--- /dev/null
+## Copyright (C) 2006 Michel D. Schmid <email: michaelschmid@users.sourceforge.net>
+##
+##
+## This program is free software; you can redistribute it and/or modify it
+## under the terms of the GNU General Public License as published by
+## the Free Software Foundation; either version 2, or (at your option)
+## any later version.
+##
+## This program is distributed in the hope that it will be useful, but
+## WITHOUT ANY WARRANTY; without even the implied warranty of
+## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with this program; see the file COPYING. If not, see
+## <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {}[@var{perf}, @var{Ee}, @var{Aa}, @var{Nn}] = __calcperf (@var{net},@var{xx},@var{Im},@var{Tt})
+## @code{__calcperf} calculates the performance of a multi-layer neural network.
+## PLEASE DON'T USE IT ELSEWHERE, it proparly won't work.
+## @end deftypefn
+
+## Author: Michel D. Schmid
+
+
+function [perf,Ee,Aa,Nn] = __calcperf(net,xx,Im,Tt)
+
+ ## comment:
+ ## perf, net performance.. from input to output through the hidden layers
+ ## Aa, output values of the hidden and last layer (output layer)
+ ## is used for NEWFF network types
+
+ ## calculate bias terms
+ ## must have the same number of columns like the input matrix Im
+ [nRows, nColumns] = size(Im);
+ Btemp = cell(net.numLayers,1); # Btemp: bias matrix
+ ones1xQ = ones(1,nColumns);
+ for i= 1:net.numLayers
+ Btemp{i} = net.b{i}(:,ones1xQ);
+ endfor
+
+ ## shortcuts
+ IWtemp = cell(net.numLayers,net.numInputs,1);# IW: input weights ...
+ LWtemp = cell(net.numLayers,net.numLayers,1);# LW: layer weights ...
+ Aa = cell(net.numLayers,1);# Outputs hidden and output layer
+ Nn = cell(net.numLayers,1);# outputs before the transfer function
+ IW = net.IW; # input weights
+ LW = net.LW; # layer weights
+
+ ## calculate the whole network till outputs are reached...
+ for iLayers = 1:net.numLayers
+
+ ## calculate first input weights to weighted inputs..
+ ## this can be done with matrix calculation...
+ ## called "dotprod"
+ ## to do this, there must be a special matrix ...
+ ## 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];
+ if (iLayers==1)
+ IWtemp{iLayers,1} = IW{iLayers,1} * Im;
+ onlyTempVar = [IWtemp(iLayers,1) Btemp(iLayers)];
+ else
+ IWtemp{iLayers,1} = [];
+ endif
+
+ ## now calculate layer weights to weighted layer outputs
+ if (iLayers>1)
+ Ad = Aa{iLayers-1,1};
+ LWtemp{iLayers,1} = LW{iLayers,iLayers-1} * Ad;
+ onlyTempVar = [LWtemp(iLayers,1) Btemp(iLayers)];
+ else
+ LWtemp{iLayers,1} = [];
+ endif
+
+ Nn{iLayers,1} = onlyTempVar{1};
+ for k=2:length(onlyTempVar)
+ Nn{iLayers,1} = Nn{iLayers,1} + onlyTempVar{k};
+ endfor
+
+ ## now calculate with the transfer functions the layer output
+ switch net.layers{iLayers}.transferFcn
+ case "purelin"
+ Aa{iLayers,1} = purelin(Nn{iLayers,1});
+ case "tansig"
+ Aa{iLayers,1} = tansig(Nn{iLayers,1});
+ case "logsig"
+ Aa{iLayers,1} = logsig(Nn{iLayers,1});
+ otherwise
+ error(["Transfer function: " net.layers{iLayers}.transferFcn " doesn't exist!"])
+ endswitch
+
+ endfor # iLayers = 1:net.numLayers
+
+ ## now calc network error
+ Ee = cell(net.numLayers,1);
+
+ for i=net.numLayers
+ Ee{i,1} = Tt{i,1} - Aa{i,1};# Tt: target
+ # Ee will be the error vector cell array
+ endfor
+
+ ## now calc network performance
+ switch(net.performFcn)
+ case "mse"
+ perf = __mse(Ee);
+ otherwise
+ error("for performance functions, only mse is currently valid!")
+ endswitch
+
+endfunction