List *Path(World *world, Point *source, Point *destination)
{
int tentative_gscore;
List *result = NULL;
int tries = 0;
Hashmap *nodes = Hashmap_create(cmp, hash);
Hashmap *closedset = Hashmap_create(cmp, hash);
PQueue *openset = PQueue_create(cmp, hash);
Node *current;
Node *start = Node_create(source, 0, 0, NULL);
Hashmap_set(nodes, start, start);
start->fscore = start->gscore + heuristic_cost_estimate(start->point, destination);
PQueue_push(openset, start, start->fscore);
while(!PQueue_empty(openset) &&
tries < 300) {
tries++;
current = PQueue_pop(openset);
Hashmap_set(closedset, current, current);
if(POINT_EQ(current->point, destination)) {
result = reconstruct_path(current);
break;
} else {
List *neighbours = neighbours_list(world, current->point, destination, nodes);
LIST_FOREACH(neighbours, first, next, cur) {
Node *neighbour = cur->value;
if(Hashmap_get(closedset, neighbour) == NULL) {
tentative_gscore = current->gscore + 1;
if(!PQueue_contains(openset, neighbour) ||
tentative_gscore > neighbour->gscore) {
if(!PQueue_contains(openset, neighbour)) {
neighbour->came_from = current;
neighbour->gscore = tentative_gscore;
neighbour->fscore = neighbour->gscore + heuristic_cost_estimate(neighbour->point, destination);
PQueue_push(openset, neighbour, neighbour->fscore);
}
}
}
}
List_destroy(neighbours);
}
}
char *test_create()
{
map = Hashmap_create(NULL, NULL);
mu_assert(map != NULL, "Failed to create map.");
return NULL;
}
char *test_create()
{
map = Hashmap_create(NULL, NULL, DEFAULT_NUMBER_OF_BUCKETS);
mu_assert(map != NULL, "Failed to create map.");
return NULL;
}
Hashmap *Server_initialize()
{
Hashmap *store = Hashmap_create(NULL, NULL);
check(store != NULL, "Could not create hashmap");
return store;
error:
return NULL;
}
IntegerIndexedFeatures IntegerIndexedFeatures_create() {
IntegerIndexedFeatures imap = (IntegerIndexedFeatures) malloc(sizeof (struct IntegerIndexedFeatures));
check_mem(imap);
imap->feature_id = 0;
imap->map = Hashmap_create(feature_equal, feature_hash);
return imap;
error:
log_err("IntegerIndexedFeatures allocation error");
exit(1);
}
Object *Lobby_new()
{
Object *lobby = calloc(1, sizeof(Object));
check_mem(lobby);
lobby->type = tObject;
lobby->immortal = 1;
lobby->slots = Hashmap_create(NULL, NULL);
return lobby;
error:
return NULL;
}
PQueue *PQueue_create(PQueue_compare compare, PQueue_hash hash)
{
PQueue *p_queue = malloc(sizeof(PQueue));
check_mem(p_queue);
p_queue->heap = BHeap_create(PQueueNode_cmp, 10);
check_mem(p_queue->heap);
p_queue->map = Hashmap_create(compare, hash);
check_mem(p_queue->map);
return p_queue;
error:
if(p_queue) PQueue_destroy(p_queue);
return NULL;
}
Object *Object_new()
{
Object *object = calloc(1, sizeof(Object));
check_mem(object);
object->type = tObject;
object->refcount = 0;
object->immortal = 0;
object->native = 0;
object->parent = NULL;
object->slots = Hashmap_create(NULL, NULL);
return object;
error:
return NULL;
}
int main(int argc, char const *argv[])
{
Hashmap *map = Hashmap_create(NULL, Hashmap_fnv1a_hash);
char * test1 = "test1";
char * test2 = "test2";
char * test3 = "test3";
char *expect1 = "expect1";
char *expect2 = "expect2";
char *expect3 = "expect3";
int rc1 = Hashmap_set(map, &test1, &expect1);
int rc2 = Hashmap_set(map, &test2, &expect2);
int rc3 = Hashmap_set(map, &test3, &expect3);
int *res = Hashmap_get(map, &test1);
printf("res = %s\n", (char *)*res);
return 0;
}
Object*
Hash_new(Object *array_obj) {
DArray *array = (DArray*)array_obj->value.other;
int count = DArray_count(array);
assert(count % 2 == 0 && "Hash element count must be even.");
Hashmap *hash = Hashmap_create(String_compare, String_hash);
int i=0;
for(i=0; i < count; i += 2) {
Object *key = retain((Object*)DArray_at(array, i));
Object *value = retain((Object*)DArray_at(array, i+1));
assert(key->type == tString && "All hash keys must be strings");
Hashmap_set(hash, key, value, value->type);
}
Object *object = Object_new();
object->type = tHash;
object->value.other = hash;
Object_define_native_method(object, bfromcstr("[]"), Primitive_Hash_get, 1);
return object;
}
//Use the plausibility checker overhead
void plausibilityChecker(tree *tr, analdef *adef)
{
FILE
*treeFile,
*treeFile2,
*rfFile;
tree
*smallTree = (tree *)rax_malloc(sizeof(tree));
char
rfFileName[1024];
int
numberOfTreesAnalyzed = 0,
i;
double
avgRF = 0.0,
sumEffectivetime = 0.0;
/* set up an output file name */
strcpy(rfFileName, workdir);
strcat(rfFileName, "RAxML_RF-Distances.");
strcat(rfFileName, run_id);
rfFile = myfopen(rfFileName, "wb");
assert(adef->mode == PLAUSIBILITY_CHECKER);
/* open the big reference tree file and parse it */
treeFile = myfopen(tree_file, "r");
printBothOpen("Parsing reference tree %s\n", tree_file);
treeReadLen(treeFile, tr, FALSE, TRUE, TRUE, adef, TRUE, FALSE);
assert(tr->mxtips == tr->ntips);
/*************************************************************************************/
/* Preprocessing Step */
double
preprocesstime = gettime();
/* taxonToLabel[2*tr->mxtips - 2];
Array storing all 2n-2 labels from the preordertraversal: (Taxonnumber - 1) -> (Preorderlabel) */
int
*taxonToLabel = (int *)rax_malloc((2*tr->mxtips - 2) * sizeof(int)),
/* taxonHasDeg[2*tr->mxtips - 2]
Array used to store the degree of every taxon, is needed to extract Bipartitions from multifurcating trees
(Taxonnumber - 1) -> (degree of node(Taxonnumber)) */
*taxonHasDeg = (int *)rax_calloc((2*tr->mxtips - 2),sizeof(int)),
/* taxonToReduction[2*tr->mxtips - 2];
Array used for reducing bitvector and speeding up extraction:
(Taxonnumber - 1) -> Index in smallTreeTaxa (starting from 0)
which is also:
(Taxonnumber - 1) -> (0..1 (increment count of taxa appearing in small tree))
(Taxonnumber - 1) -> (0..1 (increment count of inner nodes appearing in small tree)) */
*taxonToReduction = (int *)rax_malloc((2*tr->mxtips - 2) * sizeof(int));
int
newcount = 0; //counter used for correct traversals
/* labelToTaxon[2*tr->mxtips - 2];
is used to translate between Perorderlabel and p->number: (Preorderlabel) -> (Taxonnumber) */
int
*labelToTaxon = (int *)rax_malloc((2*tr->mxtips - 2) * sizeof(int));
/* Preorder-Traversal of the large tree */
preOrderTraversal(tr->start->back,tr->mxtips, tr->start->number, taxonToLabel, labelToTaxon, &newcount);
newcount = 0; //counter set to 0 to be now used for Eulertraversal
/* eulerIndexToLabel[4*tr->mxtips - 5];
Array storing all 4n-5 PreOrderlabels created during eulertour: (Eulerindex) -> (Preorderlabel) */
int*
eulerIndexToLabel = (int *)rax_malloc((4*tr->mxtips - 5) * sizeof(int));
/* taxonToEulerIndex[tr->mxtips];
Stores all indices of the first appearance of a taxa in the eulerTour: (Taxonnumber - 1) -> (Index of the Eulertour where Taxonnumber first appears)
is used for efficient computation of the Lowest Common Ancestor during Reconstruction Step
*/
int*
taxonToEulerIndex = (int *)rax_malloc((tr->mxtips) * sizeof(int));
/* Init taxonToEulerIndex and taxonToReduction */
int
ix;
for(ix = 0; ix < tr->mxtips; ++ix)
taxonToEulerIndex[ix] = -1;
for(ix = 0; ix < (2*tr->mxtips - 2); ++ix)
taxonToReduction[ix] = -1;
/* Eulertraversal of the large tree*/
unrootedEulerTour(tr->start->back,tr->mxtips, eulerIndexToLabel, taxonToLabel, &newcount, taxonToEulerIndex);
/* Creating RMQ Datastructure for efficient retrieval of LCAs, using Johannes Fischers Library rewritten in C
Following Files: rmq.h,rmqs.c,rmqs.h are included in Makefile.RMQ.gcc */
RMQ_succinct(eulerIndexToLabel,4*tr->mxtips - 5);
double
preprocessendtime = gettime() - preprocesstime;
/* Proprocessing Step End */
/*************************************************************************************/
printBothOpen("The reference tree has %d tips\n", tr->ntips);
fclose(treeFile);
/***********************************************************************************/
/* RF-OPT Preprocessing Step */
/***********************************************************************************/
/* now see how many small trees we have */
treeFile = getNumberOfTrees(tr, bootStrapFile, adef);
treeFile2 = getNumberOfTrees(tr, bootStrapFile, adef);
checkTreeNumber(tr->numberOfTrees, bootStrapFile);
/* allocate a data structure for parsing the potentially mult-furcating tree */
allocateMultifurcations(tr, smallTree);
/* Start Additional preprocessing step */
int
numberOfBips = 0,
numberOfSets = 0;
//Stores the number of bips of each tree
int *bipsPerTree = (int *)rax_malloc(tr->numberOfTrees * sizeof(int));
//Stores the number of taxa for each tree
int *taxaPerTree = (int *)rax_malloc(tr->numberOfTrees * sizeof(int));
//To calculate all bipartitions, I created a new treeFile2 and a new getNumberOfTrees method!!
for(i = 0; i < tr->numberOfTrees; i++) {
int this_treeBips = readMultifurcatingTree(treeFile2, smallTree, adef, TRUE);
numberOfBips = numberOfBips + this_treeBips;
numberOfSets = numberOfSets + this_treeBips * this_treeBips;
bipsPerTree[i] = this_treeBips;
}
printf("numberOfBips: %i , numberOfSets: %i \n \n", numberOfBips, numberOfSets);
//stores induced bips (OLD?)
unsigned int *ind_bips = (unsigned int *)rax_malloc(numberOfBips * sizeof(unsigned int));
//stores smalltree bips (OLD?)
unsigned int *s_bips = (unsigned int *)rax_malloc(numberOfBips * sizeof(unsigned int));
//stores small bips per tree
unsigned int ***sBipsPerTree = (unsigned int ***)rax_malloc(tr->numberOfTrees * sizeof(unsigned int**));
//stores induced bips per tree
unsigned int ***indBipsPerTree = (unsigned int ***)rax_malloc(tr->numberOfTrees * sizeof(unsigned int**));
//stores vLength of each tree for processing bitVectors
unsigned int *vectorLengthPerTree = (unsigned int *)rax_malloc(tr->numberOfTrees * sizeof(unsigned int*));
//stores the corresponding tree number for each bip
int *treenumberOfBip = (int *)rax_malloc(numberOfBips * sizeof(int));
//Stores all dropsets of all trees
int **sets = (int **)rax_malloc(numberOfSets * sizeof(int*));
//int **sets = NULL;
//For each tree, stores a translation array from taxanumber smalltree->largetree
int **smallTreeTaxaList = (int **)rax_malloc(tr->numberOfTrees * sizeof(int*));
//For each tree, store a translation array from taxanumber largetree->smalltree
int **taxonToReductionList = (int **)rax_malloc(tr->numberOfTrees * sizeof(int*));
//I use these variables as global variables for all trees to determine the max number of possible sets to generate a static array
int currentBips = 0;
int currentSmallBips = 0;
int currentSets = 0;
//int currentTree = 0; already there in number of trees analyzed
//Prefill sets with -1s
for(int it = 0;it < (numberOfSets);it++){
int fill[1] = {-1};
sets[it] = fill;
}
/***********************************************************************************/
/* RF-OPT Preprocessing Step End */
/***********************************************************************************/
/* loop over all small trees */
for(i = 0; i < tr->numberOfTrees; i++)
{
int
numberOfSplits = readMultifurcatingTree(treeFile, smallTree, adef, TRUE);
if(numberOfSplits > 0)
{
int
firstTaxon;
double
rec_rf,
maxRF;
if(numberOfTreesAnalyzed % 100 == 0)
printBothOpen("Small tree %d has %d tips and %d bipartitions\n", i, smallTree->ntips, numberOfSplits);
/* compute the maximum RF distance for computing the relative RF distance later-on */
/* note that here we need to pay attention, since the RF distance is not normalized
by 2 * (n-3) but we need to account for the fact that the multifurcating small tree
will potentially contain less bipartitions.
Hence the normalization factor is obtained as n-3 + numberOfSplits, where n-3 is the number
of bipartitions of the pruned down large reference tree for which we know that it is
bifurcating/strictly binary */
maxRF = (double)(2 * numberOfSplits);
/* now get the index of the first taxon of the small tree.
we will use this to unambiguously store the bipartitions
*/
firstTaxon = smallTree->start->number;
//Saves the number of taxa in the tree (for RF-OPT)
taxaPerTree[numberOfTreesAnalyzed] = smallTree->ntips;
/***********************************************************************************/
/* Reconstruction Step */
double
time_start = gettime();
/* Init hashtable to store Bipartitions of the induced subtree T|t_i */
/*
using smallTree->ntips instead of smallTree->mxtips yields faster code
e.g. 120 versus 128 seconds for 20,000 small trees on my laptop
*/
hashtable
*s_hash = initHashTable(smallTree->ntips * 4);
/* Init hashtable to store Bipartitions of the reference tree t_i*/
hashtable
*ind_hash = initHashTable(smallTree->ntips * 4);
/* smallTreeTaxa[smallTree->ntips];
Stores all taxa numbers from smallTree into an array called smallTreeTaxa: (Index) -> (Taxonnumber) */
int*
smallTreeTaxa = (int *)rax_malloc((smallTree->ntips) * sizeof(int));
/* counter is set to 0 for correctly extracting taxa of the small tree */
newcount = 0;
int
newcount2 = 0;
/* seq2[2*smallTree->ntips - 2];
stores PreorderSequence of the reference smalltree: (Preorderindex) -> (Taxonnumber) */
int*
seq2 = (int *)rax_malloc((2*smallTree->ntips - 2) * sizeof(int));
/* used to store the vectorLength of the bitvector */
unsigned int
vectorLength;
/* extract all taxa of the smalltree and store it into an array,
also store all counts of taxa and nontaxa in taxonToReduction */
rec_extractTaxa(smallTreeTaxa, taxonToReduction, smallTree->start, smallTree->mxtips, &newcount, &newcount2);
rec_extractTaxa(smallTreeTaxa, taxonToReduction, smallTree->start->back, smallTree->mxtips, &newcount, &newcount2);
/* counter is set to 0 to correctly preorder traverse the small tree */
newcount = 0;
/* Preordertraversal of the small reference tree and save its sequence into seq2 for later extracting the bipartitions, it
also stores information about the degree of every node */
rec_preOrderTraversalMulti(smallTree->start->back,smallTree->mxtips, smallTree->start->number, seq2, taxonHasDeg, &newcount);
/* calculate the bitvector length */
if(smallTree->ntips % MASK_LENGTH == 0)
vectorLength = smallTree->ntips / MASK_LENGTH;
else
vectorLength = 1 + (smallTree->ntips / MASK_LENGTH);
/***********************************************************************************/
/* RF-OPT Additional Preprocessing storing Bipartitions */
/***********************************************************************************/
vectorLengthPerTree[numberOfTreesAnalyzed] = vectorLength;
unsigned int
**bitVectors = rec_initBitVector(smallTree, vectorLength);
unsigned int
**sBips;
/* store all non trivial bitvectors using an subtree approach for the reference subtree and
store it into a hashtable, this method was changed for multifurcation */
sBips = RFOPT_extractBipartitionsMulti(bitVectors, seq2, newcount,tr->mxtips, vectorLength, smallTree->ntips,
firstTaxon, s_hash, taxonToReduction, taxonHasDeg, numberOfSplits);
sBipsPerTree[numberOfTreesAnalyzed] = sBips;
/***********************************************************************************/
/* End RF-OPT Additional Preprocessing storing Bipartitions */
/***********************************************************************************/
/* counter is set to 0 to be used for correctly storing all EulerIndices */
newcount = 0;
/* smallTreeTaxonToEulerIndex[smallTree->ntips];
Saves all first Euler indices for all Taxons appearing in small Tree:
(Index) -> (Index of the Eulertour where the taxonnumber of the small tree first appears) */
int*
smallTreeTaxonToEulerIndex = (int *)rax_malloc((smallTree->ntips) * sizeof(int));
/* seq[(smallTree->ntips*2) - 1]
Stores the Preordersequence of the induced small tree */
int*
seq = (int *)rax_malloc((2*smallTree->ntips - 1) * sizeof(int));
/* iterate through all small tree taxa */
for(ix = 0; ix < smallTree->ntips; ix++)
{
int
taxanumber = smallTreeTaxa[ix];
/* To create smallTreeTaxonToEulerIndex we filter taxonToEulerIndex for taxa in the small tree*/
smallTreeTaxonToEulerIndex[newcount] = taxonToEulerIndex[taxanumber-1];
/* Saves all Preorderlabel of the smalltree taxa in seq*/
seq[newcount] = taxonToLabel[taxanumber-1];
newcount++;
}
/* sort the euler indices to correctly calculate LCA */
//quicksort(smallTreeTaxonToEulerIndex,0,newcount - 1);
qsort(smallTreeTaxonToEulerIndex, newcount, sizeof(int), sortIntegers);
//printf("newcount2 %i \n", newcount2);
/* Iterate through all small tree taxa */
for(ix = 1; ix < newcount; ix++)
{
/* query LCAs using RMQ Datastructure */
seq[newcount - 1 + ix] = eulerIndexToLabel[query(smallTreeTaxonToEulerIndex[ix - 1],smallTreeTaxonToEulerIndex[ix])];
/* Used for dynamic programming. We save an index for every inner node:
For example the reference tree has 3 inner nodes which we saves them as 0,1,2.
Now we calculate for example 5 LCA to construct the induced subtree, which are also inner nodes.
Therefore we mark them as 3,4,5,6,7 */
taxonToReduction[labelToTaxon[seq[newcount - 1 + ix]] - 1] = newcount2;
newcount2 += 1;
}
/* sort to construct the Preordersequence of the induced subtree */
//quicksort(seq,0,(2*smallTree->ntips - 2));
qsort(seq, (2 * smallTree->ntips - 2) + 1, sizeof(int), sortIntegers);
/* calculates all bipartitions of the reference small tree and count how many bipartition it
shares with the induced small tree and stores those bipartitions in a additional hashtable called ind_hash */
int
rec_bips = 0;
unsigned int
**indBips;
indBips = RFOPT_findAddBipartitions(bitVectors, seq,(2*smallTree->ntips - 1), labelToTaxon, tr->mxtips, vectorLength, smallTree->ntips, firstTaxon, s_hash, ind_hash, taxonToReduction);
indBipsPerTree[numberOfTreesAnalyzed] = indBips;
/* calculates all bipartitions of the reference small tree and put them into ind_hash*/
// rec_extractBipartitionsMulti(bitVectors, seq2, (2*smallTree->ntips - 1),tr->mxtips, vectorLength, smallTree->ntips,
// firstTaxon, s_hash, taxonToReduction, taxonHasDeg, numberOfSplits);
/* Reconstruction Step End */
/***********************************************************************************/
double
effectivetime = gettime() - time_start;
/*
if(numberOfTreesAnalyzed % 100 == 0)
printBothOpen("Reconstruction time: %.10f secs\n\n", effectivetime);
*/
/* compute the relative RF */
/***********************************************************************************/
/* RF-OPT Save Translation Vectors */
/***********************************************************************************/
//copy array taxonToReduction because it is originally defined in preprocessing step
int * taxonToReductionCopy = (int *)rax_malloc((tr->mxtips)*sizeof(int));
memcpy(taxonToReductionCopy,taxonToReduction,(tr->mxtips)*sizeof(int));
//storing smallTree and taxonToReduction Arrays for further usage
smallTreeTaxaList[numberOfTreesAnalyzed] = smallTreeTaxa;
taxonToReductionList[numberOfTreesAnalyzed] = taxonToReductionCopy;
int this_currentSmallBips = 0; //Variable resets everytime for each tree analyzed
/***********************************************************************************/
/* End RF-OPT Save Translation Vectors */
/***********************************************************************************/
rec_rf = (double)(2 * (numberOfSplits - rec_bips)) / maxRF;
assert(numberOfSplits >= rec_bips);
avgRF += rec_rf;
sumEffectivetime += effectivetime;
//if(numberOfTreesAnalyzed % 100 == 0)
printBothOpen("Relative RF tree %d: %f\n\n", i, rec_rf);
fprintf(rfFile, "%d %f\n", i, rec_rf);
//rax_free(smallTreeTaxa); //Need it for calculating the SmallTreeTaxaList after all iterations!
rax_free(seq);
rax_free(seq2);
rax_free(smallTreeTaxonToEulerIndex);
numberOfTreesAnalyzed++; //Counting the number of trees analyzed
}
}// End of Small Tree Iterations
/***********************************************************************************/
/* RF-OPT DropSet Calculation using BitVectors */
/***********************************************************************************/
log_info("===> Create DropSet Datastructure \n");
static Hashmap* map = NULL;
//Set a hashmap for dropsets with a dropset comparision and standard hash
map = Hashmap_create(compareDropSet, NULL);
static Hashmap** mapArray = NULL;
//Set an array to store the pointers to bitvector hashtables for each tree
mapArray = rax_malloc(tr->numberOfTrees * sizeof(Hashmap*));
printf("===> BitVector Set Calculation \n");
//Calculate dropsets of two given bips lists and extract all sets into array sets and into a hashmap. Each set has following format
//dropset = {taxa_1,taxa_2,...,taxa_n,-1};
//Furtheremore calculate Dropset generates two data structures from type bips and dropsets which are pointing to each other in hashtables
calculateDropSets(mapArray, map, indBipsPerTree, sBipsPerTree, sets, smallTreeTaxaList, bipsPerTree,
taxaPerTree, vectorLengthPerTree, tr->numberOfTrees);
/***********************************************************************************/
/* RF-OPT Graph Construction */
/***********************************************************************************/
// printf("\n == Sets == \n");
// for(int fooo = 0; fooo < numberOfSets; fooo++){
// printf("Set %i: ", fooo);
// int i = 0;
// while(sets[fooo][i] > -1) {
// printf("%i ",sets[fooo][i]);
// i++;
// }
// printf("\n");
// }
// printf("\n");
/*
Filter for unique sets
*/
log_info("===> Hashmap tests...\n");
Hashmap_traverse(map, traverse_cb);
// int key[2] = {0,-1};
// Dropset* drop = Hashmap_get(map,key);
// DArray* bips = drop->bipartitions;
// for(int i = 0; i < DArray_count(bips); i++) {
// Bipartition* bip = DArray_get(bips,i);
// printBitVector(bip->bitvector[0]);
// printf("matching: %i \n", bip->matching);
// printf("tree: %i \n", bip->treenumber);
// }
// Bipartition* bipFromHash = DArray_first(bips);
// Bipartition* testBip = Hashmap_get(mapArray[0],bipFromHash->bitvector);
// printf("matching before: %i",testBip->matching);
// testBip->matching = 999;
// for(int i = 0; i < DArray_count(bips); i++) {
// Bipartition* bip = DArray_get(bips,i);
// printBitVector(bip->bitvector[0]);
// printf("matching: %i \n", bip->matching);
// printf("tree: %i \n", bip->treenumber);
// }
printf("===> Filter for unique sets (naive)...\n");
/* unique sets array data structures */
int** uniqSets = (int **) rax_malloc(sizeof(int*) * numberOfSets);
int* setsToUniqSets = (int*) rax_malloc(sizeof(int) * numberOfSets);
int numberOfUniqueSets = 0;
int dropSetCount = 0;
//stores the scores for each bips, we are using a bitvector approach (need to scale)
//Legacy Code
int bvec_scores = 0;
numberOfUniqueSets = getUniqueDropSets(sets, uniqSets, setsToUniqSets, numberOfSets);
printf("number of unique sets: %i \n", numberOfUniqueSets);
/*
Detect initial matchings, we calculate them using bitvectors to represent our bipartitions
*/
printf("===> Detect initial matchings...\n");
int vLengthBip = 0;
//determine the bitVector Length of our bitVector
if(numberOfBips % MASK_LENGTH == 0)
vLengthBip = numberOfBips / MASK_LENGTH;
else
vLengthBip = numberOfBips / MASK_LENGTH + 1;
//Initialize a bvecScore vector with 0s
int* bvecScores = (int*)rax_calloc(vLengthBip,sizeof(int));
//Calculate Initial Matchings and save the result in bvecScores
detectInitialMatchings(sets, bvecScores, bipsPerTree, numberOfTreesAnalyzed, vLengthBip);
//Short summary until now:
// - bipsPerTree consists of all bipartitions per tree
// - bvecScores is the bitvector setting 1 to all bipartition indices which can score
// - taxaPerTree number of taxa per tree
// - smallTreeTaxaList list of all smalltree->largetree translation arrays
/*
Generate useful data structures for calculating and updating scores
*/
printf("===> Create data structures...\n");
//Stores the number of bips per Set and initialize it with 0s
int* numberOfBipsPerSet = (int*)rax_calloc(numberOfUniqueSets,sizeof(int));
//Stores all sets which includes this taxa
int **setsOfTaxa = (int**)rax_malloc((tr->mxtips + 1) *sizeof(int*));
//Now calculate number of bipartitions affected by each unique set
for(int i = 0; i < numberOfSets; i++) {
int setindex = setsToUniqSets[i];
numberOfBipsPerSet[setindex]++;
}
//Now using the knowledge of how many bips there are per set, generate an array for each unique dropset containing all bips
int** bipsOfDropSet = (int**)rax_malloc(sizeof(int*)*numberOfUniqueSets);
//Allocate the space needed for storing all bips
for(int i = 0; i < numberOfUniqueSets; i++) {
bipsOfDropSet[i] = (int*)rax_malloc(sizeof(int)*numberOfBipsPerSet[i]);
}
printf("==> Initialize the Bips Of Taxa \n");
//Stores the number of bips each taxa is included (ABC|DE is stored by A,B,C,D and E)
//It can be calculated by iterating through all trees and adding the taxa
int **bipsOfTaxa = (int**)rax_malloc((tr->mxtips + 1) * sizeof(int*));
int *numberOfBipsPerTaxa = (int*)rax_calloc((tr->mxtips + 1), sizeof(int));
int *taxaBipsCounter = (int*)rax_calloc((tr->mxtips + 1), sizeof(int));
//Now add up all
for (int tree = 0; tree < tr->numberOfTrees; tree++) {
int* list = smallTreeTaxaList[tree];
for (int j = 0; j < taxaPerTree[tree]; j++) {
int taxa = list[j];
numberOfBipsPerTaxa[taxa] = numberOfBipsPerTaxa[taxa] + bipsPerTree[tree];
}
}
//Now create dummy arrays inside bipsOfTaxa
for(int i = 1; i < tr->mxtips+1; i++) {
bipsOfTaxa[i] = (int*)rax_malloc(sizeof(int)*numberOfBipsPerTaxa[i]);
}
printf("==> Storing all bip indices of a certain dropset into an array \n");
//For checking if all dropsets are iterated
dropSetCount = 0;
//Arrays of counter to keep in track
int* counterOfSet = (int*)rax_malloc(sizeof(int)*numberOfUniqueSets);
for(int i = 0; i < numberOfUniqueSets; i++) {
counterOfSet[i] = 0;
}
currentBips = 0; //Need to keep in track of the number of bips
//First iterate through all trees
for(int i = 0; i < numberOfTreesAnalyzed; i++ ) {
//get the correct smallTreeTaxa List
int* list = smallTreeTaxaList[i];
//For each bipartition in the tree
for(int j = 0; j < bipsPerTree[i]; j++) {
//Look at all bips it is compared too
int dropSetsPerBip = bipsPerTree[i];
for(int k = 0; k < dropSetsPerBip; k++){
int indexOfUniqDropSet = setsToUniqSets[dropSetCount + k];
int* bips_array = bipsOfDropSet[indexOfUniqDropSet];
//add bipartition j into the bips array of its dropset
bips_array[counterOfSet[indexOfUniqDropSet]] = currentBips;
//increment the internal array index
counterOfSet[indexOfUniqDropSet]++;
}
//Jump to the next correct dropSetCount!
dropSetCount = dropSetCount + dropSetsPerBip;
//now insert the bip into bipsOfTaxa Array
for(int ix = 0; ix < taxaPerTree[i]; ix++) {
//get the taxa number
int stree_Taxa = list[ix];
//get the bips list of this taxa number
int* bipsList = bipsOfTaxa[stree_Taxa];
//now get the position of the biplist and put in our bip index
bipsList[taxaBipsCounter[stree_Taxa]] = currentBips;
//increment the counter
taxaBipsCounter[stree_Taxa]++;
}
//increment currentBips
currentBips++;
}
}
/***********************************************************************************/
/* End RF-OPT Graph Construction */
/***********************************************************************************/
/* Short summary :
sets - array of all dropsets
uniqSets - array of all unique dropsets
bipsPerTree - bips per tree
setsToUniqSets - translates the index of sets to the index of its unique dropset index
bipsOfDropSets - all bips which disappear when dropset i is pruned
scores - has all scores between 0 and 1 for the bips (however 0s can be found out by looking at all dropsets with link to dropset 0 (because we sort and it will always be the lowest))
*/
/***********************************************************************************/
/* RF-OPT Initial Score Calculation */
/***********************************************************************************/
unsigned int bipsVectorLength;
/* calculate the bitvector length for bips bitvector */
if(numberOfBips % MASK_LENGTH == 0)
bipsVectorLength = numberOfBips / MASK_LENGTH;
else
bipsVectorLength = 1 + (numberOfBips / MASK_LENGTH);
//Starting from index 1 (because 0 stands for all who already matches)
//We need a score array saving the scores for each uniqset
int* rf_score = (int*)rax_calloc(numberOfUniqueSets,sizeof(int));
printf("==> Calculating the score for the first iteration \n \n");
//Store all bvecs of all merged and destroyed bipartitions per DropSet
int* bvecs_bips = (int*)rax_malloc(sizeof(int)*numberOfUniqueSets);
int* bvecs_destroyed = (int*)rax_malloc(sizeof(int)*numberOfUniqueSets);
//Iterate through all sets
for(int i = 0; i < numberOfUniqueSets; i++) {
//Bitvectors of merged and destroyed
int bvec_destroyed = 0;
int* set = uniqSets[i]; //Get the dropset, first dropset is 0 (if something is matching)
//printf(" ==> Analyze Unique DropSet %i \n", i);
//We use this data structure to keep track of the to toggled bits
int* toggleBits = (int*)rax_calloc(numberOfBips, sizeof(int));
//Now iterate through the set
int j = 0;
//Stores the affected bips into a bitvector
int bvec_bips = 0;
while(set[j] != -1) {
int taxa = set[j]; //Get the taxa
//printf(" Taxa number is %i \n",taxa);
//Check if set[j] is itself already a set
int test[2] = {taxa,-1};
//0 if it is not a set, index + 1 otherwise
int test_index = contains(test, uniqSets, numberOfUniqueSets);
if(test_index){
//printf(" It also is in uniqSet %i \n", test_index - 1);
bvec_bips = getBipsOfDropSet(bvec_bips, (test_index - 1), numberOfBipsPerSet, bipsOfDropSet);
}
//Get all bips of this taxa to detect which one will be destroyed
int* listOfBips = bipsOfTaxa[taxa];
//Go through all bipartitions containing this taxa
for(int k = 0; k < numberOfBipsPerTaxa[taxa]; k++){
int bipindex = listOfBips[k]; //Get the index of the Bipartition
int bip = ind_bips[bipindex];
//Now analyze this Bipartition
//Which tree does this bipartition belongs too?
int treenumber = treenumberOfBip[bipindex];
//Get the taxonToSmallTree Array of this tree
int* stTaxa = taxonToReductionList[treenumber];
//Translate the global taxon number it into the local index used by our bips
int translated_index = stTaxa[taxa - 1]; //We use taxa - 1 because we start counting at taxa 1 = 0 !
//Save the to toggle index into toggleBits vector
toggleBits[bipindex] |= 1 << translated_index;
//Sort for bits set on one side of the bip and on the other side
int leftBits = __builtin_popcount(toggleBits[bipindex] & bip);
int rightBits = __builtin_popcount(toggleBits[bipindex]) - leftBits;
//Check for the number of bits set in the original bip
int leftBip = __builtin_popcount(bip);
int rightBip = taxaPerTree[treenumber] - leftBip;
//Subtract the total number of bits set on one side of the bip with the bits we have to toggle
int leftBip_after = leftBip - leftBits;
int rightBip_after = rightBip - rightBits;
//Check if bipartition gets trivial/destroyed due to pruning the taxa and set the bit (representing the bip) which is destroyed
if((leftBip_after <= 1) | (rightBip_after <=1)) {
//Add bips to the bits which represent destroyed bipartitions
bvec_destroyed = setBit(bvec_destroyed,bipindex);
}
}
j++;
}//End iterate through the set
int penality = 0;
int score = 0;
int bvec_mask = 0;
bvec_mask = setOffSet(bvec_mask, numberOfBips);
//Bitvector of already matching bips
int bvec_tmp = 0;
bvec_tmp = ~bvec_scores & bvec_mask;
//Penality score are all bitvectors who were matching but is destroyed
penality = __builtin_popcount(bvec_destroyed & bvec_tmp);
//Now iterate through bipsOfDropSet list and extract all bips which will merge into a bitVector
bvec_bips = getBipsOfDropSet(bvec_bips, i, numberOfBipsPerSet, bipsOfDropSet);
//Calculate the bitvectors which remains
bvec_tmp = ~bvec_destroyed & bvec_mask;
bvec_tmp = bvec_bips & bvec_tmp;
score = __builtin_popcount(bvec_scores & bvec_tmp);
rf_score[i] = score - penality;
//Save our results for convenience into an array
bvecs_bips[i] = bvec_bips;
bvecs_destroyed[i] = bvec_destroyed;
}//End Score Calculation
printf("======> Scores:\n");
for(int i = 0; i < numberOfUniqueSets; i++) {
printf("RF Score for %i : %i \n", i, rf_score[i]);
//printBitVector(bvecs_bips[i]);
//printBitVector(bvecs_destroyed[i]);
}
int maxDropSet = getMax(rf_score, numberOfUniqueSets);
printf("Max Element is %i \n", maxDropSet);
/***********************************************************************************/
/* RF-OPT Create Update Data Structures */
/***********************************************************************************/
printf("====> Delete DropSet from all bips and update numbers \n");
//Create a bitVector to store all deleted taxa
int bvec_deletedTaxa = 0;
//Create a bitVector to store all still existing bips
int bvec_existingBips = 0;
//Create a bitvector to store deleted dropsets
int bvec_deletedDropSets = 0;
//Get the dropset
int* deleteDropSet = uniqSets[maxDropSet];
//Store it into a BitVector
bvec_deletedDropSets = setBit(bvec_deletedDropSets,maxDropSet);
//Select all bips destroyed by removing this dropset
int bvec_destroyedBips = bvecs_destroyed[maxDropSet];
//Select all bips that are now matching
int bvec_matchingBips = bvecs_bips[maxDropSet];
//Filter for existent bipartitions
bvec_existingBips = getExistingBips(bvec_existingBips, numberOfBips, bvec_destroyedBips);
//Iterate through its taxa
int iterSet = 0;
while(deleteDropSet[iterSet] != -1) {
//Get taxon
int taxon = deleteDropSet[iterSet];
//Store the taxon into deletedTaxa BitVector
bvec_deletedTaxa = setBit(bvec_deletedTaxa, taxon - 1);
//Check if taxon is inside
int test[2] = {taxon, -1};
int index = contains(test, uniqSets, numberOfUniqueSets);
iterSet++;
}
//printBitVector(bvec_existingBips);
//printBitVector(bvec_deletedTaxa);
//Update the scores with now matching bips
bvec_scores = bvec_scores & (~bvec_matchingBips);
//printBitVector(bvec_scores);
/* Short summary :
bvec_existingBips - bitVector of all still existing bips
bvec_deletedTaxa - bitVector to keep track of destroyed taxa
*/
/***********************************************************************************/
/* TODO RF-OPT Update function */
/***********************************************************************************/
/***********************************************************************************/
/* End RF-OPT Update function */
/***********************************************************************************/
//printf("Ind Bipartitions?: ");
// printf("Induced Bipartitions: ");
// printBitVector(ind_bips[0]);
// printBitVector(ind_bips[1]);
// printBitVector(ind_bips[2]);
// printBitVector(ind_bips[3]);
// printBitVector(ind_bips[4]);
// printBitVector(ind_bips[5]);
// printBitVector(ind_bips[6]);
/***********************************************************************************/
/* Console Logs for debugging */
/***********************************************************************************/
//Printing if
printf("==> Unique Sets: ");
for(int i = 0; i < numberOfUniqueSets; i++) {
int j = 0;
int* set = uniqSets[i];
while(set[j] > -1) {
printf("%i ",set[j]);
j++;
}
printf("; ");
}
printf("\n");
printf("\n == Sets == \n");
for(int fooo = 0; fooo < numberOfSets; fooo++){
printf("Set %i: ", fooo);
int i = 0;
while(sets[fooo][i] > -1) {
printf("%i ",sets[fooo][i]);
i++;
}
printf("\n");
}
printf("\n");
//#define _PRINT_
#ifdef _PRINT_
for(int i = 0; i < numberOfUniqueSets; i++) {
printf("Bips of Set %i: ", i);
for(int j = 0; j < numberOfBipsPerSet[i]; j++) {
int* bips = bipsOfDropSet[i];
printf("%i ", bips[j]);
}
printf("\n");
}
printf("Induced Bips! \n");
// Now checking which dropset would destroy which bipartition
for(int i = 0 ; i < numberOfBips; i++) {
printf("Bip %i is %i \n",i,ind_bips[i]);
}
printf("Taxa Names : \n");
for(int i = 0; i < tr->mxtips + 1; i++) {
printf("%s ",tr->nameList[i]);
}
printf("\n");
printf("Small Tree Taxa Names 0 : \n");
for(int i = 0; i < taxaPerTree[0]; i++) {
int* list = smallTreeTaxaList[0];
int taxa = list[i];
printf("%s ",tr->nameList[taxa]);
}
printf("\n");
printf("Small Tree Taxa Names 1 : \n");
for(int i = 0; i < taxaPerTree[1]; i++) {
int* list = smallTreeTaxaList[1];
int taxa = list[i];
printf("%s ",tr->nameList[taxa]);
}
printf("\n");
printf("Small Tree Taxa Names 2 : \n");
for(int i = 0; i < taxaPerTree[2]; i++) {
int* list = smallTreeTaxaList[2];
int taxa = list[i];
printf("%s ",tr->nameList[taxa]);
}
printf("\n");
printf("Number of DropSets extracted%i \n",dropSetCount);
printf("Number of Bips extracted %i \n",currentBips);
//Testing ...
printf("Number of Sets is %i \n",numberOfSets);
printf("Number of Unique Sets is %i \n",numberOfUniqueSets);
printf("==> Testing bips of unique sets \n");
for(int i = 0; i < numberOfUniqueSets; i++) {
printf("Bips of Set %i: ", i);
for(int j = 0; j < numberOfBipsPerSet[i]; j++) {
int* bips = bipsOfDropSet[i];
printf("%i ", bips[j]);
}
printf("\n");
}
printf("==> Testing bips of taxa \n");
for(int i = 1; i < tr->mxtips + 1; i++) {
printf("Bips of Taxa %i: ", i);
for(int j = 0; j < numberOfBipsPerTaxa[i]; j++) {
int* bips = bipsOfTaxa[i];
printf("%i ", bips[j]);
}
printf("\n");
}
printf("==> Unique Sets: ");
for(int i = 0; i < numberOfUniqueSets; i++) {
int j = 0;
int* set = uniqSets[i];
while(set[j] > -1) {
printf("%i ",set[j]);
j++;
}
printf("; ");
}
printf("\n");
printf("==> setsToUniqSets: ");
for(int i = 0; i < numberOfSets; i++) {
printf("%i ",setsToUniqSets[i]);
}
printf("\n");
//=== TREE GRAPH CONSTRUCTION ENDS ===
printf("Scores: ");
printBitVector(bvec_scores);
printf("BipsPerTree: ");
for(int foo = 0; foo < tr->numberOfTrees; foo++) {
printf("%i ",bipsPerTree[foo]);
}
printf("\nInduced Bips: ");
for(int foo = 0;foo < numberOfBips; foo++) {
printf("%u ",ind_bips[foo]);
}
printf("\nSmall Tree Bips: ");
for(int foo = 0;foo < numberOfBips; foo++) {
printf("%u ",s_bips[foo]);
}
printf("\n == Sets == \n");
for(int fooo = 0; fooo < numberOfSets; fooo++){
printf("Set %i: ", fooo);
int i = 0;
while(sets[fooo][i] > -1) {
printf("%i ",sets[fooo][i]);
i++;
}
printf("\n");
}
printf("\n");
#endif
printBothOpen("Number of small trees skipped: %d\n\n", tr->numberOfTrees - numberOfTreesAnalyzed);
printBothOpen("Average RF distance %f\n\n", avgRF / (double)numberOfTreesAnalyzed);
printBothOpen("Large Tree: %i, Number of SmallTrees analyzed: %i \n\n", tr->mxtips, numberOfTreesAnalyzed);
printBothOpen("Total execution time: %f secs\n\n", gettime() - masterTime);
printBothOpen("File containing all %d pair-wise RF distances written to file %s\n\n", numberOfTreesAnalyzed, rfFileName);
printBothOpen("execution stats:\n\n");
printBothOpen("Accumulated time Effective algorithm: %.5f sec \n", sumEffectivetime);
printBothOpen("Average time for effective: %.10f sec \n",sumEffectivetime / (double)numberOfTreesAnalyzed);
printBothOpen("Preprocessingtime: %0.5f sec \n\n", preprocessendtime);
fclose(treeFile);
fclose(rfFile);
/* free the data structure used for parsing the potentially multi-furcating tree */
freeMultifurcations(smallTree);
rax_free(smallTree);
rax_free(taxonToLabel);
rax_free(taxonToEulerIndex);
rax_free(labelToTaxon);
rax_free(eulerIndexToLabel);
rax_free(taxonToReduction);
rax_free(taxonHasDeg);
}