Documentations

docs/api_PF.rst

@@ -161,7 +161,10 @@ Inverse problem
     :width: 800px
     :align: center
     :height: 400px
-    :alt: alternate text    
+    :alt: alternate text
+
+.. raw:: html
+    :file: examples/movie.html
 
 Mag Differential eq. approach
 *****************************

docs/conf.py

@@ -10,7 +10,7 @@
 #
 # All configuration values have a default; values that are commented out
 # serve to show the default.
-
+import sphinx_rtd_theme
 import sys, os
 
 # If extensions (or modules to document with autodoc) are in another directory,
@@ -93,8 +93,8 @@ pygments_style = 'sphinx'
 
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
-html_theme = 'default'
-
+html_theme = 'sphinx_rtd_theme'
+html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
 # Theme options are theme-specific and customize the look and feel of a theme
 # further.  For a list of options available for each theme, see the
 # documentation.

docs/examples/movie.html

@@ -1,4 +1,4 @@
-<div class="output" style=""><div class="output_area"><div class="prompt output_prompt">Out[509]:</div><div class="output_subarea output_html rendered_html output_pyout">
+<div class="output" style=""><div class="output_area"><div class="prompt output_prompt"></div><div class="output_subarea output_html rendered_html output_pyout">
 <script language="javascript">
   /* Define the Animation class */
   function Animation(frames, img_id, slider_id, interval, loop_select_id){
@@ -55,7 +55,7 @@
   Animation.prototype.last_frame = function()
   {
     this.set_frame(this.frames.length - 1);
-  } 
+  }
 
   Animation.prototype.slower = function()
   {
@@ -201,9 +201,9 @@ FnSONdiL8Qci0lzwpOM5sQAAAABJRU5ErkJggg==
 "></button>
     <button onclick="animERCBNNRFBIVTPCOM.faster()">+</button>
   <form action="#n" name="_anim_loop_selectERCBNNRFBIVTPCOM" class="anim_control">
-    <input type="radio" name="state" value="once"> Once 
-    <input type="radio" name="state" value="loop" checked=""> Loop 
-    <input type="radio" name="state" value="reflect"> Reflect 
+    <input type="radio" name="state" value="once"> Once
+    <input type="radio" name="state" value="loop" checked=""> Loop
+    <input type="radio" name="state" value="reflect"> Reflect
   </form>
 </div>
 
@@ -216,7 +216,7 @@ FnSONdiL8Qci0lzwpOM5sQAAAABJRU5ErkJggg==
     var slider_id = "_anim_sliderERCBNNRFBIVTPCOM";
     var loop_select_id = "_anim_loop_selectERCBNNRFBIVTPCOM";
     var frames = new Array(0);
-    
+
   frames[0] = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABIAAAAFoCAYAAAAvh4ASAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\
 AAALEgAACxIB0t1+/AAAIABJREFUeJzt3b1SG+maB/BHnKna2oQPebNNQLC5DczGp4zF5rZh5gIM\
 +AZm8JnI4QDnAsZwso3WQG28x9KUc2PhfIzgAnZAcrChewOPdJAt2ZivRq9+vypVoX718bQa9Lz8\
@@ -2271,4 +2271,4 @@ aQABAAAAJE4DCAAAACBx/z85KJK1LamKyAAAAABJRU5ErkJggg==\
     }, 0);
   })()
 </script>
-</div></div></div>
+</div></div></div>

simpegPF/notebooks/MagForward_secondary.ipynb

@@ -24,17 +24,9 @@
        "text": [
         "Populating the interactive namespace from numpy and matplotlib\n"
        ]
-      },
-      {
-       "output_type": "stream",
-       "stream": "stderr",
-       "text": [
-        "WARNING: pylab import has clobbered these variables: ['axes', 'info', 'flag']\n",
-        "`%pylab --no-import-all` prevents importing * from pylab and numpy\n"
-       ]
       }
      ],
-     "prompt_number": 24
+     "prompt_number": 1
     },
     {
      "cell_type": "markdown",
@@ -56,16 +48,16 @@
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "hxind = ((5,25,1.3),(41, 12.5),(5,25,1.3))\n",
-      "hyind = ((5,25,1.3),(41, 12.5),(5,25,1.3))\n",
-      "hzind = ((5,25,1.3),(40, 12.5),(5,25,1.3))\n",
-      "hx, hy, hz = Utils.meshTensors(hxind, hyind, hzind)\n",
-      "M3 = Mesh.TensorMesh([hx, hy, hz], [-sum(hx)/2,-sum(hy)/2,-sum(hz)/2])"
+      "cs = 25.\n",
+      "hxind = [(cs,5,-1.3), (cs, 41),(cs,5,1.3)]\n",
+      "hyind = [(cs,5,-1.3), (cs, 41),(cs,5,1.3)]\n",
+      "hzind = [(cs,5,-1.3), (cs, 40),(cs,5,1.3)]\n",
+      "M3 = Mesh.TensorMesh([hxind, hyind, hzind], 'CCC')"
      ],
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 25
+     "prompt_number": 10
     },
     {
      "cell_type": "markdown",
@@ -88,7 +80,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 27
+     "prompt_number": 11
     },
     {
      "cell_type": "code",
@@ -101,7 +93,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 29
+     "prompt_number": 12
     },
     {
      "cell_type": "markdown",
@@ -123,18 +115,18 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 30
+     "prompt_number": 13
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "Bbc = CongruousMagBC(M3, np.array([Box, Boy, Boz]), chi)"
+      "Bbc, Bbc_const = CongruousMagBC(M3, np.array([Box, Boy, Boz]), chi)"
      ],
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 31
+     "prompt_number": 28
     },
     {
      "cell_type": "code",
@@ -149,19 +141,19 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAjwAAAI8CAYAAAD1D3GaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x338be50>"
+        "<matplotlib.figure.Figure at 0xa46fb38>"
        ]
       }
      ],
-     "prompt_number": 32
+     "prompt_number": 29
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "M3.plotImage(np.log10(mu), imageType='CC')"
+      "M3.plotImage(np.log10(mu))"
      ],
      "language": "python",
      "metadata": {},
@@ -169,21 +161,21 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 33,
+       "prompt_number": 30,
        "text": [
-        "<matplotlib.collections.QuadMesh at 0x92842d0>"
+        "<matplotlib.collections.QuadMesh at 0x10166160>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x57af690>"
+        "<matplotlib.figure.Figure at 0xa504278>"
        ]
       }
      ],
-     "prompt_number": 33
+     "prompt_number": 30
     },
     {
      "cell_type": "markdown",
@@ -225,15 +217,40 @@
       "Pbc,Pin, Pout = M3.getBCProjWF(BC, discretization='CC')\n",
       "Mc = Utils.sdiag(M3.vol)\n",
       "Div = Mc*Dface*Pin.T*Pin\n",
-      "MfmuI = Utils.sdiag(1/M3.getFaceInnerProduct(mu = 1/mu).diagonal())\n",
-      "Mfmu0 = 1/mu0*M3.getFaceInnerProduct()\n",
+      "MfmuI = Utils.sdiag(1/M3.getFaceInnerProduct(1/mu).diagonal())\n",
+      "Mfmu0 = M3.getFaceInnerProduct(1/mu0)\n",
       "A = -Div*MfmuI*Div.T\n",
       "rhs = -Div*MfmuI*Mfmu0*B0 + Div*B0 - Mc*Dface*Pout.T*Bbc"
      ],
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 34
+     "prompt_number": 31
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "print Mc.shape\n",
+      "print Dface.shape\n",
+      "print Pout.shape\n",
+      "print Bbc.shape"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "(130050, 130050)\n",
+        "(130050, 397851)\n",
+        "(15402, 397851)\n",
+        "(15402L,)\n"
+       ]
+      }
+     ],
+     "prompt_number": 32
     },
     {
      "cell_type": "code",
@@ -252,21 +269,21 @@
        ]
       }
      ],
-     "prompt_number": 35
+     "prompt_number": 33
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "import petsc4py\n",
-      "import sys\n",
-      "from sys import getrefcount\n",
-      "petsc4py.init(sys.argv)\n",
-      "from petsc4py import PETSc\n",
-      "import PETScIO as IO\n",
-      "Apetsc = PETSc.Mat().createAIJ(size=A.shape,csr=(A.indptr, A.indices, A.data))\n",
-      "bpetsc = IO.arrayToVec(rhs)\n",
-      "xpetsc = IO.arrayToVec(0*rhs)"
+      "# import petsc4py\n",
+      "# import sys\n",
+      "# from sys import getrefcount\n",
+      "# petsc4py.init(sys.argv)\n",
+      "# from petsc4py import PETSc\n",
+      "# import PETScIO as IO\n",
+      "# Apetsc = PETSc.Mat().createAIJ(size=A.shape,csr=(A.indptr, A.indices, A.data))\n",
+      "# bpetsc = IO.arrayToVec(rhs)\n",
+      "# xpetsc = IO.arrayToVec(0*rhs)"
      ],
      "language": "python",
      "metadata": {},
@@ -286,55 +303,41 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
+     "prompt_number": 35
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "# %%time\n",
+      "# ksp = PETSc.KSP().create()\n",
+      "# pc = PETSc.PC().create()\n",
+      "# ksp.setOperators(Apetsc)\n",
+      "# ksp.setType(ksp.Type.BCGS)\n",
+      "# pc = ksp.getPC()\n",
+      "# pc.setType(pc.Type.BJACOBI)\n",
+      "# OptDB = PETSc.Options()\n",
+      "# OptDB[\"ksp_rtol\"] = 1e-8\n",
+      "# OptDB[\"pc_factor_levels\"] = 1\n",
+      "# ksp.setFromOptions()\n",
+      "# ksp.view()\n",
+      "# ksp.solve(bpetsc, xpetsc)\n",
+      "# print ksp.its# print ksp.its\n",
+      "# phi = IO.vecToArray(xpetsc)\n",
+      "# print np.linalg.norm(A*phi-rhs)/norm(rhs)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
      "prompt_number": 37
     },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "%%time\n",
-      "ksp = PETSc.KSP().create()\n",
-      "pc = PETSc.PC().create()\n",
-      "ksp.setOperators(Apetsc)\n",
-      "ksp.setType(ksp.Type.BCGS)\n",
-      "pc = ksp.getPC()\n",
-      "pc.setType(pc.Type.BJACOBI)\n",
-      "OptDB = PETSc.Options()\n",
-      "OptDB[\"ksp_rtol\"] = 1e-8\n",
-      "OptDB[\"pc_factor_levels\"] = 1\n",
-      "ksp.setFromOptions()\n",
-      "ksp.view()\n",
-      "ksp.solve(bpetsc, xpetsc)\n",
-      "print ksp.its# print ksp.its\n",
-      "phi = IO.vecToArray(xpetsc)\n",
-      "print np.linalg.norm(A*phi-rhs)/norm(rhs)"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
-      {
-       "output_type": "stream",
-       "stream": "stdout",
-       "text": [
-        "81\n",
-        "7.00090107929e-09\n",
-        "CPU times: user 639 ms, sys: 7.95 ms, total: 647 ms\n",
-        "Wall time: 647 ms\n"
-       ]
-      }
-     ],
-     "prompt_number": 39
-    },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
       "%%time\n",
       "m1 = sp.linalg.interface.aslinearoperator(Utils.sdiag(-1/A.diagonal()))\n",
-      "phi, info = sp.linalg.bicgstab(A, rhs, tol=1e-6, maxiter = 1000, M =m1)\n",
-      "# m1 = sp.linalg.interface.aslinearoperator(Utils.sdiag(np.sqrt(1/(Utils.mkvc(-A.diagonal())))))\n",
-      "# m2 = m1\n",
-      "# phi, info = sp.linalg.qmr(A, rhs, tol = 1e-5, M1 = m1, M2=m2)"
+      "phi, info = sp.linalg.bicgstab(A, rhs, tol=1e-6, maxiter = 1000, M =m1)"
      ],
      "language": "python",
      "metadata": {},
@@ -343,12 +346,11 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "CPU times: user 994 ms, sys: 0 ns, total: 994 ms\n",
-        "Wall time: 994 ms\n"
+        "Wall time: 1.53 s\n"
        ]
       }
      ],
-     "prompt_number": 41
+     "prompt_number": 40
     },
     {
      "cell_type": "code",
@@ -369,7 +371,7 @@
        ]
       }
      ],
-     "prompt_number": 42
+     "prompt_number": 41
     },
     {
      "cell_type": "code",
@@ -388,11 +390,11 @@
        "stream": "stdout",
        "text": [
         "0\n",
-        "7.98141453262e-07\n"
+        "8.03408261327e-07\n"
        ]
       }
      ],
-     "prompt_number": 43
+     "prompt_number": 42
     },
     {
      "cell_type": "markdown",
@@ -405,22 +407,30 @@
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "figsize(16,5)\n",
-      "M3.plotImage(B, imageType='F')"
+      "figsize(5,5)\n",
+      "M3.plotSlice(phi)"
      ],
      "language": "python",
      "metadata": {},
      "outputs": [
       {
        "metadata": {},
-       "output_type": "display_data",
-       "png": 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+       "output_type": "pyout",
+       "prompt_number": 53,
        "text": [
-        "<matplotlib.figure.Figure at 0x7477190>"
+        "(<matplotlib.collections.QuadMesh at 0xa55a1d0>,)"
+       ]
+      },
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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truncated
+       "text": [
+        "<matplotlib.figure.Figure at 0x1018d400>"
        ]
       }
      ],
-     "prompt_number": 17
+     "prompt_number": 53
     },
     {
      "cell_type": "markdown",
@@ -464,7 +474,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 18
+     "prompt_number": 54
     },
     {
      "cell_type": "code",
@@ -478,7 +488,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 19
+     "prompt_number": 55
     },
     {
      "cell_type": "code",
@@ -499,7 +509,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 20
+     "prompt_number": 56
     },
     {
      "cell_type": "code",
@@ -519,21 +529,21 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 21,
+       "prompt_number": 57,
        "text": [
-        "[<matplotlib.lines.Line2D at 0x33a4250>]"
+        "[<matplotlib.lines.Line2D at 0xaddff28>]"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x33a1110>"
+        "<matplotlib.figure.Figure at 0xa53b2b0>"
        ]
       }
      ],
-     "prompt_number": 21
+     "prompt_number": 57
     },
     {
      "cell_type": "code",
@@ -553,21 +563,21 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 22,
+       "prompt_number": 58,
        "text": [
-        "<matplotlib.colorbar.Colorbar instance at 0x84e4518>"
+        "<matplotlib.colorbar.Colorbar instance at 0x0000000012124588>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x33a1590>"
+        "<matplotlib.figure.Figure at 0xa5422b0>"
        ]
       }
      ],
-     "prompt_number": 22
+     "prompt_number": 58
     },
     {
      "cell_type": "code",
@@ -596,21 +606,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x4b21e90>"
+        "<matplotlib.figure.Figure at 0x1232e908>"
        ]
       }
      ],
-     "prompt_number": 23
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [],
-     "language": "python",
-     "metadata": {},
-     "outputs": []
+     "prompt_number": 59
     },
     {
      "cell_type": "code",
@@ -630,21 +632,21 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 59,
+       "prompt_number": 60,
        "text": [
-        "[<matplotlib.lines.Line2D at 0x851d590>]"
+        "[<matplotlib.lines.Line2D at 0x213e39e8>]"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x630ec90>"
+        "<matplotlib.figure.Figure at 0x1232c550>"
        ]
       }
      ],
-     "prompt_number": 59
+     "prompt_number": 60
     },
     {
      "cell_type": "code",
@@ -672,13 +674,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x1138dfd0>"
+        "<matplotlib.figure.Figure at 0x17dc7550>"
        ]
       }
      ],
-     "prompt_number": 73
+     "prompt_number": 61
     },
     {
      "cell_type": "code",