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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) 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); } }




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