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

basic savefig

png, pdf, ps, eps, svg

going to OS and looking at the file

Multiple plots

overlays
- linspace
  - give one with very few points, more points
  - show smoothness of the curve

legend

figure 1, figure2

Subplots

run basic Python commands on the ipython console
use Plots interactively
Embellish a plot

Additional features of IPython

%save, %history, %run

Module 2: Plotting Experimental Data

loading data from files

loadtxt with unpack=True
- primes.list (one col)
- pendulum.txt (two col)

Plotting the data

plot L vs. T²
- using square function

problem with 3 cols
- 3rd column is error
- error bar

Other types of plots

scatter

log-log plots

Plotting charts

pie chart

bar chart

illustration of other plots, matplotlib help

Module 4: Handling Large Data Files

Getting started with lists

empty

filled lists
- heterogenity

accessing

len

append elements

del (+ remove)

Getting started with for

blocks in python
- (indentation)

blocks in ipython
- … prompt
- hitting enter

for with a list

range function

Getting started with strings

strings
- single, double, triple quoted

accessing elements

show immutability

tell that there are methods for manipulation

Getting started with files

show file object

read the file with read

closing the file

for line in file:

print a line

append the lines to a list

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