Adding Data Visualization to Python for Producing Graphs
Pages: 1, 2, 3, 4

Going Beyond the Basics

Creating custom plots or significantly modifying some of the previous examples will force you to engross yourself in the DISLIN function set. If this is your desire, you need to check out the pxDislin module written by Paul Magwene available here. PxDislin is an Object-Oriented wrapper for DISLIN that provides a straightforward and simple programming model.

PxDislin

To get started with pxDislin, start a new console session and import the library.

>>> from pxdislin import *

This takes care of importing the DISLIN library itself. Of course if you want NumPy (don't we all?), remember to import it as well.

PxDislin has a class hierarchy that builds on the basic dPlot object. The most basic graphic consists of a dPlot object incorporating a dAxis object. The dPlot object can be thought as the canvas on which the drawing is made. The dAxis object helps to define the size. Let's try an example

>>> plot = dPlot()
>>> axis = dAxis(-10,10,-10,10)
>>> plot.add_axis(axis)
>>> plot.show()

The first line creates the basic plot object. The second line created an axis object. The third associated the two and the fourth caused the plot to be drawn. If you are following along, you should have a rectangular window on your screen with an empty axis.

PxDislin objects support many options via attributes. The attributes are broken up into 'options' and 'info' types. Options refer to features of a plot that you might want to change after the object is created, perhaps to alter its appearance. Options are set by calling the objects config(). In pxDislin, calling object.config() is equivalent to calling object(). In the above example click the right mouse button to clear the plot and type

>>>plot(ttext="Title")
>>>plot.show()

A new plot window should appear looking as before but with a title string. To see a list of options for a particular object, simply type the object name followed by an empty set of parenthesis.

>>> plot()

*dPlot:

        app_look = console
        color = fore
        continue_key = Return
        display_type = screen
        external_ID = None
        external_type = window
        filename = dis.out
        font = default
        font_size = 36
        height = 500
        origin = (25, 25)
        page_height = 3000
        page_width = 3000
        ps_origin = (25, 25)
        pscript = None
        pscript = None
        psfont = courier
        psfont = courier
        scale = 1.0
        screen_mode = normal
        size = None
        suppress_disout = 1
        tsize = 64
        ttext = test
        width = 500
        *END OBJECT: dPlot

Notice the nice additional feature of the command telling you what the current setting is for each option.

The info attributes directly affect the generation of the object (typically they contain the data to be plotted) and are set by using the . (dot) notation. The info attributes are typically passed into the object at creation time as parameters to the function.

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