[1558] | 1 | package de.ugoe.cs.autoquest.tasktrees.alignment.algorithms; |
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| 2 | |
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| 3 | import java.util.ArrayList; |
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| 4 | import java.util.List; |
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| 5 | |
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| 6 | import de.ugoe.cs.autoquest.tasktrees.alignment.substitution.SubstitutionMatrix; |
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| 7 | |
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| 8 | public class SmithWatermanRepeated implements Alignment { |
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| 9 | |
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| 10 | /** |
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| 11 | * The first input |
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| 12 | */ |
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| 13 | private int[] input1; |
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| 14 | |
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| 15 | /** |
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| 16 | * The second input String |
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| 17 | */ |
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| 18 | private int[] input2; |
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| 19 | |
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| 20 | /** |
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| 21 | * The lengths of the input |
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| 22 | */ |
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| 23 | private int length1, length2; |
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| 24 | |
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| 25 | /** |
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| 26 | * The score matrix. The true scores should be divided by the normalization |
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| 27 | * factor. |
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| 28 | */ |
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| 29 | private MatrixEntry[][] matrix; |
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| 30 | |
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| 31 | |
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| 32 | |
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| 33 | private float scoreThreshold; |
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| 34 | |
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| 35 | /** |
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| 36 | * Substitution matrix to calculate scores |
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| 37 | */ |
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| 38 | private SubstitutionMatrix submat; |
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| 39 | |
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| 40 | public SmithWatermanRepeated(int[] input1, int[] input2, SubstitutionMatrix submat,float threshold) { |
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| 41 | this.input1 = input1; |
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| 42 | this.input2 = input2; |
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| 43 | length1 = input1.length; |
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| 44 | length2 = input2.length; |
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| 45 | this.submat = submat; |
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| 46 | |
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| 47 | //System.out.println("Starting SmithWaterman algorithm with a " |
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| 48 | // + submat.getClass() + " Substitution Matrix: " + submat.getClass().getCanonicalName()); |
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| 49 | this.scoreThreshold = threshold; |
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| 50 | |
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| 51 | matrix = new MatrixEntry[length1+2][length2+1]; |
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| 52 | |
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| 53 | for (int i = 0; i <= length1; i++) { |
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| 54 | for(int j = 0; j< length2; j++) { |
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| 55 | matrix[i][j] = new MatrixEntry(); |
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| 56 | } |
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| 57 | } |
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| 58 | |
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| 59 | |
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| 60 | buildMatrix(); |
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| 61 | } |
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| 62 | |
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| 63 | /** |
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| 64 | * Compute the similarity score of substitution The position of the first |
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| 65 | * character is 1. A position of 0 represents a gap. |
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| 66 | * |
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| 67 | * @param i |
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| 68 | * Position of the character in str1 |
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| 69 | * @param j |
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| 70 | * Position of the character in str2 |
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| 71 | * @return Cost of substitution of the character in str1 by the one in str2 |
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| 72 | */ |
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| 73 | private float similarity(int i, int j) { |
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| 74 | if (i == 0 || j == 0) { |
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| 75 | // it's a gap |
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| 76 | return submat.getGapPenalty(); |
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| 77 | } |
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| 78 | // System.out.println("Diag letters: " + input1[i-1] + " " + |
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| 79 | // input2[j-1]); |
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| 80 | // return (input1[i - 1] == input2[j - 1]) ? MATCH_SCORE : |
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| 81 | // MISMATCH_SCORE; |
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| 82 | return submat.getDistance(input1[i - 1], input2[j - 1]); |
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| 83 | } |
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| 84 | |
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| 85 | /** |
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| 86 | * Build the score matrix using dynamic programming. Note: The indel scores |
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| 87 | * must be negative. Otherwise, the part handling the first row and column |
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| 88 | * has to be modified. |
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| 89 | */ |
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| 90 | private void buildMatrix() { |
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| 91 | if (submat.getGapPenalty() >= 0) { |
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| 92 | throw new Error("Indel score must be negative"); |
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| 93 | } |
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| 94 | |
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| 95 | |
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| 96 | // base case |
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| 97 | matrix[0][0].setScore(0); |
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| 98 | matrix[0][0].setPrevious(null); // starting point |
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| 99 | |
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| 100 | // the first column |
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| 101 | for (int j = 1; j < length2; j++) { |
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| 102 | matrix[0][j].setScore(0); |
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| 103 | matrix[0][j].setPrevious(matrix[0][j-1]); |
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| 104 | |
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| 105 | } |
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| 106 | |
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| 107 | |
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| 108 | |
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| 109 | for (int i = 1; i <= length1; i++) { |
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| 110 | |
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| 111 | // Formula for first row: |
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| 112 | // F(i,0) = max { F(i-1,0), F(i-1,j)-T j=1,...,m |
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| 113 | |
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| 114 | float firstRowLeftScore = matrix[i-1][0].getScore(); |
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| 115 | float tempMax = matrix[i-1][1].getScore(); |
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| 116 | |
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| 117 | //position of the maximal score of the previous row |
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| 118 | int maxRowIndex = 1; |
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| 119 | |
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| 120 | for(int j = 2; j < length2;j++) { |
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| 121 | if(matrix[i-1][j].getScore() > tempMax) { |
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| 122 | tempMax = matrix[i-1][j].getScore(); |
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| 123 | maxRowIndex = j; |
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| 124 | } |
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| 125 | } |
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| 126 | |
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| 127 | tempMax -= scoreThreshold; |
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| 128 | matrix[i][0].setScore(Math.max(firstRowLeftScore, tempMax)); |
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| 129 | |
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| 130 | |
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| 131 | for (int j = 1; j < length2; j++) { |
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| 132 | float diagScore = matrix[i - 1][j - 1].getScore() + similarity(i, j); |
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| 133 | float upScore = matrix[i][j - 1].getScore() + similarity(0, j); |
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| 134 | float leftScore = matrix[i - 1][j].getScore() + similarity(i, 0); |
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| 135 | |
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| 136 | matrix[i][j].setScore(Math.max(diagScore,Math.max(upScore, Math.max(leftScore,matrix[i][0].getScore())))); |
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| 137 | |
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| 138 | // find the directions that give the maximum scores. |
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| 139 | // Multiple directions are ignored TODO |
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| 140 | if (diagScore == matrix[i][j].getScore()) { |
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| 141 | matrix[i][j].setPrevious(matrix[i-1][j-1]); |
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| 142 | } |
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| 143 | if (leftScore == matrix[i][j].getScore()) { |
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| 144 | matrix[i][j].setPrevious(matrix[i-1][j]); |
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| 145 | } |
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| 146 | if (upScore == matrix[i][j].getScore()) { |
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| 147 | matrix[i][j].setPrevious(matrix[i][j-1]); |
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| 148 | } |
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| 149 | if (matrix[i][0].getScore() == matrix[i][j].getScore()) { |
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| 150 | matrix[i][j].setPrevious(matrix[i-1][maxRowIndex]); |
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| 151 | } |
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| 152 | } |
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| 153 | } |
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| 154 | } |
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| 155 | |
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| 156 | /** |
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| 157 | * Get the maximum value in the score matrix. |
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| 158 | */ |
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| 159 | public double getMaxScore() { |
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| 160 | double maxScore = 0; |
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| 161 | |
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| 162 | // skip the first row and column |
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| 163 | for (int i = 1; i <= length1; i++) { |
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| 164 | for (int j = 1; j < length2; j++) { |
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| 165 | if (matrix[i][j].getScore() > maxScore) { |
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| 166 | maxScore = matrix[i][j].getScore(); |
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| 167 | } |
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| 168 | } |
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| 169 | } |
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| 170 | |
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| 171 | return maxScore; |
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| 172 | } |
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| 173 | |
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| 174 | /** |
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| 175 | * Get the alignment score between the two input strings. |
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| 176 | */ |
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| 177 | public double getAlignmentScore() { |
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| 178 | return getMaxScore(); |
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| 179 | } |
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| 180 | |
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| 181 | |
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| 182 | |
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| 183 | |
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| 184 | /** |
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| 185 | * given the bottom right corner point trace back the top left conrner. at |
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| 186 | * entry: i, j hold bottom right (end of Aligment coords) at return: hold |
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| 187 | * top left (start of Alignment coords) |
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| 188 | */ |
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| 189 | private int[] traceback(int i, int j) { |
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| 190 | |
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| 191 | return null; |
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| 192 | } |
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| 193 | |
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| 194 | |
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| 195 | /** |
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| 196 | * print the dynmaic programming matrix |
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| 197 | */ |
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| 198 | public void printDPMatrix() { |
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| 199 | System.out.print(" "); |
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| 200 | for (int i = 1; i <= length1; i++) |
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| 201 | System.out.format("%5d", input1[i - 1]); |
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| 202 | System.out.println(); |
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| 203 | for (int j = 0; j < length2; j++) { |
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| 204 | if (j > 0) |
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| 205 | System.out.format("%5d ",input2[j - 1]); |
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| 206 | else{ |
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| 207 | System.out.print(" "); |
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| 208 | } |
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| 209 | for (int i = 0; i <= length1; i++) { |
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| 210 | System.out.format("%4.1f ",matrix[i][j].getScore()); |
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| 211 | } |
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| 212 | System.out.println(); |
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| 213 | } |
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| 214 | } |
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| 215 | |
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| 216 | /** |
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| 217 | * Return a set of Matches identified in Dynamic programming matrix. A match |
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| 218 | * is a pair of subsequences whose score is higher than the preset |
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| 219 | * scoreThreshold |
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| 220 | **/ |
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| 221 | public List<Match> getMatches() { |
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| 222 | ArrayList<Match> matchList = new ArrayList(); |
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| 223 | int fA = 0, fB = 0; |
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| 224 | // skip the first row and column, find the next maxScore after |
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| 225 | // prevmaxScore |
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| 226 | for (int i = 1; i <= length1; i++) { |
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| 227 | for (int j = 1; j <= length2; j++) { |
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| 228 | if (matrix[i][j].getScore() > scoreThreshold |
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| 229 | && matrix[i][j].getScore() > matrix[i - 1][j - 1].getScore() |
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| 230 | && matrix[i][j].getScore() > matrix[i - 1][j].getScore() |
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| 231 | && matrix[i][j].getScore() > matrix[i][j - 1].getScore()) { |
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| 232 | if (i == length1 || j == length2 |
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| 233 | || matrix[i][j].getScore() > matrix[i + 1][j + 1].getScore()) { |
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| 234 | // should be lesser than prev maxScore |
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| 235 | fA = i; |
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| 236 | fB = j; |
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| 237 | int[] f = traceback(fA, fB); // sets the x, y to |
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| 238 | // startAlignment |
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| 239 | // coordinates |
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| 240 | System.out.println(f[0] + " " + i + " " + f[1] + " " |
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| 241 | + j + " " + matrix[i][j].getScore()); |
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| 242 | // TODO Add matches to matchList |
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| 243 | } |
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| 244 | } |
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| 245 | } |
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| 246 | } |
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| 247 | return matchList; |
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| 248 | } |
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| 249 | |
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| 250 | } |
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