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Single tree methods are running

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This commit is contained in:
vasiloglou
2007-05-05 23:31:45 +00:00
parent f4f92a67d8
commit 3e2a0773cb
8 changed files with 112 additions and 58 deletions
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fastlib/u/nvasil/tree/binary_tree_impl.h
+19 -4
View File
@@ -210,6 +210,10 @@ void TREE__::NearestNeighbor(NodePtr_t ptr,
NEIGHBORTYPE range,
bool &found) {
computations_.UpdateComparisons();
Precision_t max_distance;
if (Loki::TypeTraits<NEIGHBORTYPE>::isStdFloat==true) {
max_distance=range;
}
if (!ptr->IsLeaf()){
computations_.UpdateComparisons();
pair<NodePtr_t, NodePtr_t> child_pair =
@@ -217,9 +221,13 @@ void TREE__::NearestNeighbor(NodePtr_t ptr,
NearestNeighbor(child_pair.first, test_point, nearest_point,
range, found);
if (Loki::TypeTraits<NEIGHBORTYPE>::isStdFloat==false) {
max_distance=nearest_point->back().first;
}
if (child_pair.second->get_box().CrossesBoundaries(test_point,
dimension_,
nearest_point->end()->first,
max_distance,
computations_)) {
NearestNeighbor(child_pair.second,
test_point,
@@ -230,8 +238,12 @@ void TREE__::NearestNeighbor(NodePtr_t ptr,
if (found == true) {
return;
} else {
if (Loki::TypeTraits<NEIGHBORTYPE>::isStdFloat==false) {
max_distance=nearest_point->back().first;
}
found = ptr->get_box().IsWithin(test_point,
dimension_, nearest_point->end()->first,
dimension_,
max_distance,
computations_)==0;
if (found == true) {
return;
@@ -242,8 +254,11 @@ void TREE__::NearestNeighbor(NodePtr_t ptr,
range, dimension_,
discriminator_,
computations_);
if (Loki::TypeTraits<NEIGHBORTYPE>::isStdFloat==false) {
max_distance=nearest_point->back().first;
}
found = ptr->get_box().IsWithin(test_point, dimension_,
nearest_point->end()->first,
max_distance,
computations_);
}
}
@@ -373,7 +388,7 @@ void TREE__::InitAllKNearestNeighborOutput(string file,
fwrite(buffer, sizeof(typename Node_t::NNResult),
(num_of_points_%kChunk)*knns, fp );
fclose(fp);
delete buffer;
delete []buffer;
int fd=open(file.c_str(), O_RDWR);
typename Node_t::NNResult *ptr =(typename Node_t::NNResult *)mmap(NULL,
sizeof(typename Node_t::NNResult)*knns*num_of_points_,
fastlib/u/nvasil/tree/binary_tree_impl.h~
+20 -4
View File
@@ -21,6 +21,7 @@ void TREE__::Init(BinaryDataset<Precision_t> *data) {
min_depth_ = numeric_limits<index_t>::max();
max_points_on_leaf_ = 30;
log_progress_=true;
pivoter_.Init(data_);
}
TEMPLATE__
@@ -209,6 +210,10 @@ void TREE__::NearestNeighbor(NodePtr_t ptr,
NEIGHBORTYPE range,
bool &found) {
computations_.UpdateComparisons();
Precision_t max_distance;
if (Loki::TypeTraits<NEIGHBORTYPE>::isStdFloat==true) {
max_distance=range;
}
if (!ptr->IsLeaf()){
computations_.UpdateComparisons();
pair<NodePtr_t, NodePtr_t> child_pair =
@@ -216,9 +221,13 @@ void TREE__::NearestNeighbor(NodePtr_t ptr,
NearestNeighbor(child_pair.first, test_point, nearest_point,
range, found);
if (Loki::TypeTraits<NEIGHBORTYPE>::isStdFloat==false) {
max_distance=nearest_point->back().first;
}
if (child_pair.second->get_box().CrossesBoundaries(test_point,
dimension_,
nearest_point->end()->first,
max_distance,
computations_)) {
NearestNeighbor(child_pair.second,
test_point,
@@ -229,8 +238,12 @@ void TREE__::NearestNeighbor(NodePtr_t ptr,
if (found == true) {
return;
} else {
if (Loki::TypeTraits<NEIGHBORTYPE>::isStdFloat==false) {
max_distance=nearest_point->back().first;
}
found = ptr->get_box().IsWithin(test_point,
dimension_, nearest_point->end()->first,
dimension_,
max_distance,
computations_)==0;
if (found == true) {
return;
@@ -241,8 +254,11 @@ void TREE__::NearestNeighbor(NodePtr_t ptr,
range, dimension_,
discriminator_,
computations_);
if (Loki::TypeTraits<NEIGHBORTYPE>::isStdFloat==false) {
max_distance=nearest_point->back().first;
}
found = ptr->get_box().IsWithin(test_point, dimension_,
nearest_point->end()->first,
max_distance,
computations_);
}
}
@@ -372,7 +388,7 @@ void TREE__::InitAllKNearestNeighborOutput(string file,
fwrite(buffer, sizeof(typename Node_t::NNResult),
(num_of_points_%kChunk)*knns, fp );
fclose(fp);
delete buffer;
delete buffer[];
int fd=open(file.c_str(), O_RDWR);
typename Node_t::NNResult *ptr =(typename Node_t::NNResult *)mmap(NULL,
sizeof(typename Node_t::NNResult)*knns*num_of_points_,
fastlib/u/nvasil/tree/binary_tree_unit.cc
+15 -14
View File
@@ -76,22 +76,24 @@ class BinaryTreeTest {
void BuildDepthFirst(){
printf("Testing BuildDepthFirst...\n");
tree_.BuildDepthFirst();
tree_.Print();
//tree_.Print();
printf("%s\n", tree_.Statistics().c_str());
}
void BuildBreadthFirst() {
printf("Testing BuildBreadthFirst...\n");
tree_.BuildBreadthFirst();
tree_.Print();
// tree_.Print();
printf("%s\n", tree_.Statistics().c_str());
}
void kNearestNeighbor() {
printf("Testing kNearestNeighbor...\n");
tree_.BuildDepthFirst();
tree_.Print();
vector<pair<Precision_t, Point_t> > nearest_tree;
pair<Precision_t, index_t> nearest_naive[num_of_points_];
for(index_t i=0; i<num_of_points_; i++) {
tree_.NearestNeighbor(data_.get_point(i),
nearest_tree.clear();
tree_.NearestNeighbor(data_.get_point(i),
&nearest_tree,
knns_);
Naive(i, nearest_naive);
@@ -110,14 +112,17 @@ class BinaryTreeTest {
vector<pair<Precision_t, Point_t> > nearest_tree;
pair<Precision_t, index_t> nearest_naive[num_of_points_];
for(index_t i=0; i<num_of_points_; i++) {
tree_.NearestNeighbor(data_.get_point(i),
nearest_tree.clear();
tree_.NearestNeighbor(data_.get_point(i),
&nearest_tree,
range_);
std::sort(nearest_tree.begin(), nearest_tree.end(),
typename Node_t::PairComparator());
Naive(i, nearest_naive);
for(index_t j=0; j<(index_t)nearest_tree.size(); j++) {
TEST_DOUBLE_APPROX(nearest_naive[j+1].first,
nearest_tree[j].first,
numeric_limits<Precision_t>::epsilon());
nearest_tree[j].first,
numeric_limits<Precision_t>::epsilon());
TEST_ASSERT(nearest_tree[j].second.get_id()==
nearest_naive[j+1].second) ;
}
@@ -131,11 +136,11 @@ class BinaryTreeTest {
tree_.AllNearestNeighbors(tree_.parent_, knns_);
tree_.CloseAllKNearestNeighborOutput(knns_);
struct stat info;
if (stat(data_file_.c_str(), &info)!=0) {
if (stat(result_file_.c_str(), &info)!=0) {
FATAL("Error %s file %s\n",
strerror(errno), data_file_.c_str());
}
uint64 map_size = info.st_size-sizeof(int32);
uint64 map_size = info.st_size;
int fp=open(result_file_.c_str(), O_RDWR);
typename Node_t::NNResult *res;
@@ -232,18 +237,14 @@ class BinaryTreeTest {
void Naive(index_t query,
pair<Precision_t, index_t> *result) {
for(index_t i=0; i<num_of_points_; i++) {
if (unlikely(data_.get_id(i)==data_.get_id(query))) {
continue;
}
Precision_t dist=Metric_t::Distance(data_.At(i),
data_.At(query),
dimension_);
result[i].first=dist;
result[i].second=i;
result[i].second=data_.get_id(i);
}
sort(result, result+num_of_points_);
std::sort(result, result+num_of_points_);
}
};
fastlib/u/nvasil/tree/binary_tree_unit.cc~
+14 -12
View File
@@ -76,21 +76,24 @@ class BinaryTreeTest {
void BuildDepthFirst(){
printf("Testing BuildDepthFirst...\n");
tree_.BuildDepthFirst();
tree_.Print();
//tree_.Print();
printf("%s\n", tree_.Statistics().c_str());
}
void BuildBreadthFirst() {
printf("Testing BuildBreadthFirst...\n");
tree_.BuildBreadthFirst();
// tree_.Print();
printf("%s\n", tree_.Statistics().c_str());
}
void kNearestNeighbor() {
printf("Testing kNearestNeighbor...\n");
tree_.BuildDepthFirst();
tree_.Print();
vector<pair<Precision_t, Point_t> > nearest_tree;
pair<Precision_t, index_t> nearest_naive[num_of_points_];
for(index_t i=0; i<num_of_points_; i++) {
tree_.NearestNeighbor(data_.get_point(i),
nearest_tree.clear();
tree_.NearestNeighbor(data_.get_point(i),
&nearest_tree,
knns_);
Naive(i, nearest_naive);
@@ -109,14 +112,17 @@ class BinaryTreeTest {
vector<pair<Precision_t, Point_t> > nearest_tree;
pair<Precision_t, index_t> nearest_naive[num_of_points_];
for(index_t i=0; i<num_of_points_; i++) {
tree_.NearestNeighbor(data_.get_point(i),
nearest_tree.clear();
tree_.NearestNeighbor(data_.get_point(i),
&nearest_tree,
range_);
std::sort(nearest_tree.begin(), nearest_tree.end(),
typename Node_t::PairComparator());
Naive(i, nearest_naive);
for(index_t j=0; j<(index_t)nearest_tree.size(); j++) {
TEST_DOUBLE_APPROX(nearest_naive[j+1].first,
nearest_tree[j].first,
numeric_limits<Precision_t>::epsilon());
nearest_tree[j].first,
numeric_limits<Precision_t>::epsilon());
TEST_ASSERT(nearest_tree[j].second.get_id()==
nearest_naive[j+1].second) ;
}
@@ -130,7 +136,7 @@ class BinaryTreeTest {
tree_.AllNearestNeighbors(tree_.parent_, knns_);
tree_.CloseAllKNearestNeighborOutput(knns_);
struct stat info;
if (stat(data_file_.c_str(), &info)!=0) {
if (stat(result_file_.c_str(), &info)!=0) {
FATAL("Error %s file %s\n",
strerror(errno), data_file_.c_str());
}
@@ -231,18 +237,14 @@ class BinaryTreeTest {
void Naive(index_t query,
pair<Precision_t, index_t> *result) {
for(index_t i=0; i<num_of_points_; i++) {
if (unlikely(data_.get_id(i)==data_.get_id(query))) {
continue;
}
Precision_t dist=Metric_t::Distance(data_.At(i),
data_.At(query),
dimension_);
result[i].first=dist;
result[i].second=i;
result[i].second=data_.get_id(i);
}
sort(result, result+num_of_points_);
std::sort(result, result+num_of_points_);
}
};
fastlib/u/nvasil/tree/node.h
+8 -7
View File
@@ -45,6 +45,13 @@ class Node {
Point_t nearest_;
Precision_t distance_;
};
class PairComparator {
public:
bool operator()(const pair<Precision_t, Point_t> &a,
const pair<Precision_t, Point_t> &b) {
return a.first<b.first;
}
};
Node();
// Use this for node
void Init(const BoundingBox_t &box,
@@ -160,13 +167,7 @@ class Node {
FILE *range_nn_fp_;
};
Precision_t min_dist_so_far_;
class PairComparator {
public:
bool operator()(const pair<Precision_t, Point_t> &a,
const pair<Precision_t, Point_t> &b) {
return a.first<b.first;
}
};
};
#include "node_impl.h"
fastlib/u/nvasil/tree/node.h~
+3 -4
View File
@@ -144,9 +144,8 @@ class Node {
void set_min_dist_so_far(Precision_t distance) {
min_dist_so_far_=distance;
}
string Print(int32 dimension) {
}
string Print(int32 dimension);
private:
BoundingBox_t box_;
index_t node_id_;
@@ -163,7 +162,7 @@ class Node {
Precision_t min_dist_so_far_;
class PairComparator {
public:
bool operator()(const pair<Precision_t, Point_t> &a,
bool operator()(const pair<Precision_t, Point_t> &a,
const pair<Precision_t, Point_t> &b) {
return a.first<b.first;
}
fastlib/u/nvasil/tree/node_impl.h
+16 -6
View File
@@ -140,13 +140,23 @@ inline void NODE__::FindNearest(POINTTYPE query_point,
// for k-nearest neighbors
if (Loki::TypeTraits<NEIGHBORTYPE>::isStdFloat==false) {
typename std::vector<pair<Precision_t, Point_t> >::iterator it;
it=nearest.begin()+(index_t)range;
std::partial_sort(nearest.begin(),
it,
nearest.end(),
PairComparator());
if (nearest.size()>(uint32)range) {
//it=nearest.begin()+(index_t)range;
index_t j=0;
for(it=nearest.begin(), j=0; j<(index_t)range; j++) {
it++;
}
std::sort(nearest.begin(),
nearest.end(),
PairComparator());
if (likely(nearest.size()>(uint32)range)) {
nearest.erase(it, nearest.end());
} else {
pair<Precision_t, Point_t> dummy;
dummy.first=numeric_limits<Precision_t>::max();
index_t extra_size=(index_t)(range-nearest.size());
for(index_t i=0; i<extra_size; i++) {
nearest.push_back(dummy);
}
}
}
}
fastlib/u/nvasil/tree/node_impl.h~
+17 -7
View File
@@ -140,13 +140,23 @@ inline void NODE__::FindNearest(POINTTYPE query_point,
// for k-nearest neighbors
if (Loki::TypeTraits<NEIGHBORTYPE>::isStdFloat==false) {
typename std::vector<pair<Precision_t, Point_t> >::iterator it;
it=nearest.begin()+(index_t)range;
std::partial_sort(nearest.begin(),
it,
nearest.end(),
PairComparator());
if (nearest.size()>(uint32)range) {
//it=nearest.begin()+(index_t)range;
index_t j=0;
for(it=nearest.begin(), j=0; j<range; j++) {
it++;
}
std::sort(nearest.begin(),
nearest.end(),
PairComparator());
if (likely(nearest.size()>(uint32)range)) {
nearest.erase(it, nearest.end());
} else {
pair<Precision_t, Point_t> dummy;
dummy.first=numeric_limits<Precision_t>::max();
index_t extra_size=(index_t)(range-nearest.size());
for(index_t i=0; i<extra_size; i++) {
nearest.push_back(dummy);
}
}
}
}
@@ -251,7 +261,7 @@ string NODE__::Print(int32 dimension) {
sprintf(buf,"%lg ", points_[i*dimension+j]);
str.append(buf);
}
sprintf(buf, "-"LI" \n", index_[i]);
sprintf(buf, "-%llu \n",(unsigned long long) index_[i]);
str.append(buf);
}
}