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newviewGenericSpecial.c
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newviewGenericSpecial.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 <stdint.h>
#include <limits.h>
#include "axml.h"
#ifdef __SIM_SSE3
#include <stdint.h>
#ifdef __x86_64__
#include <xmmintrin.h>
#include <pmmintrin.h>
#elif __aarch64__
#include "sse2neon.h"
#endif
const union __attribute__ ((aligned (BYTE_ALIGNMENT)))
{
uint64_t i[2];
__m128d m;
} absMask = {{0x7fffffffffffffffULL , 0x7fffffffffffffffULL }};
#endif
#ifdef _USE_PTHREADS
#include <pthread.h>
extern volatile int NumberOfThreads;
extern pthread_mutex_t mutex;
#endif
extern const unsigned int mask32[32];
boolean isGap(unsigned int *x, int pos)
{
return (x[pos / 32] & mask32[pos % 32]);
}
boolean noGap(unsigned int *x, int pos)
{
return (!(x[pos / 32] & mask32[pos % 32]));
}
void makeP_Flex(double z1, double z2, double *rptr, double *EI, double *EIGN, int numberOfCategories, double *left, double *right, const int numStates)
{
int
i,
j,
k;
const int
rates = numStates - 1,
statesSquare = numStates * numStates;
double
lz1[64],
lz2[64],
d1[64],
d2[64];
assert(numStates <= 64);
for(i = 0; i < rates; i++)
{
lz1[i] = EIGN[i] * z1;
lz2[i] = EIGN[i] * z2;
}
for(i = 0; i < numberOfCategories; i++)
{
for(j = 0; j < rates; j++)
{
d1[j] = EXP (rptr[i] * lz1[j]);
d2[j] = EXP (rptr[i] * lz2[j]);
}
for(j = 0; j < numStates; j++)
{
left[statesSquare * i + numStates * j] = 1.0;
right[statesSquare * i + numStates * j] = 1.0;
for(k = 1; k < numStates; k++)
{
left[statesSquare * i + numStates * j + k] = d1[k-1] * EI[rates * j + (k-1)];
right[statesSquare * i + numStates * j + k] = d2[k-1] * EI[rates * j + (k-1)];
}
}
}
}
#ifdef _HET
static void makeP_FlexHet(double z1, double z2, double *rptr, double *EI_1, double *EIGN_1,
double *EI_2, double *EIGN_2, int numberOfCategories, double *left, double *right, const int numStates)
{
int
i,
j,
k;
const int
rates = numStates - 1,
statesSquare = numStates * numStates;
double
lz1[64],
lz2[64],
d1[64],
d2[64];
assert(numStates <= 64);
for(i = 0; i < rates; i++)
{
lz1[i] = EIGN_1[i] * z1;
lz2[i] = EIGN_2[i] * z2;
}
for(i = 0; i < numberOfCategories; i++)
{
for(j = 0; j < rates; j++)
{
d1[j] = EXP (rptr[i] * lz1[j]);
d2[j] = EXP (rptr[i] * lz2[j]);
}
for(j = 0; j < numStates; j++)
{
left[statesSquare * i + numStates * j] = 1.0;
right[statesSquare * i + numStates * j] = 1.0;
for(k = 1; k < numStates; k++)
{
left[statesSquare * i + numStates * j + k] = d1[k-1] * EI_1[rates * j + (k-1)];
right[statesSquare * i + numStates * j + k] = d2[k-1] * EI_2[rates * j + (k-1)];
}
}
}
}
#endif
void makeP_FlexLG4(double z1, double z2, double *rptr, double *EI[4], double *EIGN[4], int numberOfCategories, double *left, double *right, const int numStates)
{
int
i,
j,
k;
const int
rates = numStates - 1,
statesSquare = numStates * numStates;
double
d1[64],
d2[64];
assert(numStates <= 64);
for(i = 0; i < numberOfCategories; i++)
{
for(j = 0; j < rates; j++)
{
d1[j] = EXP (rptr[i] * EIGN[i][j] * z1);
d2[j] = EXP (rptr[i] * EIGN[i][j] * z2);
}
for(j = 0; j < numStates; j++)
{
left[statesSquare * i + numStates * j] = 1.0;
right[statesSquare * i + numStates * j] = 1.0;
for(k = 1; k < numStates; k++)
{
left[statesSquare * i + numStates * j + k] = d1[k-1] * EI[i][rates * j + (k-1)];
right[statesSquare * i + numStates * j + k] = d2[k-1] * EI[i][rates * j + (k-1)];
}
}
}
}
static void newviewFlexCat(int tipCase, double *extEV,
int *cptr,
double *x1, double *x2, double *x3, double *tipVector,
int *ex3, unsigned char *tipX1, unsigned char *tipX2,
int n, double *left, double *right, int *wgt, int *scalerIncrement, const boolean useFastScaling, const int numStates)
{
double
*le, *ri, *v, *vl, *vr,
ump_x1, ump_x2, x1px2;
int i, l, j, scale, addScale = 0;
const int
statesSquare = numStates * numStates;
switch(tipCase)
{
case TIP_TIP:
{
for (i = 0; i < n; i++)
{
le = &left[cptr[i] * statesSquare];
ri = &right[cptr[i] * statesSquare];
vl = &(tipVector[numStates * tipX1[i]]);
vr = &(tipVector[numStates * tipX2[i]]);
v = &x3[numStates * i];
for(l = 0; l < numStates; l++)
v[l] = 0.0;
for(l = 0; l < numStates; l++)
{
ump_x1 = 0.0;
ump_x2 = 0.0;
for(j = 0; j < numStates; j++)
{
ump_x1 += vl[j] * le[l * numStates + j];
ump_x2 += vr[j] * ri[l * numStates + j];
}
x1px2 = ump_x1 * ump_x2;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[l * numStates + j];
}
}
}
break;
case TIP_INNER:
{
for (i = 0; i < n; i++)
{
le = &left[cptr[i] * statesSquare];
ri = &right[cptr[i] * statesSquare];
vl = &(tipVector[numStates * tipX1[i]]);
vr = &x2[numStates * i];
v = &x3[numStates * i];
for(l = 0; l < numStates; l++)
v[l] = 0.0;
for(l = 0; l < numStates; l++)
{
ump_x1 = 0.0;
ump_x2 = 0.0;
for(j = 0; j < numStates; j++)
{
ump_x1 += vl[j] * le[l * numStates + j];
ump_x2 += vr[j] * ri[l * numStates + j];
}
x1px2 = ump_x1 * ump_x2;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[l * numStates + j];
}
scale = 1;
for(l = 0; scale && (l < numStates); l++)
scale = ((v[l] < minlikelihood) && (v[l] > minusminlikelihood));
if(scale)
{
for(l = 0; l < numStates; l++)
v[l] *= twotothe256;
if(useFastScaling)
addScale += wgt[i];
else
ex3[i] += 1;
}
}
}
break;
case INNER_INNER:
for(i = 0; i < n; i++)
{
le = &left[cptr[i] * statesSquare];
ri = &right[cptr[i] * statesSquare];
vl = &x1[numStates * i];
vr = &x2[numStates * i];
v = &x3[numStates * i];
for(l = 0; l < numStates; l++)
v[l] = 0.0;
for(l = 0; l < numStates; l++)
{
ump_x1 = 0.0;
ump_x2 = 0.0;
for(j = 0; j < numStates; j++)
{
ump_x1 += vl[j] * le[l * numStates + j];
ump_x2 += vr[j] * ri[l * numStates + j];
}
x1px2 = ump_x1 * ump_x2;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[l * numStates + j];
}
scale = 1;
for(l = 0; scale && (l < numStates); l++)
scale = ((v[l] < minlikelihood) && (v[l] > minusminlikelihood));
if(scale)
{
for(l = 0; l < numStates; l++)
v[l] *= twotothe256;
if(useFastScaling)
addScale += wgt[i];
else
ex3[i] += 1;
}
}
break;
default:
assert(0);
}
if(useFastScaling)
*scalerIncrement = addScale;
}
static void newviewFlexGamma(int tipCase,
double *x1, double *x2, double *x3, double *extEV, double *tipVector,
int *ex3, unsigned char *tipX1, unsigned char *tipX2,
int n, double *left, double *right, int *wgt, int *scalerIncrement, const boolean useFastScaling,
const int numStates)
{
double *v;
double x1px2;
int i, j, l, k, scale, addScale = 0;
double *vl, *vr, al, ar;
const int
statesSquare = numStates * numStates,
gammaStates = 4 * numStates;
switch(tipCase)
{
case TIP_TIP:
{
for(i = 0; i < n; i++)
{
for(k = 0; k < 4; k++)
{
vl = &(tipVector[numStates * tipX1[i]]);
vr = &(tipVector[numStates * tipX2[i]]);
v = &(x3[gammaStates * i + numStates * k]);
for(l = 0; l < numStates; l++)
v[l] = 0;
for(l = 0; l < numStates; l++)
{
al = 0.0;
ar = 0.0;
for(j = 0; j < numStates; j++)
{
al += vl[j] * left[k * statesSquare + l * numStates + j];
ar += vr[j] * right[k * statesSquare + l * numStates + j];
}
x1px2 = al * ar;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[numStates * l + j];
}
}
}
}
break;
case TIP_INNER:
{
for (i = 0; i < n; i++)
{
for(k = 0; k < 4; k++)
{
vl = &(tipVector[numStates * tipX1[i]]);
vr = &(x2[gammaStates * i + numStates * k]);
v = &(x3[gammaStates * i + numStates * k]);
for(l = 0; l < numStates; l++)
v[l] = 0;
for(l = 0; l < numStates; l++)
{
al = 0.0;
ar = 0.0;
for(j = 0; j < numStates; j++)
{
al += vl[j] * left[k * statesSquare + l * numStates + j];
ar += vr[j] * right[k * statesSquare + l * numStates + j];
}
x1px2 = al * ar;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[numStates * l + j];
}
}
v = &x3[gammaStates * i];
scale = 1;
for(l = 0; scale && (l < gammaStates); l++)
scale = (ABS(v[l]) < minlikelihood);
if(scale)
{
for(l = 0; l < gammaStates; l++)
v[l] *= twotothe256;
if(useFastScaling)
addScale += wgt[i];
else
ex3[i] += 1;
}
}
}
break;
case INNER_INNER:
for (i = 0; i < n; i++)
{
for(k = 0; k < 4; k++)
{
vl = &(x1[gammaStates * i + numStates * k]);
vr = &(x2[gammaStates * i + numStates * k]);
v = &(x3[gammaStates * i + numStates * k]);
for(l = 0; l < numStates; l++)
v[l] = 0;
for(l = 0; l < numStates; l++)
{
al = 0.0;
ar = 0.0;
for(j = 0; j < numStates; j++)
{
al += vl[j] * left[k * statesSquare + l * numStates + j];
ar += vr[j] * right[k * statesSquare + l * numStates + j];
}
x1px2 = al * ar;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[numStates * l + j];
}
}
v = &(x3[gammaStates * i]);
scale = 1;
for(l = 0; scale && (l < gammaStates); l++)
scale = ((ABS(v[l]) < minlikelihood));
if (scale)
{
for(l = 0; l < gammaStates; l++)
v[l] *= twotothe256;
if(useFastScaling)
addScale += wgt[i];
else
ex3[i] += 1;
}
}
break;
default:
assert(0);
}
if(useFastScaling)
*scalerIncrement = addScale;
}
static void newviewAscCat(int tipCase,
double *x1, double *x2, double *x3, double *extEV, double *tipVector,
int *ex3,
const int n, double *left, double *right,
const int numStates, int dataType, const int qNumber, const int rNumber, int maxtips)
{
double
*le, *ri, *v, *vl, *vr,
ump_x1, ump_x2, x1px2;
int
i, l, j, scale;
switch(tipCase)
{
case TIP_TIP:
{
unsigned char
tip1[32],
tip2[32];
ascertainmentBiasSequence(tip1, numStates, dataType, qNumber);
ascertainmentBiasSequence(tip2, numStates, dataType, rNumber);
assert(qNumber <= maxtips && rNumber <= maxtips);
for (i = 0; i < n; i++)
{
le = &left[0];
ri = &right[0];
vl = &(tipVector[numStates * tip1[i]]);
vr = &(tipVector[numStates * tip2[i]]);
v = &x3[numStates * i];
for(l = 0; l < numStates; l++)
v[l] = 0.0;
for(l = 0; l < numStates; l++)
{
ump_x1 = 0.0;
ump_x2 = 0.0;
for(j = 0; j < numStates; j++)
{
ump_x1 += vl[j] * le[l * numStates + j];
ump_x2 += vr[j] * ri[l * numStates + j];
}
x1px2 = ump_x1 * ump_x2;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[l * numStates + j];
}
}
}
break;
case TIP_INNER:
{
unsigned char
tip[32];
if(rNumber <= maxtips)
ascertainmentBiasSequence(tip, numStates, dataType, rNumber);
else
ascertainmentBiasSequence(tip, numStates, dataType, qNumber);
for (i = 0; i < n; i++)
{
le = &left[0];
ri = &right[0];
vl = &(tipVector[numStates * tip[i]]);
vr = &x2[numStates * i];
v = &x3[numStates * i];
for(l = 0; l < numStates; l++)
v[l] = 0.0;
for(l = 0; l < numStates; l++)
{
ump_x1 = 0.0;
ump_x2 = 0.0;
for(j = 0; j < numStates; j++)
{
ump_x1 += vl[j] * le[l * numStates + j];
ump_x2 += vr[j] * ri[l * numStates + j];
}
x1px2 = ump_x1 * ump_x2;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[l * numStates + j];
}
scale = 1;
for(l = 0; scale && (l < numStates); l++)
scale = ((v[l] < minlikelihood) && (v[l] > minusminlikelihood));
if(scale)
{
for(l = 0; l < numStates; l++)
v[l] *= twotothe256;
ex3[i] += 1;
}
}
}
break;
case INNER_INNER:
for(i = 0; i < n; i++)
{
le = &left[0];
ri = &right[0];
vl = &x1[numStates * i];
vr = &x2[numStates * i];
v = &x3[numStates * i];
for(l = 0; l < numStates; l++)
v[l] = 0.0;
for(l = 0; l < numStates; l++)
{
ump_x1 = 0.0;
ump_x2 = 0.0;
for(j = 0; j < numStates; j++)
{
ump_x1 += vl[j] * le[l * numStates + j];
ump_x2 += vr[j] * ri[l * numStates + j];
}
x1px2 = ump_x1 * ump_x2;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[l * numStates + j];
}
scale = 1;
for(l = 0; scale && (l < numStates); l++)
scale = ((v[l] < minlikelihood) && (v[l] > minusminlikelihood));
if(scale)
{
for(l = 0; l < numStates; l++)
v[l] *= twotothe256;
ex3[i] += 1;
}
}
break;
default:
assert(0);
}
}
static void newviewAscGamma(int tipCase,
double *x1, double *x2, double *x3, double *extEV, double *tipVector,
int *ex3,
const int n, double *left, double *right,
const int numStates, int dataType, const int qNumber, const int rNumber, int maxtips)
{
int
i, j, l, k, scale;
const int
statesSquare = numStates * numStates,
gammaStates = 4 * numStates;
double
*vl, *vr, al, ar, *v, x1px2;
switch(tipCase)
{
case TIP_TIP:
{
unsigned char
tip1[32],
tip2[32];
ascertainmentBiasSequence(tip1, numStates, dataType, qNumber);
ascertainmentBiasSequence(tip2, numStates, dataType, rNumber);
assert(qNumber <= maxtips && rNumber <= maxtips);
for(i = 0; i < n; i++)
{
for(k = 0; k < 4; k++)
{
vl = &(tipVector[numStates * tip1[i]]);
vr = &(tipVector[numStates * tip2[i]]);
v = &(x3[gammaStates * i + numStates * k]);
for(l = 0; l < numStates; l++)
v[l] = 0;
for(l = 0; l < numStates; l++)
{
al = 0.0;
ar = 0.0;
for(j = 0; j < numStates; j++)
{
al += vl[j] * left[k * statesSquare + l * numStates + j];
ar += vr[j] * right[k * statesSquare + l * numStates + j];
}
x1px2 = al * ar;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[numStates * l + j];
}
}
}
}
break;
case TIP_INNER:
{
unsigned char
tip[32];
if(rNumber <= maxtips)
ascertainmentBiasSequence(tip, numStates, dataType, rNumber);
else
ascertainmentBiasSequence(tip, numStates, dataType, qNumber);
for (i = 0; i < n; i++)
{
for(k = 0; k < 4; k++)
{
vl = &(tipVector[numStates * tip[i]]);
vr = &(x2[gammaStates * i + numStates * k]);
v = &(x3[gammaStates * i + numStates * k]);
for(l = 0; l < numStates; l++)
v[l] = 0;
for(l = 0; l < numStates; l++)
{
al = 0.0;
ar = 0.0;
for(j = 0; j < numStates; j++)
{
al += vl[j] * left[k * statesSquare + l * numStates + j];
ar += vr[j] * right[k * statesSquare + l * numStates + j];
}
x1px2 = al * ar;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[numStates * l + j];
}
}
v = &x3[gammaStates * i];
scale = 1;
for(l = 0; scale && (l < gammaStates); l++)
scale = (ABS(v[l]) < minlikelihood);
if(scale)
{
for(l = 0; l < gammaStates; l++)
v[l] *= twotothe256;
ex3[i] += 1;
}
}
}
break;
case INNER_INNER:
for (i = 0; i < n; i++)
{
for(k = 0; k < 4; k++)
{
vl = &(x1[gammaStates * i + numStates * k]);
vr = &(x2[gammaStates * i + numStates * k]);
v = &(x3[gammaStates * i + numStates * k]);
for(l = 0; l < numStates; l++)
v[l] = 0;
for(l = 0; l < numStates; l++)
{
al = 0.0;
ar = 0.0;
for(j = 0; j < numStates; j++)
{
al += vl[j] * left[k * statesSquare + l * numStates + j];
ar += vr[j] * right[k * statesSquare + l * numStates + j];
}
x1px2 = al * ar;
for(j = 0; j < numStates; j++)
v[j] += x1px2 * extEV[numStates * l + j];
}
}
v = &(x3[gammaStates * i]);
scale = 1;
for(l = 0; scale && (l < gammaStates); l++)
scale = ((ABS(v[l]) < minlikelihood));
if(scale)
{
for(l = 0; l < gammaStates; l++)
v[l] *= twotothe256;
ex3[i] += 1;
}
}
break;
default:
assert(0);
}
}
static void makeP(double z1, double z2, double *rptr, double *EI, double *EIGN, int numberOfCategories, double *left, double *right, int data, boolean saveMem, int maxCat)
{
int i, j, k;
switch(data)
{
case BINARY_DATA:
{
double d1, d2;
for(i = 0; i < numberOfCategories; i++)
{
d1 = EXP(rptr[i] * EIGN[0] * z1);
d2 = EXP(rptr[i] * EIGN[0] * z2);
for(j = 0; j < 2; j++)
{
left[i * 4 + j * 2] = 1.0;
right[i * 4 + j * 2] = 1.0;
left[i * 4 + j * 2 + 1] = d1 * EI[j];
right[i * 4 + j * 2 + 1] = d2 * EI[j];
}
}
}
break;
case DNA_DATA:
{
#ifdef __SIM_SSE3
double
d1[4] __attribute__ ((aligned (BYTE_ALIGNMENT))),
d2[4] __attribute__ ((aligned (BYTE_ALIGNMENT))),
ez1[3],
ez2[3],
EI_16[16] __attribute__ ((aligned (BYTE_ALIGNMENT)));
for(j = 0; j < 4; j++)
{
EI_16[j * 4] = 1.0;
for(k = 0; k < 3; k++)
EI_16[j * 4 + k + 1] = EI[3 * j + k];
}
for(j = 0; j < 3; j++)
{
ez1[j] = EIGN[j] * z1;
ez2[j] = EIGN[j] * z2;
}
for(i = 0; i < numberOfCategories; i++)
{
__m128d
d1_0, d1_1,
d2_0, d2_1;
d1[0] = 1.0;
d2[0] = 1.0;
for(j = 0; j < 3; j++)
{
d1[j+1] = EXP(rptr[i] * ez1[j]);
d2[j+1] = EXP(rptr[i] * ez2[j]);
}
d1_0 = _mm_load_pd(&d1[0]);
d1_1 = _mm_load_pd(&d1[2]);
d2_0 = _mm_load_pd(&d2[0]);
d2_1 = _mm_load_pd(&d2[2]);
for(j = 0; j < 4; j++)
{
double *ll = &left[i * 16 + j * 4];
double *rr = &right[i * 16 + j * 4];
__m128d eev = _mm_load_pd(&EI_16[4 * j]);
_mm_store_pd(&ll[0], _mm_mul_pd(d1_0, eev));
_mm_store_pd(&rr[0], _mm_mul_pd(d2_0, eev));
eev = _mm_load_pd(&EI_16[4 * j + 2]);
_mm_store_pd(&ll[2], _mm_mul_pd(d1_1, eev));
_mm_store_pd(&rr[2], _mm_mul_pd(d2_1, eev));
}
}
if(saveMem)
{
i = maxCat;
{
__m128d
d1_0, d1_1,
d2_0, d2_1;
d1[0] = 1.0;
d2[0] = 1.0;
for(j = 0; j < 3; j++)
{
d1[j+1] = EXP(ez1[j]);
d2[j+1] = EXP(ez2[j]);
}
d1_0 = _mm_load_pd(&d1[0]);
d1_1 = _mm_load_pd(&d1[2]);
d2_0 = _mm_load_pd(&d2[0]);
d2_1 = _mm_load_pd(&d2[2]);
for(j = 0; j < 4; j++)
{
double *ll = &left[i * 16 + j * 4];
double *rr = &right[i * 16 + j * 4];
__m128d eev = _mm_load_pd(&EI_16[4 * j]);
_mm_store_pd(&ll[0], _mm_mul_pd(d1_0, eev));
_mm_store_pd(&rr[0], _mm_mul_pd(d2_0, eev));
eev = _mm_load_pd(&EI_16[4 * j + 2]);
_mm_store_pd(&ll[2], _mm_mul_pd(d1_1, eev));
_mm_store_pd(&rr[2], _mm_mul_pd(d2_1, eev));
}
}
}