Nice fast code, but does it return the right values?
I checked with the orig mma routine, the my_mma routine and your reduce_mma routine. Using the same set of @nums, the results differ.
use Benchmark qw(:all :hireswallclock);
my @nums = map {rand} 1 .. 10000;
my $subs = {
mma => sub { my @r = min_max_avg(\@nums) },
reduce_mma => sub { my @r = reduce_mma(\@nums) },
mymma => sub { my @r = my_mma(\@nums) }
};
cmpthese(-1, $subs);
$count = 1000;
for my $sub (keys %$subs){
$t = timeit($count, $subs->{$sub});
print "$count loops of $sub:",timestr($t),"\n";
}
for my $sub (keys %$subs){
print "$sub results:\n";
print (join ' ', &{$subs->{$sub}} , "\n");
}
##### Subs to test ######
__END__
$ perl benchmark.pl
Rate mma mymma reduce_mma
mma 86.3/s -- -49% -100%
mymma 171/s 98% -- -100%
reduce_mma 89229/s 103265% 52110% --
1000 loops of reduce_mma:0.0114148 wallclock secs ( 0.00 usr + 0.00 s
+ys = 0.00 CPU)
1000 loops of mma:12.0897 wallclock secs (12.05 usr + 0.01 sys = 12.0
+6 CPU) @ 82.91/s (n=1000)
1000 loops of mymma:5.98583 wallclock secs ( 5.97 usr + 0.00 sys = 5
+.97 CPU) @ 167.56/s (n=1000)
reduce_mma results:
0.956444677504809 0.209810070551129 0.765697545177442
mma results:
0.000119859684559742 0.999992750475673 0.505291691541093
mymma results:
0.000119859684559742 0.999992750475673 0.505291691541093
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