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A fast and easy to use dense and sparse matrix linear algebra library written in Java.
/*
* 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.fixed;
import org.ejml.data.FMatrix2;
import org.ejml.data.FMatrix2x2;
import javax.annotation.Generated;
/**
* Matrix norm related operations for fixed sized matrices of size 2.
* DO NOT MODIFY. Automatically generated code created by GenerateNormOps_DDF
*
* @author Peter Abeles
*/
@Generated("org.ejml.dense.fixed.GenerateNormOps_DDF")
public class NormOps_FDF2 {
public static void normalizeF( FMatrix2x2 M ) {
float val = normF(M);
CommonOps_FDF2.divide(M,val);
}
public static void normalizeF( FMatrix2 M ) {
float val = normF(M);
CommonOps_FDF2.divide(M,val);
}
public static float fastNormF( FMatrix2x2 M ) {
float sum = 0;
sum += M.a11*M.a11 + M.a12*M.a12;
sum += M.a21*M.a21 + M.a22*M.a22;
return (float)Math.sqrt(sum);
}
public static float fastNormF( FMatrix2 M ) {
float sum = M.a1*M.a1 + M.a2*M.a2;
return (float)Math.sqrt(sum);
}
public static float normF( FMatrix2x2 M ) {
float scale = CommonOps_FDF2.elementMaxAbs(M);
if( scale == 0.0f )
return 0.0f;
float a11 = M.a11/scale, a12 = M.a12/scale;
float a21 = M.a21/scale, a22 = M.a22/scale;
float sum = 0;
sum += a11*a11 + a12*a12;
sum += a21*a21 + a22*a22;
return scale * (float)Math.sqrt(sum);
}
public static float normF( FMatrix2 M ) {
float scale = CommonOps_FDF2.elementMaxAbs(M);
if( scale == 0.0f )
return 0.0f;
float a1 = M.a1/scale, a2 = M.a2/scale;
float sum = a1*a1 + a2*a2;
return scale * (float)Math.sqrt(sum);
}
}