void newviewGenericAncestral (tree *tr, nodeptr p, boolean atRoot)
{
if(atRoot)
{
assert(!tr->multiGene);
tr->td[0].count = 1;
traversalInfoAncestralRoot(p, &(tr->td[0].ti[0]), &(tr->td[0].count), tr->mxtips, tr->numBranches);
if(tr->td[0].count > 1)
{
#ifdef _USE_PTHREADS
masterBarrier(THREAD_NEWVIEW_ANCESTRAL, tr);
#else
newviewIterativeAncestral(tr);
#endif
}
}
else
{
if(isTip(p->number, tr->mxtips))
return;
if(tr->multiGene)
assert(0);
else
{
tr->td[0].count = 1;
computeTraversalInfo(p, &(tr->td[0].ti[0]), &(tr->td[0].count), tr->mxtips, tr->numBranches);
if(tr->td[0].count > 1)
{
#ifdef _USE_PTHREADS
masterBarrier(THREAD_NEWVIEW_ANCESTRAL, tr);
#else
newviewIterativeAncestral(tr);
#endif
}
}
}
}
void evaluateGeneric (tree *tr, nodeptr p, boolean fullTraversal)
{
/* now this may be the entry point of the library to compute
the log like at a branch defined by p and p->back == q */
volatile double
result = 0.0;
nodeptr
q = p->back;
int
i,
model;
/* set the first entry of the traversal descriptor to contain the indices
of nodes p and q */
tr->td[0].ti[0].pNumber = p->number;
tr->td[0].ti[0].qNumber = q->number;
/* copy the branch lengths of the tree into the first entry of the traversal descriptor.
if -M is not used tr->numBranches must be 1 */
for(i = 0; i < tr->numBranches; i++)
tr->td[0].ti[0].qz[i] = q->z[i];
/* now compute how many conditionals must be re-computed/re-oriented by newview
to be able to calculate the likelihood at the root defined by p and q.
*/
/* one entry in the traversal descriptor is already used, hence set the tarversal length counter to 1 */
tr->td[0].count = 1;
/* do we need to recompute any of the vectors at or below p ? */
if(fullTraversal)
{
assert(isTip(p->number, tr->mxtips));
computeTraversalInfo(q, &(tr->td[0].ti[0]), &(tr->td[0].count), tr->mxtips, tr->numBranches, FALSE);
}
else
{
if(!p->x)
computeTraversalInfo(p, &(tr->td[0].ti[0]), &(tr->td[0].count), tr->mxtips, tr->numBranches, TRUE);
/* recompute/reorient any descriptors at or below q ?
computeTraversalInfo computes and stores the newview() to be executed for the traversal descriptor */
if(!q->x)
computeTraversalInfo(q, &(tr->td[0].ti[0]), &(tr->td[0].count), tr->mxtips, tr->numBranches, TRUE);
}
/* now we copy this partition execute mask into the traversal descriptor which must come from the
calling program, the logic of this should not form part of the library */
storeExecuteMaskInTraversalDescriptor(tr);
/* also store in the traversal descriptor that something has changed i.e., in the parallel case that the
traversal descriptor list of nodes needs to be broadcast once again */
tr->td[0].traversalHasChanged = TRUE;
evaluateIterative(tr);
if(0)
{
double
*recv = (double *)malloc(sizeof(double) * tr->NumberOfModels);
MPI_Allreduce(tr->perPartitionLH, recv, tr->NumberOfModels, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);
for(model = 0; model < tr->NumberOfModels; model++)
{
/* TODO ??? */
/*tr->perPartitionLH[model] = recv[model]; */
result += recv[model];
}
rax_free(recv);
}
else
{
double
*recv = (double *)malloc(sizeof(double) * tr->NumberOfModels);
MPI_Reduce(tr->perPartitionLH, recv, tr->NumberOfModels, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
MPI_Bcast(recv, tr->NumberOfModels, MPI_DOUBLE, 0, MPI_COMM_WORLD);
for(model = 0; model < tr->NumberOfModels; model++)
{
/* TODO ??? */
tr->perPartitionLH[model] = recv[model];
result += recv[model];
}
rax_free(recv);
}
/* set the tree data structure likelihood value to the total likelihood */
tr->likelihood = result;
/*
MPI_Barrier(MPI_COMM_WORLD);
printf("Process %d likelihood: %f\n", processID, tr->likelihood);
MPI_Barrier(MPI_COMM_WORLD);
*/
/* do some bookkeeping to have traversalHasChanged in a consistent state */
tr->td[0].traversalHasChanged = FALSE;
}