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

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/*
 * Copyright (c) 2009-2017, 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;

import org.ejml.data.CMatrixRMaj;

/**
 * @author Peter Abeles
 */
public class NormOps_CDRM {
    /**
     * 

* Computes the Frobenius matrix norm:
*
* normF = Sqrt{ ∑i=1:mj=1:n { aij2} } *

*

* This is equivalent to the element wise p=2 norm. *

* * @param a The matrix whose norm is computed. Not modified. * @return The norm's value. */ public static float normF( CMatrixRMaj a ) { float total = 0; float scale = CommonOps_CDRM.elementMaxAbs(a); if( scale == 0.0f ) return 0.0f; final int size = a.getDataLength(); for( int i = 0; i < size; i += 2 ) { float real = a.data[i]/scale; float imag = a.data[i+1]/scale; total += real*real + imag*imag; } return scale* (float)Math.sqrt(total); } }




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