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/*!
@authors Andrei Novikov (pyclustering@yandex.ru)
@date 2014-2020
@copyright BSD-3-Clause
*/
#include <gtest/gtest.h>
#include <pyclustering/interface/silhouette_interface.h>
#include <pyclustering/interface/pyclustering_package.hpp>
#include <pyclustering/utils/metric.hpp>
#include "samples.hpp"
#include "answer.hpp"
#include "answer_reader.hpp"
#include "utenv_utils.hpp"
#include <memory>
using namespace pyclustering;
TEST(utest_interface_silhouette, silhouette) {
dataset_ptr data = simple_sample_factory::create_sample(SAMPLE_SIMPLE::SAMPLE_SIMPLE_01);
answer ans = answer_reader::read(SAMPLE_SIMPLE::SAMPLE_SIMPLE_01);
dataset matrix;
distance_matrix(*data, distance_metric_factory<point>::euclidean_square(), matrix);
std::shared_ptr<pyclustering_package> data_package = pack(*data);
std::shared_ptr<pyclustering_package> matrix_package = pack(matrix);
std::shared_ptr<pyclustering_package> cluster_package = pack(ans.clusters());
pyclustering_package * result_points = silhouette_algorithm(data_package.get(), cluster_package.get(), nullptr, 0);
pyclustering_package * result_matrix = silhouette_algorithm(matrix_package.get(), cluster_package.get(), nullptr, 1);
ASSERT_NE(nullptr, result_points);
ASSERT_NE(nullptr, result_matrix);
ASSERT_EQ(result_points->size, result_matrix->size);
ASSERT_EQ(result_points->type, result_matrix->type);
delete result_matrix;
delete result_points;
}
TEST(utest_interface_silhouette, silhouette_ksearch) {
dataset_ptr data = simple_sample_factory::create_sample(SAMPLE_SIMPLE::SAMPLE_SIMPLE_01);
std::shared_ptr<pyclustering_package> sample = pack(*data);
pyclustering_package * result = silhouette_ksearch_algorithm(sample.get(), 2, 5, 0, -1);
ASSERT_EQ((std::size_t) SILHOUETTE_KSEARCH_PACKAGE_SIZE, result->size);
delete result;
}
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