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/*!
@authors Andrei Novikov (pyclustering@yandex.ru)
@date 2014-2020
@copyright BSD-3-Clause
*/
#pragma once
#include <pyclustering/interface/pyclustering_package.hpp>
#include <pyclustering/cluster/silhouette_ksearch.hpp>
#include <pyclustering/definitions.hpp>
/**
*
* @brief Silhouette K-Search result is returned using pyclustering_package that consist sub-packages and this enumerator provides
* named indexes for sub-packages.
*
*/
enum silhouette_ksearch_package_indexer {
SILHOUETTE_KSEARCH_PACKAGE_AMOUNT = 0,
SILHOUETTE_KSEARCH_PACKAGE_SCORE,
SILHOUETTE_KSEARCH_PACKAGE_SCORES,
SILHOUETTE_KSEARCH_PACKAGE_SIZE
};
/**
*
* @brief Silhouette K-Search cluster allocators.
*
*/
enum silhouette_ksearch_type {
KMEANS = 0,
KMEDIANS,
KMEDOIDS
};
/**
*
* @brief Returns cluster allocator for Silhouette K-Search algorithm.
*
* @param[in] p_algorithm: cluster allocator type that should be created.
*
* @return Returns cluster allocator.
*
*/
pyclustering::clst::silhouette_ksearch_allocator::ptr get_silhouette_ksearch_allocator(
const silhouette_ksearch_type p_algorithm);
/**
*
* @brief Performs data analysis using Silhouette method using center initializer that is specified by template.
* @details Caller should destroy returned result by 'free_pyclustering_package'.
*
* @param[in] p_sample: input data for clustering.
* @param[in] p_clusters: clusters that have been allocated for that data.
* @param[in] p_metric: pointer to distance metric 'distance_metric' that is used for distance calculation between two points.
* @param[in] p_data_type: defines data type that is used for clustering process ('0' - points, '1' - distance matrix).
*
* @return Returns Silhouette's analysis results as a pyclustering package [ scores ].
*
*/
extern "C" DECLARATION pyclustering_package * silhouette_algorithm(
const pyclustering_package * const p_sample,
const pyclustering_package * const p_clusters,
const void * const p_metric,
const std::size_t p_data_type);
/**
*
* @brief Performs data analysis using Silhouette K-Search algorithm using center initializer that is specified by template.
* @details Caller should destroy returned result by 'free_pyclustering_package'.
*
* @param[in] p_sample: input data for clustering.
* @param[in] p_kmin: minimum amount of clusters that should be considered.
* @param[in] p_kmax: maximum amount of clusters that should be considered.
* @param[in] p_metric: cluster allocator that is used by Silhouette K-Search method.
* @param[in] p_random_state: seed for random state (by default is `RANDOM_STATE_CURRENT_TIME`, current system time is used).
*
* @return Returns Silhouette K-Search results as a pyclustering package [ [ amount of clusters], [ optimal score ], [ score for each K ] ].
*
*/
extern "C" DECLARATION pyclustering_package * silhouette_ksearch_algorithm(
const pyclustering_package * const p_sample,
const std::size_t p_kmin,
const std::size_t p_kmax,
const std::size_t p_algorithm,
const long long p_random_state);
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