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Some greeting - Hi or Hello or Welcome - would be polite to start with

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Hello, in this tutorial, we will cover the basics of the Plotting features available in Python. We shall use Ipython and pylab. Ipython is An Enhanced Interactive Python interpreter. It provides additional features like tab completion, help etc. pylab is python library which provides plotting functionality. 

$ ipython -pylab

press RETURN

This will give us a prompt where we can get started. 

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

In []: lins<Tab>pace?

It shows documentation related to linspace function. 'help' talks in detail about arguments to be passed, return values, some examples on usage. (To scroll down the page use 'SPACE' key and to scroll up use 'b')To navigate through content use arrow(/Page Up and Page Down) keys. ':See Also' section hints about other related or similar functions which might be useful. To exit help (mode) press 'q'.

Check value of x by

In []: x

 x is a sequence of 100 points starting from 0 to 2*pi. Length of x can be seen via function

In []: len(x)

To obtain the plot we say,

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

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Both 'pi' and 'sin' come from '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').

Now we will add a legend to the plot. 

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

To go to previous command, we can use 'UP Arrow key' and 'DOWN' will take us (in reverse order)/back.

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

In []: legend(['sin(2y)'], loc = 'center')

other positions which can be tried are

'best' 

'right'

In []: annotate('local max', xy=(1.5, 1))

Now, we save the plot as follows

When we use plot again by default plots get overlaid.

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

we update Y axis label 

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

In []: clf()

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)

plot() plot command plots a sin plot on figure(1)

to creates a new plain figure window without any plot. 

In []: figure(2)

Any command issued henceforth applies to this window only.

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

The previous plot window remains unchanged to these commands.

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

figure(1) shifts the focus back to figure(1).

In []: figure(1)

title() sets the title of figure(1) 

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

Here we save the plot of figure(1). 

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 takes the following optional parameters such as 'r' which generates the plot in red color. 

Use up arrow key to get till this command

In []: plot(x, cos(x), 'r') and add argument.

In []: clf()

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

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

In []: clf()

In []: clf()

A plot using dashed lines can be generated by passing the '--' parameter

In []: plot(x, y, '--')

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

In []: clf()

and finally to close the plot

In []: close()

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This brings us to the end of this tutorial.  This tutorial is first in the series of Python for Scientific Computing Tutorials.

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