You want to pick a random value where the probabilities of the values are not equal (the distribution is not even). You might be trying to randomly select a banner to display on a web page, given a set of relative weights saying how often each banner is to be displayed. Alternatively, you might want to simulate behavior according to a normal distribution (the bell curve).

If you want a random value distributed according to a specific function—e.g., the Gaussian (Normal) distribution—consult a statistics textbook to find the appropriate function or algorithm. This subroutine generates random numbers that are normally distributed, with a standard deviation of 1 and a mean of 0.

sub gaussian_rand { my ($u1, $u2); # uniformly distributed random numbers my $w; # variance, then a weight my ($g1, $g2); # gaussian-distributed numbers do { $u1 = 2 * rand() - 1; $u2 = 2 * rand() - 1; $w = $u1*$u1 + $u2*$u2; while ($w >= 1 || $w == 0) $w = sqrt( (-2 * log($w)) / $w ); $g2 = $u1 * $w; $g1 = $u2 * $w; # return both if wanted, else just one return wantarray ? ($g1, $g2) : $g1; }

If you have a list of weights and values you want to randomly pick
from, follow this two-step process: First, turn the weights into a
probability distribution with `weight_to_dist`

below, and then use the distribution to randomly pick a value with
`weighted_rand`

:

# weight_to_dist: takes a hash mapping key to weight and returns # a hash mapping key to probability sub weight_to_dist ...

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