Problem - Kevin Tafuro

You might worry about a situation where performance suffers because this code has
to retry too many times. The worst case for this solution is when the size of the range
is UINT_MAX / 2 + 1. Even in such a case, you would not expect to call spc_rand_
uint( ) very many times. The average number of times it would be called here would
be slightly less than two. While the worst-case performance is theoretically
unbounded, the chances of calling spc_rand_uint( ) more than a dozen times are
essentially zero. Therefore, this technique will not have a significant performance
impact for most applications.
If you are okay with some items being slightly more likely than others, there are two
different things you can do, both of which are fairly easy. First, you can perform a
modulo operation and an addition to get the integer in the right range, and just not
worry about the fact that some values are more likely than others:
#include
int spc_rand_range(int min, int max) {
if (max < min) abort( );
return min + (spc_rand_uint( ) % (max - min + 1));
}
Of course, this solution clumps together all the values that are more likely to be chosen,
which is somewhat undesirable. As an alternative, you can spread them out by
using division and rounding down, instead of a simple modulus:
#include
int spc_rand_range(int min, int max) {
if (max < min) abort( );
return min + (int)((double)spc_rand_uint( ) *
(max - min + 1) / (double)UINT_MAX) % (max - min);
}
Note the modulo operation in this solution. That is to prevent getting a value that is
out of range in the very rare occasion that spc_rand_uint( ) returns UINT_MAX.
See Also
Recipe 11.10
11.12 Getting a Random Floating-Point Value
with Uniform Distribution
Problem
When looking for a random floating-point number, we usually want a value between
0 and 1 that is just as likely to be between 0 and 0.1 as it is to be between 0.9 and 1.
608 | Chapter 11: Random Numbers
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