package AI::Pathfinding::OptimizeMultiple::App::CmdLine;
use strict;
use warnings;
use MooX qw/late/;
use Getopt::Long qw(GetOptionsFromArray);
use IO::File;
use AI::Pathfinding::OptimizeMultiple;
use AI::Pathfinding::OptimizeMultiple::PostProcessor;
our $VERSION = '0.0.12';
# TODO : restore later.
# use MyInput;
use Carp ();
has argv => (isa => 'ArrayRef[Str]', is => 'ro', required => 1,);
has _arbitrator => (is => 'rw');
has _add_horne_prune => (isa => 'Bool', is => 'rw');
has _chosen_scans => (isa => 'ArrayRef', is => 'rw');
has _should_exit_immediately => (isa => 'Bool', is => 'rw', default => sub { 0; },);
has input_obj_class => (isa => 'Str', is => 'rw');
has _input_obj => (is => 'rw');
has _is_flares => (is => 'rw', isa => 'Bool', default => sub { 0; },);
has _num_boards => (isa => 'Int', is => 'rw');
has _offset_quotas => (isa => 'Int', is => 'rw');
has _optimize_for => (isa => 'Str', is => 'rw');
has _output_filename => (isa => 'Str', is => 'rw');
has _post_processor => (isa => 'Maybe[AI::Pathfinding::OptimizeMultiple::PostProcessor]', is => 'rw');
has _quotas_are_cb => (isa => 'Bool', is => 'rw');
has _quotas_expr => (isa => 'Maybe[Str]', is => 'rw');
has _should_rle_be_done => (isa => 'Bool', is => 'rw');
has _should_trace_be_done => (isa => 'Bool', is => 'rw');
has _simulate_to => (isa => 'Maybe[Str]', is => 'rw');
has _start_board => (isa => 'Int', is => 'rw');
has _stats_factors => (isa => 'HashRef', is => 'rw', default => sub { return +{}; },);
my $_component_re = qr/[A-Za-z][A-Za-z0-9_]*/;
my $_module_re = qr/$_component_re(?:::$_component_re)*/;
sub BUILD
{
my $self = shift;
# Command line parameters
my $_start_board = 1;
my $num_boards = 32000;
my $output_filename = "-";
my $should_trace_be_done = 0;
my $should_rle_be_done = 1;
my $_quotas_expr = undef;
my $quotas_are_cb = 0;
my $optimize_for = "speed";
my $offset_quotas = 0;
my $simulate_to = undef;
my $_add_horne_prune = 0;
my $input_obj_class = 'AI::Pathfinding::OptimizeMultiple::DataInputObj';
my %stats_factors;
my $help = 0;
my $man = 0;
GetOptionsFromArray(
$self->argv(),
'help|h' => \$help,
man => \$man,
"o|output=s" => \$output_filename,
"num-boards=i" => \$num_boards,
"trace" => \$should_trace_be_done,
"rle!" => \$should_rle_be_done,
"start-board=i" => \$_start_board,
"quotas-expr=s" => \$_quotas_expr,
"quotas-are-cb" => \$quotas_are_cb,
"offset-quotas" => \$offset_quotas,
"opt-for=s" => \$optimize_for,
"simulate-to=s" => \$simulate_to,
"sprtf" => \$_add_horne_prune,
"input-class=s" => \$input_obj_class,
"stats-factors=f" => \%stats_factors,
) or die "Extracting options from ARGV array failed - $!";
if ($help)
{
$self->_should_exit_immediately(1);
print <<"EOF";
$0 - optimize a game AI multi-tasking configuration
--help | -h - displays this help screen
--output=[filename] | -o [filename] - output to this file instead of STDOUT.
EOF
return;
}
$self->_start_board($_start_board);
$self->_num_boards($num_boards);
$self->_output_filename($output_filename);
$self->_should_trace_be_done($should_trace_be_done);
$self->_should_rle_be_done($should_rle_be_done);
$self->_quotas_expr($_quotas_expr);
$self->_quotas_are_cb($quotas_are_cb);
$self->_optimize_for($optimize_for);
$self->_offset_quotas($offset_quotas);
$self->_simulate_to($simulate_to);
$self->_add_horne_prune($_add_horne_prune);
$self->_stats_factors(\%stats_factors);
$self->input_obj_class($input_obj_class);
{
my $class = $self->input_obj_class();
if ($class !~ m{\A$_module_re\z})
{
Carp::confess(
"Input object class does not seem like a good class:"
. $self->input_obj_class()
);
}
eval "require $class;";
if ($@)
{
die "Could not load '$class' - <<$@>>";
}
# TODO : Restore later.
$self->_input_obj(
$class->new(
{
start_board => $self->_start_board(),
num_boards => $self->_num_boards(),
}
)
);
}
$self->_post_processor(
AI::Pathfinding::OptimizeMultiple::PostProcessor->new(
{
do_rle => $self->_should_rle_be_done(),
offset_quotas => $self->_offset_quotas(),
}
)
);
return;
}
sub _selected_scans
{
my $self = shift;
return $self->_input_obj->selected_scans();
}
sub _map_all_but_last
{
my $self = shift;
my ($cb, $arr_ref) = (@_);
return [ (map {$cb->($_)} @$arr_ref[0 .. $#$arr_ref-1]), $arr_ref->[-1] ];
}
sub _get_quotas
{
my $self = shift;
if ($self->_quotas_are_cb())
{
return scalar(eval($self->_quotas_expr()));
}
elsif (defined($self->_quotas_expr()))
{
return [eval $self->_quotas_expr()];
}
else
{
return $self->_get_default_quotas();
}
}
sub _get_default_quotas
{
return [(350) x 5000];
}
sub _get_script_fh
{
my $self = shift;
return IO::File->new(
($self->_output_filename() eq "-") ?
">&STDOUT" :
($self->_output_filename(), "w")
);
}
sub _get_script_terminator
{
return "\n\n\n";
}
sub _out_script
{
my $self = shift;
my $cmd_line_string = shift;
$self->_get_script_fh()->print(
$cmd_line_string,
$self->_get_script_terminator($cmd_line_string)
);
}
sub _get_line_of_command
{
my $self = shift;
my $args_string =
join(" ",
$self->_start_board(),
$self->_start_board() + $self->_num_boards() - 1,
1
);
return "freecell-solver-range-parallel-solve $args_string";
}
sub _line_ends_mapping
{
my $self = shift;
return $self->_map_all_but_last(sub { "$_[0] \\\n" }, shift);
}
sub _get_used_scans
{
my $self = shift;
return [ grep { $_->is_used() } @{$self->_selected_scans()}];
}
sub _get_scan_line
{
my ($self, $line) = @_;
return $line->{'cmd_line'} . " -step 500 "
. join(" ", map { $_, $line->{'id'} }
("--st-name", ($self->_is_flares() ? "--flare-name" : ()))
);
}
sub _get_lines_of_scan_defs
{
my $self = shift;
return
[map
{ $self->_get_scan_line($_) }
@{$self->_get_used_scans()}
];
}
sub _scan_def_line_mapping
{
my ($self, $lines_aref) = @_;
return $self->_map_all_but_last(
sub
{
my ($line) = @_;
return $line . ' ' . ($self->_is_flares() ? "-nf" : "-nst");
},
[
map
{
my $line = $_;
# Add the -sp r:tf flag to each scan if specified - it enhances
# performance, but timing the scans with it makes the total
# scan sub-optimal.
if ($self->_add_horne_prune())
{
$line =~ s/( --st-name)/ -sp r:tf$1/;
}
$line;
}
@$lines_aref
],
);
}
sub _calc_iter_quota
{
my $self = shift;
my $quota = shift;
if ($self->_offset_quotas())
{
return $quota+1;
}
else
{
return $quota;
}
}
sub _map_scan_idx_to_id
{
my $self = shift;
my $index = shift;
return $self->_selected_scans()->[$index]->id();
}
sub _format_prelude_iter
{
my $self = shift;
my $iter = shift;
return ($self->_is_flares() ? "Run:" : "") . $iter->iters() . '@'
. $self->_map_scan_idx_to_id($iter->scan_idx())
;
}
sub _get_line_of_prelude
{
my $self = shift;
return +($self->_is_flares() ? "--flares-plan" : "--prelude") . qq{ "} .
join(",",
map { $self->_format_prelude_iter($_) }
@{$self->_chosen_scans()}
) . "\"";
}
sub _calc_script_lines
{
my $self = shift;
return
[
$self->_get_line_of_command(),
@{$self->_scan_def_line_mapping(
$self->_get_lines_of_scan_defs()
)},
$self->_get_line_of_prelude()
];
}
sub _calc_script_text
{
my $self = shift;
return
join("",
@{$self->_line_ends_mapping(
$self->_calc_script_lines()
)}
);
}
sub _write_script
{
my $self = shift;
$self->_out_script(
$self->_calc_script_text()
);
}
sub _calc_scans_iters_pdls
{
my $self = shift;
my $method =
(($self->_optimize_for() =~ m{len})
? "get_scans_lens_iters_pdls"
: "get_scans_iters_pdls"
);
return $self->_input_obj->$method();
}
sub _arbitrator_trace_cb
{
my $args = shift;
printf("%s \@ %s (%s solved)\n",
@$args{qw(iters_quota selected_scan_idx total_boards_solved)}
);
}
sub _init_arbitrator
{
my $self = shift;
return $self->_arbitrator(
AI::Pathfinding::OptimizeMultiple->new(
{
'scans' =>
[
map { +{ name => $_->id() } }
@{$self->_input_obj->_suitable_scans_list()},
],
'quotas' => $self->_get_quotas(),
'selected_scans' => $self->_selected_scans(),
'num_boards' => $self->_num_boards(),
'scans_iters_pdls' => $self->_calc_scans_iters_pdls(),
'trace_cb' => \&_arbitrator_trace_cb,
'optimize_for' => $self->_optimize_for(),
'stats_factors' => $self->_stats_factors(),
}
)
);
}
sub _report_total_iters
{
my $self = shift;
if ($self->_arbitrator()->get_final_status() eq "solved_all")
{
print "Solved all!\n";
}
printf("total_iters = %s\n", $self->_arbitrator()->get_total_iters());
}
sub _arbitrator_process
{
my $self = shift;
$self->_arbitrator()->calc_meta_scan();
my $scans = $self->_post_processor->process(
$self->_arbitrator->chosen_scans()
);
$self->_chosen_scans($scans);
}
sub _do_trace_for_board
{
my $self = shift;
my $board = shift;
my $results = $self->_arbitrator()->calc_board_iters($board);
print "\@info=". join(",", @{$results->{per_scan_iters}}). "\n";
print +($board+$self->_start_board()) . ": ". $results->{board_iters} . "\n";
}
sub _real_do_trace
{
my $self = shift;
foreach my $board (0 .. $self->_num_boards()-1)
{
$self->_do_trace_for_board($board);
}
}
sub _do_trace
{
my $self = shift;
# Analyze the results
if ($self->_should_trace_be_done())
{
$self->_real_do_trace();
}
}
sub _get_run_string
{
my $self = shift;
my $results = shift;
return join("",
map
{
sprintf('%i@%i,',
$_->iters(),
$self->_map_scan_idx_to_id($_->scan_idx())
)
}
@{$self->_post_processor->process($results->scan_runs())},
);
}
sub _do_simulation_for_board
{
my ($self, $board) = @_;
my $results = $self->_arbitrator()->simulate_board($board);
my $scan_mapper = sub {
my $index = shift;
return $self->_map_scan_idx_to_id($index);
};
return
sprintf("%i:%s:%s:%i",
$board+1,
$results->get_status(),
$self->_get_run_string($results),
$results->get_total_iters(),
);
}
sub _real_do_simulation
{
my $self = shift;
open my $simulate_out_fh, ">", $self->_simulate_to()
or Carp::confess("Could not open " . $self->_simulate_to() . " - $!");
foreach my $board (0 .. $self->_num_boards()-1)
{
print {$simulate_out_fh} $self->_do_simulation_for_board($board), "\n";
}
close($simulate_out_fh);
return;
}
sub _do_simulation
{
my $self = shift;
# Analyze the results
if (defined($self->_simulate_to()))
{
$self->_real_do_simulation();
}
return;
}
sub run
{
my $self = shift;
if ($self->_should_exit_immediately())
{
return 0;
}
$self->_init_arbitrator();
$self->_arbitrator_process();
$self->_report_total_iters();
$self->_write_script();
$self->_do_trace();
$self->_do_simulation();
return 0;
}
sub run_flares
{
my $self = shift;
$self->_optimize_for("len");
$self->_is_flares(1);
$self->_init_arbitrator();
$self->_arbitrator()->calc_flares_meta_scan();
my $scans = $self->_post_processor->process(
$self->_arbitrator->chosen_scans()
);
$self->_chosen_scans($scans);
$self->_report_total_iters();
$self->_write_script();
$self->_do_trace();
$self->_do_simulation();
return 0;
}
1;
__END__
=pod
=encoding UTF-8
=head1 NAME
AI::Pathfinding::OptimizeMultiple::App::CmdLine - the command line application class.
=head1 VERSION
version 0.0.12
=head1 SUBROUTINES/METHODS
=head2 $self->run()
For internal use.
=head2 $self->run_flares()
For internal use.
=head2 $self->argv()
An array ref of command line arguments.
=head2 $self->input_obj_class()
The class to handle the input data - by default -
L<AI::Pathfinding::OptimizeMultiple::DataInputObj>.
=head2 BUILD()
Moo leftover. B<INTERNAL USE>.
=head1 COPYRIGHT AND LICENSE
Copyright (c) 2010 Shlomi Fish
Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation
files (the "Software"), to deal in the Software without
restriction, including without limitation the rights to use,
copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following
conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
=head1 AUTHOR
Shlomi Fish <shlomif@cpan.org>
=head1 COPYRIGHT AND LICENSE
This software is Copyright (c) 2012 by Shlomi Fish.
This is free software, licensed under:
The MIT (X11) License
=head1 BUGS
Please report any bugs or feature requests on the bugtracker website
http://rt.cpan.org/NoAuth/Bugs.html?Dist=AI-Pathfinding-OptimizeMultiple or
by email to bug-ai-pathfinding-optimizemultiple@rt.cpan.org.
When submitting a bug or request, please include a test-file or a
patch to an existing test-file that illustrates the bug or desired
feature.
=for :stopwords cpan testmatrix url annocpan anno bugtracker rt cpants kwalitee diff irc mailto metadata placeholders metacpan
=head1 SUPPORT
=head2 Perldoc
You can find documentation for this module with the perldoc command.
perldoc AI::Pathfinding::OptimizeMultiple
=head2 Websites
The following websites have more information about this module, and may be of help to you. As always,
in addition to those websites please use your favorite search engine to discover more resources.
=over 4
=item *
MetaCPAN
A modern, open-source CPAN search engine, useful to view POD in HTML format.
L<http://metacpan.org/release/AI-Pathfinding-OptimizeMultiple>
=item *
Search CPAN
The default CPAN search engine, useful to view POD in HTML format.
L<http://search.cpan.org/dist/AI-Pathfinding-OptimizeMultiple>
=item *
RT: CPAN's Bug Tracker
The RT ( Request Tracker ) website is the default bug/issue tracking system for CPAN.
L<http://rt.cpan.org/NoAuth/Bugs.html?Dist=AI-Pathfinding-OptimizeMultiple>
=item *
AnnoCPAN
The AnnoCPAN is a website that allows community annotations of Perl module documentation.
L<http://annocpan.org/dist/AI-Pathfinding-OptimizeMultiple>
=item *
CPAN Ratings
The CPAN Ratings is a website that allows community ratings and reviews of Perl modules.
L<http://cpanratings.perl.org/d/AI-Pathfinding-OptimizeMultiple>
=item *
CPAN Forum
The CPAN Forum is a web forum for discussing Perl modules.
L<http://cpanforum.com/dist/AI-Pathfinding-OptimizeMultiple>
=item *
CPANTS
The CPANTS is a website that analyzes the Kwalitee ( code metrics ) of a distribution.
L<http://cpants.perl.org/dist/overview/AI-Pathfinding-OptimizeMultiple>
=item *
CPAN Testers
The CPAN Testers is a network of smokers who run automated tests on uploaded CPAN distributions.
L<http://www.cpantesters.org/distro/A/AI-Pathfinding-OptimizeMultiple>
=item *
CPAN Testers Matrix
The CPAN Testers Matrix is a website that provides a visual overview of the test results for a distribution on various Perls/platforms.
L<http://matrix.cpantesters.org/?dist=AI-Pathfinding-OptimizeMultiple>
=item *
CPAN Testers Dependencies
The CPAN Testers Dependencies is a website that shows a chart of the test results of all dependencies for a distribution.
L<http://deps.cpantesters.org/?module=AI::Pathfinding::OptimizeMultiple>
=back
=head2 Bugs / Feature Requests
Please report any bugs or feature requests by email to C<bug-ai-pathfinding-optimizemultiple at rt.cpan.org>, or through
the web interface at L<http://rt.cpan.org/NoAuth/ReportBug.html?Queue=AI-Pathfinding-OptimizeMultiple>. You will be automatically notified of any
progress on the request by the system.
=head2 Source Code
The code is open to the world, and available for you to hack on. Please feel free to browse it and play
with it, or whatever. If you want to contribute patches, please send me a diff or prod me to pull
from your repository :)
L<http://bitbucket.org/shlomif/fc-solve>
git clone ssh://git@bitbucket.org/shlomif/fc-solve.git
=cut