--- /dev/null
+/*
+ * This file is part of TISEAN
+ *
+ * Copyright (c) 1998-2007 Rainer Hegger, Holger Kantz, Thomas Schreiber
+ *
+ * TISEAN is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 2 of the License, or
+ * (at your option) any later version.
+ *
+ * TISEAN 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 General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with TISEAN; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
+ */
+/*Author: Rainer Hegger. Last modified: Jun 21, 2005 */
+/*changes:
+ Jun 17, 2005: Comments in the output file updated
+ Jun 21, 2005: free imat in make_fit
+*/
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include <limits.h>
+#include "routines/tsa.h"
+#include <math.h>
+
+#define WID_STR "Estimates the average forecast error for a local\n\t\
+linear fit as a function of the neighborhood size."
+
+
+/*number of boxes for the neighbor search algorithm*/
+#define NMAX 256
+
+unsigned int nmax=(NMAX-1);
+long **box,*list;
+unsigned long *found;
+double *error;
+double **series;
+
+char eps0set=0,eps1set=0,causalset=0,dimset=0;
+char *outfile=NULL,stdo=1;
+char *column=NULL;
+unsigned int dim=1,embed=2,delay=1;
+unsigned int verbosity=0xff;
+int STEP=1;
+double EPS0=1.e-3,EPS1=1.0,EPSF=1.2;
+unsigned long LENGTH=ULONG_MAX,exclude=0,CLENGTH=ULONG_MAX,causal;
+char *infile=NULL;
+double **mat,*vec,*localav,*foreav,*hvec;
+
+void show_options(char *progname)
+{
+ what_i_do(progname,WID_STR);
+ fprintf(stderr," Usage: %s [options]\n",progname);
+ fprintf(stderr," Options:\n");
+ fprintf(stderr,"Everything not being a valid option will be interpreted"
+ " as a possible"
+ " datafile.\nIf no datafile is given stdin is read. Just - also"
+ " means stdin\n");
+ fprintf(stderr,"\t-l # of data to use [default: whole file]\n");
+ fprintf(stderr,"\t-x # of lines to be ignored [default: 0]\n");
+ fprintf(stderr,"\t-c columns to read [default: 1,...,# of components]\n");
+ fprintf(stderr,"\t-m # of components,embedding dimension [default: 1,2]\n");
+ fprintf(stderr,"\t-d delay [default: 1]\n");
+ fprintf(stderr,"\t-i iterations [default: length]\n");
+ fprintf(stderr,"\t-r neighborhood size to start with [default:"
+ " (interval of data)/1000)]\n");
+ fprintf(stderr,"\t-R neighborhood size to end with [default:"
+ " interval of data]\n");
+ fprintf(stderr,"\t-f factor to increase size [default: 1.2]\n");
+ fprintf(stderr,"\t-s steps to forecast [default: 1]\n");
+ fprintf(stderr,"\t-C width of causality window [default: steps]\n");
+ fprintf(stderr,"\t-o output file name [default: 'datafile.ll']\n");
+ fprintf(stderr,"\t-V verbosity level [default: 1]\n\t\t"
+ "0='only panic messages'\n\t\t"
+ "1='+ input/output messages'\n");
+ fprintf(stderr,"\t-h show these options\n");
+ exit(0);
+}
+
+void scan_options(int n,char **in)
+{
+ char *out;
+
+ if ((out=check_option(in,n,'l','u')) != NULL)
+ sscanf(out,"%lu",&LENGTH);
+ if ((out=check_option(in,n,'x','u')) != NULL)
+ sscanf(out,"%lu",&exclude);
+ if ((out=check_option(in,n,'c','s')) != NULL) {
+ column=out;
+ dimset=1;
+ }
+ if ((out=check_option(in,n,'m','2')) != NULL)
+ sscanf(out,"%u,%u",&dim,&embed);
+ if ((out=check_option(in,n,'d','u')) != NULL)
+ sscanf(out,"%u",&delay);
+ if ((out=check_option(in,n,'i','u')) != NULL)
+ sscanf(out,"%lu",&CLENGTH);
+ if ((out=check_option(in,n,'r','f')) != NULL) {
+ eps0set=1;
+ sscanf(out,"%lf",&EPS0);
+ }
+ if ((out=check_option(in,n,'R','f')) != NULL) {
+ eps1set=1;
+ sscanf(out,"%lf",&EPS1);
+ }
+ if ((out=check_option(in,n,'f','f')) != NULL)
+ sscanf(out,"%lf",&EPSF);
+ if ((out=check_option(in,n,'s','u')) != NULL)
+ sscanf(out,"%u",&STEP);
+ if ((out=check_option(in,n,'C','u')) != NULL) {
+ sscanf(out,"%lu",&causal);
+ causalset=1;
+ }
+ if ((out=check_option(in,n,'V','u')) != NULL)
+ sscanf(out,"%u",&verbosity);
+ if ((out=check_option(in,n,'o','o')) != NULL) {
+ stdo=0;
+ if (strlen(out) > 0)
+ outfile=out;
+ }
+}
+
+void multiply_matrix(double **mat,double *vec)
+{
+ long i,j;
+
+ for (i=0;i<dim*embed;i++) {
+ hvec[i]=0.0;
+ for (j=0;j<dim*embed;j++)
+ hvec[i] += mat[i][j]*vec[j];
+ }
+ for (i=0;i<dim*embed;i++)
+ vec[i]=hvec[i];
+}
+
+void make_fit(long act,unsigned long number)
+{
+ double *si,*sj,lavi,lavj,fav,**imat,cast;
+ long i,i1,hi,hi1,j,j1,hj,hj1,n,which;
+
+ for (i=0;i<embed*dim;i++)
+ localav[i]=0;
+ for (i=0;i<dim;i++)
+ foreav[i]=0.0;
+
+ for (n=0;n<number;n++) {
+ which=found[n];
+ for (j=0;j<dim;j++) {
+ sj=series[j];
+ foreav[j] += sj[which+STEP];
+ for (j1=0;j1<embed;j1++) {
+ hj=j*embed+j1;
+ localav[hj] += sj[which-j1*delay];
+ }
+ }
+ }
+
+ for (i=0;i<dim*embed;i++)
+ localav[i] /= number;
+ for (i=0;i<dim;i++)
+ foreav[i] /= number;
+
+ for (i=0;i<dim;i++) {
+ si=series[i];
+ for (i1=0;i1<embed;i1++) {
+ hi=i*embed+i1;
+ lavi=localav[hi];
+ hi1=i1*delay;
+ for (j=0;j<dim;j++) {
+ sj=series[j];
+ for (j1=0;j1<embed;j1++) {
+ hj=j*embed+j1;
+ lavj=localav[hj];
+ hj1=j1*delay;
+ mat[hi][hj]=0.0;
+ if (hj >= hi) {
+ for (n=0;n<number;n++) {
+ which=found[n];
+ mat[hi][hj] += (si[which-hi1]-lavi)*(sj[which-hj1]-lavj);
+ }
+ }
+ }
+ }
+ }
+ }
+
+ for (i=0;i<dim*embed;i++)
+ for (j=i;j<dim*embed;j++) {
+ mat[i][j] /= number;
+ mat[j][i]=mat[i][j];
+ }
+
+ imat=invert_matrix(mat,dim*embed);
+
+ for (i=0;i<dim;i++) {
+ si=series[i];
+ fav=foreav[i];
+ for (j=0;j<dim;j++) {
+ sj=series[j];
+ for (j1=0;j1<embed;j1++) {
+ hj=j*embed+j1;
+ lavj=localav[hj];
+ hj1=j1*delay;
+ vec[hj]=0.0;
+ for (n=0;n<number;n++) {
+ which=found[n];
+ vec[hj] += (si[which+STEP]-fav)*(sj[which-hj1]-lavj);
+ }
+ vec[hj] /= number;
+ }
+ }
+
+ multiply_matrix(imat,vec);
+
+ cast=foreav[i];
+ for (j=0;j<dim;j++) {
+ sj=series[j];
+ for (j1=0;j1<embed;j1++) {
+ hj=j*embed+j1;
+ cast += vec[hj]*(sj[act-j1*delay]-localav[hj]);
+ }
+ }
+ error[i] += sqr(cast-series[i][act+STEP]);
+ }
+ for (i=0;i<embed*dim;i++)
+ free(imat[i]);
+ free(imat);
+}
+
+int main(int argc,char **argv)
+{
+ char stdi=0;
+ unsigned long actfound;
+ unsigned long *hfound;
+ long pfound,i,j;
+ unsigned long clength;
+ double interval,min,maxinterval;
+ double epsilon;
+ double **hser;
+ double avfound,*hrms,*hav,sumerror=0.0;
+ FILE *file=NULL;
+
+ if (scan_help(argc,argv))
+ show_options(argv[0]);
+
+ scan_options(argc,argv);
+#ifndef OMIT_WHAT_I_DO
+ if (verbosity&VER_INPUT)
+ what_i_do(argv[0],WID_STR);
+#endif
+
+ if (!causalset)
+ causal=STEP;
+
+ infile=search_datafile(argc,argv,NULL,verbosity);
+ if (infile == NULL)
+ stdi=1;
+
+ if (outfile == NULL) {
+ if (!stdi) {
+ check_alloc(outfile=(char*)calloc(strlen(infile)+4,(size_t)1));
+ sprintf(outfile,"%s.ll",infile);
+ }
+ else {
+ check_alloc(outfile=(char*)calloc((size_t)9,(size_t)1));
+ sprintf(outfile,"stdin.ll");
+ }
+ }
+ if (!stdo)
+ test_outfile(outfile);
+
+ if (column == NULL)
+ series=(double**)get_multi_series(infile,&LENGTH,exclude,&dim,"",dimset,
+ verbosity);
+ else
+ series=(double**)get_multi_series(infile,&LENGTH,exclude,&dim,column,
+ dimset,verbosity);
+ maxinterval=0.0;
+ for (i=0;i<dim;i++) {
+ rescale_data(series[i],LENGTH,&min,&interval);
+ if (interval > maxinterval)
+ maxinterval=interval;
+ }
+ interval=maxinterval;
+
+ check_alloc(list=(long*)malloc(sizeof(long)*LENGTH));
+ check_alloc(found=(unsigned long*)malloc(sizeof(long)*LENGTH));
+ check_alloc(hfound=(unsigned long*)malloc(sizeof(long)*LENGTH));
+ check_alloc(box=(long**)malloc(sizeof(long*)*NMAX));
+ for (i=0;i<NMAX;i++)
+ check_alloc(box[i]=(long*)malloc(sizeof(long)*NMAX));
+ check_alloc(vec=(double*)malloc(sizeof(double)*(embed*dim)));
+ check_alloc(hvec=(double*)malloc(sizeof(double)*(embed*dim)));
+ check_alloc(mat=(double**)malloc(sizeof(double*)*(embed*dim)));
+ for (i=0;i<dim*embed;i++)
+ check_alloc(mat[i]=(double*)malloc(sizeof(double)*(embed*dim)));
+ check_alloc(error=(double*)malloc(sizeof(double)*dim));
+ check_alloc(hrms=(double*)malloc(sizeof(double)*dim));
+ check_alloc(hav=(double*)malloc(sizeof(double)*dim));
+ check_alloc(hser=(double**)malloc(sizeof(double*)*dim));
+ check_alloc(foreav=(double*)malloc(sizeof(double)*dim));
+ check_alloc(localav=(double*)malloc(sizeof(double)*(embed*dim)));
+
+ if (eps0set)
+ EPS0 /= interval;
+ if (eps1set)
+ EPS1 /= interval;
+
+ clength=(CLENGTH <= LENGTH) ? CLENGTH-STEP : LENGTH-STEP;
+
+ if (!stdo) {
+ file=fopen(outfile,"w");
+ if (verbosity&VER_INPUT)
+ fprintf(stderr,"Opened %s for writing\n",outfile);
+ fprintf(file,"#1.) neighborhood size\n");
+ fprintf(file,"#2.) average relative forecast error\n");
+ fprintf(file,"#next n.) relative forecast error of the n components\n");
+ fprintf(file,"#second last.) fraction of points with enough neighbors\n");
+ fprintf(file,"#last .) average number of neighbors used for the fit\n");
+ }
+ else {
+ if (verbosity&VER_INPUT)
+ fprintf(stderr,"Writing to stdout\n");
+ }
+
+ for (epsilon=EPS0;epsilon<EPS1*EPSF;epsilon*=EPSF) {
+ pfound=0;
+ for (i=0;i<dim;i++)
+ error[i]=hrms[i]=hav[i]=0.0;
+ avfound=0.0;
+ make_multi_box(series,box,list,LENGTH-STEP,NMAX,dim,
+ embed,delay,epsilon);
+ for (i=(embed-1)*delay;i<clength;i++) {
+ for (j=0;j<dim;j++)
+ hser[j]=series[j]+i;
+ actfound=find_multi_neighbors(series,box,list,hser,LENGTH,
+ NMAX,dim,embed,delay,epsilon,hfound);
+ actfound=exclude_interval(actfound,i-causal+1,i+causal+(embed-1)*delay-1,
+ hfound,found);
+ if (actfound > 2*(dim*embed+1)) {
+ make_fit(i,actfound);
+ pfound++;
+ avfound += (double)(actfound-1);
+ for (j=0;j<dim;j++) {
+ hrms[j] += series[j][i+STEP]*series[j][i+STEP];
+ hav[j] += series[j][i+STEP];
+ }
+ }
+ }
+ if (pfound > 1) {
+ sumerror=0.0;
+ for (j=0;j<dim;j++) {
+ hav[j] /= pfound;
+ hrms[j]=sqrt(fabs(hrms[j]/(pfound-1)-hav[j]*hav[j]*pfound/(pfound-1)));
+ error[j]=sqrt(error[j]/pfound)/hrms[j];
+ sumerror += error[j];
+ }
+ }
+ if (stdo) {
+ if (pfound > 1) {
+ fprintf(stdout,"%e %e ",epsilon*interval,sumerror/(double)dim);
+ for (j=0;j<dim;j++)
+ fprintf(stdout,"%e ",error[j]);
+ fprintf(stdout,"%e %e\n",(double)pfound/(clength-(embed-1)*delay),
+ avfound/pfound);
+ fflush(stdout);
+ }
+ }
+ else {
+ if (pfound > 1) {
+ fprintf(file,"%e %e ",epsilon*interval,sumerror/(double)dim);
+ for (j=0;j<dim;j++)
+ fprintf(file,"%e ",error[j]);
+ fprintf(file,"%e %e\n",(double)pfound/(clength-(embed-1)*delay),
+ avfound/pfound);
+ fflush(file);
+ }
+ }
+ }
+ if (!stdo)
+ fclose(file);
+
+ return 0;
+}
git://source.jalview.org / jabaws.git / blobdiff