JavaPlex Tutorial
In this tutorial we will learn how to use the JavaPlex[1] package in Matlab. For a more complete picture of JavaPlex please visit the projects homepage and consider also reading the tutorial provided there.
Installation
Make sure you have a working version of Matlab.
Furthermore, JavaPlex requires Java version number 1.5 or higher.
You can check your Java version in Matlab by entering version -java
To install JavaPlex for Matlab download the latest release at [1]. Download the zip file containing the Matlab examples, which should be called something like matlab-examples-4.2.2.zip
.
Unzip the folder to a known location, the resulting folder should be called matlab_examples
.
In Matlab, change your current folder to matlab_examples
. Then run the script load_javaplex.m
and import the JavaPlex routines provided by the package.
You can do this for example by entering the following commands into the command line
load_javaplex.m; import edu.stanford.math.plex4.*;
You will need to reload the package every time you open a new Matlab session.
To check wether JavaPlex was loaded correctly, enter
api.Plex4.createExplicitSimplexStream()
which will return something like
ans = edu.stanford.math.plex4.streams.impl.ExplicitSimplexStream@513fd4
Basic constructions
Simplex Streams
JavaPlex implements abstract simplicial complexes via simplex streams, which are provided by the function api.Plex4.createExplicitSimplexStream()
.
Furthermore, for a given simplicial complex [math] X[/math], the algorithm api.Plex4.getModularSimplicialAlgorithm(dimension, p)
calculates the (persistence module of) homology groups [math] H_i(X,\mathbb{Z}/p\mathbb{Z}), i\leq \text{dimension}[/math] and representatives of the classes [math] [x]\in H_i [/math].
In the following we will use these functions to create a simplicial complex that corresponds to spheres [math] S^1[/math] and [math] S^n[/math] and find the homology groups [math] H_i(X,\mathbb{Z}/2\mathbb{Z})[/math].
Implementing the one-sphere
In order to build a simplicial complex by hand, we first load the relevant function onto our target object
complex = api.Plex4.createExplicitSimplexStream();
and pass the vertices of the complex to it:
complex.addVertex(0); complex.addVertex(1); complex.addVertex(2);
In general a complex will have higher simplicies, which by definition are sets of vertices. These are added to the simplicial complex by similarly passing sets to the stream.
complex.addElement([0, 1]); complex.addElement([0, 2]); complex.addElement([1, 2]);
Once all simplices have been put into the stream, we close it by calling
complex.finalizeStream();
At this point complex
is a simplicial complex that encodes the boundary of a triangle.
We can get the number of simplices (of all dimension) contained in the simplicial complex by calling
complex.getSize()
The homology groups over [math] \mathbb{Z}/2\mathbb{Z}[/math] of complex
up to dimension 3 can be extracted via
homology = api.Plex4.getModularSimplicialAlgorithm(3, 2); persistenceIntervals = homology.computeIntervals(complex)
Note: The Modular Simplicial Algorithm automatically interprets our complex as a filtered complex
If we are also interested in representatives of the non-trivial classes we can use
persistenceAnnotatedIntervals = homology.computeAnnotatedIntervals(complex)
and get the parameter values of non-trivial classes together with their representatives.
Implementing the [math] n [/math]-Sphere
The explicit construction above is of course too tiresome for more complicated simplicial complexes. We exemplify additional methods of simplex stream objects to generate [math] n[/math]-spheres.
% set dimension and load simplex stream dimension = 9; sphere = api.Plex4.createExplicitSimplexStream(); % construct simplicial sphere stream.addElement(0:(dimension + 1)); stream.ensureAllFaces(); stream.removeElementIfPresent(0:(dimension + 1)); stream.finalizeStream(); % print out the total number of simplices in the complex stream.getSize() % get homology algorithm over Z/2Z up to dimension+1 persistence = api.Plex4.getModularSimplicialAlgorithm(dimension + 1, 2); % compute and print the homology groups intervals = persistence.computeIntervals(stream)
Filtered Chain Complexes
Generating Barcodes
Customization
Examples
We can now use what we've learned above to investigate more complicated data sets.