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foreach my $algo (@algos) {
  die "unknown algorithm: $algo"
    if !Algorithm::Networksort::nw_algorithm_name($algo);

  my @network = Algorithm::Networksort::Chooser::silence_carps(sub {
    Algorithm::Networksort::nw_comparators($network_size, algorithm => $algo)
  });

  if (!@network) {
    warn "network $algo returned empty comparator list, skipping\n";
    next;
  }

  push @candidates, {
    algo => $algo,
    network => \@network,
  };
}




#### Selection network processing

if ($opt->{median}) {
  die "--selection and --median are incompatible" if defined $opt->{selection};

  $opt->{selection} = int($network_size / 2);
}


if (defined $opt->{selection}) {
  my $selection = [ split(',', $opt->{selection}) ];

  foreach my $ind (@$selection) {
    die "badly formed selection index: $ind" unless $ind =~ /^\d+$/;
    die "selection index $ind is too large for the network size" if $ind >= $network_size;
  }

  foreach my $candidate (@candidates) {
    $candidate->{network} = Algorithm::Networksort::Chooser::build_selection_network($candidate->{network}, $selection);
  }
}




#### Score the generated networks

foreach my $candidate (@candidates) {
  my @network = @{ $candidate->{network} };
  my @grouped_network = Algorithm::Networksort::nw_group(\@network, $network_size, grouping=>'parallel');

  $candidate->{comparators} = (0+@network);
  $candidate->{stages} = (0+@grouped_network);
}




#### Remove 'best' network if it's the same as batcher

my $batcher = [grep { $_->{algo} eq 'batcher' } @candidates]->[0];
my $best = [grep { $_->{algo} eq 'best' } @candidates]->[0];

if ($batcher->{comparators} == $best->{comparators} && $batcher->{stages} == $best->{stages}) {
  @candidates = grep { $_->{algo} ne 'best' } @candidates;
}




#### Sort by optimisation criteria

my @sorted_candidates;

if ($opt->{opt} eq 'comparators') {
  @sorted_candidates = sort {
     ($a->{comparators} <=> $b->{comparators}) || ($a->{stages} <=> $b->{stages})
  } @candidates;
} elsif ($opt->{opt} eq 'stages') {
  @sorted_candidates = sort {
     ($a->{stages} <=> $b->{stages}) || ($a->{comparators} <=> $b->{comparators})
  } @candidates;
} elsif ($opt->{opt} eq 'swaps') {
  foreach my $candidate (@candidates) {
    if ($opt->{'swap-mode'} eq 'zero-one') {
      $candidate->{swaps} = Algorithm::Networksort::Chooser::average_swaps_zero_one($network_size, $candidate->{network});
    } elsif ($opt->{'swap-mode'} eq 'permutation') {
      $candidate->{swaps} = Algorithm::Networksort::Chooser::average_swaps_permutation($network_size, $candidate->{network});
    }
  }

  @sorted_candidates = sort {
     ($a->{swaps} <=> $b->{swaps}) || ($a->{comparators} <=> $b->{comparators}) || ($a->{stages} <=> $b->{stages})
  } @candidates;
} else {
  die "Unknown optimisation criteria: $opt->{opt}";
}




#### Output results


if ($opt->{raw}) {
  print "[";
  print join(',', map { "[$_->[0],$_->[1]]" } @{ $sorted_candidates[0]->{network} });
  print "]\n";
  exit;
}


print "Network size: $network_size\n";

if ($opt->{median}) {
  print "Network type: Median network\n";
} elsif ($opt->{selection}) {
  print "Network type: Selection network: $opt->{selection}\n";
} else {
  print "Network type: Sorting network\n";
}

print "\n";

print "Optimisation criteria: $opt->{opt}\n";

print "\n";

print "Optimal network:\n";

output_network($sorted_candidates[0]);

if ($opt->{all}) {
  print "\nAdditional candidate networks:\n";
  foreach my $network (@sorted_candidates[1..$#sorted_candidates]) {
    output_network($network);
  }
}



sub output_network {
  my $network = shift;

  print "  Algorithm \"$network->{algo}\":\n";
  print "    Comparators: $network->{comparators}\n";
  print "    Stages: $network->{stages}\n";
  print "    Avg swaps: $network->{swaps}\n" if exists $network->{swaps};

  if ($opt->{show}) {
    print "\n";
    print Algorithm::Networksort::nw_graph($network->{network}, $network_size, graph => 'text');
  }
}




__END__

=encoding utf-8

=head1 NAME

algorithm-networksort-chooser - Helper utility for Algorithm::Networksort

=head1 SYNOPSIS

The C<algorithm-networksort-chooser> script helps you find the best sorting network for your particular use-case.

    $ algorithm-networksort-chooser 9  ## find best sorting network for array size 9
    $ algorithm-networksort-chooser 9 --all  ## show all candiate networks
    $ algorithm-networksort-chooser 9 --algorithms=batcher,bitonic  ## only consider batcher and bitonic algos

    $ algorithm-networksort-chooser 9 --opt=comparators  ## optimise for comparators (default)
    $ algorithm-networksort-chooser 9 --opt=stages  ## optimise for stages
    $ algorithm-networksort-chooser 9 --opt=swaps  ## optimise for average swaps

    $ algorithm-networksort-chooser 9 --median  ## best median network
    $ algorithm-networksort-chooser 9 --selection=4  ## also best median network
    $ algorithm-networksort-chooser 9 --selection=0,1,2  ## top-3 elements selection net

    $ algorithm-networksort-chooser 9 --validate  ## run 0-1 validation test
    $ algorithm-networksort-chooser 9 --show  ## show network as ASCII diagram
    $ algorithm-networksort-chooser 9 --raw  ## show network as raw comparators



=head1 DESCRIPTION

This module uses L<Algorithm::Networksort> to experiment with sorting networks.

L<Introduction To Sorting Networks|http://hoytech.github.io/sorting-networks/>

By default this script examines the output of all implemented algorithms and the currently best known special-cases, and chooses the one that best meets your specified criteria.

This module allows you to trim sorting networks into median or selection networks.

You can then choose the optimal net based on comparators (total number of operations) or on stages (number of operations considering parallelism).

Normally the output is something like this:

    $ algorithm-networksort-chooser --median 22
    Network size: 22
    Network type: Median network

    Optimisation criteria: stages

    Optimal network:
      Algorithm "best":
        Comparators: 86
        Stages: 12

For the description of the various algorithms and best-known special cases, see L<Algorithm::Networksort>'s documentation and source code.

In order to use this output in another program, there is a C<--raw> switch. Its output is C<eval>able perl and is valid JSON:

    $ algorithm-networksort-chooser --median 7 --raw
    [[0,4],[1,5],[2,6],[0,2],[1,3],[4,6],[2,4],[3,5],[0,1],[2,3],[4,5],[1,4],[3,6],[3,4]]

L<Algorithm::Networksort>'s ASCII output can be seen with C<--show>:

    $ algorithm-networksort-chooser --median 7 --show
    Network size: 7
    Network type: Median network

    Optimisation criteria: comparators

    Optimal network:
      Algorithm "batcher":
        Comparators: 14
        Stages: 6

    o--^--------^-----^-----------------o
       |        |     |                  
    o--|--^-----|--^--v--------^--------o
       |  |     |  |           |         
    o--|--|--^--v--|--^-----^--|--------o
       |  |  |     |  |     |  |         
    o--|--|--|-----v--|--^--v--|--^--^--o
       |  |  |        |  |     |  |  |   
    o--v--|--|--^-----v--|--^--v--|--v--o
          |  |  |        |  |     |      
    o-----v--|--|--------v--v-----|-----o
             |  |                 |      
    o--------v--v-----------------v-----o


The C<--all> switch shows all networks that were considered.

Sometimes which algorithm or which best special-case network is surprising. For instance, selecting the top-3 elements in a size-9 array is best done by adapting Hibbard's algorithm, even though there is a special best (by comparators) network for si...

    $ algorithm-networksort-chooser 9 --selection=0,1,2 --all
    Network size: 9
    Network type: Selection network: 0,1,2

    Optimisation criteria: comparators

    Optimal network:
      Algorithm "hibbard":
        Comparators: 18
        Stages: 7

    Additional candidate networks:
      Algorithm "batcher":
        Comparators: 20
        Stages: 8
      Algorithm "bosenelson":
        Comparators: 22
        Stages: 10
      Algorithm "best":
        Comparators: 23
        Stages: 9
      Algorithm "bitonic":
        Comparators: 24
        Stages: 8
      Algorithm "bubble":
        Comparators: 36
        Stages: 15




=head1 FUTURE IDEAS

Algorithm::Networksort::Validate::XS



=head1 SEE ALSO

L<Introduction To Sorting Networks|http://hoytech.github.io/sorting-networks/>

L<Algorithm-Networksort-Chooser github repo|https://github.com/hoytech/Algorithm-Networksort-Chooser>

John Gamble's L<Algorithm-Networksort github repo|https://github.com/jgamble/Algorithm-Networksort>



=head1 AUTHOR

Doug Hoyte, C<< <doug@hcsw.org> >>

=head1 COPYRIGHT & LICENSE

Copyright 2013-2016 Doug Hoyte.

This module is licensed under the same terms as perl itself.