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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) 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.row;

import org.ejml.data.Complex_F64;
import org.ejml.data.ZMatrixRMaj;
import org.ejml.dense.row.mult.VectorVectorMult_ZDRM;
import org.ejml.interfaces.linsol.LinearSolverDense;

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

    /**
     * 

* Creates a reflector from the provided vector.
*
* Q = I - γ u uT
* γ = 2/||u||2 *

* * @param u A vector. Not modified. * @return An orthogonal reflector. */ public static ZMatrixRMaj createReflector(ZMatrixRMaj u ) { if( !MatrixFeatures_ZDRM.isVector(u)) throw new IllegalArgumentException("u must be a vector"); double norm = NormOps_ZDRM.normF(u); double gamma = -2.0/(norm*norm); ZMatrixRMaj Q = CommonOps_ZDRM.identity(u.getNumElements()); CommonOps_ZDRM.multAddTransB(gamma,0,u,u,Q); return Q; } /** *

* Creates a reflector from the provided vector and gamma.
*
* Q = I - γ u uH
*

* * @param u A vector. Not modified. * @param gamma To produce a reflector gamma needs to be equal to 2/||u||. * @return An orthogonal reflector. */ public static ZMatrixRMaj createReflector(ZMatrixRMaj u , double gamma) { if( !MatrixFeatures_ZDRM.isVector(u)) throw new IllegalArgumentException("u must be a vector"); ZMatrixRMaj Q = CommonOps_ZDRM.identity(u.getNumElements()); CommonOps_ZDRM.multAddTransB(-gamma,0,u,u,Q); return Q; } /** *

* Creates a pivot matrix that exchanges the rows in a matrix: *
* A' = P*A
*

*

* For example, if element 0 in 'pivots' is 2 then the first row in A' will be the 3rd row in A. *

* * @param ret If null then a new matrix is declared otherwise the results are written to it. Is modified. * @param pivots Specifies the new order of rows in a matrix. * @param numPivots How many elements in pivots are being used. * @param transposed If the transpose of the matrix is returned. * @return A pivot matrix. */ public static ZMatrixRMaj pivotMatrix(ZMatrixRMaj ret, int pivots[], int numPivots, boolean transposed ) { if( ret == null ) { ret = new ZMatrixRMaj(numPivots, numPivots); } else { if( ret.numCols != numPivots || ret.numRows != numPivots ) throw new IllegalArgumentException("Unexpected matrix dimension"); CommonOps_ZDRM.fill(ret, 0,0); } if( transposed ) { for( int i = 0; i < numPivots; i++ ) { ret.set(pivots[i],i,1,0); } } else { for( int i = 0; i < numPivots; i++ ) { ret.set(i,pivots[i],1,0); } } return ret; } /** *

* Returns the magnitude squared of the complex element along the diagonal with the largest magnitude
*
* Max{ |aij|^2 } for all i and j
*

* * @param a A matrix. Not modified. * @return The max magnitude squared */ public static double elementDiagMaxMagnitude2(ZMatrixRMaj a) { final int size = Math.min(a.numRows,a.numCols); int rowStride = a.getRowStride(); double max = 0; for( int i = 0; i < size; i++ ) { int index = i*rowStride + i*2; double real = a.data[index]; double imaginary = a.data[index+1]; double m = real*real + imaginary*imaginary; if( m > max ) { max = m; } } return max; } /** * Computes the quality of a triangular matrix, where the quality of a matrix * is defined in {@link LinearSolverDense#quality()}. In * this situation the quality is the magnitude of the product of * each diagonal element divided by the magnitude of the largest diagonal element. * If all diagonal elements are zero then zero is returned. * * @return the quality of the system. */ public static double qualityTriangular(ZMatrixRMaj T) { int N = Math.min(T.numRows,T.numCols); double max = elementDiagMaxMagnitude2(T); if( max == 0.0 ) return 0.0; max = Math.sqrt(max); int rowStride = T.getRowStride(); double qualityR = 1.0; double qualityI = 0.0; for( int i = 0; i < N; i++ ) { int index = i*rowStride + i*2; double real = T.data[index]/max; double imaginary = T.data[index]/max; double r = qualityR*real - qualityI*imaginary; double img = qualityR*imaginary + real*qualityI; qualityR = r; qualityI = img; } return Math.sqrt(qualityR*qualityR + qualityI*qualityI); } /** * Q = I - gamma*u*uH */ public static ZMatrixRMaj householder(ZMatrixRMaj u , double gamma ) { int N = u.getDataLength()/2; // u*u^H ZMatrixRMaj uut = new ZMatrixRMaj(N,N); VectorVectorMult_ZDRM.outerProdH(u, u, uut); // foo = -gamma*u*u^H CommonOps_ZDRM.elementMultiply(uut,-gamma,0,uut); // I + foo for (int i = 0; i < N; i++) { int index = (i*uut.numCols+i)*2; uut.data[index] = 1 + uut.data[index]; } return uut; } /** * Computes the householder vector used in QR decomposition. * * u = x / max(x) * u(0) = u(0) + |u| * u = u / u(0) * * @param x Input vector. Unmodified. * @return The found householder reflector vector */ public static ZMatrixRMaj householderVector(ZMatrixRMaj x ) { ZMatrixRMaj u = x.copy(); double max = CommonOps_ZDRM.elementMaxAbs(u); CommonOps_ZDRM.elementDivide(u, max, 0, u); double nx = NormOps_ZDRM.normF(u); Complex_F64 c = new Complex_F64(); u.get(0,0,c); double realTau,imagTau; if( c.getMagnitude() == 0 ) { realTau = nx; imagTau = 0; } else { realTau = c.real/c.getMagnitude()*nx; imagTau = c.imaginary/c.getMagnitude()*nx; } u.set(0,0,c.real + realTau,c.imaginary + imagTau); CommonOps_ZDRM.elementDivide(u,u.getReal(0,0),u.getImag(0,0),u); return u; } }




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