bgrenet · October 4, 2016 09:50
diff --git a/Quicksort.ipynb b/Quicksort.ipynb
 {
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from random import randint\n",
    "from IPython.display import clear_output\n",
    "from ipywidgets import interact, interactive, fixed\n",
    "import ipywidgets as widgets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def my_plot(t, fig, axe):\n",
    "    clear_output(wait = True)\n",
    "    axe.clear()\n",
    "    axe.plot(range(len(t)), t, \"k.\");\n",
    "    display(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def partition(t, i, j):\n",
    "    pivot = t[i]\n",
    "    l = []\n",
    "    u = []\n",
    "    for k in range(i+1, j+1):\n",
    "        if t[k] <= pivot:\n",
    "            l.append(t[k])\n",
    "        else:\n",
    "            u.append(t[k])\n",
    "    return t[:i]+l+[pivot]+u+t[j+1:], i+len(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def quicksort(t, trace=False):\n",
    "    def quicksort_rec(t, i, k):\n",
    "       \n",
    "        if i < k:\n",
    "            j = randint(i, k)\n",
    "            t[i], t[j] = t[j], t[i]\n",
    "            t, j = partition(t, i, k)\n",
    "\n",
    "            if trace and (len(T) == 0 or t != T[-1]): T.append(t)\n",
    "\n",
    "            t = quicksort_rec(t, i, j)\n",
    "            t = quicksort_rec(t, j+1, k)\n",
    "        return t\n",
    "    \n",
    "    #x = list(range(len(t)))\n",
    "    #fig = plt.figure()\n",
    "    #axe = fig.add_subplot(111);\n",
    "    if trace: T = [t]\n",
    "    t = quicksort_rec(t, 0, len(t)-1)\n",
    "    if trace:\n",
    "        return t,T\n",
    "    return t\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "162"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = list(range(200))\n",
    "shuffle(t)\n",
    "u, T = quicksort(t, trace=True)\n",
    "len(T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bd4a79e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "axe = fig.add_subplot(111)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6bd4a79e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def _plot(i=0):\n",
    "    my_plot(T[i], fig, axe)\n",
    "slider = interactive(_plot, i=(0,len(T)-1))\n",
    "bouton = widgets.Button(description=\"Next step\")\n",
    "def click(b):\n",
    "    slider.children[0].value += 1\n",
    "bouton.on_click(click)\n",
    "display(slider, bouton)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "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": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
 }
	{
	"cells": [
	{
	"cell_type": "code",
	"execution_count": 1,
	"metadata": {
	"collapsed": false
	},
	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"Populating the interactive namespace from numpy and matplotlib\n"
	]
	}
	],
	"source": [
	"%pylab inline"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 2,
	"metadata": {
	"collapsed": true
	},
	"outputs": [],
	"source": [
	"from random import randint\n",
	"from IPython.display import clear_output\n",
	"from ipywidgets import interact, interactive, fixed\n",
	"import ipywidgets as widgets"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 3,
	"metadata": {
	"collapsed": true
	},
	"outputs": [],
	"source": [
	"def my_plot(t, fig, axe):\n",
	" clear_output(wait = True)\n",
	" axe.clear()\n",
	" axe.plot(range(len(t)), t, \"k.\");\n",
	" display(fig)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 4,
	"metadata": {
	"collapsed": true
	},
	"outputs": [],
	"source": [
	"def partition(t, i, j):\n",
	" pivot = t[i]\n",
	" l = []\n",
	" u = []\n",
	" for k in range(i+1, j+1):\n",
	" if t[k] <= pivot:\n",
	" l.append(t[k])\n",
	" else:\n",
	" u.append(t[k])\n",
	" return t[:i]+l+[pivot]+u+t[j+1:], i+len(l)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 5,
	"metadata": {
	"collapsed": true
	},
	"outputs": [],
	"source": [
	"def quicksort(t, trace=False):\n",
	" def quicksort_rec(t, i, k):\n",
	" \n",
	" if i < k:\n",
	" j = randint(i, k)\n",
	" t[i], t[j] = t[j], t[i]\n",
	" t, j = partition(t, i, k)\n",
	"\n",
	" if trace and (len(T) == 0 or t != T[-1]): T.append(t)\n",
	"\n",
	" t = quicksort_rec(t, i, j)\n",
	" t = quicksort_rec(t, j+1, k)\n",
	" return t\n",
	" \n",
	" #x = list(range(len(t)))\n",
	" #fig = plt.figure()\n",
	" #axe = fig.add_subplot(111);\n",
	" if trace: T = [t]\n",
	" t = quicksort_rec(t, 0, len(t)-1)\n",
	" if trace:\n",
	" return t,T\n",
	" return t\n",
	" \n"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 6,
	"metadata": {
	"collapsed": false
	},
	"outputs": [
	{
	"data": {
	"text/plain": [
	"162"
	]
	},
	"execution_count": 6,
	"metadata": {},
	"output_type": "execute_result"
	}
	],
	"source": [
	"t = list(range(200))\n",
	"shuffle(t)\n",
	"u, T = quicksort(t, trace=True)\n",
	"len(T)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 7,
	"metadata": {
	"collapsed": false,
	"scrolled": true
	},
	"outputs": [
	{
	"data": {
	"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXkAAAEACAYAAABWLgY0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMSMvSY39H2x3icMl2bwzAAAAAElFTkSuQmCC\n",
	"text/plain": [
	"<matplotlib.figure.Figure at 0x7f6bd4a79e10>"
	]
	},
	"metadata": {},
	"output_type": "display_data"
	}
	],
	"source": [
	"fig = plt.figure()\n",
	"axe = fig.add_subplot(111)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 8,
	"metadata": {
	"collapsed": false
	},
	"outputs": [
	{
	"data": {
	"image/png": 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	"text/plain": [
	"<matplotlib.figure.Figure at 0x7f6bd4a79e10>"
	]
	},
	"metadata": {},
	"output_type": "display_data"
	}
	],
	"source": [
	"def _plot(i=0):\n",
	" my_plot(T[i], fig, axe)\n",
	"slider = interactive(_plot, i=(0,len(T)-1))\n",
	"bouton = widgets.Button(description=\"Next step\")\n",
	"def click(b):\n",
	" slider.children[0].value += 1\n",
	"bouton.on_click(click)\n",
	"display(slider, bouton)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": null,
	"metadata": {
	"collapsed": true
	},
	"outputs": [],
	"source": []
	},
	{
	"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": "2.7.10"
	}
	},
	"nbformat": 4,
	"nbformat_minor": 0
	}
No results found