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/* ocamlgsl - OCaml interface to GSL */
/* Copyright () 2002 - Olivier Andrieu */
/* distributed under the terms of the GPL version 2 */
#include <gsl/gsl_statistics_double.h>
#include <caml/mlvalues.h>
#include <caml/fail.h>
#include "wrappers.h"
static inline void check_array_size(value a, value b)
{
if(Double_array_length(a) != Double_array_length(b))
invalid_argument("arrays sizes differ");
}
CAMLprim value ml_gsl_stats_mean(value ow, value data)
{
size_t len = Double_array_length(data);
double result;
if(ow == Val_none)
result = gsl_stats_mean(Double_array_val(data), 1, len);
else {
value w = Unoption(ow);
check_array_size(data, w);
result = gsl_stats_wmean(Double_array_val(w), 1,
Double_array_val(data), 1, len);
}
return copy_double(result);
}
CAMLprim value ml_gsl_stats_variance(value ow, value omean, value data)
{
size_t len = Double_array_length(data);
double result;
if(ow == Val_none)
if(omean == Val_none)
result = gsl_stats_variance(Double_array_val(data), 1, len);
else
result = gsl_stats_variance_m(Double_array_val(data), 1, len,
Double_val(Unoption(omean)));
else {
value w = Unoption(ow);
check_array_size(data, w);
if(omean == Val_none)
result = gsl_stats_wvariance(Double_array_val(w), 1,
Double_array_val(data), 1, len);
else
result = gsl_stats_wvariance_m(Double_array_val(w), 1,
Double_array_val(data), 1, len,
Double_val(Unoption(omean)));
}
return copy_double(result);
}
CAMLprim value ml_gsl_stats_sd(value ow, value omean, value data)
{
size_t len = Double_array_length(data);
double result;
if(ow == Val_none)
if(omean == Val_none)
result = gsl_stats_sd(Double_array_val(data), 1, len);
else
result = gsl_stats_sd_m(Double_array_val(data), 1, len,
Double_val(Unoption(omean)));
else {
value w = Unoption(ow);
check_array_size(data, w);
if(omean == Val_none)
result = gsl_stats_wsd(Double_array_val(w), 1,
Double_array_val(data), 1, len);
else
result = gsl_stats_wsd_m(Double_array_val(w), 1,
Double_array_val(data), 1, len,
Double_val(Unoption(omean)));
}
return copy_double(result);
}
CAMLprim value ml_gsl_stats_variance_with_fixed_mean(value ow,
value mean, value data)
{
size_t len = Double_array_length(data);
double result;
if(ow == Val_none)
result = gsl_stats_variance_with_fixed_mean(Double_array_val(data),
1, len, Double_val(mean));
else {
value w = Unoption(ow);
check_array_size(data, w);
result = gsl_stats_wvariance_with_fixed_mean(Double_array_val(w), 1,
Double_array_val(data), 1,
len, Double_val(mean));
}
return copy_double(result);
}
CAMLprim value ml_gsl_stats_sd_with_fixed_mean(value ow,
value mean, value data)
{
size_t len = Double_array_length(data);
double result;
if(ow == Val_none)
result = gsl_stats_sd_with_fixed_mean(Double_array_val(data),
1, len, Double_val(mean));
else {
value w = Unoption(ow);
check_array_size(data, w);
result = gsl_stats_wsd_with_fixed_mean(Double_array_val(w), 1,
Double_array_val(data), 1,
len, Double_val(mean));
}
return copy_double(result);
}
CAMLprim value ml_gsl_stats_absdev(value ow, value omean, value data)
{
size_t len = Double_array_length(data);
double result;
if(ow == Val_none)
if(omean == Val_none)
result = gsl_stats_absdev(Double_array_val(data), 1, len);
else
result = gsl_stats_absdev_m(Double_array_val(data), 1, len,
Double_val(Unoption(omean)));
else {
value w = Unoption(ow);
check_array_size(data, w);
if(omean == Val_none)
result = gsl_stats_wabsdev(Double_array_val(w), 1,
Double_array_val(data), 1, len);
else
result = gsl_stats_wabsdev_m(Double_array_val(w), 1,
Double_array_val(data), 1, len,
Double_val(Unoption(omean)));
}
return copy_double(result);
}
CAMLprim value ml_gsl_stats_skew(value ow, value data)
{
size_t len = Double_array_length(data);
double result;
if(ow == Val_none)
result = gsl_stats_skew(Double_array_val(data), 1, len);
else {
value w = Unoption(ow);
check_array_size(data, w);
result = gsl_stats_wskew(Double_array_val(w), 1,
Double_array_val(data), 1, len);
}
return copy_double(result);
}
CAMLprim value ml_gsl_stats_skew_m_sd(value ow, value mean,
value sd, value data)
{
size_t len = Double_array_length(data);
double result;
if(ow == Val_none)
result = gsl_stats_skew_m_sd(Double_array_val(data), 1, len,
Double_val(mean), Double_val(sd));
else {
value w = Unoption(ow);
check_array_size(data, w);
result = gsl_stats_wskew_m_sd(Double_array_val(w), 1,
Double_array_val(data), 1, len,
Double_val(mean), Double_val(sd));
}
return copy_double(result);
}
CAMLprim value ml_gsl_stats_kurtosis(value ow, value data)
{
size_t len = Double_array_length(data);
double result;
if(ow == Val_none)
result = gsl_stats_kurtosis(Double_array_val(data), 1, len);
else {
value w = Unoption(ow);
check_array_size(data, w);
result = gsl_stats_wkurtosis(Double_array_val(w), 1,
Double_array_val(data), 1, len);
}
return copy_double(result);
}
CAMLprim value ml_gsl_stats_kurtosis_m_sd(value ow, value mean,
value sd, value data)
{
size_t len = Double_array_length(data);
double result;
if(ow == Val_none)
result = gsl_stats_kurtosis_m_sd(Double_array_val(data), 1, len,
Double_val(mean), Double_val(sd));
else {
value w = Unoption(ow);
check_array_size(data, w);
result = gsl_stats_wkurtosis_m_sd(Double_array_val(w), 1,
Double_array_val(data), 1, len,
Double_val(mean), Double_val(sd));
}
return copy_double(result);
}
CAMLprim value ml_gsl_stats_lag1_autocorrelation(value omean, value data)
{
size_t len = Double_array_length(data);
double result;
if(omean == Val_none)
result = gsl_stats_lag1_autocorrelation(Double_array_val(data), 1, len);
else
result = gsl_stats_lag1_autocorrelation_m(Double_array_val(data), 1, len,
Double_val(Unoption(omean)));
return copy_double(result);
}
CAMLprim value ml_gsl_stats_covariance(value data1, value data2)
{
size_t len = Double_array_length(data1);
double result;
check_array_size(data1, data2);
result = gsl_stats_covariance(Double_array_val(data1), 1,
Double_array_val(data2), 1, len);
return copy_double(result);
}
CAMLprim value ml_gsl_stats_covariance_m(value mean1, value data1,
value mean2, value data2)
{
size_t len = Double_array_length(data1);
double result;
check_array_size(data1, data2);
result = gsl_stats_covariance_m(Double_array_val(data1), 1,
Double_array_val(data2), 1, len,
Double_val(mean1), Double_val(mean2));
return copy_double(result);
}
CAMLprim value ml_gsl_stats_max(value data)
{
size_t len = Double_array_length(data);
double result = gsl_stats_max(Double_array_val(data), 1, len);
return copy_double(result);
}
CAMLprim value ml_gsl_stats_min(value data)
{
size_t len = Double_array_length(data);
double result = gsl_stats_min(Double_array_val(data), 1, len);
return copy_double(result);
}
CAMLprim value ml_gsl_stats_minmax(value data)
{
size_t len = Double_array_length(data);
double mi, ma;
gsl_stats_minmax(&mi, &ma, Double_array_val(data), 1, len);
return copy_two_double(mi, ma);
}
CAMLprim value ml_gsl_stats_max_index(value data)
{
size_t len = Double_array_length(data);
size_t result = gsl_stats_max_index(Double_array_val(data), 1, len);
return Val_int(result);
}
CAMLprim value ml_gsl_stats_min_index(value data)
{
size_t len = Double_array_length(data);
size_t result = gsl_stats_min_index(Double_array_val(data), 1, len);
return Val_int(result);
}
CAMLprim value ml_gsl_stats_minmax_index(value data)
{
size_t len = Double_array_length(data);
size_t mi, ma;
value r;
gsl_stats_minmax_index(&mi, &ma, Double_array_val(data), 1, len);
r = alloc_small(2, 0);
Field(r, 0) = Val_int(mi);
Field(r, 1) = Val_int(ma);
return r;
}
CAMLprim value ml_gsl_stats_quantile_from_sorted_data(value data, value f)
{
size_t len = Double_array_length(data);
double r = gsl_stats_quantile_from_sorted_data(Double_array_val(data),
1, len, Double_val(f));
return copy_double(r);
}
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