NAG C Library Function Document

nag_zero_nonlin_eqns_deriv_rcomm (c05rdc)

1
Purpose

nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) is a comprehensive reverse communication function that finds a solution of a system of nonlinear equations by a modification of the Powell hybrid method. You must provide the Jacobian.

2
Specification

#include <nag.h>
#include <nagc05.h>
void  nag_zero_nonlin_eqns_deriv_rcomm (Integer *irevcm, Integer n, double x[], double fvec[], double fjac[], double xtol, Nag_ScaleType scale_mode, double diag[], double factor, double r[], double qtf[], Integer iwsav[], double rwsav[], NagError *fail)

3
Description

The system of equations is defined as:
fi x1,x2,,xn = 0 ,   i= 1, 2, , n .  
nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) is based on the MINPACK routine HYBRJ (see Moré et al. (1980)). It chooses the correction at each step as a convex combination of the Newton and scaled gradient directions. The Jacobian is updated by the rank-1 method of Broyden. For more details see Powell (1970).

4
References

Moré J J, Garbow B S and Hillstrom K E (1980) User guide for MINPACK-1 Technical Report ANL-80-74 Argonne National Laboratory
Powell M J D (1970) A hybrid method for nonlinear algebraic equations Numerical Methods for Nonlinear Algebraic Equations (ed P Rabinowitz) Gordon and Breach

5
Arguments

Note: this function uses reverse communication. Its use involves an initial entry, intermediate exits and re-entries, and a final exit, as indicated by the argument irevcm. Between intermediate exits and re-entries, all arguments other than fvec and fjac must remain unchanged.
1:     irevcm Integer *Input/Output
On initial entry: must have the value 0.
On intermediate exit: specifies what action you must take before re-entering nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) with irevcm unchanged. The value of irevcm should be interpreted as follows:
irevcm=1
Indicates the start of a new iteration. No action is required by you, but x and fvec are available for printing.
irevcm=2
Indicates that before re-entry to nag_zero_nonlin_eqns_deriv_rcomm (c05rdc), fvec must contain the function values fix .
irevcm=3
Indicates that before re-entry to nag_zero_nonlin_eqns_deriv_rcomm (c05rdc), fjac[j-1×n+i-1]  must contain the value of fi xj  at the point x, for i=1,2,,n and j=1,2,,n.
On final exit: irevcm=0 and the algorithm has terminated.
Constraint: irevcm=0, 1, 2 or 3.
Note: any values you return to nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) as part of the reverse communication procedure should not include floating-point NaN (Not a Number) or infinity values, since these are not handled by nag_zero_nonlin_eqns_deriv_rcomm (c05rdc). If your code inadvertently does return any NaNs or infinities, nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) is likely to produce unexpected results.
2:     n IntegerInput
On entry: n, the number of equations.
Constraint: n>0 .
3:     x[n] doubleInput/Output
On initial entry: an initial guess at the solution vector.
On intermediate exit: contains the current point.
On final exit: the final estimate of the solution vector.
4:     fvec[n] doubleInput/Output
On initial entry: need not be set.
On intermediate re-entry: if irevcm2 , fvec must not be changed.
If irevcm=2 , fvec must be set to the values of the functions computed at the current point x.
On final exit: the function values at the final point, x.
5:     fjac[n×n] doubleInput/Output
Note: the i,jth element of the matrix is stored in fjac[j-1×n+i-1].
On initial entry: need not be set.
On intermediate re-entry: if irevcm3 , fjac must not be changed.
If irevcm=3 , fjac[j-1×n+i-1]  must contain the value of fi xj  at the point x, for i=1,2,,n and j=1,2,,n.
On final exit: the orthogonal matrix Q produced by the QR  factorization of the final approximate Jacobian, stored by columns.
6:     xtol doubleInput
On initial entry: the accuracy in x to which the solution is required.
Suggested value: ε, where ε is the machine precision returned by nag_machine_precision (X02AJC).
Constraint: xtol0.0 .
7:     scale_mode Nag_ScaleTypeInput
On initial entry: indicates whether or not you have provided scaling factors in diag.
If scale_mode=Nag_ScaleProvided, the scaling must have been supplied in diag.
Otherwise, if scale_mode=Nag_NoScaleProvided, the variables will be scaled internally.
Constraint: scale_mode=Nag_NoScaleProvided or Nag_ScaleProvided.
8:     diag[n] doubleInput/Output
On initial entry: if scale_mode=Nag_ScaleProvided, diag must contain multiplicative scale factors for the variables.
If scale_mode=Nag_NoScaleProvided, diag need not be set.
Constraint: if scale_mode=Nag_ScaleProvided, diag[i-1]>0.0 , for i=1,2,,n.
On intermediate exit: diag must not be changed.
On final exit: the scale factors actually used (computed internally if scale_mode=Nag_NoScaleProvided).
9:     factor doubleInput
On initial entry: a quantity to be used in determining the initial step bound. In most cases, factor should lie between 0.1 and 100.0. (The step bound is factor×diag×x2  if this is nonzero; otherwise the bound is factor.)
Suggested value: factor=100.0 .
Constraint: factor>0.0 .
10:   r[n×n+1/2] doubleInput/Output
On initial entry: need not be set.
On intermediate exit: must not be changed.
On final exit: the upper triangular matrix R produced by the QR  factorization of the final approximate Jacobian, stored row-wise.
11:   qtf[n] doubleInput/Output
On initial entry: need not be set.
On intermediate exit: must not be changed.
On final exit: the vector QTf .
12:   iwsav[17] IntegerCommunication Array
13:   rwsav[4×n+10] doubleCommunication Array
The arrays iwsav and rwsav MUST NOT be altered between calls to nag_zero_nonlin_eqns_deriv_rcomm (c05rdc).
14:   fail NagError *Input/Output
The NAG error argument (see Section 3.7 in How to Use the NAG Library and its Documentation).

6
Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 2.3.1.2 in How to Use the NAG Library and its Documentation for further information.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_DIAG_ELEMENTS
On entry, scale_mode=Nag_ScaleProvided and diag contained a non-positive element.
NE_INT
On entry, irevcm=value.
Constraint: irevcm=0, 1, 2 or 3.
On entry, n=value.
Constraint: n>0.
NE_INTERNAL_ERROR
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 2.7.6 in How to Use the NAG Library and its Documentation for further information.
NE_NO_IMPROVEMENT
The iteration is not making good progress, as measured by the improvement from the last value iterations. This failure exit may indicate that the system does not have a zero, or that the solution is very close to the origin (see Section 7). Otherwise, rerunning nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) from a different starting point may avoid the region of difficulty.
The iteration is not making good progress, as measured by the improvement from the last value Jacobian evaluations. This failure exit may indicate that the system does not have a zero, or that the solution is very close to the origin (see Section 7). Otherwise, rerunning nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) from a different starting point may avoid the region of difficulty.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 2.7.5 in How to Use the NAG Library and its Documentation for further information.
NE_REAL
On entry, factor=value.
Constraint: factor>0.0.
On entry, xtol=value.
Constraint: xtol0.0.
NE_TOO_SMALL
No further improvement in the solution is possible. xtol is too small: xtol=value.

7
Accuracy

If x^  is the true solution and D denotes the diagonal matrix whose entries are defined by the array diag, then nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) tries to ensure that
D x-x^ 2 xtol × D x^ 2 .  
If this condition is satisfied with xtol = 10-k , then the larger components of Dx  have k significant decimal digits. There is a danger that the smaller components of Dx  may have large relative errors, but the fast rate of convergence of nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) usually obviates this possibility.
If xtol is less than machine precision and the above test is satisfied with the machine precision in place of xtol, then the function exits with fail.code= NE_TOO_SMALL.
Note:  this convergence test is based purely on relative error, and may not indicate convergence if the solution is very close to the origin.
The convergence test assumes that the functions and the Jacobian are coded consistently and that the functions are reasonably well behaved. If these conditions are not satisfied, then nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) may incorrectly indicate convergence. The coding of the Jacobian can be checked using nag_check_derivs (c05zdc). If the Jacobian is coded correctly, then the validity of the answer can be checked by rerunning nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) with a lower value for xtol.

8
Parallelism and Performance

nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the x06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9
Further Comments

The time required by nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) to solve a given problem depends on n, the behaviour of the functions, the accuracy requested and the starting point. The number of arithmetic operations executed by nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) is approximately 11.5×n2  to process each evaluation of the functions and approximately 1.3×n3  to process each evaluation of the Jacobian. The timing of nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) is strongly influenced by the time spent evaluating the functions.
Ideally the problem should be scaled so that, at the solution, the function values are of comparable magnitude.

10
Example

This example determines the values x1 , , x9  which satisfy the tridiagonal equations:
3-2x1x1-2x2 = -1, -xi-1+3-2xixi-2xi+1 = -1,  i=2,3,,8 -x8+3-2x9x9 = -1.  

10.1
Program Text

Program Text (c05rdce.c)

10.2
Program Data

None.

10.3
Program Results

Program Results (c05rdce.r)