{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Chapter 1 Introduction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Ex1.2 page 7" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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Z3glmlgM8BrQHmgGXmplqz2OUlweLFsHIkWHZVhHJPrF0uXX3ZRCKRnvRGljh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\nEUnY/wfincqi2HtregAAAABJRU5ErkJggg==\n", 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zSqtNKpV6UQalGaUeKUqERNwskLoJUSyVjBEXsRql4OLq9yywyPFtRqknijwt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\nmKgbhmEkxP8H1mfQrGLrivYAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from numpy import arange\n", "%matplotlib inline\n", "from matplotlib.pyplot import plot,title,xlabel,ylabel,show,figure,text\n", "from math import sin,pi,sqrt\n", "\n", "#Figure 1.2: Analog to Digital Conversion\n", "t = arange(-1,1.01,0.01)\n", "x = [2*sin((pi/2)*tt) for tt in t]\n", "dig_data = [0,1,0,0,0,0,1,0,0,0,0,0,0,0,1,1,0,1,0,1]\n", "figure=figure()\n", "#a=gca()#\n", "#a.x_location =\"origin\"#\n", "#a.y_location =\"origin\"#\n", "#a.data_bounds =[-2,-3#2,3]\n", "plot(t,x)\n", "text(0.5,sqrt(2),'gnn')\n", "text(-0.5,-sqrt(2),'gnn')\n", "text(1,2,'gnn')\n", "text(-1,-2,'gnn')\n", "xlabel(' Time')\n", "ylabel(' Voltage')\n", "title('Analog Waveform')\n", "show()\n", "plot(range(1,len(dig_data)+1),dig_data)\n", "title('Digital Representation')\n", "show()\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.9" } }, "nbformat": 4, "nbformat_minor": 0 }