private static final int MAX_NAME_LENGTH = 30;
//&!
- //private static final int GAP_OPEN_COST = 120;
- private static final int GAP_OPEN_COST = 10;
+ private static final int GAP_OPEN_COST = 120;
+ //private static final int GAP_OPEN_COST = 100;
- //private static final int GAP_EXTEND_COST = 20;
- private static final float GAP_EXTEND_COST = 0.5f;
+ private static final int GAP_EXTEND_COST = 20;
+ //private static final int GAP_EXTEND_COST = 5;
private static final int GAP_INDEX = -1;
public float meanScore; //needed for PaSiMap
- public float hypotheticMaxScore; // needed for PaSiMap
+ public int hypotheticMaxScore; // needed for PaSiMap
int prev = 0;
int i = maxi;
int j = maxj;
int trace;
- //maxscore = score[i][j] / 10f;
- maxscore = score[i][j];
+ maxscore = score[i][j] / 10f;
+ //maxscore = score[i][j];
//&! get trailing gaps
while ((i < seq1.length - 1) || (j < seq2.length - 1))
int t = 0;
float pairwiseScore = scoreMatrix.getPairwiseScore(s1str.charAt(i),
s2str.charAt(j));
- //float max = score[i - 1][j - 1] + (pairwiseScore * 10);
- float max = score[i - 1][j - 1] + (pairwiseScore);
+ float max = score[i - 1][j - 1] + (pairwiseScore * 10);
+ //float max = score[i - 1][j - 1] + (pairwiseScore);
if (F[i][j] > max)
{
// top left hand element
score[0][0] = scoreMatrix.getPairwiseScore(s1str.charAt(0),
- s2str.charAt(0));
- //s2str.charAt(0)) * 10;
+ //s2str.charAt(0));
+ s2str.charAt(0)) * 10;
E[0][0] = -GAP_EXTEND_COST;
F[0][0] = 0;
float pairwiseScore = scoreMatrix.getPairwiseScore(s1str.charAt(0),
s2str.charAt(j));
- //score[0][j] = max(pairwiseScore * 10, -GAP_OPEN_COST,
- score[0][j] = max(pairwiseScore, -GAP_OPEN_COST,
+ score[0][j] = max(pairwiseScore * 10, -GAP_OPEN_COST,
+ //score[0][j] = max(pairwiseScore, -GAP_OPEN_COST,
-GAP_EXTEND_COST);
traceback[0][j] = 1;
float pairwiseScore = scoreMatrix.getPairwiseScore(s1str.charAt(i),
s2str.charAt(0));
- //score[i][0] = max(pairwiseScore * 10, E[i][0], F[i][0]);
- score[i][0] = max(pairwiseScore, E[i][0], F[i][0]);
+ score[i][0] = max(pairwiseScore * 10, E[i][0], F[i][0]);
+ //score[i][0] = max(pairwiseScore, E[i][0], F[i][0]);
traceback[i][0] = -1;
}
float pairwiseScore = scoreMatrix.getPairwiseScore(s1str.charAt(i),
s2str.charAt(j));
- //score[i][j] = max(score[i - 1][j - 1] + (pairwiseScore * 10),
- score[i][j] = max(score[i - 1][j - 1] + (pairwiseScore),
+ score[i][j] = max(score[i - 1][j - 1] + (pairwiseScore * 10),
+ //score[i][j] = max(score[i - 1][j - 1] + (pairwiseScore),
E[i][j], F[i][j]);
traceback[i][j] = findTrace(i, j);
}
*/
public void meanScore()
{
- int length = (indelfreeAstr1.length() > indelfreeAstr2.length()) ? indelfreeAstr1.length() : indelfreeAstr2.length();
+ //int length = (indelfreeAstr1.length() > indelfreeAstr2.length()) ? indelfreeAstr1.length() : indelfreeAstr2.length();
+ int length = indelfreeAstr1.length(); //both have the same length
+ //create HashMap for counting residues in each sequence
HashMap<Character, Integer> seq1ResCount = new HashMap<Character, Integer>();
HashMap<Character, Integer> seq2ResCount = new HashMap<Character, Integer>();
- for (char residue: s1str.toCharArray())
+ // for both sequences (String indelfreeAstr1 or 2) create a key for the residue and add 1 each time its encountered
+ for (char residue: indelfreeAstr1.toCharArray())
{
seq1ResCount.putIfAbsent(residue, 0);
seq1ResCount.replace(residue, seq1ResCount.get(residue) + 1);
}
- for (char residue: s2str.toCharArray())
+ for (char residue: indelfreeAstr2.toCharArray())
{
seq2ResCount.putIfAbsent(residue, 0);
seq2ResCount.replace(residue, seq2ResCount.get(residue) + 1);
}
+ // meanscore = for each residue pair get the number of appearance and add (countA * countB * pairwiseScore(AB))
+ // divide the meanscore by the sequence length afterwards
float _meanscore = 0;
for (char resA : seq1ResCount.keySet())
{
*/
public void hypotheticMaxScore()
{
- float _hmsA = 0f;
- float _hmsB = 0f;
- for (char residue: s1str.toCharArray())
+ int _hmsA = 0;
+ int _hmsB = 0;
+ for (char residue: indelfreeAstr1.toCharArray())
{
_hmsA += scoreMatrix.getPairwiseScore(residue, residue);
}
- for (char residue: s2str.toCharArray())
+ for (char residue: indelfreeAstr2.toCharArray())
{
_hmsB += scoreMatrix.getPairwiseScore(residue, residue);
}
- this.hypotheticMaxScore = (_hmsA < _hmsB) ? _hmsA : _hmsB;
+ this.hypotheticMaxScore = (_hmsA < _hmsB) ? _hmsA : _hmsB; // take the lower self alignment
+
}
- public float getHypotheticMaxScore()
+ public int getHypotheticMaxScore()
{
return this.hypotheticMaxScore;
}
int n = astr1.length(); // both have the same length
for (int i = 0; i < n; i++)
{
- if (Character.isLetter(astr1.charAt(i)) && Character.isLetter(astr2.charAt(i)))
+ if (Character.isLetter(astr1.charAt(i)) && Character.isLetter(astr2.charAt(i))) // if both sequences dont have a gap -> add to indelfreeAstr
{
this.indelfreeAstr1 += astr1.charAt(i);
this.indelfreeAstr2 += astr2.charAt(i);
/**
* calculates the overall score of the alignment
- * alignmentScore = sum of all scores - all penalties
- *
+ * preprescore = sum of all scores - all penalties
+ * if preprescore < 1 ~ alignmentScore = Float.NaN >
+ * alignmentScore = ((preprescore - meanScore) / (hypotheticMaxScore - meanScore)) * coverage
*/
public void scoreAlignment() throws RuntimeException
{
+
getIndelfreeAstr();
meanScore();
hypotheticMaxScore();
{
throw new IllegalArgumentException(String.format("hypotheticMaxScore (%8.2f) == meanScore (%8.2f) - division by 0", hypotheticMaxScore, meanScore));
}
- int n = (astr1.length() > astr2.length()) ? astr1.length() : astr2.length();
+ //int n = (astr1.length() > astr2.length()) ? astr1.length() : astr2.length();
+ int n = indelfreeAstr1.length();
- System.out.println(String.format("astr1: %c .. %c ; astr2: %c .. %c", astr1.toCharArray()[0], astr1.toCharArray()[astr1.length() - 1], astr2.toCharArray()[0], astr2.toCharArray()[astr2.length() - 1]));
-
float score = 0;
boolean aGapOpen = false;
boolean bGapOpen = false;
for (int i = 0; i < n; i++)
{
- char char1 = astr1.charAt(i);
- char char2 = astr2.charAt(i);
+ char char1 = indelfreeAstr1.charAt(i);
+ char char2 = indelfreeAstr2.charAt(i);
boolean aIsLetter = Character.isLetter(char1);
boolean bIsLetter = Character.isLetter(char2);
if (aIsLetter && bIsLetter) // if pair -> get score
} else { // no gap open -> score - gap_open
score -= GAP_OPEN_COST;
}
+ // adjust GapOpen status in both sequences
aGapOpen = (!aIsLetter) ? true : false;
bGapOpen = (!bIsLetter) ? true : false;
}
- float preprescore = score;
+ float preprescore = score; // if this score < 1 --> alignment score = Float.NaN
score = (score - this.meanScore) / (this.hypotheticMaxScore - this.meanScore);
int[] _max = MiscMath.findMax(new int[]{astr1.replace("-","").length(), astr2.replace("-","").length()}); // {index of max, max}
- float coverage = (float) indelfreeAstr1.length() / (float) _max[1];
- float prescore = score;
+ float coverage = (float) n / (float) _max[1]; // indelfreeAstr length / longest sequence length
+ float prescore = score; // only debug
score *= coverage;
- System.out.println(String.format("prepre-score: %f, pre-score: %f, longlength: %d\nscore: %f, mean: %f, max: %f", preprescore, prescore, indelfreeAstr1.length(), score, this.meanScore, this.hypotheticMaxScore));
+ System.out.println(String.format("prepre-score: %f, pre-score: %f, longlength: %d\nscore: %f, mean: %f, max: %d", preprescore, prescore, _max[1], score, this.meanScore, this.hypotheticMaxScore));
this.alignmentScore = (preprescore < 1) ? Float.NaN : score;
}
}
git://source.jalview.org / jalview.git / blobdiff