/Users/garethloy/Musimathics/Musimat1.2/MusimatChapter9/C091405.cpp File Reference

#include "MusimatChapter9.h"

Go to the source code of this file.

Functions
	MusimatChapter9Section (C091405)

---

Function Documentation

MusimatChapter9Section

(

C091405

)

Definition at line 2 of file C091405.cpp.

                                {
        Print("*** 9.14.5 Generating Outcomes from Probability Distributions ***");
        /*****************************************************************************
         
         9.14.5 Generating Outcomes from Probability Distributions
         
         Probability distributions allow us to analyze random systems like dice and coins, but we can also 
         use them to synthesize random numbers that are distributed in probability according to our choos-
         ing. We can use such systems to drive compositional processes to automatically generate music 
         according to rules that we supply.
         
         Say, for instance, we wish to use a random system to create a melody so that it favors lower 
         pitches in the scale. Let's limit the sample space to one octave of the chromatic scale. We can rep-
         resent this as a probability inequality:
         
         f (x) == P( R = C ) > P(R = C#) > P(R = D)  > . . . > P(R = B).
         
         To be specific, suppose we want to create a probability distribution function that is 12 times more 
         likely to pick C than B, 11 times more likely to pick C# than B, 10 times more likely to pick D than 
         B, and so on. The probability distribution function would look like the one in figure 9.20.
         
         We know what we want, but how do we get it? So far, the only things we have to work with are 
         a random number generator, Random() (see appendix B, B.1.27) and a probability distribution 
         function (figure 9.21).
         
         *****************************************************************************/
}