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pllnni.cpp
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/***************************************************************************
* Copyright (C) 2014 by *
* Lam-Tung Nguyen <nltung@gmail.com> *
* *
* *
* 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 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. *
* *
* You should have received a copy of the GNU General Public License *
* along with this program; if not, write to the *
* Free Software Foundation, Inc., *
* 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. *
***************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <cmath>
#include <assert.h>
#define GLOBAL_VARIABLES_DEFINITION
#if !defined WIN32 && !defined _WIN32 && !defined __WIN32__ && !defined WIN64
#include <sys/resource.h>
#endif
#include "tree/phylotree.h"
#include "pllnni.h"
#include "alignment/alignment.h"
/* program options */
int nni0;
int nni5;
extern VerboseMode verbose_mode;
int NNI_MAX_NR_STEP = 10;
/* program options */
extern Params *globalParams;
extern Alignment *globalAlignment;
/**
* map from newick tree string to frequencies that a tree is revisited during tree search
*/
StringIntMap pllTreeCounter;
/*
* ****************************************************************************
* pllUFBoot area
* ****************************************************************************
*/
pllUFBootData * pllUFBootDataPtr = NULL;
int compareDouble(const void * a, const void * b) {
if (*(double*) a > *(double*) b)
return 1;
else if (*(double*) a < *(double*) b)
return -1;
else
return 0;
}
pllNNIMove *getNNIList(pllInstance* tr) {
static pllNNIMove* nniList;
if (nniList == NULL) {
nniList = (pllNNIMove*) malloc(2 * (tr->mxtips - 3) * sizeof(pllNNIMove));
ASSERT(nniList != NULL);
}
return nniList;
}
pllNNIMove *getNonConflictNNIList(pllInstance* tr) {
static pllNNIMove* nonConfNNIList;
if (nonConfNNIList == NULL) {
nonConfNNIList = (pllNNIMove*) malloc((tr->mxtips - 3) * sizeof(pllNNIMove));
ASSERT(nonConfNNIList != NULL);
}
return nonConfNNIList;
}
double pllDoRandomNNIs(pllInstance *tr, partitionList *pr, int numNNI) {
int numInBrans = tr->mxtips - 3;
int numNNIinStep = (int) numInBrans / 5;
// devided in multiple round, each round collect 1/5 of numNNI
int cnt1 = 0;
unordered_set<int> selectedNodes;
vector<nodeptr> selectedBrans;
vector<nodeptr> brans;
do {
int cnt2 = 0;
selectedNodes.clear();
selectedBrans.clear();
brans.clear();
pllGetAllInBran(tr, brans);
ASSERT(brans.size() == numInBrans);
while(cnt2 < numNNIinStep && cnt2 < numNNI) {
int branIndex = random_int(numInBrans);
if (selectedNodes.find(brans[branIndex]->number) == selectedNodes.end() &&
selectedNodes.find(brans[branIndex]->back->number) == selectedNodes.end()) {
selectedNodes.insert(brans[branIndex]->number);
selectedNodes.insert(brans[branIndex]->back->number);
selectedBrans.push_back(brans[branIndex]);
cnt2++;
}
}
for (vector<nodeptr>::iterator it = selectedBrans.begin(); it != selectedBrans.end(); ++it) {
int nniType = random_int(2);
doOneNNI(tr, pr, (*it), nniType, TOPO_ONLY);
}
cnt1 += selectedBrans.size();
if (numNNI - cnt1 < numNNIinStep) {
numNNIinStep = numNNI - cnt1;
}
} while (cnt1 < numNNI);
pllEvaluateLikelihood(tr, pr, tr->start, PLL_TRUE, PLL_FALSE);
pllOptimizeBranchLengths(tr, pr, 1);
return tr->likelihood;
}
void pllGetAllInBran(pllInstance *tr, vector<nodeptr> &branlist) {
nodeptr p = tr->start->back;
nodeptr q = p->next;
while (q != p) {
pllGetAllInBranForSubtree(tr, q->back, branlist);
q = q->next;
}
}
void pllGetAllInBranForSubtree(pllInstance *tr, nodeptr p, vector<nodeptr> &branlist) {
if (!isTip(p->number, tr->mxtips) && !isTip(p->back->number, tr->mxtips)) {
branlist.push_back(p);
nodeptr q = p->next;
while (q != p) {
pllGetAllInBranForSubtree(tr, q->back, branlist);
q = q->next;
}
}
}
double pllPerturbTree(pllInstance *tr, partitionList *pr, vector<pllNNIMove> &nnis) {
//printf("Perturbing %d NNIs \n", numNNI);
for (vector<pllNNIMove>::iterator it = nnis.begin(); it != nnis.end(); it++) {
printf("Do pertubing NNI (%d - %d) with logl = %10.4f \n", (*it).p->number, (*it).p->back->number, (*it).likelihood);
doOneNNI(tr, pr, (*it).p, (*it).nniType, TOPO_ONLY);
updateBranchLengthForNNI(tr, pr, (*it));
}
pllEvaluateLikelihood(tr, pr, tr->start, PLL_TRUE, PLL_FALSE);
pllOptimizeBranchLengths(tr, pr, 1);
return tr->likelihood;
}
void quicksort_nni(pllNNIMove* arr,int left, int right) {
int i = left, j = right;
pllNNIMove tmp, pivot = arr[(left + right) / 2];
/* partition */
while (i <= j) {
while (arr[i].likelihood < pivot.likelihood)
i++;
while (pivot.likelihood < arr[j].likelihood)
j--;
if (i <= j) {
tmp = arr[i];
arr[i] = arr[j];
arr[j] = tmp;
i++;
j--;
}
};
/* recursion */
if (left < j)
quicksort_nni(arr, left, j);
if (i < right)
quicksort_nni(arr, i, right);
}
//TODO: Workaround for memory leak problem when calling setupTopol within doNNISearch
topol *_setupTopol(pllInstance* tr) {
static topol* tree;
if (tree == NULL)
tree = setupTopol(tr->mxtips);
return tree;
}
vector<string> getAffectedBranches(pllInstance* tr, nodeptr p) {
vector<string> res;
res.push_back(getBranString(p));
nodeptr q = p->back;
nodeptr p_nei = p->next;
nodeptr q_nei = q->next;
while (p_nei != p) {
res.push_back(getBranString(p_nei));
if (!isTip(p_nei->back->number, tr->mxtips)) {
res.push_back(getBranString(p_nei->back->next));
res.push_back(getBranString(p_nei->back->next->next));
}
p_nei = p_nei->next;
}
while (q_nei != q) {
res.push_back(getBranString(q_nei));
if (!isTip(q_nei->back->number, tr->mxtips)) {
res.push_back(getBranString(q_nei->back->next));
res.push_back(getBranString(q_nei->back->next->next));
}
q_nei = q_nei->next;
}
return res;
}
string getBranString(nodeptr p) {
stringstream branString;
nodeptr q = p->back;
if (p->number < q->number) {
branString << p->number << "-" << q->number;
} else {
branString << q->number << "-" << p->number;
}
return branString.str();
}
set<int> getAffectedNodes(pllInstance* tr, nodeptr p) {
set<int> nodeSet;
nodeptr q = p->back;
nodeptr p_nei = p->next;
nodeptr q_nei = q->next;
nodeSet.insert(p->number);
nodeSet.insert(q->number);
while (p_nei != p) {
nodeptr nei = p_nei->back;
if (isTip(nei->number, tr->mxtips)) {
nodeSet.insert(nei->number);
} else {
nodeSet.insert(nei->number);
nodeSet.insert(nei->next->back->number);
nodeSet.insert(nei->next->next->back->number);
}
p_nei = p_nei->next;
}
while (q_nei != q) {
nodeptr nei = q_nei->back;
if (isTip(nei->number, tr->mxtips)) {
nodeSet.insert(nei->number);
} else {
nodeSet.insert(nei->number);
nodeSet.insert(nei->next->back->number);
nodeSet.insert(nei->next->next->back->number);
}
q_nei = q_nei->next;
}
return nodeSet;
}
void pllEvalAllNNIs(pllInstance *tr, partitionList *pr, SearchInfo &searchinfo) {
/* DTH: mimic IQTREE::optimizeNNI 's first call to IQTREE::saveCurrentTree */
if((globalParams->online_bootstrap == PLL_TRUE) &&
(globalParams->gbo_replicates > 0)){
tr->fastScaling = PLL_FALSE;
pllEvaluateLikelihood(tr, pr, tr->start, PLL_FALSE, PLL_TRUE);
pllSaveCurrentTree(tr, pr, tr->start);
}
nodeptr p = tr->start->back;
nodeptr q = p->next;
while (q != p) {
evalNNIForSubtree(tr, pr, q->back, searchinfo);
q = q->next;
}
}
/*
void pllSaveQuartetForSubTree(pllInstance *tr, nodeptr p, SearchInfo &searchinfo) {
if (!isTip(p->number, tr->mxtips) && !isTip(p->back->number, tr->mxtips)) {
evalNNIForBran(tr, pr, p, searchinfo);
nodeptr q = p->next;
while (q != p) {
pllSaveQuartetForSubTree(tr, q->back, searchinfo);
q = q->next;
}
}
}
void pllSaveAllQuartet(pllInstance *tr, SearchInfo &searchinfo) {
nodeptr p = tr->start->back;
nodeptr q = p->next;
while (q != p) {
pllSaveQuartetForSubTree(tr, q->back, searchinfo);
}
}
*/
double pllDoNNISearch(pllInstance* tr, partitionList *pr, SearchInfo &searchinfo) {
double initLH = tr->likelihood;
double finalLH = initLH;
vector<pllNNIMove> selectedNNIs;
unordered_set<int> selectedNodes;
int numBranches = pr->perGeneBranchLengths ? pr->numberOfPartitions : 1;
/* data structure to store the initial tree topology + branch length */
topol* curTree = _setupTopol(tr);
saveTree(tr, curTree, numBranches);
/* evaluate NNIs */
pllEvalAllNNIs(tr, pr, searchinfo);
if (globalParams->speednni) {
searchinfo.aBranches.clear();
}
/* apply non-conflicting positive NNIs */
if (searchinfo.posNNIList.size() != 0) {
sort(searchinfo.posNNIList.begin(), searchinfo.posNNIList.end(), comparePLLNNIMove);
if (verbose_mode >= VB_DEBUG) {
cout << "curScore: " << searchinfo.curLogl << endl;
for (int i = 0; i < searchinfo.posNNIList.size(); i++) {
cout << "Logl of positive NNI " << i << " : " << searchinfo.posNNIList[i].likelihood << endl;
}
}
for (vector<pllNNIMove>::reverse_iterator rit = searchinfo.posNNIList.rbegin(); rit != searchinfo.posNNIList.rend(); ++rit) {
if (selectedNodes.find((*rit).p->number) == selectedNodes.end() && selectedNodes.find((*rit).p->back->number) == selectedNodes.end()) {
selectedNNIs.push_back((*rit));
selectedNodes.insert((*rit).p->number);
selectedNodes.insert((*rit).p->back->number);
} else {
continue;
}
}
/* Applying all independent NNI moves */
searchinfo.curNumAppliedNNIs = selectedNNIs.size();
for (vector<pllNNIMove>::iterator it = selectedNNIs.begin(); it != selectedNNIs.end(); it++) {
/* do the topological change */
doOneNNI(tr, pr, (*it).p, (*it).nniType, TOPO_ONLY);
if (globalParams->speednni) {
vector<string> aBranches = getAffectedBranches(tr, (*it).p);
searchinfo.aBranches.insert(aBranches.begin(), aBranches.end());
}
updateBranchLengthForNNI(tr, pr, (*it));
if (numBranches > 1 && !tr->useRecom) {
pllUpdatePartials(tr, pr, (*it).p, PLL_TRUE);
pllUpdatePartials(tr, pr, (*it).p->back, PLL_TRUE);
} else {
pllUpdatePartials(tr, pr, (*it).p, PLL_FALSE);
pllUpdatePartials(tr, pr, (*it).p->back, PLL_FALSE);
}
}
if (selectedNNIs.size() != 0) {
//pllEvaluateLikelihood(tr, pr, tr->start, PLL_FALSE, PLL_FALSE);
pllOptimizeBranchLengths(tr, pr, 1);
if (globalParams->count_trees) {
countDistinctTrees(tr, pr);
}
int numNNI = selectedNNIs.size();
/* new tree likelihood should not be smaller the likelihood of the computed best NNI */
while (tr->likelihood < selectedNNIs.back().likelihood) {
if (numNNI == 1) {
printf("ERROR: new logl=%10.4f after applying only the best NNI < best NNI logl=%10.4f\n",
tr->likelihood, selectedNNIs[0].likelihood);
ASSERT(0);
} else {
cout << "Best logl: " << selectedNNIs.back().likelihood << " / " << "NNI step " << searchinfo.curNumNNISteps<< " / Applying " << numNNI << " NNIs give logl: " << tr->likelihood << " (worse than best)";
cout << " / Roll back tree ... " << endl;
//restoreTL(rl, tr, 0, pr->perGeneBranchLengths ? pr->numberOfPartitions : 1);
if (!restoreTree(curTree, tr, pr)) {
printf("ERROR: failed to roll back tree \n");
ASSERT(0);
}
// If tree log-likelihood decreases only apply the best NNI
numNNI = 1;
int count = numNNI;
for (vector<pllNNIMove>::reverse_iterator rit = selectedNNIs.rbegin(); rit != selectedNNIs.rend(); ++rit) {
doOneNNI(tr, pr, (*rit).p, (*rit).nniType, TOPO_ONLY);
updateBranchLengthForNNI(tr, pr, (*rit));
if (numBranches > 1 && !tr->useRecom) {
pllUpdatePartials(tr, pr, (*rit).p, PLL_TRUE);
pllUpdatePartials(tr, pr, (*rit).p->back, PLL_TRUE);
} else {
pllUpdatePartials(tr, pr, (*rit).p, PLL_FALSE);
pllUpdatePartials(tr, pr, (*rit).p->back, PLL_FALSE);
}
count--;
if (count == 0) {
break;
}
}
//pllEvaluateLikelihood(tr, pr, tr->start, PLL_FALSE, PLL_FALSE);
pllOptimizeBranchLengths(tr, pr, 1);
//cout << "Number of NNIs reduced to " << numNNI << ": " << tr->likelihood << endl;
/* Only apply the best NNI after the tree has been rolled back */
searchinfo.curNumAppliedNNIs = numNNI;
}
}
if (tr->likelihood - initLH < 0.1) {
searchinfo.curNumAppliedNNIs = 0;
}
finalLH = tr->likelihood;
}
} else {
searchinfo.curNumAppliedNNIs = 0;
}
//freeTopol(curTree);
return finalLH;
}
void updateBranchLengthForNNI(pllInstance* tr, partitionList *pr, pllNNIMove &nni) {
int numBranches = pr->perGeneBranchLengths ? pr->numberOfPartitions : 1;
/* apply branch lengths */
for (int i = 0; i < numBranches; i++) {
nni.p->z[i] = nni.z0[i];
nni.p->back->z[i] = nni.z0[i];
nni.p->next->z[i] = nni.z1[i];
nni.p->next->back->z[i] = nni.z1[i];
nni.p->next->next->z[i] = nni.z2[i];
nni.p->next->next->back->z[i] = nni.z2[i];
nni.p->back->next->z[i] = nni.z3[i];
nni.p->back->next->back->z[i] = nni.z3[i];
nni.p->back->next->next->z[i] = nni.z4[i];
nni.p->back->next->next->back->z[i] = nni.z4[i];
}
/* update partial likelihood */
// if (numBranches > 1 && !tr->useRecom) {
// pllNewviewGeneric(tr, pr, nni.p, PLL_TRUE);
// pllNewviewGeneric(tr, pr, nni.p->back, PLL_TRUE);
// } else {
// pllNewviewGeneric(tr, pr, nni.p, PLL_FALSE);
// pllNewviewGeneric(tr, pr, nni.p->back, PLL_FALSE);
// }
}
void pllOptimizeOneBranch(pllInstance *tr, partitionList *pr, nodeptr p) {
nodeptr q;
int i;
double z[PLL_NUM_BRANCHES], z0[PLL_NUM_BRANCHES];
int numBranches = pr->perGeneBranchLengths ? pr->numberOfPartitions : 1;
#ifdef _DEBUG_UPDATE
double
startLH;
pllEvaluateLikelihood (tr, p);
startLH = tr->likelihood;
#endif
q = p->back;
for(i = 0; i < numBranches; i++)
z0[i] = q->z[i];
if(numBranches > 1)
makenewzGeneric(tr, pr, p, q, z0, PLL_ITERATIONS, z, PLL_TRUE);
else
makenewzGeneric(tr, pr, p, q, z0, PLL_ITERATIONS, z, PLL_FALSE);
for(i = 0; i < numBranches; i++)
{
if(!tr->partitionConverged[i])
{
if(PLL_ABS(z[i] - z0[i]) > PLL_DELTAZ)
{
tr->partitionSmoothed[i] = PLL_FALSE;
}
p->z[i] = q->z[i] = z[i];
}
}
#ifdef _DEBUG_UPDATE
pllEvaluateLikelihood (tr, p);
if(tr->likelihood <= startLH)
{
if(fabs(tr->likelihood - startLH) > 0.01)
{
printf("%f %f\n", startLH, tr->likelihood);
ASSERT(0);
}
}
#endif
}
double doOneNNI(pllInstance *tr, partitionList *pr, nodeptr p, int swap, NNI_Type nni_type, SearchInfo *searchinfo) {
ASSERT(swap == 0 || swap == 1);
nodeptr q;
nodeptr tmp;
q = p->back;
ASSERT(!isTip(q->number, tr->mxtips));
ASSERT(!isTip(p->number, tr->mxtips));
int numBranches = pr->perGeneBranchLengths ? pr->numberOfPartitions : 1;
if (swap == 1) {
tmp = p->next->back;
hookup(p->next, q->next->back, q->next->z, numBranches);
hookup(q->next, tmp, tmp->z, numBranches);
} else {
tmp = p->next->next->back;
hookup(p->next->next, q->next->back, q->next->z, numBranches);
hookup(q->next, tmp, tmp->z, numBranches);
}
if (nni_type == TOPO_ONLY) {
return 0.0;
}
if (numBranches > 1 && !tr->useRecom) {
pllUpdatePartials(tr, pr, p, PLL_TRUE);
pllUpdatePartials(tr, pr, q, PLL_TRUE);
} else {
pllUpdatePartials(tr, pr, p, PLL_FALSE);
pllUpdatePartials(tr, pr, q, PLL_FALSE);
}
// Optimize the central branch
pllOptimizeOneBranch(tr, pr, p);
if((globalParams->online_bootstrap == PLL_TRUE) && (globalParams->gbo_replicates > 0)){
tr->fastScaling = PLL_FALSE;
pllEvaluateLikelihood(tr, pr, p, PLL_FALSE, PLL_TRUE); // DTH: modified the last arg
pllSaveCurrentTree(tr, pr, p);
}else{
pllEvaluateLikelihood(tr, pr, p, PLL_FALSE, PLL_FALSE);
}
// if after optimizing the central branch we already obtain better logl
// then there is no need for optimizing other branches
if (tr->likelihood > searchinfo->curLogl) {
return tr->likelihood;
}
// Optimize 4 other branches
if (nni_type == NNI5) {
if (numBranches > 1 && !tr->useRecom) {
pllUpdatePartials(tr, pr, q, PLL_TRUE);
} else {
pllUpdatePartials(tr, pr, q, PLL_FALSE);
}
nodeptr r;
r = p->next;
if (numBranches > 1 && !tr->useRecom) {
pllUpdatePartials(tr, pr, r, PLL_TRUE);
} else {
pllUpdatePartials(tr, pr, r, PLL_FALSE);
}
pllOptimizeOneBranch(tr, pr, r);
// pllEvaluateLikelihood(tr, pr, p, PLL_FALSE, PLL_FALSE);
// if (tr->likelihood > searchinfo->curLogl) {
// return tr->likelihood;
// }
r = p->next->next;
if (numBranches > 1 && !tr->useRecom)
pllUpdatePartials(tr, pr, r, PLL_TRUE);
else
pllUpdatePartials(tr, pr, r, PLL_FALSE);
pllOptimizeOneBranch(tr, pr, r);
// pllEvaluateLikelihood(tr, pr, p, PLL_FALSE, PLL_FALSE);
// if (tr->likelihood > searchinfo->curLogl) {
// return tr->likelihood;
// }
if (numBranches > 1 && !tr->useRecom)
pllUpdatePartials(tr, pr, p, PLL_TRUE);
else
pllUpdatePartials(tr, pr, p, PLL_FALSE);
pllOptimizeOneBranch(tr, pr, p);
// pllEvaluateLikelihood(tr, pr, p, PLL_FALSE, PLL_FALSE);
// if (tr->likelihood > searchinfo->curLogl) {
// return tr->likelihood;
// }
// optimize 2 branches at node q
r = q->next;
if (numBranches > 1 && !tr->useRecom)
pllUpdatePartials(tr, pr, r, PLL_TRUE);
else
pllUpdatePartials(tr, pr, r, PLL_FALSE);
pllOptimizeOneBranch(tr, pr, r);
// pllEvaluateLikelihood(tr, pr, p, PLL_FALSE, PLL_FALSE);
// if (tr->likelihood > searchinfo->curLogl) {
// return tr->likelihood;
// }
r = q->next->next;
if (numBranches > 1 && !tr->useRecom)
pllUpdatePartials(tr, pr, r, PLL_TRUE);
else
pllUpdatePartials(tr, pr, r, PLL_FALSE);
pllOptimizeOneBranch(tr, pr, r);
if((globalParams->online_bootstrap == PLL_TRUE) &&
(globalParams->gbo_replicates > 0)){
tr->fastScaling = PLL_FALSE;
pllEvaluateLikelihood(tr, pr, r, PLL_FALSE, PLL_TRUE); // DTH: modified the last arg
pllSaveCurrentTree(tr, pr, r);
}else{
pllEvaluateLikelihood(tr, pr, r, PLL_FALSE, PLL_FALSE);
}
}
return tr->likelihood;
}
double estBestLoglImp(SearchInfo* searchinfo) {
double res = 0.0;
int index = floor(searchinfo->deltaLogl.size() * 5 / 100);
set<double>::reverse_iterator ri;
for (ri = searchinfo->deltaLogl.rbegin(); ri != searchinfo->deltaLogl.rend(); ++ri) {
//cout << (*ri) << " ";
--index;
if (index == 0) {
res = (*ri);
break;
}
}
//cout << res << endl;
//cout << searchinfo->deltaLogl.size() << endl;
return res;
}
string convertQuartet2String(nodeptr p) {
nodeptr q = p->back;
int pNr = p->number;
int qNr = q->number;
int pNei1Nr = p->next->back->number;
int pNei2Nr = p->next->next->back->number;
int qNei1Nr = q->next->back->number;
int qNei2Nr = q->next->next->back->number;
stringstream middle;
stringstream left;
stringstream right;
stringstream res;
if (pNr < qNr) {
middle << "-" << pNr << "-" << qNr << "-";
} else {
middle << "-" << qNr << "-" << pNr << "-";
}
if (pNei1Nr < pNei2Nr) {
left << pNei1Nr << "-" << pNei2Nr;
} else {
left << pNei2Nr << "-" << pNei1Nr;
}
if (qNei1Nr < qNei2Nr) {
right << qNei1Nr << "-" << qNei2Nr;
} else {
right << qNei2Nr << "-" << qNei1Nr;
}
res << left.str() << middle.str() << right.str();
return res.str();
}
void countDistinctTrees(pllInstance* pllInst, partitionList *pllPartitions) {
pllTreeToNewick(pllInst->tree_string, pllInst, pllPartitions, pllInst->start->back, PLL_FALSE,
PLL_TRUE, PLL_FALSE, PLL_FALSE, PLL_FALSE, PLL_SUMMARIZE_LH, PLL_FALSE, PLL_FALSE);
PhyloTree mtree;
mtree.rooted = false;
mtree.aln = globalAlignment;
mtree.readTreeString(string(pllInst->tree_string));
// mtree.root = mtree.findNodeName(globalAlignment->getSeqName(0));
mtree.setRootNode(mtree.params->root);
ostringstream ostr;
mtree.printTree(ostr, WT_TAXON_ID | WT_SORT_TAXA);
string tree_str = ostr.str();
if (pllTreeCounter.find(tree_str) == pllTreeCounter.end()) {
// not found in hash_map
pllTreeCounter[tree_str] = 1;
} else {
// found in hash_map
pllTreeCounter[tree_str]++;
}
}
int evalNNIForBran(pllInstance* tr, partitionList *pr, nodeptr p, SearchInfo &searchinfo) {
nodeptr q = p->back;
ASSERT(!isTip(p->number, tr->mxtips));
ASSERT(!isTip(q->number, tr->mxtips));
int numBranches = pr->perGeneBranchLengths ? pr->numberOfPartitions : 1;
int numPosNNI = 0;
int i;
pllNNIMove nni0; // dummy NNI to store backup information
nni0.p = p;
nni0.nniType = 0;
nni0.likelihood = searchinfo.curLogl;
for (i = 0; i < PLL_NUM_BRANCHES; i++) {
nni0.z0[i] = p->z[i];
nni0.z1[i] = p->next->z[i];
nni0.z2[i] = p->next->next->z[i];
nni0.z3[i] = q->next->z[i];
nni0.z4[i] = q->next->next->z[i];
}
pllNNIMove bestNNI;
/* do an NNI move of type 1 */
double lh1 = doOneNNI(tr, pr, p, 0, searchinfo.nni_type, &searchinfo);
if (globalParams->count_trees)
countDistinctTrees(tr, pr);
pllNNIMove nni1;
nni1.p = p;
nni1.nniType = 0;
// Store the optimized branch lengths
for (i = 0; i < PLL_NUM_BRANCHES; i++) {
nni1.z0[i] = p->z[i];
nni1.z1[i] = p->next->z[i];
nni1.z2[i] = p->next->next->z[i];
nni1.z3[i] = q->next->z[i];
nni1.z4[i] = q->next->next->z[i];
}
nni1.likelihood = lh1;
nni1.loglDelta = lh1 - nni0.likelihood;
nni1.negLoglDelta = -nni1.loglDelta;
/* Restore previous NNI move */
doOneNNI(tr, pr, p, 0, TOPO_ONLY);
/* Restore the old branch length */
for (i = 0; i < PLL_NUM_BRANCHES; i++) {
p->z[i] = nni0.z0[i];
q->z[i] = nni0.z0[i];
p->next->z[i] = nni0.z1[i];
p->next->back->z[i] = nni0.z1[i];
p->next->next->z[i] = nni0.z2[i];
p->next->next->back->z[i] = nni0.z2[i];
q->next->z[i] = nni0.z3[i];
q->next->back->z[i] = nni0.z3[i];
q->next->next->z[i] = nni0.z4[i];
q->next->next->back->z[i] = nni0.z4[i];
}
/* do an NNI move of type 2 */
double lh2 = doOneNNI(tr, pr, p, 1, searchinfo.nni_type, &searchinfo);
if (globalParams->count_trees)
countDistinctTrees(tr, pr);
// Create the nniMove struct to store this move
pllNNIMove nni2;
nni2.p = p;
nni2.nniType = 1;
// Store the optimized central branch length
for (i = 0; i < PLL_NUM_BRANCHES; i++) {
nni2.z0[i] = p->z[i];
nni2.z1[i] = p->next->z[i];
nni2.z2[i] = p->next->next->z[i];
nni2.z3[i] = q->next->z[i];
nni2.z4[i] = q->next->next->z[i];
}
nni2.likelihood = lh2;
nni2.loglDelta = lh2 - nni0.likelihood;
nni2.negLoglDelta = -nni2.loglDelta;
if (nni2.likelihood > nni1.likelihood) {
bestNNI = nni2;
} else {
bestNNI = nni1;
}
if (bestNNI.likelihood > searchinfo.curLogl + 1e-6) {
numPosNNI++;
searchinfo.posNNIList.push_back(bestNNI);
}
/* Restore previous NNI move */
doOneNNI(tr, pr, p, 1, TOPO_ONLY);
/* Restore the old branch length */
for (i = 0; i < PLL_NUM_BRANCHES; i++) {
p->z[i] = nni0.z0[i];
q->z[i] = nni0.z0[i];
p->next->z[i] = nni0.z1[i];
p->next->back->z[i] = nni0.z1[i];
p->next->next->z[i] = nni0.z2[i];
p->next->next->back->z[i] = nni0.z2[i];
q->next->z[i] = nni0.z3[i];
q->next->back->z[i] = nni0.z3[i];
q->next->next->z[i] = nni0.z4[i];
q->next->next->back->z[i] = nni0.z4[i];
}
// Re-compute the partial likelihood vectors
// TODO: One could save these instead of recomputation
if (numBranches > 1 && !tr->useRecom) {
pllUpdatePartials(tr, pr, p, PLL_TRUE);
pllUpdatePartials(tr, pr, p->back, PLL_TRUE);
} else {
pllUpdatePartials(tr, pr, p, PLL_FALSE);
pllUpdatePartials(tr, pr, p->back, PLL_FALSE);
}
return numPosNNI;
}
//void recomputePartial(pllInstance tr, partitionList pr, nodeptr p) {
// if (numBranches > 1 && !tr->useRecom) {
// pllUpdatePartials(tr, pr, p, PLL_TRUE);
// pllUpdatePartials(tr, pr, p->back, PLL_TRUE);
// } else {
// pllUpdatePartials(tr, pr, p, PLL_FALSE);
// pllUpdatePartials(tr, pr, p->back, PLL_FALSE);
// }
//}
bool isAffectedBranch(nodeptr p, SearchInfo &searchinfo) {
string branString = getBranString(p);
if (searchinfo.aBranches.find(branString) != searchinfo.aBranches.end()) {
return true;
} else {
return false;
}
}
void evalNNIForSubtree(pllInstance* tr, partitionList *pr, nodeptr p, SearchInfo &searchinfo) {
if (!isTip(p->number, tr->mxtips) && !isTip(p->back->number, tr->mxtips)) {
if (globalParams->speednni && searchinfo.curNumNNISteps != 1) {
if (isAffectedBranch(p, searchinfo)) {
evalNNIForBran(tr, pr, p, searchinfo);
}
} else {
evalNNIForBran(tr, pr, p, searchinfo);
}
nodeptr q = p->next;
while (q != p) {
evalNNIForSubtree(tr, pr, q->back, searchinfo);
q = q->next;
}
}
}
/**
* DTH:
* The PLL version of saveCurrentTree function
* @param tr: the tree (a pointer to a pllInstance)
* @param pr: pointer to a partitionList (this one keeps tons of tree info)
* @param p: root?
*/
void pllSaveCurrentTree(pllInstance* tr, partitionList *pr, nodeptr p){
double cur_logl = tr->likelihood;
struct pllHashItem * item_ptr = (struct pllHashItem *) malloc(sizeof(struct pllHashItem));
item_ptr->data = (int *) malloc(sizeof(int));
item_ptr->next = NULL;
item_ptr->str = NULL;
unsigned int tree_index = -1;
char * tree_str = NULL;
pllTree2StringREC(tr->tree_string, tr, pr, tr->start->back, PLL_FALSE,
PLL_FALSE, PLL_FALSE, PLL_FALSE, PLL_TRUE, PLL_SUMMARIZE_LH, PLL_FALSE, PLL_FALSE);
tree_str = (char *) malloc (strlen(tr->tree_string) + 1);
#ifdef CLANG_UNDER_VS
strcpy_s(tree_str, strlen(tr->tree_string) + 1, tr->tree_string);
#else
strcpy(tree_str, tr->tree_string);
#endif
pllBoolean is_stored = PLL_FALSE;
if(is_stored){ // if found the tree_str
pllUFBootDataPtr->duplication_counter++;
tree_index = *((int *)item_ptr->data);
if (cur_logl <= pllUFBootDataPtr->treels_logl[tree_index] + 1e-4) {
if (cur_logl < pllUFBootDataPtr->treels_logl[tree_index] - 5.0)
if (verbose_mode >= VB_MED)
printf("Current lh %f is much worse than expected %f\n",
cur_logl, pllUFBootDataPtr->treels_logl[tree_index]);
return;
}
if (verbose_mode >= VB_MAX)
printf("Updated logl %f to %f\n", pllUFBootDataPtr->treels_logl[tree_index], cur_logl);
pllUFBootDataPtr->treels_logl[tree_index] = cur_logl;
if (pllUFBootDataPtr->boot_samples == NULL) {
(pllUFBootDataPtr->treels_ptnlh)[tree_index] =
(double *) malloc(pllUFBootDataPtr->n_patterns * sizeof(double));
pllComputePatternLikelihood(tr, (pllUFBootDataPtr->treels_ptnlh)[tree_index], &cur_logl);
return;
}
if (verbose_mode >= VB_MAX)
printf("Update treels_logl[%d] := %f\n", tree_index, cur_logl);
} else {
if (pllUFBootDataPtr->logl_cutoff != 0.0 && cur_logl <= pllUFBootDataPtr->logl_cutoff + 1e-4){
free(tree_str); //James B. 23-Jul-2020 (memory leak)
free(item_ptr->data); //James B. 23-Jul-2020 (memory leak)
free(item_ptr); //James B. 23-Jul-2020 (memory leak)
return;
}
if (pllUFBootDataPtr->treels_size == pllUFBootDataPtr->candidate_trees_count) {
pllResizeUFBootData();
}
tree_index = pllUFBootDataPtr->candidate_trees_count;
pllUFBootDataPtr->candidate_trees_count++;
pllUFBootDataPtr->treels_logl[tree_index] = cur_logl;
if (verbose_mode >= VB_MAX)
printf("Add treels_logl[%d] := %f\n", tree_index, cur_logl);
}
//if (write_intermediate_trees)
// printTree(out_treels, WT_NEWLINE | WT_BR_LEN);
double *pattern_lh = (double *) malloc(pllUFBootDataPtr->n_patterns * sizeof(double));
if (!pattern_lh) {
outError("Not enough dynamic memory!");
}
pllComputePatternLikelihood(tr, pattern_lh, &cur_logl);
if (pllUFBootDataPtr->boot_samples == NULL) {
// for runGuidedBootstrap
pllUFBootDataPtr->treels_ptnlh[tree_index] = pattern_lh;
free(tree_str); //James B. 23-Jul-2020 (memory leak)
free(item_ptr->data); //James B. 23-Jul-2020 (memory leak)
free(item_ptr); //James B. 23-Jul-2020 (memory leak)
}
else {
// online bootstrap
int nptn = pllUFBootDataPtr->n_patterns;
int updated = 0;
int nsamples = globalParams->gbo_replicates;
for (int sample = 0; sample < nsamples; sample++) {
double rell = 0.0;
for (int ptn = 0; ptn < nptn; ptn++)
rell += pattern_lh[ptn] * pllUFBootDataPtr->boot_samples[sample][ptn];
if (rell > pllUFBootDataPtr->boot_logl[sample] + globalParams->ufboot_epsilon ||
(rell > pllUFBootDataPtr->boot_logl[sample] - globalParams->ufboot_epsilon &&
random_double() <= 1.0 / (pllUFBootDataPtr->boot_counts[sample] + 1))) {
{
is_stored = pllHashSearch(pllUFBootDataPtr->treels, tree_str, &(item_ptr->data));
if (is_stored)
tree_index = *((int*)item_ptr->data);
else {
*((int*)item_ptr->data) = tree_index = pllUFBootDataPtr->candidate_trees_count - 1;
item_ptr->str = tree_str;
pllHashAdd(pllUFBootDataPtr->treels, pllHashString(tree_str, pllUFBootDataPtr->treels->size), tree_str, item_ptr->data);
}
}
if (rell <= pllUFBootDataPtr->boot_logl[sample] +
globalParams->ufboot_epsilon) {
pllUFBootDataPtr->boot_counts[sample]++;
}
else {
pllUFBootDataPtr->boot_counts[sample] = 1;
}
if (rell > pllUFBootDataPtr->boot_logl[sample])
pllUFBootDataPtr->boot_logl[sample] = rell;
pllUFBootDataPtr->boot_trees[sample] = tree_index;
updated++;
}
}
}
if (pllUFBootDataPtr->boot_samples){
free(pattern_lh);
pllUFBootDataPtr->treels_ptnlh[tree_index] = NULL;
}
}
/**
* DTH:
* Extract the array of site log likelihood to be kept in ptnlh
* And update *cur_log
* @param tr: the tree (pointer to an pllInstance)
* @param ptnlh: to-be-kept array of site log likelihood
* @param cur_logl: pointer to current tree log likelihood
*/
void pllComputePatternLikelihood(pllInstance* tr, double * ptnlh, double * cur_logl){
int i;
double tree_logl = 0;
for(i = 0; i < pllUFBootDataPtr->n_patterns; i++){
ptnlh[i] = tr->lhs[i];
tree_logl += tr->lhs[i] * tr->aliaswgt[i];
}
*cur_logl = tree_logl;
}
/**
* DTH:
* Resize some of the arrays in UFBootData if they're full
* Along with update treels_size (to track the size of these arrays)
*/
void pllResizeUFBootData(){
int count = pllUFBootDataPtr->candidate_trees_count;
pllUFBootDataPtr->treels_size = 2 * count;
double * rtreels_logl =
(double *) malloc(2 * count * (sizeof(double)));
if(!rtreels_logl) outError("Not enough dynamic memory!");
memcpy(rtreels_logl, pllUFBootDataPtr->treels_logl, count * sizeof(double));
free(pllUFBootDataPtr->treels_logl);
pllUFBootDataPtr->treels_logl = rtreels_logl;
double ** rtreels_ptnlh =
(double **) malloc(2 * count * (sizeof(double *)));
if(!rtreels_ptnlh) outError("Not enough dynamic memory!");
memset(rtreels_ptnlh, 0, 2 * count * sizeof(double *));
memcpy(rtreels_ptnlh, pllUFBootDataPtr->treels_ptnlh, count * sizeof(double *));
free(pllUFBootDataPtr->treels_ptnlh);
pllUFBootDataPtr->treels_ptnlh = rtreels_ptnlh;
}
/**