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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.row.decomposition;

import javax.annotation.Generated;
/**
 * 

* This contains algorithms for solving systems of equations where T is a * non-singular triangular matrix:
*
* T*x = b
*
* where x and b are vectors, and T is an n by n matrix. T can either be a lower or upper triangular matrix.
*

*

* These functions are designed for use inside of other algorithms. To use them directly * is dangerous since no sanity checks are performed. *

* * @author Peter Abeles */ @Generated("org.ejml.dense.row.decomposition.TriangularSolver_DDRM") public class TriangularSolver_FDRM { /** *

* Inverts a square lower triangular matrix: L = L-1 *

*/ public static void invertLower( float[] L, int m ) { for (int i = 0; i < m; i++) { float L_ii = L[i*m + i]; for (int j = 0; j < i; j++) { float val = 0; for (int k = j; k < i; k++) { val += L[i*m + k]*L[k*m + j]; } L[i*m + j] = -val/L_ii; } L[i*m + i] = 1.0f/L_ii; } } public static void invertLower( float[] L, float[] L_inv, int m ) { for (int i = 0; i < m; i++) { float L_ii = L[i*m + i]; for (int j = 0; j < i; j++) { float val = 0; for (int k = j; k < i; k++) { val -= L[i*m + k]*L_inv[k*m + j]; } L_inv[i*m + j] = val/L_ii; } L_inv[i*m + i] = 1.0f/L_ii; } } /** *

* Solves for non-singular lower triangular matrices using forward substitution. *
* b = L-1b
*
* where b is a vector, L is an n by n matrix.
*

* * @param L An n by n non-singular lower triangular matrix. Not modified. * @param b A vector of length n. Modified. * @param n The size of the matrices. */ public static void solveL( float[] L, float[] b, int n ) { // for( int i = 0; i < n; i++ ) { // float sum = b[i]; // for( int k=0; k * This is a forward substitution solver for non-singular lower triangular matrices. *
* b = (LT)-1b
*
* where b is a vector, L is an n by n matrix.
*

*

* L is a lower triangular matrix, but it comes up with a solution as if it was * an upper triangular matrix that was computed by transposing L. *

* * @param L An n by n non-singular lower triangular matrix. Not modified. * @param b A vector of length n. Modified. * @param n The size of the matrices. */ public static void solveTranL( float[] L, float[] b, int n ) { for (int i = n - 1; i >= 0; i--) { float sum = b[i]; for (int k = i + 1; k < n; k++) { sum -= L[k*n + i]*b[k]; } b[i] = sum/L[i*n + i]; } } /** *

* This is a forward substitution solver for non-singular upper triangular matrices. *
* b = U-1b
*
* where b is a vector, U is an n by n matrix.
*

* * @param U An n by n non-singular upper triangular matrix. Not modified. * @param b A vector of length n. Modified. * @param n The size of the matrices. */ public static void solveU( float[] U, float[] b, int n ) { // for( int i =n-1; i>=0; i-- ) { // float sum = b[i]; // for( int j = i+1; j = 0; i--) { float sum = b[i]; int indexU = i*n + i + 1; for (int j = i + 1; j < n; j++) { sum -= U[indexU++]*b[j]; } b[i] = sum/U[i*n + i]; } } public static void solveU( float[] U, float[] b, int sideLength, int minRow, int maxRow ) { // for( int i =maxRow-1; i>=minRow; i-- ) { // float sum = b[i]; // for( int j = i+1; j = minRow; i--) { float sum = b[i]; int indexU = i*sideLength + i + 1; for (int j = i + 1; j < maxRow; j++) { sum -= U[indexU++]*b[j]; } b[i] = sum/U[i*sideLength + i]; } } /** *

* This is a forward substitution solver for non-singular upper triangular matrices which are * a sub-matrix inside a larger. The columns of 'b' are solved for individually *
* b = U-1b
*
* where b is a matrix, U is an n by n matrix.
*

* * @param U Matrix containing the upper triangle system * @param startU Index of the first element in U * @param strideU stride between rows * @param widthU How wide the square matrix is * @param b Matrix containing the solution to the system. Overwritten with the solution. * @param startB Index of the first element in B * @param strideB stride between rows * @param widthB How wide the matrix is. Length is the same as U's width */ public static void solveU( float[] U, int startU, int strideU, int widthU, float[] b, int startB, int strideB, int widthB ) { for (int colB = 0; colB < widthB; colB++) { for (int i = widthU - 1; i >= 0; i--) { float sum = b[startB + i*strideB + colB]; for (int j = i + 1; j < widthU; j++) { sum -= U[startU + i*strideU + j]*b[startB + j*strideB + colB]; } b[startB + i*strideB + colB] = sum/U[startU + i*strideU + i]; } } // todo comment out the above and optimize it } }




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