``` A Tutorial for Creating Movies from Graphs of Data ```

Introduction

This tutorial briefly demonstrates tools for making movies of graphed data, as might be needed to show how data change with time. Before getting into details, it will help to have an example of a completed movie:

Below is an example of one of the images that made up a single frame of the above movie (the 21st frame, to be exact):

The Python script that produced the movie and its constituent frames: `[GraphMovieDemo.py]`

Requirements

To create movies from graphed data as in this tutorial, you will need the following software, all of which are open source projects available for many different hardware platforms and operating systems:
• Python
A general purpose programming language available at http://www.python.org. In this tutorial, Python is used to coordinate all the steps in creating movies of graphs.
• matplotlib
This Python package, available at http://matplotlib.sourceforge.net, replicates much of the 2D graphing functionality and feel of the popular Matlab software. matplotlib uses the numarray Python package to efficiently handle large arrays of data. In this tutorial, mplotlib is used to create graphs of data and then save the graphs as images.
• MEncoder
A movie encoder included as part of MPlayer, available at http://www.mplayerhq.hu. MPlayer and MEncoder can be used to create, edit and play almost any kind of movie format, including MPGs, AVIs, MOVs, DVDs and VCDs, to name a few. In this tutorial, MEncoder is used to stitch together images into a movie.
Each of these pieces of software is useful for much more beyond what is described in this tutorial; learning any of them in detail is worth the effort. Fortunately, they are all well-documented. At the time of this writing, MPlayer was the most difficult to install (compile from source), but the instructions included with the download tell you everything you need to know.

Instructions

Read through `GraphMovieDemo.py`. This is the Python script essentially performs three tasks. First, it creates some data to use as an example. The arrays `x` and `y` store the data. The array `x` is a 1-by-1000 array of equally spaced 64-bit floating point numbers that represent the the x-axis. The array `y` is a 100-by-1000 array. Each of the 100 rows of `y` represent a snapshot of a function at a point in time. Once these arrays have been created, the script goes on to plot each row of `y` as a function of `x`. Each of the these graphs is saved as a separate image in the directory the script is located. Finally, the script calls upon MEncoder to piece all the images in the directory together into an AVI movie called `output.avi`. More detailed comments as to what the script is doing are included in the script itself.

End Matter

Thanks to James McBride for help with MEncoder.

This tutorial was created on 2004 August 15.