I was sent the following answer to the puzzle with the following challenge:
- Why does this work
- How efficient is is. i.e., how fast it
calculates group_cats(50, 1..150) -- with the caveat that it might not be that efficient in memory.
If you think you know who sent this, please do not speculate! I will neither confirm nor deny ...
use strict;
use Carp;
use Data::Dumper;
$Data::Dumper::Indent = 1;
print Dumper [group_cats(3, 1..7)];
{
my @sizes;
my %ans;
sub group_cats {
(my $num, @sizes) = @_;
%ans = ();
my ($size, @partition) = _group_cats($num, 0, $#sizes);
return @partition;
}
sub _group_cats {
my $key = join ":", @_;
my ($num, $start, $end) = @_;
if (not exists $ans{$key}) {
if ($num < 1) {
$ans{$key} = [0];
}
elsif (1 == $num) {
my @part = map $sizes[$_], $start..$end;
$ans{$key} = [sum(@part), \@part];
}
else {
my $num_a = int($num/2);
my $num_b = $num - $num_a;
my $min_mid = $start + $num_a - 1;
my $max_mid = $end - $num_b;
my $mid = int(($min_mid + $max_mid)/2);
my ($last_a, @part_a) = _group_cats($num_a, $start, $mid);
my ($last_b, @part_b) = _group_cats($num_b, $mid + 1, $end);
my $best = max($last_a, $last_b);
my @best_part = (@part_a, @part_b);
while ($min_mid < $max_mid) {
if ($last_a <= $last_b) {
if ($min_mid < $mid) {
$min_mid = $mid;
}
else {
$min_mid = $mid + 1;
}
}
else {
$max_mid = $mid;
}
$mid = int(($min_mid + $max_mid)/2);
($last_a, @part_a) = _group_cats($num_a, $start, $mid);
($last_b, @part_b) = _group_cats($num_b, $mid + 1, $end);
if (max($last_a, $last_b) < $best) {
$best = max($last_a, $last_b);
@best_part = (@part_a, @part_b);
}
}
$ans{$key} = [$best, @best_part];
}
}
return @{$ans{$key}};
}
}
sub max {
my $max = shift;
for (@_) {
$max = $_ if $max < $_;
}
$max;
}
sub sum {
my $sum = 0;
$sum += $_ for @_;
return $sum;
}
Cheers,
Ovid
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