Exemplo n.º 1
0
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 eFitFn,int nskip)
{
  FILE    *fp,*gp=NULL;
  int     i,k,nfour;
  real    *csum;
  real    *ctmp,*fit;
  real    c0,sum,Ct2av,Ctav;
  gmx_bool    bFour = acf.bFour;
 
  /* Check flags and parameters */ 
  nout = get_acfnout();
  if (nout == -1)
    nout = acf.nout = (nframes+1)/2;
  else if (nout > nframes)
    nout=nframes;
  
  if (MODE(eacCos) && MODE(eacVector))
    gmx_fatal(FARGS,"Incompatible options bCos && bVector (%s, %d)",
		__FILE__,__LINE__);
  if ((MODE(eacP3) || MODE(eacRcross)) && bFour) {
    fprintf(stderr,"Can't combine mode %lu with FFT, turning off FFT\n",mode);
    bFour = FALSE;
  }
  if (MODE(eacNormal) && MODE(eacVector)) 
    gmx_fatal(FARGS,"Incompatible mode bits: normal and vector (or Legendre)");
    
  /* Print flags and parameters */
  if (bVerbose) {
    printf("Will calculate %s of %d thingies for %d frames\n",
	   title ? title : "autocorrelation",nitem,nframes);
    printf("bAver = %s, bFour = %s bNormalize= %s\n",
	   bool_names[bAver],bool_names[bFour],bool_names[bNormalize]);
    printf("mode = %lu, dt = %g, nrestart = %d\n",mode,dt,nrestart);
  }
  if (bFour) {  
    c0 = log((double)nframes)/log(2.0);
    k  = c0;
    if (k < c0)
      k++;
    k++;
    nfour = 1<<k;
    if (debug)
      fprintf(debug,"Using FFT to calculate %s, #points for FFT = %d\n",
	      title,nfour);
	
    /* Allocate temp arrays */
    snew(csum,nfour);
    snew(ctmp,nfour);
  } else {
    nfour = 0; /* To keep the compiler happy */
    snew(csum,nframes);
    snew(ctmp,nframes);
  }
  
  /* Loop over items (e.g. molecules or dihedrals) 
   * In this loop the actual correlation functions are computed, but without
   * normalizing them.
   */
  k = max(1,pow(10,(int)(log(nitem)/log(100))));
  for(i=0; i<nitem; i++) {
    if (bVerbose && ((i%k==0 || i==nitem-1)))
      fprintf(stderr,"\rThingie %d",i+1);
    
    if (bFour)
      do_four_core(mode,nfour,nframes,nframes,c1[i],csum,ctmp);
    else 
      do_ac_core(nframes,nout,ctmp,c1[i],nrestart,mode);
  }
  if (bVerbose)
    fprintf(stderr,"\n");
  sfree(ctmp);
  sfree(csum);
  
  if (fn) {
    snew(fit,nout);
    fp=xvgropen(fn,title,"Time (ps)","C(t)",oenv);
  } else {
    fit = NULL;
    fp  = NULL;
  }
  if (bAver) {
    if (nitem > 1)
      average_acf(bVerbose,nframes,nitem,c1);
    
    if (bNormalize)
      normalize_acf(nout,c1[0]);
    
    if (eFitFn != effnNONE) {
      fit_acf(nout,eFitFn,oenv,fn!=NULL,tbeginfit,tendfit,dt,c1[0],fit);
      sum = print_and_integrate(fp,nout,dt,c1[0],fit,1);
    } else {
      sum = print_and_integrate(fp,nout,dt,c1[0],NULL,1);
      if (bVerbose)
	printf("Correlation time (integral over corrfn): %g (ps)\n",sum);
    }
  } else {
    /* Not averaging. Normalize individual ACFs */
    Ctav = Ct2av = 0;
    if (debug)
      gp = xvgropen("ct-distr.xvg","Correlation times","item","time (ps)",oenv);
    for(i=0; i<nitem; i++) {
      if (bNormalize)
	normalize_acf(nout,c1[i]);
      if (eFitFn != effnNONE) {
	fit_acf(nout,eFitFn,oenv,fn!=NULL,tbeginfit,tendfit,dt,c1[i],fit);
	sum = print_and_integrate(fp,nout,dt,c1[i],fit,1);
      } else {
	sum = print_and_integrate(fp,nout,dt,c1[i],NULL,1);
	if (debug)
	  fprintf(debug,
		  "CORRelation time (integral over corrfn %d): %g (ps)\n",
		  i,sum);
      }
      Ctav += sum;
      Ct2av += sum*sum;
      if (debug)
	fprintf(gp,"%5d  %.3f\n",i,sum);
    }
    if (debug)
      ffclose(gp);
    if (nitem > 1) {
      Ctav  /= nitem;
      Ct2av /= nitem;
      printf("Average correlation time %.3f Std. Dev. %.3f Error %.3f (ps)\n",
	     Ctav,sqrt((Ct2av - sqr(Ctav))),
	     sqrt((Ct2av - sqr(Ctav))/(nitem-1)));
    }
  }
  if (fp)
    ffclose(fp);
  sfree(fit);
}
Exemplo n.º 2
0
int main(int argc,char *argv[])
{
  FILE *fp;
  const char *desc[] = {
    "testac tests the functioning of the GROMACS acf routines"
  };
  static int nframes = 1024;
  static int datatp  = 0;
  static real a=0.02*M_PI;
  output_env_t oenv;
  t_pargs pa[] = {
    { "-np", FALSE, etINT, &nframes,
      "Number of data points" },
    { "-dtp",FALSE, etINT, &datatp,
      "Which data: 0=all 0.0, 1=all 1.0, 2=cos(a t), 3=random, 4=cos(a t)+random, 5=sin(a t)/(a t)" }
  };
  static char *str[] = {
    "all 0.0", 
    "all 1.0",
    "cos(a t)",
    "random", 
    "cos(a t)+random",
    "sin(a t)/(a t)"
  };
  t_filenm fnm[] = {
    { efXVG, "-d", "acf-data", ffWRITE },
    { efXVG, "-c", "acf-corr", ffWRITE },
    { efXVG, "-comb", "acf-comb.xvg", ffWRITE }
  };
#define NFILE asize(fnm)
  int     npargs,i,nlag;
  int     seed=1993;
  real    *data,*data2,x;
  t_pargs *ppa;
  
  CopyRight(stderr,argv[0]);
  npargs = asize(pa);
  ppa    = add_acf_pargs(&npargs,pa);
  parse_common_args_r(&argc,argv,PCA_CAN_TIME | PCA_CAN_VIEW | PCA_BE_NICE,
		      NFILE,fnm,npargs,ppa,asize(desc),desc,0,NULL,&oenv);
  snew(data,nframes);
  snew(data2,nframes);
  
  fp = xvgropen(opt2fn("-d",NFILE,fnm),"testac","x","y",oenv);
  for(i=0; (i<nframes); i++) {
    x = a*i;
    switch (datatp) {
    case 1:
      data[i] = 1;
      break;
    case 2:
      data[i] = cos(x);
      break;
    case 3:
      data[i] = 2*rando(&seed)-1.0;
      break;
    case 4:
      data[i] = cos(x)+2*rando(&seed)-1.0;
      break;
    case 5:
      if (i==0)
	data[i] = 1;
      else
	data[i] = sin(x)/(x);
    default:
      /* Data remains 0.0 */
      break;
    }
    fprintf(fp,"%10g  %10g\n",x,data[i]);
    data2[i] = data[i];
  }
  ffclose(fp);
  
  do_autocorr(opt2fn("-c",NFILE,fnm),oenv,str[datatp],
	      nframes,1,&data,a,eacNormal,FALSE);
	      
  nlag = get_acfnout();
  fp = xvgropen(opt2fn("-comb",NFILE,fnm),"testac","x","y",oenv);
  for(i=0; (i<nlag); i++) {
    fprintf(fp,"%10g  %10g  %10g\n",a*i,data2[i],data[i]);
  }
  ffclose(fp);

  do_view(opt2fn("-c",NFILE,fnm),"-nxy");
    
  thanx(stderr);

  return 0;
}
Exemplo n.º 3
0
void low_do_autocorr(const char *fn, const gmx_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 eFitFn)
{
    FILE       *fp, *gp = NULL;
    int         i;
    real       *csum;
    real       *ctmp, *fit;
    real        sum, Ct2av, Ctav;
    gmx_bool    bFour = acf.bFour;

    /* Check flags and parameters */
    nout = get_acfnout();
    if (nout == -1)
    {
        nout = acf.nout = (nframes+1)/2;
    }
    else if (nout > nframes)
    {
        nout = nframes;
    }

    if (MODE(eacCos) && MODE(eacVector))
    {
        gmx_fatal(FARGS, "Incompatible options bCos && bVector (%s, %d)",
                  __FILE__, __LINE__);
    }
    if ((MODE(eacP3) || MODE(eacRcross)) && bFour)
    {
        if (bVerbose)
        {
            fprintf(stderr, "Can't combine mode %lu with FFT, turning off FFT\n", mode);
        }
        bFour = FALSE;
    }
    if (MODE(eacNormal) && MODE(eacVector))
    {
        gmx_fatal(FARGS, "Incompatible mode bits: normal and vector (or Legendre)");
    }

    /* Print flags and parameters */
    if (bVerbose)
    {
        printf("Will calculate %s of %d thingies for %d frames\n",
               title ? title : "autocorrelation", nitem, nframes);
        printf("bAver = %s, bFour = %s bNormalize= %s\n",
               gmx::boolToString(bAver), gmx::boolToString(bFour),
               gmx::boolToString(bNormalize));
        printf("mode = %lu, dt = %g, nrestart = %d\n", mode, dt, nrestart);
    }
    /* Allocate temp arrays */
    snew(csum, nframes);
    snew(ctmp, nframes);

    /* Loop over items (e.g. molecules or dihedrals)
     * In this loop the actual correlation functions are computed, but without
     * normalizing them.
     */
    for (int i = 0; i < nitem; i++)
    {
        if (bVerbose && (((i % 100) == 0) || (i == nitem-1)))
        {
            fprintf(stderr, "\rThingie %d", i+1);
            fflush(stderr);
        }

        if (bFour)
        {
            do_four_core(mode, nframes, c1[i], csum, ctmp);
        }
        else
        {
            do_ac_core(nframes, nout, ctmp, c1[i], nrestart, mode);
        }
    }
    if (bVerbose)
    {
        fprintf(stderr, "\n");
    }
    sfree(ctmp);
    sfree(csum);

    if (fn)
    {
        snew(fit, nout);
        fp = xvgropen(fn, title, "Time (ps)", "C(t)", oenv);
    }
    else
    {
        fit = NULL;
        fp  = NULL;
    }
    if (bAver)
    {
        if (nitem > 1)
        {
            average_acf(bVerbose, nframes, nitem, c1);
        }

        if (bNormalize)
        {
            normalize_acf(nout, c1[0]);
        }

        if (eFitFn != effnNONE)
        {
            fit_acf(nout, eFitFn, oenv, fn != NULL, tbeginfit, tendfit, dt, c1[0], fit);
            sum = print_and_integrate(fp, nout, dt, c1[0], fit, 1);
        }
        else
        {
            sum = print_and_integrate(fp, nout, dt, c1[0], NULL, 1);
        }
        if (bVerbose)
        {
            printf("Correlation time (integral over corrfn): %g (ps)\n", sum);
        }
    }
    else
    {
        /* Not averaging. Normalize individual ACFs */
        Ctav = Ct2av = 0;
        if (debug)
        {
            gp = xvgropen("ct-distr.xvg", "Correlation times", "item", "time (ps)", oenv);
        }
        for (i = 0; i < nitem; i++)
        {
            if (bNormalize)
            {
                normalize_acf(nout, c1[i]);
            }
            if (eFitFn != effnNONE)
            {
                fit_acf(nout, eFitFn, oenv, fn != NULL, tbeginfit, tendfit, dt, c1[i], fit);
                sum = print_and_integrate(fp, nout, dt, c1[i], fit, 1);
            }
            else
            {
                sum = print_and_integrate(fp, nout, dt, c1[i], NULL, 1);
                if (debug)
                {
                    fprintf(debug,
                            "CORRelation time (integral over corrfn %d): %g (ps)\n",
                            i, sum);
                }
            }
            Ctav  += sum;
            Ct2av += sum*sum;
            if (debug)
            {
                fprintf(gp, "%5d  %.3f\n", i, sum);
            }
        }
        if (debug)
        {
            xvgrclose(gp);
        }
        if (nitem > 1)
        {
            Ctav  /= nitem;
            Ct2av /= nitem;
            printf("Average correlation time %.3f Std. Dev. %.3f Error %.3f (ps)\n",
                   Ctav, std::sqrt((Ct2av - gmx::square(Ctav))),
                   std::sqrt((Ct2av - gmx::square(Ctav))/(nitem-1)));
        }
    }
    if (fp)
    {
        xvgrclose(fp);
    }
    sfree(fit);
}