{
 "metadata": {
  "name": "",
  "signature": "sha256:2aa6562ce56a22699d07327912ff516ed48493f67bbddc1babb0722b0ee1a0ff"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from timedomaineuler import *\n",
      "#import timedomaineuler"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Globalconf accessable with cvar.gc\n",
      "f=85.785\n",
      "T=1/f\n",
      "loglevel=20\n",
      "L=1e-2\n",
      "gp=10\n",
      "gc=cvar.gc #Reference!\n",
      "dx=L/(gp-1);                    # One left and right gp, so\n",
      "CFL=0.1;\n",
      "gc.setfreq(f)\n",
      "tube=TubeLF(L,gp)\n",
      "dt=min(CFL*dx/gc.c0(),T/50)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nr_p_period=1\n",
      "intsteps=int(floor(1./(gc.getfreq()*dt)/nr_p_period))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "intsteps=1000"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print(\"DoIntegration relative time step of one period: %0.2e\" %(dt*gc.getfreq()))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "DoIntegration relative time step of one period: 2.78e-05\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tube.gp"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "10"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tube.DoIntegration(dt,1)\n",
      "sol=tube.getSol()\n",
      "u=sol.u()\n",
      "p=sol.p()\n",
      "#rho=sol.rho()\n",
      "figure(figsize=(9,6))\n",
      "subplot(221)\n",
      "plot(p)\n",
      "subplot(222)\n",
      "plot(u)\n",
      "subplot(223)\n",
      "#plot(rho)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "<matplotlib.axes._subplots.AxesSubplot at 0x7f8a6779fac8>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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19J73ZOuSvPlm+XVt3Qrnnw+XXAJve1v59ZlZ/+OeI7PqcHJUQ0OGwCGHwPLl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\n8/8BoPUqgBBhb9gAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f8a721c74e0>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "rho"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "<timedomaineuler.vd; proxy of <Swig Object of type 'vd *' at 0x7f8a724e5e10> >"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "p"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "array([ -4.29085417e-16,   0.00000000e+00,   0.00000000e+00,\n",
        "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
        "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
        "         0.00000000e+00])"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}