comparison toolboxes/FullBNT-1.0.7/netlab3.3/dem2ddat.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function [data, c, prior, sd] = dem2ddat(ndata)
+%DEM2DDAT Generates two dimensional data for demos.
+%
+%	Description
+%	The data is drawn from three spherical Gaussian distributions with
+%	priors 0.3, 0.5 and 0.2; centres (2, 3.5), (0, 0) and (0,2); and
+%	standard deviations 0.2, 0.5 and 1.0.  DATA = DEM2DDAT(NDATA)
+%	generates NDATA points.
+%
+%	[DATA, C] = DEM2DDAT(NDATA) also returns a matrix containing the
+%	centres of the Gaussian distributions.
+%
+%	See also
+%	DEMGMM1, DEMKMEAN, DEMKNN1
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+input_dim = 2;
+
+% Fix seed for reproducible results
+randn('state', 42);
+
+% Generate mixture of three Gaussians in two dimensional space
+data = randn(ndata, input_dim);
+
+% Priors for the three clusters
+prior(1) = 0.3;
+prior(2) = 0.5;
+prior(3) = 0.2;
+
+% Cluster centres
+c = [2.0, 3.5; 0.0, 0.0; 0.0, 2.0];
+
+% Cluster standard deviations
+sd  = [0.2 0.5 1.0];
+
+% Put first cluster at (2, 3.5)
+data(1:prior(1)*ndata, 1) = data(1:prior(1)*ndata, 1) * 0.2 + c(1,1);
+data(1:prior(1)*ndata, 2) = data(1:prior(1)*ndata, 2) * 0.2 + c(1,2);
+
+% Leave second cluster at (0,0)
+data((prior(1)*ndata + 1):(prior(2)+prior(1))*ndata, :) = ...
+	data((prior(1)*ndata + 1):(prior(2)+prior(1))*ndata, :) * 0.5;
+
+% Put third cluster at (0,2)
+data((prior(1)+prior(2))*ndata +1:ndata, 2) = ...
+	data((prior(1)+prior(2))*ndata+1:ndata, 2) + c(3, 2);