+++ /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 */
-/*Changes:
- Sep 8, 2006: Add -o functionality
- Sep 7, 2006: Completely rewritten to handle multivariate data
- */
-#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 of a local\n\t\
-linear fit"
-
-
-/*number of boxes for the neighbor search algorithm*/
-#define NMAX 512
-
-unsigned int nmax=(NMAX-1),comp1,hdim,**indexes;
-long **box,*list;
-unsigned long *found,*hfound;
-double **series;
-double epsilon;
-double **mat,**imat,*vec,*localav,*foreav;
-
-char epsset=0,causalset=0;
-unsigned int verbosity=VER_INPUT|VER_FIRST_LINE;
-unsigned int COMP=1,EMBED=2,DIM,DELAY=1,MINN=30,STEP=1;
-double EPS0=1.e-3,EPSF=1.2;
-unsigned long LENGTH=ULONG_MAX,exclude=0,CLENGTH=ULONG_MAX,causal;
-char *infile=NULL,*COLUMN=NULL,*outfile=NULL;
-char dimset=0,stout=1;
-
-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]\n");
- fprintf(stderr,"\t-m # of components, embedding dimension "
- "[default: %u,%u]\n",COMP,EMBED);
- fprintf(stderr,"\t-d delay [default: 1]\n");
- fprintf(stderr,"\t-n iterations [default: length]\n");
- fprintf(stderr,"\t-k minimal number of neighbors for the fit "
- "[default: 30]\n");
- fprintf(stderr,"\t-r neighborhoud size to start with "
- "[default: (data interval)/1000]\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 [default 'datafile'.fce"
- " no -o means write to stdout]\n");
- fprintf(stderr,"\t-V verbosity level [default: 1]\n\t\t"
- "0='only panic messages'\n\t\t"
- "1='+ input/output messages'\n\t\t"
- "2='+ print indiviual forecast errors'\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",&COMP,&EMBED);
- if ((out=check_option(in,n,'d','u')) != NULL)
- sscanf(out,"%u",&DELAY);
- if ((out=check_option(in,n,'n','u')) != NULL)
- sscanf(out,"%lu",&CLENGTH);
- if ((out=check_option(in,n,'V','u')) != NULL)
- sscanf(out,"%u",&verbosity);
- if ((out=check_option(in,n,'k','u')) != NULL)
- sscanf(out,"%u",&MINN);
- if ((out=check_option(in,n,'r','f')) != NULL) {
- epsset=1;
- sscanf(out,"%lf",&EPS0);
- }
- 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,'o','o')) != NULL) {
- stout=0;
- if (strlen(out) > 0)
- outfile=out;
- }
-}
-
-void put_in_boxes(void)
-{
- int i,j,n;
- double epsinv;
-
- epsinv=1.0/epsilon;
- for (i=0;i<NMAX;i++)
- for (j=0;j<NMAX;j++)
- box[i][j]= -1;
-
- for (n=hdim;n<LENGTH-STEP;n++) {
- i=(int)(series[0][n]*epsinv)&nmax;
- j=(int)(series[comp1][n-hdim]*epsinv)&nmax;
- list[n]=box[i][j];
- box[i][j]=n;
- }
-}
-
-unsigned int hfind_neighbors(unsigned long act)
-{
- char toolarge;
- int i,j,i1,i2,j1,k,element;
- unsigned long nfound=0;
- unsigned int hcomp,hdel;
- double max,dx,epsinv;
-
- epsinv=1.0/epsilon;
-
- i=(int)(series[0][act]*epsinv)&nmax;
- j=(int)(series[comp1][act-hdim]*epsinv)&nmax;
-
- for (i1=i-1;i1<=i+1;i1++) {
- i2=i1&nmax;
- for (j1=j-1;j1<=j+1;j1++) {
- element=box[i2][j1&nmax];
- while (element != -1) {
- max=0.0;
- toolarge=0;
- for (k=0;k<DIM;k += 1) {
- hcomp=indexes[0][k];
- hdel=indexes[1][k];
- dx=fabs(series[hcomp][element-hdel]-series[hcomp][act-hdel]);
- max=(dx>max) ? dx : max;
- if (max > epsilon) {
- toolarge=1;
- break;
- }
- if (toolarge)
- break;
- }
- if (max <= epsilon)
- hfound[nfound++]=element;
- element=list[element];
- }
- }
- }
- return nfound;
-}
-
-void multiply_matrix(double **mat,double *vec)
-{
- double *hvec;
- long i,j;
-
- check_alloc(hvec=(double*)malloc(sizeof(double)*DIM));
- for (i=0;i<DIM;i++) {
- hvec[i]=0.0;
- for (j=0;j<DIM;j++)
- hvec[i] += mat[i][j]*vec[j];
- }
- for (i=0;i<DIM;i++)
- vec[i]=hvec[i];
- free(hvec);
-}
-
-void make_fit(int number,unsigned long act,double *newcast)
-{
- double *sj,*si,lavi,lavj,fav;
- unsigned int hci,hdi,hcj,hdj;
- long i,j,n,which;
-
- for (i=0;i<DIM;i++)
- localav[i]=0.0;
- for (i=0;i<COMP;i++)
- foreav[i]=0.0;
-
- for (n=0;n<number;n++) {
- which=found[n];
- for (j=0;j<COMP;j++)
- foreav[j] += series[j][which+STEP];
- for (j=0;j<DIM;j++) {
- hcj=indexes[0][j];
- hdj=indexes[1][j];
- localav[j] += series[hcj][which-hdj];
- }
- }
-
- for (i=0;i<DIM;i++)
- localav[i] /= number;
- for (i=0;i<COMP;i++)
- foreav[i] /= number;
-
- for (i=0;i<DIM;i++) {
- hci=indexes[0][i];
- hdi=indexes[1][i];
- lavi=localav[i];
- si=series[hci];
- for (j=i;j<DIM;j++) {
- hcj=indexes[0][j];
- hdj=indexes[1][j];
- lavj=localav[j];
- sj=series[hcj];
- mat[i][j]=0.0;
- for (n=0;n<number;n++) {
- which=found[n];
- mat[i][j] += (si[which-hdi]-lavi)*(sj[which-hdj]-lavj);
- }
- mat[i][j] /= number;
- mat[j][i] = mat[i][j];
- }
- }
-
- imat=invert_matrix(mat,DIM);
-
- for (i=0;i<COMP;i++) {
- si=series[i];
- fav=foreav[i];
- for (j=0;j<DIM;j++) {
- hcj=indexes[0][j];
- hdj=indexes[1][j];
- lavj=localav[j];
- vec[j]=0.0;
- sj=series[hcj];
- for (n=0;n<number;n++) {
- which=found[n];
- vec[j] += (si[which+STEP]-fav)*(sj[which-hdj]);
- }
- vec[j] /= number;
- }
-
- multiply_matrix(imat,vec);
-
- newcast[i]=foreav[i];
- for (j=0;j<DIM;j++) {
- hcj=indexes[0][j];
- hdj=indexes[1][j];
- newcast[i] += vec[j]*(series[hcj][act-hdj]-localav[j]);
- }
- }
-
-
- for (i=0;i<DIM;i++)
- free(imat[i]);
- free(imat);
-}
-
-int main(int argc,char **argv)
-{
- char stin=0,alldone,*done;
- long i,j;
- unsigned long actfound;
- unsigned long clength;
- double *rms,*av,*min,*interval,maxinterval,norm;
- double *error,**individual=NULL;
- double *newcast;
- FILE *fout;
-
- if (scan_help(argc,argv))
- show_options(argv[0]);
-
- scan_options(argc,argv);
-
- if (!causalset)
- causal=STEP;
-
-#ifndef OMIT_WHAT_I_DO
- if (verbosity&VER_INPUT)
- what_i_do(argv[0],WID_STR);
-#endif
-
- infile=search_datafile(argc,argv,NULL,verbosity);
- if (infile == NULL)
- stin=1;
-
- if (outfile == NULL) {
- if (!stin) {
- check_alloc(outfile=(char*)calloc(strlen(infile)+5,(size_t)1));
- strcpy(outfile,infile);
- strcat(outfile,".fce");
- }
- else {
- check_alloc(outfile=(char*)calloc((size_t)10,(size_t)1));
- strcpy(outfile,"stdin.fce");
- }
- }
- if (!stout)
- test_outfile(outfile);
-
- if (COLUMN == NULL)
- series=(double**)get_multi_series(infile,&LENGTH,exclude,&COMP,"",dimset,
- verbosity);
- else
- series=(double**)get_multi_series(infile,&LENGTH,exclude,&COMP,COLUMN,
- dimset,verbosity);
-
- if ((LENGTH-(EMBED-1)*DELAY) < MINN) {
- fprintf(stderr,"Data set is too short to find enough neighbors "
- "for the fit! Exiting!\n");
- exit(ONESTEP_TOO_FEW_POINTS);
- }
-
- DIM=EMBED*COMP;
- check_alloc(min=(double*)malloc(sizeof(double)*COMP));
- check_alloc(interval=(double*)malloc(sizeof(double)*COMP));
- check_alloc(av=(double*)malloc(sizeof(double)*COMP));
- check_alloc(rms=(double*)malloc(sizeof(double)*COMP));
-
- maxinterval=0.0;
- for (i=0;i<COMP;i++) {
- rescale_data(series[i],LENGTH,&min[i],&interval[i]);
- maxinterval=(maxinterval<interval[i])?interval[i]:maxinterval;
- variance(series[i],LENGTH,&av[i],&rms[i]);
- }
-
- if (verbosity&VER_USR1) {
- check_alloc(individual=(double**)malloc(sizeof(double*)*COMP));
- for (j=0;j<COMP;j++) {
- check_alloc(individual[j]=(double*)malloc(sizeof(double)*LENGTH));
- for (i=0;i<LENGTH;i++)
- individual[j][i]=0.0;
- }
- }
-
- 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(done=(char*)malloc(sizeof(char)*LENGTH));
- check_alloc(box=(long**)malloc(sizeof(long*)*NMAX));
- for (i=0;i<NMAX;i++)
- check_alloc(box[i]=(long*)malloc(sizeof(long)*NMAX));
-
- for (i=0;i<LENGTH;i++)
- done[i]=0;
-
- alldone=0;
- if (epsset)
- EPS0 /= maxinterval;
-
- epsilon=EPS0/EPSF;
- clength=(CLENGTH <= LENGTH) ? CLENGTH-STEP : LENGTH-STEP;
- comp1=COMP-1;
- indexes=make_multi_index(COMP,EMBED,DELAY);
-
- hdim=(EMBED-1)*DELAY;
- check_alloc(newcast=(double*)malloc(sizeof(double)*COMP));
-
-
- check_alloc(localav=(double*)malloc(sizeof(double)*DIM));
- check_alloc(foreav=(double*)malloc(sizeof(double)*COMP));
- check_alloc(vec=(double*)malloc(sizeof(double)*DIM));
- check_alloc(mat=(double**)malloc(sizeof(double*)*DIM));
- for (i=0;i<=DIM;i++)
- check_alloc(mat[i]=(double*)malloc(sizeof(double)*DIM));
-
- check_alloc(error=(double*)malloc(sizeof(double)*COMP));
- for (i=0;i<COMP;i++)
- error[i]=0.0;
-
- while (!alldone) {
- alldone=1;
- epsilon*=EPSF;
- put_in_boxes() ;
- for (i=(EMBED-1)*DELAY;i<clength;i++)
- if (!done[i]) {
- actfound=hfind_neighbors(i);
- actfound=exclude_interval(actfound,i-causal+1,
- i+causal+(EMBED-1)*DELAY-1,hfound,found);
- if (actfound > MINN) {
- make_fit(actfound,i,newcast);
- for (j=0;j<COMP;j++)
- error[j] += sqr(newcast[j]-series[j][i+STEP]);
- if (verbosity&VER_USR1) {
- for (j=0;j<COMP;j++)
- individual[j][i]=(newcast[j]-series[j][i+STEP])*interval[j];
- }
- done[i]=1;
- }
- alldone &= done[i];
- }
- }
- norm=((double)clength-(double)((EMBED-1)*DELAY));
- if (stout) {
- if (verbosity&VER_USR1) {
- fprintf(stdout,"#Relative forecast errors for each component:\n");
- for (i=0;i<COMP;i++)
- fprintf(stdout,"# %e\n",sqrt(error[i]/norm)/rms[i]);
-
- for (i=(EMBED-1)*DELAY;i<clength;i++) {
- for (j=0;j<COMP-1;j++)
- fprintf(stdout,"%e ",individual[j][i]);
- fprintf(stdout,"%e\n",individual[COMP-1][i]);
- }
- }
- else {
- fprintf(stdout,"#Relative forecast errors for each component:\n");
- for (i=0;i<COMP;i++)
- fprintf(stdout,"%e\n",sqrt(error[i]/norm)/rms[i]);
- }
- }
- else {
- fout=fopen(outfile,"w");
- if (verbosity&VER_INPUT)
- fprintf(stderr,"Opened %s for writing\n",outfile);
- if (verbosity&VER_USR1) {
- fprintf(fout,"#Relative forecast errors for each component:\n");
- for (i=0;i<COMP;i++)
- fprintf(fout,"# %e\n",sqrt(error[i]/norm)/rms[i]);
-
- for (i=(EMBED-1)*DELAY;i<clength;i++) {
- for (j=0;j<COMP-1;j++)
- fprintf(fout,"%e ",individual[j][i]);
- fprintf(fout,"%e\n",individual[COMP-1][i]);
- }
- }
- else {
- fprintf(fout,"#Relative forecast errors for each component:\n");
- for (i=0;i<COMP;i++)
- fprintf(fout,"%e\n",sqrt(error[i]/norm)/rms[i]);
- }
- fclose(fout);
- free(outfile);
- }
-
- return 0;
-}
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