diff options
Diffstat (limited to 'advanced_python/slides')
| -rw-r--r-- | advanced_python/slides/arrays.tex | 341 | ||||
| -rw-r--r-- | advanced_python/slides/lambda.tex | 189 | ||||
| -rw-r--r-- | advanced_python/slides/modules.tex | 163 | ||||
| -rw-r--r-- | advanced_python/slides/oop.tex | 226 | ||||
| -rw-r--r-- | advanced_python/slides/plotting.tex | 450 | ||||
| -rw-r--r-- | advanced_python/slides/scipy.tex | 273 | ||||
| -rw-r--r-- | advanced_python/slides/tmp.tex | 316 |
7 files changed, 0 insertions, 1958 deletions
diff --git a/advanced_python/slides/arrays.tex b/advanced_python/slides/arrays.tex deleted file mode 100644 index e4501c8..0000000 --- a/advanced_python/slides/arrays.tex +++ /dev/null @@ -1,341 +0,0 @@ -\section{Arrays} - -\begin{frame}[fragile] - \frametitle{Arrays: Introduction} - \begin{itemize} - \item Similar to lists, but homogeneous - \item Much faster than arrays - \end{itemize} - \begin{lstlisting} - In[]: a1 = array([1,2,3,4]) - In[]: a1 # 1-D - In[]: a2 = array([[1,2,3,4],[5,6,7,8]]) - In[]: a2 # 2-D - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{arange} and \texttt{shape}} - \begin{lstlisting} - In[]: ar1 = arange(1, 5) - In[]: ar2 = arange(1, 9) - In[]: print ar2 - In[]: ar2.shape = 2, 4 - In[]: print ar2 - \end{lstlisting} - \begin{itemize} - \item \texttt{linspace} and \texttt{loadtxt} also returned arrays - \end{itemize} - \begin{lstlisting} - In[]: ar1.shape - In[]: ar2.shape - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Special methods} - \begin{lstlisting} - In[]: identity(3) - \end{lstlisting} - \begin{itemize} - \item array of shape (3, 3) with diagonals as 1s, rest 0s - \end{itemize} - \begin{lstlisting} - In[]: zeros((4,5)) - \end{lstlisting} - \begin{itemize} - \item array of shape (4, 5) with all 0s - \end{itemize} - \begin{lstlisting} - In[]: a = zeros_like([1.5, 1, 2, 3]) - In[]: print a, a.dtype - \end{lstlisting} - \begin{itemize} - \item An array with all 0s, with similar shape and dtype as argument - \item Homogeneity makes the dtype of a to be float - \item \texttt{ones, ones\_like, empty, empty\_like} - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Operations on arrays} - \begin{lstlisting} - In[]: a1 - In[]: a1 * 2 - In[]: a1 - \end{lstlisting} - \begin{itemize} - \item The array is not changed; New array is returned - \end{itemize} - \begin{lstlisting} - In[]: a1 + 3 - In[]: a1 - 7 - In[]: a1 / 2.0 - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Operations on arrays \ldots} - \begin{itemize} - \item Like lists, we can assign the new array, the old name - \end{itemize} - \begin{lstlisting} - In[]: a1 = a1 + 2 - In[]: a1 - \end{lstlisting} - \begin{itemize} - \item \alert{Beware of Augmented assignment!} - \end{itemize} - \begin{lstlisting} - In[]: a, b = arange(1, 5), arange(1, 5) - In[]: print a, a.dtype, b, b.dtype - In[]: a = a/2.0 - In[]: b /= 2.0 - In[]: print a, a.dtype, b, b.dtype - \end{lstlisting} - \begin{itemize} - \item Operations on two arrays; element-wise - \end{itemize} - \begin{lstlisting} - In[]: a1 + a1 - In[]: a1 * a2 - \end{lstlisting} -\end{frame} - -\section{Accessing pieces of arrays} - -\begin{frame}[fragile] - \frametitle{Accessing \& changing elements} - \begin{lstlisting} - In[]: A = array([12, 23, 34, 45, 56]) - - In[]: C = array([[11, 12, 13, 14, 15], - [21, 22, 23, 24, 25], - [31, 32, 33, 34, 35], - [41, 42, 43, 44, 45], - [51, 52, 53, 54, 55]]) - - In[]: A[2] - In[]: C[2, 3] - \end{lstlisting} - \begin{itemize} - \item Indexing starts from 0 - \item Assign new values, to change elements - \end{itemize} - \begin{lstlisting} - In[]: A[2] = -34 - In[]: C[2, 3] = -34 - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Accessing rows} - \begin{itemize} - \item Indexing works just like with lists - \end{itemize} - \begin{lstlisting} - In[]: C[2] - In[]: C[4] - In[]: C[-1] - \end{lstlisting} - \begin{itemize} - \item Change the last row into all zeros - \end{itemize} - \begin{lstlisting} - In[]: C[-1] = [0, 0, 0, 0, 0] - \end{lstlisting} - OR - \begin{lstlisting} - In[]: C[-1] = 0 - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Accessing columns} - \begin{lstlisting} - In[]: C[:, 2] - In[]: C[:, 4] - In[]: C[:, -1] - \end{lstlisting} - \begin{itemize} - \item The first parameter is replaced by a \texttt{:} to specify we - require all elements of that dimension - \end{itemize} - \begin{lstlisting} - In[]: C[:, -1] = 0 - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Slicing} - \begin{lstlisting} - In[]: I = imread('squares.png') - In[]: imshow(I) - \end{lstlisting} - \begin{itemize} - \item The image is just an array - \end{itemize} - \begin{lstlisting} - In[]: print I, I.shape - \end{lstlisting} - \begin{enumerate} - \item Get the top left quadrant of the image - \item Obtain the square in the center of the image - \end{enumerate} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Slicing \ldots} - \begin{itemize} - \item Slicing works just like with lists - \end{itemize} - \begin{lstlisting} - In[]: C[0:3, 2] - In[]: C[2, 0:3] - In[]: C[2, :3] - \end{lstlisting} - \begin{lstlisting} - In[]: imshow(I[:150, :150]) - - In[]: imshow(I[75:225, 75:225]) - \end{lstlisting} -\end{frame} - -\begin{frame} -\frametitle{Image after slicing} -\includegraphics[scale=0.45]{../advanced_python/images/slice.png}\\ -\end{frame} - - - -\begin{frame}[fragile] - \frametitle{Striding} - \begin{itemize} - \item Compress the image to a fourth, by dropping alternate rows and - columns - \item We shall use striding - \item The idea is similar to striding in lists - \end{itemize} - \begin{lstlisting} - In[]: C[0:5:2, 0:5:2] - In[]: C[::2, ::2] - In[]: C[1::2, ::2] - \end{lstlisting} - \begin{itemize} - \item Now, the image can be shrunk by - \end{itemize} - \begin{lstlisting} - In[]: imshow(I[::2, ::2]) - \end{lstlisting} -\end{frame} - -\section{Matrix Operations} - -\begin{frame}[fragile] - \frametitle{Matrix Operations using \texttt{arrays}} - We can perform various matrix operations on \texttt{arrays}\\ - A few are listed below. - - \begin{center} - \begin{tabular}{lll} - Operation & How? & Example \\ - \hline - Transpose & \texttt{.T} & \texttt{A.T} \\ - Product & \texttt{dot} & \texttt{dot(A, B)} \\ - Inverse & \texttt{inv} & \texttt{inv(A)} \\ - Determinant & \texttt{det} & \texttt{det(A)} \\ - Sum of all elements & \texttt{sum} & \texttt{sum(A)} \\ - Eigenvalues & \texttt{eigvals} & \texttt{eigvals(A)} \\ - Eigenvalues \& Eigenvectors & \texttt{eig} & \texttt{eig(A)} \\ - Norms & \texttt{norm} & \texttt{norm(A)} \\ - SVD & \texttt{svd} & \texttt{svd(A)} \\ - \end{tabular} - \end{center} -\end{frame} - -\section{Least square fit} - -\begin{frame}[fragile] - \frametitle{Least Square Fit} - \begin{lstlisting} - In[]: L, t = loadtxt("pendulum.txt", - unpack=True) - In[]: L - In[]: t - In[]: tsq = t * t - In[]: plot(L, tsq, 'bo') - In[]: plot(L, tsq, 'r') - \end{lstlisting} - \begin{itemize} - \item Both the plots, aren't what we expect -- linear plot - \item Enter Least square fit! - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Matrix Formulation} - \begin{itemize} - \item We need to fit a line through points for the equation $T^2 = m \cdot L+c$ - \item In matrix form, the equation can be represented as $T_{sq} = A \cdot p$, where $T_{sq}$ is - $\begin{bmatrix} - T^2_1 \\ - T^2_2 \\ - \vdots\\ - T^2_N \\ - \end{bmatrix}$ - , A is - $\begin{bmatrix} - L_1 & 1 \\ - L_2 & 1 \\ - \vdots & \vdots\\ - L_N & 1 \\ - \end{bmatrix}$ - and p is - $\begin{bmatrix} - m\\ - c\\ - \end{bmatrix}$ - \item We need to find $p$ to plot the line - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Least Square Fit Line} - \begin{lstlisting} - In[]: A = array((L, ones_like(L))) - In[]: A.T - In[]: A - \end{lstlisting} - \begin{itemize} - \item We now have \texttt{A} and \texttt{tsq} - \end{itemize} - \begin{lstlisting} - In[]: result = lstsq(A, tsq) - \end{lstlisting} - \begin{itemize} - \item Result has a lot of values along with m and c, that we need - \end{itemize} - \begin{lstlisting} - In[]: m, c = result[0] - In[]: print m, c - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Least Square Fit Line} - \begin{itemize} - \item Now that we have m and c, we use them to generate line and plot - \end{itemize} - \begin{lstlisting} - In[]: tsq_fit = m * L + c - In[]: plot(L, tsq, 'bo') - In[]: plot(L, tsq_fit, 'r') - \end{lstlisting} -\end{frame} - -\begin{frame} -\frametitle{Least Square Fit Line} -\includegraphics[scale=0.45]{../advanced_python/images/lst-sq-fit.png}\\ -\end{frame} - - diff --git a/advanced_python/slides/lambda.tex b/advanced_python/slides/lambda.tex deleted file mode 100644 index 25c4f97..0000000 --- a/advanced_python/slides/lambda.tex +++ /dev/null @@ -1,189 +0,0 @@ -\section{Functional programming} - -\begin{frame}[fragile] - \frametitle{List Comprehensions} - \begin{itemize} - \item A different style of Programming - \item Functions `emulate' mathematical functions - \item Output depends only on input arguments - \item There is no `state' associated with the program - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{List Comprehensions} - \begin{block}{} - Given a list of weights of people, and we need to - calculate the corresponding weights on the moon. Return a new - list, with each of the values divided by 6.0. - \end{block} - - \begin{itemize} - \item Solution using \texttt{for} loop is shown - \end{itemize} - \begin{lstlisting} - weights = [30, 45.5, 78, 81, 55.5, 62.5] - weights_moon = [] - for w in weights: - weights_moon.append(w/6.0) - print weights_moon - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{List Comprehensions \ldots} - \begin{itemize} - \item List comprehensions are compact and readable - \end{itemize} - \begin{lstlisting} - [ w/6.0 for w in weights ] - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{List Comprehensions \ldots} - \begin{itemize} - \item Return the weight on moon, only if weight on earth > 50 - \end{itemize} - \begin{lstlisting} - weights = [30, 45.5, 78, 81, 55.5, 62.5] - weights_moon = [] - for w in weights: - if w > 50: - weights_moon.append(w/6.0) - - print weights_moon - \end{lstlisting} - \begin{itemize} - \item List comprehension that checks for a condition - \end{itemize} - \begin{lstlisting} - [ w/6.0 for w in weights if w>50 ] - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{List Comprehensions \ldots} - \begin{itemize} - \item if weight > 50, return weight/6.0 - \item else, return weight*3.0 - \end{itemize} - \begin{lstlisting} - weights = [30, 45.5, 78, 81, 55.5, 62.5] - weights_migrate = [] - for w in weights: - if w > 50: - weights_migrate.append(w/6.0) - else: - weights_migrate.append(w * 3.0) - - print weights_migrate - \end{lstlisting} - \begin{itemize} - \item This problem \alert{CANNOT} be solved using list - comprehensions - \item Try \texttt{map} - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{map}} - \begin{itemize} - \item Takes a function and a sequence as arguments - \item Calls function with each element of sequence as argument - \item Returns a sequence with all the results as elements - \item We solve the easier problem first, using \texttt{map} - \end{itemize} - - \begin{lstlisting} - def moonize(weight): - return weight/6.0 - - map(moonize, weights) - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{map} \ldots} - \begin{lstlisting} - def migrate(weight): - if weight < 50: - return weight*3.0 - else: - return weight/6.0 - \end{lstlisting} - - \begin{itemize} - \item \texttt{migrate} compares weight with 50 and returns the - required value. - \item We can now use \texttt{map} - \end{itemize} - \begin{lstlisting} - map(migrate, weights) - \end{lstlisting} - \begin{itemize} - \item Now, we wish to get away with the function definition - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{lambda}} - \begin{itemize} - \item Allows function definition, anonymously - \end{itemize} - \begin{lstlisting} - map(lambda x: x/6.0, weights) - \end{lstlisting} - \begin{itemize} - \item \texttt{lambda} actually returns a function which we could in - fact assign to a name and use later. - \end{itemize} - \begin{lstlisting} - l_moonize = lambda x: x/6.0 - map(l_moonize, weights) - \end{lstlisting} - \begin{lstlisting} - l_migrate = lambda x: x*3.0 if x < 50 else x/6.0 - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{filter}} - - \begin{itemize} - \item We avoided discussion of problem of returning new weights only - when actual weight is more than 50. - \item \texttt{filter} can be used to filter out ``bad'' weights - \item Later, we could use \texttt{map} - \end{itemize} - \begin{lstlisting} - filter(lambda x: x > 50, weights) - \end{lstlisting} - \begin{itemize} - \item Takes a function and a sequence - \item Returns a sequence, containing only those elements of the - original sequence, for which the function returned \texttt{True} - \end{itemize} - \begin{lstlisting} - map(lambda x: x/6.0, filter(lambda x: x > 50, weights)) - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{reduce}} - \begin{itemize} - \item ``reduces'' a sequence - \end{itemize} - \begin{lstlisting} - reduce(lambda x,y: x*y, [1, 2, 3, 4]) - \end{lstlisting} - \begin{itemize} - \item Takes function and sequence as arguments; the function should - take two arguments - \item Passes first two elements of sequence, and continues to move - over the sequence, passing the output in the previous step and the - current element as the arguments - \item The function above essentially calculates $((1*2)*3)*4$ - \end{itemize} -\end{frame} - diff --git a/advanced_python/slides/modules.tex b/advanced_python/slides/modules.tex deleted file mode 100644 index d6de640..0000000 --- a/advanced_python/slides/modules.tex +++ /dev/null @@ -1,163 +0,0 @@ -\section{Using Python modules} - -\begin{frame}[fragile] - \frametitle{\texttt{hello.py}} - \begin{itemize} - \item Script to print `hello world' -- \texttt{hello.py} - \end{itemize} - \begin{lstlisting} - print "Hello world!" - \end{lstlisting} - \begin{itemize} - \item We have been running scripts from IPython - \end{itemize} - \begin{lstlisting} - In[]: %run -i hello.py - \end{lstlisting} - \begin{itemize} - \item Now, we run from the shell using python - \end{itemize} - \begin{lstlisting} - $ python hello.py - \end{lstlisting} %$ -\end{frame} - -\begin{frame}[fragile] - \frametitle{Simple plot} - \begin{itemize} - \item Save the following in \texttt{sine\_plot.py} - \end{itemize} - \begin{lstlisting} - x = linspace(-2*pi, 2*pi, 100) - plot(x, sin(x)) - show() - \end{lstlisting} - \begin{itemize} - \item Now, let us run the script - \end{itemize} - \begin{lstlisting} - $ python sine_plot.py - \end{lstlisting} % $ - \begin{itemize} - \item What's wrong? - \end{itemize} -\end{frame} - - -\begin{frame}[fragile] - \frametitle{Importing} - \begin{itemize} - \item \texttt{-pylab} is importing a lot of functionality - \item Add the following to the top of your file - \end{itemize} - \begin{lstlisting} - from scipy import * - \end{lstlisting} - \begin{lstlisting} - $ python sine_plot.py - \end{lstlisting} % $ - \begin{itemize} - \item Now, plot is not found - \item Add the following as the second line of your script - \end{itemize} - \begin{lstlisting} - from pylab import * - \end{lstlisting} - \begin{lstlisting} - $ python sine_plot.py - \end{lstlisting} % $ - \begin{itemize} - \item It works! - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Importing \ldots} - \begin{itemize} - \item \texttt{*} imports everything from \texttt{scipy} and - \texttt{pylab} - \item But, It imports lot of unnecessary stuff - \item And two modules may contain the same name, causing a conflict - \item There are two ways out - \end{itemize} - \begin{lstlisting} - from scipy import linspace, pi, sin - from pylab import plot, show - \end{lstlisting} - \begin{itemize} - \item OR change the imports to following and - \item Replace \texttt{pi} with \texttt{scipy.pi}, etc. - \end{itemize} - \begin{lstlisting} - import scipy - import pylab - \end{lstlisting} -\end{frame} - -\section{Writing modules} - -\begin{frame}[fragile] - \frametitle{GCD script} - \begin{itemize} - \item Function that computes gcd of two numbers - \item Save it as \texttt{gcd\_script.py} - \end{itemize} - \begin{lstlisting} - def gcd(a, b): - while b: - a, b = b, a%b - return a - \end{lstlisting} - \begin{itemize} - \item Also add the tests to the file - \end{itemize} - \begin{lstlisting} - if gcd(40, 12) == 4 and gcd(12, 13) == 1: - print "Everything OK" - else: - print "The GCD function is wrong" - \end{lstlisting} - \begin{lstlisting} - $ python gcd_script.py - \end{lstlisting} % $ -\end{frame} - -\begin{frame}[fragile] - \frametitle{Python path} - \begin{itemize} - \item In IPython type the following - \end{itemize} - \begin{lstlisting} - import sys - sys.path - \end{lstlisting} - \begin{itemize} - \item List of locations where python searches for a module - \item \texttt{import sys} -- searches for file \texttt{sys.py} or - dir \texttt{sys} in all these locations - \item So, our own modules can be in any one of the locations - \item Current working directory is one of the locations - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{\_\_name\_\_}} - \begin{lstlisting} - import gcd_script - \end{lstlisting} - \begin{itemize} - \item The import is successful - \item But the test code, gets run - \item Add the tests to the following \texttt{if} block - \end{itemize} - \begin{lstlisting} - if __name__ == "__main__": - \end{lstlisting} - \begin{itemize} - \item Now the script runs properly - \item As well as the import works; test code not executed - \item \texttt{\_\_name\_\_} is local to every module and is equal - to \texttt{\_\_main\_\_} only when the file is run as a script. - \end{itemize} -\end{frame} - diff --git a/advanced_python/slides/oop.tex b/advanced_python/slides/oop.tex deleted file mode 100644 index bdb983c..0000000 --- a/advanced_python/slides/oop.tex +++ /dev/null @@ -1,226 +0,0 @@ -\section{Object Oriented Programming} - -\begin{frame}[fragile] - \frametitle{Objectives} - At the end of this section, you will be able to - - \begin{itemize} - \item Understand the differences between Object Oriented Programming - and Procedural Programming - \item Appreciate the need for Object Oriented Programming - \item Read and understand Object Oriented Programs - \item Write simple Object Oriented Programs - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Example: Managing Talks} - \begin{itemize} - \item A list of talks at a conference - \item We want to manage the details of the talks - \end{itemize} - \begin{lstlisting} - talk = {'Speaker': 'Guido van Rossum', - 'Title': 'The History of Python' - 'Tags': 'python,history,C,advanced'} - - def get_first_name(talk): - return talk['Speaker'].split()[0] - - def get_tags(talk): - return talk['Tags'].split(',') - \end{lstlisting} - \begin{itemize} - \item Not convenient to handle large number of talks - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Objects and Methods} - \begin{itemize} - \item Objects group data with the procedures/functions - \item A single entity called \texttt{object} - \item Everything in Python is an object - \item Strings, Lists, Functions and even Modules - \end{itemize} - \begin{lstlisting} - s = "Hello World" - s.lower() - - l = [1, 2, 3, 4, 5] - l.append(6) - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Objects \ldots} - \begin{itemize} - \item Objects provide a consistent interface - \end{itemize} - \begin{lstlisting} - for element in (1, 2, 3): - print element - for key in {'one':1, 'two':2}: - print key - for char in "123": - print char - for line in open("myfile.txt"): - print line - for line in urllib2.urlopen('http://site.com'): - print line - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Classes} - \begin{itemize} - \item A new string, comes along with methods - \item A template or a blue-print, where these definitions lie - \item This blue print for building objects is called a - \texttt{class} - \item \texttt{s} is an object of the \texttt{str} class - \item An object is an ``instance'' of a class - \end{itemize} - \begin{lstlisting} - s = "Hello World" - type(s) - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Defining Classes} - \begin{itemize} - \item A class equivalent of the talk dictionary - \item Combines data and methods into a single entity - \end{itemize} - \begin{lstlisting} - class Talk: - """A class for the Talks.""" - - def __init__(self, speaker, title, tags): - self.speaker = speaker - self.title = title - self.tags = tags - - def get_speaker_firstname(self): - return self.speaker.split()[0] - - def get_tags(self): - return self.tags.split(',') - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{class} block} - \begin{itemize} - \item Defined just like a function block - \item \texttt{class} is a keyword - \item \texttt{Talk} is the name of the class - \item Classes also come with doc-strings - \item All the statements of within the class are inside the block - \end{itemize} - \begin{lstlisting} - class Talk: - """A class for the Talks.""" - - def __init__(self, speaker, title, tags): - self.speaker = speaker - self.title = title - self.tags = tags - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{self}} - \begin{itemize} - \item Every method has an additional first argument, \texttt{self} - \item \texttt{self} is a reference to the object itself, of which - the method is a part of - \item Variables of the class are referred to as \texttt{self.variablename} - \end{itemize} - \begin{lstlisting} - def get_speaker_firstname(self): - return self.speaker.split()[0] - - def get_tags(self): - return self.tags.split(',') - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Instantiating a Class} - \begin{itemize} - \item Creating objects or instances of a class is simple - \item We call the class name, with arguments as required by it's - \texttt{\_\_init\_\_} function. - \end{itemize} - \begin{lstlisting} - bdfl = Talk('Guido van Rossum', - 'The History of Python', - 'python,history,C,advanced') - \end{lstlisting} - \begin{itemize} - \item We can now call the methods of the Class - \end{itemize} - \begin{lstlisting} - bdfl.get_tags() - bdfl.get_speaker_firstname() - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{\_\_init\_\_} method} - \begin{itemize} - \item A special method - \item Called every time an instance of the class is created - \end{itemize} - \begin{lstlisting} - print bdfl.speaker - print bdfl.tags - print bdfl.title - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile, allowframebreaks] - \frametitle{Inheritance} - \begin{itemize} - \item Suppose, we wish to write a \texttt{Tutorial} class - \item It's almost same as \texttt{Talk} except for minor differences - \item We can ``inherit'' from \texttt{Talk} - \end{itemize} - \begin{lstlisting} - class Tutorial(Talk): - """A class for the tutorials.""" - - def __init__(self, speaker, title, tags, handson=True): - Talk.__init__(self, speaker, title, tags) - self.handson = handson - - def is_handson(self): - return self.handson - \end{lstlisting} - \begin{itemize} - \item Modified \texttt{\_\_init\_\_} method - \item New \texttt{is\_handson} method - \item It also has, \texttt{get\_tags} and - \texttt{get\_speaker\_firstname} - \end{itemize} - \begin{lstlisting} - numpy = Tutorial('Travis Oliphant', - 'Numpy Basics', - 'numpy,python,beginner') - numpy.is_handson() - numpy.get_speaker_firstname() - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Summary} - In this section we have learnt, - \begin{itemize} - \item the fundamental difference in paradigm, between Object Oriented - Programming and Procedural Programming - \item to write our own classes - \item to write new classes that inherit from existing classes - \end{itemize} -\end{frame} - diff --git a/advanced_python/slides/plotting.tex b/advanced_python/slides/plotting.tex deleted file mode 100644 index fbc7aa2..0000000 --- a/advanced_python/slides/plotting.tex +++ /dev/null @@ -1,450 +0,0 @@ -\section{Interactive Plotting} - -\begin{frame}[fragile] - \frametitle{First Plot} - \begin{itemize} - \item Start IPython with \texttt{-pylab} - \end{itemize} - \begin{lstlisting} - $ ipython -pylab - \end{lstlisting} % $ - \begin{lstlisting} - In[]: p = linspace(-pi,pi,100) - In[]: plot(p, cos(p)) - \end{lstlisting} -\end{frame} - - -\begin{frame}[fragile] - \frametitle{\texttt{linspace}} - \begin{itemize} - \item \texttt{p} has a hundred points in the range -pi to pi - \begin{lstlisting} - In[]: print p[0], p[-1], len(p) - \end{lstlisting} - \item Look at the doc-string of \texttt{linspace} for more details - \begin{lstlisting} - In[]: linspace? - \end{lstlisting} - \end{itemize} - \begin{itemize} - \item \texttt{plot} simply plots the two arguments with default - properties - \end{itemize} -\end{frame} - -\section{Embellishing Plots} - -\begin{frame}[fragile] - \frametitle{Plot color and thickness} - \begin{lstlisting} - In[]: clf() - In[]: plot(p, sin(p), 'r') - \end{lstlisting} - \begin{itemize} - \item Gives a sine curve in Red. - \end{itemize} - \begin{lstlisting} - In[]: plot(p, cos(p), linewidth=2) - \end{lstlisting} - \begin{itemize} - \item Sets line thickness to 2 - \end{itemize} - \begin{lstlisting} - In[]: clf() - In[]: plot(p, sin(p), '.') - \end{lstlisting} - \begin{itemize} - \item Produces a plot with only points - \end{itemize} - \begin{lstlisting} - In[]: plot? - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{title}} - \begin{lstlisting} - In[]: x = linspace(-2, 4, 50) - In[]: plot(x, -x*x + 4*x - 5, 'r', - linewidth=2) - In[]: title("Parabolic function -x^2+4x-5") - \end{lstlisting} - \begin{itemize} - \item We can set title using \LaTeX~ - \end{itemize} - \begin{lstlisting} - In[]: title("Parabolic function $-x^2+4x-5$") - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Axes labels} - \begin{lstlisting} - In[]: xlabel("x") - In[]: ylabel("f(x)") - \end{lstlisting} - \begin{itemize} - \item We could, if required use \LaTeX~ - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Annotate} - \begin{lstlisting} - In[]: annotate("local maxima", xy=(2, -1)) - \end{lstlisting} - \begin{itemize} - \item First argument is the annotation text - \item The argument to \texttt{xy} is a tuple that gives the location - of the text. - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Limits of Plot area} - \begin{lstlisting} - In[]: xlim() - In[]: ylim() - \end{lstlisting} - \begin{itemize} - \item With no arguments, \texttt{xlim} \& \texttt{ylim} get the - current limits - \item New limits are set, when arguments are passed to them - \end{itemize} - \begin{lstlisting} - In[]: xlim(-4, 5) - \end{lstlisting} - \begin{lstlisting} - In[]: ylim(-15, 2) - \end{lstlisting} -\end{frame} - -\begin{frame} -\frametitle{Plot} -\includegraphics[scale=0.45]{../advanced_python/images/plot.png}\\ -\end{frame} - - - -\section{Saving to Scripts} - -\begin{frame}[fragile] - \frametitle{Command history} - \begin{itemize} - \item To see the history of commands, we typed - \begin{lstlisting} - In[]: %hist - \end{lstlisting} - \item All commands, valid or invalid, appear in the history - \item \texttt{\%hist} is a magic command, available only in IPython - \end{itemize} - \begin{lstlisting} - In[]: %hist 5 - # last 5 commands - \end{lstlisting} - \begin{lstlisting} - In[]: %hist 5 10 - # commands between 5 and 10 - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Saving to a script} - \begin{itemize} - \item We wish to save commands for reproducing the parabola - \item Look at the history and identify the commands that will - reproduce the parabolic function along with all embellishment - \item \texttt{\%save} magic command to save the commands to a file - \end{itemize} - \begin{lstlisting} - In[]: %save plot_script.py 1 3-6 8 - \end{lstlisting} - \begin{itemize} - \item File name must have a \texttt{.py} extension - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Running the script} - \begin{lstlisting} - In[]: %run -i plot_script.py - \end{lstlisting} - \begin{itemize} - \item There were no errors in the plot, but we don't see it! - \item Running the script means, we are not in interactive mode - \item We need to explicitly ask for the image to be shown - \end{itemize} - \begin{lstlisting} - In[]: show() - \end{lstlisting} - \begin{itemize} - \item \texttt{-i} asks the interpreter to check for names, - unavailable in the script, in the interpreter - \item \texttt{sin}, \texttt{plot}, etc. are taken from the - interpreter - \end{itemize} -\end{frame} - -\section{Saving Plots} - -\begin{frame}[fragile] - \frametitle{\texttt{savefig}} - \begin{lstlisting} - In[]: x = linspace(-3*pi,3*pi,100) - In[]: plot(x,sin(x)) - In[]: savefig('sine.png') - \end{lstlisting} - \begin{itemize} - \item \texttt{savefig} takes one argument - \item The file-type is decided based on the extension - \item \texttt{savefig} can save as png, pdf, ps, eps, svg - \end{itemize} -\end{frame} - -\section{Multiple Plots} - -\begin{frame}[fragile] - \frametitle{Overlaid plots} - \begin{lstlisting} - In[]: x = linspace(0, 50, 10) - In[]: plot(x, sin(x)) - \end{lstlisting} - \begin{itemize} - \item The curve isn't as smooth as we expected - \item We chose too few points in the interval - \end{itemize} - \begin{lstlisting} - In[]: y = linspace(0, 50, 500) - In[]: plot(y, sin(y)) - \end{lstlisting} - \begin{itemize} - \item The plots are overlaid - \item It is the default behaviour of \texttt{pylab} - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Legend} - \begin{lstlisting} - In[]: legend(['sine-10 points', - 'sine-500 points']) - \end{lstlisting} - \begin{itemize} - \item Placed in the location, \texttt{pylab} thinks is `best' - \item \texttt{loc} parameter allows to change the location - \end{itemize} - \begin{lstlisting} - In[]: legend(['sine-10 points', - 'sine-500 points'], - loc='center') - \end{lstlisting} -\end{frame} - -\begin{frame} -\frametitle{Overlaid Plots} -\includegraphics[scale=0.45]{../advanced_python/images/overlaid.png}\\ -\end{frame} - - - -\begin{frame}[fragile] - \frametitle{Plotting in separate figures} - \begin{lstlisting} - In[]: clf() - In[]: x = linspace(0, 50, 500) - In[]: figure(1) - In[]: plot(x, sin(x), 'b') - In[]: figure(2) - In[]: plot(x, cos(x), 'g') - \end{lstlisting} - \begin{itemize} - \item \texttt{figure} command allows us to have plots separately - \item It is also used to switch context between the plots - \end{itemize} - \begin{lstlisting} - In[]: savefig('cosine.png') - In[]: figure(1) - In[]: title('sin(y)') - In[]: savefig('sine.png') - In[]: close() - In[]: close() - \end{lstlisting} - \begin{itemize} - \item \texttt{close('all')} closes all the figures - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Subplots} - \begin{lstlisting} - In[]: subplot(2, 1, 1) - \end{lstlisting} - \begin{itemize} - \item number of rows - \item number of columns - \item plot number, in serial order, to access or create - \end{itemize} - \begin{lstlisting} - In[]: subplot(2, 1, 2) - In[]: x = linspace(0, 50, 500) - In[]: plot(x, cos(x)) - - In[]: subplot(2, 1, 1) - In[]: y = linspace(0, 5, 100) - In[]: plot(y, y ** 2) - \end{lstlisting} -\end{frame} - -\begin{frame} -\frametitle{Subplots} -\includegraphics[scale=0.45]{../advanced_python/images/subplot.png}\\ -\end{frame} - - - -\section{Plotting Data} - -\begin{frame}[fragile] - \frametitle{Loading data} - \begin{itemize} - \item \texttt{primes.txt} contains a list of primes listed - column-wise - \item We read the data using \texttt{loadtxt} - \end{itemize} - \begin{lstlisting} - In[]: primes = loadtxt('primes.txt') - In[]: print primes - \end{lstlisting} - \begin{itemize} - \item \texttt{primes} is a sequence of floats - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Reading two column data} - \begin{itemize} - \item \texttt{pendulum.txt} has two columns of data - \item Length of pendulum in the first column - \item Corresponding time period in second column - \item \texttt{loadtxt} requires both columns to be of same length - \end{itemize} - \begin{lstlisting} - In[]: pend = loadtxt('pendulum.txt') - In[]: print pend - \end{lstlisting} - \begin{itemize} - \item \texttt{pend} is not a simple sequence like \texttt{primes} - \end{itemize} -\end{frame} - -\begin{frame}[fragile] - \frametitle{Unpacking with \texttt{loadtxt}} - \begin{lstlisting} - In[]: L, T = loadtxt('pendulum.txt', - unpack=True) - In[]: print L - In[]: print T - \end{lstlisting} - \begin{itemize} - \item We wish to plot L vs. $T^2$ - \item \texttt{square} function gives us the squares - \item (We could instead iterate over T and calculate) - \end{itemize} - \begin{lstlisting} - In[]: Tsq = square(T) - - In[]: plot(L, Tsq, '.') - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] - \frametitle{\texttt{errorbar}} - \begin{itemize} - \item Experimental data always has errors - \item \texttt{pendulum\_error.txt} contains errors in L and T - \item Read the values and make an error bar plot - \end{itemize} - \begin{lstlisting} - In[]: L, T, L_err, T_err = \ - loadtxt('pendulum_error.txt', - unpack=True) - In[]: Tsq = square(T) - - In[]: errorbar(L, Tsq , xerr=L_err, - yerr=T_err, fmt='b.') - \end{lstlisting} -\end{frame} - -\begin{frame} -\frametitle{Errorbar} -\includegraphics[scale=0.45]{../advanced_python/images/L-Tsq.png}\\ -\end{frame} - -\section{Other kinds of Plots} - -\begin{frame}[fragile] - \frametitle{Scatter Plot} - \begin{itemize} - \item The data is displayed as a collection of points - \item Value of one variable determines position along x-axis - \item Value of other variable determines position along y-axis - \item Let's plot the data of profits of a company - \end{itemize} - \begin{lstlisting} - In[]: year, profit = loadtxt( - 'company-a-data.txt', - dtype=type(int())) - - In[]: scatter(year, profit) - \end{lstlisting} - \begin{itemize} - \item \alert{\texttt{dtype=int}; default is float} - \end{itemize} -\end{frame} - -\begin{frame} -\frametitle{Scatter Plot} -\includegraphics[scale=0.45]{../advanced_python/images/scatter.png}\\ -\end{frame} - -\begin{frame}[fragile] - \frametitle{Pie Chart} - \begin{lstlisting} - In[]: pie(profit, labels=year) - \end{lstlisting} -\includegraphics[scale=0.35]{../advanced_python/images/pie.png}\\ -\end{frame} - -\begin{frame}[fragile] - \frametitle{Bar Chart} - \begin{lstlisting} - In[]: bar(year, profit) - \end{lstlisting} -\includegraphics[scale=0.35]{../advanced_python/images/bar.png}\\ -\end{frame} - -\begin{frame}[fragile] - \frametitle{Log-log plot} - \begin{itemize} - \item Plot a \texttt{log-log} chart of $y=5x^3$ for x from 1 to 20 - \end{itemize} - \begin{lstlisting} - In[]: x = linspace(1,20,100) - In[]: y = 5*x**3 - - In[]: loglog(x, y) - In[]: plot(x, y) - \end{lstlisting} - \begin{itemize} - \item Look at \url{http://matplotlib.sourceforge.net/contents.html} - for more! - \end{itemize} -\end{frame} - -\begin{frame} -\frametitle{Log-log plot Plot} -\includegraphics[scale=0.45]{../advanced_python/images/loglog.png}\\ -\end{frame} - - diff --git a/advanced_python/slides/scipy.tex b/advanced_python/slides/scipy.tex deleted file mode 100644 index 1116c3d..0000000 --- a/advanced_python/slides/scipy.tex +++ /dev/null @@ -1,273 +0,0 @@ -\section{Solving Equations} - -\begin{frame}[fragile] -\frametitle{Solution of linear equations} -Consider, - \begin{align*} - 3x + 2y - z & = 1 \\ - 2x - 2y + 4z & = -2 \\ - -x + \frac{1}{2}y -z & = 0 - \end{align*} -Solution: - \begin{align*} - x & = 1 \\ - y & = -2 \\ - z & = -2 - \end{align*} -\end{frame} - -\begin{frame}[fragile] -\frametitle{Solving using Matrices} -Let us now look at how to solve this using \texttt{matrices} - \begin{lstlisting} -In []: A = array([[3,2,-1], - [2,-2,4], - [-1, 0.5, -1]]) -In []: b = array([1, -2, 0]) -In []: x = solve(A, b) - \end{lstlisting} -\end{frame} - -\begin{frame}[fragile] -\frametitle{Solution:} -\begin{lstlisting} -In []: x -Out[]: array([ 1., -2., -2.]) -\end{lstlisting} -\end{frame} - -\begin{frame}[fragile] -\frametitle{Let's check!} -\begin{small} -\begin{lstlisting} -In []: Ax = dot(A, x) -In []: Ax -Out[]: array([ 1.00000000e+00, -2.00000000e+00, - -1.11022302e-16]) -\end{lstlisting} -\end{small} -\begin{block}{} -The last term in the matrix is actually \alert{0}!\\ -We can use \texttt{allclose()} to check. -\end{block} -\begin{lstlisting} -In []: allclose(Ax, b) -Out[]: True -\end{lstlisting} -\end{frame} - -\begin{frame}[fragile] -\frametitle{\texttt{roots} of polynomials} -\begin{itemize} -\item \texttt{roots} function can find roots of polynomials -\item To calculate the roots of $x^2-5x+6$ -\end{itemize} -\begin{lstlisting} - In []: coeffs = [1, -5, 6] - In []: roots(coeffs) - Out[]: array([3., 2.]) -\end{lstlisting} -\vspace*{-.2in} -\begin{center} -\includegraphics[height=1.6in, interpolate=true]{images/roots} -\end{center} -\end{frame} - -\begin{frame}[fragile] -\frametitle{SciPy: \texttt{fsolve}} -\begin{small} -\begin{lstlisting} - In []: from scipy.optimize import fsolve -\end{lstlisting} -\end{small} -\begin{itemize} -\item Finds the roots of a system of non-linear equations -\item Input arguments - Function and initial estimate -\item Returns the solution -\end{itemize} -\end{frame} - -\begin{frame}[fragile] -\frametitle{\texttt{fsolve} \ldots} -Find the root of $sin(z)+cos^2(z)$ nearest to $0$ -\begin{lstlisting} -In []: def g(z): - ....: return sin(z)+cos(z)*cos(z) - -In []: fsolve(g, 0) -Out[]: -0.66623943249251527 -\end{lstlisting} -\begin{center} -\includegraphics[height=2in, interpolate=true]{images/fsolve} -\end{center} -\end{frame} - -\section{ODEs} - -\begin{frame}[fragile] -\frametitle{Solving ODEs using SciPy} -\begin{itemize} -\item Consider the spread of an epidemic in a population -\item $\frac{dy}{dt} = ky(L-y)$ gives the spread of the disease -\item $L$ is the total population. -\item Use $L = 2.5E5, k = 3E-5, y(0) = 250$ -\item Define a function as below -\end{itemize} -\begin{lstlisting} -In []: from scipy.integrate import odeint -In []: def epid(y, t): - .... k = 3.0e-5 - .... L = 2.5e5 - .... return k*y*(L-y) - .... -\end{lstlisting} -\end{frame} - -\begin{frame}[fragile] -\frametitle{Solving ODEs using SciPy \ldots} -\begin{lstlisting} -In []: t = linspace(0, 12, 61) - -In []: y = odeint(epid, 250, t) - -In []: plot(t, y) -\end{lstlisting} -%Insert Plot -\end{frame} - -\begin{frame}[fragile] -\frametitle{Result} -\begin{center} -\includegraphics[height=2in, interpolate=true]{images/epid} -\end{center} -\end{frame} - - -\begin{frame}[fragile] -\frametitle{ODEs - Simple Pendulum} -We shall use the simple ODE of a simple pendulum. -\begin{equation*} -\ddot{\theta} = -\frac{g}{L}sin(\theta) -\end{equation*} -\begin{itemize} -\item This equation can be written as a system of two first order ODEs -\end{itemize} -\begin{align} -\dot{\theta} &= \omega \\ -\dot{\omega} &= -\frac{g}{L}sin(\theta) \\ - \text{At}\ t &= 0 : \nonumber \\ - \theta = \theta_0(10^o)\quad & \&\quad \omega = 0\ (Initial\ values)\nonumber -\end{align} -\end{frame} - -\begin{frame}[fragile] -\frametitle{ODEs - Simple Pendulum \ldots} -\begin{itemize} -\item Use \texttt{odeint} to do the integration -\end{itemize} -\begin{lstlisting} -In []: def pend_int(initial, t): - .... theta = initial[0] - .... omega = initial[1] - .... g = 9.81 - .... L = 0.2 - .... F=[omega, -(g/L)*sin(theta)] - .... return F - .... -\end{lstlisting} -\end{frame} - -\begin{frame}[fragile] -\frametitle{ODEs - Simple Pendulum \ldots} -\begin{itemize} -\item \texttt{t} is the time variable \\ -\item \texttt{initial} has the initial values -\end{itemize} -\begin{lstlisting} -In []: t = linspace(0, 20, 101) -In []: initial = [10*2*pi/360, 0] -\end{lstlisting} -\end{frame} - -\begin{frame}[fragile] -\frametitle{ODEs - Simple Pendulum \ldots} -%%\begin{small} -\texttt{} -%%\end{small} -\begin{lstlisting} -In []: from scipy.integrate import odeint -In []: pend_sol = odeint(pend_int, - initial,t) -\end{lstlisting} -\end{frame} - -\begin{frame}[fragile] -\frametitle{Result} -\begin{center} -\includegraphics[height=2in, interpolate=true]{images/ode} -\end{center} -\end{frame} - -%% \section{FFTs} - -%% \begin{frame}[fragile] -%% \frametitle{The FFT} -%% \begin{itemize} -%% \item We have a simple signal $y(t)$ -%% \item Find the FFT and plot it -%% \end{itemize} -%% \begin{lstlisting} -%% In []: t = linspace(0, 2*pi, 500) -%% In []: y = sin(4*pi*t) - -%% In []: f = fft(y) -%% In []: freq = fftfreq(500, t[1] - t[0]) - -%% In []: plot(freq[:250], abs(f)[:250]) -%% In []: grid() -%% \end{lstlisting} -%% \end{frame} - -%% \begin{frame}[fragile] -%% \frametitle{FFTs cont\dots} -%% \begin{lstlisting} -%% In []: y1 = ifft(f) # inverse FFT -%% In []: allclose(y, y1) -%% Out[]: True -%% \end{lstlisting} -%% \end{frame} - -%% \begin{frame}[fragile] -%% \frametitle{FFTs cont\dots} -%% Let us add some noise to the signal -%% \begin{lstlisting} -%% In []: yr = y + random(size=500)*0.2 -%% In []: yn = y + normal(size=500)*0.2 - -%% In []: plot(t, yr) -%% In []: figure() -%% In []: plot(freq[:250], -%% ...: abs(fft(yn))[:250]) -%% \end{lstlisting} -%% \begin{itemize} -%% \item \texttt{random}: produces uniform deviates in $[0, 1)$ -%% \item \texttt{normal}: draws random samples from a Gaussian -%% distribution -%% \item Useful to create a random matrix of any shape -%% \end{itemize} -%% \end{frame} - -%% \begin{frame}[fragile] -%% \frametitle{FFTs cont\dots} -%% Filter the noisy signal: -%% \begin{lstlisting} -%% In []: from scipy import signal -%% In []: yc = signal.wiener(yn, 5) -%% In []: clf() -%% In []: plot(t, yc) -%% In []: figure() -%% In []: plot(freq[:250], -%% ...: abs(fft(yc))[:250]) -%% \end{lstlisting} -%% Only scratched the surface here \dots -%% \end{frame} diff --git a/advanced_python/slides/tmp.tex b/advanced_python/slides/tmp.tex deleted file mode 100644 index 9913703..0000000 --- a/advanced_python/slides/tmp.tex +++ /dev/null @@ -1,316 +0,0 @@ -% Created 2011-04-18 Mon 03:20 -\documentclass[presentation]{beamer} -\usepackage[utf8]{inputenc} -\usepackage[T1]{fontenc} -\usepackage{fixltx2e} -\usepackage{graphicx} -\usepackage{longtable} -\usepackage{float} -\usepackage{wrapfig} -\usepackage{soul} -\usepackage{textcomp} -\usepackage{marvosym} -\usepackage{wasysym} -\usepackage{latexsym} -\usepackage{amssymb} -\usepackage{hyperref} -\tolerance=1000 -\usepackage[english]{babel} \usepackage{ae,aecompl} -\usepackage{mathpazo,courier,euler} \usepackage[scaled=.95]{helvet} -\usepackage{listings} -\lstset{language=Python, basicstyle=\ttfamily\bfseries, -commentstyle=\color{red}\itshape, stringstyle=\color{darkgreen}, -showstringspaces=false, keywordstyle=\color{blue}\bfseries} -\providecommand{\alert}[1]{\textbf{#1}} - -\title{modules.rst.org} -\author{} -\date{\today} - -\usetheme{Warsaw}\usecolortheme{default}\useoutertheme{infolines}\setbeamercovered{transparent} -\begin{document} - -\maketitle - -\begin{frame} -\frametitle{Outline} -\setcounter{tocdepth}{3} -\tableofcontents -\end{frame} - - - - -\section{Using Python modules} -\label{sec-1} - - -We shall, in this section, see how to run Python scripts from the -command line, and more details about importing modules. - -Let us create a simple python script to print hello world. Open your -text editor and type the following, and save the script as \texttt{hello.py}. - -\begin{verbatim} -print "Hello world!" -\end{verbatim} - -Until now we have been running scripts from inside IPython, using - -\begin{verbatim} -%run -i hello.py -\end{verbatim} - -But, as we know, IPython is just an advanced interpreter and it is not -mandatory that every one who wants to run your program has IPython -installed. - -So, the right method to run the script, would be to run it using the -Python interpreter. Open the terminal and navigate to the directory -where \texttt{hello.py} is saved. - -Then run the script by saying, - -\begin{verbatim} -python hello.py -\end{verbatim} - -The script is executed and the string \texttt{Hello World!} has been printed. - -Now let us run a script that plots a simple sine curve in the range -2pi -to 2pi, using Python, instead of running it from within IPython. - -Type the following lines and save it in \texttt{sine\_plot.py} file. - -\begin{verbatim} -x = linspace(-2*pi, 2*pi, 100) -plot(x, sin(x)) -show() -\end{verbatim} - -Now let us run sine\_plot.py as a python script. - -\begin{verbatim} -python sine_plot.py -\end{verbatim} - -Do we get the plot? No! All we get is error messages. Python complains -that \texttt{linspace} isn't defined. What happened? Let us try to run the same -script from within IPython. Start IPython, with the \texttt{-pylab} argument -and run the script. It works! - -What is going on, here? IPython when started with the \texttt{-pylab} option, -is importing a whole set of functionality for us to work with, without -bothering about importing etc. - -Let us now try to fix the problem by importing \texttt{linspace}. - -Let's add the following line as the first line in the script. - -\begin{verbatim} -from scipy import * -\end{verbatim} - -Now let us run the script again, - -\begin{verbatim} -python sine_plot.py -\end{verbatim} - -Now we get an error, that says \texttt{plot} is not defined. Let's edit the -file and import this from pylab. Let's add the following line, as the -second line of our script. - -\begin{verbatim} -from pylab import * -\end{verbatim} - -And run the script, - -\begin{verbatim} -python sine_plot.py -\end{verbatim} - -Yes! it worked. So what did we do? - -We actually imported the required functions and keywords, using -\texttt{import}. By using the *, we are asking python to import everything from -the \texttt{scipy} and \texttt{pylab} modules. This isn't a good practice, as 1. it -imports a lot of unnecessary things 2. the two modules may have -functions with the same name, which would cause a conflict. - -One of the ways out is to import only the stuff that we need, -explicitly. - -Let us modify sine\_plot.py by replacing the import statements with the -following lines. - -\begin{verbatim} -from scipy import linspace, pi, sin -from pylab import plot, show -\end{verbatim} - -Now let us try running the code again as, - -\begin{verbatim} -python show_plot.py -\end{verbatim} - -As expected, this works. But, once the number of functions that you need -to import increases, this is slightly inconvenient. Also, you cannot use -functions with the same name, from different modules. To overcome this, -there's another method. - -We could just import the modules as it is, and use the functions or -other objects as a part of those modules. Change the import lines, to -the following. - -\begin{verbatim} -import scipy -import pylab -\end{verbatim} - -Now, replace \texttt{pi} with \texttt{scipy.pi}. Similarly, for \texttt{sin} and \texttt{linspace}. -Replace \texttt{plot} and \texttt{show} with \texttt{pylab.plot} and \texttt{pylab.show}, -respectively. - -Now, run the file and see that we get the output, as expected. - -We have learned how to import from modules, but what exactly is a -module? How is one written? - -A module is simply a Python script containing the definitions and -statements, which can be imported. So, it is very easy to create your -own modules. You just need to stick in all your definitions into your -python file and put the file in your current directory. - -When importing, Python searches the locations present in a variable -called the Python path. So, our module file should be present in one of -the locations in the Python path. The first location to be searched is -the current directory of the script being run. So, having our module -file in the current working directory, is the simplest way to allow it -to be used as a module and import things from it. - -Python has a very rich standard library of modules. It is very -extensive, offering a wide range of facilities. Some of the standard -modules are, - -for Math: math, random for Internet access: urllib2, smtplib for System, -Command line arguments: sys for Operating system interface: os for -regular expressions: re for compression: gzip, zipfile, tarfile And -there are lot more. - -Find more information at Python Library reference, -\texttt{http://docs.python.org/library/} - -There are a lot of other modules like pylab, scipy, Mayavi, etc which -are not part of the standard Python library. - -This brings us to the end of our discussion on modules and running -scripts from the command line. -\section{Writing modules} -\label{sec-2} - - -In this section we shall look at writing modules, in some more detail. -Often we will have to reuse the code that we have previously written. We -do that by writing functions. Functions can then be put into modules, -and imported as and when required. - -Let us first write a function that computes the gcd of two numbers and -save it in a script. - -\begin{verbatim} -def gcd(a, b): - while b: - a, b = b, a%b - return a -\end{verbatim} - -Now, we shall write a test function in the script that tests the gcd -function, to see if it works. - -\begin{verbatim} -if gcd(40, 12) == 4 and gcd(12, 13) == 1: - print "Everything OK" -else: - print "The GCD function is wrong" -\end{verbatim} - -Let us save the file as gcd\_script.py in \texttt{/home/fossee/gcd\_script.py} -and run it. - -\begin{verbatim} -$ python /home/fossee/gcd_script.py -\end{verbatim} - -We can see that the script is executed and everything is fine. - -What if we want to use the gcd function in some of our other scripts. -This is also possible since every python file can be used as a module. - -But first, we shall understand what happens when you import a module. - -Open IPython and type - -\begin{verbatim} -import sys -sys.path -\end{verbatim} - -This is a list of locations where python searches for a module when it -encounters an import statement. Hence, when we just did \texttt{import sys}, -python searches for a file named \texttt{sys.py} or a folder named \texttt{sys} in all -these locations one by one, until it finds one. We can place our script -in any one of these locations and import it. - -The first item in the list is an empty string which means the current -working directory is also searched. - -Alternatively, we can also import the module if we are working in same -directory where the script exists. - -Since we are in /home/fossee, we can simply do - -\begin{verbatim} -import gcd_script -\end{verbatim} - -We can see that the gcd\_script is imported. But the test code that we -added at the end of the file is also executed. - -But we want the test code to be executed only when the file is run as a -python script and not when it is imported. - -This is possible by using \texttt{\_\_name\_\_} variable. - -Go to the file and add - -\begin{verbatim} -if __name__ == "__main__": -\end{verbatim} - -before the test code and indent the test code. - -Let us first run the code. - -\begin{verbatim} -$ python gcd_script.py -\end{verbatim} - -We can see that the test runs successfully. - -Now we shall import the file - -\begin{verbatim} -import gcd_script -\end{verbatim} - -We see that now the test code is not executed. - -The \texttt{\_\_name\_\_} variable is local to every module and it is equal to -\texttt{\_\_main\_\_} only when the file is run as a script. Hence, all the code -that goes in to the if block, \texttt{if \_\_name\_\_ =} ``__main__'':= is executed -only when the file is run as a python script. - -\end{document} |