+    loc = None
+
+    def __init__(self, rxList, **kwargs):
+        SimPEG.Survey.BaseSrc.__init__(self, rxList, **kwargs)
+
+    def eval(self, prob):
+        raise NotImplementedError
+
+    def evalDeriv(self, prob):
+        return Zero()
+
+    @property
+    def nD(self):
+        """Number of data"""
+        return self.vnD.sum()
+
+    @property
+    def vnD(self):
+        """Vector number of data"""
+        return np.array([rx.nD*len(rx.times) for rx in self.rxList])
+
+
+
+class Dipole(BaseSrc):
+
+    def __init__(self, rxList, locA, locB, **kwargs):
+        assert locA.shape == locB.shape, 'Shape of locA and locB should be the same'
+        self.loc = [locA, locB]
+        BaseSrc.__init__(self, rxList, **kwargs)
+
+    def eval(self, prob):
+        if prob._formulation == 'HJ':
+            inds = closestPoints(prob.mesh, self.loc, gridLoc='CC')
+            q = np.zeros(prob.mesh.nC)
+            q[inds] = self.current * np.r_[1., -1.]
+        elif prob._formulation == 'EB':
+            qa = prob.mesh.getInterpolationMat(self.loc[0], locType='N').todense()
+            qb = -prob.mesh.getInterpolationMat(self.loc[1], locType='N').todense()
+            q = self.current * mkvc(qa+qb)
+        return q
+
+class Pole(BaseSrc):
+
+    def __init__(self, rxList, loc, **kwargs):
+        BaseSrc.__init__(self, rxList, loc=loc, **kwargs)
+
+    def eval(self, prob):
+        if prob._formulation == 'HJ':
+            inds = closestPoints(prob.mesh, self.loc)
+            q = np.zeros(prob.mesh.nC)
+            q[inds] = self.current * np.r_[1.]
+        elif prob._formulation == 'EB':
+            q = prob.mesh.getInterpolationMat(self.loc, locType='N').todense()
+            q = self.current * mkvc(q)
+        return q
+

SimPEG/EM/Static/SIP/SurveySIP.py

@@ -0,0 +1,109 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import str
+import SimPEG
+from SimPEG.EM.Base import BaseEMSurvey
+from SimPEG import np, sp, Survey, Utils
+from SimPEG.Utils import Zero, Identity
+from SimPEG.EM.Static.SIP.SrcSIP import BaseSrc
+from SimPEG.EM.Static.SIP.RxSIP import BaseRx
+import uuid
+
+
+class Survey(BaseEMSurvey):
+    rxPair  = BaseRx
+    srcPair = BaseSrc
+    times = None
+
+    def __init__(self, srcList, **kwargs):
+        self.srcList = srcList
+        BaseEMSurvey.__init__(self, srcList, **kwargs)
+        self.getUniqueTimes()
+
+    def getUniqueTimes(self):
+        time_rx = []
+        for src in self.srcList:
+            for rx in src.rxList:
+                time_rx.append(rx.times)
+        self.times = np.unique(np.hstack(time_rx))
+
+    def dpred(self, m, f=None):
+        """
+            Predicted data.
+
+            .. math::
+                d_\\text{pred} = Pf(m)
+        """
+        return self.prob.forward(m, f=f)
+
+
+class Data(SimPEG.Survey.Data):
+    """Fancy data storage by Src and Rx"""
+
+    def __init__(self, survey, v=None):
+        self.uid = str(uuid.uuid4())
+        self.survey = survey
+        self._dataDict = {}
+        for src in self.survey.srcList:
+            self._dataDict[src] = {}
+            for rx in src.rxList:
+                self._dataDict[src][rx] = {}
+
+        if v is not None:
+            self.fromvec(v)
+
+    def _ensureCorrectKey(self, key):
+        if type(key) is tuple:
+            if len(key) is not 3:
+                raise KeyError('Key must be [Src, Rx, tInd]')
+            if key[0] not in self.survey.srcList:
+                raise KeyError('Src Key must be a source in the survey.')
+            if key[1] not in key[0].rxList:
+                raise KeyError('Rx Key must be a receiver for the source.')
+            return key
+        elif isinstance(key, self.survey.srcPair):
+            if key not in self.survey.srcList:
+                raise KeyError('Key must be a source in the survey.')
+            return key, None, None
+        else:
+            raise KeyError('Key must be [Src] or [Src,Rx] or [Src, Rx, tInd]')
+
+    def __setitem__(self, key, value):
+        src, rx, t = self._ensureCorrectKey(key)
+        assert rx is not None, 'set data using [Src, Rx]'
+        assert isinstance(value, np.ndarray), 'value must by ndarray'
+        assert value.size == rx.nD, "value must have the same number of data as the source."
+        self._dataDict[src][rx][t] = Utils.mkvc(value)
+
+    def __getitem__(self, key):
+        src, rx, t = self._ensureCorrectKey(key)
+        if rx is not None:
+            if rx not in self._dataDict[src]:
+                raise Exception('Data for receiver has not yet been set.')
+            return self._dataDict[src][rx][t]
+
+        return np.concatenate([self[src,rx, t] for rx in src.rxList])
+
+    def tovec(self):
+        val = []
+        for src in self.survey.srcList:
+            for rx in src.rxList:
+                for t in rx.times:
+                    val.append(self[src, rx, t])
+        return np.concatenate(val)
+
+
+    def fromvec(self, v):
+        v = Utils.mkvc(v)
+        assert v.size == self.survey.nD, 'v must have the correct number of data.'
+        indBot, indTop = 0, 0
+        for src in self.survey.srcList:
+            for rx in src.rxList:
+                for t in rx.times:
+                    indTop += rx.nRx
+                    self[src, rx, t] = v[indBot:indTop]
+                    indBot += rx.nRx

SimPEG/EM/Static/SIP/__init__.py

@@ -0,0 +1,11 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .ProblemSIP import Problem3D_CC, Problem3D_N
+from .SurveySIP import Survey, Data
+from . import SrcSIP as Src #Pole
+from . import RxSIP as Rx
+from .Regularization import MultiRegularization

SimPEG/EM/Static/Utils/StaticUtils.py

@@ -0,0 +1,325 @@
+from __future__ import print_function
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import absolute_import
+from builtins import int
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
+from SimPEG import np
+from SimPEG.EM.Static import DC, IP
+
+def plot_pseudoSection(DCsurvey, axs, stype='dpdp', dtype="appc", clim=None):
+    """
+        Read list of 2D tx-rx location and plot a speudo-section of apparent
+        resistivity.
+
+        Assumes flat topo for now...
+
+        Input:
+        :param d2D, z0
+        :switch stype -> Either 'pdp' (pole-dipole) | 'dpdp' (dipole-dipole)
+        :switch dtype=-> Either 'appr' (app. res) | 'appc' (app. con) | 'volt' (potential)
+        Output:
+        :figure scatter plot overlayed on image
+
+        Edited Feb 17th, 2016
+
+        @author: dominiquef
+
+    """
+    from SimPEG import np
+    from scipy.interpolate import griddata
+    import pylab as plt
+
+    # Set depth to 0 for now
+    z0 = 0.
+
+    # Pre-allocate
+    midx = []
+    midz = []
+    rho = []
+    LEG = []
+    count = 0 # Counter for data
+    for ii in range(DCsurvey.nSrc):
+
+        Tx = DCsurvey.srcList[ii].loc
+        Rx = DCsurvey.srcList[ii].rxList[0].locs
+
+        nD = DCsurvey.srcList[ii].rxList[0].nD
+
+        data = DCsurvey.dobs[count:count+nD]
+        count += nD
+
+        # Get distances between each poles A-B-M-N
+        if stype == 'pdp':
+            MA = np.abs(Tx[0] - Rx[0][:,0])
+            NA = np.abs(Tx[0] - Rx[1][:,0])
+            MN = np.abs(Rx[1][:,0] - Rx[0][:,0])
+
+            # Create mid-point location
+            Cmid = Tx[0]
+            Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
+            if DCsurvey.mesh.dim == 2:
+                zsrc = Tx[1]
+            elif DCsurvey.mesh.dim ==3:
+                zsrc = Tx[2]
+
+        elif stype == 'dpdp':
+            MA = np.abs(Tx[0][0] - Rx[0][:,0])
+            MB = np.abs(Tx[1][0] - Rx[0][:,0])
+            NA = np.abs(Tx[0][0] - Rx[1][:,0])
+            NB = np.abs(Tx[1][0] - Rx[1][:,0])
+
+            # Create mid-point location
+            Cmid = (Tx[0][0] + Tx[1][0])/2
+            Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
+            if DCsurvey.mesh.dim == 2:
+                zsrc = (Tx[0][1] + Tx[1][1])/2
+            elif DCsurvey.mesh.dim ==3:
+                zsrc = (Tx[0][2] + Tx[1][2])/2
+
+        # Change output for dtype
+        if dtype == 'volt':
+
+            rho = np.hstack([rho,data])
+
+        else:
+
+            # Compute pant leg of apparent rho
+            if stype == 'pdp':
+
+                leg =  data * 2*np.pi  * MA * ( MA + MN ) / MN
+
+            elif stype == 'dpdp':
+
+                leg = data * 2*np.pi / (1/MA - 1/MB + 1/NB - 1/NA)
+                LEG.append(1./(2*np.pi) * (1/MA - 1/MB + 1/NB - 1/NA))
+            else:
+                print("""dtype must be 'pdp'(pole-dipole) | 'dpdp' (dipole-dipole) """)
+                break
+
+
+            if dtype == 'appc':
+
+                leg = np.log10(abs(1./leg))
+                rho = np.hstack([rho,leg])
+
+            elif dtype == 'appr':
+
+                leg = np.log10(abs(leg))
+                rho = np.hstack([rho,leg])
+
+            else:
+                print("""dtype must be 'appr' | 'appc' | 'volt' """)
+                break
+
+
+        midx = np.hstack([midx, ( Cmid + Pmid )/2 ])
+        if DCsurvey.mesh.dim==3:
+            midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + zsrc ])
+        elif DCsurvey.mesh.dim==2:
+            midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + zsrc ])
+    ax = axs
+
+    # Grid points
+    grid_x, grid_z = np.mgrid[np.min(midx):np.max(midx), np.min(midz):np.max(midz)]
+    grid_rho = griddata(np.c_[midx,midz], rho.T, (grid_x, grid_z), method='linear')
+
+    if clim == None:
+        vmin, vmax = rho.min(), rho.max()
+    else:
+        vmin, vmax = clim[0], clim[1]
+
+    grid_rho = np.ma.masked_where(np.isnan(grid_rho), grid_rho)
+    ph = plt.pcolormesh(grid_x[:,0],grid_z[0,:],grid_rho.T, clim=(vmin, vmax), vmin=vmin, vmax=vmax)
+    cbar = plt.colorbar(format="$10^{%.1f}$",fraction=0.04,orientation="horizontal")
+
+    cmin,cmax = cbar.get_clim()
+    ticks = np.linspace(cmin,cmax,3)
+    cbar.set_ticks(ticks)
+    cbar.ax.tick_params(labelsize=10)
+
+    if dtype == 'appc':
+        cbar.set_label("App.Cond",size=12)
+    elif dtype == 'appr':
+        cbar.set_label("App.Res.",size=12)
+    elif dtype == 'volt':
+        cbar.set_label("Potential (V)",size=12)
+
+    # Plot apparent resistivity
+    ax.scatter(midx,midz,s=10,c=rho.T, vmin =vmin, vmax = vmax, clim=(vmin, vmax))
+
+    #ax.set_xticklabels([])
+    #ax.set_yticklabels([])
+
+    plt.gca().set_aspect('equal', adjustable='box')
+
+
+
+    return ph, LEG
+
+def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
+    """
+        Load in endpoints and survey specifications to generate Tx, Rx location
+        stations.
+
+        Assumes flat topo for now...
+
+        Input:
+        :param endl -> input endpoints [x1, y1, z1, x2, y2, z2]
+        :object mesh -> SimPEG mesh object
+        :switch stype -> "dpdp" (dipole-dipole) | "pdp" (pole-dipole) | 'gradient'
+        : param a, n -> pole seperation, number of rx dipoles per tx
+
+        Output:
+        :param Tx, Rx -> List objects for each tx location
+            Lines: P1x, P1y, P1z, P2x, P2y, P2z
+
+        Created on Wed December 9th, 2015
+
+        @author: dominiquef
+        !! Require clean up to deal with DCsurvey
+    """
+
+    from SimPEG import np
+
+    def xy_2_r(x1,x2,y1,y2):
+        r = np.sqrt( np.sum((x2 - x1)**2 + (y2 - y1)**2) )
+        return r
+
+    ## Evenly distribute electrodes and put on surface
+    # Mesure survey length and direction
+    dl_len = xy_2_r(endl[0,0],endl[1,0],endl[0,1],endl[1,1])
+
+    dl_x = (endl[1,0] - endl[0,0]) / dl_len
+    dl_y = (endl[1,1] - endl[0,1]) / dl_len
+
+    nstn = np.floor(dl_len / a)
+
+    # Compute discrete pole location along line
+    stn_x = endl[0,0] + np.array(list(range(int(nstn))))*dl_x*a
+    stn_y = endl[0,1] + np.array(list(range(int(nstn))))*dl_y*a
+
+    if mesh.dim==2:
+        ztop = mesh.vectorNy[-1]
+        # Create line of P1 locations
+        M = np.c_[stn_x, np.ones(nstn).T*ztop]
+        # Create line of P2 locations
+        N = np.c_[stn_x+a*dl_x, np.ones(nstn).T*ztop]
+
+    elif mesh.dim==3:
+        ztop = mesh.vectorNz[-1]
+        # Create line of P1 locations
+        M = np.c_[stn_x, stn_y, np.ones(nstn).T*ztop]
+        # Create line of P2 locations
+        N = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*ztop]
+
+
+    ## Build list of Tx-Rx locations depending on survey type
+    # Dipole-dipole: Moving tx with [a] spacing -> [AB a MN1 a MN2 ... a MNn]
+    # Pole-dipole: Moving pole on one end -> [A a MN1 a MN2 ... MNn a B]
+    SrcList = []
+
+
+    if stype != 'gradient':
+
+        for ii in range(0, int(nstn)-1):
+
+
+            if stype == 'dpdp':
+                tx = np.c_[M[ii,:],N[ii,:]]
+            elif stype == 'pdp':
+                tx = np.c_[M[ii,:],M[ii,:]]
+
+            # Rx.append(np.c_[M[ii+1:indx,:],N[ii+1:indx,:]])
+
+            # Current elctrode seperation
+            AB = xy_2_r(tx[0,1],endl[1,0],tx[1,1],endl[1,1])
+
+            # Number of receivers to fit
+            nstn = np.min([(AB - b) // a, n])
+
+            # Check if there is enough space, else break the loop
+            if nstn <= 0:
+                continue
+
+            # Compute discrete pole location along line
+            stn_x = N[ii,0] + dl_x*b + np.array(list(range(int(nstn))))*dl_x*a
+            stn_y = N[ii,1] + dl_y*b + np.array(list(range(int(nstn))))*dl_y*a
+
+            # Create receiver poles
+
+            if mesh.dim==3:
+                # Create line of P1 locations
+                P1 = np.c_[stn_x, stn_y, np.ones(nstn).T*ztop]
+                # Create line of P2 locations
+                P2 = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*ztop]
+                rxClass = DC.Rx.Dipole(P1, P2)
+
+            elif mesh.dim==2:
+                # Create line of P1 locations
+                P1 = np.c_[stn_x, np.ones(nstn).T*ztop]
+                # Create line of P2 locations
+                P2 = np.c_[stn_x+a*dl_x, np.ones(nstn).T*ztop]
+                rxClass = DC.Rx.Dipole_ky(P1, P2)
+
+            if stype == 'dpdp':
+                    srcClass = DC.Src.Dipole([rxClass], M[ii,:],N[ii,:])
+            elif stype == 'pdp':
+                    srcClass = DC.Src.Pole([rxClass], M[ii,:])
+            SrcList.append(srcClass)
+
+    elif stype == 'gradient':
+
+        # Gradient survey only requires Tx at end of line and creates a square
+        # grid of receivers at in the middle at a pre-set minimum distance
+
+        # Get the edge limit of survey area
+        min_x = endl[0,0] + dl_x * b
+        min_y = endl[0,1] + dl_y * b
+
+        max_x = endl[1,0] - dl_x * b
+        max_y = endl[1,1] - dl_y * b
+
+        box_l = np.sqrt( (min_x - max_x)**2 + (min_y - max_y)**2 )
+        box_w = box_l / 2.
+
+        nstn = np.floor(box_l / a)
+
+        # Compute discrete pole location along line
+        stn_x = min_x + np.array(list(range(int(nstn))))*dl_x*a
+        stn_y = min_y + np.array(list(range(int(nstn))))*dl_y*a
+
+        # Define number of cross lines
+        nlin = int(box_w // a)
+        lind = list(range(-nlin,nlin+1))
+
+        ngrad = nstn * len(lind)
+
+        rx = np.zeros([ngrad,6])
+        for ii in range( len(lind) ):
+
+            # Move line in perpendicular direction by dipole spacing
+            lxx = stn_x - lind[ii]*a*dl_y
+            lyy = stn_y + lind[ii]*a*dl_x
+
+
+            M = np.c_[ lxx, lyy , np.ones(nstn).T*ztop]
+            N = np.c_[ lxx+a*dl_x, lyy+a*dl_y, np.ones(nstn).T*ztop]
+            rx[(ii*nstn):((ii+1)*nstn),:] = np.c_[M,N]
+
+            if mesh.dim==3:
+                rxClass = DC.Rx.Dipole(rx[:,:3], rx[:,3:])
+            elif mesh.dim==2:
+                M = M[:,[0,2]]
+                N = N[:,[0,2]]
+                rxClass = DC.Rx.Dipole_ky(rx[:,[0,2]], rx[:,[3,5]])
+            srcClass = DC.Src.Dipole([rxClass], M[0,:], N[-1,:])
+        SrcList.append(srcClass)
+    else:
+        print("""stype must be either 'pdp', 'dpdp' or 'gradient'. """)
+
+
+    return SrcList
+

SimPEG/EM/Static/Utils/__init__.py

@@ -0,0 +1,7 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .StaticUtils import *

SimPEG/EM/Static/__init__.py

@@ -0,0 +1,9 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from . import DC
+from . import IP
+from . import SIP

SimPEG/EM/TDEM/BaseTDEM.py

@@ -1,3 +1,10 @@
+from __future__ import print_function
+from __future__ import unicode_literals
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
 from SimPEG import Solver, Problem
 from SimPEG.Problem import BaseTimeProblem
 from SimPEG.EM.Utils import *
@@ -47,7 +54,7 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
         self.waveformType = "GENERAL"
 
     def fields(self, m):
-        if self.verbose: print '%s\nCalculating fields(m)\n%s'%('*'*50,'*'*50)
+        if self.verbose: print('%s\nCalculating fields(m)\n%s'%('*'*50,'*'*50))
         self.curModel = m
         # Create a fields storage object
         F = self._FieldsForward_pair(self.mesh, self.survey)
@@ -55,7 +62,7 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
             # Set the initial conditions
             F[src,:,0] = src.getInitialFields(self.mesh)
         F = self.forward(m, self.getRHS, F=F)
-        if self.verbose: print '%s\nDone calculating fields(m)\n%s'%('*'*50,'*'*50)
+        if self.verbose: print('%s\nDone calculating fields(m)\n%s'%('*'*50,'*'*50))
         return F
 
     def forward(self, m, RHS, F=None):
@@ -70,13 +77,13 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
                 if Ainv is not None:
                     Ainv.clean()
                 A = self.getA(tInd)
-                if self.verbose: print 'Factoring...   (dt = %e)'%dt
+                if self.verbose: print('Factoring...   (dt = %e)'%dt)
                 Ainv = self.Solver(A, **self.solverOpts)
-                if self.verbose: print 'Done'
+                if self.verbose: print('Done')
             rhs = RHS(tInd, F)
-            if self.verbose: print '    Solving...   (tInd = %d)'%tInd
+            if self.verbose: print('    Solving...   (tInd = %d)'%tInd)
             sol = Ainv * rhs
-            if self.verbose: print '    Done...'
+            if self.verbose: print('    Done...')
             if sol.ndim == 1:
                 sol.shape = (sol.size,1)
             F[:,self.solType,tInd+1] = sol
@@ -95,24 +102,24 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
                 if Ainv is not None:
                     Ainv.clean()
                 A = self.getA(tInd)
-                if self.verbose: print 'Factoring (Adjoint)...   (dt = %e)'%dt
+                if self.verbose: print('Factoring (Adjoint)...   (dt = %e)'%dt)
                 Ainv = self.Solver(A, **self.solverOpts)
-                if self.verbose: print 'Done'
+                if self.verbose: print('Done')
             rhs = RHS(tInd, F)
-            if self.verbose: print '    Solving (Adjoint)...   (tInd = %d)'%tInd
+            if self.verbose: print('    Solving (Adjoint)...   (tInd = %d)'%tInd)
             sol = Ainv * rhs
-            if self.verbose: print '    Done...'
+            if self.verbose: print('    Done...')
             if sol.ndim == 1:
                 sol.shape = (sol.size,1)
             F[:,self.solType,tInd+1] = sol
         Ainv.clean()
         return F
 
-    def Jvec(self, m, v, u=None):
+    def Jvec(self, m, v, f=None):
         """
             :param numpy.array m: Conductivity model
             :param numpy.ndarray v: vector (model object)
-            :param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
+            :param FieldsTDEM f: Fields resulting from m
             :rtype: numpy.ndarray
             :return: w (data object)
 
@@ -123,21 +130,21 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
             * Compute \\\(\\\\vec{w} = -\\\mathbf{Q} \\\\vec{y}\\\)
 
         """
-        if self.verbose: print '%s\nCalculating J(v)\n%s'%('*'*50,'*'*50)
+        if self.verbose: print('%s\nCalculating J(v)\n%s'%('*'*50,'*'*50))
         self.curModel = m
-        if u is None:
-            u = self.fields(m)
-        p = self.Gvec(m, v, u)
+        if f is None:
+            f = self.fields(m)
+        p = self.Gvec(m, v, f)
         y = self.solveAh(m, p)
-        Jv = self.survey.evalDeriv(u, v=y)
-        if self.verbose: print '%s\nDone calculating J(v)\n%s'%('*'*50,'*'*50)
+        Jv = self.survey.evalDeriv(f, v=y)
+        if self.verbose: print('%s\nDone calculating J(v)\n%s'%('*'*50,'*'*50))
         return - mkvc(Jv)
 
-    def Jtvec(self, m, v, u=None):
+    def Jtvec(self, m, v, f=None):
         """
             :param numpy.array m: Conductivity model
-            :param numpy.ndarray,SimPEG.Survey.Data v: vector (data object)
-            :param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
+            :param numpy.ndarray v: vector (or a :class:`SimPEG.Survey.Data` object)
+            :param FieldsTDEM u: Fields resulting from m
             :rtype: numpy.ndarray
             :return: w (model object)
 
@@ -148,17 +155,17 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
             * Compute \\\(\\\\vec{w} = -\\\mathbf{G}^\\\\top y\\\)
 
         """
-        if self.verbose: print '%s\nCalculating J^T(v)\n%s'%('*'*50,'*'*50)
+        if self.verbose: print('%s\nCalculating J^T(v)\n%s'%('*'*50,'*'*50))
         self.curModel = m
-        if u is None:
-            u = self.fields(m)
+        if f is None:
+            f = self.fields(m)
 
         if not isinstance(v, self.dataPair):
             v = self.dataPair(self.survey, v)
 
-        p = self.survey.evalDeriv(u, v=v, adjoint=True)
+        p = self.survey.evalDeriv(f, v=v, adjoint=True)
         y = self.solveAht(m, p)
-        w = self.Gtvec(m, y, u)
-        if self.verbose: print '%s\nDone calculating J^T(v)\n%s'%('*'*50,'*'*50)
+        w = self.Gtvec(m, y, f)
+        if self.verbose: print('%s\nDone calculating J^T(v)\n%s'%('*'*50,'*'*50))
         return - mkvc(w)
 

SimPEG/EM/TDEM/SurveyTDEM.py

@@ -1,7 +1,13 @@
+from __future__ import print_function
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import Utils, Survey, np
 from SimPEG.Survey import BaseSurvey
 from SimPEG.EM.Utils import *
-from BaseTDEM import FieldsTDEM
+from .BaseTDEM import FieldsTDEM
 
 
 class RxTDEM(Survey.BaseTimeRx):
@@ -87,7 +93,7 @@ class SrcTDEM_VMD_MVP(SrcTDEM):
     def getInitialFields(self, mesh):
         """Vertical magnetic dipole, magnetic vector potential"""
         if self.waveformType == "STEPOFF":
-            print ">> Step waveform: Non-zero initial condition"        
+            print(">> Step waveform: Non-zero initial condition")
             if mesh._meshType is 'CYL':
                 if mesh.isSymmetric:
                     MVP = MagneticDipoleVectorPotential(self.loc, mesh, 'Ey')
@@ -96,10 +102,10 @@ class SrcTDEM_VMD_MVP(SrcTDEM):
             elif mesh._meshType is 'TENSOR':
                 MVP = MagneticDipoleVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'])
             else:
-                raise Exception('Unknown mesh for VMD') 
-            return {"b": mesh.edgeCurl*MVP}               
+                raise Exception('Unknown mesh for VMD')
+            return {"b": mesh.edgeCurl*MVP}
         elif self.waveformType == "GENERAL":
-            print ">> General waveform: Zero initial condition"
+            print(">> General waveform: Zero initial condition")
             return {"b": np.zeros(mesh.nF)}
         else:
             raise NotImplementedError("Only use STEPOFF or GENERAL")
@@ -113,7 +119,7 @@ class SrcTDEM_VMD_MVP(SrcTDEM):
         elif mesh._meshType is 'TENSOR':
             MVP = MagneticDipoleVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'])
         else:
-            raise Exception('Unknown mesh for VMD')            
+            raise Exception('Unknown mesh for VMD')
         return mesh.edgeCurl.T*MfMui*mesh.edgeCurl*MVP
 
 
@@ -122,12 +128,12 @@ class SrcTDEM_CircularLoop_MVP(SrcTDEM):
         self.loc = loc
         self.radius = radius
         self.waveformType = waveformType
-        SrcTDEM.__init__(self,rxList)        
+        SrcTDEM.__init__(self,rxList)
 
     def getInitialFields(self, mesh):
         """Circular Loop, magnetic vector potential"""
         if self.waveformType == "STEPOFF":
-            print ">> Step waveform: Non-zero initial condition"
+            print(">> Step waveform: Non-zero initial condition")
             if mesh._meshType is 'CYL':
                 if mesh.isSymmetric:
                     MVP = MagneticLoopVectorPotential(self.loc, mesh, 'Ey', self.radius)
@@ -139,7 +145,7 @@ class SrcTDEM_CircularLoop_MVP(SrcTDEM):
                 raise Exception('Unknown mesh for CircularLoop')
             return {"b": mesh.edgeCurl*MVP}
         elif self.waveformType == "GENERAL":
-            print ">> General waveform: Zero initial condition"
+            print(">> General waveform: Zero initial condition")
             return {"b": np.zeros(mesh.nF)}
         else:
             raise NotImplementedError("Only use STEPOFF or GENERAL")
@@ -153,7 +159,7 @@ class SrcTDEM_CircularLoop_MVP(SrcTDEM):
         elif mesh._meshType is 'TENSOR':
             MVP = MagneticLoopVectorPotential(self.loc, mesh, ['Ex','Ey','Ez'], self.radius)
         else:
-            raise Exception('Unknown mesh for CircularLoop')            
+            raise Exception('Unknown mesh for CircularLoop')
         return mesh.edgeCurl.T*MfMui*mesh.edgeCurl*MVP
 
 

SimPEG/EM/TDEM/TDEM_b.py

@@ -1,7 +1,14 @@
-from BaseTDEM import BaseTDEMProblem, FieldsTDEM
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
+from .BaseTDEM import BaseTDEMProblem, FieldsTDEM
 from SimPEG.Utils import mkvc, sdiag
 import numpy as np
-from SurveyTDEM import SurveyTDEM
+from .SurveyTDEM import SurveyTDEM
 
 
 class FieldsTDEM_e_from_b(FieldsTDEM):
@@ -87,8 +94,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
         """
             :param numpy.array m: Conductivity model
             :param numpy.array vec: vector (like a model)
-            :param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
-            :rtype: simpegEM.TDEM.FieldsTDEM
+            :param FieldsTDEM u: Fields resulting from m
+            :rtype: FieldsTDEM
             :return: f
 
             Multiply G by a vector
@@ -125,9 +132,9 @@ class ProblemTDEM_b(BaseTDEMProblem):
         """
             :param numpy.array m: Conductivity model
             :param numpy.array vec: vector (like a fields)
-            :param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
-            :rtype: np.ndarray (like a model)
-            :return: p
+            :param FieldsTDEM u: Fields resulting from m
+            :rtype: numpy.ndarray
+            :return: p (like a model)
 
             Multiply G.T by a vector
         """
@@ -153,8 +160,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
     def solveAh(self, m, p):
         """
             :param numpy.array m: Conductivity model
-            :param simpegEM.TDEM.FieldsTDEM p: Fields object
-            :rtype: simpegEM.TDEM.FieldsTDEM
+            :param FieldsTDEM p: Fields object
+            :rtype: FieldsTDEM
             :return: y
 
             Solve the block-matrix system \\\(\\\hat{A} \\\hat{y} = \\\hat{p}\\\):
@@ -200,8 +207,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
     def solveAht(self, m, p):
         """
             :param numpy.array m: Conductivity model
-            :param simpegEM.TDEM.FieldsTDEM p: Fields object
-            :rtype: simpegEM.TDEM.FieldsTDEM
+            :param FieldsTDEM p: Fields object
+            :rtype: FieldsTDEM
             :return: y
 
             Solve the block-matrix system \\\(\\\hat{A}^\\\\top \\\hat{y} = \\\hat{p}\\\):
@@ -270,8 +277,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
     def _AhVec(self, m, vec):
         """
             :param numpy.array m: Conductivity model
-            :param simpegEM.TDEM.FieldsTDEM vec: Fields object
-            :rtype: simpegEM.TDEM.FieldsTDEM
+            :param FieldsTDEM vec: Fields object
+            :rtype: FieldsTDEM
             :return: f
 
             Multiply the matrix \\\(\\\hat{A}\\\) by a fields vector where
@@ -315,8 +322,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
     def _AhtVec(self, m, vec):
         """
             :param numpy.array m: Conductivity model
-            :param simpegEM.TDEM.FieldsTDEM vec: Fields object
-            :rtype: simpegEM.TDEM.FieldsTDEM
+            :param FieldsTDEM vec: Fields object
+            :rtype: FieldsTDEM
             :return: f
 
             Multiply the matrix \\\(\\\hat{A}\\\) by a fields vector where

SimPEG/EM/TDEM/__init__.py

@@ -1,3 +1,9 @@
-from SurveyTDEM import * #SurveyTDEM, RxTDEM, SrcTDEM
-from BaseTDEM import BaseTDEMProblem, FieldsTDEM
-from TDEM_b import ProblemTDEM_b
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .SurveyTDEM import * #SurveyTDEM, RxTDEM, SrcTDEM
+from .BaseTDEM import BaseTDEMProblem, FieldsTDEM
+from .TDEM_b import ProblemTDEM_b

SimPEG/EM/Utils/AnalyticUtils.py

@@ -1,3 +1,10 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
 from SimPEG import *
 from scipy.special import ellipk, ellipe
 from scipy.constants import mu_0, pi
@@ -17,7 +24,7 @@ def MagneticDipoleVectorPotential(srcLoc, obsLoc, component, moment=1., dipoleMo
     #TODO: break this out!
 
     if type(component) in [list, tuple]:
-        out = range(len(component))
+        out = list(range(len(component)))
         for i, comp in enumerate(component):
             out[i] = MagneticDipoleVectorPotential(srcLoc, obsLoc, comp, dipoleMoment=dipoleMoment)
         return np.concatenate(out)
@@ -118,7 +125,7 @@ def MagneticLoopVectorPotential(srcLoc, obsLoc, component, radius, mu=mu_0):
     """
 
     if type(component) in [list, tuple]:
-        out = range(len(component))
+        out = list(range(len(component)))
         for i, comp in enumerate(component):
             out[i] = MagneticLoopVectorPotential(srcLoc, obsLoc, comp, radius, mu)
         return np.concatenate(out)
@@ -158,11 +165,11 @@ def MagneticLoopVectorPotential(srcLoc, obsLoc, component, radius, mu=mu_0):
             # % 1/r singular at r = 0 and K(m) singular at m = 1
             Aphi = np.zeros(n)
             # % Common factor is (mu * I) / pi with I = 1 and mu = 4e-7 * pi.
-            Aphi[ind] = 4e-7 / np.sqrt(m[ind])  * np.sqrt(radius / r[ind]) *((1. - m[ind] / 2.) * K[ind] - E[ind])
+            Aphi[ind] = 4e-7 / np.sqrt(m[ind])  * np.sqrt(radius/ r[ind]) *((1. - m[ind] / 2.) * K[ind] - E[ind])
             if component == 'x':
-                A[ind, i] = Aphi[ind] * (-y[ind] / r[ind] )
+                A[ind, i] = Aphi[ind] * (-y[ind] / r[ind])
             elif component == 'y':
-                A[ind, i] = Aphi[ind] * ( x[ind] / r[ind] )
+                A[ind, i] = Aphi[ind] * (x[ind] / r[ind])
             else:
                 raise ValueError('Invalid component')
 

SimPEG/EM/Utils/EMUtils.py

@@ -1,3 +1,9 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 import numpy as np
 from scipy.constants import mu_0, epsilon_0
 
@@ -9,8 +15,8 @@ def omega(freq):
 def k(freq, sigma, mu=mu_0, eps=epsilon_0):
     """ Eq 1.47 - 1.49 in Ward and Hohmann """
     w = omega(freq)
-    alp  = w * np.sqrt( mu*eps/2 * ( np.sqrt(1. + (sigma / (eps*w))**2 ) + 1) ) 
-    beta = w * np.sqrt( mu*eps/2 * ( np.sqrt(1. + (sigma / (eps*w))**2 ) - 1) ) 
+    alp  = w * np.sqrt( mu*eps/2 * ( np.sqrt(1. + (sigma / (eps*w)))**2 ) + 1)
+    beta = w * np.sqrt( mu*eps/2 * ( np.sqrt(1. + (sigma / (eps*w)))**2 ) - 1)
     return alp - 1j*beta
 
 

SimPEG/EM/Utils/__init__.py

@@ -1,2 +1,8 @@
-from EMUtils import omega, k
-from AnalyticUtils import MagneticDipoleFields, MagneticDipoleVectorPotential, MagneticLoopVectorPotential
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .EMUtils import omega, k
+from .AnalyticUtils import MagneticDipoleFields, MagneticDipoleVectorPotential, MagneticLoopVectorPotential

SimPEG/EM/Utils/testingUtils.py

@@ -1,3 +1,10 @@
+from __future__ import print_function
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import absolute_import
+from builtins import int
+from future import standard_library
+standard_library.install_aliases()
 import unittest
 from SimPEG import *
 from SimPEG import EM
@@ -20,56 +27,61 @@ def getFDEMProblem(fdemType, comp, SrcList, freq, useMu=False, verbose=False):
     mesh = Mesh.TensorMesh([hx,hy,hz],['C','C','C'])
 
     if useMu is True:
-        mapping = [('sigma', Maps.ExpMap(mesh)), ('mu', Maps.IdentityMap(mesh))] 
+        mapping = [('sigma', Maps.ExpMap(mesh)), ('mu', Maps.IdentityMap(mesh))]
     else:
         mapping = Maps.ExpMap(mesh)
 
     x = np.array([np.linspace(-5.*cs,-2.*cs,3),np.linspace(5.*cs,2.*cs,3)]) + cs/4. #don't sample right by the source, slightly off alignment from either staggered grid
     XYZ = Utils.ndgrid(x,x,np.linspace(-2.*cs,2.*cs,5))
-    Rx0 = EM.FDEM.Rx(XYZ, comp)
+    Rx0 = getattr(EM.FDEM.Rx, 'Point_' + comp[0])
+    if comp[2] == 'r':
+        real_or_imag = 'real'
+    elif comp[2] == 'i':
+        real_or_imag = 'imag'
+    rx0 = Rx0(XYZ, comp[1], 'imag')
 
     Src = []
 
     for SrcType in SrcList:
         if SrcType is 'MagDipole':
-            Src.append(EM.FDEM.Src.MagDipole([Rx0], freq=freq, loc=np.r_[0.,0.,0.]))
+            Src.append(EM.FDEM.Src.MagDipole([rx0], freq=freq, loc=np.r_[0.,0.,0.]))
         elif SrcType is 'MagDipole_Bfield':
-            Src.append(EM.FDEM.Src.MagDipole_Bfield([Rx0], freq=freq, loc=np.r_[0.,0.,0.]))
+            Src.append(EM.FDEM.Src.MagDipole_Bfield([rx0], freq=freq, loc=np.r_[0.,0.,0.]))
         elif SrcType is 'CircularLoop':
-            Src.append(EM.FDEM.Src.CircularLoop([Rx0], freq=freq, loc=np.r_[0.,0.,0.]))
+            Src.append(EM.FDEM.Src.CircularLoop([rx0], freq=freq, loc=np.r_[0.,0.,0.]))
         elif SrcType is 'RawVec':
             if fdemType is 'e' or fdemType is 'b':
                 S_m = np.zeros(mesh.nF)
                 S_e = np.zeros(mesh.nE)
                 S_m[Utils.closestPoints(mesh,[0.,0.,0.],'Fz') + np.sum(mesh.vnF[:1])] = 1e-3
                 S_e[Utils.closestPoints(mesh,[0.,0.,0.],'Ez') + np.sum(mesh.vnE[:1])] = 1e-3
-                Src.append(EM.FDEM.Src.RawVec([Rx0], freq, S_m, S_e))
+                Src.append(EM.FDEM.Src.RawVec([rx0], freq, S_m, mesh.getEdgeInnerProduct()*S_e))
 
             elif fdemType is 'h' or fdemType is 'j':
                 S_m = np.zeros(mesh.nE)
                 S_e = np.zeros(mesh.nF)
                 S_m[Utils.closestPoints(mesh,[0.,0.,0.],'Ez') + np.sum(mesh.vnE[:1])] = 1e-3
                 S_e[Utils.closestPoints(mesh,[0.,0.,0.],'Fz') + np.sum(mesh.vnF[:1])] = 1e-3
-                Src.append(EM.FDEM.Src.RawVec([Rx0], freq, S_m, S_e))
+                Src.append(EM.FDEM.Src.RawVec([rx0], freq, mesh.getEdgeInnerProduct()*S_m, S_e))
 
     if verbose:
-        print '  Fetching %s problem' % (fdemType)
+        print('  Fetching %s problem' % (fdemType))
 
     if fdemType == 'e':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem_e(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem3D_e(mesh, mapping=mapping)
 
     elif fdemType == 'b':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem_b(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem3D_b(mesh, mapping=mapping)
 
     elif fdemType == 'j':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem_j(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem3D_j(mesh, mapping=mapping)
 
     elif fdemType == 'h':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem_h(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem3D_h(mesh, mapping=mapping)
 
     else:
         raise NotImplementedError()
@@ -78,7 +90,7 @@ def getFDEMProblem(fdemType, comp, SrcList, freq, useMu=False, verbose=False):
     try:
         from pymatsolver import MumpsSolver
         prb.Solver = MumpsSolver
-    except ImportError, e:
+    except ImportError as e:
         prb.Solver = SolverLU
 
     return prb
@@ -89,8 +101,8 @@ def crossCheckTest(SrcList, fdemType1, fdemType2, comp, addrandoms = False, useM
 
     prb1 = getFDEMProblem(fdemType1, comp, SrcList, freq, useMu, verbose)
     mesh = prb1.mesh
-    print 'Cross Checking Forward: %s, %s formulations - %s' % (fdemType1, fdemType2, comp)
-    
+    print('Cross Checking Forward: %s, %s formulations - %s' % (fdemType1, fdemType2, comp))
+
     logsig = np.log(np.ones(mesh.nC)*CONDUCTIVITY)
     mu = np.ones(mesh.nC)*MU
 
@@ -107,7 +119,7 @@ def crossCheckTest(SrcList, fdemType1, fdemType2, comp, addrandoms = False, useM
     d1 = survey1.dpred(m)
 
     if verbose:
-        print '  Problem 1 solved'
+        print('  Problem 1 solved')
 
 
     prb2 = getFDEMProblem(fdemType2, comp, SrcList, freq, useMu, verbose)
@@ -116,11 +128,11 @@ def crossCheckTest(SrcList, fdemType1, fdemType2, comp, addrandoms = False, useM
     d2 = survey2.dpred(m)
 
     if verbose:
-        print '  Problem 2 solved'
+        print('  Problem 2 solved')
 
     r = d2-d1
     l2r = l2norm(r)
 
     tol = np.max([TOL*(10**int(np.log10(0.5* (l2norm(d1) + l2norm(d2)) ))),FLR])
-    print l2norm(d1), l2norm(d2),  l2r , tol, l2r < tol
+    print(l2norm(d1), l2norm(d2),  l2r , tol, l2r < tol)
     return l2r < tol

SimPEG/EM/__init__.py

@@ -1,6 +1,13 @@
-import TDEM
-import FDEM
-import Base
-import Analytics
-import Utils
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from . import TDEM
+from . import FDEM
+from . import Static
+from . import Base
+from . import Analytics
+from . import Utils
 from scipy.constants import mu_0, epsilon_0

SimPEG/Examples/DC_Analytic_Dipole.py

@@ -1,7 +1,13 @@
+from __future__ import print_function
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import *
-import SimPEG.DCIP as DC
+import SimPEG.EM.Static.DC as DC
 
-def run(plotIt=False):
+def run(plotIt=True):
     cs = 25.
     hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
     hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
@@ -21,15 +27,15 @@ def run(plotIt=False):
     #     ax.plot(xyz_rxP[:,0],xyz_rxP[:,1], 'w.')
     #     ax.plot(xyz_rxN[:,0],xyz_rxN[:,1], 'r.', ms = 3)
 
-    rx = DC.RxDipole(xyz_rxP, xyz_rxN)
-    src = DC.SrcDipole([rx], [-200, 0, -12.5], [+200, 0, -12.5])
-    survey = DC.SurveyDC([src])
-    problem = DC.ProblemDC_CC(mesh)
+    rx = DC.Rx.Dipole(xyz_rxP, xyz_rxN)
+    src = DC.Src.Dipole([rx], np.r_[-200, 0, -12.5], np.r_[+200, 0, -12.5])
+    survey = DC.Survey([src])
+    problem = DC.Problem3D_CC(mesh)
     problem.pair(survey)
     try:
         from pymatsolver import MumpsSolver
         problem.Solver = MumpsSolver
-    except Exception, e:
+    except Exception as e:
         pass
     data = survey.dpred(sigma)
 
@@ -61,8 +67,8 @@ def run(plotIt=False):
         ax[0].set_title('Computed')
         plt.show()
 
-    return np.linalg.norm(data-data_ana)/np.linalg.norm(data_ana)
+    return np.linalg.norm(data-data_ana) / np.linalg.norm(data_ana)
 
 
 if __name__ == '__main__':
-    print run(plotIt=True)
+    print(run())

SimPEG/Examples/DC_Forward_PseudoSection.py

@@ -1,20 +1,36 @@
+from __future__ import print_function
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import absolute_import
+from builtins import int
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
 from SimPEG import Mesh, Utils, np, sp
 import SimPEG.DCIP as DC
 import time
 
-def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
+def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', unitType='appConductivity', plotIt=True):
     """
         DC Forward Simulation
         =====================
 
-        Forward model conductive spheres in a half-space and plot a pseudo-section
+        Forward model two conductive spheres in a half-space and plot a
+        pseudo-section. Assumes an infinite line source and measures along the
+        center of the spheres.
 
-        Created by @fourndo on Mon Feb 01 19:28:06 2016
+        INPUT:
+        loc     = Location of spheres [[x1,y1,z1],[x2,y2,z2]]
+        radi    = Radius of spheres [r1,r2]
+        param   = Conductivity of background and two spheres [m0,m1,m2]
+        surveyType = survey type 'pole-dipole' or 'dipole-dipole'
+        unitType = Data type "appResistivity" | "appConductivity"  | "volt"
+        Created by @fourndo
 
     """
 
-    assert stype in ['pdp', 'dpdp'], "Source type (stype) must be pdp or dpdp (pole dipole or dipole dipole)"
-
+    assert surveyType in ['pole-dipole', 'dipole-dipole'], "Source type (surveyType) must be pdp or dpdp (pole dipole or dipole dipole)"
+    assert unitType in ['appResistivity', 'appConductivity', 'volt'], "Unit type (unitType) must be appResistivity or appConductivity or volt (potential)"
 
     if loc is None:
         loc = np.c_[[-50.,0.,-50.],[50.,0.,-50.]]
@@ -27,7 +43,6 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
 
 
     # First we need to create a mesh and a model.
-
     # This is our mesh
     dx    = 5.
 
@@ -50,16 +65,12 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
     model[ind] = sig[2]
 
     # Get index of the center
-    indy = int(mesh.nCy/2)
-
+    indy = int(mesh.nCy // 2)
 
     # Plot the model for reference
     # Define core mesh extent
     xlim = 200
-    zlim = 125
-
-    # Specify the survey type: "pdp" | "dpdp"
-
+    zlim = 100
 
     # Then specify the end points of the survey. Let's keep it simple for now and survey above the anomalies, top of the mesh
     ends = [(-175,0),(175,0)]
@@ -70,19 +81,20 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
     locs = np.c_[mesh.gridCC[indx,0],mesh.gridCC[indx,1],np.ones(2).T*mesh.vectorNz[-1]]
 
     # We will handle the geometry of the survey for you and create all the combination of tx-rx along line
-    # [Tx, Rx] = DC.gen_DCIPsurvey(locs, mesh, stype, param[0], param[1], param[2])
-    survey, Tx, Rx = DC.gen_DCIPsurvey(locs, mesh, stype, param[0], param[1], param[2])
+    # [Tx, Rx] = DC.gen_DCIPsurvey(locs, mesh, surveyType, param[0], param[1], param[2])
+    survey, Tx, Rx = DC.gen_DCIPsurvey(locs, mesh, surveyType, param[0], param[1], param[2])
 
     # Define some global geometry
     dl_len = np.sqrt( np.sum((locs[0,:] - locs[1,:])**2) )
     dl_x = ( Tx[-1][0,1] - Tx[0][0,0] ) / dl_len
     dl_y = ( Tx[-1][1,1] - Tx[0][1,0]  ) / dl_len
-    azm =  np.arctan(dl_y/dl_x)
+    #azm =  np.arctan(dl_y/dl_x)
 
     #Set boundary conditions
     mesh.setCellGradBC('neumann')
 
-    # Define the differential operators needed for the DC problem
+    # Define the linear system needed for the DC problem. We assume an infitite
+    # line source for simplicity.
     Div = mesh.faceDiv
     Grad = mesh.cellGrad
     Msig = Utils.sdiag(1./(mesh.aveF2CC.T*(1./model)))
@@ -114,16 +126,16 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
         rxloc_N = np.asarray(Rx[ii][:,3:])
 
 
-        # For usual cases "dpdp" or "gradient"
-        if stype == 'pdp':
+        # For usual cases 'dipole-dipole' or "gradient"
+        if surveyType == 'pole-dipole':
             # Create an "inifinity" pole
             tx =  np.squeeze(Tx[ii][:,0:1])
             tinf = tx + np.array([dl_x,dl_y,0])*dl_len*2
             inds = Utils.closestPoints(mesh, np.c_[tx,tinf].T)
-            RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( [-1] / mesh.vol[inds] )
+            RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*([-1] / mesh.vol[inds])
         else:
             inds = Utils.closestPoints(mesh, np.asarray(Tx[ii]).T )
-            RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( [-1,1] / mesh.vol[inds] )
+            RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*([-1,1] / mesh.vol[inds])
 
         # Iterative Solve
         Ainvb = sp.linalg.bicgstab(P*A,P*RHS, tol=1e-5)
@@ -139,22 +151,29 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
         dtemp = (P1*phi - P2*phi)*np.pi
 
         data.append( dtemp )
-        print '\rTransmitter {0} of {1} -> Time:{2} sec'.format(ii,len(Tx),time.time()- start_time),
+        print('\rTransmitter {0} of {1} -> Time:{2} sec'.format(ii,len(Tx),time.time()- start_time), end=' ')
 
-    print 'Transmitter {0} of {1}'.format(ii,len(Tx))
-    print 'Forward completed'
+    print('Transmitter {0} of {1}'.format(ii,len(Tx)))
+    print('Forward completed')
 
     # Let's just convert the 3D format into 2D (distance along line) and plot
-    # [Tx2d, Rx2d] = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc))
-    survey2D = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc))
+    survey2D = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc) , 'Xloc')
     survey2D.dobs =np.hstack(data)
-    # Here is an example for the first tx-rx array
+
     if plotIt:
         import matplotlib.pyplot as plt
-        fig = plt.figure()
+        fig = plt.figure(figsize=(7,7))
         ax = plt.subplot(2,1,1, aspect='equal')
-        mesh.plotSlice(np.log10(model), ax =ax, normal = 'Y', ind = indy,grid=True)
-        ax.set_title('E-W section at '+str(mesh.vectorCCy[indy])+' m')
+        # Plot the location of the spheres for reference
+        circle1=plt.Circle((loc[0,0], loc[2,0]), radi[0], color='w', fill=False, lw=3)
+        circle2=plt.Circle((loc[0,1], loc[2,1]), radi[1], color='k', fill=False, lw=3)
+        ax.add_artist(circle1)
+        ax.add_artist(circle2)
+
+        dat = mesh.plotSlice(np.log10(model), ax = ax, normal = 'Y',
+                             ind = indy,grid=True, clim = np.log10([sig.min(),sig.max()]))
+
+        ax.set_title('3-D model')
         plt.gca().set_aspect('equal', adjustable='box')
 
         plt.scatter(Tx[0][0,:],Tx[0][2,:],s=40,c='g', marker='v')
@@ -163,22 +182,32 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
         plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
 
 
-        ax = plt.subplot(2,1,2, aspect='equal')
+        pos =  ax.get_position()
+        ax.set_position([pos.x0 , pos.y0 + 0.025 ,  pos.width, pos.height])
+        pos =  ax.get_position()
+        cbarax = fig.add_axes([pos.x0 , pos.y0 + 0.025 ,  pos.width, pos.height * 0.04])  ## the parameters are the specified position you set
+        cb = fig.colorbar(dat[0],cax=cbarax, orientation="horizontal",
+                          ax = ax, ticks=np.linspace(np.log10(sig.min()),
+                         np.log10(sig.max()), 3), format="$10^{%.1f}$")
+        cb.set_label("Conductivity (S/m)",size=12)
+        cb.ax.tick_params(labelsize=12)
+
+        # Second plot for the predicted apparent resistivity data
+        ax2 = plt.subplot(2,1,2, aspect='equal')
 
         # Plot the location of the spheres for reference
-        circle1=plt.Circle((loc[0,0]-Tx[0][0,0],loc[2,0]),radi[0],color='w',fill=False, lw=3)
-        circle2=plt.Circle((loc[0,1]-Tx[0][0,0],loc[2,1]),radi[1],color='k',fill=False, lw=3)
-        ax.add_artist(circle1)
-        ax.add_artist(circle2)
+        circle1=plt.Circle((loc[0,0], loc[2,0]), radi[0], color='w', fill=False, lw=3)
+        circle2=plt.Circle((loc[0,1], loc[2,1]), radi[1], color='k', fill=False, lw=3)
+        ax2.add_artist(circle1)
+        ax2.add_artist(circle2)
 
         # Add the speudo section
-        DC.plot_pseudoSection(survey2D,ax,stype)
-
-        # plt.scatter(Tx2d[0][:],Tx[0][2,:],s=40,c='g', marker='v')
+        dat = DC.plot_pseudoSection(survey2D, ax2, surveyType=surveyType, unitType=unitType)        # plt.scatter(Tx2d[0][:],Tx[0][2,:],s=40,c='g', marker='v')
         # plt.scatter(Rx2d[0][:],Rx[0][:,2::3],s=40,c='y')
         # plt.plot(np.r_[Tx2d[0][0],Rx2d[-1][-1,-1]],np.ones(2)*mesh.vectorNz[-1], color='k')
-        plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
+        ax2.set_title('Apparent Conductivity data')
 
+        plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
         plt.show()
 
         return fig, ax

SimPEG/Examples/EM_FDEM_1D_Inversion.py

@@ -1,3 +1,9 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import *
 import SimPEG.EM as EM
 from SimPEG.EM import mu_0
@@ -42,22 +48,21 @@ def run(plotIt=True):
         ax.grid(color='k', alpha=0.5, linestyle='dashed', linewidth=0.5)
 
 
-    rxOffset=10. 
-    bzi = EM.FDEM.Rx(np.array([[rxOffset, 0., 1e-3]]), 'bzi')
+    rxOffset=10.
+    bzi = EM.FDEM.Rx.Point_b(np.array([[rxOffset, 0., 1e-3]]), orientation='z', component='imag')
 
     freqs = np.logspace(1,3,10)
     srcLoc = np.array([0., 0., 10.])
 
-    srcList = []
-    [srcList.append(EM.FDEM.Src.MagDipole([bzi],freq, srcLoc,orientation='Z')) for freq in freqs]
+    srcList = [EM.FDEM.Src.MagDipole([bzi],freq, srcLoc,orientation='Z') for freq in freqs]
 
     survey = EM.FDEM.Survey(srcList)
-    prb = EM.FDEM.Problem_b(mesh, mapping=mapping)
+    prb = EM.FDEM.Problem3D_b(mesh, mapping=mapping)
 
     try:
         from pymatsolver import MumpsSolver
         prb.Solver = MumpsSolver
-    except ImportError, e:
+    except ImportError as e:
         prb.Solver = SolverLU
 
     prb.pair(survey)

SimPEG/Examples/EM_FDEM_Analytic_MagDipoleWholespace.py

@@ -1,3 +1,9 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import *
 import SimPEG.EM as EM
 

SimPEG/Examples/EM_Schenkel_Morrison_Casing.py

@@ -0,0 +1,285 @@
+from __future__ import print_function
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
+from SimPEG import *
+from SimPEG.EM import FDEM, Analytics, mu_0
+import time
+
+try:
+    from pymatsolver import MumpsSolver
+    solver = MumpsSolver
+except Exception:
+    solver = SolverLU
+    pass
+
+def run(plotIt=True):
+    """
+        EM: Schenkel and Morrison Casing Model
+        ======================================
+
+        Here we create and run a FDEM forward simulation to calculate the vertical
+        current inside a steel-cased. The model is based on the Schenkel and
+        Morrison Casing Model, and the results are used in a 2016 SEG abstract by
+        Yang et al.
+
+        .. code-block:: text
+
+            Schenkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
+
+
+        The model consists of:
+
+        - Air: Conductivity 1e-8 S/m, above z = 0
+        - Background: conductivity 1e-2 S/m, below z = 0
+        - Casing: conductivity 1e6 S/m
+            - 300m long
+            - radius of 0.1m
+            - thickness of 6e-3m
+
+        Inside the casing, we take the same conductivity as the background.
+
+        We are using an EM code to simulate DC, so we use frequency low enough
+        that the skin depth inside the casing is longer than the casing length (f
+        = 1e-6 Hz). The plot produced is of the current inside the casing.
+
+        These results are shown in the SEG abstract by Yang et al., 2016: 3D DC
+        resistivity modeling of steel casing for reservoir monitoring using
+        equivalent resistor network. The solver used to produce these results and
+        achieve the CPU time of ~30s is Mumps, which was installed using pymatsolver_
+
+        .. _pymatsolver: https://github.com/rowanc1/pymatsolver
+
+        This example is on figshare: https://dx.doi.org/10.6084/m9.figshare.3126961.v1
+
+        If you would use this example for a code comparison, or build upon it, a
+        citation would be much appreciated!
+
+    """
+
+    if plotIt:
+        import matplotlib.pylab as plt
+
+    # ------------------ MODEL ------------------
+    sigmaair = 1e-8 # air
+    sigmaback = 1e-2 # background
+    sigmacasing = 1e6 # casing
+    sigmainside = sigmaback # inside the casing
+
+
+    casing_t = 0.006  # 1cm thickness
+    casing_l = 300   # length of the casing
+
+    casing_r = 0.1
+    casing_a = casing_r - casing_t / 2. # inner radius
+    casing_b = casing_r + casing_t / 2. # outer radius
+    casing_z = np.r_[-casing_l,0.]
+
+
+    # ------------------ SURVEY PARAMETERS ------------------
+    freqs = np.r_[1e-6] #[1e-1, 1, 5] # frequencies
+    dsz = -300 # down-hole z source location
+    src_loc = np.r_[0.,0.,dsz]
+    inf_loc = np.r_[0.,0.,1e4]
+
+    print('Skin Depth: ', [(500. / np.sqrt(sigmaback*_)) for _ in freqs])
+
+
+    # ------------------ MESH ------------------
+    # fine cells near well bore
+    csx1, csx2 = 2e-3, 60.
+    pfx1, pfx2 = 1.3, 1.3
+    ncx1 = np.ceil(casing_b/csx1)+2
+
+    # pad nicely to second cell size
+    npadx1 = np.log(csx2/csx1) // np.log(pfx1)
+    hx1a,hx1b = Utils.meshTensor([(csx1,ncx1)]),Utils.meshTensor([(csx1,npadx1,pfx1)])
+    dx1 = sum(hx1a)+sum(hx1b)
+    dx1 = dx1 // csx2
+    hx1b *= (dx1*csx2 - sum(hx1a)) / sum(hx1b)
+
+    # second chunk of mesh
+    dx2 = 300. # uniform mesh out to here
+    ncx2 = np.ceil((dx2 - dx1) / csx2)
+    npadx2 = 45
+    hx2a, hx2b = Utils.meshTensor([(csx2,ncx2)]), Utils.meshTensor([(csx2,npadx2,pfx2)])
+    hx = np.hstack([hx1a,hx1b,hx2a,hx2b])
+
+    # z-direction
+    csz = 0.05
+    nza = 10
+    ncz, npadzu, npadzd = np.int(np.ceil(np.diff(casing_z)[0]/csz))+10, 68, 68 # cell size, number of core cells, number of padding cells in the x- direction
+    hz = Utils.meshTensor([(csz,npadzd,-1.3), (csz,ncz), (csz,npadzu,1.3)]) # vector of cell widths in the z-direction
+
+    # Mesh
+    mesh = Mesh.CylMesh([hx,1.,hz], [0.,0.,-np.sum(hz[:npadzu+ncz-nza])])
+
+    print('Mesh Extent xmax: %f,: zmin: %f, zmax: %f'%(mesh.vectorCCx.max(), mesh.vectorCCz.min(), mesh.vectorCCz.max()))
+    print('Number of cells', mesh.nC)
+
+    if plotIt is True:
+        fig, ax = plt.subplots(1, 1, figsize=(6, 4))
+        ax.set_title('Simulation Mesh')
+        mesh.plotGrid(ax=ax)
+        plt.show()
+
+    # Put the model on the mesh
+    sigWholespace = sigmaback*np.ones((mesh.nC))
+
+    sigBack = sigWholespace.copy()
+    sigBack[mesh.gridCC[:,2] > 0.] = sigmaair
+
+    sigCasing = sigBack.copy()
+    iCasingZ = (mesh.gridCC[:,2] <= casing_z[1]) & (mesh.gridCC[:,2] >= casing_z[0])
+    iCasingX = (mesh.gridCC[:,0] >= casing_a) & (mesh.gridCC[:,0] <= casing_b)
+    iCasing = iCasingX & iCasingZ
+    sigCasing[iCasing] = sigmacasing
+
+
+    if plotIt is True:
+
+        # plotting parameters
+        xlim = np.r_[0., 0.2]
+        zlim = np.r_[-350., 10.]
+        clim_sig = np.r_[-8,6]
+
+        # plot models
+        fig, ax = plt.subplots(1,1,figsize=(4,4))
+
+        f = plt.colorbar(mesh.plotImage(np.log10(sigCasing),ax=ax)[0], ax=ax)
+        ax.grid(which='both')
+        ax.set_title('Log_10 (Sigma)')
+        ax.set_xlim(xlim)
+        ax.set_ylim(zlim)
+        f.set_clim(clim_sig)
+
+        plt.show()
+
+
+    # -------------- Sources --------------------
+    # Define Custom Current Sources
+
+    # surface source
+    sg_x = np.zeros(mesh.vnF[0],dtype=complex)
+    sg_y = np.zeros(mesh.vnF[1],dtype=complex)
+    sg_z = np.zeros(mesh.vnF[2],dtype=complex)
+
+    nza = 2 # put the wire two cells above the surface
+    ncin = 2
+
+    # vertically directed wire
+    sgv_indx = (mesh.gridFz[:,0] > casing_a) & (mesh.gridFz[:,0] < casing_a + csx1)  # hook it up to casing at the surface
+    sgv_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] >= -csz*2)
+    sgv_ind = sgv_indx & sgv_indz
+    sg_z[sgv_ind] = -1.
+
+    # horizontally directed wire
+    sgh_indx = (mesh.gridFx[:,0] > casing_a)    & (mesh.gridFx[:,0] <= inf_loc[2])
+    sgh_indz = (mesh.gridFx[:,2] > csz*(nza-0.5)) & (mesh.gridFx[:,2] < csz*(nza+0.5))
+    sgh_ind = sgh_indx & sgh_indz
+    sg_x[sgh_ind] = -1.
+
+    sgv2_indx = (mesh.gridFz[:,0] >= mesh.gridFx[sgh_ind,0].max()) & (mesh.gridFz[:,0] <= inf_loc[2]*1.2)  # hook it up to casing at the surface
+    sgv2_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] >= -csz*2)
+    sgv2_ind = sgv2_indx & sgv2_indz
+    sg_z[sgv2_ind] = 1.
+
+    # assemble the source
+    sg = np.hstack([sg_x,sg_y,sg_z])
+    sg_p = [FDEM.Src.RawVec_e([],_,sg/mesh.area) for _ in freqs]
+
+    # downhole source
+    dg_x = np.zeros(mesh.vnF[0],dtype=complex)
+    dg_y = np.zeros(mesh.vnF[1],dtype=complex)
+    dg_z = np.zeros(mesh.vnF[2],dtype=complex)
+
+    # vertically directed wire
+    dgv_indx = (mesh.gridFz[:,0] < csx1)  # go through the center of the well
+    dgv_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] > dsz + csz/2.)
+    dgv_ind = dgv_indx & dgv_indz
+    dg_z[dgv_ind] = -1.
+
+    # couple to the casing downhole
+    dgh_indx = mesh.gridFx[:,0] < casing_a + csx1
+    dgh_indz = (mesh.gridFx[:,2] < dsz + csz)  & (mesh.gridFx[:,2] >= dsz)
+    dgh_ind = dgh_indx & dgh_indz
+    dg_x[dgh_ind] = 1.
+
+    # horizontal part at surface
+    dgh2_indx = mesh.gridFx[:,0] <= inf_loc[2]*1.2
+    dgh2_indz = sgh_indz.copy()
+    dgh2_ind = dgh2_indx & dgh2_indz
+    dg_x[dgh2_ind] = -1.
+
+    # vertical part at surface
+    dgv2_ind = sgv2_ind.copy()
+    dg_z[dgv2_ind] = 1.
+
+    # assemble the source
+    dg = np.hstack([dg_x,dg_y,dg_z])
+    dg_p = [FDEM.Src.RawVec_e([],_,dg/mesh.area) for _ in freqs]
+
+    # ------------ Problem and Survey ---------------
+    survey = FDEM.Survey(sg_p + dg_p)
+    mapping = [('sigma', Maps.IdentityMap(mesh))]
+    problem = FDEM.Problem3D_h(mesh, mapping=mapping, Solver=solver)
+    problem.pair(survey)
+
+    # ------------- Solve ---------------------------
+    t0 = time.time()
+    fieldsCasing = problem.fields(sigCasing)
+    print('Time to solve 2 sources', time.time() - t0)
+
+    # Plot current
+
+    # current density
+    jn0 = fieldsCasing[dg_p,'j']
+    jn1 = fieldsCasing[sg_p,'j']
+
+    # current
+    in0 = [mesh.area*fieldsCasing[dg_p,'j'][:,i] for i in range(len(freqs))]
+    in1 = [mesh.area*fieldsCasing[sg_p,'j'][:,i] for i in range(len(freqs))]
+
+    in0 = np.vstack(in0).T
+    in1 = np.vstack(in1).T
+
+    # integrate to get z-current inside casing
+    inds_inx = (mesh.gridFz[:,0] >= casing_a) & (mesh.gridFz[:,0] <= casing_b)
+    inds_inz = (mesh.gridFz[:,2] >= dsz )     & (mesh.gridFz[:,2] <= 0)
+    inds_fz = inds_inx & inds_inz
+
+    indsx = [False]*mesh.nFx
+    inds = list(indsx) + list(inds_fz)
+
+    in0_in = in0[np.r_[inds]]
+    in1_in = in1[np.r_[inds]]
+    z_in = mesh.gridFz[inds_fz,2]
+
+    in0_in = in0_in.reshape([in0_in.shape[0]//3,3])
+    in1_in = in1_in.reshape([in1_in.shape[0]//3,3])
+    z_in = z_in.reshape([z_in.shape[0]//3,3])
+
+    I0 = in0_in.sum(1).real
+    I1 = in1_in.sum(1).real
+    z_in = z_in[:,0]
+
+    if plotIt is True:
+        fig, ax = plt.subplots(1,2,figsize=(12,4))
+
+        ax[0].plot(z_in,np.absolute(I0), z_in,np.absolute(I1))
+        ax[0].legend(['top casing', 'bottom casing'],loc='best')
+        ax[0].set_title('Magnitude of Vertical Current in Casing')
+
+        ax[1].semilogy(z_in,np.absolute(I0), z_in,np.absolute(I1))
+        ax[1].legend(['top casing', 'bottom casing'],loc='best')
+        ax[1].set_title('Magnitude of Vertical Current in Casing')
+        ax[1].set_ylim([1e-2, 1.])
+
+        plt.show()
+
+if __name__ == '__main__':
+    run()
+

SimPEG/Examples/EM_TDEM_1D_Inversion.py

@@ -1,3 +1,9 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import *
 import SimPEG.EM as EM
 from SimPEG.EM import mu_0

SimPEG/Examples/FLOW_Richards_1D_Celia1990.py

@@ -1,3 +1,9 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import *
 from SimPEG.FLOW import Richards
 

SimPEG/Examples/Inversion_IRLS.py

@@ -0,0 +1,110 @@
+from __future__ import print_function
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import str
+from builtins import range
+from SimPEG import *
+
+
+def run(N=100, plotIt=True):
+    """
+        Inversion: Linear Problem
+        =========================
+
+        Here we go over the basics of creating a linear problem and inversion.
+
+    """
+
+
+    np.random.seed(1)
+
+    std_noise = 1e-2
+
+    mesh = Mesh.TensorMesh([N])
+
+    m0 = np.ones(mesh.nC) * 1e-4
+    mref = np.zeros(mesh.nC)
+
+    nk = 10
+    jk = np.linspace(1.,nk,nk)
+    p = -2.
+    q = 1.
+
+    g = lambda k: np.exp(p*jk[k]*mesh.vectorCCx)*np.cos(np.pi*q*jk[k]*mesh.vectorCCx)
+
+    G = np.empty((nk, mesh.nC))
+
+    for i in range(nk):
+        G[i,:] = g(i)
+
+    mtrue = np.zeros(mesh.nC)
+    mtrue[mesh.vectorCCx > 0.3] = 1.
+    mtrue[mesh.vectorCCx > 0.45] = -0.5
+    mtrue[mesh.vectorCCx > 0.6] = 0
+
+
+    prob = Problem.LinearProblem(mesh, G)
+    survey = Survey.LinearSurvey()
+    survey.pair(prob)
+    survey.dobs = prob.fields(mtrue) + std_noise * np.random.randn(nk)
+
+    wd = np.ones(nk) * std_noise
+
+    # Distance weighting
+    wr = np.sum(prob.G**2.,axis=0)**0.5
+    wr = ( wr/np.max(wr))
+
+    dmis = DataMisfit.l2_DataMisfit(survey)
+    dmis.Wd = 1./wd
+
+    betaest = Directives.BetaEstimate_ByEig()
+
+    reg = Regularization.Sparse(mesh)
+    reg.mref = mref
+    reg.cell_weights = wr
+
+    reg.mref = np.zeros(mesh.nC)
+
+
+    opt = Optimization.ProjectedGNCG(maxIter=100 ,lower=-2.,upper=2., maxIterLS = 20, maxIterCG= 10, tolCG = 1e-3)
+    invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
+    update_Jacobi = Directives.Update_lin_PreCond()
+
+    # Set the IRLS directive, penalize the lowest 25 percentile of model values
+    # Start with an l2-l2, then switch to lp-norms
+    norms   = [0., 0., 2., 2.]
+    IRLS = Directives.Update_IRLS( norms=norms, prctile = 25, maxIRLSiter = 15, minGNiter=3)
+
+    inv = Inversion.BaseInversion(invProb, directiveList=[IRLS,betaest,update_Jacobi])
+
+    # Run inversion
+    mrec = inv.run(m0)
+
+    print("Final misfit:" + str(invProb.dmisfit.eval(mrec)))
+
+
+    if plotIt:
+        import matplotlib.pyplot as plt
+
+        fig, axes = plt.subplots(1,2,figsize=(12*1.2,4*1.2))
+        for i in range(prob.G.shape[0]):
+            axes[0].plot(prob.G[i,:])
+        axes[0].set_title('Columns of matrix G')
+
+        axes[1].plot(mesh.vectorCCx, mtrue, 'b-')
+        axes[1].plot(mesh.vectorCCx, reg.l2model, 'r-')
+        #axes[1].legend(('True Model', 'Recovered Model'))
+        axes[1].set_ylim(-1.0,1.25)
+
+        axes[1].plot(mesh.vectorCCx, mrec, 'k-',lw = 2)
+        axes[1].legend(('True Model', 'Smooth l2-l2',
+        'Sparse lp:' + str(reg.norms[0]) + ', lqx:' + str(reg.norms[1]) ), fontsize = 12)
+        plt.show()
+
+    return prob, survey, mesh, mrec
+
+if __name__ == '__main__':
+    run()

SimPEG/Examples/Inversion_Linear.py

@@ -1,3 +1,10 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
 from SimPEG import *
 
 

SimPEG/Examples/MT_1D_ForwardAndInversion.py

@@ -1,3 +1,9 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 import SimPEG as simpeg
 import numpy as np
 import SimPEG.MT as MT
@@ -7,7 +13,7 @@ import matplotlib.pyplot as plt
 def run(plotIt=True):
     """
         MT: 1D: Inversion
-        =======================
+        =================
 
         Forward model 1D MT data.
         Setup and run a MT 1D inversion.
@@ -50,7 +56,7 @@ def run(plotIt=True):
     m_0 = np.log(sigma_0[active])
 
     # Set the mapping
-    actMap = simpeg.Maps.ActiveCells(m1d, active, np.log(1e-8), nC=m1d.nCx)
+    actMap = simpeg.Maps.InjectActiveCells(m1d, active, np.log(1e-8), nC=m1d.nCx)
     mappingExpAct = simpeg.Maps.ExpMap(m1d) * actMap
 
     ## Setup the layout of the survey, set the sources and the connected receivers
@@ -76,7 +82,7 @@ def run(plotIt=True):
     survey.dobs = survey.dtrue + 0.025*abs(survey.dtrue)*np.random.randn(*survey.dtrue.shape)
 
     if plotIt:
-        fig = MT.Utils.dataUtils.plotMT1DModelData(problem)
+        fig = MT.Utils.dataUtils.plotMT1DModelData(problem, [m_0])
         fig.suptitle('Target - smooth true')
 
 
@@ -100,7 +106,7 @@ def run(plotIt=True):
     # Regularization - with a regularization mesh
     regMesh = simpeg.Mesh.TensorMesh([m1d.hx[problem.mapping.sigmaMap.maps[-1].indActive]],m1d.x0)
     reg = simpeg.Regularization.Tikhonov(regMesh)
-    reg.smoothModel = True
+    reg.mrefInSmooth = True
     reg.alpha_s = 1e-7
     reg.alpha_x = 1.
     # Inversion problem

SimPEG/Examples/MT_3D_Foward.py

@@ -1,3 +1,9 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 # Test script to use SimPEG.MT platform to forward model synthetic data.
 
 # Import
@@ -12,7 +18,7 @@ except:
 def run(plotIt=True, nFreq=1):
     """
         MT: 3D: Forward
-        =======================
+        ===============
 
         Forward model 3D MT data.
 
@@ -46,16 +52,15 @@ def run(plotIt=True, nFreq=1):
     survey = MT.Survey(srcList)
 
     ## Setup the problem object
-    problem = MT.Problem3D.eForm_ps(M, sigmaPrimary=sigBG)
+    problem = MT.Problem3D.eForm_ps(M, sigmaPrimary=sigBG, Solver=Solver)
     problem.pair(survey)
-    problem.Solver = Solver
 
     # Calculate the data
     fields = problem.fields(sig)
     dataVec = survey.eval(fields)
 
     # Make the data
-    mtData = MT.Data(survey,dataVec)
+    mtData = MT.Data(survey, dataVec)
     # Add plots
     if plotIt:
         pass

SimPEG/Examples/Maps_ComboMaps.py

@@ -0,0 +1,69 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from builtins import dict
+from future import standard_library
+standard_library.install_aliases()
+from SimPEG import Mesh, Maps, np
+
+def run(plotIt=True):
+    """
+
+        Maps: ComboMaps
+        ===============
+
+        We will use an example where we want a 1D layered earth as
+        our model, but we want to map this to a 2D discretization to do our forward
+        modeling. We will also assume that we are working in log conductivity still,
+        so after the transformation we want to map to conductivity space.
+        To do this we will introduce the vertical 1D map (:class:`SimPEG.Maps.SurjectVertical1D`),
+        which does the first part of what we just described. The second part will be
+        done by the :class:`SimPEG.Maps.ExpMap` described above.
+
+        .. code-block:: python
+            :linenos:
+
+            M = Mesh.TensorMesh([7,5])
+            v1dMap = Maps.SurjectVertical1D(M)
+            expMap = Maps.ExpMap(M)
+            myMap = expMap * v1dMap
+            m = np.r_[0.2,1,0.1,2,2.9] # only 5 model parameters!
+            sig = myMap * m
+
+        If you noticed, it was pretty easy to combine maps. What is even cooler is
+        that the derivatives also are made for you (if everything goes right).
+        Just to be sure that the derivative is correct, you should always run the test
+        on the mapping that you create.
+
+    """
+
+
+    M = Mesh.TensorMesh([7,5])
+    v1dMap = Maps.SurjectVertical1D(M)
+    expMap = Maps.ExpMap(M)
+    myMap = expMap * v1dMap
+    m = np.r_[0.2,1,0.1,2,2.9] # only 5 model parameters!
+    sig = myMap * m
+
+    if not plotIt: return
+
+    import matplotlib.pyplot as plt
+    figs, axs = plt.subplots(1,2)
+    axs[0].plot(m, M.vectorCCy, 'b-o')
+    axs[0].set_title('Model')
+    axs[0].set_ylabel('Depth, y')
+    axs[0].set_xlabel('Value, $m_i$')
+    axs[0].set_xlim(0,3)
+    axs[0].set_ylim(0,1)
+    clbar = plt.colorbar(M.plotImage(sig,ax=axs[1],grid=True,gridOpts=dict(color='grey'))[0])
+    axs[1].set_title('Physical Property')
+    axs[1].set_ylabel('Depth, y')
+    clbar.set_label('$\sigma = \exp(\mathbf{P}m)$')
+    plt.tight_layout()
+    plt.show()
+
+
+if __name__ == '__main__':
+    run()
+

SimPEG/Examples/Maps_Mesh2Mesh.py

@@ -0,0 +1,47 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from SimPEG import Mesh, Maps, Utils
+
+def run(plotIt=True):
+    """
+
+        Maps: Mesh2Mesh
+        ===============
+
+        This mapping allows you to go from one mesh to another.
+
+    """
+
+    M = Mesh.TensorMesh([100,100])
+    h1 = Utils.meshTensor([(6,7,-1.5),(6,10),(6,7,1.5)])
+    h1 = h1/h1.sum()
+    M2 = Mesh.TensorMesh([h1,h1])
+    V = Utils.ModelBuilder.randomModel(M.vnC, seed=79, its=50)
+    v = Utils.mkvc(V)
+    modh = Maps.Mesh2Mesh([M,M2])
+    modH = Maps.Mesh2Mesh([M2,M])
+    H = modH * v
+    h = modh * H
+
+    if not plotIt: return
+
+    import matplotlib.pyplot as plt
+    ax = plt.subplot(131)
+    M.plotImage(v, ax=ax)
+    ax.set_title('Fine Mesh (Original)')
+    ax = plt.subplot(132)
+    M2.plotImage(H,clim=[0,1],ax=ax)
+    ax.set_title('Course Mesh')
+    ax = plt.subplot(133)
+    M.plotImage(h,clim=[0,1],ax=ax)
+    ax.set_title('Fine Mesh (Interpolated)')
+    plt.show()
+
+
+if __name__ == '__main__':
+    run()
+

SimPEG/Examples/Mesh_Basic_ForwardDC.py

@@ -1,22 +1,31 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import Mesh, Utils, np, SolverLU
 
-## 2D DC forward modeling example with Tensor and Curvilinear Meshes
-
 def run(plotIt=True):
+
+    """
+        Mesh: Basic Forward 2D DC Resistivity
+        =====================================
+
+        2D DC forward modeling example with Tensor and Curvilinear Meshes
+    """
+
     # Step1: Generate Tensor and Curvilinear Mesh
     sz = [40,40]
-    # Tensor Mesh
     tM = Mesh.TensorMesh(sz)
-    # Curvilinear Mesh
     rM = Mesh.CurvilinearMesh(Utils.meshutils.exampleLrmGrid(sz,'rotate'))
+
     # Step2: Direct Current (DC) operator
     def DCfun(mesh, pts):
         D = mesh.faceDiv
-        G = D.T
         sigma = 1e-2*np.ones(mesh.nC)
-        Msigi = mesh.getFaceInnerProduct(1./sigma)
-        MsigI = Utils.sdInv(Msigi)
-        A = D*MsigI*G
+        MsigI = mesh.getFaceInnerProduct(sigma, invProp=True, invMat=True)
+        A = -D*MsigI*D.T
         A[-1,-1] /= mesh.vol[-1] # Remove null space
         rhs = np.zeros(mesh.nC)
         txind = Utils.meshutils.closestPoints(mesh, pts)
@@ -37,39 +46,17 @@ def run(plotIt=True):
     if not plotIt: return
 
     import matplotlib.pyplot as plt
-    import matplotlib
-    from matplotlib.mlab import griddata
 
     #Step4: Making Figure
     fig, axes = plt.subplots(1,2,figsize=(12*1.2,4*1.2))
-    label = ["(a)", "(b)"]
-    opts = {}
     vmin, vmax = phitM.min(), phitM.max()
     dat = tM.plotImage(phitM, ax=axes[0], clim=(vmin, vmax), grid=True)
-
-    #TODO: At the moment Curvilinear Mesh do not have plotimage
-
-    Xi = tM.gridCC[:,0].reshape(sz[0], sz[1], order='F')
-    Yi = tM.gridCC[:,1].reshape(sz[0], sz[1], order='F')
-    PHIrM = griddata(rM.gridCC[:,0], rM.gridCC[:,1], phirM, Xi, Yi, interp='linear')
-    axes[1].contourf(Xi, Yi, PHIrM, 100, vmin=vmin, vmax=vmax)
-
+    dat = rM.plotImage(phirM, ax=axes[1], clim=(vmin, vmax), grid=True)
     cb = plt.colorbar(dat[0], ax=axes[0]); cb.set_label("Voltage (V)")
     cb = plt.colorbar(dat[0], ax=axes[1]); cb.set_label("Voltage (V)")
 
-    tM.plotGrid(ax=axes[0], **opts)
     axes[0].set_title('TensorMesh')
-    rM.plotGrid(ax=axes[1], **opts)
     axes[1].set_title('CurvilinearMesh')
-    for i in range(2):
-        axes[i].set_xlim(0.025, 0.975)
-        axes[i].set_ylim(0.025, 0.975)
-        axes[i].text(0., 1.0, label[i], fontsize=20)
-        if i==0:
-            axes[i].set_ylabel("y")
-        else:
-            axes[i].set_ylabel(" ")
-        axes[i].set_xlabel("x")
     plt.show()
 
 

SimPEG/Examples/Mesh_Basic_PlotImage.py

@@ -1,3 +1,9 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import *
 
 def run(plotIt=True):

SimPEG/Examples/Mesh_Basic_Types.py

@@ -1,3 +1,9 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import *
 
 def run(plotIt=True):

SimPEG/Examples/Mesh_Operators_CahnHilliard.py

@@ -1,3 +1,11 @@
+from __future__ import print_function
+from __future__ import unicode_literals
+from __future__ import division
+from __future__ import absolute_import
+from builtins import int
+from future import standard_library
+standard_library.install_aliases()
+from builtins import zip
 from SimPEG import *
 
 def run(plotIt=True, n=60):
@@ -87,7 +95,7 @@ def run(plotIt=True, n=60):
         if elapsed > capture[jj]:
             PHIS += [(elapsed, phi.copy())]
             jj += 1
-        if ii % 10 == 0: print ii, elapsed
+        if ii % 10 == 0: print(ii, elapsed)
         ii += 1
 
     if plotIt:

SimPEG/Examples/Mesh_QuadTree_Creation.py

@@ -1,3 +1,10 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
 from SimPEG import *
 
 def run(plotIt=True):

SimPEG/Examples/Mesh_QuadTree_FaceDiv.py

@@ -1,3 +1,11 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import zip
+from builtins import range
 from SimPEG import *
 
 def run(plotIt=True, n=60):
@@ -28,15 +36,15 @@ def run(plotIt=True, n=60):
         axes[0].set_xlim([-1,17])
         axes[0].set_ylim([-1,17])
 
-        for ii, loc in zip(range(M.nC),M.gridCC):
+        for ii, loc in zip(list(range(M.nC)),M.gridCC):
             axes[0].text(loc[0]+0.2,loc[1],'%d'%ii, color='r')
 
         axes[0].plot(M.gridFx[:,0],M.gridFx[:,1], 'g>')
-        for ii, loc in zip(range(M.nFx),M.gridFx):
+        for ii, loc in zip(list(range(M.nFx)),M.gridFx):
             axes[0].text(loc[0]+0.2,loc[1],'%d'%ii, color='g')
 
         axes[0].plot(M.gridFy[:,0],M.gridFy[:,1], 'm^')
-        for ii, loc in zip(range(M.nFy),M.gridFy):
+        for ii, loc in zip(list(range(M.nFy)),M.gridFy):
             axes[0].text(loc[0]+0.2,loc[1]+0.2,'%d'%(ii+M.nFx), color='m')
 
         axes[1].spy(M.faceDiv)

SimPEG/Examples/Mesh_QuadTree_HangingNodes.py

@@ -1,3 +1,9 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import *
 
 def run(plotIt=True):

SimPEG/Examples/Mesh_Tensor_Creation.py

@@ -1,3 +1,9 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import *
 
 def run(plotIt=True):

SimPEG/Examples/Utils_surface2ind_topo.py

@@ -0,0 +1,49 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from SimPEG import *
+from SimPEG.Utils import surface2ind_topo
+
+
+def run(plotIt=True, nx=5, ny=5):
+    """
+
+        Utils: surface2ind_topo
+        =======================
+
+        Here we show how to use :code:`Utils.surface2ind_topo` to identify cells below
+        a topographic surface.
+
+    """
+
+    mesh = Mesh.TensorMesh([nx,ny], x0='CC') # 2D mesh
+    xtopo = np.linspace(mesh.gridN[:,0].min(), mesh.gridN[:,0].max())
+    topo = 0.4*np.sin(xtopo*5) # define a topographic surface
+
+    Topo = np.hstack([Utils.mkvc(xtopo,2), Utils.mkvc(topo,2)]) #make it an array
+
+    indcc = surface2ind_topo(mesh, Topo, 'CC')
+
+    if plotIt:
+        from matplotlib.pylab import plt
+        from scipy.interpolate import interp1d
+        fig, ax = plt.subplots(1,1, figsize=(6,6))
+        mesh.plotGrid(ax=ax, nodes=True, centers=True)
+        ax.plot(xtopo,topo,'k',linewidth=1)
+        ax.plot(mesh.vectorCCx, interp1d(xtopo,topo)(mesh.vectorCCx),'--k',linewidth=3)
+
+        aveN2CC = Utils.sdiag(mesh.aveN2CC.T.sum(1))*mesh.aveN2CC.T
+        a = aveN2CC * indcc
+        a[a > 0] = 1.
+        a[a < 0.25] = np.nan
+        a = a.reshape(mesh.vnN, order='F')
+        masked_array = np.ma.array(a, mask=np.isnan(a))
+        ax.pcolor(mesh.vectorNx,mesh.vectorNy,masked_array.T, cmap=plt.cm.gray, alpha=0.2)
+        plt.show()
+
+
+if __name__ == '__main__':
+    run(plotIt=True)

SimPEG/Examples/__init__.py

@@ -1,25 +1,37 @@
+from __future__ import print_function
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import division
+from builtins import open
+from future import standard_library
+standard_library.install_aliases()
 # Run this file to add imports.
 
 ##### AUTOIMPORTS #####
-import DC_Analytic_Dipole
-import DC_Forward_PseudoSection
-import EM_FDEM_1D_Inversion
-import EM_FDEM_Analytic_MagDipoleWholespace
-import EM_TDEM_1D_Inversion
-import FLOW_Richards_1D_Celia1990
-import Forward_BasicDirectCurrent
-import Inversion_Linear
-import Mesh_Basic_PlotImage
-import Mesh_Basic_Types
-import Mesh_Operators_CahnHilliard
-import Mesh_QuadTree_Creation
-import Mesh_QuadTree_FaceDiv
-import Mesh_QuadTree_HangingNodes
-import Mesh_Tensor_Creation
-import MT_1D_ForwardAndInversion
-import MT_3D_Foward
+from . import DC_Analytic_Dipole
+from . import DC_Forward_PseudoSection
+from . import EM_FDEM_1D_Inversion
+from . import EM_FDEM_Analytic_MagDipoleWholespace
+from . import EM_Schenkel_Morrison_Casing
+from . import EM_TDEM_1D_Inversion
+from . import FLOW_Richards_1D_Celia1990
+from . import Inversion_IRLS
+from . import Inversion_Linear
+from . import Maps_ComboMaps
+from . import Maps_Mesh2Mesh
+from . import Mesh_Basic_ForwardDC
+from . import Mesh_Basic_PlotImage
+from . import Mesh_Basic_Types
+from . import Mesh_Operators_CahnHilliard
+from . import Mesh_QuadTree_Creation
+from . import Mesh_QuadTree_FaceDiv
+from . import Mesh_QuadTree_HangingNodes
+from . import Mesh_Tensor_Creation
+from . import MT_1D_ForwardAndInversion
+from . import MT_3D_Foward
+from . import Utils_surface2ind_topo
 
-__examples__ = ["DC_Analytic_Dipole", "DC_Forward_PseudoSection", "EM_FDEM_1D_Inversion", "EM_FDEM_Analytic_MagDipoleWholespace", "EM_TDEM_1D_Inversion", "FLOW_Richards_1D_Celia1990", "Forward_BasicDirectCurrent", "Inversion_Linear", "Mesh_Basic_PlotImage", "Mesh_Basic_Types", "Mesh_Operators_CahnHilliard", "Mesh_QuadTree_Creation", "Mesh_QuadTree_FaceDiv", "Mesh_QuadTree_HangingNodes", "Mesh_Tensor_Creation", "MT_1D_ForwardAndInversion", "MT_3D_Foward"]
+__examples__ = ["DC_Analytic_Dipole", "DC_Forward_PseudoSection", "EM_FDEM_1D_Inversion", "EM_FDEM_Analytic_MagDipoleWholespace", "EM_Schenkel_Morrison_Casing", "EM_TDEM_1D_Inversion", "FLOW_Richards_1D_Celia1990", "Inversion_IRLS", "Inversion_Linear", "Maps_ComboMaps", "Maps_Mesh2Mesh", "Mesh_Basic_ForwardDC", "Mesh_Basic_PlotImage", "Mesh_Basic_Types", "Mesh_Operators_CahnHilliard", "Mesh_QuadTree_Creation", "Mesh_QuadTree_FaceDiv", "Mesh_QuadTree_HangingNodes", "Mesh_Tensor_Creation", "MT_1D_ForwardAndInversion", "MT_3D_Foward", "Utils_surface2ind_topo"]
 
 ##### AUTOIMPORTS #####
 
@@ -35,7 +47,7 @@ if __name__ == '__main__':
 
     # Create the examples dir in the docs folder.
     fName = os.path.realpath(__file__)
-    docExamplesDir = os.path.sep.join(fName.split(os.path.sep)[:-3] + ['docs', 'examples'])
+    docExamplesDir = os.path.sep.join(fName.split(os.path.sep)[:-3] + ['docs', 'content', 'examples'])
     shutil.rmtree(docExamplesDir)
     os.makedirs(docExamplesDir)
 
@@ -92,14 +104,14 @@ if __name__ == '__main__':
     from SimPEG import Examples
     Examples.%s.run()
 
-.. literalinclude:: ../../SimPEG/Examples/%s.py
+.. literalinclude:: ../../../SimPEG/Examples/%s.py
     :language: python
     :linenos:
 """%(name,doc,name,name)
 
-        rst = os.path.sep.join((filePath.split(os.path.sep)[:-3] + ['docs', 'examples', name + '.rst']))
+        rst = os.path.sep.join((filePath.split(os.path.sep)[:-3] + ['docs', 'content', 'examples', name + '.rst']))
 
-        print 'Creating: %s.rst'%name
+        print('Creating: %s.rst'%name)
         f = open(rst, 'w')
         f.write(out)
         f.close()

SimPEG/FLOW/Richards/Empirical.py

@@ -1,14 +1,20 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import object
 from SimPEG import Mesh, Maps, Utils, np
+from future.utils import with_metaclass
 
 
-class NonLinearMap(object):
+class NonLinearMap(with_metaclass(Utils.SimPEGMetaClass, object)):
     """
     SimPEG NonLinearMap
 
     """
 
-    __metaclass__ = Utils.SimPEGMetaClass
-
     counter = None   #: A SimPEG.Utils.Counter object
     mesh = None      #: A SimPEG Mesh
 
@@ -31,7 +37,7 @@ class NonLinearMap(object):
         """
             :param numpy.array u: fields
             :param numpy.array m: model
-            :rtype: scipy.csr_matrix
+            :rtype: scipy.sparse.csr_matrix
             :return: derivative of transformed model
 
             The *transform* changes the model into the physical property.
@@ -44,7 +50,7 @@ class NonLinearMap(object):
         """
             :param numpy.array u: fields
             :param numpy.array m: model
-            :rtype: scipy.csr_matrix
+            :rtype: scipy.sparse.csr_matrix
             :return: derivative of transformed model
 
             The *transform* changes the model into the physical property.
@@ -186,7 +192,7 @@ class _haverkamp_theta(NonLinearMap):
 
     def transformDerivU(self, u, m):
         self.setModel(m)
-        g = (self.alpha*((self.theta_s - self.theta_r)/
+        g = (self.alpha*((self.theta_s - self.theta_r) /
              (self.alpha + abs(u)**self.beta)**2)
              *(-self.beta*abs(u)**(self.beta-1)*np.sign(u)))
         g[u >= 0] = 0
@@ -273,7 +279,7 @@ class _vangenuchten_theta(NonLinearMap):
     def transform(self, u, m):
         self.setModel(m)
         m = 1 - 1.0/self.n
-        f = ((  self.theta_s  -  self.theta_r  )/
+        f = ((  self.theta_s  -  self.theta_r  ) /
              ((1+abs(self.alpha*u)**self.n)**m)   +  self.theta_r)
         if Utils.isScalar(self.theta_s):
             f[u >= 0] = self.theta_s
@@ -343,7 +349,7 @@ class _vangenuchten_k(NonLinearMap):
         Ks = self.Ks
         m = 1.0 - 1.0/n
 
-        g = I*alpha*n*np.exp(Ks)*abs(alpha*u)**(n - 1.0)*np.sign(alpha*u)*(1.0/n - 1.0)*((abs(alpha*u)**n + 1)**(1.0/n - 1))**(I - 1)*((1 - 1.0/((abs(alpha*u)**n + 1)**(1.0/n - 1))**(1.0/(1.0/n - 1)))**(1 - 1.0/n) - 1)**2*(abs(alpha*u)**n + 1)**(1.0/n - 2) - (2*alpha*n*np.exp(Ks)*abs(alpha*u)**(n - 1)*np.sign(alpha*u)*(1.0/n - 1)*((abs(alpha*u)**n + 1)**(1.0/n - 1))**I*((1 - 1.0/((abs(alpha*u)**n + 1)**(1.0/n - 1))**(1.0/(1.0/n - 1)))**(1 - 1.0/n) - 1)*(abs(alpha*u)**n + 1)**(1.0/n - 2))/(((abs(alpha*u)**n + 1)**(1.0/n - 1))**(1.0/(1.0/n - 1) + 1)*(1 - 1.0/((abs(alpha*u)**n + 1)**(1.0/n - 1))**(1.0/(1.0/n - 1)))**(1.0/n))
+        g = I*alpha*n*np.exp(Ks)*abs(alpha*u)**(n - 1.0)*np.sign(alpha*u)*(1.0/n - 1.0)*((abs(alpha*u)**n + 1)**(1.0/n - 1))**(I - 1)*((1 - 1.0/((abs(alpha*u)**n + 1)**(1.0/n - 1))**(1.0/(1.0/n - 1)))**(1 - 1.0/n) - 1)**2*(abs(alpha*u)**n + 1)**(1.0/n - 2) - (2*alpha*n*np.exp(Ks)*abs(alpha*u)**(n - 1)*np.sign(alpha*u)*(1.0/n - 1)*((abs(alpha*u)**n + 1)**(1.0/n - 1))**I*((1 - 1.0/((abs(alpha*u)**n + 1)**(1.0/n - 1))**(1.0/(1.0/n - 1)))**(1 - 1.0/n) - 1)*(abs(alpha*u)**n + 1)**(1.0/n - 2))/(((abs(alpha*u)**n + 1)**(1.0/n - 1))**(1.0/(1.0/n - 1))+ 1)*(1 - 1.0/((abs(alpha*u)**n + 1)**(1.0/n - 1))**(1.0/(1.0/n - 1)))**(1.0/n)
         g[u >= 0] = 0
         g = Utils.sdiag(g)
         return g

SimPEG/FLOW/Richards/RichardsProblem.py

@@ -1,5 +1,12 @@
+from __future__ import print_function
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
 from SimPEG import *
-from Empirical import RichardsMap
+from .Empirical import RichardsMap
 import time
 
 
@@ -45,23 +52,23 @@ class RichardsSurvey(Survey.BaseSurvey):
 
     @Utils.count
     @Utils.requires('prob')
-    def dpred(self, m, u=None):
+    def dpred(self, m, f=None):
         """
             Create the projected data from a model.
-            The field, u, (if provided) will be used for the predicted data
+            The field, f, (if provided) will be used for the predicted data
             instead of recalculating the fields (which may be expensive!).
 
             .. math::
-                d_\\text{pred} = P(u(m), m)
+                d_\\text{pred} = P(f(m), m)
 
             Where P is a projection of the fields onto the data space.
         """
-        if u is None: u = self.prob.fields(m)
-        return Utils.mkvc(self.eval(u, m))
+        if f is None: f = self.prob.fields(m)
+        return Utils.mkvc(self.eval(f, m))
 
     @Utils.requires('prob')
     def eval(self, U, m):
-        Ds = range(len(self.rxList))
+        Ds = list(range(len(self.rxList)))
         for ii, rx in enumerate(self.rxList):
             Ds[ii] = rx.eval(U, m,
                                 self.prob.mapping,
@@ -73,7 +80,7 @@ class RichardsSurvey(Survey.BaseSurvey):
     @Utils.requires('prob')
     def evalDeriv(self, U, m):
         """The Derivative with respect to the fields."""
-        Ds = range(len(self.rxList))
+        Ds = list(range(len(self.rxList)))
         for ii, rx in enumerate(self.rxList):
             Ds[ii] = rx.evalDeriv(U, m,
                                 self.prob.mapping,
@@ -135,12 +142,12 @@ class RichardsProblem(Problem.BaseTimeProblem):
     @Utils.timeIt
     def fields(self, m):
         tic = time.time()
-        u = range(self.nT+1)
+        u = list(range(self.nT+1))
         u[0] = self.initialConditions
         for ii, dt in enumerate(self.timeSteps):
             bc = self.getBoundaryConditions(ii, u[ii])
             u[ii+1] = self.rootFinder.root(lambda hn1m, return_g=True: self.getResidual(m, u[ii], hn1m, dt, bc, return_g=return_g), u[ii])
-            if self.debug: print "Solving Fields (%4d/%d - %3.1f%% Done) %d Iterations, %4.2f seconds"%(ii+1, self.nT, 100.0*(ii+1)/self.nT, self.rootFinder.iter, time.time() - tic)
+            if self.debug: print("Solving Fields (%4d/%d - %3.1f%% Done) %d Iterations, %4.2f seconds"%(ii+1, self.nT, 100.0*(ii+1)/self.nT, self.rootFinder.iter, time.time() - tic))
         return u
 
     @Utils.timeIt
@@ -233,16 +240,16 @@ class RichardsProblem(Problem.BaseTimeProblem):
         return r, J
 
     @Utils.timeIt
-    def Jfull(self, m, u=None):
-        if u is None:
-            u = self.fields(m)
+    def Jfull(self, m, f=None):
+        if f is None:
+            f = self.fields(m)
 
-        nn = len(u)-1
-        Asubs, Adiags, Bs = range(nn), range(nn), range(nn)
+        nn = len(f)-1
+        Asubs, Adiags, Bs = list(range(nn)), list(range(nn)), list(range(nn))
         for ii in range(nn):
             dt = self.timeSteps[ii]
-            bc = self.getBoundaryConditions(ii, u[ii])
-            Asubs[ii], Adiags[ii], Bs[ii] = self.diagsJacobian(m, u[ii], u[ii+1], dt, bc)
+            bc = self.getBoundaryConditions(ii, f[ii])
+            Asubs[ii], Adiags[ii], Bs[ii] = self.diagsJacobian(m, f[ii], f[ii+1], dt, bc)
         Ad = sp.block_diag(Adiags)
         zRight = Utils.spzeros((len(Asubs)-1)*Asubs[0].shape[0],Adiags[0].shape[1])
         zTop = Utils.spzeros(Adiags[0].shape[0], len(Adiags)*Adiags[0].shape[1])
@@ -251,7 +258,7 @@ class RichardsProblem(Problem.BaseTimeProblem):
         B = np.array(sp.vstack(Bs).todense())
 
         Ainv = self.Solver(A, **self.solverOpts)
-        P = self.survey.evalDeriv(u, m)
+        P = self.survey.evalDeriv(f, m)
         AinvB = Ainv * B
         z = np.zeros((self.mesh.nC, B.shape[1]))
         zAinvB = np.vstack((z, AinvB))
@@ -259,43 +266,43 @@ class RichardsProblem(Problem.BaseTimeProblem):
         return J
 
     @Utils.timeIt
-    def Jvec(self, m, v, u=None):
-        if u is None:
-            u = self.fields(m)
+    def Jvec(self, m, v, f=None):
+        if f is None:
+            f = self.fields(m)
 
-        JvC = range(len(u)-1) # Cell to hold each row of the long vector.
+        JvC = list(range(len(f)-1)) # Cell to hold each row of the long vector.
 
         # This is done via forward substitution.
-        bc = self.getBoundaryConditions(0, u[0])
-        temp, Adiag, B = self.diagsJacobian(m, u[0], u[1], self.timeSteps[0], bc)
+        bc = self.getBoundaryConditions(0, f[0])
+        temp, Adiag, B = self.diagsJacobian(m, f[0], f[1], self.timeSteps[0], bc)
         Adiaginv = self.Solver(Adiag, **self.solverOpts)
         JvC[0] = Adiaginv * (B*v)
 
-        for ii in range(1,len(u)-1):
-            bc = self.getBoundaryConditions(ii, u[ii])
-            Asub, Adiag, B = self.diagsJacobian(m, u[ii], u[ii+1], self.timeSteps[ii], bc)
+        for ii in range(1,len(f)-1):
+            bc = self.getBoundaryConditions(ii, f[ii])
+            Asub, Adiag, B = self.diagsJacobian(m, f[ii], f[ii+1], self.timeSteps[ii], bc)
             Adiaginv = self.Solver(Adiag, **self.solverOpts)
             JvC[ii] = Adiaginv * (B*v - Asub*JvC[ii-1])
 
-        P = self.survey.evalDeriv(u, m)
+        P = self.survey.evalDeriv(f, m)
         return P * np.concatenate([np.zeros(self.mesh.nC)] + JvC)
 
     @Utils.timeIt
-    def Jtvec(self, m, v, u=None):
-        if u is None:
-            u = self.field(m)
+    def Jtvec(self, m, v, f=None):
+        if f is None:
+            f = self.field(m)
 
-        P = self.survey.evalDeriv(u, m)
+        P = self.survey.evalDeriv(f, m)
         PTv = P.T*v
 
         # This is done via backward substitution.
         minus = 0
         BJtv = 0
-        for ii in range(len(u)-1,0,-1):
-            bc = self.getBoundaryConditions(ii-1, u[ii-1])
-            Asub, Adiag, B = self.diagsJacobian(m, u[ii-1], u[ii], self.timeSteps[ii-1], bc)
+        for ii in range(len(f)-1,0,-1):
+            bc = self.getBoundaryConditions(ii-1, f[ii-1])
+            Asub, Adiag, B = self.diagsJacobian(m, f[ii-1], f[ii], self.timeSteps[ii-1], bc)
             #select the correct part of v
-            vpart = range((ii)*Adiag.shape[0], (ii+1)*Adiag.shape[0])
+            vpart = list(range((ii)*Adiag.shape[0], (ii+1)*Adiag.shape[0]))
             AdiaginvT = self.Solver(Adiag.T, **self.solverOpts)
             JTvC = AdiaginvT * (PTv[vpart] - minus)
             minus = Asub.T*JTvC  # this is now the super diagonal.

SimPEG/FLOW/Richards/__init__.py

@@ -1,2 +1,8 @@
-import Empirical
-from RichardsProblem import *
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from . import Empirical
+from .RichardsProblem import *

SimPEG/FLOW/__init__.py

@@ -1 +1,7 @@
-import Richards
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from . import Richards

SimPEG/Fields.py

@@ -1,4 +1,13 @@
-import Utils, numpy as np, scipy.sparse as sp
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import range
+from builtins import object
+from . import Utils
+import numpy as np, scipy.sparse as sp
 
 class Fields(object):
     """Fancy Field Storage
@@ -244,7 +253,7 @@ class TimeFields(Fields):
                 out = func(pointerFields, srcII, timeII)
             else: #loop over the time steps
                 nT = pointerShape[2]
-                out = range(nT)
+                out = list(range(nT))
                 for i, TIND_i in enumerate(timeII):
                     fieldI = pointerFields[:,:,i]
                     if fieldI.shape[0] == fieldI.size:

SimPEG/InvProblem.py

@@ -1,14 +1,21 @@
-import Utils, Survey, Problem, numpy as np, scipy.sparse as sp, gc
-from Utils.SolverUtils import *
-import DataMisfit
-import Regularization
+from __future__ import print_function
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from builtins import object
+from . import Utils, Survey, Problem
+import numpy as np, scipy.sparse as sp, gc
+from .Utils.SolverUtils import *
+from . import DataMisfit
+from . import Regularization
+from future.utils import with_metaclass
 
 
-class BaseInvProblem(object):
+class BaseInvProblem(with_metaclass(Utils.SimPEGMetaClass, object)):
     """BaseInvProblem(dmisfit, reg, opt)"""
 
-    __metaclass__ = Utils.SimPEGMetaClass
-
     beta    = 1.0    #: Trade-off parameter
 
     debug   = False  #: Print debugging information
@@ -54,10 +61,10 @@ class BaseInvProblem(object):
 
             Called when inversion is first starting.
         """
-        if self.debug: print 'Calling InvProblem.startup'
+        if self.debug: print('Calling InvProblem.startup')
 
         if self.reg.mref is None:
-            print 'SimPEG.InvProblem will set Regularization.mref to m0.'
+            print('SimPEG.InvProblem will set Regularization.mref to m0.')
             self.reg.mref = m0
 
         self.phi_d = np.nan
@@ -65,8 +72,8 @@ class BaseInvProblem(object):
 
         self.curModel = m0
 
-        print """SimPEG.InvProblem is setting bfgsH0 to the inverse of the eval2Deriv.
-                    ***Done using same Solver and solverOpts as the problem***"""
+        print("""SimPEG.InvProblem is setting bfgsH0 to the inverse of the eval2Deriv.
+                    ***Done using same Solver and solverOpts as the problem***""")
         self.opt.bfgsH0 = self.prob.Solver(self.reg.eval2Deriv(self.curModel), **self.prob.solverOpts)
 
     @property
@@ -82,23 +89,23 @@ class BaseInvProblem(object):
         self._warmstart = value
 
     def getFields(self, m, store=False, deleteWarmstart=True):
-        u = None
+        f = None
 
         for mtest, u_ofmtest in self.warmstart:
             if m is mtest:
-                u = u_ofmtest
-                if self.debug: print 'InvProb is Warm Starting!'
+                f = u_ofmtest
+                if self.debug: print('InvProb is Warm Starting!')
                 break
 
-        if u is None:
-            u = self.prob.fields(m)
+        if f is None:
+            f = self.prob.fields(m)
 
         if deleteWarmstart:
             self.warmstart = []
         if store:
-            self.warmstart += [(m,u)]
+            self.warmstart += [(m,f)]
 
-        return u
+        return f
 
     @Utils.timeIt
     def evalFunction(self, m, return_g=True, return_H=True):
@@ -109,21 +116,21 @@ class BaseInvProblem(object):
         gc.collect()
 
         # Store fields if doing a line-search
-        u = self.getFields(m, store=(return_g==False and return_H==False))
+        f = self.getFields(m, store=(return_g==False and return_H==False))
 
-        phi_d = self.dmisfit.eval(m, u=u)
+        phi_d = self.dmisfit.eval(m, f=f)
         phi_m = self.reg.eval(m)
 
-        self.dpred = self.survey.dpred(m, u=u)  # This is a cheap matrix vector calculation.
+        self.dpred = self.survey.dpred(m, f=f)  # This is a cheap matrix vector calculation.
 
         self.phi_d, self.phi_d_last  = phi_d, self.phi_d
         self.phi_m, self.phi_m_last  = phi_m, self.phi_m
 
-        f = phi_d + self.beta * phi_m
+        phi = phi_d + self.beta * phi_m
 
-        out = (f,)
+        out = (phi,)
         if return_g:
-            phi_dDeriv = self.dmisfit.evalDeriv(m, u=u)
+            phi_dDeriv = self.dmisfit.evalDeriv(m, f=f)
             phi_mDeriv = self.reg.evalDeriv(m)
 
             g = phi_dDeriv + self.beta * phi_mDeriv
@@ -131,7 +138,7 @@ class BaseInvProblem(object):
 
         if return_H:
             def H_fun(v):
-                phi_d2Deriv = self.dmisfit.eval2Deriv(m, v, u=u)
+                phi_d2Deriv = self.dmisfit.eval2Deriv(m, v, f=f)
                 phi_m2Deriv = self.reg.eval2Deriv(m, v=v)
 
                 return phi_d2Deriv + self.beta * phi_m2Deriv

SimPEG/Inversion.py

@@ -1,18 +1,24 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from builtins import object
 import SimPEG
 from SimPEG import Utils, sp, np
-from Optimization import Remember, IterationPrinters, StoppingCriteria
-import Directives
+from .Optimization import Remember, IterationPrinters, StoppingCriteria
+from . import Directives
+from future.utils import with_metaclass
 
 
-class BaseInversion(object):
+class BaseInversion(with_metaclass(Utils.SimPEGMetaClass, object)):
     """
 
         Inversion Class.
 
     """
 
-    __metaclass__ = Utils.SimPEGMetaClass
-
     name = 'BaseInversion'
 
     debug   = False    #: Print debugging information
@@ -33,7 +39,9 @@ class BaseInversion(object):
         self._directiveList = value
         self._directiveList.inversion = self
 
-    def __init__(self, invProb, directiveList=[], **kwargs):
+    def __init__(self, invProb, directiveList=None, **kwargs):
+        if directiveList is None:
+            directiveList = []
         self.directiveList = directiveList
         Utils.setKwargs(self, **kwargs)
 

SimPEG/MT/BaseMT.py

@@ -1,7 +1,13 @@
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import SolverLU as SimpegSolver, PropMaps, Utils, mkvc, sp, np
-from SimPEG.EM.FDEM.FDEM import BaseFDEMProblem
-from SurveyMT import Survey, Data
-from FieldsMT import BaseMTFields
+from SimPEG.EM.FDEM.ProblemFDEM import BaseFDEMProblem
+from .SurveyMT import Survey, Data
+from .FieldsMT import BaseMTFields
 
 
 class BaseMTProblem(BaseFDEMProblem):
@@ -27,7 +33,7 @@ class BaseMTProblem(BaseFDEMProblem):
     # Might need to add more stuff here.
 
     ## NEED to clean up the Jvec and Jtvec to use Zero and Identities for None components.
-    def Jvec(self, m, v, u=None):
+    def Jvec(self, m, v, f=None):
         """
         Function to calculate the data sensitivities dD/dm times a vector.
 
@@ -39,8 +45,8 @@ class BaseMTProblem(BaseFDEMProblem):
         """
 
         # Calculate the fields
-        if u is None:
-           u = self.fields(m)
+        if f is None:
+           f= self.fields(m)
         # Set current model
         self.curModel = m
         # Initiate the Jv object
@@ -56,9 +62,9 @@ class BaseMTProblem(BaseFDEMProblem):
                 # We need fDeriv_m = df/du*du/dm + df/dm
                 # Construct du/dm, it requires a solve
                 # NOTE: need to account for the 2 polarizations in the derivatives.
-                u_src = u[src,:]
+                f_src = f[src,:]
                 # dA_dm and dRHS_dm should be of size nE,2, so that we can multiply by dA_duI. The 2 columns are each of the polarizations.
-                dA_dm = self.getADeriv_m(freq, u_src, v) # Size: nE,2 (u_px,u_py) in the columns.
+                dA_dm = self.getADeriv_m(freq, f_src, v) # Size: nE,2 (u_px,u_py) in the columns.
                 dRHS_dm = self.getRHSDeriv_m(freq, v) # Size: nE,2 (u_px,u_py) in the columns.
                 if dRHS_dm is None:
                     du_dm = dA_duI * ( -dA_dm )
@@ -68,13 +74,13 @@ class BaseMTProblem(BaseFDEMProblem):
                 for rx in src.rxList:
                     # Get the projection derivative
                     # v should be of size 2*nE (for 2 polarizations)
-                    PDeriv_u = lambda t: rx.evalDeriv(src, self.mesh, u, t) # wrt u, we don't have have PDeriv wrt m
+                    PDeriv_u = lambda t: rx.evalDeriv(src, self.mesh, f, t) # wrt u, we don't have have PDeriv wrt m
                     Jv[src, rx] = PDeriv_u(mkvc(du_dm))
             dA_duI.clean()
         # Return the vectorized sensitivities
         return mkvc(Jv)
 
-    def Jtvec(self, m, v, u=None):
+    def Jtvec(self, m, v, f=None):
         """
         Function to calculate the transpose of the data sensitivities (dD/dm)^T times a vector.
 
@@ -85,8 +91,8 @@ class BaseMTProblem(BaseFDEMProblem):
             :return: Data sensitivities wrt m
         """
 
-        if u is None:
-            u = self.fields(m)
+        if f is None:
+            f = self.fields(m)
 
         self.curModel = m
 
@@ -103,15 +109,15 @@ class BaseMTProblem(BaseFDEMProblem):
 
             for src in self.survey.getSrcByFreq(freq):
                 ftype = self._fieldType + 'Solution'
-                u_src = u[src, :]
+                f_src = f[src, :]
 
                 for rx in src.rxList:
                     # Get the adjoint evalDeriv
                     # PTv needs to be nE,
-                    PTv = rx.evalDeriv(src, self.mesh, u, mkvc(v[src, rx],2), adjoint=True) # wrt u, need possibility wrt m
+                    PTv = rx.evalDeriv(src, self.mesh, f, mkvc(v[src, rx],2), adjoint=True) # wrt u, need possibility wrt m
                     # Get the
                     dA_duIT = ATinv * PTv
-                    dA_dmT = self.getADeriv_m(freq, u_src, mkvc(dA_duIT), adjoint=True)
+                    dA_dmT = self.getADeriv_m(freq, f_src, mkvc(dA_duIT), adjoint=True)
                     dRHS_dmT = self.getRHSDeriv_m(freq, mkvc(dA_duIT), adjoint=True)
                     # Make du_dmT
                     if dRHS_dmT is None:
@@ -129,4 +135,4 @@ class BaseMTProblem(BaseFDEMProblem):
                         raise Exception('Must be real or imag')
             # Clean the factorization, clear memory.
             ATinv.clean()
-        return Jtv
+        return Jtv

SimPEG/MT/FieldsMT.py

@@ -1,3 +1,9 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import Survey, Utils, Problem, np, sp, mkvc
 from scipy.constants import mu_0
 import sys
@@ -63,7 +69,7 @@ class Fields1D_e(BaseMTFields):
         C = self.mesh.nodalGrad
         b = (C * eSolution)
         for i, src in enumerate(srcList):
-            b[:,i] *= - 1./(1j*omega(src.freq))
+            b[:,i] *= -1./(1j*omega(src.freq))
             # There is no magnetic source in the MT problem
             # S_m, _ = src.eval(self.survey.prob)
             # if S_m is not None:
@@ -188,7 +194,7 @@ class Fields3D_e(BaseMTFields):
             # adjoint: returns a 2*nE long vector with zero's for py
             return np.vstack((v,np.zeros_like(v)))
         # Not adjoint: return only the px part of the vector
-        return v[:len(v)/2]
+        return v[:len(v)//2]
 
     def _e_pyDeriv_u(self, src, v, adjoint = False):
         '''
@@ -198,7 +204,7 @@ class Fields3D_e(BaseMTFields):
             # adjoint: returns a 2*nE long vector with zero's for px
             return np.vstack((np.zeros_like(v),v))
         # Not adjoint: return only the px part of the vector
-        return v[len(v)/2::]
+        return v[len(v)//2::]
 
     def _e_pxDeriv_m(self, src, v, adjoint = False):
         # assuming primary does not depend on the model
@@ -227,7 +233,7 @@ class Fields3D_e(BaseMTFields):
         C = self.mesh.edgeCurl
         b = (C * e_pxSolution)
         for i, src in enumerate(srcList):
-            b[:,i] *= - 1./(1j*omega(src.freq))
+            b[:,i] *= -1./(1j*omega(src.freq))
             # There is no magnetic source in the MT problem
             # S_m, _ = src.eval(self.survey.prob)
             # if S_m is not None:
@@ -238,7 +244,7 @@ class Fields3D_e(BaseMTFields):
         C = self.mesh.edgeCurl
         b = (C * e_pySolution)
         for i, src in enumerate(srcList):
-            b[:,i] *= - 1./(1j*omega(src.freq))
+            b[:,i] *= -1./(1j*omega(src.freq))
             # There is no magnetic source in the MT problem
             # S_m, _ = src.eval(self.survey.prob)
             # if S_m is not None:
@@ -348,4 +354,4 @@ class Fields3D_e(BaseMTFields):
         This function stacks the fields derivatives appropriately
         """
         # The fields have no dependance to the model.
-        return None
+        return None

SimPEG/MT/Problem1D/Probs.py

@@ -1,3 +1,9 @@
+from __future__ import print_function
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG.EM.Utils import omega
 from SimPEG import mkvc
 from scipy.constants import mu_0
@@ -46,7 +52,7 @@ class eForm_psField(BaseMTProblem):
             Edge inner product matrix
         """
         if getattr(self, '_MeMui', None) is None:
-            self._MeMui = self.mesh.getEdgeInnerProduct(1.0/mu_0)
+            self._MeMui = self.mesh.getEdgeInnerProduct(old_div(1.0,mu_0))
         return self._MeMui
 
     @property
@@ -142,7 +148,7 @@ class eForm_psField(BaseMTProblem):
         for freq in self.survey.freqs:
             if self.verbose:
                 startTime = time.time()
-                print 'Starting work for {:.3e}'.format(freq)
+                print('Starting work for {:.3e}'.format(freq))
                 sys.stdout.flush()
             A = self.getA(freq)
             rhs  = self.getRHS(freq)
@@ -158,7 +164,7 @@ class eForm_psField(BaseMTProblem):
             # b = -( self.mesh.nodalGrad * e )/( 1j*omega(freq) )
             # F[Src, 'b_1d'] = b[:,1]
             if self.verbose:
-                print 'Ran for {:f} seconds'.format(time.time()-startTime)
+                print('Ran for {:f} seconds'.format(time.time()-startTime))
                 sys.stdout.flush()
         return F
 
@@ -191,7 +197,7 @@ class eForm_TotalField(BaseMTProblem):
             Edge inner product matrix
         """
         if getattr(self, '_MeMui', None) is None:
-            self._MeMui = self.mesh.getEdgeInnerProduct(1.0/mu_0)
+            self._MeMui = self.mesh.getEdgeInnerProduct(old_div(1.0,mu_0))
         return self._MeMui
 
     @property
@@ -249,7 +255,7 @@ class eForm_TotalField(BaseMTProblem):
         Ed, Eu, Hd, Hu = getEHfields(self.mesh,self.curModel.sigma,freq,self.mesh.vectorNx)
         Etot = (Ed + Eu)
         sourceAmp = 1.0
-        Etot = ((Etot/Etot[-1])*sourceAmp) # Scale the fields to be equal to sourceAmp at the top
+        Etot = ((old_div(Etot,Etot[-1]))*sourceAmp) # Scale the fields to be equal to sourceAmp at the top
         ## Note: The analytic solution is derived with e^iwt
         eBC = np.r_[Etot[0],Etot[-1]]
         # The right hand side
@@ -274,7 +280,7 @@ class eForm_TotalField(BaseMTProblem):
         for freq in self.survey.freqs:
             if self.verbose:
                 startTime = time.time()
-                print 'Starting work for {:.3e}'.format(freq)
+                print('Starting work for {:.3e}'.format(freq))
                 sys.stdout.flush()
             A = self.getA(freq)
             rhs, e_o = self.getRHS(freq)
@@ -286,6 +292,6 @@ class eForm_TotalField(BaseMTProblem):
             # NOTE: only store e fields
             F[Src, 'e_1dSolution'] = e[:,0]
             if self.verbose:
-                print 'Ran for {:f} seconds'.format(time.time()-startTime)
+                print('Ran for {:f} seconds'.format(time.time()-startTime))
                 sys.stdout.flush()
         return F

SimPEG/MT/Problem1D/__init__.py

@@ -1 +1,7 @@
-from Probs import eForm_TotalField, eForm_psField
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .Probs import eForm_TotalField, eForm_psField

SimPEG/MT/Problem2D/__init__.py

@@ -1 +1,7 @@
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 pass

SimPEG/MT/Problem3D/Probs.py

@@ -1,3 +1,9 @@
+from __future__ import print_function
+from __future__ import unicode_literals
+from __future__ import division
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import Survey, Problem, Utils, Models, np, sp, mkvc, SolverLU as SimpegSolver
 from SimPEG.EM.Utils import omega
 from scipy.constants import mu_0
@@ -115,7 +121,7 @@ class eForm_ps(BaseMTProblem):
         for freq in self.survey.freqs:
             if self.verbose:
                 startTime = time.time()
-                print 'Starting work for {:.3e}'.format(freq)
+                print('Starting work for {:.3e}'.format(freq))
                 sys.stdout.flush()
             A = self.getA(freq)
             rhs  = self.getRHS(freq)
@@ -131,7 +137,7 @@ class eForm_ps(BaseMTProblem):
             # Note curl e = -iwb so b = -curl/iw
 
             if self.verbose:
-                print 'Ran for {:f} seconds'.format(time.time()-startTime)
+                print('Ran for {:f} seconds'.format(time.time()-startTime))
                 sys.stdout.flush()
             Ainv.clean()
         return F

SimPEG/MT/Problem3D/__init__.py

@@ -1 +1,7 @@
-from Probs import eForm_ps
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .Probs import eForm_ps

SimPEG/MT/SrcMT.py

@@ -1,10 +1,16 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import Utils, Problem, Maps, np, sp, mkvc
 from SimPEG.EM.FDEM.SrcFDEM import BaseSrc as FDEMBaseSrc
 from SimPEG.EM.Utils import omega
 from scipy.constants import mu_0
 from numpy.lib import recfunctions as recFunc
-from Utils.sourceUtils import homo1DModelSource
-from Utils import rec2ndarr
+from .Utils.sourceUtils import homo1DModelSource
+from .Utils import rec2ndarr
 import sys
 
 #################
@@ -78,7 +84,7 @@ class polxy_1Dprimary(BaseMTSrc):
             C = problem.mesh.nodalGrad
         elif problem.mesh.dim == 3:
             C = problem.mesh.edgeCurl
-        bBG_bp = (- C * self.ePrimary(problem) )*(1/( 1j*omega(self.freq) ))
+        bBG_bp = (- C * self.ePrimary(problem) )*(1/(1j*omega(self.freq)))
         return bBG_bp
 
     def S_e(self,problem):
@@ -86,7 +92,7 @@ class polxy_1Dprimary(BaseMTSrc):
         Get the electrical field source
         """
         e_p = self.ePrimary(problem)
-        Map_sigma_p = Maps.Vertical1DMap(problem.mesh)
+        Map_sigma_p = Maps.SurjectVertical1D(problem.mesh)
         sigma_p = Map_sigma_p._transform(self.sigma1d)
         # Make mass matrix
         # Note: M(sig) - M(sig_p) = M(sig - sig_p)
@@ -155,7 +161,7 @@ class polxy_3Dprimary(BaseMTSrc):
             C = problem.mesh.nodalGrad
         elif problem.mesh.dim == 3:
             C = problem.mesh.edgeCurl
-        bBG_bp = (- C * self.ePrimary(problem) )*(1/( 1j*omega(self.freq) ))
+        bBG_bp = (- C * self.ePrimary(problem) )*(1/(1j*omega(self.freq)))
         return bBG_bp
 
     def S_e(self,problem):
@@ -163,7 +169,7 @@ class polxy_3Dprimary(BaseMTSrc):
         Get the electrical field source
         """
         e_p = self.ePrimary(problem)
-        Map_sigma_p = Maps.Vertical1DMap(problem.mesh)
+        Map_sigma_p = Maps.SurjectVertical1D(problem.mesh)
         sigma_p = Map_sigma_p._transform(self.sigma1d)
         # Make mass matrix
         # Note: M(sig) - M(sig_p) = M(sig - sig_p)

SimPEG/MT/SurveyMT.py

@@ -1,10 +1,16 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from future import standard_library
+standard_library.install_aliases()
 from SimPEG import Survey as SimPEGsurvey, Utils, Problem, Maps, np, sp, mkvc
 from SimPEG.EM.FDEM.SrcFDEM import BaseSrc as FDEMBaseSrc
 from SimPEG.EM.Utils import omega
 from scipy.constants import mu_0
 from numpy.lib import recfunctions as recFunc
-from Utils import rec2ndarr
-import SrcMT
+from .Utils import rec2ndarr
+from . import SrcMT
 import sys
 
 #################
@@ -76,7 +82,7 @@ class Rx(SimPEGsurvey.BaseRx):
             bx = Pbx*mkvc(f[src,'b_1d'],2)/mu_0
             # Note: Has a minus sign in front, to comply with quadrant calculations.
             # Can be derived from zyx case for the 3D case.
-            f_part_complex = -ex/bx
+            f_part_complex = old_div(-ex,bx)
         # elif self.projType is 'Z2D':
         elif self.projType is 'Z3D':
             ## NOTE: Assumes that e is on edges and b on the faces. Need to generalize that or use a prop of fields to determine that.
@@ -103,13 +109,13 @@ class Rx(SimPEGsurvey.BaseRx):
             hy_py = Pby*f[src,'b_py']/mu_0
             # Make the complex data
             if 'zxx' in self.rxType:
-                f_part_complex = ( ex_px*hy_py - ex_py*hy_px)/(hx_px*hy_py - hx_py*hy_px)
+                f_part_complex = old_div(( ex_px*hy_py - ex_py*hy_px),(hx_px*hy_py - hx_py*hy_px))
             elif 'zxy' in self.rxType:
-                f_part_complex = (-ex_px*hx_py + ex_py*hx_px)/(hx_px*hy_py - hx_py*hy_px)
+                f_part_complex = old_div((-ex_px*hx_py + ex_py*hx_px),(hx_px*hy_py - hx_py*hy_px))
             elif 'zyx' in self.rxType:
-                f_part_complex = ( ey_px*hy_py - ey_py*hy_px)/(hx_px*hy_py - hx_py*hy_px)
+                f_part_complex = old_div(( ey_px*hy_py - ey_py*hy_px),(hx_px*hy_py - hx_py*hy_px))
             elif 'zyy' in self.rxType:
-                f_part_complex = (-ey_px*hx_py + ey_py*hx_px)/(hx_px*hy_py - hx_py*hy_px)
+                f_part_complex = old_div((-ey_px*hx_py + ey_py*hx_px),(hx_px*hy_py - hx_py*hy_px))
         elif self.projType is 'T3D':
             if self.locs.ndim == 3:
                 horLoc = self.locs[:,:,0]
@@ -127,9 +133,9 @@ class Rx(SimPEGsurvey.BaseRx):
             by_py = Pby*f[src,'b_py']
             bz_py = Pbz*f[src,'b_py']
             if 'tzx' in self.rxType:
-                f_part_complex = (- by_px*bz_py + by_py*bz_px)/(bx_px*by_py - bx_py*by_px)
+                f_part_complex = old_div((- by_px*bz_py + by_py*bz_px),(bx_px*by_py - bx_py*by_px))
             if 'tzy' in self.rxType:
-                f_part_complex = (  bx_px*bz_py - bx_py*bz_px)/(bx_px*by_py - bx_py*by_px)
+                f_part_complex = old_div((  bx_px*bz_py - bx_py*bz_px),(bx_px*by_py - bx_py*by_px))
 
         else:
             NotImplementedError('Projection of {:s} receiver type is not implemented.'.format(self.rxType))
@@ -157,8 +163,8 @@ class Rx(SimPEGsurvey.BaseRx):
                 Pbx = mesh.getInterpolationMat(self.locs[:,-1],'Ex')
                 # ex = Pex*mkvc(f[src,'e_1d'],2)
                 # bx = Pbx*mkvc(f[src,'b_1d'],2)/mu_0
-                dP_de = -mkvc(Utils.sdiag(1./(Pbx*mkvc(f[src,'b_1d'],2)/mu_0))*(Pex*v),2)
-                dP_db = mkvc( Utils.sdiag(Pex*mkvc(f[src,'e_1d'],2))*(Utils.sdiag(1./(Pbx*mkvc(f[src,'b_1d'],2)/mu_0)).T*Utils.sdiag(1./(Pbx*mkvc(f[src,'b_1d'],2)/mu_0)))*(Pbx*f._bDeriv_u(src,v)/mu_0),2)
+                dP_de = -mkvc(Utils.sdiag(old_div(1.,(Pbx*mkvc(f[src,'b_1d'],2)/mu_0)))*(Pex*v),2)
+                dP_db = mkvc( Utils.sdiag(Pex*mkvc(f[src,'e_1d'],2))*(Utils.sdiag(old_div(1.,(Pbx*mkvc(f[src,'b_1d'],2)/mu_0))).T*Utils.sdiag(old_div(1.,(Pbx*mkvc(f[src,'b_1d'],2)/mu_0))))*(Pbx*f._bDeriv_u(src,v)/mu_0),2)
                 PDeriv_complex = np.sum(np.hstack((dP_de,dP_db)),1)
             elif self.projType is 'Z2D':
                 raise NotImplementedError('Has not been implement for 2D impedance tensor')
@@ -198,7 +204,7 @@ class Rx(SimPEGsurvey.BaseRx):
                 # Update the input vector
                 sDiag = lambda t: Utils.sdiag(mkvc(t,2))
                 # Define the components of the derivative
-                Hd = sDiag(1./(sDiag(hx_px)*hy_py - sDiag(hx_py)*hy_px))
+                Hd = sDiag(old_div(1.,(sDiag(hx_px)*hy_py - sDiag(hx_py)*hy_px)))
                 Hd_uV = sDiag(hy_py)*hx_px_u(v) + sDiag(hx_px)*hy_py_u(v) - sDiag(hx_py)*hy_px_u(v) - sDiag(hy_px)*hx_py_u(v)
                 # Calculate components
                 if 'zxx' in self.rxType:
@@ -247,7 +253,7 @@ class Rx(SimPEGsurvey.BaseRx):
                 # Update the input vector
                 sDiag = lambda t: Utils.sdiag(mkvc(t,2))
                 # Define the components of the derivative
-                Hd = sDiag(1./(sDiag(bx_px)*by_py - sDiag(bx_py)*by_px))
+                Hd = sDiag(old_div(1.,(sDiag(bx_px)*by_py - sDiag(bx_py)*by_px)))
                 Hd_uV = sDiag(by_py)*bx_px_u(v) + sDiag(bx_px)*by_py_u(v) - sDiag(bx_py)*by_px_u(v) - sDiag(by_px)*bx_py_u(v)
                 if 'tzx' in self.rxType:
                     Tij = sDiag(Hd*( - sDiag(by_px)*bz_py + sDiag(by_py)*bz_px ))
@@ -267,8 +273,8 @@ class Rx(SimPEGsurvey.BaseRx):
                 Pbx = mesh.getInterpolationMat(self.locs[:,-1],'Ex')
                 # ex = Pex*mkvc(f[src,'e_1d'],2)
                 # bx = Pbx*mkvc(f[src,'b_1d'],2)/mu_0
-                dP_deTv = -mkvc(Pex.T*Utils.sdiag(1./(Pbx*mkvc(f[src,'b_1d'],2)/mu_0)).T*v,2)
-                db_duv = Pbx.T/mu_0*Utils.sdiag(1./(Pbx*mkvc(f[src,'b_1d'],2)/mu_0))*(Utils.sdiag(1./(Pbx*mkvc(f[src,'b_1d'],2)/mu_0))).T*Utils.sdiag(Pex*mkvc(f[src,'e_1d'],2)).T*v
+                dP_deTv = -mkvc(Pex.T*Utils.sdiag(old_div(1.,(Pbx*mkvc(f[src,'b_1d'],2)/mu_0))).T*v,2)
+                db_duv = Pbx.T/mu_0*Utils.sdiag(old_div(1.,(Pbx*mkvc(f[src,'b_1d'],2)/mu_0)))*(Utils.sdiag(old_div(1.,(Pbx*mkvc(f[src,'b_1d'],2)/mu_0)))).T*Utils.sdiag(Pex*mkvc(f[src,'e_1d'],2)).T*v
                 dP_dbTv = mkvc(f._bDeriv_u(src,db_duv,adjoint=True),2)
                 PDeriv_real = np.sum(np.hstack((dP_deTv,dP_dbTv)),1)
             elif self.projType is 'Z2D':
@@ -300,17 +306,17 @@ class Rx(SimPEGsurvey.BaseRx):
                 aey_px_u = lambda vec: f._e_pxDeriv_u(src,Pey.T*vec,adjoint=True)
                 aex_py_u = lambda vec: f._e_pyDeriv_u(src,Pex.T*vec,adjoint=True)
                 aey_py_u = lambda vec: f._e_pyDeriv_u(src,Pey.T*vec,adjoint=True)
-                ahx_px_u = lambda vec: f._b_pxDeriv_u(src,Pbx.T*vec,adjoint=True)/mu_0
-                ahy_px_u = lambda vec: f._b_pxDeriv_u(src,Pby.T*vec,adjoint=True)/mu_0
-                ahx_py_u = lambda vec: f._b_pyDeriv_u(src,Pbx.T*vec,adjoint=True)/mu_0
-                ahy_py_u = lambda vec: f._b_pyDeriv_u(src,Pby.T*vec,adjoint=True)/mu_0
+                ahx_px_u = lambda vec: old_div(f._b_pxDeriv_u(src,Pbx.T*vec,adjoint=True),mu_0)
+                ahy_px_u = lambda vec: old_div(f._b_pxDeriv_u(src,Pby.T*vec,adjoint=True),mu_0)
+                ahx_py_u = lambda vec: old_div(f._b_pyDeriv_u(src,Pbx.T*vec,adjoint=True),mu_0)
+                ahy_py_u = lambda vec: old_div(f._b_pyDeriv_u(src,Pby.T*vec,adjoint=True),mu_0)
 
                 # Update the input vector
                 # Define shortcuts
                 sDiag = lambda t: Utils.sdiag(mkvc(t,2))
                 sVec = lambda t: Utils.sp.csr_matrix(mkvc(t,2))
                 # Define the components of the derivative
-                aHd = sDiag(1./(sDiag(ahx_px)*ahy_py - sDiag(ahx_py)*ahy_px))
+                aHd = sDiag(old_div(1.,(sDiag(ahx_px)*ahy_py - sDiag(ahx_py)*ahy_px)))
                 aHd_uV = lambda x: ahx_px_u(sDiag(ahy_py)*x) + ahx_px_u(sDiag(ahy_py)*x) - ahy_px_u(sDiag(ahx_py)*x) - ahx_py_u(sDiag(ahy_px)*x)
                 # Need to fix this to reflect the adjoint
                 if 'zxx' in self.rxType:
@@ -362,7 +368,7 @@ class Rx(SimPEGsurvey.BaseRx):
                 sDiag = lambda t: Utils.sdiag(mkvc(t,2))
                 sVec = lambda t: Utils.sp.csr_matrix(mkvc(t,2))
                 # Define the components of the derivative
-                aHd = sDiag(1./(sDiag(abx_px)*aby_py - sDiag(abx_py)*aby_px))
+                aHd = sDiag(old_div(1.,(sDiag(abx_px)*aby_py - sDiag(abx_py)*aby_px)))
                 aHd_uV = lambda x: abx_px_u(sDiag(aby_py)*x) + abx_px_u(sDiag(aby_py)*x) - aby_px_u(sDiag(abx_py)*x) - abx_py_u(sDiag(aby_px)*x)
                 # Need to fix this to reflect the adjoint
                 if 'tzx' in self.rxType:
@@ -427,15 +433,15 @@ class Survey(SimPEGsurvey.BaseSurvey):
         assert freq in self._freqDict, "The requested frequency is not in this survey."
         return self._freqDict[freq]
 
-    def eval(self, u):
+    def eval(self, f):
         data = Data(self)
         for src in self.srcList:
             sys.stdout.flush()
             for rx in src.rxList:
-                data[src, rx] = rx.eval(src, self.mesh, u)
+                data[src, rx] = rx.eval(src, self.mesh, f)
         return data
 
-    def evalDeriv(self, u):
+    def evalDeriv(self, f):
         raise Exception('Use Transmitters to project fields deriv.')
 
 #################

SimPEG/MT/Utils/MT1Danalytic.py

@@ -1,3 +1,10 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
+from builtins import zip
 # Analytic solution of EM fields due to a plane wave
 
 import numpy as np, SimPEG as simpeg
@@ -33,8 +40,8 @@ def getEHfields(m1d,sigma,freq,zd,scaleUD=True):
     # Loop over all the layers, starting at the bottom layer
     for lnr, h in enumerate(m1d.hx): # lnr-number of layer, h-thickness of the layer
         # Calculate
-        yp1 = k[lnr]/(w*mu[lnr]) # Admittance of the layer below the current layer
-        zp = (w*mu[lnr+1])/k[lnr+1] # Impedance in the current layer
+        yp1 = old_div(k[lnr],(w*mu[lnr])) # Admittance of the layer below the current layer
+        zp = old_div((w*mu[lnr+1]),k[lnr+1]) # Impedance in the current layer
         # Build the propagation matrix
 
         # Convert fields to down/up going components in layer below current layer
@@ -48,7 +55,7 @@ def getEHfields(m1d,sigma,freq,zd,scaleUD=True):
         UDp[:,lnr+1] = elamh.dot(Pjinv.dot(Pj1)).dot(UDp[:,lnr])
 
         if scaleUD:
-             UDp[:,lnr+1::-1] = UDp[:,lnr+1::-1]/UDp[1,lnr+1]
+             UDp[:,lnr+1::-1] = old_div(UDp[:,lnr+1::-1],UDp[1,lnr+1])
 
     # Calculate the fields
     Ed = np.empty((zd.size,),dtype=complex)
@@ -62,14 +69,14 @@ def getEHfields(m1d,sigma,freq,zd,scaleUD=True):
     dind = dup >= zd
     Ed[dind] = UDp[1,0]*np.exp(-1j*k[0]*(dup-zd[dind]))
     Eu[dind] = UDp[0,0]*np.exp(1j*k[0]*(dup-zd[dind]))
-    Hd[dind] = (k[0]/(w*mu[0]))*UDp[1,0]*np.exp(-1j*k[0]*(dup-zd[dind]))
-    Hu[dind] = -(k[0]/(w*mu[0]))*UDp[0,0]*np.exp(1j*k[0]*(dup-zd[dind]))
+    Hd[dind] = (old_div(k[0],(w*mu[0])))*UDp[1,0]*np.exp(-1j*k[0]*(dup-zd[dind]))
+    Hu[dind] = -(old_div(k[0],(w*mu[0])))*UDp[0,0]*np.exp(1j*k[0]*(dup-zd[dind]))
     for ki,mui,epsi,dlow,dup,Up,Dp in zip(k[1::],mu[1::],eps[1::],m1d.vectorNx[:-1],m1d.vectorNx[1::],UDp[0,1::],UDp[1,1::]):
         dind = np.logical_and(dup >= zd, zd > dlow)
         Ed[dind] = Dp*np.exp(-1j*ki*(dup-zd[dind]))
         Eu[dind] = Up*np.exp(1j*ki*(dup-zd[dind]))
-        Hd[dind] = (ki/(w*mui))*Dp*np.exp(-1j*ki*(dup-zd[dind]))
-        Hu[dind] = -(ki/(w*mui))*Up*np.exp(1j*ki*(dup-zd[dind]))
+        Hd[dind] = (old_div(ki,(w*mui)))*Dp*np.exp(-1j*ki*(dup-zd[dind]))
+        Hu[dind] = -(old_div(ki,(w*mui)))*Up*np.exp(1j*ki*(dup-zd[dind]))
 
     # Return return the fields
     return Ed, Eu, Hd, Hu
@@ -92,15 +99,15 @@ def getImpedance(m1d,sigma,freq):
         om = 2*np.pi*fr
         Zall = np.empty(len(h)+1,dtype='complex')
         # Calculate the impedance for the bottom layer
-        Zall[0] = (mu_0*om)/np.sqrt(mu_0*eps_0*(om)**2 - 1j*mu_0*sigma[0]*om)
+        Zall[0] = old_div((mu_0*om),np.sqrt(mu_0*eps_0*(om)**2 - 1j*mu_0*sigma[0]*om))
 
         for nr,hi in enumerate(h):
             # Calculate the wave number
             # print nr,sigma[nr]
             k = np.sqrt(mu_0*eps_0*om**2 - 1j*mu_0*sigma[nr]*om)
-            Z = (mu_0*om)/k
+            Z = old_div((mu_0*om),k)
 
-            Zall[nr+1] = Z *((Zall[nr] + Z*np.tanh(1j*k*hi))/(Z + Zall[nr]*np.tanh(1j*k*hi)))
+            Zall[nr+1] = Z *(old_div((Zall[nr] + Z*np.tanh(1j*k*hi)),(Z + Zall[nr]*np.tanh(1j*k*hi))))
 
         #pdb.set_trace()
         Z1d[nrFr] = Zall[-1]

SimPEG/MT/Utils/MT1Dsolutions.py

@@ -1,5 +1,11 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from future import standard_library
+standard_library.install_aliases()
 import numpy as np, SimPEG as simpeg
-from MT1Danalytic import getEHfields
+from .MT1Danalytic import getEHfields
 from scipy.constants import mu_0
 
 def get1DEfields(m1d,sigma,freq,sourceAmp=1.0):
@@ -9,7 +15,7 @@ def get1DEfields(m1d,sigma,freq,sourceAmp=1.0):
     G = m1d.nodalGrad
     # Mass matrices
     # Magnetic permeability
-    Mmu = simpeg.Utils.sdiag(m1d.vol*(1.0/mu_0))
+    Mmu = simpeg.Utils.sdiag(m1d.vol*(old_div(1.0,mu_0)))
     # Conductivity
     Msig = m1d.getFaceInnerProduct(sigma)
     # Set up the solution matrix
@@ -23,7 +29,7 @@ def get1DEfields(m1d,sigma,freq,sourceAmp=1.0):
     Ed, Eu, Hd, Hu = getEHfields(m1d,sigma,freq,m1d.vectorNx)
     Etot = (Ed + Eu)
     if sourceAmp is not None:
-        Etot = ((Etot/Etot[-1])*sourceAmp) # Scale the fields to be equal to sourceAmp at the top
+        Etot = ((old_div(Etot,Etot[-1]))*sourceAmp) # Scale the fields to be equal to sourceAmp at the top
     ## Note: The analytic solution is derived with e^iwt
     bc = np.r_[Etot[0],Etot[-1]]
     # The right hand side

SimPEG/MT/Utils/__init__.py

@@ -1,4 +1,10 @@
-from MT1Dsolutions import *  # Add the names of the functions
-from MT1Danalytic import *
-from dataUtils import *
-from ediFilesUtils import *
+from __future__ import absolute_import
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import division
+from future import standard_library
+standard_library.install_aliases()
+from .MT1Dsolutions import *  # Add the names of the functions
+from .MT1Danalytic import *
+from .dataUtils import *
+from .ediFilesUtils import *

SimPEG/MT/Utils/dataUtils.py

@@ -1,3 +1,9 @@
+from __future__ import print_function
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+from future import standard_library
+standard_library.install_aliases()
 # Utils used for the data,
 import numpy as np, matplotlib.pyplot as plt, sys
 import SimPEG as simpeg
@@ -19,7 +25,7 @@ def getAppRes(MTdata):
         zList.append(zc)
     return [appResPhs(zList[i][0],np.sum(zList[i][1:3])) for i in np.arange(len(zList))]
 
-def rotateData(MTdata,rotAngle):
+def rotateData(MTdata, rotAngle):
     '''
     Function that rotates clockwist by rotAngle (- negative for a counter-clockwise rotation)
     '''
@@ -44,19 +50,19 @@ def rotateData(MTdata,rotAngle):
     return MT.Data.fromRecArray(outRec)
 
 
-def appResPhs(freq,z):
-    app_res = ((1./(8e-7*np.pi**2))/freq)*np.abs(z)**2
-    app_phs = np.arctan2(z.imag,z.real)*(180/np.pi)
+def appResPhs(freq, z):
+    app_res = (old_div((old_div(1.,(8e-7*np.pi**2))),freq))*np.abs(z)**2
+    app_phs = np.arctan2(z.imag,z.real)*(old_div(180,np.pi))
     return app_res, app_phs
 
-def skindepth(rho,freq):
+def skindepth(rho, freq):
     ''' Function to calculate the skindepth of EM waves'''
-    return np.sqrt( (rho*((1/(freq * mu_0 * np.pi )))))
+    return np.sqrt( (rho*((old_div(1,(freq * mu_0 * np.pi ))))))
 
-def rec2ndarr(x,dt=float):
+def rec2ndarr(x, dt=float):
     return x.view((dt, len(x.dtype.names)))
 
-def makeAnalyticSolution(mesh,model,elev,freqs):
+def makeAnalyticSolution(mesh, model, elev, freqs):
     from SimPEG import MT
     data1D = []
     for freq in freqs:
@@ -64,13 +70,13 @@ def makeAnalyticSolution(mesh,model,elev,freqs):
         anaE = anaEd+anaEu
         anaH = anaHd+anaHu
 
-        anaZ = anaE/anaH
+        anaZ = old_div(anaE,anaH)
         # Add to the list
         data1D.append((freq,0,0,elev,anaZ[0]))
     dataRec = np.array(data1D,dtype=[('freq',float),('x',float),('y',float),('z',float),('zyx',complex)])
     return dataRec
 
-def plotMT1DModelData(problem,models,symList=None):
+def plotMT1DModelData(problem, models, symList=None):
     from SimPEG import MT
     # Setup the figure
     fontSize = 15
@@ -97,7 +103,7 @@ def plotMT1DModelData(problem,models,symList=None):
 
     # if not symList:
     #   symList = ['x']*len(models)
-    import plotDataTypes as pDt
+    from . import plotDataTypes as pDt
     # Loop through the models.
     modelList = [problem.survey.mtrue]
     modelList.extend(models)
@@ -110,14 +116,14 @@ def plotMT1DModelData(problem,models,symList=None):
         else:
             data1D = problem.dataPair(problem.survey,problem.survey.dpred(model)).toRecArray('Complex')
         # Plot the data and the model
-        colRat = nr/((len(modelList)-1.999)*1.)
+        colRat = old_div(nr,((len(modelList)-1.999)*1.))
         if colRat > 1.:
             col = 'k'
         else:
             col = plt.cm.seismic(1-colRat)
         # The model - make the pts to plot
         meshPts = np.concatenate((problem.mesh.gridN[0:1],np.kron(problem.mesh.gridN[1::],np.ones(2))[:-1]))
-        modelPts = np.kron(1./(problem.mapping.sigmaMap*model),np.ones(2,))
+        modelPts = np.kron(old_div(1.,(problem.mapping.sigmaMap*model)),np.ones(2,))
         axM.semilogx(modelPts,meshPts,color=col)
 
         ## Data
@@ -144,7 +150,7 @@ def plotMT1DModelData(problem,models,symList=None):
 
     # Fix labels and ticks
 
-    yMtick = [l/1000 for l in axM.get_yticks().tolist()]
+    yMtick = [old_div(l,1000) for l in axM.get_yticks().tolist()]
     axM.set_yticklabels(yMtick)
     [ l.set_rotation(90) for l in axM.get_yticklabels()]
     [ l.set_rotation(90) for l in axR.get_yticklabels()]
@@ -157,7 +163,7 @@ def plotMT1DModelData(problem,models,symList=None):
 
 def printTime():
     import time
-    print time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.localtime())
+    print(time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.localtime()))
 
 def convert3Dto1Dobject(MTdata,rxType3D='zyx'):
     from SimPEG import MT

SimPEG/MT/Utils/ediFilesUtils.py

@@ -1,3 +1,12 @@
+from __future__ import print_function
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import absolute_import
+from builtins import open
+from builtins import int
+from future import standard_library
+standard_library.install_aliases()
+from builtins import object
 # Functions to import and export MT EDI files.
 from SimPEG import mkvc
 from scipy.constants import mu_0
@@ -7,27 +16,26 @@ from SimPEG.MT.Utils.dataUtils import rec2ndarr
 # Import modules
 import numpy as np
 import os, sys, re
-try:
-    import osr
-except ImportError as e:
-    print 'Could not import osr, missing the gdal package'
-    pass
 
-class EDIimporter:
+
+class EDIimporter(object):
     """
     A class to import EDIfiles.
 
     """
+
+
+    # Define data converters
     _impUnitEDI2SI = 4*np.pi*1e-4 # Convert Z[mV/km/nT] (as in EDI)to Z[V/A] SI unit
-    _impUnitSI2EDI = 1./_impUnitEDI2SI # ConvertZ[V/A] SI unit to Z[mV/km/nT] (as in EDI)
+    _impUnitSI2EDI = old_div(1.,_impUnitEDI2SI) # ConvertZ[V/A] SI unit to Z[mV/km/nT] (as in EDI)
 
     # Properties
     filesList = None
     comps = None
 
     # Hidden properties
-    _outEPSG = None
-    _2out = None
+    _outEPSG = None # Project info
+    _2out = None    # The projection operator
 
 
     def __init__(self, EDIfilesList, compList=None, outEPSG=None):
@@ -113,6 +121,12 @@ class EDIimporter:
     # nOutData=length(obj.data);
     # obj.data(nOutData+1:nOutData+length(TEMP.data),:) = TEMP.data;
     def _transfromPoints(self,longD,latD):
+        # Import the coordinate projections
+        try:
+            import osr
+        except ImportError as e:
+            print('Could not import osr, missing the gdal package\nCan not project coordinates')
+            raise e
         # Coordinates convertor
         if self._2out is None:
             src = osr.SpatialReference()
@@ -121,7 +135,7 @@ class EDIimporter:
             if self._outEPSG is None:
                 # Find the UTM EPSG number
                 Nnr =  700 if latD < 0.0 else 600
-                utmZ = int(1+(longD+180.0)/6.0)
+                utmZ = int(1+old_div((longD+180.0),6.0))
                 self._outEPSG = 32000 + Nnr + utmZ
             out.ImportFromEPSG(self._outEPSG)
             self._2out = osr.CoordinateTransformation(src,out)

SimPEG/MT/Utils/plotDataTypes.py

@@ -1,3 +1,9 @@
+from __future__ import division
+from __future__ import unicode_literals
+from __future__ import print_function
+from __future__ import absolute_import
+from future import standard_library
+standard_library.install_aliases()
 from matplotlib import pyplot as plt, colors, numpy as np
 
 
@@ -35,7 +41,7 @@ def plotIsoFreqNSimpedance(ax,freq,array,flag,par='abs',colorbar=True,colorNorm=
 		cmap = plt.get_cmap('RdYlBu')
 		level = np.concatenate((-np.logspace(0,-10,31),np.logspace(-10,0,31)))
 		clevel = np.concatenate((-np.logspace(0,-8,5),np.logspace(-8,0,5)))
-		plotNorm = colors.SymLogNorm(1e-10,linscale=2)		
+		plotNorm = colors.SymLogNorm(1e-10,linscale=2)
 		if cLevel:
 			level = np.concatenate((-np.logspace(0,-10,31),np.logspace(-10,0,31)))
 			clevel = np.concatenate((-np.logspace(0,-8,5),np.logspace(-8,0,5)))
@@ -65,45 +71,45 @@ def plotIsoFreqNSDiff(ax,freq,arrayList,flag,par='abs',colorbar=True,cLevel=True
 	x, y = arrayList[0]['x'][indUniFreq0],arrayList[0]['y'][indUniFreq0]
 	if par == 'abs':
 		if useLog:
-			zPlot = (np.log10(np.abs(arrayList[0][flag][indUniFreq0])) - np.log10(np.abs(arrayList[1][flag][indUniFreq1])))/np.log10(np.abs(arrayList[1][flag][indUniFreq1]))
+			zPlot = old_div((np.log10(np.abs(arrayList[0][flag][indUniFreq0])) - np.log10(np.abs(arrayList[1][flag][indUniFreq1]))),np.log10(np.abs(arrayList[1][flag][indUniFreq1])))
 		else:
-			zPlot = (np.abs(arrayList[0][flag][indUniFreq0]) - np.abs(arrayList[1][flag][indUniFreq1]))/np.abs(arrayList[1][flag][indUniFreq1])
+			zPlot = old_div((np.abs(arrayList[0][flag][indUniFreq0]) - np.abs(arrayList[1][flag][indUniFreq1])),np.abs(arrayList[1][flag][indUniFreq1]))
 		if mask:
 			maskInd = np.logical_or(np.abs(arrayList[0][flag][indUniFreq0])< 1e-3,np.abs(arrayList[1][flag][indUniFreq1]) < 1e-3)
 			zPlot = np.ma.array(zPlot)
 			zPlot[maskInd] = mask
 		if cLevel:
-			level = np.arange(-200,201,10) 
+			level = np.arange(-200,201,10)
 			clevel = np.arange(-200,201,25)
 		else:
 			level = np.linspace(zPlot.min(),zPlot.max(),100)
 			clevel = np.linspace(zPlot.min(),zPlot.max(),10)
 	elif par == 'real':
 		if useLog:
-			zPlot = (np.log10(np.real(arrayList[0][flag][indUniFreq0])) -np.log10(np.real(arrayList[1][flag][indUniFreq1])))/np.log10(np.abs((np.real(arrayList[1][flag][indUniFreq1]))))
+			zPlot = old_div((np.log10(np.real(arrayList[0][flag][indUniFreq0])) -np.log10(np.real(arrayList[1][flag][indUniFreq1]))),np.log10(np.abs((np.real(arrayList[1][flag][indUniFreq1])))))
 		else:
-			zPlot = (np.real(arrayList[0][flag][indUniFreq0]) -np.real(arrayList[1][flag][indUniFreq1]))/np.abs((np.real(arrayList[1][flag][indUniFreq1])))
+			zPlot = old_div((np.real(arrayList[0][flag][indUniFreq0]) -np.real(arrayList[1][flag][indUniFreq1])),np.abs((np.real(arrayList[1][flag][indUniFreq1]))))
 		if mask:
 			maskInd = np.logical_or(np.abs(np.real(arrayList[0][flag][indUniFreq0])) < 1e-3,np.abs(np.real(arrayList[1][flag][indUniFreq1])) < 1e-3)
 			zPlot = np.ma.array(zPlot)
 			zPlot[maskInd] = mask
 		if cLevel:
-			level = np.arange(-200,201,10) 
+			level = np.arange(-200,201,10)
 			clevel = np.arange(-200,201,25)
 		else:
 			level = np.linspace(zPlot.min(),zPlot.max(),100)
 			clevel = np.linspace(zPlot.min(),zPlot.max(),10)
 	elif par == 'imag':
 		if useLog:
-			zPlot = (np.log10(np.imag(arrayList[0][flag][indUniFreq0])) -np.log10(np.imag(arrayList[1][flag][indUniFreq1])))/np.log10(np.abs((np.imag(arrayList[1][flag][indUniFreq1]))))
+			zPlot = old_div((np.log10(np.imag(arrayList[0][flag][indUniFreq0])) -np.log10(np.imag(arrayList[1][flag][indUniFreq1]))),np.log10(np.abs((np.imag(arrayList[1][flag][indUniFreq1])))))
 		else:
-			zPlot = (np.imag(arrayList[0][flag][indUniFreq0]) -np.imag(arrayList[1][flag][indUniFreq1]))/np.abs((np.imag(arrayList[1][flag][indUniFreq1])))
+			zPlot = old_div((np.imag(arrayList[0][flag][indUniFreq0]) -np.imag(arrayList[1][flag][indUniFreq1])),np.abs((np.imag(arrayList[1][flag][indUniFreq1]))))
 		if mask:
 			maskInd = np.logical_or(np.abs(np.imag(arrayList[0][flag][indUniFreq0])) < 1e-3,np.abs(np.imag(arrayList[1][flag][indUniFreq1])) < 1e-3)
 			zPlot = np.ma.array(zPlot)
 			zPlot[maskInd] = mask
 		if cLevel:
-			level = np.arange(-200,201,10) 
+			level = np.arange(-200,201,10)
 			clevel = np.arange(-200,201,25)
 		else:
 			level = np.linspace(zPlot.min(),zPlot.max(),100)
@@ -174,13 +180,13 @@ def plotIsoFreqNStipper(ax,freq,array,flag,par='abs',colorbar=True,colorNorm='Sy
 		plt.colorbar(cs,cax=ax.cax,ticks=clevel,format='%1.2e')
 	ax.set_title(flag+' '+par,fontsize=8)
 
-def plotIsoStaImpedance(ax,loc,array,flag,par='abs',pSym='s',pColor=None):	
-	
-	appResFact = 1/(8*np.pi**2*10**(-7))
+def plotIsoStaImpedance(ax,loc,array,flag,par='abs',pSym='s',pColor=None):
+
+	appResFact = old_div(1,(8*np.pi**2*10**(-7)))
 	treshold = 1.0 # 1 meter
 	indUniSta = np.sqrt(np.sum((rec2nd(array[['x','y']])-loc)**2,axis=1)) < treshold
 	freq = array['freq'][indUniSta]
-	
+
 	if par == 'abs':
 		zPlot = np.abs(array[flag][indUniSta])
 	elif par == 'real':
@@ -188,9 +194,9 @@ def plotIsoStaImpedance(ax,loc,array,flag,par='abs',pSym='s',pColor=None):
 	elif par == 'imag':
 		zPlot = np.imag(array[flag][indUniSta])
 	elif par == 'res':
-		zPlot = (appResFact/freq)*np.abs(array[flag][indUniSta])**2
+		zPlot = (old_div(appResFact,freq))*np.abs(array[flag][indUniSta])**2
 	elif par == 'phs':
-		zPlot = np.arctan2(array[flag][indUniSta].imag,array[flag][indUniSta].real)*(180/np.pi)
+		zPlot = np.arctan2(array[flag][indUniSta].imag,array[flag][indUniSta].real)*(old_div(180,np.pi))
 
 	if not pColor:
 		if 'xx' in flag:
@@ -198,7 +204,7 @@ def plotIsoStaImpedance(ax,loc,array,flag,par='abs',pSym='s',pColor=None):
 			pColor = 'g'
 		elif 'xy' in flag:
 			lab = 'XY'
-			pColor = 'r'	
+			pColor = 'r'
 		elif 'yx' in flag:
 			lab = 'YX'
 			pColor = 'b'
@@ -207,14 +213,14 @@ def plotIsoStaImpedance(ax,loc,array,flag,par='abs',pSym='s',pColor=None):
 			pColor = 'y'
 
 	ax.plot(freq,zPlot,color=pColor,marker=pSym,label=flag)
-	
+
 
 def plotPsudoSectNSimpedance(ax,sectDict,array,flag,par='abs',colorbar=True,colorNorm='None',cLevel=None,contour=True):
 
-	indSect = np.where(sectDict.values()[0]==array[sectDict.keys()[0]])
+	indSect = np.where(list(sectDict.values())[0]==array[list(sectDict.keys())[0]])
 
 	# Define the plot axes
-	if 'x' in sectDict.keys()[0]:
+	if 'x' in list(sectDict.keys())[0]:
 		x = array['y'][indSect]
 	else:
 		x = array['x'][indSect]
@@ -229,9 +235,9 @@ def plotPsudoSectNSimpedance(ax,sectDict,array,flag,par='abs',colorbar=True,colo
 		else:
 			level = np.linspace(zPlot.min(),zPlot.max(),100,endpoint=True)
 			clevel = np.linspace(zPlot.min(),zPlot.max(),10,endpoint=True)
-		
-	elif par == 'ares':	
-		zPlot = np.abs(array[flag][indSect])**2/(8*np.pi**2*10**(-7)*array['freq'][indSect])
+
+	elif par == 'ares':
+		zPlot = old_div(np.abs(array[flag][indSect])**2,(8*np.pi**2*10**(-7)*array['freq'][indSect]))
 		cmap = plt.get_cmap('RdYlBu')#seismic)
 		if cLevel:
 			zMax = np.log10(cLevel[1])
@@ -244,7 +250,7 @@ def plotPsudoSectNSimpedance(ax,sectDict,array,flag,par='abs',colorbar=True,colo
 		plotNorm = colors.LogNorm()
 
 	elif par == 'aphs':
-		zPlot = np.arctan2(array[flag][indSect].imag,array[flag][indSect].real)*(180/np.pi)
+		zPlot = np.arctan2(array[flag][indSect].imag,array[flag][indSect].real)*(old_div(180,np.pi))
 		cmap = plt.get_cmap('RdYlBu')#seismic)
 		if cLevel:
 			zMax = cLevel[1]
@@ -271,7 +277,7 @@ def plotPsudoSectNSimpedance(ax,sectDict,array,flag,par='abs',colorbar=True,colo
 	elif par == 'imag':
 		zPlot = np.imag(array[flag][indSect])
 		cmap = plt.get_cmap('Spectral') #('RdYlBu')
-		
+
 		if cLevel:
 			zMax = np.log10(cLevel[1])
 			zMin = np.log10(cLevel[0])
@@ -281,7 +287,7 @@ def plotPsudoSectNSimpedance(ax,sectDict,array,flag,par='abs',colorbar=True,colo
 		level = np.concatenate((-np.logspace(zMax,zMin-.125,(zMax-zMin)*8+1,endpoint=True),np.logspace(zMin-.125,zMax,(zMax-zMin)*8+1,endpoint=True)))
 		clevel = np.concatenate((-np.logspace(zMax,zMin,(zMax-zMin)*1+1,endpoint=True),np.logspace(zMin,zMax,(zMax-zMin)*1+1,endpoint=True)))
 		plotNorm = colors.SymLogNorm(np.abs(level).min(),linscale=0.1)
-	
+
 	if colorNorm=='SymLog':
 		plotNorm = colors.SymLogNorm(np.abs(level).min(),linscale=0.1)
 	elif colorNorm=='Lin':
@@ -307,14 +313,14 @@ def plotPsudoSectNSDiff(ax,sectDict,arrayList,flag,par='abs',colorbar=True,color
 	def sortInArr(arr):
 		return np.sort(arr,order=['freq','x','y','z'])
 	# Find the index for the slice
-	indSect0 = np.where(sectDict.values()[0]==arrayList[0][sectDict.keys()[0]])
-	indSect1 = np.where(sectDict.values()[0]==arrayList[1][sectDict.keys()[0]])
+	indSect0 = np.where(list(sectDict.values())[0]==arrayList[0][list(sectDict.keys())[0]])
+	indSect1 = np.where(list(sectDict.values())[0]==arrayList[1][list(sectDict.keys())[0]])
 	# Extract and sort the mats
 	arr0 = sortInArr(arrayList[0][indSect0])
 	arr1 = sortInArr(arrayList[1][indSect1])
 
 	# Define the plot axes
-	if 'x' in sectDict.keys()[0]:
+	if 'x' in list(sectDict.keys())[0]:
 		x0 = arr0['y']
 		x1 = arr1['y']
 	else:
@@ -322,35 +328,35 @@ def plotPsudoSectNSDiff(ax,sectDict,arrayList,flag,par='abs',colorbar=True,color
 		x1 = arr1['x']
 	y0 = arr0['freq']
 	y1 = arr1['freq']
-	
+
 
 	if par == 'abs':
 		if useLog:
-			zPlot = (np.log10(np.abs(arr0[flag])) - np.log10(np.abs(arr1[flag])))/np.log10(np.abs(arr1[flag]))
+			zPlot = old_div((np.log10(np.abs(arr0[flag])) - np.log10(np.abs(arr1[flag]))),np.log10(np.abs(arr1[flag])))
 		else:
-			zPlot = (np.abs(arr0[flag]) - np.abs(arr1[flag]))/np.abs(arr1[flag])
+			zPlot = old_div((np.abs(arr0[flag]) - np.abs(arr1[flag])),np.abs(arr1[flag]))
 		if mask:
 			maskInd = np.logical_or(np.abs(arr0[flag])< 1e-3,np.abs(arr1[flag]) < 1e-3)
 			zPlot = np.ma.array(zPlot)
 			zPlot[maskInd] = mask
 		cmap = plt.get_cmap('RdYlBu')#seismic)
 	elif par == 'ares':
-		arF = 1/(8*np.pi**2*10**(-7))		
+		arF = old_div(1,(8*np.pi**2*10**(-7)))
 		if useLog:
-			zPlot = (np.log10((arF/arr0['freq'])*np.abs(arr0[flag])**2) - np.log10((arF/arr1['freq'])*np.abs(arr1[flag])**2))/np.log10((arF/arr1['freq'])*np.abs(arr1[flag])**2)
+			zPlot = old_div((np.log10((old_div(arF,arr0['freq']))*np.abs(arr0[flag])**2) - np.log10((old_div(arF,arr1['freq']))*np.abs(arr1[flag])**2)),np.log10((old_div(arF,arr1['freq']))*np.abs(arr1[flag])**2))
 		else:
-			zPlot = ((arF/arr0['freq'])*np.abs(arr0[flag])**2 - (arF/arr1['freq'])*np.abs(arr1[flag])**2)/((arF/arr1['freq'])*np.abs(arr1[flag])**2)
+			zPlot = old_div(((old_div(arF,arr0['freq']))*np.abs(arr0[flag])**2 - (old_div(arF,arr1['freq']))*np.abs(arr1[flag])**2),((old_div(arF,arr1['freq']))*np.abs(arr1[flag])**2))
 		if mask:
 			maskInd = np.logical_or(np.abs(arr0[flag])< 1e-3,np.abs(arr1[flag]) < 1e-3)
 			zPlot = np.ma.array(zPlot)
 			zPlot[maskInd] = mask
 		cmap = plt.get_cmap('Spectral')#seismic)
-	
+
 	elif par == 'aphs':
 		if useLog:
-			zPlot = (np.log10(np.arctan2(arr0[flag].imag,arr0[flag].real)*(180/np.pi)) - np.log10(np.arctan2(arr1[flag].imag,arr1[flag].real)*(180/np.pi)) )/np.log10(np.arctan2(arr1[flag].imag,arr1[flag].real)*(180/np.pi))
+			zPlot = old_div((np.log10(np.arctan2(arr0[flag].imag,arr0[flag].real)*(old_div(180,np.pi))) - np.log10(np.arctan2(arr1[flag].imag,arr1[flag].real)*(old_div(180,np.pi))) ),np.log10(np.arctan2(arr1[flag].imag,arr1[flag].real)*(old_div(180,np.pi))))
 		else:
-			zPlot = ( np.arctan2(arr0[flag].imag,arr0[flag].real)*(180/np.pi) - np.arctan2(arr1[flag].imag,arr1[flag].real)*(180/np.pi) )/(np.arctan2(arr1[flag].imag,arr1[flag].real)*(180/np.pi))
+			zPlot = old_div(( np.arctan2(arr0[flag].imag,arr0[flag].real)*(old_div(180,np.pi)) - np.arctan2(arr1[flag].imag,arr1[flag].real)*(old_div(180,np.pi)) ),(np.arctan2(arr1[flag].imag,arr1[flag].real)*(old_div(180,np.pi))))
 		if mask:
 			maskInd = np.logical_or(np.abs(arr0[flag])< 1e-3,np.abs(arr1[flag]) < 1e-3)
 			zPlot = np.ma.array(zPlot)
@@ -358,26 +364,26 @@ def plotPsudoSectNSDiff(ax,sectDict,arrayList,flag,par='abs',colorbar=True,color
 		cmap = plt.get_cmap('Spectral')#seismic)
 	elif par == 'real':
 		if useLog:
-			zPlot = (np.log10(arr0[flag].real) - np.log10(arr1[flag].real))/np.log10(arr1[flag].real)
+			zPlot = old_div((np.log10(arr0[flag].real) - np.log10(arr1[flag].real)),np.log10(arr1[flag].real))
 		else:
-			zPlot = (arr0[flag].real - arr1[flag].real)/arr1[flag].real
+			zPlot = old_div((arr0[flag].real - arr1[flag].real),arr1[flag].real)
 		if mask:
 			maskInd = np.logical_or(arr0[flag].real< 1e-3,arr1[flag].real < 1e-3)
 			zPlot = np.ma.array(zPlot)
 			zPlot[maskInd] = mask
 		cmap = plt.get_cmap('Spectral') #('Spectral')
-		
+
 	elif par == 'imag':
 		if useLog:
-			zPlot = (np.log10(arr0[flag].imag) - np.log10(arr1[flag].imag))/np.log10(arr1[flag].imag)
+			zPlot = old_div((np.log10(arr0[flag].imag) - np.log10(arr1[flag].imag)),np.log10(arr1[flag].imag))
 		else:
-			zPlot = (arr0[flag].imag - arr1[flag].imag)/arr1[flag].imag
+			zPlot = old_div((arr0[flag].imag - arr1[flag].imag),arr1[flag].imag)
 		if mask:
 			maskInd = np.logical_or(arr0[flag].imag< 1e-3,arr1[flag].imag < 1e-3)
 			zPlot = np.ma.array(zPlot)
 			zPlot[maskInd] = mask
 		cmap = plt.get_cmap('Spectral') #('RdYlBu')
-		
+
 	if cLevel:
 		zMax = np.log10(cLevel[1])
 		zMin = np.log10(cLevel[0])
@@ -385,18 +391,18 @@ def plotPsudoSectNSDiff(ax,sectDict,arrayList,flag,par='abs',colorbar=True,color
 		zMax = (np.ceil(np.log10(np.abs(zPlot).max())))
 		zMin = (np.floor(np.log10(np.abs(zPlot).min())))
 
-	
+
 	if colorNorm=='SymLog':
 		level = np.concatenate((-np.logspace(zMax,zMin-.125,(zMax-zMin)*8+1,endpoint=True),np.logspace(zMin-.125,zMax,(zMax-zMin)*8+1,endpoint=True)))
 		clevel = np.concatenate((-np.logspace(zMax,zMin,(zMax-zMin)*1+1,endpoint=True),np.logspace(zMin,zMax,(zMax-zMin)*1+1,endpoint=True)))
 		plotNorm = colors.SymLogNorm(np.abs(level).min(),linscale=0.1)
 	elif colorNorm=='Lin':
 		if cLevel:
-			level = np.arange(cLevel[0],cLevel[1]+.1,(cLevel[1] - cLevel[0])/50.) 
-			clevel = np.arange(cLevel[0],cLevel[1]+.1,(cLevel[1] - cLevel[0])/10.)
+			level = np.arange(cLevel[0],cLevel[1]+.1,old_div((cLevel[1] - cLevel[0]),50.))
+			clevel = np.arange(cLevel[0],cLevel[1]+.1,old_div((cLevel[1] - cLevel[0]),10.))
 		else:
-			level = np.arange(zPlot.min(),zPlot.max(),(zPlot.max() - zPlot.min())/50.)
-			clevel = np.arange(zPlot.min(),zPlot.max(),(zPlot.max() - zPlot.min())/10.)
+			level = np.arange(zPlot.min(),zPlot.max(),old_div((zPlot.max() - zPlot.min()),50.))
+			clevel = np.arange(zPlot.min(),zPlot.max(),old_div((zPlot.max() - zPlot.min()),10.))
 		plotNorm = colors.Normalize()
 	elif colorNorm=='Log':
 		level = np.logspace(zMin-.125,zMax,(zMax-zMin)*8+1,endpoint=True)