ans/10219017/Answer_draw_shapes.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cca11c7c",
   "metadata": {},
   "source": [
    "# draw_shapes\n",
    "Jalankan kode pada sel-sel di bawah ini sehingga identitas Anda tertampilkan dengan benar dan gambarkan beberapa bentuk."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f17daa2f",
   "metadata": {},
   "outputs": [],
   "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 = 10219017\n",
    "print(nim, end=' ')\n",
    "print(stu[nim]['name'], end=' ')\n",
    "print(\"https://github.com/\", stu[nim]['github'], sep='')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb234146",
   "metadata": {},
   "source": [
    "<img src=\"Answer for Identity.jpeg\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d1c0d218",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4d42d14",
   "metadata": {},
   "source": [
    "## circle\n",
    "Sebuah lingkaran dengan pusat `(xc, yc)`, radius `r`, berisi warna `#ccf`, garis batas berwarna `k`, tebal garis `2`, dan jenis garis `dashed` digambarkan dengan kode berikut ini."
   ]
  },
  {
   "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": [
    "xc = 1\n",
    "yc = 0\n",
    "r = 0.5\n",
    "circle = plt.Circle(\n",
    "    (xc, yc), radius=r,\n",
    "    fc='#ccf',\n",
    "    lw=2, ls='dashed', color='k'\n",
    ")\n",
    "plt.gca().add_patch(circle)\n",
    "plt.axis('scaled')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "245c36e1",
   "metadata": {},
   "source": [
    "## rectangle\n",
    "Sebuah persegi panjang dengan titik sudut `(x, y)`, lebar `w`, tinggi `h`, berisi warna `y`, garis batas bewarna `r`, jenis garis `dotted`, tebal garis `3` dapat digambarkan dengan kode berikut ini."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "54a23f33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOoAAAD4CAYAAADiinreAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAZ1ElEQVR4nO3dbXBU53n/8e+FQELSSiAkkFcgrZQWaFy7dkCT2k7yN7Gduo0hzsQlAzQp7rhW2rRuEvCkEE8GeTp2/QJcOskktZw2pq7BxQ9TI9yp42DkJoOxR+vSiJpIdiwJiV1LSDxoBUJC4v6/OEdarVY86Czy2Zu9PjNn9uy5VvdeiP1pz8Oes2KMQSmV3mb43YBS6vI0qEpZQIOqlAU0qEpZQIOqlAVm+t0AQElJiamsrPS7DaV8FQ6He4wx8yerpUVQKysraWxs9LsNpXwlIu0Xq+mqr1IW0KAqZQENqlIW0KAqZQENqlIW0KAqZQENqlIWsCOoIs5UUJBci0Ti9bKy5HpLS7y+ZElyPRyO15cvT643NMTrK1Yk1+vr4/VVq5LrO3fG6+vWJdfr6uL1mprk+rZt8frGjcn12tp4vbY2ub5xY7y+bVtyvaYmXq+rS66vWxev79yZXF+1Kl6vr0+ur1gRrzc0JNeXL4/Xw+Hk+pIl8XpLS3K9rCxej0SS6wUF8XosllwfrYkk12Kxq/fau9hzXKG0+MDDFevvp7W1NmFRVleMCnd+eCRGx4T6zI5eyt358+d76ZxQzz4WYaE7PzgUJTKhPjvaRtCdHzjXxkcT6rldzVznzp8920LXhHp+dxMLxtpv4viEekFPmBJ3vi8WpndCvfDEAYrd+dOnD3BiQn3uyQaK3PmTJxs4NaE+7/QB5rjzvSdeo6818cVaHAtT6M739NQTa018sc/vbyLgznd3v8SZ1sSwlJ5tIc+d/6hrJwOtiWG77lwbue58NPoM51obEuplQ1Fy3Pljx55iaF7iC37R+V5mufMdHT9geFZxQr18JDb2Ij56dBsjg4mBCpmhsXejtrbHMYGchHrVuPmJry3pH6TSnb9ghmj3+Nozs2ZwoaKMrBm5eGVXUIH29kcT7mf3MPbLGhnpT6rnRogHdfhEUj0QZSyoQ4PRpPrcLsaCOniuPale3E08qAMtSfUFPYwF9cyZw7S3H06oB3sZC2p/7F3a299NqC86yVhQ+/oO0t5+MKEupxkL6unTb9Le/mZCfWYfY0E9efJ1OttfT6jnxBgLam/vXqLtexPqeWcYC2pPz8t0t7+cUC8YYCyox7ufp3fCZ2uKzjEW1K6uHZyaUC8ZZCyo0ejT9Bcm1kuHGQtqJPJDBrIS62Uj8RdxZ+eTDJ1LrJdfiK82dnQ8wUheYn18UCf+32WdJR7UC0OeX3uD8y5w/Kf3Uf657Xgl6XCFh+rqanPJjxDGYrS1PT7pL1opG4RCW6iqqr3kY0QkbIypnqxmxzZqQQEmkKMhVRnLjqAqleE0qEpNs0AzZDdFJt+rfYWs25mklG2q/wLgaWfyuE/IjqCKUIWzh65hv9/NKPXxsyOoSlksthiyc4LkZAcv/+CL0G1UpaZZuA4ie2pS2ka1I6jG0PrhFl3tVRnLjqAqleE0qEpZQIOq1DSbewhmH2yb/OyhK2THXt9YDOkfJOss+jFCZZ2bvwOww5mu6eOohYVU4pzJoDuUVCayI6hKWezUTZAzO0Tu7ErPY9ixjRoIcCE/m2Hv590q5ZtD2+GjXfentI1qR1BjMdqbNvPL//S7EaX8cdmgisi/iEi3iBwet2yeiLwuIu+7t0XjaptF5AMRaRaRu6ercaUyyZW8oz4D/OGEZZuAfcaYxcA+9z4icj2wBvhd92d+JCITLp6hlJqqywbVGPPfwIkJi+/F2d+Me/vlccufN8YMGmNagQ+AT1+dVpWyU/EByN3XPPlVGq+Q172+pcaYKIAxJioio9fvWgiMv/pWJ/FrhyUQkRqgBqCiomKyh8RFImR1xcjugaGSSz9UqXRz4yMAzztTmhxHnezCpZN2ZoypA+rAubjZJUdduJAKnCu+6XFUlYm8BrVLRILuu2kQ6HaXdxK/OifAImCSqyIrlTl6boW83CXk5U1yAfgr5PXwzB5gvTu/Hnhl3PI1IpIjIlXAYuAdz92NCgYZXhBgsPjyD1Uq3Rx+HLp+snZ6t1FFZBewAigRkU5gC/AEsFtEHgCOAqsBjDH/JyK7gfeAYeCvjDEjnrsbFYnQ0VqbdIFjpTLFZYNqjFl7kdKdF3n8Y8BjqTSllEpkxyeTlMpwGlSlptmCn0P+K02TfxveFbLj7JmWFmZ29JIbgYHyyz9cqXRy/WMALzvTZF+9eQXsCOrSpZTjHPfR46gqE9kRVKUs1nUH5OffQCBwo+cx7Ajq4sWcP9/L+eGJHzlWKv0d+T6EQvcRuMzXLl6KHTuTWlrofOMh3nnW70aU8ocdQVUqw2lQlbKABlWpaRash4JdYair8zyGHTuTwmGyj0UIRKF/qd/NKDU1S58E2OtMNTWexrAjqNXVLMQ5A12Po6pMZEdQlbJY5B4IFCyjsGC55zHsCOqyZQwORRkajPrdiVJT1vIwhEKrKLzmj6OGw0T21BD2vi2ulNXsCKpSGU6DqpQFNKhKTbNFu6HwJwdg2zbPY9ixM6mhgdnRNuZ2wamb/W5Gqan57R8DvO5MGzd6GsOOoH7+8wSBIHocVWUmO4KqlMU6VkNh4S3MmXOb5zHsCOrttzNwro3Bc+1+d6LUlP3mmxAK3c2ca/44akMDH+26n0Pb/W5EKX/YEVSlMpwGVSkLaFCVmmaVz8Dc7Q1QW+t5DDt2JtXXk9vVTHE39HrfcaaULyp3ALzpTB7DakdQv/QlrgOuQ4+jqsxkR1CVsljbepgz53aKilZ4HsOOoK5cydmzLZwdaPG7E6WmrO1+CIVWUJTCcVQ7glpfT5d+P6rKYLrXVykLaFCVsoAdq75KWey3fgSFha/BnJjnc1LtCOrOneR3N7GgB7rv8rsZpaam/AWAg87kR1BF5DvAnwMGaAL+DMgD/h2oBNqArxpjTqbyPPzJn7AAWIAGVWUmz0EVkYXA3wDXG2MGRGQ3sAa4HthnjHlCRDYBm4C/vSrdKmWhD/4Sioq+QPG8uz2Pkeqq70wgV0TO47yTRoDNwAq3vgNoINWgrl1Lf38TZ84cTmkYpfzQ+VXICt1GcZW3y7BACkE1xhwTka3AUWAA+Jkx5mciUmqMibqPiYrIgsl+XkRqgBqAioqKSz/Zzp0cb62lvV2DqjKT58MzIlIE3AtUAWVAvoh87Up/3hhTZ4ypNsZUz58/32sbSmWEVI6j3gW0GmOOG2POAy8DtwFdIhIEcG+7U29TqcyWyjbqUeAWEcnDWfW9E2gEzgDrgSfc21dSbVIpmy3ZCoGCeiiIeP6O1FS2Ud8WkReBd4Fh4H+AOiAA7BaRB3DCvNrrc4ypq6OgJ0ywF6KrUh5NqY9V2avgxOTdjz+oAMaYLcCWCYsHcd5dr55vfIMSoAQNqspMdnwySSmLNW+A4uKVlJR4f5exI6gPPkhfLEx/7F2/O1FqyqKrIDu0nJKqGs9j2BHUujp6W2tpb9egqsykp7kpZQENqlIWsGPVVymLffLvID//JQi0wM6dnsawI6jbtlF44gCLTjofcFbKJqVvABx2pms6qA8/TDFQjAZVZSY7gqqUxd57BEpKvsKCBfd5HsOOoG7YwOnTB+jrO+h3J0pNWfddkBu6EarWeR7DjqBu28aJ1lra2zWoKjPp4RmlLKBBVcoCdqz6KmWxG74Hebm7IC8M9fWexrAjqLW1zD3ZgJx2vnBHKZuUvAXQ4k7e2BHURx+lCChCg6oykx1BVcpiTY/B/AVruK70Wj88s2ULJ082cPr0m353otSU9d4GgdBSqLrWTxyvreVUay3t7RpUlZn08IxSFtCgKmUBO1Z9lbLYzd+GnNnPwOwGaGjwNIYdQd24kXmnDzCzD37zTb+bUWpq5v4vQLs7eWNHUJ98kjnAHDSoKjPZEVSlLHboH6C0dD3B4P2ex7AjqFu30nviNU6efN3vTpSaslM3w5xQJVSt8DyGHUHduJG+1hid7RpUlZn08IxSFtCgKmUBO1Z9lbLY8hrIzqmD7HoIhz2NYUdQa2oojoXJiUHLw343o9TUFLwPEHUnb+wI6tNPUwgUokFVmcmOoCplscZ/gmDwQRYu/IbnMewI6lNP0dNTT2/vXr87UWrK+pfCUKgMqpZ7HsOOoNbUEGuNEG3XoKrMlNLhGRGZKyIvisivReSIiNwqIvNE5HURed+9LbpazSqVqVI9jvqPwH8ZY34HuAk4AmwC9hljFgP73PtKqRR4DqqIFAL/D/hnAGPMkDHmFHAvsMN92A7gy6m1qJTdPv11WHTHD2DJEs9jpLKN+gngOPBTEbkJCAPfAkqNMVEAY0xURBZM9sMiUgPUAFRUVFz6mdatY35/E3ln4Mj3U+hYKR/kdQKccCdvUln1nQksA35sjPkUcIYprOYaY+qMMdXGmOr58+df+sG7dhGoP+x+IaxSmSeVoHYCncaYt937L+IEt0tEggDubXdqLSplt7f/FTp+/tfQ3Ox5DM+rvsaYj0SkQ0SWGmOagTuB99xpPfCEe/uK5+5GPfcc3d0v0dPzcspDKfVxGyiH4VAxVPmzjQrwEPCciGQDHwJ/hvMuvVtEHgCOAqtTfA5Yt44zrS10t2tQVWZKKajGmENA9SSlO1MZVymVSM9HVcoCGlSlptmtfwzlt2yDsjLPY9jxWd9Vqyg920LBABx+3O9mlJqanF6Afnfyxo6g7t1LHpDndx9K+URXfZWaZgdegKNvbYBjxzyPYcc76p49fNS1k+Pdz/vdiVJTNlQCI6UFmbGNOtAaptf7V3coZTVd9VXKAhpUpSygQVVqmn32ixC68e+hoMDzGHZso65YwXXn2ig6B4e2+92MUlMzcwBgyJ08jnG1mplWb75JLpDrdx9K+URXfZWaZr94Fdp+tQn6+jyPYcc76v79RKPP0NW14/KPVSrNjOSBCeRkxjbqudYGTulxVJWhdNVXKQtoUJWygAZVqWm24vNQ9YlHQcTzGHZsoy5fTtlQlJJBCNf53YxSHz87gvruu+QAOX73oZRPdNVXqWnWsB9aP9wCxngew4531MZGjh17imj0ab87UcoXdgR1+XKG5pXRX+h3I0r5Q1d9lbKABlWpaZZ1FqR/EGIxz2NoUJWaZp+7Byp/7wko9L7tZsc26pIlLDrfS+kwvPOs380o9fGzI6jvv88sYJbffSjlwXAuzJiRzQzJ9jyGrvoqNc1++Z/Q3rQ5pW1UO95Rm5vp6PgBkcgP/e5EKV/YEdQlSxieVcxAlt+NKOUPXfVVygIaVKWmWXYPZHXFIBLxPIYdq75KWey21QBPOpPHD+bbEdSyMspHYpSNwFsv+t2MUh+/lIMqIllAI3DMGLNSROYB/w5UAm3AV40xJ1N6kmiUmdjyV0WpRIPFkJUVYGaW96sQXo1t1G8BR8bd3wTsM8YsBva595XKWG+9CB0HN6a0jZpSUEVkEXAP8JNxi+8FRi/AuwP4cirPAcCxYxx9awMHXkh5JKWslOo76nbgu8CFcctKjTFRAPd2wWQ/KCI1ItIoIo3Hjx+/9LOUlTFSWsBQSYrdKmUpz0EVkZVAtzEm7OXnjTF1xphqY0z1/PnzvbahVEZIZf/MZ4AvicgXgdlAoYj8G9AlIkFjTFREgkD31WhUKVvldsDMkV443wJLlngaw/M7qjFmszFmkTGmElgDvGGM+RqwB1jvPmw98IrX51DqWvD7fwrld/0Qli71PMZ0HPF4AtgtIg8AR4HVKY9YUEDIDFF+wTkTQalMc1WCaoxpABrc+V7gzqsx7pj+fmagn3dUdjq7CGbNnMesWcWex9DXvlLT7J1nofONh6ClxfMYdgS1r4+2X23iF6/63YhS/rAjqAUFmEAOI3l+N6KUP+wIqlIZToOq1DQLNEN2UwTCnj4bBOgJKUpNu+q/AHjama7p81FFqAKqcL4ZS6lMY0dQlbJYbDFk5wTJyQ56HkO3UZWaZuE6iOypSWkb1Y6gGkPrh1t0tVdlLDuCqlSG06AqZQENqlLTbO4hmH2wDRoaPI9hx17fWAzpHyTrLPoxQmWdm78DzuXDdlzjx1ELC6nEuf6o7lBSmciOoCplsVM3Qc7sELmzKz2PYcc2aiDAhfxshnP9bkSpqTu0HT7adX9K26h2BDUWo71ps16GRWUsO4KqVIbToCplAQ2qUtOs+ADk7muG+nrPY9ix1zcSIasrRnYP+rUWyjo3PgLwvDNd08dRFy6kAqhAj6OqzGRHUJWyWM+tkJe7hLw8b19nAbYENRhkeCTGyEi/350oNWWHH4dQaC1VVbWex7BjZ1IkQsfBjbz1ot+NKOUPO4KqVIbToCplAQ2qUtNswc8h/5Um2LnT8xh27ExqaWFmRy+5ERgo97sZpabm+scAXnamdes8jWFHUJcupRwoR4+jqsxkR1CVsljXHZCffwOBwI2ex7AjqIsXc/58L+eHT/jdiVJTduT7EArdR+CaP47a0kLnGw/xzrN+N6KUP+wIqlIZznNQRaRcRPaLyBER+T8R+Za7fJ6IvC4i77u3RVevXaUyUyrvqMPARmPMJ4FbgL8SkeuBTcA+Y8xiYJ97X6mMFayHgl1hqKvzPIbnnUnGmCgQdedjInIEWAjcC6xwH7YDaAD+1nOHAOEwpd/dRdUbzt229dB2f+JDfutHUP6CM//BX0LnVxPrS7ZC2avOfPMGiK5KrH/y76DUHf+9R6D7rsT6Dd+Dkrec+abHoPe2xPrN34a5/+vMH/oHOHVzYn15DRS878w3/hP0L02sf/rrkNfpzL/9r8nHi2/9Y8jpdeYPvJB8Xu5nvwgzB5z5X7yafP3jFZ+Pz088xJV1Fj53jzM/nEvStamye+C21c78YDFJn7nO7YDf/1Nn/uwikvYlBJpHvyPU+Waz8ITX69xDo9e+da7Yd2h7Yr34wOg5nc6ZKIcfT6wv+PnosUpnD+uR7yfWg/Ww9ElnPnIPtDycWF+0G377x858x2r4zTcT65XPQOUOZ97La8957r3OVFODF1dlr6+IVAKfAt4GSt0QY4yJisiCi/xMDVADUFFRceknqK8n742Wsbtz5txOKLQi4SGFha8BBwEoKvoCWaHEJAUK6oF3ASguXkl2aHlCPT//JeAwACUlXyE3lLgrPS93F+D0MH/BGgKhxKTlzH4GaAegtHQ9c0KVCfXsnDrcv2sEgw8yFCpLqM+a+QPA2atdVvbXDIeKE+pZWdsA5+yhRYs2MFJakFCfMePvgSEAyss3YQI5JHp0bC4U2pJQkf5B4Al3nGxCoc2Jzz07Bjzp9hEgFNqYUJ850gv80P13zCMUeijx394XwfkiX+frB0OhxBfr7Ggbzt9057KaodD9CfXcD5pxTrx2ThcLhdYm1PNLmnA+UOAcBgmF7kuoFxSHcYICgYJlhEKJf6ULiw4ArzvzhbcQCt2dUJ8zpwF4052f+mtv4LPPkvvLD0mJMSalCQgAYeAr7v1TE+onLzfG8uXLzWVt2WKMc368Mz/Rhg3x+tatyfUHH4zXn3oqub52bbz+3HPJ9ZUr4/U9e5Lrt98er+/fn1xftixeb2xMri9eHK83NyfXg8F4/dix5HogEK/39SXXR2uQXOvri9cCgeT6sWPxejCYXG9ujtcXL06uNzbG68uWJdf374/Xb789ub5nT7y+cmVy/bnn4vW1a5PrTz0Vrz/4YHJ969Z4fcOG5PrVfO1dAtBoLpIRMR4vDQEgIrNw/lS9Zox50l3WDKwwzrtpEGgwxiy91DjV1dWmsbHRcx9KXQtEJGyMqZ6slspeXwH+GTgyGlLXHmC9O78eeMXrcyilHKlso34G+DrQJCKH3GXfw9nY2S0iDwBHgdUpdaiUSmmv7y8BuUj5Tq/jKqWS6SeTlLKABlUpC2hQlbKABlUpC6R0HPWqNSFynNGP9VxcCdDzMbRztWi/0+ta7DdkjJk/WSEtgnolRKTxYgeD05H2O70yrV9d9VXKAhpUpSxgU1C9n8znD+13emVUv9ZsoyqVyWx6R1UqY2lQlbJA2gXV1oumiUiWiPyPiOx176dtvyIyV0ReFJFfu7/nW9O83++4r4XDIrJLRGanU78i8i8i0i0ih8ctu2h/IrJZRD4QkWYRuXvyUROlXVCx96Jp3wKOjLufzv3+I/BfxpjfAW7C6Tst+xWRhcDfANXGmBuALGAN6dXvM8AfTlg2aX/ua3kN8Lvuz/xIRLIu+wwXu/RDukw4J55/AWgGgu6yINDsd2/jelzk/mfcAex1l6Vlv0Ah0Iq7I3Hc8nTtdyHQAczDOS1zL/AH6dYvUAkcvtzvE9gMbB73uNeAWy83fjq+o4651EXTgEkvmuaT7cB3gQvjlqVrv58AjgM/dVfVfyIi+aRpv8aYY8BWnIsQRIHTxpifkab9jnOx/kb/8IzqdJddUtoGVUQCwEvAt40xfX73czEishLoNsaE/e7lCs0ElgE/NsZ8CjhDmqzmTsbdtrsXqALKgHwR+Zq/XaVksostXPYYaVoG1b1o2kvAc8aYl93FXe7F0nBvu/3qb4LPAF8SkTaca1reISL/Rvr22wl0GmPedu+/iBPcdO33LqDVGHPcGHMe57qgt5G+/Y66WH+dON8gOmoRELncYGkXVNsummaM2WyMWWSMqcTZSfCGMeZrpG+/HwEdIjJ6Zcg7gfdI035xVnlvEZE897VxJ87Or3Ttd9TF+tsDrBGRHBGpAhYD71x2NL93FkyyUf5ZnFWBXwGH3OmLQDHODpv33dt5fvc6Se8riO9MStt+gZuBRvd3/B9AUZr3+yjwa5wrpD8L5KRTv8AunO3n8zjvmA9cqj/gEeA3ODuc/uhKnkM/QqiUBdJu1VcplUyDqpQFNKhKWUCDqpQFNKhKWUCDqpQFNKhKWeD/A/kW6qnuoCOXAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = 20\n",
    "y = 20\n",
    "w = 80\n",
    "h = 90\n",
    "rectangle = plt.Rectangle(\n",
    "    (x, y), w, h,\n",
    "    fc='y',\n",
    "    color='r', ls='dotted', lw=3\n",
    ")\n",
    "plt.gca().add_patch(rectangle)\n",
    "plt.axis('scaled')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "184aa2b4",
   "metadata": {},
   "source": [
    "## line\n",
    "Sebuah garis lurus yang menghubungkan titik `(x1, y1)` dan `(x2, y2)` dengan warna garis `#aca`, tebal `1`, dan jenis garis `solid` dapat diperoleh menggunakan kode berikut ini."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e5023430",
   "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": [
    "x1 = 10\n",
    "y1 = 20\n",
    "x2 = 50\n",
    "y2 = 60\n",
    "line = plt.Line2D((x1, x2), (y1, y2), color='#4c4', lw=1, ls='solid')\n",
    "plt.gca().add_line(line)\n",
    "plt.axis('scaled')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6426f3ed",
   "metadata": {},
   "source": [
    "## shapes\n",
    "Untuk mendapatkan gambar di bawah ini\n",
    "\n",
    "![](draw_3_shapes.png)\n",
    "\n",
    "lengkapi kode berikut."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "637475be",
   "metadata": {},
   "source": [
    "## Jawaban"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "63618a80",
   "metadata": {
    "scrolled": true
   },
   "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": [
    "import math\n",
    "\n",
    "xc = 20\n",
    "yc = 20\n",
    "r = 10\n",
    "circle = plt.Circle(\n",
    "    (xc, yc), radius=r,\n",
    "    fc='#ccf',\n",
    "    lw=2, ls='dashed', color='k'\n",
    ")\n",
    "plt.gca().add_patch(circle)\n",
    "\n",
    "x = 80\n",
    "y = 80\n",
    "w = 20\n",
    "h = 20\n",
    "rectangle = plt.Rectangle(\n",
    "    (x, y), w, h,\n",
    "    fc='b',\n",
    "    color='r', ls='solid', lw=4\n",
    ")\n",
    "plt.gca().add_patch(rectangle)\n",
    "\n",
    "x1 = 27\n",
    "y1 = 27\n",
    "x2 = 80\n",
    "y2 = 80\n",
    "line = plt.Line2D((x1, x2), (y1, y2), color='#4c4', lw=2, ls='solid')\n",
    "plt.gca().add_line(line)\n",
    "\n",
    "plt.axis('scaled')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cc30a2f4",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}