Example programs

The following example programs demonstrate the use of ntuples in managing a large dataset. The first program creates a set of 100,000 simulated "events", each with 3 associated values @math{(x,y,z)}. These are generated from a gaussian distribution with unit variance, for demonstration purposes, and written to the ntuple file `test.dat'.

#include <config.h>
#include <gsl/gsl_ntuple.h>
#include <gsl/gsl_rng.h>
#include <gsl/gsl_randist.h>

struct data
{
  double x;
  double y;
  double z;
};

int
main (void)
{
  const gsl_rng_type * T;
  gsl_rng * r;

  struct data ntuple_row;
  int i;

  gsl_ntuple *ntuple 
    = gsl_ntuple_create ("test.dat", &ntuple_row, 
                         sizeof (ntuple_row));

  gsl_rng_env_setup();

  T = gsl_rng_default; 
  r = gsl_rng_alloc (T);

  for (i = 0; i < 10000; i++)
    {
      ntuple_row.x = gsl_ran_ugaussian (r);
      ntuple_row.y = gsl_ran_ugaussian (r);
      ntuple_row.z = gsl_ran_ugaussian (r);
      
      gsl_ntuple_write (ntuple);
    }
  
  gsl_ntuple_close(ntuple);
  return 0;
}

The next program analyses the ntuple data in the file `test.dat'. The analysis procedure is to compute the squared-magnitude of each event, @math{E^2=x^2+y^2+z^2}, and select only those which exceed a lower limit of 1.5. The selected events are then histogrammed using their @math{E^2} values.

#include <config.h>
#include <math.h>
#include <gsl/gsl_ntuple.h>
#include <gsl/gsl_histogram.h>

struct data
{
  double x;
  double y;
  double z;
};

int sel_func (void *ntuple_data, void *params);
double val_func (void *ntuple_data, void *params);

int
main (void)
{
  struct data ntuple_row;
  int i;

  gsl_ntuple *ntuple 
    = gsl_ntuple_open ("test.dat", &ntuple_row,
                       sizeof (ntuple_row));
  double lower = 1.5;

  gsl_ntuple_select_fn S;
  gsl_ntuple_value_fn V;

  gsl_histogram *h = gsl_histogram_alloc (100);
  gsl_histogram_set_ranges_uniform(h, 0.0, 10.0);

  S.function = &sel_func;
  S.params = &lower;

  V.function = &val_func;
  V.params = 0;

  gsl_ntuple_project (h, ntuple, &V, &S);

  gsl_histogram_fprintf (stdout, h, "%f", "%f");

  gsl_histogram_free (h);

  gsl_ntuple_close (ntuple);
  return 0;
}

int
sel_func (void *ntuple_data, void *params)
{
  double x, y, z, E, scale;
  scale = *(double *) params;

  x = ((struct data *) ntuple_data)->x;
  y = ((struct data *) ntuple_data)->y;
  z = ((struct data *) ntuple_data)->z;

  E2 = x * x + y * y + z * z;

  return E2 > scale;
}

double
val_func (void *ntuple_data, void *params)
{
  double x, y, z;

  x = ((struct data *) ntuple_data)->x;
  y = ((struct data *) ntuple_data)->y;
  z = ((struct data *) ntuple_data)->z;

  return x * x + y * y + z * z;
}

The following plot shows the distribution of the selected events. Note the cut-off at the lower bound.

@image{ntuple,4in}