📄 consist.m
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function errstring = consist(model, type, inputs, outputs)%CONSIST Check that arguments are consistent.%% Description%% ERRSTRING = CONSIST(NET, TYPE, INPUTS) takes a network data structure% NET together with a string TYPE containing the correct network type,% a matrix INPUTS of input vectors and checks that the data structure% is consistent with the other arguments. An empty string is returned% if there is no error, otherwise the string contains the relevant% error message. If the TYPE string is empty, then any type of network% is allowed.%% ERRSTRING = CONSIST(NET, TYPE) takes a network data structure NET% together with a string TYPE containing the correct network type, and% checks that the two types match.%% ERRSTRING = CONSIST(NET, TYPE, INPUTS, OUTPUTS) also checks that the% network has the correct number of outputs, and that the number of% patterns in the INPUTS and OUTPUTS is the same. The fields in NET% that are used are% type% nin% nout%% See also% MLPFWD%% Copyright (c) Ian T Nabney (1996-2001)% Assume that all is OK as defaulterrstring = '';% If type string is not emptyif ~isempty(type) % First check that model has type field if ~isfield(model, 'type') errstring = 'Data structure does not contain type field'; return end % Check that model has the correct type s = model.type; if ~strcmp(s, type) errstring = ['Model type ''', s, ''' does not match expected type ''',... type, '''']; return endend% If inputs are present, check that they have correct dimensionif nargin > 2 if ~isfield(model, 'nin') errstring = 'Data structure does not contain nin field'; return end data_nin = size(inputs, 2); if model.nin ~= data_nin errstring = ['Dimension of inputs ', num2str(data_nin), ... ' does not match number of model inputs ', num2str(model.nin)]; return endend% If outputs are present, check that they have correct dimensionif nargin > 3 if ~isfield(model, 'nout') errstring = 'Data structure does not conatin nout field'; return end data_nout = size(outputs, 2); if model.nout ~= data_nout errstring = ['Dimension of outputs ', num2str(data_nout), ... ' does not match number of model outputs ', num2str(model.nout)]; return end% Also check that number of data points in inputs and outputs is the same num_in = size(inputs, 1); num_out = size(outputs, 1); if num_in ~= num_out errstring = ['Number of input patterns ', num2str(num_in), ... ' does not match number of output patterns ', num2str(num_out)]; return endend
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