Array_item *add_to_array (Array *array, Array_item *item)
{
int count;
int location = 0;
Array_item *ret = (void *) 0 ;
u_32int_t mask;
if (array->hash == HASH_INSENSITIVE)
item->hash = ci_alist_hash(item->name, &mask);
else
item->hash = cs_alist_hash(item->name, &mask);
check_array_size(array);
if (array->max)
{
find_array_item(array, item->name, &count, &location);
if (count < 0)
{
ret = ((Array_item *) (( array ) -> list [ ( location ) ])) ;
array->max--;
}
else
move_array_items(array, location, array->max, 1);
}
array->list[location] = item;
array->max++;
return ret;
}
/*
* Returns an entry that has been displaced, if any.
*/
Array_item *BX_add_to_array (Array *array, Array_item *item)
{
int count;
int location = 0;
Array_item *ret = NULL;
u_32int_t mask; /* Dummy var */
if (array->hash == HASH_INSENSITIVE)
item->hash = ci_alist_hash(item->name, &mask);
else
item->hash = cs_alist_hash(item->name, &mask);
check_array_size(array);
if (array->max)
{
find_array_item(array, item->name, &count, &location);
if (count < 0)
{
ret = ARRAY_ITEM(array, location);
array->max--;
}
else
move_array_items(array, location, array->max, 1);
}
array->list[location] = item;
array->max++;
return ret;
}
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);
}
/* Remove the 'which'th item from the given array */
array_item *array_pop (array *a, int which)
{
array_item *ret = NULL;
if (which < 0 || which >= a->max)
return NULL;
ret = ARRAY_ITEM(a, which);
move_array_items(a, which + 1, a->max, -1);
a->max--;
check_array_size(a);
return ret;
}
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_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_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);
}
