All Downloads are FREE. Search and download functionalities are using the official Maven repository.

org.ejml.data.FSubmatrixD1 Maven / Gradle / Ivy

Go to download

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

There is a newer version: 0.43.1
Show newest version
/*
 * 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.data;

import org.ejml.ops.MatrixIO;

/**
 * 

* Describes a rectangular submatrix inside of a {@link FMatrixD1}. *

* *

* Rows are row0 ≤ i < row1 and Columns are col0 ≤ j < col1 *

* * @author Peter Abeles */ public class FSubmatrixD1 { public FMatrixD1 original; // bounding rows and columns public int row0,col0; public int row1,col1; public FSubmatrixD1() { } public FSubmatrixD1(FMatrixD1 original) { set(original); } public FSubmatrixD1(FMatrixD1 original, int row0, int row1, int col0, int col1) { set(original,row0,row1,col0,col1); } public void set(FMatrixD1 original, int row0, int row1, int col0, int col1) { this.original = original; this.row0 = row0; this.col0 = col0; this.row1 = row1; this.col1 = col1; } public void set(FMatrixD1 original) { this.original = original; row1 = original.numRows; col1 = original.numCols; } public int getRows() { return row1 - row0; } public int getCols() { return col1 - col0; } public float get(int row, int col ) { return original.get(row+row0,col+col0); } public void set(int row, int col, float value) { original.set(row+row0,col+col0,value); } public FMatrixRMaj extract() { FMatrixRMaj ret = new FMatrixRMaj(row1-row0,col1-col0); for( int i = 0; i < ret.numRows; i++ ) { for( int j = 0; j < ret.numCols; j++ ) { ret.set(i,j,get(i,j)); } } return ret; } public void print() { MatrixIO.print(System.out,original,"%6.3ff",row0,row1,col0,col1); } }




© 2015 - 2024 Weber Informatics LLC | Privacy Policy