Adding the markov machine abstraction.

svn path=/trunk/externals/aalex/; revision=5625

2 files changed, 252 insertions, 0 deletions

diff --git a/markov-machine-help.pd b/markov-machine-help.pd
new file mode 100644
index 0000000..db02b44
--- /dev/null
+++ b/markov-machine-help.pd
@@ -0,0 +1,57 @@
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+#X msg 221 149 size 4;
+#X obj 138 111 t b b b b b;
+#X msg 221 170 row 1 1 2 3 4;
+#X obj 88 331 markov-machine 4;
+#X text 60 9 States are numbered from 1 to n.;
+#X text 283 147 Already implied by argument.;
+#X msg 215 192 row 2 4 3 2 1;
+#X msg 220 215 row 3 200 300 4000 0;
+#X msg 220 238 row 4 1 1 1 1;
+#X text 337 240 Equal chances;
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+#X msg 91 66 bang;
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+#X msg -30 257 set 1;
+#X text 92 43 1 Setup;
+#X text 4 133 2 Get state;
+#X text -34 225 3 Set state;
+#X msg 276 294 content;
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+#X obj 277 -17 iemmatrix;
+#X obj 370 -17 zexy;
+#X text -26 -117 )c( Copyleft 2006 Alexandre Quessy http://alexandre.quessy.net/
+;
+#X text 71 -16 Using -lib iemmatrix \, zexy;
+#X text 374 -134 ABOUT;
+#X obj 138 87 loadbang;
+#X text 210 331 A four states weighted FSM;
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+#X text -26 -86 [markov-machine] is a weighted finite states machine
+using an adjacency matrix for storing probabilities to obtain every
+other state next \, It can be illustrated as an oriented graph. Probabilities
+are calculated on the sum of each numbers or every row.;
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diff --git a/markov-machine.pd b/markov-machine.pd
new file mode 100644
index 0000000..913bd95
--- /dev/null
+++ b/markov-machine.pd
@@ -0,0 +1,195 @@
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+#X obj 20 50 f \$1;
+#X obj 111 396 f;
+#X text 138 398 current state;
+#X obj 12 755 outlet;
+#X obj 456 325 drip;
+#X obj 495 326 sum;
+#X obj 469 403 /;
+#X obj 159 456 random 1e+06;
+#X obj 159 480 / 1e+06;
+#X text 218 482 1/1000000;
+#X msg 574 339 set;
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+#X obj 589 713 moses;
+#X obj 635 715 moses;
+#X obj 677 716 moses;
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+#X msg 245 418 row \$1;
+#X text 207 822 next state;
+#X obj 16 694 f;
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+#X text 54 288 sets state;
+#X obj 67 311 t b b;
+#X text 109 309 gets next state;
+#X text 452 515 threshold (n/1.0) for each state according to its probability
+;
+#X text 20 -5 arg: size;
+#X obj 453 364 +;
+#X msg 530 329 0;
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+#X obj 518 373 f;
+#X text 509 402 Each treshold is added to all the numbers before...
+;
+#X obj 161 250 mtx_print;
+#X obj 267 195 print debug;
+#X msg 178 733 1;
+#X msg 226 731 2;
+#X msg 266 734 3;
+#X msg 323 735 4;
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+#X msg 144 378 1;
+#X obj 160 193 route matrix;
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+#X text 667 624 MARKOV CHAIN;
+#X text 427 242 WEIGHTS FOR THIS ROW/STATE;
+#X text 260 332 STATE;
+#X text 219 90 ADJACENCY MATRIX;
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+#N canvas 0 0 485 139 todo 0;
+#N canvas 0 0 450 300 1008-dynamic 0;
+#X restore 69 65 pd \$0-dynamic;
+#X text 67 43 todo: dynamic patching for unlimited number of states
+;
+#X text 67 93 todo: use [list] and not dynamic messages (faster?);
+#X restore 775 -20 pd todo;
+#X text 437 -26 )c( Copyleft 2006 Alexandre Quessy http://alexandre.quessy.net/
+;
+#X text 500 75 Using -lib iemmatrix \, zexy;
+#X text 435 18 [markov-machine] is a weighted finite states machine
+using an adjency matrix for storing probabilities to get to each other
+state \, It can be illustrated as an oriented graph.;
+#X text 837 -43 ABOUT;
+#X msg 23 126 bang;
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