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authorPrabhu Ramachandran2010-06-20 18:23:34 -0400
committerPrabhu Ramachandran2010-06-20 18:23:34 -0400
commit54c3980bf73911fff449bbbc47ce64dc124122d0 (patch)
tree1b5af9c3b12910c1dc913a59e05fa1e047916684
parent2bd3579f32eada4a99e27c7fa39217d7ff8de843 (diff)
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Updating session4, adding example for computation of norm and SVD.
--HG-- branch : scipy2010
-rw-r--r--day1/session4.tex61
1 files 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}