ketch/Accuracy and stability comparison.ipynb

## Accuracy and stability comparison.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from nodepy import rk\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ssp75 = rk.loadRKM('SSP75')\n",
    "bs85 = rk.loadRKM('BS5')\n",
    "Merson54 = rk.loadRKM('Merson43')\n",
    "ssp54 = rk.loadRKM('SSP54'); ssp54.p=4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error constants:\n",
      "SSP54: 0.00643865899439\n",
      "Merson54: 0.00570544330735\n",
      "SSP75: 0.00270977330321\n",
      "bs85: 2.21693277847e-05\n"
     ]
    }
   ],
   "source": [
    "print('Error constants:')\n",
    "print('SSP54: '+str(ssp54.principal_error_norm()))\n",
    "print('Merson54: '+str(Merson54.principal_error_norm()))\n",
    "print('SSP75: '+str(ssp75.principal_error_norm()))\n",
    "print('bs85: '+str(bs85.principal_error_norm()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x113c5a750>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x111ddf450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112902150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f=ssp54.plot_stability_region();\n",
    "Merson54.main_method.plot_stability_region();\n",
    "plt.title('Merson')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1143d3f90>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0ayNih6Q3Al8ClgAXRcT1JZdltmCNCSdARFwJXFl2HVbMn+cs1qRurVmjOJxWCn+es5jD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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1140081d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11433edd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ssp75.plot_stability_region();\n",
    "bs85.main_method.plot_stability_region();\n",
    "plt.title('Bogacki')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}