--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/day1/links.tex	Fri Oct 09 12:10:46 2009 +0530
@@ -0,0 +1,22 @@
+\documentclass[12pt]{article}
+\title{Links and References}
+\author{Asokan Pichai\\Prabhu Ramachandran}
+\begin{document}
+\maketitle
+\begin{itemize}
+  \item Most referred and trusted material for learning \emph{Python} language is available at \url{http://docs.python.org/tutorial/}
+  \item ``may be one of the thinnest programming language books on my shelf, but it's also one of the best.'' -- \emph{Slashdot, AccordianGuy, September 8, 2004}- available at \url{http://diveintopython.org/}
+  \item How to Think Like a Computer Scientist: Learning with Python available at \url{http://www.openbookproject.net/thinkcs/python/english/}\\``The concepts covered here apply to all programming languages and to problem solving in general.'' -- \emph{Guido van Rossum, creator of Python}
+  \item Some assorted articles related to Python \url{http://effbot.org/zone/index.htm}
+  \item To read more on strings refer to: \\ \url{http://docs.python.org/library/stdtypes.html#string-methods}
+  \item For documentation on IPython refer: \\ \url{http://ipython.scipy.org/moin/Documentation}
+  \item Documentation for Numpy and Scipy is available at: \url{http://docs.scipy.org/doc/}
+  \item For "recipes" or worked examples of commonly-done tasks in SciPy explore: \url{http://www.scipy.org/Cookbook/}
+  \item User Guide for Mayavi is the best place to look for Mayavi Documentation, available at: \\ \url{http://code.enthought.com/projects/mayavi/docs/development/html/mayavi/}
+  \item Explore examples and plots based on matplotlib at \\ \url{http://matplotlib.sourceforge.net/examples/index.html}
+  \item One stop go for Sage is \url{http://www.sagemath.org/doc/}
+  \item Central page for all SymPy’s documentation is at \\ \url{http://docs.sympy.org/}
+  \item For videos from basics to advanced Python check out: \\ \url{http://www.archive.org/search.php?query=scipy09}
+
+\end{itemize}
+\end{document}

--- a/day2/handout.tex	Fri Oct 09 12:09:08 2009 +0530
+++ b/day2/handout.tex	Fri Oct 09 12:10:46 2009 +0530
@@ -7,6 +7,7 @@
 
 \section{Matrices and Arrays \& 2D Plotting}
 \subsection{Matrices and Arrays}
+\subsubsection{Basic Numpy}
 \begin{verbatim}
 # Simple array math example
 >>> import numpy as np
@@ -54,7 +55,10 @@
 
 >>> np.greater(a,4)
 >>> np.sqrt(a)
+\end{verbatim}
 
+\subsubsection{Array Creation}
+\begin{verbatim}
 >>> np.array([2,3,4])  
 array([2, 3, 4])
 
@@ -69,7 +73,9 @@
 >>>np.ones_like(a)
 array([[1, 1, 1],
        [1, 1, 1]])
-
+\end{verbatim}
+\subsubsection{Slicing, Striding Arrays}
+\begin{verbatim}
 >>> a = np.array([[1,2,3], [4,5,6], 
                [7,8,9]])
 >>> a[0,1:3]
@@ -87,7 +93,9 @@
        [7, 9]])
 # Slices are references to the 
 # same memory!
-
+\end{verbatim}
+\subsubsection{Random Numbers}
+\begin{verbatim}
 >>> np.random.rand(3,2)
 array([[ 0.96276665,  0.77174861],
        [ 0.35138557,  0.61462271],
@@ -96,7 +104,7 @@
 42
 \end{verbatim}
 
-\subsection{Problem Set}
+\subsubsection{Problem Set}
 \begin{verbatim}
     >>> from scipy import misc
     >>> A=misc.imread(name)
@@ -112,6 +120,7 @@
 \end{enumerate}
 
 \subsection{2D Plotting}
+\subsubsection{Basic 2D Plotting}
 \begin{verbatim}
 $ ipython -pylab
 >>> x = linspace(0, 2*pi, 1000)
@@ -122,7 +131,9 @@
 >>> ylabel(r'sin($\chi$)', color='r')
 >>> title('Simple figure', fontsize=20)
 >>> savefig('/tmp/test.eps')
-
+\end{verbatim}
+\subsubsection{Tweaking plots}
+\begin{verbatim}
 # Set properties of objects:
 >>> l, = plot(x, sin(x))
 # Why "l,"?
@@ -132,7 +143,10 @@
 >>> setp(l) # Print properties.
 >>> clf() # Clear figure.
 >>> close() # Close figure.
+\end{verbatim}
 
+\subsubsection{Working with text}
+\begin{verbatim}
 >>> w = arange(-2,2,.1)
 >>> plot(w,exp(-(w*w))*cos)
 >>> ylabel('$f(\omega)$')
@@ -144,7 +158,10 @@
              arrowprops=dict(
              facecolor='black', 
              shrink=0.05))
+\end{verbatim}
 
+\subsubsection{Legends}
+\begin{verbatim}
 >>> x = linspace(0, 2*np.pi, 1000)
 >>> plot(x, cos(5*x), 'r--', 
          label='cosine')
@@ -153,7 +170,10 @@
 >>> legend() 
 # Or use:
 >>> legend(['cosine', 'sine'])
+\end{verbatim}
 
+\subsubsection{Multiple figures}
+\begin{verbatim}
 >>> figure(1)
 >>> plot(x, sin(x))
 >>> figure(2)
@@ -163,7 +183,7 @@
 
 \end{verbatim}
 
-\subsection{Problem Set}
+\subsubsection{Problem Set}
   \begin{enumerate}
     \item Write a function that plots any regular n-gon given n.
     \item Consider the logistic map, $f(x) = kx(1-x)$, plot it for
@@ -187,11 +207,12 @@
 \begin{verbatim}
 >>> a = np.arange(4)
 >>> b = np.arange(5)
->>> a+b
+>>> a+b #Does this work?
 >>> a+3
 >>> c=np.array([3])
->>> a+c
->>> b+c
+>>> a+c #Works!
+>>> b+c #But how?
+>>> a.shape, b.shape, c.shape
 
 >>> a = np.arange(4)
 >>> a+3

--- a/day2/session1.tex	Fri Oct 09 12:09:08 2009 +0530
+++ b/day2/session1.tex	Fri Oct 09 12:10:46 2009 +0530
@@ -134,10 +134,8 @@
       \item Why?
   \item What:
     \begin{itemize}
-    \item An efficient and powerful array type for various common data
-      types
-    \item Abstracts out the most commonly used standard operations on
-      arrays
+    \item An efficient and powerful array type for various common data types
+    \item Abstracts out the most commonly used standard operations on arrays
     \end{itemize}
   \end{itemize}
 \end{frame}
@@ -803,4 +801,11 @@
 \end{columns}
 \inctime{20}
 \end{frame}
+\begin{frame}{Summary}
+  \begin{itemize}
+  \item Basics of Numpy.
+  \item Array operations.
+  \item Plotting in 2D.
+  \end{itemize}
+\end{frame}
 \end{document}

--- a/day2/session2.tex	Fri Oct 09 12:09:08 2009 +0530
+++ b/day2/session2.tex	Fri Oct 09 12:10:46 2009 +0530
@@ -124,11 +124,12 @@
   \begin{lstlisting}
     >>> a = np.arange(4)
     >>> b = np.arange(5)
-    >>> a+b
+    >>> a+b #Does this work?
     >>> a+3
     >>> c=np.array([3])
-    >>> a+c
-    >>> b+c
+    >>> a+c #Works!
+    >>> b+c #But how?
+    >>> a.shape, b.shape, c.shape
   \end{lstlisting}
   \begin{itemize}
     \item Enter Broadcasting!
@@ -426,8 +427,18 @@
   Make a plot of $\frac{dx}{dt}$ vs. $x$.
 \inctime{30}
 \end{frame}
-
-
+\begin{frame}{Summary}
+  \begin{itemize}
+    \item Advanced NumPy
+    \item SciPy
+      \begin{itemize}
+        \item Linear Algebra
+        \item Integration
+        \item Interpolation
+        \item Signal and Image processing
+      \end{itemize}
+  \end{itemize}
+\end{frame}
 \end{document}
 
 - Numpy arrays (30 mins)

--- a/day2/session3.tex	Fri Oct 09 12:09:08 2009 +0530
+++ b/day2/session3.tex	Fri Oct 09 12:10:46 2009 +0530
@@ -194,7 +194,7 @@
 
 \section{Tools at your disposal}
 
-\subsection{Mayavi2.0}
+\subsection{Mayavi2}
 
 \begin{frame}
   \frametitle{Introduction to Mayavi}

--- a/day2/tda.tex	Fri Oct 09 12:09:08 2009 +0530
+++ b/day2/tda.tex	Fri Oct 09 12:10:46 2009 +0530
@@ -261,7 +261,7 @@
 
 \begin{frame}[fragile]
     \frametitle{Exercise}
-    Based on Euclid's theorem:
+    Based on Euclid's algorithm:
         $gcd(a,b)=gcd(b,b\%a)$\\
     gcd function can be written as:
     \begin{lstlisting}
@@ -269,14 +269,15 @@
       if a%b == 0: return b
       return gcd(b, a%b)
     \end{lstlisting}
+    \vspace*{-0.15in}
     \begin{block}{Task}
-      For given gcd implementation write
-      at least two tests.
-    \end{block}
-    \begin{block}{Task}
-      Write a non recursive implementation
+      \begin{itemize}
+      \item Write at least 
+        two tests for above mentioned function.
+      \item Write a non recursive implementation
       of gcd(), and test it using already 
       written tests.
+      \end{itemize}
     \end{block}
     
 \inctime{15}