--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyPRADA_1.2/tools/samtools-0.1.16/errmod.c	Thu Feb 20 00:44:58 2014 -0500
@@ -0,0 +1,130 @@
+#include <math.h>
+#include "errmod.h"
+#include "ksort.h"
+KSORT_INIT_GENERIC(uint16_t)
+
+typedef struct __errmod_coef_t {
+	double *fk, *beta, *lhet;
+} errmod_coef_t;
+
+typedef struct {
+	double fsum[16], bsum[16];
+	uint32_t c[16];
+} call_aux_t;
+
+static errmod_coef_t *cal_coef(double depcorr, double eta)
+{
+	int k, n, q;
+	long double sum, sum1;
+	double *lC;
+	errmod_coef_t *ec;
+
+	ec = calloc(1, sizeof(errmod_coef_t));
+	// initialize ->fk
+	ec->fk = (double*)calloc(256, sizeof(double));
+	ec->fk[0] = 1.0;
+	for (n = 1; n != 256; ++n)
+		ec->fk[n] = pow(1. - depcorr, n) * (1.0 - eta) + eta;
+	// initialize ->coef
+	ec->beta = (double*)calloc(256 * 256 * 64, sizeof(double));
+	lC = (double*)calloc(256 * 256, sizeof(double));
+	for (n = 1; n != 256; ++n) {
+		double lgn = lgamma(n+1);
+		for (k = 1; k <= n; ++k)
+			lC[n<<8|k] = lgn - lgamma(k+1) - lgamma(n-k+1);
+	}
+	for (q = 1; q != 64; ++q) {
+		double e = pow(10.0, -q/10.0);
+		double le = log(e);
+		double le1 = log(1.0 - e);
+		for (n = 1; n <= 255; ++n) {
+			double *beta = ec->beta + (q<<16|n<<8);
+			sum1 = sum = 0.0;
+			for (k = n; k >= 0; --k, sum1 = sum) {
+				sum = sum1 + expl(lC[n<<8|k] + k*le + (n-k)*le1);
+				beta[k] = -10. / M_LN10 * logl(sum1 / sum);
+			}
+		}
+	}
+	// initialize ->lhet
+	ec->lhet = (double*)calloc(256 * 256, sizeof(double));
+	for (n = 0; n < 256; ++n)
+		for (k = 0; k < 256; ++k)
+			ec->lhet[n<<8|k] = lC[n<<8|k] - M_LN2 * n;
+	free(lC);
+	return ec;
+}
+
+errmod_t *errmod_init(float depcorr)
+{
+	errmod_t *em;
+	em = (errmod_t*)calloc(1, sizeof(errmod_t));
+	em->depcorr = depcorr;
+	em->coef = cal_coef(depcorr, 0.03);
+	return em;
+}
+
+void errmod_destroy(errmod_t *em)
+{
+	if (em == 0) return;
+	free(em->coef->lhet); free(em->coef->fk); free(em->coef->beta);
+	free(em->coef); free(em);
+}
+// qual:6, strand:1, base:4
+int errmod_cal(const errmod_t *em, int n, int m, uint16_t *bases, float *q)
+{
+	call_aux_t aux;
+	int i, j, k, w[32];
+
+	if (m > m) return -1;
+	memset(q, 0, m * m * sizeof(float));
+	if (n == 0) return 0;
+	// calculate aux.esum and aux.fsum
+	if (n > 255) { // then sample 255 bases
+		ks_shuffle(uint16_t, n, bases);
+		n = 255;
+	}
+	ks_introsort(uint16_t, n, bases);
+	memset(w, 0, 32 * sizeof(int));
+	memset(&aux, 0, sizeof(call_aux_t));
+	for (j = n - 1; j >= 0; --j) { // calculate esum and fsum
+		uint16_t b = bases[j];
+		int q = b>>5 < 4? 4 : b>>5;
+		if (q > 63) q = 63;
+		k = b&0x1f;
+		aux.fsum[k&0xf] += em->coef->fk[w[k]];
+		aux.bsum[k&0xf] += em->coef->fk[w[k]] * em->coef->beta[q<<16|n<<8|aux.c[k&0xf]];
+		++aux.c[k&0xf];
+		++w[k];
+	}
+	// generate likelihood
+	for (j = 0; j != m; ++j) {
+		float tmp1, tmp3;
+		int tmp2, bar_e;
+		// homozygous
+		for (k = 0, tmp1 = tmp3 = 0.0, tmp2 = 0; k != m; ++k) {
+			if (k == j) continue;
+			tmp1 += aux.bsum[k]; tmp2 += aux.c[k]; tmp3 += aux.fsum[k];
+		}
+		if (tmp2) {
+			bar_e = (int)(tmp1 / tmp3 + 0.499);
+			if (bar_e > 63) bar_e = 63;
+			q[j*m+j] = tmp1;
+		}
+		// heterozygous
+		for (k = j + 1; k < m; ++k) {
+			int cjk = aux.c[j] + aux.c[k];
+			for (i = 0, tmp2 = 0, tmp1 = tmp3 = 0.0; i < m; ++i) {
+				if (i == j || i == k) continue;
+				tmp1 += aux.bsum[i]; tmp2 += aux.c[i]; tmp3 += aux.fsum[i];
+			}
+			if (tmp2) {
+				bar_e = (int)(tmp1 / tmp3 + 0.499);
+				if (bar_e > 63) bar_e = 63;
+				q[j*m+k] = q[k*m+j] = -4.343 * em->coef->lhet[cjk<<8|aux.c[k]] + tmp1;
+			} else q[j*m+k] = q[k*m+j] = -4.343 * em->coef->lhet[cjk<<8|aux.c[k]]; // all the bases are either j or k
+		}
+		for (k = 0; k != m; ++k) if (q[j*m+k] < 0.0) q[j*m+k] = 0.0;
+	}
+	return 0;
+}