Commit 254680c1 authored by Wuttke, Joachim's avatar Wuttke, Joachim
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start new library libransampl

ransampl-1.0, released 15aug13:
Initial release.
The package ransampl is distributed under the FreeBSD License:
Copyright (c) 2013 Joachim Wuttke, Forschungszentrum Juelich GmbH
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pkgconfigdir = $(libdir)/pkgconfig
pkgconfig_DATA = ransampl.pc
SUBDIRS = lib man demo
AC_INIT([ransampl], [1:0], [])
# standard configuration for shared libraries
AM_INIT_AUTOMAKE([foreign]) # don't insert GNU blala files
AC_SUBST(AM_CFLAGS,"-pedantic -Wall -Werror")
AC_CONFIG_HEADERS([config.h]) # to avoid endless -D options
# consistency check: is source code present?
# dependency checks
[AC_MSG_ERROR(GSL header gsl_rng.h not found)])
AC_CHECK_LIB([gsl], [gsl_rng_uniform],,
[AC_MSG_ERROR(libgsl not found or corrupted: missing gsl_rng_uniform)])
# make these Makefiles
AC_CONFIG_FILES([Makefile lib/Makefile man/Makefile demo/Makefile ransampl.pc])
AM_CFLAGS = -I$(srcdir)/../lib
noinst_PROGRAMS = sampling1
sampling1_SOURCES = sampling1.c
AM_LDFLAGS = -lm -L../lib -lransampl
* Library: ransampl (random number sampling)
* File: sampling1.c
* Contents: Draw samples from a given discrete probability distribution
* Note: Any modification of this example should be copied to
* the manual page source ransampl.pod and to the wiki.
* Author: Joachim Wuttke 2013
* Licence: see ../COPYING (FreeBSD)
* Homepage:
#include "ransampl.h"
#include <stdio.h>
int main()
printf( "Precomputing tables ...\n" );
printf( "Drawing samples ...\n" );
printf( "Result (input->output):\n");
return 0;
include_HEADERS = ransampl.h
libransampl_la_SOURCES = ransampl.c ransampl.h
libransampl_la_LDFLAGS = -version-info $(VERSION)
\ No newline at end of file
* Library: ransampl (random number sampling)
* File: ransampl.c
* Contents: Random-number sampling using the Walker-Vose alias method
* Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2013)
* License: see ../COPYING (FreeBSD)
* Homepage:
#include <stdlib.h>
#include <stdio.h>
#include "ransampl.h"
* Library: ransampl (random number sampling)
* File: ransampl.h
* Contents: Random-number sampling using the Walker-Vose alias method
* Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2013)
* License: see ../COPYING (FreeBSD)
* Homepage:
#ifndef RANSAMPL_H
#define RANSAMPL_H
#ifdef __cplusplus
extern "C" {
#ifdef __cplusplus
#endif /* RANSAMPL_H */
man_MANS = ransampl.3
noinst_DATA = ransampl.html
%.3 : %.pod
pod2man -s 3 -c "ransampl manual" -n "$*" $< > $@
%.html : %.pod
pod2html --title="ransampl: a C library for random number sampling" --noindex $< > $@
=begin html
<link rel="stylesheet" href="podstyle.css" type="text/css" />
=end html
=head1 NAME
lmmin - Levenberg-Marquardt least-squares minimization
B<#include <lmmin.h>>
B<void lmmin( int> I<n_par>B<, double *>I<par>B<, int> I<m_dat>B<, constS< >void *>I<data>B<,
void *>I<evaluate>B<(
constS< >double *>I<par>B<, int >I<m_dat>B<,
constS< >void *>I<data>B<, double *>I<fvec>B<, int *>I<userbreak>B<),
constS< >lm_control_struct *>I<control>B<,
lm_status_struct *>I<status>B< );>
B<extern const lm_control_struct lm_control_double;>
B<extern const lm_control_struct lm_control_float;>
B<extern const char *lm_infmsg[];>
B<extern const char *lm_shortmsg[];>
B<lmmin()> determines a vector I<par> that minimizes the sum of squared elements of a vector I<fvec> that is computed by a user-supplied function I<evaluate>().
On success, I<par> represents a local minimum, not necessarily a global one; it may depend on its starting value.
For applications in curve fitting, the wrapper function B<lmcurve(3)> offers a simplified API.
The Levenberg-Marquardt minimization starts with a steepest-descent exploration of the parameter space, and achieves rapid convergence by crossing over into the Newton-Gauss method. For more background, see Moré 1978, Madsen et al. 2004, and comments in the source code.
Function arguments:
=item I<n_par>
Number of free variables. Dimension of parameter vector I<par>.
=item I<par>
Parameter vector. On input, it must contain a reasonable guess; on output, it contains the solution found to minimize ||I<fvec>||.
=item I<m_dat>
Dimension of vector I<fvec>.
Must statisfy I<n_par> <= I<m_dat>.
=item I<data>
This pointer is ignored by the fit algorithm,
except for appearing as an argument in all calls to the user-supplied
routines I<evaluate> and I<printout>.
=item I<evaluate>
Pointer to a user-supplied function that computes I<m_dat> elements of vector I<fvec> for a given parameter vector I<par>. If I<evaluate> return with *I<userbreak> set to a negative value, B<lmmin()> will interrupt the fitting and terminate.
=item I<printout>
A function that prints messages about the fit progress. Legitimate values of this pointer argument are NULL (to indicate that no messages are wanted), &I<lm_printout_std> (pointer to a default implementation), or a pointer to a user-supplied function.
=item I<control>
Parameter collection for tuning the fit procedure.
In most cases, the default &I<lm_control_double> is adequate.
If I<f> is only computed with single-precision accuracy,
I<&lm_control_float> should be used.
See also below, NOTES on initializing parameter records.
I<control> has the following members (for more details, see the source file I<lmstruct.h>):
=item B<double> I<control.ftol>
Relative error desired in the sum of squares; recommended setting: somewhat above machine precision; less if I<fvec> is computed with reduced accuracy.
=item B<double> I<control.xtol>
Relative error between last two approximations; recommended setting: as I<ftol>.
=item B<double> I<control.gtol>
A measure for degeneracy; recommended setting: as I<ftol>.
=item B<double> I<control.epsilon>
Step used to calculate the Jacobian; recommended setting: as I<ftol>, but definitely less than the accuracy of I<fvec>.
=item B<double> I<control.stepbound>