ans/10219101/draw_polygon.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cca11c7c",
   "metadata": {},
   "source": [
    "# draw_polygon\n",
    "Jalankan kode pada sel-sel di bawah ini sehingga identitas Anda tertampilkan dengan benar dan gambarkan sebuah poligon."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4e2d555c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10219101 Muhammad Ervandy Rachmat https://github.com/ErvandyR\n"
     ]
    }
   ],
   "source": [
    "from IPython.core.display import HTML\n",
    "HTML(\"<script>Jupyter.notebook.kernel.restart()</script>\")\n",
    "\n",
    "import sys, os\n",
    "sys.path.insert(1, os.path.join(sys.path[0], '../..'))\n",
    "\n",
    "from src.student import Students as stu\n",
    "nim = 10219101\n",
    "print(nim, end=' ')\n",
    "print(stu[nim]['name'], end=' ')\n",
    "print(\"https://github.com/\", stu[nim]['github'], sep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d1c0d218",
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4d42d14",
   "metadata": {},
   "source": [
    "## polygon\n",
    "Poligon digambarkan dengan titik-titik $(x_1, y_1)$, $(x_2, y_2)$, $\\dots$, $(x_N, y_N)$, bila terdapat $N$ buah titik."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "86684f45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "R = 10\n",
    "N = 6\n",
    "dq = 2 * math.pi / N\n",
    "q0 = 0\n",
    "\n",
    "points = []\n",
    "\n",
    "for i in range(N):\n",
    "    q = i * dq + q0\n",
    "    x = R * math.cos(q)\n",
    "    y = R * math.sin(q)\n",
    "\n",
    "    p = [x, y]\n",
    "    points.append(p)\n",
    "    \n",
    "line = plt.Polygon(\n",
    "    points, closed=True,\n",
    "    fill=None,\n",
    "    edgecolor='r', lw=2\n",
    ")\n",
    "plt.gca().add_patch(line)\n",
    "plt.axis('scaled')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4fd87e5",
   "metadata": {},
   "source": [
    "## rotating hexagonal\n",
    "Heksagonal hasil dari kode sebelumnya dapat digambarkan dengan sisi miringnya menjadi searah dengan arah vertikal seperti di bawah ini."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "40a29a42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/CnCQiDQKui7nUkHQe6EFeAZYqaoPlrBM09hyiEjnWE1bgqzLuVQR9F7orkB/YJmILI4992fgx/D/7WUvBH4vInuBXUC/WKtZ51wpgu4LPYf41z4qvsyjwKNB1uFcqvKZWM5FmAfYuQjzADsXYR5g5yLMA+xchHmAnYswD7BzEeYBdi7CPMDORZgH2LkI8wA7F2EeYOcizAPsXIR5gJ2LMA+wcxHmAXYuwqqiJ1ZPEVktItkiMjzO6yIij8ReXyoiHYOuyblUEXRPrDRgNNALyAAuFpGMfRbrBaTHblcDjwdZk3OpJOg1cGcgW1XXqeoe4CWgzz7L9AGeUzMXaCAizQKuy7mUEHSAmwOfF3ucy/5XZijLMt7Y3bk4gg5wvIZ2+3acLMsy3tjduTiCDnAu0LLY4xbAhgos45yLI+gALwDSRaSNiNQC+gGT91lmMnBZbG/0KcA2Vd0YcF3OpYSg+0LvFZEhwFtAGjBWVVeIyKDY608AU4DeQDaQBwwIsibnUknQV2YovN7RlH2ee6LYfQUGB12Hc6nIZ2I5F2EeYOcizAPsXIR5gJ2LMA+wcxHmAXYuwjzAzkWYB9i5CPMAOxdhHmDnIswD7FyEeYCdizAPsHMR5gF2LsI8wM5FmAfYuQgL7IR+Efkb8AtgD7AWGKCqW+MslwPsAPKBvaqaGVRNzqWaINfA04HjVPUEYA1w8wGWPVNVT/LwOlc+gQVYVd9W1b2xh3OxbpPOuQSqqm3ggcDUEl5T4G0RWSQiV5f0Ad7Y3bn9VWobWERmAE3jvHSLqk6KLXMLsBd4voSP6aqqG0TkCGC6iKxS1dn7LqSqY4AxAJmZmfs1fneuOqpUgFX1nAO9LiKXA+cBZ8e6T8b7jA2xr5tEZCJ2PaX9Auyc219gQ2gR6QkMA36pqnklLFNXROoX3gd6AMuDqsm5VBPkNvCjQH1sWLxYRJ4AEJEjRaSwT3QTYI6ILAHmA2+q6rQAa3IupQR2HFhVjynh+Q3YlRhQ1XXAiUHV4Fyq85lYzkWYB9i5CPMAOxdhHmDnIswD7FyEeYCdizAPsHMR5gF2LsI8wM5FmAfYuQjzADsXYR5g5yLMA+xchHmAnYswD7BzERZkR47bRWR97GT+xSLSu4TleorIahHJFpHhQdXjXCoK7IT+mFGqen9JL4pIGjAa6A7kAgtEZLKqfhxwXc6lhLCH0J2BbFVdp6p7gJeAPgn55IKChHyMc4FJwL/RoAM8RESWishYEflRnNebA58Xe5wbe24/5e4L/cADcNttsHNnRep2Ljj5+fD003B1iW3Qy6xSARaRGSKyPM6tD/A4cDRwErAReCDeR8R5rqT2s2NUNVNVMxs3blxyUQMHwiWXwO7d8Ne/Qrt28MILEL+rrXNV67334OST4aqrYNMm6NoV7rij4p+nqoHfgNbA8jjPdwHeKvb4ZuDm0j6vU6dOWqo5c1Q7dVK16KqeeqrqggWlv8+5IHz6qepvflP077FlS9WXXlItKCj1rcBCLSELQe6Fblbs4fnE7/e8AEgXkTYiUgvoB0xOSAFdu8L8+TB2LDRpAh98YP/zDRgAGzcm5Fs4V6qdO+Evf7GR4L/+BYccArffDqtWwW9+AxJvEFoOJSW7sjfgH8AyYCkWymax548EphRbrjd29cK12CVZSv3sMq2Bi9u2TXXYMNVatex/v3r1VO+5R3X37vJ9jnNlVVCg+sILqi1aFK11+/WzNXE5cYA1cJUMoRN9K3eAC2VlqfbpU/QLPfpo1YkTyzSMca7MFixQ7dq16N9Zx46q771X4Y87UIDDPoxUtY45Bl57Dd5+GzIyYO1aOP986N4dlvsVXVwlffGF7UTt3Bnefx+OOAKeeQYWLIDTTgvkW1avABfq3h2WLIG//x1+9COYORNOPBGGDIEtW8KuzkXNd9/BffdB27bw7LNQsyb86U+QlWWBrhFczKpngMF+yUOG2C95yBDbmTB6NKSnW7C//z7sCl2yU4VJk+DYY2HYMNixA375S1ixwgJ96KGBl1B9A1zo8MMtsIsXw9lnwzffwHXXwUknwfTpYVfnktWKFdCjB/Tta5tiGRnw1lsW6PT0KivDA1zouOMssK+9BkcfDR9/bH+gPn0gOzvs6lyy+PpruPZa2+SaMcM2wR55xFYAPXpUeTke4OJELLArVsC990K9ejB5sv3vOmwYbN8edoUuLHv3Fm1iPfqoDZ8HD7ZNsGuvhYMOCqUsD3A8tWvDTTfZH2fAAPvjFe6kGDvWT5SobmbMsE2qIUNsDXzWWbbGffRR2wQLkQf4QJo2tcDOnw+nngpffgm/+13RYQKX2rKzbRu3e3cblR11FEycaIE+/viwqwM8wGWTmQlz5thJES1awKJFdlzv4ovhs8/Crs4l2o4dMHy47V2eNMk2pe65x/aL9O1b+emPCeQBLisRC+yqVXaa4sEHw0svQfv2djZJXl7YFbrKKiiw47jp6bYPZM8euOIKWLPG9oHUrh12hfvxAJdX3boW2MLJ6Lt22eT09u1tsrr6aYuR9MEHtmk0cKBtKnXpYptOzz4LzZqV/v6QeIArqlUrWwPPng0/+Ql8/jn06wdnnGFDbBcNubnw29/a2WuLFkHz5vD887aP4+STw66uVB7gyjr9dJvr+tRTNvd1zhz7w195pf1P7pJTXh6MHFnU8OHgg2HECFi92hpCJNF27oF4gBMhLc0Cu2YN/PGPNk3zmWdsW+pvf7O5si45qMLLL0OHDnaebl4eXHSRbRKNHGmbSBHiAU6kww6zwC5fDuedZ3szb7rJZnm9/rpvH4ftv/+Fn/3M9l189pkd2501y/ZdtGoVdnUV4gEOQtu2FtipU23nVna2TXLv2dMORbiqtWmT9aDq1Ml6UjVuDGPGwMKFts8iwoJsqfOvYk3dc0RkcQnL5YjIsthyC4OqJxQ9e8LSpfDww9CggZ2HfMIJdrLE11+HXV3q27PHupOmp1sXyLQ0uOEG29S56ip7HHUlnemfyBvWkfK2El7LARqV5/Mq3JEjTF99pfr736vWqGFdGho2VB09WvX778OuLPUUFKi+/rpqenpRV4xzz1VdtSrsyiqEMDtyiIgAFwEvBv29klqjRvDYY7YdduaZtgYePNgOQc2cGXZ1qWPlSujVC37xC5vL3q4dTJkCb7xh91NMVWwDnw58qapZJbyuwNsiskhESux0Xe7G7snqhBMssBMmQJs2tsPrnHPgV7+CdevCri66vvkGhg61OcpvvWU7FEeNgmXLLNCpqqRVc1luwAysXey+tz7FlnkcuPEAn3Fk7OsRwBLgjNK+bySH0PHs2qV6992qdevaMK9WLdXhw1W3bw+7suj4/nvVxx5TPfxw+x3WqKE6aJDqpk1hV5YwhNWVErt42pdAizIufzvwx9KWS5kAF1q/XvWyy4q215o2VR03TjU/P+zKktvMmarHH1/0e+vWTXXx4rCrSrgDBTjoIfQ5wCpVzY33oojUFZH6hfeBHsRvAJ/ajjwSxo+HefPgpz+17oZXXAGnnAIffhh2dcln3Tq44AJrgbRsGbRuDa++Cu+8Y50yqpGgA9yPfXZeiciRIjIl9rAJMEdElgDzgTdVdVrANSWvzp1tUv0//mGhXrDAzkO+9FKbs1vdffst3HKLdUiZMMFmTd11l+24uuCCyEx/TKiSVs3JfEu5IXQ8O3ao3nqrau3aNjysU0f1r39VzcsLu7Kql5+vOn68arNmRcPl/v1Vc3PDrqxK4I3dI6hePbu64sqVcOGFNmd3xAibw/vKK9VnWubcuXZq3+WX2zWtOne2zYrnnrMzh6o5D3Cya9PGAvvuu3YI6tNPbfJ9t27WlylVrV8P/fsXnZfbrJmF9sMPbd+AAzzA0dGtG3z0ETz5pE0KmT0bOnaEa66xub6pYtcu265t2xb++U/rgvHnP9v0x/79A73KQRT5byNK0tLsqu5ZWXD99fZ4zBib6/vggzb3N6pU4d//th1Ut95qmwwXXGCbEHfdZZsUbj8e4Chq0MACWzjLaPt2uPFGm4U0ZUqpb086S5bY9NILL4ScHPs53nnHDg21aRN2dUnNAxxl7dtbYN980+b5rlkD555roV61KuzqSvfVVzBokG0KzJplPZYff9w2Fc48M+zqIsEDnAp697bTFh980OYAT5tma7Hrr4etW8Oubn979tg85fR026avUcPmMWdlWaBr1gy7wsjwAKeKWrUssGvW2HZyfj489FBRSPLzw67QTJ1qe9NvuAG2bYOf/9z+8xk1yq4z5MrFA5xqjjjCAvvRR9Y+ZvPmomHqf/4TXl2rV9vwvndvu5+ebqf4TZ1qx7ZdhXiAU9VJJ9mx41desX5PS5cW7Sj65JOqq2PrVtvBdtxxtr1+6KFw//12GuW551bP6Y8J5AFOZSIW2JUrbVZXnTp2qKZDBztU8+23wX3v/PwfHuLKz7c2NllZFuhatYL73tWIB7g6OOQQC+yaNXZixHff2bHVdu3sxIlEX21x1ixrIHfNNTaEP/10a5o+ZowN8V3CeICrk+bNLbAffGDN5zdsgMsuszOe5s2r/Ofn5BRN81yyBH78Y2vZOmuWtQ5yCecBro66dLGTBMaNs0uozptn84svv9xCXV47d9qJFu3b2zb3IYdYk/RVqyzQvp0bGA9wdVWjhgV2zRq4+WbbJn3uOZuDfPfdsHt36Z+hatcRatcO7rzThuaXXGJ7mUeMsCC7QHmAq7v69S2wK1fC+efb2vSWW2xH14QJJZ+2uGCBXRDs0kvtzKHMTLsg2PPPQ8uWVfszVGOVCrCI/FpEVohIgYhk7vPazSKSLSKrReTnJby/oYhMF5Gs2Fc/kh+Wo46ywM6caYd8cnKK2tYsXVq03MaN1u6n8LzcJk3sEpzz5tm2tKtaJZ3pX5Yb0AFoB/wHyCz2fAbWYbI20AZYC6TFef99wPDY/eHAvWX5vtWiI0eYCjs9NmyoP+j0eNddqvXq6f930Bw2THXbtrCrTXkE3ZUyToBvBm4u9vgtoEuc960GmsXuNwNWl+X7eYCryJYtqtddp5qWVtTKBlT79lXNzg67umrjQAEOahu4OfB5sce5sef21URVNwLEvpZ4kDBlGrtHScOGdl2npUuhRw849liYPh0mToSjjw67Oof1bT4gEZkBNI3z0i2qOqmkt8V5rlJNnFR1DDAGIDMzs5o0hEoSGRl2hlNBQWpcECyFlBpgVT2nAp+bCxTfFdkCiHeA8UsRaaaqG0WkGZBCvWFSjIiHNwkFNYSeDPQTkdoi0gZIx/o+x1vu8tj9y4GS1ujOuTgqexjpfBHJBboAb4rIWwCqugJ4GfgYmAYMVtX82HueLnbI6R6gu4hkAd1jj51zZSQawf7CmZmZunBhal0L3LmSiMgiVc2M95rPxHIuwjzAzkWYB9i5CPMAOxdhkdyJJSJfAZ+GXUc5NQI2h11EJaXCzwDR+zlaqWrjeC9EMsBRJCILS9qTGBWp8DNA6vwc4ENo5yLNA+xchHmAq86YsAtIgFT4GSB1fg7fBnYuynwN7FyEeYCdizAPcBURkdtFZL2ILI7deoddU3mISM9Yg8JsERkedj0VISI5IrIs9vtPibNhfBu4iojI7cC3qnp/2LWUl4ikAWuwUz5zgQXAxar6caiFlZOI5GC926I0ieOAfA3syqIzkK2q61R1D/AS0Cfkmhwe4Ko2RESWisjYiPXALmuTwmSnwNsiskhErg67mETwACeQiMwQkeVxbn2Ax4GjgZOAjcADYdZaTglvUhiSrqraEegFDBaRM8IuqLJKbWrnyq6sDQBF5CngjYDLSaSyNilMaqq6IfZ1k4hMxDYNZodbVeX4GriKxLpuFjofWB5WLRWwAEgXkTYiUgvohzUkjAwRqSsi9QvvAz2I1t8gLl8DV537ROQkbOiZA1wTajXloKp7RWQIdoWNNGBsrHFhlDQBJopd6rQm8IKqTgu3pMrzw0jORZgPoZ2LMA+wcxHmAXYuwjzAzkWYB9i5CPMAOxdhHmDnIuz/AHWjLNUPDVS6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "R = 10\n",
    "N = 6\n",
    "dq = 2 * math.pi / N\n",
    "q0 = 0\n",
    "\n",
    "points = []\n",
    "\n",
    "for i in range(N):\n",
    "    q = i * dq + q0\n",
    "    x = R * math.sin(q)\n",
    "    y = R * math.cos(q)\n",
    "\n",
    "    p = [x, y]\n",
    "    points.append(p)\n",
    "    \n",
    "line = plt.Polygon(\n",
    "    points, closed=True,\n",
    "    fill=None,\n",
    "    edgecolor='r', lw=2\n",
    ")\n",
    "plt.gca().add_patch(line)\n",
    "plt.axis('scaled')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9461815c",
   "metadata": {},
   "source": [
    "Modifikasi kode di atas agar diperoleh gambar berikut ini.\n",
    "\n",
    "![](hexagonal_vertical.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a4346a7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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