{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "-" } }, "source": [ "# 信號與系統實習\n", "\n", "\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)前往 https://github.com/htygithub/SS_EXP 點選右下角按鈕 \"Download Zip\"\n", "\n", "(2)將 Zip 檔解壓縮至\"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 jupyter notebook 指令來開啟 Jupyter 視窗\n", "\n", "(5)開啟Lesson_0_Scipy_intro.ipynb 開始以下實驗作答\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 實驗一: Numpy , Matplotlib 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
" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "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。
\n", "(2)再按加號新增一個\"code\"區塊，嘗試畫出 \"三個帽子\"的波形
\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
" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "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。
\n", "(1)請推論 np.arange 這個函數的用處，以及三個輸入值的意義。
\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
" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "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)？
\n", "(新增一個\"Markdown\"區塊，回答此問題)

\n", "(2)又我們如何改變指令，畫出一個 3 Hz的Cosine波呢？
\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
" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "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？
\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
" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "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)
\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", "****************************************************************************************" ] } ], "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": "3.7.10" } }, "nbformat": 4, "nbformat_minor": 1 }