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Resolve Tests

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This commit is contained in:
Yashwant
2019-05-31 16:05:57 +05:30
parent 25c5315777
commit 4b0a41fa64
3 changed files with 49 additions and 41 deletions
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src/mlpack/tests/main_tests/gmm_generate_test.cpp
+6 -6
View File
@@ -45,8 +45,8 @@ BOOST_AUTO_TEST_CASE(GmmGenerateSamplesTest)
{
arma::mat inputData(5, 10, arma::fill::randu);
GMM gmm(1, 2);
gmm.Train(inputData, 2);
GMM gmm(1, 5);
gmm.Train(inputData, 5);
SetInputParam("input_model", &gmm);
@@ -61,8 +61,8 @@ BOOST_AUTO_TEST_CASE(GmmGenerateSamples)
{
arma::mat inputData(5, 10, arma::fill::randu);
GMM gmm(1, 2);
gmm.Train(inputData, 2);
GMM gmm(1, 5);
gmm.Train(inputData, 5);
SetInputParam("input_model", &gmm);
@@ -76,8 +76,8 @@ BOOST_AUTO_TEST_CASE(GmmGenerateDimensionality)
{
arma::mat inputData(5, 10, arma::fill::randu);
GMM gmm(1, 2);
gmm.Train(inputData, 2);
GMM gmm(1, 5);
gmm.Train(inputData, 5);
SetInputParam("input_model", &gmm);
SetInputParam("samples", (int) 10);
src/mlpack/tests/main_tests/gmm_probability_test.cpp
+2 -2
View File
@@ -54,8 +54,8 @@ BOOST_AUTO_TEST_CASE(GmmProbabilityDimensionality)
{
arma::mat inputData(5, 10, arma::fill::randu);
GMM gmm(1, 2);
gmm.Train(std::move(inputData), 2);
GMM gmm(1, 5);
gmm.Train(std::move(inputData), 5);
arma::mat inputPoints(1, 8, arma::fill::randu);
src/mlpack/tests/main_tests/gmm_train_test.cpp
+41 -33
View File
@@ -47,6 +47,7 @@ void ResetGmmTrainSetting()
CLI::RestoreSettings(testName);
}
BOOST_FIXTURE_TEST_SUITE(GmmTrainMainTest, GmmTrainTestFixture);
// To check if the gaussian is positive or not.
@@ -175,17 +176,18 @@ BOOST_AUTO_TEST_CASE(GmmTrainNoisetest)
SetInputParam("gaussians", (int) 2);
SetInputParam("noise", (double) 0.0);
mlpack::math::FixedRandomSeed();
mlpackMain();
GMM* gmm = CLI::GetParam<GMM*>("output_model");
CLI::GetSingleton().Parameters()["input"].wasPassed = false;
CLI::GetSingleton().Parameters()["gaussians"].wasPassed = false;
CLI::GetSingleton().Parameters()["noise"].wasPassed = false;
ResetGmmTrainSetting();
SetInputParam("input", std::move(inputData));
SetInputParam("gaussians", (int) 2);
SetInputParam("noise", (double) 1.5);
SetInputParam("noise", (double) 100.0);
mlpack::math::FixedRandomSeed();
mlpackMain();
GMM* gmm1 = CLI::GetParam<GMM*>("output_model");
@@ -193,8 +195,10 @@ BOOST_AUTO_TEST_CASE(GmmTrainNoisetest)
arma::uvec sortedIndices = sort_index(gmm->Weights());
for (size_t k = 0; k < sortedIndices.n_elem; k++)
CheckMatricesNotEqual(gmm->Component(sortedIndices[k]).Covariance(),
gmm1->Component(sortedIndices[k]).Covariance());
BOOST_REQUIRE(arma::norm(gmm->Component(sortedIndices[k]).Mean() -
gmm1->Component(sortedIndices[k]).Mean()) > 1e-50 ||
arma::norm(gmm->Component(sortedIndices[k]).Covariance() -
gmm1->Component(sortedIndices[k]).Covariance()) > 1e-50);
}
// Ensure that Percentage affects the final result when refined_start is true.
@@ -205,22 +209,23 @@ BOOST_AUTO_TEST_CASE(GmmTrainPercentageTest)
SetInputParam("input", inputData);
SetInputParam("gaussians", (int) 2);
SetInputParam("refined_start", true);
SetInputParam("percentage", (double) 0.22);
SetInputParam("percentage", (double) 0.01);
SetInputParam("samplings", (int) 200);
mlpack::math::FixedRandomSeed();
mlpackMain();
GMM* gmm = CLI::GetParam<GMM*>("output_model");
CLI::GetSingleton().Parameters()["input"].wasPassed = false;
CLI::GetSingleton().Parameters()["gaussians"].wasPassed = false;
CLI::GetSingleton().Parameters()["refined_start"].wasPassed = false;
CLI::GetSingleton().Parameters()["percentage"].wasPassed = false;
ResetGmmTrainSetting();
SetInputParam("input", std::move(inputData));
SetInputParam("gaussians", (int) 2);
SetInputParam("refined_start", true);
SetInputParam("percentage", (double) 0.82);
SetInputParam("percentage", (double) 0.99);
SetInputParam("samplings", (int) 200);
mlpack::math::FixedRandomSeed();
mlpackMain();
GMM* gmm1 = CLI::GetParam<GMM*>("output_model");
@@ -228,8 +233,10 @@ BOOST_AUTO_TEST_CASE(GmmTrainPercentageTest)
arma::uvec sortedIndices = sort_index(gmm->Weights());
for (size_t k = 0; k < sortedIndices.n_elem; k++)
CheckMatricesNotEqual(gmm->Component(sortedIndices[k]).Covariance(),
gmm1->Component(sortedIndices[k]).Covariance());
BOOST_REQUIRE(arma::norm(gmm->Component(sortedIndices[k]).Mean() -
gmm1->Component(sortedIndices[k]).Mean()) > 1e-50 ||
arma::norm(gmm->Component(sortedIndices[k]).Covariance() -
gmm1->Component(sortedIndices[k]).Covariance()) > 1e-50);
}
// Ensure that Sampling affects the final result when refined_start is true.
@@ -240,25 +247,23 @@ BOOST_AUTO_TEST_CASE(GmmTrainSamplingsTest)
SetInputParam("input", inputData);
SetInputParam("gaussians", (int) 2);
SetInputParam("refined_start", true);
SetInputParam("percentage", (double) 0.5);
SetInputParam("samplings", (int) 100);
SetInputParam("percentage", (double) 0.950);
SetInputParam("samplings", (int) 10);
mlpack::math::FixedRandomSeed();
mlpackMain();
GMM* gmm = CLI::GetParam<GMM*>("output_model");
CLI::GetSingleton().Parameters()["input"].wasPassed = false;
CLI::GetSingleton().Parameters()["gaussians"].wasPassed = false;
CLI::GetSingleton().Parameters()["refined_start"].wasPassed = false;
CLI::GetSingleton().Parameters()["percentage"].wasPassed = false;
CLI::GetSingleton().Parameters()["samplings"].wasPassed = false;
ResetGmmTrainSetting();
SetInputParam("input", std::move(inputData));
SetInputParam("gaussians", (int) 2);
SetInputParam("refined_start", true);
SetInputParam("percentage", (double) 0.5);
SetInputParam("samplings", (int) 500);
SetInputParam("percentage", (double) 0.950);
SetInputParam("samplings", (int) 1000);
mlpack::math::FixedRandomSeed();
mlpackMain();
GMM* gmm1 = CLI::GetParam<GMM*>("output_model");
@@ -266,9 +271,10 @@ BOOST_AUTO_TEST_CASE(GmmTrainSamplingsTest)
arma::uvec sortedIndices = sort_index(gmm->Weights());
for (size_t k = 0; k < sortedIndices.n_elem; k++)
CheckMatricesNotEqual(gmm->Component(sortedIndices[k]).Covariance(),
gmm1->Component(sortedIndices[k]).Covariance());
BOOST_REQUIRE(arma::norm(gmm->Component(sortedIndices[k]).Mean() -
gmm1->Component(sortedIndices[k]).Mean()) > 1e-50 ||
arma::norm(gmm->Component(sortedIndices[k]).Covariance() -
gmm1->Component(sortedIndices[k]).Covariance()) > 1e-50);
}
// Ensure that tolerance affects the final result.
@@ -280,20 +286,20 @@ BOOST_AUTO_TEST_CASE(GmmTrainToleranceTest)
SetInputParam("input", inputData);
SetInputParam("gaussians", (int) 2);
SetInputParam("tolerance", (double) 1e-10);
SetInputParam("tolerance", (double) 1e-8);
mlpack::math::FixedRandomSeed();
mlpackMain();
GMM* gmm = CLI::GetParam<GMM*>("output_model");
CLI::GetSingleton().Parameters()["input"].wasPassed = false;
CLI::GetSingleton().Parameters()["gaussians"].wasPassed = false;
CLI::GetSingleton().Parameters()["tolerance"].wasPassed = false;
ResetGmmTrainSetting();
SetInputParam("input", std::move(inputData));
SetInputParam("gaussians", (int) 2);
SetInputParam("tolerance", (double) 1e-30);
SetInputParam("tolerance", (double) 10);
mlpack::math::FixedRandomSeed();
mlpackMain();
GMM* gmm1 = CLI::GetParam<GMM*>("output_model");
@@ -301,8 +307,10 @@ BOOST_AUTO_TEST_CASE(GmmTrainToleranceTest)
arma::uvec sortedIndices = sort_index(gmm->Weights());
for (size_t k = 0; k < sortedIndices.n_elem; k++)
CheckMatricesNotEqual(gmm->Component(sortedIndices[k]).Covariance(),
gmm1->Component(sortedIndices[k]).Covariance());
BOOST_REQUIRE(arma::norm(gmm->Component(sortedIndices[k]).Mean() -
gmm1->Component(sortedIndices[k]).Mean()) > 1e-50 ||
arma::norm(gmm->Component(sortedIndices[k]).Covariance() -
gmm1->Component(sortedIndices[k]).Covariance()) > 1e-50);
}
// Ensure that saved model can be used again.