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 sys =  0.00 CPU)
1000 loops of mma:12.0897 wallclock secs (12.05 usr +  0.01 sys = 12.06 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