/// \brief TODOCUMENT
size_vec common_residue_select_best_score_percent_policy::do_select_common_residues_with_scores(const doub_doub_pair_vec &arg_scores ///< TODOCUMENT
) const {
// Grab the a list of the smaller value from each pair of scores
const auto min_scores = transform_build<doub_vec>(
arg_scores,
[] (const doub_doub_pair &x) { return min( x.first, x.second ); }
);
// Build a stable_sorted list of indices in descending order of the score to which each corresponds
const auto score_sorted_indices = stable_sort_build<size_vec>(
irange( 0_z, min_scores.size() ),
[&] (const size_t &x, const size_t &y) {
return ( min_scores.at( x ) > min_scores.at( y ) );
}
);
// Calculate the total score of all values and the cutoff for best_score_percentage % of it
const double total_score = accumulate( min_scores, 0.0 );
const double percentile_total_score = total_score * best_score_percentage / 100.0;
// Step through score_sorted_indices and grab them until the sum of their scores exceeds
// percentile_total_score, then return a sorted copy of all those indices
double temp_sum( 0.0 );
return sort_build<size_vec>(
common::cbegin( score_sorted_indices ),
find_if(
score_sorted_indices,
[&] (const size_t &x) {
temp_sum += min_scores[ x ];
return ( temp_sum > percentile_total_score );
}
)
);
}
/// \brief TODOCUMENT
///
/// Things for investigation:
/// * raw/final score from alignment
/// * expected raw/final score
/// * top categorised reasons by raw score
/// * repeat for varying scan_stride (can just be called by nmnf fn)
alignment_scan_comparison check_scan_on_final_alignment::do_check(const alignment &arg_alignment, ///< TODOCUMENT
const protein &arg_protein_a, ///< TODOCUMENT
const protein &arg_protein_b, ///< TODOCUMENT
const quad_criteria &arg_criteria, ///< TODOCUMENT
const scan_stride &arg_scan_stride ///< TODOCUMENT
) const {
const auto aln_range = irange( 0_z, arg_alignment.length() );
cerr << "SHOULD THE RANGE BE 7.0 RATHER THAN SQRT(40.0)????\n";
return accumulate(
cross( aln_range, aln_range ),
alignment_scan_comparison{},
[&] (alignment_scan_comparison x, const size_size_tpl &y) {
const size_t aln_from_ctr = get<0>( y );
const size_t aln_to_ctr = get<1>( y );
const bool from_alns_both = has_both_positions_of_index( arg_alignment, aln_from_ctr );
const bool to_alns_both = has_both_positions_of_index( arg_alignment, aln_to_ctr );
if ( from_alns_both && to_alns_both ) {
const auto a_from = get_a_position_of_index( arg_alignment, aln_from_ctr );
const auto b_from = get_b_position_of_index( arg_alignment, aln_from_ctr );
const auto a_to = get_a_position_of_index( arg_alignment, aln_to_ctr );
const auto b_to = get_b_position_of_index( arg_alignment, aln_to_ctr );
const bool a_included = difference( a_from, a_to ) > NUM_EXCLUDED_ON_SIDES;
const bool b_included = difference( b_from, b_to ) > NUM_EXCLUDED_ON_SIDES;
if ( a_included && b_included ) {
const auto the_distance = distance_between_points(
view_vector_of_residue_pair(
arg_protein_a.get_residue_ref_of_index( a_from ),
arg_protein_a.get_residue_ref_of_index( a_to )
),
view_vector_of_residue_pair(
arg_protein_b.get_residue_ref_of_index( b_from ),
arg_protein_b.get_residue_ref_of_index( b_to )
)
);
// const auto score = ( the_distance >= 7.0 ) ? 0.0 : ( 1.0 - the_distance / 7.0 );
const auto score = ( the_distance >= sqrt( 40.0 ) ) ? 0.0 : ( 1.0 - the_distance / 7.0 );
if ( score > 0.0 ) {
const auto scan_result = quad_and_rep_criteria_result_of(
arg_protein_a,
arg_protein_b,
arg_criteria,
arg_scan_stride,
numeric_cast<index_type>( a_from ),
numeric_cast<index_type>( a_to ),
numeric_cast<index_type>( b_from ),
numeric_cast<index_type>( b_to )
);
x += make_pair( scan_result, score );
}
}
}
return x;
}
);
}
