* Script

*Hello and welcome to the tutorial on Basic Plotting using Python. 

*The intended audience for this tutorial are Engineering, mathematics and science teachers and students

*In this tutorial, we will cover the basics of the Plotting features available in Python. 

For this we shall use  Ipython and pylab. 

Ipython is An Enhanced Interactive Python interpreter. It provides additional features like tab completion,easier access to help , and many other useful features which are not present in the vanilla Python interpreter.

Pylab is python library which provides plotting functionality. 

I am assuming that both Ipython and Pylab are installed on your system .

*On your terminal type in the command

$ ipython -pylab

press RETURN

We will first start with the customary Hello world program by writing:

In []: print 'hello world'

Voila we have got hello world as the output 

To exit ipython press Ctrl-D.

*Now we will get back to plotting.

type again :

$ ipython -pylab

press RETURN

First, we will create a sequence of equally spaced points starting from 0 to 2*pi , we will use function linspace for that

Type:

In []: x = lins<Tab> This is an Ipython feature that will auto-suggest the word

In []  x=linspace( RETURN

oops  I made a mistake . As you can see I made the mistake of not writing command correctly

and Ipython changed the prompt . To get the old prompt back type crtl-c

In []: x = linspace(0, 2*pi, 100)

*As you can see linspace can take three parameters start, stop, and num and returns num evenly space points . You can scroll through the help to know more about the function

*To know more about any function,  example for the 'linspace' function you can type ? after it .

In []: linspace?

It shows documentation related to linspace function. 'help' talks in detail about arguments to be passed, return values, some examples on usage. You can scroll the help using up, and down arrows keys.

At any time you want to come out of the help use 'q' key. 

See how easy it is  to get help in IPython.  

To obtain the plot we use,

In []: plot(x, sin(x))

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As you can see a plot has appeared on the screen. 

***

The plot has the default color and line properties. 

In this case we have used two commands 

'pi' and 'sin' these come from 'pylab' library called using -pylab. 

*Now that we have a basic plot, we can label and title the plot. 

In []: xla<TAB>bel('x') will add a label to the x-axis. Note that 'x' is enclosed in quotes. 

Similarly

In []: ylabel('sin(x)') adds a label to the y-axis.

To add a title to plot we simply use 

In []: tit<TAB>le('Sinusoid').

Hmm we also got the axis's nicely labeled and the plot titled but there is still a important detail left.That might leave a teacher unsatisfied, it lacks a legend. 

Add a legend to the plot by typing 

In []: legend(['sin(x)'])

Ok what if I want the legend to be in different location. It just requires us to define one extra parameter. 

We have just typed legend command can we reuse it . Yes 

To go to previous command, we can use 'UP Arrow key' and 'DOWN' will take us back.

We can modify previous command to specify the location of the legend, by passing an additional argument to the function. 

#Ask madhu how to describe the feature here.

Once you start editing a previous command and then you try to use 'Up arrow key ' you can get commands that are only similar to the command you are editing. But if you move your cursor to the beginning of the line you can get all the previous commands using up and down arrow keys.

In []: legend(['sin(x)'], loc = 'center')

Note that once 

other positions which can be tried are

'best' 

'right'

Very often in mathematical plots we have to define certain points and their meaning also called annotating . We next look at how to annotate

In this case, let's add a comment at the point of origin. 

In []: annotate('origin', xy=(0, 0))

The first argument is the comment string and second one is the position for it. 

Ok, what do I do with all this effort . I obviously have to save it . 

We save the plot by the function savefig

In []: savefig('sin.png') saves the figure with the name 'sin.png' in the current directory. 

#other supported formats are: eps, ps, pdf etc.

When we use plot again 

In []: plot(x, cos(x)) by default plots get overlaid.

we update Y axis label 

In []: ylabel('f(x)')

Now in these situations with overlaid graphs, legend becomes absolutely essential. To add multiple legends, we pass the strings within quotes separated by commas and enclosed within square brackets as shown.

In []: legend( [ 'sin(x)' , 'cos(x)'] )

In []: clf()

clears the plot area and starts afresh.

*In case we want to create multiple plots rather than overlaid plots, we use 'figure' function.

The figure command is used to open a plain figure window without any plot.

In []: figure(1)

We will use plot() plot again to plot a sin curve on figure(1)

In []: plot(x, sin(x))

to creates a new plain figure window without any plot type: 

In []: figure(2)

figure() is also used to shift the focus between multiple windows. 

Any command issued henceforth applies to this window only so typing

In []: plot(x, cos(x))

plots cos curve on second window now.

The previous plot window remains unchanged to these commands.

calling function figure using argument 1 shifts the focus back to figure(1).

In []: figure(1)

title() sets the title of figure(1) 

In []: title('sin(x)')

Now we save the plot of figure(1) by typing 

In []: savefig('sine.png')

close() closes figure(1). Now there is just one figure that is open and hence 

the focus is automatically shifted to figure(2).

In []: close()

close() now closes the figure(2).

In []: close()

The plot command can take the additional parameters such as 'g' which generates the plot in green color. 

Passing the linewidth=2 option to plot, generates the plot with linewidth of two units.

Use Up arrow to get to the previous commands 

In []: plot(x, sin(x), 'g', linewidth=2) and add arguments

In []: clf()

In order to plot points you may pass '.' as a parameter to plot

In []: plot(x, sin(x), '.')

In []: clf()

You may look at more options related to colors and type of lines using plot?(question mark)

quit the documentation using 'q'

In []: clf()

and finally to close the plot

In []: close()

In this tutorial we learned 

Some IPython Features

Starting and exiting.

autocompletion.

help functionality.

Regarding plotting we covered:

How to create basic plots.

Adding labels, legends annotation etc.

How to change looks of the plot like colors, linewidth formats etc

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This brings us to the end of this tutorial. This is the first tutorial in a series of tutorials on Python for Scientific Computing. This tutorial is created by the FOSSEE team, IIT Bombay. Hope you enjoyed it and found it useful.

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A slide of review of what has been covered and sequentially/rapidly going through them.

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Various problems of Ipython, navigation and enter, exit.

What about xlim and ylim?