{
/* The variables for which the covariance matrix is to be calculated. */
size_t n_vars;
- const struct variable **vars;
+ const struct variable *const *vars;
/* Categorical variables. */
struct categoricals *categoricals;
/* Create a covariance struct.
*/
struct covariance *
-covariance_1pass_create (size_t n_vars, const struct variable **vars,
+covariance_1pass_create (size_t n_vars, const struct variable *const *vars,
const struct variable *weight, enum mv_class exclude)
{
size_t i;
- struct covariance *cov = xmalloc (sizeof *cov);
+ struct covariance *cov = xzalloc (sizeof *cov);
cov->passes = 1;
cov->state = 0;
cov->n_cm = (n_vars * (n_vars - 1) ) / 2;
- cov->cm = xcalloc (sizeof *cov->cm, cov->n_cm);
+ if (cov->n_cm > 0)
+ cov->cm = xcalloc (sizeof *cov->cm, cov->n_cm);
+ cov->categoricals = NULL;
return cov;
}
until then.
*/
struct covariance *
-covariance_2pass_create (size_t n_vars, const struct variable **vars,
- size_t n_catvars, const struct variable **catvars,
+covariance_2pass_create (size_t n_vars, const struct variable *const *vars,
+ size_t n_catvars, const struct variable *const *catvars,
const struct variable *wv, enum mv_class exclude)
{
size_t i;
cov->exclude = exclude;
- cov->n_cm = - 1;
+ cov->n_cm = -1;
cov->cm = NULL;
- cov->categoricals = categoricals_create (catvars, n_catvars, wv);
+ cov->categoricals = categoricals_create (catvars, n_catvars, wv, exclude);
return cov;
}
return categoricals_get_binary_by_subscript (cov->categoricals, i - cov->n_vars, c);
}
-static void
+#if 0
+void
dump_matrix (const gsl_matrix *m)
{
size_t i, j;
printf ("\n");
}
}
+#endif
/* Call this function for every case in the data set */
void
if (! cov->pass_two_first_case_seen)
{
+ size_t m;
assert (cov->state == 1);
cov->state = 2;
- cov->dim = cov->n_vars + categoricals_total (cov->categoricals);
+ cov->dim = cov->n_vars +
+ categoricals_total (cov->categoricals) - categoricals_get_n_variables (cov->categoricals);
+
cov->n_cm = (cov->dim * (cov->dim - 1) ) / 2;
cov->cm = xcalloc (sizeof *cov->cm, cov->n_cm);
categoricals_done (cov->categoricals);
+ /* Populate the moments matrices with the categorical value elements */
+ for (i = cov->n_vars; i < cov->dim; ++i)
+ {
+ for (j = 0 ; j < cov->dim ; ++j) /* FIXME: This is WRONG !!! */
+ {
+ double w = categoricals_get_weight_by_subscript (cov->categoricals, i - cov->n_vars);
+
+ gsl_matrix_set (cov->moments[MOMENT_NONE], i, j, w);
+
+ w = categoricals_get_sum_by_subscript (cov->categoricals, i - cov->n_vars);
+
+ gsl_matrix_set (cov->moments[MOMENT_MEAN], i, j, w);
+ }
+ }
+
+ /* FIXME: This is WRONG!! It must be fixed to properly handle missing values. For
+ now it assumes there are none */
+ for (m = 0 ; m < n_MOMENTS; ++m)
+ {
+ for (i = 0 ; i < cov->dim ; ++i)
+ {
+ double x = gsl_matrix_get (cov->moments[m], i, cov->n_vars -1);
+ for (j = cov->n_vars; j < cov->dim; ++j)
+ {
+ gsl_matrix_set (cov->moments[m], i, j, x);
+ }
+ }
+ }
+
/* Divide the means by the number of samples */
- for (i = 0; i < cov->n_vars; ++i)
+ for (i = 0; i < cov->dim; ++i)
{
- for (j = 0; j < cov->n_vars; ++j)
+ for (j = 0; j < cov->dim; ++j)
{
double *x = gsl_matrix_ptr (cov->moments[MOMENT_MEAN], i, j);
*x /= gsl_matrix_get (cov->moments[MOMENT_NONE], i, j);
{
cov->cm [idx] += ss;
}
-
}
}
}
-
/*
Return a pointer to gsl_matrix containing the pairwise covariances.
The matrix remains owned by the COV object, and must not be freed.
const gsl_matrix *
covariance_calculate (struct covariance *cov)
{
- assert ( cov->state > 0 );
+ if ( cov->state <= 0 )
+ return NULL;
switch (cov->passes)
{
}
}
+/*
+ Covariance computed without dividing by the sample size.
+ */
+static const gsl_matrix *
+covariance_calculate_double_pass_unnormalized (struct covariance *cov)
+{
+ size_t i, j;
+ for (i = 0 ; i < cov->dim; ++i)
+ {
+ for (j = 0 ; j < cov->dim; ++j)
+ {
+ int idx;
+ double *x = gsl_matrix_ptr (cov->moments[MOMENT_VARIANCE], i, j);
+
+ idx = cm_idx (cov, i, j);
+ if ( idx >= 0)
+ {
+ x = &cov->cm [idx];
+ }
+ }
+ }
+
+ return cm_to_gsl (cov);
+}
+
+static const gsl_matrix *
+covariance_calculate_single_pass_unnormalized (struct covariance *cov)
+{
+ size_t i, j;
+
+ for (i = 0 ; i < cov->dim; ++i)
+ {
+ for (j = 0 ; j < cov->dim; ++j)
+ {
+ double *x = gsl_matrix_ptr (cov->moments[MOMENT_VARIANCE], i, j);
+ *x -= pow2 (gsl_matrix_get (cov->moments[MOMENT_MEAN], i, j))
+ / gsl_matrix_get (cov->moments[MOMENT_NONE], i, j);
+ }
+ }
+ for ( j = 0 ; j < cov->dim - 1; ++j)
+ {
+ for (i = j + 1 ; i < cov->dim; ++i)
+ {
+ double *x = &cov->cm [cm_idx (cov, i, j)];
+
+ *x -=
+ gsl_matrix_get (cov->moments[MOMENT_MEAN], i, j)
+ *
+ gsl_matrix_get (cov->moments[MOMENT_MEAN], j, i)
+ / gsl_matrix_get (cov->moments[MOMENT_NONE], i, j);
+ }
+ }
+
+ return cm_to_gsl (cov);
+}
+
+/*
+ Return a pointer to gsl_matrix containing the pairwise covariances.
+ The matrix remains owned by the COV object, and must not be freed.
+ Call this function only after all data have been accumulated.
+*/
+const gsl_matrix *
+covariance_calculate_unnormalized (struct covariance *cov)
+{
+ if ( cov->state <= 0 )
+ return NULL;
+
+ switch (cov->passes)
+ {
+ case 1:
+ return covariance_calculate_single_pass_unnormalized (cov);
+ break;
+ case 2:
+ return covariance_calculate_double_pass_unnormalized (cov);
+ break;
+ default:
+ NOT_REACHED ();
+ }
+}
+
+/* Function to access the categoricals used by COV
+ The return value is owned by the COV
+*/
+const struct categoricals *
+covariance_get_categoricals (const struct covariance *cov)
+{
+ return cov->categoricals;
+}
/* Destroy the COV object */
covariance_destroy (struct covariance *cov)
{
size_t i;
- free (cov->vars);
+
categoricals_destroy (cov->categoricals);
for (i = 0; i < n_MOMENTS; ++i)
projects / pspp / blobdiff