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<title>GNU Scientific Library – Reference Manual: Example ntuple programs</title>
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<a name="Example-ntuple-programs"></a>
<div class="header">
<p>
Next: <a href="Ntuple-References-and-Further-Reading.html#Ntuple-References-and-Further-Reading" accesskey="n" rel="next">Ntuple References and Further Reading</a>, Previous: <a href="Histogramming-ntuple-values.html#Histogramming-ntuple-values" accesskey="p" rel="previous">Histogramming ntuple values</a>, Up: <a href="N_002dtuples.html#N_002dtuples" accesskey="u" rel="up">N-tuples</a> [<a href="Function-Index.html#Function-Index" title="Index" rel="index">Index</a>]</p>
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<hr>
<a name="Examples-15"></a>
<h3 class="section">23.8 Examples</h3>
<p>The following example programs demonstrate the use of ntuples in
managing a large dataset. The first program creates a set of 10,000
simulated “events”, each with 3 associated values <em>(x,y,z)</em>. These
are generated from a Gaussian distribution with unit variance, for
demonstration purposes, and written to the ntuple file <samp>test.dat</samp>.
</p>
<div class="example">
<pre class="verbatim">#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);
gsl_rng_free (r);
return 0;
}
</pre></div>
<p>The next program analyses the ntuple data in the file <samp>test.dat</samp>.
The analysis procedure is to compute the squared-magnitude of each
event, <em>E^2=x^2+y^2+z^2</em>, and select only those which exceed a
lower limit of 1.5. The selected events are then histogrammed using
their <em>E^2</em> values.
</p>
<div class="example">
<pre class="verbatim">#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;
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)
{
struct data * data = (struct data *) ntuple_data;
double x, y, z, E2, scale;
scale = *(double *) params;
x = data->x;
y = data->y;
z = data->z;
E2 = x * x + y * y + z * z;
return E2 > scale;
}
double
val_func (void *ntuple_data, void *params)
{
struct data * data = (struct data *) ntuple_data;
double x, y, z;
x = data->x;
y = data->y;
z = data->z;
return x * x + y * y + z * z;
}
</pre></div>
<p>The following plot shows the distribution of the selected events.
Note the cut-off at the lower bound.
</p>
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