From 54c3980bf73911fff449bbbc47ce64dc124122d0 Mon Sep 17 00:00:00 2001 From: Prabhu Ramachandran Date: Sun, 20 Jun 2010 18:23:34 -0400 Subject: Updating session4, adding example for computation of norm and SVD. --HG-- branch : scipy2010 --- day1/session4.tex | 61 +++++++++++++++++++++++++++---------------------------- 1 file changed, 30 insertions(+), 31 deletions(-) diff --git a/day1/session4.tex b/day1/session4.tex index 5aa66d4..66dd049 100644 --- a/day1/session4.tex +++ b/day1/session4.tex @@ -74,12 +74,13 @@ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Title page -\title[Matrices \& Curve Fitting]{Python for Science and Engg: Matrices \& Least Square Fit} +\title[Matrices \& Curve Fitting]{Python for Science and Engg: Matrices +\& Least Squares Fit} \author[FOSSEE] {FOSSEE} \institute[IIT Bombay] {Department of Aerospace Engineering\\IIT Bombay} -\date[] {30 April, 2010\\Day 1, Session 4} +\date[] {SciPy 2010, Introductory tutorials\\Day 1, Session 4} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %\pgfdeclareimage[height=0.75cm]{iitmlogo}{iitmlogo} @@ -164,7 +165,7 @@ Out[]: array([[ 1., 0.], [ 0., 1.]]) \end{lstlisting} -Also available \alert{\typ{zeros, zeros_like}} +Also available \alert{\typ{zeros, zeros_like, empty, empty_like}} \end{small} \end{frame} @@ -209,7 +210,7 @@ array([[11, 12, 13], [31, 32, 33]]) \end{lstlisting} \end{small} -How to access one \alert{column}? +How do you access one \alert{column}? \end{frame} \begin{frame}[fragile] @@ -444,32 +445,31 @@ Out[]: array([-1., 8., -1.]) \end{small} \end{frame} -%% \begin{frame}[fragile] -%% \frametitle{Computing Norms} -%% \begin{lstlisting} -%% In []: norm(e) -%% Out[]: 8.1240384046359608 -%% \end{lstlisting} -%% \end{frame} +\begin{frame}[fragile] +\frametitle{Computing Norms} +\begin{lstlisting} +In []: norm(e) +Out[]: 8.1240384046359608 +\end{lstlisting} +\end{frame} -%% \begin{frame}[fragile] -%% \frametitle{Singular Value Decomposition} -%% \begin{small} -%% \begin{lstlisting} -%% In []: svd(e) -%% Out[]: -%% (array( -%% [[ -6.66666667e-01, -1.23702565e-16, 7.45355992e-01], -%% [ -3.33333333e-01, -8.94427191e-01, -2.98142397e-01], -%% [ -6.66666667e-01, 4.47213595e-01, -5.96284794e-01]]), -%% array([ 8., 1., 1.]), -%% array([[-0.66666667, -0.33333333, -0.66666667], -%% [-0. , 0.89442719, -0.4472136 ], -%% [-0.74535599, 0.2981424 , 0.59628479]])) -%% \end{lstlisting} -%% \end{small} -%% \inctime{15} -%% \end{frame} +\begin{frame}[fragile] + \frametitle{Singular Value Decomposition} + \begin{small} + \begin{lstlisting} +In []: svd(e) +Out[]: +(array( +[[ -6.66666667e-01, -1.23702565e-16, 7.45355992e-01], + [ -3.33333333e-01, -8.94427191e-01, -2.98142397e-01], + [ -6.66666667e-01, 4.47213595e-01, -5.96284794e-01]]), + array([ 8., 1., 1.]), + array([[-0.66666667, -0.33333333, -0.66666667], + [-0. , 0.89442719, -0.4472136 ], + [-0.74535599, 0.2981424 , 0.59628479]])) + \end{lstlisting} + \end{small} +\end{frame} \section{Least Squares Fit} \begin{frame}[fragile] @@ -618,8 +618,7 @@ In []: plot(L, tsq, 'o') \item Inverse of a matrix \item Determinant \item Eigenvalues and Eigen vector - %% \item Norms - %% \item Singular Value Decomposition + \item Singular Value Decomposition \end{itemize} \item Least Square Curve fitting \end{itemize} -- cgit