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mas.c
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mas.c
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/*
* SMART: string matching algorithms research tool.
* Copyright (C) 2012 Simone Faro and Thierry Lecroq
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>
*
* contact the authors at: [email protected], [email protected]
* download the tool at: http://www.dmi.unict.it/~faro/smart/
*
* This is an implementation of the Maximal Average Shift algorithm
* in C. Ryu, T. Lecroq, and K. Park.
*/
#include "include/define.h"
#include "include/main.h"
#define DSIGMA 4 // DNA sequences have alphabet of size 4.
/* Input : pattern P = P[0..m-1], text T = T[0..n-1]
* Output : the number of occurrences of P in T */
int search(unsigned char *P, int m, unsigned char *T, int n) {
int count = 0;
int i, l, k, s, w, nMinusm;
int max_pos, avr_shift, max_avr_shift;
int scan[XSIZE], shift[XSIZE][SIGMA];
int U[XSIZE], safe[XSIZE + 1];
char dna[DSIGMA] = { 'A','C','G','T' };
//freq('A') = 0.293, freq('C') = 0.207, freq('G') = 0.207, freq('T') = 0.293.
int freq[SIGMA];
BEGIN_PREPROCESSING
freq['A'] = 293; freq['C'] = 207;
freq['G'] = 207; freq['T'] = 293;
/* Initialize */
for (l = 0; l < m; l++) {
U[l] = 1; // Set U to {0,1,...,m-1}.
for (s = 0; s < DSIGMA; s++) {
shift[l][dna[s]] = 1;
}
}
for (k = 1; k <= m; k++) {
safe[k] = 0;
}
/* Preprocessing */
for (i = 0; i < m; i++) {
for (l = 0; l < m; l++) {
if (U[l] == 1) {
for (s = 0; s < DSIGMA; s++) {
for (k = shift[l][dna[s]]; k <= m; k++) {
if (safe[k] == 0 && ((l - k < 0) || dna[s] == (P[l - k]))) { // (l - k < 0) means that P[l - k] for l - k < 0 matches any character.
shift[l][dna[s]] = k;
break;
}
}
}
}
}
max_avr_shift = 0;
for (l = 0; l < m; l++) {
if (U[l] == 1) {
avr_shift = 0;
for (s = 0; s < DSIGMA; s++) {
avr_shift = avr_shift + shift[l][dna[s]] * freq[dna[s]];
}
if ((max_avr_shift < avr_shift) || (max_avr_shift == avr_shift && freq[P[max_pos]] > freq[P[l]])) {
max_avr_shift = avr_shift;
max_pos = l;
}
}
}
scan[i] = max_pos; // Determine scan[0],scan[1],...,scan[m-1].
U[max_pos] = 0;
for (k = 1; k <= max_pos; k++) {
if (P[max_pos] != P[max_pos - k])
safe[k] = 1;
}
}
END_PREPROCESSING
BEGIN_SEARCHING
/* Searching */
memcpy(T + n, P, m); // Set T[n..n+m-1] to P[0..m-1] in order to avoid testing the end of the text but exit the algorithm only when an occurrence of P is found.
w = 0;
nMinusm = n - m;
while (1) {
while (P[(l = scan[0])] != (s = T[w + l])) { // Use the fast-loop in order to quickly shift the window when the first scan position is a mismatch.
w += shift[l][s];
}
if (w <= nMinusm) {
i = 1;
while (i < m && P[(l = scan[i])] == (s = T[w + l])) {
i++;
}
if (i == m) {
++count;
}
w += shift[l][s];
}
else {
END_SEARCHING
return count;
}
}
}