X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Fdata%2Fcategory.c;fp=src%2Fdata%2Fcategory.c;h=0000000000000000000000000000000000000000;hb=f550aee00a62fe1d8baf62d83cd7efef6cc2ee92;hp=968dd4c52da8369e629fb2797faa056db4b67227;hpb=18ef561271ad1b619f62d994e3dc2286958532f1;p=pspp-builds.git
diff --git a/src/data/category.c b/src/data/category.c
deleted file mode 100644
index 968dd4c5..00000000
--- a/src/data/category.c
+++ /dev/null
@@ -1,199 +0,0 @@
-/* PSPP - a program for statistical analysis.
- Copyright (C) 2005, 2009 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 . */
-
-/*
- Functions and data structures to store values of a categorical
- variable, and to recode those values into binary vectors.
-
- For some statistical models, it is necessary to change each value
- of a categorical variable to a vector with binary entries. These
- vectors are then stored as sub-rows within a matrix during
- model-fitting. For example, we need functions and data strucutres to map a
- value, say 'a', of a variable named 'cat_var', to a vector, say (0
- 1 0 0 0), and vice versa. We also need to be able to map the
- vector back to the value 'a', and if the vector is a sub-row of a
- matrix, we need to know which sub-row corresponds to the variable
- 'cat_var'.
-*/
-#include
-
-#include
-#include
-#include
-#include
-#include
-#include
-#include
-#include
-
-#define CAT_VALUE_NOT_FOUND -1
-
-#define N_INITIAL_CATEGORIES 1
-
-/*
- This structure contains the observed values of a
- categorical variable.
- */
-struct cat_vals
-{
- union value *vals;
- size_t n_categories;
- size_t n_allocated_categories; /* This is used only during
- initialization to keep
- track of the number of
- values stored.
- */
- size_t *value_counts; /* Element i stores the number of cases for which
- the categorical variable has that corresponding
- value. This is necessary for computing covariance
- matrices.
- */
-};
-
-void
-cat_stored_values_create (const struct variable *v)
-{
- if (!var_has_obs_vals (v))
- {
- struct cat_vals *obs_vals = xmalloc (sizeof *obs_vals);
-
- obs_vals->n_categories = 0;
- obs_vals->n_allocated_categories = N_INITIAL_CATEGORIES;
- obs_vals->vals = xnmalloc (N_INITIAL_CATEGORIES, sizeof *obs_vals->vals);
- obs_vals->value_counts = xnmalloc (N_INITIAL_CATEGORIES, sizeof *obs_vals->value_counts);
- var_set_obs_vals (v, obs_vals);
- }
-}
-
-void
-cat_stored_values_destroy (struct cat_vals *obs_vals)
-{
- if (obs_vals != NULL)
- {
- if (obs_vals->n_allocated_categories > 0)
- {
- free (obs_vals->vals);
- free (obs_vals->value_counts);
- }
- free (obs_vals);
- }
-}
-
-/*
- Which subscript corresponds to val?
- */
-size_t
-cat_value_find (const struct variable *v, const union value *val)
-{
- struct cat_vals *obs_vals = var_get_obs_vals (v);
- size_t i;
- const union value *candidate;
-
- for (i = 0; i < obs_vals->n_categories; i++)
- {
- candidate = obs_vals->vals + i;
- assert (candidate != NULL);
- if (value_equal (candidate, val, var_get_width (v)))
- {
- return i;
- }
- }
- return CAT_VALUE_NOT_FOUND;
-}
-
-/*
- Add the new value unless it is already present. Increment the count.
- */
-void
-cat_value_update (const struct variable *v, const union value *val)
-{
- if (var_is_alpha (v))
- {
- size_t i;
- struct cat_vals *cv = var_get_obs_vals (v);
- i = cat_value_find (v, val);
- if (i == CAT_VALUE_NOT_FOUND)
- {
- if (cv->n_categories >= cv->n_allocated_categories)
- {
- cv->n_allocated_categories *= 2;
- cv->vals = xnrealloc (cv->vals,
- cv->n_allocated_categories,
- sizeof *cv->vals);
- cv->value_counts = xnrealloc (cv->value_counts, cv->n_allocated_categories,
- sizeof *cv->value_counts);
- }
- cv->vals[cv->n_categories] = *val;
- cv->value_counts[cv->n_categories] = 1;
- cv->n_categories++;
- }
- else
- {
- cv->value_counts[i]++;
- }
- }
-}
-/*
- Return the count for the sth category.
- */
-size_t
-cat_get_category_count (const size_t s, const struct variable *v)
-{
- struct cat_vals *tmp;
- size_t n_categories;
-
- tmp = var_get_obs_vals (v);
- n_categories = cat_get_n_categories (v);
- if (s < n_categories)
- {
- return tmp->value_counts[s];
- }
- return CAT_VALUE_NOT_FOUND;
-}
-
-const union value *
-cat_subscript_to_value (const size_t s, const struct variable *v)
-{
- struct cat_vals *obs_vals = var_get_obs_vals (v);
- return s < obs_vals->n_categories ? obs_vals->vals + s : NULL;
-}
-
-/*
- Return the number of categories of a categorical variable.
- */
-size_t
-cat_get_n_categories (const struct variable *v)
-{
- return var_get_obs_vals (v)->n_categories;
-}
-
-/*
- If VAR is categorical with d categories, its first category should
- correspond to the origin in d-dimensional Euclidean space.
- */
-bool
-cat_is_origin (const struct variable *var, const union value *val)
-{
- if (var_is_numeric (var))
- {
- return false;
- }
- if (cat_value_find (var, val) == 0)
- {
- return true;
- }
- return false;
-}