ols_main.cc

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/*                     Author :  Alan W Black                            */
/*                     Date   :  January 1998                            */
/*-----------------------------------------------------------------------*/
/*  Ordinary least squares                                               */
/*                                                                       */
/*=======================================================================*/
#include <cstdlib>
#include <iostream>
#include <fstream>
#include <cstring>
#include "EST_Wagon.h"
#include "EST_multistats.h"
#include "EST_cmd_line.h"

static void load_ols_data(EST_FMatrix &X, EST_FMatrix &Y, WDataSet &d);
static int ols_main(int argc, char **argv);


/** @name <command>ols</command> <emphasis>Train linear regression model</emphasis>
    @id ols-manual
  * @toc
 */

//@{


/**@name Synopsis
  */
//@{

//@synopsis

/**
 */

//@}

/**@name OPTIONS
  */
//@{

//@options

//@}


int main(int argc, char **argv)
{
    return ols_main(argc,argv);
}

static int ols_main(int argc, char **argv)
{
    // Top level function loads in sample data and finds coefficients
    EST_Option al;
    EST_StrList files;
    EST_String ofile = "-";
    WDataSet dataset,test_dataset;
    EST_FMatrix coeffs;
    EST_FMatrix X,Y,Xtest,Ytest;
    LISP ignores = NIL;

    parse_command_line
    (argc, argv,
       EST_String("[options]\n")+
       "Summary: Linear Regression by ordinary least squares (defaults in {})\n"+
     "-desc <ifile>     Field description file\n"+
     "-data <ifile>     Datafile, one vector per line\n"+
     "-test <ifile>     Datafile, for testing\n"+
     "-robust           Robust, may take longer\n"+
     "-stepwise         Order the features by contribution,\n"+
     "                  implies robust.\n"+
     "-swlimit <float> {0.0}\n"+
     "                  Percentage necessary improvement for stepwise\n"+
     "-quiet            No summary\n"+
     "-o      <ofile>   \n"+
     "-output <ofile>   Output file for coefficients\n"+
     "-ignore <string>  Filename or bracket list of fields to ignore\n",
     files, al);


    if (al.present("-output"))
    ofile = al.val("-output");
    if (al.present("-o"))
    ofile = al.val("-o");

    siod_init();

    if (al.present("-ignore"))
    {
        EST_String ig = al.val("-ignore");
        if (ig[0] == '(')
            ignores = read_from_string(ig);
        else
            ignores = vload(ig,1);
    }

    // Load in the data
    if (!al.present("-desc"))
    {
    cerr << "ols: no description file specified\n";
    return -1;
    }
    else
    {
    dataset.load_description(al.val("-desc"),ignores);
        dataset.ignore_non_numbers();
    }
    if (!al.present("-data"))
    {
    cerr << "ols: no data file specified\n";
    return -1;
    }
    else
    wgn_load_dataset(dataset,al.val("-data"));
    if (al.present("-test"))
    {
    test_dataset.load_description(al.val("-desc"),ignores);
        test_dataset.ignore_non_numbers();
    wgn_load_dataset(test_dataset,al.val("-test"));
    load_ols_data(Xtest,Ytest,test_dataset);
    }
    else
    // No test data specified so use training data
    load_ols_data(Xtest,Ytest,dataset);

    load_ols_data(X,Y,dataset);

    if (al.present("-stepwise"))
    {
    EST_StrList names;
    float swlimit = al.fval("-swlimit");
        EST_IVector included;
        int i;

    names.append("Intercept");
    for (i=1; i < dataset.width(); i++)
        names.append(dataset.feat_name(i));

        included.resize(X.num_columns());
        included[0] = TRUE;  // always guarantee interceptor
        for (i=1; i<included.length(); i++)
        {
            if (dataset.ignore(i) == TRUE)
                included.a_no_check(i) = OLS_IGNORE;
            else
                included.a_no_check(i) = FALSE;
        }

    if (!stepwise_ols(X,Y,names,swlimit,coeffs,Xtest,Ytest,included))
    {
        cerr << "OLS: failed stepwise ols" << endl;
        return -1;
    }
    }
    else if (al.present("-robust"))
    {
        EST_IVector included;
        int i;

        included.resize(X.num_columns());
        included[0] = TRUE;  // always guarantee interceptor
        for (i=1; i<included.length(); i++)
        {
            if (dataset.ignore(i) == TRUE)
                included.a_no_check(i) = OLS_IGNORE;
            else
                included.a_no_check(i) = TRUE;
        }

    if (!robust_ols(X,Y,included,coeffs))
    {
        cerr << "OLS: failed robust ols" << endl;
        return -1;
    }
    }
    else if (!ols(X,Y,coeffs))
    {
    cerr << "OLS: failed no pseudo_inverse" << endl;
    return -1;
    }

    if (coeffs.save(ofile) != write_ok)
    {
    cerr << "OLS: failed to save coefficients in \"" << ofile << "\"" 
        << endl;
    return -1;
    }

    if (!al.present("-quiet"))
    {
    EST_FMatrix pred;
    float cor,rmse;

    ols_apply(Xtest,coeffs,pred);
    ols_test(Ytest,pred,cor,rmse);

    printf(";; RMSE %f Correlation is %f\n",rmse,cor);
    }

    return 0;
}

static void load_ols_data(EST_FMatrix &X, EST_FMatrix &Y, WDataSet &d)
{
    EST_Litem *p;
    int n,m;

    X.resize(d.length(),d.width());
    Y.resize(d.length(),1);

    for (n=0,p=d.head(); p != 0; p=p->next(),n++)
    {
    Y.a_no_check(n,0) = d(p)->get_flt_val(0);
    X.a_no_check(n,0) = 1;
    for (m=1; m < d.width(); m++)
        {
            if (d.ignore(m))
            {
                X.a_no_check(n,m) = 0;
            }
            else
                X.a_no_check(n,m) = d(p)->get_flt_val(m);
        }
    }

}