Revision 594dda756565a8833633b21c17e4d22d33bcb573 authored by stamatak on 17 November 2014, 10:05:03 UTC, committed by stamatak on 17 November 2014, 10:05:03 UTC
This bug was associated with the additional optimization of the likelihood functions based on Andre Aberer's idea.
1 parent e8634fe
fastSearch.c
/* 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 <sys/times.h>
#include <sys/types.h>
#include <sys/time.h>
#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"
#define POSTERIOR_THRESHOLD 0.90
extern int Thorough;
extern double masterTime;
extern char permFileName[1024], resultFileName[1024],
logFileName[1024], checkpointFileName[1024], infoFileName[1024], run_id[128], workdir[1024], bootStrapFile[1024], bootstrapFileName[1024],
bipartitionsFileName[1024],bipartitionsFileNameBranchLabels[1024];
typedef struct
{
nodeptr p;
double lh;
} scores;
typedef struct
{
scores *s;
int count;
int maxCount;
} insertions;
static void addInsertion(nodeptr p, double lh, insertions *ins)
{
if(ins->count < ins->maxCount)
{
ins->s[ins->count].lh = lh;
ins->s[ins->count].p = p;
ins->count = ins->count + 1;
}
else
{
ins->s = rax_realloc(ins->s, sizeof(scores) * ins->maxCount * 2, FALSE);
ins->maxCount *= 2;
ins->s[ins->count].lh = lh;
ins->s[ins->count].p = p;
ins->count = ins->count + 1;
}
}
/* the two functions below just compute the subtree insertion likelihood score into
a branch using the thorough method.
*/
static void insertFast (tree *tr, nodeptr p, nodeptr q, int numBranches)
{
nodeptr r, s;
int i;
r = q->back;
s = p->back;
for(i = 0; i < numBranches; i++)
tr->lzi[i] = q->z[i];
if(Thorough)
{
double zqr[NUM_BRANCHES], zqs[NUM_BRANCHES], zrs[NUM_BRANCHES], lzqr, lzqs, lzrs, lzsum, lzq, lzr, lzs, lzmax;
double defaultArray[NUM_BRANCHES];
double e1[NUM_BRANCHES], e2[NUM_BRANCHES], e3[NUM_BRANCHES];
double *qz;
qz = q->z;
for(i = 0; i < numBranches; i++)
defaultArray[i] = defaultz;
makenewzGeneric(tr, q, r, qz, iterations, zqr, FALSE);
makenewzGeneric(tr, q, s, defaultArray, iterations, zqs, FALSE);
makenewzGeneric(tr, r, s, defaultArray, iterations, zrs, FALSE);
for(i = 0; i < numBranches; i++)
{
lzqr = (zqr[i] > zmin) ? log(zqr[i]) : log(zmin);
lzqs = (zqs[i] > zmin) ? log(zqs[i]) : log(zmin);
lzrs = (zrs[i] > zmin) ? log(zrs[i]) : log(zmin);
lzsum = 0.5 * (lzqr + lzqs + lzrs);
lzq = lzsum - lzrs;
lzr = lzsum - lzqs;
lzs = lzsum - lzqr;
lzmax = log(zmax);
if (lzq > lzmax) {lzq = lzmax; lzr = lzqr; lzs = lzqs;}
else if (lzr > lzmax) {lzr = lzmax; lzq = lzqr; lzs = lzrs;}
else if (lzs > lzmax) {lzs = lzmax; lzq = lzqs; lzr = lzrs;}
e1[i] = exp(lzq);
e2[i] = exp(lzr);
e3[i] = exp(lzs);
}
hookup(p->next, q, e1, numBranches);
hookup(p->next->next, r, e2, numBranches);
hookup(p, s, e3, numBranches);
}
else
{
double z[NUM_BRANCHES];
for(i = 0; i < numBranches; i++)
{
z[i] = sqrt(q->z[i]);
if(z[i] < zmin)
z[i] = zmin;
if(z[i] > zmax)
z[i] = zmax;
}
hookup(p->next, q, z, tr->numBranches);
hookup(p->next->next, r, z, tr->numBranches);
}
newviewGeneric(tr, p);
if(Thorough)
{
localSmooth(tr, p, smoothings);
for(i = 0; i < numBranches; i++)
{
tr->lzq[i] = p->next->z[i];
tr->lzr[i] = p->next->next->z[i];
tr->lzs[i] = p->z[i];
}
}
}
static double testInsertFast (tree *tr, nodeptr p, nodeptr q, insertions *ins, boolean veryFast)
{
double qz[NUM_BRANCHES], pz[NUM_BRANCHES];
nodeptr r, s;
double LH;
int i;
r = q->back;
for(i = 0; i < tr->numBranches; i++)
{
qz[i] = q->z[i];
pz[i] = p->z[i];
}
insertFast(tr, p, q, tr->numBranches);
evaluateGeneric(tr, p->next->next);
addInsertion(q, tr->likelihood, ins);
if(veryFast)
if(tr->likelihood > tr->endLH)
{
tr->insertNode = q;
tr->removeNode = p;
for(i = 0; i < tr->numBranches; i++)
tr->currentZQR[i] = tr->zqr[i];
tr->endLH = tr->likelihood;
}
LH = tr->likelihood;
hookup(q, r, qz, tr->numBranches);
p->next->next->back = p->next->back = (nodeptr) NULL;
if(Thorough)
{
s = p->back;
hookup(p, s, pz, tr->numBranches);
}
return LH;
}
static double testInsertCandidates(tree *tr, nodeptr p, nodeptr q)
{
double qz[NUM_BRANCHES], pz[NUM_BRANCHES];
nodeptr r, s;
double LH;
int i;
r = q->back;
for(i = 0; i < tr->numBranches; i++)
{
qz[i] = q->z[i];
pz[i] = p->z[i];
}
insertFast(tr, p, q, tr->numBranches);
evaluateGeneric(tr, p->next->next);
if(tr->likelihood > tr->endLH)
{
tr->insertNode = q;
tr->removeNode = p;
for(i = 0; i < tr->numBranches; i++)
tr->currentZQR[i] = tr->zqr[i];
tr->endLH = tr->likelihood;
}
LH = tr->likelihood;
hookup(q, r, qz, tr->numBranches);
p->next->next->back = p->next->back = (nodeptr) NULL;
if(Thorough)
{
s = p->back;
hookup(p, s, pz, tr->numBranches);
}
return LH;
}
/*
function below just computes all subtree roots,
we go to every inner node and store the three outgoing subtree
roots. Assumes evidently that nodeptr p that is passed to the first
instance of this recursion is not a tip ;-)
*/
static void getSubtreeRoots(nodeptr p, nodeptr *ptr, int *count, int mxtips)
{
if(isTip(p->number, mxtips))
return;
ptr[*count] = p;
*count = *count + 1;
ptr[*count] = p->next;
*count = *count + 1;
ptr[*count] = p->next->next;
*count = *count + 1;
getSubtreeRoots(p->next->back, ptr, count, mxtips);
getSubtreeRoots(p->next->next->back, ptr, count, mxtips);
}
/*
conducts linear SPRs, computes the approximate likelihood score
fo an insertion of the subtree being rearranged into the left and
right branch. Depending on the score it then descends into
either the right or the left tree.
I also added a radius that limits the number of branches away from the original pruning position into which the tree
will be inserted.
We actually need to test empirically what a good setting may be !
*/
static void insertBeyond(tree *tr, nodeptr p, nodeptr q, int radius, insertions *ins, boolean veryFast)
{
if(radius > 0)
{
int count = 0;
double
twoScores[2];
twoScores[0] = unlikely;
twoScores[1] = unlikely;
if(isTip(q->next->back->number, tr->mxtips) && isTip(q->next->next->back->number, tr->mxtips))
return;
if(!isTip(q->next->back->number, tr->mxtips))
{
twoScores[0] = testInsertFast(tr, p, q->next->back, ins, veryFast);
count++;
}
if(!isTip(q->next->next->back->number, tr->mxtips))
{
twoScores[1] = testInsertFast(tr, p, q->next->next->back, ins, veryFast);
count++;
}
if(count == 2 && !veryFast)
{
double
weight;
if(twoScores[0] > twoScores[1])
{
weight = exp(twoScores[0] - twoScores[0]) / (exp(twoScores[0] - twoScores[0]) + exp(twoScores[1] - twoScores[0]));
if(weight >= POSTERIOR_THRESHOLD)
insertBeyond(tr, p, q->next->back, radius - 1, ins, veryFast);
else
{
insertBeyond(tr, p, q->next->back, radius - 1, ins, veryFast);
insertBeyond(tr, p, q->next->next->back, radius - 1, ins, veryFast);
}
}
else
{
weight = exp(twoScores[1] - twoScores[1]) / (exp(twoScores[1] - twoScores[0]) + exp(twoScores[1] - twoScores[1]));
if(weight >= POSTERIOR_THRESHOLD)
insertBeyond(tr, p, q->next->next->back, radius - 1, ins, veryFast);
else
{
insertBeyond(tr, p, q->next->back, radius - 1, ins, veryFast);
insertBeyond(tr, p, q->next->next->back, radius - 1, ins, veryFast);
}
}
}
else
{
if(twoScores[0] > twoScores[1])
insertBeyond(tr, p, q->next->back, radius - 1, ins, veryFast);
else
insertBeyond(tr, p, q->next->next->back, radius - 1, ins, veryFast);
}
}
}
typedef struct
{
int direction;
double likelihood;
} fourLikelihoods;
static int fourCompare(const void *p1, const void *p2)
{
fourLikelihoods *rc1 = (fourLikelihoods *)p1;
fourLikelihoods *rc2 = (fourLikelihoods *)p2;
double i = rc1->likelihood;
double j = rc2->likelihood;
if (i > j)
return (-1);
if (i < j)
return (1);
return (0);
}
static int scoreCompare(const void *p1, const void *p2)
{
scores *rc1 = (scores *)p1;
scores *rc2 = (scores *)p2;
double i = rc1->lh;
double j = rc2->lh;
if (i > j)
return (-1);
if (i < j)
return (1);
return (0);
}
static double linearSPRs(tree *tr, int radius, boolean veryFast)
{
int
numberOfSubtrees = (tr->mxtips - 2) * 3,
count = 0,
k,
i;
double
fourScores[4];
nodeptr
*ptr = (nodeptr *)rax_malloc(sizeof(nodeptr) * numberOfSubtrees);
fourLikelihoods
*fourLi = (fourLikelihoods *)rax_malloc(sizeof(fourLikelihoods) * 4);
insertions
*ins = (insertions*)rax_malloc(sizeof(insertions));
ins->count = 0;
ins->maxCount = 2048;
ins->s = (scores *)rax_malloc(sizeof(scores) * ins->maxCount);
/* recursively compute the roots of all subtrees in the current tree
and store them in ptr */
getSubtreeRoots(tr->start->back, ptr, &count, tr->mxtips);
assert(count == numberOfSubtrees);
tr->startLH = tr->endLH = tr->likelihood;
/* loop over subtrees, i.e., execute a full SPR cycle */
for(i = 0; i < numberOfSubtrees; i++)
{
nodeptr
p = ptr[i],
p1 = p->next->back,
p2 = p->next->next->back;
double
p1z[NUM_BRANCHES],
p2z[NUM_BRANCHES];
ins->count = 0;
/*printf("Node %d %d\n", p->number, i);*/
tr->bestOfNode = unlikely;
for(k = 0; k < 4; k++)
fourScores[k] = unlikely;
assert(!isTip(p->number, tr->rdta->numsp));
if(!isTip(p1->number, tr->rdta->numsp) || !isTip(p2->number, tr->rdta->numsp))
{
double
max = unlikely;
int
maxInt = -1;
for(k = 0; k < tr->numBranches; k++)
{
p1z[k] = p1->z[k];
p2z[k] = p2->z[k];
}
/* remove the current subtree */
removeNodeBIG(tr, p, tr->numBranches);
/* pre score with fast insertions */
if(veryFast)
Thorough = 1;
else
Thorough = 0;
if (!isTip(p1->number, tr->rdta->numsp))
{
fourScores[0] = testInsertFast(tr, p, p1->next->back, ins, veryFast);
fourScores[1] = testInsertFast(tr, p, p1->next->next->back, ins, veryFast);
}
if (!isTip(p2->number, tr->rdta->numsp))
{
fourScores[2] = testInsertFast(tr, p, p2->next->back, ins, veryFast);
fourScores[3] = testInsertFast(tr, p, p2->next->next->back, ins, veryFast);
}
if(veryFast)
Thorough = 1;
else
Thorough = 0;
/* find the most promising direction */
if(!veryFast)
{
int
j = 0,
validEntries = 0;
double
lmax = unlikely,
posterior = 0.0;
for(k = 0; k < 4; k++)
{
fourLi[k].direction = k;
fourLi[k].likelihood = fourScores[k];
}
qsort(fourLi, 4, sizeof(fourLikelihoods), fourCompare);
for(k = 0; k < 4; k++)
if(fourLi[k].likelihood > unlikely)
validEntries++;
lmax = fourLi[0].likelihood;
while(posterior <= POSTERIOR_THRESHOLD && j < validEntries)
{
double
all = 0.0,
prob = 0.0;
for(k = 0; k < validEntries; k++)
all += exp(fourLi[k].likelihood - lmax);
posterior += (prob = (exp(fourLi[j].likelihood - lmax) / all));
switch(fourLi[j].direction)
{
case 0:
insertBeyond(tr, p, p1->next->back, radius, ins, veryFast);
break;
case 1:
insertBeyond(tr, p, p1->next->next->back, radius, ins, veryFast);
break;
case 2:
insertBeyond(tr, p, p2->next->back, radius, ins, veryFast);
break;
case 3:
insertBeyond(tr, p, p2->next->next->back, radius, ins, veryFast);
break;
default:
assert(0);
}
j++;
}
qsort(ins->s, ins->count, sizeof(scores), scoreCompare);
Thorough = 1;
for(k = 0; k < MIN(ins->count, 20); k++)
testInsertCandidates(tr, p, ins->s[k].p);
}
else
{
Thorough = 1;
for(k = 0; k < 4; k++)
{
if(max < fourScores[k])
{
max = fourScores[k];
maxInt = k;
}
}
/* descend into this direction and re-insert subtree there */
if(maxInt >= 0)
{
switch(maxInt)
{
case 0:
insertBeyond(tr, p, p1->next->back, radius, ins, veryFast);
break;
case 1:
insertBeyond(tr, p, p1->next->next->back, radius, ins, veryFast);
break;
case 2:
insertBeyond(tr, p, p2->next->back, radius, ins, veryFast);
break;
case 3:
insertBeyond(tr, p, p2->next->next->back, radius, ins, veryFast);
break;
default:
assert(0);
}
}
}
/* repair branch and reconnect subtree to its original position from which it was pruned */
hookup(p->next, p1, p1z, tr->numBranches);
hookup(p->next->next, p2, p2z, tr->numBranches);
/* repair likelihood vectors */
newviewGeneric(tr, p);
/* if the rearrangement of subtree rooted at p yielded a better likelihood score
restore the altered topology and use it from now on
*/
if(tr->endLH > tr->startLH)
{
restoreTreeFast(tr);
tr->startLH = tr->endLH = tr->likelihood;
}
}
}
return tr->startLH;
}
static boolean allSmoothed(tree *tr)
{
int i;
boolean result = TRUE;
for(i = 0; i < tr->numBranches; i++)
{
if(tr->partitionSmoothed[i] == FALSE)
result = FALSE;
else
tr->partitionConverged[i] = TRUE;
}
return result;
}
void nniSmooth(tree *tr, nodeptr p, int maxtimes)
{
int
i;
for(i = 0; i < tr->numBranches; i++)
tr->partitionConverged[i] = FALSE;
while (--maxtimes >= 0)
{
for(i = 0; i < tr->numBranches; i++)
tr->partitionSmoothed[i] = TRUE;
assert(!isTip(p->number, tr->mxtips));
assert(!isTip(p->back->number, tr->mxtips));
update(tr, p);
update(tr, p->next);
update(tr, p->next->next);
update(tr, p->back->next);
update(tr, p->back->next->next);
if (allSmoothed(tr))
break;
}
for(i = 0; i < tr->numBranches; i++)
{
tr->partitionSmoothed[i] = FALSE;
tr->partitionConverged[i] = FALSE;
}
}
static void storeBranches(tree *tr, nodeptr p, double *pqz, double *pz1, double *pz2, double *qz1, double *qz2)
{
int
i;
nodeptr
q = p->back;
for(i = 0; i < tr->numBranches; i++)
{
pqz[i] = p->z[i];
pz1[i] = p->next->z[i];
pz2[i] = p->next->next->z[i];
qz1[i] = q->next->z[i];
qz2[i] = q->next->next->z[i];
}
}
static int SHSupport(int nPos, int nBootstrap, int *col, double loglk[3], double *siteloglk[3], int lower, int upper, boolean perPartition)
{
double
resampleDelta,
resample1,
resample2,
support = 0.0,
delta1 = loglk[0] - loglk[1],
delta2 = loglk[0] - loglk[2],
delta = delta1 < delta2 ? delta1 : delta2,
diff;
int
iBest,
i,
j,
nSupport = 0,
iBoot;
boolean
shittySplit = FALSE;
if(loglk[1] >= loglk[0])
{
diff = ABS(loglk[1] - loglk[0]);
//printf("%1.80f %1.80f\n", loglk[0], loglk[1]);
shittySplit = TRUE;
if(!perPartition)
assert(diff < 0.1);
}
if(loglk[2] >= loglk[0])
{
diff = ABS(loglk[2] - loglk[0]);
//printf("%1.80f %1.80f\n", loglk[0], loglk[2]);
shittySplit = TRUE;
if(!perPartition)
assert(diff < 0.1);
}
if(loglk[0] > loglk[2] && loglk[0] > loglk[1])
{
if(loglk[2] > loglk[1])
diff = ABS(loglk[2] - loglk[0]);
else
diff = ABS(loglk[1] - loglk[0]);
if(diff < 0.1)
shittySplit = TRUE;
}
if(shittySplit)
return 0;
/*
printf("%f %f %f\n", loglk[0], loglk[1], loglk[2]);
assert(loglk[0] >= loglk[1] && loglk[0] >= loglk[2]);
*/
for(iBoot = 0; iBoot < nBootstrap; iBoot++)
{
double resampled[3];
for (i = 0; i < 3; i++)
resampled[i] = -loglk[i];
for (j = lower; j < upper; j++)
{
int
pos = col[iBoot * nPos + j];
for (i = 0; i < 3; i++)
resampled[i] += pos * siteloglk[i][j];
}
iBest = 0;
/*printf("%d %f %f %f\n", iBoot, resampled[0], resampled[1], resampled[2]);*/
for (i = 1; i < 3; i++)
if (resampled[i] > resampled[iBest])
iBest = i;
resample1 = resampled[iBest] - resampled[(iBest+1)%3];
resample2 = resampled[iBest] - resampled[(iBest+2)%3];
resampleDelta = resample1 < resample2 ? resample1 : resample2;
if(resampleDelta < delta)
nSupport++;
}
support = (nSupport/(double)nBootstrap);
return ((int)((support * 100.0) + 0.5));
}
static void setupBranchInfo(nodeptr p, tree *tr, int *counter)
{
if(!isTip(p->number, tr->mxtips))
{
nodeptr q;
if(!(isTip(p->back->number, tr->mxtips)))
{
p->bInf = p->back->bInf = &(tr->bInf[*counter]);
p->bInf->oP = p;
p->bInf->oQ = p->back;
*counter = *counter + 1;
}
q = p->next;
while(q != p)
{
setupBranchInfo(q->back, tr, counter);
q = q->next;
}
return;
}
}
static void doNNIs(tree *tr, nodeptr p, double *lhVectors[3], boolean shSupport, int *interchanges, int *innerBranches,
double *pqz_0, double *pz1_0, double *pz2_0, double *qz1_0, double *qz2_0, double *pqz_1, double *pz1_1, double *pz2_1,
double *qz1_1, double *qz2_1, double *pqz_2, double *pz1_2, double *pz2_2, double *qz1_2, double *qz2_2)
{
nodeptr
q = p->back,
pb1 = p->next->back,
pb2 = p->next->next->back;
assert(!isTip(p->number, tr->mxtips));
if(!isTip(q->number, tr->mxtips))
{
int
model,
whichNNI = 0;
nodeptr
qb1 = q->next->back,
qb2 = q->next->next->back;
double
lh[3],
*lhv[3];
lhv[0] = (double*)rax_malloc(sizeof(double) * tr->NumberOfModels);
lhv[1] = (double*)rax_malloc(sizeof(double) * tr->NumberOfModels);
lhv[2] = (double*)rax_malloc(sizeof(double) * tr->NumberOfModels);
*innerBranches = *innerBranches + 1;
nniSmooth(tr, p, 16);
if(shSupport)
{
evaluateGenericVector(tr, p);
memcpy(lhVectors[0], tr->perSiteLL, sizeof(double) * tr->cdta->endsite);
}
else
evaluateGeneric(tr, p);
lh[0] = tr->likelihood;
for(model = 0; model < tr->NumberOfModels; model++)
lhv[0][model] = tr->perPartitionLH[model];
storeBranches(tr, p, pqz_0, pz1_0, pz2_0, qz1_0, qz2_0);
/*******************************************/
hookup(p, q, pqz_0, tr->numBranches);
hookup(p->next, qb1, qz1_0, tr->numBranches);
hookup(p->next->next, pb2, pz2_0, tr->numBranches);
hookup(q->next, pb1, pz1_0, tr->numBranches);
hookup(q->next->next, qb2, qz2_0, tr->numBranches);
newviewGeneric(tr, p);
newviewGeneric(tr, p->back);
nniSmooth(tr, p, 16);
if(shSupport)
{
evaluateGenericVector(tr, p);
memcpy(lhVectors[1], tr->perSiteLL, sizeof(double) * tr->cdta->endsite);
}
else
evaluateGeneric(tr, p);
lh[1] = tr->likelihood;
for(model = 0; model < tr->NumberOfModels; model++)
lhv[1][model] = tr->perPartitionLH[model];
storeBranches(tr, p, pqz_1, pz1_1, pz2_1, qz1_1, qz2_1);
if(lh[1] > lh[0])
whichNNI = 1;
/*******************************************/
hookup(p, q, pqz_0, tr->numBranches);
hookup(p->next, qb1, qz1_0, tr->numBranches);
hookup(p->next->next, pb1, pz1_0, tr->numBranches);
hookup(q->next, pb2, pz2_0, tr->numBranches);
hookup(q->next->next, qb2, qz2_0, tr->numBranches);
newviewGeneric(tr, p);
newviewGeneric(tr, p->back);
nniSmooth(tr, p, 16);
if(shSupport)
{
evaluateGenericVector(tr, p);
memcpy(lhVectors[2], tr->perSiteLL, sizeof(double) * tr->cdta->endsite);
}
else
evaluateGeneric(tr, p);
lh[2] = tr->likelihood;
for(model = 0; model < tr->NumberOfModels; model++)
lhv[2][model] = tr->perPartitionLH[model];
storeBranches(tr, p, pqz_2, pz1_2, pz2_2, qz1_2, qz2_2);
if(lh[2] > lh[0] && lh[2] > lh[1])
whichNNI = 2;
/*******************************************/
if(shSupport)
whichNNI = 0;
switch(whichNNI)
{
case 0:
hookup(p, q, pqz_0, tr->numBranches);
hookup(p->next, pb1, pz1_0, tr->numBranches);
hookup(p->next->next, pb2, pz2_0, tr->numBranches);
hookup(q->next, qb1, qz1_0, tr->numBranches);
hookup(q->next->next, qb2, qz2_0, tr->numBranches);
break;
case 1:
hookup(p, q, pqz_1, tr->numBranches);
hookup(p->next, qb1, pz1_1, tr->numBranches);
hookup(p->next->next, pb2, pz2_1, tr->numBranches);
hookup(q->next, pb1, qz1_1, tr->numBranches);
hookup(q->next->next, qb2, qz2_1, tr->numBranches);
break;
case 2:
hookup(p, q, pqz_2, tr->numBranches);
hookup(p->next, qb1, pz1_2, tr->numBranches);
hookup(p->next->next, pb1, pz2_2, tr->numBranches);
hookup(q->next, pb2, qz1_2, tr->numBranches);
hookup(q->next->next, qb2, qz2_2, tr->numBranches);
break;
default:
assert(0);
}
newviewGeneric(tr, p);
newviewGeneric(tr, q);
if(whichNNI > 0)
*interchanges = *interchanges + 1;
if(shSupport)
{
p->bInf->support = SHSupport(tr->cdta->endsite, 1000, tr->resample, lh, lhVectors, 0, tr->cdta->endsite, FALSE);
//printf("ALL: %f %f %f ", lh[0], lh[1], lh[2]);
for(model = 0; model < tr->NumberOfModels; model++)
{
double
perPartitionLH[3];
perPartitionLH[0] = lhv[0][model];
perPartitionLH[1] = lhv[1][model];
perPartitionLH[2] = lhv[2][model];
p->bInf->supports[model] = SHSupport(tr->cdta->endsite, 1000, tr->resample, perPartitionLH, lhVectors, tr->partitionData[model].lower, tr->partitionData[model].upper, TRUE);
//printf(" p%d %f %f %f ", model, perPartitionLH[0], perPartitionLH[1], perPartitionLH[2]);
}
//printf("\n");
}
rax_free(lhv[0]);
rax_free(lhv[1]);
rax_free(lhv[2]);
}
if(!isTip(pb1->number, tr->mxtips))
doNNIs(tr, pb1, lhVectors, shSupport, interchanges, innerBranches,
pqz_0, pz1_0, pz2_0, qz1_0, qz2_0, pqz_1, pz1_1, pz2_1,
qz1_1, qz2_1, pqz_2, pz1_2, pz2_2, qz1_2, qz2_2);
if(!isTip(pb2->number, tr->mxtips))
doNNIs(tr, pb2, lhVectors, shSupport, interchanges, innerBranches,
pqz_0, pz1_0, pz2_0, qz1_0, qz2_0, pqz_1, pz1_1, pz2_1,
qz1_1, qz2_1, pqz_2, pz1_2, pz2_2, qz1_2, qz2_2);
return;
}
static int encapsulateNNIs(tree *tr, double *lhVectors[3], boolean shSupport)
{
int
innerBranches = 0,
interchanges = 0;
double
pqz_0[NUM_BRANCHES],
pz1_0[NUM_BRANCHES],
pz2_0[NUM_BRANCHES],
qz1_0[NUM_BRANCHES],
qz2_0[NUM_BRANCHES],
pqz_1[NUM_BRANCHES],
pz1_1[NUM_BRANCHES],
pz2_1[NUM_BRANCHES],
qz1_1[NUM_BRANCHES],
qz2_1[NUM_BRANCHES],
pqz_2[NUM_BRANCHES],
pz1_2[NUM_BRANCHES],
pz2_2[NUM_BRANCHES],
qz1_2[NUM_BRANCHES],
qz2_2[NUM_BRANCHES];
doNNIs(tr, tr->start->back, lhVectors, shSupport, &interchanges, &innerBranches,
pqz_0, pz1_0, pz2_0, qz1_0, qz2_0, pqz_1, pz1_1, pz2_1,
qz1_1, qz2_1, pqz_2, pz1_2, pz2_2, qz1_2, qz2_2);
assert(innerBranches == (tr->mxtips - 3));
return interchanges;
}
int *permutationSH(tree *tr, int nBootstrap, int64_t _randomSeed)
{
int
replicate,
model,
maxNonZero = 0,
*weightBuffer,
*col = (int*)rax_calloc(((size_t)tr->cdta->endsite) * ((size_t)nBootstrap), sizeof(int)),
*nonzero = (int*)rax_calloc(tr->NumberOfModels, sizeof(int));
int64_t
randomSeed = _randomSeed;
size_t
bufferSize;
for(model = 0; model < tr->NumberOfModels; model++)
{
int
j;
for (j = 0; j < tr->cdta->endsite; j++)
{
if(tr->originalModel[j] == model)
nonzero[model] += tr->originalWeights[j];
}
if(nonzero[model] > maxNonZero)
maxNonZero = nonzero[model];
}
bufferSize = ((size_t)maxNonZero) * sizeof(int);
weightBuffer = (int*)rax_malloc(bufferSize);
for(replicate = 0; replicate < nBootstrap; replicate++)
{
int
j,
*wgt = &col[((size_t)tr->cdta->endsite) * ((size_t)replicate)];
for(model = 0; model < tr->NumberOfModels; model++)
{
int
pos,
nonz = nonzero[model];
memset(weightBuffer, 0, bufferSize);
for(j = 0; j < nonz; j++)
weightBuffer[(int) (nonz * randum(&randomSeed))]++;
for(j = 0, pos = 0; j < tr->cdta->endsite; j++)
{
if(model == tr->originalModel[j])
{
int
w;
for(w = 0; w < tr->originalWeights[j]; w++)
{
wgt[j] += weightBuffer[pos];
pos++;
}
}
}
}
}
rax_free(weightBuffer);
rax_free(nonzero);
return col;
}
void fastSearch(tree *tr, analdef *adef, rawdata *rdta, cruncheddata *cdta)
{
double
likelihood,
startLikelihood,
*lhVectors[3];
char
bestTreeFileName[1024];
FILE
*f;
int
model;
lhVectors[0] = (double *)NULL;
lhVectors[1] = (double *)NULL;
lhVectors[2] = (double *)NULL;
/* initialize model parameters with standard starting values */
initModel(tr, rdta, cdta, adef);
printBothOpen("Time after init : %f\n", gettime() - masterTime);
/*
compute starting tree, either by reading in a tree specified via -t
or by building one
*/
getStartingTree(tr, adef);
printBothOpen("Time after init and starting tree: %f\n", gettime() - masterTime);
/*
rough model parameter optimization, the log likelihood epsilon should
actually be determined based on the initial tree score and not be hard-coded
*/
if(adef->useBinaryModelFile)
{
readBinaryModel(tr, adef);
evaluateGenericInitrav(tr, tr->start);
treeEvaluate(tr, 2);
}
else
modOpt(tr, adef, FALSE, 10.0);
printBothOpen("Time after init, starting tree, mod opt: %f\n", gettime() - masterTime);
/* print out the number of rate categories used for the CAT model, one should
use less then the default, e.g., -c 16 works quite well */
for(model = 0; model < tr->NumberOfModels; model++)
printBothOpen("Partion %d number of Cats: %d\n", model, tr->partitionData[model].numberOfCategories);
/*
means that we are going to do thorough insertions
with real newton-raphson based br-len opt at the three branches
adjactent to every insertion point
*/
Thorough = 1;
/*
loop over SPR cycles until the likelihood difference
before and after the SPR cycle is <= 0.5 log likelihood units.
Rather than being hard-coded this should also be determined based on the
actual likelihood of the tree
*/
do
{
startLikelihood = tr->likelihood;
/* conduct a cycle of linear SPRs */
linearSPRs(tr, 20, adef->veryFast);
evaluateGeneric(tr, tr->start);
likelihood = tr->likelihood;
/* the NNIs also optimize br-lens of resulting topology a bit */
encapsulateNNIs(tr, lhVectors, FALSE);
evaluateGeneric(tr, tr->start);
assert(tr->likelihood >= likelihood);
printBothOpen("LH after SPRs %f, after NNI %f\n", likelihood, tr->likelihood);
}
while(ABS(tr->likelihood - startLikelihood) > 0.5);
/* print out the resulting tree to the RAxML_bestTree. file.
note that boosttrapping or doing multiple inferences won't work.
This thing computes a single tree and that's it */
strcpy(bestTreeFileName, workdir);
strcat(bestTreeFileName, "RAxML_fastTree.");
strcat(bestTreeFileName, run_id);
Tree2String(tr->tree_string, tr, tr->start->back, FALSE, TRUE, FALSE, FALSE, FALSE, adef, SUMMARIZE_LH, FALSE, FALSE, FALSE, FALSE);
f = myfopen(bestTreeFileName, "wb");
fprintf(f, "%s", tr->tree_string);
fclose(f);
printBothOpen("RAxML fast tree written to file: %s\n", bestTreeFileName);
writeBinaryModel(tr, adef);
printBothOpen("Total execution time: %f\n", gettime() - masterTime);
printBothOpen("Good bye ... \n");
}
void shSupports(tree *tr, analdef *adef, rawdata *rdta, cruncheddata *cdta)
{
double
diff,
*lhVectors[3];
char
bestTreeFileName[1024],
shSupportFileName[1024];
FILE
*f;
int
nniRounds = 0,
i,
interchanges = 0,
counter = 0;
assert(adef->restart);
tr->resample = permutationSH(tr, 1000, adef->parsimonySeed);
//a tiny bit dirty here, all allocs should be cleaned up!
lhVectors[0] = (double *)rax_malloc(sizeof(double) * tr->cdta->endsite);
lhVectors[1] = (double *)rax_malloc(sizeof(double) * tr->cdta->endsite);
lhVectors[2] = (double *)rax_malloc(sizeof(double) * tr->cdta->endsite);
tr->bInf = (branchInfo*)rax_malloc(sizeof(branchInfo) * (tr->mxtips - 3));
for(i = 0; i < tr->mxtips - 3; i++)
tr->bInf[i].supports = (int*)rax_malloc(sizeof(int) * tr->NumberOfModels);
initModel(tr, rdta, cdta, adef);
getStartingTree(tr, adef);
if(adef->useBinaryModelFile)
{
readBinaryModel(tr, adef);
evaluateGenericInitrav(tr, tr->start);
treeEvaluate(tr, 2);
}
else
{
evaluateGenericInitrav(tr, tr->start);
modOpt(tr, adef, FALSE, 1.0);
}
printBothOpen("Time after model optimization: %f\n", gettime() - masterTime);
printBothOpen("Initial Likelihood %f\n\n", tr->likelihood);
do
{
double
lh1,
lh2;
lh1 = tr->likelihood;
interchanges = encapsulateNNIs(tr, lhVectors, FALSE);
evaluateGeneric(tr, tr->start);
lh2 = tr->likelihood;
diff = ABS(lh1 - lh2);
printBothOpen("NNI interchanges %d Likelihood %f\n", interchanges, tr->likelihood);
nniRounds++;
}
/*
limit number of nniRounds to 10 if the difference between likelihoods before and after the NNI
is smaller or equal to 0.01. The NNI optimization also converges when no applicable interchanges have been
found
*/
while((diff > 0.01 || nniRounds < 10) && interchanges != 0);
printBothOpen("\nFinal Likelihood of NNI-optimized tree: %f\n\n", tr->likelihood);
setupBranchInfo(tr->start->back, tr, &counter);
assert(counter == tr->mxtips - 3);
interchanges = encapsulateNNIs(tr, lhVectors, TRUE);
strcpy(bestTreeFileName, workdir);
strcat(bestTreeFileName, "RAxML_fastTree.");
strcat(bestTreeFileName, run_id);
Tree2String(tr->tree_string, tr, tr->start->back, FALSE, TRUE, FALSE, FALSE, FALSE, adef, SUMMARIZE_LH, FALSE, FALSE, FALSE, FALSE);
f = myfopen(bestTreeFileName, "wb");
fprintf(f, "%s", tr->tree_string);
fclose(f);
strcpy(shSupportFileName, workdir);
strcat(shSupportFileName, "RAxML_fastTreeSH_Support.");
strcat(shSupportFileName, run_id);
Tree2String(tr->tree_string, tr, tr->start->back, TRUE, TRUE, FALSE, FALSE, FALSE, adef, SUMMARIZE_LH, FALSE, TRUE, FALSE, FALSE);
f = myfopen(shSupportFileName, "wb");
fprintf(f, "%s", tr->tree_string);
fclose(f);
printBothOpen("RAxML NNI-optimized tree written to file: %s\n", bestTreeFileName);
printBothOpen("\nSame tree with SH-like supports written to file: %s\n", shSupportFileName);
if(tr->NumberOfModels > 1)
{
char
shSupportPerPartitionFileName[1024];
strcpy(shSupportPerPartitionFileName, workdir);
strcat(shSupportPerPartitionFileName, "RAxML_fastTree_perPartition_SH_Support.");
strcat(shSupportPerPartitionFileName, run_id);
Tree2String(tr->tree_string, tr, tr->start->back, TRUE, TRUE, FALSE, FALSE, FALSE, adef, SUMMARIZE_LH, FALSE, FALSE, FALSE, TRUE);
f = myfopen(shSupportPerPartitionFileName, "wb");
fprintf(f, "%s", tr->tree_string);
fclose(f);
printBothOpen("\nSame tree with SH-like support for each partition written to file: %s\n", shSupportPerPartitionFileName);
}
printBothOpen("\nTotal execution time: %f\n", gettime() - masterTime);
exit(0);
}
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