simpeg/notebooks/exPlotImage2D.ipynb

{
 "metadata": {
  "name": "exPlotImage2D"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import sys\n",
      "sys.path.append('../')\n",
      "\n",
      "import numpy as np\n",
      "import matplotlib.pyplot as plt\n",
      "from SimPEG import TensorMesh"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Test 1D Plots\n",
      "\n",
      "For 1D nodal or cell-centered plots are supported.\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x0 = np.zeros(1)\n",
      "h = np.random.rand(51)\n",
      "mesh = TensorMesh([h],x0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "TypeError",
       "evalue": "'module' object is not callable",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-6-1d4a57352580>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mx0\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mh\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrandom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrand\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m51\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mmesh\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTensorMesh\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mh\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mx0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;31mTypeError\u001b[0m: 'module' object is not callable"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sin = lambda x: np.sin(x)\n",
      "xc   = mesh.gridCC\n",
      "xn   = mesh.gridN\n",
      "\n",
      "fig = plt.figure(1)\n",
      "fig.clf()\n",
      "ph1 = mesh.plotImage(sin(xc),ax=subplot(111))\n",
      "ph2 = mesh.plotImage(sin(xn),ax=subplot(111),imageType='N')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "NameError",
       "evalue": "name 'mesh' is not defined",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-4-3c7d7da1661e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0msin\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mxc\u001b[0m   \u001b[0;34m=\u001b[0m \u001b[0mmesh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgridCC\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mxn\u001b[0m   \u001b[0;34m=\u001b[0m \u001b[0mmesh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgridN\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mfig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;31mNameError\u001b[0m: name 'mesh' is not defined"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Test 2D Plots\n",
      "\n",
      "Plot x and y coordinates of cell-centred points"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x0 = np.zeros(2)\n",
      "h1 = np.linspace(.1,.5,3)\n",
      "h2 = np.linspace(.1,.5,5)\n",
      "mesh = TensorMesh([h1,h2],x0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = plt.figure(1)\n",
      "fig.clf()\n",
      "ax1 = subplot(121)\n",
      "ax2 = subplot(122)\n",
      "mesh.plotImage(mesh.gridCC[:,0],ax = ax1)\n",
      "ax1.set_title('x coordinates') \n",
      "mesh.plotImage(mesh.gridCC[:,1],ax = ax2)\n",
      "ax2.set_title('y coordinates')            "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "<matplotlib.text.Text at 0x10c3dd390>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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gZWZmKiwszLvfGKMxY8Zo7ty5euihh1RWVuZEGYDt6G34M9vfIZSXl0uS+vfvr4iICA0a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\nkCT9PxL88fDsDe+RAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10c3a1190>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "SyntaxError",
       "evalue": "invalid syntax (<ipython-input-8-2ecb5b820872>, line 2)",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-8-2ecb5b820872>\"\u001b[0;36m, line \u001b[0;32m2\u001b[0m\n\u001b[0;31m    type(ax)\u001b[0m\n\u001b[0m       ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}