/*
 * Copyright (c) 2009-2020, Peter Abeles. All Rights Reserved.
 *
 * This file is part of Efficient Java Matrix Library (EJML).
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.ejml.interfaces.decomposition;

import org.ejml.data.IGrowArray;
import org.ejml.data.Matrix;
import org.jetbrains.annotations.Nullable;


/**
 * LU Decomposition refactors the original matrix such that:<br>
 * <center> P<sup>T</sup>*L*U = A</center>
 * where P is a pivot matrix, L is a lower triangular matrix, U is an upper triangular matrix and A is
 * the original matrix.
 *
 * <p>
 * LU Decomposition is useful since once the decomposition has been performed linear
 * equations can be quickly solved and the original matrix A inverted.  Different algorithms
 * can be selected to perform the decomposition, all will have the same end result.
 * </p>
 * <p>
 * To use this class first specify the size of the matrix that will be decomposed by it in
 * the constructor.  Only square m by m matrices can be decomposed.  Then to decompose a matrix
 * call {@link #decompose}.  If it encounters any problems an exception will be thrown.  After
 * that all the other functions will be available for solving and inverting matrices.
 * </p>
 *
 * @author Peter Abeles
 */
// TODO add pivot vectors
    // TODO specify is row or column pivots
public interface LUDecomposition <T extends Matrix>
        extends DecompositionInterface<T> {

    /**
     * <p>
     * Returns the L matrix from the decomposition.  Should only
     * be called after {@link #decompose(org.ejml.data.Matrix)} has
     * been called.
     * </p>
     *
     * <p>
     * If parameter 'lower' is not null, then that matrix is used to store the L matrix.  Otherwise
     * a new matrix is created.
     * </p>
     *
     * @param lower Storage for T matrix. If null then a new matrix is returned.  Modified.
     * @return The L matrix.
     */
    T getLower( @Nullable T lower );

    /**
     * <p>
     * Returns the U matrix from the decomposition.  Should only
     * be called after {@link #decompose(org.ejml.data.Matrix)}  has
     * been called.
     * </p>
     *
     * <p>
     * If parameter 'upper' is not null, then that matrix is used to store the U matrix.  Otherwise
     * a new matrix is created.
     * </p>
     *
     * @param upper Storage for U matrix. If null then a new matrix is returned. Modified.
     * @return The U matrix.
     */
    T getUpper( @Nullable T upper );

    /**
     * <p>
     * For numerical stability there are often row interchanges.  This computes
     * a pivot matrix that will undo those changes.
     * </p>
     *
     * @param pivot Storage for the pivot matrix. If null then a new matrix is returned. Modified.
     * @return The pivot matrix.
     */
    T getRowPivot( @Nullable T pivot );

    /**
     * Returns the row pivot vector
     *
     * @param pivot (Optional) Storage for pivot vector
     * @return The pivot vector
     */
    int[] getRowPivotV( @Nullable IGrowArray pivot );

    /**
     * Returns true if the decomposition detected a singular matrix.  This check
     * will not work 100% of the time due to machine precision issues.
     *
     * @return True if the matrix is singular and false if it is not.
     */
    // TODO Remove?  If singular decomposition will fail.
    boolean isSingular();
}
