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1 function [data, c, prior, sd] = dem2ddat(ndata)
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2 %DEM2DDAT Generates two dimensional data for demos.
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3 %
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4 % Description
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5 % The data is drawn from three spherical Gaussian distributions with
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6 % priors 0.3, 0.5 and 0.2; centres (2, 3.5), (0, 0) and (0,2); and
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7 % standard deviations 0.2, 0.5 and 1.0. DATA = DEM2DDAT(NDATA)
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8 % generates NDATA points.
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9 %
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10 % [DATA, C] = DEM2DDAT(NDATA) also returns a matrix containing the
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11 % centres of the Gaussian distributions.
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12 %
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13 % See also
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14 % DEMGMM1, DEMKMEAN, DEMKNN1
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15 %
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16
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17 % Copyright (c) Ian T Nabney (1996-2001)
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18
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19 input_dim = 2;
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20
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21 % Fix seed for reproducible results
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22 randn('state', 42);
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23
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24 % Generate mixture of three Gaussians in two dimensional space
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25 data = randn(ndata, input_dim);
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26
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27 % Priors for the three clusters
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28 prior(1) = 0.3;
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29 prior(2) = 0.5;
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30 prior(3) = 0.2;
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31
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32 % Cluster centres
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33 c = [2.0, 3.5; 0.0, 0.0; 0.0, 2.0];
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34
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35 % Cluster standard deviations
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36 sd = [0.2 0.5 1.0];
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37
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38 % Put first cluster at (2, 3.5)
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39 data(1:prior(1)*ndata, 1) = data(1:prior(1)*ndata, 1) * 0.2 + c(1,1);
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40 data(1:prior(1)*ndata, 2) = data(1:prior(1)*ndata, 2) * 0.2 + c(1,2);
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41
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42 % Leave second cluster at (0,0)
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43 data((prior(1)*ndata + 1):(prior(2)+prior(1))*ndata, :) = ...
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44 data((prior(1)*ndata + 1):(prior(2)+prior(1))*ndata, :) * 0.5;
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45
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46 % Put third cluster at (0,2)
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47 data((prior(1)+prior(2))*ndata +1:ndata, 2) = ...
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48 data((prior(1)+prior(2))*ndata+1:ndata, 2) + c(3, 2);
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