org.ejml.dense.row.linsol.LinearSolverUnrolled_FDRM Maven / Gradle / Ivy

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A fast and easy to use dense and sparse matrix linear algebra library written in Java.

There is a newer version: 0.43.1

/*
 * Copyright (c) 2022, 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.dense.row.linsol;

import javax.annotation.Generated;
import org.ejml.data.FMatrixRMaj;
import org.ejml.dense.row.misc.UnrolledInverseFromMinor_FDRM;
import org.ejml.interfaces.decomposition.DecompositionInterface;
import org.ejml.interfaces.linsol.LinearSolverDense;
import org.jetbrains.annotations.Nullable;

/**
 * Solver which uses an unrolled inverse to compute the inverse. This can only invert matrices and not solve.
 * This is faster than LU inverse but only supports small matrices..
 *
 * @author Peter Abeles
 */
@Generated("org.ejml.dense.row.linsol.LinearSolverUnrolled_DDRM")
public class LinearSolverUnrolled_FDRM implements LinearSolverDense {
    @Nullable FMatrixRMaj A;

    @Override
    public boolean setA( FMatrixRMaj A ) {
        if (A.numRows != A.numCols)
            return false;

        this.A = A;
        return A.numRows <= UnrolledInverseFromMinor_FDRM.MAX;
    }

    @Override
    public /**/double quality() {
        throw new IllegalArgumentException("Not supported by this solver.");
    }

    @Override
    public void solve( FMatrixRMaj B, FMatrixRMaj X ) {
        throw new RuntimeException("Not supported");
    }

    @Override
    public void invert( FMatrixRMaj A_inv ) {
        if (A == null)
            throw new RuntimeException("Must call setA() first");
        if (A.numRows == 1)
            A_inv.set(0, 1.0f/A.get(0));
        UnrolledInverseFromMinor_FDRM.inv(A, A_inv);
    }

    @Override
    public boolean modifiesA() {
        return false;
    }

    @Override
    public boolean modifiesB() {
        return false;
    }

    @Override
    public  D getDecomposition() {
        throw new RuntimeException("Not supported");
    }
}