After mulling on this one for a while, in particular thinking about how to track when a letter was due to get output again and how to maintain a distribution, I think I have something good. Compute a rolling score for each element, where it accumulates based upon probability of output and gets dinged when its element gets selected; maximum score always gets chosen.

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outputsuse strict; use warnings; use List::Util 'sum'; use Data::Dump qw[ pp ]; sub gen { my $href = shift; my %score = %$href; my $norm = sum values %score; my @series; for (1 .. $norm) { my ($max, $elem) = 0; for (keys %score) { ($max, $elem) = ($score{$_}, $_) if $score{$_} >= $max; $score{$_} += $href->{$_}; } push @series, $elem; $score{$elem} -= $norm; } return \@series; } pp gen( { A => 4, B => 2, C => 3, D => 1 } ); pp gen( { A => 5, B => 4, C => 3, D => 2, E => 1 } );

["A", "C", "B", "A", "D", "C", "A", "B", "C", "A"] ["A" .. "D", "A", "B", "E", "A", "C", "B", "A", "D", "C", "B", "A"]

It also naturally extends to infinite series and non-integer element counts. The infinite series case is why it's necessary to have a `>=` in the score comparison; you could alternatively initialize `$max` to something negative since the sum of all scores is necessarily zero at all times. N*M complexity, where N is the length of desired series and M is number of distinct elements.

This approach also lends itself to designing a metric for how smooth a series is:

outputsuse strict; use warnings; use List::Util 'sum'; sub measure { my @series = @_; my %count; $count{$_}++ for @series; my $norm = sum values %count; $_ /= $norm for values %count; my %score = %count; my $metric = 0; for my $elem (@series) { $score{$elem} -= 1; for (keys %score) { $metric += $score{$_}**2; $score{$_} += $count{$_}; } } return $metric/@series; } print measure("A", "C", "B", "A", "D", "C", "A", "B", "C", "A"), "\n"; print measure("A", "C", "B", "A", "C", "D", "A", "B", "C", "A"), "\n"; print measure("A", "A", "A", "A", "B", "B", "C", "C", "C", "D"), "\n";

0.37 0.37 3.45

#11929 First ask yourself `How would I do this without a computer?' Then have the computer do it the same way.

*In reply to* **Re: Bag uniform distribution algorithms**
*by* **kennethk**
*in thread* **Bag uniform distribution algorithms**
*by* **davido**

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