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   "execution_count": 1,
   "metadata": {},
   "outputs": [
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       "<style>\n",
       "\n",
       "    /* DOWNLOAD COMPUTER MODERN FONT JUST IN CASE */\n",
       "    @font-face {\n",
       "        font-family: \"Computer Modern\";\n",
       "        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunss.otf');\n",
       "    }\n",
       "    @font-face {\n",
       "        font-family: \"Computer Modern\";\n",
       "        font-weight: bold;\n",
       "        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunsx.otf');\n",
       "    }\n",
       "    @font-face {\n",
       "        font-family: \"Computer Modern\";\n",
       "        font-style: oblique;\n",
       "        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunsi.otf');\n",
       "    }\n",
       "    @font-face {\n",
       "        font-family: \"Computer Modern\";\n",
       "        font-weight: bold;\n",
       "        font-style: oblique;\n",
       "        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunso.otf');\n",
       "    }\n",
       "\n",
       "    /* GLOBAL TEXT FONT */\n",
       "    div#notebook,\n",
       "    div.output_area pre,\n",
       "    div.output_wrapper,\n",
       "    div.prompt {\n",
       "      font-family: Times new Roman, monospace !important;\n",
       "    }\n",
       "\n",
       "    /* CENTER FIGURE */\n",
       "    .output_png {\n",
       "        display: table-cell;\n",
       "        text-align: center;\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    /* LINK */\n",
       "    a {\n",
       "        color: #FF8000;\n",
       "    }\n",
       "\n",
       "    /* H1 */\n",
       "    h1 {\n",
       "        font-size: 42px !important;\n",
       "        text-align: center;\n",
       "        color: #FF8000;\n",
       "    }\n",
       "\n",
       "    /* H2 */\n",
       "    h2 {\n",
       "        font-size: 32px !important;\n",
       "    }\n",
       "\n",
       "    /* H2 */\n",
       "    h3 {\n",
       "        font-size: 24px !important;\n",
       "    }\n",
       "\n",
       "    /* H2 */\n",
       "    h4 {\n",
       "        font-size: 20px !important;\n",
       "    }\n",
       "\n",
       "    /* PARAGRAPH */\n",
       "    p {\n",
       "        font-size: 16px !important;\n",
       "        text-align: center;\n",
       "    }\n",
       "\n",
       "    /* LIST ITEM */\n",
       "    li {\n",
       "        font-size: 16px !important;\n",
       "    }\n",
       "\n",
       "</style>\n",
       "\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
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    }
   ],
   "source": [
    "%run ../../../common_functions/import_all.py\n",
    "\n",
    "import time\n",
    "from common_functions.setup_notebook import set_css_style, setup_matplotlib, config_ipython\n",
    "\n",
    "config_ipython()\n",
    "setup_matplotlib()\n",
    "set_css_style()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sorting algorithms\n",
    "\n",
    "We will illustrate how different sorting algorithms work, using a sample array."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# we will use the sample array\n",
    "\n",
    "array = [6, 5, 3, 1, 8, 7, 2, 4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mergesort\n",
    "\n",
    "Note that this implementation, which is recursive, is inspired by [[1]](#mergesort-so)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4, 5, 6, 7, 8]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def mergesort(my_array):\n",
    "\n",
    "    if len(my_array) == 1:\n",
    "        return my_array\n",
    "\n",
    "    new = []\n",
    "    n = len(my_array)\n",
    "    midpoint = int(n/2)\n",
    "\n",
    "    right = mergesort(my_array[:midpoint])\n",
    "    left = mergesort(my_array[midpoint:])\n",
    "\n",
    "    while len(right) > 0 and len(left) > 0:\n",
    "            if right[0] > left[0]:\n",
    "                new.append(left[0])\n",
    "                left.pop(0)\n",
    "            else:\n",
    "                new.append(right[0])\n",
    "                right.pop(0)\n",
    "     \n",
    "    new += right + left\n",
    "        \n",
    "    return new\n",
    "\n",
    "mergesort(array)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bubble sort\n",
    "\n",
    "An implementation which is also recursive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4, 5, 6, 7, 8]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def bubblesort(my_array):\n",
    "    \n",
    "    my_array_copy = my_array.copy()\n",
    "    n = len(my_array_copy)\n",
    "    \n",
    "    if (all([my_array_copy[i] < my_array_copy[i+1] for i in range(n-1)])):\n",
    "        return my_array_copy\n",
    "        \n",
    "    for i in range(n-1):\n",
    "        if my_array_copy[i] > my_array_copy[i + 1]:\n",
    "            my_array_copy[i], my_array_copy[i+1] = my_array_copy[i+1], my_array_copy[i]\n",
    "   \n",
    "    my_array_copy = bubblesort(my_array_copy)\n",
    "\n",
    "    return my_array_copy\n",
    "\n",
    "bubblesort(array)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Insertion sort"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4, 5, 6, 7, 8]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def insertionsort(my_array):\n",
    "    \n",
    "    my_array_copy = my_array.copy()\n",
    "    n = len(my_array_copy)\n",
    "    \n",
    "    for i in range(1, n):\n",
    "        for j in range(i):\n",
    "            if my_array_copy[i] < my_array_copy[j]:\n",
    "                my_array_copy[i], my_array_copy[j] = my_array_copy[j], my_array_copy[i]\n",
    "                \n",
    "    return my_array_copy\n",
    "\n",
    "insertionsort(array)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quicksort"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This code here is admittedly awful (quite imperative). Also note that unlike the previous ones, this method is modifying the original array so to not lose the original order it is better to pass a copy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('original array', [7, 1, 3, 8, 2, 0])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[0, 1, 2, 3, 7, 8]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def quicksort(my_array, pivot_index, end_index):\n",
    "            \n",
    "    my_array_slice = my_array[pivot_index: end_index]\n",
    "        \n",
    "    if len(my_array_slice) <= 1:\n",
    "        return\n",
    "    \n",
    "    pivot = my_array[pivot_index]\n",
    "                \n",
    "    l, r = pivot_index + 1, end_index - 1\n",
    "\n",
    "    while l <= r - 1:\n",
    "                \n",
    "        i = r\n",
    "        while i > pivot_index:\n",
    "            if my_array[i] < pivot:\n",
    "                break\n",
    "            i -= 1\n",
    "        r = i\n",
    "                \n",
    "        i = l\n",
    "        while i < end_index:\n",
    "            if my_array[i] >= pivot:\n",
    "                break\n",
    "            i += 1\n",
    "        l = i\n",
    "\n",
    "        if l <= r:\n",
    "            my_array[l], my_array[r] = my_array[r], my_array[l]\n",
    "        \n",
    "    if l < r:\n",
    "        my_array[l], my_array[pivot_index] = my_array[pivot_index], my_array[l]\n",
    "    elif l == r:\n",
    "        if my_array[l] < my_array[pivot_index]:\n",
    "            my_array[l], my_array[pivot_index] = my_array[pivot_index], my_array[l]\n",
    "    else:\n",
    "        my_array[r], my_array[pivot_index] = my_array[pivot_index], my_array[r]\n",
    "\n",
    "    new_pivot_index = my_array.index(pivot)\n",
    "    my_array_slice = my_array[pivot_index: end_index]\n",
    "    \n",
    "    right = my_array_slice[pivot_index: new_pivot_index]\n",
    "    left = my_array_slice[my_array_slice.index(pivot) + 1:]\n",
    "    \n",
    "    quicksort(my_array, 0, len(right))\n",
    "    quicksort(my_array, new_pivot_index + 1, new_pivot_index + 1 + len(left))\n",
    "            \n",
    "    return\n",
    "\n",
    "array_copy = array.copy()\n",
    "array_copy = [7, 1, 3, 8, 2, 0]\n",
    "('original array', array_copy)\n",
    "quicksort(array_copy, 0, len(array_copy))\n",
    "array_copy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What does Python use\n",
    "\n",
    "The `sort` and `sorted` built-in methods in Python use a very efficient algorithm called Timsort [[5]](#timsort), designed by Tim Peters specifically for use in Python itself in 2002. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Measurement time (!)\n",
    "\n",
    "Let's measure the time taken by the implementations we wrote above, and by timsort, on arrays of different length. Note that we wanted to use bubblesort as well but our implementation easily exceeds recursion limits! So we will use mergesort, insertion sort and timsort. \n",
    "\n",
    "From the plot below you can see both the quadratic trend of insertion sort, and the fact that timsort is the most efficient one. Note that our implementation of mergesort includes some calls to `.pop`, which may add some overhead."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now let's run these\n",
    "\n",
    "Going to run all these codes on arrays of various lengths, scaling as powers of ten, and measuring the time taken. Note that the implementations above may add some unneeded overhead give the way they've been written so the results here shouldn't be taken at face value. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "mergesort_t = []\n",
    "bubblesort_t = []\n",
    "insertionsort_t = []\n",
    "quicksort_t = []\n",
    "timsort_t = []\n",
    "\n",
    "#n_range = [10, 100, 1000, 10000]\n",
    "n_range = np.arange(1, 1000, 100)\n",
    "\n",
    "for n in n_range:\n",
    "    \n",
    "    an_array = random.sample(range(n), n)\n",
    "    \n",
    "    t = time.process_time()\n",
    "    sorted_array = mergesort(an_array)\n",
    "    mergesort_t.append(time.process_time() - t)\n",
    "    \n",
    "    t = time.process_time()\n",
    "    sorted_array = bubblesort(an_array)\n",
    "    bubblesort_t.append(time.process_time() - t)\n",
    "    \n",
    "    t = time.process_time()\n",
    "    sorted_array = insertionsort(an_array)\n",
    "    insertionsort_t.append(time.process_time() - t)\n",
    "    \n",
    "    t = time.process_time()\n",
    "    sorted_array = quicksort(an_array.copy(), 0, len(an_array))\n",
    "    quicksort_t.append(time.process_time() - t)\n",
    "    \n",
    "    t = time.process_time()\n",
    "    sorted_array = sorted(an_array)\n",
    "    timsort_t.append(time.process_time() - t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 396,
       "width": 899
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "\n",
    "plt.semilogy(n_range, mergesort_t, marker='o', label='mergesort')\n",
    "plt.plot(n_range, bubblesort_t, marker='o', label='bubblesort')\n",
    "\n",
    "plt.plot(n_range, insertionsort_t, marker='o', label='insertionsort')\n",
    "plt.plot(n_range, quicksort_t, marker='o', label='quicksort')\n",
    "plt.plot(n_range, timsort_t, marker='o', label='timsort')\n",
    "\n",
    "plt.legend()\n",
    "plt.title('Time taken by sorting algorithm versus length of array')\n",
    "plt.xlabel('Array length')\n",
    "plt.ylabel('Seconds')\n",
    "plt.savefig('sorting.png', dpi=200)\n",
    "plt.show();"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}