/*
 * Copyright (c) 2009-2014, 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.ops;

import org.ejml.data.CDenseMatrix64F;

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

     * Computes the Frobenius matrix norm:

     * 

     * normF = Sqrt{  ∑i=1:m ∑j=1:n { aij2}   }
     * 
     * 

     * This is equivalent to the element wise p=2 norm.  See {@link #fastNormF} for another implementation
     * that is faster, but more prone to underflow/overflow errors.
     * 
     *
     * @param a The matrix whose norm is computed.  Not modified.
     * @return The norm's value.
     */
    public static double normF( CDenseMatrix64F a ) {
        double total = 0;

        double scale = CCommonOps.elementMaxAbs(a);

        if( scale == 0.0 )
            return 0.0;

        final int size = a.getDataLength();

        for( int i = 0; i < size; i += 2 ) {
            double real = a.data[i]/scale;
            double imag = a.data[i+1]/scale;

            total += real*real + imag*imag;
        }

        return scale*Math.sqrt(total);
    }
}