New GMR example added

demoGMR01.m

+function demoGMR01
+% Gaussian mixture model (GMM) and Gaussian mixture regression (GMR)
+%
+% Author:	Sylvain Calinon, 2014
+%         http://programming-by-demonstration.org/lib/
+%
+% This source code is given for free! In exchange, please cite the following 
+% reference in any academic publication that uses this code or part of it:
+%
+% @article{Calinon07SMC,
+%   author="Calinon, S. and Guenter, F. and Billard, A. G.",
+%   title="On Learning, Representing and Generalizing a Task in a Humanoid Robot",
+%   journal="{IEEE} Trans. on Systems, Man and Cybernetics, Part {B}",
+%   year="2007",
+%   volume="37",
+%   number="2",
+%   pages="286--298",
+% }
+
+addpath('./m_fcts/');
+
+%% Parameters
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+model.nbVar = 3; %Number of variables 
+model.nbStates = 5; %Number of states 
+nbData = 250; %Length of each trajectory
+
+%% Load AMARSI data 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+demos=[];
+load('data/AMARSI/GShape.mat');
+nbSamples = length(demos);
+Data=[];
+for n=1:nbSamples
+  Data = [Data [1:nbData; demos{n}.pos(:,1:4:end)]]; %-> 250 datapoints for each demo
+end
+
+%% Learning and reproduction
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+model = init_GMM_timeBased(Data, model);
+model = EM_GMM(Data, model);
+DataOut = GMR(model, 1:nbData, 1, [2,3]);
+
+%% Plots
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+figure('position',[20,100,500,600]); hold on; box on;
+plotGMM(model.Mu(2:model.nbVar,:), model.Sigma(2:model.nbVar,2:model.nbVar,:), [0 .8 0]);
+plot(Data(2,:),Data(3,:),'.','markersize',8,'color',[.75 .75 .75]);
+plot(DataOut(1,:),DataOut(2,:),'-','linewidth',2,'color',[.2 .2 .2]);
+axis equal; set(gca,'Xtick',[]); set(gca,'Ytick',[]);
+
+%pause;
+%close all;
+