#include <config.h>
+#include <libpspp/assertion.h>
#include "covariance.h"
#include <gl/xalloc.h>
#include "moments.h"
struct covariance
{
- /* The variables for which the covariance matrix is to be calculated */
+ /* The variables for which the covariance matrix is to be calculated. */
size_t n_vars;
const struct variable **vars;
-
+
+ /* Categorical variables. */
+ size_t n_catvars;
+ const struct variable **catvars;
+
+ /* Array containing number of categories per categorical variable. */
+ size_t *n_categories;
+
+ /* Dimension of the covariance matrix. */
+ size_t dim;
+
/* The weight variable (or NULL if none) */
const struct variable *wv;
Only the top triangle is included, and no diagonals */
double *cm;
int n_cm;
+
+ /* 1 for single pass algorithm;
+ 2 for double pass algorithm
+ */
+ short passes;
+
+ /*
+ 0 : No pass has been made
+ 1 : First pass has been started
+ 2 : Second pass has been
+
+ IE: How many passes have been (partially) made. */
+ short state;
+
+ /* Flags indicating that the first case has been seen */
+ bool pass_one_first_case_seen;
+ bool pass_two_first_case_seen;
};
-/* Create a covariance struct */
+/* Create a covariance struct.
+ */
struct covariance *
covariance_create (size_t n_vars, const struct variable **vars,
- const struct variable *weight, enum mv_class exclude)
+ const struct variable *weight, enum mv_class exclude,
+ short passes)
{
size_t i;
struct covariance *cov = xmalloc (sizeof *cov);
+ assert (passes == 1 || passes == 2);
+ cov->passes = passes;
+ cov->state = 0;
+ cov->pass_one_first_case_seen = cov->pass_two_first_case_seen = false;
+
cov->vars = xmalloc (sizeof *cov->vars * n_vars);
cov->wv = weight;
cov->n_vars = n_vars;
+ cov->dim = n_vars;
for (i = 0; i < n_vars; ++i)
cov->vars[i] = vars[i];
return cov;
}
+/*
+ Create a covariance struct for a two-pass algorithm. If categorical
+ variables are involed, the dimension cannot be know until after the
+ first data pass, so the actual covariances will not be allocated
+ until then.
+ */
+struct covariance *
+covariance_2pass_create (size_t n_vars, const struct variable **vars,
+ size_t n_catvars, const struct variable **catvars,
+ const struct variable *weight, enum mv_class exclude)
+{
+ size_t i;
+ struct covariance *cov = xmalloc (sizeof *cov);
+ cov->vars = xmalloc (sizeof *cov->vars * n_vars);
+ cov->catvars = xnmalloc (n_catvars, sizeof (*cov->catvars));
+ cov->n_categories = xnmalloc (n_catvars, sizeof (cov->n_categories));
+
+ cov->wv = weight;
+ cov->n_vars = n_vars;
+ cov->n_catvars = n_catvars;
+
+ for (i = 0; i < n_vars; ++i)
+ cov->vars[i] = vars[i];
+
+ for (i = 0; i < n_catvars; i++)
+ {
+ cov->catvars[i] = catvars[i];
+ cov->n_categories[i] = 0;
+ }
+
+ cov->moments = xmalloc (sizeof *cov->moments * n_MOMENTS);
+
+ cov->exclude = exclude;
+
+ return cov;
+}
+
/* Return an integer, which can be used to index
into COV->cm, to obtain the I, J th element
of the covariance matrix. If COV->cm does not
return i - 1 + as;
}
+static void
+dump_matrix (const gsl_matrix *m)
+{
+ size_t i, j;
+
+ for (i = 0 ; i < m->size1; ++i)
+ {
+ for (j = 0 ; j < m->size2; ++j)
+ printf ("%02f ", gsl_matrix_get (m, i, j));
+ printf ("\n");
+ }
+}
/* Call this function for every case in the data set */
void
+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;
+
+ assert (cov->passes == 2);
+ if (!cov->pass_one_first_case_seen)
+ {
+ assert (cov->state == 0);
+ cov->state = 1;
+ }
+
+ for (i = 0 ; i < cov->n_vars; ++i)
+ {
+ const union value *val1 = case_data (c, cov->vars[i]);
+
+ if ( var_is_value_missing (cov->vars[i], val1, cov->exclude))
+ continue;
+
+ for (j = 0 ; j < cov->n_vars; ++j)
+ {
+ double pwr = 1.0;
+ const union value *val2 = case_data (c, cov->vars[j]);
+
+ if ( var_is_value_missing (cov->vars[j], val2, cov->exclude))
+ continue;
+
+ for (m = 0 ; m <= MOMENT_MEAN; ++m)
+ {
+ double *x = gsl_matrix_ptr (cov->moments[m], i, j);
+
+ *x += pwr * weight;
+ pwr *= val1->f;
+ }
+ }
+ }
+
+ cov->pass_one_first_case_seen = true;
+}
+
+
+/* Call this function for every case in the data set */
+void
+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;
+
+ assert (cov->passes == 2);
+ assert (cov->state >= 1);
+
+ if (! cov->pass_two_first_case_seen)
+ {
+ assert (cov->state == 1);
+ cov->state = 2;
+
+ /* Divide the means by the number of samples */
+ for (i = 0; i < cov->n_vars; ++i)
+ {
+ for (j = 0; j < cov->n_vars; ++j)
+ {
+ double *x = gsl_matrix_ptr (cov->moments[MOMENT_MEAN], i, j);
+ *x /= gsl_matrix_get (cov->moments[MOMENT_NONE], i, j);
+ }
+ }
+ }
+
+ for (i = 0 ; i < cov->n_vars; ++i)
+ {
+ const union value *val1 = case_data (c, cov->vars[i]);
+
+ if ( var_is_value_missing (cov->vars[i], val1, cov->exclude))
+ continue;
+
+ for (j = 0 ; j < cov->n_vars; ++j)
+ {
+ int idx;
+ double ss ;
+ const union value *val2 = case_data (c, cov->vars[j]);
+
+ const double s = pow2 (val1->f - gsl_matrix_get (cov->moments[MOMENT_MEAN], i, j)) * weight;
+
+ if ( var_is_value_missing (cov->vars[j], val2, cov->exclude))
+ continue;
+
+ {
+ double *x = gsl_matrix_ptr (cov->moments[MOMENT_VARIANCE], i, j);
+ *x += s;
+ }
+
+ ss =
+ (val1->f - gsl_matrix_get (cov->moments[MOMENT_MEAN], i, j))
+ *
+ (val2->f - gsl_matrix_get (cov->moments[MOMENT_MEAN], i, j))
+ * weight
+ ;
+
+ idx = cm_idx (cov, i, j);
+ if (idx >= 0)
+ {
+ cov->cm [idx] += ss;
+ }
+
+ }
+ }
+
+ cov->pass_two_first_case_seen = true;
+}
+
+
+/* Call this function for every case in the data set.
+ After all cases have been passed, call covariance_calculate
+ */
+void
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;
+ assert (cov->passes == 1);
+
+ if ( !cov->pass_one_first_case_seen)
+ {
+ assert ( cov->state == 0);
+ cov->state = 1;
+ }
+
for (i = 0 ; i < cov->n_vars; ++i)
{
const union value *val1 = case_data (c, cov->vars[i]);
}
}
}
+
+ cov->pass_one_first_case_seen = true;
}
}
+static const gsl_matrix *
+covariance_calculate_double_pass (struct covariance *cov)
+{
+ size_t i, j;
+ for (i = 0 ; i < cov->n_vars; ++i)
+ {
+ for (j = 0 ; j < cov->n_vars; ++j)
+ {
+ int idx;
+ double *x = gsl_matrix_ptr (cov->moments[MOMENT_VARIANCE], i, j);
+ *x /= gsl_matrix_get (cov->moments[MOMENT_NONE], i, j);
-/*
- 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 (struct covariance *cov)
+ idx = cm_idx (cov, i, j);
+ if ( idx >= 0)
+ {
+ x = &cov->cm [idx];
+ *x /= gsl_matrix_get (cov->moments[MOMENT_NONE], i, j);
+ }
+ }
+ }
+
+ return cm_to_gsl (cov);
+}
+
+static const gsl_matrix *
+covariance_calculate_single_pass (struct covariance *cov)
{
size_t i, j;
size_t m;
}
+
+/*
+ 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 (struct covariance *cov)
+{
+ assert ( cov->state > 0 );
+
+ switch (cov->passes)
+ {
+ case 1:
+ return covariance_calculate_single_pass (cov);
+ break;
+ case 2:
+ return covariance_calculate_double_pass (cov);
+ break;
+ default:
+ NOT_REACHED ();
+ }
+}
+
+
+
+
/* Destroy the COV object */
void
covariance_destroy (struct covariance *cov)
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