int main(int argc, char** argv)
{
// Contains query points.
arma::mat query(2,3);
query << 5 << 6 << 2.75 << arma::endr << 1.45 << 2 << 0.75 << arma::endr;
// Load the data.
arma::mat data;
data::Load("../data/fisheriris_data.csv", data, true);
// Choose the last two columns.
data = data.rows(2,3);
std::vector<size_t> oldFromNewRefs;
std::vector<size_t> oldFromNewQueries;
arma::mat distancesOut;
arma::Mat<size_t> neighborsOut;
// Calculate the all 2-nearest-neighbors .
BinarySpaceTree<bound::HRectBound<2>, QueryStat<NearestNeighborSort> >
refTree(data, oldFromNewRefs, 20);
BinarySpaceTree<bound::HRectBound<2>, QueryStat<NearestNeighborSort> >*
queryTree = new BinarySpaceTree<bound::HRectBound<2>,
QueryStat<NearestNeighborSort> >(query, oldFromNewQueries, 20);
AllkNN* allknn = new AllkNN(&refTree, queryTree, data, query, false);
allknn->Search(2, neighborsOut, distancesOut);
arma::Mat<size_t> neighbors;
arma::mat distances;
// Map the results back to the correct places.
Unmap(neighborsOut, distancesOut, oldFromNewRefs, oldFromNewQueries,
neighbors, distances);
// Clean up.
delete queryTree;
delete allknn;
// Show the results.
Log::cout << distances.t() << std::endl;
Log::cout << neighbors.t() << std::endl;
return 0;
}
int main(int argc, char *argv[])
{
// Give CLI the command line parameters the user passed in.
CLI::ParseCommandLine(argc, argv);
if (CLI::GetParam<int>("seed") != 0)
math::RandomSeed((size_t) CLI::GetParam<int>("seed"));
else
math::RandomSeed((size_t) std::time(NULL));
// Get all the parameters.
const string referenceFile = CLI::GetParam<string>("reference_file");
const string queryFile = CLI::GetParam<string>("query_file");
const string distancesFile = CLI::GetParam<string>("distances_file");
const string neighborsFile = CLI::GetParam<string>("neighbors_file");
int lsInt = CLI::GetParam<int>("leaf_size");
size_t k = CLI::GetParam<int>("k");
bool naive = CLI::HasParam("naive");
bool singleMode = CLI::HasParam("single_mode");
const bool randomBasis = CLI::HasParam("random_basis");
arma::mat referenceData;
arma::mat queryData; // So it doesn't go out of scope.
data::Load(referenceFile, referenceData, true);
Log::Info << "Loaded reference data from '" << referenceFile << "' ("
<< referenceData.n_rows << " x " << referenceData.n_cols << ")." << endl;
if (queryFile != "")
{
data::Load(queryFile, queryData, true);
Log::Info << "Loaded query data from '" << queryFile << "' ("
<< queryData.n_rows << " x " << queryData.n_cols << ")." << endl;
}
// Sanity check on k value: must be greater than 0, must be less than the
// number of reference points.
if (k > referenceData.n_cols)
{
Log::Fatal << "Invalid k: " << k << "; must be greater than 0 and less ";
Log::Fatal << "than or equal to the number of reference points (";
Log::Fatal << referenceData.n_cols << ")." << endl;
}
// Sanity check on leaf size.
if (lsInt < 0)
{
Log::Fatal << "Invalid leaf size: " << lsInt << ". Must be greater "
"than or equal to 0." << endl;
}
size_t leafSize = lsInt;
// Naive mode overrides single mode.
if (singleMode && naive)
{
Log::Warn << "--single_mode ignored because --naive is present." << endl;
}
if (naive)
leafSize = referenceData.n_cols;
// See if we want to project onto a random basis.
if (randomBasis)
{
// Generate the random basis.
while (true)
{
// [Q, R] = qr(randn(d, d));
// Q = Q * diag(sign(diag(R)));
arma::mat q, r;
if (arma::qr(q, r, arma::randn<arma::mat>(referenceData.n_rows,
referenceData.n_rows)))
{
arma::vec rDiag(r.n_rows);
for (size_t i = 0; i < rDiag.n_elem; ++i)
{
if (r(i, i) < 0)
rDiag(i) = -1;
else if (r(i, i) > 0)
rDiag(i) = 1;
else
rDiag(i) = 0;
}
q *= arma::diagmat(rDiag);
// Check if the determinant is positive.
if (arma::det(q) >= 0)
{
referenceData = q * referenceData;
if (queryFile != "")
queryData = q * queryData;
break;
}
}
}
}
arma::Mat<size_t> neighbors;
arma::mat distances;
if (!CLI::HasParam("cover_tree"))
{
// Because we may construct it differently, we need a pointer.
AllkNN* allknn = NULL;
// Mappings for when we build the tree.
std::vector<size_t> oldFromNewRefs;
// Build trees by hand, so we can save memory: if we pass a tree to
// NeighborSearch, it does not copy the matrix.
Log::Info << "Building reference tree..." << endl;
Timer::Start("tree_building");
BinarySpaceTree<bound::HRectBound<2>,
NeighborSearchStat<NearestNeighborSort> >
refTree(referenceData, oldFromNewRefs, leafSize);
BinarySpaceTree<bound::HRectBound<2>,
NeighborSearchStat<NearestNeighborSort> >*
queryTree = NULL; // Empty for now.
Timer::Stop("tree_building");
std::vector<size_t> oldFromNewQueries;
if (CLI::GetParam<string>("query_file") != "")
{
if (naive && leafSize < queryData.n_cols)
leafSize = queryData.n_cols;
Log::Info << "Loaded query data from '" << queryFile << "' ("
<< queryData.n_rows << " x " << queryData.n_cols << ")." << endl;
Log::Info << "Building query tree..." << endl;
// Build trees by hand, so we can save memory: if we pass a tree to
// NeighborSearch, it does not copy the matrix.
if (!singleMode)
{
Timer::Start("tree_building");
queryTree = new BinarySpaceTree<bound::HRectBound<2>,
NeighborSearchStat<NearestNeighborSort> >(queryData,
oldFromNewQueries, leafSize);
Timer::Stop("tree_building");
}
allknn = new AllkNN(&refTree, queryTree, referenceData, queryData,
singleMode);
Log::Info << "Tree built." << endl;
}
else
{
allknn = new AllkNN(&refTree, referenceData, singleMode);
Log::Info << "Trees built." << endl;
}
arma::mat distancesOut;
arma::Mat<size_t> neighborsOut;
Log::Info << "Computing " << k << " nearest neighbors..." << endl;
allknn->Search(k, neighborsOut, distancesOut);
Log::Info << "Neighbors computed." << endl;
// We have to map back to the original indices from before the tree
// construction.
Log::Info << "Re-mapping indices..." << endl;
// Map the results back to the correct places.
if ((CLI::GetParam<string>("query_file") != "") && !singleMode)
Unmap(neighborsOut, distancesOut, oldFromNewRefs, oldFromNewQueries,
neighbors, distances);
else if ((CLI::GetParam<string>("query_file") != "") && singleMode)
Unmap(neighborsOut, distancesOut, oldFromNewRefs, neighbors, distances);
else
Unmap(neighborsOut, distancesOut, oldFromNewRefs, oldFromNewRefs,
neighbors, distances);
// Clean up.
if (queryTree)
delete queryTree;
delete allknn;
}
else // Cover trees.
{
// Make sure to notify the user that they are using cover trees.
Log::Info << "Using cover trees for nearest-neighbor calculation." << endl;
// Build our reference tree.
Log::Info << "Building reference tree..." << endl;
Timer::Start("tree_building");
CoverTree<metric::LMetric<2, true>, tree::FirstPointIsRoot,
NeighborSearchStat<NearestNeighborSort> > referenceTree(referenceData,
1.3);
CoverTree<metric::LMetric<2, true>, tree::FirstPointIsRoot,
NeighborSearchStat<NearestNeighborSort> >* queryTree = NULL;
Timer::Stop("tree_building");
NeighborSearch<NearestNeighborSort, metric::LMetric<2, true>,
CoverTree<metric::LMetric<2, true>, tree::FirstPointIsRoot,
NeighborSearchStat<NearestNeighborSort> > >* allknn = NULL;
// See if we have query data.
if (CLI::HasParam("query_file"))
{
// Build query tree.
if (!singleMode)
{
Log::Info << "Building query tree..." << endl;
Timer::Start("tree_building");
queryTree = new CoverTree<metric::LMetric<2, true>,
tree::FirstPointIsRoot, NeighborSearchStat<NearestNeighborSort> >(
queryData, 1.3);
Timer::Stop("tree_building");
}
allknn = new NeighborSearch<NearestNeighborSort, metric::LMetric<2, true>,
CoverTree<metric::LMetric<2, true>, tree::FirstPointIsRoot,
NeighborSearchStat<NearestNeighborSort> > >(&referenceTree, queryTree,
referenceData, queryData, singleMode);
}
else
{
allknn = new NeighborSearch<NearestNeighborSort, metric::LMetric<2, true>,
CoverTree<metric::LMetric<2, true>, tree::FirstPointIsRoot,
NeighborSearchStat<NearestNeighborSort> > >(&referenceTree,
referenceData, singleMode);
}
Log::Info << "Computing " << k << " nearest neighbors..." << endl;
allknn->Search(k, neighbors, distances);
Log::Info << "Neighbors computed." << endl;
delete allknn;
if (queryTree)
delete queryTree;
}
// Save output.
data::Save(distancesFile, distances);
data::Save(neighborsFile, neighbors);
}
