#include "libpspp/hmapx.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
{
const struct variable *var;
- /* The position for reporting purposes */
- int posn;
-
/* N, Mean, Variance */
struct moments *mom;
struct one_samp
{
- struct hmapx hmap;
+ struct per_var_stats *stats;
+ size_t n_stats;
double testval;
};
static void
one_sample_test (const struct tt *tt, const struct one_samp *os)
{
- struct hmapx_node *node;
- struct per_var_stats *per_var_stats;
-
- const int heading_rows = 3;
- const size_t rows = heading_rows + tt->n_vars;
- const size_t cols = 7;
- const struct fmt_spec *wfmt = tt->wv ? var_get_print_format (tt->wv) : & F_8_0;
-
- struct tab_table *t = tab_create (cols, rows);
- tab_set_format (t, RC_WEIGHT, wfmt);
-
- tab_headers (t, 0, 0, heading_rows, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_0, 0, 0, cols - 1, rows - 1);
- tab_hline (t, TAL_2, 0, cols - 1, 3);
-
- tab_title (t, _("One-Sample Test"));
- tab_hline (t, TAL_1, 1, cols - 1, 1);
- tab_vline (t, TAL_2, 1, 0, rows - 1);
-
- tab_joint_text_format (t, 1, 0, cols - 1, 0, TAB_CENTER,
- _("Test Value = %f"), os->testval);
-
- tab_box (t, -1, -1, -1, TAL_1, 1, 1, cols - 1, rows - 1);
-
- tab_joint_text_format (t, 5, 1, 6, 1, TAB_CENTER,
- _("%g%% Confidence Interval of the Difference"),
- tt->confidence * 100.0);
-
- tab_hline (t, TAL_1, 5, 6, 2);
- tab_text (t, 1, 2, TAB_CENTER | TAT_TITLE, _("t"));
- tab_text (t, 2, 2, TAB_CENTER | TAT_TITLE, _("df"));
- tab_text (t, 3, 2, TAB_CENTER | TAT_TITLE, _("Sig. (2-tailed)"));
- tab_text (t, 4, 2, TAB_CENTER | TAT_TITLE, _("Mean Difference"));
- tab_text (t, 5, 2, TAB_CENTER | TAT_TITLE, _("Lower"));
- tab_text (t, 6, 2, TAB_CENTER | TAT_TITLE, _("Upper"));
-
- HMAPX_FOR_EACH (per_var_stats, node, &os->hmap)
+ struct pivot_table *table = pivot_table_create (N_("One-Sample Test"));
+ pivot_table_set_weight_var (table, tt->wv);
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"));
+ struct pivot_category *group = pivot_category_create_group__ (
+ statistics->root, pivot_value_new_user_text_nocopy (
+ xasprintf (_("Test Value = %.*g"), DBL_DIG + 1, os->testval)));
+ pivot_category_create_leaves (
+ group,
+ N_("t"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_COUNT,
+ N_("Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Mean Difference"), PIVOT_RC_OTHER);
+ struct pivot_category *subgroup = pivot_category_create_group__ (
+ group, pivot_value_new_user_text_nocopy (
+ xasprintf (_("%g%% Confidence Interval of the Difference"),
+ tt->confidence * 100.0)));
+ pivot_category_create_leaves (subgroup,
+ N_("Lower"), PIVOT_RC_OTHER,
+ N_("Upper"), PIVOT_RC_OTHER);
+
+ struct pivot_dimension *dep_vars = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
+
+ for (size_t i = 0; i < os->n_stats; i++)
{
+ const struct per_var_stats *per_var_stats = &os->stats[i];
const struct moments *m = per_var_stats->mom;
- double cc, mean, sigma;
- double tval, df;
- double p, q;
- double mean_diff;
- double se_mean ;
- const int v = per_var_stats->posn;
-
- moments_calculate (m, &cc, &mean, &sigma, NULL, NULL);
-
- tval = (mean - os->testval) * sqrt (cc / sigma);
-
- mean_diff = per_var_stats->sum_diff / cc;
- se_mean = sqrt (sigma / cc);
- df = cc - 1.0;
- p = gsl_cdf_tdist_P (tval, df);
- q = gsl_cdf_tdist_Q (tval, df);
-
- tab_text (t, 0, v + heading_rows, TAB_LEFT, var_to_string (per_var_stats->var));
- tab_double (t, 1, v + heading_rows, TAB_RIGHT, tval, NULL, RC_OTHER);
- tab_double (t, 2, v + heading_rows, TAB_RIGHT, df, NULL, RC_WEIGHT);
- /* Multiply by 2 to get 2-tailed significance, makeing sure we've got
- the correct tail*/
- tab_double (t, 3, v + heading_rows, TAB_RIGHT, 2.0 * (tval > 0 ? q : p), NULL, RC_PVALUE);
+ int dep_var_idx = pivot_category_create_leaf (
+ dep_vars->root, pivot_value_new_variable (per_var_stats->var));
- tab_double (t, 4, v + heading_rows, TAB_RIGHT, mean_diff, NULL, RC_OTHER);
-
- tval = gsl_cdf_tdist_Qinv ( (1.0 - tt->confidence) / 2.0, df);
-
- tab_double (t, 5, v + heading_rows, TAB_RIGHT, mean_diff - tval * se_mean, NULL, RC_OTHER);
- tab_double (t, 6, v + heading_rows, TAB_RIGHT, mean_diff + tval * se_mean, NULL, RC_OTHER);
+ double cc, mean, sigma;
+ moments_calculate (m, &cc, &mean, &sigma, NULL, NULL);
+ double tval = (mean - os->testval) * sqrt (cc / sigma);
+ double mean_diff = per_var_stats->sum_diff / cc;
+ double se_mean = sqrt (sigma / cc);
+ double df = cc - 1.0;
+ double p = gsl_cdf_tdist_P (tval, df);
+ double q = gsl_cdf_tdist_Q (tval, df);
+ double sig = 2.0 * (tval > 0 ? q : p);
+ double tval_qinv = gsl_cdf_tdist_Qinv ((1.0 - tt->confidence) / 2.0, df);
+ double lower = mean_diff - tval_qinv * se_mean;
+ double upper = mean_diff + tval_qinv * se_mean;
+
+ double entries[] = { tval, df, sig, mean_diff, lower, upper };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, dep_var_idx,
+ pivot_value_new_number (entries[j]));
}
- tab_submit (t);
+ pivot_table_submit (table);
}
static void
one_sample_summary (const struct tt *tt, const struct one_samp *os)
{
- struct hmapx_node *node;
- struct per_var_stats *per_var_stats;
-
- const int cols = 5;
- const int heading_rows = 1;
- const int rows = tt->n_vars + heading_rows;
- struct tab_table *t = tab_create (cols, rows);
- const struct fmt_spec *wfmt = tt->wv ? var_get_print_format (tt->wv) : & F_8_0;
- tab_set_format (t, RC_WEIGHT, wfmt);
- tab_headers (t, 0, 0, heading_rows, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_1, 0, 0, cols - 1, rows - 1);
- tab_hline (t, TAL_2, 0, cols - 1, 1);
-
- tab_title (t, _("One-Sample Statistics"));
- tab_vline (t, TAL_2, 1, 0, rows - 1);
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("N"));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Mean"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("S.E. Mean"));
-
- HMAPX_FOR_EACH (per_var_stats, node, &os->hmap)
+ struct pivot_table *table = pivot_table_create (N_("One-Sample Statistics"));
+ pivot_table_set_weight_var (table, tt->wv);
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Mean"), PIVOT_RC_OTHER,
+ N_("Std. Deviation"), PIVOT_RC_OTHER,
+ N_("S.E. Mean"), PIVOT_RC_OTHER);
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
+
+ for (size_t i = 0; i < os->n_stats; i++)
{
+ const struct per_var_stats *per_var_stats = &os->stats[i];
const struct moments *m = per_var_stats->mom;
- const int v = per_var_stats->posn;
+
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (per_var_stats->var));
+
double cc, mean, sigma;
moments_calculate (m, &cc, &mean, &sigma, NULL, NULL);
- tab_text (t, 0, v + heading_rows, TAB_LEFT, var_to_string (per_var_stats->var));
- tab_double (t, 1, v + heading_rows, TAB_RIGHT, cc, NULL, RC_WEIGHT);
- tab_double (t, 2, v + heading_rows, TAB_RIGHT, mean, NULL, RC_OTHER);
- tab_double (t, 3, v + heading_rows, TAB_RIGHT, sqrt (sigma), NULL, RC_OTHER);
- tab_double (t, 4, v + heading_rows, TAB_RIGHT, sqrt (sigma / cc), NULL, RC_OTHER);
+ double entries[] = { cc, mean, sqrt (sigma), sqrt (sigma / cc) };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put2 (table, j, var_idx,
+ pivot_value_new_number (entries[j]));
}
- tab_submit (t);
+ pivot_table_submit (table);
}
void
one_sample_run (const struct tt *tt, double testval, struct casereader *reader)
{
- int i;
- struct ccase *c;
struct one_samp os;
- struct casereader *r;
- struct hmapx_node *node;
- struct per_var_stats *per_var_stats;
-
os.testval = testval;
- hmapx_init (&os.hmap);
-
- /* Insert all the variables into the map */
- for (i = 0; i < tt->n_vars; ++i)
+ os.stats = xcalloc (tt->n_vars, sizeof *os.stats);
+ os.n_stats = tt->n_vars;
+ for (size_t i = 0; i < tt->n_vars; ++i)
{
- struct per_var_stats *per_var_stats = xzalloc (sizeof (*per_var_stats));
-
- per_var_stats->posn = i;
+ struct per_var_stats *per_var_stats = &os.stats[i];
per_var_stats->var = tt->vars[i];
per_var_stats->mom = moments_create (MOMENT_VARIANCE);
-
- hmapx_insert (&os.hmap, per_var_stats, hash_pointer (per_var_stats->var, 0));
}
- r = casereader_clone (reader);
+ struct casereader *r = casereader_clone (reader);
+ struct ccase *c;
for ( ; (c = casereader_read (r) ); case_unref (c))
{
double w = dict_get_case_weight (tt->dict, c, NULL);
- struct hmapx_node *node;
- struct per_var_stats *per_var_stats;
- HMAPX_FOR_EACH (per_var_stats, node, &os.hmap)
- {
+ for (size_t i = 0; i < os.n_stats; i++)
+ {
+ const struct per_var_stats *per_var_stats = &os.stats[i];
const struct variable *var = per_var_stats->var;
const union value *val = case_data (c, var);
if (var_is_value_missing (var, val, tt->exclude))
for ( ; (c = casereader_read (r) ); case_unref (c))
{
double w = dict_get_case_weight (tt->dict, c, NULL);
- struct hmapx_node *node;
- struct per_var_stats *per_var_stats;
- HMAPX_FOR_EACH (per_var_stats, node, &os.hmap)
- {
+ for (size_t i = 0; i < os.n_stats; i++)
+ {
+ struct per_var_stats *per_var_stats = &os.stats[i];
const struct variable *var = per_var_stats->var;
const union value *val = case_data (c, var);
if (var_is_value_missing (var, val, tt->exclude))
one_sample_summary (tt, &os);
one_sample_test (tt, &os);
- HMAPX_FOR_EACH (per_var_stats, node, &os.hmap)
+ for (size_t i = 0; i < os.n_stats; i++)
{
+ const struct per_var_stats *per_var_stats = &os.stats[i];
moments_destroy (per_var_stats->mom);
- free (per_var_stats);
}
-
- hmapx_destroy (&os.hmap);
+ free (os.stats);
}
projects / pspp / blobdiff