06 Jupyter 的互動介面.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6. Jupyter 的互動介面\n",
    "\n",
    "Jupyter 非常酷、非常炫的互動功能!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Dictionary\n",
    "\n",
    "開始互動之前, 我們來補一個 Python 很重要、但我們還沒介紹的 `dictionary` 資料型態。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mydict = {'apple':'蘋果', 'banana':'香蕉'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple': '蘋果', 'banana': '香蕉'}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mydict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 查字典"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'蘋果'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mydict['apple']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 加字進去"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mydict['orange'] = '橘子'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'apple': '蘋果', 'banana': '香蕉', 'orange': '橘子'}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mydict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 字典裡內容一一列出"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "apple: 蘋果\n",
      "banana: 香蕉\n",
      "orange: 橘子\n"
     ]
    }
   ],
   "source": [
    "for key in mydict:\n",
    "    print(key + \": \" + mydict[key])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Jupyter 很炫的互動\n",
    "\n",
    "在 Jupyter 做互動功能非常容易, 基本上只要做一個有引數的函數, 互動的世界就開啟了。\n",
    "\n",
    "首先, 請善用 `tab` 鍵打入以下指令..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from ipywidgets import interact, interact_manual"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 定義你要互動的函數\n",
    "\n",
    "我們來定個再簡單不過的..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def f(x):\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 然後就可以互動!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n"
     ]
    }
   ],
   "source": [
    "interact(f, x=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 有小數的數值滑桿"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.3\n"
     ]
    }
   ],
   "source": [
    "interact(f, x=3.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 自訂範圍的數值滑桿"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n"
     ]
    }
   ],
   "source": [
    "interact(f, x=(-5,5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### [提示]\n",
    "\n",
    "1. 要有小數的相信大家也會做了!\n",
    "2. 可以輸入 `x=(-5,5,2)` 看會發生什麼事?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 文字輸入框"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "天氣\n"
     ]
    }
   ],
   "source": [
    "interact(f, x=\"你好\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 輸入一個 list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "台南\n"
     ]
    }
   ],
   "source": [
    "interact(f, x=['台北', '台中', '台南', '高雄', '花蓮'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 輸入一個字典"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n"
     ]
    }
   ],
   "source": [
    "interact(f, x={'台北':1, '台中':2, '台南':3})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 小結論\n",
    "\n",
    "1. 我們發現, 一個資料結構就會對應一個「合理」的互動介面。\n",
    "2. 如果熟悉網頁 HTML, 就知道基本上可以在網頁呈現的互動方式都可以做出來。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 實用 (?) 的例子\n",
    "\n",
    "我們來個耍寶的例子。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def move(n):\n",
    "    print(\" \"*n + \"oooo\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          oooo\n"
     ]
    }
   ],
   "source": [
    "move(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              oooo\n"
     ]
    }
   ],
   "source": [
    "interact(move, n=(1,50))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. 動態繪圖\n",
    "\n",
    "互動功能當然也可以用在繪圖上!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = np.linspace(0, 10, 1000)\n",
    "\n",
    "def draw(n):   \n",
    "    y = np.sin(n*x)\n",
    "    plt.plot(x,y, lw=3)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### [注意]\n",
    "\n",
    "平常用了 `%matplot inline` 我們不用加 `plt.show()` 就可以畫出圖, 這裡一定要加的原因是不加互動會有悲劇發生。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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XmahGnc4xk4B2hiGBt6uLe04yGQEzAylRaGygDQF1k3HOgAMgntYVFibWrCTy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\nGQYHBwcHBwn/Pzc3Gb4CKeXiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1178d45f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interact(draw, n=(1., 20.))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 按鈕後再動作\n",
    "\n",
    "有時我們想要參數都設好了, 按個鈕再動作。這時我們可以用\n",
    "\n",
    "    interact_manual\n",
    "    \n",
    "用法和 `interact` 基本上是一樣的!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "02466693935f4c92a64d0a73062a50fb"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.draw>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interact_manual(draw, n=(1.,20.))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. 練習: BMI 計算器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def 計算BMI(身高,體重):\n",
    "    身高 = float(身高)\n",
    "    體重 = float(體重)\n",
    "    bmi = 體重/(身高/100)**2\n",
    "    print(\"你的 BMI = %.2f\" % bmi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "你的 BMI = 34.26\n"
     ]
    }
   ],
   "source": [
    "interact_manual(計算BMI, 身高=\"請輸入你的身高\", 體重=\"請輸入你的體重\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}