/* PSPP - a program for statistical analysis.
- Copyright (C) 2009 Free Software Foundation, Inc.
+ Copyright (C) 2009, 2010, 2011 Free Software Foundation, Inc.
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
#include <config.h>
-#include <libpspp/assertion.h>
-#include "covariance.h"
-#include <gl/xalloc.h>
-#include "moments.h"
+#include "math/covariance.h"
+
#include <gsl/gsl_matrix.h>
-#include <data/case.h>
-#include <data/variable.h>
-#include <libpspp/misc.h>
-#include "categoricals.h"
+
+#include "data/case.h"
+#include "data/variable.h"
+#include "libpspp/assertion.h"
+#include "libpspp/misc.h"
+#include "math/categoricals.h"
+#include "math/interaction.h"
+#include "math/moments.h"
+
+#include "gl/xalloc.h"
#define n_MOMENTS (MOMENT_VARIANCE + 1)
cov->n_cm = (n_vars * (n_vars - 1) ) / 2;
- if (cov->n_cm > 0)
- cov->cm = xcalloc (sizeof *cov->cm, cov->n_cm);
+
+ cov->cm = xcalloc (cov->n_cm, sizeof *cov->cm);
cov->categoricals = NULL;
return cov;
{
const struct variable *var = i < cov->n_vars ?
cov->vars[i] :
- categoricals_get_variable_by_subscript (cov->categoricals, i - cov->n_vars);
+ categoricals_get_interaction_by_subscript (cov->categoricals, i - cov->n_vars)->vars[0];
const union value *val = case_data (c, var);
return val->f;
}
- return categoricals_get_binary_by_subscript (cov->categoricals, i - cov->n_vars, c);
+ return categoricals_get_code_for_case (cov->categoricals, i - cov->n_vars, c);
}
#if 0
assert (cov->state == 1);
cov->state = 2;
+ if (cov->categoricals)
+ categoricals_done (cov->categoricals);
+
cov->dim = cov->n_vars;
if (cov->categoricals)
- cov->dim += categoricals_total (cov->categoricals)
- - categoricals_get_n_variables (cov->categoricals);
+ cov->dim += categoricals_df_total (cov->categoricals);
cov->n_cm = (cov->dim * (cov->dim - 1) ) / 2;
- cov->cm = xcalloc (sizeof *cov->cm, cov->n_cm);
+ cov->cm = xcalloc (cov->n_cm, sizeof *cov->cm);
/* Grow the moment matrices so that they're large enough to accommodate the
categorical elements */
cov->moments[i] = resize_matrix (cov->moments[i], cov->dim);
}
- if (cov->categoricals)
- categoricals_done (cov->categoricals);
-
/* Populate the moments matrices with the categorical value elements */
for (i = cov->n_vars; i < cov->dim; ++i)
{
}
-static const gsl_matrix *
+static gsl_matrix *
covariance_calculate_double_pass (struct covariance *cov)
{
size_t i, j;
return cm_to_gsl (cov);
}
-static const gsl_matrix *
+static gsl_matrix *
covariance_calculate_single_pass (struct covariance *cov)
{
size_t 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 *
+/* Return a pointer to gsl_matrix containing the pairwise covariances. The
+ caller owns the returned matrix and must free it when it is no longer
+ needed.
+
+ Call this function only after all data have been accumulated. */
+gsl_matrix *
covariance_calculate (struct covariance *cov)
{
if ( cov->state <= 0 )
/*
Covariance computed without dividing by the sample size.
*/
-static const gsl_matrix *
+static 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 *
+static gsl_matrix *
covariance_calculate_single_pass_unnormalized (struct covariance *cov)
{
size_t 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 *
+/* Return a pointer to gsl_matrix containing the pairwise covariances. The
+ caller owns the returned matrix and must free it when it is no longer
+ needed.
+
+ Call this function only after all data have been accumulated. */
+gsl_matrix *
covariance_calculate_unnormalized (struct covariance *cov)
{
if ( cov->state <= 0 )
free (cov->cm);
free (cov);
}
+
+size_t
+covariance_dim (const struct covariance * cov)
+{
+ return (cov->dim);
+}
+
+\f
+
+/*
+ Routines to assist debugging.
+ The following are not thoroughly tested and in certain respects
+ unreliable. They should only be
+ used for aids to development. Not as user accessible code.
+*/
+
+#include "libpspp/str.h"
+#include "output/tab.h"
+#include "data/format.h"
+
+
+/* Create a table which can be populated with the encodings for
+ the covariance matrix COV */
+struct tab_table *
+covariance_dump_enc_header (const struct covariance *cov, int length)
+{
+ struct tab_table *t = tab_create (cov->dim, length);
+ int n;
+ int i;
+
+ tab_title (t, "Covariance Encoding");
+
+ tab_box (t,
+ TAL_2, TAL_2, 0, 0,
+ 0, 0, tab_nc (t) - 1, tab_nr (t) - 1);
+
+ tab_hline (t, TAL_2, 0, tab_nc (t) - 1, 1);
+
+
+ for (i = 0 ; i < cov->n_vars; ++i)
+ {
+ tab_text (t, i, 0, TAT_TITLE, var_get_name (cov->vars[i]));
+ tab_vline (t, TAL_1, i + 1, 0, tab_nr (t) - 1);
+ }
+
+ n = 0;
+ while (i < cov->dim)
+ {
+ struct string str;
+ int idx = i - cov->n_vars;
+ const struct interaction *iact =
+ categoricals_get_interaction_by_subscript (cov->categoricals, idx);
+ int df;
+
+ ds_init_empty (&str);
+ interaction_to_string (iact, &str);
+
+ df = categoricals_df (cov->categoricals, n);
+
+ tab_joint_text (t,
+ i, 0,
+ i + df - 1, 0,
+ TAT_TITLE, ds_cstr (&str));
+
+ if (i + df < tab_nr (t) - 1)
+ tab_vline (t, TAL_1, i + df, 0, tab_nr (t) - 1);
+
+ i += df;
+ n++;
+ ds_destroy (&str);
+ }
+
+ return t;
+}
+
+
+/*
+ Append table T, which should have been returned by covariance_dump_enc_header
+ with an entry corresponding to case C for the covariance matrix COV
+ */
+void
+covariance_dump_enc (const struct covariance *cov, const struct ccase *c,
+ struct tab_table *t)
+{
+ static int row = 0;
+ int i;
+ ++row;
+ for (i = 0 ; i < cov->dim; ++i)
+ {
+ double v = get_val (cov, i, c);
+ tab_double (t, i, row, 0, v, i < cov->n_vars ? NULL : &F_8_0);
+ }
+}