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#X text 12 125 LIBRARY internal;
#X text 12 165 WEBSITE http://crca.ucsd.edu/~msp/;
#X text 12 25 LICENSE SIBSD;
#X text 12 145 AUTHOR Miller Puckette;
#X text 12 205 HELP_PATCH_AUTHORS This help patch was updated for Pd
version 0.35 test 29 by Dave Sabine as part of a project called pddp
proposed by Krzysztof Czaja to build comprehensive documentation for
Pd. Jonathan Wilkes revised the patch to conform to the PDDP template
for Pd version 0.42.;
#X text 12 45 DESCRIPTION pseudorandom integer generator;
#X text 12 5 KEYWORDS control random;
#X text 12 85 INLET_1 float;
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#X text 12 65 INLET_0 bang seed;
#X text 12 185 RELEASE_DATE 1997;
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#X text 20 255 These objects are offered in Pd only if you have downloaded
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may not exist in a single library.;
#X text 20 297 The best places to find information about Pd's libraries
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#X text 21 314 www.puredata.org and click on "Downloads" then "Software"
;
#X text 23 328 or;
#X text 20 343 iem.kug.ac.at/pdb/;
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#X text 98 408 <- triggers a dirty flag;
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#X obj 481 3 random;
#X obj 455 20 pddp/pddplink http://wiki.puredata.info/en/random -text
pdpedia: random;
#X text 81 56 [random] outputs pseudorandom integers between 0 and
N-1 where N is the creation argument or the value of the right inlet.
;
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#X text 154 122 Generates random numbers between 0 and 99;
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#X text 181 162 Changes the 'range' of random numbers.;
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#X text 168 299 - to specify the seed \, use the seed message followed
by a float ( "seed 42" ).;
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#X text 21 158 However \, "seeds" can be inputted into [random] by
sending a message \, like below:;
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#X text 21 294 Seeds are kept locally so that if two [random]s are
seeded the same \, they will have the same output - as demonstrated
below. Furthermore \, you can seed the same one twice to repeat the
output.;
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#X text 233 363 Click again to repeat output.;
#X text 20 38 Random numbers are generated via a complex equation which
produces a pseudo-predictable sequence of numbers. Each [random] object's
equation is provided with a "seed" which is really just one of the
variables in the equation which produces the sequence. The "seed" is
generated by Pd based on specific parameters in each patch which contains
a [random] object. If more than one [random] object is contained within
a single patch \, each gets a different "seed".;
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#X text 20 39 While the "default" seed for each [random] is usually
very effective \, it may be necessary to find better - more unpredictable
- more indeterminate ways to seed the object to produce a more pleasing
result.;
#X text 20 96 Here are some ideas that may improve the implementation
of [random]:;
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#X text 64 137 Both methods here produce random numbers between 0 and
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#X text 41 226 Produces whole numbers;
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#X text 20 283 2;
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#X text 240 226 between 0 and 5;
#X text 240 212 produces fractional results;
#X text 240 195 within range.;
#X text 240 182 divide by 100 to keep output;
#X text 206 298 "Time is on your side". Using the;
#X text 206 314 [timer] object here (which is;
#X text 206 343 interesting trick.;
#X text 207 329 started via loadbang) is an;
#X text 8 2 [random] More Info on Seeds;
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#N canvas 107 145 428 418 weighted_random_numbers 0;
#X msg 23 118 bang;
#X text 20 58 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 23 144 random 100;
#X obj 23 202 bng 15 250 50 0 empty empty empty 0 -6 0 8 -262144 -1
-1;
#X obj 89 202 bng 15 250 50 0 empty empty empty 0 -6 0 8 -262144 -1
-1;
#X floatatom 125 151 3 0 100 0 - - -;
#X obj 23 177 moses 80;
#X text 20 230 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 24 293 bang;
#X obj 24 319 random 100;
#X obj 24 372 bng 15 250 50 0 empty empty empty 0 -6 0 8 -262144 -1
-1;
#X obj 114 373 bng 15 250 50 0 empty empty empty 0 -6 0 8 -262144 -1
-1;
#X obj 24 347 moses 10;
#X obj 114 348 moses 30;
#X obj 182 373 bng 15 250 50 0 empty empty empty 0 -6 0 8 -262144 -1
-1;
#X text 22 388 10%;
#X text 112 389 20%;
#X text 184 388 70%;
#X obj 1 1 cnv 15 425 20 empty \$0-pddp.cnv.subheading empty 3 12 0
14 -204280 -1 0;
#X text 8 2 [random] Weighted Random Numbers;
#X text 62 117 <- click to test;
#X text 156 150 <- change probablilty;
#X text 64 293 <- click to test;
#X text 20 25 There are many ways that [random] can be incorporated
into other structures that change the qualities of the results.;
#X connect 0 0 2 0;
#X connect 2 0 6 0;
#X connect 5 0 6 1;
#X connect 6 0 3 0;
#X connect 6 1 4 0;
#X connect 8 0 9 0;
#X connect 9 0 12 0;
#X connect 12 0 10 0;
#X connect 12 1 13 0;
#X connect 13 0 11 0;
#X connect 13 1 14 0;
#X restore 102 507 pd weighted_random_numbers;
#X text 11 23 pseudorandom integer generator;
#X text 168 397 - the output is an integer between 0 and N-1.;
#X text 168 442 - sets the initial value of N \, where the output ranges
between 0 and N-1.;
#X text 168 260 - a bang to [random] will output an integer between
0 and N-1 \, where N is the creation argument or the value to the right
inlet.;
#X text 167 355 - a float to the right inlet sets N \, where the output
ranges between 0 and N-1.;
#X text 78 442 1) float;
#X obj 4 597 pddp/pddplink all_about_help_patches.pd -text Usage Guide;
#X obj 102 527 pddp/pddplink ../2.control.examples/19.random.pd -text
doc/2.control.examples/19.random.pd;
#X obj 102 542 pddp/pddplink ../2.control.examples/20.weighted-random.pd
-text doc/2.control.examples/20.weighted-random.pd;
#X obj 102 557 pddp/pddplink ../2.control.examples/21.markov.chain.pd
-text doc/2.control.examples/21.markov.chain.pd;
#X obj 102 572 pddp/pddplink ../2.control.examples/22.random-walk.pd
-text doc/2.control.examples/22.random-walk.pd;
#X connect 16 0 18 0;
#X connect 17 0 16 0;
#X connect 20 0 22 0;
#X connect 21 0 20 0;
#X connect 23 0 20 1;