be identical. If missing values are involved, then element (i,j)
is the moment of the i th variable, when paired with the j th variable.
*/
-const gsl_matrix *
+gsl_matrix *
covariance_moments (const struct covariance *cov, int m)
{
return cov->moments[m];
bool centered)
{
size_t i;
- struct covariance *cov = xzalloc (sizeof *cov);
+ struct covariance *cov = XZALLOC (struct covariance);
cov->centered = centered;
cov->passes = 1;
cov->exclude = exclude;
- cov->n_cm = (n_vars * (n_vars - 1) ) / 2;
+ cov->n_cm = (n_vars * (n_vars - 1)) / 2;
cov->cm = xcalloc (cov->n_cm, sizeof *cov->cm);
assert (i >= 0);
assert (j < cov->dim);
- if ( i == 0)
+ if (i == 0)
return -1;
if (j >= cov->dim - 1)
return -1;
- if ( i <= j)
+ if (i <= j)
return -1 ;
as = nj * (nj + 1) ;
const union value *val = case_data (c, var);
- return var_is_value_missing (var, val, cov->exclude);
+ return (var_is_value_missing (var, val) & cov->exclude) != 0;
}
static double
get_val (const struct covariance *cov, int i, const struct ccase *c)
{
- if ( i < cov->n_vars)
+ if (i < cov->n_vars)
{
const struct variable *var = cov->vars[i];
covariance_accumulate_pass1 (struct covariance *cov, const struct ccase *c)
{
size_t i, j, m;
- const double weight = cov->wv ? case_data (c, cov->wv)->f : 1.0;
+ const double weight = cov->wv ? case_num (c, cov->wv) : 1.0;
assert (cov->passes == 2);
if (!cov->pass_one_first_case_seen)
{
double v1 = get_val (cov, i, c);
- if ( is_missing (cov, i, c))
+ if (is_missing (cov, i, c))
continue;
for (j = 0 ; j < cov->dim; ++j)
{
double pwr = 1.0;
- if ( is_missing (cov, j, c))
+ if (is_missing (cov, j, c))
continue;
for (m = 0 ; m <= MOMENT_MEAN; ++m)
covariance_accumulate_pass2 (struct covariance *cov, const struct ccase *c)
{
size_t i, j;
- const double weight = cov->wv ? case_data (c, cov->wv)->f : 1.0;
+ const double weight = cov->wv ? case_num (c, cov->wv) : 1.0;
assert (cov->passes == 2);
assert (cov->state >= 1);
if (cov->categoricals)
cov->dim += categoricals_df_total (cov->categoricals);
- cov->n_cm = (cov->dim * (cov->dim - 1) ) / 2;
+ cov->n_cm = (cov->dim * (cov->dim - 1)) / 2;
cov->cm = xcalloc (cov->n_cm, sizeof *cov->cm);
/* Grow the moment matrices so that they're large enough to accommodate the
{
double v1 = get_val (cov, i, c);
- if ( is_missing (cov, i, c))
+ if (is_missing (cov, i, c))
continue;
for (j = 0 ; j < cov->dim; ++j)
const double s = pow2 (v1 - gsl_matrix_get (cov->moments[MOMENT_MEAN], i, j)) * weight;
- if ( is_missing (cov, j, c))
+ if (is_missing (cov, j, c))
continue;
{
covariance_accumulate (struct covariance *cov, const struct ccase *c)
{
size_t i, j, m;
- const double weight = cov->wv ? case_data (c, cov->wv)->f : 1.0;
+ const double weight = cov->wv ? case_num (c, cov->wv) : 1.0;
assert (cov->passes == 1);
- if ( !cov->pass_one_first_case_seen)
+ if (!cov->pass_one_first_case_seen)
{
- assert ( cov->state == 0);
+ assert (cov->state == 0);
cov->state = 1;
}
{
const union value *val1 = case_data (c, cov->vars[i]);
- if ( is_missing (cov, i, c))
+ if (is_missing (cov, i, c))
continue;
for (j = 0 ; j < cov->dim; ++j)
int idx;
const union value *val2 = case_data (c, cov->vars[j]);
- if ( is_missing (cov, j, c))
+ if (is_missing (cov, j, c))
continue;
idx = cm_idx (cov, i, j);
gsl_matrix *m = gsl_matrix_calloc (cov->dim, cov->dim);
/* Copy the non-diagonal elements from cov->cm */
- for ( j = 0 ; j < cov->dim - 1; ++j)
+ for (j = 0 ; j < cov->dim - 1; ++j)
{
for (i = j+1 ; i < cov->dim; ++i)
{
*x /= gsl_matrix_get (cov->moments[MOMENT_NONE], i, j);
idx = cm_idx (cov, i, j);
- if ( idx >= 0)
+ if (idx >= 0)
{
x = &cov->cm [idx];
*x /= gsl_matrix_get (cov->moments[MOMENT_NONE], i, j);
for (m = 0; m < n_MOMENTS; ++m)
{
/* Divide the moments by the number of samples */
- if ( m > 0)
+ if (m > 0)
{
for (i = 0 ; i < cov->dim; ++i)
{
double *x = gsl_matrix_ptr (cov->moments[m], i, j);
*x /= gsl_matrix_get (cov->moments[0], i, j);
- if ( m == MOMENT_VARIANCE)
+ if (m == MOMENT_VARIANCE)
*x -= pow2 (gsl_matrix_get (cov->moments[1], i, j));
}
}
if (cov->centered)
{
/* Centre the moments */
- for ( j = 0 ; j < cov->dim - 1; ++j)
+ for (j = 0 ; j < cov->dim - 1; ++j)
{
for (i = j + 1 ; i < cov->dim; ++i)
{
gsl_matrix *
covariance_calculate (struct covariance *cov)
{
- if ( cov->state <= 0 )
+ if (cov->state <= 0)
return NULL;
switch (cov->passes)
}
}
- for ( j = 0 ; j < cov->dim - 1; ++j)
+ for (j = 0 ; j < cov->dim - 1; ++j)
{
for (i = j + 1 ; i < cov->dim; ++i)
{
const gsl_matrix *
covariance_calculate_unnormalized (struct covariance *cov)
{
- if ( cov->state <= 0 )
+ if (cov->state <= 0)
return NULL;
if (cov->unnormalised != NULL)