//private int _targetScore;
//private readonly int[] _maxAchievableScore;
public void ComputeGeneratingFunction()//int targetScore = 0)
{
//_targetScore = targetScore;
var gfTable = new ScoreDistribution[_graph.GetNumNodes()];
// Source
var sourceDist = new ScoreDistribution(0, 1);
sourceDist.SetEValue(0, 1);
gfTable[0] = sourceDist;
// All the other nodes
for (var nodeIndex = 1; nodeIndex < _graph.GetNumNodes(); nodeIndex++)
{
gfTable[nodeIndex] = GetScoreDistribution(nodeIndex, gfTable);
}
// Sink
// TODO: adjusting the distribution depending on neighboring amino acid (e.g. R.PEPTIDEK. vs A.PEPTIDEK)
_scoreDistribution = gfTable[gfTable.Length - 1];
}
//private int _targetScore;
//private readonly int[] _maxAchievableScore;
public void ComputeGeneratingFunction()//int targetScore = 0)
{
//_targetScore = targetScore;
var gfTable = new ScoreDistribution[_graph.GetNumNodes()];
// Source
var sourceDist = new ScoreDistribution(0, 1);
sourceDist.SetEValue(0, 1);
gfTable[0] = sourceDist;
// All the other nodes
for (var nodeIndex = 1; nodeIndex < _graph.GetNumNodes(); nodeIndex++)
{
gfTable[nodeIndex] = GetScoreDistribution(nodeIndex, gfTable);
}
// Sink
// TODO: adjusting the distribution depending on neighboring amino acid (e.g. R.PEPTIDEK. vs A.PEPTIDEK)
_scoreDistribution = gfTable[gfTable.Length - 1];
}
