Merge commit 'origin/covariance'

[pspp-builds.git] / src / math / covariance-matrix.c

diff --git a/src/math/covariance-matrix.c b/src/math/covariance-matrix.c
deleted file mode 100644 (file)
index 69aaf53..0000000
--- a/src/math/covariance-matrix.c
+++ /dev/null
@@ -1,151 +0,0 @@
-/* PSPP - a program for statistical analysis.
-   Copyright (C) 2008 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
-   the Free Software Foundation, either version 3 of the License, or
-   (at your option) any later version.
-
-   This program is distributed in the hope that it will be useful,
-   but WITHOUT ANY WARRANTY; without even the implied warranty of
-   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-   GNU General Public License for more details.
-
-   You should have received a copy of the GNU General Public License
-   along with this program.  If not, see <http://www.gnu.org/licenses/>. */
-
-/*
-  Create and update the values in the covariance matrix.
-*/
-#include <assert.h>
-#include <config.h>
-#include <data/variable.h>
-#include <data/value.h>
-#include "covariance-matrix.h"
-#include "moments.h"
-
-/*
-  The covariances are stored in a DESIGN_MATRIX structure.
- */
-struct design_matrix *
-covariance_matrix_create (int n_variables, const struct variable *v_variables[])
-{
-  return design_matrix_create (n_variables, v_variables, (size_t) n_variables);
-}
-
-void covariance_matrix_destroy (struct design_matrix *x)
-{
-  design_matrix_destroy (x);
-}
-
-/*
-  Update the covariance matrix with the new entries, assuming that V1 
-  is categorical and V2 is numeric.
- */
-static void
-covariance_update_categorical_numeric (struct design_matrix *cov, double mean,
-                         double weight, double ssize, const struct variable *v1, 
-                         const struct variable *v2, const union value *val1, const union value *val2)
-{
-  double x;
-  size_t i;
-  size_t col;
-  size_t row;
-  
-  assert (var_is_alpha (v1));
-  assert (var_is_numeric (v2));
-
-  row = design_matrix_var_to_column (cov, v1);  
-  col = design_matrix_var_to_column (cov, v2);
-  for (i = 0; i < cat_get_n_categories (v1); i++)
-    {
-      row += i;
-      x = -1.0 * cat_get_n_categories (v1) / ssize;
-      if (i == cat_value_find (v1, val1))
-       {
-         x += 1.0;
-       }
-      assert (val2 != NULL);
-      gsl_matrix_set (cov->m, row, col, (val2->f - mean) * x * weight);
-    }
-}
-static void
-column_iterate (struct design_matrix *cov, const struct variable *v, double weight,
-               double ssize, double x, const union value *val1, size_t row)
-{
-  size_t col;
-  size_t i;
-  double y;
-  union value *tmp_val;
-
-  col = design_matrix_var_to_column (cov, v);  
-  for (i = 0; i < cat_get_n_categories (v) - 1; i++)
-    {
-      col += i;
-      y = -1.0 * cat_get_category_count (i, v) / ssize;
-      tmp_val = cat_subscript_to_value (i, v);
-      if (compare_values (tmp_val, val1, var_get_width (v)))
-       {
-         y += -1.0;
-       }
-      gsl_matrix_set (cov->m, row, col, x * y * weight);
-      gsl_matrix_set (cov->m, col, row, x * y * weight);
-    }
-}
-/*
-  Call this function in the second data pass. The central moments are
-  MEAN1 and MEAN2. Any categorical variables should already have their
-  values summarized in in its OBS_VALS element.
- */
-void covariance_pass_two (struct design_matrix *cov, double mean1, double mean2,
-                         double weight, double ssize, const struct variable *v1, 
-                         const struct variable *v2, const union value *val1, const union value *val2)
-{
-  size_t row;
-  size_t col;
-  size_t i;
-  double x;
-  union value *tmp_val;
-
-  if (var_is_alpha (v1))
-    {
-      if (var_is_numeric (v2))
-       {
-         covariance_update_categorical_numeric (cov, mean2, weight, ssize, v1, 
-                                                v2, val1, val2);
-       }
-      else
-       {
-         row = design_matrix_var_to_column (cov, v1);
-         for (i = 0; i < cat_get_n_categories (v1) - 1; i++)
-           {
-             row += i;
-             x = -1.0 * cat_get_category_count (i, v1) / ssize;
-             tmp_val = cat_subscript_to_value (i, v1);
-             if (compare_values (tmp_val, val1, var_get_width (v1)))
-               {
-                 x += 1.0;
-               }
-             column_iterate (cov, v1, weight, ssize, x, val1, row);
-             column_iterate (cov, v2, weight, ssize, x, val2, row);
-           }
-       }
-    }
-  else if (var_is_alpha (v2))
-    {
-      covariance_update_categorical_numeric (cov, mean1, weight, ssize, v2, 
-                                            v1, val2, val1);
-    }
-  else
-    {
-      /*
-       Both variables are numeric.
-      */
-      row = design_matrix_var_to_column (cov, v1);  
-      col = design_matrix_var_to_column (cov, v2);
-      x = (val1->f - mean1) * (val2->f - mean2) * weight;
-      gsl_matrix_set (cov->m, row, col, x);
-      gsl_matrix_set (cov->m, col, row, x);
-    }
-}
-