//void NNI(tree *T, double **avgDistArray, int *count)
void NNI(tree *T, double **avgDistArray, int *count, double **D, int numSpecies)
{
edge *e, *centerEdge;
edge **edgeArray;
int *location;
int *p,*q;
int i,j;
int possibleSwaps;
double *weights;
p = initPerm(T->size+1);
q = initPerm(T->size+1);
edgeArray = (edge **) malloc((T->size+1)*sizeof(double));
weights = (double *) malloc((T->size+1)*sizeof(double));
location = (int *) malloc((T->size+1)*sizeof(int));
double epsilon = 0.0;
for (i=0; i<numSpecies; i++)
for (j=0; j<numSpecies; j++)
epsilon += D[i][j];
epsilon = (epsilon / (numSpecies * numSpecies)) * EPSILON;
for (i=0;i<T->size+1;i++)
{
weights[i] = 0.0;
location[i] = NONE;
}
e = findBottomLeft(T->root->leftEdge);
/* *count = 0; */
while (NULL != e)
{
edgeArray[e->head->index+1] = e;
location[e->head->index+1] =
NNIEdgeTest(e,T,avgDistArray,weights + e->head->index + 1);
e = depthFirstTraverse(T,e);
}
possibleSwaps = makeThreshHeap(p,q,weights,T->size+1,0.0);
permInverse(p,q,T->size+1);
/*we put the negative values of weights into a heap, indexed by p
with the minimum value pointed to by p[1]*/
/*p[i] is index (in edgeArray) of edge with i-th position
in the heap, q[j] is the position of edge j in the heap */
while (weights[p[1]] + epsilon < 0)
{
centerEdge = edgeArray[p[1]];
(*count)++;
T->weight = T->weight + weights[p[1]];
NNItopSwitch(T,edgeArray[p[1]],location[p[1]],avgDistArray);
location[p[1]] = NONE;
weights[p[1]] = 0.0; /*after the NNI, this edge is in optimal
configuration*/
popHeap(p,q,weights,possibleSwaps--,1);
/*but we must retest the other four edges*/
e = centerEdge->head->leftEdge;
NNIRetestEdge(p,q,e,T,avgDistArray,weights,location,&possibleSwaps);
e = centerEdge->head->rightEdge;
NNIRetestEdge(p,q,e,T,avgDistArray,weights,location,&possibleSwaps);
e = siblingEdge(centerEdge);
NNIRetestEdge(p,q,e,T,avgDistArray,weights,location,&possibleSwaps);
e = centerEdge->tail->parentEdge;
NNIRetestEdge(p,q,e,T,avgDistArray,weights,location,&possibleSwaps);
}
free(p);
free(q);
free(location);
free(edgeArray);
}
//void bNNI(tree *T, double **avgDistArray, int *count)
void bNNI(tree *T, double **avgDistArray, int *count, double **D, int numSpecies)
{
edge *e;//, *centerEdge deleted by EP, 2013-09-26, see also below
edge **edgeArray;
int *p, *location, *q;
int i,j;
int possibleSwaps;
double *weights;
p = initPerm(T->size+1);
q = initPerm(T->size+1);
edgeArray = (edge **) malloc((T->size+1)*sizeof(double));
weights = (double *) malloc((T->size+1)*sizeof(double));
location = (int *) malloc((T->size+1)*sizeof(int));
double epsilon = 0.0;
for (i=0; i<numSpecies; i++)
for (j=0; j<numSpecies; j++)
epsilon += D[i][j];
epsilon = (epsilon / (numSpecies * numSpecies)) * EPSILON;
for (i=0;i<T->size+1;i++)
{
weights[i] = 0.0;
location[i] = NONE;
}
/* if (verbose)
{
assignBMEWeights(T,avgDistArray);
weighTree(T);
}*/
e = findBottomLeft(T->root->leftEdge);
while (NULL != e)
{
edgeArray[e->head->index+1] = e;
location[e->head->index+1] =
bNNIEdgeTest(e,T,avgDistArray,weights + e->head->index + 1);
e = depthFirstTraverse(T,e);
}
possibleSwaps = makeThreshHeap(p,q,weights,T->size+1,0.0);
permInverse(p,q,T->size+1);
/*we put the negative values of weights into a heap, indexed by p
with the minimum value pointed to by p[1]*/
/*p[i] is index (in edgeArray) of edge with i-th position
in the heap, q[j] is the position of edge j in the heap */
while (weights[p[1]] + epsilon < 0)
{
/* centerEdge = edgeArray[p[1]]; apparently unused later, deleted by EP, 2013-09-26 */
(*count)++;
/* if (verbose)
{
T->weight = T->weight + weights[p[1]];
printf("New tree weight is %lf.\n",T->weight);
}*/
bNNItopSwitch(T,edgeArray[p[1]],location[p[1]],avgDistArray);
location[p[1]] = NONE;
weights[p[1]] = 0.0; /*after the bNNI, this edge is in optimal
configuration*/
popHeap(p,q,weights,possibleSwaps--,1);
/*but we must retest the other edges of T*/
/*CHANGE 2/28/2003 expanding retesting to _all_ edges of T*/
e = depthFirstTraverse(T,NULL);
while (NULL != e)
{
bNNIRetestEdge(p,q,e,T,avgDistArray,weights,location,&possibleSwaps);
e = depthFirstTraverse(T,e);
}
}
free(p);
free(q);
free(location);
free(edgeArray);
free(weights);
assignBMEWeights(T,avgDistArray);
}
void bNNI(meTree *T, double **avgDistArray, int *count)
{
meEdge *e, *centerEdge;
meEdge **edgeArray;
int *p, *location, *q;
int i;
int possibleSwaps;
double *weights;
p = initPerm(T->size+1);
q = initPerm(T->size+1);
edgeArray = (meEdge **) malloc((T->size+1)*sizeof(double));
weights = (double *) malloc((T->size+1)*sizeof(double));
location = (int *) malloc((T->size+1)*sizeof(int));
for (i=0;i<T->size+1;i++)
{
weights[i] = 0.0;
location[i] = NONE;
}
if (verbose)
{
assignBalWeights(T,avgDistArray);
weighTree(T);
}
e = findBottomLeft(T->root->leftEdge);
while (NULL != e)
{
edgeArray[e->head->index+1] = e;
location[e->head->index+1] =
bNNIEdgeTest(e,T,avgDistArray,weights + e->head->index + 1);
e = depthFirstTraverse(T,e);
}
possibleSwaps = makeThreshHeap(p,q,weights,T->size+1,0.0);
permInverse(p,q,T->size+1);
/*we put the negative values of weights into a heap, indexed by p
with the minimum value pointed to by p[1]*/
/*p[i] is index (in edgeArray) of edge with i-th position
in the heap, q[j] is the position of edge j in the heap */
/*NOTE: the loop below should test that weights[p[1]] < 0, but
if compiled with optimization it is possible that weights[p[1]]
ends up negative and very small, so that changes to the heap
become cyclic and the loop becomes infinite. To avoid this
behavior, stop the loop short of 0.0. This is a workaround
until the roundoff sensitivity is removed algorithmically */
while (weights[p[1]] < -1e-8)
{
centerEdge = edgeArray[p[1]];
(*count)++;
if (verbose)
{
T->weight = T->weight + weights[p[1]];
printf("New tree weight is %lf.\n",T->weight);
}
bNNItopSwitch(T,edgeArray[p[1]],location[p[1]],avgDistArray);
location[p[1]] = NONE;
weights[p[1]] = 0.0; /*after the bNNI, this edge is in optimal
configuration*/
popHeap(p,q,weights,possibleSwaps--,1);
/*but we must retest the other edges of T*/
/*CHANGE 2/28/2003 expanding retesting to _all_ edges of T*/
e = depthFirstTraverse(T,NULL);
while (NULL != e)
{
bNNIRetestEdge(p,q,e,T,avgDistArray,weights,location,&possibleSwaps);
e = depthFirstTraverse(T,e);
}
}
free(p);
free(q);
free(location);
free(edgeArray);
assignBalWeights(T,avgDistArray);
}
void bNNI (tree *T, double **avgDistArray, int *count, FILE *statfile)
{
edge *e;
edge **edgeArray;
int *p, *location, *q;
int i;
int possibleSwaps;
double *weights;
p = initPerm (T->size+1);
q = initPerm (T->size+1);
edgeArray = (edge **) mCalloc ((T->size+1), sizeof (edge *));
weights = (double *) mCalloc ((T->size+1), sizeof (double));
location = (int *) mCalloc ((T->size+1), sizeof (int));
for (i=0; i<T->size+1; i++)
{
weights[i] = 0.0;
location[i] = NONE;
}
assignBMEWeights (T, avgDistArray);
weighTree (T);
if (!isBoostrap)
{
if (statfile)
fprintf (statfile, "\tBefore NNI: tree length is %f.\n", T->weight);
if (verbose > 2)
Debug ( (char*)"Before NNI: tree length is %f.", T->weight);
else if (verbose > 1)
Message ( (char*)". Before NNI: tree length is %f.", T->weight);
}
e = findBottomLeft (T->root->leftEdge);
while (NULL != e)
{
edgeArray[e->head->index+1] = e;
location[e->head->index+1] = bNNIEdgeTest (e, T, avgDistArray,
weights + e->head->index + 1);
e = depthFirstTraverse (T,e);
}
possibleSwaps = makeThreshHeap (p, q, weights, T->size+1,0.0);
permInverse (p, q, T->size+1);
/* We put the negative values of weights into a heap, indexed by p
* with the minimum value pointed to by p[1]
* p[i] is index (in edgeArray) of edge with i-th position in the
* heap, q[j] is the position of edge j in the heap */
while (weights[p[1]] < -DBL_EPSILON)
{
(*count)++;
T->weight = T->weight + weights[p[1]];
if (!isBoostrap)
{
if (statfile)
fprintf (statfile, "\tNNI %5d: new tree length is %f.\n", *count, T->weight);
if (verbose > 2)
Debug ( (char*)"NNI %5d: new tree length is %f.", *count, T->weight);
else if (verbose > 1)
Message ( (char*)". NNI %5d: new tree length is %f.", *count, T->weight);
}
bNNItopSwitch (edgeArray[p[1]], location[p[1]], avgDistArray);
location[p[1]] = NONE;
weights[p[1]] = 0.0; //after the bNNI, this edge is in optimal configuration
popHeap (p, q, weights, possibleSwaps--, 1);
/* but we must retest the other edges of T */
/* CHANGE 2/28/2003 expanding retesting to _all_ edges of T */
e = depthFirstTraverse (T, NULL);
while (NULL != e)
{
bNNIRetestEdge (p, q, e, T, avgDistArray, weights, location, &possibleSwaps);
e = depthFirstTraverse (T, e);
}
}
free (p);
free (q);
free (location);
free (edgeArray);
free (weights);
assignBMEWeights (T, avgDistArray);
return;
}
