timedomainresonace/timedomain.ipynb

{
 "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": "iVBORw0KGgoAAAANSUhEUgAAAkcAAAF2CAYAAABkjTxiAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XmYXVWZ7/Hvj4QwKBACGsjAcCEiUYYikEEbLRSwiN2E\nBhWiCAq3zdMhircflcTbTULbymB7GR4gRiahVYICbccmBqJQLW1DwpxgEkiE0EkFAjKpSGuG9/6x\nV8Wdw6mqU3XGOvX7PM95cvbea6/11klq5z1rrb22IgIzMzMzy+xQ7wDMzMzMGomTIzMzM7McJ0dm\nZmZmOU6OzMzMzHKcHJmZmZnlODkyMzMzy3FyZGZWZZJulLRR0vIK1HWcpMdyrzclnVyJOM0sI69z\nZGZWXZKOBX4P3BIRh1Ww3j2BNcDIiPifStVrNtC558jMrMoi4n7g1fw+SQdJ+qmkhyX9QtIhfaj6\n48BCJ0ZmleXkyMysPr4DfD4ijga+DFzbhzrOAG6taFRmxuB6B2BmNtBIejswCfiRpM7dQ9KxU4GL\nipy2PiJOytWxL/Be4O7qRms28Dg5MjOrvR2A1yKipfBARNwJ3FlCHZ8A7oyILZUOzmygK3tYTVKb\npFWSVku6oIsyV6XjT0hq6elcScMkLZb0tKR7JA3NHZuVyq+SdGJu/zhJy9OxK3P7/07Sr1LbP5O0\nX+7Y2amNpyWdVe5nYWbNpdS7zCQdI2lz6vXpUUT8FnhW0sfS+ZJ0eC/Dm4qH1MyqoqzkSNIg4Gqg\nDRgLTJV0aEGZycDBETEG+Bwwt4RzZwKLI+JdwM/TNpLGAqen8m3Atfpzn/Rc4NzUzhhJbWn/o8C4\niDgCuB24LNU1DLgQGJ9es/NJmJkZcBPZtaZL6Vp2KbAIUBdlbgX+CzhE0jpJnwU+BZwr6XHgSaDk\n2/ElHUB2h9p/lHqOmZWu3GG18cCaiFgLIGk+MAVYmStzMnAzQEQskTRU0j7Agd2cezLwwXT+zUA7\nWYI0Bbg1IjYBayWtASZIeg7YLSKWpnNuAU4BFkVEey6WJcCZ6f1HgHsi4rXU/mKyi+D88j4SM2sW\nEXF/SkS683myL17HdFPP1C4OndTF/p7iWguM7su5ZtazcofVRgLrctvr075Syozo5tzhEbExvd8I\nDE/vR6RyxerK7+8oEgfAucDCHuoyMyuJpJFkX9rmpl1eOM6sCZSbHJV6ISja1VykzFvqi2yVyrIv\nOJLOBI4CvlluXWZmyRXAzHSdEqVd68yswZU7rNbB9l27o9m+N6ZYmVGpzI5F9nek9xsl7RMRL6Tb\nVV/soa6O9L5YXUg6Hvgq8IE0JNdZV2tB7PcW/oCS/E3QrIFERCMlIOOA+Wnq497ASZI2RcSCfCFf\nR8waS4/XkYjo84ssufo1cADZGh2PA4cWlJlMtoIrwETgwZ7OJZs0fUF6PxO4JL0fm8oNIZuz9Gv+\n/AiUJcAEsm9uC4G2tL+FbHn9gwri2hN4Bhiaf1/kZ4xqmz17dtXbqFU7zdJGrdrxz9I76fexrOtW\nb1/pGrW8hHI3Aad2caxaH8k2/rfUeG3Uqp1maaNW7ZRyHSmr5ygiNkuaQbYI2SDghohYKWlaOj4v\nIhZKmpwmT78BfLa7c1PVlwA/lHQusJZsPQ8iYoWkHwIrgM3A9PSDAkwHvgvsQpaMLUr7LwPeBtye\nvt09FxGnRMSrkr4GPJTKXRRpcraZGWy7y+yDwN6S1gGzyXq9iYh59YzNzKqn7EUgI+KnwE8L9s0r\n2J5R6rlp/yvA8V2c8w3gG0X2PwK85YGOEXFCN7HfRPZtz8zsLaLru8yKlf1sNWMxs9rxs9UaQGtr\na9O00yxt1Kod/yxWKf631Hht1KqdZmmjlu30RH8elbJiJIU/I7PGIKnRJmSXxNcRs8ZRynXEPUdm\nZmZmOU6OzMzMzHKcHJmZmZnlODkyMzMzy3FyZGZmZpbj5MjMzMwsx8mRmZmZWY6TIzMzM7McJ0dm\nZmZmOU6OSrBlS70jMDMzs1pxclSCp5+udwRmZmZWK06OSvDYY/WOwMzqQdKNkjZKWt7F8U9JekLS\nMkm/lHR4V3W99FL14jSzynJyVILHH693BGZWJzcBbd0cfwb4QEQcDnwN+E5XBZcsqXBkZlY1To5K\n4J4js4EpIu4HXu3m+AMR8XraXAKM6qrsAw9UODgzqxonRyV47DGIqHcUZtbgzgUWdnXwwQdrGImZ\nlaXs5EhSm6RVklZLuqCLMlel409IaunpXEnDJC2W9LSkeyQNzR2blcqvknRibv84ScvTsStz+z8g\n6VFJmySdVhDXFkmPpdePu/oZBw2C9et7/9mY2cAg6TjgHKDoNRDgoYd856tZfzG4nJMlDQKuBo4H\nOoCHJC2IiJW5MpOBgyNijKQJwFxgYg/nzgQWR8RlKWmaCcyUNBY4HRgLjAR+JmlMRESq99yIWCpp\noaS2iFgEPAecDXypyI/wh4hoKbJ/Oy0tWe/R6NF9+pjMrImlSdjXAW0R0eUQ3JAhczjvPNhnH2ht\nbaW1tbVmMZoNZO3t7bS3t/fqnLKSI2A8sCYi1gJImg9MAVbmypwM3AwQEUskDZW0D3BgN+eeDHww\nnX8z0E6WIE0Bbo2ITcBaSWuACZKeA3aLiKXpnFuAU4BFEfFcqn9rX3/IzuTo5JP7WoOZNSNJ+wF3\nAmdGxJruyv7lX86hpQWmTatNbGaWKfwyctFFF/V4TrnDaiOBdbnt9WlfKWVGdHPu8IjYmN5vBIan\n9yNSuWJ15fd3FImjmJ0lPSLpAUlTuirUmRyZ2cAi6Vbgv4BDJK2TdI6kaZI6U5wLgT2BuWl4fmlX\ndU2a5EnZZv1FuT1HpU5TVoll3lJfRISkak2H3i8inpd0IHCvpOUR8Uxhofvvn8N998GcOe4ON6ul\nvnSHV1JETO3h+P8G/ncpdU2aBJdfXpGwzKzKyk2OOoD8TJzRbN+DU6zMqFRmxyL7O9L7jZL2iYgX\nJO0LvNhDXR1sfwttvq687ZKsiHg+/fmspHaghWzdku1ceeUcbr4ZPv952GuvIrWaWVX0pTu8Ub3n\nPbBhA7zyCgwbVu9ozKw75Q6rPQyMkXSApCFkk6UXFJRZAJwFIGki8FoaMuvu3AVkk6hJf/44t/8M\nSUNSb88YYGlEvAD8VtIESQI+nTunk8j1YKW5Tzul93sD7wd+VeyH3GEHOOIILwZpZn03aBAcc4wX\ngzTrD8pKjiJiMzADuBtYAdwWESvzY/IRsRB4Jk2engdM7+7cVPUlwAmSngY+lLaJiBXAD1P5nwLT\n051qpHqvB1aTTfReBCDpGEnrgI8B83KPARhLdofc48C9wMURsaqrn7WlxcmRmZVn4kTPOzLrDxRe\n3bBbkiIiuOkm+PnP4Xvfq3dEZgOXJCKilDmMDaXzOvLv/w5XXgmLF9c7IrOBq5TriFfILpHvWDOz\nck2YAEuXejFIs0bn5KhEY8fCs8/CH/5Q70jMrL96xzvgne+ElSt7Lmtm9ePkqERDhsAhh8Dy5T2X\nNTPryqRJfs6aWaNzctQLHlozs3J5UrZZ43Ny1AtOjsysXF4p26zxOTnqBSdHZlauww6Ddevgtdfq\nHYmZdcXJUS8ccQT86leweXO9IzGz/mrwYBg3zotBmjUyJ0e9sNtuMHIkPPVUvSMxs/5s4kRPyjZr\nZE6OeslDa2ZWLs87MmtsTo56ycmR2cAh6UZJG3OPHSpW5ipJqyU9IamllHonTsyG1bZurVysZlY5\nTo566cgjnRyZDSA3AW1dHZQ0GTg4IsYAnwPmllLp8OGw554eojdrVE6OeqnzAbR+JJ1Z84uI+4FX\nuylyMnBzKrsEGCppeCl1e2jNrHE5Oeql4cNh553huefqHYmZNYCRwLrc9npgVCknelK2WeMaXO8A\n+qPOeUcHHFDvSMysARQ+3btov/KcOXO2vW9tbWXSpFa+850qRmVmALS3t9Pe3t6rcxQeH+qWpCj8\njP7+72GHHeAf/7FOQZkNUJKI
       "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": {}
  }
 ]
}