Matlab implementation of Elastic Principal Graphs (ElPiGraph) method.
To overview the features of the method, make ElPiGraph working directory, and execute
setallpaths;
basicCodeTest;
Basic self-contained formal description of ElPiGraph can be found here.
Principal graphs are graphs that are embedded into a high-dimensional space and minimize the distance to the data points, while maximizing some regular properties.
Elastic principal graphs are based on minimization of the energy potential containing three parts :
where MSE is the mean squared error of data approximation, - is the sum of squared edge lengths, is a term minimizing the deviation of the principal graph embedment from harmonicity (generalization of linearity), , are coefficients of regularization.
The structure of the graph is computed by an optimal application of a sequence of graph transformations, using operations from predefined graph grammar. The simplest graph grammar "Bisect an edge", "Add a node to a node" leads to construction of a principal tree.
Read wiki of this repository for more detailed information on the algorithm and examples of its application.
Go to R implementation of elastic principal graphs coded by Luca Albergante.
For more details of elastic principal graph theory read:
ElPiGraph/core_algorithm - contains the core MATLAB code of the algorithm (self-contained)
ElPiGraph/core_algorithm_java - old MATLAB wrapper of the Java code for ElPiGraph
ElPiGraph/docs - some documentation on the method and the code
ElPiGraph/examples - some example applications of the method
ElPiGraph/simulations - code generating synthetic datasets (e.g., with known branching topology)
ElPiGraph/test_code - testing critical parts of the code (not needed for the package use)
ElPiGraph/test_data - example datasets
ElPiGraph/utils - utility functions for manipulating data and the graph (e.g., projection function)
ElPiGraph/visualization - utility functions used for visualizing the results of the method application (such as applying metro map layout of the principal tree)
MasterApplet - Java applet implementing several methods for constructing complex data approximators including elastic principal trees. The applet can be run as a standalone jar file.
computeElasticPrincipalCircle.m - computes closed elastic principal curve with a given number of nodes
computeElasticPrincipalCurve.m - computes elastic principal curve with a given number of nodes
computeElasticPrincipalGraph.m - computes elastic principal graph for a dataset with a given number of nodes and defined set of grammars (principal tree grammar by default)
computeRobustElasticPrincipalGraph.m - computes robust version of elastic principal graph for a dataset with a given number of nodes and defined set of grammars (principal tree grammar by default)
setallpaths.m - set all paths to other folders (needed if some functions are called directly, bypassing the root folder "computeElasticPrincipalXXX.m" functions)