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1 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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2 % Tutorial slides on Python. |
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3 % |
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4 % Author: Prabhu Ramachandran <prabhu at aero.iitb.ac.in> |
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5 % Copyright (c) 2005-2009, Prabhu Ramachandran |
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6 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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7 |
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8 \documentclass[14pt,compress]{beamer} |
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9 %\documentclass[draft]{beamer} |
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10 %\documentclass[compress,handout]{beamer} |
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11 %\usepackage{pgfpages} |
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12 %\pgfpagesuselayout{2 on 1}[a4paper,border shrink=5mm] |
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13 |
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14 % Modified from: generic-ornate-15min-45min.de.tex |
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15 \mode<presentation> |
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16 { |
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17 \usetheme{Warsaw} |
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18 \useoutertheme{split} |
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19 \setbeamercovered{transparent} |
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20 } |
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21 |
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22 \usepackage[english]{babel} |
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23 \usepackage[latin1]{inputenc} |
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24 %\usepackage{times} |
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25 \usepackage[T1]{fontenc} |
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26 |
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27 % Taken from Fernando's slides. |
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28 \usepackage{ae,aecompl} |
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29 \usepackage{mathpazo,courier,euler} |
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30 \usepackage[scaled=.95]{helvet} |
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31 \usepackage{amsmath} |
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32 |
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33 \definecolor{darkgreen}{rgb}{0,0.5,0} |
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34 |
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35 \usepackage{listings} |
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36 \lstset{language=Python, |
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37 basicstyle=\ttfamily\bfseries, |
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38 commentstyle=\color{red}\itshape, |
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39 stringstyle=\color{darkgreen}, |
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40 showstringspaces=false, |
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41 keywordstyle=\color{blue}\bfseries} |
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42 |
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43 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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44 % Macros |
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45 \setbeamercolor{emphbar}{bg=blue!20, fg=black} |
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46 \newcommand{\emphbar}[1] |
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47 {\begin{beamercolorbox}[rounded=true]{emphbar} |
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48 {#1} |
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49 \end{beamercolorbox} |
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50 } |
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51 \newcounter{time} |
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52 \setcounter{time}{0} |
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53 \newcommand{\inctime}[1]{\addtocounter{time}{#1}{\tiny \thetime\ m}} |
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54 |
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55 \newcommand{\typ}[1]{\lstinline{#1}} |
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56 |
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57 \newcommand{\kwrd}[1]{ \texttt{\textbf{\color{blue}{#1}}} } |
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58 |
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59 %%% This is from Fernando's setup. |
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60 % \usepackage{color} |
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61 % \definecolor{orange}{cmyk}{0,0.4,0.8,0.2} |
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62 % % Use and configure listings package for nicely formatted code |
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63 % \usepackage{listings} |
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64 % \lstset{ |
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65 % language=Python, |
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66 % basicstyle=\small\ttfamily, |
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67 % commentstyle=\ttfamily\color{blue}, |
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68 % stringstyle=\ttfamily\color{orange}, |
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69 % showstringspaces=false, |
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70 % breaklines=true, |
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71 % postbreak = \space\dots |
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72 % } |
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73 |
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74 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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75 % Title page |
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76 \title[]{Finding Roots} |
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77 |
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78 \author[FOSSEE] {FOSSEE} |
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79 |
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80 \institute[IIT Bombay] {Department of Aerospace Engineering\\IIT Bombay} |
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81 \date[] {31, October 2009\\Day 1, Session 6} |
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82 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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83 |
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84 %\pgfdeclareimage[height=0.75cm]{iitmlogo}{iitmlogo} |
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85 %\logo{\pgfuseimage{iitmlogo}} |
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86 |
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87 |
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88 %% Delete this, if you do not want the table of contents to pop up at |
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89 %% the beginning of each subsection: |
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90 \AtBeginSubsection[] |
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91 { |
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92 \begin{frame}<beamer> |
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93 \frametitle{Outline} |
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94 \tableofcontents[currentsection,currentsubsection] |
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95 \end{frame} |
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96 } |
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97 |
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98 \AtBeginSection[] |
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99 { |
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100 \begin{frame}<beamer> |
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101 \frametitle{Outline} |
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102 \tableofcontents[currentsection,currentsubsection] |
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103 \end{frame} |
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104 } |
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105 |
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106 % If you wish to uncover everything in a step-wise fashion, uncomment |
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107 % the following command: |
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108 %\beamerdefaultoverlayspecification{<+->} |
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109 |
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110 %\includeonlyframes{current,current1,current2,current3,current4,current5,current6} |
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111 |
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112 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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113 % DOCUMENT STARTS |
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114 \begin{document} |
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115 |
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116 \begin{frame} |
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117 \maketitle |
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118 \end{frame} |
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119 |
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120 %% \begin{frame} |
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121 %% \frametitle{Outline} |
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122 %% \tableofcontents |
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123 %% % You might wish to add the option [pausesections] |
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124 %% \end{frame} |
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125 |
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126 |
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127 \begin{frame}[fragile] |
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128 \frametitle{Roots of $f(x)=0$} |
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129 \begin{itemize} |
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130 \item Roots --- values of $x$ satisfying $f(x)=0$ |
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131 \item $f(x)=0$ may have real or complex roots |
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132 \item Presently, let's look at real roots |
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133 \end{itemize} |
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134 \end{frame} |
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135 |
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136 \begin{frame}[fragile] |
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137 \frametitle{Initial Estimates} |
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138 \begin{itemize} |
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139 \item Find the roots of $cosx-x^2$ between $-\pi/2$ and $\pi/2$ |
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140 \item We shall use a crude method to get an initial estimate first |
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141 \end{itemize} |
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142 \begin{enumerate} |
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143 \item Check for change of signs of $f(x)$ in the given interval |
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144 \item A root lies in the interval where the sign change occurs |
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145 \end{enumerate} |
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146 \end{frame} |
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147 |
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148 \begin{frame}[fragile] |
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149 \frametitle{Initial Estimates \ldots} |
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150 \begin{lstlisting} |
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151 In []: def our_f(x): |
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152 ....: return cos(x)-x**2 |
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153 ....: |
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154 In []: x = linspace(-pi/2, pi/2, 11) |
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155 \end{lstlisting} |
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156 \begin{itemize} |
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157 \item Get the intervals of x, where sign changes occur |
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158 \end{itemize} |
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159 \end{frame} |
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160 |
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161 %% \begin{frame}[fragile] |
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162 %% \frametitle{Initial Estimates \ldots} |
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163 %% \begin{lstlisting} |
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164 %% In []: pos = y[:-1]*y[1:] < 0 |
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165 %% In []: rpos = zeros(x.shape, dtype=bool) |
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166 %% In []: rpos[:-1] = pos |
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167 %% In []: rpos[1:] += pos |
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168 %% In []: rts = x[rpos] |
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169 %% \end{lstlisting} |
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170 %% \end{frame} |
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171 |
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172 \begin{frame}[fragile] |
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173 \frametitle{Fixed Point Method} |
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174 \begin{enumerate} |
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175 \item Convert $f(x)=0$ to the form $x=g(x)$ |
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176 \item Start with an initial value of $x$ and iterate successively |
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177 \item $x_{n+1}=g(x_n)$ and $x_0$ is our initial guess |
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178 \item Iterate until $x_{n+1}-x_n \le tolerance$ |
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179 \end{enumerate} |
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180 \end{frame} |
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181 |
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182 %% \begin{frame}[fragile] |
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183 %% \frametitle{Fixed Point \dots} |
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184 %% \begin{lstlisting} |
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185 %% In []: def our_g(x): |
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186 %% ....: return sqrt(cos(x)) |
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187 %% ....: |
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188 %% In []: tolerance = 1e-5 |
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189 %% In []: while abs(x1-x0)>tolerance: |
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190 %% ....: x0 = x1 |
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191 %% ....: x1 = our_g(x1) |
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192 %% ....: |
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193 %% In []: x0 |
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194 %% \end{lstlisting} |
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195 %% \end{frame} |
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196 |
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197 \begin{frame}[fragile] |
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198 \frametitle{Bisection Method} |
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199 \begin{enumerate} |
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200 \item Start with an interval $(a, b)$ within wphich a root exists |
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201 \item $f(a)\cdot f(b) < 0$ |
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202 \item Bisect the interval. $c = \frac{a+b}{2}$ |
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203 \item Change the interval to $(a, c)$ if $f(a)\cdot f(c) < 0$ |
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204 \item Else, change the interval to $(c, b)$ |
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205 \item Go back to 3 until $(b-a) \le$ tolerance |
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206 \end{enumerate} |
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207 \end{frame} |
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208 |
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209 %% \begin{frame}[fragile] |
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210 %% \frametitle{Bisection \dots} |
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211 %% \begin{lstlisting} |
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212 %% In []: tolerance = 1e-5 |
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213 %% In []: a = -pi/2 |
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214 %% In []: b = 0 |
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215 %% In []: while b-a > tolerance: |
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216 %% ....: c = (a+b)/2 |
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217 %% ....: if our_f(a)*our_f(c) < 0: |
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218 %% ....: b = c |
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219 %% ....: else: |
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220 %% ....: a = c |
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221 %% ....: |
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222 %% \end{lstlisting} |
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223 %% \end{frame} |
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224 |
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225 \begin{frame}[fragile] |
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226 \frametitle{Newton Raphson Method} |
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227 \begin{enumerate} |
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228 \item Start with an initial guess of x for the root |
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229 \item $\Delta x = -f(x)/f^{'}(x)$ |
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230 \item $ x \leftarrow x + \Delta x$ |
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231 \item Go back to 2 until $|\Delta x| \le$ tolerance |
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232 \end{enumerate} |
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233 \end{frame} |
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234 |
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235 %% \begin{frame}[fragile] |
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236 %% \frametitle{Newton Raphson \dots} |
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237 %% \begin{lstlisting} |
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238 %% In []: def our_df(x): |
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239 %% ....: return -sin(x)-2*x |
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240 %% ....: |
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241 %% In []: delx = 10*tolerance |
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242 %% In []: while delx > tolerance: |
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243 %% ....: delx = -our_f(x)/our_df(x) |
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244 %% ....: x = x + delx |
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245 %% ....: |
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246 %% ....: |
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247 %% \end{lstlisting} |
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248 %% \end{frame} |
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249 |
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250 \begin{frame}[fragile] |
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251 \frametitle{Newton Raphson \ldots} |
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252 \begin{itemize} |
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253 \item What if $f^{'}(x) = 0$? |
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254 \item Can you write a better version of the Newton Raphson? |
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255 \item What if the differential is not easy to calculate? |
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256 \item Look at Secant Method |
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257 \end{itemize} |
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258 \end{frame} |
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259 |
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260 \begin{frame}[fragile] |
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261 \frametitle{Scipy Methods - \typ{roots}} |
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262 \begin{itemize} |
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263 \item Calculates the roots of polynomials |
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264 \item Array of coefficients is the only parameter |
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265 \end{itemize} |
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266 \begin{lstlisting} |
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267 In []: coeffs = [1, 6, 13] |
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268 In []: roots(coeffs) |
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269 \end{lstlisting} |
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270 \end{frame} |
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271 |
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272 \begin{frame}[fragile] |
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273 \frametitle{Scipy Methods - \typ{fsolve}} |
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274 \begin{small} |
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275 \begin{lstlisting} |
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276 In []: from scipy.optimize import fsolve |
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277 \end{lstlisting} |
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278 \end{small} |
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279 \begin{itemize} |
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280 \item Finds the roots of a system of non-linear equations |
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281 \item Input arguments - Function and initial estimate |
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282 \item Returns the solution |
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283 \end{itemize} |
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284 \begin{lstlisting} |
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285 In []: fsolve(our_f, -pi/2) |
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286 \end{lstlisting} |
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287 \end{frame} |
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288 |
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289 \begin{frame}[fragile] |
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290 \frametitle{Scipy Methods \dots} |
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291 \small{ |
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292 \begin{lstlisting} |
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293 In []: from scipy.optimize import fixed_point |
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294 |
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295 In []: from scipy.optimize import bisect |
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296 |
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297 In []: from scipy.optimize import newton |
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298 \end{lstlisting}} |
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299 \end{frame} |
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300 |
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301 |
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302 \end{document} |