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#N canvas 711 130 586 632 10;
#X text 198 23 ::::_gen_trainfile_::::;
#X text 46 68 This abstraction generates a trainig file for ann_mlp
and ann_td;
#X obj 351 443 gen_trainfile;
#X msg 437 154 test.txt;
#X text 313 153 1) set filename:;
#X msg 394 215 4 2 1;
#X text 249 217 2) set file header:;
#X text 183 241 4 = nr. of training datasets;
#X text 184 255 2 = inputs of the neural net;
#X text 184 269 1 = output of the neural net;
#X msg 150 393 0 0 0;
#X msg 197 393 0 1 1;
#X msg 247 393 1 0 1;
#X msg 293 393 1 1 0;
#X text 46 116 Example:;
#X text 36 311 3) send training data (first inputs \, then output)
;
#X text 58 327 because you have now 4 training datasets you;
#X text 57 342 must pass 4 lists !!!;
#X text 162 374 a;
#X text 209 374 b;
#X text 259 375 c;
#X text 302 374 d;
#X floatatom 351 469 5 0 0 0 - - -;
#X obj 437 501 bng 15 250 50 0 empty empty empty 0 -6 0 8 -262144 -1
-1;
#X text 332 502 file is ready:;
#X text 238 468 added datasets:;
#X text 150 573 (c) 2005 \, Georg Holzmann <grh@mur.at>;
#X connect 2 0 22 0;
#X connect 2 1 23 0;
#X connect 3 0 2 2;
#X connect 5 0 2 1;
#X connect 10 0 2 0;
#X connect 11 0 2 0;
#X connect 12 0 2 0;
#X connect 13 0 2 0;
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