1## Copyright (C) 2006 Michel D. Schmid    <email: michaelschmid@users.sourceforge.net>
2##
3##
4## This program is free software; you can redistribute it and/or modify it
5## under the terms of the GNU General Public License as published by
6## the Free Software Foundation; either version 2, or (at your option)
7## any later version.
8##
9## This program is distributed in the hope that it will be useful, but
10## WITHOUT ANY WARRANTY; without even the implied warranty of
11## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
12## General Public License for more details.
13##
14## You should have received a copy of the GNU General Public License
15## along with this program; see the file COPYING.  If not, see
16## <http://www.gnu.org/licenses/>.
17
18## -*- texinfo -*-
19## @deftypefn {Function File} {}[@var{perf}, @var{Ee}, @var{Aa}, @var{Nn}] = __calcperf (@var{net},@var{xx},@var{Im},@var{Tt})
20## @code{__calcperf} calculates the performance of a multi-layer neural network.
21## PLEASE DON'T USE IT ELSEWHERE, it proparly won't work.
22## @end deftypefn
23
24## Author: Michel D. Schmid
25
26
27function [perf,Ee,Aa,Nn] = __calcperf(net,xx,Im,Tt)
28
29  ## comment:
30  ## perf, net performance.. from input to output through the hidden layers
31  ## Aa, output values of the hidden and last layer (output layer)
32  ## is used for NEWFF network types
33
34  ## calculate bias terms
35  ## must have the same number of columns like the input matrix Im
36  [nRows, nColumns] = size(Im);
37  Btemp = cell(net.numLayers,1); # Btemp: bias matrix
38  ones1xQ = ones(1,nColumns);
39  for i= 1:net.numLayers
40    Btemp{i} = net.b{i}(:,ones1xQ);
41  endfor
42
43  ## shortcuts
44  IWtemp = cell(net.numLayers,net.numInputs,1);# IW: input weights ...
45  LWtemp = cell(net.numLayers,net.numLayers,1);# LW: layer weights ...
46  Aa = cell(net.numLayers,1);# Outputs hidden and output layer
47  Nn = cell(net.numLayers,1);# outputs before the transfer function
48  IW = net.IW; # input weights
49  LW = net.LW; # layer weights
50
51  ## calculate the whole network till outputs are reached...
52  for iLayers = 1:net.numLayers
53
54    ## calculate first input weights to weighted inputs..
55    ## this can be done with matrix calculation...
56    ## called "dotprod"
57    ## to do this, there must be a special matrix ...
58    ## e.g.  IW = [1 2 3 4 5; 6 7 8 9 10] * [ 1 2 3; 4 5 6; 7 8 9; 10 11 12; 1 2 3];
59    if (iLayers==1)
60      IWtemp{iLayers,1} = IW{iLayers,1} * Im;
61      onlyTempVar = [IWtemp(iLayers,1) Btemp(iLayers)];
62    else
63      IWtemp{iLayers,1} = [];
64    endif
65
66    ## now calculate layer weights to weighted layer outputs
67    if (iLayers>1)
68      Ad = Aa{iLayers-1,1};
69      LWtemp{iLayers,1} = LW{iLayers,iLayers-1} * Ad;
70      onlyTempVar = [LWtemp(iLayers,1) Btemp(iLayers)];
71    else
72      LWtemp{iLayers,1} = [];
73    endif
74
75    Nn{iLayers,1} = onlyTempVar{1};
76    for k=2:length(onlyTempVar)
77      Nn{iLayers,1} = Nn{iLayers,1} + onlyTempVar{k};
78    endfor
79
80    ## now calculate with the transfer functions the layer output
81    switch net.layers{iLayers}.transferFcn
82    case "purelin"
83      Aa{iLayers,1} = purelin(Nn{iLayers,1});
84    case "tansig"
85      Aa{iLayers,1} = tansig(Nn{iLayers,1});
86    case "logsig"
87      Aa{iLayers,1} = logsig(Nn{iLayers,1});
88    otherwise
89      error(["Transfer function: " net.layers{iLayers}.transferFcn " doesn't exist!"])
90    endswitch
91
92  endfor  # iLayers = 1:net.numLayers
93
94  ## now calc network error
95  Ee = cell(net.numLayers,1);
96
97  for i=net.numLayers
98    Ee{i,1} = Tt{i,1} - Aa{i,1};# Tt: target
99    # Ee will be the error vector cell array
100  endfor
101
102  ## now calc network performance
103  switch(net.performFcn)
104  case "mse"
105    perf = __mse(Ee);
106  otherwise
107    error("for performance functions, only mse is currently valid!")
108  endswitch
109
110endfunction
111