1931 lines
40 KiB
C++
1931 lines
40 KiB
C++
#include "qr_solve.h"
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#ifdef AUTO_BED_LEVELING_GRID
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#include <stdlib.h>
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#include <math.h>
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//# include "r8lib.h"
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int i4_min ( int i1, int i2 )
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/******************************************************************************/
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/*
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Purpose:
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I4_MIN returns the smaller of two I4's.
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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29 August 2006
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Author:
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John Burkardt
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Parameters:
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Input, int I1, I2, two integers to be compared.
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Output, int I4_MIN, the smaller of I1 and I2.
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*/
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{
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int value;
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if ( i1 < i2 )
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{
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value = i1;
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}
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else
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{
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value = i2;
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}
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return value;
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}
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double r8_epsilon ( void )
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/******************************************************************************/
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/*
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Purpose:
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R8_EPSILON returns the R8 round off unit.
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Discussion:
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R8_EPSILON is a number R which is a power of 2 with the property that,
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to the precision of the computer's arithmetic,
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1 < 1 + R
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but
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1 = ( 1 + R / 2 )
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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01 September 2012
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Author:
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John Burkardt
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Parameters:
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Output, double R8_EPSILON, the R8 round-off unit.
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*/
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{
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const double value = 2.220446049250313E-016;
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return value;
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}
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double r8_max ( double x, double y )
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/******************************************************************************/
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/*
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Purpose:
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R8_MAX returns the maximum of two R8's.
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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07 May 2006
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Author:
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John Burkardt
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Parameters:
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Input, double X, Y, the quantities to compare.
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Output, double R8_MAX, the maximum of X and Y.
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*/
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{
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double value;
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if ( y < x )
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{
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value = x;
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}
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else
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{
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value = y;
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}
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return value;
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}
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double r8_abs ( double x )
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/******************************************************************************/
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/*
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Purpose:
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R8_ABS returns the absolute value of an R8.
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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07 May 2006
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Author:
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John Burkardt
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Parameters:
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Input, double X, the quantity whose absolute value is desired.
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Output, double R8_ABS, the absolute value of X.
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*/
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{
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double value;
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if ( 0.0 <= x )
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{
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value = + x;
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}
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else
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{
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value = - x;
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}
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return value;
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}
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double r8_sign ( double x )
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/******************************************************************************/
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/*
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Purpose:
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R8_SIGN returns the sign of an R8.
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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08 May 2006
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Author:
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John Burkardt
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Parameters:
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Input, double X, the number whose sign is desired.
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Output, double R8_SIGN, the sign of X.
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*/
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{
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double value;
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if ( x < 0.0 )
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{
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value = - 1.0;
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}
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else
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{
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value = + 1.0;
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}
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return value;
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}
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double r8mat_amax ( int m, int n, double a[] )
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/******************************************************************************/
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/*
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Purpose:
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R8MAT_AMAX returns the maximum absolute value entry of an R8MAT.
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Discussion:
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An R8MAT is a doubly dimensioned array of R8 values, stored as a vector
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in column-major order.
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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07 September 2012
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Author:
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John Burkardt
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Parameters:
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Input, int M, the number of rows in A.
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Input, int N, the number of columns in A.
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Input, double A[M*N], the M by N matrix.
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Output, double R8MAT_AMAX, the maximum absolute value entry of A.
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*/
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{
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int i;
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int j;
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double value;
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value = r8_abs ( a[0+0*m] );
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for ( j = 0; j < n; j++ )
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{
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for ( i = 0; i < m; i++ )
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{
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if ( value < r8_abs ( a[i+j*m] ) )
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{
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value = r8_abs ( a[i+j*m] );
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}
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}
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}
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return value;
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}
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double *r8mat_copy_new ( int m, int n, double a1[] )
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/******************************************************************************/
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/*
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Purpose:
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R8MAT_COPY_NEW copies one R8MAT to a "new" R8MAT.
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Discussion:
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An R8MAT is a doubly dimensioned array of R8 values, stored as a vector
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in column-major order.
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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26 July 2008
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Author:
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John Burkardt
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Parameters:
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Input, int M, N, the number of rows and columns.
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Input, double A1[M*N], the matrix to be copied.
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Output, double R8MAT_COPY_NEW[M*N], the copy of A1.
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*/
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{
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double *a2;
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int i;
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int j;
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a2 = ( double * ) malloc ( m * n * sizeof ( double ) );
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for ( j = 0; j < n; j++ )
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{
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for ( i = 0; i < m; i++ )
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{
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a2[i+j*m] = a1[i+j*m];
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}
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}
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return a2;
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}
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/******************************************************************************/
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void daxpy ( int n, double da, double dx[], int incx, double dy[], int incy )
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/******************************************************************************/
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/*
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Purpose:
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DAXPY computes constant times a vector plus a vector.
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Discussion:
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This routine uses unrolled loops for increments equal to one.
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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30 March 2007
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Author:
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C version by John Burkardt
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Reference:
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Jack Dongarra, Cleve Moler, Jim Bunch, Pete Stewart,
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LINPACK User's Guide,
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SIAM, 1979.
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Charles Lawson, Richard Hanson, David Kincaid, Fred Krogh,
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Basic Linear Algebra Subprograms for Fortran Usage,
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Algorithm 539,
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ACM Transactions on Mathematical Software,
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Volume 5, Number 3, September 1979, pages 308-323.
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Parameters:
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Input, int N, the number of elements in DX and DY.
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Input, double DA, the multiplier of DX.
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Input, double DX[*], the first vector.
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Input, int INCX, the increment between successive entries of DX.
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Input/output, double DY[*], the second vector.
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On output, DY[*] has been replaced by DY[*] + DA * DX[*].
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Input, int INCY, the increment between successive entries of DY.
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*/
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{
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int i;
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int ix;
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int iy;
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int m;
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if ( n <= 0 )
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{
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return;
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}
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if ( da == 0.0 )
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{
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return;
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}
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/*
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Code for unequal increments or equal increments
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not equal to 1.
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*/
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if ( incx != 1 || incy != 1 )
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{
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if ( 0 <= incx )
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{
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ix = 0;
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}
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else
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{
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ix = ( - n + 1 ) * incx;
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}
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if ( 0 <= incy )
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{
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iy = 0;
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}
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else
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{
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iy = ( - n + 1 ) * incy;
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}
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for ( i = 0; i < n; i++ )
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{
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dy[iy] = dy[iy] + da * dx[ix];
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ix = ix + incx;
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iy = iy + incy;
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}
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}
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/*
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Code for both increments equal to 1.
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*/
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else
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{
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m = n % 4;
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for ( i = 0; i < m; i++ )
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{
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dy[i] = dy[i] + da * dx[i];
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}
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for ( i = m; i < n; i = i + 4 )
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{
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dy[i ] = dy[i ] + da * dx[i ];
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dy[i+1] = dy[i+1] + da * dx[i+1];
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dy[i+2] = dy[i+2] + da * dx[i+2];
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dy[i+3] = dy[i+3] + da * dx[i+3];
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}
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}
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return;
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}
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/******************************************************************************/
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double ddot ( int n, double dx[], int incx, double dy[], int incy )
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/******************************************************************************/
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/*
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Purpose:
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DDOT forms the dot product of two vectors.
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Discussion:
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This routine uses unrolled loops for increments equal to one.
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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30 March 2007
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Author:
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C version by John Burkardt
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Reference:
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Jack Dongarra, Cleve Moler, Jim Bunch, Pete Stewart,
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LINPACK User's Guide,
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SIAM, 1979.
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Charles Lawson, Richard Hanson, David Kincaid, Fred Krogh,
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Basic Linear Algebra Subprograms for Fortran Usage,
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Algorithm 539,
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ACM Transactions on Mathematical Software,
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Volume 5, Number 3, September 1979, pages 308-323.
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Parameters:
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Input, int N, the number of entries in the vectors.
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Input, double DX[*], the first vector.
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Input, int INCX, the increment between successive entries in DX.
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Input, double DY[*], the second vector.
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Input, int INCY, the increment between successive entries in DY.
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Output, double DDOT, the sum of the product of the corresponding
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entries of DX and DY.
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*/
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{
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double dtemp;
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int i;
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int ix;
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int iy;
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int m;
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dtemp = 0.0;
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if ( n <= 0 )
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{
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return dtemp;
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}
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/*
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Code for unequal increments or equal increments
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not equal to 1.
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*/
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if ( incx != 1 || incy != 1 )
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{
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if ( 0 <= incx )
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{
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ix = 0;
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}
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else
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{
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ix = ( - n + 1 ) * incx;
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}
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if ( 0 <= incy )
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{
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iy = 0;
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}
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else
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{
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iy = ( - n + 1 ) * incy;
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}
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for ( i = 0; i < n; i++ )
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{
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dtemp = dtemp + dx[ix] * dy[iy];
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ix = ix + incx;
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iy = iy + incy;
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}
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}
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/*
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Code for both increments equal to 1.
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*/
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else
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{
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m = n % 5;
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for ( i = 0; i < m; i++ )
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{
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dtemp = dtemp + dx[i] * dy[i];
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}
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for ( i = m; i < n; i = i + 5 )
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{
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dtemp = dtemp + dx[i ] * dy[i ]
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+ dx[i+1] * dy[i+1]
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+ dx[i+2] * dy[i+2]
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+ dx[i+3] * dy[i+3]
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+ dx[i+4] * dy[i+4];
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}
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}
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return dtemp;
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}
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/******************************************************************************/
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double dnrm2 ( int n, double x[], int incx )
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/******************************************************************************/
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/*
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Purpose:
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DNRM2 returns the euclidean norm of a vector.
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Discussion:
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DNRM2 ( X ) = sqrt ( X' * X )
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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30 March 2007
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Author:
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C version by John Burkardt
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Reference:
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Jack Dongarra, Cleve Moler, Jim Bunch, Pete Stewart,
|
|
LINPACK User's Guide,
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SIAM, 1979.
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Charles Lawson, Richard Hanson, David Kincaid, Fred Krogh,
|
|
Basic Linear Algebra Subprograms for Fortran Usage,
|
|
Algorithm 539,
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|
ACM Transactions on Mathematical Software,
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Volume 5, Number 3, September 1979, pages 308-323.
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Parameters:
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Input, int N, the number of entries in the vector.
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Input, double X[*], the vector whose norm is to be computed.
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Input, int INCX, the increment between successive entries of X.
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Output, double DNRM2, the Euclidean norm of X.
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*/
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{
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double absxi;
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int i;
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int ix;
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double norm;
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double scale;
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double ssq;
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double value;
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if ( n < 1 || incx < 1 )
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{
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norm = 0.0;
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}
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else if ( n == 1 )
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{
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norm = r8_abs ( x[0] );
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}
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else
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{
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scale = 0.0;
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ssq = 1.0;
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ix = 0;
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for ( i = 0; i < n; i++ )
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{
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if ( x[ix] != 0.0 )
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{
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absxi = r8_abs ( x[ix] );
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if ( scale < absxi )
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{
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ssq = 1.0 + ssq * ( scale / absxi ) * ( scale / absxi );
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scale = absxi;
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}
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else
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{
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ssq = ssq + ( absxi / scale ) * ( absxi / scale );
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}
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}
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ix = ix + incx;
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}
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norm = scale * sqrt ( ssq );
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}
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return norm;
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}
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/******************************************************************************/
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void dqrank ( double a[], int lda, int m, int n, double tol, int *kr,
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int jpvt[], double qraux[] )
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/******************************************************************************/
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/*
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Purpose:
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DQRANK computes the QR factorization of a rectangular matrix.
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Discussion:
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This routine is used in conjunction with DQRLSS to solve
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overdetermined, underdetermined and singular linear systems
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in a least squares sense.
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DQRANK uses the LINPACK subroutine DQRDC to compute the QR
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factorization, with column pivoting, of an M by N matrix A.
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The numerical rank is determined using the tolerance TOL.
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Note that on output, ABS ( A(1,1) ) / ABS ( A(KR,KR) ) is an estimate
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of the condition number of the matrix of independent columns,
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and of R. This estimate will be <= 1/TOL.
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Licensing:
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This code is distributed under the GNU LGPL license.
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Modified:
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21 April 2012
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Author:
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|
C version by John Burkardt.
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|
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Reference:
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|
|
Jack Dongarra, Cleve Moler, Jim Bunch, Pete Stewart,
|
|
LINPACK User's Guide,
|
|
SIAM, 1979,
|
|
ISBN13: 978-0-898711-72-1,
|
|
LC: QA214.L56.
|
|
|
|
Parameters:
|
|
|
|
Input/output, double A[LDA*N]. On input, the matrix whose
|
|
decomposition is to be computed. On output, the information from DQRDC.
|
|
The triangular matrix R of the QR factorization is contained in the
|
|
upper triangle and information needed to recover the orthogonal
|
|
matrix Q is stored below the diagonal in A and in the vector QRAUX.
|
|
|
|
Input, int LDA, the leading dimension of A, which must
|
|
be at least M.
|
|
|
|
Input, int M, the number of rows of A.
|
|
|
|
Input, int N, the number of columns of A.
|
|
|
|
Input, double TOL, a relative tolerance used to determine the
|
|
numerical rank. The problem should be scaled so that all the elements
|
|
of A have roughly the same absolute accuracy, EPS. Then a reasonable
|
|
value for TOL is roughly EPS divided by the magnitude of the largest
|
|
element.
|
|
|
|
Output, int *KR, the numerical rank.
|
|
|
|
Output, int JPVT[N], the pivot information from DQRDC.
|
|
Columns JPVT(1), ..., JPVT(KR) of the original matrix are linearly
|
|
independent to within the tolerance TOL and the remaining columns
|
|
are linearly dependent.
|
|
|
|
Output, double QRAUX[N], will contain extra information defining
|
|
the QR factorization.
|
|
*/
|
|
{
|
|
int i;
|
|
int j;
|
|
int job;
|
|
int k;
|
|
double *work;
|
|
|
|
for ( i = 0; i < n; i++ )
|
|
{
|
|
jpvt[i] = 0;
|
|
}
|
|
|
|
work = ( double * ) malloc ( n * sizeof ( double ) );
|
|
job = 1;
|
|
|
|
dqrdc ( a, lda, m, n, qraux, jpvt, work, job );
|
|
|
|
*kr = 0;
|
|
k = i4_min ( m, n );
|
|
|
|
for ( j = 0; j < k; j++ )
|
|
{
|
|
if ( r8_abs ( a[j+j*lda] ) <= tol * r8_abs ( a[0+0*lda] ) )
|
|
{
|
|
return;
|
|
}
|
|
*kr = j + 1;
|
|
}
|
|
|
|
free ( work );
|
|
|
|
return;
|
|
}
|
|
/******************************************************************************/
|
|
|
|
void dqrdc ( double a[], int lda, int n, int p, double qraux[], int jpvt[],
|
|
double work[], int job )
|
|
|
|
/******************************************************************************/
|
|
/*
|
|
Purpose:
|
|
|
|
DQRDC computes the QR factorization of a real rectangular matrix.
|
|
|
|
Discussion:
|
|
|
|
DQRDC uses Householder transformations.
|
|
|
|
Column pivoting based on the 2-norms of the reduced columns may be
|
|
performed at the user's option.
|
|
|
|
Licensing:
|
|
|
|
This code is distributed under the GNU LGPL license.
|
|
|
|
Modified:
|
|
|
|
07 June 2005
|
|
|
|
Author:
|
|
|
|
C version by John Burkardt.
|
|
|
|
Reference:
|
|
|
|
Jack Dongarra, Cleve Moler, Jim Bunch and Pete Stewart,
|
|
LINPACK User's Guide,
|
|
SIAM, (Society for Industrial and Applied Mathematics),
|
|
3600 University City Science Center,
|
|
Philadelphia, PA, 19104-2688.
|
|
ISBN 0-89871-172-X
|
|
|
|
Parameters:
|
|
|
|
Input/output, double A(LDA,P). On input, the N by P matrix
|
|
whose decomposition is to be computed. On output, A contains in
|
|
its upper triangle the upper triangular matrix R of the QR
|
|
factorization. Below its diagonal A contains information from
|
|
which the orthogonal part of the decomposition can be recovered.
|
|
Note that if pivoting has been requested, the decomposition is not that
|
|
of the original matrix A but that of A with its columns permuted
|
|
as described by JPVT.
|
|
|
|
Input, int LDA, the leading dimension of the array A. LDA must
|
|
be at least N.
|
|
|
|
Input, int N, the number of rows of the matrix A.
|
|
|
|
Input, int P, the number of columns of the matrix A.
|
|
|
|
Output, double QRAUX[P], contains further information required
|
|
to recover the orthogonal part of the decomposition.
|
|
|
|
Input/output, integer JPVT[P]. On input, JPVT contains integers that
|
|
control the selection of the pivot columns. The K-th column A(*,K) of A
|
|
is placed in one of three classes according to the value of JPVT(K).
|
|
> 0, then A(K) is an initial column.
|
|
= 0, then A(K) is a free column.
|
|
< 0, then A(K) is a final column.
|
|
Before the decomposition is computed, initial columns are moved to
|
|
the beginning of the array A and final columns to the end. Both
|
|
initial and final columns are frozen in place during the computation
|
|
and only free columns are moved. At the K-th stage of the
|
|
reduction, if A(*,K) is occupied by a free column it is interchanged
|
|
with the free column of largest reduced norm. JPVT is not referenced
|
|
if JOB == 0. On output, JPVT(K) contains the index of the column of the
|
|
original matrix that has been interchanged into the K-th column, if
|
|
pivoting was requested.
|
|
|
|
Workspace, double WORK[P]. WORK is not referenced if JOB == 0.
|
|
|
|
Input, int JOB, initiates column pivoting.
|
|
0, no pivoting is done.
|
|
nonzero, pivoting is done.
|
|
*/
|
|
{
|
|
int j;
|
|
int jp;
|
|
int l;
|
|
int lup;
|
|
int maxj;
|
|
double maxnrm;
|
|
double nrmxl;
|
|
int pl;
|
|
int pu;
|
|
int swapj;
|
|
double t;
|
|
double tt;
|
|
|
|
pl = 1;
|
|
pu = 0;
|
|
/*
|
|
If pivoting is requested, rearrange the columns.
|
|
*/
|
|
if ( job != 0 )
|
|
{
|
|
for ( j = 1; j <= p; j++ )
|
|
{
|
|
swapj = ( 0 < jpvt[j-1] );
|
|
|
|
if ( jpvt[j-1] < 0 )
|
|
{
|
|
jpvt[j-1] = -j;
|
|
}
|
|
else
|
|
{
|
|
jpvt[j-1] = j;
|
|
}
|
|
|
|
if ( swapj )
|
|
{
|
|
if ( j != pl )
|
|
{
|
|
dswap ( n, a+0+(pl-1)*lda, 1, a+0+(j-1), 1 );
|
|
}
|
|
jpvt[j-1] = jpvt[pl-1];
|
|
jpvt[pl-1] = j;
|
|
pl = pl + 1;
|
|
}
|
|
}
|
|
pu = p;
|
|
|
|
for ( j = p; 1 <= j; j-- )
|
|
{
|
|
if ( jpvt[j-1] < 0 )
|
|
{
|
|
jpvt[j-1] = -jpvt[j-1];
|
|
|
|
if ( j != pu )
|
|
{
|
|
dswap ( n, a+0+(pu-1)*lda, 1, a+0+(j-1)*lda, 1 );
|
|
jp = jpvt[pu-1];
|
|
jpvt[pu-1] = jpvt[j-1];
|
|
jpvt[j-1] = jp;
|
|
}
|
|
pu = pu - 1;
|
|
}
|
|
}
|
|
}
|
|
/*
|
|
Compute the norms of the free columns.
|
|
*/
|
|
for ( j = pl; j <= pu; j++ )
|
|
{
|
|
qraux[j-1] = dnrm2 ( n, a+0+(j-1)*lda, 1 );
|
|
}
|
|
|
|
for ( j = pl; j <= pu; j++ )
|
|
{
|
|
work[j-1] = qraux[j-1];
|
|
}
|
|
/*
|
|
Perform the Householder reduction of A.
|
|
*/
|
|
lup = i4_min ( n, p );
|
|
|
|
for ( l = 1; l <= lup; l++ )
|
|
{
|
|
/*
|
|
Bring the column of largest norm into the pivot position.
|
|
*/
|
|
if ( pl <= l && l < pu )
|
|
{
|
|
maxnrm = 0.0;
|
|
maxj = l;
|
|
for ( j = l; j <= pu; j++ )
|
|
{
|
|
if ( maxnrm < qraux[j-1] )
|
|
{
|
|
maxnrm = qraux[j-1];
|
|
maxj = j;
|
|
}
|
|
}
|
|
|
|
if ( maxj != l )
|
|
{
|
|
dswap ( n, a+0+(l-1)*lda, 1, a+0+(maxj-1)*lda, 1 );
|
|
qraux[maxj-1] = qraux[l-1];
|
|
work[maxj-1] = work[l-1];
|
|
jp = jpvt[maxj-1];
|
|
jpvt[maxj-1] = jpvt[l-1];
|
|
jpvt[l-1] = jp;
|
|
}
|
|
}
|
|
/*
|
|
Compute the Householder transformation for column L.
|
|
*/
|
|
qraux[l-1] = 0.0;
|
|
|
|
if ( l != n )
|
|
{
|
|
nrmxl = dnrm2 ( n-l+1, a+l-1+(l-1)*lda, 1 );
|
|
|
|
if ( nrmxl != 0.0 )
|
|
{
|
|
if ( a[l-1+(l-1)*lda] != 0.0 )
|
|
{
|
|
nrmxl = nrmxl * r8_sign ( a[l-1+(l-1)*lda] );
|
|
}
|
|
|
|
dscal ( n-l+1, 1.0 / nrmxl, a+l-1+(l-1)*lda, 1 );
|
|
a[l-1+(l-1)*lda] = 1.0 + a[l-1+(l-1)*lda];
|
|
/*
|
|
Apply the transformation to the remaining columns, updating the norms.
|
|
*/
|
|
for ( j = l + 1; j <= p; j++ )
|
|
{
|
|
t = -ddot ( n-l+1, a+l-1+(l-1)*lda, 1, a+l-1+(j-1)*lda, 1 )
|
|
/ a[l-1+(l-1)*lda];
|
|
daxpy ( n-l+1, t, a+l-1+(l-1)*lda, 1, a+l-1+(j-1)*lda, 1 );
|
|
|
|
if ( pl <= j && j <= pu )
|
|
{
|
|
if ( qraux[j-1] != 0.0 )
|
|
{
|
|
tt = 1.0 - pow ( r8_abs ( a[l-1+(j-1)*lda] ) / qraux[j-1], 2 );
|
|
tt = r8_max ( tt, 0.0 );
|
|
t = tt;
|
|
tt = 1.0 + 0.05 * tt * pow ( qraux[j-1] / work[j-1], 2 );
|
|
|
|
if ( tt != 1.0 )
|
|
{
|
|
qraux[j-1] = qraux[j-1] * sqrt ( t );
|
|
}
|
|
else
|
|
{
|
|
qraux[j-1] = dnrm2 ( n-l, a+l+(j-1)*lda, 1 );
|
|
work[j-1] = qraux[j-1];
|
|
}
|
|
}
|
|
}
|
|
}
|
|
/*
|
|
Save the transformation.
|
|
*/
|
|
qraux[l-1] = a[l-1+(l-1)*lda];
|
|
a[l-1+(l-1)*lda] = -nrmxl;
|
|
}
|
|
}
|
|
}
|
|
return;
|
|
}
|
|
/******************************************************************************/
|
|
|
|
int dqrls ( double a[], int lda, int m, int n, double tol, int *kr, double b[],
|
|
double x[], double rsd[], int jpvt[], double qraux[], int itask )
|
|
|
|
/******************************************************************************/
|
|
/*
|
|
Purpose:
|
|
|
|
DQRLS factors and solves a linear system in the least squares sense.
|
|
|
|
Discussion:
|
|
|
|
The linear system may be overdetermined, underdetermined or singular.
|
|
The solution is obtained using a QR factorization of the
|
|
coefficient matrix.
|
|
|
|
DQRLS can be efficiently used to solve several least squares
|
|
problems with the same matrix A. The first system is solved
|
|
with ITASK = 1. The subsequent systems are solved with
|
|
ITASK = 2, to avoid the recomputation of the matrix factors.
|
|
The parameters KR, JPVT, and QRAUX must not be modified
|
|
between calls to DQRLS.
|
|
|
|
DQRLS is used to solve in a least squares sense
|
|
overdetermined, underdetermined and singular linear systems.
|
|
The system is A*X approximates B where A is M by N.
|
|
B is a given M-vector, and X is the N-vector to be computed.
|
|
A solution X is found which minimimzes the sum of squares (2-norm)
|
|
of the residual, A*X - B.
|
|
|
|
The numerical rank of A is determined using the tolerance TOL.
|
|
|
|
DQRLS uses the LINPACK subroutine DQRDC to compute the QR
|
|
factorization, with column pivoting, of an M by N matrix A.
|
|
|
|
Licensing:
|
|
|
|
This code is distributed under the GNU LGPL license.
|
|
|
|
Modified:
|
|
|
|
10 September 2012
|
|
|
|
Author:
|
|
|
|
C version by John Burkardt.
|
|
|
|
Reference:
|
|
|
|
David Kahaner, Cleve Moler, Steven Nash,
|
|
Numerical Methods and Software,
|
|
Prentice Hall, 1989,
|
|
ISBN: 0-13-627258-4,
|
|
LC: TA345.K34.
|
|
|
|
Parameters:
|
|
|
|
Input/output, double A[LDA*N], an M by N matrix.
|
|
On input, the matrix whose decomposition is to be computed.
|
|
In a least squares data fitting problem, A(I,J) is the
|
|
value of the J-th basis (model) function at the I-th data point.
|
|
On output, A contains the output from DQRDC. The triangular matrix R
|
|
of the QR factorization is contained in the upper triangle and
|
|
information needed to recover the orthogonal matrix Q is stored
|
|
below the diagonal in A and in the vector QRAUX.
|
|
|
|
Input, int LDA, the leading dimension of A.
|
|
|
|
Input, int M, the number of rows of A.
|
|
|
|
Input, int N, the number of columns of A.
|
|
|
|
Input, double TOL, a relative tolerance used to determine the
|
|
numerical rank. The problem should be scaled so that all the elements
|
|
of A have roughly the same absolute accuracy EPS. Then a reasonable
|
|
value for TOL is roughly EPS divided by the magnitude of the largest
|
|
element.
|
|
|
|
Output, int *KR, the numerical rank.
|
|
|
|
Input, double B[M], the right hand side of the linear system.
|
|
|
|
Output, double X[N], a least squares solution to the linear
|
|
system.
|
|
|
|
Output, double RSD[M], the residual, B - A*X. RSD may
|
|
overwrite B.
|
|
|
|
Workspace, int JPVT[N], required if ITASK = 1.
|
|
Columns JPVT(1), ..., JPVT(KR) of the original matrix are linearly
|
|
independent to within the tolerance TOL and the remaining columns
|
|
are linearly dependent. ABS ( A(1,1) ) / ABS ( A(KR,KR) ) is an estimate
|
|
of the condition number of the matrix of independent columns,
|
|
and of R. This estimate will be <= 1/TOL.
|
|
|
|
Workspace, double QRAUX[N], required if ITASK = 1.
|
|
|
|
Input, int ITASK.
|
|
1, DQRLS factors the matrix A and solves the least squares problem.
|
|
2, DQRLS assumes that the matrix A was factored with an earlier
|
|
call to DQRLS, and only solves the least squares problem.
|
|
|
|
Output, int DQRLS, error code.
|
|
0: no error
|
|
-1: LDA < M (fatal error)
|
|
-2: N < 1 (fatal error)
|
|
-3: ITASK < 1 (fatal error)
|
|
*/
|
|
{
|
|
int ind;
|
|
|
|
if ( lda < m )
|
|
{
|
|
/*fprintf ( stderr, "\n" );
|
|
fprintf ( stderr, "DQRLS - Fatal error!\n" );
|
|
fprintf ( stderr, " LDA < M.\n" );*/
|
|
ind = -1;
|
|
return ind;
|
|
}
|
|
|
|
if ( n <= 0 )
|
|
{
|
|
/*fprintf ( stderr, "\n" );
|
|
fprintf ( stderr, "DQRLS - Fatal error!\n" );
|
|
fprintf ( stderr, " N <= 0.\n" );*/
|
|
ind = -2;
|
|
return ind;
|
|
}
|
|
|
|
if ( itask < 1 )
|
|
{
|
|
/*fprintf ( stderr, "\n" );
|
|
fprintf ( stderr, "DQRLS - Fatal error!\n" );
|
|
fprintf ( stderr, " ITASK < 1.\n" );*/
|
|
ind = -3;
|
|
return ind;
|
|
}
|
|
|
|
ind = 0;
|
|
/*
|
|
Factor the matrix.
|
|
*/
|
|
if ( itask == 1 )
|
|
{
|
|
dqrank ( a, lda, m, n, tol, kr, jpvt, qraux );
|
|
}
|
|
/*
|
|
Solve the least-squares problem.
|
|
*/
|
|
dqrlss ( a, lda, m, n, *kr, b, x, rsd, jpvt, qraux );
|
|
|
|
return ind;
|
|
}
|
|
/******************************************************************************/
|
|
|
|
void dqrlss ( double a[], int lda, int m, int n, int kr, double b[], double x[],
|
|
double rsd[], int jpvt[], double qraux[] )
|
|
|
|
/******************************************************************************/
|
|
/*
|
|
Purpose:
|
|
|
|
DQRLSS solves a linear system in a least squares sense.
|
|
|
|
Discussion:
|
|
|
|
DQRLSS must be preceeded by a call to DQRANK.
|
|
|
|
The system is to be solved is
|
|
A * X = B
|
|
where
|
|
A is an M by N matrix with rank KR, as determined by DQRANK,
|
|
B is a given M-vector,
|
|
X is the N-vector to be computed.
|
|
|
|
A solution X, with at most KR nonzero components, is found which
|
|
minimizes the 2-norm of the residual (A*X-B).
|
|
|
|
Once the matrix A has been formed, DQRANK should be
|
|
called once to decompose it. Then, for each right hand
|
|
side B, DQRLSS should be called once to obtain the
|
|
solution and residual.
|
|
|
|
Licensing:
|
|
|
|
This code is distributed under the GNU LGPL license.
|
|
|
|
Modified:
|
|
|
|
10 September 2012
|
|
|
|
Author:
|
|
|
|
C version by John Burkardt
|
|
|
|
Parameters:
|
|
|
|
Input, double A[LDA*N], the QR factorization information
|
|
from DQRANK. The triangular matrix R of the QR factorization is
|
|
contained in the upper triangle and information needed to recover
|
|
the orthogonal matrix Q is stored below the diagonal in A and in
|
|
the vector QRAUX.
|
|
|
|
Input, int LDA, the leading dimension of A, which must
|
|
be at least M.
|
|
|
|
Input, int M, the number of rows of A.
|
|
|
|
Input, int N, the number of columns of A.
|
|
|
|
Input, int KR, the rank of the matrix, as estimated by DQRANK.
|
|
|
|
Input, double B[M], the right hand side of the linear system.
|
|
|
|
Output, double X[N], a least squares solution to the
|
|
linear system.
|
|
|
|
Output, double RSD[M], the residual, B - A*X. RSD may
|
|
overwite B.
|
|
|
|
Input, int JPVT[N], the pivot information from DQRANK.
|
|
Columns JPVT[0], ..., JPVT[KR-1] of the original matrix are linearly
|
|
independent to within the tolerance TOL and the remaining columns
|
|
are linearly dependent.
|
|
|
|
Input, double QRAUX[N], auxiliary information from DQRANK
|
|
defining the QR factorization.
|
|
*/
|
|
{
|
|
int i;
|
|
int info;
|
|
int j;
|
|
int job;
|
|
int k;
|
|
double t;
|
|
|
|
if ( kr != 0 )
|
|
{
|
|
job = 110;
|
|
info = dqrsl ( a, lda, m, kr, qraux, b, rsd, rsd, x, rsd, rsd, job );
|
|
}
|
|
|
|
for ( i = 0; i < n; i++ )
|
|
{
|
|
jpvt[i] = - jpvt[i];
|
|
}
|
|
|
|
for ( i = kr; i < n; i++ )
|
|
{
|
|
x[i] = 0.0;
|
|
}
|
|
|
|
for ( j = 1; j <= n; j++ )
|
|
{
|
|
if ( jpvt[j-1] <= 0 )
|
|
{
|
|
k = - jpvt[j-1];
|
|
jpvt[j-1] = k;
|
|
|
|
while ( k != j )
|
|
{
|
|
t = x[j-1];
|
|
x[j-1] = x[k-1];
|
|
x[k-1] = t;
|
|
jpvt[k-1] = -jpvt[k-1];
|
|
k = jpvt[k-1];
|
|
}
|
|
}
|
|
}
|
|
return;
|
|
}
|
|
/******************************************************************************/
|
|
|
|
int dqrsl ( double a[], int lda, int n, int k, double qraux[], double y[],
|
|
double qy[], double qty[], double b[], double rsd[], double ab[], int job )
|
|
|
|
/******************************************************************************/
|
|
/*
|
|
Purpose:
|
|
|
|
DQRSL computes transformations, projections, and least squares solutions.
|
|
|
|
Discussion:
|
|
|
|
DQRSL requires the output of DQRDC.
|
|
|
|
For K <= min(N,P), let AK be the matrix
|
|
|
|
AK = ( A(JPVT[0]), A(JPVT(2)), ..., A(JPVT(K)) )
|
|
|
|
formed from columns JPVT[0], ..., JPVT(K) of the original
|
|
N by P matrix A that was input to DQRDC. If no pivoting was
|
|
done, AK consists of the first K columns of A in their
|
|
original order. DQRDC produces a factored orthogonal matrix Q
|
|
and an upper triangular matrix R such that
|
|
|
|
AK = Q * (R)
|
|
(0)
|
|
|
|
This information is contained in coded form in the arrays
|
|
A and QRAUX.
|
|
|
|
The parameters QY, QTY, B, RSD, and AB are not referenced
|
|
if their computation is not requested and in this case
|
|
can be replaced by dummy variables in the calling program.
|
|
To save storage, the user may in some cases use the same
|
|
array for different parameters in the calling sequence. A
|
|
frequently occuring example is when one wishes to compute
|
|
any of B, RSD, or AB and does not need Y or QTY. In this
|
|
case one may identify Y, QTY, and one of B, RSD, or AB, while
|
|
providing separate arrays for anything else that is to be
|
|
computed.
|
|
|
|
Thus the calling sequence
|
|
|
|
dqrsl ( a, lda, n, k, qraux, y, dum, y, b, y, dum, 110, info )
|
|
|
|
will result in the computation of B and RSD, with RSD
|
|
overwriting Y. More generally, each item in the following
|
|
list contains groups of permissible identifications for
|
|
a single calling sequence.
|
|
|
|
1. (Y,QTY,B) (RSD) (AB) (QY)
|
|
|
|
2. (Y,QTY,RSD) (B) (AB) (QY)
|
|
|
|
3. (Y,QTY,AB) (B) (RSD) (QY)
|
|
|
|
4. (Y,QY) (QTY,B) (RSD) (AB)
|
|
|
|
5. (Y,QY) (QTY,RSD) (B) (AB)
|
|
|
|
6. (Y,QY) (QTY,AB) (B) (RSD)
|
|
|
|
In any group the value returned in the array allocated to
|
|
the group corresponds to the last member of the group.
|
|
|
|
Licensing:
|
|
|
|
This code is distributed under the GNU LGPL license.
|
|
|
|
Modified:
|
|
|
|
07 June 2005
|
|
|
|
Author:
|
|
|
|
C version by John Burkardt.
|
|
|
|
Reference:
|
|
|
|
Jack Dongarra, Cleve Moler, Jim Bunch and Pete Stewart,
|
|
LINPACK User's Guide,
|
|
SIAM, (Society for Industrial and Applied Mathematics),
|
|
3600 University City Science Center,
|
|
Philadelphia, PA, 19104-2688.
|
|
ISBN 0-89871-172-X
|
|
|
|
Parameters:
|
|
|
|
Input, double A[LDA*P], contains the output of DQRDC.
|
|
|
|
Input, int LDA, the leading dimension of the array A.
|
|
|
|
Input, int N, the number of rows of the matrix AK. It must
|
|
have the same value as N in DQRDC.
|
|
|
|
Input, int K, the number of columns of the matrix AK. K
|
|
must not be greater than min(N,P), where P is the same as in the
|
|
calling sequence to DQRDC.
|
|
|
|
Input, double QRAUX[P], the auxiliary output from DQRDC.
|
|
|
|
Input, double Y[N], a vector to be manipulated by DQRSL.
|
|
|
|
Output, double QY[N], contains Q * Y, if requested.
|
|
|
|
Output, double QTY[N], contains Q' * Y, if requested.
|
|
|
|
Output, double B[K], the solution of the least squares problem
|
|
minimize norm2 ( Y - AK * B),
|
|
if its computation has been requested. Note that if pivoting was
|
|
requested in DQRDC, the J-th component of B will be associated with
|
|
column JPVT(J) of the original matrix A that was input into DQRDC.
|
|
|
|
Output, double RSD[N], the least squares residual Y - AK * B,
|
|
if its computation has been requested. RSD is also the orthogonal
|
|
projection of Y onto the orthogonal complement of the column space
|
|
of AK.
|
|
|
|
Output, double AB[N], the least squares approximation Ak * B,
|
|
if its computation has been requested. AB is also the orthogonal
|
|
projection of Y onto the column space of A.
|
|
|
|
Input, integer JOB, specifies what is to be computed. JOB has
|
|
the decimal expansion ABCDE, with the following meaning:
|
|
|
|
if A != 0, compute QY.
|
|
if B != 0, compute QTY.
|
|
if C != 0, compute QTY and B.
|
|
if D != 0, compute QTY and RSD.
|
|
if E != 0, compute QTY and AB.
|
|
|
|
Note that a request to compute B, RSD, or AB automatically triggers
|
|
the computation of QTY, for which an array must be provided in the
|
|
calling sequence.
|
|
|
|
Output, int DQRSL, is zero unless the computation of B has
|
|
been requested and R is exactly singular. In this case, INFO is the
|
|
index of the first zero diagonal element of R, and B is left unaltered.
|
|
*/
|
|
{
|
|
int cab;
|
|
int cb;
|
|
int cqty;
|
|
int cqy;
|
|
int cr;
|
|
int i;
|
|
int info;
|
|
int j;
|
|
int jj;
|
|
int ju;
|
|
double t;
|
|
double temp;
|
|
/*
|
|
Set INFO flag.
|
|
*/
|
|
info = 0;
|
|
/*
|
|
Determine what is to be computed.
|
|
*/
|
|
cqy = ( job / 10000 != 0 );
|
|
cqty = ( ( job % 10000 ) != 0 );
|
|
cb = ( ( job % 1000 ) / 100 != 0 );
|
|
cr = ( ( job % 100 ) / 10 != 0 );
|
|
cab = ( ( job % 10 ) != 0 );
|
|
|
|
ju = i4_min ( k, n-1 );
|
|
/*
|
|
Special action when N = 1.
|
|
*/
|
|
if ( ju == 0 )
|
|
{
|
|
if ( cqy )
|
|
{
|
|
qy[0] = y[0];
|
|
}
|
|
|
|
if ( cqty )
|
|
{
|
|
qty[0] = y[0];
|
|
}
|
|
|
|
if ( cab )
|
|
{
|
|
ab[0] = y[0];
|
|
}
|
|
|
|
if ( cb )
|
|
{
|
|
if ( a[0+0*lda] == 0.0 )
|
|
{
|
|
info = 1;
|
|
}
|
|
else
|
|
{
|
|
b[0] = y[0] / a[0+0*lda];
|
|
}
|
|
}
|
|
|
|
if ( cr )
|
|
{
|
|
rsd[0] = 0.0;
|
|
}
|
|
return info;
|
|
}
|
|
/*
|
|
Set up to compute QY or QTY.
|
|
*/
|
|
if ( cqy )
|
|
{
|
|
for ( i = 1; i <= n; i++ )
|
|
{
|
|
qy[i-1] = y[i-1];
|
|
}
|
|
}
|
|
|
|
if ( cqty )
|
|
{
|
|
for ( i = 1; i <= n; i++ )
|
|
{
|
|
qty[i-1] = y[i-1];
|
|
}
|
|
}
|
|
/*
|
|
Compute QY.
|
|
*/
|
|
if ( cqy )
|
|
{
|
|
for ( jj = 1; jj <= ju; jj++ )
|
|
{
|
|
j = ju - jj + 1;
|
|
|
|
if ( qraux[j-1] != 0.0 )
|
|
{
|
|
temp = a[j-1+(j-1)*lda];
|
|
a[j-1+(j-1)*lda] = qraux[j-1];
|
|
t = -ddot ( n-j+1, a+j-1+(j-1)*lda, 1, qy+j-1, 1 ) / a[j-1+(j-1)*lda];
|
|
daxpy ( n-j+1, t, a+j-1+(j-1)*lda, 1, qy+j-1, 1 );
|
|
a[j-1+(j-1)*lda] = temp;
|
|
}
|
|
}
|
|
}
|
|
/*
|
|
Compute Q'*Y.
|
|
*/
|
|
if ( cqty )
|
|
{
|
|
for ( j = 1; j <= ju; j++ )
|
|
{
|
|
if ( qraux[j-1] != 0.0 )
|
|
{
|
|
temp = a[j-1+(j-1)*lda];
|
|
a[j-1+(j-1)*lda] = qraux[j-1];
|
|
t = -ddot ( n-j+1, a+j-1+(j-1)*lda, 1, qty+j-1, 1 ) / a[j-1+(j-1)*lda];
|
|
daxpy ( n-j+1, t, a+j-1+(j-1)*lda, 1, qty+j-1, 1 );
|
|
a[j-1+(j-1)*lda] = temp;
|
|
}
|
|
}
|
|
}
|
|
/*
|
|
Set up to compute B, RSD, or AB.
|
|
*/
|
|
if ( cb )
|
|
{
|
|
for ( i = 1; i <= k; i++ )
|
|
{
|
|
b[i-1] = qty[i-1];
|
|
}
|
|
}
|
|
|
|
if ( cab )
|
|
{
|
|
for ( i = 1; i <= k; i++ )
|
|
{
|
|
ab[i-1] = qty[i-1];
|
|
}
|
|
}
|
|
|
|
if ( cr && k < n )
|
|
{
|
|
for ( i = k+1; i <= n; i++ )
|
|
{
|
|
rsd[i-1] = qty[i-1];
|
|
}
|
|
}
|
|
|
|
if ( cab && k+1 <= n )
|
|
{
|
|
for ( i = k+1; i <= n; i++ )
|
|
{
|
|
ab[i-1] = 0.0;
|
|
}
|
|
}
|
|
|
|
if ( cr )
|
|
{
|
|
for ( i = 1; i <= k; i++ )
|
|
{
|
|
rsd[i-1] = 0.0;
|
|
}
|
|
}
|
|
/*
|
|
Compute B.
|
|
*/
|
|
if ( cb )
|
|
{
|
|
for ( jj = 1; jj <= k; jj++ )
|
|
{
|
|
j = k - jj + 1;
|
|
|
|
if ( a[j-1+(j-1)*lda] == 0.0 )
|
|
{
|
|
info = j;
|
|
break;
|
|
}
|
|
|
|
b[j-1] = b[j-1] / a[j-1+(j-1)*lda];
|
|
|
|
if ( j != 1 )
|
|
{
|
|
t = -b[j-1];
|
|
daxpy ( j-1, t, a+0+(j-1)*lda, 1, b, 1 );
|
|
}
|
|
}
|
|
}
|
|
/*
|
|
Compute RSD or AB as required.
|
|
*/
|
|
if ( cr || cab )
|
|
{
|
|
for ( jj = 1; jj <= ju; jj++ )
|
|
{
|
|
j = ju - jj + 1;
|
|
|
|
if ( qraux[j-1] != 0.0 )
|
|
{
|
|
temp = a[j-1+(j-1)*lda];
|
|
a[j-1+(j-1)*lda] = qraux[j-1];
|
|
|
|
if ( cr )
|
|
{
|
|
t = -ddot ( n-j+1, a+j-1+(j-1)*lda, 1, rsd+j-1, 1 )
|
|
/ a[j-1+(j-1)*lda];
|
|
daxpy ( n-j+1, t, a+j-1+(j-1)*lda, 1, rsd+j-1, 1 );
|
|
}
|
|
|
|
if ( cab )
|
|
{
|
|
t = -ddot ( n-j+1, a+j-1+(j-1)*lda, 1, ab+j-1, 1 )
|
|
/ a[j-1+(j-1)*lda];
|
|
daxpy ( n-j+1, t, a+j-1+(j-1)*lda, 1, ab+j-1, 1 );
|
|
}
|
|
a[j-1+(j-1)*lda] = temp;
|
|
}
|
|
}
|
|
}
|
|
|
|
return info;
|
|
}
|
|
/******************************************************************************/
|
|
|
|
/******************************************************************************/
|
|
|
|
void dscal ( int n, double sa, double x[], int incx )
|
|
|
|
/******************************************************************************/
|
|
/*
|
|
Purpose:
|
|
|
|
DSCAL scales a vector by a constant.
|
|
|
|
Licensing:
|
|
|
|
This code is distributed under the GNU LGPL license.
|
|
|
|
Modified:
|
|
|
|
30 March 2007
|
|
|
|
Author:
|
|
|
|
C version by John Burkardt
|
|
|
|
Reference:
|
|
|
|
Jack Dongarra, Cleve Moler, Jim Bunch, Pete Stewart,
|
|
LINPACK User's Guide,
|
|
SIAM, 1979.
|
|
|
|
Charles Lawson, Richard Hanson, David Kincaid, Fred Krogh,
|
|
Basic Linear Algebra Subprograms for Fortran Usage,
|
|
Algorithm 539,
|
|
ACM Transactions on Mathematical Software,
|
|
Volume 5, Number 3, September 1979, pages 308-323.
|
|
|
|
Parameters:
|
|
|
|
Input, int N, the number of entries in the vector.
|
|
|
|
Input, double SA, the multiplier.
|
|
|
|
Input/output, double X[*], the vector to be scaled.
|
|
|
|
Input, int INCX, the increment between successive entries of X.
|
|
*/
|
|
{
|
|
int i;
|
|
int ix;
|
|
int m;
|
|
|
|
if ( n <= 0 )
|
|
{
|
|
}
|
|
else if ( incx == 1 )
|
|
{
|
|
m = n % 5;
|
|
|
|
for ( i = 0; i < m; i++ )
|
|
{
|
|
x[i] = sa * x[i];
|
|
}
|
|
|
|
for ( i = m; i < n; i = i + 5 )
|
|
{
|
|
x[i] = sa * x[i];
|
|
x[i+1] = sa * x[i+1];
|
|
x[i+2] = sa * x[i+2];
|
|
x[i+3] = sa * x[i+3];
|
|
x[i+4] = sa * x[i+4];
|
|
}
|
|
}
|
|
else
|
|
{
|
|
if ( 0 <= incx )
|
|
{
|
|
ix = 0;
|
|
}
|
|
else
|
|
{
|
|
ix = ( - n + 1 ) * incx;
|
|
}
|
|
|
|
for ( i = 0; i < n; i++ )
|
|
{
|
|
x[ix] = sa * x[ix];
|
|
ix = ix + incx;
|
|
}
|
|
}
|
|
return;
|
|
}
|
|
/******************************************************************************/
|
|
|
|
|
|
void dswap ( int n, double x[], int incx, double y[], int incy )
|
|
|
|
/******************************************************************************/
|
|
/*
|
|
Purpose:
|
|
|
|
DSWAP interchanges two vectors.
|
|
|
|
Licensing:
|
|
|
|
This code is distributed under the GNU LGPL license.
|
|
|
|
Modified:
|
|
|
|
30 March 2007
|
|
|
|
Author:
|
|
|
|
C version by John Burkardt
|
|
|
|
Reference:
|
|
|
|
Jack Dongarra, Cleve Moler, Jim Bunch, Pete Stewart,
|
|
LINPACK User's Guide,
|
|
SIAM, 1979.
|
|
|
|
Charles Lawson, Richard Hanson, David Kincaid, Fred Krogh,
|
|
Basic Linear Algebra Subprograms for Fortran Usage,
|
|
Algorithm 539,
|
|
ACM Transactions on Mathematical Software,
|
|
Volume 5, Number 3, September 1979, pages 308-323.
|
|
|
|
Parameters:
|
|
|
|
Input, int N, the number of entries in the vectors.
|
|
|
|
Input/output, double X[*], one of the vectors to swap.
|
|
|
|
Input, int INCX, the increment between successive entries of X.
|
|
|
|
Input/output, double Y[*], one of the vectors to swap.
|
|
|
|
Input, int INCY, the increment between successive elements of Y.
|
|
*/
|
|
{
|
|
int i;
|
|
int ix;
|
|
int iy;
|
|
int m;
|
|
double temp;
|
|
|
|
if ( n <= 0 )
|
|
{
|
|
}
|
|
else if ( incx == 1 && incy == 1 )
|
|
{
|
|
m = n % 3;
|
|
|
|
for ( i = 0; i < m; i++ )
|
|
{
|
|
temp = x[i];
|
|
x[i] = y[i];
|
|
y[i] = temp;
|
|
}
|
|
|
|
for ( i = m; i < n; i = i + 3 )
|
|
{
|
|
temp = x[i];
|
|
x[i] = y[i];
|
|
y[i] = temp;
|
|
|
|
temp = x[i+1];
|
|
x[i+1] = y[i+1];
|
|
y[i+1] = temp;
|
|
|
|
temp = x[i+2];
|
|
x[i+2] = y[i+2];
|
|
y[i+2] = temp;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
if ( 0 <= incx )
|
|
{
|
|
ix = 0;
|
|
}
|
|
else
|
|
{
|
|
ix = ( - n + 1 ) * incx;
|
|
}
|
|
|
|
if ( 0 <= incy )
|
|
{
|
|
iy = 0;
|
|
}
|
|
else
|
|
{
|
|
iy = ( - n + 1 ) * incy;
|
|
}
|
|
|
|
for ( i = 0; i < n; i++ )
|
|
{
|
|
temp = x[ix];
|
|
x[ix] = y[iy];
|
|
y[iy] = temp;
|
|
ix = ix + incx;
|
|
iy = iy + incy;
|
|
}
|
|
|
|
}
|
|
|
|
return;
|
|
}
|
|
/******************************************************************************/
|
|
|
|
/******************************************************************************/
|
|
|
|
double *qr_solve ( int m, int n, double a[], double b[] )
|
|
|
|
/******************************************************************************/
|
|
/*
|
|
Purpose:
|
|
|
|
QR_SOLVE solves a linear system in the least squares sense.
|
|
|
|
Discussion:
|
|
|
|
If the matrix A has full column rank, then the solution X should be the
|
|
unique vector that minimizes the Euclidean norm of the residual.
|
|
|
|
If the matrix A does not have full column rank, then the solution is
|
|
not unique; the vector X will minimize the residual norm, but so will
|
|
various other vectors.
|
|
|
|
Licensing:
|
|
|
|
This code is distributed under the GNU LGPL license.
|
|
|
|
Modified:
|
|
|
|
11 September 2012
|
|
|
|
Author:
|
|
|
|
John Burkardt
|
|
|
|
Reference:
|
|
|
|
David Kahaner, Cleve Moler, Steven Nash,
|
|
Numerical Methods and Software,
|
|
Prentice Hall, 1989,
|
|
ISBN: 0-13-627258-4,
|
|
LC: TA345.K34.
|
|
|
|
Parameters:
|
|
|
|
Input, int M, the number of rows of A.
|
|
|
|
Input, int N, the number of columns of A.
|
|
|
|
Input, double A[M*N], the matrix.
|
|
|
|
Input, double B[M], the right hand side.
|
|
|
|
Output, double QR_SOLVE[N], the least squares solution.
|
|
*/
|
|
{
|
|
double *a_qr;
|
|
int ind;
|
|
int itask;
|
|
int *jpvt;
|
|
int kr;
|
|
int lda;
|
|
double *qraux;
|
|
double *r;
|
|
double tol;
|
|
double *x;
|
|
|
|
a_qr = r8mat_copy_new ( m, n, a );
|
|
lda = m;
|
|
tol = r8_epsilon ( ) / r8mat_amax ( m, n, a_qr );
|
|
x = ( double * ) malloc ( n * sizeof ( double ) );
|
|
jpvt = ( int * ) malloc ( n * sizeof ( int ) );
|
|
qraux = ( double * ) malloc ( n * sizeof ( double ) );
|
|
r = ( double * ) malloc ( m * sizeof ( double ) );
|
|
itask = 1;
|
|
|
|
ind = dqrls ( a_qr, lda, m, n, tol, &kr, b, x, r, jpvt, qraux, itask );
|
|
|
|
free ( a_qr );
|
|
free ( jpvt );
|
|
free ( qraux );
|
|
free ( r );
|
|
|
|
return x;
|
|
}
|
|
/******************************************************************************/
|
|
|
|
#endif
|