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

org.ejml.dense.block.decomposition.hessenberg.TridiagonalHelper_DDRB Maven / Gradle / Ivy

/*
 * 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.dense.block.decomposition.hessenberg;

import org.ejml.data.DSubmatrixD1;
import org.ejml.dense.block.VectorOps_DDRB;
import org.ejml.dense.block.decomposition.qr.BlockHouseHolder_DDRB;
import org.ejml.dense.row.CommonOps_DDRM;

import static org.ejml.dense.block.decomposition.qr.BlockHouseHolder_DDRB.computeHouseHolderRow;


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

    /**
     * 

* Performs a tridiagonal decomposition on the upper row only. *

* *

* For each row 'a' in 'A': * Compute 'u' the householder reflector. * y(:) = A*u * v(i) = y - (1/2)*(y^T*u)*u * a(i+1) = a(i) - u*γ*v^T - v*u^t *

* * @param blockLength Size of a block * @param A is the row block being decomposed. Modified. * @param gammas Householder gammas. * @param V Where computed 'v' are stored in a row block. Modified. */ public static void tridiagUpperRow( final int blockLength , final DSubmatrixD1 A , final double gammas[] , final DSubmatrixD1 V ) { int blockHeight = Math.min(blockLength,A.row1-A.row0); if( blockHeight <= 1 ) return; int width = A.col1-A.col0; int num = Math.min(width-1,blockHeight); int applyIndex = Math.min(width,blockHeight); // step through rows in the block for( int i = 0; i < num; i++ ) { // compute the new reflector and save it in a row in 'A' computeHouseHolderRow(blockLength,A,gammas,i); double gamma = gammas[A.row0+i]; // compute y computeY(blockLength,A,V,i,gamma); // compute v from y computeRowOfV(blockLength,A,V,i,gamma); // Apply the reflectors to the next row in 'A' only if( i+1 < applyIndex ) { applyReflectorsToRow( blockLength , A , V , i+1 ); } } } /** *

* Computes W from the householder reflectors stored in the columns of the row block * submatrix Y. *

* *

* Y = v(1)
* W = -β1v(1)
* for j=2:r
*   z = -β(I +WYT)v(j)
*   W = [W z]
*   Y = [Y v(j)]
* end
*
* where v(.) are the house holder vectors, and r is the block length. Note that * Y already contains the householder vectors so it does not need to be modified. *

* *

* Y and W are assumed to have the same number of rows and columns. *

*/ public static void computeW_row(final int blockLength , final DSubmatrixD1 Y , final DSubmatrixD1 W , final double beta[] , int betaIndex ) { final int heightY = Y.row1-Y.row0; CommonOps_DDRM.fill(W.original, 0); // W = -beta*v(1) BlockHouseHolder_DDRB.scale_row(blockLength,Y,W,0,1,-beta[betaIndex++]); final int min = Math.min(heightY,W.col1-W.col0); // set up rest of the rows for( int i = 1; i < min; i++ ) { // w=-beta*(I + W*Y^T)*u double b = -beta[betaIndex++]; // w = w -beta*W*(Y^T*u) for( int j = 0; j < i; j++ ) { double yv = BlockHouseHolder_DDRB.innerProdRow(blockLength,Y,i,Y,j,1); VectorOps_DDRB.add_row(blockLength,W,i,1,W,j,b*yv,W,i,1,Y.col1-Y.col0); } //w=w -beta*u + stuff above BlockHouseHolder_DDRB.add_row(blockLength,Y,i,b,W,i,1,W,i,1,Y.col1-Y.col0); } } /** *

* Given an already computed tridiagonal decomposition, compute the V row block vector.
*
* y(:) = A*u
* v(i) = y - (1/2)*γ*(y^T*u)*u *

*/ public static void computeV_blockVector( final int blockLength , final DSubmatrixD1 A , final double gammas[] , final DSubmatrixD1 V ) { int blockHeight = Math.min(blockLength,A.row1-A.row0); if( blockHeight <= 1 ) return; int width = A.col1-A.col0; int num = Math.min(width-1,blockHeight); for( int i = 0; i < num; i++ ) { double gamma = gammas[A.row0+i]; // compute y computeY(blockLength,A,V,i,gamma); // compute v from y computeRowOfV(blockLength,A,V,i,gamma); } } /** *

* Applies the reflectors that have been computed previously to the specified row. *
* A = A + u*v^T + v*u^T only along the specified row in A. *

* * @param blockLength * @param A Contains the reflectors and the row being updated. * @param V Contains previously computed 'v' vectors. * @param row The row of 'A' that is to be updated. */ public static void applyReflectorsToRow( final int blockLength , final DSubmatrixD1 A , final DSubmatrixD1 V , int row ) { int height = Math.min(blockLength, A.row1 - A.row0); double dataA[] = A.original.data; double dataV[] = V.original.data; int indexU,indexV; // for each previously computed reflector for( int i = 0; i < row; i++ ) { int width = Math.min(blockLength,A.col1 - A.col0); indexU = A.original.numCols*A.row0 + height*A.col0 + i*width + row; indexV = V.original.numCols*V.row0 + height*V.col0 + i*width + row; double u_row = (i+1 == row) ? 1.0 : dataA[ indexU ]; double v_row = dataV[ indexV ]; // take in account the leading one double before = A.get(i,i+1); A.set(i,i+1,1); // grab only the relevant row from A = A + u*v^T + v*u^T VectorOps_DDRB.add_row(blockLength,A,row,1,V,i,u_row,A,row,row,A.col1-A.col0); VectorOps_DDRB.add_row(blockLength,A,row,1,A,i,v_row,A,row,row,A.col1-A.col0); A.set(i,i+1,before); } } /** *

* Computes the 'y' vector and stores the result in 'v'
*
* y = -γ(A + U*V^T + V*U^T)u *

* * @param blockLength * @param A Contains the reflectors and the row being updated. * @param V Contains previously computed 'v' vectors. * @param row The row of 'A' that is to be updated. */ public static void computeY( final int blockLength , final DSubmatrixD1 A , final DSubmatrixD1 V , int row , double gamma ) { // Elements in 'y' before 'row' are known to be zero and the element at 'row' // is not used. Thus only elements after row and after are computed. // y = A*u multA_u(blockLength,A,V,row); for( int i = 0; i < row; i++ ) { // y = y + u_i*v_i^t*u + v_i*u_i^t*u // v_i^t*u double dot_v_u = BlockHouseHolder_DDRB.innerProdRow(blockLength,A,row,V,i,1); // u_i^t*u double dot_u_u = BlockHouseHolder_DDRB.innerProdRow(blockLength,A,row,A,i,1); // y = y + u_i*(v_i^t*u) // the ones in these 'u' are skipped over since the next submatrix of A // is only updated VectorOps_DDRB.add_row(blockLength,V,row,1,A,i,dot_v_u,V,row,row+1,A.col1-A.col0); // y = y + v_i*(u_i^t*u) // the 1 in U is taken account above VectorOps_DDRB.add_row(blockLength,V,row,1,V,i,dot_u_u,V,row,row+1,A.col1-A.col0); } // y = -gamma*y VectorOps_DDRB.scale_row(blockLength,V,row,-gamma,V,row,row+1,V.col1-V.col0); } /** *

* Multiples the appropriate submatrix of A by the specified reflector and stores * the result ('y') in V.
*
* y = A*u
*

* * @param blockLength * @param A Contains the 'A' matrix and 'u' vector. * @param V Where resulting 'y' row vectors are stored. * @param row row in matrix 'A' that 'u' vector and the row in 'V' that 'y' is stored in. */ public static void multA_u( final int blockLength , final DSubmatrixD1 A , final DSubmatrixD1 V , int row ) { int heightMatA = A.row1-A.row0; for( int i = row+1; i < heightMatA; i++ ) { double val = innerProdRowSymm(blockLength,A,row,A,i,1); V.set(row,i,val); } } public static double innerProdRowSymm(int blockLength, DSubmatrixD1 A, int rowA, DSubmatrixD1 B, int rowB, int zeroOffset ) { int offset = rowA + zeroOffset; if( offset + B.col0 >= B.col1 ) return 0; if( offset < rowB ) { // take in account the one in 'A' double total = B.get(offset,rowB); total += VectorOps_DDRB.dot_row_col(blockLength,A,rowA,B,rowB,offset+1,rowB); total += VectorOps_DDRB.dot_row(blockLength,A,rowA,B,rowB,rowB,A.col1-A.col0); return total; } else { // take in account the one in 'A' double total = B.get(rowB,offset); total += VectorOps_DDRB.dot_row(blockLength,A,rowA,B,rowB,offset+1,A.col1-A.col0); return total; } } /** *

* Final computation for a single row of 'v':
*
* v = y -(1/2)γ(y^T*u)*u *

* * @param blockLength * @param A * @param V * @param row * @param gamma */ public static void computeRowOfV( final int blockLength , final DSubmatrixD1 A , final DSubmatrixD1 V , int row , double gamma ) { // val=(y^T*u) double val = BlockHouseHolder_DDRB.innerProdRow(blockLength,A,row,V,row,1); // take in account the one double before = A.get(row,row+1); A.set(row,row+1,1); // v = y - (1/2)gamma*val * u VectorOps_DDRB.add_row(blockLength,V,row,1,A,row,-0.5*gamma*val,V,row,row+1,A.col1-A.col0); A.set(row,row+1,before); } }




© 2015 - 2024 Weber Informatics LLC | Privacy Policy