pygridgen_test.ipynb

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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "pygridgen test"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "conda install using phobson's binstar channel:\n",
      "```\n",
      "conda create --name=grids python=2.7 nose pip ipython-notebook\n",
      "source activate grids\n",
      "conda install --channel=phobson nn csa gridutils gridgen pygridgen\n",
      "```"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib.pyplot as plt\n",
      "import pygridgen\n",
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Basic Example"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = [0, 1, 2, 1, 0]\n",
      "y = [0, 0, 1, 2, 2]\n",
      "beta = [1, 1, 0, 1, 1]\n",
      "\n",
      "grid = pygridgen.grid.Gridgen(x, y, beta, shape=(10, 5))\n",
      "\n",
      "fig, ax = plt.subplots()\n",
      "ax.plot(x, y, 'k-')\n",
      "ax.plot(grid.x, grid.y, 'b.')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7f4471dd9310>"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Example with focus\n",
      "Note that `add_focus_x` means focus *along* the x axis, not\n",
      "*at* a specific x-postion."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = [0, 1, 2, 1, 0]\n",
      "y = [0, 0, 1, 2, 2]\n",
      "beta = [1, 1, 0, 1, 1]\n",
      "\n",
      "focus = pygridgen.grid.Focus()\n",
      "focus.add_focus_x(xo=0.5, factor=3, Rx=0.2)\n",
      "focus.add_focus_y(yo=0.75, factor=5, Ry=0.1)\n",
      "grid = pygridgen.grid.Gridgen(x, y, beta, shape=(20, 20), focus=focus)\n",
      "\n",
      "fig, ax = plt.subplots()\n",
      "ax.plot(x, y, 'k-')\n",
      "ax.plot(grid.x, grid.y, 'b.')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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bmX9PUXAqj9+VbaFk85r/7iVXP4q6ikL+/T/+Yzc++OAkDBv2KSxb1hfDh/cN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\nRK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f4470a72dd0>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    }
   ],
   "metadata": {}
  }
 ]
}