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Include new KNN and KFN tests and some fixes.

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This commit is contained in:
Ryan Curtin
2019-08-16 10:13:35 -04:00
parent 52c11a93c0
commit b03ee8bd3b
3 changed files with 41 additions and 42 deletions
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src/mlpack/tests/CMakeLists.txt
+2
View File
@@ -131,6 +131,8 @@ add_executable(mlpack_test
main_tests/gmm_train_test.cpp
main_tests/fastmks_test.cpp
main_tests/kde_test.cpp
main_tests/kfn_test.cpp
main_tests/knn_test.cpp
main_tests/linear_regression_test.cpp
main_tests/logistic_regression_test.cpp
main_tests/local_coordinate_coding_test.cpp
src/mlpack/tests/main_tests/kfn_test.cpp
+23 -24
View File
@@ -78,7 +78,7 @@ BOOST_AUTO_TEST_CASE(KFNInvalidKTest)
referenceData.randu(3, 100); // 100 points in 3 dimensions.
// Random input, some k > number of reference points.
SetInputParam("reference", std::move(referenceData));
SetInputParam("reference", referenceData);
SetInputParam("k", (int) 101);
Log::Fatal.ignoreInput = true;
@@ -422,33 +422,30 @@ BOOST_AUTO_TEST_CASE(KFNRandomBasisTest)
// Random input, some k <= number of reference points.
SetInputParam("reference", referenceData);
SetInputParam("k", (int) 10);
SetInputParam("algorithm", (string) "greedy");
CLI::SetPassed("random_basis");
mlpackMain();
KFNModel* randomBasisModel;
arma::Mat<size_t> neighbors;
arma::mat distances;
neighbors = std::move(CLI::GetParam<arma::Mat<size_t>>("neighbors"));
distances = std::move(CLI::GetParam<arma::mat>("distances"));
randomBasisModel = std::move(CLI::GetParam<KFNModel*>("output_model"));
BOOST_REQUIRE_EQUAL(CLI::GetParam<KFNModel*>("output_model")->RandomBasis(),
true);
bindings::tests::CleanMemory();
CLI::GetSingleton().Parameters()["reference"].wasPassed = false;
CLI::GetSingleton().Parameters()["random_basis"].wasPassed = false;
SetInputParam("reference", std::move(referenceData));
mlpackMain();
CheckMatrices(neighbors,
CLI::GetParam<arma::Mat<size_t>>("neighbors"));
CheckMatrices(distances,
CLI::GetParam<arma::mat>("distances"));
BOOST_REQUIRE_EQUAL(randomBasisModel->RandomBasis(), true);
BOOST_REQUIRE_EQUAL(CLI::GetParam<KFNModel*>("distances")->RandomBasis(),
false);
CheckMatrices(neighbors, CLI::GetParam<arma::Mat<size_t>>("neighbors"));
CheckMatrices(distances, CLI::GetParam<arma::mat>("distances"));
BOOST_REQUIRE_EQUAL(CLI::GetParam<KFNModel*>("output_model")->RandomBasis(),
false);
}
/*
@@ -483,10 +480,10 @@ BOOST_AUTO_TEST_CASE(KFNTrueNeighborDistanceTest)
BOOST_REQUIRE_NO_THROW(mlpackMain());
// True output matrices have incorrect shape.
arma::Mat<size_t> dummy_neighbors;
arma::mat dummy_distances;
dummy_neighbors.randu(20, 100);
dummy_distances.randu(20, 100);
arma::Mat<size_t> dummyNeighbors;
arma::mat dummyDistances;
dummyNeighbors.randu(20, 100);
dummyDistances.randu(20, 100);
// bindings::tests::CleanMemory();
@@ -495,8 +492,8 @@ BOOST_AUTO_TEST_CASE(KFNTrueNeighborDistanceTest)
CLI::GetSingleton().Parameters()["true_distances"].wasPassed = false;
SetInputParam("reference", std::move(referenceData));
SetInputParam("true_neighbors", std::move(dummy_neighbors));
SetInputParam("true_distances", std::move(dummy_distances));
SetInputParam("true_neighbors", std::move(dummyNeighbors));
SetInputParam("true_distances", std::move(dummyDistances));
Log::Fatal.ignoreInput = true;
BOOST_REQUIRE_THROW(mlpackMain(), std::runtime_error);
@@ -596,8 +593,8 @@ BOOST_AUTO_TEST_CASE(KFNAllTreeTypesTest)
if (i == 0)
{
neighborsCompare = std::move(CLI::GetParam<arma::Mat<size_t>>
("neighbors"));
neighborsCompare = std::move(
CLI::GetParam<arma::Mat<size_t>>("neighbors"));
distancesCompare = std::move(CLI::GetParam<arma::mat>("distances"));
}
else
@@ -625,14 +622,17 @@ BOOST_AUTO_TEST_CASE(KFNDifferentLeafSizes)
referenceData.randu(3, 100); // 100 points in 3 dimensions.
// Random input, some k <= number of reference points.
SetInputParam("reference", std::move(referenceData));
SetInputParam("reference", referenceData);
SetInputParam("k", (int) 10);
SetInputParam("leaf_size", (int) 1);
KFNModel* output_model;
output_model = std::move(CLI::GetParam<KFNModel*>("output_model"));
mlpackMain();
BOOST_CHECK_EQUAL(CLI::GetParam<KFNModel*>("output_model")->LeafSize(),
(int) 1);
bindings::tests::CleanMemory();
// Reset passed parameters.
CLI::GetSingleton().Parameters()["reference"].wasPassed = false;
@@ -645,9 +645,8 @@ BOOST_AUTO_TEST_CASE(KFNDifferentLeafSizes)
// Check that initial output matrices and the output matrices using
// saved model are equal.
BOOST_CHECK_EQUAL(output_model->LeafSize(), (int) 1);
BOOST_CHECK_EQUAL(CLI::GetParam<KFNModel*>("output_model")->LeafSize(),
(int) 10);
(int) 10);
}
BOOST_AUTO_TEST_SUITE_END();
src/mlpack/tests/main_tests/knn_test.cpp
+16 -18
View File
@@ -258,8 +258,8 @@ BOOST_AUTO_TEST_CASE(KNNInvalidRhoTest)
}
/**
* Make sure that dimensions of the neighbors and distances
* matrices are correct given a value of k.
* Make sure that dimensions of the neighbors and distances matrices are correct
* given a value of k.
*/
BOOST_AUTO_TEST_CASE(KNNOutputDimensionTest)
{
@@ -377,7 +377,7 @@ BOOST_AUTO_TEST_CASE(KNNDifferentRhoTest)
SetInputParam("k", (int) 10);
SetInputParam("tree_type", (string) "spill");
SetInputParam("tau", (double) 0.3);
SetInputParam("rho", (double) 0.2);
SetInputParam("rho", (double) 0.01);
SetInputParam("algorithm", (string) "greedy");
mlpackMain();
@@ -393,7 +393,7 @@ BOOST_AUTO_TEST_CASE(KNNDifferentRhoTest)
CLI::GetSingleton().Parameters()["rho"].wasPassed = false;
SetInputParam("reference", std::move(referenceData));
SetInputParam("rho", (double) 0.8);
SetInputParam("rho", (double) 0.99);
mlpackMain();
@@ -458,27 +458,25 @@ BOOST_AUTO_TEST_CASE(KNNRandomBasisTest)
mlpackMain();
arma::Mat<size_t> neighbors;
KNNModel* randomBasisModel;
arma::mat distances;
neighbors = std::move(CLI::GetParam<arma::Mat<size_t>>("neighbors"));
distances = std::move(CLI::GetParam<arma::mat>("distances"));
randomBasisModel = std::move(CLI::GetParam<KNNModel*>("output_model"));
BOOST_REQUIRE_EQUAL(CLI::GetParam<KNNModel*>("output_model")->RandomBasis(),
true);
bindings::tests::CleanMemory();
CLI::GetSingleton().Parameters()["reference"].wasPassed = false;
CLI::GetSingleton().Parameters()["random_basis"].wasPassed = false;
SetInputParam("reference", std::move(referenceData));
mlpackMain();
CheckMatrices(neighbors,
CLI::GetParam<arma::Mat<size_t>>("neighbors"));
CheckMatrices(distances,
CLI::GetParam<arma::mat>("distances"));
BOOST_REQUIRE_EQUAL(randomBasisModel->RandomBasis(), true);
BOOST_REQUIRE_EQUAL(CLI::GetParam<KNNModel*>("distances")->RandomBasis(),
false);
CheckMatrices(neighbors, CLI::GetParam<arma::Mat<size_t>>("neighbors"));
CheckMatrices(distances, CLI::GetParam<arma::mat>("distances"));
BOOST_REQUIRE_EQUAL(CLI::GetParam<KNNModel*>("output_model")->RandomBasis(),
false);
}
/*
@@ -567,8 +565,8 @@ BOOST_AUTO_TEST_CASE(KNNAllAlgorithmsTest)
if (i == 0)
{
neighborsCompare = std::move(CLI::GetParam<arma::Mat<size_t>>
("neighbors"));
neighborsCompare = std::move(
CLI::GetParam<arma::Mat<size_t>>("neighbors"));
distancesCompare = std::move(CLI::GetParam<arma::mat>("distances"));
}
else
@@ -625,8 +623,8 @@ BOOST_AUTO_TEST_CASE(KNNAllTreeTypesTest)
if (i == 0)
{
neighborsCompare = std::move(CLI::GetParam<arma::Mat<size_t>>
("neighbors"));
neighborsCompare = std::move(
CLI::GetParam<arma::Mat<size_t>>("neighbors"));
distancesCompare = std::move(CLI::GetParam<arma::mat>("distances"));
}
else
@@ -654,7 +652,7 @@ BOOST_AUTO_TEST_CASE(KNNDifferentLeafSizes)
referenceData.randu(3, 100); // 100 points in 3 dimensions.
// Random input, some k <= number of reference points.
SetInputParam("reference", std::move(referenceData));
SetInputParam("reference", referenceData);
SetInputParam("k", (int) 10);
SetInputParam("leaf_size", (int) 1);