fuz_aux.m

The neuro-fuzzy software for identification and data analysis has been implemented in the MATLAB lan

function fuz_aux(pr,arg2,arg3,arg4,arg5,arg6)

global model
global memb_fun
global model_bias
global arch
global format_out
global init
global no_sets
global fid_h
global file_e

global mod_id
global mod_path
global mhist_id
global mhist_path
global err_id
global err_path
global ehist_id
global ehist_path
global pred_id
global pred_path
global memo_id
global memo_path

if nargin==3
	comp=arg2;
	data=arg3;
elseif nargin==4
	comp_min=arg2;
	comp_max=arg3;
	data=arg4;
elseif nargin==6
	centers=arg2;
	bases=arg3;
	par=arg4;
	bias=arg5;
	inputs=arg6;
end


model='fuz';

fprintf('FIS is working...\n');

if strcmp(pr,'comp_err')
	fid_h=fopen([ehist_path,ehist_id],'w');
	file_e=[err_path, err_id];

	valid='x_valid';

	[errors]=eval([valid '(data,comp_min,comp_max)']);

	fclose(fid_h);

	err_mean=mean(errors);
	err_std=std(errors);

	figure,
	errorbar(comp_min:comp_max,err_mean,err_std);

	fid_memo=fopen([memo_path,memo_id],'w');
	fprintf(fid_memo,'FUZZY INFERENCE SYSTEM memo:\n');	
	fprintf(fid_memo,'Number of rules vs Mean Square Error\n');		      
	fprintf(fid_memo,'\nNumber of cross validation sets:__________________%g',no_sets);			
	fprintf(fid_memo,'\nShape of the membership functions:________________');	
		fprintf(fid_memo,memb_fun);	
	fprintf(fid_memo,'\nOutput of each local model:_______________________');		
		fprintf(fid_memo,format_out);	
	fprintf(fid_memo,'\nArchitecture of the fuzzy model:__________________');	
		fprintf(fid_memo,arch);
	fprintf(fid_memo,'\nInitialization:___________________________________');	
		fprintf(fid_memo,init);		
	fprintf(fid_memo,'\nBias vs No-Bias:__________________________________');	
		fprintf(fid_memo,model_bias);
	fprintf(fid_memo,'\nMinimun Number of Rules:__________________________%g',comp_min);	
	fprintf(fid_memo,'\nMaximum Number of Rules:__________________________%g',comp_max);,		
	fprintf(fid_memo,'\nThe matrix errors vs complexity has been saved in the file:\n\t');	
		fwrite(fid_memo,[err_path,err_id],'char');						
	fprintf(fid_memo,'\nThe diary of the computation has been saved in the file:\n\t');	
		fwrite(fid_memo,[ehist_path,ehist_id],'char');
	fclose(fid_memo);

 
elseif strcmp(pr,'one_mod')
	fid_h=fopen([mhist_path,mhist_id],'w');

	[centers,bases,par,bias]=fuz_id(comp,data);

	fclose(fid_h);

	eval(['save ',mod_path,mod_id,' centers bases par bias ',...
		'memb_fun model_bias arch format_out']);

	fid_memo=fopen([memo_path,memo_id],'w');
	fprintf(fid_memo,'FUZZY INFERENCE SYSTEM memo:\n');				      		
	fprintf(fid_memo,'\nShape of the membership functions:________________');	
		fprintf(fid_memo,memb_fun);	
	fprintf(fid_memo,'\nOutput of each local model:_______________________');		
		fprintf(fid_memo,format_out);	
	fprintf(fid_memo,'\nArchitecture of the fuzzy model:__________________');	
		fprintf(fid_memo,arch);
	fprintf(fid_memo,'\nInitialization:___________________________________');	
		fprintf(fid_memo,init);,		
	fprintf(fid_memo,'\nBias vs No-Bias:__________________________________');	
		fprintf(fid_memo,model_bias);
	fprintf(fid_memo,'\nNumber of Rules:__________________________________%g',comp);		
	fprintf(fid_memo,'\nThe trained model has been saved in the file:\n\t');	
		fwrite(fid_memo,[mod_path,mod_id],'char');							
	fprintf(fid_memo,'\nThe diary of the computation has been saved in the file:\n\t');	
		fwrite(fid_memo,[mhist_path,mhist_id],'char');	
	fclose(fid_memo);

elseif strcmp(pr,'evaluate')
	out_hat=fuz_mod(inputs,centers,bases,par,bias);

	eval(['save ',pred_path,pred_id,' out_hat']);

	fid_memo=fopen([memo_path,memo_id],'w');
	fprintf(fid_memo,'FUZZY INFERENCE SYSTEM memo:\n');		      		
	fprintf(fid_memo,'\nShape of the membership functions:________________');	
		fprintf(fid_memo,memb_fun);	
	fprintf(fid_memo,'\nOutput of each local model:_______________________');		
		fprintf(fid_memo,format_out);	
	fprintf(fid_memo,'\nArchitecture of the fuzzy model:__________________');	
		fprintf(fid_memo,arch);
	fprintf(fid_memo,'\nBias vs No-Bias:__________________________________');	
		fprintf(fid_memo,model_bias);
	fprintf(fid_memo,'\nNumber of Rules:__________________________________%g',size(centers,1));
	fprintf(fid_memo,'\nThe predicted output has been saved in the file:\n\t');	
		fwrite(fid_memo,[pred_path,pred_id],'char');							

end

fprintf('Done.\n\n');

eval(['type ', memo_path, memo_id]);
fprintf('\n');
return
%________________________________________________________