set kwargs through **kwargs

.bumpversion.cfg

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

.gitignore

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

.travis.yml

@@ -24,25 +24,18 @@ 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:
-# 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
+  - 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
   - conda update --yes conda
 
+# Install packages
 install:
-  - conda install --yes pip python=$TRAVIS_PYTHON_VERSION numpy scipy matplotlib cython ipython nose vtk sphinx
+  - conda install --yes pip python=$TRAVIS_PYTHON_VERSION numpy scipy matplotlib cython ipython nose vtk
   - pip install nose-cov python-coveralls
 
   - git clone https://github.com/rowanc1/pymatsolver.git
@@ -53,26 +46,11 @@ install:
 
 # Run test
 script:
-  # test docs
   - nosetests $TEST_DIR --with-cov --cov SimPEG --cov-config .coveragerc -v -s
 
 # Calculate coverage
 after_success:
-  - 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
-
+  - coveralls --config_file .coveragerc
 
 notifications:
   email:

README.rst

@@ -1,4 +1,4 @@
-.. image:: https://raw.github.com/simpeg/simpeg/master/docs/images/simpeg-logo.png
+.. image:: https://raw.github.com/simpeg/simpeg/master/docs/simpeg-logo.png
     :alt: SimPEG Logo
 
 ======
@@ -15,7 +15,7 @@ SimPEG
 
 .. image:: https://img.shields.io/badge/license-MIT-blue.svg
     :target: https://github.com/simpeg/simpeg/blob/master/LICENSE
-    :alt: MIT license
+    :alt: BSD 3 clause license.
 
 .. image:: https://api.travis-ci.org/simpeg/simpeg.svg?branch=master
     :target: https://travis-ci.org/simpeg/simpeg
@@ -25,15 +25,6 @@ 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
-    :alt: Coverage status
-
-
 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

@@ -162,8 +162,8 @@ class ProblemDC_CC(Problem.BaseProblem):
         """
             Makes the matrix A(m) for the DC resistivity problem.
 
-            :param numpy.ndarray m: model
-            :rtype: scipy.sparse.csc_matrix
+            :param numpy.array m: model
+            :rtype: scipy.csc_matrix
             :return: A(m)
 
             .. math::

SimPEG/DCIP/BaseIP.py

@@ -71,7 +71,7 @@ class ProblemIP(Problem.BaseProblem):
             Makes the matrix A(m) for the DC resistivity problem.
 
             :param numpy.array m: model
-            :rtype: scipy.sparse.csc_matrix
+            :rtype: scipy.csc_matrix
             :return: A(m)
 
             .. math::

SimPEG/DCIP/DCIPUtils.py

@@ -1,16 +1,12 @@
-from SimPEG import np, Utils
+from SimPEG import np
 import BaseDC as DC
 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
@@ -32,9 +28,6 @@ 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')
@@ -125,27 +118,34 @@ 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
 
-    :param string fileName: path to the UBC GIF 2D model file
-    :rtype: TensorMesh
-    :return: SimPEG TensorMesh 2D object
+        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
 
     """
     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 +153,10 @@ 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])
@@ -169,25 +169,32 @@ def readUBC_DC2DModel(fileName):
 
     return model
 
-
-def plot_pseudoSection(DCsurvey, axs, surveyType='dipole-dipole', unitType='volt', clim=None, cblabel=True, axlabel = True, colorbar = True, contour = None):
+def plot_pseudoSection(DCsurvey, axs, stype):
     """
-    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...
 
-    :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
+        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
 
     """
     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 = []
@@ -214,117 +221,69 @@ def plot_pseudoSection(DCsurvey, axs, surveyType='dipole-dipole', unitType='volt
         Cmid = (Tx[0][0] + Tx[1][0])/2
         Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
 
-        # Change output for unitType
-        if unitType == 'volt':
+        # Compute pant leg of apparent rho
+        if stype == 'pdp':
+            leg =  data * 2*np.pi  * MA * ( MA + MN ) / MN
 
-            rho = np.hstack([rho,data])
+            leg = np.log10(abs(1/leg))
 
-        else:
+        elif stype == 'dpdp':
+            leg = data * 2*np.pi / ( 1/MA - 1/MB - 1/NB + 1/NA )
 
-            # 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
-
-
-            if unitType == 'appConductivity':
-
-                leg = np.log10(abs(1./leg))
-                rho = np.hstack([rho,leg])
-
-            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 ])
+        midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + z0 ])
+        rho = np.hstack([rho,leg])
+
+
+    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')
 
-    # Scale the color scheme
-    if clim == None:
-        vmin, vmax = rho.min(), rho.max()
-    else:
-        vmin, vmax = clim[0], clim[1]
 
-    # Plot data
-    grid_rho = np.ma.masked_where(np.isnan(grid_rho), grid_rho)
+    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")
 
+    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)
 
-    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_xticklabels([])
 
+    ax.set_ylabel('Z')
+    ax.yaxis.tick_right()
+    ax.yaxis.set_label_position('right')
     plt.gca().set_aspect('equal', adjustable='box')
 
 
+    return ax
 
-    return ph
-
-def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
+def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
     """
-    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...
 
-    :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
+        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
 
-    :rtype: DC.Survey, Src, Rx
-    :returns: DC survey, Source
+        Output:
+        :param Tx, Rx -> List objects for each tx location
+            Lines: P1x, P1y, P1z, P2x, P2y, P2z
 
-    !! Require clean up to deal with DCsurvey
+        Created on Wed December 9th, 2015
+
+        @author: dominiquef
+        !! Require clean up to deal with DCsurvey
     """
 
     from SimPEG import np
@@ -340,17 +299,17 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
     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 / AM_sep )
+    nstn = np.floor( dl_len / a )
 
     # Compute discrete pole location along line
-    stn_x = endl[0,0] + np.array(range(int(nstn)))*dl_x*AM_sep
-    stn_y = endl[0,1] + np.array(range(int(nstn)))*dl_y*AM_sep
+    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
 
     # 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+AM_sep*dl_x, stn_y+AM_sep*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
+    N = np.c_[stn_x+a*dl_x, stn_y+a*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]
@@ -360,14 +319,14 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
     SrcList = []
 
 
-    if surveyType != 'gradient':
+    if stype != 'gradient':
 
         for ii in range(0, int(nstn)-1):
 
 
-            if surveyType == 'dipole-dipole':
+            if stype == 'dpdp':
                 tx = np.c_[M[ii,:],N[ii,:]]
-            elif surveyType == 'pole-dipole':
+            elif stype == 'pdp':
                 tx = np.c_[M[ii,:],M[ii,:]]
 
             # Rx.append(np.c_[M[ii+1:indx,:],N[ii+1:indx,:]])
@@ -376,33 +335,43 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
             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 - MN_sep) / AM_sep ) , nrx])
+            nstn = np.min([np.floor( (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*MN_sep + np.array(range(int(nstn)))*dl_x*AM_sep
-            stn_y = N[ii,1] + dl_y*MN_sep + np.array(range(int(nstn)))*dl_y*AM_sep
+            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
 
             # 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+AM_sep*dl_x, stn_y+AM_sep*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
+            P2 = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
 
             Rx.append(np.c_[P1,P2])
             rxClass = DC.RxDipole(P1, P2)
             Tx.append(tx)
-            if surveyType == 'dipole-dipole':
+            if stype == 'dpdp':
                 srcClass = DC.SrcDipole([rxClass], M[ii,:],N[ii,:])
-            elif surveyType == 'pole-dipole':
+            elif stype == 'pdp':
                 srcClass = DC.SrcDipole([rxClass], M[ii,:],M[ii,:])
             SrcList.append(srcClass)
 
-    elif surveyType == 'gradient':
+#==============================================================================
+#     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':
 
         # 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
@@ -410,23 +379,23 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
         Tx.append(np.c_[M[0,:],N[-1,:]])
 
         # Get the edge limit of survey area
-        min_x = endl[0,0] + dl_x * MN_sep
-        min_y = endl[0,1] + dl_y * MN_sep
+        min_x = endl[0,0] + dl_x * b
+        min_y = endl[0,1] + dl_y * b
 
-        max_x = endl[1,0] - dl_x * MN_sep
-        max_y = endl[1,1] - dl_y * MN_sep
+        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 / AM_sep )
+        nstn = np.floor( box_l / a )
 
         # Compute discrete pole location along line
-        stn_x = min_x + np.array(range(int(nstn)))*dl_x*AM_sep
-        stn_y = min_y + np.array(range(int(nstn)))*dl_y*AM_sep
+        stn_x = min_x + np.array(range(int(nstn)))*dl_x*a
+        stn_y = min_y + np.array(range(int(nstn)))*dl_y*a
 
         # Define number of cross lines
-        nlin = int(np.floor( box_w / AM_sep ))
+        nlin = int(np.floor( box_w / a ))
         lind = range(-nlin,nlin+1)
 
         ngrad = nstn * len(lind)
@@ -435,12 +404,12 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
         for ii in range( len(lind) ):
 
             # Move line in perpendicular direction by dipole spacing
-            lxx = stn_x - lind[ii]*AM_sep*dl_y
-            lyy = stn_y + lind[ii]*AM_sep*dl_x
+            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*mesh.vectorNz[-1]]
-            N = np.c_[ lxx+AM_sep*dl_x, lyy+AM_sep*dl_y, 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]]
 
             rx[(ii*nstn):((ii+1)*nstn),:] = np.c_[M,N]
 
@@ -449,37 +418,37 @@ def gen_DCIPsurvey(endl, mesh, surveyType, AM_sep, MN_sep, nrx):
         srcClass = DC.SrcDipole([rxClass], M[0,:], N[-1,:])
         SrcList.append(srcClass)
     else:
-        print """surveyType must be either 'pole-dipole', 'dipole-dipole' or 'gradient'. """
+        print """stype must be either 'pdp', 'dpdp' or 'gradient'. """
 
     survey = DC.SurveyDC(SrcList)
     return survey, Tx, Rx
 
-
-def writeUBC_DCobs(fileName, DCsurvey, dim, surveyType, iptype = 0):
+def writeUBC_DCobs(fileName, DCsurvey, dtype, stype):
     """
         Write UBC GIF DCIP 2D or 3D observation file
 
-        :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
-    """
+        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
+
+    """
     from SimPEG import mkvc
 
-    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'"
+    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'"
 
     fid = open(fileName,'w')
-    fid.write('! ' + surveyType + ' FORMAT\n')
-
-    if iptype!=0:
-        fid.write('IPTYPE=%i\n'%iptype)
-
-    else:
-        fid.write('! ' + stype + ' FORMAT\n')
+    fid.write('! ' + stype + ' FORMAT\n')
 
     count = 0
 
@@ -494,10 +463,10 @@ def writeUBC_DCobs(fileName, DCsurvey, dim, surveyType, iptype = 0):
         M = rx[0]
         N = rx[1]
 
-        # Adapt source-receiver location for dim and surveyType
-        if dim=='2D':
+        # Adapt source-receiver location for dtype and stype
+        if dtype=='2D':
 
-            if surveyType == 'SIMPLE':
+            if stype == 'SIMPLE':
 
                 #fid.writelines("%e " % ii for ii in mkvc(tx[0,:]))
                 A = np.repeat(tx[0,0],M.shape[0],axis=0)
@@ -510,60 +479,58 @@ def writeUBC_DCobs(fileName, DCsurvey, dim, surveyType, iptype = 0):
 
             else:
 
-                if surveyType == 'SURFACE':
+                if stype == 'SURFACE':
 
-                    fid.writelines("%f " % ii for ii in mkvc(tx[0,:]))
+                    fid.writelines("%e " % ii for ii in mkvc(tx[0,:]))
                     M = M[:,0]
                     N = N[:,0]
 
-                if surveyType == 'GENERAL':
-
-                    # Flip sign for z-elevation to depth
-                    tx[2::2,:] = -tx[2::2,:]
+                if stype == 'GENERAL':
 
                     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='%f',delimiter=' ',newline='\n')
+                np.savetxt(fid, np.c_[ M, N , DCsurvey.dobs[count:count+nD], DCsurvey.std[count:count+nD] ], fmt='%e',delimiter=' ',newline='\n')
 
-        if dim=='3D':
+        if dtype=='3D':
 
-            if surveyType == 'SURFACE':
+            if stype == 'SURFACE':
 
                 fid.writelines("%e " % ii for ii in mkvc(tx[0:2,:]))
                 M = M[:,0:2]
                 N = N[:,0:2]
 
-            if surveyType == 'GENERAL':
+            if stype == 'GENERAL':
 
-                fid.writelines("%e " % ii for ii in mkvc(tx[0:3,:]))
+                fid.writelines("%e " % ii for ii in mkvc(tx))
 
             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, flag='local'):
+def convertObs_DC3D_to_2D(DCsurvey,lineID):
     """
-        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]
+        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
 
-        The Z value is preserved, but Y coordinates zeroed.
+        Assumes flat topo for now...
 
-        :param DC.Survey survey3D: 3D simpeg DC survey
-        :rtype: DC.Survey
-        :return: survey2D
+        Input:
+        :param Tx, Rx
+
+        Output:
+        :figure Tx2d, Rx2d
+
+        Edited Feb 17th, 2016
+
+        @author: dominiquef
 
     """
     from SimPEG import np
@@ -603,39 +570,25 @@ def convertObs_DC3D_to_2D(DCsurvey, lineID, flag='local'):
             Rx = DCsurvey.srcList[indx[ii]].rxList[0].locs
             nrx = Rx[0].shape[0]
 
-            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 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)
-            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]
+                # Find all N electrodes along line
+                vec, r = r_unit(x0,Rx[1][kk,0:2])
+                N[kk] = stn_id(vecTx,vec,r)
 
             Rx = DC.RxDipole(np.c_[M,np.zeros(nrx),Rx[0][:,2]],np.c_[N,np.zeros(nrx),Rx[1][:,2]])
 
@@ -649,53 +602,50 @@ def convertObs_DC3D_to_2D(DCsurvey, lineID, flag='local'):
 
     return DCsurvey2D
 
-def readUBC_DC3Dobs(fileName, rtype = 'DC'):
+def readUBC_DC3Dobs(fileName):
     """
-        Read UBC GIF IP 3D observation file and generate survey
+        Read UBC GIF DCIP 3D observation file and generate arrays for tx-rx location
 
-        :param string fileName:, path to the UBC GIF 3D obs file
-        :rtype: Survey
-        :return: DCIPsurvey
+        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
 
     """
-    zflag = True # Flag for z value provided
 
     # Load file
-    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'"
+    obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
 
     # 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 or end of a transmitter block, read transmitter info
+        # First line is transmitter with number of receivers
         if count==0:
-            # Read the line
-            temp = (np.fromstring(obsfile[ii], dtype=float, sep=' ').T)
+
+            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[2:4],np.nan]
-
-                zflag = False # Pass on the flag to the receiver loc
+                tx = np.r_[temp[0:2],np.nan,temp[0:2],np.nan]
+                zflag = False
 
             else:
                 tx = temp[:-1]
@@ -703,16 +653,8 @@ def readUBC_DC3Dobs(fileName, rtype = 'DC'):
             rx = []
             continue
 
-        temp = np.fromstring(obsfile[ii], dtype=float,sep=' ') # Get the string
+        temp = np.fromstring(obsfile[ii], dtype=float,sep=' ')
 
-        # 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])
@@ -722,7 +664,7 @@ def readUBC_DC3Dobs(fileName, rtype = 'DC'):
                 wd.append(temp[-1])
 
         else:
-            rx.append(np.r_[temp[0:2],np.nan,temp[2:4],np.nan] )
+            rx.append(np.r_[temp[0:2],np.nan,temp[0:2],np.nan] )
             # Check if there is data with the location
             if len(temp)==6:
                 d.append(temp[-2])
@@ -730,7 +672,7 @@ def readUBC_DC3Dobs(fileName, rtype = 'DC'):
 
         count = count -1
 
-        # Reach the end of transmitter block, append the src, rx and continue
+        # Reach the end of transmitter block
         if count == 0:
             rx = np.asarray(rx)
             Rx = DC.RxDipole(rx[:,:3],rx[:,3:])
@@ -746,12 +688,19 @@ def readUBC_DC3Dobs(fileName, rtype = 'DC'):
 
 def readUBC_DC2Dobs(fileName):
     """
-        ------- NEEDS TO BE UPDATED ------
         Read UBC GIF 2D observation file and generate arrays for tx-rx location
 
-        :param string fileName: path to the UBC GIF 2D model file
-        :rtype: (DC.Src, DC.Rx, ??, ??)
-        :return: source_locs, rx_locs, ??, ??
+        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
+
     """
 
     from SimPEG import np
@@ -786,78 +735,16 @@ 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
 
-        :param string fileName: path to the UBC GIF mesh file
-        :rtype: Mesh.TensorMesh
-        :return: SimPEG TensorMesh 2D object
+        Input:
+        :param fileName, path to the UBC GIF mesh file
+
+        Output:
+        :param SimPEG TensorMesh 2D object
+        :return
 
         Created on Thu Nov 12 13:14:10 2015
 
@@ -923,9 +810,12 @@ def xy_2_lineID(DCsurvey):
         they were collected. May need to generalize for random
         point locations, but will be more expensive
 
-        :param numpy.array DCdict: Vectors of station location
-        :rtype: numpy.array
-        :return: LineID Vector of integers
+        Input:
+        :param DCdict Vectors of station location
+
+        Output:
+        :param LineID Vector of integers
+        :return
 
         Created on Thu Feb 11, 2015
 
@@ -1038,6 +928,7 @@ 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/Directives.py

@@ -144,18 +144,12 @@ class BetaSchedule(InversionDirective):
             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:
-            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
+            self._target = self.survey.nD*0.5
         return self._target
     @target.setter
     def target(self, val):
@@ -167,7 +161,7 @@ class TargetMisfit(InversionDirective):
 
 
 
-class SaveEveryIteration(InversionDirective):
+class _SaveEveryIteration(InversionDirective):
     @property
     def name(self):
         if getattr(self, '_name', None) is None:
@@ -188,7 +182,7 @@ class SaveEveryIteration(InversionDirective):
         self._fileName = value
 
 
-class SaveModelEveryIteration(SaveEveryIteration):
+class SaveModelEveryIteration(_SaveEveryIteration):
     """SaveModelEveryIteration"""
 
     def initialize(self):
@@ -198,7 +192,7 @@ class SaveModelEveryIteration(SaveEveryIteration):
         np.save('%03d-%s' % (self.opt.iter, self.fileName), self.opt.xc)
 
 
-class SaveOutputEveryIteration(SaveEveryIteration):
+class SaveOutputEveryIteration(_SaveEveryIteration):
     """SaveModelEveryIteration"""
 
     def initialize(self):
@@ -212,7 +206,7 @@ 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):
@@ -222,13 +216,13 @@ class SaveOutputDictEveryIteration(SaveEveryIteration):
         # 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.mrefInSmooth == True:
+        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:
+        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:
@@ -243,210 +237,49 @@ 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

@@ -1,118 +0,0 @@
-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/FDEMDipolarfields.py

@@ -1,302 +0,0 @@
-from __future__ import division
-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/__init__.py

@@ -1,5 +1,3 @@
 from TDEM import hzAnalyticDipoleT
 from FDEM import hzAnalyticDipoleF
 from FDEMcasing import *
-from DC import DCAnalyticHalf, DCAnalyticSphere
-from FDEMDipolarfields import *

SimPEG/EM/Base.py

@@ -1,7 +1,6 @@
 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)
@@ -20,10 +19,10 @@ class BaseEMProblem(Problem.BaseProblem):
         Problem.BaseProblem.__init__(self, mesh, **kwargs)
 
 
-    surveyPair = Survey.BaseSurvey #: The survey to pair with.
-    dataPair = Survey.Data #: The data to pair with.
+    surveyPair = Survey.BaseSurvey
+    dataPair = Survey.Data
 
-    PropMap = EMPropMap #: The property mapping
+    PropMap = EMPropMap
 
     Solver = SimpegSolver
     solverOpts = {}
@@ -62,15 +61,6 @@ 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):
         """
@@ -80,20 +70,6 @@ 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
-
-    @property
-    def Vol(self):
-        if getattr(self, '_Vol', None) is None:
-            self._Vol = Utils.sdiag(self.mesh.vol)
-        return self._Vol
 
     # ----- Magnetic Permeability ----- #
     @property
@@ -151,6 +127,7 @@ class BaseEMProblem(Problem.BaseProblem):
         """
         return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma)(u) * self.curModel.sigmaDeriv
 
+
     @property
     def MeSigmaI(self):
         """
@@ -169,7 +146,10 @@ class BaseEMProblem(Problem.BaseProblem):
 
         dMeSigmaI_dI = -self.MeSigmaI**2
         dMe_dsig = self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma)(u)
-        return dMeSigmaI_dI * ( dMe_dsig * self.curModel.sigmaDeriv )
+        dsig_dm = self.curModel.sigmaDeriv
+        return dMeSigmaI_dI * ( dMe_dsig * ( dsig_dm))
+        # return self.mesh.getEdgeInnerProductDeriv(self.curModel.sigma, invMat=True)(u)
+
 
     @property
     def MfRho(self):
@@ -185,7 +165,8 @@ class BaseEMProblem(Problem.BaseProblem):
         """
             Derivative of :code:`MfRho` with respect to the model.
         """
-        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u) * self.curModel.rhoDeriv
+        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u) * (-Utils.sdiag(self.curModel.rho**2) * self.curModel.sigmaDeriv)
+        # self.curModel.rhoDeriv
 
     @property
     def MfRhoI(self):
@@ -202,10 +183,7 @@ class BaseEMProblem(Problem.BaseProblem):
         """
             Derivative of :code:`MfRhoI` with respect to the model.
         """
-
-        dMfRhoI_dI = -self.MfRhoI**2
-        dMf_drho = self.mesh.getFaceInnerProductDeriv(self.curModel.rho)(u)
-        return dMfRhoI_dI * ( dMf_drho * self.curModel.rhoDeriv )
+        return self.mesh.getFaceInnerProductDeriv(self.curModel.rho, invMat=True)(u) * self.curModel.rhoDeriv
 
 class BaseEMSurvey(Survey.BaseSurvey):
 
@@ -214,10 +192,9 @@ class BaseEMSurvey(Survey.BaseSurvey):
         self.srcList = srcList
         Survey.BaseSurvey.__init__(self, **kwargs)
 
-    def eval(self, f):
+    def eval(self, u):
         """
         Project fields to receiver locations
-
         :param Fields u: fields object
         :rtype: numpy.ndarray
         :return: data
@@ -225,8 +202,8 @@ class BaseEMSurvey(Survey.BaseSurvey):
         data = Survey.Data(self)
         for src in self.srcList:
             for rx in src.rxList:
-                data[src, rx] = rx.eval(src, self.mesh, f)
+                data[src, rx] = rx.eval(src, self.mesh, u)
         return data
 
-    def evalDeriv(self, f):
+    def evalDeriv(self, u):
         raise Exception('Use Receivers to project fields deriv.')

SimPEG/EM/FDEM/FDEM.py

@@ -1,7 +1,7 @@
 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 FieldsFDEM, Fields3D_e, Fields3D_b, Fields3D_h, Fields3D_j
+from FieldsFDEM import Fields, Fields_e, Fields_b, Fields_h, Fields_j
 from SimPEG.EM.Base import BaseEMProblem
 from SimPEG.EM.Utils import omega
 
@@ -17,8 +17,8 @@ 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:`Problem3D_e`
-        or :code:`Problem3D_b`). Note that in this case, :math:`\mathbf{s_e}` is an integrated quantity.
+        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 we write Maxwell's equations in terms of
         \\\(\\\mathbf{h}\\\) and current density \\\(\\\mathbf{j}\\\)
@@ -28,14 +28,13 @@ 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:`Problem3D_j` or :code:`Problem3D_h`). Note that here, :math:`\mathbf{s_m}` is an integrated quantity.
+        if using the H-J formulation (:code:`Problem_j` or :code:`Problem_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 = FieldsFDEM
+    fieldsPair = Fields
 
     def fields(self, m):
         """
@@ -65,7 +64,7 @@ class BaseFDEMProblem(BaseEMProblem):
 
         :param numpy.array m: inversion model (nP,)
         :param numpy.array v: vector which we take sensitivity product with (nP,)
-        :param SimPEG.EM.FDEM.FieldsFDEM.FieldsFDEM u: fields object
+        :param SimPEG.EM.FDEM.Fields u: fields object
         :rtype numpy.array:
         :return: Jv (ndata,)
         """
@@ -88,7 +87,7 @@ class BaseFDEMProblem(BaseEMProblem):
                 du_dm_v = Ainv * ( - dA_dm_v + dRHS_dm_v )
 
                 for rx in src.rxList:
-                    df_dmFun = getattr(f, '_{0}Deriv'.format(rx.projField), None)
+                    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)
             Ainv.clean()
@@ -100,7 +99,7 @@ class BaseFDEMProblem(BaseEMProblem):
 
         :param numpy.array m: inversion model (nP,)
         :param numpy.array v: vector which we take adjoint product with (nP,)
-        :param SimPEG.EM.FDEM.FieldsFDEM.FieldsFDEM u: fields object
+        :param SimPEG.EM.FDEM.Fields u: fields object
         :rtype numpy.array:
         :return: Jv (ndata,)
         """
@@ -126,7 +125,7 @@ class BaseFDEMProblem(BaseEMProblem):
                 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, '_{0}Deriv'.format(rx.projField), None)
+                    df_duTFun = getattr(f, '_%sDeriv'%rx.projField, None)
                     df_duT, df_dmT = df_duTFun(src, None, PTv, adjoint=True)
 
                     ATinvdf_duT = ATinv * df_duT
@@ -138,9 +137,10 @@ class BaseFDEMProblem(BaseEMProblem):
                     df_dmT = df_dmT + du_dmT
 
                     # TODO: this should be taken care of by the reciever?
-                    if rx.component is 'real':
+                    real_or_imag = rx.projComp
+                    if real_or_imag is 'real':
                         Jtv +=   np.array(df_dmT, dtype=complex).real
-                    elif rx.component is 'imag':
+                    elif real_or_imag is 'imag':
                         Jtv += - np.array(df_dmT, dtype=complex).real
                     else:
                         raise Exception('Must be real or imag')
@@ -154,8 +154,8 @@ class BaseFDEMProblem(BaseEMProblem):
         Evaluates the sources for a given frequency and puts them in matrix form
 
         :param float freq: Frequency
-        :rtype: tuple
-        :return: (s_m, s_e) (nE or nF, nSrc)
+        :rtype: (numpy.ndarray, numpy.ndarray)
+        :return: s_m, s_e (nE or nF, nSrc)
         """
         Srcs = self.survey.getSrcByFreq(freq)
         if self._formulation is 'EB':
@@ -167,7 +167,6 @@ class BaseFDEMProblem(BaseEMProblem):
 
         for i, src in enumerate(Srcs):
             smi, sei = src.eval(self)
-            #Why are you adding?
             s_m[:,i] = s_m[:,i] + smi
             s_e[:,i] = s_e[:,i] + sei
 
@@ -178,7 +177,7 @@ class BaseFDEMProblem(BaseEMProblem):
 ################################ E-B Formulation #########################################
 ##########################################################################################
 
-class Problem3D_e(BaseFDEMProblem):
+class Problem_e(BaseFDEMProblem):
     """
     By eliminating the magnetic flux density using
 
@@ -195,12 +194,12 @@ class Problem3D_e(BaseFDEMProblem):
 
     which we solve for :math:`\mathbf{e}`.
 
-    :param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
+    :param SimPEG.Mesh mesh: mesh
     """
 
     _solutionType = 'eSolution'
     _formulation  = 'EB'
-    fieldsPair    = Fields3D_e
+    fieldsPair    = Fields_e
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -270,7 +269,7 @@ class Problem3D_e(BaseFDEMProblem):
         Derivative of the right hand side with respect to the model
 
         :param float freq: frequency
-        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
+        :param SimPEG.EM.FDEM.Src src: FDEM source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
@@ -289,7 +288,7 @@ class Problem3D_e(BaseFDEMProblem):
             return C.T * (MfMui * s_mDeriv(v)) -1j * omega(freq) * s_eDeriv(v)
 
 
-class Problem3D_b(BaseFDEMProblem):
+class Problem_b(BaseFDEMProblem):
     """
     We eliminate :math:`\mathbf{e}` using
 
@@ -306,12 +305,12 @@ class Problem3D_b(BaseFDEMProblem):
     .. note ::
         The inverse problem will not work with full anisotropy
 
-    :param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
+    :param SimPEG.Mesh mesh: mesh
     """
 
     _solutionType = 'bSolution'
     _formulation  = 'EB'
-    fieldsPair    = Fields3D_b
+    fieldsPair    = Fields_b
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -401,7 +400,7 @@ class Problem3D_b(BaseFDEMProblem):
         Derivative of the right hand side with respect to the model
 
         :param float freq: frequency
-        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
+        :param SimPEG.EM.FDEM.Src src: FDEM source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
@@ -437,7 +436,7 @@ class Problem3D_b(BaseFDEMProblem):
 ##########################################################################################
 
 
-class Problem3D_j(BaseFDEMProblem):
+class Problem_j(BaseFDEMProblem):
     """
     We eliminate \\\(\\\mathbf{h}\\\) using
 
@@ -445,7 +444,6 @@ class Problem3D_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 ::
@@ -455,12 +453,12 @@ class Problem3D_j(BaseFDEMProblem):
     .. note::
         This implementation does not yet work with full anisotropy!!
 
-    :param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
+    :param SimPEG.Mesh mesh: mesh
     """
 
     _solutionType = 'jSolution'
     _formulation  = 'HJ'
-    fieldsPair    = Fields3D_j
+    fieldsPair    = Fields_j
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -531,8 +529,8 @@ class Problem3D_j(BaseFDEMProblem):
             \mathbf{RHS} = \mathbf{C} \mathbf{M_{\mu}^e}^{-1}\mathbf{s_m} -i\omega \mathbf{s_e}
 
         :param float freq: Frequency
-        :rtype: numpy.ndarray
-        :return: RHS (nE, nSrc)
+        :rtype: numpy.ndarray (nE, nSrc)
+        :return: RHS
         """
 
         s_m, s_e = self.getSourceTerm(freq)
@@ -551,7 +549,7 @@ class Problem3D_j(BaseFDEMProblem):
         Derivative of the right hand side with respect to the model
 
         :param float freq: frequency
-        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
+        :param SimPEG.EM.FDEM.Src src: FDEM source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
@@ -579,7 +577,7 @@ class Problem3D_j(BaseFDEMProblem):
 
 
 
-class Problem3D_h(BaseFDEMProblem):
+class Problem_h(BaseFDEMProblem):
     """
     We eliminate \\\(\\\mathbf{j}\\\) using
 
@@ -593,12 +591,12 @@ class Problem3D_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.BaseMesh.BaseMesh mesh: mesh
+    :param SimPEG.Mesh mesh: mesh
     """
 
     _solutionType = 'hSolution'
     _formulation  = 'HJ'
-    fieldsPair    = Fields3D_h
+    fieldsPair    = Fields_h
 
     def __init__(self, mesh, **kwargs):
         BaseFDEMProblem.__init__(self, mesh, **kwargs)
@@ -610,11 +608,9 @@ class Problem3D_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
@@ -657,7 +653,6 @@ class Problem3D_h(BaseFDEMProblem):
         :param float freq: Frequency
         :rtype: numpy.ndarray
         :return: RHS (nE, nSrc)
-
         """
 
         s_m, s_e = self.getSourceTerm(freq)
@@ -671,7 +666,7 @@ class Problem3D_h(BaseFDEMProblem):
         Derivative of the right hand side with respect to the model
 
         :param float freq: frequency
-        :param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
+        :param SimPEG.EM.FDEM.Src src: FDEM source
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray

SimPEG/EM/FDEM/FieldsFDEM.py

@@ -6,11 +6,11 @@ from SimPEG.EM.Utils import omega
 from SimPEG.Utils import Zero, Identity, sdiag
 
 
-class FieldsFDEM(SimPEG.Problem.Fields):
+class Fields(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 object acts like an array and is indexed by
+    each problem, the rest are computed. The fields obejct acts like an array and is indexed by
 
     .. code-block:: python
 
@@ -92,7 +92,7 @@ class FieldsFDEM(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 SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
+        :param Src src: sorce
         :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?
@@ -110,7 +110,7 @@ class FieldsFDEM(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 SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
+        :param Src src: sorce
         :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?
@@ -128,7 +128,7 @@ class FieldsFDEM(SimPEG.Problem.Fields):
         """
         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 SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
+        :param Src src: sorce
         :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?
@@ -146,7 +146,7 @@ class FieldsFDEM(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 SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
+        :param Src src: sorce
         :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?
@@ -160,12 +160,12 @@ class FieldsFDEM(SimPEG.Problem.Fields):
             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 Fields3D_e(FieldsFDEM):
+class Fields_e(Fields):
     """
-    Fields object for Problem3D_e.
+    Fields object for Problem_e.
 
-    :param BaseMesh mesh: mesh
-    :param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
+    :param Mesh mesh: mesh
+    :param Survey survey: survey
     """
 
     knownFields = {'eSolution':'E'}
@@ -180,6 +180,9 @@ class Fields3D_e(FieldsFDEM):
                     '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
@@ -423,12 +426,12 @@ class Fields3D_e(FieldsFDEM):
 
 
 
-class Fields3D_b(FieldsFDEM):
+class Fields_b(Fields):
     """
-    Fields object for Problem3D_b.
+    Fields object for Problem_b.
 
-    :param BaseMesh mesh: mesh
-    :param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
+    :param Mesh mesh: mesh
+    :param Survey survey: survey
     """
 
     knownFields = {'bSolution':'F'}
@@ -443,6 +446,9 @@ class Fields3D_b(FieldsFDEM):
                     '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
@@ -687,12 +693,12 @@ class Fields3D_b(FieldsFDEM):
         return Zero()
 
 
-class Fields3D_j(FieldsFDEM):
+class Fields_j(Fields):
     """
-    Fields object for Problem3D_j.
+    Fields object for Problem_j.
 
-    :param BaseMesh mesh: mesh
-    :param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
+    :param Mesh mesh: mesh
+    :param Survey survey: survey
     """
 
     knownFields = {'jSolution':'F'}
@@ -707,6 +713,9 @@ class Fields3D_j(FieldsFDEM):
                     '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
@@ -979,12 +988,12 @@ class Fields3D_j(FieldsFDEM):
         return 1./(1j * omega(src.freq)) * VI * (self._aveE2CCV * ( s_mDeriv(v) - self._edgeCurl.T * ( self._MfRhoDeriv(jSolution) * v ) ) )
 
 
-class Fields3D_h(FieldsFDEM):
+class Fields_h(Fields):
     """
-    Fields object for Problem3D_h.
+    Fields object for Problem_h.
 
-    :param BaseMesh mesh: mesh
-    :param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
+    :param Mesh mesh: mesh
+    :param Survey survey: survey
     """
 
     knownFields = {'hSolution':'E'}
@@ -999,6 +1008,9 @@ class Fields3D_h(FieldsFDEM):
                     '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

SimPEG/EM/FDEM/RxFDEM.py

@@ -1,126 +0,0 @@
-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

@@ -10,21 +10,18 @@ class BaseSrc(Survey.BaseSrc):
 
     freq = None
     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
 
-        :param BaseFDEMProblem prob: FDEM Problem
-        :rtype: tuple
+        :param Problem prob: FDEM Problem
+        :rtype: (numpy.ndarray, numpy.ndarray)
         :return: tuple with magnetic source term and electric source term
         """
         s_m = self.s_m(prob)
@@ -37,10 +34,10 @@ class BaseSrc(Survey.BaseSrc):
         - :code:`s_mDeriv` : derivative of the magnetic source term
         - :code:`s_eDeriv` : derivative of the electric source term
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
-        :rtype: tuple
+        :rtype: (numpy.ndarray, numpy.ndarray)
         :return: tuple with magnetic source term and electric source term derivatives times a vector
         """
         if v is not None:
@@ -52,55 +49,56 @@ class BaseSrc(Survey.BaseSrc):
         """
         Primary magnetic flux density
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: primary magnetic flux density
         """
-        if self._bPrimary is None:
-            return Zero()
-        return self._bPrimary
+        #TODO : allow hPrimary to be provided and get bPrimary from it
+        if getattr(self, '_bPrimary', None) is not None:
+            return self._bPrimary
+        return Zero()
 
     def hPrimary(self, prob):
         """
         Primary magnetic field
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
-        if self._hPrimary is None:
-            return Zero()
-        return self._hPrimary
+        if getattr(self, '_hPrimary', None) is not None:
+            return self._hPrimary
+        return Zero()
 
     def ePrimary(self, prob):
         """
         Primary electric field
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: primary electric field
         """
-        if self._ePrimary is None:
-            return Zero()
-        return self._ePrimary
+        if getattr(self, '_ePrimary', None) is not None:
+            return self._ePrimary
+        return Zero()
 
     def jPrimary(self, prob):
         """
         Primary current density
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: primary current density
         """
-        if self._jPrimary is None:
-            return Zero()
-        return self._jPrimary
+        if getattr(self, '_jPrimary', None) is not None:
+            return self._jPrimary
+        return Zero()
 
     def s_m(self, prob):
         """
         Magnetic source term
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: magnetic source term on mesh
         """
@@ -110,7 +108,7 @@ class BaseSrc(Survey.BaseSrc):
         """
         Electric source term
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: electric source term on mesh
         """
@@ -120,7 +118,7 @@ class BaseSrc(Survey.BaseSrc):
         """
         Derivative of magnetic source term with respect to the inversion model
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
@@ -133,7 +131,7 @@ class BaseSrc(Survey.BaseSrc):
         """
         Derivative of electric source term with respect to the inversion model
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :param numpy.ndarray v: vector to take product with
         :param bool adjoint: adjoint?
         :rtype: numpy.ndarray
@@ -152,17 +150,17 @@ class RawVec_e(BaseSrc):
     :param bool integrate: Integrate the source term (multiply by Me) [False]
     """
 
-    def __init__(self, rxList, freq, s_e, **kwargs):
+    def __init__(self, rxList, freq, s_e, **kwargs): #ePrimary=None, jPrimary=None, hPrimary=None, bPrimary=None
         self._s_e = np.array(s_e, dtype=complex)
         self.freq = float(freq)
-
-        BaseSrc.__init__(self, rxList, **kwargs)
+        [setattr(self, '_%s'%primField, kwargs[primField]) for primField in ['ePrimary', 'jPrimary', 'hPrimary', 'bPrimary'] if kwargs.get(primField) is not None]
+        BaseSrc.__init__(self, rxList)
 
     def s_e(self, prob):
         """
         Electric source term
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: electric source term on mesh
         """
@@ -181,17 +179,17 @@ class RawVec_m(BaseSrc):
     :param bool integrate: Integrate the source term (multiply by Me) [False]
     """
 
-    def __init__(self, rxList, freq, s_m, **kwargs):  #ePrimary=Zero(), bPrimary=Zero(), hPrimary=Zero(), jPrimary=Zero()):
+    def __init__(self, rxList, freq, s_m, **kwargs): #ePrimary=None, jPrimary=None, hPrimary=None, bPrimary=None):
         self._s_m = np.array(s_m, dtype=complex)
         self.freq = float(freq)
-
-        BaseSrc.__init__(self, rxList, **kwargs)
+        [setattr(self, '_%s'%primField, kwargs[primField]) for primField in ['ePrimary', 'jPrimary', 'hPrimary', 'bPrimary'] if kwargs.get(primField) is not None]
+        BaseSrc.__init__(self, rxList)
 
     def s_m(self, prob):
         """
         Magnetic source term
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: magnetic source term on mesh
         """
@@ -210,17 +208,18 @@ class RawVec(BaseSrc):
     :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, **kwargs):
+    def __init__(self, rxList, freq, s_m, s_e, **kwargs): #ePrimary=None, jPrimary=None, hPrimary=None, bPrimary=None, **kwargs):
         self._s_m = np.array(s_m, dtype=complex)
         self._s_e = np.array(s_e, dtype=complex)
         self.freq = float(freq)
+        [setattr(self, '_%s'%primField, kwargs[primField]) for primField in ['ePrimary', 'jPrimary', 'hPrimary', 'bPrimary'] if kwargs.get(primField) is not None]
         BaseSrc.__init__(self, rxList, **kwargs)
 
     def s_m(self, prob):
         """
         Magnetic source term
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: magnetic source term on mesh
         """
@@ -232,7 +231,7 @@ class RawVec(BaseSrc):
         """
         Electric source term
 
-        :param BaseFDEMProblem prob: FDEM Problem
+        :param Problem prob: FDEM Problem
         :rtype: numpy.ndarray
         :return: electric source term on mesh
         """
@@ -301,7 +300,7 @@ class MagDipole(BaseSrc):
         """
         The primary magnetic flux density from a magnetic vector potential
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -339,7 +338,7 @@ class MagDipole(BaseSrc):
         """
         The primary magnetic field from a magnetic vector potential
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -350,7 +349,7 @@ class MagDipole(BaseSrc):
         """
         The magnetic source term
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -364,7 +363,7 @@ class MagDipole(BaseSrc):
         """
         The electric source term
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -416,7 +415,7 @@ class MagDipole_Bfield(BaseSrc):
         """
         The primary magnetic flux density from the analytic solution for magnetic fields from a dipole
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -455,7 +454,7 @@ class MagDipole_Bfield(BaseSrc):
         """
         The primary magnetic field from a magnetic vector potential
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -466,7 +465,7 @@ class MagDipole_Bfield(BaseSrc):
         """
         The magnetic source term
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -479,7 +478,7 @@ class MagDipole_Bfield(BaseSrc):
         """
         The electric source term
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -530,7 +529,7 @@ class CircularLoop(BaseSrc):
         """
         The primary magnetic flux density from a magnetic vector potential
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -567,7 +566,7 @@ class CircularLoop(BaseSrc):
         """
         The primary magnetic field from a magnetic vector potential
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -578,7 +577,7 @@ class CircularLoop(BaseSrc):
         """
         The magnetic source term
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """
@@ -591,7 +590,7 @@ class CircularLoop(BaseSrc):
         """
         The electric source term
 
-        :param BaseFDEMProblem prob: FDEM problem
+        :param Problem prob: FDEM problem
         :rtype: numpy.ndarray
         :return: primary magnetic field
         """

SimPEG/EM/FDEM/SurveyFDEM.py

@@ -4,9 +4,126 @@ from SimPEG.EM.Base import BaseEMSurvey
 from scipy.constants import mu_0
 from SimPEG.Utils import Zero, Identity
 import SrcFDEM as Src
-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, f):
+        """
+        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(f))
+        f_part_complex = f[src, self.projField]
+        # get the real or imag component
+        real_or_imag = self.projComp
+        f_part = getattr(f_part_complex, real_or_imag)
+
+        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 Source src: FDEM source
+        :param Mesh 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
+            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(BaseEMSurvey):
     """
     Frequency domain electromagnetic survey
@@ -15,7 +132,7 @@ class Survey(BaseEMSurvey):
     """
 
     srcPair = Src.BaseSrc
-    rxPair = Rx.BaseRx
+    rxPair = Rx
 
     def __init__(self, srcList, **kwargs):
         # Sort these by frequency

SimPEG/EM/FDEM/__init__.py

@@ -1,5 +1,3 @@
-from SurveyFDEM import Survey
-import SrcFDEM as Src
-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
+from SurveyFDEM import Rx, Src, Survey
+from FDEM import BaseFDEMProblem, Problem_e, Problem_b, Problem_j, Problem_h
+from FieldsFDEM import *

SimPEG/EM/Static/DC/BoundaryUtils.py

@@ -1,160 +0,0 @@
-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

@@ -1,148 +0,0 @@
-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' %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' %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' %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

@@ -1,146 +0,0 @@
-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' %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' %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' %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

@@ -1,296 +0,0 @@
-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

@@ -1,349 +0,0 @@
-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

@@ -1,129 +0,0 @@
-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

@@ -1,86 +0,0 @@
-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

@@ -1,38 +0,0 @@
-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

@@ -1,38 +0,0 @@
-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

@@ -1,8 +0,0 @@
-from ProblemDC import Problem3D_CC, Problem3D_N
-from ProblemDC_2D import Problem2D_CC, Problem2D_N
-from SurveyDC import Survey, Survey_ky
-import SrcDC as Src #Pole
-import RxDC as Rx
-from FieldsDC import Fields_CC
-from BoundaryUtils import getxBCyBC_CC
-import Utils

SimPEG/EM/Static/IP/ProblemIP.py

@@ -1,372 +0,0 @@
-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

@@ -1,23 +0,0 @@
-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

@@ -1,2 +0,0 @@
-from ProblemIP import Problem3D_CC, Problem3D_N
-from SurveyIP import Survey

SimPEG/EM/Static/SIP/ProblemSIP.py

@@ -1,445 +0,0 @@
-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((int(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

@@ -1,204 +0,0 @@
-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

@@ -1,88 +0,0 @@
-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

@@ -1,64 +0,0 @@
-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

@@ -1,102 +0,0 @@
-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

@@ -1,5 +0,0 @@
-from ProblemSIP import Problem3D_CC, Problem3D_N
-from SurveySIP import Survey, Data
-import SrcSIP as Src #Pole
-import RxSIP as Rx
-from Regularization import MultiRegularization

SimPEG/EM/Static/Utils/StaticUtils.py

@@ -1,317 +0,0 @@
-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(range(int(nstn)))*dl_x*a
-    stn_y = endl[0,1] + np.array(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([np.floor( (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(range(int(nstn)))*dl_x*a
-            stn_y = N[ii,1] + dl_y*b + np.array(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(range(int(nstn)))*dl_x*a
-        stn_y = min_y + np.array(range(int(nstn)))*dl_y*a
-
-        # Define number of cross lines
-        nlin = int(np.floor( box_w / a ))
-        lind = 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

@@ -1 +0,0 @@
-from StaticUtils import *

SimPEG/EM/Static/__init__.py

@@ -1,3 +0,0 @@
-import DC
-import IP
-import SIP

SimPEG/EM/TDEM/BaseTDEM.py

@@ -112,7 +112,7 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
         """
             :param numpy.array m: Conductivity model
             :param numpy.ndarray v: vector (model object)
-            :param FieldsTDEM f: Fields resulting from m
+            :param simpegEM.TDEM.FieldsTDEM f: Fields resulting from m
             :rtype: numpy.ndarray
             :return: w (data object)
 
@@ -136,8 +136,8 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
     def Jtvec(self, m, v, f=None):
         """
             :param numpy.array m: Conductivity model
-            :param numpy.ndarray v: vector (or a :class:`SimPEG.Survey.Data` object)
-            :param FieldsTDEM u: Fields resulting from m
+            :param numpy.ndarray,SimPEG.Survey.Data v: vector (data object)
+            :param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
             :rtype: numpy.ndarray
             :return: w (model object)
 

SimPEG/EM/TDEM/SurveyTDEM.py

@@ -87,7 +87,7 @@ 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')
@@ -96,8 +96,8 @@ 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"
             return {"b": np.zeros(mesh.nF)}
@@ -113,7 +113,7 @@ 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
 
 
@@ -122,7 +122,7 @@ 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"""
@@ -153,7 +153,7 @@ 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

@@ -87,8 +87,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
         """
             :param numpy.array m: Conductivity model
             :param numpy.array vec: vector (like a model)
-            :param FieldsTDEM u: Fields resulting from m
-            :rtype: FieldsTDEM
+            :param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
+            :rtype: simpegEM.TDEM.FieldsTDEM
             :return: f
 
             Multiply G by a vector
@@ -125,9 +125,9 @@ class ProblemTDEM_b(BaseTDEMProblem):
         """
             :param numpy.array m: Conductivity model
             :param numpy.array vec: vector (like a fields)
-            :param FieldsTDEM u: Fields resulting from m
-            :rtype: numpy.ndarray
-            :return: p (like a model)
+            :param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
+            :rtype: np.ndarray (like a model)
+            :return: p
 
             Multiply G.T by a vector
         """
@@ -153,8 +153,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
     def solveAh(self, m, p):
         """
             :param numpy.array m: Conductivity model
-            :param FieldsTDEM p: Fields object
-            :rtype: FieldsTDEM
+            :param simpegEM.TDEM.FieldsTDEM p: Fields object
+            :rtype: simpegEM.TDEM.FieldsTDEM
             :return: y
 
             Solve the block-matrix system \\\(\\\hat{A} \\\hat{y} = \\\hat{p}\\\):
@@ -200,8 +200,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
     def solveAht(self, m, p):
         """
             :param numpy.array m: Conductivity model
-            :param FieldsTDEM p: Fields object
-            :rtype: FieldsTDEM
+            :param simpegEM.TDEM.FieldsTDEM p: Fields object
+            :rtype: simpegEM.TDEM.FieldsTDEM
             :return: y
 
             Solve the block-matrix system \\\(\\\hat{A}^\\\\top \\\hat{y} = \\\hat{p}\\\):
@@ -270,8 +270,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
     def _AhVec(self, m, vec):
         """
             :param numpy.array m: Conductivity model
-            :param FieldsTDEM vec: Fields object
-            :rtype: FieldsTDEM
+            :param simpegEM.TDEM.FieldsTDEM vec: Fields object
+            :rtype: simpegEM.TDEM.FieldsTDEM
             :return: f
 
             Multiply the matrix \\\(\\\hat{A}\\\) by a fields vector where
@@ -315,8 +315,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
     def _AhtVec(self, m, vec):
         """
             :param numpy.array m: Conductivity model
-            :param FieldsTDEM vec: Fields object
-            :rtype: FieldsTDEM
+            :param simpegEM.TDEM.FieldsTDEM vec: Fields object
+            :rtype: simpegEM.TDEM.FieldsTDEM
             :return: f
 
             Multiply the matrix \\\(\\\hat{A}\\\) by a fields vector where

SimPEG/EM/Utils/testingUtils.py

@@ -26,55 +26,50 @@ def getFDEMProblem(fdemType, comp, SrcList, freq, useMu=False, verbose=False):
 
     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 = 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')
+    Rx0 = EM.FDEM.Rx(XYZ, comp)
 
     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, mesh.getEdgeInnerProduct()*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, mesh.getEdgeInnerProduct()*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)
 
     if fdemType == 'e':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem3D_e(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem_e(mesh, mapping=mapping)
 
     elif fdemType == 'b':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem3D_b(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem_b(mesh, mapping=mapping)
 
     elif fdemType == 'j':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem3D_j(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem_j(mesh, mapping=mapping)
 
     elif fdemType == 'h':
         survey = EM.FDEM.Survey(Src)
-        prb = EM.FDEM.Problem3D_h(mesh, mapping=mapping)
+        prb = EM.FDEM.Problem_h(mesh, mapping=mapping)
 
     else:
         raise NotImplementedError()

SimPEG/EM/__init__.py

@@ -1,6 +1,5 @@
 import TDEM
 import FDEM
-import Static
 import Base
 import Analytics
 import Utils

SimPEG/Examples/DC_Analytic_Dipole.py

@@ -1,7 +1,7 @@
 from SimPEG import *
-import SimPEG.EM.Static.DC as DC
+import SimPEG.DCIP as DC
 
-def run(plotIt=True):
+def run(plotIt=False):
     cs = 25.
     hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
     hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
@@ -21,10 +21,10 @@ def run(plotIt=True):
     #     ax.plot(xyz_rxP[:,0],xyz_rxP[:,1], 'w.')
     #     ax.plot(xyz_rxN[:,0],xyz_rxN[:,1], 'r.', ms = 3)
 
-    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)
+    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)
     problem.pair(survey)
     try:
         from pymatsolver import MumpsSolver
@@ -65,4 +65,4 @@ def run(plotIt=True):
 
 
 if __name__ == '__main__':
-    print run()
+    print run(plotIt=True)

SimPEG/Examples/DC_Forward_PseudoSection.py

@@ -2,27 +2,19 @@ from SimPEG import Mesh, Utils, np, sp
 import SimPEG.DCIP as DC
 import time
 
-def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', unitType='appConductivity', plotIt=True):
+def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
     """
         DC Forward Simulation
         =====================
 
-        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.
+        Forward model conductive spheres in a half-space and plot a pseudo-section
 
-        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
+        Created by @fourndo on Mon Feb 01 19:28:06 2016
 
     """
 
-    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)"
+    assert stype in ['pdp', 'dpdp'], "Source type (stype) must be pdp or dpdp (pole dipole or dipole dipole)"
+
 
     if loc is None:
         loc = np.c_[[-50.,0.,-50.],[50.,0.,-50.]]
@@ -35,6 +27,7 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
 
 
     # First we need to create a mesh and a model.
+
     # This is our mesh
     dx    = 5.
 
@@ -59,10 +52,14 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
     # Get index of the center
     indy = int(mesh.nCy/2)
 
+
     # Plot the model for reference
     # Define core mesh extent
     xlim = 200
-    zlim = 100
+    zlim = 125
+
+    # Specify the survey type: "pdp" | "dpdp"
+
 
     # 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)]
@@ -73,20 +70,19 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
     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, surveyType, param[0], param[1], param[2])
-    survey, Tx, Rx = DC.gen_DCIPsurvey(locs, mesh, surveyType, param[0], param[1], param[2])
+    # [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])
 
     # 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 linear system needed for the DC problem. We assume an infitite
-    # line source for simplicity.
+    # Define the differential operators needed for the DC problem
     Div = mesh.faceDiv
     Grad = mesh.cellGrad
     Msig = Utils.sdiag(1./(mesh.aveF2CC.T*(1./model)))
@@ -118,8 +114,8 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
         rxloc_N = np.asarray(Rx[ii][:,3:])
 
 
-        # For usual cases 'dipole-dipole' or "gradient"
-        if surveyType == 'pole-dipole':
+        # For usual cases "dpdp" or "gradient"
+        if stype == 'pdp':
             # Create an "inifinity" pole
             tx =  np.squeeze(Tx[ii][:,0:1])
             tinf = tx + np.array([dl_x,dl_y,0])*dl_len*2
@@ -149,23 +145,16 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
     print 'Forward completed'
 
     # Let's just convert the 3D format into 2D (distance along line) and plot
-    survey2D = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc) , 'Xloc')
+    # [Tx2d, Rx2d] = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc))
+    survey2D = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc))
     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(figsize=(7,7))
+        fig = plt.figure()
         ax = plt.subplot(2,1,1, aspect='equal')
-        # 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')
+        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')
         plt.gca().set_aspect('equal', adjustable='box')
 
         plt.scatter(Tx[0][0,:],Tx[0][2,:],s=40,c='g', marker='v')
@@ -174,32 +163,22 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
         plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
 
 
-        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')
+        ax = plt.subplot(2,1,2, aspect='equal')
 
         # 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)
-        ax2.add_artist(circle1)
-        ax2.add_artist(circle2)
+        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)
 
         # Add the speudo section
-        dat = DC.plot_pseudoSection(survey2D, ax2, surveyType=surveyType, unitType=unitType)        # plt.scatter(Tx2d[0][:],Tx[0][2,:],s=40,c='g', marker='v')
+        DC.plot_pseudoSection(survey2D,ax,stype)
+
+        # 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')
-        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

@@ -42,16 +42,17 @@ def run(plotIt=True):
         ax.grid(color='k', alpha=0.5, linestyle='dashed', linewidth=0.5)
 
 
-    rxOffset=10.
-    bzi = EM.FDEM.Rx.Point_b(np.array([[rxOffset, 0., 1e-3]]), orientation='z', component='imag')
+    rxOffset=10. 
+    bzi = EM.FDEM.Rx(np.array([[rxOffset, 0., 1e-3]]), 'bzi')
 
     freqs = np.logspace(1,3,10)
     srcLoc = np.array([0., 0., 10.])
 
-    srcList = [EM.FDEM.Src.MagDipole([bzi],freq, srcLoc,orientation='Z') for freq in freqs]
+    srcList = []
+    [srcList.append(EM.FDEM.Src.MagDipole([bzi],freq, srcLoc,orientation='Z')) for freq in freqs]
 
     survey = EM.FDEM.Survey(srcList)
-    prb = EM.FDEM.Problem3D_b(mesh, mapping=mapping)
+    prb = EM.FDEM.Problem_b(mesh, mapping=mapping)
 
     try:
         from pymatsolver import MumpsSolver

SimPEG/Examples/EM_Schenkel_Morrison_Casing.py

@@ -1,278 +0,0 @@
-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.floor(np.log(csx2/csx1) / np.log(pfx1))
-    hx1a,hx1b = Utils.meshTensor([(csx1,ncx1)]),Utils.meshTensor([(csx1,npadx1,pfx1)])
-    dx1 = sum(hx1a)+sum(hx1b)
-    dx1 = np.floor(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/Forward_BasicDirectCurrent.py

@@ -1,25 +1,22 @@
 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(sigma, invProp=True, invMat=True)
-        A = -D*MsigI*D.T
+        Msigi = mesh.getFaceInnerProduct(1./sigma)
+        MsigI = Utils.sdInv(Msigi)
+        A = D*MsigI*G
         A[-1,-1] /= mesh.vol[-1] # Remove null space
         rhs = np.zeros(mesh.nC)
         txind = Utils.meshutils.closestPoints(mesh, pts)
@@ -40,17 +37,39 @@ 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)
-    dat = rM.plotImage(phirM, ax=axes[1], 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)
+
     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/Inversion_IRLS.py

@@ -1,102 +0,0 @@
-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/MT_1D_ForwardAndInversion.py

@@ -7,7 +7,7 @@ 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 +50,7 @@ def run(plotIt=True):
     m_0 = np.log(sigma_0[active])
 
     # Set the mapping
-    actMap = simpeg.Maps.InjectActiveCells(m1d, active, np.log(1e-8), nC=m1d.nCx)
+    actMap = simpeg.Maps.ActiveCells(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 +76,7 @@ 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, [m_0])
+        fig = MT.Utils.dataUtils.plotMT1DModelData(problem)
         fig.suptitle('Target - smooth true')
 
 
@@ -100,7 +100,7 @@ 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.mrefInSmooth = True
+    reg.smoothModel = True
     reg.alpha_s = 1e-7
     reg.alpha_x = 1.
     # Inversion problem

SimPEG/Examples/MT_3D_Foward.py

@@ -12,7 +12,7 @@ except:
 def run(plotIt=True, nFreq=1):
     """
         MT: 3D: Forward
-        ===============
+        =======================
 
         Forward model 3D MT data.
 
@@ -46,15 +46,16 @@ def run(plotIt=True, nFreq=1):
     survey = MT.Survey(srcList)
 
     ## Setup the problem object
-    problem = MT.Problem3D.eForm_ps(M, sigmaPrimary=sigBG, Solver=Solver)
+    problem = MT.Problem3D.eForm_ps(M, sigmaPrimary=sigBG)
     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

@@ -1,62 +0,0 @@
-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

@@ -1,41 +0,0 @@
-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/Utils_surface2ind_topo.py

@@ -1,43 +0,0 @@
-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

@@ -5,14 +5,10 @@ import DC_Analytic_Dipole
 import DC_Forward_PseudoSection
 import EM_FDEM_1D_Inversion
 import EM_FDEM_Analytic_MagDipoleWholespace
-import EM_Schenkel_Morrison_Casing
 import EM_TDEM_1D_Inversion
 import FLOW_Richards_1D_Celia1990
-import Inversion_IRLS
+import Forward_BasicDirectCurrent
 import Inversion_Linear
-import Maps_ComboMaps
-import Maps_Mesh2Mesh
-import Mesh_Basic_ForwardDC
 import Mesh_Basic_PlotImage
 import Mesh_Basic_Types
 import Mesh_Operators_CahnHilliard
@@ -22,9 +18,8 @@ import Mesh_QuadTree_HangingNodes
 import Mesh_Tensor_Creation
 import MT_1D_ForwardAndInversion
 import MT_3D_Foward
-import Utils_surface2ind_topo
 
-__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"]
+__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"]
 
 ##### AUTOIMPORTS #####
 
@@ -40,7 +35,7 @@ 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', 'content', 'examples'])
+    docExamplesDir = os.path.sep.join(fName.split(os.path.sep)[:-3] + ['docs', 'examples'])
     shutil.rmtree(docExamplesDir)
     os.makedirs(docExamplesDir)
 
@@ -97,12 +92,12 @@ 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', 'content', 'examples', name + '.rst']))
+        rst = os.path.sep.join((filePath.split(os.path.sep)[:-3] + ['docs', 'examples', name + '.rst']))
 
         print 'Creating: %s.rst'%name
         f = open(rst, 'w')

SimPEG/FLOW/Richards/Empirical.py

@@ -31,7 +31,7 @@ class NonLinearMap(object):
         """
             :param numpy.array u: fields
             :param numpy.array m: model
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: derivative of transformed model
 
             The *transform* changes the model into the physical property.
@@ -44,7 +44,7 @@ class NonLinearMap(object):
         """
             :param numpy.array u: fields
             :param numpy.array m: model
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: derivative of transformed model
 
             The *transform* changes the model into the physical property.

SimPEG/Inversion.py

@@ -33,9 +33,7 @@ class BaseInversion(object):
         self._directiveList = value
         self._directiveList.inversion = self
 
-    def __init__(self, invProb, directiveList=None, **kwargs):
-        if directiveList is None:
-            directiveList = []
+    def __init__(self, invProb, directiveList=[], **kwargs):
         self.directiveList = directiveList
         Utils.setKwargs(self, **kwargs)
 

SimPEG/MT/BaseMT.py

@@ -1,5 +1,5 @@
 from SimPEG import SolverLU as SimpegSolver, PropMaps, Utils, mkvc, sp, np
-from SimPEG.EM.FDEM.ProblemFDEM import BaseFDEMProblem
+from SimPEG.EM.FDEM.FDEM import BaseFDEMProblem
 from SurveyMT import Survey, Data
 from FieldsMT import BaseMTFields
 

SimPEG/MT/SrcMT.py

@@ -86,7 +86,7 @@ class polxy_1Dprimary(BaseMTSrc):
         Get the electrical field source
         """
         e_p = self.ePrimary(problem)
-        Map_sigma_p = Maps.SurjectVertical1D(problem.mesh)
+        Map_sigma_p = Maps.Vertical1DMap(problem.mesh)
         sigma_p = Map_sigma_p._transform(self.sigma1d)
         # Make mass matrix
         # Note: M(sig) - M(sig_p) = M(sig - sig_p)
@@ -163,7 +163,7 @@ class polxy_3Dprimary(BaseMTSrc):
         Get the electrical field source
         """
         e_p = self.ePrimary(problem)
-        Map_sigma_p = Maps.SurjectVertical1D(problem.mesh)
+        Map_sigma_p = Maps.Vertical1DMap(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/Utils/dataUtils.py

@@ -19,7 +19,7 @@ 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 +44,19 @@ def rotateData(MTdata, rotAngle):
     return MT.Data.fromRecArray(outRec)
 
 
-def appResPhs(freq, z):
+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)
     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 )))))
 
-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:
@@ -70,7 +70,7 @@ def makeAnalyticSolution(mesh, model, elev, freqs):
     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

SimPEG/MT/Utils/ediFilesUtils.py

@@ -7,16 +7,17 @@ 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:
     """
     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)
 
@@ -25,8 +26,8 @@ class EDIimporter:
     comps = None
 
     # Hidden properties
-    _outEPSG = None # Project info
-    _2out = None    # The projection operator
+    _outEPSG = None
+    _2out = None
 
 
     def __init__(self, EDIfilesList, compList=None, outEPSG=None):
@@ -112,12 +113,6 @@ 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()

SimPEG/Maps.py

@@ -41,8 +41,8 @@ class IdentityMap(object):
             If this is a meshless mapping (i.e. nP is defined independently)
             the shape will be the the shape (nP,nP).
 
-            :rtype: tuple
-            :return: shape of the operator as a tuple (int,int)
+            :rtype: (int,int)
+            :return: shape of the operator as a tuple
         """
         if self._nP is not None:
             return (self.nP, self.nP)
@@ -86,7 +86,7 @@ class IdentityMap(object):
             The derivative of the transformation.
 
             :param numpy.array m: model
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: derivative of transformed model
 
         """
@@ -216,7 +216,7 @@ class ExpMap(IdentityMap):
     def deriv(self, m):
         """
             :param numpy.array m: model
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: derivative of transformed model
 
             The *transform* changes the model into the physical property.
@@ -366,7 +366,7 @@ class SurjectVertical1D(IdentityMap):
     def deriv(self, m):
         """
             :param numpy.array m: model
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: derivative of transformed model
         """
         repNum = self.mesh.vnC[:self.mesh.dim-1].prod()
@@ -427,7 +427,7 @@ class Surject2Dto3D(IdentityMap):
     def deriv(self, m):
         """
             :param numpy.array m: model
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: derivative of transformed model
         """
         inds = self * np.arange(self.nP)
@@ -502,9 +502,7 @@ class InjectActiveCells(IdentityMap):
         if Utils.isScalar(valInactive):
             self.valInactive = np.ones(self.nC)*float(valInactive)
         else:
-            self.valInactive = np.ones(self.nC)
-            self.valInactive[self.indInactive] = valInactive.copy()
-            
+            self.valInactive = valInactive.copy()
         self.valInactive[self.indActive] = 0
 
         inds = np.nonzero(self.indActive)[0]
@@ -535,6 +533,83 @@ class ActiveCells(InjectActiveCells):
             FutureWarning)
         InjectActiveCells.__init__(self, mesh, indActive, valInactive, nC)
 
+class InjectActiveCellsTopo(IdentityMap):
+    """
+        Active model parameters. Extend for cells on topography to air cell (only works for tensor mesh)
+
+    """
+
+    indActive   = None #: Active Cells
+    valInactive = None #: Values of inactive Cells
+    nC          = None #: Number of cells in the full model
+
+    def __init__(self, mesh, indActive, nC=None):
+        self.mesh  = mesh
+
+        self.nC = nC or mesh.nC
+
+        if indActive.dtype is not bool:
+            z = np.zeros(self.nC,dtype=bool)
+            z[indActive] = True
+            indActive = z
+        self.indActive = indActive
+
+        self.indInactive = np.logical_not(indActive)
+        inds = np.nonzero(self.indActive)[0]
+        self.P = sp.csr_matrix((np.ones(inds.size),(inds, range(inds.size))), shape=(self.nC, self.nP))
+
+    @property
+    def shape(self):
+        return (self.nC, self.nP)
+
+    @property
+    def nP(self):
+        """Number of parameters in the model."""
+        return self.indActive.sum()
+
+    def _transform(self, m):
+        val_temp = np.zeros(self.mesh.nC)
+        val_temp[self.indActive] = m
+        valInactive = np.zeros(self.mesh.nC)
+        #1D
+        if self.mesh.dim == 1:
+            z_temp = self.mesh.gridCC
+            val_temp[~self.indActive] = val_temp[np.argmax(z_temp[self.indActive])]
+        #2D
+        elif self.mesh.dim == 2:
+            act_temp = self.indActive.reshape((self.mesh.nCx, self.mesh.nCy), order = 'F')
+            val_temp = val_temp.reshape((self.mesh.nCx, self.mesh.nCy), order = 'F')
+            y_temp = self.mesh.gridCC[:,1].reshape((self.mesh.nCx, self.mesh.nCy), order = 'F')
+            for i in range(self.mesh.nCx):
+                act_tempx = act_temp[i,:] == 1
+                val_temp[i,~act_tempx] = val_temp[i,np.argmax(y_temp[i,act_tempx])]
+            valInactive[~self.indActive] = Utils.mkvc(val_temp)[~self.indActive]
+        #3D
+        elif self.mesh.dim == 3:
+            act_temp = self.indActive.reshape((self.mesh.nCx*self.mesh.nCy, self.mesh.nCz), order = 'F')
+            val_temp = val_temp.reshape((self.mesh.nCx*self.mesh.nCy, self.mesh.nCz), order = 'F')
+            z_temp = self.mesh.gridCC[:,2].reshape((self.mesh.nCx*self.mesh.nCy, self.mesh.nCz), order = 'F')
+            for i in range(self.mesh.nCx*self.mesh.nCy):
+                act_tempxy = act_temp[i,:] == 1
+                val_temp[i,~act_tempxy] = val_temp[i,np.argmax(z_temp[i,act_tempxy])]
+            valInactive[~self.indActive] = Utils.mkvc(val_temp)[~self.indActive]
+
+        self.valInactive = valInactive
+
+        return self.P*m + self.valInactive
+
+    def inverse(self, D):
+        return self.P.T*D
+
+    def deriv(self, m):
+        return self.P
+
+class ActiveCellsTopo(InjectActiveCellsTopo):
+    def __init__(self, mesh, indActive, valInactive, nC=None):
+        warnings.warn(
+            "`ActiveCellsTopo` is deprecated and will be removed in future versions. Use `InjectActiveCellsTopo` instead",
+            FutureWarning)
+        InjectActiveCellsTopo.__init__(self, mesh, indActive, valInactive, nC)
 
 class Weighting(IdentityMap):
     """
@@ -684,29 +759,15 @@ class PolyMap(IdentityMap):
 
             m = [\sigma_1, \sigma_2, c]
 
-        Can take in an actInd vector to account for topography.
-
     """
-    def __init__(self, mesh, order, logSigma=True, normal='X', actInd = None):
+    def __init__(self, mesh, order, logSigma=True, normal='X'):
         IdentityMap.__init__(self, mesh)
         self.logSigma = logSigma
         self.order = order
         self.normal = normal
-        self.actInd = actInd
-
-        if getattr(self, 'actInd', None) is None:
-            self.actInd = range(self.mesh.nC)
-            self.nC = self.mesh.nC
-
-        else:
-            self.nC = len(self.actInd)
 
     slope = 1e4
 
-    @property
-    def shape(self):
-        return (self.nC, self.nP)
-
     @property
     def nP(self):
         if np.isscalar(self.order):
@@ -724,8 +785,8 @@ class PolyMap(IdentityMap):
             sig1, sig2 = np.exp(sig1), np.exp(sig2)
         #2D
         if self.mesh.dim == 2:
-            X = self.mesh.gridCC[self.actInd,0]
-            Y = self.mesh.gridCC[self.actInd,1]
+            X = self.mesh.gridCC[:,0]
+            Y = self.mesh.gridCC[:,1]
             if self.normal =='X':
                 f = polynomial.polyval(Y, c) - X
             elif self.normal =='Y':
@@ -734,9 +795,9 @@ class PolyMap(IdentityMap):
                 raise(Exception("Input for normal = X or Y or Z"))
         #3D
         elif self.mesh.dim == 3:
-            X = self.mesh.gridCC[self.actInd,0]
-            Y = self.mesh.gridCC[self.actInd,1]
-            Z = self.mesh.gridCC[self.actInd,2]
+            X = self.mesh.gridCC[:,0]
+            Y = self.mesh.gridCC[:,1]
+            Z = self.mesh.gridCC[:,2]
             if self.normal =='X':
                 f = polynomial.polyval2d(Y, Z, c.reshape((self.order[0]+1,self.order[1]+1))) - X
             elif self.normal =='Y':
@@ -745,7 +806,6 @@ class PolyMap(IdentityMap):
                 f = polynomial.polyval2d(X, Y, c.reshape((self.order[0]+1,self.order[1]+1))) - Z
             else:
                 raise(Exception("Input for normal = X or Y or Z"))
-
         else:
             raise(Exception("Only supports 2D"))
 
@@ -759,8 +819,8 @@ class PolyMap(IdentityMap):
             sig1, sig2 = np.exp(sig1), np.exp(sig2)
         #2D
         if self.mesh.dim == 2:
-            X = self.mesh.gridCC[self.actInd,0]
-            Y = self.mesh.gridCC[self.actInd,1]
+            X = self.mesh.gridCC[:,0]
+            Y = self.mesh.gridCC[:,1]
 
             if self.normal =='X':
                 f = polynomial.polyval(Y, c) - X
@@ -772,9 +832,9 @@ class PolyMap(IdentityMap):
                 raise(Exception("Input for normal = X or Y or Z"))
         #3D
         elif self.mesh.dim == 3:
-            X = self.mesh.gridCC[self.actInd,0]
-            Y = self.mesh.gridCC[self.actInd,1]
-            Z = self.mesh.gridCC[self.actInd,2]
+            X = self.mesh.gridCC[:,0]
+            Y = self.mesh.gridCC[:,1]
+            Z = self.mesh.gridCC[:,2]
 
             if self.normal =='X':
                 f = polynomial.polyval2d(Y, Z, c.reshape((self.order[0]+1,self.order[1]+1))) - X

SimPEG/Mesh/BaseMesh.py

@@ -7,8 +7,8 @@ class BaseMesh(object):
     BaseMesh does all the counting you don't want to do.
     BaseMesh should be inherited by meshes with a regular structure.
 
-    :param numpy.array n: (or list) number of cells in each direction (dim, )
-    :param numpy.array x0: (or list) Origin of the mesh (dim, )
+    :param numpy.array,list n: number of cells in each direction (dim, )
+    :param numpy.array,list x0: Origin of the mesh (dim, )
 
     """
 
@@ -34,8 +34,8 @@ class BaseMesh(object):
         """
         Origin of the mesh
 
-        :rtype: numpy.array
-        :return: x0, (dim, )
+        :rtype: numpy.array (dim, )
+        :return: x0
         """
         return self._x0
 
@@ -116,8 +116,8 @@ class BaseMesh(object):
         """
         Total number of edges in each direction
 
-        :rtype: numpy.array
-        :return: [nEx, nEy, nEz], (dim, )
+        :rtype: numpy.array (dim, )
+        :return: [nEx, nEy, nEz]
 
         .. plot::
             :include-source:
@@ -173,8 +173,8 @@ class BaseMesh(object):
         """
         Total number of faces in each direction
 
-        :rtype: numpy.array
-        :return: [nFx, nFy, nFz], (dim, )
+        :rtype: numpy.array (dim, )
+        :return: [nFx, nFy, nFz]
 
         .. plot::
             :include-source:
@@ -200,8 +200,8 @@ class BaseMesh(object):
         """
         Face Normals
 
-        :rtype: numpy.array
-        :return: normals, (sum(nF), dim)
+        :rtype: numpy.array (sum(nF), dim)
+        :return: normals
         """
         if self.dim == 2:
             nX = np.c_[np.ones(self.nFx), np.zeros(self.nFx)]
@@ -218,8 +218,8 @@ class BaseMesh(object):
         """
         Edge Tangents
 
-        :rtype: numpy.array
-        :return: normals, (sum(nE), dim)
+        :rtype: numpy.array (sum(nE), dim)
+        :return: normals
         """
         if self.dim == 2:
             tX = np.c_[np.ones(self.nEx), np.zeros(self.nEx)]
@@ -236,9 +236,8 @@ class BaseMesh(object):
         Given a vector, fV, in cartesian coordinates, this will project it onto the mesh using the normals
 
         :param numpy.array fV: face vector with shape (nF, dim)
-        :rtype: numpy.array
-        :return: projected face vector, (nF, )
-
+        :rtype: numpy.array with shape (nF, )
+        :return: projected face vector
         """
         assert isinstance(fV, np.ndarray), 'fV must be an ndarray'
         assert len(fV.shape) == 2 and fV.shape[0] == self.nF and fV.shape[1] == self.dim, 'fV must be an ndarray of shape (nF x dim)'
@@ -249,9 +248,8 @@ class BaseMesh(object):
         Given a vector, eV, in cartesian coordinates, this will project it onto the mesh using the tangents
 
         :param numpy.array eV: edge vector with shape (nE, dim)
-        :rtype: numpy.array
-        :return: projected edge vector, (nE, )
-
+        :rtype: numpy.array with shape (nE, )
+        :return: projected edge vector
         """
         assert isinstance(eV, np.ndarray), 'eV must be an ndarray'
         assert len(eV.shape) == 2 and eV.shape[0] == self.nE and eV.shape[1] == self.dim, 'eV must be an ndarray of shape (nE x dim)'
@@ -297,7 +295,7 @@ class BaseRectangularMesh(BaseMesh):
         """
         Total number of cells in each direction
 
-        :rtype: numpy.array
+        :rtype: numpy.array (dim, )
         :return: [nCx, nCy, nCz]
         """
         return np.array([x for x in [self.nCx, self.nCy, self.nCz] if not x is None])
@@ -337,7 +335,7 @@ class BaseRectangularMesh(BaseMesh):
         """
         Total number of nodes in each direction
 
-        :rtype: numpy.array
+        :rtype: numpy.array (dim, )
         :return: [nNx, nNy, nNz]
         """
         return np.array([x for x in [self.nNx, self.nNy, self.nNz] if not x is None])
@@ -347,7 +345,7 @@ class BaseRectangularMesh(BaseMesh):
         """
         Number of x-edges in each direction
 
-        :rtype: numpy.array
+        :rtype: numpy.array (dim, )
         :return: vnEx
         """
         return np.array([x for x in [self.nCx, self.nNy, self.nNz] if not x is None])
@@ -357,7 +355,7 @@ class BaseRectangularMesh(BaseMesh):
         """
         Number of y-edges in each direction
 
-        :rtype: numpy.array
+        :rtype: numpy.array (dim, )
         :return: vnEy or None if dim < 2
         """
         return None if self.dim < 2 else np.array([x for x in [self.nNx, self.nCy, self.nNz] if not x is None])
@@ -367,7 +365,7 @@ class BaseRectangularMesh(BaseMesh):
         """
         Number of z-edges in each direction
 
-        :rtype: numpy.array
+        :rtype: numpy.array (dim, )
         :return: vnEz or None if dim < 3
         """
         return None if self.dim < 3 else np.array([x for x in [self.nNx, self.nNy, self.nCz] if not x is None])
@@ -377,7 +375,7 @@ class BaseRectangularMesh(BaseMesh):
         """
         Number of x-faces in each direction
 
-        :rtype: numpy.array
+        :rtype: numpy.array (dim, )
         :return: vnFx
         """
         return np.array([x for x in [self.nNx, self.nCy, self.nCz] if not x is None])
@@ -387,7 +385,7 @@ class BaseRectangularMesh(BaseMesh):
         """
         Number of y-faces in each direction
 
-        :rtype: numpy.array
+        :rtype: numpy.array (dim, )
         :return: vnFy or None if dim < 2
         """
         return None if self.dim < 2 else np.array([x for x in [self.nCx, self.nNy, self.nCz] if not x is None])
@@ -397,7 +395,7 @@ class BaseRectangularMesh(BaseMesh):
         """
         Number of z-faces in each direction
 
-        :rtype: numpy.array
+        :rtype: numpy.array (dim, )
         :return: vnFz or None if dim < 3
         """
         return None if self.dim < 3 else np.array([x for x in [self.nCx, self.nCy, self.nNz] if not x is None])

SimPEG/Mesh/CurvilinearMesh.py

@@ -2,7 +2,6 @@ from SimPEG import Utils, np
 from BaseMesh import BaseRectangularMesh
 from DiffOperators import DiffOperators
 from InnerProducts import InnerProducts
-from View import CurvView
 
 # Some helper functions.
 length2D = lambda x: (x[:, 0]**2 + x[:, 1]**2)**0.5
@@ -11,7 +10,7 @@ normalize2D = lambda x: x/np.kron(np.ones((1, 2)), Utils.mkvc(length2D(x), 2))
 normalize3D = lambda x: x/np.kron(np.ones((1, 3)), Utils.mkvc(length3D(x), 2))
 
 
-class CurvilinearMesh(BaseRectangularMesh, DiffOperators, InnerProducts, CurvView):
+class CurvilinearMesh(BaseRectangularMesh, DiffOperators, InnerProducts):
     """
     CurvilinearMesh is a mesh class that deals with curvilinear meshes.
 
@@ -331,6 +330,102 @@ class CurvilinearMesh(BaseRectangularMesh, DiffOperators, InnerProducts, CurvVie
 
 
 
+    #############################################
+    #            Plotting Functions             #
+    #############################################
+
+    def plotGrid(self, ax=None, nodes=False, faces=False, centers=False, edges=False, lines=True,  showIt=False):
+        """Plot the nodal, cell-centered and staggered grids for 1,2 and 3 dimensions.
+
+
+        .. plot::
+            :include-source:
+
+            from SimPEG import Mesh, Utils
+            X, Y = Utils.exampleLrmGrid([3,3],'rotate')
+            M = Mesh.CurvilinearMesh([X, Y])
+            M.plotGrid(showIt=True)
+
+        """
+        import matplotlib.pyplot as plt
+        import matplotlib
+        from mpl_toolkits.mplot3d import Axes3D
+        mkvc = Utils.mkvc
+
+        axOpts = {'projection':'3d'} if self.dim == 3 else {}
+        if ax is None: ax = plt.subplot(111, **axOpts)
+
+        NN = self.r(self.gridN, 'N', 'N', 'M')
+        if self.dim == 2:
+
+            if lines:
+                X1 = np.c_[mkvc(NN[0][:-1, :]), mkvc(NN[0][1:, :]), mkvc(NN[0][:-1, :])*np.nan].flatten()
+                Y1 = np.c_[mkvc(NN[1][:-1, :]), mkvc(NN[1][1:, :]), mkvc(NN[1][:-1, :])*np.nan].flatten()
+
+                X2 = np.c_[mkvc(NN[0][:, :-1]), mkvc(NN[0][:, 1:]), mkvc(NN[0][:, :-1])*np.nan].flatten()
+                Y2 = np.c_[mkvc(NN[1][:, :-1]), mkvc(NN[1][:, 1:]), mkvc(NN[1][:, :-1])*np.nan].flatten()
+
+                X = np.r_[X1, X2]
+                Y = np.r_[Y1, Y2]
+
+                ax.plot(X, Y, 'b-')
+            if centers:
+                ax.plot(self.gridCC[:,0],self.gridCC[:,1],'ro')
+
+            # Nx = self.r(self.normals, 'F', 'Fx', 'V')
+            # Ny = self.r(self.normals, 'F', 'Fy', 'V')
+            # Tx = self.r(self.tangents, 'E', 'Ex', 'V')
+            # Ty = self.r(self.tangents, 'E', 'Ey', 'V')
+
+            # ax.plot(self.gridN[:, 0], self.gridN[:, 1], 'bo')
+
+            # nX = np.c_[self.gridFx[:, 0], self.gridFx[:, 0] + Nx[0]*length, self.gridFx[:, 0]*np.nan].flatten()
+            # nY = np.c_[self.gridFx[:, 1], self.gridFx[:, 1] + Nx[1]*length, self.gridFx[:, 1]*np.nan].flatten()
+            # ax.plot(self.gridFx[:, 0], self.gridFx[:, 1], 'rs')
+            # ax.plot(nX, nY, 'r-')
+
+            # nX = np.c_[self.gridFy[:, 0], self.gridFy[:, 0] + Ny[0]*length, self.gridFy[:, 0]*np.nan].flatten()
+            # nY = np.c_[self.gridFy[:, 1], self.gridFy[:, 1] + Ny[1]*length, self.gridFy[:, 1]*np.nan].flatten()
+            # #ax.plot(self.gridFy[:, 0], self.gridFy[:, 1], 'gs')
+            # ax.plot(nX, nY, 'g-')
+
+            # tX = np.c_[self.gridEx[:, 0], self.gridEx[:, 0] + Tx[0]*length, self.gridEx[:, 0]*np.nan].flatten()
+            # tY = np.c_[self.gridEx[:, 1], self.gridEx[:, 1] + Tx[1]*length, self.gridEx[:, 1]*np.nan].flatten()
+            # ax.plot(self.gridEx[:, 0], self.gridEx[:, 1], 'r^')
+            # ax.plot(tX, tY, 'r-')
+
+            # nX = np.c_[self.gridEy[:, 0], self.gridEy[:, 0] + Ty[0]*length, self.gridEy[:, 0]*np.nan].flatten()
+            # nY = np.c_[self.gridEy[:, 1], self.gridEy[:, 1] + Ty[1]*length, self.gridEy[:, 1]*np.nan].flatten()
+            # #ax.plot(self.gridEy[:, 0], self.gridEy[:, 1], 'g^')
+            # ax.plot(nX, nY, 'g-')
+
+        elif self.dim == 3:
+            X1 = np.c_[mkvc(NN[0][:-1, :, :]), mkvc(NN[0][1:, :, :]), mkvc(NN[0][:-1, :, :])*np.nan].flatten()
+            Y1 = np.c_[mkvc(NN[1][:-1, :, :]), mkvc(NN[1][1:, :, :]), mkvc(NN[1][:-1, :, :])*np.nan].flatten()
+            Z1 = np.c_[mkvc(NN[2][:-1, :, :]), mkvc(NN[2][1:, :, :]), mkvc(NN[2][:-1, :, :])*np.nan].flatten()
+
+            X2 = np.c_[mkvc(NN[0][:, :-1, :]), mkvc(NN[0][:, 1:, :]), mkvc(NN[0][:, :-1, :])*np.nan].flatten()
+            Y2 = np.c_[mkvc(NN[1][:, :-1, :]), mkvc(NN[1][:, 1:, :]), mkvc(NN[1][:, :-1, :])*np.nan].flatten()
+            Z2 = np.c_[mkvc(NN[2][:, :-1, :]), mkvc(NN[2][:, 1:, :]), mkvc(NN[2][:, :-1, :])*np.nan].flatten()
+
+            X3 = np.c_[mkvc(NN[0][:, :, :-1]), mkvc(NN[0][:, :, 1:]), mkvc(NN[0][:, :, :-1])*np.nan].flatten()
+            Y3 = np.c_[mkvc(NN[1][:, :, :-1]), mkvc(NN[1][:, :, 1:]), mkvc(NN[1][:, :, :-1])*np.nan].flatten()
+            Z3 = np.c_[mkvc(NN[2][:, :, :-1]), mkvc(NN[2][:, :, 1:]), mkvc(NN[2][:, :, :-1])*np.nan].flatten()
+
+            X = np.r_[X1, X2, X3]
+            Y = np.r_[Y1, Y2, Y3]
+            Z = np.r_[Z1, Z2, Z3]
+
+            ax.plot(X, Y, 'b', zs=Z)
+            ax.set_zlabel('x3')
+
+        ax.grid(True)
+        ax.set_xlabel('x1')
+        ax.set_ylabel('x2')
+
+        if showIt: plt.show()
+
+
 if __name__ == '__main__':
     nc = 5
     h1 = np.cumsum(np.r_[0, np.ones(nc)/(nc)])

SimPEG/Mesh/CylMesh.py

@@ -68,8 +68,8 @@ class CylMesh(BaseTensorMesh, BaseRectangularMesh, InnerProducts, CylView):
         """
         Number of x-faces in each direction
 
-        :rtype: numpy.array 
-        :return: vnFx, (dim, )
+        :rtype: numpy.array (dim, )
+        :return: vnFx
         """
         return self.vnC
 
@@ -78,8 +78,8 @@ class CylMesh(BaseTensorMesh, BaseRectangularMesh, InnerProducts, CylView):
         """
         Number of y-edges in each direction
 
-        :rtype: numpy.array 
-        :return: vnEy or None if dim < 2, (dim, )
+        :rtype: numpy.array (dim, )
+        :return: vnEy or None if dim < 2
         """
         nNx = self.nNx if self.isSymmetric else self.nNx - 1
         return np.r_[nNx, self.nCy, self.nNz]
@@ -89,8 +89,8 @@ class CylMesh(BaseTensorMesh, BaseRectangularMesh, InnerProducts, CylView):
         """
         Number of z-edges in each direction
 
-        :rtype: numpy.array 
-        :return: vnEz or None if nCy > 1, (dim, )
+        :rtype: numpy.array (dim, )
+        :return: vnEz or None if nCy > 1
         """
         if self.isSymmetric:
             return np.r_[self.nNx, self.nNy, self.nCz]
@@ -330,7 +330,7 @@ class CylMesh(BaseTensorMesh, BaseRectangularMesh, InnerProducts, CylView):
                 raise NotImplementedError('wrapping in the averaging is not yet implemented')
         return self._aveF2CCV
 
-    def getInterpolationMatCartMesh(self, Mrect, locType='CC', locTypeTo=None):
+    def getInterpolationMatCartMesh(self, Mrect, locType='CC'):
         """
             Takes a cartesian mesh and returns a projection to translate onto the cartesian grid.
         """
@@ -338,22 +338,19 @@ class CylMesh(BaseTensorMesh, BaseRectangularMesh, InnerProducts, CylView):
         assert self.isSymmetric, "Currently we have not taken into account other projections for more complicated CylMeshes"
 
 
-        if locTypeTo is None:
-            locTypeTo = locType
-
         if locType == 'F':
             # do this three times for each component
-            X = self.getInterpolationMatCartMesh(Mrect, locType='Fx', locTypeTo=locTypeTo+'x')
-            Y = self.getInterpolationMatCartMesh(Mrect, locType='Fy', locTypeTo=locTypeTo+'y')
-            Z = self.getInterpolationMatCartMesh(Mrect, locType='Fz', locTypeTo=locTypeTo+'z')
+            X = self.getInterpolationMatCartMesh(Mrect, locType='Fx')
+            Y = self.getInterpolationMatCartMesh(Mrect, locType='Fy')
+            Z = self.getInterpolationMatCartMesh(Mrect, locType='Fz')
             return sp.vstack((X,Y,Z))
         if locType == 'E':
-            X = self.getInterpolationMatCartMesh(Mrect, locType='Ex', locTypeTo=locTypeTo+'x')
-            Y = self.getInterpolationMatCartMesh(Mrect, locType='Ey', locTypeTo=locTypeTo+'y')
-            Z = spzeros(getattr(Mrect, 'n' + locTypeTo + 'z'), self.nE)
+            X = self.getInterpolationMatCartMesh(Mrect, locType='Ex')
+            Y = self.getInterpolationMatCartMesh(Mrect, locType='Ey')
+            Z = spzeros(Mrect.nEz, self.nE)
             return sp.vstack((X,Y,Z))
 
-        grid = getattr(Mrect, 'grid' + locTypeTo)
+        grid = getattr(Mrect, 'grid' + locType)
         # This is unit circle stuff, 0 to 2*pi, starting at x-axis, rotating counter clockwise in an x-y slice
         theta = - np.arctan2(grid[:,0] - self.cartesianOrigin[0], grid[:,1] - self.cartesianOrigin[1]) + np.pi/2
         theta[theta < 0] += np.pi*2.0
@@ -369,7 +366,7 @@ class CylMesh(BaseTensorMesh, BaseRectangularMesh, InnerProducts, CylView):
                         'Ex': Mrect.tangents[:Mrect.nEx,:],
                         'Ey': Mrect.tangents[Mrect.nEx:(Mrect.nEx+Mrect.nEy),:],
                         'Ez': Mrect.tangents[-Mrect.nEz:,:],
-                    }[locTypeTo]
+                    }[locType]
             if 'F' in locType:
                 normals = np.c_[np.cos(theta), np.sin(theta), np.zeros(theta.size)]
                 proj = ( normals * dotMe ).sum(axis=1)

SimPEG/Mesh/DiffOperators.py

@@ -307,28 +307,24 @@ class DiffOperators(object):
         return BC
     _cellGradBC_list = 'neumann'
 
-    def _cellGradStencil(self):
-        BC = self.setCellGradBC(self._cellGradBC_list)
-        n = self.vnC
-        if(self.dim == 1):
-            G = ddxCellGrad(n[0], BC[0])
-        elif(self.dim == 2):
-            G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC[0]))
-            G2 = sp.kron(ddxCellGrad(n[1], BC[1]), speye(n[0]))
-            G = sp.vstack((G1, G2), format="csr")
-        elif(self.dim == 3):
-            G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC[0]))
-            G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC[1]), speye(n[0]))
-            G3 = kron3(ddxCellGrad(n[2], BC[2]), speye(n[1]), speye(n[0]))
-            G = sp.vstack((G1, G2, G3), format="csr")
-        return G
-
     def cellGrad():
         doc = "The cell centered Gradient, takes you to cell faces."
 
         def fget(self):
             if(self._cellGrad is None):
-                G = self._cellGradStencil()
+                BC = self.setCellGradBC(self._cellGradBC_list)
+                n = self.vnC
+                if(self.dim == 1):
+                    G = ddxCellGrad(n[0], BC[0])
+                elif(self.dim == 2):
+                    G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC[0]))
+                    G2 = sp.kron(ddxCellGrad(n[1], BC[1]), speye(n[0]))
+                    G = sp.vstack((G1, G2), format="csr")
+                elif(self.dim == 3):
+                    G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC[0]))
+                    G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC[1]), speye(n[0]))
+                    G3 = kron3(ddxCellGrad(n[2], BC[2]), speye(n[1]), speye(n[0]))
+                    G = sp.vstack((G1, G2, G3), format="csr")
                 # Compute areas of cell faces & volumes
                 S = self.area
                 V = self.aveCC2F*self.vol  # Average volume between adjacent cells
@@ -365,24 +361,19 @@ class DiffOperators(object):
     _cellGradBC = None
     cellGradBC = property(**cellGradBC())
 
-    def _cellGradxStencil(self):
-        BC = ['neumann', 'neumann']
-        n = self.vnC
-        if(self.dim == 1):
-            G1 = ddxCellGrad(n[0], BC)
-        elif(self.dim == 2):
-            G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC))
-        elif(self.dim == 3):
-            G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC))
-        return G1
-
-
     def cellGradx():
         doc = "Cell centered Gradient in the x dimension. Has neumann boundary conditions."
 
         def fget(self):
             if getattr(self, '_cellGradx', None) is None:
-                G1 = self._cellGradxStencil()
+                BC = ['neumann', 'neumann']
+                n = self.vnC
+                if(self.dim == 1):
+                    G1 = ddxCellGrad(n[0], BC)
+                elif(self.dim == 2):
+                    G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC))
+                elif(self.dim == 3):
+                    G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC))
                 # Compute areas of cell faces & volumes
                 V = self.aveCC2F*self.vol
                 L = self.r(self.area/V, 'F','Fx', 'V')
@@ -391,22 +382,17 @@ class DiffOperators(object):
         return locals()
     cellGradx = property(**cellGradx())
 
-    def _cellGradyStencil(self):
-        if self.dim < 2: return None
-        BC = ['neumann', 'neumann']
-        n = self.vnC
-        if(self.dim == 2):
-            G2 = sp.kron(ddxCellGrad(n[1], BC), speye(n[0]))
-        elif(self.dim == 3):
-            G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC), speye(n[0]))
-        return G2
-
     def cellGrady():
         doc = "Cell centered Gradient in the x dimension. Has neumann boundary conditions."
         def fget(self):
             if self.dim < 2: return None
             if getattr(self, '_cellGrady', None) is None:
-                G2 = self._cellGradyStencil()
+                BC = ['neumann', 'neumann']
+                n = self.vnC
+                if(self.dim == 2):
+                    G2 = sp.kron(ddxCellGrad(n[1], BC), speye(n[0]))
+                elif(self.dim == 3):
+                    G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC), speye(n[0]))
                 # Compute areas of cell faces & volumes
                 V = self.aveCC2F*self.vol
                 L = self.r(self.area/V, 'F','Fy', 'V')
@@ -415,19 +401,14 @@ class DiffOperators(object):
         return locals()
     cellGrady = property(**cellGrady())
 
-    def _cellGradzStencil(self):
-        if self.dim < 3: return None
-        BC = ['neumann', 'neumann']
-        n = self.vnC
-        G3 = kron3(ddxCellGrad(n[2], BC), speye(n[1]), speye(n[0]))
-        return G3
-
     def cellGradz():
         doc = "Cell centered Gradient in the x dimension. Has neumann boundary conditions."
         def fget(self):
             if self.dim < 3: return None
             if getattr(self, '_cellGradz', None) is None:
-                G3 = self._cellGradzStencil()
+                BC = ['neumann', 'neumann']
+                n = self.vnC
+                G3 = kron3(ddxCellGrad(n[2], BC), speye(n[1]), speye(n[0]))
                 # Compute areas of cell faces & volumes
                 V = self.aveCC2F*self.vol
                 L = self.r(self.area/V, 'F','Fz', 'V')
@@ -584,67 +565,7 @@ class DiffOperators(object):
 
         return Pbc, Pin, Pout
 
-    def getBCProjWF_simple(self, discretization='CC'):
-        """
 
-        The weak form boundary condition projection matrices
-        when mixed boundary condition is used
-
-
-        """
-
-        if discretization is not 'CC':
-            raise NotImplementedError('Boundary conditions only implemented for CC discretization.')
-
-        def projBC(n):
-            ij = ([0,n], [0,1])
-            vals = [0,0]
-            vals[0] = 1
-            vals[1] = 1
-            return sp.csr_matrix((vals, ij), shape=(n+1,2))
-
-        def projDirichlet(n, bc):
-            bc = checkBC(bc)
-            ij = ([0,n], [0,1])
-            vals = [0,0]
-            if(bc[0] == 'dirichlet'):
-                vals[0] = -1
-            if(bc[1] == 'dirichlet'):
-                vals[1] = 1
-            return sp.csr_matrix((vals, ij), shape=(n+1,2))
-
-        BC = [['dirichlet','dirichlet'],['dirichlet','dirichlet'],['dirichlet','dirichlet']]
-        n = self.vnC
-        indF = self.faceBoundaryInd
-        if(self.dim == 1):
-            Pbc = projDirichlet(n[0], BC[0])
-            B = projBC(n[0])
-            indF = indF[0] | indF[1]
-            Pbc = Pbc*sdiag(self.area[indF])
-
-        elif(self.dim == 2):
-            Pbc1 = sp.kron(speye(n[1]), projDirichlet(n[0], BC[0]))
-            Pbc2 = sp.kron(projDirichlet(n[1], BC[1]), speye(n[0]))
-            Pbc = sp.block_diag((Pbc1, Pbc2), format="csr")
-            B1 = sp.kron(speye(n[1]), projBC(n[0]))
-            B2 = sp.kron(projBC(n[1]), speye(n[0]))
-            B = sp.block_diag((B1, B2), format="csr")
-            indF = np.r_[(indF[0] | indF[1]), (indF[2] | indF[3])]
-            Pbc = Pbc*sdiag(self.area[indF])
-
-        elif(self.dim == 3):
-            Pbc1 = kron3(speye(n[2]), speye(n[1]), projDirichlet(n[0], BC[0]))
-            Pbc2 = kron3(speye(n[2]), projDirichlet(n[1], BC[1]), speye(n[0]))
-            Pbc3 = kron3(projDirichlet(n[2], BC[2]), speye(n[1]), speye(n[0]))
-            Pbc = sp.block_diag((Pbc1, Pbc2, Pbc3), format="csr")
-            B1 = kron3(speye(n[2]), speye(n[1]), projBC(n[0]))
-            B2 = kron3(speye(n[2]), projBC(n[1]), speye(n[0]))
-            B3 = kron3(projBC(n[2]), speye(n[1]), speye(n[0]))
-            B = sp.block_diag((B1, B2, B3), format="csr")
-            indF = np.r_[(indF[0] | indF[1]), (indF[2] | indF[3]), (indF[4] | indF[5])]
-            Pbc = Pbc*sdiag(self.area[indF])
-
-        return Pbc, B.T
     # --------------- Averaging ---------------------
 
     @property

SimPEG/Mesh/InnerProducts.py

@@ -16,7 +16,7 @@ class InnerProducts(object):
             :param bool invProp: inverts the material property
             :param bool invMat: inverts the matrix
             :param bool doFast: do a faster implementation if available.
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: M, the inner product matrix (nF, nF)
         """
         return self._getInnerProduct('F', prop=prop, invProp=invProp, invMat=invMat, doFast=doFast)
@@ -27,7 +27,7 @@ class InnerProducts(object):
             :param bool invProp: inverts the material property
             :param bool invMat: inverts the matrix
             :param bool doFast: do a faster implementation if available.
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: M, the inner product matrix (nE, nE)
         """
         return self._getInnerProduct('E', prop=prop, invProp=invProp, invMat=invMat, doFast=doFast)
@@ -39,7 +39,7 @@ class InnerProducts(object):
             :param bool invProp: inverts the material property
             :param bool invMat: inverts the matrix
             :param bool doFast: do a faster implementation if available.
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: M, the inner product matrix (nE, nE)
         """
         assert projType in ['F', 'E'], "projType must be 'F' for faces or 'E' for edges"
@@ -115,12 +115,13 @@ class InnerProducts(object):
             :param bool doFast: do a faster implementation if available.
             :param bool invProp: inverts the material property
             :param bool invMat: inverts the matrix
+            :rtype: function
             :return: dMdmu(u), the derivative of the inner product matrix (u)
 
             Given u, dMdmu returns (nF, nC*nA)
 
-            :param numpy.ndarray u: vector that multiplies dMdmu
-            :rtype: scipy.sparse.csr_matrix
+            :param np.ndarray u: vector that multiplies dMdmu
+            :rtype: scipy.csr_matrix
             :return: dMdmu, the derivative of the inner product matrix for a certain u
         """
         return self._getInnerProductDeriv(prop, 'F', doFast=doFast, invProp=invProp, invMat=invMat)
@@ -132,7 +133,7 @@ class InnerProducts(object):
             :param bool doFast: do a faster implementation if available.
             :param bool invProp: inverts the material property
             :param bool invMat: inverts the matrix
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: dMdm, the derivative of the inner product matrix (nE, nC*nA)
         """
         return self._getInnerProductDeriv(prop, 'E', doFast=doFast, invProp=invProp, invMat=invMat)
@@ -144,7 +145,7 @@ class InnerProducts(object):
             :param bool doFast: do a faster implementation if available.
             :param bool invProp: inverts the material property
             :param bool invMat: inverts the matrix
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: dMdm, the derivative of the inner product matrix (nE, nC*nA)
         """
         fast = None
@@ -168,7 +169,7 @@ class InnerProducts(object):
             :param numpy.array v: vector to multiply (required in the general implementation)
             :param list P: list of projection matrices
             :param str projType: 'F' for faces 'E' for edges
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: dMdm, the derivative of the inner product matrix (n, nC*nA)
         """
         assert projType in ['F', 'E'], "projType must be 'F' for faces or 'E' for edges"

SimPEG/Mesh/MeshIO.py

@@ -6,11 +6,13 @@ class TensorMeshIO(object):
     @classmethod
     def readUBC(TensorMesh, fileName):
         """
-            Read UBC GIF 3D tensor mesh and generate 3D TensorMesh in SimPEG.
+            Read UBC GIF 3DTensor mesh and generate 3D Tensor mesh in simpegTD
 
-            :param string fileName: path to the UBC GIF mesh file
-            :rtype: TensorMesh
-            :return: The tensor mesh for the fileName.
+            Input:
+            :param fileName, path to the UBC GIF mesh file
+
+            Output:
+            :param SimPEG TensorMesh object
         """
 
         # Interal function to read cell size lines for the UBC mesh files.
@@ -19,9 +21,10 @@ class TensorMeshIO(object):
                 if '*' in seg:
                     st = seg
                     sp = seg.split('*')
-                    re = int(sp[0])*(' ' + sp[1])
+                    re = np.array(sp[0],dtype=int)*(' ' + sp[1])
                     line = line.replace(st,re.strip())
             return np.array(line.split(),dtype=float)
+
         # Read the file as line strings, remove lines with comment = !
         msh = np.genfromtxt(fileName,delimiter='\n',dtype=np.str,comments='!')
 
@@ -46,9 +49,11 @@ class TensorMeshIO(object):
             Read VTK Rectilinear (vtr xml file) and return SimPEG Tensor mesh and model
 
             Input:
-            :param string fileName: path to the vtr model file to read
-            :rtype: tuple
-            :return: (TensorMesh, modelDictionary)
+            :param vtrFileName, path to the vtr model file to write to
+
+            Output:
+            :return SimPEG TensorMesh object
+            :return SimPEG model dictionary
 
         """
         # Import
@@ -98,8 +103,9 @@ class TensorMeshIO(object):
         Makes and saves a VTK rectilinear file (vtr) for a simpeg Tensor mesh and model.
 
         Input:
-        :param string fileName: path to the output vtk file
-        :param dict models: dictionary of numpy.array - Name('s) and array('s). Match number of cells
+        :param str, path to the output vtk file
+        :param mesh, SimPEG TensorMesh object - mesh to be transfer to VTK
+        :param models, dictionary of numpy.array - Name('s) and array('s). Match number of cells
 
         """
         # Import
@@ -157,9 +163,12 @@ class TensorMeshIO(object):
         """
             Read UBC 3DTensor mesh model and generate 3D Tensor mesh model in simpeg
 
-            :param string fileName: path to the UBC GIF mesh file to read
-            :rtype: numpy.ndarray
-            :return: model with TensorMesh ordered
+            Input:
+            :param fileName, path to the UBC GIF mesh file to read
+            :param mesh, TensorMesh object, mesh that coresponds to the model
+
+            Output:
+            :return numpy array, model with TensorMesh ordered
         """
         f = open(fileName, 'r')
         model = np.array(map(float, f.readlines()))
@@ -175,7 +184,8 @@ class TensorMeshIO(object):
             Writes a model associated with a SimPEG TensorMesh
             to a UBC-GIF format model file.
 
-            :param string fileName: File to write to
+            :param str fileName: File to write to
+            :param simpeg.Mesh.TensorMesh mesh: The mesh
             :param numpy.ndarray model: The model
         """
 
@@ -192,8 +202,8 @@ class TensorMeshIO(object):
         """
             Writes a SimPEG TensorMesh to a UBC-GIF format mesh file.
 
-            :param string fileName: File to write to
-            :param dict models: A dictionary of the models
+            :param str fileName: File to write to
+            :param simpeg.Mesh.TensorMesh mesh: The mesh
 
         """
         assert mesh.dim == 3
@@ -222,8 +232,9 @@ class TreeMeshIO(object):
         """
             Write UBC ocTree mesh and model files from a simpeg ocTree mesh and model.
 
-            :param string fileName: File to write to
-            :param dict models: The models in a dictionary, where the keys is the name of the of the model file
+            :param str fileName: File to write to
+            :param simpeg.Mesh.TreeMesh mesh: The mesh
+            :param dictionary models: The models in a dictionary, where the keys is the name of the of the model file
         """
 
         # Calculate information to write in the file.
@@ -276,9 +287,10 @@ class TreeMeshIO(object):
 
             Input:
             :param str meshFile: path to the UBC GIF OcTree mesh file to read
-            :rtype: SimPEG.Mesh.TreeMesh
-            :return: The octree mesh
 
+            Output:
+            :return SimPEG.Mesh.TreeMesh mesh: The octree mesh
+            :return list of ndarray's: models as a list of numpy array's
         """
 
         ## Read the file lines
@@ -324,9 +336,11 @@ class TreeMeshIO(object):
         """
             Read UBC OcTree model and get vector
 
-            :param string fileName: path to the UBC GIF model file to read
-            :rtype: numpy.ndarray
-            :return: OcTree model
+            Input:
+            :param fileName, path to the UBC GIF model file to read
+
+            Output:
+            :return numpy array, OcTree model
         """
 
         if type(fileName) is list:

SimPEG/Mesh/TensorMesh.py

@@ -198,8 +198,8 @@ class BaseTensorMesh(BaseMesh):
         Determines if a set of points are inside a mesh.
 
         :param numpy.ndarray pts: Location of points to test
-        :rtype numpy.ndarray:
-        :return: inside, numpy array of booleans
+        :rtype numpy.ndarray
+        :return inside, numpy array of booleans
         """
         pts = Utils.asArray_N_x_Dim(pts, self.dim)
 
@@ -221,7 +221,7 @@ class BaseTensorMesh(BaseMesh):
 
         :param numpy.ndarray loc: Location of points to interpolate to
         :param str locType: What to interpolate (see below)
-        :rtype: scipy.sparse.csr_matrix
+        :rtype: scipy.sparse.csr.csr_matrix
         :return: M, the interpolation matrix
 
         locType can be::
@@ -289,7 +289,7 @@ class BaseTensorMesh(BaseMesh):
             :param bool returnP: returns the projection matrices
             :param bool invProp: inverts the material property
             :param bool invMat: inverts the matrix
-            :rtype: scipy.sparse.csr_matrix
+            :rtype: scipy.csr_matrix
             :return: M, the inner product matrix (nF, nF)
         """
         assert projType in ['F', 'E'], "projType must be 'F' for faces or 'E' for edges"

SimPEG/Mesh/TreeMesh.py

@@ -1875,7 +1875,7 @@ class TreeMesh(BaseTensorMesh, InnerProducts, TreeMeshIO):
 
         :param numpy.ndarray locs: Location of points to interpolate to
         :param str locType: What to interpolate (see below)
-        :rtype: scipy.sparse.csr_matrix
+        :rtype: scipy.sparse.csr.csr_matrix
         :return: M, the interpolation matrix
 
         locType can be::
@@ -2131,16 +2131,10 @@ class TreeMesh(BaseTensorMesh, InnerProducts, TreeMeshIO):
     def plotSlice(self, v, vType='CC',
         normal='Z', ind=None, grid=True, view='real',
         ax=None, clim=None, showIt=False,
-        pcolorOpts=None,
-        streamOpts=None,
-        gridOpts=None):
+        pcolorOpts={},
+        streamOpts={'color':'k'},
+        gridOpts={'color':'k', 'alpha':0.5}):
 
-        if pcolorOpts is None:
-            pcolorOpts = {}
-        if streamOpts is None:
-            streamOpts = {'color':'k'}
-        if gridOpts is None:
-            gridOpts = {'color':'k', 'alpha':0.5}
         assert vType in ['CC','F','E']
         assert self.dim == 3
 

SimPEG/Mesh/View.py

@@ -42,9 +42,9 @@ class TensorView(object):
 
     def plotImage(self, v, vType='CC', grid=False, view='real',
               ax=None, clim=None, showIt=False,
-              pcolorOpts=None,
-              streamOpts=None,
-              gridOpts=None,
+              pcolorOpts={},
+              streamOpts={'color':'k'},
+              gridOpts={'color':'k'},
               numbering=True, annotationColor='w'
               ):
         """
@@ -84,12 +84,6 @@ class TensorView(object):
             M.plotImage(v, annotationColor='k', showIt=True)
 
         """
-        if pcolorOpts is None:
-            pcolorOpts = {}
-        if streamOpts is None:
-            streamOpts = {'color':'k'}
-        if gridOpts is None:
-            gridOpts = {'color':'k'}
 
         if ax is None:
             fig = plt.figure()
@@ -180,9 +174,9 @@ class TensorView(object):
     def plotSlice(self, v, vType='CC',
                   normal='Z', ind=None, grid=False, view='real',
                   ax=None, clim=None, showIt=False,
-                  pcolorOpts=None,
-                  streamOpts=None,
-                  gridOpts=None
+                  pcolorOpts={},
+                  streamOpts={'color':'k'},
+                  gridOpts={'color':'k', 'alpha':0.5}
                   ):
 
         """
@@ -203,12 +197,6 @@ class TensorView(object):
             M.plotSlice(M.cellGrad*b, 'F', view='vec', grid=True, showIt=True, pcolorOpts={'alpha':0.8})
 
         """
-        if pcolorOpts is None:
-            pcolorOpts = {}
-        if streamOpts is None:
-            streamOpts = {'color':'k'}
-        if gridOpts is None:
-            gridOpts = {'color':'k', 'alpha':0.5}
         if type(vType) in [list, tuple]:
             assert ax is None, "cannot specify an axis to plot on with this function."
             fig, axs = plt.subplots(1,len(vType))
@@ -218,7 +206,7 @@ class TensorView(object):
             return out
         viewOpts = ['real','imag','abs','vec']
         normalOpts = ['X', 'Y', 'Z']
-        vTypeOpts = ['CC', 'CCv','N','F','E','Fx','Fy','Fz','E','Ex','Ey','Ez']
+        vTypeOpts = ['CC', 'CCv','F','E','Fx','Fy','Fz','E','Ex','Ey','Ez']
 
         # Some user error checking
         assert vType in vTypeOpts, "vType must be in ['%s']" % "','".join(vTypeOpts)
@@ -301,17 +289,11 @@ class TensorView(object):
 
     def _plotImage2D(self, v, vType='CC', grid=False, view='real',
               ax=None, clim=None, showIt=False,
-              pcolorOpts=None,
-              streamOpts=None,
-              gridOpts=None
+              pcolorOpts={},
+              streamOpts={'color':'k'},
+              gridOpts={'color':'k'}
               ):
 
-        if pcolorOpts is None:
-            pcolorOpts = {}
-        if streamOpts is None:
-            streamOpts = {'color':'k'}
-        if gridOpts is None:
-            gridOpts = {'color':'k'}
         vTypeOptsCC = ['N','CC','Fx','Fy','Ex','Ey']
         vTypeOptsV = ['CCv','F','E']
         vTypeOpts = vTypeOptsCC + vTypeOptsV
@@ -552,8 +534,7 @@ class CurvView(object):
     def __init__(self):
         pass
 
-
-    def plotGrid(self, ax=None, nodes=False, faces=False, centers=False, edges=False, lines=True,  showIt=False):
+    def plotGrid(self, length=0.05, showIt=False):
         """Plot the nodal, cell-centered and staggered grids for 1,2 and 3 dimensions.
 
 
@@ -561,63 +542,60 @@ class CurvView(object):
             :include-source:
 
             from SimPEG import Mesh, Utils
-            X, Y = Utils.exampleLrmGrid([3,3],'rotate')
+            X, Y = Utils.exampleCurvGird([3,3],'rotate')
             M = Mesh.CurvilinearMesh([X, Y])
             M.plotGrid(showIt=True)
 
         """
-        import matplotlib.pyplot as plt
-        import matplotlib
-        from mpl_toolkits.mplot3d import Axes3D
-
-        axOpts = {'projection':'3d'} if self.dim == 3 else {}
-        if ax is None: ax = plt.subplot(111, **axOpts)
-
         NN = self.r(self.gridN, 'N', 'N', 'M')
         if self.dim == 2:
+            fig = plt.figure(2)
+            fig.clf()
+            ax = plt.subplot(111)
+            X1 = np.c_[mkvc(NN[0][:-1, :]), mkvc(NN[0][1:, :]), mkvc(NN[0][:-1, :])*np.nan].flatten()
+            Y1 = np.c_[mkvc(NN[1][:-1, :]), mkvc(NN[1][1:, :]), mkvc(NN[1][:-1, :])*np.nan].flatten()
 
-            if lines:
-                X1 = np.c_[mkvc(NN[0][:-1, :]), mkvc(NN[0][1:, :]), mkvc(NN[0][:-1, :])*np.nan].flatten()
-                Y1 = np.c_[mkvc(NN[1][:-1, :]), mkvc(NN[1][1:, :]), mkvc(NN[1][:-1, :])*np.nan].flatten()
+            X2 = np.c_[mkvc(NN[0][:, :-1]), mkvc(NN[0][:, 1:]), mkvc(NN[0][:, :-1])*np.nan].flatten()
+            Y2 = np.c_[mkvc(NN[1][:, :-1]), mkvc(NN[1][:, 1:]), mkvc(NN[1][:, :-1])*np.nan].flatten()
 
-                X2 = np.c_[mkvc(NN[0][:, :-1]), mkvc(NN[0][:, 1:]), mkvc(NN[0][:, :-1])*np.nan].flatten()
-                Y2 = np.c_[mkvc(NN[1][:, :-1]), mkvc(NN[1][:, 1:]), mkvc(NN[1][:, :-1])*np.nan].flatten()
+            X = np.r_[X1, X2]
+            Y = np.r_[Y1, Y2]
 
-                X = np.r_[X1, X2]
-                Y = np.r_[Y1, Y2]
+            plt.plot(X, Y)
 
-                ax.plot(X, Y, 'b-')
-            if centers:
-                ax.plot(self.gridCC[:,0],self.gridCC[:,1],'ro')
+            plt.hold(True)
+            Nx = self.r(self.normals, 'F', 'Fx', 'V')
+            Ny = self.r(self.normals, 'F', 'Fy', 'V')
+            Tx = self.r(self.tangents, 'E', 'Ex', 'V')
+            Ty = self.r(self.tangents, 'E', 'Ey', 'V')
 
-            # Nx = self.r(self.normals, 'F', 'Fx', 'V')
-            # Ny = self.r(self.normals, 'F', 'Fy', 'V')
-            # Tx = self.r(self.tangents, 'E', 'Ex', 'V')
-            # Ty = self.r(self.tangents, 'E', 'Ey', 'V')
+            plt.plot(self.gridN[:, 0], self.gridN[:, 1], 'bo')
 
-            # ax.plot(self.gridN[:, 0], self.gridN[:, 1], 'bo')
+            nX = np.c_[self.gridFx[:, 0], self.gridFx[:, 0] + Nx[0]*length, self.gridFx[:, 0]*np.nan].flatten()
+            nY = np.c_[self.gridFx[:, 1], self.gridFx[:, 1] + Nx[1]*length, self.gridFx[:, 1]*np.nan].flatten()
+            plt.plot(self.gridFx[:, 0], self.gridFx[:, 1], 'rs')
+            plt.plot(nX, nY, 'r-')
 
-            # nX = np.c_[self.gridFx[:, 0], self.gridFx[:, 0] + Nx[0]*length, self.gridFx[:, 0]*np.nan].flatten()
-            # nY = np.c_[self.gridFx[:, 1], self.gridFx[:, 1] + Nx[1]*length, self.gridFx[:, 1]*np.nan].flatten()
-            # ax.plot(self.gridFx[:, 0], self.gridFx[:, 1], 'rs')
-            # ax.plot(nX, nY, 'r-')
+            nX = np.c_[self.gridFy[:, 0], self.gridFy[:, 0] + Ny[0]*length, self.gridFy[:, 0]*np.nan].flatten()
+            nY = np.c_[self.gridFy[:, 1], self.gridFy[:, 1] + Ny[1]*length, self.gridFy[:, 1]*np.nan].flatten()
+            #plt.plot(self.gridFy[:, 0], self.gridFy[:, 1], 'gs')
+            plt.plot(nX, nY, 'g-')
 
-            # nX = np.c_[self.gridFy[:, 0], self.gridFy[:, 0] + Ny[0]*length, self.gridFy[:, 0]*np.nan].flatten()
-            # nY = np.c_[self.gridFy[:, 1], self.gridFy[:, 1] + Ny[1]*length, self.gridFy[:, 1]*np.nan].flatten()
-            # #ax.plot(self.gridFy[:, 0], self.gridFy[:, 1], 'gs')
-            # ax.plot(nX, nY, 'g-')
+            tX = np.c_[self.gridEx[:, 0], self.gridEx[:, 0] + Tx[0]*length, self.gridEx[:, 0]*np.nan].flatten()
+            tY = np.c_[self.gridEx[:, 1], self.gridEx[:, 1] + Tx[1]*length, self.gridEx[:, 1]*np.nan].flatten()
+            plt.plot(self.gridEx[:, 0], self.gridEx[:, 1], 'r^')
+            plt.plot(tX, tY, 'r-')
 
-            # tX = np.c_[self.gridEx[:, 0], self.gridEx[:, 0] + Tx[0]*length, self.gridEx[:, 0]*np.nan].flatten()
-            # tY = np.c_[self.gridEx[:, 1], self.gridEx[:, 1] + Tx[1]*length, self.gridEx[:, 1]*np.nan].flatten()
-            # ax.plot(self.gridEx[:, 0], self.gridEx[:, 1], 'r^')
-            # ax.plot(tX, tY, 'r-')
-
-            # nX = np.c_[self.gridEy[:, 0], self.gridEy[:, 0] + Ty[0]*length, self.gridEy[:, 0]*np.nan].flatten()
-            # nY = np.c_[self.gridEy[:, 1], self.gridEy[:, 1] + Ty[1]*length, self.gridEy[:, 1]*np.nan].flatten()
-            # #ax.plot(self.gridEy[:, 0], self.gridEy[:, 1], 'g^')
-            # ax.plot(nX, nY, 'g-')
+            nX = np.c_[self.gridEy[:, 0], self.gridEy[:, 0] + Ty[0]*length, self.gridEy[:, 0]*np.nan].flatten()
+            nY = np.c_[self.gridEy[:, 1], self.gridEy[:, 1] + Ty[1]*length, self.gridEy[:, 1]*np.nan].flatten()
+            #plt.plot(self.gridEy[:, 0], self.gridEy[:, 1], 'g^')
+            plt.plot(nX, nY, 'g-')
+            plt.axis('equal')
 
         elif self.dim == 3:
+            fig = plt.figure(3)
+            fig.clf()
+            ax = fig.add_subplot(111, projection='3d')
             X1 = np.c_[mkvc(NN[0][:-1, :, :]), mkvc(NN[0][1:, :, :]), mkvc(NN[0][:-1, :, :])*np.nan].flatten()
             Y1 = np.c_[mkvc(NN[1][:-1, :, :]), mkvc(NN[1][1:, :, :]), mkvc(NN[1][:-1, :, :])*np.nan].flatten()
             Z1 = np.c_[mkvc(NN[2][:-1, :, :]), mkvc(NN[2][1:, :, :]), mkvc(NN[2][:-1, :, :])*np.nan].flatten()
@@ -634,50 +612,16 @@ class CurvView(object):
             Y = np.r_[Y1, Y2, Y3]
             Z = np.r_[Z1, Z2, Z3]
 
-            ax.plot(X, Y, 'b', zs=Z)
+            plt.plot(X, Y, 'b', zs=Z)
             ax.set_zlabel('x3')
 
         ax.grid(True)
+        ax.hold(False)
         ax.set_xlabel('x1')
         ax.set_ylabel('x2')
 
         if showIt: plt.show()
 
-    def plotImage(self, I, ax=None, showIt=False, grid=False, clim=None):
-        if self.dim == 3: raise NotImplementedError('This is not yet done!')
-
-        import matplotlib.pyplot as plt
-        import matplotlib
-        from mpl_toolkits.mplot3d import Axes3D
-        import matplotlib.colors as colors
-        import matplotlib.cm as cmx
-
-        if ax is None: ax = plt.subplot(111)
-        jet = cm = plt.get_cmap('jet')
-        cNorm  = colors.Normalize(
-            vmin=I.min() if clim is None else clim[0],
-            vmax=I.max() if clim is None else clim[1])
-
-        scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet)
-        # ax.set_xlim((self.x0[0], self.h[0].sum()))
-        # ax.set_ylim((self.x0[1], self.h[1].sum()))
-
-        Nx = self.r(self.gridN[:,0],'N','N','M')
-        Ny = self.r(self.gridN[:,1],'N','N','M')
-        cell = self.r(I,'CC','CC','M')
-
-        for ii in range(self.nCx):
-            for jj in range(self.nCy):
-                I = [ii,ii+1,ii+1,ii]
-                J = [jj,jj,jj+1,jj+1]
-                ax.add_patch(plt.Polygon(np.c_[Nx[I,J],Ny[I,J]], facecolor=scalarMap.to_rgba(cell[ii,jj]), edgecolor='k' if grid else 'none'))
-
-        scalarMap._A = []  # http://stackoverflow.com/questions/8342549/matplotlib-add-colorbar-to-a-sequence-of-line-plots
-        ax.set_xlabel('x')
-        ax.set_ylabel('y')
-        if showIt: plt.show()
-        return [scalarMap]
-
 
 if __name__ == '__main__':
     from SimPEG import *

SimPEG/Optimization.py

@@ -131,7 +131,7 @@ class Minimize(object):
 
         Minimizes the function (evalFunction) starting at the location x0.
 
-        :param callable evalFunction: function handle that evaluates: f, g, H = F(x)
+        :param def evalFunction: function handle that evaluates: f, g, H = F(x)
         :param numpy.ndarray x0: starting location
         :rtype: numpy.ndarray
         :return: x, the last iterate of the optimization algorithm
@@ -372,8 +372,8 @@ class Minimize(object):
             Else, a modifySearchDirectionBreak call is preformed.
 
             :param numpy.ndarray p: searchDirection
-            :rtype: tuple
-            :return: (xt, passLS) numpy.ndarray, bool
+            :rtype: numpy.ndarray,bool
+            :return: (xt, passLS)
         """
         # Projected Armijo linesearch
         self._LS_t = 1
@@ -408,8 +408,8 @@ class Minimize(object):
             evalFunction returns a False indicating the break was not caught.
 
             :param numpy.ndarray p: searchDirection
-            :rtype: tuple
-            :return: (xt, breakCaught) numpy.ndarray, bool
+            :rtype: numpy.ndarray,bool
+            :return: (xt, breakCaught)
         """
         self.printDone(inLS=True)
         print 'The linesearch got broken. Boo.'
@@ -888,8 +888,6 @@ class ProjectedGNCG(BFGS, Minimize, Remember):
     maxIterCG = 5
     tolCG = 1e-1
 
-    stepOffBoundsFact = 0.1 # perturbation of the inactive set off the bounds
-
     lower = -np.inf
     upper = np.inf
 
@@ -992,20 +990,4 @@ class ProjectedGNCG(BFGS, Minimize, Remember):
                     cgFlag = 1
                 # End CG Iterations
 
-            # Take a gradient step on the active cells if exist
-            if temp != self.xc.size:
-
-                rhs_a = (Active) * -self.g
-
-                dm_i = max( abs( delx ) )
-                dm_a = max( abs(rhs_a) )
-
-                # perturb inactive set off of bounds so that they are included in the step
-                delx = delx + self.stepOffBoundsFact * (rhs_a * dm_i / dm_a)
-
-
-            # Only keep gradients going in the right direction on the active set
-            indx = ((self.xc<=self.lower) & (delx < 0)) | ((self.xc>=self.upper) & (delx > 0))
-            delx[indx] = 0.
-
-            return delx
+            return delx

SimPEG/PropMaps.py

@@ -74,7 +74,7 @@ class Property(object):
                 if linkedMap is None:
                     return None
                 linkMap = linkMapClass(None) * linkedMap
-                m = getattr(self, '%sModel'%linkName)
+                m = getattr(self, '%s'%linkName)
                 return linkMap.deriv( m )
 
             m = getattr(self, '%sModel'%prop.name)
@@ -187,7 +187,7 @@ class _PropMapMetaClass(type):
             attrs[attr + 'Model'] = prop._getModelProperty()
             attrs[attr + 'Deriv'] = prop._getModelDerivProperty()
 
-        return type('PropModel', (PropModel, ), attrs)
+        return type(name.replace('PropMap', 'PropModel'), (PropModel, ), attrs)
 
 
 class PropMap(object):
@@ -239,7 +239,7 @@ class PropMap(object):
             setattr(self, '%sMap'%name, mapping)
             setattr(self, '%sIndex'%name, slices.get(name, slice(nP, nP + mapping.nP)))
             nP += mapping.nP
-        self.nP = nP
+        self.nP = nP 
 
     @property
     def defaultInvProp(self):

SimPEG/Survey.py

@@ -311,6 +311,7 @@ class BaseSurvey(object):
         if f is None: f = self.prob.fields(m)
         return Utils.mkvc(self.eval(f))
 
+
     @Utils.count
     def eval(self, f):
         """eval(f)
@@ -321,7 +322,7 @@ class BaseSurvey(object):
 
                 d_\\text{pred} = \mathbf{P} f(m)
         """
-        raise NotImplementedError('eval is not yet implemented.')
+        raise NotImplemented('eval is not yet implemented.')
 
     @Utils.count
     def evalDeriv(self, f):
@@ -333,7 +334,7 @@ class BaseSurvey(object):
 
                 \\frac{\partial d_\\text{pred}}{\partial u} = \mathbf{P}
         """
-        raise NotImplementedError('eval is not yet implemented.')
+        raise NotImplemented('eval is not yet implemented.')
 
     @Utils.count
     def residual(self, m, f=None):

SimPEG/Tests.py

@@ -237,7 +237,7 @@ def checkDerivative(fctn, x0, num=7, plotIt=True, dx=None, expectedOrder=2, tole
         Compares error decay of 0th and 1st order Taylor approximation at point
         x0 for a randomized search direction.
 
-        :param callable fctn: function handle
+        :param lambda fctn: function handle
         :param numpy.array x0: point at which to check derivative
         :param int num: number of times to reduce step length, h
         :param bool plotIt: if you would like to plot

SimPEG/Utils/ModelBuilder.py

@@ -7,11 +7,11 @@ def addBlock(gridCC, modelCC, p0, p1, blockProp):
     """
         Add a block to an exsisting cell centered model, modelCC
 
-        :param numpy.array gridCC: mesh.gridCC is the cell centered grid
-        :param numpy.array modelCC: cell centered model
-        :param numpy.array p0: bottom, southwest corner of block
-        :param numpy.array p1: top, northeast corner of block
-        :blockProp float blockProp: property to assign to the model
+        :param numpy.array, gridCC: mesh.gridCC is the cell centered grid
+        :param numpy.array, modelCC: cell centered model
+        :param numpy.array, p0: bottom, southwest corner of block
+        :param numpy.array, p1: top, northeast corner of block
+        :blockProp float, blockProp: property to assign to the model 
 
         :return numpy.array, modelBlock: model with block
     """
@@ -88,14 +88,12 @@ def getIndicesBlock(p0,p1,ccMesh):
     # Return a tuple
     return ind
 
-def defineBlock(ccMesh,p0,p1,vals=None):
+def defineBlock(ccMesh,p0,p1,vals=[0,1]):
     """
         Build a block with the conductivity specified by condVal.  Returns an array.
         vals[0]  conductivity of the block
         vals[1]  conductivity of the ground
     """
-    if vals is None:
-        vals = [0,1]
     sigma = np.zeros(ccMesh.shape[0]) + vals[1]
     ind   = getIndicesBlock(p0,p1,ccMesh)
 
@@ -103,11 +101,7 @@ def defineBlock(ccMesh,p0,p1,vals=None):
 
     return mkvc(sigma)
 
-def defineElipse(ccMesh, center=None, anisotropy=None, slope=10., theta=0.):
-    if center is None:
-        center = [0,0,0]
-    if anisotropy is None:
-        anisotropy = [1,1,1]
+def defineElipse(ccMesh, center=[0,0,0], anisotropy=[1,1,1], slope=10., theta=0.):
     G = ccMesh.copy()
     dim = ccMesh.shape[1]
     for i in range(dim):
@@ -147,7 +141,7 @@ def getIndicesSphere(center,radius,ccMesh):
 
     if dimMesh == 1:
        # Define the reference points
-
+        
         ind  = np.abs(center[0] - ccMesh[:,0]) < radius
 
     elif dimMesh == 2:
@@ -162,7 +156,7 @@ def getIndicesSphere(center,radius,ccMesh):
     # Return a tuple
     return ind
 
-def defineTwoLayers(ccMesh,depth,vals=None):
+def defineTwoLayers(ccMesh,depth,vals=[0,1]):
     """
     Define a two layered model.  Depth of the first layer must be specified.
     CondVals vector with the conductivity values of the layers.  Eg:
@@ -173,8 +167,6 @@ def defineTwoLayers(ccMesh,depth,vals=None):
         0                          depth                                 zf
              1st layer                       2nd layer
     """
-    if vals is None:
-        vals = [0,1]
     sigma = np.zeros(ccMesh.shape[0]) + vals[1]
 
     dim = np.size(ccMesh[0,:])
@@ -222,14 +214,14 @@ def layeredModel(ccMesh, layerTops, layerValues):
 
         :param numpy.array ccMesh: cell-centered mesh
         :param numpy.array layerTops: z-locations of the tops of each layer
-        :param numpy.array layerValue: values of the property to assign for each layer (starting at the top)
+        :param numpy.array layerValue: values of the property to assign for each layer (starting at the top) 
         :rtype: numpy.array
-        :return: M, layered model on the mesh
+        :return: M, layered model on the mesh 
     """
 
     descending = np.linalg.norm(sorted(layerTops, reverse=True) - layerTops) < 1e-20
 
-    # TODO: put an error check to make sure that there is an ordering... needs to work with inf elts
+    # TODO: put an error check to make sure that there is an ordering... needs to work with inf elts 
     # assert ascending or descending, "Layers must be listed in either ascending or descending order"
 
     # start from bottom up
@@ -253,21 +245,21 @@ def layeredModel(ccMesh, layerTops, layerValues):
     model = np.zeros(ccMesh.shape[0])
 
     for i, top in enumerate(layerTops):
-        zind = z <= top
+        zind = z <= top 
         model[zind] = layerValues[i]
 
-    return model
+    return model 
 
 
 
-def randomModel(shape, seed=None, anisotropy=None, its=100, bounds=None):
+def randomModel(shape, seed=None, anisotropy=None, its=100, bounds=[0,1]):
     """
         Create a random model by convolving a kernel with a
         uniformly distributed model.
 
-        :param tuple shape: shape of the model.
+        :param int,tuple shape: shape of the model.
         :param int seed: pick which model to produce, prints the seed if you don't choose.
-        :param numpy.ndarray anisotropy: this is the (3 x n) blurring kernel that is used.
+        :param numpy.ndarray,list anisotropy: this is the (3 x n) blurring kernel that is used.
         :param int its: number of smoothing iterations
         :param list bounds: bounds on the model, len(list) == 2
         :rtype: numpy.ndarray
@@ -284,8 +276,6 @@ def randomModel(shape, seed=None, anisotropy=None, its=100, bounds=None):
 
 
     """
-    if bounds is None:
-        bounds = [0,1]
 
     if seed is None:
         seed = np.random.randint(1e3)

SimPEG/Utils/SolverUtils.py

@@ -13,7 +13,7 @@ def _checkAccuracy(A, b, X, accuracyTol):
         warnings.warn(msg, RuntimeWarning)
 
 
-def SolverWrapD(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-6, name=None):
+def SolverWrapD(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-6):
     """
     Wraps a direct Solver.
 
@@ -72,11 +72,11 @@ def SolverWrapD(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-6, name=
         if factorize and hasattr(self.solver, 'clean'):
             return self.solver.clean()
 
-    return type(name if name is not None else fun.__name__, (object,), {"__init__": __init__, "clean": clean, "__mul__": __mul__})
+    return type(fun.__name__+'_Wrapped', (object,), {"__init__": __init__, "clean": clean, "__mul__": __mul__})
 
 
 
-def SolverWrapI(fun, checkAccuracy=True, accuracyTol=1e-5, name=None):
+def SolverWrapI(fun, checkAccuracy=True, accuracyTol=1e-5):
     """
     Wraps an iterative Solver.
 
@@ -128,13 +128,13 @@ def SolverWrapI(fun, checkAccuracy=True, accuracyTol=1e-5, name=None):
     def clean(self):
         pass
 
-    return type(name if name is not None else fun.__name__, (object,), {"__init__": __init__, "clean": clean, "__mul__": __mul__})
+    return type(fun.__name__+'_Wrapped', (object,), {"__init__": __init__, "clean": clean, "__mul__": __mul__})
 
 
 from scipy.sparse import linalg
-Solver   = SolverWrapD(linalg.spsolve, factorize=False, name="Solver")
-SolverLU = SolverWrapD(linalg.splu, factorize=True, name="SolverLU")
-SolverCG = SolverWrapI(linalg.cg, name="SolverCG")
+Solver   = SolverWrapD(linalg.spsolve, factorize=False)
+SolverLU = SolverWrapD(linalg.splu, factorize=True)
+SolverCG = SolverWrapI(linalg.cg)
 
 
 class SolverDiag(object):

SimPEG/Utils/__init__.py

@@ -7,4 +7,3 @@ from CounterUtils import *
 import ModelBuilder
 import SolverUtils
 from coordutils import *
-from modelutils import *

SimPEG/Utils/codeutils.py

@@ -55,10 +55,8 @@ def hook(obj, method, name=None, overwrite=False, silent=False):
         print 'Method '+name+' was not overwritten.'
 
 
-def setKwargs(obj, ignore=None,  **kwargs):
+def setKwargs(obj, ignore=[],  **kwargs):
     """Sets key word arguments (kwargs) that are present in the object, throw an error if they don't exist."""
-    if ignore is None:
-        ignore = []
     for attr in kwargs:
         if attr in ignore:
             continue

SimPEG/Utils/interputils.py

@@ -25,7 +25,7 @@ def interpmat(locs, x, y=None, z=None):
         :param numpy.ndarray x: Tensor vector of 1st dimension of grid.
         :param numpy.ndarray y: Tensor vector of 2nd dimension of grid. None by default.
         :param numpy.ndarray z: Tensor vector of 3rd dimension of grid. None by default.
-        :rtype: scipy.sparse.csr_matrix
+        :rtype: scipy.sparse.csr.csr_matrix
         :return: Interpolation matrix
 
         .. plot::

SimPEG/Utils/io_utils.py

@@ -1,137 +0,0 @@
-from SimPEG import np, Mesh
-import time as tm
-import vtk, vtk.util.numpy_support as npsup
-import re
-
-def read_GOCAD_ts(tsfile):
-    """
-
-    Read GOCAD triangulated surface (*.ts) file
-    INPUT:
-    tsfile: Triangulated surface
-
-    OUTPUT:
-    vrts : Array of vertices in XYZ coordinates [n x 3]
-    trgl : Array of index for triangles [m x 3]. The order of the vertices
-            is important and describes the normal
-            n = cross( (P2 - P1 ) , (P3 - P1) )
-
-    Author: @fourndo
-
-
-    .. note::
-
-        Remove all attributes from the GoCAD surface before exporting it!
-
-    """
-
-
-    fid = open(tsfile,'r')
-    line = fid.readline()
-
-    # Skip all the lines until the vertices
-    while re.match('TFACE',line)==None:
-        line = fid.readline()
-
-    line = fid.readline()
-    vrtx = []
-
-    # Run down all the vertices and save in array
-    while re.match('VRTX',line):
-        l_input  = re.split('[\s*]',line)
-        temp = np.array(l_input[2:5])
-        vrtx.append(temp.astype(np.float))
-
-        # Read next line
-        line = fid.readline()
-
-    vrtx = np.asarray(vrtx)
-
-    # Skip lines to the triangles
-    while re.match('TRGL',line)==None:
-        line = fid.readline()
-
-    # Run down the list of triangles
-    trgl = []
-
-    # Run down all the vertices and save in array
-    while re.match('TRGL',line):
-        l_input  = re.split('[\s*]',line)
-        temp = np.array(l_input[1:4])
-        trgl.append(temp.astype(np.int))
-
-        # Read next line
-        line = fid.readline()
-
-    trgl = np.asarray(trgl)
-
-    return vrtx, trgl
-
-def surface2inds(vrtx, trgl, mesh, boundaries=True, internal=True):
-    """"
-    Function to read gocad polystructure file and output indexes of mesh with in the structure.
-
-    """
-    # Adjust the index
-    trgl = trgl - 1
-
-    # Make vtk pts
-    ptsvtk = vtk.vtkPoints()
-    ptsvtk.SetData(npsup.numpy_to_vtk(vrtx,deep=1))
-
-    # Make the polygon connection
-    polys = vtk.vtkCellArray()
-    for face in trgl:
-        poly = vtk.vtkPolygon()
-        poly.GetPointIds().SetNumberOfIds(len(face))
-        for nrv, vert in enumerate(face):
-            poly.GetPointIds().SetId(nrv,vert)
-        polys.InsertNextCell(poly)
-
-    # Make the polydata, structure of connections and vrtx
-    polyData = vtk.vtkPolyData()
-    polyData.SetPoints(ptsvtk)
-    polyData.SetPolys(polys)
-
-    # Make implicit func
-    ImpDistFunc = vtk.vtkImplicitPolyDataDistance()
-    ImpDistFunc.SetInput(polyData)
-
-    # Convert the mesh
-    vtkMesh = vtk.vtkRectilinearGrid()
-    vtkMesh.SetDimensions(mesh.nNx,mesh.nNy,mesh.nNz)
-    vtkMesh.SetXCoordinates(npsup.numpy_to_vtk(mesh.vectorNx, deep=1))
-    vtkMesh.SetYCoordinates(npsup.numpy_to_vtk(mesh.vectorNy, deep=1))
-    vtkMesh.SetZCoordinates(npsup.numpy_to_vtk(mesh.vectorNz, deep=1))
-    # Add indexes
-    vtkInd = npsup.numpy_to_vtk(np.arange(mesh.nC), deep=1)
-    vtkInd.SetName('Index')
-    vtkMesh.GetCellData().AddArray(vtkInd)
-
-    extractImpDistRectGridFilt = vtk.vtkExtractGeometry() # Object constructor
-    extractImpDistRectGridFilt.SetImplicitFunction(ImpDistFunc) #
-    extractImpDistRectGridFilt.SetInputData(vtkMesh)
-
-    if boundaries is True:
-        extractImpDistRectGridFilt.ExtractBoundaryCellsOn()
-
-    else:
-        extractImpDistRectGridFilt.ExtractBoundaryCellsOff()
-
-    if internal is True:
-        extractImpDistRectGridFilt.ExtractInsideOn()
-
-    else:
-        extractImpDistRectGridFilt.ExtractInsideOff()
-
-    print "Extracting indices from grid..."
-    # Executing the pipe
-    extractImpDistRectGridFilt.Update()
-
-    # Get index inside
-    insideGrid = extractImpDistRectGridFilt.GetOutput()
-    insideGrid = npsup.vtk_to_numpy(insideGrid.GetCellData().GetArray('Index'))
-
-
-    # Return the indexes inside
-    return insideGrid

SimPEG/Utils/matutils.py

@@ -27,7 +27,7 @@ def mkvc(x, numDims=1):
 
     if isinstance(x, Zero):
         return x
-
+    
     assert isinstance(x, np.ndarray), "Vector must be a numpy array"
 
     if numDims == 1:
@@ -355,9 +355,9 @@ def diagEst(matFun, n, k=None, approach='Probing'):
         2. Ones : random +/- 1 entries
         3. Random : random vectors
 
-    :param callable matFun: takes a (numpy.array) and multiplies it by a matrix to estimate the diagonal
-    :param int n: size of the vector that should be used to compute matFun(v)
-    :param int k: number of vectors to be used to estimate the diagonal
+    :param lambda (numpy.array) matFun: matrix to estimate the diagonal of
+    :param int64 n: size of the vector that should be used to compute matFun(v)
+    :param int64 k: number of vectors to be used to estimate the diagonal
     :param str approach: approach to be used for getting vectors
     :rtype: numpy.array
     :return: est_diag(A)
@@ -422,9 +422,9 @@ class Zero(object):
     def __ge__(self, v):return 0 >= v
     def __gt__(self, v):return 0 > v
 
-    @property
+    @property 
     def transpose(self): return Zero()
-
+    
     @property
     def T(self): return Zero()
 

SimPEG/Utils/meshutils.py

@@ -83,7 +83,7 @@ def closestPoints(mesh, pts, gridLoc='CC'):
     """
         Move a list of points to the closest points on a grid.
 
-        :param BaseMesh mesh: The mesh
+        :param simpeg.Mesh.BaseMesh mesh: The mesh
         :param numpy.ndarray pts: Points to move
         :param string gridLoc: ['CC', 'N', 'Fx', 'Fy', 'Fz', 'Ex', 'Ex', 'Ey', 'Ez']
         :rtype: numpy.ndarray
@@ -104,20 +104,16 @@ def closestPoints(mesh, pts, gridLoc='CC'):
 
 def ExtractCoreMesh(xyzlim, mesh, meshType='tensor'):
     """
-    Extracts Core Mesh from Global mesh
-
-    :param numpy.ndarray xyzlim: 2D array [ndim x 2]
-    :param BaseMesh mesh: The mesh
-
-    This function ouputs::
-
-        - actind: corresponding boolean index from global to core
-        - meshcore: core SimPEG mesh
-
-    Warning: 1D and 2D has not been tested
+        Extracts Core Mesh from Global mesh
+        xyzlim: 2D array [ndim x 2]
+        mesh: SimPEG mesh
+        This function ouputs:
+            - actind: corresponding boolean index from global to core
+            - meshcore: core SimPEG mesh
+        Warning: 1D and 2D has not been tested
     """
     from SimPEG import Mesh
-    if mesh.dim == 1:
+    if mesh.dim ==1:
         xyzlim = xyzlim.flatten()
         xmin, xmax = xyzlim[0], xyzlim[1]
 
@@ -129,11 +125,11 @@ def ExtractCoreMesh(xyzlim, mesh, meshType='tensor'):
 
         x0 = [xc[0]-hx[0]*0.5, yc[0]-hy[0]*0.5]
 
-        meshCore = Mesh.TensorMesh([hx, hy], x0=x0)
+        meshCore = Mesh.TensorMesh([hx, hy] ,x0=x0)
 
         actind = (mesh.gridCC[:,0]>xmin) & (mesh.gridCC[:,0]<xmax)
 
-    elif mesh.dim == 2:
+    elif mesh.dim ==2:
         xmin, xmax = xyzlim[0,0], xyzlim[0,1]
         ymin, ymax = xyzlim[1,0], xyzlim[1,1]
 
@@ -148,12 +144,12 @@ def ExtractCoreMesh(xyzlim, mesh, meshType='tensor'):
 
         x0 = [xc[0]-hx[0]*0.5, yc[0]-hy[0]*0.5]
 
-        meshCore = Mesh.TensorMesh([hx, hy], x0=x0)
+        meshCore = Mesh.TensorMesh([hx, hy] ,x0=x0)
 
         actind = (mesh.gridCC[:,0]>xmin) & (mesh.gridCC[:,0]<xmax) \
                & (mesh.gridCC[:,1]>ymin) & (mesh.gridCC[:,1]<ymax) \
 
-    elif mesh.dim == 3:
+    elif mesh.dim==3:
         xmin, xmax = xyzlim[0,0], xyzlim[0,1]
         ymin, ymax = xyzlim[1,0], xyzlim[1,1]
         zmin, zmax = xyzlim[2,0], xyzlim[2,1]
@@ -172,7 +168,7 @@ def ExtractCoreMesh(xyzlim, mesh, meshType='tensor'):
 
         x0 = [xc[0]-hx[0]*0.5, yc[0]-hy[0]*0.5, zc[0]-hz[0]*0.5]
 
-        meshCore = Mesh.TensorMesh([hx, hy, hz], x0=x0)
+        meshCore = Mesh.TensorMesh([hx, hy, hz] ,x0=x0)
 
         actind = (mesh.gridCC[:,0]>xmin) & (mesh.gridCC[:,0]<xmax) \
                & (mesh.gridCC[:,1]>ymin) & (mesh.gridCC[:,1]<ymax) \

SimPEG/Utils/modelutils.py

@@ -1,63 +0,0 @@
-from matutils import mkvc, ndgrid
-import numpy as np
-
-def surface2ind_topo(mesh, topo, gridLoc='CC'):
-# def genActiveindfromTopo(mesh, topo):
-    """
-    Get active indices from topography
-    """
-
-
-    if mesh.dim == 3:
-        from scipy.interpolate import NearestNDInterpolator
-        Ftopo = NearestNDInterpolator(topo[:,:2], topo[:,2])
-
-        if gridLoc == 'CC':
-            XY = ndgrid(mesh.vectorCCx, mesh.vectorCCy)
-            Zcc = mesh.gridCC[:,2].reshape((np.prod(mesh.vnC[:2]), mesh.nCz), order='F')
-
-            gridTopo = Ftopo(XY)
-            actind = [gridTopo[ixy] <= Zcc[ixy,:] for ixy in range(np.prod(mesh.vnC[0]))]
-            actind = np.hstack(actind)
-
-        elif gridLoc == 'N':
-
-            XY = ndgrid(mesh.vectorNx, mesh.vectorNy)
-            gridTopo = Ftopo(XY).reshape(mesh.vnN[:2], order='F')
-
-            if mesh._meshType not in ['TENSOR', 'CYL', 'BASETENSOR']:
-                raise NotImplementedError('Nodal surface2ind_topo not implemented for %s mesh'%mesh._meshType)
-
-            Nz = mesh.vectorNz[1:] # TODO: this will only work for tensor meshes
-            actind = np.array([False]*mesh.nC).reshape(mesh.vnC, order='F')
-
-            for ii in range(mesh.nCx):
-                for jj in range(mesh.nCy):
-                     actind[ii,jj,:] = [np.all(gridTopo[ii:ii+2, jj:jj+2] >= Nz[kk]) for kk in range(len(Nz)) ]
-
-    elif mesh.dim == 2:
-        from scipy.interpolate import interp1d
-        Ftopo = interp1d(topo[:,0], topo[:,1])
-
-        if gridLoc == 'CC':
-            gridTopo = Ftopo(mesh.gridCC[:,0])
-            actind = mesh.gridCC[:,1] <= gridTopo
-
-        elif gridLoc == 'N':
-
-            gridTopo = Ftopo(mesh.vectorNx)
-            if mesh._meshType not in ['TENSOR', 'CYL', 'BASETENSOR']:
-                raise NotImplementedError('Nodal surface2ind_topo not implemented for %s mesh'%mesh._meshType)
-
-            Ny = mesh.vectorNy[1:] # TODO: this will only work for tensor meshes
-            actind = np.array([False]*mesh.nC).reshape(mesh.vnC, order='F')
-
-            for ii in range(mesh.nCx):
-                actind[ii,:] = [np.all(gridTopo[ii:ii+2] > Ny[kk]) for kk in range(len(Ny)) ]
-
-    else:
-        raise NotImplementedError('surface2ind_topo not implemented for 1D mesh')
-
-    return mkvc(actind)
-
-

SimPEG/__init__.py

@@ -15,7 +15,7 @@ import Directives
 import Inversion
 import Tests
 
-__version__   = '0.1.12'
+__version__   = '0.1.10'
 __author__    = 'Rowan Cockett'
 __license__   = 'MIT'
 __copyright__ = 'Copyright 2014 Rowan Cockett'

docs/Makefile

@@ -2,7 +2,7 @@
 #
 
 # You can set these variables from the command line.
-SPHINXOPTS    = -n -w warnings.txt
+SPHINXOPTS    =
 SPHINXBUILD   = sphinx-build
 PAPER         =
 BUILDDIR      = _build

docs/_templates/layout.html

@@ -1,22 +0,0 @@
-{# Import the theme's layout. #}
-{% extends "!layout.html" %}
-
-{% block extrahead %}
-{{ super() }}
-
-<meta name="description" content="Simulation and Parameter Estimation in Geophysics">
-<meta name="author" content="SimPEG Developers">
-<meta name="keywords" content="python, geophysics, inversion, electromagnetics, magnetotellurics, magnetics, gravity, DC, flow inverse problems, open source, finite volume">
-
-
-<script>
-  (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
-  (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
-  m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
-  })(window,document,'script','https://www.google-analytics.com/analytics.js','ga');
-
-  ga('create', 'UA-45185336-1', 'auto');
-  ga('send', 'pageview');
-
-</script>
-{% endblock %}

docs/api_DC.rst

@@ -1,3 +1,5 @@
+.. _api_DC:
+
 .. math::
 
     \renewcommand{\div}{\nabla\cdot\,}
@@ -36,16 +38,8 @@
     \renewcommand {\u}  { {\vec u} }
     \newcommand{\I}{\vec{I}}
 
-
-Direct Current Resistivity
-**************************
-
-`SimPEG.DCIP` uses SimPEG as the framework for the forward and inverse
-direct current (DC) resistivity and induced polarization (IP) geophysical problems.
-
-
 DC resistivity survey
-=====================
+*********************
 
 Electrical resistivity of subsurface materials is measured by causing an electrical current to flow in the earth between one pair of electrodes while the voltage across a second pair of electrodes is measured. The result is an "apparent" resistivity which is a value representing the weighted average resistivity over a volume of the earth. Variations in this measurement are caused by variations in the soil, rock, and pore fluid electrical resistivity. Surveys require contact with the ground, so they can be labour intensive. Results are sometimes interpreted directly, but more commonly, 1D, 2D or 3D models are estimated using inversion procedures (`GPG <http://www.eos.ubc.ca/courses/eosc350/content/>`_).
 
@@ -61,7 +55,7 @@ As direct current (DC) implies, in DC resistivity survey, we assume steady-state
 
     \curl \e = 0
 
-Then by taking \\(\\div\\) of the first equation, we have
+Then by taking \\(\\curl\\) for the first equation, we have
 
 .. math::
 
@@ -143,14 +137,13 @@ Comparing to the analytic function:
 
 .. plot::
 
-    from SimPEG import Examples
-    Examples.DC_Analytic_Dipole.run(plotIt=True)
+    import simpegDC as DC
+    DC.Examples.Verification.run(plotIt=True)
 
+API
+===
 
-API for DC codes
-================
-
-.. automodule:: SimPEG.DCIP.BaseDC
+.. automodule:: simpegDC.BaseDC
     :show-inheritance:
     :members:
     :undoc-members:

docs/api_Examples.rst

@@ -7,7 +7,7 @@ Examples
     :maxdepth: 1
     :glob:
 
-    ../examples/*
+    examples/*
 
 
 External Notebooks

docs/api_FiniteVolume.rst

@@ -0,0 +1,19 @@
+.. _api_FiniteVolume:
+
+Finite Volume
+*************
+
+Any numerical implementation requires the discretization of continuous functions into discrete approximations. These approximations are typically organized in a mesh, which defines boundaries, locations, and connectivity. Of specific interest to geophysical simulations, we require that averaging, interpolation and differential operators be defined for any mesh. In SimPEG, we have implemented a staggered mimetic finite volume approach (`Hyman and Shashkov, 1999 <http://math.lanl.gov/~mac/papers/numerics/HS99B.pdf>`_). This approach requires the definitions of variables at either cell-centers, nodes, faces, or edges as seen in the figure below.
+
+.. image:: images/finitevolrealestate.png
+   :width: 400 px
+   :alt: FiniteVolume
+   :align: center
+
+
+.. toctree::
+   :maxdepth: 2
+
+   api_Mesh
+   api_DiffOps
+   api_InnerProducts

docs/api_ForwardProblem.rst

@@ -52,15 +52,13 @@ We can take the derivative of the PDE:
 
     \nabla_m c(m, u) \partial m + \nabla_u c(m, u) \partial u = 0
 
-If the forward problem is invertible, then we can rearrange for
-\\(\\frac{\\partial u}{\\partial m}\\):
+If the forward problem is invertible, then we can rearrange for \\(\\frac{\\partial u}{\\partial m}\\):
 
 .. math::
 
     J = - P \left( \nabla_u c(m, u) \right)^{-1} \nabla_m c(m, u)
 
-This can often be computed given a vector (i.e. \\(J(v)\\)) rather than
-stored, as \\(J\\) is a large dense matrix.
+This can often be computed given a vector (i.e. \\(J(v)\\)) rather than stored, as \\(J\\) is a large dense matrix.
 
 
 
@@ -69,45 +67,13 @@ The API
 
 Problem
 -------
-
-.. autoclass:: SimPEG.Problem.BaseProblem
-    :members:
-    :undoc-members:
-
-.. autoclass:: SimPEG.Problem.BaseTimeProblem
-    :members:
-    :undoc-members:
-
-Fields
-------
-
-.. autoclass:: SimPEG.Fields.Fields
-    :members:
-    :undoc-members:
-
-.. autoclass:: SimPEG.Fields.TimeFields
+.. automodule:: SimPEG.Problem
     :members:
     :undoc-members:
 
 Survey
 ------
-
-.. autoclass:: SimPEG.Survey.BaseSurvey
+.. automodule:: SimPEG.Survey
     :members:
     :undoc-members:
 
-.. autoclass:: SimPEG.Survey.BaseSrc
-    :members:
-    :undoc-members:
-
-.. autoclass:: SimPEG.Survey.BaseRx
-    :members:
-    :undoc-members:
-
-.. autoclass:: SimPEG.Survey.BaseTimeRx
-    :members:
-    :undoc-members:
-
-.. autoclass:: SimPEG.Survey.Data
-    :members:
-    :undoc-members:

docs/api_InnerProducts.rst

@@ -4,10 +4,7 @@
 Inner Products
 **************
 
-By using the weak formulation of many of the PDEs in geophysical applications,
-we can rapidly develop discretizations. Much of this work, however, needs a
-good understanding of how to approximate inner products on our discretized
-meshes. We will define the inner product as:
+By using the weak formulation of many of the PDEs in geophysical applications, we can rapidly develop discretizations. Much of this work, however, needs a good understanding of how to approximate inner products on our discretized meshes. We will define the inner product as:
 
 .. math::
 
@@ -17,15 +14,12 @@ where a and b are either scalars or vectors.
 
 .. note::
 
-    The InnerProducts class is a base class providing inner product matrices
-    for meshes and cannot run on its own.
+    The InnerProducts class is a base class providing inner product matrices for meshes and cannot run on its own.
 
 
 Example problem for DC resistivity
 ----------------------------------
-
-We will start with the formulation of the Direct Current (DC) resistivity
-problem in geophysics.
+We will start with the formulation of the Direct Current (DC) resistivity problem in geophysics.
 
 
 .. math::
@@ -34,13 +28,12 @@ problem in geophysics.
 
         \nabla\cdot \vec{j} = q
 
-In the following discretization, :math:`\sigma` and :math:`\phi`
-will be discretized on the cell-centers and the flux, :math:`\vec{j}`,
+In the following discretization, \\\( \\sigma \\\) and \\\( \\phi \\\)
+will be discretized on the cell-centers and the flux, \\\(\\vec{j}\\\),
 will be on the faces. We will use the weak formulation to discretize
 the DC resistivity equation.
 
-We can define in weak form by integrating with a general face function
-:math:`\vec{f}`:
+We can define in weak form by integrating with a general face function \\\(\\vec{f}\\\):
 
 .. math::
 
@@ -68,16 +61,9 @@ We can then discretize for every cell:
 
 .. note::
 
-    We have discretized the dot product above, but remember that we do not
-    really have a single vector :math:`\mathbf{J}`, but approximations of
-    :math:`\vec{j}` on each face of our cell. In 2D that means 2
-    approximations of :math:`\mathbf{J}_x` and 2 approximations of
-    :math:`\mathbf{J}_y`. In 3D we also have 2 approximations of
-    :math:`\mathbf{J}_z`.
+    We have discretized the dot product above, but remember that we do not really have a single vector \\\(\\mathbf{J}\\\), but approximations of \\\(\\vec{j}\\\) on each face of our cell. In 2D that means 2 approximations of \\\(\\mathbf{J}_x\\\) and 2 approximations of \\\(\\mathbf{J}_y\\\). In 3D we also have 2 approximations of \\\(\\mathbf{J}_z\\\).
 
-Regardless of how we choose to approximate this dot product, we can represent
-this in vector form (again this is for every cell), and will generalize for
-the case of anisotropic (tensor) sigma.
+Regardless of how we choose to approximate this dot product, we can represent this in vector form (again this is for every cell), and will generalize for the case of anisotropic (tensor) sigma.
 
 .. math::
 
@@ -85,17 +71,14 @@ the case of anisotropic (tensor) sigma.
     -\phi^{\top} v_{\text{cell}} \mathbf{D}_{\text{cell}} \mathbf{F})
     + \text{BC}
 
-We multiply by  square-root of volume on each side of the tensor conductivity
-to keep symmetry in the system. Here :math:`\mathbf{J}_c` is the Cartesian
-:math:`\mathbf{J}` (on the faces that we choose to use in our approximation)
-and must be calculated differently depending on the mesh:
+We multiply by  square-root of volume on each side of the tensor conductivity to keep symmetry in the system. Here \\\(\\mathbf{J}_c\\\) is the Cartesian \\\(\\mathbf{J}\\\) (on the faces that we choose to use in our approximation) and must be calculated differently depending on the mesh:
 
 .. math::
     \mathbf{J}_c = \mathbf{Q}_{(i)}\mathbf{J}_\text{TENSOR} \\
     \mathbf{J}_c = \mathbf{N}_{(i)}^{-1}\mathbf{Q}_{(i)}\mathbf{J}_\text{Curv}
 
-Here the :math:`i` index refers to where we choose to approximate this integral, as discussed in the note above.
-We will approximate this integral by taking the fluxes clustered around every node of the cell, there are 8 combinations in 3D, and 4 in 2D. We will use a projection matrix :math:`\mathbf{Q}_{(i)}` to pick the appropriate fluxes. So, now that we have 8 approximations of this integral, we will just take the average. For the TensorMesh, this looks like:
+Here the \\\(i\\\) index refers to where we choose to approximate this integral, as discussed in the note above.
+We will approximate this integral by taking the fluxes clustered around every node of the cell, there are 8 combinations in 3D, and 4 in 2D. We will use a projection matrix \\\( \\mathbf{Q}_{(i)} \\\) to pick the appropriate fluxes. So, now that we have 8 approximations of this integral, we will just take the average. For the TensorMesh, this looks like:
 
 .. math::
 
@@ -124,12 +107,10 @@ By defining the faceInnerProduct (8 combinations of fluxes in 3D, 4 in 2D, 2 in
         \sum_{i=1}^{2^d}
         \mathbf{P}_{(i)}^{\top} \Sigma^{-1} \mathbf{P}_{(i)}
 
-Where :math:`d` is the dimension of the mesh.
-The :math:`\mathbf{M}^f` is returned when given the input of :math:`\Sigma^{-1}`.
+Where \\\(d\\\) is the dimension of the mesh.
+The \\\( \\mathbf{M}^f \\\) is returned when given the input of \\\( \\Sigma^{-1} \\\).
 
-Here each :math:`\mathbf{P} ~ \in ~ \mathbb{R}^{(d*nC, nF)}` is a combination
-of the projection, volume, and any normalization to Cartesian coordinates
-(where the dot product is well defined):
+Here each \\( \\mathbf{P} \\in \\mathbb{R}^{(d*nC, nF)} \\\) is a combination of the projection, volume, and any normalization to Cartesian coordinates (where the dot product is well defined):
 
 .. math::
 
@@ -148,10 +129,7 @@ If ``returnP=True`` is requested in any of these methods the projection matrices
     # In 1D
     P = [P0, P1]
 
-The derivation for ``edgeInnerProducts`` is exactly the same, however, when we
-approximate the integral using the fields around each node, the projection
-matrices look a bit different because we have 12 edges in 3D instead of just 6
-faces. The interface to the code is exactly the same.
+The derivation for ``edgeInnerProducts`` is exactly the same, however, when we approximate the integral using the fields around each node, the projection matrices look a bit different because we have 12 edges in 3D instead of just 6 faces. The interface to the code is exactly the same.
 
 
 Defining Tensor Properties
@@ -159,8 +137,7 @@ Defining Tensor Properties
 
 **For 3D:**
 
-Depending on the number of columns (either 1, 3, or 6) of mu, the material
-property is interpreted as follows:
+Depending on the number of columns (either 1, 3, or 6) of mu, the material property is interpreted as follows:
 
 .. math::
 
@@ -211,16 +188,13 @@ Which is nice and easy to invert if necessary, however, in the fully anisotropic
 Taking Derivatives
 ------------------
 
-We will take the derivative of the fully anisotropic tensor for a 3D mesh, the
-other cases are easier and will not be discussed here. Let us start with one
-part of the sum which makes up :math:`\mathbf{M}^f_\Sigma` and take the
-derivative when this is multiplied by some vector :math:`\mathbf{v}`:
+We will take the derivative of the fully anisotropic tensor for a 3D mesh, the other cases are easier and will not be discussed here. Let us start with one part of the sum which makes up \\\(\\mathbf{M}^f_\\Sigma\\\) and take the derivative when this is multiplied by some vector \\\(\\mathbf{v}\\\):
 
 .. math::
 
     \mathbf{P}^\top \boldsymbol{\Sigma} \mathbf{Pv}
 
-Here we will let :math:`\mathbf{Pv} = \mathbf{y}` and :math:`\mathbf{y}` will have the form:
+Here we will let \\\( \\mathbf{Pv} = \\mathbf{y} \\\) and \\\(\\mathbf{y}\\\) will have the form:
 
 .. math::
 
@@ -259,9 +233,7 @@ Here we will let :math:`\mathbf{Pv} = \mathbf{y}` and :math:`\mathbf{y}` will ha
         \end{matrix}
     \right]
 
-Now it is easy to take the derivative with respect to any one of the
-parameters, for example,
-:math:`\frac{\partial}{\partial\boldsymbol{\sigma}_1}`
+Now it is easy to take the derivative with respect to any one of the parameters, for example, \\\(\\frac{\\partial}{\\partial\\boldsymbol{\\sigma}_1}\\\)
 
 .. math::
     \frac{\partial}{\partial \boldsymbol{\sigma}_1}\left(\mathbf{P}^\top\Sigma\mathbf{y}\right)
@@ -275,8 +247,7 @@ parameters, for example,
         \end{matrix}
     \right]
 
-Whereas :math:`\frac{\partial}{\partial\boldsymbol{\sigma}_4}`, for
-example, is:
+Whereas \\\(\\frac{\\partial}{\\partial\\boldsymbol{\\sigma}_4}\\\), for example, is:
 
 .. math::
     \frac{\partial}{\partial \boldsymbol{\sigma}_4}\left(\mathbf{P}^\top\Sigma\mathbf{y}\right)
@@ -290,12 +261,11 @@ example, is:
         \end{matrix}
     \right]
 
-These are computed for each of the 8 projections, horizontally concatenated,
-and returned.
+These are computed for each of the 8 projections, horizontally concatenated, and returned.
 
 The API
 -------
 
-.. autoclass:: SimPEG.Mesh.InnerProducts.InnerProducts
+.. automodule:: SimPEG.Mesh.InnerProducts
     :members:
     :undoc-members: