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1 function [h1, h2] = mlphint(net);
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2 %MLPHINT Plot Hinton diagram for 2-layer feed-forward network.
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3 %
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4 % Description
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5 %
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6 % MLPHINT(NET) takes a network structure NET and plots the Hinton
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7 % diagram comprised of two figure windows, one displaying the first-
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8 % layer weights and biases, and one displaying the second-layer weights
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9 % and biases.
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10 %
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11 % [H1, H2] = MLPHINT(NET) also returns handles H1 and H2 to the
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12 % figures which can be used, for instance, to delete the figures when
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13 % they are no longer needed.
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14 %
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15 % To print the figure correctly, you should call SET(H,
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16 % 'INVERTHARDCOPY', 'ON') before printing.
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17 %
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18 % See also
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19 % DEMHINT, HINTMAT, MLP, MLPPAK, MLPUNPAK
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20 %
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21
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22 % Copyright (c) Ian T Nabney (1996-2001)
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23
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24 % Set scale to be up to 0.9 of maximum absolute weight value, where scale
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25 % defined so that area of box proportional to weight value.
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26
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27 % Use no more than 640x480 pixels
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28 xmax = 640; ymax = 480;
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29
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30 % Offset bottom left hand corner
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31 x01 = 40; y01 = 40;
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32 x02 = 80; y02 = 80;
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33
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34 % Need to allow 5 pixels border for window frame: but 30 at top
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35 border = 5;
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36 top_border = 30;
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37
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38 ymax = ymax - top_border;
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39 xmax = xmax - border;
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40
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41 % First layer
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42
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43 wb1 = [net.w1; net.b1];
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44 [xvals, yvals, color] = hintmat(wb1');
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45 % Try to preserve aspect ratio approximately
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46 if (8*net.nhidden < 6*(net.nin + 1))
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47 delx = xmax; dely = xmax*net.nhidden/(net.nin + 1);
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48 else
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49 delx = ymax*(net.nin + 1)/net.nhidden; dely = ymax;
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50 end
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51
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52 h1 = figure('Color', [0.5 0.5 0.5], ...
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53 'Name', 'Hinton diagram: first-layer weights and biases', ...
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54 'NumberTitle', 'off', ...
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55 'Colormap', [0 0 0; 1 1 1], ...
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56 'Units', 'pixels', ...
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57 'Position', [x01 y01 delx dely]);
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58 set(gca, 'Visible', 'off', 'Position', [0 0 1 1]);
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59 hold on
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60
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61 cmap = [0 0 0; 1 1 1];
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62 colors(1, :, :) = cmap(color, :);
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63 patch(xvals', yvals', colors, 'Edgecolor', 'none');
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64 axis equal;
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65 xpos = net.nin;
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66 line([xpos xpos], [0 net.nhidden], 'color', 'red', 'linewidth', 3);
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67
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68 % Second layer
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69
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70 wb2 = [net.w2; net.b2];
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71 [xvals, yvals, color] = hintmat(wb2');
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72 if (8*net.nout < 6*(net.nhidden + 1))
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73 delx = xmax; dely = xmax*net.nout/(net.nhidden + 1);
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74 else
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75 delx = ymax*(net.nhidden + 1)/net.nout; dely = ymax;
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76 end
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77
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78 h2 = figure('Color', [0.5 0.5 0.5], ...
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79 'Name', 'Hinton diagram: second-layer weights and biases', ...
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80 'NumberTitle', 'off', ...
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81 'Colormap', [0 0 0; 1 1 1], ...
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82 'Units', 'pixels', ...
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83 'Position', [x02 y02 delx dely]);
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84 set(gca, 'Visible', 'off', 'Position', [0 0 1 1]);
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85
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86 hold on
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87 colors2(1, :, :) = cmap(color, :);
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88 patch(xvals', yvals', colors2, 'Edgecolor', 'none');
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89 axis equal;
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90 xpos = net.nhidden;
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91 line([xpos xpos], [0 net.nout], 'color', 'red', 'linewidth', 3);
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92
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