Python 3.4.3

IIT Bombay is leading the effort to popularise Python for Scientific Computing in India. This is part of the Free and Open source Software for Science and Engineering Education (http://fossee.in) project, supported by the National Mission on Education through ICT of MHRD.

IIT Bombay is using Spoken Tutorials (http://spoken-tutorial.org) to create learning material for FOSS. This is the main page for the organisation of the scripts required for Standard two day workshop we conduct on "Python for Scientific Computing" spoken tutorials.

Learners: UG/PG CSE/IT/CS students and CBSE high school students

Module 1: Basic Plotting

Getting started with ipython

Use Python 3.5.2
Use Ipython version 5.1.0
IPython is an enhanced interactive Python interpreter.
Invoke the IPython interpreter
Quit the IPython interpreter
Navigate the IPython session history
Use tab-completion to work faster.
See the documentation of functions using question mark.
Interrupt commands using Ctrl + C when we make an error.
round command

Using the plot command interactively

Use Python 3.4.3
Use Ipython version 5.1.0
Start IPython with pylab.
ImportError if matplotlib is not installed
clf() function
Use the linspace function to create equally spaced points in a region.
Find the length of sequences using len function.
Plot mathematical functions using plot.
Clear drawing area using clf.
Usage of buttons in the UI of the plot window such as - save, zoom, move axis, back and forward and Home

Embellishing a plot

Use Python 3.4.3
Use Ipython version 5.1.0
Modify the attributes of a plot
Pass additional keyword arguments to plot command
Add title to a plot using 'title' command.
Incorporate LaTeX style formatting by adding a $ sign before and after the string.
Label x and y axes using xlabel() and ylabel() commands.
Add annotations to a plot using annotate() command.
Get the limits of axes using xlim() and ylim() commands.
Set the limits of axes using xlim() and ylim() commands.

Saving plots

Use Python 3.4.3
Use Ipython version 5.1.0
Save plots using the savefig() function.
Save the plots in different formats like
- pdf
- ps
- png
- svg
- eps

Multiple plots

Use Python 3.4.3
Use IPython 5.1.0
Draw multiple plots which are overlaid.
Operations on individual plots.
Use the figure command.
Distinguish between multiple overlaid plots.
Use the legend command.
Serial number of the plot to select corresponding plot.
Switch between the plots
Saving individual plots.

Subplots

Use Python 3.4.3
Use IPython 5.1.0
Creating subplots
Switching between subplots.
Subplot command
Passing arguments to subplot command.
First argument is the number of rows of subplots.
Second argument is the number of columns of subplots
Third argument specifies the serial number for subplot.

Additional features of IPython

Use Python 3.4.3
Use IPython 5.1.0
Retrieve the history using %history command.
View only a part of history by passing argument to %history command.
Pass arguments to %history to get particular lines of code
Save the required lines of code in required order using '%save' command.
Use '%run -i' command to run a saved script.

Module 2: Plotting Experimental Data

loading data from files

load data from file
single column
multiple columns separated by delimiter
cat command
loadtxt()
columns separated by spaces
columns separated by semi-colon
unpack argument
delimiter argument
three columns of data

Plotting the data

plotting data
list
list element-wise squaring
plot data points
clear plots
errorbar function
dots or filled circles in plot
plot with red pluses
explore documentation in ipython
plot with errorbars
using format argument

Other types of plots

scatter plot
scatter function
scatter plot with various arguments
logarithmic plot
loglog function
cat command
loadtxt function
unpack parameter of loadtxt
linspace
scatter versus plot

Plotting charts

Use Python 3.4.3
Use IPython 5.1.0
To produce scatter plot
Plot a pie chart using pie() function
Plot a bar chart using bar() function
Access the matplotlib online help
Charts with line hatching

Module 4: Handling Large Data Files

Getting started with lists

What is a list?
- Define List
- List index
Create:
- List with elements
- Empty list
- List within a list
Find out the list length using len function
- Access elements using their index numbers
- Append elements to list using the function append
- Delete element from list using the del and remove function

Getting started with for

For loop syntax
Example to use For loop
Indentation in for loop
Create blocks in python using for
Iterate over a list using for loop
How to get out of the block
use of Range() function
Range function in for loop
How to use Python interpreter
IPython interpreter to specify blocks

Getting started with strings

What are strings?
How are strings denoted in Python?
String concatenation
Multiply a string with an integer
Accessing individual elements of a string
Accessing elements of a string using negative indices
Split() function
Join() function
Define a string in different ways
Print a string repeatedly

Getting started with files

Open a file
Open() function
Different Modes of opening a file
Read() method
Read the content of the file line by line
Read the entire content of the file
Append the lines of a file to a list
Close a file
Demonstration using a txt file
Splitlines() method

Parsing data

explain what is parsing

strip (with strings)

split (with strings)
- with delimiters
  - specify space as delimiter

datatype conversion

reading from files
- do the same problem done with loadtxt (for pendulum)
- basic parse sslc text

Statistics

mean
- summing

median

std

Module 5: Arrays and Matrices

Getting started with arrays

why arrays
- speed - simply say
- array level operations

creating arrays
- direct data
- list conversion
- homogeneous
- builtins - identitiy, zeros,

array operations
- + - * /

Accessing parts of arrays

accessing individual elements

changing individual elements

slicing, striding

image manipulation

Matrices

creating matrices
- direct data
- list conversion
- builtins - identitiy, zeros,

matrix operations
- + - * /
- dot
- inv
- det
- eig
- norm
- svd

Least square fit

show pendulum
- use loadtxt

lstsq

Module 6: Python Language: Basics

Basic datatypes & operators

int
- L, long

float
- repr, str

complex

boolean

conversion functions

sequence datatypes & mutability
- list available sequence datatypes
  - string
  - list
  - tuple
- mutability
- conversion
- common stuff
  - len
  - in
  - max, min, sum, sorted, reversed
  - accessing individual elements
  - slicing, striding

I/O

Input Output in Python

Conditionals

if, elif, else

pass

Loops

while

for

pass, break, continue

Module 7: Python Language: Datastructures

Manipulating lists

concatenation

slicing

striding

.sort

sorted

.reverse

reversed

Manipulating strings

upper, lower,

replace

slicing

[::-1]

reversed

palindrome check

Getting started with tuples

immutability

tuple packing, unpacking
- a, b = b, a

accessing individual elements

slicing, striding

Dictionaries

empty

filled

accessing via keys

.values(), .keys()

in

iteration

Sets

About sets in python

Module 8: Python Language: Advanced

Getting started with functions

defining function

arguments

docstrings

return values
- can return multiple values

code reading exercises

Advanced features of functions

default arguments

keyword arguments

built-in functions show off

Using python modules

scipy

pylab

sys

Writing python scripts

import

Testing and debugging

Handling Errors and Exceptions

ValueError exception
ZeroDivisionError exception
try except clause in Python
debugging

Contributors and Content Editors

Nancyvarkey, Nirmala Venkat, PoojaMoolya, Trupti