#include <output/manager.h>
#include <output/table.h>
#include "sort-criteria.h"
+#include <data/format.h>
#include "xalloc.h"
/* Routines to show the output tables */
-static void show_anova_table (void);
-static void show_descriptives (void);
-static void show_homogeneity (void);
+static void show_anova_table(void);
+static void show_descriptives (const struct dictionary *dict);
+static void show_homogeneity(void);
static void show_contrast_coeffs (short *);
static void show_contrast_tests (short *);
static enum stat_table_t stat_tables;
-void output_oneway (void);
+static void output_oneway (const struct dictionary *dict);
int
}
-void
-output_oneway (void)
+static void
+output_oneway (const struct dictionary *dict)
{
size_t i;
short *bad_contrast;
}
if ( stat_tables & STAT_DESC )
- show_descriptives ();
+ show_descriptives (dict);
if ( stat_tables & STAT_HOMO )
show_homogeneity ();
/* Sums of Squares */
- tab_float (t, 2, i * 3 + 1, 0, ssa, 10, 2);
- tab_float (t, 2, i * 3 + 3, 0, sst, 10, 2);
- tab_float (t, 2, i * 3 + 2, 0, sst - ssa, 10, 2);
+ tab_double (t, 2, i * 3 + 1, 0, ssa, NULL);
+ tab_double (t, 2, i * 3 + 3, 0, sst, NULL);
+ tab_double (t, 2, i * 3 + 2, 0, sst - ssa, NULL);
/* Degrees of freedom */
- tab_float (t, 3, i * 3 + 1, 0, df1, 4, 0);
- tab_float (t, 3, i * 3 + 2, 0, df2, 4, 0);
- tab_float (t, 3, i * 3 + 3, 0, totals->n - 1, 4, 0);
+ tab_fixed (t, 3, i * 3 + 1, 0, df1, 4, 0);
+ tab_fixed (t, 3, i * 3 + 2, 0, df2, 4, 0);
+ tab_fixed (t, 3, i * 3 + 3, 0, totals->n - 1, 4, 0);
/* Mean Squares */
- tab_float (t, 4, i * 3 + 1, TAB_RIGHT, msa, 8, 3);
- tab_float (t, 4, i * 3 + 2, TAB_RIGHT, gp->mse, 8, 3);
+ tab_double (t, 4, i * 3 + 1, TAB_RIGHT, msa, NULL);
+ tab_double (t, 4, i * 3 + 2, TAB_RIGHT, gp->mse, NULL);
{
- const double F = msa/gp->mse;
+ const double F = msa / gp->mse ;
/* The F value */
- tab_float (t, 5, i * 3 + 1, 0, F, 8, 3);
+ tab_double (t, 5, i * 3 + 1, 0, F, NULL);
/* The significance */
- tab_float (t, 6, i * 3 + 1, 0, gsl_cdf_fdist_Q (F, df1, df2), 8, 3);
+ tab_double (t, 6, i * 3 + 1, 0, gsl_cdf_fdist_Q (F, df1, df2), NULL);
}
}
}
/* Show the descriptives table */
static void
-show_descriptives (void)
+show_descriptives (const struct dictionary *dict)
{
size_t v;
- int n_cols =10;
+ int n_cols = 10;
struct tab_table *t;
int row;
const double confidence = 0.95;
const double q = (1.0 - confidence) / 2.0;
+ const struct variable *wv = dict_get_weight (dict);
+ const struct fmt_spec *wfmt = wv ? var_get_print_format (wv) : & F_8_0;
int n_rows = 2;
struct group_statistics *totals = &gp->ugs;
const char *s = var_to_string (vars[v]);
+ const struct fmt_spec *fmt = var_get_print_format (vars[v]);
struct group_statistics *const *gs_array =
(struct group_statistics *const *) hsh_sort (gp->group_hash);
/* Now fill in the numbers ... */
- tab_float (t, 2, row + count, 0, gs->n, 8, 0);
+ tab_fixed (t, 2, row + count, 0, gs->n, 8, 0);
- tab_float (t, 3, row + count, 0, gs->mean, 8, 2);
+ tab_double (t, 3, row + count, 0, gs->mean, NULL);
- tab_float (t, 4, row + count, 0, gs->std_dev, 8, 2);
+ tab_double (t, 4, row + count, 0, gs->std_dev, NULL);
- std_error = gs->std_dev/sqrt (gs->n);
- tab_float (t, 5, row + count, 0,
- std_error, 8, 2);
+ std_error = gs->std_dev / sqrt (gs->n) ;
+ tab_double (t, 5, row + count, 0,
+ std_error, NULL);
/* Now the confidence interval */
T = gsl_cdf_tdist_Qinv (q, gs->n - 1);
- tab_float (t, 6, row + count, 0,
- gs->mean - T * std_error, 8, 2);
+ tab_double (t, 6, row + count, 0,
+ gs->mean - T * std_error, NULL);
- tab_float (t, 7, row + count, 0,
- gs->mean + T * std_error, 8, 2);
+ tab_double (t, 7, row + count, 0,
+ gs->mean + T * std_error, NULL);
/* Min and Max */
- tab_float (t, 8, row + count, 0, gs->minimum, 8, 2);
- tab_float (t, 9, row + count, 0, gs->maximum, 8, 2);
+
+ tab_double (t, 8, row + count, 0, gs->minimum, fmt);
+ tab_double (t, 9, row + count, 0, gs->maximum, fmt);
}
tab_text (t, 1, row + count,
TAB_LEFT | TAT_TITLE, _("Total"));
- tab_float (t, 2, row + count, 0, totals->n, 8, 0);
+ tab_double (t, 2, row + count, 0, totals->n, wfmt);
- tab_float (t, 3, row + count, 0, totals->mean, 8, 2);
+ tab_double (t, 3, row + count, 0, totals->mean, NULL);
- tab_float (t, 4, row + count, 0, totals->std_dev, 8, 2);
+ tab_double (t, 4, row + count, 0, totals->std_dev, NULL);
- std_error = totals->std_dev/sqrt (totals->n);
+ std_error = totals->std_dev / sqrt (totals->n) ;
- tab_float (t, 5, row + count, 0, std_error, 8, 2);
+ tab_double (t, 5, row + count, 0, std_error, NULL);
/* Now the confidence interval */
T = gsl_cdf_tdist_Qinv (q, totals->n - 1);
- tab_float (t, 6, row + count, 0,
- totals->mean - T * std_error, 8, 2);
+ tab_double (t, 6, row + count, 0,
+ totals->mean - T * std_error, NULL);
- tab_float (t, 7, row + count, 0,
- totals->mean + T * std_error, 8, 2);
+ tab_double (t, 7, row + count, 0,
+ totals->mean + T * std_error, NULL);
/* Min and Max */
- tab_float (t, 8, row + count, 0, totals->minimum, 8, 2);
- tab_float (t, 9, row + count, 0, totals->maximum, 8, 2);
+
+ tab_double (t, 8, row + count, 0, totals->minimum, fmt);
+ tab_double (t, 9, row + count, 0, totals->maximum, fmt);
row += gp->n_groups + 1;
}
tab_text (t, 0, v + 1, TAB_LEFT | TAT_TITLE, s);
F = gp->levene;
- tab_float (t, 1, v + 1, TAB_RIGHT, F, 8, 3);
- tab_float (t, 2, v + 1, TAB_RIGHT, df1, 8, 0);
- tab_float (t, 3, v + 1, TAB_RIGHT, df2, 8, 0);
+ tab_double (t, 1, v + 1, TAB_RIGHT, F, NULL);
+ tab_fixed (t, 2, v + 1, TAB_RIGHT, df1, 8, 0);
+ tab_fixed (t, 3, v + 1, TAB_RIGHT, df2, 8, 0);
/* Now the significance */
- tab_float (t, 4, v + 1, TAB_RIGHT, gsl_cdf_fdist_Q (F, df1, df2), 8, 3);
+ tab_double (t, 4, v + 1, TAB_RIGHT,gsl_cdf_fdist_Q (F, df1, df2), NULL);
}
tab_submit (t);
}
sec_vneq = sqrt (sec_vneq);
- df_numerator = pow2(df_numerator);
+ df_numerator = pow2 (df_numerator);
- tab_float (t, 3, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, contrast_value, 8, 2);
+ tab_double (t, 3, (v * lines_per_variable) + i + 1,
+ TAB_RIGHT, contrast_value, NULL);
- tab_float (t, 3, (v * lines_per_variable) + i + 1 +
+ tab_double (t, 3, (v * lines_per_variable) + i + 1 +
cmd.sbc_contrast,
- TAB_RIGHT, contrast_value, 8, 2);
+ TAB_RIGHT, contrast_value, NULL);
std_error_contrast = sqrt (grp_data->mse * coef_msq);
/* Std. Error */
- tab_float (t, 4, (v * lines_per_variable) + i + 1,
+ tab_double (t, 4, (v * lines_per_variable) + i + 1,
TAB_RIGHT, std_error_contrast,
- 8, 3);
+ NULL);
T = fabs (contrast_value / std_error_contrast);
/* T Statistic */
- tab_float (t, 5, (v * lines_per_variable) + i + 1,
+ tab_double (t, 5, (v * lines_per_variable) + i + 1,
TAB_RIGHT, T,
- 8, 3);
+ NULL);
df = grp_data->ugs.n - grp_data->n_groups;
/* Degrees of Freedom */
- tab_float (t, 6, (v * lines_per_variable) + i + 1,
+ tab_fixed (t, 6, (v * lines_per_variable) + i + 1,
TAB_RIGHT, df,
8, 0);
/* Significance TWO TAILED !!*/
- tab_float (t, 7, (v * lines_per_variable) + i + 1,
+ tab_double (t, 7, (v * lines_per_variable) + i + 1,
TAB_RIGHT, 2 * gsl_cdf_tdist_Q (T, df),
- 8, 3);
-
+ NULL);
/* Now for the Variances NOT Equal case */
/* Std. Error */
- tab_float (t, 4,
+ tab_double (t, 4,
(v * lines_per_variable) + i + 1 + cmd.sbc_contrast,
TAB_RIGHT, sec_vneq,
- 8, 3);
-
+ NULL);
T = contrast_value / sec_vneq;
- tab_float (t, 5,
+ tab_double (t, 5,
(v * lines_per_variable) + i + 1 + cmd.sbc_contrast,
TAB_RIGHT, T,
- 8, 3);
-
+ NULL);
df = df_numerator / df_denominator;
- tab_float (t, 6,
+ tab_double (t, 6,
(v * lines_per_variable) + i + 1 + cmd.sbc_contrast,
TAB_RIGHT, df,
- 8, 3);
+ NULL);
/* The Significance */
- tab_float (t, 7, (v * lines_per_variable) + i + 1 + cmd.sbc_contrast,
- TAB_RIGHT, 2 * gsl_cdf_tdist_Q (T, df),
- 8, 3);
-
-
+ tab_double (t, 7, (v * lines_per_variable) + i + 1 + cmd.sbc_contrast,
+ TAB_RIGHT, 2 * gsl_cdf_tdist_Q (T,df),
+ NULL);
}
if ( v > 0 )
}
tab_submit (t);
-
}
ostensible_number_of_groups = hsh_count (global_group_hash);
if (!taint_has_tainted_successor (taint))
- output_oneway ();
+ output_oneway (dict);
+
taint_destroy (taint);
}
projects / pspp-builds.git / blobdiff