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Diffstat (limited to 'desiredata/doc/2.control.examples/20.weighted-random.pd')
-rw-r--r-- | desiredata/doc/2.control.examples/20.weighted-random.pd | 44 |
1 files changed, 0 insertions, 44 deletions
diff --git a/desiredata/doc/2.control.examples/20.weighted-random.pd b/desiredata/doc/2.control.examples/20.weighted-random.pd deleted file mode 100644 index ed964a06..00000000 --- a/desiredata/doc/2.control.examples/20.weighted-random.pd +++ /dev/null @@ -1,44 +0,0 @@ -#N canvas 161 46 660 441 12; -#X msg 103 95 bang; -#X text 389 414 updated for Pd version 0.35; -#X text 44 19 You can generate weighted random numbers from uniformly -distributed ones. If you just want two possible outcomes with a varying -probability for each one \, you can do as shown:; -#X obj 103 121 random 100; -#X obj 102 174 bng 20 250 50 0 empty empty empty 0 -6 0 8 -262144 -1 --1; -#X obj 169 174 bng 20 250 50 0 empty empty empty 0 -6 0 8 -262144 -1 --1; -#X floatatom 205 148 3 0 100; -#X text 250 148 <-- change probablilty; -#X obj 103 149 moses 80; -#X text 152 93 <-- click to test; -#X text 61 219 This outputs a number at left 80% of the time \, otherwise -at right \, unless you override the "80" using the number box. You -may extend this to more than two possible outcomes \, for instance -like this:; -#X msg 106 305 bang; -#X obj 106 331 random 100; -#X obj 105 384 bng 20 250 50 0 empty empty empty 0 -6 0 8 -262144 -1 --1; -#X obj 195 387 bng 20 250 50 0 empty empty empty 0 -6 0 8 -262144 -1 --1; -#X text 155 303 <-- click to test; -#X obj 106 359 moses 10; -#X obj 196 360 moses 30; -#X obj 263 387 bng 20 250 50 0 empty empty empty 0 -6 0 8 -262144 -1 --1; -#X text 103 409 10%; -#X text 193 410 20%; -#X text 265 409 70%; -#X connect 0 0 3 0; -#X connect 3 0 8 0; -#X connect 6 0 8 1; -#X connect 8 0 4 0; -#X connect 8 1 5 0; -#X connect 11 0 12 0; -#X connect 12 0 16 0; -#X connect 16 0 13 0; -#X connect 16 1 17 0; -#X connect 17 0 14 0; -#X connect 17 1 18 0; |