-/* PSPP - computes sample statistics.
+/* PSPP - a program for statistical analysis.
Copyright (C) 2006 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 2 of the
- License, or (at your option) any later version.
+ 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.
+ 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, write to the Free Software
- Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
- 02110-1301, USA. */
+ along with this program. If not, see <http://www.gnu.org/licenses/>. */
#include <config.h>
#include <libpspp/compiler.h>
#include <libpspp/alloc.h>
#include <data/case.h>
-#include <data/casefile.h>
+#include <data/casereader.h>
#include <data/dictionary.h>
#include <data/procedure.h>
#include <data/variable.h>
#include <data/value.h>
#include <data/value-labels.h>
-#include <data/casefilter.h>
#include <libpspp/message.h>
#include <libpspp/assertion.h>
static double
calculate_binomial_internal (double n1, double n2, double p)
{
- /* SPSS Statistical Algorithms has completely different and WRONG
+ /* SPSS Statistical Algorithms has completely different and WRONG
advice here. */
double sig1tailed = gslextras_cdf_binomial_P (n1, n1 + n2, p);
return sig1tailed ;
}
-static void
+static bool
do_binomial (const struct dictionary *dict,
- const struct casefile *cf,
+ struct casereader *input,
const struct binomial_test *bst,
- struct freq *cat1,
- struct freq *cat2,
- const struct casefilter *filter
+ struct freq_mutable *cat1,
+ struct freq_mutable *cat2,
+ enum mv_class exclude
)
{
bool warn = true;
const struct one_sample_test *ost = (const struct one_sample_test *) bst;
struct ccase c;
- struct casereader *r = casefile_get_reader (cf, NULL);
- while (casereader_read(r, &c))
+ while (casereader_read(input, &c))
{
int v;
- double w =
- dict_get_case_weight (dict, &c, &warn);
+ double w = dict_get_case_weight (dict, &c, &warn);
for (v = 0 ; v < ost->n_vars ; ++v )
{
const struct variable *var = ost->vars[v];
const union value *value = case_data (&c, var);
+ int width = var_get_width (var);
- if ( casefilter_variable_missing (filter, &c, var))
+ if (var_is_value_missing (var, value, exclude))
break;
if ( NULL == cat1[v].value )
{
- cat1[v].value = value_dup (value, var_get_width (var));
+ cat1[v].value = value_dup (value, width);
cat1[v].count = w;
}
- else if ( 0 == compare_values (cat1[v].value, value,
- var_get_width (var)))
+ else if ( 0 == compare_values (cat1[v].value, value, width))
cat1[v].count += w;
else if ( NULL == cat2[v].value )
{
- cat2[v].value = value_dup (value, var_get_width (var));
+ cat2[v].value = value_dup (value, width);
cat2[v].count = w;
}
- else if ( 0 == compare_values (cat2[v].value, value,
- var_get_width (var)))
+ else if ( 0 == compare_values (cat2[v].value, value, width))
cat2[v].count += w;
else if ( bst->category1 == SYSMIS)
msg (ME, _("Variable %s is not dichotomous"), var_get_name (var));
case_destroy (&c);
}
- casereader_destroy (r);
+ return casereader_destroy (input);
}
void
binomial_execute (const struct dataset *ds,
- const struct casefile *cf,
- struct casefilter *filter,
+ struct casereader *input,
+ enum mv_class exclude,
const struct npar_test *test)
{
int v;
const struct binomial_test *bst = (const struct binomial_test *) test;
const struct one_sample_test *ost = (const struct one_sample_test*) test;
- struct freq *cat1 = xzalloc (sizeof (*cat1) * ost->n_vars);
- struct freq *cat2 = xzalloc (sizeof (*cat1) * ost->n_vars);
- struct tab_table *table ;
+ struct freq_mutable *cat1 = xzalloc (sizeof (*cat1) * ost->n_vars);
+ struct freq_mutable *cat2 = xzalloc (sizeof (*cat1) * ost->n_vars);
assert ((bst->category1 == SYSMIS) == (bst->category2 == SYSMIS) );
cat2->value = value_dup (&v, 0);
}
- do_binomial (dataset_dict(ds), cf, bst, cat1, cat2, filter);
-
- table = tab_create (7, ost->n_vars * 3 + 1, 0);
-
- tab_dim (table, tab_natural_dimensions);
-
- tab_title (table, _("Binomial Test"));
-
- tab_headers (table, 2, 0, 1, 0);
-
- tab_box (table, TAL_1, TAL_1, -1, TAL_1,
- 0, 0, table->nc - 1, tab_nr(table) - 1 );
-
- for (v = 0 ; v < ost->n_vars; ++v)
+ if (do_binomial (dataset_dict(ds), input, bst, cat1, cat2, exclude))
{
- double n_total, sig;
- const struct variable *var = ost->vars[v];
- tab_hline (table, TAL_1, 0, tab_nc (table) -1, 1 + v * 3);
-
- /* Titles */
- tab_text (table, 0, 1 + v * 3, TAB_LEFT,
- var_to_string (var));
-
- tab_text (table, 1, 1 + v * 3, TAB_LEFT,
- _("Group1"));
+ struct tab_table *table = tab_create (7, ost->n_vars * 3 + 1, 0);
- tab_text (table, 1, 2 + v * 3, TAB_LEFT,
- _("Group2"));
+ tab_dim (table, tab_natural_dimensions);
- tab_text (table, 1, 3 + v * 3, TAB_LEFT,
- _("Total"));
+ tab_title (table, _("Binomial Test"));
- /* Test Prop */
- tab_float (table, 5, 1 + v * 3, TAB_NONE, bst->p, 8, 3);
+ tab_headers (table, 2, 0, 1, 0);
- /* Category labels */
- tab_text (table, 2, 1 + v * 3, TAB_NONE,
- var_get_value_name (var, cat1[v].value));
+ tab_box (table, TAL_1, TAL_1, -1, TAL_1,
+ 0, 0, table->nc - 1, tab_nr(table) - 1 );
- tab_text (table, 2, 2 + v * 3, TAB_NONE,
- var_get_value_name (var, cat2[v].value));
+ for (v = 0 ; v < ost->n_vars; ++v)
+ {
+ double n_total, sig;
+ const struct variable *var = ost->vars[v];
+ tab_hline (table, TAL_1, 0, tab_nc (table) -1, 1 + v * 3);
- /* Observed N */
- tab_float (table, 3, 1 + v * 3, TAB_NONE,
- cat1[v].count, 8, 0);
+ /* Titles */
+ tab_text (table, 0, 1 + v * 3, TAB_LEFT, var_to_string (var));
+ tab_text (table, 1, 1 + v * 3, TAB_LEFT, _("Group1"));
+ tab_text (table, 1, 2 + v * 3, TAB_LEFT, _("Group2"));
+ tab_text (table, 1, 3 + v * 3, TAB_LEFT, _("Total"));
- tab_float (table, 3, 2 + v * 3, TAB_NONE,
- cat2[v].count, 8, 0);
+ /* Test Prop */
+ tab_float (table, 5, 1 + v * 3, TAB_NONE, bst->p, 8, 3);
- n_total = cat1[v].count + cat2[v].count;
+ /* Category labels */
+ tab_text (table, 2, 1 + v * 3, TAB_NONE,
+ var_get_value_name (var, cat1[v].value));
+ tab_text (table, 2, 2 + v * 3, TAB_NONE,
+ var_get_value_name (var, cat2[v].value));
+ /* Observed N */
+ tab_float (table, 3, 1 + v * 3, TAB_NONE, cat1[v].count, 8, 0);
+ tab_float (table, 3, 2 + v * 3, TAB_NONE, cat2[v].count, 8, 0);
- tab_float (table, 3, 3 + v * 3, TAB_NONE,
- n_total, 8, 0);
+ n_total = cat1[v].count + cat2[v].count;
+ tab_float (table, 3, 3 + v * 3, TAB_NONE, n_total, 8, 0);
- /* Observed Proportions */
+ /* Observed Proportions */
+ tab_float (table, 4, 1 + v * 3, TAB_NONE,
+ cat1[v].count / n_total, 8, 3);
+ tab_float (table, 4, 2 + v * 3, TAB_NONE,
+ cat2[v].count / n_total, 8, 3);
+ tab_float (table, 4, 3 + v * 3, TAB_NONE,
+ (cat1[v].count + cat2[v].count) / n_total, 8, 2);
- tab_float (table, 4, 1 + v * 3, TAB_NONE,
- cat1[v].count / n_total, 8, 3);
+ /* Significance */
+ sig = calculate_binomial (cat1[v].count, cat2[v].count, bst->p);
+ tab_float (table, 6, 1 + v * 3, TAB_NONE, sig, 8, 3);
+ }
- tab_float (table, 4, 2 + v * 3, TAB_NONE,
- cat2[v].count / n_total, 8, 3);
+ tab_text (table, 2, 0, TAB_CENTER, _("Category"));
+ tab_text (table, 3, 0, TAB_CENTER, _("N"));
+ tab_text (table, 4, 0, TAB_CENTER, _("Observed Prop."));
+ tab_text (table, 5, 0, TAB_CENTER, _("Test Prop."));
- tab_float (table, 4, 3 + v * 3, TAB_NONE,
- (cat1[v].count + cat2[v].count) / n_total, 8, 2);
+ tab_text (table, 6, 0, TAB_CENTER | TAT_PRINTF,
+ _("Exact Sig. (%d-tailed)"),
+ bst->p == 0.5 ? 2: 1);
-
- /* Significance */
- sig = calculate_binomial (cat1[v].count, cat2[v].count,
- bst->p);
-
- tab_float (table, 6, 1 + v * 3, TAB_NONE,
- sig, 8, 3);
+ tab_vline (table, TAL_2, 2, 0, tab_nr (table) -1);
+ tab_submit (table);
}
- tab_text (table, 2, 0, TAB_CENTER, _("Category"));
- tab_text (table, 3, 0, TAB_CENTER, _("N"));
- tab_text (table, 4, 0, TAB_CENTER, _("Observed Prop."));
- tab_text (table, 5, 0, TAB_CENTER, _("Test Prop."));
-
- tab_text (table, 6, 0, TAB_CENTER | TAT_PRINTF,
- _("Exact Sig. (%d-tailed)"),
- bst->p == 0.5 ? 2: 1);
-
- tab_vline (table, TAL_2, 2, 0, tab_nr (table) -1);
-
+ for (v = 0; v < ost->n_vars; v++)
+ {
+ free (cat1[v].value);
+ free (cat2[v].value);
+ }
free (cat1);
free (cat2);
-
- tab_submit (table);
-
}