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Always turn off hyphenation; it makes .\" way too many mistakes in technical documents. .if n .ad l .nh .SH "NAME" lmcurve \- Levenberg\-Marquardt least\-squares fit of a curve (t,y) .SH "SYNOPSIS" .IX Header "SYNOPSIS" \&\fB#include <lmcurve.h\fR> .PP \&\fBvoid lmcurve( const int\fR \fIn_par\fR\fB, double *\fR\fIpar\fR\fB, const int\fR \fIm_dat\fR\fB, const\ double *\fR\fIt\fR\fB, const\ double *\fR\fIy\fR\fB, double (*\fR\fIf\fR\fB)( const double \fR\fIti\fR\fB, const double *\fR\fIpar\fR\fB ), const\ lm_control_struct *\fR\fIcontrol\fR\fB, lm_status_struct *\fR\fIstatus\fR\fB);\fR .PP \&\fBvoid lmcurve_tyd( const int\fR \fIn_par\fR\fB, double *\fR\fIpar\fR\fB, const int\fR \fIm_dat\fR\fB, const\ double *\fR\fIt\fR\fB, const\ double *\fR\fIy\fR\fB, const\ double *\fR\fIdy\fR\fB, double (*\fR\fIf\fR\fB)( const double \fR\fIti\fR\fB, const double *\fR\fIpar\fR\fB ), const\ lm_control_struct *\fR\fIcontrol\fR\fB, lm_status_struct *\fR\fIstatus\fR\fB);\fR .PP \&\fBextern const lm_control_struct lm_control_double;\fR .PP \&\fBextern const lm_control_struct lm_control_float;\fR .PP \&\fBextern const char *lm_infmsg[];\fR .PP \&\fBextern const char *lm_shortmsg[];\fR .SH "DESCRIPTION" .IX Header "DESCRIPTION" \&\fB\f(BIlmcurve()\fB\fR and \fB\f(BIlmcurve_tyd()\fB\fR wrap the more generic minimization function \fB\f(BIlmmin()\fB\fR, for use in curve fitting. .PP \&\fB\f(BIlmcurve()\fB\fR determines a vector \fIpar\fR that minimizes the sum of squared elements of a residue vector \fIr\fR[i] := \fIy\fR[i] \- \fIf\fR(\fIt\fR[i];\fIpar\fR). Typically, \fB\f(BIlmcurve()\fB\fR is used to approximate a data set \fIt\fR,\fIy\fR by a parametric function \fIf\fR(\fIti\fR;\fIpar\fR). On success, \fIpar\fR represents a local minimum, not necessarily a global one; it may depend on its starting value. .PP \&\fB\f(BIlmcurve_tyd()\fB\fR does the same for a data set \fIt\fR,\fIy\fR,\fIdy\fR, where \fIdy\fR represents the standard deviation of empirical data \fIy\fR. Residues are computed as \fIr\fR[i] := (\fIy\fR[i] \- \fIf\fR(\fIt\fR[i];\fIpar\fR))/\fIdy\fR[i]. Users must ensure that all \fIdy\fR[i] are positive. .PP Function arguments: .IP "\fIn_par\fR" 4 .IX Item "n_par" Number of free variables. Length of parameter vector \fIpar\fR. .IP "\fIpar\fR" 4 .IX Item "par" Parameter vector. On input, it must contain a reasonable guess. On output, it contains the solution found to minimize ||\fIr\fR||. .IP "\fIm_dat\fR" 4 .IX Item "m_dat" Number of data points. Length of vectors \fIt\fR and \fIy\fR. Must statisfy \fIn_par\fR <= \fIm_dat\fR. .IP "\fIt\fR" 4 .IX Item "t" Array of length \fIm_dat\fR. Contains the abcissae (time, or \*(L"x\*(R") for which function \fIf\fR will be evaluated. .IP "\fIy\fR" 4 .IX Item "y" Array of length \fIm_dat\fR. Contains the ordinate values that shall be fitted. .IP "\fIdy\fR" 4 .IX Item "dy" Only in \fB\f(BIlmcurve_tyd()\fB\fR. Array of length \fIm_dat\fR. Contains the standard deviations of the values \fIy\fR. .IP "\fIf\fR" 4 .IX Item "f" A user-supplied parametric function \fIf\fR(ti;\fIpar\fR). .IP "\fIcontrol\fR" 4 .IX Item "control" Parameter collection for tuning the fit procedure. In most cases, the default &\fIlm_control_double\fR is adequate. If \fIf\fR is only computed with single-precision accuracy, \&\fI&lm_control_float\fR should be used. Parameters are explained in \fB\f(BIlmmin\fB\|(3)\fR. .IP "\fIstatus\fR" 4 .IX Item "status" A record used to return information about the minimization process: For details, see \fB\f(BIlmmin\fB\|(3)\fR. .SH "EXAMPLE" .IX Header "EXAMPLE" Fit a data set y(x) by a curve f(x;p): .PP .Vb 2 \& #include "lmcurve.h" \& #include <stdio.h> \& \& /* model function: a parabola */ \& \& double f( double t, const double *p ) \& { \& return p[0] + p[1]*t + p[2]*t*t; \& } \& \& int main() \& { \& int n = 3; /* number of parameters in model function f */ \& double par[3] = { 100, 0, \-10 }; /* really bad starting value */ \& \& /* data points: a slightly distorted standard parabola */ \& int m = 9; \& int i; \& double t[9] = { \-4., \-3., \-2., \-1., 0., 1., 2., 3., 4. }; \& double y[9] = { 16.6, 9.9, 4.4, 1.1, 0., 1.1, 4.2, 9.3, 16.4 }; \& \& lm_control_struct control = lm_control_double; \& lm_status_struct status; \& control.verbosity = 7; \& \& printf( "Fitting ...\en" ); \& lmcurve( n, par, m, t, y, f, &control, &status ); \& \& printf( "Results:\en" ); \& printf( "status after %d function evaluations:\en %s\en", \& status.nfev, lm_infmsg[status.outcome] ); \& \& printf("obtained parameters:\en"); \& for ( i = 0; i < n; ++i) \& printf(" par[%i] = %12g\en", i, par[i]); \& printf("obtained norm:\en %12g\en", status.fnorm ); \& \& printf("fitting data as follows:\en"); \& for ( i = 0; i < m; ++i) \& printf( " t[%2d]=%4g y=%6g fit=%10g residue=%12g\en", \& i, t[i], y[i], f(t[i],par), y[i] \- f(t[i],par) ); \& \& return 0; \& } .Ve .SH "COPYING" .IX Header "COPYING" Copyright (C) 2009\-2015 Joachim Wuttke, Forschungszentrum Juelich GmbH .PP Software: FreeBSD License .PP Documentation: Creative Commons Attribution Share Alike .SH "SEE ALSO" .IX Header "SEE ALSO" \fBlmmin\fR(3) .PP Homepage: http://apps.jcns.fz\-juelich.de/lmfit .SH "BUGS" .IX Header "BUGS" Please send bug reports and suggestions to the author <j.wuttke@fz\-juelich.de>.