{
 "cells": [
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   "source": [
    "#數位邏輯與應用實習 (3/3)\n",
    "\n",
    "有任何問題隨時舉手發問，助教及老師會協助你解決。\n",
    "\n",
    "若想要在家中電腦執行以下程式，請前往 https://store.continuum.io/cshop/anaconda/ 下載Anaconda Python 軟體\n",
    "\n",
    "實驗開始步驟：\n",
    "\n",
    "(1)點右上角按鈕下載此份文件\"ipython notebook\"\n",
    "\n",
    "(2)將 EECS_exp3.ipynb 存放至\"我的文件\"\n",
    "\n",
    "(3)按下開始工具列->附屬應用程式->命令提示字元 來開啟命令列視窗\n",
    "\n",
    "(4)於命令列鍵入 ipython notebook 指令來開啟 Jupyter 視窗\n",
    "\n",
    "(5)開啟EECS_exp3.ipynb 開始以下實驗作答\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##實驗一: Python 程式語言初見面\n",
    "\n",
    "用滑鼠點選以下程式碼，並按下\"Play\"鈕執行看看結果<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#coding: utf-8\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x=np.array([0,0,0,0,1,1,1,1,0,0,0,0])\n",
    "plt.plot(x,'ro-')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##問題一\n",
    "(1)按加號新增一個\"Markdown\"區塊，描述你看到了什麼。 <br>\n",
    "(2)再按加號新增一個\"code\"區塊，嘗試畫出 \"三個帽子\"的波形<BR>\n",
    "(按加號後，點選 'Cell Toolbar' 左方是下拉式選單，選擇 CODE)\n",
    "****************************************************************************************"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##實驗二: Python 之資料顯示以及np 陣列\n",
    "用滑鼠點選以下程式碼，並按下\"Play\"鈕執行看看結果<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#coding: utf-8\n",
    "import numpy as np\n",
    "\n",
    "t=np.arange(0,1,0.1)\n",
    "print t\n",
    "print \"這是 np.arange(0,1,0.1)的結果:\" + str(t)\n",
    "print \"加上一些換行字元\\n\\n\\n\" + \"換行的結果是這樣\\n\"\n",
    "t=np.arange(0,1,0.01)\n",
    "print \"這是 np.arange(0,1,0.01)的結果:\"\n",
    "print t\n",
    "sumt=sum(np.arange(0,10,1))\n",
    "print \"\\n\\n\\n這是 sum(np.arange(0,10,1))的結果:\" +str(sumt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "##問題二\n",
    "新增一個\"Markdown\"區塊，將以下問題之答案寫下來。<BR>\n",
    "(1)請推論 np.arange 這個函數的用處，以及三個輸入值的意義。<BR>\n",
    "(2)新增一個\"code\"區塊，利用python 程式碼，計算100以下偶數之總合。\n",
    "****************************************************************************************\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "##實驗三 : 弦波的頻率以及繪圖\n",
    "用滑鼠點選以下程式碼，並按下\"Play\"鈕執行看看結果<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#coding: utf-8\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "t=np.arange(0,1,0.01)\n",
    "pi=np.pi\n",
    "curve=np.sin(2*pi*10*t)\n",
    "curve2=np.sin(2*pi*5*t)\n",
    "plt.plot(t,curve,'b',t,curve2,'r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##問題三\n",
    "\n",
    "(1)假設橫軸時間單位為秒，請問curve及curve2各為幾Hz弦波(也就是在一秒內走了幾個週期)？<br>\n",
    "(新增一個\"Markdown\"區塊，回答此問題)<BR><BR>\n",
    "(2)又我們如何改變指令，畫出一個 3 Hz的Cosine波呢？<BR>\n",
    "(新增一個\"CODE\"區塊，回答此問題)\n",
    "****************************************************************************************"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##實驗四 : 影像以及RGB色彩\n",
    "用滑鼠點選以下程式碼，並按下\"Play\"鈕執行看看結果<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#coding: utf-8\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x=np.array([0,0,0,1,1,1,1,0,0,0])\n",
    "y=np.array([x,x,x,x,x,x,x,x,x,x])\n",
    "print y\n",
    "print y.shape\n",
    "plt.figure(1)\n",
    "plt.imshow(y,cmap='gray',interpolation='nearest')\n",
    "y=np.array([x/5.,x/4.,x/3.,x/2.,x/1.,x,x,x,x,x])\n",
    "plt.figure(2)\n",
    "plt.imshow(y,cmap='gray',interpolation='nearest')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##問題四\n",
    "(1)請問y 矩陣的大小為何？<br>\n",
    "(2)試完成一個10x10的矩陣，顯示一個白色十字。\n",
    "(新增一個\"CODE\"區塊，回答此問題)\n",
    "****************************************************************************************"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##實驗五 :RGB色彩\n",
    "用滑鼠點選以下程式碼，並按下\"Play\"鈕執行看看結果<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#coding: utf-8\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x=np.array([0,0,0,1,1,1,1,0,0,0])\n",
    "y=np.array([x,x,x,x,x,x,x,x,x,x])\n",
    "z=np.zeros([10,10,3])\n",
    "z[:,:,0]=y \n",
    "plt.figure(figsize=[15,5])\n",
    "plt.subplot(1,4,1)\n",
    "plt.imshow(z,interpolation='nearest')\n",
    "#######################################\n",
    "z=np.zeros([10,10,3])\n",
    "z[:,:,1]=y\n",
    "plt.subplot(1,4,2)\n",
    "plt.imshow(z,interpolation='nearest')\n",
    "#######################################\n",
    "z=np.zeros([10,10,3])\n",
    "z[:,:,2]=y\n",
    "plt.subplot(1,4,3)\n",
    "plt.imshow(z,interpolation='nearest')\n",
    "#######################################\n",
    "z=np.zeros([10,10,3])\n",
    "z[:,:,0]=y\n",
    "z[:,:,1]=y\n",
    "plt.subplot(1,4,4)\n",
    "plt.imshow(z,interpolation='nearest')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##問題五\n",
    "以上範例是將紅光、綠光、藍光分別開至最大亮度 (數值1)<br>\n",
    "若是將紅、綠、藍分別以1, 0.5, 0  來表示, 試著新增一組程式碼完成配色，並說明合成的顏色為？\n",
    "\n",
    "****************************************************************************************"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##實驗六 :照片中的RGB色彩\n",
    "(1)前往 http://mri.ee.ntust.edu.tw ->course --> 電機基礎實作測試資料 下載924-lena.zip\n",
    "\n",
    "(2)將zip解壓後存放至 EECS_exp3.ipynb之相同目錄\n",
    "\n",
    "(3)用滑鼠點選以下程式碼，並按下\"Play\"鈕執行看看結果<br>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#coding: utf-8\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.misc as misc\n",
    "\n",
    "lena_img=misc.imread('lena_std.jpg');\n",
    "\n",
    "print lena_img.shape\n",
    "plt.figure(figsize=[15,5])\n",
    "plt.subplot(1,4,1)\n",
    "plt.imshow(lena_img)\n",
    "plt.title('Original')\n",
    "\n",
    "plt.subplot(1,4,2)\n",
    "plt.imshow(lena_img[:,:,2],cmap='gray')\n",
    "plt.title('Fig. 1');\n",
    "plt.subplot(1,4,3)\n",
    "plt.imshow(lena_img[:,:,1],cmap='gray')\n",
    "plt.title('Fig. 2');\n",
    "plt.subplot(1,4,4)\n",
    "plt.imshow(lena_img[:,:,0],cmap='gray')\n",
    "plt.title('Fig. 3');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##問題六\n",
    "(1)Fig.1 , 2, 3 代表Lena 圖其中的三原色，若紅光影像數值愈高者(愈白愈亮)，代表該像素的中的紅光成份愈高。<br>\n",
    "請用肉眼觀察以及程式碼的觀察，來說明Fig. 1, 2,3 各代表 R、G、B 中的那一原色。<br>\n",
    "(2)新增一個code 區塊，將Lena影像中的紅色影像減少20%。<BR>\n",
    "(hint: lena_img[:,:,X]=lena_img[:,:,X]*0.9, 就代表將X色光通道減弱 10%)\n",
    "\n",
    "****************************************************************************************"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##介面範例：\n",
    "恭喜你，做到這步實驗課就結束囉。通知助教來檢查。最後這個範例你可以執行看看，用滑鼠調整RGB值，來觀察影像。\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#coding: utf-8\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import scipy.misc as misc\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.html.widgets import interact, interactive, fixed\n",
    "from IPython.display import display\n",
    "\n",
    "\n",
    "lena_img=misc.imread('lena_std.jpg')\n",
    "\n",
    "lims = (0.1,1.0,0.1)\n",
    "\n",
    "\n",
    "def edit_image( r=1.0, g=1.0, b=1.0):\n",
    "    lena_img2=lena_img*0\n",
    "    lena_img2[:,:,0] = r*lena_img[:,:,0]\n",
    "    lena_img2[:,:,1] = g*lena_img[:,:,1]\n",
    "    lena_img2[:,:,2] = b*lena_img[:,:,2]\n",
    "    plt.imshow(lena_img2)\n",
    "    #return lena_img2\n",
    "\n",
    "w = interactive(edit_image, r=lims, g=lims, b=lims)\n",
    "display(w)\n"
   ]
  }
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