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evaluatePartialGenericSpecial.c
1058 lines (818 loc) · 27 KB
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evaluatePartialGenericSpecial.c
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/* RAxML-VI-HPC (version 2.2) a program for sequential and parallel estimation of phylogenetic trees
* Copyright August 2006 by Alexandros Stamatakis
*
* Partially derived from
* fastDNAml, a program for estimation of phylogenetic trees from sequences by Gary J. Olsen
*
* and
*
* Programs of the PHYLIP package by Joe Felsenstein.
* This program is free software; you may redistribute it and/or modify its
* under the terms of the GNU General Public License as published by the Free
* Software Foundation; either version 2 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.
*
*
* For any other enquiries send an Email to Alexandros Stamatakis
* Alexandros.Stamatakis@epfl.ch
*
* When publishing work that is based on the results from RAxML-VI-HPC please cite:
*
* Alexandros Stamatakis:"RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models".
* Bioinformatics 2006; doi: 10.1093/bioinformatics/btl446
*/
#ifndef WIN32
#include <unistd.h>
#endif
#include <math.h>
#include <time.h>
#include <stdlib.h>
#include <stdio.h>
#include <ctype.h>
#include <string.h>
#include "axml.h"
#ifdef __SIM_SSE3
#include <xmmintrin.h>
#include <pmmintrin.h>
#endif
#if defined(_OPTIMIZED_FUNCTIONS) && !defined(__MIC_NATIVE)
static inline void computeVectorGTRCATPROT(double *lVector, int *eVector, double ki, int i, double qz, double rz,
traversalInfo *ti, double *EIGN, double *EI, double *EV, double *tipVector,
unsigned char **yVector, int mxtips);
static double evaluatePartialGTRCATPROT(int i, double ki, int counter, traversalInfo *ti, double qz,
int w, double *EIGN, double *EI, double *EV,
double *tipVector, unsigned char **yVector,
int branchReference, int mxtips);
static inline void computeVectorGTRGAMMAPROT(double *lVector, int *eVector, double *gammaRates, int i, double qz, double rz,
traversalInfo *ti, double *EIGN, double *EI, double *EV, double *tipVector,
unsigned char **yVector, int mxtips);
static double evaluatePartialGTRGAMMAPROT(int i, int counter, traversalInfo *ti, double qz,
int w, double *EIGN, double *EI, double *EV,
double *tipVector, unsigned char **yVector,
double *gammaRates,
int branchReference, int mxtips);
static inline void computeVectorGTRCAT(double *lVector, int *eVector, double ki, int i, double qz, double rz,
traversalInfo *ti, double *EIGN, double *EI, double *EV, double *tipVector,
unsigned char **yVector, int mxtips);
static double evaluatePartialGTRCAT(int i, double ki, int counter, traversalInfo *ti, double qz,
int w, double *EIGN, double *EI, double *EV,
double *tipVector, unsigned char **yVector,
int branchReference, int mxtips);
static inline void computeVectorGTRCAT_BINARY(double *lVector, int *eVector, double ki, int i, double qz, double rz,
traversalInfo *ti, double *EIGN, double *EI, double *EV, double *tipVector,
unsigned char **yVector, int mxtips);
static double evaluatePartialGTRCAT_BINARY(int i, double ki, int counter, traversalInfo *ti, double qz,
int w, double *EIGN, double *EI, double *EV,
double *tipVector, unsigned char **yVector,
int branchReference, int mxtips);
#else
static inline void computeVectorCAT_FLEX(double *lVector, int *eVector, double ki, int i, double qz, double rz,
traversalInfo *ti, double *EIGN, double *EI, double *EV, double *tipVector,
unsigned char **yVector, int mxtips, const int states)
{
double
*d1 = (double *)malloc(sizeof(double) * states),
*d2 = (double *)malloc(sizeof(double) * states),
*x1px2 = (double *)malloc(sizeof(double) * states),
ump_x1,
ump_x2,
lz1,
lz2,
*x1,
*x2,
*x3;
int
scale,
j,
k,
pNumber = ti->pNumber,
rNumber = ti->rNumber,
qNumber = ti->qNumber;
x3 = &lVector[states * (pNumber - mxtips)];
switch(ti->tipCase)
{
case TIP_TIP:
x1 = &(tipVector[states * yVector[qNumber][i]]);
x2 = &(tipVector[states * yVector[rNumber][i]]);
break;
case TIP_INNER:
x1 = &(tipVector[states * yVector[qNumber][i]]);
x2 = &(lVector[states * (rNumber - mxtips)]);
break;
case INNER_INNER:
x1 = &(lVector[states * (qNumber - mxtips)]);
x2 = &(lVector[states * (rNumber - mxtips)]);
break;
default:
assert(0);
}
lz1 = qz * ki;
lz2 = rz * ki;
d1[0] = x1[0];
d2[0] = x2[0];
for(j = 1; j < states; j++)
{
d1[j] = x1[j] * EXP(EIGN[j] * lz1);
d2[j] = x2[j] * EXP(EIGN[j] * lz2);
}
for(j = 0; j < states; j++)
{
ump_x1 = 0.0;
ump_x2 = 0.0;
for(k = 0; k < states; k++)
{
ump_x1 += d1[k] * EI[j * states + k];
ump_x2 += d2[k] * EI[j * states + k];
}
x1px2[j] = ump_x1 * ump_x2;
}
for(j = 0; j < states; j++)
x3[j] = 0.0;
for(j = 0; j < states; j++)
for(k = 0; k < states; k++)
x3[k] += x1px2[j] * EV[states * j + k];
scale = 1;
for(j = 0; scale && (j < states); j++)
scale = ((x3[j] < minlikelihood) && (x3[j] > minusminlikelihood));
if(scale)
{
for(j = 0; j < states; j++)
x3[j] *= twotothe256;
*eVector = *eVector + 1;
}
free(d1);
free(d2);
free(x1px2);
return;
}
static double evaluatePartialCAT_FLEX(int i, double ki, int counter, traversalInfo *ti, double qz,
int w, double *EIGN, double *EI, double *EV,
double *tipVector, unsigned char **yVector,
int branchReference, int mxtips, const int states)
{
int
scale = 0,
k;
double
*lVector = (double *)malloc_aligned(sizeof(double) * states * mxtips),
*d = (double *)malloc_aligned(sizeof(double) * states),
lz,
term,
*x1,
*x2;
traversalInfo
*trav = &ti[0];
assert(isTip(trav->pNumber, mxtips));
x1 = &(tipVector[states * yVector[trav->pNumber][i]]);
for(k = 1; k < counter; k++)
{
double
qz = ti[k].qz[branchReference],
rz = ti[k].rz[branchReference];
qz = (qz > zmin) ? log(qz) : log(zmin);
rz = (rz > zmin) ? log(rz) : log(zmin);
computeVectorCAT_FLEX(lVector, &scale, ki, i, qz, rz, &ti[k],
EIGN, EI, EV,
tipVector, yVector, mxtips, states);
}
x2 = &lVector[states * (trav->qNumber - mxtips)];
assert(0 <= (trav->qNumber - mxtips) && (trav->qNumber - mxtips) < mxtips);
if(qz < zmin)
lz = zmin;
lz = log(qz);
lz *= ki;
d[0] = 1.0;
for(k = 1; k < states; k++)
d[k] = EXP (EIGN[k] * lz);
term = 0.0;
for(k = 0; k < states; k++)
term += x1[k] * x2[k] * d[k];
term = LOG(FABS(term)) + (scale * LOG(minlikelihood));
term = term * w;
free(lVector);
free(d);
return term;
}
#endif
double evaluatePartialGeneric (tree *tr, int i, double ki, int _model)
{
double result;
int
branchReference,
states = tr->partitionData[_model].states;
int
index;
index = i;
if(tr->numBranches > 1)
branchReference = _model;
else
branchReference = 0;
#ifndef _OPTIMIZED_FUNCTIONS
if(tr->rateHetModel == CAT)
result = evaluatePartialCAT_FLEX(index, ki, tr->td[0].count, tr->td[0].ti, tr->td[0].ti[0].qz[branchReference],
tr->partitionData[_model].wgt[index],
tr->partitionData[_model].EIGN,
tr->partitionData[_model].EI,
tr->partitionData[_model].EV,
tr->partitionData[_model].tipVector,
tr->partitionData[_model].yVector, branchReference, tr->mxtips, states);
else
/*
the per-site site likelihood function should only be called for the CAT model
under the GAMMA model this is required only for estimating per-site protein models
which has however been removed in this version of the code
*/
assert(0);
#elif defined(__MIC_NATIVE)
if (tr->rateHetModel == CAT)
result = evaluatePartialCAT_FLEX(index, ki, tr->td[0].count, tr->td[0].ti, tr->td[0].ti[0].qz[branchReference],
tr->partitionData[_model].wgt[index],
tr->partitionData[_model].EIGN,
tr->partitionData[_model].EI,
tr->partitionData[_model].EV,
tr->partitionData[_model].tipVector,
tr->partitionData[_model].yVector, branchReference, tr->mxtips, states);
else
assert(0);
#else
switch(states)
{
case 2:
assert(!tr->saveMemory);
assert(tr->rateHetModel == CAT);
result = evaluatePartialGTRCAT_BINARY(index, ki, tr->td[0].count, tr->td[0].ti, tr->td[0].ti[0].qz[branchReference],
tr->partitionData[_model].wgt[index],
tr->partitionData[_model].EIGN,
tr->partitionData[_model].EI,
tr->partitionData[_model].EV,
tr->partitionData[_model].tipVector,
tr->partitionData[_model].yVector, branchReference, tr->mxtips);
break;
case 4: /* DNA */
assert(tr->rateHetModel == CAT);
result = evaluatePartialGTRCAT(index, ki, tr->td[0].count, tr->td[0].ti, tr->td[0].ti[0].qz[branchReference],
tr->partitionData[_model].wgt[index],
tr->partitionData[_model].EIGN,
tr->partitionData[_model].EI,
tr->partitionData[_model].EV,
tr->partitionData[_model].tipVector,
tr->partitionData[_model].yVector, branchReference, tr->mxtips);
break;
case 20: /* proteins */
if(tr->rateHetModel == CAT)
result = evaluatePartialGTRCATPROT(index, ki, tr->td[0].count, tr->td[0].ti, tr->td[0].ti[0].qz[branchReference],
tr->partitionData[_model].wgt[index],
tr->partitionData[_model].EIGN,
tr->partitionData[_model].EI,
tr->partitionData[_model].EV,
tr->partitionData[_model].tipVector,
tr->partitionData[_model].yVector, branchReference, tr->mxtips);
else
result = evaluatePartialGTRGAMMAPROT(index, tr->td[0].count, tr->td[0].ti, tr->td[0].ti[0].qz[branchReference],
tr->partitionData[_model].wgt[index],
tr->partitionData[_model].EIGN,
tr->partitionData[_model].EI,
tr->partitionData[_model].EV,
tr->partitionData[_model].tipVector,
tr->partitionData[_model].yVector,
tr->partitionData[_model].gammaRates,
branchReference, tr->mxtips);
break;
default:
assert(0);
}
#endif
return result;
}
#ifdef _OPTIMIZED_FUNCTIONS
static inline void computeVectorGTRCAT_BINARY(double *lVector, int *eVector, double ki, int i, double qz, double rz,
traversalInfo *ti, double *EIGN, double *EI, double *EV, double *tipVector,
unsigned char **yVector, int mxtips)
{
double d1, d2, ump_x1, ump_x2, x1px2[2], lz1, lz2;
double *x1, *x2, *x3;
int
j, k,
pNumber = ti->pNumber,
rNumber = ti->rNumber,
qNumber = ti->qNumber;
x3 = &lVector[2 * (pNumber - mxtips)];
switch(ti->tipCase)
{
case TIP_TIP:
x1 = &(tipVector[2 * yVector[qNumber][i]]);
x2 = &(tipVector[2 * yVector[rNumber][i]]);
break;
case TIP_INNER:
x1 = &(tipVector[2 * yVector[qNumber][i]]);
x2 = &lVector[2 * (rNumber - mxtips)];
break;
case INNER_INNER:
x1 = &lVector[2 * (qNumber - mxtips)];
x2 = &lVector[2 * (rNumber - mxtips)];
break;
default:
assert(0);
}
lz1 = qz * ki;
lz2 = rz * ki;
d1 = x1[1] * EXP(EIGN[1] * lz1);
d2 = x2[1] * EXP(EIGN[1] * lz2);
for(j = 0; j < 2; j++)
{
ump_x1 = x1[0];
ump_x2 = x2[0];
ump_x1 += d1 * EI[j * 2 + 1];
ump_x2 += d2 * EI[j * 2 + 1];
x1px2[j] = ump_x1 * ump_x2;
}
for(j = 0; j < 2; j++)
x3[j] = 0.0;
for(j = 0; j < 2; j++)
for(k = 0; k < 2; k++)
x3[k] += x1px2[j] * EV[2 * j + k];
if (x3[0] < minlikelihood && x3[0] > minusminlikelihood &&
x3[1] < minlikelihood && x3[1] > minusminlikelihood
)
{
x3[0] *= twotothe256;
x3[1] *= twotothe256;
*eVector = *eVector + 1;
}
return;
}
static double evaluatePartialGTRCAT_BINARY(int i, double ki, int counter, traversalInfo *ti, double qz,
int w, double *EIGN, double *EI, double *EV,
double *tipVector, unsigned char **yVector,
int branchReference, int mxtips)
{
double lz, term;
double d;
double *x1, *x2;
int scale = 0, k;
double *lVector = (double *)malloc(sizeof(double) * 2 * mxtips);
traversalInfo *trav = &ti[0];
assert(isTip(trav->pNumber, mxtips));
x1 = &(tipVector[2 * yVector[trav->pNumber][i]]);
for(k = 1; k < counter; k++)
{
double
qz = ti[k].qz[branchReference],
rz = ti[k].rz[branchReference];
qz = (qz > zmin) ? log(qz) : log(zmin);
rz = (rz > zmin) ? log(rz) : log(zmin);
computeVectorGTRCAT_BINARY(lVector, &scale, ki, i, qz, rz, &ti[k],
EIGN, EI, EV,
tipVector, yVector, mxtips);
}
x2 = &lVector[2 * (trav->qNumber - mxtips)];
assert(0 <= (trav->qNumber - mxtips) && (trav->qNumber - mxtips) < mxtips);
if(qz < zmin)
lz = zmin;
lz = log(qz);
lz *= ki;
d = EXP(EIGN[1] * lz);
term = x1[0] * x2[0];
term += x1[1] * x2[1] * d;
term = LOG(FABS(term)) + (scale * LOG(minlikelihood));
term = term * w;
free(lVector);
return term;
}
static inline void computeVectorGTRCATPROT(double *lVector, int *eVector, double ki, int i, double qz, double rz,
traversalInfo *ti, double *EIGN, double *EI, double *EV, double *tipVector,
unsigned char **yVector, int mxtips)
{
double *x1, *x2, *x3;
int
pNumber = ti->pNumber,
rNumber = ti->rNumber,
qNumber = ti->qNumber;
x3 = &(lVector[20 * (pNumber - mxtips)]);
switch(ti->tipCase)
{
case TIP_TIP:
x1 = &(tipVector[20 * yVector[qNumber][i]]);
x2 = &(tipVector[20 * yVector[rNumber][i]]);
break;
case TIP_INNER:
x1 = &(tipVector[20 * yVector[qNumber][i]]);
x2 = &( lVector[20 * (rNumber - mxtips)]);
break;
case INNER_INNER:
x1 = &(lVector[20 * (qNumber - mxtips)]);
x2 = &(lVector[20 * (rNumber - mxtips)]);
break;
default:
assert(0);
}
{
double
e1[20] __attribute__ ((aligned (BYTE_ALIGNMENT))),
e2[20] __attribute__ ((aligned (BYTE_ALIGNMENT))),
d1[20] __attribute__ ((aligned (BYTE_ALIGNMENT))),
d2[20] __attribute__ ((aligned (BYTE_ALIGNMENT))),
lz1,
lz2;
int
l,
k,
scale;
lz1 = qz * ki;
lz2 = rz * ki;
e1[0] = 1.0;
e2[0] = 1.0;
for(l = 1; l < 20; l++)
{
e1[l] = EXP(EIGN[l] * lz1);
e2[l] = EXP(EIGN[l] * lz2);
}
for(l = 0; l < 20; l+=2)
{
__m128d d1v = _mm_mul_pd(_mm_load_pd(&x1[l]), _mm_load_pd(&e1[l]));
__m128d d2v = _mm_mul_pd(_mm_load_pd(&x2[l]), _mm_load_pd(&e2[l]));
_mm_store_pd(&d1[l], d1v);
_mm_store_pd(&d2[l], d2v);
}
__m128d zero = _mm_setzero_pd();
for(l = 0; l < 20; l+=2)
_mm_store_pd(&x3[l], zero);
for(l = 0; l < 20; l++)
{
double *ev = &EV[l * 20];
__m128d ump_x1v = _mm_setzero_pd();
__m128d ump_x2v = _mm_setzero_pd();
__m128d x1px2v;
for(k = 0; k < 20; k+=2)
{
__m128d eiv = _mm_load_pd(&EI[20 * l + k]);
__m128d d1v = _mm_load_pd(&d1[k]);
__m128d d2v = _mm_load_pd(&d2[k]);
ump_x1v = _mm_add_pd(ump_x1v, _mm_mul_pd(d1v, eiv));
ump_x2v = _mm_add_pd(ump_x2v, _mm_mul_pd(d2v, eiv));
}
ump_x1v = _mm_hadd_pd(ump_x1v, ump_x1v);
ump_x2v = _mm_hadd_pd(ump_x2v, ump_x2v);
x1px2v = _mm_mul_pd(ump_x1v, ump_x2v);
for(k = 0; k < 20; k+=2)
{
__m128d ex3v = _mm_load_pd(&x3[k]);
__m128d EVV = _mm_load_pd(&ev[k]);
ex3v = _mm_add_pd(ex3v, _mm_mul_pd(x1px2v, EVV));
_mm_store_pd(&x3[k], ex3v);
}
}
scale = 1;
for(l = 0; scale && (l < 20); l++)
scale = ((x3[l] < minlikelihood) && (x3[l] > minusminlikelihood));
if(scale)
{
__m128d twoto = _mm_set_pd(twotothe256, twotothe256);
for(l = 0; l < 20; l+=2)
{
__m128d ex3v = _mm_mul_pd(_mm_load_pd(&x3[l]),twoto);
_mm_store_pd(&x3[l], ex3v);
}
*eVector = *eVector + 1;
}
return;
}
}
static double evaluatePartialGTRCATPROT(int i, double ki, int counter, traversalInfo *ti, double qz,
int w, double *EIGN, double *EI, double *EV,
double *tipVector, unsigned char **yVector,
int branchReference, int mxtips)
{
double lz, term;
double d[20];
double *x1, *x2;
int scale = 0, k, l;
double
*lVector = (double *)malloc_aligned(sizeof(double) * 20 * mxtips),
myEI[400] __attribute__ ((aligned (BYTE_ALIGNMENT)));
traversalInfo *trav = &ti[0];
for(k = 0; k < 20; k++)
{
for(l = 0; l < 20; l++)
myEI[k * 20 + l] = EI[k * 20 + l];
}
assert(isTip(trav->pNumber, mxtips));
x1 = &(tipVector[20 * yVector[trav->pNumber][i]]);
for(k = 1; k < counter; k++)
{
double
qz = ti[k].qz[branchReference],
rz = ti[k].rz[branchReference];
qz = (qz > zmin) ? log(qz) : log(zmin);
rz = (rz > zmin) ? log(rz) : log(zmin);
computeVectorGTRCATPROT(lVector, &scale, ki, i, qz, rz,
&ti[k], EIGN, myEI, EV,
tipVector, yVector, mxtips);
}
x2 = &lVector[20 * (trav->qNumber - mxtips)];
assert(0 <= (trav->qNumber - mxtips) && (trav->qNumber - mxtips) < mxtips);
if(qz < zmin)
lz = zmin;
lz = log(qz);
lz *= ki;
d[0] = 1.0;
for(l = 1; l < 20; l++)
d[l] = EXP (EIGN[l] * lz);
term = 0.0;
for(l = 0; l < 20; l++)
term += x1[l] * x2[l] * d[l];
term = LOG(FABS(term)) + (scale * LOG(minlikelihood));
term = term * w;
free(lVector);
return term;
}
static inline void computeVectorGTRGAMMAPROT(double *lVector, int *eVector, double *gammaRates, int i, double qz, double rz,
traversalInfo *ti, double *EIGN, double *EI, double *EV, double *tipVector,
unsigned char **yVector, int mxtips)
{
double
*x1,
*x2,
*x3;
int
s,
pNumber = ti->pNumber,
rNumber = ti->rNumber,
qNumber = ti->qNumber,
index1[4],
index2[4];
x3 = &(lVector[80 * (pNumber - mxtips)]);
switch(ti->tipCase)
{
case TIP_TIP:
x1 = &(tipVector[20 * yVector[qNumber][i]]);
x2 = &(tipVector[20 * yVector[rNumber][i]]);
for(s = 0; s < 4; s++)
{
index1[s] = 0;
index2[s] = 0;
}
break;
case TIP_INNER:
x1 = &(tipVector[20 * yVector[qNumber][i]]);
x2 = &( lVector[80 * (rNumber - mxtips)]);
for(s = 0; s < 4; s++)
index1[s] = 0;
for(s = 0; s < 4; s++)
index2[s] = s;
break;
case INNER_INNER:
x1 = &(lVector[80 * (qNumber - mxtips)]);
x2 = &(lVector[80 * (rNumber - mxtips)]);
for(s = 0; s < 4; s++)
{
index1[s] = s;
index2[s] = s;
}
break;
default:
assert(0);
}
{
double
e1[20] __attribute__ ((aligned (BYTE_ALIGNMENT))),
e2[20] __attribute__ ((aligned (BYTE_ALIGNMENT))),
d1[20] __attribute__ ((aligned (BYTE_ALIGNMENT))),
d2[20] __attribute__ ((aligned (BYTE_ALIGNMENT))),
lz1, lz2;
int
l,
k,
scale,
j;
for(j = 0; j < 4; j++)
{
lz1 = qz * gammaRates[j];
lz2 = rz * gammaRates[j];
e1[0] = 1.0;
e2[0] = 1.0;
for(l = 1; l < 20; l++)
{
e1[l] = EXP(EIGN[l] * lz1);
e2[l] = EXP(EIGN[l] * lz2);
}
for(l = 0; l < 20; l+=2)
{
__m128d d1v = _mm_mul_pd(_mm_load_pd(&x1[20 * index1[j] + l]), _mm_load_pd(&e1[l]));
__m128d d2v = _mm_mul_pd(_mm_load_pd(&x2[20 * index2[j] + l]), _mm_load_pd(&e2[l]));
_mm_store_pd(&d1[l], d1v);
_mm_store_pd(&d2[l], d2v);
}
__m128d zero = _mm_setzero_pd();
for(l = 0; l < 20; l+=2)
_mm_store_pd(&x3[j * 20 + l], zero);
for(l = 0; l < 20; l++)
{
double *ev = &EV[l * 20];
__m128d ump_x1v = _mm_setzero_pd();
__m128d ump_x2v = _mm_setzero_pd();
__m128d x1px2v;
for(k = 0; k < 20; k+=2)
{
__m128d eiv = _mm_load_pd(&EI[20 * l + k]);
__m128d d1v = _mm_load_pd(&d1[k]);
__m128d d2v = _mm_load_pd(&d2[k]);
ump_x1v = _mm_add_pd(ump_x1v, _mm_mul_pd(d1v, eiv));
ump_x2v = _mm_add_pd(ump_x2v, _mm_mul_pd(d2v, eiv));
}
ump_x1v = _mm_hadd_pd(ump_x1v, ump_x1v);
ump_x2v = _mm_hadd_pd(ump_x2v, ump_x2v);
x1px2v = _mm_mul_pd(ump_x1v, ump_x2v);
for(k = 0; k < 20; k+=2)
{
__m128d ex3v = _mm_load_pd(&x3[j * 20 + k]);
__m128d EVV = _mm_load_pd(&ev[k]);
ex3v = _mm_add_pd(ex3v, _mm_mul_pd(x1px2v, EVV));
_mm_store_pd(&x3[j * 20 + k], ex3v);
}
}
}
scale = 1;
for(l = 0; scale && (l < 80); l++)
scale = ((x3[l] < minlikelihood) && (x3[l] > minusminlikelihood));
if(scale)
{
__m128d twoto = _mm_set_pd(twotothe256, twotothe256);
for(l = 0; l < 80; l+=2)
{
__m128d ex3v = _mm_mul_pd(_mm_load_pd(&x3[l]),twoto);
_mm_store_pd(&x3[l], ex3v);
}
*eVector = *eVector + 1;
}
return;
}
}
static double evaluatePartialGTRGAMMAPROT(int i, int counter, traversalInfo *ti, double qz,
int w, double *EIGN, double *EI, double *EV,
double *tipVector, unsigned char **yVector,
double *gammaRates,
int branchReference, int mxtips)
{
double lz, term;
double d[80];
double *x1, *x2;
int scale = 0, k, l, j;
double
*lVector = (double *)malloc_aligned(sizeof(double) * 80 * mxtips),
myEI[400] __attribute__ ((aligned (BYTE_ALIGNMENT)));
traversalInfo
*trav = &ti[0];
for(k = 0; k < 20; k++)
{
for(l = 0; l < 20; l++)
myEI[k * 20 + l] = EI[k * 20 + l];
}
assert(isTip(trav->pNumber, mxtips));
x1 = &(tipVector[20 * yVector[trav->pNumber][i]]);
for(k = 1; k < counter; k++)
{
double
qz = ti[k].qz[branchReference],
rz = ti[k].rz[branchReference];
qz = (qz > zmin) ? log(qz) : log(zmin);
rz = (rz > zmin) ? log(rz) : log(zmin);
computeVectorGTRGAMMAPROT(lVector, &scale, gammaRates, i, qz, rz,
&ti[k], EIGN, myEI, EV,
tipVector, yVector, mxtips);
}
x2 = &lVector[80 * (trav->qNumber - mxtips)];
assert(0 <= (trav->qNumber - mxtips) && (trav->qNumber - mxtips) < mxtips);
if(qz < zmin)
lz = zmin;
lz = log(qz);
for(j = 0; j < 4; j++)
{
d[20 * j] = 1.0;
for(l = 1; l < 20; l++)
d[20 * j + l] = EXP(EIGN[l] * lz * gammaRates[j]);
}
for(j = 0, term = 0.0; j < 4; j++)
{
for(l = 0; l < 20; l++)
term += x1[l] * x2[20 * j + l] * d[j * 20 + l];
}
term = LOG(0.25 * FABS(term)) + (scale * LOG(minlikelihood));
term = term * w;
free(lVector);
return term;
}
static inline void computeVectorGTRCAT(double *lVector, int *eVector, double ki, int i, double qz, double rz,
traversalInfo *ti, double *EIGN, double *EI, double *EV, double *tipVector,
unsigned char **yVector, int mxtips)
{
double d1[3], d2[3], ump_x1, ump_x2, x1px2[4], lz1, lz2;
double *x1, *x2, *x3;
int j, k,
pNumber = ti->pNumber,
rNumber = ti->rNumber,
qNumber = ti->qNumber;
x3 = &lVector[4 * (pNumber - mxtips)];
switch(ti->tipCase)
{
case TIP_TIP:
x1 = &(tipVector[4 * yVector[qNumber][i]]);
x2 = &(tipVector[4 * yVector[rNumber][i]]);
break;
case TIP_INNER:
x1 = &(tipVector[4 * yVector[qNumber][i]]);
x2 = &lVector[4 * (rNumber - mxtips)];
break;
case INNER_INNER:
x1 = &lVector[4 * (qNumber - mxtips)];
x2 = &lVector[4 * (rNumber - mxtips)];
break;
default:
assert(0);
}
lz1 = qz * ki;
lz2 = rz * ki;
for(j = 0; j < 3; j++)
{
d1[j] =
x1[j + 1] *
EXP(EIGN[j + 1] * lz1);
d2[j] = x2[j + 1] * EXP(EIGN[j + 1] * lz2);
}
for(j = 0; j < 4; j++)
{
ump_x1 = x1[0];
ump_x2 = x2[0];
for(k = 0; k < 3; k++)
{
ump_x1 += d1[k] * EI[j * 4 + k + 1];
ump_x2 += d2[k] * EI[j * 4 + k + 1];
}
x1px2[j] = ump_x1 * ump_x2;
}
for(j = 0; j < 4; j++)
x3[j] = 0.0;
for(j = 0; j < 4; j++)
for(k = 0; k < 4; k++)
x3[k] += x1px2[j] * EV[4 * j + k];
if (x3[0] < minlikelihood && x3[0] > minusminlikelihood &&
x3[1] < minlikelihood && x3[1] > minusminlikelihood &&
x3[2] < minlikelihood && x3[2] > minusminlikelihood &&
x3[3] < minlikelihood && x3[3] > minusminlikelihood)
{
x3[0] *= twotothe256;
x3[1] *= twotothe256;
x3[2] *= twotothe256;
x3[3] *= twotothe256;
*eVector = *eVector + 1;
}
return;
}
static double evaluatePartialGTRCAT(int i, double ki, int counter, traversalInfo *ti, double qz,
int w, double *EIGN, double *EI, double *EV,
double *tipVector, unsigned char **yVector,