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/*
 * Copyright (c) 2018 Shapelets.io
 *
 * This Source Code Form is subject to the terms of the Mozilla Public
 * License, v. 2.0. If a copy of the MPL was not distributed with this
 * file, You can obtain one at http://mozilla.org/MPL/2.0/.
 *
 */

package io.shapelets.khiva;

/**
 * Khiva Regularization class containing different regularization methods.
 */
public class Regularization extends Library {

    private native static long[] groupBy(long ref, int aggregationFunction, int nColumnsKey, int nColumnsValue);

    /**
     * Group by operation in the input array using nColumnsKey columns as group keys and nColumnsValue columns as
     * values. The data is expected to be sorted. The aggregation function determines the operation to aggregate the
     * values.
     *
     * @param arr                 Expects an input array whose dimension zero is the length of the time
     *                            series (all the same) and dimension one indicates the number of time series.
     * @param aggregationFunction Function to be used in the aggregation. It receives an integer which indicates the
     *                            function to be applied:
     *                            {
     *                            0 : mean,
     *                            1 : median
     *                            2 : min,
     *                            3 : max,
     *                            4 : stdev,
     *                            5 : var,
     *                            default : mean
     *                            }
     * @return Array with the values of the group keys aggregated using the aggregationFunction.
     */
    public static Array groupBy(Array arr, int aggregationFunction) {
        return groupBy(arr, aggregationFunction, 1, 1);
    }

    /**
     * Group by operation in the input array using nColumnsKey columns as group keys and nColumnsValue columns as
     * values. The data is expected to be sorted. The aggregation function determines the operation to aggregate the
     * values.
     *
     * @param arr                 Expects an input array whose dimension zero is the length of the time
     *                            series (all the same) and dimension one indicates the number of time series.
     * @param aggregationFunction Function to be used in the aggregation. It receives an integer which indicates the
     *                            function to be applied:
     *                            {
     *                            0 : mean,
     *                            1 : median
     *                            2 : min,
     *                            3 : max,
     *                            4 : stdev,
     *                            5 : var,
     *                            default : mean
     *                            }
     * @param nColumnsKey         Number of columns conforming the key.
     * @return Array with the values of the group keys aggregated using the aggregationFunction.
     */
    public static Array groupBy(Array arr, int aggregationFunction, int nColumnsKey) {
        return groupBy(arr, aggregationFunction, nColumnsKey, 1);
    }

    /**
     * Group by operation in the input array using nColumnsKey columns as group keys and nColumnsValue columns as
     * values. The data is expected to be sorted. The aggregation function determines the operation to aggregate the
     * values.
     *
     * @param arr                 Expects an input array whose dimension zero is the length of the time
     *                            series (all the same) and dimension one indicates the number of time series.
     * @param aggregationFunction Function to be used in the aggregation. It receives an integer which indicates the
     *                            function to be applied:
     *                            {
     *                            0 : mean,
     *                            1 : median
     *                            2 : min,
     *                            3 : max,
     *                            4 : stdev,
     *                            5 : var,
     *                            default : mean
     *                            }
     * @param nColumnsKey         Number of columns conforming the key.
     * @param nColumnsValue       Number of columns conforming the value (they are expected to be consecutive to the
     *                            column keys).
     * @return Array with the values of the group keys aggregated using the aggregationFunction.
     */
    public static Array groupBy(Array arr, int aggregationFunction, int nColumnsKey, int nColumnsValue) {
        long[] refs = groupBy(arr.getReference(), aggregationFunction, nColumnsKey, nColumnsValue);
        arr.setReference(refs[0]);
        return new Array(refs[1]);
    }
}