10. Sun FDLIBM (Freely Distributable Maths Library)
11. Random123
12. md5
+13. lmfit
Our chosen method for packaging distributions (CPack) only permits a
package to have a single license file, so we are unfortunately forced
L. Peter Deutsch
ghost@aladdin.com
+
+13. lmfit
+============================================
+The package lmfit is distributed under the FreeBSD License:
+
+--
+ Copyright (c) 1980-1999 University of Chicago,
+ as operator of Argonne National Laboratory
+ Copyright (c) 2004-2013 Joachim Wuttke, Forschungszentrum Juelich GmbH
+
+ All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are met:
+
+ - Redistributions of source code must retain the above copyright notice,
+ this list of conditions and the following disclaimer.
+ - Redistributions in binary form must reproduce the above copyright notice,
+ this list of conditions and the following disclaimer in the documentation
+ and/or other materials provided with the distribution.
+
+ This software is provided by the copyright holders and contributors "as is"
+ and any express or implied warranties, including, but not limited to, the
+ implied warranties of merchantability and fitness for a particular purpose
+ are disclaimed. In no event shall the copyright holder or contributors
+ be liable for any direct, indirect, incidental, special, exemplary, or
+ consequential damages (including, but not limited to, procurement of
+ substitute goods or services; loss of use, data, or profits; or business
+ interruption) however caused and on any theory of liability, whether in
+ contract, strict liability, or tort (including negligence or otherwise)
+ arising in any way out of the use of this software, even if advised of the
+ possibility of such damage.
+--
fun:make_unsp
fun:nsc_dclm_pbc
}
-
+{
+ libgomp
+ Memcheck:Leak
+ ...
+ obj:*/libgomp.so*
+}
{
ctime_r
Memcheck:Leak
...
fun:ctime_r
}
-
{
libz
Memcheck:Cond
...
fun:__kmpc_global_thread_num
}
+
--- /dev/null
+This directory contains only the barebone version of the
+lmfit package, version 5.1. Full version is available from
+http://apps.jcns.fz-juelich.de/doku/sc/lmfit
+
+License in gromacs root directory in file COPYING
--- /dev/null
+/*
+ * Library: lmfit (Levenberg-Marquardt least squares fitting)
+ *
+ * File: lmcurve.c
+ *
+ * Contents: Levenberg-Marquardt curve-fitting
+ *
+ * Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2004-2013)
+ *
+ * License: see ../COPYING (FreeBSD)
+ *
+ * Homepage: apps.jcns.fz-juelich.de/lmfit
+ */
+
+#include "lmmin.h"
+#include "gromacs/utility/basedefinitions.h"
+
+typedef struct {
+ const double *t;
+ const double *y;
+ double (*f)(double t, const double *par);
+} lmcurve_data_struct;
+
+
+void lmcurve_evaluate( const double *par, int m_dat, const void *data,
+ double *fvec, gmx_unused int *info )
+{
+ int i;
+ for (i = 0; i < m_dat; i++)
+ {
+ fvec[i] =
+ ((lmcurve_data_struct*)data)->y[i] -
+ ((lmcurve_data_struct*)data)->f(
+ ((lmcurve_data_struct*)data)->t[i], par );
+ }
+}
+
+
+void lmcurve( int n_par, double *par, int m_dat,
+ const double *t, const double *y,
+ double (*f)( double t, const double *par ),
+ const lm_control_struct *control,
+ lm_status_struct *status )
+{
+ lmcurve_data_struct data;
+ data.t = t;
+ data.y = y;
+ data.f = f;
+
+ lmmin( n_par, par, m_dat, (const void*) &data,
+ lmcurve_evaluate, control, status );
+}
--- /dev/null
+/*
+ * Library: lmfit (Levenberg-Marquardt least squares fitting)
+ *
+ * File: lmcurve.h
+ *
+ * Contents: Declarations for Levenberg-Marquardt curve fitting.
+ *
+ * Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2004-2013)
+ *
+ * License: see ../COPYING (FreeBSD)
+ *
+ * Homepage: apps.jcns.fz-juelich.de/lmfit
+ */
+
+#ifndef LMCURVE_H
+#define LMCURVE_H
+#undef __BEGIN_DECLS
+#undef __END_DECLS
+#ifdef __cplusplus
+# define __BEGIN_DECLS extern "C" {
+# define __END_DECLS }
+#else
+# define __BEGIN_DECLS /* empty */
+# define __END_DECLS /* empty */
+#endif
+
+#include "lmstruct.h"
+
+__BEGIN_DECLS
+
+void lmcurve( int n_par, double *par, int m_dat,
+ const double *t, const double *y,
+ double (*f)( double t, const double *par ),
+ const lm_control_struct *control,
+ lm_status_struct *status );
+
+__END_DECLS
+#endif /* LMCURVE_H */
--- /dev/null
+/*
+ * Library: lmfit (Levenberg-Marquardt least squares fitting)
+ *
+ * File: lmmin.c
+ *
+ * Contents: Levenberg-Marquardt minimization.
+ *
+ * Copyright: MINPACK authors, The University of Chikago (1980-1999)
+ * Joachim Wuttke, Forschungszentrum Juelich GmbH (2004-2013)
+ *
+ * License: see ../COPYING (FreeBSD)
+ *
+ * Homepage: apps.jcns.fz-juelich.de/lmfit
+ */
+
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <float.h>
+#include "lmmin.h"
+
+#define MIN(a, b) (((a) <= (b)) ? (a) : (b))
+#define MAX(a, b) (((a) >= (b)) ? (a) : (b))
+#define SQR(x) (x)*(x)
+
+/* function declarations (implemented below). */
+void lm_lmpar( int n, double *r, int ldr, int *ipvt, double *diag,
+ double *qtb, double delta, double *par, double *x,
+ double *sdiag, double *aux, double *xdi );
+void lm_qrfac( int m, int n, double *a, int *ipvt,
+ double *rdiag, double *acnorm, double *wa );
+void lm_qrsolv( int n, double *r, int ldr, int *ipvt, double *diag,
+ double *qtb, double *x, double *sdiag, double *wa );
+
+
+/*****************************************************************************/
+/* Numeric constants */
+/*****************************************************************************/
+
+/* machine-dependent constants from float.h */
+#define LM_MACHEP DBL_EPSILON /* resolution of arithmetic */
+#define LM_DWARF DBL_MIN /* smallest nonzero number */
+#define LM_SQRT_DWARF sqrt(DBL_MIN) /* square should not underflow */
+#define LM_SQRT_GIANT sqrt(DBL_MAX) /* square should not overflow */
+#define LM_USERTOL 30*LM_MACHEP /* users are recommended to require this */
+
+/* If the above values do not work, the following seem good for an x86:
+ LM_MACHEP .555e-16
+ LM_DWARF 9.9e-324
+ LM_SQRT_DWARF 1.e-160
+ LM_SQRT_GIANT 1.e150
+ LM_USER_TOL 1.e-14
+ The following values should work on any machine:
+ LM_MACHEP 1.2e-16
+ LM_DWARF 1.0e-38
+ LM_SQRT_DWARF 3.834e-20
+ LM_SQRT_GIANT 1.304e19
+ LM_USER_TOL 1.e-14
+ */
+
+const lm_control_struct lm_control_double = {
+ LM_USERTOL, LM_USERTOL, LM_USERTOL, LM_USERTOL, 100., 100, 1,
+ NULL, 0, -1, -1
+};
+const lm_control_struct lm_control_float = {
+ 1.e-7, 1.e-7, 1.e-7, 1.e-7, 100., 100, 1,
+ NULL, 0, -1, -1
+};
+
+
+/*****************************************************************************/
+/* Message texts (indexed by status.info) */
+/*****************************************************************************/
+
+const char *lm_infmsg[] = {
+ "found zero (sum of squares below underflow limit)",
+ "converged (the relative error in the sum of squares is at most tol)",
+ "converged (the relative error of the parameter vector is at most tol)",
+ "converged (both errors are at most tol)",
+ "trapped (by degeneracy; increasing epsilon might help)",
+ "exhausted (number of function calls exceeding preset patience)",
+ "failed (ftol<tol: cannot reduce sum of squares any further)",
+ "failed (xtol<tol: cannot improve approximate solution any further)",
+ "failed (gtol<tol: cannot improve approximate solution any further)",
+ "crashed (not enough memory)",
+ "exploded (fatal coding error: improper input parameters)",
+ "stopped (break requested within function evaluation)"
+};
+
+const char *lm_shortmsg[] = {
+ "found zero",
+ "converged (f)",
+ "converged (p)",
+ "converged (2)",
+ "degenerate",
+ "call limit",
+ "failed (f)",
+ "failed (p)",
+ "failed (o)",
+ "no memory",
+ "invalid input",
+ "user break"
+};
+
+
+/*****************************************************************************/
+/* Monitoring auxiliaries. */
+/*****************************************************************************/
+
+void lm_print_pars( int nout, const double *par, double fnorm, FILE* fout )
+{
+ int i;
+ for (i = 0; i < nout; ++i)
+ {
+ fprintf( fout, " %16.9g", par[i] );
+ }
+ fprintf( fout, " => %18.11g\n", fnorm );
+}
+
+
+/*****************************************************************************/
+/* lmmin (main minimization routine) */
+/*****************************************************************************/
+
+void lmmin( int n, double *x, int m, const void *data,
+ void (*evaluate) (const double *par, int m_dat, const void *data,
+ double *fvec, int *userbreak),
+ const lm_control_struct *C, lm_status_struct *S )
+{
+ double *fvec, *diag, *fjac, *qtf, *wa1, *wa2, *wa3, *wf;
+ int *ipvt;
+ int j, i;
+ double actred, dirder, fnorm, fnorm1, gnorm, pnorm,
+ prered, ratio, step, sum, temp, temp1, temp2, temp3;
+ static double p0001 = 1.0e-4;
+
+ int maxfev = C->patience * (n+1);
+
+ int outer, inner; /* loop counters, for monitoring */
+ int inner_success; /* flag for loop control */
+ double lmpar = 0; /* Levenberg-Marquardt parameter */
+ double delta = 0;
+ double xnorm = 0;
+ double eps = sqrt(MAX(C->epsilon, LM_MACHEP)); /* for forward differences */
+
+ int nout = C->n_maxpri == -1 ? n : MIN( C->n_maxpri, n );
+
+ /* The workaround msgfile=NULL is needed for default initialization */
+ FILE* msgfile = C->msgfile ? C->msgfile : stdout;
+
+ /* Default status info; must be set ahead of first return statements */
+ S->outcome = 0; /* status code */
+ S->userbreak = 0;
+ S->nfev = 0; /* function evaluation counter */
+
+/*** Check input parameters for errors. ***/
+
+ if (n <= 0)
+ {
+ fprintf( stderr, "lmmin: invalid number of parameters %i\n", n );
+ S->outcome = 10; /* invalid parameter */
+ return;
+ }
+ if (m < n)
+ {
+ fprintf( stderr, "lmmin: number of data points (%i) "
+ "smaller than number of parameters (%i)\n", m, n );
+ S->outcome = 10;
+ return;
+ }
+ if (C->ftol < 0. || C->xtol < 0. || C->gtol < 0.)
+ {
+ fprintf( stderr,
+ "lmmin: negative tolerance (at least one of %g %g %g)\n",
+ C->ftol, C->xtol, C->gtol );
+ S->outcome = 10;
+ return;
+ }
+ if (maxfev <= 0)
+ {
+ fprintf( stderr, "lmmin: nonpositive function evaluations limit %i\n",
+ maxfev );
+ S->outcome = 10;
+ return;
+ }
+ if (C->stepbound <= 0.)
+ {
+ fprintf( stderr, "lmmin: nonpositive stepbound %g\n", C->stepbound );
+ S->outcome = 10;
+ return;
+ }
+ if (C->scale_diag != 0 && C->scale_diag != 1)
+ {
+ fprintf( stderr, "lmmin: logical variable scale_diag=%i, "
+ "should be 0 or 1\n", C->scale_diag );
+ S->outcome = 10;
+ return;
+ }
+
+/*** Allocate work space. ***/
+ fvec = diag = fjac = qtf = wa1 = wa2 = wa3 = wf = NULL;
+ ipvt = NULL;
+ if ( (fvec = (double *) malloc(m * sizeof(double))) == NULL ||
+ (diag = (double *) malloc(n * sizeof(double))) == NULL ||
+ (qtf = (double *) malloc(n * sizeof(double))) == NULL ||
+ (fjac = (double *) malloc(n*m*sizeof(double))) == NULL ||
+ (wa1 = (double *) malloc(n * sizeof(double))) == NULL ||
+ (wa2 = (double *) malloc(n * sizeof(double))) == NULL ||
+ (wa3 = (double *) malloc(n * sizeof(double))) == NULL ||
+ (wf = (double *) malloc(m * sizeof(double))) == NULL ||
+ (ipvt = (int *) malloc(n * sizeof(int) )) == NULL)
+ {
+ S->outcome = 9;
+ if (NULL != fvec)
+ {
+ free(fvec);
+ }
+ if (NULL != diag)
+ {
+ free(diag);
+ }
+ if (NULL != qtf)
+ {
+ free(qtf);
+ }
+ if (NULL != fjac)
+ {
+ free(fjac);
+ }
+ if (NULL != wa1)
+ {
+ free(wa1);
+ }
+ if (NULL != wa2)
+ {
+ free(wa2);
+ }
+ if (NULL != wa3)
+ {
+ free(wa3);
+ }
+ if (NULL != wf)
+ {
+ free(wf);
+ }
+ if (NULL != ipvt)
+ {
+ free(ipvt);
+ }
+ return;
+ }
+
+ if (!C->scale_diag)
+ {
+ for (j = 0; j < n; j++)
+ {
+ diag[j] = 1.;
+ }
+ }
+
+/*** Evaluate function at starting point and calculate norm. ***/
+
+ (*evaluate)( x, m, data, fvec, &(S->userbreak) );
+ S->nfev = 1;
+ if (S->userbreak)
+ {
+ goto terminate;
+ }
+ fnorm = lm_enorm(m, fvec);
+ if (C->verbosity)
+ {
+ fprintf( msgfile, "lmmin start " );
+ lm_print_pars( nout, x, fnorm, msgfile );
+ }
+ if (fnorm <= LM_DWARF)
+ {
+ S->outcome = 0; /* sum of squares almost zero, nothing to do */
+ goto terminate;
+ }
+
+/*** The outer loop: compute gradient, then descend. ***/
+
+ for (outer = 0;; ++outer)
+ {
+
+/*** [outer] Calculate the Jacobian. ***/
+
+ for (j = 0; j < n; j++)
+ {
+ temp = x[j];
+ step = MAX(eps*eps, eps * fabs(temp));
+ x[j] += step; /* replace temporarily */
+ (*evaluate)( x, m, data, wf, &(S->userbreak) );
+ ++(S->nfev);
+ if (S->userbreak)
+ {
+ goto terminate;
+ }
+ for (i = 0; i < m; i++)
+ {
+ fjac[j*m+i] = (wf[i] - fvec[i]) / step;
+ }
+ x[j] = temp; /* restore */
+ }
+ if (C->verbosity >= 10)
+ {
+ /* print the entire matrix */
+ printf("\nlmmin Jacobian\n");
+ for (i = 0; i < m; i++)
+ {
+ printf(" ");
+ for (j = 0; j < n; j++)
+ {
+ printf("%.5e ", fjac[j*m+i]);
+ }
+ printf("\n");
+ }
+ }
+
+/*** [outer] Compute the QR factorization of the Jacobian. ***/
+
+/* fjac is an m by n array. The upper n by n submatrix of fjac
+ * is made to contain an upper triangular matrix r with diagonal
+ * elements of nonincreasing magnitude such that
+ *
+ * p^T*(jac^T*jac)*p = r^T*r
+ *
+ * (NOTE: ^T stands for matrix transposition),
+ *
+ * where p is a permutation matrix and jac is the final calculated
+ * Jacobian. Column j of p is column ipvt(j) of the identity matrix.
+ * The lower trapezoidal part of fjac contains information generated
+ * during the computation of r.
+ *
+ * ipvt is an integer array of length n. It defines a permutation
+ * matrix p such that jac*p = q*r, where jac is the final calculated
+ * Jacobian, q is orthogonal (not stored), and r is upper triangular
+ * with diagonal elements of nonincreasing magnitude. Column j of p
+ * is column ipvt(j) of the identity matrix.
+ */
+
+ lm_qrfac(m, n, fjac, ipvt, wa1, wa2, wa3);
+ /* return values are ipvt, wa1=rdiag, wa2=acnorm */
+
+/*** [outer] Form q^T * fvec and store first n components in qtf. ***/
+
+ for (i = 0; i < m; i++)
+ {
+ wf[i] = fvec[i];
+ }
+
+ for (j = 0; j < n; j++)
+ {
+ temp3 = fjac[j*m+j];
+ if (temp3 != 0.)
+ {
+ sum = 0;
+ for (i = j; i < m; i++)
+ {
+ sum += fjac[j*m+i] * wf[i];
+ }
+ temp = -sum / temp3;
+ for (i = j; i < m; i++)
+ {
+ wf[i] += fjac[j*m+i] * temp;
+ }
+ }
+ fjac[j*m+j] = wa1[j];
+ qtf[j] = wf[j];
+ }
+
+/*** [outer] Compute norm of scaled gradient and detect degeneracy. ***/
+
+ gnorm = 0;
+ for (j = 0; j < n; j++)
+ {
+ if (wa2[ipvt[j]] == 0)
+ {
+ continue;
+ }
+ sum = 0.;
+ for (i = 0; i <= j; i++)
+ {
+ sum += fjac[j*m+i] * qtf[i];
+ }
+ gnorm = MAX( gnorm, fabs( sum / wa2[ipvt[j]] / fnorm ) );
+ }
+
+ if (gnorm <= C->gtol)
+ {
+ S->outcome = 4;
+ goto terminate;
+ }
+
+/*** [outer] Initialize / update diag and delta. ***/
+
+ if (!outer)
+ {
+ /* first iteration only */
+ if (C->scale_diag)
+ {
+ /* diag := norms of the columns of the initial Jacobian */
+ for (j = 0; j < n; j++)
+ {
+ diag[j] = wa2[j] ? wa2[j] : 1;
+ }
+ /* xnorm := || D x || */
+ for (j = 0; j < n; j++)
+ {
+ wa3[j] = diag[j] * x[j];
+ }
+ xnorm = lm_enorm(n, wa3);
+ if (C->verbosity >= 2)
+ {
+ fprintf( msgfile, "lmmin diag " );
+ lm_print_pars( nout, x, xnorm, msgfile );
+ }
+ /* only now print the header for the loop table */
+ if (C->verbosity >= 3)
+ {
+ fprintf( msgfile, " o i lmpar prered"
+ " ratio dirder delta"
+ " pnorm fnorm" );
+ for (i = 0; i < nout; ++i)
+ {
+ fprintf( msgfile, " p%i", i );
+ }
+ fprintf( msgfile, "\n" );
+ }
+ }
+ else
+ {
+ xnorm = lm_enorm(n, x);
+ }
+ /* initialize the step bound delta. */
+ if (xnorm)
+ {
+ delta = C->stepbound * xnorm;
+ }
+ else
+ {
+ delta = C->stepbound;
+ }
+ }
+ else
+ {
+ if (C->scale_diag)
+ {
+ for (j = 0; j < n; j++)
+ {
+ diag[j] = MAX( diag[j], wa2[j] );
+ }
+ }
+ }
+
+/*** The inner loop. ***/
+ inner = 0;
+ do
+ {
+
+/*** [inner] Determine the Levenberg-Marquardt parameter. ***/
+
+ lm_lmpar( n, fjac, m, ipvt, diag, qtf, delta, &lmpar,
+ wa1, wa2, wf, wa3 );
+ /* used return values are fjac (partly), lmpar, wa1=x, wa3=diag*x */
+
+ /* predict scaled reduction */
+ pnorm = lm_enorm(n, wa3);
+ temp2 = lmpar * SQR( pnorm / fnorm );
+ for (j = 0; j < n; j++)
+ {
+ wa3[j] = 0;
+ for (i = 0; i <= j; i++)
+ {
+ wa3[i] -= fjac[j*m+i] * wa1[ipvt[j]];
+ }
+ }
+ temp1 = SQR( lm_enorm(n, wa3) / fnorm );
+ prered = temp1 + 2 * temp2;
+ dirder = -temp1 + temp2; /* scaled directional derivative */
+
+ /* at first call, adjust the initial step bound. */
+ if (!outer && pnorm < delta)
+ {
+ delta = pnorm;
+ }
+
+/*** [inner] Evaluate the function at x + p. ***/
+
+ for (j = 0; j < n; j++)
+ {
+ wa2[j] = x[j] - wa1[j];
+ }
+
+ (*evaluate)( wa2, m, data, wf, &(S->userbreak) );
+ ++(S->nfev);
+ if (S->userbreak)
+ {
+ goto terminate;
+ }
+ fnorm1 = lm_enorm(m, wf);
+
+/*** [inner] Evaluate the scaled reduction. ***/
+
+ /* actual scaled reduction */
+ actred = 1 - SQR(fnorm1/fnorm);
+
+ /* ratio of actual to predicted reduction */
+ ratio = prered ? actred/prered : 0;
+
+ if (C->verbosity == 2)
+ {
+ fprintf( msgfile, "lmmin (%i:%i) ", outer, inner );
+ lm_print_pars( nout, wa2, fnorm1, msgfile );
+ }
+ else if (C->verbosity >= 3)
+ {
+ printf( "%3i %2i %9.2g %9.2g %14.6g"
+ " %9.2g %10.3e %10.3e %21.15e",
+ outer, inner, lmpar, prered, ratio,
+ dirder, delta, pnorm, fnorm1 );
+ for (i = 0; i < nout; ++i)
+ {
+ fprintf( msgfile, " %16.9g", wa2[i] );
+ }
+ fprintf( msgfile, "\n" );
+ }
+
+ /* update the step bound */
+ if (ratio <= 0.25)
+ {
+ if (actred >= 0)
+ {
+ temp = 0.5;
+ }
+ else if (actred > -99) /* -99 = 1-1/0.1^2 */
+ {
+ temp = MAX( dirder / (2*dirder + actred), 0.1 );
+ }
+ else
+ {
+ temp = 0.1;
+ }
+ delta = temp * MIN(delta, pnorm / 0.1);
+ lmpar /= temp;
+ }
+ else if (ratio >= 0.75)
+ {
+ delta = 2*pnorm;
+ lmpar *= 0.5;
+ }
+ else if (!lmpar)
+ {
+ delta = 2*pnorm;
+ }
+
+/*** [inner] On success, update solution, and test for convergence. ***/
+
+ inner_success = ratio >= p0001;
+ if (inner_success)
+ {
+
+ /* update x, fvec, and their norms */
+ if (C->scale_diag)
+ {
+ for (j = 0; j < n; j++)
+ {
+ x[j] = wa2[j];
+ wa2[j] = diag[j] * x[j];
+ }
+ }
+ else
+ {
+ for (j = 0; j < n; j++)
+ {
+ x[j] = wa2[j];
+ }
+ }
+ for (i = 0; i < m; i++)
+ {
+ fvec[i] = wf[i];
+ }
+ xnorm = lm_enorm(n, wa2);
+ fnorm = fnorm1;
+ }
+
+ /* convergence tests */
+ S->outcome = 0;
+ if (fnorm <= LM_DWARF)
+ {
+ goto terminate; /* success: sum of squares almost zero */
+ }
+ /* test two criteria (both may be fulfilled) */
+ if (fabs(actred) <= C->ftol && prered <= C->ftol && ratio <= 2)
+ {
+ S->outcome = 1; /* success: x almost stable */
+ }
+ if (delta <= C->xtol * xnorm)
+ {
+ S->outcome += 2; /* success: sum of squares almost stable */
+ }
+ if (S->outcome != 0)
+ {
+ goto terminate;
+ }
+
+/*** [inner] Tests for termination and stringent tolerances. ***/
+
+ if (S->nfev >= maxfev)
+ {
+ S->outcome = 5;
+ goto terminate;
+ }
+ if (fabs(actred) <= LM_MACHEP &&
+ prered <= LM_MACHEP && ratio <= 2)
+ {
+ S->outcome = 6;
+ goto terminate;
+ }
+ if (delta <= LM_MACHEP*xnorm)
+ {
+ S->outcome = 7;
+ goto terminate;
+ }
+ if (gnorm <= LM_MACHEP)
+ {
+ S->outcome = 8;
+ goto terminate;
+ }
+
+/*** [inner] End of the loop. Repeat if iteration unsuccessful. ***/
+
+ ++inner;
+ }
+ while (!inner_success);
+
+/*** [outer] End of the loop. ***/
+
+ }
+ ;
+
+terminate:
+ S->fnorm = lm_enorm(m, fvec);
+ if (C->verbosity >= 2)
+ {
+ printf("lmmin outcome (%i) xnorm %g ftol %g xtol %g\n",
+ S->outcome, xnorm, C->ftol, C->xtol );
+ }
+ if (C->verbosity & 1)
+ {
+ fprintf( msgfile, "lmmin final " );
+ lm_print_pars( nout, x, S->fnorm, msgfile );
+ }
+ if (S->userbreak) /* user-requested break */
+ {
+ S->outcome = 11;
+ }
+
+/*** Deallocate the workspace. ***/
+ free(fvec);
+ free(diag);
+ free(qtf);
+ free(fjac);
+ free(wa1);
+ free(wa2);
+ free(wa3);
+ free(wf);
+ free(ipvt);
+
+} /*** lmmin. ***/
+
+
+/*****************************************************************************/
+/* lm_lmpar (determine Levenberg-Marquardt parameter) */
+/*****************************************************************************/
+
+void lm_lmpar(int n, double *r, int ldr, int *ipvt, double *diag,
+ double *qtb, double delta, double *par, double *x,
+ double *sdiag, double *aux, double *xdi)
+{
+/* Given an m by n matrix a, an n by n nonsingular diagonal
+ * matrix d, an m-vector b, and a positive number delta,
+ * the problem is to determine a value for the parameter
+ * par such that if x solves the system
+ *
+ * a*x = b and sqrt(par)*d*x = 0
+ *
+ * in the least squares sense, and dxnorm is the euclidean
+ * norm of d*x, then either par=0 and (dxnorm-delta) < 0.1*delta,
+ * or par>0 and abs(dxnorm-delta) < 0.1*delta.
+ *
+ * Using lm_qrsolv, this subroutine completes the solution of the problem
+ * if it is provided with the necessary information from the
+ * qr factorization, with column pivoting, of a. That is, if
+ * a*p = q*r, where p is a permutation matrix, q has orthogonal
+ * columns, and r is an upper triangular matrix with diagonal
+ * elements of nonincreasing magnitude, then lmpar expects
+ * the full upper triangle of r, the permutation matrix p,
+ * and the first n components of qT*b. On output
+ * lmpar also provides an upper triangular matrix s such that
+ *
+ * p^T*(a^T*a + par*d*d)*p = s^T*s.
+ *
+ * s is employed within lmpar and may be of separate interest.
+ *
+ * Only a few iterations are generally needed for convergence
+ * of the algorithm. If, however, the limit of 10 iterations
+ * is reached, then the output par will contain the best
+ * value obtained so far.
+ *
+ * parameters:
+ *
+ * n is a positive integer input variable set to the order of r.
+ *
+ * r is an n by n array. on input the full upper triangle
+ * must contain the full upper triangle of the matrix r.
+ * on OUTPUT the full upper triangle is unaltered, and the
+ * strict lower triangle contains the strict upper triangle
+ * (transposed) of the upper triangular matrix s.
+ *
+ * ldr is a positive integer input variable not less than n
+ * which specifies the leading dimension of the array r.
+ *
+ * ipvt is an integer input array of length n which defines the
+ * permutation matrix p such that a*p = q*r. column j of p
+ * is column ipvt(j) of the identity matrix.
+ *
+ * diag is an input array of length n which must contain the
+ * diagonal elements of the matrix d.
+ *
+ * qtb is an input array of length n which must contain the first
+ * n elements of the vector (q transpose)*b.
+ *
+ * delta is a positive input variable which specifies an upper
+ * bound on the euclidean norm of d*x.
+ *
+ * par is a nonnegative variable. on input par contains an
+ * initial estimate of the levenberg-marquardt parameter.
+ * on OUTPUT par contains the final estimate.
+ *
+ * x is an OUTPUT array of length n which contains the least
+ * squares solution of the system a*x = b, sqrt(par)*d*x = 0,
+ * for the output par.
+ *
+ * sdiag is an array of length n needed as workspace; on OUTPUT
+ * it contains the diagonal elements of the upper triangular matrix s.
+ *
+ * aux is a multi-purpose work array of length n.
+ *
+ * xdi is a work array of length n. On OUTPUT: diag[j] * x[j].
+ *
+ */
+ int i, iter, j, nsing;
+ double dxnorm, fp, fp_old, gnorm, parc, parl, paru;
+ double sum, temp;
+ static double p1 = 0.1;
+
+/*** lmpar: compute and store in x the gauss-newton direction. if the
+ jacobian is rank-deficient, obtain a least squares solution. ***/
+
+ nsing = n;
+ for (j = 0; j < n; j++)
+ {
+ aux[j] = qtb[j];
+ if (r[j * ldr + j] == 0 && nsing == n)
+ {
+ nsing = j;
+ }
+ if (nsing < n)
+ {
+ aux[j] = 0;
+ }
+ }
+ for (j = nsing - 1; j >= 0; j--)
+ {
+ aux[j] = aux[j] / r[j + ldr * j];
+ temp = aux[j];
+ for (i = 0; i < j; i++)
+ {
+ aux[i] -= r[j * ldr + i] * temp;
+ }
+ }
+
+ for (j = 0; j < n; j++)
+ {
+ x[ipvt[j]] = aux[j];
+ }
+
+/*** lmpar: initialize the iteration counter, evaluate the function at the
+ origin, and test for acceptance of the gauss-newton direction. ***/
+
+ for (j = 0; j < n; j++)
+ {
+ xdi[j] = diag[j] * x[j];
+ }
+ dxnorm = lm_enorm(n, xdi);
+ fp = dxnorm - delta;
+ if (fp <= p1 * delta)
+ {
+#ifdef LMFIT_DEBUG_MESSAGES
+ printf("debug lmpar nsing %d n %d, terminate (fp<p1*delta)\n",
+ nsing, n);
+#endif
+ *par = 0;
+ return;
+ }
+
+/*** lmpar: if the jacobian is not rank deficient, the newton
+ step provides a lower bound, parl, for the 0. of
+ the function. otherwise set this bound to 0.. ***/
+
+ parl = 0;
+ if (nsing >= n)
+ {
+ for (j = 0; j < n; j++)
+ {
+ aux[j] = diag[ipvt[j]] * xdi[ipvt[j]] / dxnorm;
+ }
+
+ for (j = 0; j < n; j++)
+ {
+ sum = 0.;
+ for (i = 0; i < j; i++)
+ {
+ sum += r[j * ldr + i] * aux[i];
+ }
+ aux[j] = (aux[j] - sum) / r[j + ldr * j];
+ }
+ temp = lm_enorm(n, aux);
+ parl = fp / delta / temp / temp;
+ }
+
+/*** lmpar: calculate an upper bound, paru, for the 0. of the function. ***/
+
+ for (j = 0; j < n; j++)
+ {
+ sum = 0;
+ for (i = 0; i <= j; i++)
+ {
+ sum += r[j * ldr + i] * qtb[i];
+ }
+ aux[j] = sum / diag[ipvt[j]];
+ }
+ gnorm = lm_enorm(n, aux);
+ paru = gnorm / delta;
+ if (paru == 0.)
+ {
+ paru = LM_DWARF / MIN(delta, p1);
+ }
+
+/*** lmpar: if the input par lies outside of the interval (parl,paru),
+ set par to the closer endpoint. ***/
+
+ *par = MAX(*par, parl);
+ *par = MIN(*par, paru);
+ if (*par == 0.)
+ {
+ *par = gnorm / dxnorm;
+ }
+
+/*** lmpar: iterate. ***/
+
+ for (iter = 0;; iter++)
+ {
+
+ /** evaluate the function at the current value of par. **/
+
+ if (*par == 0.)
+ {
+ *par = MAX(LM_DWARF, 0.001 * paru);
+ }
+ temp = sqrt(*par);
+ for (j = 0; j < n; j++)
+ {
+ aux[j] = temp * diag[j];
+ }
+
+ lm_qrsolv( n, r, ldr, ipvt, aux, qtb, x, sdiag, xdi );
+ /* return values are r, x, sdiag */
+
+ for (j = 0; j < n; j++)
+ {
+ xdi[j] = diag[j] * x[j]; /* used as output */
+ }
+ dxnorm = lm_enorm(n, xdi);
+ fp_old = fp;
+ fp = dxnorm - delta;
+
+ /** if the function is small enough, accept the current value
+ of par. Also test for the exceptional cases where parl
+ is zero or the number of iterations has reached 10. **/
+
+ if (fabs(fp) <= p1 * delta
+ || (parl == 0. && fp <= fp_old && fp_old < 0.)
+ || iter == 10)
+ {
+#ifdef LMFIT_DEBUG_MESSAGES
+ printf("debug lmpar nsing %d iter %d "
+ "par %.4e [%.4e %.4e] delta %.4e fp %.4e\n",
+ nsing, iter, *par, parl, paru, delta, fp);
+#endif
+ break; /* the only exit from the iteration. */
+ }
+
+ /** compute the Newton correction. **/
+
+ for (j = 0; j < n; j++)
+ {
+ aux[j] = diag[ipvt[j]] * xdi[ipvt[j]] / dxnorm;
+ }
+
+ for (j = 0; j < n; j++)
+ {
+ aux[j] = aux[j] / sdiag[j];
+ for (i = j + 1; i < n; i++)
+ {
+ aux[i] -= r[j * ldr + i] * aux[j];
+ }
+ }
+ temp = lm_enorm(n, aux);
+ parc = fp / delta / temp / temp;
+
+ /** depending on the sign of the function, update parl or paru. **/
+
+ if (fp > 0)
+ {
+ parl = MAX(parl, *par);
+ }
+ else if (fp < 0)
+ {
+ paru = MIN(paru, *par);
+ }
+ /* the case fp==0 is precluded by the break condition */
+
+ /** compute an improved estimate for par. **/
+
+ *par = MAX(parl, *par + parc);
+
+ }
+
+} /*** lm_lmpar. ***/
+
+/*****************************************************************************/
+/* lm_qrfac (QR factorization, from lapack) */
+/*****************************************************************************/
+
+void lm_qrfac(int m, int n, double *a, int *ipvt,
+ double *rdiag, double *acnorm, double *wa)
+{
+/*
+ * This subroutine uses Householder transformations with column
+ * pivoting (optional) to compute a qr factorization of the
+ * m by n matrix a. That is, qrfac determines an orthogonal
+ * matrix q, a permutation matrix p, and an upper trapezoidal
+ * matrix r with diagonal elements of nonincreasing magnitude,
+ * such that a*p = q*r. The Householder transformation for
+ * column k, k = 1,2,...,min(m,n), is of the form
+ *
+ * i - (1/u(k))*u*uT
+ *
+ * where u has zeroes in the first k-1 positions. The form of
+ * this transformation and the method of pivoting first
+ * appeared in the corresponding linpack subroutine.
+ *
+ * Parameters:
+ *
+ * m is a positive integer input variable set to the number
+ * of rows of a.
+ *
+ * n is a positive integer input variable set to the number
+ * of columns of a.
+ *
+ * a is an m by n array. On input a contains the matrix for
+ * which the qr factorization is to be computed. On OUTPUT
+ * the strict upper trapezoidal part of a contains the strict
+ * upper trapezoidal part of r, and the lower trapezoidal
+ * part of a contains a factored form of q (the non-trivial
+ * elements of the u vectors described above).
+ *
+ * ipvt is an integer OUTPUT array of length lipvt. This array
+ * defines the permutation matrix p such that a*p = q*r.
+ * Column j of p is column ipvt(j) of the identity matrix.
+ *
+ * rdiag is an OUTPUT array of length n which contains the
+ * diagonal elements of r.
+ *
+ * acnorm is an OUTPUT array of length n which contains the
+ * norms of the corresponding columns of the input matrix a.
+ * If this information is not needed, then acnorm can coincide
+ * with rdiag.
+ *
+ * wa is a work array of length n.
+ *
+ */
+ int i, j, k, kmax, minmn;
+ double ajnorm, sum, temp;
+
+/*** qrfac: compute initial column norms and initialize several arrays. ***/
+
+ for (j = 0; j < n; j++)
+ {
+ acnorm[j] = lm_enorm(m, &a[j*m]);
+ rdiag[j] = acnorm[j];
+ wa[j] = rdiag[j];
+ ipvt[j] = j;
+ }
+#ifdef LMFIT_DEBUG_MESSAGES
+ printf("debug qrfac\n");
+#endif
+
+/*** qrfac: reduce a to r with Householder transformations. ***/
+
+ minmn = MIN(m, n);
+ for (j = 0; j < minmn; j++)
+ {
+
+ /** bring the column of largest norm into the pivot position. **/
+
+ kmax = j;
+ for (k = j + 1; k < n; k++)
+ {
+ if (rdiag[k] > rdiag[kmax])
+ {
+ kmax = k;
+ }
+ }
+ if (kmax == j)
+ {
+ goto pivot_ok;
+ }
+
+ for (i = 0; i < m; i++)
+ {
+ temp = a[j*m+i];
+ a[j*m+i] = a[kmax*m+i];
+ a[kmax*m+i] = temp;
+ }
+ rdiag[kmax] = rdiag[j];
+ wa[kmax] = wa[j];
+ k = ipvt[j];
+ ipvt[j] = ipvt[kmax];
+ ipvt[kmax] = k;
+
+pivot_ok:
+ /** compute the Householder transformation to reduce the
+ j-th column of a to a multiple of the j-th unit vector. **/
+
+ ajnorm = lm_enorm(m-j, &a[j*m+j]);
+ if (ajnorm == 0.)
+ {
+ rdiag[j] = 0;
+ continue;
+ }
+
+ if (a[j*m+j] < 0.)
+ {
+ ajnorm = -ajnorm;
+ }
+ for (i = j; i < m; i++)
+ {
+ a[j*m+i] /= ajnorm;
+ }
+ a[j*m+j] += 1;
+
+ /** apply the transformation to the remaining columns
+ and update the norms. **/
+
+ for (k = j + 1; k < n; k++)
+ {
+ sum = 0;
+
+ for (i = j; i < m; i++)
+ {
+ sum += a[j*m+i] * a[k*m+i];
+ }
+
+ temp = sum / a[j + m * j];
+
+ for (i = j; i < m; i++)
+ {
+ a[k*m+i] -= temp * a[j*m+i];
+ }
+
+ if (rdiag[k] != 0.)
+ {
+ temp = a[m * k + j] / rdiag[k];
+ temp = MAX(0., 1 - temp * temp);
+ rdiag[k] *= sqrt(temp);
+ temp = rdiag[k] / wa[k];
+ if (0.05 * SQR(temp) <= LM_MACHEP)
+ {
+ rdiag[k] = lm_enorm(m-j-1, &a[m*k+j+1]);
+ wa[k] = rdiag[k];
+ }
+ }
+ }
+
+ rdiag[j] = -ajnorm;
+ }
+} /*** lm_qrfac. ***/
+
+
+/*****************************************************************************/
+/* lm_qrsolv (linear least-squares) */
+/*****************************************************************************/
+
+void lm_qrsolv(int n, double *r, int ldr, int *ipvt, double *diag,
+ double *qtb, double *x, double *sdiag, double *wa)
+{
+/*
+ * Given an m by n matrix a, an n by n diagonal matrix d,
+ * and an m-vector b, the problem is to determine an x which
+ * solves the system
+ *
+ * a*x = b and d*x = 0
+ *
+ * in the least squares sense.
+ *
+ * This subroutine completes the solution of the problem
+ * if it is provided with the necessary information from the
+ * qr factorization, with column pivoting, of a. That is, if
+ * a*p = q*r, where p is a permutation matrix, q has orthogonal
+ * columns, and r is an upper triangular matrix with diagonal
+ * elements of nonincreasing magnitude, then qrsolv expects
+ * the full upper triangle of r, the permutation matrix p,
+ * and the first n components of (q transpose)*b. The system
+ * a*x = b, d*x = 0, is then equivalent to
+ *
+ * r*z = q^T*b, p^T*d*p*z = 0,
+ *
+ * where x = p*z. If this system does not have full rank,
+ * then a least squares solution is obtained. On output qrsolv
+ * also provides an upper triangular matrix s such that
+ *
+ * p^T *(a^T *a + d*d)*p = s^T *s.
+ *
+ * s is computed within qrsolv and may be of separate interest.
+ *
+ * Parameters
+ *
+ * n is a positive integer input variable set to the order of r.
+ *
+ * r is an n by n array. On input the full upper triangle
+ * must contain the full upper triangle of the matrix r.
+ * On OUTPUT the full upper triangle is unaltered, and the
+ * strict lower triangle contains the strict upper triangle
+ * (transposed) of the upper triangular matrix s.
+ *
+ * ldr is a positive integer input variable not less than n
+ * which specifies the leading dimension of the array r.
+ *
+ * ipvt is an integer input array of length n which defines the
+ * permutation matrix p such that a*p = q*r. Column j of p
+ * is column ipvt(j) of the identity matrix.
+ *
+ * diag is an input array of length n which must contain the
+ * diagonal elements of the matrix d.
+ *
+ * qtb is an input array of length n which must contain the first
+ * n elements of the vector (q transpose)*b.
+ *
+ * x is an OUTPUT array of length n which contains the least
+ * squares solution of the system a*x = b, d*x = 0.
+ *
+ * sdiag is an OUTPUT array of length n which contains the
+ * diagonal elements of the upper triangular matrix s.
+ *
+ * wa is a work array of length n.
+ *
+ */
+ int i, kk, j, k, nsing;
+ double qtbpj, sum, temp;
+ double _sin, _cos, _tan, _cot; /* local variables, not functions */
+
+/*** qrsolv: copy r and q^T*b to preserve input and initialize s.
+ in particular, save the diagonal elements of r in x. ***/
+
+ for (j = 0; j < n; j++)
+ {
+ for (i = j; i < n; i++)
+ {
+ r[j * ldr + i] = r[i * ldr + j];
+ }
+ x[j] = r[j * ldr + j];
+ wa[j] = qtb[j];
+ }
+/*** qrsolv: eliminate the diagonal matrix d using a Givens rotation. ***/
+
+ for (j = 0; j < n; j++)
+ {
+
+/*** qrsolv: prepare the row of d to be eliminated, locating the
+ diagonal element using p from the qr factorization. ***/
+
+ if (diag[ipvt[j]] == 0.)
+ {
+ goto L90;
+ }
+ for (k = j; k < n; k++)
+ {
+ sdiag[k] = 0.;
+ }
+ sdiag[j] = diag[ipvt[j]];
+
+/*** qrsolv: the transformations to eliminate the row of d modify only
+ a single element of qT*b beyond the first n, which is initially 0. ***/
+
+ qtbpj = 0.;
+ for (k = j; k < n; k++)
+ {
+
+ /** determine a Givens rotation which eliminates the
+ appropriate element in the current row of d. **/
+
+ if (sdiag[k] == 0.)
+ {
+ continue;
+ }
+ kk = k + ldr * k;
+ if (fabs(r[kk]) < fabs(sdiag[k]))
+ {
+ _cot = r[kk] / sdiag[k];
+ _sin = 1 / sqrt(1 + SQR(_cot));
+ _cos = _sin * _cot;
+ }
+ else
+ {
+ _tan = sdiag[k] / r[kk];
+ _cos = 1 / sqrt(1 + SQR(_tan));
+ _sin = _cos * _tan;
+ }
+
+ /** compute the modified diagonal element of r and
+ the modified element of ((q^T)*b,0). **/
+
+ r[kk] = _cos * r[kk] + _sin * sdiag[k];
+ temp = _cos * wa[k] + _sin * qtbpj;
+ qtbpj = -_sin * wa[k] + _cos * qtbpj;
+ wa[k] = temp;
+
+ /** accumulate the tranformation in the row of s. **/
+
+ for (i = k + 1; i < n; i++)
+ {
+ temp = _cos * r[k * ldr + i] + _sin * sdiag[i];
+ sdiag[i] = -_sin * r[k * ldr + i] + _cos * sdiag[i];
+ r[k * ldr + i] = temp;
+ }
+ }
+
+L90:
+ /** store the diagonal element of s and restore
+ the corresponding diagonal element of r. **/
+
+ sdiag[j] = r[j * ldr + j];
+ r[j * ldr + j] = x[j];
+ }
+
+/*** qrsolv: solve the triangular system for z. if the system is
+ singular, then obtain a least squares solution. ***/
+
+ nsing = n;
+ for (j = 0; j < n; j++)
+ {
+ if (sdiag[j] == 0. && nsing == n)
+ {
+ nsing = j;
+ }
+ if (nsing < n)
+ {
+ wa[j] = 0;
+ }
+ }
+
+ for (j = nsing - 1; j >= 0; j--)
+ {
+ sum = 0;
+ for (i = j + 1; i < nsing; i++)
+ {
+ sum += r[j * ldr + i] * wa[i];
+ }
+ wa[j] = (wa[j] - sum) / sdiag[j];
+ }
+
+/*** qrsolv: permute the components of z back to components of x. ***/
+
+ for (j = 0; j < n; j++)
+ {
+ x[ipvt[j]] = wa[j];
+ }
+
+} /*** lm_qrsolv. ***/
+
+
+/*****************************************************************************/
+/* lm_enorm (Euclidean norm) */
+/*****************************************************************************/
+
+double lm_enorm(int n, const double *x)
+{
+/* Given an n-vector x, this function calculates the
+ * euclidean norm of x.
+ *
+ * The euclidean norm is computed by accumulating the sum of
+ * squares in three different sums. The sums of squares for the
+ * small and large components are scaled so that no overflows
+ * occur. Non-destructive underflows are permitted. Underflows
+ * and overflows do not occur in the computation of the unscaled
+ * sum of squares for the intermediate components.
+ * The definitions of small, intermediate and large components
+ * depend on two constants, LM_SQRT_DWARF and LM_SQRT_GIANT. The main
+ * restrictions on these constants are that LM_SQRT_DWARF**2 not
+ * underflow and LM_SQRT_GIANT**2 not overflow.
+ *
+ * Parameters
+ *
+ * n is a positive integer input variable.
+ *
+ * x is an input array of length n.
+ */
+ int i;
+ double agiant, s1, s2, s3, xabs, x1max, x3max, temp;
+
+ s1 = 0;
+ s2 = 0;
+ s3 = 0;
+ x1max = 0;
+ x3max = 0;
+ agiant = LM_SQRT_GIANT / n;
+
+ /** sum squares. **/
+
+ for (i = 0; i < n; i++)
+ {
+ xabs = fabs(x[i]);
+ if (xabs > LM_SQRT_DWARF)
+ {
+ if (xabs < agiant)
+ {
+ s2 += xabs * xabs;
+ }
+ else if (xabs > x1max)
+ {
+ temp = x1max / xabs;
+ s1 = 1 + s1 * SQR(temp);
+ x1max = xabs;
+ }
+ else
+ {
+ temp = xabs / x1max;
+ s1 += SQR(temp);
+ }
+ }
+ else if (xabs > x3max)
+ {
+ temp = x3max / xabs;
+ s3 = 1 + s3 * SQR(temp);
+ x3max = xabs;
+ }
+ else if (xabs != 0.)
+ {
+ temp = xabs / x3max;
+ s3 += SQR(temp);
+ }
+ }
+
+ /** calculation of norm. **/
+
+ if (s1 != 0)
+ {
+ return x1max * sqrt(s1 + (s2 / x1max) / x1max);
+ }
+ else if (s2 != 0)
+ {
+ if (s2 >= x3max)
+ {
+ return sqrt(s2 * (1 + (x3max / s2) * (x3max * s3)));
+ }
+ else
+ {
+ return sqrt(x3max * ((s2 / x3max) + (x3max * s3)));
+ }
+ }
+ else
+ {
+ return x3max * sqrt(s3);
+ }
+
+} /*** lm_enorm. ***/
--- /dev/null
+/*
+ * Library: lmfit (Levenberg-Marquardt least squares fitting)
+ *
+ * File: lmmin.h
+ *
+ * Contents: Declarations for Levenberg-Marquardt minimization.
+ *
+ * Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2004-2013)
+ *
+ * License: see ../COPYING (FreeBSD)
+ *
+ * Homepage: apps.jcns.fz-juelich.de/lmfit
+ */
+
+#ifndef LMMIN_H
+#define LMMIN_H
+#undef __BEGIN_DECLS
+#undef __END_DECLS
+#ifdef __cplusplus
+# define __BEGIN_DECLS extern "C" {
+# define __END_DECLS }
+#else
+# define __BEGIN_DECLS /* empty */
+# define __END_DECLS /* empty */
+#endif
+
+#include "lmstruct.h"
+
+__BEGIN_DECLS
+
+/*! \brief
+ * Levenberg-Marquardt minimization.
+ *
+ * This routine contains the core algorithm of our library.
+ *
+ * It minimizes the sum of the squares of m nonlinear functions
+ * in n variables by a modified Levenberg-Marquardt algorithm.
+ * The function evaluation is done by the user-provided routine 'evaluate'.
+ * The Jacobian is then calculated by a forward-difference approximation.
+ *
+ * Parameters:
+ *
+ * \param[in] n_par The number of variables (INPUT, positive integer).
+ * \param par The parameters to be fitted
+ * x is the solution vector (INPUT/OUTPUT, array of length n).
+ * On input it must be set to an estimated solution.
+ * On output it yields the final estimate of the solution.
+ *
+ * m is the number of functions to be minimized (INPUT, positive integer).
+ * It must fulfill m>=n.
+ *
+ * data is a pointer that is ignored by lmmin; it is however forwarded
+ * to the user-supplied functions evaluate and printout.
+ * In a typical application, it contains experimental data to be fitted.
+ *
+ * evaluate is a user-supplied function that calculates the m functions.
+ * Parameters:
+ * n, x, m, data as above.
+ * fvec is an array of length m; on OUTPUT, it must contain the
+ * m function values for the parameter vector x.
+ * userbreak is an integer pointer. When *userbreak is set to a
+ * nonzero value, lmmin will terminate.
+ *
+ * control contains INPUT variables that control the fit algorithm,
+ * as declared and explained in lmstruct.h
+ *
+ * status contains OUTPUT variables that inform about the fit result,
+ * as declared and explained in lmstruct.h
+ */
+void lmmin( int n_par, double *par, int m_dat, const void *data,
+ void (*evaluate) (const double *par, int m_dat, const void *data,
+ double *fvec, int *userbreak),
+ const lm_control_struct *control, lm_status_struct *status );
+
+/* Refined calculation of Eucledian norm. */
+double lm_enorm( int, const double * );
+
+__END_DECLS
+#endif /* LMMIN_H */
--- /dev/null
+/*
+ * Library: lmfit (Levenberg-Marquardt least squares fitting)
+ *
+ * File: lmstruct.h
+ *
+ * Contents: Declarations of parameter records, used in lmmin.h and lmcurve.h
+ *
+ * Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2004-2013)
+ *
+ * License: see ../COPYING (FreeBSD)
+ *
+ * Homepage: apps.jcns.fz-juelich.de/lmfit
+ */
+
+#ifndef LMSTRUCT_H
+#define LMSTRUCT_H
+#undef __BEGIN_DECLS
+#undef __END_DECLS
+#ifdef __cplusplus
+# define __BEGIN_DECLS extern "C" {
+# define __END_DECLS }
+#else
+# define __BEGIN_DECLS /* empty */
+# define __END_DECLS /* empty */
+#endif
+__BEGIN_DECLS
+
+#include <stdio.h>
+
+/* Collection of input parameters for fit control. */
+typedef struct {
+ double ftol; /* Relative error desired in the sum of squares.
+ Termination occurs when both the actual and
+ predicted relative reductions in the sum of squares
+ are at most ftol. */
+ double xtol; /* Relative error between last two approximations.
+ Termination occurs when the relative error between
+ two consecutive iterates is at most xtol. */
+ double gtol; /* Orthogonality desired between fvec and its derivs.
+ Termination occurs when the cosine of the angle
+ between fvec and any column of the Jacobian is at
+ most gtol in absolute value. */
+ double epsilon; /* Step used to calculate the Jacobian, should be
+ slightly larger than the relative error in the
+ user-supplied functions. */
+ double stepbound; /* Used in determining the initial step bound. This
+ bound is set to the product of stepbound and the
+ Euclidean norm of diag*x if nonzero, or else to
+ stepbound itself. In most cases stepbound should lie
+ in the interval (0.1,100.0). Generally, the value
+ 100.0 is recommended. */
+ int patience; /* Used to set the maximum number of function evaluations
+ to patience*(number_of_parameters+1). */
+ int scale_diag; /* If 1, the variables will be rescaled internally.
+ Recommended value is 1. */
+ FILE* msgfile; /* Progress messages will be written to this file. */
+ int verbosity; /* OR'ed: 1: print some messages; 2: print Jacobian. */
+ int n_maxpri; /* -1, or max number of parameters to print. */
+ int m_maxpri; /* -1, or max number of residuals to print. */
+} lm_control_struct;
+
+/* Collection of output parameters for status info. */
+typedef struct {
+ double fnorm; /* norm of the residue vector fvec. */
+ int nfev; /* actual number of iterations. */
+ int outcome; /* Status indicator. Nonnegative values are used as index
+ for the message text lm_infmsg, set in lmmin.c. */
+ int userbreak; /* Set when function evaluation requests termination. */
+} lm_status_struct;
+
+/* Preset (and recommended) control parameter settings. */
+extern const lm_control_struct lm_control_double;
+extern const lm_control_struct lm_control_float;
+
+/* Preset message texts. */
+
+extern const char *lm_infmsg[];
+extern const char *lm_shortmsg[];
+
+__END_DECLS
+#endif /* LMSTRUCT_H */
if (NOT GMX_BUILD_MDRUN_ONLY)
add_subdirectory(legacyheaders)
add_subdirectory(gmxana)
+ add_subdirectory(correlationfunctions)
add_subdirectory(statistics)
add_subdirectory(analysisdata)
add_subdirectory(selection)
--- /dev/null
+#
+# This file is part of the GROMACS molecular simulation package.
+#
+# Copyright (c) 2014, by the GROMACS development team, led by
+# Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+# and including many others, as listed in the AUTHORS file in the
+# top-level source directory and at http://www.gromacs.org.
+#
+# GROMACS is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public License
+# as published by the Free Software Foundation; either version 2.1
+# of the License, or (at your option) any later version.
+#
+# GROMACS is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with GROMACS; if not, see
+# http://www.gnu.org/licenses, or write to the Free Software Foundation,
+# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+#
+# If you want to redistribute modifications to GROMACS, please
+# consider that scientific software is very special. Version
+# control is crucial - bugs must be traceable. We will be happy to
+# consider code for inclusion in the official distribution, but
+# derived work must not be called official GROMACS. Details are found
+# in the README & COPYING files - if they are missing, get the
+# official version at http://www.gromacs.org.
+#
+# To help us fund GROMACS development, we humbly ask that you cite
+# the research papers on the package. Check out http://www.gromacs.org.
+
+file(GLOB GMXCORRFUNC_SOURCES *.c *.cpp)
+file(GLOB LMFIT_SOURCES ${CMAKE_SOURCE_DIR}/src/external/lmfit/*.c)
+
+set(LIBGROMACS_SOURCES ${LIBGROMACS_SOURCES} ${GMXCORRFUNC_SOURCES} ${LMFIT_SOURCES} PARENT_SCOPE)
+if (BUILD_TESTING)
+ add_subdirectory(tests)
+endif()
* To help us fund GROMACS development, we humbly ask that you cite
* the research papers on the package. Check out http://www.gromacs.org.
*/
+/*! \internal \file
+ * \brief
+ * Implements function to compute many autocorrelation functions
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \ingroup module_correlationfunctions
+ */
#include "gmxpre.h"
+#include "autocorr.h"
+
#include <math.h>
#include <stdio.h>
#include <string.h>
+#include "gromacs/correlationfunctions/expfit.h"
+#include "gromacs/correlationfunctions/integrate.h"
+#include "gromacs/correlationfunctions/manyautocorrelation.h"
+#include "gromacs/correlationfunctions/polynomials.h"
#include "gromacs/fileio/xvgr.h"
-#include "gromacs/gmxana/correl.h"
-#include "gromacs/gmxana/gstat.h"
#include "gromacs/legacyheaders/macros.h"
#include "gromacs/legacyheaders/names.h"
-#include "gromacs/legacyheaders/typedefs.h"
#include "gromacs/math/vec.h"
#include "gromacs/utility/fatalerror.h"
#include "gromacs/utility/futil.h"
+#include "gromacs/utility/real.h"
#include "gromacs/utility/smalloc.h"
+/*! \brief Shortcut macro to select modes. */
#define MODE(x) ((mode & (x)) == (x))
typedef struct {
real tbeginfit, tendfit;
} t_acf;
+/*! \brief Global variable set true if initialization routines are called. */
static gmx_bool bACFinit = FALSE;
+
+/*! \brief Data structure for storing command line variables. */
static t_acf acf;
enum {
enNorm, enCos, enSin
};
-int sffn2effn(const char **sffn)
-{
- int eFitFn, i;
-
- eFitFn = 0;
- for (i = 0; i < effnNR; i++)
- {
- if (sffn[i+1] && strcmp(sffn[0], sffn[i+1]) == 0)
- {
- eFitFn = i;
- }
- }
-
- return eFitFn;
-}
-
+/*! \brief Routine to compute ACF using FFT. */
static void low_do_four_core(int nfour, int nframes, real c1[], real cfour[],
- int nCos, gmx_bool bPadding)
+ int nCos)
{
int i = 0;
+ int fftcode;
real aver, *ans;
aver = 0.0;
default:
gmx_fatal(FARGS, "nCos = %d, %s %d", nCos, __FILE__, __LINE__);
}
- for (; (i < nfour); i++)
- {
- cfour[i] = 0.0;
- }
-
- if (bPadding)
- {
- aver /= nframes;
- /* printf("aver = %g\n",aver); */
- for (i = 0; (i < nframes); i++)
- {
- cfour[i] -= aver;
- }
- }
-
- snew(ans, 2*nfour);
- correl(cfour-1, cfour-1, nfour, ans-1);
- if (bPadding)
- {
- for (i = 0; (i < nfour); i++)
- {
- cfour[i] = ans[i]+sqr(aver);
- }
- }
- else
- {
- for (i = 0; (i < nfour); i++)
- {
- cfour[i] = ans[i];
- }
- }
-
- sfree(ans);
+ fftcode = many_auto_correl(1, nframes, nfour, &cfour);
}
+/*! \brief Routine to comput ACF without FFT. */
static void do_ac_core(int nframes, int nout,
real corr[], real c1[], int nrestart,
unsigned long mode)
{
int j, k, j3, jk3, m, n;
real ccc, cth;
- rvec xj, xk, rr;
+ rvec xj, xk;
if (nrestart < 1)
{
}
else if (MODE(eacP1) || MODE(eacP2) || MODE(eacP3))
{
+ unsigned int mmm;
+
for (m = 0; (m < DIM); m++)
{
xj[m] = c1[j3+m];
printf("j: %d, k: %d, xj:(%g,%g,%g), xk:(%g,%g,%g)\n",
j, k, xj[XX], xj[YY], xj[ZZ], xk[XX], xk[YY], xk[ZZ]);
}
-
- corr[k] += LegendreP(cth, mode); /* 1.5*cth*cth-0.5; */
+ mmm = 1;
+ if (MODE(eacP2))
+ {
+ mmm = 2;
+ }
+ else if (MODE(eacP3))
+ {
+ mmm = 3;
+ }
+ corr[k] += LegendreP(cth, mmm); /* 1.5*cth*cth-0.5; */
}
else if (MODE(eacRcross))
{
+ rvec xj, xk, rr;
for (m = 0; (m < DIM); m++)
{
xj[m] = c1[j3+m];
}
}
+/*! \brief Routine to normalize ACF, dividing by corr[0]. */
void normalize_acf(int nout, real corr[])
{
- int j;
- real c0;
+ int j;
+ double c0;
if (debug)
{
/* Normalisation makes that c[0] = 1.0 and that other points are scaled
* accordingly.
*/
- if (corr[0] == 0.0)
+ if (fabs(corr[0]) < 1e-5)
{
c0 = 1.0;
}
}
}
+/*! \brief Routine that averages ACFs. */
void average_acf(gmx_bool bVerbose, int n, int nitem, real **c1)
{
real c0;
}
}
+/*! \brief Normalize ACFs. */
void norm_and_scale_vectors(int nframes, real c1[], real scale)
{
int j, m;
}
}
-void dump_tmp(char *s, int n, real c[])
+/*! \brief Debugging */
+static void dump_tmp(char *s, int n, real c[])
{
FILE *fp;
int i;
gmx_ffclose(fp);
}
-real print_and_integrate(FILE *fp, int n, real dt, real c[], real *fit, int nskip)
-{
- real c0, sum;
- int j;
-
- /* Use trapezoidal rule for calculating integral */
- sum = 0.0;
- for (j = 0; (j < n); j++)
- {
- c0 = c[j];
- if (fp && (nskip == 0 || j % nskip == 0))
- {
- fprintf(fp, "%10.3f %10.5f\n", j*dt, c0);
- }
- if (j > 0)
- {
- sum += dt*(c0+c[j-1]);
- }
- }
- if (fp)
- {
- fprintf(fp, "&\n");
- if (fit)
- {
- for (j = 0; (j < n); j++)
- {
- if (nskip == 0 || j % nskip == 0)
- {
- fprintf(fp, "%10.3f %10.5f\n", j*dt, fit[j]);
- }
- }
- fprintf(fp, "&\n");
- }
- }
- return sum*0.5;
-}
-
-real evaluate_integral(int n, real x[], real y[], real dy[], real aver_start,
- real *stddev)
-{
- double sum, sum_var, w;
- double sum_tail = 0, sum2_tail = 0;
- int j, nsum_tail = 0;
-
- /* Use trapezoidal rule for calculating integral */
- if (n <= 0)
- {
- gmx_fatal(FARGS, "Evaluating integral: n = %d (file %s, line %d)",
- n, __FILE__, __LINE__);
- }
-
- sum = 0;
- sum_var = 0;
- for (j = 0; (j < n); j++)
- {
- w = 0;
- if (j > 0)
- {
- w += 0.5*(x[j] - x[j-1]);
- }
- if (j < n-1)
- {
- w += 0.5*(x[j+1] - x[j]);
- }
- sum += w*y[j];
- if (dy)
- {
- /* Assume all errors are uncorrelated */
- sum_var += sqr(w*dy[j]);
- }
-
- if ((aver_start > 0) && (x[j] >= aver_start))
- {
- sum_tail += sum;
- sum2_tail += sqrt(sum_var);
- nsum_tail += 1;
- }
- }
-
- if (nsum_tail > 0)
- {
- sum = sum_tail/nsum_tail;
- /* This is a worst case estimate, assuming all stddev's are correlated. */
- *stddev = sum2_tail/nsum_tail;
- }
- else
- {
- *stddev = sqrt(sum_var);
- }
-
- return sum;
-}
-
+/*! \brief High level ACF routine. */
void do_four_core(unsigned long mode, int nfour, int nf2, int nframes,
real c1[], real csum[], real ctmp[])
{
/********************************************
* N O R M A L
********************************************/
- low_do_four_core(nfour, nf2, c1, csum, enNorm, FALSE);
+ low_do_four_core(nfour, nf2, c1, csum, enNorm);
}
else if (MODE(eacCos))
{
}
/* Cosine term of AC function */
- low_do_four_core(nfour, nf2, ctmp, cfour, enCos, FALSE);
+ low_do_four_core(nfour, nf2, ctmp, cfour, enCos);
for (j = 0; (j < nf2); j++)
{
c1[j] = cfour[j];
}
/* Sine term of AC function */
- low_do_four_core(nfour, nf2, ctmp, cfour, enSin, FALSE);
+ low_do_four_core(nfour, nf2, ctmp, cfour, enSin);
for (j = 0; (j < nf2); j++)
{
c1[j] += cfour[j];
dump_tmp(buf, nf2, ctmp);
}
- low_do_four_core(nfour, nf2, ctmp, cfour, enNorm, FALSE);
+ low_do_four_core(nfour, nf2, ctmp, cfour, enNorm);
if (debug)
{
sprintf(buf, "c1off%d.xvg", m);
dump_tmp(buf, nf2, ctmp);
}
- low_do_four_core(nfour, nf2, ctmp, cfour, enNorm, FALSE);
+ low_do_four_core(nfour, nf2, ctmp, cfour, enNorm);
if (debug)
{
sprintf(buf, "c1ofout%d.xvg", m);
{
ctmp[j] = c1[DIM*j+m];
}
- low_do_four_core(nfour, nf2, ctmp, cfour, enNorm, FALSE);
+ low_do_four_core(nfour, nf2, ctmp, cfour, enNorm);
for (j = 0; (j < nf2); j++)
{
csum[j] += cfour[j];
}
}
-real fit_acf(int ncorr, int fitfn, const output_env_t oenv, gmx_bool bVerbose,
- real tbeginfit, real tendfit, real dt, real c1[], real *fit)
-{
- real fitparm[3];
- real tStart, tail_corr, sum, sumtot = 0, c_start, ct_estimate, *sig;
- int i, j, jmax, nf_int;
- gmx_bool bPrint;
-
- bPrint = bVerbose || bDebugMode();
-
- if (bPrint)
- {
- printf("COR:\n");
- }
-
- if (tendfit <= 0)
- {
- tendfit = ncorr*dt;
- }
- nf_int = min(ncorr, (int)(tendfit/dt));
- sum = print_and_integrate(debug, nf_int, dt, c1, NULL, 1);
-
- /* Estimate the correlation time for better fitting */
- ct_estimate = 0.5*c1[0];
- for (i = 1; (i < ncorr) && (c1[i] > 0); i++)
- {
- ct_estimate += c1[i];
- }
- ct_estimate *= dt/c1[0];
-
- if (bPrint)
- {
- printf("COR: Correlation time (plain integral from %6.3f to %6.3f ps) = %8.5f ps\n",
- 0.0, dt*nf_int, sum);
- printf("COR: Relaxation times are computed as fit to an exponential:\n");
- printf("COR: %s\n", longs_ffn[fitfn]);
- printf("COR: Fit to correlation function from %6.3f ps to %6.3f ps, results in a\n", tbeginfit, min(ncorr*dt, tendfit));
- }
-
- tStart = 0;
- if (bPrint)
- {
- printf("COR:%11s%11s%11s%11s%11s%11s%11s\n",
- "Fit from", "Integral", "Tail Value", "Sum (ps)", " a1 (ps)",
- (nfp_ffn[fitfn] >= 2) ? " a2 ()" : "",
- (nfp_ffn[fitfn] >= 3) ? " a3 (ps)" : "");
- }
-
- snew(sig, ncorr);
-
- if (tbeginfit > 0)
- {
- jmax = 3;
- }
- else
- {
- jmax = 1;
- }
- for (j = 0; ((j < jmax) && (tStart < tendfit) && (tStart < ncorr*dt)); j++)
- {
- /* Estimate the correlation time for better fitting */
- c_start = -1;
- ct_estimate = 0;
- for (i = 0; (i < ncorr) && (dt*i < tStart || c1[i] > 0); i++)
- {
- if (c_start < 0)
- {
- if (dt*i >= tStart)
- {
- c_start = c1[i];
- ct_estimate = 0.5*c1[i];
- }
- }
- else
- {
- ct_estimate += c1[i];
- }
- }
- if (c_start > 0)
- {
- ct_estimate *= dt/c_start;
- }
- else
- {
- /* The data is strange, so we need to choose somehting */
- ct_estimate = tendfit;
- }
- if (debug)
- {
- fprintf(debug, "tStart %g ct_estimate: %g\n", tStart, ct_estimate);
- }
-
- if (fitfn == effnEXP3)
- {
- fitparm[0] = 0.002*ncorr*dt;
- fitparm[1] = 0.95;
- fitparm[2] = 0.2*ncorr*dt;
- }
- else
- {
- /* Good initial guess, this increases the probability of convergence */
- fitparm[0] = ct_estimate;
- fitparm[1] = 1.0;
- fitparm[2] = 1.0;
- }
-
- /* Generate more or less appropriate sigma's */
- for (i = 0; i < ncorr; i++)
- {
- sig[i] = sqrt(ct_estimate+dt*i);
- }
-
- nf_int = min(ncorr, (int)((tStart+1e-4)/dt));
- sum = print_and_integrate(debug, nf_int, dt, c1, NULL, 1);
- tail_corr = do_lmfit(ncorr, c1, sig, dt, NULL, tStart, tendfit, oenv,
- bDebugMode(), fitfn, fitparm, 0);
- sumtot = sum+tail_corr;
- if (fit && ((jmax == 1) || (j == 1)))
- {
- for (i = 0; (i < ncorr); i++)
- {
- fit[i] = fit_function(fitfn, fitparm, i*dt);
- }
- }
- if (bPrint)
- {
- printf("COR:%11.4e%11.4e%11.4e%11.4e", tStart, sum, tail_corr, sumtot);
- for (i = 0; (i < nfp_ffn[fitfn]); i++)
- {
- printf(" %11.4e", fitparm[i]);
- }
- printf("\n");
- }
- tStart += tbeginfit;
- }
- sfree(sig);
-
- return sumtot;
-}
-
void low_do_autocorr(const char *fn, const output_env_t oenv, const char *title,
int nframes, int nitem, int nout, real **c1,
real dt, unsigned long mode, int nrestart,
}
if ((MODE(eacP3) || MODE(eacRcross)) && bFour)
{
- fprintf(stderr, "Can't combine mode %lu with FFT, turning off FFT\n", mode);
+ if (bVerbose)
+ {
+ fprintf(stderr, "Can't combine mode %lu with FFT, turning off FFT\n", mode);
+ }
bFour = FALSE;
}
if (MODE(eacNormal) && MODE(eacVector))
sfree(fit);
}
+/*! \brief Legend for selecting Legendre polynomials. */
static const char *Leg[] = { NULL, "0", "1", "2", "3", NULL };
t_pargs *add_acf_pargs(int *npargs, t_pargs *pa)
{ "-endfit", FALSE, etREAL, {&acf.tendfit},
"Time where to end the exponential fit of the correlation function, -1 is until the end" },
};
-#define NPA asize(acfpa)
t_pargs *ppa;
- int i;
+ int i, npa;
- snew(ppa, *npargs+NPA);
+ npa = asize(pa);
+ snew(ppa, *npargs+npa);
for (i = 0; (i < *npargs); i++)
{
ppa[i] = pa[i];
}
- for (i = 0; (i < NPA); i++)
+ for (i = 0; (i < npa); i++)
{
ppa[*npargs+i] = acfpa[i];
}
- (*npargs) += NPA;
+ (*npargs) += npa;
acf.mode = 0;
acf.nrestart = 1;
return sffn2effn(s_ffn);
}
-
-void cross_corr(int n, real f[], real g[], real corr[])
-{
- int i, j;
-
- if (acf.bFour)
- {
- correl(f-1, g-1, n, corr-1);
- }
- else
- {
- for (i = 0; (i < n); i++)
- {
- for (j = i; (j < n); j++)
- {
- corr[j-i] += f[i]*g[j];
- }
- corr[i] /= (real)(n-i);
- }
- }
-}
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \libinternal
+ * \defgroup module_correlationfunctions Correlation functions
+ * \ingroup group_analysismodules
+ * \brief
+ * Compute correlation functions and fit analytical functions to the result.
+ */
+/*! \libinternal
+ * \file
+ * \brief
+ * Declares routine for computing autocorrelation functions
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \inlibraryapi
+ * \ingroup module_correlationfunctions
+ */
+#ifndef GMX_AUTOCORR_H
+#define GMX_AUTOCORR_H
+
+#include "gromacs/commandline/pargs.h"
+#include "gromacs/utility/real.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*! \brief Normal correlation f(t)*f(t+dt) */
+#define eacNormal (1<<0)
+/*! \brief Cosine correlation cos(f(t)-f(t+dt)) */
+#define eacCos (1<<1)
+/*! \brief Vector correlation f(t).f(t+dt) */
+#define eacVector (1<<2)
+/*! \brief Norm of cross product |f(t) (x) f(t+dt)| */
+#define eacRcross (1<<3 | eacVector)
+/*! \brief Vector with Legendre polynomial of order 0 (same as vector) */
+#define eacP0 (1<<4 | eacVector)
+/*! \brief Vector with Legendre polynomial of order P_1(f(t).f(t+dt)) */
+#define eacP1 (1<<5 | eacVector)
+/*! \brief Vector with Legendre polynomial of order P_2(f(t).f(t+dt)) */
+#define eacP2 (1<<6 | eacVector)
+/*! \brief Vector with Legendre polynomial of order P_3(f(t).f(t+dt)) */
+#define eacP3 (1<<7 | eacVector)
+/*! \brief Vector with Legendre polynomial of order P_4(f(t).f(t+dt)) */
+#define eacP4 (1<<8 | eacVector)
+/*! \brief Binary identy correlation (f(t) == f(t+dt)) */
+#define eacIden (1<<9) //Not supported for multiple cores
+
+/*! \brief
+ * Add commandline arguments related to autocorrelations to the existing array.
+ * *npargs must be initialised to the number of elements in pa,
+ * it will be incremented appropriately.
+ *
+ * \param npargs The number of arguments before and after (is changed in this function)
+ * \param[in] pa The initial argument list
+ * \return the new array
+ */
+t_pargs *add_acf_pargs(int *npargs, t_pargs *pa);
+
+/*! \brief
+ * Returns the number of points to output from a correlation function.
+ * Works only AFTER do_auto_corr has been called!
+ * \return the output length for the correlation function
+ */
+int get_acfnout(void);
+
+/*! \brief
+ * Returns the fitting function selected.
+ * Works only AFTER do_auto_corr has been called!
+ * \return the fit function type.
+ */
+int get_acffitfn(void);
+
+/*! \brief
+ * Calls low_do_autocorr (see below). add_acf_pargs has to be called before this
+ * can be used.
+ * \param[in] fn File name for xvg output (may this be NULL)?
+ * \param[in] oenv The output environment information
+ * \param[in] title is the title in the output file
+ * \param[in] nframes is the number of frames in the time series
+ * \param[in] nitem is the number of items
+ * \param[inout] c1 is an array of dimension [ 0 .. nitem-1 ] [ 0 .. nframes-1 ]
+ * on output, this array is filled with the correlation function
+ * to reduce storage
+ * \param[in] dt is the time between frames
+ * \param[in] mode Different types of ACF can be done, see above
+ * \param[in] bAver If set, all ndih C(t) functions are averaged into a single
+ * C(t)
+ */
+void do_autocorr(const char *fn, const output_env_t oenv,
+ const char *title,
+ int nframes, int nitem, real **c1,
+ real dt, unsigned long mode, gmx_bool bAver);
+
+/*! \brief
+ * Low level computation of autocorrelation functions
+ *
+ * do_autocorr calculates autocorrelation functions for many things.
+ * It takes a 2 d array containing nitem arrays of length nframes
+ * for each item the ACF is calculated.
+ *
+ * A number of "modes" exist for computation of the ACF controlled
+ * by variable mode, with the following meaning.
+ *
+ * Mode | Function
+ * -----------|------------
+ * eacNormal | C(t) = < X (tau) * X (tau+t) >
+ * eacCos | C(t) = < cos (X(tau) - X(tau+t)) >
+ * eacIden | C(t) = < (X(tau) == X(tau+t)) > (not fully supported yet)
+ * eacVector | C(t) = < X(tau) * X(tau+t)
+ * eacP1 | C(t) = < cos (X(tau) * X(tau+t) >
+ * eacP2 | C(t) = 1/2 * < 3 cos (X(tau) * X(tau+t) - 1 >
+ * eacRcross | C(t) = < ( X(tau) * X(tau+t) )^2 >
+ *
+ * For modes eacVector, eacP1, eacP2 and eacRcross the input should be
+ * 3 x nframes long, where each triplet is taken as a 3D vector
+ *
+ * For mode eacCos inputdata must be in radians, not degrees!
+ *
+ * Other parameters are:
+ *
+ * \param[in] fn is output filename (.xvg) where the correlation function(s) are printed
+ * \param[in] oenv controls output file properties
+ * \param[in] title is the title in the output file
+ * \param[in] nframes is the number of frames in the time series
+ * \param[in] nitem is the number of items
+ * \param[in] nout
+ * \param[inout] c1 is an array of dimension [ 0 .. nitem-1 ] [ 0 .. nframes-1 ]
+ * on output, this array is filled with the correlation function
+ * to reduce storage
+ * \param[in] dt is the time between frames
+ * \param[in] mode Different types of ACF can be done, see above
+ * \param[in] nrestart is the number of steps between restarts for direct ACFs
+ * (i.e. without FFT) When set to 1 all points are used as
+ * time origin for averaging
+ * \param[in] bAver If set, all ndih C(t) functions are averaged into a single
+ * C(t)
+ * \param[in] bNormalize If set, all ACFs will be normalized to start at 0
+ * \param[in] bVerbose If set output to console will be generated
+ * \param[in] tbeginfit Time to start fitting to the ACF
+ * \param[in] tendfit Time to end fitting to the ACF
+ * \param[in] nfitparm Number of fitting parameters in a multi-exponential fit
+ */
+void low_do_autocorr(const char *fn, const output_env_t oenv,
+ const char *title, int nframes, int nitem,
+ int nout, real **c1, real dt, unsigned long mode,
+ int nrestart, gmx_bool bAver, gmx_bool bNormalize,
+ gmx_bool bVerbose, real tbeginfit, real tendfit,
+ int nfitparm);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \internal
+ * \file
+ * \brief
+ * Implements routine for computing a cross correlation between two data sets
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \ingroup module_correlationfunctions
+ */
+#include "gmxpre.h"
+
+#include "crosscorr.h"
+
+#include "gromacs/fft/fft.h"
+#include "gromacs/legacyheaders/macros.h"
+#include "gromacs/utility/smalloc.h"
+
+/*! \brief
+ * return the size witch the array should be after zero padding
+ *
+ * \param[in] n Factor to multiply by 2
+ * \return zeroPaddingSize
+ */
+static int zeroPaddingSize(int n)
+{
+ return 2*n;
+}
+
+/*! \brief
+ * Compute complex conjugate. Output in the first input variable.
+ *
+ * \param[in] in1 first complex number
+ * \param[in] in2 second complex number
+ */
+static void complexConjugatMult(double in1[], double in2[])
+{
+ double res[2];
+ res[0] = in1[0] * in2[0] + in1[1] * in2[1];
+ res[1] = in1[0] * -in2[1] + in1[1] * in2[0];
+ in1[0] = res[0];
+ in1[1] = res[1];
+}
+
+/*! \brief
+ * Compute one cross correlation corr = f x g using FFT.
+ *
+ * \param[in] n number of data point
+ * \param[in] f first function
+ * \param[in] g second function
+ * \param[out] corr output correlation
+ * \param[in] fft FFT data structure
+ */
+static void cross_corr_low(int n, real f[], real g[], real corr[], gmx_fft_t fft)
+{
+ int i;
+ const int size = zeroPaddingSize(n);
+ double ** in1, ** in2;
+ snew(in1, size);
+ snew(in2, size);
+
+ for (i = 0; i < size; i++)
+ {
+ snew(in1[i], 2);
+ snew(in2[i], 2);
+ }
+
+ for (i = 0; i < n; i++)
+ {
+ in1[i][0] = (double)f[i];
+ in1[i][1] = 0;
+ in2[i][0] = (double)g[i];
+ in2[i][1] = 0;
+ }
+ for (; i < size; i++)
+ {
+ in1[i][0] = 0;
+ in1[i][1] = 0;
+ in2[i][0] = 0;
+ in2[i][1] = 0;
+ }
+
+
+ gmx_fft_1d(fft, GMX_FFT_FORWARD, in1, in1);
+ gmx_fft_1d(fft, GMX_FFT_FORWARD, in2, in2);
+
+ for (i = 0; i < size; i++)
+ {
+ complexConjugatMult(in1[i], in2[i]);
+ in1[i][0] /= size;
+ }
+ gmx_fft_1d(fft, GMX_FFT_BACKWARD, in1, in1);
+
+ for (i = 0; i < n; i++)
+ {
+ corr[i] = (real)(in1[i][0]);
+ }
+
+ for (i = 0; i < size; i++)
+ {
+ sfree(in1[i]);
+ sfree(in2[i]);
+ }
+
+ sfree(in1);
+ sfree(in2);
+
+}
+
+void cross_corr(int n, real f[], real g[], real corr[])
+{
+ gmx_fft_t fft;
+ gmx_fft_init_1d(&fft, zeroPaddingSize(n), GMX_FFT_FLAG_CONSERVATIVE);
+ cross_corr_low( n, f, g, corr, fft);
+ gmx_fft_destroy(fft);
+ gmx_fft_cleanup();
+}
+
+void many_cross_corr(int nFunc, int * nData, real ** f, real ** g, real ** corr)
+{
+#pragma omp parallel
+ //gmx_fft_t is not thread safe, so structure are allocated per thread.
+ {
+ int i;
+
+#pragma omp for
+ for (i = 0; i < nFunc; i++)
+ {
+ gmx_fft_t fft;
+ gmx_fft_init_1d(&fft, zeroPaddingSize(nData[i]), GMX_FFT_FLAG_CONSERVATIVE);
+ cross_corr_low( nData[i], f[i], g[i], corr[i], fft);
+ gmx_fft_destroy(fft);
+ }
+ }
+ gmx_fft_cleanup();
+
+}
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \libinternal
+ * \file
+ * \brief
+ * Declares routine for computing a cross correlation between two data sets
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \inlibraryapi
+ * \ingroup module_correlationfunctions
+ */
+#ifndef GMX_CROSSCORR_H
+#define GMX_CROSSCORR_H
+
+#include "gromacs/utility/real.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*! \brief
+ * fft cross correlation algorithm.
+ * Computes corr = f (.) g
+ *
+ * \param[in] n number of data point
+ * \param[in] f First function
+ * \param[in] g Second function
+ * \param[out] corr The cross correlation
+ */
+void cross_corr(int n, real f[], real g[], real corr[]);
+
+/*! \brief
+ * fft cross correlation algorithm.
+ *
+ * Computes corr[n] = f[n][i] (.) g[n][i], that is for nFunc
+ * pairs of arrays n the cross correlation is computed in parallel
+ * using OpenMP.
+ *
+ * \param[in] nFunc nuber of function to crosscorrelate
+ * \param[in] nData number of data point in eatch function
+ * \param[in] f 2D array of first function to crosscorrelate
+ * \param[in] g 2D array of second function to crosscorrelate
+ * \param[out] corr 2D array of the cross correlations
+ */
+void many_cross_corr(int nFunc, int * nData, real ** f, real ** g, real ** corr);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 1991-2000, University of Groningen, The Netherlands.
+ * Copyright (c) 2001-2004, The GROMACS development team.
+ * Copyright (c) 2013,2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \internal
+ * \file
+ * \brief
+ * Implements routine for fitting a data set to a curve
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \ingroup module_correlationfunctions
+ */
+#include "gmxpre.h"
+
+#include "expfit.h"
+
+#include <math.h>
+#include <string.h>
+
+#include "external/lmfit/lmcurve.h"
+
+#include "gromacs/correlationfunctions/integrate.h"
+#include "gromacs/fileio/xvgr.h"
+#include "gromacs/legacyheaders/macros.h"
+#include "gromacs/math/vec.h"
+#include "gromacs/utility/fatalerror.h"
+#include "gromacs/utility/futil.h"
+#include "gromacs/utility/real.h"
+#include "gromacs/utility/smalloc.h"
+
+/*! \brief Number of parameters for each fitting function */
+static const int nfp_ffn[effnNR] = { 0, 1, 2, 3, 2, 5, 7, 9, 4, 3, 6};
+
+const char *s_ffn[effnNR+2] = {
+ NULL, "none", "exp", "aexp", "exp_exp", "vac",
+ "exp5", "exp7", "exp9", "erffit", "effnPRES", NULL, NULL
+};
+/* We don't allow errest as a choice on the command line */
+
+/*! \brief Long description for each fitting function type */
+static const char *longs_ffn[effnNR] = {
+ "no fit",
+ "y = exp(-x/a1)",
+ "y = a2 exp(-x/a1)",
+ "y = a2 exp(-x/a1) + (1-a2) exp(-x/a3)",
+ "y = exp(-v) (cosh(wv) + 1/w sinh(wv)), v = x/(2 a1), w = sqrt(1 - a2)",
+ "y = a1 exp(-x/a2) + a3 exp(-x/a4) + a5",
+ "y = a1 exp(-x/a2) + a3 exp(-x/a4) + a5 exp(-x/a6) + a7",
+ "y = a1 exp(-x/a2) + a3 exp(-x/a4) + a5 exp(-x/a6) + a7 exp(-x/a8) + a9",
+ "y = 1/2*(a1+a2) - 1/2*(a1-a2)*erf( (x-a3) /a4^2)",
+ "y = a2 *2*a1*((exp(-x/a1)-1)*(a1/x)+1)+(1-a2)*2*a3*((exp(-x/a3)-1)*(a3/x)+1)",
+ "y = (1-a1) * exp(-(x/a3)^a4)*cos(x*a2) + a1*exp(-(x/a5)^a6)"
+};
+
+int effnNparams(int effn)
+{
+ if ((0 <= effn) && (effn < effnNR))
+ {
+ return nfp_ffn[effn];
+ }
+ else
+ {
+ return -1;
+ }
+}
+
+const char *effnDescription(int effn)
+{
+ if ((0 <= effn) && (effn < effnNR))
+ {
+ return longs_ffn[effn];
+ }
+ else
+ {
+ return NULL;
+ }
+}
+
+int sffn2effn(const char **sffn)
+{
+ int eFitFn, i;
+
+ eFitFn = 0;
+ for (i = 0; i < effnNR; i++)
+ {
+ if (sffn[i+1] && strcmp(sffn[0], sffn[i+1]) == 0)
+ {
+ eFitFn = i;
+ }
+ }
+
+ return eFitFn;
+}
+
+/*! \brief Compute exponential function A exp(-x/tau) */
+static double myexp(double x, double A, double tau)
+{
+ if ((A == 0) || (tau == 0))
+ {
+ return 0;
+ }
+ return A*exp(-x/tau);
+}
+
+/*! \brief Compute y=(a0+a1)/2-(a0-a1)/2*erf((x-a2)/a3^2) */
+static double lmc_erffit (double x, const double *a)
+{
+ double erfarg;
+
+ erfarg = (x-a[2])/(a[3]*a[3]);
+ return (a[0]+a[1])/2-(a[0]-a[1])*gmx_erf(erfarg);
+}
+
+/*! \brief Compute y = exp(-x/a0) */
+static double lmc_exp_one_parm(double x, const double *a)
+{
+ return exp(-x/a[0]);
+}
+
+/*! \brief Compute y = a1 exp(-x/a0) */
+static double lmc_exp_two_parm(double x, const double *a)
+{
+ return a[1]*exp(-x/a[0]);
+}
+
+/*! \brief Compute y = a1 exp(-x/a0) + (1-a1) exp(-x/a2) */
+static double lmc_exp_3_parm(double x, const double *a)
+{
+ double e1, e2;
+
+ e1 = exp(-x/a[0]);
+ e2 = exp(-x/a[2]);
+ return a[1]*e1 + (1-a[1])*e2;
+}
+
+/*! \brief Compute y = a0 exp(-x/a1) + a2 exp(-x/a3) + a4 */
+static double lmc_exp_5_parm(double x, const double *a)
+{
+ double e1, e2;
+
+ e1 = exp(-x/a[1]);
+ e2 = exp(-x/a[3]);
+ return a[0]*e1 + a[2]*e2 + a[4];
+}
+
+/*! \brief Compute y = a0 exp(-x/a1) + a2 exp(-x/a3) + a4 exp(-x/a5) + a6 */
+static double lmc_exp_7_parm(double x, const double *a)
+{
+ double e1, e2, e3;
+
+ e1 = exp(-x/a[1]);
+ e2 = exp(-x/a[3]);
+ e3 = exp(-x/a[5]);
+ return a[0]*e1 + a[2]*e2 + a[4]*e3 + a[6];
+}
+
+/*! \brief Compute y = a0 exp(-x/a1) + a2 exp(-x/a3) + a4 exp(-x/a5) + a6 exp(-x/a7) + a8 */
+static double lmc_exp_9_parm(double x, const double *a)
+{
+ double e1, e2, e3, e4;
+
+ e1 = exp(-x/a[1]);
+ e2 = exp(-x/a[3]);
+ e3 = exp(-x/a[5]);
+ e4 = exp(-x/a[7]);
+ return a[0]*e1 + a[2]*e2 + a[4]*e3 + a[6]*e4 + a[8];
+}
+
+/*! \brief Compute y = (1-a1) * exp(-(x/a3)^a4)*cos(x*a2) + a1*exp(-(x/a5)^a6) */
+static double effnPRES_fun(double x, const double *a)
+{
+ double term1, term2, term3;
+
+ if (a[0] != 0)
+ {
+ term3 = a[0] * exp(-pow((x/a[4]), a[5]));
+ }
+ else
+ {
+ term3 = 0;
+ }
+
+ term1 = 1-a[0];
+ if (term1 != 0)
+ {
+ term2 = exp(-pow((x/a[2]), a[3])) * cos(x*a[1]);
+ }
+ else
+ {
+ term2 = 0;
+ }
+
+ return term1*term2 + term3;
+}
+
+/*! \brief Compute vac function */
+static double lmc_vac_2_parm(double x, const double *a)
+{
+ /* Fit to function
+ *
+ * y = 1/2 (1 - 1/w) exp(-(1+w)v) + 1/2 (1 + 1/w) exp(-(1-w)v)
+ *
+ * = exp(-v) (cosh(wv) + 1/w sinh(wv))
+ *
+ * v = x/(2 a1)
+ * w = sqrt(1 - a2)
+ *
+ * For tranverse current autocorrelation functions:
+ * a1 = tau
+ * a2 = 4 tau (eta/rho) k^2
+ *
+ */
+
+ double y, v, det, omega, omega2, em, ec, es;
+
+ v = x/(2*a[0]);
+ det = 1 - a[1];
+ em = exp(-v);
+ if (det != 0)
+ {
+ omega2 = fabs(det);
+ omega = sqrt(omega2);
+ if (det > 0)
+ {
+ ec = em*0.5*(exp(omega*v)+exp(-omega*v));
+ es = em*0.5*(exp(omega*v)-exp(-omega*v))/omega;
+ }
+ else
+ {
+ ec = em*cos(omega*v);
+ es = em*sin(omega*v)/omega;
+ }
+ y = ec + es;
+ }
+ else
+ {
+ y = (1+v)*em;
+ }
+ return y;
+}
+
+/*! \brief Compute error estimate */
+static double lmc_errest_3_parm(double x, const double *a)
+{
+ /*
+ e1 = (exp(-x/a1) - 1)
+ e2 = (exp(-x/a3) - 1)
+ v1= 2*a1 * (e1*a1/x + 1)
+ v2 = 2*a3 * (e2*a3/x + 1)
+ fun = a2*v1 + (1 - a2) * v2
+ */
+ double e1, e2, v1, v2;
+
+ if (a[0] != 0)
+ {
+ e1 = exp(-x/a[0]) - 1;
+ }
+ else
+ {
+ e1 = 0;
+ }
+ if (a[2] != 0)
+ {
+ e2 = exp(-x/a[2]) - 1;
+ }
+ else
+ {
+ e2 = 0;
+ }
+
+ if (x > 0)
+ {
+ v1 = 2*a[0]*(e1*a[0]/x + 1);
+ v2 = 2*a[2]*(e2*a[2]/x + 1);
+ return a[1]*v1 + (1-a[1])*v2;
+ }
+ else
+ {
+ return 0;
+ }
+}
+
+/*! \brief function type for passing to fitting routine */
+typedef double (*t_lmcurve)(double x, const double *a);
+
+/*! \brief array of fitting functions corresponding to the pre-defined types */
+t_lmcurve lmcurves[effnNR] = {
+ lmc_exp_one_parm, lmc_exp_one_parm, lmc_exp_two_parm,
+ lmc_exp_3_parm, lmc_vac_2_parm,
+ lmc_exp_5_parm, lmc_exp_7_parm,
+ lmc_exp_9_parm, lmc_erffit, lmc_errest_3_parm, effnPRES_fun
+};
+
+double fit_function(int eFitFn, double *parm, double x)
+{
+ // TODO: check that eFitFn is within bounds
+ return lmcurves[eFitFn](x, parm);
+}
+
+/*! \brief lmfit_exp supports up to 3 parameter fitting of exponential functions */
+static gmx_bool lmfit_exp(int nfit, double x[], double y[],
+ real ftol, int maxiter,
+ double parm[], gmx_bool bVerbose,
+ int eFitFn)
+{
+ double chisq, ochisq;
+ gmx_bool bCont;
+ int i, j;
+ lm_control_struct *control;
+ lm_status_struct *status;
+
+ if ((eFitFn < 0) || (eFitFn >= effnNR))
+ {
+ gmx_fatal(FARGS, "fitfn = %d, should be in 0..%d (%s,%d)",
+ effnNR-1, eFitFn, __FILE__, __LINE__);
+ }
+
+ snew(control, 1);
+ control->ftol = ftol;
+ control->xtol = ftol;
+ control->gtol = ftol;
+ control->epsilon = 0.1;
+ control->stepbound = 100;
+ control->patience = maxiter;
+ control->scale_diag = 1;
+ control->msgfile = stdout;
+ control->verbosity = (bVerbose ? 1 : 0);
+ control->n_maxpri = nfp_ffn[eFitFn];
+ control->m_maxpri = 0;
+ snew(status, 1);
+ /* Initial params */
+ chisq = 1e12;
+ j = 0;
+ if (bVerbose)
+ {
+ fprintf(stderr, "%4s %10s Parameters\n",
+ "Step", "chi^2");
+ }
+ do
+ {
+ ochisq = chisq;
+
+ lmcurve(nfp_ffn[eFitFn], parm, nfit, x, y,
+ lmcurves[eFitFn], control, status);
+ chisq = sqr(status->fnorm);
+ if (bVerbose)
+ {
+ int mmm;
+ fprintf(stderr, "%4d %10.5e", j, chisq);
+ for (mmm = 0; (mmm < nfp_ffn[eFitFn]); mmm++)
+ {
+ fprintf(stderr, " %10.5e", parm[mmm]);
+ }
+ fprintf(stderr, "\n");
+ }
+ j++;
+ bCont = ((fabs(ochisq - chisq) > fabs(ftol*chisq)) ||
+ ((ochisq == chisq)));
+ }
+ while (bCont && (j < maxiter));
+ if (bVerbose)
+ {
+ fprintf(stderr, "\n");
+ }
+
+ sfree(control);
+ sfree(status);
+
+ return TRUE;
+}
+
+/*! \brief See description in header file. */
+real do_lmfit(int ndata, real c1[], real sig[], real dt, real x0[],
+ real begintimefit, real endtimefit, const output_env_t oenv,
+ gmx_bool bVerbose, int eFitFn, double fitparms[], int fix)
+{
+ FILE *fp;
+ char buf[32];
+
+ int i, j, nparm, nfitpnts;
+ double integral, ttt;
+ double *parm, *dparm;
+ double *x, *y, *dy;
+#ifdef GMX_DOUBLE
+ real ftol = 1e-16;
+#else
+ real ftol = 1e-8;
+#endif
+ int maxiter = 50;
+
+ if (0 != fix)
+ {
+ fprintf(stderr, "Using fixed parameters in curve fitting is not working anymore\n");
+ }
+ nparm = nfp_ffn[eFitFn];
+ if (debug)
+ {
+ fprintf(debug, "There are %d points to fit %d vars!\n", ndata, nparm);
+ fprintf(debug, "Fit to function %d from %g through %g, dt=%g\n",
+ eFitFn, begintimefit, endtimefit, dt);
+ }
+
+ snew(x, ndata);
+ snew(y, ndata);
+ snew(dy, ndata);
+
+ j = 0;
+ for (i = 0; i < ndata; i++)
+ {
+ ttt = x0 ? x0[i] : dt*i;
+ if (ttt >= begintimefit && ttt <= endtimefit)
+ {
+ x[j] = ttt;
+ y[j] = c1[i];
+
+ /* mrqmin does not like sig to be zero */
+ if (sig[i] < 1.0e-7)
+ {
+ dy[j] = 1.0e-7;
+ }
+ else
+ {
+ dy[j] = sig[i];
+ }
+ if (debug)
+ {
+ fprintf(debug, "j= %d, i= %d, x= %g, y= %g, dy= %g\n",
+ j, i, x[j], y[j], dy[j]);
+ }
+ j++;
+ }
+ }
+ nfitpnts = j;
+ integral = 0;
+ if (nfitpnts < nparm)
+ {
+ fprintf(stderr, "Not enough data points for fitting!\n");
+ }
+ else
+ {
+ snew(parm, nparm);
+ snew(dparm, nparm);
+ if (fitparms)
+ {
+ for (i = 0; (i < nparm); i++)
+ {
+ parm[i] = fitparms[i];
+ }
+ }
+
+ if (!lmfit_exp(nfitpnts, x, y, ftol, maxiter, parm, bVerbose, eFitFn))
+ {
+ fprintf(stderr, "Fit failed!\n");
+ }
+ else if (nparm <= 3)
+ {
+ /* Compute the integral from begintimefit */
+ if (nparm == 3)
+ {
+ integral = (parm[0]*myexp(begintimefit, parm[1], parm[0]) +
+ parm[2]*myexp(begintimefit, 1-parm[1], parm[2]));
+ }
+ else if (nparm == 2)
+ {
+ integral = parm[0]*myexp(begintimefit, parm[1], parm[0]);
+ }
+ else if (nparm == 1)
+ {
+ integral = parm[0]*myexp(begintimefit, 1, parm[0]);
+ }
+ else
+ {
+ gmx_fatal(FARGS, "nparm = %d in file %s, line %d",
+ nparm, __FILE__, __LINE__);
+ }
+
+ /* Generate THE output */
+ if (bVerbose)
+ {
+ fprintf(stderr, "FIT: # points used in fit is: %d\n", nfitpnts);
+ fprintf(stderr, "FIT: %21s%21s%21s\n",
+ "parm0 ", "parm1 (ps) ", "parm2 (ps) ");
+ fprintf(stderr, "FIT: ------------------------------------------------------------\n");
+ fprintf(stderr, "FIT: %8.3g +/- %8.3g%9.4g +/- %8.3g%8.3g +/- %8.3g\n",
+ parm[0], dparm[0], parm[1], dparm[1], parm[2], dparm[2]);
+ fprintf(stderr, "FIT: Integral (calc with fitted function) from %g ps to inf. is: %g\n",
+ begintimefit, integral);
+
+ sprintf(buf, "test%d.xvg", nfitpnts);
+ fp = xvgropen(buf, "C(t) + Fit to C(t)", "Time (ps)", "C(t)", oenv);
+ fprintf(fp, "# parm0 = %g, parm1 = %g, parm2 = %g\n",
+ parm[0], parm[1], parm[2]);
+ for (j = 0; (j < nfitpnts); j++)
+ {
+ ttt = x0 ? x0[j] : dt*j;
+ fprintf(fp, "%10.5e %10.5e %10.5e\n",
+ ttt, c1[j],
+ lmcurves[eFitFn](ttt, parm));
+ }
+ xvgrclose(fp);
+ }
+ }
+ if (fitparms)
+ {
+ for (i = 0; (i < nparm); i++)
+ {
+ fitparms[i] = parm[i];
+ }
+ }
+ sfree(parm);
+ sfree(dparm);
+ }
+
+ sfree(x);
+ sfree(y);
+ sfree(dy);
+
+ return integral;
+}
+
+/*! See description in header file. */
+real fit_acf(int ncorr, int fitfn, const output_env_t oenv, gmx_bool bVerbose,
+ real tbeginfit, real tendfit, real dt, real c1[], real *fit)
+{
+ double fitparm[3];
+ double tStart, tail_corr, sum, sumtot = 0, c_start, ct_estimate;
+ real *sig;
+ int i, j, jmax, nf_int;
+ gmx_bool bPrint;
+
+ bPrint = bVerbose || bDebugMode();
+
+ if (bPrint)
+ {
+ printf("COR:\n");
+ }
+
+ if (tendfit <= 0)
+ {
+ tendfit = ncorr*dt;
+ }
+ nf_int = min(ncorr, (int)(tendfit/dt));
+ sum = print_and_integrate(debug, nf_int, dt, c1, NULL, 1);
+
+ /* Estimate the correlation time for better fitting */
+ ct_estimate = 0.5*c1[0];
+ for (i = 1; (i < ncorr) && (c1[i] > 0); i++)
+ {
+ ct_estimate += c1[i];
+ }
+ ct_estimate *= dt/c1[0];
+
+ if (bPrint)
+ {
+ printf("COR: Correlation time (plain integral from %6.3f to %6.3f ps) = %8.5f ps\n",
+ 0.0, dt*nf_int, sum);
+ printf("COR: Relaxation times are computed as fit to an exponential:\n");
+ printf("COR: %s\n", longs_ffn[fitfn]);
+ printf("COR: Fit to correlation function from %6.3f ps to %6.3f ps, results in a\n", tbeginfit, min(ncorr*dt, tendfit));
+ }
+
+ tStart = 0;
+ if (bPrint)
+ {
+ printf("COR:%11s%11s%11s%11s%11s%11s%11s\n",
+ "Fit from", "Integral", "Tail Value", "Sum (ps)", " a1 (ps)",
+ (nfp_ffn[fitfn] >= 2) ? " a2 ()" : "",
+ (nfp_ffn[fitfn] >= 3) ? " a3 (ps)" : "");
+ }
+
+ snew(sig, ncorr);
+
+ if (tbeginfit > 0)
+ {
+ jmax = 3;
+ }
+ else
+ {
+ jmax = 1;
+ }
+ for (j = 0; ((j < jmax) && (tStart < tendfit) && (tStart < ncorr*dt)); j++)
+ {
+ /* Estimate the correlation time for better fitting */
+ c_start = -1;
+ ct_estimate = 0;
+ for (i = 0; (i < ncorr) && (dt*i < tStart || c1[i] > 0); i++)
+ {
+ if (c_start < 0)
+ {
+ if (dt*i >= tStart)
+ {
+ c_start = c1[i];
+ ct_estimate = 0.5*c1[i];
+ }
+ }
+ else
+ {
+ ct_estimate += c1[i];
+ }
+ }
+ if (c_start > 0)
+ {
+ ct_estimate *= dt/c_start;
+ }
+ else
+ {
+ /* The data is strange, so we need to choose somehting */
+ ct_estimate = tendfit;
+ }
+ if (debug)
+ {
+ fprintf(debug, "tStart %g ct_estimate: %g\n", tStart, ct_estimate);
+ }
+
+ if (fitfn == effnEXP3)
+ {
+ fitparm[0] = 0.002*ncorr*dt;
+ fitparm[1] = 0.95;
+ fitparm[2] = 0.2*ncorr*dt;
+ }
+ else
+ {
+ /* Good initial guess, this increases the probability of convergence */
+ fitparm[0] = ct_estimate;
+ fitparm[1] = 1.0;
+ fitparm[2] = 1.0;
+ }
+
+ /* Generate more or less appropriate sigma's */
+ for (i = 0; i < ncorr; i++)
+ {
+ sig[i] = sqrt(ct_estimate+dt*i);
+ }
+
+ nf_int = min(ncorr, (int)((tStart+1e-4)/dt));
+ sum = print_and_integrate(debug, nf_int, dt, c1, NULL, 1);
+ tail_corr = do_lmfit(ncorr, c1, sig, dt, NULL, tStart, tendfit, oenv,
+ bDebugMode(), fitfn, fitparm, 0);
+ sumtot = sum+tail_corr;
+ if (fit && ((jmax == 1) || (j == 1)))
+ {
+ double mfp[3];
+ for (i = 0; (i < 3); i++)
+ {
+ mfp[i] = fitparm[i];
+ }
+ for (i = 0; (i < ncorr); i++)
+ {
+ fit[i] = lmcurves[fitfn](i*dt, mfp);
+ }
+ }
+ if (bPrint)
+ {
+ printf("COR:%11.4e%11.4e%11.4e%11.4e", tStart, sum, tail_corr, sumtot);
+ for (i = 0; (i < nfp_ffn[fitfn]); i++)
+ {
+ printf(" %11.4e", fitparm[i]);
+ }
+ printf("\n");
+ }
+ tStart += tbeginfit;
+ }
+ sfree(sig);
+
+ return sumtot;
+}
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \libinternal
+ * \file
+ * \brief
+ * Declares routine for fitting a data set to a curve
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \inlibraryapi
+ * \ingroup module_correlationfunctions
+ */
+#ifndef GMX_EXPFIT_H
+#define GMX_EXPFIT_H
+
+#include "gromacs/legacyheaders/oenv.h"
+#include "gromacs/utility/real.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*! \brief
+ * Enum to select fitting functions
+ */
+enum {
+ effnNONE, effnEXP1, effnEXP2, effnEXP3, effnVAC,
+ effnEXP5, effnEXP7, effnEXP9, effnERF, effnERREST, effnPRES, effnNR
+};
+
+/*! \brief
+ * Short name of each function type.
+ * This is exported for now in order to use when
+ * calling parse_common_args.
+ */
+extern const char *s_ffn[effnNR+2];
+
+/*! \brief
+ * Returns description corresponding to the enum above, or NULL if out of range
+ * \param[in] effn Index
+ * \return Description or NULL
+ */
+const char *effnDescription(int effn);
+
+/*! \brief
+ * Returns number of function parameters associated with a fitting function.
+ * \param[in] effn Index
+ * \return number or -1 if index out of range
+ */
+int effnNparams(int effn);
+
+/*! \brief
+ * Returns corresponding to the selected enum option in sffn
+ * \param[in] sffn Two dimensional string array coming from parse_common_args
+ * \return the ffn enum
+ */
+int sffn2effn(const char **sffn);
+
+/*! \brief
+ * Returns the value of fit function eFitFn at x
+ * \param[in] eFitFn the index to the fitting function (0 .. effnNR)
+ * \param[in] parm Array of parameters, the length of which depends on eFitFn
+ * \param[in] x The value of x
+ * \return the value of the fit
+ */
+double fit_function(int eFitFn, double *parm, double x);
+
+/*! \brief
+ * Use Levenberg-Marquardt method to fit to a nfitparm parameter exponential
+ * or to a transverse current autocorrelation function.
+ *
+ * If x == NULL, the timestep dt will be used to create a time axis.
+ * \param[in] ndata Number of data points
+ * \param[in] c1 The data points
+ * \param[in] sig The standard deviation in the points
+ * \param[in] dt The time step
+ * \param[in] x The X-axis (may be NULL, see above)
+ * \param[in] begintimefit Starting time for fitting
+ * \param[in] endtimefit Ending time for fitting
+ * \param[in] oenv Output formatting information
+ * \param[in] bVerbose Should the routine write to console?
+ * \param[in] eFitFn Fitting function (0 .. effnNR)
+ * \param[out] fitparms[]
+ * \param[in] fix Constrains fit parameter i at it's starting value, when the i'th bit
+ * of fix is set.
+ * \return integral.
+ */
+real do_lmfit(int ndata, real c1[], real sig[], real dt, real *x,
+ real begintimefit, real endtimefit, const output_env_t oenv,
+ gmx_bool bVerbose, int eFitFn, double fitparms[], int fix);
+
+/*! \brief
+ * Fit an autocorrelation function to a pre-defined functional form
+ *
+ * \todo check parameters
+ * \param[in] ncorr
+ * \param[in] fitfn Fitting function (0 .. effnNR)
+ * \param[in] oenv Output formatting information
+ * \param[in] bVerbose Should the routine write to console?
+ * \param[in] tbeginfit Starting time for fitting
+ * \param[in] tendfit Ending time for fitting
+ * \param[in] dt The time step
+ * \param[in] c1 The data points
+ * \param[out] fit The fitting parameters
+ * \return the integral over the autocorrelation function?
+ */
+real fit_acf(int ncorr, int fitfn, const output_env_t oenv, gmx_bool bVerbose,
+ real tbeginfit, real tendfit, real dt, real c1[], real *fit);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 1991-2000, University of Groningen, The Netherlands.
+ * Copyright (c) 2001-2004, The GROMACS development team.
+ * Copyright (c) 2013,2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \brief
+ * Implement routines for integrating a data set
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ */
+#include "gmxpre.h"
+
+#include "integrate.h"
+
+#include <math.h>
+#include <stdio.h>
+
+#include "gromacs/math/vec.h"
+#include "gromacs/utility/fatalerror.h"
+
+/*! \brief Integrate a function and printe the integral value. */
+real print_and_integrate(FILE *fp, int n, real dt, const real c[],
+ const real *fit, int nskip)
+{
+ real c0, sum;
+ int j;
+
+ /* Use trapezoidal rule for calculating integral */
+ sum = 0.0;
+ for (j = 0; (j < n); j++)
+ {
+ c0 = c[j];
+ if (fp && (nskip == 0 || j % nskip == 0))
+ {
+ fprintf(fp, "%10.3f %10.5f\n", j*dt, c0);
+ }
+ if (j > 0)
+ {
+ sum += dt*(c0+c[j-1]);
+ }
+ }
+ if (fp)
+ {
+ fprintf(fp, "&\n");
+ if (fit)
+ {
+ for (j = 0; (j < n); j++)
+ {
+ if (nskip == 0 || j % nskip == 0)
+ {
+ fprintf(fp, "%10.3f %10.5f\n", j*dt, fit[j]);
+ }
+ }
+ fprintf(fp, "&\n");
+ }
+ }
+ return sum*0.5;
+}
+
+/*! \brief Compute and return the integral of a function. */
+real evaluate_integral(int n, const real x[], const real y[],
+ const real dy[], real aver_start,
+ real *stddev)
+{
+ double sum, sum_var, w;
+ double sum_tail = 0, sum2_tail = 0;
+ int j, nsum_tail = 0;
+
+ /* Use trapezoidal rule for calculating integral */
+ if (n <= 0)
+ {
+ gmx_fatal(FARGS, "Evaluating integral: n = %d (file %s, line %d)",
+ n, __FILE__, __LINE__);
+ }
+
+ sum = 0;
+ sum_var = 0;
+ for (j = 0; (j < n); j++)
+ {
+ w = 0;
+ if (j > 0)
+ {
+ w += 0.5*(x[j] - x[j-1]);
+ }
+ if (j < n-1)
+ {
+ w += 0.5*(x[j+1] - x[j]);
+ }
+ sum += w*y[j];
+ if (dy)
+ {
+ /* Assume all errors are uncorrelated */
+ sum_var += sqr(w*dy[j]);
+ }
+
+ if ((aver_start > 0) && (x[j] >= aver_start))
+ {
+ sum_tail += sum;
+ sum2_tail += sqrt(sum_var);
+ nsum_tail += 1;
+ }
+ }
+
+ if (nsum_tail > 0)
+ {
+ sum = sum_tail/nsum_tail;
+ /* This is a worst case estimate, assuming all stddev's are correlated. */
+ *stddev = sum2_tail/nsum_tail;
+ }
+ else
+ {
+ *stddev = sqrt(sum_var);
+ }
+
+ return sum;
+}
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \libinternal
+ * \file
+ * \brief
+ * Declares routines for integrating a data set
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \inlibraryapi
+ * \ingroup module_correlationfunctions
+ */
+#ifndef GMX_INTEGRATE_H
+#define GMX_INTEGRATE_H
+
+#include <stdio.h>
+
+#include "gromacs/utility/real.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*! \brief
+ * Integrate the equispaced data in c[] from 0 to n using trapezium rule.
+ * If fit != NULL the fit is written as well.
+ * \param[in] fp File pointer to write to (maybe NULL)
+ * \param[in] n Number of data points
+ * \param[in] dt The time step between data points
+ * \param[in] c The data set
+ * \param[in] fit Fit to the function that is printed too if not a NULL pointer is passed.
+ * \param[in] nskip Determines whether all elements are written to the output file
+ * (written when i % nskip == 0)
+ * \return The integral
+ */
+real print_and_integrate(FILE *fp, int n, real dt, const real c[], const real *fit, int nskip);
+
+/*! \brief
+ * Integrate data in y using the trapezium rule, and, if given, use dy as weighting
+ *
+ * \param[in] n The number of data points
+ * \param[in] x The x coordinate
+ * \param[in] y The y data (function values)
+ * \param[in] dy The uncertainties (can be NULL)
+ * \param[in] aver_start should be set to a value where the function has
+ * converged to 0.
+ * \param[out] stddev The standard deviation in the integral
+ * \return the integral
+ */
+real evaluate_integral(int n, const real x[], const real y[], const real dy[], real aver_start,
+ real *stddev);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \internal \file
+ * \brief
+ * Implements function to compute many autocorrelation functions
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \ingroup module_correlationfunctions
+ */
+#include "gmxpre.h"
+
+#include "manyautocorrelation.h"
+
+#include <math.h>
+#include <stdio.h>
+#include <stdlib.h>
+
+#include "gromacs/fft/fft.h"
+#include "gromacs/legacyheaders/macros.h"
+#include "gromacs/utility/gmxomp.h"
+#include "gromacs/utility/smalloc.h"
+
+int many_auto_correl(int nfunc, int ndata, int nfft, real **c)
+{
+ #pragma omp parallel
+ {
+ typedef real complex[2];
+ int i, t, j, fftcode;
+ gmx_fft_t fft1;
+ complex *in, *out;
+ int i0, i1;
+ int nthreads, thread_id;
+
+ nthreads = gmx_omp_get_max_threads();
+ thread_id = gmx_omp_get_thread_num();
+ if ((0 == thread_id))
+ {
+ // fprintf(stderr, "There are %d threads for correlation functions\n", nthreads);
+ }
+ i0 = thread_id*nfunc/nthreads;
+ i1 = min(nfunc, (thread_id+1)*nfunc/nthreads);
+
+ fftcode = gmx_fft_init_1d(&fft1, nfft, GMX_FFT_FLAG_CONSERVATIVE);
+ /* Allocate temporary arrays */
+ snew(in, nfft);
+ snew(out, nfft);
+ for (i = i0; (i < i1); i++)
+ {
+ for (j = 0; j < ndata; j++)
+ {
+ in[j][0] = c[i][j];
+ in[j][1] = 0;
+ }
+ for (; (j < nfft); j++)
+ {
+ in[j][0] = in[j][1] = 0;
+ }
+
+ fftcode = gmx_fft_1d(fft1, GMX_FFT_BACKWARD, (void *)in, (void *)out);
+ for (j = 0; j < nfft; j++)
+ {
+ in[j][0] = (out[j][0]*out[j][0] + out[j][1]*out[j][1])/nfft;
+ in[j][1] = 0;
+ }
+ for (; (j < nfft); j++)
+ {
+ in[j][0] = in[j][1] = 0;
+ }
+
+ fftcode = gmx_fft_1d(fft1, GMX_FFT_FORWARD, (void *)in, (void *)out);
+ for (j = 0; (j < nfft); j++)
+ {
+ c[i][j] = out[j][0]/ndata;
+ }
+ }
+ /* Free the memory */
+ gmx_fft_destroy(fft1);
+ sfree(in);
+ sfree(out);
+ }
+ // gmx_fft_cleanup();
+ return 0;
+}
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \libinternal
+ * \file
+ * \brief
+ * Declares routine for computing many correlation functions using OpenMP
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \inlibraryapi
+ * \ingroup module_correlationfunctions
+ */
+#ifndef GMX_MANYAUTOCORRELATION_H
+#define GMX_MANYAUTOCORRELATION_H
+
+#include "gromacs/fft/fft.h"
+#include "gromacs/utility/real.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*! \brief
+ * Perform many autocorrelation calculations.
+ *
+ * This routine performs many autocorrelation function calculations using FFTs.
+ * The GROMACS FFT library wrapper is employed. On return the c[] arrays contain
+ * a symmetric function that is useful for further FFT:ing, for instance in order to
+ * compute spectra.
+ *
+ * The functions uses OpenMP parallellization.
+ *
+ * \param[in] nfunc Number of data functions to autocorrelate
+ * \param[in] ndata Number of valid data points in the data
+ * \param[in] nfft Length of the data arrays, this should at least be 50% larger than ndata. The c arrays will filled with zero beyond ndata before computing the correlation.
+ * \param[inout] c Data array of size nfunc x nfft, will also be used for output
+ * \return fft error code, or zero if everything went fine (see fft/fft.h)
+ */
+int many_auto_correl(int nfunc, int ndata, int nfft, real **c);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif
* To help us fund GROMACS development, we humbly ask that you cite
* the research papers on the package. Check out http://www.gromacs.org.
*/
+/*! \internal \file
+ * \brief
+ * Implements help function to compute Legendre polynomials
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \author Anders Gärdenäs <anders.gardenas@gmail.com>
+ * \ingroup module_correlationfunctions
+ */
#include "gmxpre.h"
-#include <math.h>
-#include <stdio.h>
+#include "polynomials.h"
-#include "gromacs/gmxana/gstat.h"
-#include "gromacs/legacyheaders/typedefs.h"
#include "gromacs/utility/fatalerror.h"
-real LegendreP(real x, unsigned long m)
+real LegendreP(real x, unsigned int m)
{
real polynomial = 0, x2, x3;
switch (m)
{
- case eacP0:
+ case 0:
polynomial = 1.0;
break;
- case eacP1:
+ case 1:
polynomial = x;
break;
- case eacP2:
+ case 2:
x2 = x*x;
polynomial = 1.5*x2 - 0.5;
break;
- case eacP3:
+ case 3:
+ x2 = x*x;
+ polynomial = (5*x2*x - 3*x )* 0.5;
+ break;
+ case 4:
x2 = x*x;
polynomial = (35*x2*x2 - 30*x2 + 3)/8;
break;
- case eacP4:
+ case 5:
x2 = x*x;
x3 = x2*x;
polynomial = (63*x3*x2 - 70*x3 + 15*x)/8;
break;
default:
- gmx_fatal(FARGS, "Legendre polynomials of order %d are not supported, %s %d",
- m, __FILE__, __LINE__);
+ gmx_fatal(FARGS, "Legendre polynomials of order %u are not supported", m);
}
return (polynomial);
}
/*
* This file is part of the GROMACS molecular simulation package.
*
- * Copyright (c) 1991-2000, University of Groningen, The Netherlands.
- * Copyright (c) 2001-2008, The GROMACS development team.
- * Copyright (c) 2013,2014, by the GROMACS development team, led by
+ * Copyright (c) 2014, by the GROMACS development team, led by
* Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
* and including many others, as listed in the AUTHORS file in the
* top-level source directory and at http://www.gromacs.org.
* To help us fund GROMACS development, we humbly ask that you cite
* the research papers on the package. Check out http://www.gromacs.org.
*/
+/*! \libinternal
+ * \file
+ * \brief
+ * Declares routine for computing a Legendre polynomial
+ *
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \inlibraryapi
+ * \ingroup module_correlationfunctions
+ */
+#ifndef GMX_POLYNOMIALS_H
+#define GMX_POLYNOMIALS_H
+#include "gromacs/utility/real.h"
-#ifndef _correl_h
-#define _correl_h
-
-#include "gromacs/fft/fft.h"
-#include "gromacs/legacyheaders/typedefs.h"
-
-typedef struct {
- int n;
- gmx_fft_t fft_setup;
- real *buf1, *buf2, *abuf;
-} correl_t;
+#ifdef __cplusplus
+extern "C" {
+#endif
-extern correl_t *init_correl(int n);
-extern void done_correl(correl_t *c);
+/*! \brief
+ * Return Legendre polynomial value Pm(x)
+ * http://en.wikipedia.org/wiki/Legendre_polynomials
+ * \param[in] x The value
+ * \param[in] m The order of the polynomial (0-4 are supported)
+ * \return Pm(x)
+ */
+real LegendreP(real x, unsigned int m);
-extern void correl(real data1[], real data2[], int n, real ans[]);
-extern void four1(real data[], int nn, int isign);
+#ifdef __cplusplus
+}
+#endif
#endif
--- /dev/null
+#
+# This file is part of the GROMACS molecular simulation package.
+#
+# Copyright (c) 2014, by the GROMACS development team, led by
+# Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+# and including many others, as listed in the AUTHORS file in the
+# top-level source directory and at http://www.gromacs.org.
+#
+# GROMACS is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public License
+# as published by the Free Software Foundation; either version 2.1
+# of the License, or (at your option) any later version.
+#
+# GROMACS is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with GROMACS; if not, see
+# http://www.gnu.org/licenses, or write to the Free Software Foundation,
+# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+#
+# If you want to redistribute modifications to GROMACS, please
+# consider that scientific software is very special. Version
+# control is crucial - bugs must be traceable. We will be happy to
+# consider code for inclusion in the official distribution, but
+# derived work must not be called official GROMACS. Details are found
+# in the README & COPYING files - if they are missing, get the
+# official version at http://www.gromacs.org.
+#
+# To help us fund GROMACS development, we humbly ask that you cite
+# the research papers on the package. Check out http://www.gromacs.org.
+
+gmx_add_unit_test(CorrelationsTest correlations-test
+ autocorr.cpp
+ correlationdataset.cpp
+ expfit.cpp)
+
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \internal \file
+ * \brief
+ * Implements test of autocorrelation function routines
+ *
+ * \author Anders Gärdenäs <anders.gardenas@gmail.com>
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \ingroup module_correlationfunctions
+ */
+#include "gmxpre.h"
+
+#include "gromacs/correlationfunctions/autocorr.h"
+
+#include <cmath>
+
+#include <gtest/gtest.h>
+
+#include "gromacs/correlationfunctions/expfit.h"
+#include "gromacs/fft/fft.h"
+#include "gromacs/legacyheaders/oenv.h"
+#include "gromacs/utility/gmxassert.h"
+#include "gromacs/utility/smalloc.h"
+#include "gromacs/utility/uniqueptr.h"
+
+#include "testutils/refdata.h"
+#include "testutils/testasserts.h"
+#include "testutils/testfilemanager.h"
+
+#include "correlationdataset.h"
+
+namespace gmx
+{
+namespace
+{
+
+//! Definition of pointer to class containing test data.
+typedef gmx_unique_ptr<CorrelationDataSet>::type CorrelationDataSetPointer;
+
+class AutocorrTest : public ::testing::Test
+{
+ protected:
+
+ static int nrFrames_;
+ static CorrelationDataSetPointer data_;
+ // Need raw pointer for passing this to C routines
+ static t_pargs * tempArgs_;
+
+ test::TestReferenceData refData_;
+ test::TestReferenceChecker checker_;
+
+ // Use erefdataCreateMissing for creating new files
+ AutocorrTest( )
+ : checker_(refData_.rootChecker())
+ {
+#ifdef GMX_DOUBLE
+ checker_.setDefaultTolerance(test::relativeToleranceAsFloatingPoint(1, 1e-6));
+#else
+ checker_.setDefaultTolerance(test::relativeToleranceAsFloatingPoint(1, 1e-3));
+#endif
+ }
+
+ // Static initiation, only run once every test.
+ static void SetUpTestCase()
+ {
+ int n = 0;
+ std::string fileName = "testCOS3.xvg";
+ data_ = CorrelationDataSetPointer(new CorrelationDataSet(fileName));
+ nrFrames_ = data_->getNrLines();
+ tempArgs_ = add_acf_pargs(&n, NULL);
+ }
+
+ static void TearDownTestCase()
+ {
+
+ sfree(tempArgs_);
+ tempArgs_ = NULL;
+ gmx_fft_cleanup();
+ }
+
+ void test(unsigned long mode)
+ {
+ bool bAverage = false;
+ bool bNormalize = true;
+ bool bVerbose = false;
+ int nrRestart = 1;
+ int dim = getDim(mode);
+ std::vector<real> result;
+
+ for (int i = 0; i < nrFrames_; i++)
+ {
+ for (int m = 0; m < dim; m++)
+ {
+ result.push_back(data_->getValue(m, i));
+ }
+ }
+ real *ptr = static_cast<real*>(&(result[0]));
+ low_do_autocorr(0, 0, 0, nrFrames_, 1,
+ get_acfnout(), &ptr, data_->getDt(), mode,
+ nrRestart, bAverage, bNormalize,
+ bVerbose, data_->getStartTime(), data_->getEndTime(),
+ effnNONE);
+
+ double testResult = 0;
+ for (int i = 0; i < nrFrames_; i++)
+ {
+ testResult += result[i];
+ }
+ checker_.checkSequenceArray(nrFrames_, ptr,
+ "AutocorrelationFunction");
+ checker_.checkReal(testResult, "Integral");
+ }
+
+ int getDim(unsigned long type)
+ {
+ switch (type)
+ {
+ case eacNormal:
+ return 1;
+ case eacVector:
+ return 3;
+ case eacCos:
+ return 1;
+ case eacRcross:
+ return 3;
+ case eacP0:
+ return 3;
+ case eacP1:
+ return 3;
+ case eacP2:
+ return 3;
+ case eacP3:
+ return 3;
+ case eacP4:
+ return 3;
+ case eacIden:
+ return 1;
+ default:
+ GMX_RELEASE_ASSERT(false, "Invalid auto correlation option");
+ return -1;
+ }
+
+ }
+
+};
+
+int AutocorrTest::nrFrames_;
+CorrelationDataSetPointer AutocorrTest::data_;
+t_pargs * AutocorrTest::tempArgs_;
+
+TEST_F (AutocorrTest, EacNormal)
+{
+ test(eacNormal);
+}
+
+TEST_F (AutocorrTest, EacCos)
+{
+ test(eacCos);
+}
+
+TEST_F (AutocorrTest, EacVector)
+{
+ test(eacVector);
+}
+
+TEST_F (AutocorrTest, EacRcross)
+{
+ test(eacRcross);
+}
+
+TEST_F (AutocorrTest, EacP0)
+{
+ test(eacP0);
+}
+
+TEST_F (AutocorrTest, EacP1)
+{
+ test(eacP1);
+}
+
+TEST_F (AutocorrTest, EacP2)
+{
+ test(eacP2);
+}
+
+TEST_F (AutocorrTest, EacP3)
+{
+ test(eacP3);
+}
+
+TEST_F (AutocorrTest, EacP4)
+{
+ test(eacP4);
+}
+
+
+}
+
+}
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \internal \file
+ * \brief
+ * Implements helper class for autocorrelation tests
+ *
+ * \author Anders Gärdenäs <anders.gardenas@gmail.com>
+ * \ingroup module_correlationfunctions
+ */
+#include "gmxpre.h"
+
+#include "correlationdataset.h"
+
+#include <cmath>
+
+#include <sstream>
+
+#include "gromacs/fileio/xvgr.h"
+#include "gromacs/legacyheaders/oenv.h"
+#include "gromacs/utility/smalloc.h"
+
+#include "testutils/testfilemanager.h"
+
+CorrelationDataSet::CorrelationDataSet(const std::string &fileName)
+{
+ std::string fileNm = gmx::test::TestFileManager::getInputFilePath(fileName.c_str());
+ nrLines_ = read_xvg(fileNm.c_str(), &tempValues_, &nrColumns_);
+
+ dt_ = tempValues_[0][1] - tempValues_[0][0];
+ startTime_ = tempValues_[0][0];
+ endTime_ = tempValues_[0][nrLines_-1];
+}
+
+CorrelationDataSet::~CorrelationDataSet()
+{
+ // Allocated in read_xvg, destroyed here.
+ for (int i = 0; i < nrColumns_; i++)
+ {
+ sfree(tempValues_[i]);
+ tempValues_[i] = NULL;
+ }
+ sfree(tempValues_);
+ tempValues_ = NULL;
+}
+
+real CorrelationDataSet::getValue(int set, int time) const
+{
+ if (set+1 < nrColumns_)
+ {
+ return tempValues_[set+1][time];
+ }
+ else
+ {
+ return 0;
+ }
+}
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \internal \file
+ * \brief
+ * Declares helper class for autocorrelation tests
+ *
+ * \author Anders Gärdenäs <anders.gardenas@gmail.com>
+ * \ingroup module_correlationfunctions
+ */
+#ifndef GMX_CORRELATIONDATASET_H
+#define GMX_CORRELATIONDATASET_H
+
+#include <string>
+#include <vector>
+
+#include "gromacs/utility/common.h"
+#include "gromacs/utility/real.h"
+
+class CorrelationDataSet
+{
+ double ** tempValues_;
+
+ int nrLines_;
+ int nrColumns_;
+ double startTime_;
+ double endTime_;
+ double dt_;
+
+ public:
+
+ /*! \brief
+ * Constructor
+ * \param[in] fileName containing function to test. *.xvg
+ */
+ explicit CorrelationDataSet(const std::string &fileName);
+
+ /*! \brief
+ * Return a value at an index
+ * \param[in] set the set number
+ * \param[in] t the time index of the value
+ */
+ real getValue(int set, int t) const;
+
+ /*! \brief
+ * Return the nummber of columns
+ */
+ int getNrColumns() const { return nrColumns_; }
+
+ /*! \brief
+ * Return the nummber of Lines
+ */
+ int getNrLines() const { return nrLines_; }
+
+ /*! \brief
+ * Return the time witch the function starts at
+ */
+ real getStartTime() const { return startTime_; }
+
+ /*! \brief
+ * Return the time the function ends at
+ */
+ real getEndTime() const { return endTime_; }
+
+ /*! \brief
+ * return delta time
+ */
+ real getDt() const { return dt_; }
+
+ /*! \brief
+ * Destructor
+ */
+ ~CorrelationDataSet();
+
+ private:
+ //! This class should not be copyable or assignable
+ GMX_DISALLOW_COPY_AND_ASSIGN(CorrelationDataSet);
+};
+
+#endif
--- /dev/null
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+/*! \internal \file
+ * \brief
+ * Implements test of exponential fitting routines
+ *
+ * \author Anders Gärdenäs <anders.gardenas@gmail.com>
+ * \author David van der Spoel <david.vanderspoel@icm.uu.se>
+ * \ingroup module_correlationfunctions
+ */
+#include "gmxpre.h"
+
+#include "gromacs/correlationfunctions/expfit.h"
+
+#include <cmath>
+
+#include <gtest/gtest.h>
+
+#include "gromacs/fileio/xvgr.h"
+#include "gromacs/utility/smalloc.h"
+
+#include "testutils/refdata.h"
+#include "testutils/testasserts.h"
+#include "testutils/testfilemanager.h"
+
+//! Number of data files for testing.
+#define expTestNrTypes 3
+
+namespace gmx
+{
+
+namespace
+{
+
+class ExpfitTest : public ::testing::Test
+{
+
+ protected:
+ static int nrLines_;
+ static std::vector<real> values_[expTestNrTypes];
+ static int nrColumns_;
+ static std::vector<real> standardDev_;
+ static real startTime_;
+ static real endTime_;
+ static real timeDeriv_;
+ test::TestReferenceData refData_;
+ test::TestReferenceChecker checker_;
+ ExpfitTest( )
+ : checker_(refData_.rootChecker())
+ {
+ }
+
+ // Static initiation, only run once every test.
+ static void SetUpTestCase()
+ {
+ double ** tempValues;
+ std::string fileName[expTestNrTypes];
+ fileName[0] = test::TestFileManager::getInputFilePath("testINVEXP.xvg");
+ fileName[1] = test::TestFileManager::getInputFilePath("testPRES.xvg");
+ fileName[2] = test::TestFileManager::getInputFilePath("testEXP.xvg");
+ for (int i = 0; i < expTestNrTypes; i++)
+ {
+ const char * name = fileName[i].c_str();
+ // TODO: this assumes all files have the same length.
+ nrLines_ = read_xvg(name, &tempValues, &nrColumns_);
+
+ // Generating standard deviation
+ if (i == 0)
+ {
+ double fac = 1.0/nrLines_;
+ for (int j = 0; j < nrLines_; j++)
+ {
+ standardDev_.push_back(fac);
+ }
+ timeDeriv_ = tempValues[0][1] - tempValues[0][0];
+ startTime_ = tempValues[0][0];
+ endTime_ = tempValues[0][nrLines_-1];
+ }
+
+ for (int j = 0; j < nrLines_; j++)
+ {
+ values_[i].push_back((real)tempValues[1][j]);
+ }
+
+ // Free memory that was allocated in read_xvg
+ for (int i = 0; i < nrColumns_; i++)
+ {
+ sfree(tempValues[i]);
+ tempValues[i] = NULL;
+ }
+ sfree(tempValues);
+ tempValues = NULL;
+ }
+ }
+
+ static void TearDownTestCase()
+ {
+ }
+
+ void test(int type, double result[], double tolerance, int testType)
+ {
+ int nfitparm = effnNparams(type);
+
+ do_lmfit(nrLines_, &values_[testType][0], &standardDev_[0], timeDeriv_,
+ NULL, startTime_, endTime_, NULL, false, type, result, 0);
+
+ checker_.setDefaultTolerance(test::relativeToleranceAsFloatingPoint(1, tolerance));
+ checker_.checkSequenceArray(nfitparm, result, "result");
+ }
+};
+
+
+//static var
+int ExpfitTest::nrLines_;
+std::vector<real> ExpfitTest::values_[expTestNrTypes];
+int ExpfitTest::nrColumns_;
+std::vector<real> ExpfitTest::standardDev_;
+real ExpfitTest::startTime_;
+real ExpfitTest::endTime_;
+real ExpfitTest::timeDeriv_;
+
+TEST_F (ExpfitTest, EffnEXP1) {
+ double param[] = {25};
+ test(effnEXP1, param, 1e-6, 0);
+}
+
+TEST_F (ExpfitTest, EffnEXP2) {
+ double param[] = {35, 0.5};
+ test(effnEXP2, param, 1e-6, 0);
+}
+
+TEST_F (ExpfitTest, EffnEXP3) {
+ double param[] = {45, 0.5, 5};
+ test(effnEXP3, param, 1e-4, 0);
+}
+
+TEST_F (ExpfitTest, EffnEXP5) {
+ double param[] = {0.5, 5, 0.5, 50, 0.002};
+ test(effnEXP5, param, 1e-4, 0);
+}
+
+TEST_F (ExpfitTest, EffnEXP7) {
+ double param[] = {0.5, 5, -0.02, 0.5, 0.5, 50, -0.002};
+ test(effnEXP7, param, 1e-4, 0);
+}
+
+TEST_F (ExpfitTest, EffnEXP9) {
+ double param[] = {2, 1200, -1, 300, 0.7, 70, 0.5, 6, -0.5};
+ test(effnEXP9, param, 4e-2, 0);
+}
+
+TEST_F (ExpfitTest, EffnERF) {
+ double param[] = {0.5, 0.5, 0.5, 1};
+ test(effnERF, param, 1e-2, 0);
+}
+
+TEST_F (ExpfitTest, EffnERREST) {
+ double param[] = {0.5, 0.7, 0.3};
+ test(effnERREST, param, 1e-4, 2);
+}
+
+TEST_F (ExpfitTest, EffnVAC) {
+ double param[] = {0.5, 0.05};
+ test(effnVAC, param, 1e-4, 0);
+}
+
+TEST_F (ExpfitTest, EffnPRES) {
+ double param[] = {0, 10, 4, 1, 0.5, 1};
+ test(effnPRES, param, 1e-4, 1);
+}
+
+}
+
+}
--- /dev/null
+<?xml version="1.0"?>
+<?xml-stylesheet type="text/xsl" href="referencedata.xsl"?>
+<ReferenceData>
+ <Sequence Name="AutocorrelationFunction">
+ <Int Name="Length">501</Int>
+ <Real>1</Real>
+ <Real>0.99659538</Real>
+ <Real>0.99595559</Real>
+ <Real>0.9944247</Real>
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static int wordcount(char *ptr)
{
- int i, n, is[2];
+ int i, n = 0, is[2];
int cur = 0;
#define prev (1-cur)
- if (strlen(ptr) == 0)
+ if (NULL != ptr)
{
- return 0;
- }
- /* fprintf(stderr,"ptr='%s'\n",ptr); */
- n = 1;
- for (i = 0; (ptr[i] != '\0'); i++)
- {
- is[cur] = isspace(ptr[i]);
- if ((i > 0) && (is[cur] && !is[prev]))
+ for (i = 0; (ptr[i] != '\0'); i++)
{
- n++;
+ is[cur] = isspace(ptr[i]);
+ if ((0 == i) && !is[cur])
+ {
+ n++;
+ }
+ else if ((i > 0) && (!is[cur] && is[prev]))
+ {
+ n++;
+ }
+ cur = prev;
}
- cur = prev;
}
return n;
}
*y = yy;
sfree(tmpbuf);
+ sfree(base);
+ sfree(fmt);
if (legend_nalloc > 0)
{
+++ /dev/null
-/*
- * This file is part of the GROMACS molecular simulation package.
- *
- * Copyright (c) 1991-2000, University of Groningen, The Netherlands.
- * Copyright (c) 2001-2008, The GROMACS development team.
- * Copyright (c) 2013,2014, by the GROMACS development team, led by
- * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
- * and including many others, as listed in the AUTHORS file in the
- * top-level source directory and at http://www.gromacs.org.
- *
- * GROMACS is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public License
- * as published by the Free Software Foundation; either version 2.1
- * of the License, or (at your option) any later version.
- *
- * GROMACS is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with GROMACS; if not, see
- * http://www.gnu.org/licenses, or write to the Free Software Foundation,
- * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
- *
- * If you want to redistribute modifications to GROMACS, please
- * consider that scientific software is very special. Version
- * control is crucial - bugs must be traceable. We will be happy to
- * consider code for inclusion in the official distribution, but
- * derived work must not be called official GROMACS. Details are found
- * in the README & COPYING files - if they are missing, get the
- * official version at http://www.gromacs.org.
- *
- * To help us fund GROMACS development, we humbly ask that you cite
- * the research papers on the package. Check out http://www.gromacs.org.
- */
-
-#include "gmxpre.h"
-
-#include "correl.h"
-
-#include <math.h>
-#include <stdio.h>
-#include <stdlib.h>
-
-#include "gromacs/fft/fft.h"
-#include "gromacs/utility/smalloc.h"
-
-#define SWAP(a, b) tempr = (a); (a) = (b); (b) = tempr
-
-void four1(real data[], int nn, int isign)
-{
- int n, mmax, m, j, istep, i;
- double wtemp, wr, wpr, wpi, wi, theta;
- real tempr, tempi;
-
- n = nn << 1;
- j = 1;
- for (i = 1; i < n; i += 2)
- {
- if (j > i)
- {
- SWAP(data[j], data[i]);
- SWAP(data[j+1], data[i+1]);
- }
- m = n >> 1;
- while (m >= 2 && j > m)
- {
- j -= m;
- m >>= 1;
- }
- j += m;
- }
- mmax = 2;
- while (n > mmax)
- {
- istep = 2*mmax;
- theta = 6.28318530717959/(isign*mmax);
- wtemp = sin(0.5*theta);
- wpr = -2.0*wtemp*wtemp;
- wpi = sin(theta);
- wr = 1.0;
- wi = 0.0;
- for (m = 1; m < mmax; m += 2)
- {
- for (i = m; i <= n; i += istep)
- {
- j = i+mmax;
- tempr = wr*data[j]-wi*data[j+1];
- tempi = wr*data[j+1]+wi*data[j];
- data[j] = data[i]-tempr;
- data[j+1] = data[i+1]-tempi;
- data[i] += tempr;
- data[i+1] += tempi;
- }
- wr = (wtemp = wr)*wpr-wi*wpi+wr;
- wi = wi*wpr+wtemp*wpi+wi;
- }
- mmax = istep;
- }
-}
-
-#undef SWAP
-
-static void realft(real data[], int n, int isign)
-{
- int i, i1, i2, i3, i4, n2p3;
- real c1 = 0.5, c2, h1r, h1i, h2r, h2i;
- double wr, wi, wpr, wpi, wtemp, theta;
-
- theta = 3.141592653589793/(double) n;
- if (isign == 1)
- {
- c2 = -0.5;
- four1(data, n, 1);
- }
- else
- {
- c2 = 0.5;
- theta = -theta;
- }
- wtemp = sin(0.5*theta);
- wpr = -2.0*wtemp*wtemp;
- wpi = sin(theta);
- wr = 1.0+wpr;
- wi = wpi;
- n2p3 = 2*n+3;
- for (i = 2; i <= n/2; i++)
- {
- i4 = 1+(i3 = n2p3-(i2 = 1+(i1 = i+i-1)));
- h1r = c1*(data[i1]+data[i3]);
- h1i = c1*(data[i2]-data[i4]);
- h2r = -c2*(data[i2]+data[i4]);
- h2i = c2*(data[i1]-data[i3]);
- data[i1] = h1r+wr*h2r-wi*h2i;
- data[i2] = h1i+wr*h2i+wi*h2r;
- data[i3] = h1r-wr*h2r+wi*h2i;
- data[i4] = -h1i+wr*h2i+wi*h2r;
- wr = (wtemp = wr)*wpr-wi*wpi+wr;
- wi = wi*wpr+wtemp*wpi+wi;
- }
- if (isign == 1)
- {
- data[1] = (h1r = data[1])+data[2];
- data[2] = h1r-data[2];
- }
- else
- {
- data[1] = c1*((h1r = data[1])+data[2]);
- data[2] = c1*(h1r-data[2]);
- four1(data, n, -1);
- }
-}
-
-static void twofft(real data1[], real data2[], real fft1[], real fft2[], int n)
-{
- int nn3, nn2, jj, j;
- real rep, rem, aip, aim;
-
- nn3 = 1+(nn2 = 2+n+n);
- for (j = 1, jj = 2; j <= n; j++, jj += 2)
- {
- fft1[jj-1] = data1[j];
- fft1[jj] = data2[j];
- }
- four1(fft1, n, 1);
- fft2[1] = fft1[2];
- fft1[2] = fft2[2] = 0.0;
- for (j = 3; j <= n+1; j += 2)
- {
- rep = 0.5*(fft1[j]+fft1[nn2-j]);
- rem = 0.5*(fft1[j]-fft1[nn2-j]);
- aip = 0.5*(fft1[j+1]+fft1[nn3-j]);
- aim = 0.5*(fft1[j+1]-fft1[nn3-j]);
- fft1[j] = rep;
- fft1[j+1] = aim;
- fft1[nn2-j] = rep;
- fft1[nn3-j] = -aim;
- fft2[j] = aip;
- fft2[j+1] = -rem;
- fft2[nn2-j] = aip;
- fft2[nn3-j] = rem;
- }
-}
-
-void correl(real data1[], real data2[], int n, real ans[])
-{
- int no2, i;
- real dum, *fft;
-
- snew(fft, 2*n+1);
- twofft(data1, data2, fft, ans, n);
- no2 = n/2;
- for (i = 2; i <= n+2; i += 2)
- {
- dum = ans[i-1];
- ans[i-1] = (fft[i-1]*dum+fft[i]*ans[i])/no2;
- ans[i] = (fft[i]*dum-fft[i-1]*ans[i])/no2;
- }
- ans[2] = ans[n+1];
- realft(ans, no2, -1);
- sfree(fft);
-}
+++ /dev/null
-/*
- * This file is part of the GROMACS molecular simulation package.
- *
- * Copyright (c) 1991-2000, University of Groningen, The Netherlands.
- * Copyright (c) 2001-2004, The GROMACS development team.
- * Copyright (c) 2013,2014, by the GROMACS development team, led by
- * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
- * and including many others, as listed in the AUTHORS file in the
- * top-level source directory and at http://www.gromacs.org.
- *
- * GROMACS is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public License
- * as published by the Free Software Foundation; either version 2.1
- * of the License, or (at your option) any later version.
- *
- * GROMACS is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with GROMACS; if not, see
- * http://www.gnu.org/licenses, or write to the Free Software Foundation,
- * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
- *
- * If you want to redistribute modifications to GROMACS, please
- * consider that scientific software is very special. Version
- * control is crucial - bugs must be traceable. We will be happy to
- * consider code for inclusion in the official distribution, but
- * derived work must not be called official GROMACS. Details are found
- * in the README & COPYING files - if they are missing, get the
- * official version at http://www.gromacs.org.
- *
- * To help us fund GROMACS development, we humbly ask that you cite
- * the research papers on the package. Check out http://www.gromacs.org.
- */
-#include "gmxpre.h"
-
-#include <math.h>
-#include <string.h>
-
-#include "gromacs/fileio/xvgr.h"
-#include "gromacs/gmxana/gstat.h"
-#include "gromacs/legacyheaders/typedefs.h"
-#include "gromacs/math/vec.h"
-#include "gromacs/utility/fatalerror.h"
-#include "gromacs/utility/futil.h"
-#include "gromacs/utility/smalloc.h"
-
-const int nfp_ffn[effnNR] = { 0, 1, 2, 3, 2, 5, 7, 9, 4, 3};
-
-const char *s_ffn[effnNR+2] = {
- NULL, "none", "exp", "aexp", "exp_exp", "vac",
- "exp5", "exp7", "exp9", "erffit", NULL, NULL
-};
-/* We don't allow errest as a choice on the command line */
-
-const char *longs_ffn[effnNR] = {
- "no fit",
- "y = exp(-x/a1)",
- "y = a2 exp(-x/a1)",
- "y = a2 exp(-x/a1) + (1-a2) exp(-x/a3)",
- "y = exp(-v) (cosh(wv) + 1/w sinh(wv)), v = x/(2 a1), w = sqrt(1 - a2)",
- "y = a1 exp(-x/a2) + a3 exp(-x/a4) + a5",
- "y = a1 exp(-x/a2) + a3 exp(-x/a4) + a5 exp(-x/a6) + a7",
- "y = a1 exp(-x/a2) + a3 exp(-x/a4) + a5 exp(-x/a6) + a7 exp(-x/a8) + a9",
- "y = 1/2*(a1+a2) - 1/2*(a1-a2)*erf( (x-a3) /a4^2)",
- "y = a2*ee(a1,x) + (1-a2)*ee(a2,x)"
-};
-
-extern gmx_bool mrqmin_new(real x[], real y[], real sig[], int ndata, real a[],
- int ia[], int ma, real **covar, real **alpha, real *chisq,
- void (*funcs)(real, real [], real *, real []),
- real *alamda);
-
-static real myexp(real x, real A, real tau)
-{
- if ((A == 0) || (tau == 0))
- {
- return 0;
- }
- return A*exp(-x/tau);
-}
-
-void erffit (real x, real a[], real *y, real dyda[])
-{
-/* Fuction
- * y=(a1+a2)/2-(a1-a2)/2*erf((x-a3)/a4^2)
- */
-
- real erfarg;
- real erfval;
- real erfarg2;
- real derf;
-
- erfarg = (x-a[3])/(a[4]*a[4]);
- erfarg2 = erfarg*erfarg;
- erfval = gmx_erf(erfarg)/2;
- derf = M_2_SQRTPI*(a[1]-a[2])/2*exp(-erfarg2)/(a[4]*a[4]);
- *y = (a[1]+a[2])/2-(a[1]-a[2])*erfval;
- dyda[1] = 1/2-erfval;
- dyda[2] = 1/2+erfval;
- dyda[3] = derf;
- dyda[4] = 2*derf*erfarg;
-}
-
-
-
-static void exp_one_parm(real x, real a[], real *y, real dyda[])
-{
- /* Fit to function
- *
- * y = exp(-x/a1)
- *
- */
-
- real e1;
-
- e1 = exp(-x/a[1]);
- *y = e1;
- dyda[1] = x*e1/sqr(a[1]);
-}
-
-static void exp_two_parm(real x, real a[], real *y, real dyda[])
-{
- /* Fit to function
- *
- * y = a2 exp(-x/a1)
- *
- */
-
- real e1;
-
- e1 = exp(-x/a[1]);
- *y = a[2]*e1;
- dyda[1] = x*a[2]*e1/sqr(a[1]);
- dyda[2] = e1;
-}
-
-static void exp_3_parm(real x, real a[], real *y, real dyda[])
-{
- /* Fit to function
- *
- * y = a2 exp(-x/a1) + (1-a2) exp(-x/a3)
- *
- */
-
- real e1, e2;
-
- e1 = exp(-x/a[1]);
- e2 = exp(-x/a[3]);
- *y = a[2]*e1 + (1-a[2])*e2;
- dyda[1] = x*a[2]*e1/sqr(a[1]);
- dyda[2] = e1-e2;
- dyda[3] = x*(1-a[2])*e2/sqr(a[3]);
-}
-
-static void exp_5_parm(real x, real a[], real *y, real dyda[])
-{
- /* Fit to function
- *
- * y = a1 exp(-x/a2) + a3 exp(-x/a4) + a5
- *
- */
-
- real e1, e2;
-
- e1 = exp(-x/a[2]);
- e2 = exp(-x/a[4]);
- *y = a[1]*e1 + a[3]*e2 + a[5];
-
- if (debug)
- {
- fprintf(debug, "exp_5_parm called: x = %10.3f y = %10.3f\n"
- "a = ( %8.3f %8.3f %8.3f %8.3f %8.3f)\n",
- x, *y, a[1], a[2], a[3], a[4], a[5]);
- }
- dyda[1] = e1;
- dyda[2] = x*e1/sqr(a[2]);
- dyda[3] = e2;
- dyda[4] = x*e2/sqr(a[4]);
- dyda[5] = 0;
-}
-
-static void exp_7_parm(real x, real a[], real *y, real dyda[])
-{
- /* Fit to function
- *
- * y = a1 exp(-x/a2) + a3 exp(-x/a4) + a5 exp(-x/a6) + a7
- *
- */
-
- real e1, e2, e3;
-
- e1 = exp(-x/a[2]);
- e2 = exp(-x/a[4]);
- e3 = exp(-x/a[6]);
- *y = a[1]*e1 + a[3]*e2 + a[5]*e3 + a[7];
-
- dyda[1] = e1;
- dyda[2] = x*e1/sqr(a[2]);
- dyda[3] = e2;
- dyda[4] = x*e2/sqr(a[4]);
- dyda[5] = e3;
- dyda[6] = x*e3/sqr(a[6]);
- dyda[7] = 0;
-}
-
-static void exp_9_parm(real x, real a[], real *y, real dyda[])
-{
- /* Fit to function
- *
- * y = a1 exp(-x/a2) + a3 exp(-x/a4) + a5 exp(-x/a6) + a7
- *
- */
-
- real e1, e2, e3, e4;
-
- e1 = exp(-x/a[2]);
- e2 = exp(-x/a[4]);
- e3 = exp(-x/a[6]);
- e4 = exp(-x/a[8]);
- *y = a[1]*e1 + a[3]*e2 + a[5]*e3 + a[7]*e4 + a[9];
-
- dyda[1] = e1;
- dyda[2] = x*e1/sqr(a[2]);
- dyda[3] = e2;
- dyda[4] = x*e2/sqr(a[4]);
- dyda[5] = e3;
- dyda[6] = x*e3/sqr(a[6]);
- dyda[7] = e4;
- dyda[8] = x*e4/sqr(a[8]);
- dyda[9] = 0;
-}
-
-static void vac_2_parm(real x, real a[], real *y, real dyda[])
-{
- /* Fit to function
- *
- * y = 1/2 (1 - 1/w) exp(-(1+w)v) + 1/2 (1 + 1/w) exp(-(1-w)v)
- *
- * = exp(-v) (cosh(wv) + 1/w sinh(wv))
- *
- * v = x/(2 a1)
- * w = sqrt(1 - a2)
- *
- * For tranverse current autocorrelation functions:
- * a1 = tau
- * a2 = 4 tau (eta/rho) k^2
- *
- */
-
- double v, det, omega, omega2, em, ec, es;
-
- v = x/(2*a[1]);
- det = 1 - a[2];
- em = exp(-v);
- if (det != 0)
- {
- omega2 = fabs(det);
- omega = sqrt(omega2);
- if (det > 0)
- {
- ec = em*0.5*(exp(omega*v)+exp(-omega*v));
- es = em*0.5*(exp(omega*v)-exp(-omega*v))/omega;
- }
- else
- {
- ec = em*cos(omega*v);
- es = em*sin(omega*v)/omega;
- }
- *y = ec + es;
- dyda[2] = (v/det*ec+(v-1/det)*es)/(-2.0);
- dyda[1] = (1-det)*v/a[1]*es;
- }
- else
- {
- *y = (1+v)*em;
- dyda[2] = -v*v*em*(0.5+v/6);
- dyda[1] = v*v/a[1]*em;
- }
-}
-
-static void errest_3_parm(real x, real a[], real *y, real dyda[])
-{
- real e1, e2, v1, v2;
-
- if (a[1])
- {
- e1 = exp(-x/a[1]) - 1;
- }
- else
- {
- e1 = 0;
- }
- if (a[3])
- {
- e2 = exp(-x/a[3]) - 1;
- }
- else
- {
- e2 = 0;
- }
-
- if (x > 0)
- {
- v1 = 2*a[1]*(e1*a[1]/x + 1);
- v2 = 2*a[3]*(e2*a[3]/x + 1);
- *y = a[2]*v1 + (1-a[2])*v2;
- dyda[1] = 2* a[2] *(v1/a[1] + e1);
- dyda[3] = 2*(1 - a[2])*(v2/a[3] + e2);
- dyda[2] = (v1 - v2);
- }
- else
- {
- *y = 0;
- dyda[1] = 0;
- dyda[3] = 0;
- dyda[2] = 0;
- }
-}
-
-typedef void (*myfitfn)(real x, real a[], real *y, real dyda[]);
-myfitfn mfitfn[effnNR] = {
- exp_one_parm, exp_one_parm, exp_two_parm, exp_3_parm, vac_2_parm,
- exp_5_parm, exp_7_parm, exp_9_parm, erffit, errest_3_parm
-};
-
-real fit_function(int eFitFn, real *parm, real x)
-{
- static real y, dum[8];
-
- mfitfn[eFitFn](x, parm-1, &y, dum);
-
- return y;
-}
-
-/* lmfit_exp supports up to 3 parameter fitting of exponential functions */
-static gmx_bool lmfit_exp(int nfit, real x[], real y[], real dy[], real ftol,
- real parm[], real dparm[], gmx_bool bVerbose,
- int eFitFn, int fix)
-{
- real chisq, ochisq, alamda;
- real *a, **covar, **alpha, *dum;
- gmx_bool bCont;
- int i, j, ma, mfit, *lista, *ia;
-
- if ((eFitFn < 0) || (eFitFn >= effnNR))
- {
- gmx_fatal(FARGS, "fitfn = %d, should be in 0..%d (%s,%d)",
- effnNR-1, eFitFn, __FILE__, __LINE__);
- }
-
- ma = mfit = nfp_ffn[eFitFn]; /* number of parameters to fit */
- snew(a, ma+1);
- snew(covar, ma+1);
- snew(alpha, ma+1);
- snew(lista, ma+1);
- snew(ia, ma+1);
- snew(dum, ma+1);
- for (i = 1; (i < ma+1); i++)
- {
- lista[i] = i;
- ia[i] = 1; /* fixed bug B.S.S 19/11 */
- snew(covar[i], ma+1);
- snew(alpha[i], ma+1);
- }
- if (fix)
- {
- if (bVerbose)
- {
- fprintf(stderr, "Will keep parameters fixed during fit procedure: %d\n",
- fix);
- }
- for (i = 0; i < ma; i++)
- {
- if (fix & 1<<i)
- {
- ia[i+1] = 0;
- }
- }
- }
- if (debug)
- {
- fprintf(debug, "%d parameter fit\n", mfit);
- }
-
- /* Initial params */
- alamda = -1; /* Starting value */
- chisq = 1e12;
- for (i = 0; (i < mfit); i++)
- {
- a[i+1] = parm[i];
- }
-
- j = 0;
- if (bVerbose)
- {
- fprintf(stderr, "%4s %10s %10s %10s %10s %10s %10s\n",
- "Step", "chi^2", "Lambda", "A1", "A2", "A3", "A4");
- }
- do
- {
- ochisq = chisq;
- /* mrqmin(x-1,y-1,dy-1,nfit,a,ma,lista,mfit,covar,alpha,
- * &chisq,expfn[mfit-1],&alamda)
- */
- if (!mrqmin_new(x-1, y-1, dy-1, nfit, a, ia, ma, covar, alpha, &chisq,
- mfitfn[eFitFn], &alamda))
- {
- return FALSE;
- }
-
- if (bVerbose)
- {
- fprintf(stderr, "%4d %10.5e %10.5e %10.5e",
- j, chisq, alamda, a[1]);
- if (mfit > 1)
- {
- fprintf(stderr, " %10.5e", a[2]);
- }
- if (mfit > 2)
- {
- fprintf(stderr, " %10.5e", a[3]);
- }
- if (mfit > 3)
- {
- fprintf(stderr, " %10.5e", a[4]);
- }
- fprintf(stderr, "\n");
- }
- j++;
- bCont = ((fabs(ochisq - chisq) > fabs(ftol*chisq)) ||
- ((ochisq == chisq)));
- }
- while (bCont && (alamda != 0.0) && (j < 50));
- if (bVerbose)
- {
- fprintf(stderr, "\n");
- }
-
- /* Now get the covariance matrix out */
- alamda = 0;
-
- /* mrqmin(x-1,y-1,dy-1,nfit,a,ma,lista,mfit,covar,alpha,
- * &chisq,expfn[mfit-1],&alamda)
- */
- if (!mrqmin_new(x-1, y-1, dy-1, nfit, a, ia, ma, covar, alpha, &chisq,
- mfitfn[eFitFn], &alamda))
- {
- return FALSE;
- }
-
- for (j = 0; (j < mfit); j++)
- {
- parm[j] = a[j+1];
- dparm[j] = covar[j+1][j+1];
- }
-
- for (i = 0; (i < ma+1); i++)
- {
- sfree(covar[i]);
- sfree(alpha[i]);
- }
- sfree(a);
- sfree(covar);
- sfree(alpha);
- sfree(lista);
- sfree(dum);
-
- return TRUE;
-}
-
-real do_lmfit(int ndata, real c1[], real sig[], real dt, real x0[],
- real begintimefit, real endtimefit, const output_env_t oenv,
- gmx_bool bVerbose, int eFitFn, real fitparms[], int fix)
-{
- FILE *fp;
- char buf[32];
-
- int i, j, nparm, nfitpnts;
- real integral, ttt;
- real *parm, *dparm;
- real *x, *y, *dy;
- real ftol = 1e-4;
-
- nparm = nfp_ffn[eFitFn];
- if (debug)
- {
- fprintf(debug, "There are %d points to fit %d vars!\n", ndata, nparm);
- fprintf(debug, "Fit to function %d from %g through %g, dt=%g\n",
- eFitFn, begintimefit, endtimefit, dt);
- }
-
- snew(x, ndata);
- snew(y, ndata);
- snew(dy, ndata);
-
- j = 0;
- for (i = 0; i < ndata; i++)
- {
- ttt = x0 ? x0[i] : dt*i;
- if (ttt >= begintimefit && ttt <= endtimefit)
- {
- x[j] = ttt;
- y[j] = c1[i];
-
- /* mrqmin does not like sig to be zero */
- if (sig[i] < 1.0e-7)
- {
- dy[j] = 1.0e-7;
- }
- else
- {
- dy[j] = sig[i];
- }
- if (debug)
- {
- fprintf(debug, "j= %d, i= %d, x= %g, y= %g, dy= %g\n",
- j, i, x[j], y[j], dy[j]);
- }
- j++;
- }
- }
- nfitpnts = j;
- integral = 0;
- if (nfitpnts < nparm)
- {
- fprintf(stderr, "Not enough data points for fitting!\n");
- }
- else
- {
- snew(parm, nparm);
- snew(dparm, nparm);
- if (fitparms)
- {
- for (i = 0; (i < nparm); i++)
- {
- parm[i] = fitparms[i];
- }
- }
-
- if (!lmfit_exp(nfitpnts, x, y, dy, ftol, parm, dparm, bVerbose, eFitFn, fix))
- {
- fprintf(stderr, "Fit failed!\n");
- }
- else if (nparm <= 3)
- {
- /* Compute the integral from begintimefit */
- if (nparm == 3)
- {
- integral = (parm[0]*myexp(begintimefit, parm[1], parm[0]) +
- parm[2]*myexp(begintimefit, 1-parm[1], parm[2]));
- }
- else if (nparm == 2)
- {
- integral = parm[0]*myexp(begintimefit, parm[1], parm[0]);
- }
- else if (nparm == 1)
- {
- integral = parm[0]*myexp(begintimefit, 1, parm[0]);
- }
- else
- {
- gmx_fatal(FARGS, "nparm = %d in file %s, line %d",
- nparm, __FILE__, __LINE__);
- }
-
- /* Generate THE output */
- if (bVerbose)
- {
- fprintf(stderr, "FIT: # points used in fit is: %d\n", nfitpnts);
- fprintf(stderr, "FIT: %21s%21s%21s\n",
- "parm0 ", "parm1 (ps) ", "parm2 (ps) ");
- fprintf(stderr, "FIT: ------------------------------------------------------------\n");
- fprintf(stderr, "FIT: %8.3g +/- %8.3g%9.4g +/- %8.3g%8.3g +/- %8.3g\n",
- parm[0], dparm[0], parm[1], dparm[1], parm[2], dparm[2]);
- fprintf(stderr, "FIT: Integral (calc with fitted function) from %g ps to inf. is: %g\n",
- begintimefit, integral);
-
- sprintf(buf, "test%d.xvg", nfitpnts);
- fp = xvgropen(buf, "C(t) + Fit to C(t)", "Time (ps)", "C(t)", oenv);
- fprintf(fp, "# parm0 = %g, parm1 = %g, parm2 = %g\n",
- parm[0], parm[1], parm[2]);
- for (j = 0; (j < nfitpnts); j++)
- {
- ttt = x0 ? x0[j] : dt*j;
- fprintf(fp, "%10.5e %10.5e %10.5e\n",
- ttt, c1[j], fit_function(eFitFn, parm, ttt));
- }
- xvgrclose(fp);
- }
- }
- if (fitparms)
- {
- for (i = 0; (i < nparm); i++)
- {
- fitparms[i] = parm[i];
- }
- }
- sfree(parm);
- sfree(dparm);
- }
-
- sfree(x);
- sfree(y);
- sfree(dy);
-
- return integral;
-}
-
-void do_expfit(int ndata, real c1[], real dt, real begintimefit, real endtimefit)
-{
- int i, n;
- real *x, *y, *Dy;
- real aa, bb, saa, sbb, A, tau, dA, dtau;
-
- fprintf(stderr, "Will fit data from %g (ps) to %g (ps).\n",
- begintimefit, endtimefit);
-
- snew(x, ndata); /* allocate the maximum necessary space */
- snew(y, ndata);
- snew(Dy, ndata);
- n = 0;
-
- for (i = 0; (i < ndata); i++)
- {
- if ( (dt*i >= begintimefit) && (dt*i <= endtimefit) )
- {
- x[n] = dt*i;
- y[n] = c1[i];
- Dy[n] = 0.5;
- fprintf(stderr, "n= %d, i= %d, x= %g, y= %g\n", n, i, x[n], y[n]);
- n++;
- }
- }
- fprintf(stderr, "# of data points used in the fit is : %d\n\n", n);
- expfit(n, x, y, Dy, &aa, &saa, &bb, &sbb);
-
- A = exp(aa);
- dA = exp(aa)*saa;
- tau = -1.0/bb;
- dtau = sbb/sqr(bb);
- fprintf(stderr, "Fitted to y=exp(a+bx):\n");
- fprintf(stderr, "a = %10.5f\t b = %10.5f", aa, bb);
- fprintf(stderr, "\n");
- fprintf(stderr, "Fitted to y=Aexp(-x/tau):\n");
- fprintf(stderr, "A = %10.5f\t tau = %10.5f\n", A, tau);
- fprintf(stderr, "dA = %10.5f\t dtau = %10.5f\n", dA, dtau);
-}
-
-
-void expfit(int n, real *x, real *y, real *Dy, real *a, real *sa,
- real *b, real *sb)
-{
- real *w, *ly, A, SA, B, SB;
- int i;
- real sum, xbar, ybar, Sxx, Sxy, wr2, chi2, gamma, Db;
-
-#define ZERO 0.0
-#define ONE 1.0
-#define ONEP5 1.5
-#define TWO 2.0
-
-#define sqr(x) ((x)*(x))
-
- /*allocate memory */
- snew(w, n);
- snew(ly, n);
-
- /* Calculate weights and values of ln(y). */
- for (i = 0; (i < n); i++)
- {
- w[i] = sqr(y[i]/Dy[i]);
- ly[i] = log(y[i]);
- }
-
- /* The weighted averages of x and y: xbar and ybar. */
- sum = ZERO;
- xbar = ZERO;
- ybar = ZERO;
- for (i = 0; (i < n); i++)
- {
- sum += w[i];
- xbar += w[i]*x[i];
- ybar += w[i]*ly[i];
- }
- xbar /= sum;
- ybar /= sum;
-
- /* The centered product sums Sxx and Sxy, and hence A and B. */
- Sxx = ZERO;
- Sxy = ZERO;
- for (i = 0; (i < n); i++)
- {
- Sxx += w[i]*sqr(x[i]-xbar);
- Sxy += w[i]*(x[i]-xbar)*(ly[i]-ybar);
- }
- B = Sxy/Sxx;
- A = ybar-B*xbar;
-
- /* Chi-squared (chi2) and gamma. */
- chi2 = ZERO;
- gamma = ZERO;
- for (i = 0; (i < n); i++)
- {
- wr2 = w[i]*sqr(ly[i]-A-B*x[i]);
- chi2 += wr2;
- gamma += wr2*(x[i]-xbar);
- }
-
- /* Refined values of A and B. Also SA and SB. */
- Db = -ONEP5*gamma/Sxx;
- B += Db;
- A -= ONEP5*chi2/sum-xbar*Db;
- SB = sqrt((chi2/(n-2))/Sxx);
- SA = SB*sqrt(Sxx/sum+sqr(xbar));
- *a = A;
- *b = B;
- *sa = SA;
- *sb = SB;
-}
#include <string.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
+#include "gromacs/correlationfunctions/expfit.h"
+#include "gromacs/correlationfunctions/integrate.h"
#include "gromacs/fileio/xvgr.h"
#include "gromacs/gmxana/geminate.h"
#include "gromacs/gmxana/gmx_ana.h"
}
}
-static real anal_ee_inf(real *parm, real T)
+static real anal_ee_inf(double *parm, real T)
{
return sqrt(parm[1]*2*parm[0]/T+parm[3]*2*parm[2]/T);
}
double blav, var;
char **leg;
real *tbs, *ybs, rtmp, dens, *fitsig, twooe, tau1_est, tau_sig;
- real fitparm[4];
+ double fitparm[4];
real ee, a, tau1, tau2;
if (n < 4)
if (bFitAc)
{
- int fitlen;
- real *ac, acint, ac_fit[4];
+ int fitlen;
+ real *ac, acint;
+ double ac_fit[4];
snew(ac, n);
for (i = 0; i < n; i++)
int ny, real *x0, real **val,
int npargs, t_pargs *ppa, const output_env_t oenv)
{
- real *c1 = NULL, *sig = NULL, *fitparm;
- real tendfit, tbeginfit;
- int i, efitfn, nparm;
+ real *c1 = NULL, *sig = NULL;
+ double *fitparm;
+ real tendfit, tbeginfit;
+ int i, efitfn, nparm;
efitfn = get_acffitfn();
- nparm = nfp_ffn[efitfn];
+ nparm = effnNparams(efitfn);
fprintf(out, "Will fit to the following function:\n");
- fprintf(out, "%s\n", longs_ffn[efitfn]);
+ fprintf(out, "%s\n", effnDescription(efitfn));
c1 = val[n];
if (bYdy)
{
#include <string.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
#include "gromacs/fileio/trnio.h"
#include "gromacs/fileio/xvgr.h"
#include "gromacs/gmxana/gmx_ana.h"
#include "gromacs/utility/futil.h"
#include "gromacs/utility/smalloc.h"
-
static void dump_dih_trn(int nframes, int nangles, real **dih, const char *fn,
real *time)
{
#include <string.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
#include "gromacs/fileio/confio.h"
#include "gromacs/fileio/matio.h"
#include "gromacs/fileio/pdbio.h"
#include "gromacs/utility/fatalerror.h"
#include "gromacs/utility/futil.h"
#include "gromacs/utility/smalloc.h"
+#include "gmx_ana.h"
static gmx_bool bAllowed(real phi, real psi)
{
#include <string.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
+#include "gromacs/correlationfunctions/expfit.h"
#include "gromacs/fileio/matio.h"
#include "gromacs/fileio/tpxio.h"
#include "gromacs/fileio/trxio.h"
t_interf ****intf2, const output_env_t oenv)
{
/*Returns two pointers to 3D arrays of t_interf structs containing (position,thickness) of the interface(s)*/
- FILE *xvg;
- real *zDensavg; /* zDensavg[z]*/
- int i, j, k, n;
- int xysize;
- int ndx1, ndx2, *zperm;
- real densmid;
- real splitpoint, startpoint, endpoint;
- real *sigma1, *sigma2;
- real beginfit1[4];
- real beginfit2[4];
- real *fit1 = NULL, *fit2 = NULL;
- const real *avgfit1;
- const real *avgfit2;
- const real onehalf = 1.00/2.00;
- t_interf ***int1 = NULL, ***int2 = NULL; /*Interface matrices [t][x,y] - last index in row-major order*/
+ FILE *xvg;
+ real *zDensavg; /* zDensavg[z]*/
+ int i, j, k, n;
+ int xysize;
+ int ndx1, ndx2, *zperm;
+ real densmid;
+ real splitpoint, startpoint, endpoint;
+ real *sigma1, *sigma2;
+ double beginfit1[4];
+ double beginfit2[4];
+ double *fit1 = NULL, *fit2 = NULL;
+ const double *avgfit1;
+ const double *avgfit2;
+ const real onehalf = 1.00/2.00;
+ t_interf ***int1 = NULL, ***int2 = NULL; /*Interface matrices [t][x,y] - last index in row-major order*/
/*Create int1(t,xy) and int2(t,xy) arrays with correct number of interf_t elements*/
xysize = xslices*yslices;
snew(int1, tblocks);
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
+#include <string.h>
+#include "gromacs/correlationfunctions/expfit.h"
+#include "gromacs/correlationfunctions/integrate.h"
+#include "gromacs/fft/fft.h"
#include "gromacs/fileio/xvgr.h"
-#include "gromacs/gmxana/correl.h"
#include "gromacs/gmxana/gmx_ana.h"
#include "gromacs/gmxana/gstat.h"
#include "gromacs/legacyheaders/copyrite.h"
#include "gromacs/utility/fatalerror.h"
#include "gromacs/utility/futil.h"
#include "gromacs/utility/smalloc.h"
+#include "gromacs/utility/fatalerror.h"
+#include "gromacs/math/gmxcomplex.h"
+#include "gromacs/math/utilities.h"
+#include "gmx_ana.h"
/* Determines at which point in the array the fit should start */
int calc_nbegin(int nx, real x[], real tbegin)
t_complex *tmp, gw, hw, kw;
int i, nnx, nxsav;
real fac, nu, dt, *ptr, maxeps, numax;
+ gmx_fft_t fft;
+ int fftcode;
nxsav = nx;
/*while ((dy[nx-1] == 0.0) && (nx > 0))
{
nnx *= 2;
}
+
snew(tmp, 2*nnx);
printf("Doing FFT of %d points\n", nnx);
for (i = 0; (i < nx); i++)
{
tmp[i].re = dy[i];
}
- ptr = &tmp[0].re;
- four1(ptr-1, nnx, -1);
-
+ if ((fftcode = gmx_fft_init_1d_real(&fft, nnx,
+ GMX_FFT_FLAG_NONE)) != 0)
+ {
+ gmx_fatal(FARGS, "gmx_fft_init_1d_real returned %d", fftcode);
+ }
+ if ((fftcode = gmx_fft_1d_real(fft, GMX_FFT_COMPLEX_TO_REAL,
+ (void *)tmp, (void *)tmp)) != 0)
+ {
+ gmx_fatal(FARGS, "gmx_fft_1d_real returned %d", fftcode);
+ }
+ gmx_fft_destroy(fft);
dt = x[1]-x[0];
if (epsRF == 0)
{
#define NFILE asize(fnm)
output_env_t oenv;
int i, j, nx, ny, nxtail, eFitFn, nfitparm;
- real dt, integral, fitintegral, *fitparms, fac, rffac;
+ real dt, integral, fitintegral, fac, rffac;
+ double *fitparms;
double **yd;
real **y;
const char *legend[] = { "Correlation", "Std. Dev.", "Fit", "Combined", "Derivative" };
- static int fix = 0, bFour = 0, bX = 1, nsmooth = 3;
+ static int fix = 0, bX = 1, nsmooth = 3;
static real tendInt = 5.0, tbegin = 5.0, tend = 500.0;
static real A = 0.5, tau1 = 10.0, tau2 = 1.0, eps0 = 80, epsRF = 78.5, tail = 500.0;
real lambda;
t_pargs pa[] = {
- { "-fft", FALSE, etBOOL, {&bFour},
- "use fast fourier transform for correlation function" },
{ "-x1", FALSE, etBOOL, {&bX},
"use first column as [IT]x[it]-axis rather than first data set" },
{ "-eint", FALSE, etREAL, {&tendInt},
}
eFitFn = sffn2effn(s_ffn);
- nfitparm = nfp_ffn[eFitFn];
+ nfitparm = effnNparams(eFitFn);
snew(fitparms, 4);
fitparms[0] = tau1;
if (nfitparm > 1)
#include <algorithm>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
#include "gromacs/fileio/enxio.h"
#include "gromacs/fileio/matio.h"
#include "gromacs/fileio/trxio.h"
#include "gromacs/fileio/xvgr.h"
#include "gromacs/gmxana/gmx_ana.h"
-#include "gromacs/gmxana/gstat.h"
#include "gromacs/legacyheaders/calcmu.h"
#include "gromacs/legacyheaders/copyrite.h"
#include "gromacs/legacyheaders/macros.h"
#include <string.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
+#include "gromacs/correlationfunctions/integrate.h"
#include "gromacs/fft/fft.h"
#include "gromacs/fileio/confio.h"
#include "gromacs/fileio/trxio.h"
#include "gromacs/fileio/xvgr.h"
-#include "gromacs/gmxana/correl.h"
#include "gromacs/gmxana/gmx_ana.h"
-#include "gromacs/gmxana/gstat.h"
#include "gromacs/legacyheaders/copyrite.h"
#include "gromacs/legacyheaders/macros.h"
#include "gromacs/legacyheaders/txtdump.h"
#include "gromacs/utility/fatalerror.h"
#include "gromacs/utility/futil.h"
#include "gromacs/utility/smalloc.h"
+#include "gmx_ana.h"
enum {
VACF, MVACF, DOS, DOS_SOLID, DOS_DIFF, DOS_CP, DOS_S, DOS_A, DOS_E, DOS_NR
#include <string.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
#include "gromacs/fileio/enxio.h"
#include "gromacs/fileio/tpxio.h"
#include "gromacs/fileio/trxio.h"
#include <string.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
#include "gromacs/fileio/tpxio.h"
#include "gromacs/fileio/trxio.h"
#include "gromacs/fileio/xvgr.h"
#include "gromacs/utility/fatalerror.h"
#include "gromacs/utility/futil.h"
#include "gromacs/utility/smalloc.h"
+#include "gmx_ana.h"
real calc_gyro(rvec x[], int gnx, atom_id index[], t_atom atom[], real tm,
rvec gvec, rvec d, gmx_bool bQ, gmx_bool bRot, gmx_bool bMOI, matrix trans)
#include <math.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
+#include "gromacs/correlationfunctions/crosscorr.h"
+#include "gromacs/correlationfunctions/expfit.h"
+#include "gromacs/correlationfunctions/integrate.h"
#include "gromacs/fileio/matio.h"
#include "gromacs/fileio/tpxio.h"
#include "gromacs/fileio/trxio.h"
#include "gromacs/fileio/xvgr.h"
-#include "gromacs/gmxana/correl.h"
#include "gromacs/gmxana/geminate.h"
#include "gromacs/gmxana/gmx_ana.h"
-#include "gromacs/gmxana/gstat.h"
#include "gromacs/legacyheaders/copyrite.h"
#include "gromacs/legacyheaders/macros.h"
#include "gromacs/legacyheaders/txtdump.h"
#include "gromacs/utility/gmxomp.h"
#include "gromacs/utility/smalloc.h"
+#include "geminate.h"
+
/*#define HAVE_NN_LOOPS*/
typedef short int t_E;
static void smooth_tail(int n, real t[], real c[], real sigma_c[], real start,
const output_env_t oenv)
{
- FILE *fp;
- real e_1, fitparm[4];
- int i;
+ FILE *fp;
+ real e_1;
+ double fitparm[4];
+ int i;
e_1 = exp(-1);
for (i = 0; (i < n); i++)
fitparm[0] = 10;
}
fitparm[1] = 0.95;
- do_lmfit(n, c, sigma_c, 0, t, start, t[n-1], oenv, bDebugMode(), effnEXP2, fitparm, 0);
+ do_lmfit(n, c, sigma_c, 0, t, start, t[n-1], oenv, bDebugMode(),
+ effnEXP2, fitparm, 0);
}
void analyse_corr(int n, real t[], real ct[], real nt[], real kt[],
#include <math.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/integrate.h"
#include "gromacs/fileio/tpxio.h"
#include "gromacs/fileio/trxio.h"
#include "gromacs/fileio/xvgr.h"
#include <string.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
#include "gromacs/fileio/trxio.h"
#include "gromacs/gmxana/gmx_ana.h"
-#include "gromacs/gmxana/gstat.h"
#include "gromacs/legacyheaders/macros.h"
#include "gromacs/legacyheaders/typedefs.h"
#include "gromacs/legacyheaders/viewit.h"
#include <string.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
+#include "gromacs/correlationfunctions/expfit.h"
#include "gromacs/fileio/confio.h"
#include "gromacs/fileio/trxio.h"
#include "gromacs/fileio/xvgr.h"
#include "gromacs/utility/futil.h"
#include "gromacs/utility/smalloc.h"
-
#define NK 24
#define NPK 4
{
FILE *fp, *fp_vk, *fp_cub = NULL;
int nk, ntc;
- real **tcaf, **tcafc = NULL, eta;
+ real **tcaf, **tcafc = NULL, eta, *sig;
int i, j, k, kc;
int ncorr;
- real fitparms[3], *sig;
+ double fitparms[3];
nk = kset_c[nkc];
ntc = nk*NPK;
#include <string.h>
#include "gromacs/commandline/pargs.h"
+#include "gromacs/correlationfunctions/autocorr.h"
#include "gromacs/fft/fft.h"
#include "gromacs/fileio/confio.h"
#include "gromacs/fileio/trxio.h"
#include "gromacs/utility/fatalerror.h"
#include "gromacs/utility/futil.h"
#include "gromacs/utility/smalloc.h"
+#include "gmx_ana.h"
static void index_atom2mol(int *n, atom_id *index, t_block *mols)
{
struct gmx_residuetype_t;
-/***********************************************
- *
- * A U T O C O R R E L A T I O N
- *
- ***********************************************/
-
-real LegendreP(real x, unsigned long m);
-
-#define eacNormal (1<<0)
-#define eacCos (1<<1)
-#define eacVector (1<<2)
-#define eacRcross (1<<3 | eacVector)
-#define eacP0 (1<<4 | eacVector)
-#define eacP1 (1<<5 | eacVector)
-#define eacP2 (1<<6 | eacVector)
-#define eacP3 (1<<7 | eacVector)
-#define eacP4 (1<<8 | eacVector)
-#define eacIden (1<<9)
-
-enum {
- effnNONE, effnEXP1, effnEXP2, effnEXP3, effnVAC,
- effnEXP5, effnEXP7, effnEXP9, effnERF, effnERREST, effnNR
-};
-
/* must correspond with 'leg' g_chi.c:727 */
enum {
edPhi = 0, edPsi, edOmega, edChi1, edChi2, edChi3, edChi4, edChi5, edChi6, edMax
} t_dlist;
-extern const int nfp_ffn[effnNR];
-
-extern const char *s_ffn[effnNR+2];
-
-extern const char *longs_ffn[effnNR];
-
-int sffn2effn(const char **sffn);
-/* Returns the ffn enum corresponding to the selected enum option in sffn */
-
-t_pargs *add_acf_pargs(int *npargs, t_pargs *pa);
-/* Add options for autocorr to the current set of options.
- * *npargs must be initialised to the number of elements in pa,
- * it will be incremented appropriately.
- */
-
-void cross_corr(int n, real f[], real g[], real corr[]);
-/* Simple minded cross correlation algorithm */
-
-real fit_acf(int ncorr, int fitfn, const output_env_t oenv, gmx_bool bVerbose,
- real tbeginfit, real tendfit, real dt, real c1[], real *fit);
-/* Fit an ACF to a given function */
-
-void do_autocorr(const char *fn, const output_env_t oenv,
- const char *title,
- int nframes, int nitem, real **c1,
- real dt, unsigned long mode, gmx_bool bAver);
-/* Calls low_do_autocorr (see below). After calling add_acf_pargs */
-
-void low_do_autocorr(const char *fn, const output_env_t oenv,
- const char *title, int nframes, int nitem,
- int nout, real **c1, real dt, unsigned long mode,
- int nrestart, gmx_bool bAver, gmx_bool bNormalize,
- gmx_bool bVerbose, real tbeginfit, real tendfit,
- int nfitparm);
-/*
- * do_autocorr calculates autocorrelation functions for many things.
- * It takes a 2 d array containing nitem arrays of length nframes
- * for each item the ACF is calculated.
- *
- * A number of "modes" exist for computation of the ACF
- *
- * if (mode == eacNormal) {
- * C(t) = < X (tau) * X (tau+t) >
- * }
- * else if (mode == eacCos) {
- * C(t) = < cos (X(tau) - X(tau+t)) >
- * }
- * else if (mode == eacIden) { **not fully supported yet**
- * C(t) = < (X(tau) == X(tau+t)) >
- * }
- * else if (mode == eacVector) {
- * C(t) = < X(tau) * X(tau+t)
- * }
- * else if (mode == eacP1) {
- * C(t) = < cos (X(tau) * X(tau+t) >
- * }
- * else if (mode == eacP2) {
- * C(t) = 1/2 * < 3 cos (X(tau) * X(tau+t) - 1 >
- * }
- * else if (mode == eacRcross) {
- * C(t) = < ( X(tau) * X(tau+t) )^2 >
- * }
- *
- * For modes eacVector, eacP1, eacP2 and eacRcross the input should be
- * 3 x nframes long, where each triplet is taken as a 3D vector
- *
- * For mode eacCos inputdata must be in radians, not degrees!
- *
- * Other parameters are:
- *
- * fn is output filename (.xvg) where the correlation function(s) are printed
- * title is the title in the output file
- * nframes is the number of frames in the time series
- * nitem is the number of items
- * c1 is an array of dimension [ 0 .. nitem-1 ] [ 0 .. nframes-1 ]
- * on output, this array is filled with the correlation function
- * to reduce storage
- * nrestart is the number of steps between restarts for direct ACFs
- * (i.e. without FFT) When set to 1 all points are used as
- * time origin for averaging
- * dt is the time between frames
- * bAver If set, all ndih C(t) functions are averaged into a single
- * C(t)
- * (bFour If set, will use fast fourier transform (FFT) for evaluating
- * the ACF: removed option, now on the command line only)
- * bNormalize If set, all ACFs will be normalized to start at 0
- * nskip Determines whether steps a re skipped in the output
- */
-
typedef struct {
const char *name; /* Description of the J coupling constant */
real A, B, C; /* Karplus coefficients */
*
*/
-
-/***********************************************
- *
- * F I T R O U T I N E S
- *
- ***********************************************/
-void do_expfit(int ndata, real c1[], real dt,
- real begintimefit, real endtimefit);
-
-void expfit(int n, real x[], real y[], real Dy[],
- real *a, real *sa,
- real *b, real *sb);
-/* This procedure fits y=exp(a+bx) for n (x,y) pairs to determine a and b.
- * The uncertainties in the y values must be in the vector Dy.
- * The standard deviations of a and b, sa and sb, are also calculated.
- *
- * Routine from Computers in physics, 7(3) (1993), p. 280-285.
- */
-
void ana_dih_trans(const char *fn_trans, const char *fn_histo,
real **dih, int nframes, int nangles,
const char *grpname, real *time, gmx_bool bRb,
* normhisto normalized output histogram
*/
-real fit_function(int eFitFn, real *parm, real x);
-/* Returns the value of fit function eFitFn at x */
-
-/* Use Levenberg-Marquardt method to fit to a nfitparm parameter exponential */
-/* or to a transverse current autocorrelation function */
-/* Or: "There is no KILL like OVERKILL", Dr. Ir. D. van der Spoel */
-real do_lmfit(int ndata, real c1[], real sig[], real dt, real *x,
- real begintimefit, real endtimefit, const output_env_t oenv,
- gmx_bool bVerbose, int eFitFn, real fitparms[], int fix);
-/* Returns integral.
- * If x == NULL, the timestep dt will be used to create a time axis.
- * fix fixes fit parameter i at it's starting value, when the i'th bit
- * of fix is set.
- */
-
-real evaluate_integral(int n, real x[], real y[], real dy[],
- real aver_start, real *stddev);
-/* Integrate data in y, and, if given, use dy as weighting
- * aver_start should be set to a value where the function has
- * converged to 0.
- */
-
-real print_and_integrate(FILE *fp, int n, real dt,
- real c[], real *fit, int nskip);
-/* Integrate the data in c[] from 0 to n using trapezium rule.
- * If fp != NULL output is written to it
- * nskip determines whether all elements are written to the output file
- * (written when i % nskip == 0)
- * If fit != NULL the fit is also written.
- */
-
-int get_acfnout(void);
-/* Return the output length for the correlation function
- * Works only AFTER do_auto_corr has been called!
- */
-
-int get_acffitfn(void);
-/* Return the fit function type.
- * Works only AFTER do_auto_corr has been called!
- */
-
/* Routines from pp2shift (anadih.c etc.) */
void do_pp2shifts(FILE *fp, int nframes,
+++ /dev/null
-/*
- * This file is part of the GROMACS molecular simulation package.
- *
- * Copyright (c) 1991-2000, University of Groningen, The Netherlands.
- * Copyright (c) 2001-2004, The GROMACS development team.
- * Copyright (c) 2013,2014, by the GROMACS development team, led by
- * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
- * and including many others, as listed in the AUTHORS file in the
- * top-level source directory and at http://www.gromacs.org.
- *
- * GROMACS is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public License
- * as published by the Free Software Foundation; either version 2.1
- * of the License, or (at your option) any later version.
- *
- * GROMACS is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with GROMACS; if not, see
- * http://www.gnu.org/licenses, or write to the Free Software Foundation,
- * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
- *
- * If you want to redistribute modifications to GROMACS, please
- * consider that scientific software is very special. Version
- * control is crucial - bugs must be traceable. We will be happy to
- * consider code for inclusion in the official distribution, but
- * derived work must not be called official GROMACS. Details are found
- * in the README & COPYING files - if they are missing, get the
- * official version at http://www.gromacs.org.
- *
- * To help us fund GROMACS development, we humbly ask that you cite
- * the research papers on the package. Check out http://www.gromacs.org.
- */
-#include "gmxpre.h"
-
-#include <math.h>
-#include <stdio.h>
-#include <stdlib.h>
-
-#include "gromacs/utility/basedefinitions.h"
-#include "gromacs/utility/real.h"
-
-static void nrerror(const char error_text[], gmx_bool bExit)
-{
- fprintf(stderr, "Numerical Recipes run-time error...\n");
- fprintf(stderr, "%s\n", error_text);
- if (bExit)
- {
- fprintf(stderr, "...now exiting to system...\n");
- exit(1);
- }
-}
-
-/* dont use the keyword vector - it will clash with the
- * altivec extensions used for powerpc processors.
- */
-
-static real *rvector(int nl, int nh)
-{
- real *v;
-
- v = (real *)malloc((unsigned) (nh-nl+1)*sizeof(real));
- if (!v)
- {
- nrerror("allocation failure in rvector()", TRUE);
- }
- /* cppcheck-suppress memleak
- * free_vector does the same vector arithmetic */
- return v-nl;
-}
-
-static int *ivector(int nl, int nh)
-{
- int *v;
-
- v = (int *)malloc((unsigned) (nh-nl+1)*sizeof(int));
- if (!v)
- {
- nrerror("allocation failure in ivector()", TRUE);
- }
- /* cppcheck-suppress memleak
- * free_vector does the same vector arithmetic */
- return v-nl;
-}
-
-
-static real **matrix1(int nrl, int nrh, int ncl, int nch)
-{
- int i;
- real **m;
-
- m = (real **) malloc((unsigned) (nrh-nrl+1)*sizeof(real*));
- if (!m)
- {
- nrerror("allocation failure 1 in matrix1()", TRUE);
- }
- m -= nrl;
-
- for (i = nrl; i <= nrh; i++)
- {
- m[i] = (real *) malloc((unsigned) (nch-ncl+1)*sizeof(real));
- if (!m[i])
- {
- nrerror("allocation failure 2 in matrix1()", TRUE);
- }
- m[i] -= ncl;
- }
- return m;
-}
-
-static double **dmatrix(int nrl, int nrh, int ncl, int nch)
-{
- int i;
- double **m;
-
- m = (double **) malloc((unsigned) (nrh-nrl+1)*sizeof(double*));
- if (!m)
- {
- nrerror("allocation failure 1 in dmatrix()", TRUE);
- }
- m -= nrl;
-
- for (i = nrl; i <= nrh; i++)
- {
- m[i] = (double *) malloc((unsigned) (nch-ncl+1)*sizeof(double));
- if (!m[i])
- {
- nrerror("allocation failure 2 in dmatrix()", TRUE);
- }
- m[i] -= ncl;
- }
- return m;
-}
-
-static int **imatrix1(int nrl, int nrh, int ncl, int nch)
-{
- int i, **m;
-
- m = (int **)malloc((unsigned) (nrh-nrl+1)*sizeof(int*));
- if (!m)
- {
- nrerror("allocation failure 1 in imatrix1()", TRUE);
- }
- m -= nrl;
-
- for (i = nrl; i <= nrh; i++)
- {
- m[i] = (int *)malloc((unsigned) (nch-ncl+1)*sizeof(int));
- if (!m[i])
- {
- nrerror("allocation failure 2 in imatrix1()", TRUE);
- }
- m[i] -= ncl;
- }
- return m;
-}
-
-
-
-static real **submatrix(real **a, int oldrl, int oldrh, int oldcl,
- int newrl, int newcl)
-{
- int i, j;
- real **m;
-
- m = (real **) malloc((unsigned) (oldrh-oldrl+1)*sizeof(real*));
- if (!m)
- {
- nrerror("allocation failure in submatrix()", TRUE);
- }
- m -= newrl;
-
- for (i = oldrl, j = newrl; i <= oldrh; i++, j++)
- {
- m[j] = a[i]+oldcl-newcl;
- }
-
- return m;
-}
-
-
-
-static void free_vector(real *v, int nl)
-{
- free((char*) (v+nl));
-}
-
-static void free_ivector(int *v, int nl)
-{
- free((char*) (v+nl));
-}
-
-static void free_dvector(int *v, int nl)
-{
- free((char*) (v+nl));
-}
-
-
-
-static void free_matrix(real **m, int nrl, int nrh, int ncl)
-{
- int i;
-
- for (i = nrh; i >= nrl; i--)
- {
- free((char*) (m[i]+ncl));
- }
- free((char*) (m+nrl));
-}
-
-static real **convert_matrix(real *a, int nrl, int nrh, int ncl, int nch)
-{
- int i, j, nrow, ncol;
- real **m;
-
- nrow = nrh-nrl+1;
- ncol = nch-ncl+1;
- m = (real **) malloc((unsigned) (nrow)*sizeof(real*));
- if (!m)
- {
- nrerror("allocation failure in convert_matrix()", TRUE);
- }
- m -= nrl;
- for (i = 0, j = nrl; i <= nrow-1; i++, j++)
- {
- m[j] = a+ncol*i-ncl;
- }
- return m;
-}
-
-
-
-static void free_convert_matrix(real **b, int nrl)
-{
- free((char*) (b+nrl));
-}
-
-#define SWAP(a, b) {real temp = (a); (a) = (b); (b) = temp; }
-
-static void dump_mat(int n, real **a)
-{
- int i, j;
-
- for (i = 1; (i <= n); i++)
- {
- for (j = 1; (j <= n); j++)
- {
- fprintf(stderr, " %10.3f", a[i][j]);
- }
- fprintf(stderr, "\n");
- }
-}
-
-gmx_bool gaussj(real **a, int n, real **b, int m)
-{
- int *indxc, *indxr, *ipiv;
- int i, icol = 0, irow = 0, j, k, l, ll;
- real big, dum, pivinv;
-
- indxc = ivector(1, n);
- indxr = ivector(1, n);
- ipiv = ivector(1, n);
- for (j = 1; j <= n; j++)
- {
- ipiv[j] = 0;
- }
- for (i = 1; i <= n; i++)
- {
- big = 0.0;
- for (j = 1; j <= n; j++)
- {
- if (ipiv[j] != 1)
- {
- for (k = 1; k <= n; k++)
- {
- if (ipiv[k] == 0)
- {
- if (fabs(a[j][k]) >= big)
- {
- big = fabs(a[j][k]);
- irow = j;
- icol = k;
- }
- }
- else if (ipiv[k] > 1)
- {
- nrerror("GAUSSJ: Singular Matrix-1", FALSE);
- return FALSE;
- }
- }
- }
- }
- ++(ipiv[icol]);
- if (irow != icol)
- {
- for (l = 1; l <= n; l++)
- {
- SWAP(a[irow][l], a[icol][l]);
- }
- for (l = 1; l <= m; l++)
- {
- SWAP(b[irow][l], b[icol][l]);
- }
- }
- indxr[i] = irow;
- indxc[i] = icol;
- if (a[icol][icol] == 0.0)
- {
- fprintf(stderr, "irow = %d, icol = %d\n", irow, icol);
- dump_mat(n, a);
- nrerror("GAUSSJ: Singular Matrix-2", FALSE);
- return FALSE;
- }
- pivinv = 1.0/a[icol][icol];
- a[icol][icol] = 1.0;
- for (l = 1; l <= n; l++)
- {
- a[icol][l] *= pivinv;
- }
- for (l = 1; l <= m; l++)
- {
- b[icol][l] *= pivinv;
- }
- for (ll = 1; ll <= n; ll++)
- {
- if (ll != icol)
- {
- dum = a[ll][icol];
- a[ll][icol] = 0.0;
- for (l = 1; l <= n; l++)
- {
- a[ll][l] -= a[icol][l]*dum;
- }
- for (l = 1; l <= m; l++)
- {
- b[ll][l] -= b[icol][l]*dum;
- }
- }
- }
- }
- for (l = n; l >= 1; l--)
- {
- if (indxr[l] != indxc[l])
- {
- for (k = 1; k <= n; k++)
- {
- SWAP(a[k][indxr[l]], a[k][indxc[l]]);
- }
- }
- }
- free_ivector(ipiv, 1);
- free_ivector(indxr, 1);
- free_ivector(indxc, 1);
-
- return TRUE;
-}
-
-#undef SWAP
-
-
-static void covsrt(real **covar, int ma, int lista[], int mfit)
-{
- int i, j;
- real swap;
-
- for (j = 1; j < ma; j++)
- {
- for (i = j+1; i <= ma; i++)
- {
- covar[i][j] = 0.0;
- }
- }
- for (i = 1; i < mfit; i++)
- {
- for (j = i+1; j <= mfit; j++)
- {
- if (lista[j] > lista[i])
- {
- covar[lista[j]][lista[i]] = covar[i][j];
- }
- else
- {
- covar[lista[i]][lista[j]] = covar[i][j];
- }
- }
- }
- swap = covar[1][1];
- for (j = 1; j <= ma; j++)
- {
- covar[1][j] = covar[j][j];
- covar[j][j] = 0.0;
- }
- covar[lista[1]][lista[1]] = swap;
- for (j = 2; j <= mfit; j++)
- {
- covar[lista[j]][lista[j]] = covar[1][j];
- }
- for (j = 2; j <= ma; j++)
- {
- for (i = 1; i <= j-1; i++)
- {
- covar[i][j] = covar[j][i];
- }
- }
-}
-
-#define SWAP(a, b) {swap = (a); (a) = (b); (b) = swap; }
-
-static void covsrt_new(real **covar, int ma, int ia[], int mfit)
-/* Expand in storage the covariance matrix covar, so as to take
- * into account parameters that are being held fixed. (For the
- * latter, return zero covariances.)
- */
-{
- int i, j, k;
- real swap;
- for (i = mfit+1; i <= ma; i++)
- {
- for (j = 1; j <= i; j++)
- {
- covar[i][j] = covar[j][i] = 0.0;
- }
- }
- k = mfit;
- for (j = ma; j >= 1; j--)
- {
- if (ia[j])
- {
- for (i = 1; i <= ma; i++)
- {
- SWAP(covar[i][k], covar[i][j]);
- }
- for (i = 1; i <= ma; i++)
- {
- SWAP(covar[k][i], covar[j][i]);
- }
- k--;
- }
- }
-}
-#undef SWAP
-
-static void mrqcof(real x[], real y[], real sig[], int ndata, real a[],
- int ma, int lista[], int mfit,
- real **alpha, real beta[], real *chisq,
- void (*funcs)(real, real *, real *, real *))
-{
- int k, j, i;
- real ymod, wt, sig2i, dy, *dyda;
-
- dyda = rvector(1, ma);
- for (j = 1; j <= mfit; j++)
- {
- for (k = 1; k <= j; k++)
- {
- alpha[j][k] = 0.0;
- }
- beta[j] = 0.0;
- }
- *chisq = 0.0;
- for (i = 1; i <= ndata; i++)
- {
- (*funcs)(x[i], a, &ymod, dyda);
- sig2i = 1.0/(sig[i]*sig[i]);
- dy = y[i]-ymod;
- for (j = 1; j <= mfit; j++)
- {
- wt = dyda[lista[j]]*sig2i;
- for (k = 1; k <= j; k++)
- {
- alpha[j][k] += wt*dyda[lista[k]];
- }
- beta[j] += dy*wt;
- }
- (*chisq) += dy*dy*sig2i;
- }
- for (j = 2; j <= mfit; j++)
- {
- for (k = 1; k <= j-1; k++)
- {
- alpha[k][j] = alpha[j][k];
- }
- }
- free_vector(dyda, 1);
-}
-
-
-gmx_bool mrqmin(real x[], real y[], real sig[], int ndata, real a[],
- int ma, int lista[], int mfit,
- real **covar, real **alpha, real *chisq,
- void (*funcs)(real, real *, real *, real *),
- real *alamda)
-{
- int k, kk, j, ihit;
- static real *da, *atry, **oneda, *beta, ochisq;
-
- if (*alamda < 0.0)
- {
- oneda = matrix1(1, mfit, 1, 1);
- atry = rvector(1, ma);
- da = rvector(1, ma);
- beta = rvector(1, ma);
- kk = mfit+1;
- for (j = 1; j <= ma; j++)
- {
- ihit = 0;
- for (k = 1; k <= mfit; k++)
- {
- if (lista[k] == j)
- {
- ihit++;
- }
- }
- if (ihit == 0)
- {
- lista[kk++] = j;
- }
- else if (ihit > 1)
- {
- nrerror("Bad LISTA permutation in MRQMIN-1", FALSE);
- return FALSE;
- }
- }
- if (kk != ma+1)
- {
- nrerror("Bad LISTA permutation in MRQMIN-2", FALSE);
- return FALSE;
- }
- *alamda = 0.001;
- mrqcof(x, y, sig, ndata, a, ma, lista, mfit, alpha, beta, chisq, funcs);
- ochisq = (*chisq);
- }
- for (j = 1; j <= mfit; j++)
- {
- for (k = 1; k <= mfit; k++)
- {
- covar[j][k] = alpha[j][k];
- }
- covar[j][j] = alpha[j][j]*(1.0+(*alamda));
- oneda[j][1] = beta[j];
- }
- if (!gaussj(covar, mfit, oneda, 1))
- {
- return FALSE;
- }
- for (j = 1; j <= mfit; j++)
- {
- da[j] = oneda[j][1];
- }
- if (*alamda == 0.0)
- {
- covsrt(covar, ma, lista, mfit);
- free_vector(beta, 1);
- free_vector(da, 1);
- free_vector(atry, 1);
- free_matrix(oneda, 1, mfit, 1);
- return TRUE;
- }
- for (j = 1; j <= ma; j++)
- {
- atry[j] = a[j];
- }
- for (j = 1; j <= mfit; j++)
- {
- atry[lista[j]] = a[lista[j]]+da[j];
- }
- mrqcof(x, y, sig, ndata, atry, ma, lista, mfit, covar, da, chisq, funcs);
- if (*chisq < ochisq)
- {
- *alamda *= 0.1;
- ochisq = (*chisq);
- for (j = 1; j <= mfit; j++)
- {
- for (k = 1; k <= mfit; k++)
- {
- alpha[j][k] = covar[j][k];
- }
- beta[j] = da[j];
- a[lista[j]] = atry[lista[j]];
- }
- }
- else
- {
- *alamda *= 10.0;
- *chisq = ochisq;
- }
- return TRUE;
-}
-
-
-gmx_bool mrqmin_new(real x[], real y[], real sig[], int ndata, real a[],
- int ia[], int ma, real **covar, real **alpha, real *chisq,
- void (*funcs)(real, real [], real *, real []),
- real *alamda)
-/* Levenberg-Marquardt method, attempting to reduce the value Chi^2
- * of a fit between a set of data points x[1..ndata], y[1..ndata]
- * with individual standard deviations sig[1..ndata], and a nonlinear
- * function dependent on ma coefficients a[1..ma]. The input array
- * ia[1..ma] indicates by nonzero entries those components of a that
- * should be fitted for, and by zero entries those components that
- * should be held fixed at their input values. The program returns
- * current best-fit values for the parameters a[1..ma], and
- * Chi^2 = chisq. The arrays covar[1..ma][1..ma], alpha[1..ma][1..ma]
- * are used as working space during most iterations. Supply a routine
- * funcs(x,a,yfit,dyda,ma) that evaluates the fitting function yfit,
- * and its derivatives dyda[1..ma] with respect to the fitting
- * parameters a at x. On the first call provide an initial guess for
- * the parameters a, and set alamda < 0 for initialization (which then
- * sets alamda=.001). If a step succeeds chisq becomes smaller and
- * alamda de-creases by a factor of 10. If a step fails alamda grows by
- * a factor of 10. You must call this routine repeatedly until
- * convergence is achieved. Then, make one final call with alamda=0,
- * so that covar[1..ma][1..ma] returns the covariance matrix, and alpha
- * the curvature matrix.
- * (Parameters held fixed will return zero covariances.)
- */
-{
- void covsrt(real **covar, int ma, int ia[], int mfit);
- gmx_bool gaussj(real **a, int n, real **b, int m);
- void mrqcof_new(real x[], real y[], real sig[], int ndata, real a[],
- int ia[], int ma, real **alpha, real beta[], real *chisq,
- void (*funcs)(real, real [], real *, real []));
- int j, k, l;
- static int mfit;
- static real ochisq, *atry, *beta, *da, **oneda;
-
- if (*alamda < 0.0) /* Initialization. */
- {
- atry = rvector(1, ma);
- beta = rvector(1, ma);
- da = rvector(1, ma);
- for (mfit = 0, j = 1; j <= ma; j++)
- {
- if (ia[j])
- {
- mfit++;
- }
- }
- oneda = matrix1(1, mfit, 1, 1);
- *alamda = 0.001;
- mrqcof_new(x, y, sig, ndata, a, ia, ma, alpha, beta, chisq, funcs);
- ochisq = (*chisq);
- for (j = 1; j <= ma; j++)
- {
- atry[j] = a[j];
- }
- }
- for (j = 1; j <= mfit; j++) /* Alter linearized fitting matrix, by augmenting. */
- {
- for (k = 1; k <= mfit; k++)
- {
- covar[j][k] = alpha[j][k]; /* diagonal elements. */
- }
- covar[j][j] = alpha[j][j]*(1.0+(*alamda));
- oneda[j][1] = beta[j];
- }
- if (!gaussj(covar, mfit, oneda, 1)) /* Matrix solution. */
- {
- return FALSE;
- }
- for (j = 1; j <= mfit; j++)
- {
- da[j] = oneda[j][1];
- }
- if (*alamda == 0.0) /* Once converged, evaluate covariance matrix. */
- {
- covsrt_new(covar, ma, ia, mfit);
- free_matrix(oneda, 1, mfit, 1);
- free_vector(da, 1);
- free_vector(beta, 1);
- free_vector(atry, 1);
- return TRUE;
- }
- for (j = 0, l = 1; l <= ma; l++) /* Did the trial succeed? */
- {
- if (ia[l])
- {
- atry[l] = a[l]+da[++j];
- }
- }
- mrqcof_new(x, y, sig, ndata, atry, ia, ma, covar, da, chisq, funcs);
- if (*chisq < ochisq)
- {
- /* Success, accept the new solution. */
- *alamda *= 0.1;
- ochisq = (*chisq);
- for (j = 1; j <= mfit; j++)
- {
- for (k = 1; k <= mfit; k++)
- {
- alpha[j][k] = covar[j][k];
- }
- beta[j] = da[j];
- }
- for (l = 1; l <= ma; l++)
- {
- a[l] = atry[l];
- }
- }
- else /* Failure, increase alamda and return. */
- {
- *alamda *= 10.0;
- *chisq = ochisq;
- }
- return TRUE;
-}
-
-void mrqcof_new(real x[], real y[], real sig[], int ndata, real a[],
- int ia[], int ma, real **alpha, real beta[], real *chisq,
- void (*funcs)(real, real [], real *, real[]))
-/* Used by mrqmin to evaluate the linearized fitting matrix alpha, and
- * vector beta as in (15.5.8), and calculate Chi^2.
- */
-{
- int i, j, k, l, m, mfit = 0;
- real ymod, wt, sig2i, dy, *dyda;
-
- dyda = rvector(1, ma);
- for (j = 1; j <= ma; j++)
- {
- if (ia[j])
- {
- mfit++;
- }
- }
- for (j = 1; j <= mfit; j++) /* Initialize (symmetric) alpha), beta. */
- {
- for (k = 1; k <= j; k++)
- {
- alpha[j][k] = 0.0;
- }
- beta[j] = 0.0;
- }
- *chisq = 0.0;
- for (i = 1; i <= ndata; i++) /* Summation loop over all data. */
- {
- (*funcs)(x[i], a, &ymod, dyda);
- sig2i = 1.0/(sig[i]*sig[i]);
- dy = y[i]-ymod;
- for (j = 0, l = 1; l <= ma; l++)
- {
- if (ia[l])
- {
- wt = dyda[l]*sig2i;
- for (j++, k = 0, m = 1; m <= l; m++)
- {
- if (ia[m])
- {
- alpha[j][++k] += wt*dyda[m];
- }
- }
- beta[j] += dy*wt;
- }
- }
- *chisq += dy*dy*sig2i; /* And find Chi^2. */
- }
- for (j = 2; j <= mfit; j++) /* Fill in the symmetric side. */
- {
- for (k = 1; k < j; k++)
- {
- alpha[k][j] = alpha[j][k];
- }
- }
- free_vector(dyda, 1);
-}
biod.pnpi.spb.ru / alexxy / gromacs.git / commitdiff