[mlpack-git] master: Added the Hilbert R tree to (A)KNNTest, RangeSearchTest and KRANNTest. (6f19e4d)
gitdub at mlpack.org
gitdub at mlpack.org
Tue Jun 28 10:40:02 EDT 2016
Repository : https://github.com/mlpack/mlpack
On branch : master
Link : https://github.com/mlpack/mlpack/compare/9dd66c7312ffcce6bc7b51aff00d38b75263f4b0...6077f120935e10ffa01d80a8398e28a90a8d011a
>---------------------------------------------------------------
commit 6f19e4d6513d0f1103d708152ee4b849785fdb1e
Author: Mikhail Lozhnikov <lozhnikovma at gmail.com>
Date: Tue Jun 28 17:40:02 2016 +0300
Added the Hilbert R tree to (A)KNNTest, RangeSearchTest and KRANNTest.
>---------------------------------------------------------------
6f19e4d6513d0f1103d708152ee4b849785fdb1e
src/mlpack/tests/aknn_test.cpp | 12 ++++++++----
src/mlpack/tests/knn_test.cpp | 12 ++++++++----
src/mlpack/tests/krann_search_test.cpp | 6 ++++--
src/mlpack/tests/range_search_test.cpp | 12 ++++++++----
4 files changed, 28 insertions(+), 14 deletions(-)
diff --git a/src/mlpack/tests/aknn_test.cpp b/src/mlpack/tests/aknn_test.cpp
index 23c7c9f..4af732b 100644
--- a/src/mlpack/tests/aknn_test.cpp
+++ b/src/mlpack/tests/aknn_test.cpp
@@ -287,7 +287,7 @@ BOOST_AUTO_TEST_CASE(KNNModelTest)
arma::mat referenceData = arma::randu<arma::mat>(10, 200);
// Build all the possible models.
- KNNModel models[12];
+ KNNModel models[14];
models[0] = KNNModel(KNNModel::TreeTypes::KD_TREE, true);
models[1] = KNNModel(KNNModel::TreeTypes::KD_TREE, false);
models[2] = KNNModel(KNNModel::TreeTypes::COVER_TREE, true);
@@ -300,6 +300,8 @@ BOOST_AUTO_TEST_CASE(KNNModelTest)
models[9] = KNNModel(KNNModel::TreeTypes::X_TREE, false);
models[10] = KNNModel(KNNModel::TreeTypes::BALL_TREE, true);
models[11] = KNNModel(KNNModel::TreeTypes::BALL_TREE, false);
+ models[12] = KNNModel(KNNModel::TreeTypes::HILBERT_R_TREE, true);
+ models[13] = KNNModel(KNNModel::TreeTypes::HILBERT_R_TREE, false);
for (size_t j = 0; j < 3; ++j)
{
@@ -309,7 +311,7 @@ BOOST_AUTO_TEST_CASE(KNNModelTest)
arma::mat distancesExact;
aknn.Search(queryData, 3, neighborsExact, distancesExact);
- for (size_t i = 0; i < 12; ++i)
+ for (size_t i = 0; i < 14; ++i)
{
// We only have std::move() constructors so make a copy of our data.
arma::mat referenceCopy(referenceData);
@@ -349,7 +351,7 @@ BOOST_AUTO_TEST_CASE(KNNModelMonochromaticTest)
arma::mat referenceData = arma::randu<arma::mat>(10, 200);
// Build all the possible models.
- KNNModel models[12];
+ KNNModel models[14];
models[0] = KNNModel(KNNModel::TreeTypes::KD_TREE, true);
models[1] = KNNModel(KNNModel::TreeTypes::KD_TREE, false);
models[2] = KNNModel(KNNModel::TreeTypes::COVER_TREE, true);
@@ -362,6 +364,8 @@ BOOST_AUTO_TEST_CASE(KNNModelMonochromaticTest)
models[9] = KNNModel(KNNModel::TreeTypes::X_TREE, false);
models[10] = KNNModel(KNNModel::TreeTypes::BALL_TREE, true);
models[11] = KNNModel(KNNModel::TreeTypes::BALL_TREE, false);
+ models[12] = KNNModel(KNNModel::TreeTypes::HILBERT_R_TREE, true);
+ models[13] = KNNModel(KNNModel::TreeTypes::HILBERT_R_TREE, false);
for (size_t j = 0; j < 2; ++j)
{
@@ -371,7 +375,7 @@ BOOST_AUTO_TEST_CASE(KNNModelMonochromaticTest)
arma::mat distancesExact;
exact.Search(3, neighborsExact, distancesExact);
- for (size_t i = 0; i < 12; ++i)
+ for (size_t i = 0; i < 14; ++i)
{
// We only have a std::move() constructor... so copy the data.
arma::mat referenceCopy(referenceData);
diff --git a/src/mlpack/tests/knn_test.cpp b/src/mlpack/tests/knn_test.cpp
index 85c6b7a..398aee5 100644
--- a/src/mlpack/tests/knn_test.cpp
+++ b/src/mlpack/tests/knn_test.cpp
@@ -977,7 +977,7 @@ BOOST_AUTO_TEST_CASE(KNNModelTest)
arma::mat referenceData = arma::randu<arma::mat>(10, 200);
// Build all the possible models.
- KNNModel models[12];
+ KNNModel models[14];
models[0] = KNNModel(KNNModel::TreeTypes::KD_TREE, true);
models[1] = KNNModel(KNNModel::TreeTypes::KD_TREE, false);
models[2] = KNNModel(KNNModel::TreeTypes::COVER_TREE, true);
@@ -990,6 +990,8 @@ BOOST_AUTO_TEST_CASE(KNNModelTest)
models[9] = KNNModel(KNNModel::TreeTypes::X_TREE, false);
models[10] = KNNModel(KNNModel::TreeTypes::BALL_TREE, true);
models[11] = KNNModel(KNNModel::TreeTypes::BALL_TREE, false);
+ models[12] = KNNModel(KNNModel::TreeTypes::HILBERT_R_TREE, true);
+ models[13] = KNNModel(KNNModel::TreeTypes::HILBERT_R_TREE, false);
for (size_t j = 0; j < 2; ++j)
{
@@ -999,7 +1001,7 @@ BOOST_AUTO_TEST_CASE(KNNModelTest)
arma::mat baselineDistances;
knn.Search(queryData, 3, baselineNeighbors, baselineDistances);
- for (size_t i = 0; i < 12; ++i)
+ for (size_t i = 0; i < 14; ++i)
{
// We only have std::move() constructors so make a copy of our data.
arma::mat referenceCopy(referenceData);
@@ -1043,7 +1045,7 @@ BOOST_AUTO_TEST_CASE(KNNModelMonochromaticTest)
arma::mat referenceData = arma::randu<arma::mat>(10, 200);
// Build all the possible models.
- KNNModel models[12];
+ KNNModel models[14];
models[0] = KNNModel(KNNModel::TreeTypes::KD_TREE, true);
models[1] = KNNModel(KNNModel::TreeTypes::KD_TREE, false);
models[2] = KNNModel(KNNModel::TreeTypes::COVER_TREE, true);
@@ -1056,6 +1058,8 @@ BOOST_AUTO_TEST_CASE(KNNModelMonochromaticTest)
models[9] = KNNModel(KNNModel::TreeTypes::X_TREE, false);
models[10] = KNNModel(KNNModel::TreeTypes::BALL_TREE, true);
models[11] = KNNModel(KNNModel::TreeTypes::BALL_TREE, false);
+ models[12] = KNNModel(KNNModel::TreeTypes::HILBERT_R_TREE, true);
+ models[13] = KNNModel(KNNModel::TreeTypes::HILBERT_R_TREE, false);
for (size_t j = 0; j < 2; ++j)
{
@@ -1065,7 +1069,7 @@ BOOST_AUTO_TEST_CASE(KNNModelMonochromaticTest)
arma::mat baselineDistances;
knn.Search(3, baselineNeighbors, baselineDistances);
- for (size_t i = 0; i < 12; ++i)
+ for (size_t i = 0; i < 14; ++i)
{
// We only have a std::move() constructor... so copy the data.
arma::mat referenceCopy(referenceData);
diff --git a/src/mlpack/tests/krann_search_test.cpp b/src/mlpack/tests/krann_search_test.cpp
index 805adb3..fa95c54 100644
--- a/src/mlpack/tests/krann_search_test.cpp
+++ b/src/mlpack/tests/krann_search_test.cpp
@@ -625,7 +625,7 @@ BOOST_AUTO_TEST_CASE(RAModelTest)
data::Load("rann_test_q_3_100.csv", queryData, true);
// Build all the possible models.
- KNNModel models[10];
+ KNNModel models[12];
models[0] = KNNModel(KNNModel::TreeTypes::KD_TREE, false);
models[1] = KNNModel(KNNModel::TreeTypes::KD_TREE, true);
models[2] = KNNModel(KNNModel::TreeTypes::COVER_TREE, false);
@@ -636,13 +636,15 @@ BOOST_AUTO_TEST_CASE(RAModelTest)
models[7] = KNNModel(KNNModel::TreeTypes::R_STAR_TREE, true);
models[8] = KNNModel(KNNModel::TreeTypes::X_TREE, false);
models[9] = KNNModel(KNNModel::TreeTypes::X_TREE, true);
+ models[10] = KNNModel(KNNModel::TreeTypes::HILBERT_R_TREE, false);
+ models[11] = KNNModel(KNNModel::TreeTypes::HILBERT_R_TREE, true);
arma::Mat<size_t> qrRanks;
data::Load("rann_test_qr_ranks.csv", qrRanks, true, false); // No transpose.
for (size_t j = 0; j < 3; ++j)
{
- for (size_t i = 0; i < 10; ++i)
+ for (size_t i = 0; i < 12; ++i)
{
// We only have std::move() constructors so make a copy of our data.
arma::mat referenceCopy(referenceData);
diff --git a/src/mlpack/tests/range_search_test.cpp b/src/mlpack/tests/range_search_test.cpp
index 8842971..1c9f73b 100644
--- a/src/mlpack/tests/range_search_test.cpp
+++ b/src/mlpack/tests/range_search_test.cpp
@@ -1251,7 +1251,7 @@ BOOST_AUTO_TEST_CASE(RSModelTest)
arma::mat referenceData = arma::randu<arma::mat>(10, 200);
// Build all the possible models.
- RSModel models[12];
+ RSModel models[14];
models[0] = RSModel(RSModel::TreeTypes::KD_TREE, true);
models[1] = RSModel(RSModel::TreeTypes::KD_TREE, false);
models[2] = RSModel(RSModel::TreeTypes::COVER_TREE, true);
@@ -1264,6 +1264,8 @@ BOOST_AUTO_TEST_CASE(RSModelTest)
models[9] = RSModel(RSModel::TreeTypes::X_TREE, false);
models[10] = RSModel(RSModel::TreeTypes::BALL_TREE, true);
models[11] = RSModel(RSModel::TreeTypes::BALL_TREE, false);
+ models[12] = RSModel(RSModel::TreeTypes::HILBERT_R_TREE, true);
+ models[13] = RSModel(RSModel::TreeTypes::HILBERT_R_TREE, false);
for (size_t j = 0; j < 2; ++j)
{
@@ -1277,7 +1279,7 @@ BOOST_AUTO_TEST_CASE(RSModelTest)
vector<vector<pair<double, size_t>>> baselineSorted;
SortResults(baselineNeighbors, baselineDistances, baselineSorted);
- for (size_t i = 0; i < 12; ++i)
+ for (size_t i = 0; i < 14; ++i)
{
// We only have std::move() constructors, so make a copy of our data.
arma::mat referenceCopy(referenceData);
@@ -1321,7 +1323,7 @@ BOOST_AUTO_TEST_CASE(RSModelMonochromaticTest)
arma::mat referenceData = arma::randu<arma::mat>(10, 200);
// Build all the possible models.
- RSModel models[12];
+ RSModel models[14];
models[0] = RSModel(RSModel::TreeTypes::KD_TREE, true);
models[1] = RSModel(RSModel::TreeTypes::KD_TREE, false);
models[2] = RSModel(RSModel::TreeTypes::COVER_TREE, true);
@@ -1334,6 +1336,8 @@ BOOST_AUTO_TEST_CASE(RSModelMonochromaticTest)
models[9] = RSModel(RSModel::TreeTypes::X_TREE, false);
models[10] = RSModel(RSModel::TreeTypes::BALL_TREE, true);
models[11] = RSModel(RSModel::TreeTypes::BALL_TREE, false);
+ models[12] = RSModel(RSModel::TreeTypes::HILBERT_R_TREE, true);
+ models[13] = RSModel(RSModel::TreeTypes::HILBERT_R_TREE, false);
for (size_t j = 0; j < 2; ++j)
{
@@ -1346,7 +1350,7 @@ BOOST_AUTO_TEST_CASE(RSModelMonochromaticTest)
vector<vector<pair<double, size_t>>> baselineSorted;
SortResults(baselineNeighbors, baselineDistances, baselineSorted);
- for (size_t i = 0; i < 12; ++i)
+ for (size_t i = 0; i < 14; ++i)
{
// We only have std::move() cosntructors, so make a copy of our data.
arma::mat referenceCopy(referenceData);
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