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use strict;
use warnings;

use lib qw( ../../../../lib );

=head1 NAME

    Algorithm::Evolutionary::Fitness::wP_Peaks - wP Peaks problem generator - weighted version of P_Peaks

=head1 SYNOPSIS

    my $number_of_bits = 32;
    my @weights = (1);
    for (my $i = 0; $i < 99; $i ++ ) {
       push @weights, 0.99;
    }
    my $wp_peaks = Algorithm::Evolutionary::Fitness::wP_Peaks->new( $number_of_bits, @weights ); #Number of peaks = scalar  @weights

    # Or use an alternative ctor
    my $descriptor = { number_of_peaks => 100,
                       weight => 0.99 };
    my $wp_peaks = Algorithm::Evolutionary::Fitness::wP_Peaks->new( $number_of_bits, $descriptor)

=head1 DESCRIPTION

    wP-Peaks fitness function, weighted version of the P-Peaks fitness function, which has now a single peak

=head1 METHODS

=cut

package Algorithm::Evolutionary::Fitness::wP_Peaks;

our $VERSION =   "3.2";

use String::Random;
use Algorithm::Evolutionary::Utils qw(hamming);

use base qw(Algorithm::Evolutionary::Fitness::String);

=head2 new( $number_of_bits, @weights_array )

or new( $number_of_bits, $hash_with_number_of_peaks_and_weight )

Creates a new instance of the problem, with the said number of bits and peaks

=cut 

sub new {
  my $class = shift;
  my ( $bits ) = shift;

  my @weights;
  if ( ref $_[0] eq 'HASH' ) {
      push @weights, 1;
      for (my $i = 0; $i < $_[0]->{'number_of_peaks'}-1; $i ++ ) {
	  push @weights, $_[0]->{'weight'};
      } 
  } else {
      @weights = @_;
  }
  my $self = $class->SUPER::new();

  #Generate peaks