ans/10219082/draw_shapes-checkpoint.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": 1,
   "id": "4e2d555c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10219082 Rahmalia Nur Azizah https://github.com/RahmaliaNur\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 = 10219082\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 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": 4,
   "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": 5,
   "id": "54a23f33",
   "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": [
    "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": 6,
   "id": "e5023430",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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nUYMTEf8CLAK/Bl4C9gF/QO8ky4V0uaHqca4xhz+n9zfWGWA+fe1u0jyAPwWeTXM4C/x9Ot6YOayYz8d5+wRdo+YAvA94Ln39FPhSEfPwx2XNOqKub+PNrGCO3awjHLtZRzh2s45w7GYd4djNOsKxm3XE/wPDur/b6p5/VAAAAABJRU5ErkJggg==\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": "code",
   "execution_count": 18,
   "id": "63618a80",
   "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": [
    "import math\n",
    "\n",
    "# draw circle\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",
    "\n",
    "# draw rectangle\n",
    "x = 80\n",
    "y = 80\n",
    "w = 20\n",
    "h = 20\n",
    "rectangle = plt.Rectangle(\n",
    "    (x, y), w, h,\n",
    "    fc='y',\n",
    "    color='r', ls='solid', lw=3\n",
    ")\n",
    "plt.gca().add_patch(rectangle)\n",
    "\n",
    "\n",
    "# draw line\n",
    "x1 = 28\n",
    "y1 = 27\n",
    "x2 = 80\n",
    "y2 = 80\n",
    "line = plt.Line2D((x1, x2), (y1, y2), color='#4c4', lw=1, ls='solid')\n",
    "plt.gca().add_line(line)\n",
    "\n",
    "\n",
    "plt.axis('scaled')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d49af705",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}