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Fix allkfn so allkfn_test compiles (however, it throws an error)

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This commit is contained in:
Ryan Curtin
2010-06-18 22:58:25 +00:00
parent 20ba756bf8
commit 46f7b7b3ac
2 changed files with 53 additions and 62 deletions
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fastlib/branches/fastlib-stl/mlpack/allkfn/allkfn.h
+35 -44
View File
@@ -113,9 +113,9 @@ class AllkFN {
// The number of points in a leaf
index_t leaf_size_;
// The distance to the candidate nearest neighbor for each query
Vector neighbor_distances_;
arma::vec neighbor_distances_;
// The indices of the candidate nearest neighbor for each query
ArrayList<index_t> neighbor_indices_;
arma::Col<index_t> neighbor_indices_;
// number of nearest neighbrs
index_t kfns_;
// The module containing the parameters for this computation.
@@ -191,10 +191,10 @@ class AllkFN {
Vector query_point;
queries_.MakeColumnVector(query_index, &query_point);
index_t ind = query_index*kfns_;
index_t ind = query_index * kfns_;
for(index_t i=0; i<kfns_; i++) {
neighbors[i]=std::make_pair(neighbor_distances_[ind+i],
neighbor_indices_[ind+i]);
neighbors[i] = std::make_pair(neighbor_distances_[ind + i],
neighbor_indices_[ind + i]);
}
// We'll do the same for the references
for (index_t reference_index = reference_node->begin();
@@ -211,7 +211,7 @@ class AllkFN {
la::DistanceSqEuclidean(query_point, reference_point);
// If the reference point is closer than the current candidate,
// we'll update the candidate
if (distance > neighbor_distances_[ind+kfns_-1]) {
if (distance > neighbor_distances_[ind + kfns_ - 1]) {
neighbors.push_back(std::make_pair(distance, reference_index));
}
}
@@ -379,11 +379,10 @@ class AllkFN {
kfns_ = fx_param_int(module_, "kfns", 1);
// Initialize the list of nearest neighbor candidates
neighbor_indices_.Init(queries_.n_cols() * kfns_);
neighbor_indices_.set_size(queries_.n_cols() * kfns_);
// Initialize the vector of upper bounds for each point.
neighbor_distances_.Init(queries_.n_cols() * kfns_);
neighbor_distances_.SetAll(0);
neighbor_distances_.zeros(queries_.n_cols() * kfns_);
// We'll time tree building
fx_timer_start(module_, "tree_building");
@@ -427,11 +426,10 @@ class AllkFN {
kfns_ = fx_param_int(module_, "kfns", 1);
// Initialize the list of nearest neighbor candidates
neighbor_indices_.Init(references_.n_cols() * kfns_);
neighbor_indices_.set_size(references_.n_cols() * kfns_);
// Initialize the vector of upper bounds for each point.
neighbor_distances_.Init(references_.n_cols() * kfns_);
neighbor_distances_.SetAll(0.0);
neighbor_distances_.zeros(references_.n_cols() * kfns_);
// We'll time tree building
fx_timer_start(module_, "tree_building");
@@ -471,11 +469,10 @@ class AllkFN {
// Initialize the list of nearest neighbor candidates
neighbor_indices_.Init(queries_.n_cols() * kfns_);
neighbor_indices_.set_size(queries_.n_cols() * kfns_);
// Initialize the vector of upper bounds for each point.
neighbor_distances_.Init(queries_.n_cols() * kfns_);
neighbor_distances_.SetAll(0);
neighbor_distances_.zeros(queries_.n_cols() * kfns_);
// This call makes each tree from a matrix, leaf size, and two arrays
@@ -507,11 +504,10 @@ class AllkFN {
queries_.Alias(references_);
// Initialize the list of nearest neighbor candidates
neighbor_indices_.Init(references_.n_cols() * kfns_);
neighbor_indices_.set_size(references_.n_cols() * kfns_);
// Initialize the vector of upper bounds for each point.
neighbor_distances_.Init(references_.n_cols() * kfns_);
neighbor_distances_.SetAll(0.0);
neighbor_distances_.zeros(references_.n_cols() * kfns_);
// This call makes each tree from a matrix, leaf size, and two arrays
@@ -527,8 +523,6 @@ class AllkFN {
void Destruct() {
queries_.Destruct();
references_.Destruct();
neighbor_distances_.Destruct();
neighbor_indices_.Renew();
if (query_tree_ != NULL) {
delete query_tree_;
query_tree_=NULL;
@@ -552,9 +546,8 @@ class AllkFN {
DEBUG_SAME_SIZE(queries_.n_rows(), references_.n_rows());
neighbor_indices_.Init(queries_.n_cols()*kfns_);
neighbor_distances_.Init(queries_.n_cols()*kfns_);
neighbor_distances_.SetAll(0.0);
neighbor_indices_.set_size(queries_.n_cols()*kfns_);
neighbor_distances_.zeros(queries_.n_cols()*kfns_);
// The only difference is that we set leaf_size_ to be large enough
// that each tree has only one node
@@ -576,9 +569,8 @@ class AllkFN {
queries_.Alias(references_);
kfns_=kfns;
neighbor_indices_.Init(references_.n_cols()*kfns_);
neighbor_distances_.Init(references_.n_cols()*kfns_);
neighbor_distances_.SetAll(0.0);
neighbor_indices_.set_size(references_.n_cols()*kfns_);
neighbor_distances_.zeros(references_.n_cols()*kfns_);
// The only difference is that we set leaf_size_ to be large enough
// that each tree has only one node
@@ -594,8 +586,8 @@ class AllkFN {
/**
* Computes the nearest neighbors and stores them in *results
*/
void ComputeNeighbors(ArrayList<index_t>* resulting_neighbors,
ArrayList<double>* distances) {
void ComputeNeighbors(arma::Col<index_t>& resulting_neighbors,
arma::vec& distances) {
// Start on the root of each tree
if (query_tree_!=NULL) {
@@ -607,25 +599,25 @@ class AllkFN {
}
// We need to initialize the results list before filling it
resulting_neighbors->Init(neighbor_indices_.size());
distances->Init(neighbor_distances_.length());
resulting_neighbors.set_size(neighbor_indices_.n_elem);
distances.set_size(neighbor_distances_.n_elem);
// We need to map the indices back from how they have
// been permuted
if (query_tree_ != NULL) {
for (index_t i = 0; i < neighbor_indices_.size(); i++) {
(*resulting_neighbors)[
for (index_t i = 0; i < neighbor_indices_.n_elem; i++) {
resulting_neighbors[
old_from_new_queries_[(i / kfns_)] * kfns_ + i % kfns_] =
old_from_new_references_[neighbor_indices_[i]];
(*distances)[
distances[
old_from_new_queries_[(i / kfns_)] * kfns_ + i % kfns_] =
neighbor_distances_[i];
}
} else {
for (index_t i = 0; i < neighbor_indices_.size(); i++) {
(*resulting_neighbors)[
for (index_t i = 0; i < neighbor_indices_.n_elem; i++) {
resulting_neighbors[
old_from_new_references_[(i / kfns_)] * kfns_ + i % kfns_] =
old_from_new_references_[neighbor_indices_[i]];
(*distances)[
distances[
old_from_new_references_[(i / kfns_)] * kfns_+ i % kfns_] =
neighbor_distances_[i];
}
@@ -636,8 +628,8 @@ class AllkFN {
/**
* Does the entire computation naively
*/
void ComputeNaive(ArrayList<index_t>* resulting_neighbors,
ArrayList<double>* distances) {
void ComputeNaive(arma::Col<index_t>& resulting_neighbors,
arma::vec& distances) {
if (query_tree_!=NULL) {
ComputeBaseCase_(query_tree_, reference_tree_);
} else {
@@ -645,18 +637,17 @@ class AllkFN {
}
// The same code as above
resulting_neighbors->Init(neighbor_indices_.size());
distances->Init(neighbor_distances_.length());
resulting_neighbors.set_size(neighbor_indices_.n_elem);
distances.set_size(neighbor_distances_.n_elem);
// We need to map the indices back from how they have
// been permuted
for (index_t i = 0; i < neighbor_indices_.size(); i++) {
(*resulting_neighbors)[
for (index_t i = 0; i < neighbor_indices_.n_elem; i++) {
resulting_neighbors[
old_from_new_references_[(i / kfns_)] * kfns_ + i % kfns_] =
old_from_new_references_[neighbor_indices_[i]];
(*distances)[
distances[
old_from_new_references_[(i / kfns_)] * kfns_ + i % kfns_] =
neighbor_distances_[i];
}
}
fastlib/branches/fastlib-stl/mlpack/allkfn/allkfn_test.cc
+18 -18
View File
@@ -31,15 +31,15 @@ class TestAllkFN {
allkfn_->Init(*data_for_tree_, *data_for_tree_, 20, 5);
naive_->InitNaive(*data_for_tree_, *data_for_tree_, 5);
ArrayList<index_t> resulting_neighbors_tree;
ArrayList<double> distances_tree;
allkfn_->ComputeNeighbors(&resulting_neighbors_tree,
&distances_tree);
ArrayList<index_t> resulting_neighbors_naive;
ArrayList<double> distances_naive;
naive_->ComputeNaive(&resulting_neighbors_naive,
&distances_naive);
for(index_t i=0; i<resulting_neighbors_tree.size(); i++) {
arma::Col<index_t> resulting_neighbors_tree;
arma::vec distances_tree;
allkfn_->ComputeNeighbors(resulting_neighbors_tree,
distances_tree);
arma::Col<index_t> resulting_neighbors_naive;
arma::vec distances_naive;
naive_->ComputeNaive(resulting_neighbors_naive,
distances_naive);
for(index_t i=0; i<resulting_neighbors_tree.n_elem; i++) {
TEST_ASSERT(resulting_neighbors_tree[i] == resulting_neighbors_naive[i]);
TEST_DOUBLE_APPROX(distances_tree[i], distances_naive[i], 1e-5);
}
@@ -51,15 +51,15 @@ class TestAllkFN {
allkfn_->Init(*data_for_tree_, 20, 5);
naive_->InitNaive(*data_for_tree_, 5);
ArrayList<index_t> resulting_neighbors_tree;
ArrayList<double> distances_tree;
allkfn_->ComputeNeighbors(&resulting_neighbors_tree,
&distances_tree);
ArrayList<index_t> resulting_neighbors_naive;
ArrayList<double> distances_naive;
naive_->ComputeNaive(&resulting_neighbors_naive,
&distances_naive);
for(index_t i=0; i<resulting_neighbors_tree.size(); i++) {
arma::Col<index_t> resulting_neighbors_tree;
arma::vec distances_tree;
allkfn_->ComputeNeighbors(resulting_neighbors_tree,
distances_tree);
arma::Col<index_t> resulting_neighbors_naive;
arma::vec distances_naive;
naive_->ComputeNaive(resulting_neighbors_naive,
distances_naive);
for(index_t i=0; i<resulting_neighbors_tree.n_elem; i++) {
TEST_ASSERT(resulting_neighbors_tree[i] == resulting_neighbors_naive[i]);
TEST_DOUBLE_APPROX(distances_tree[i], distances_naive[i], 1e-5);
}