X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Flanguage%2Fstats%2Fbinomial.c;h=f2ae51513eb7c4366c993d0875eb87fa10eef936;hb=8a0397328b6230fd49724e1c6d91a5a545d2fb4b;hp=bc87a94da3316b0c0cf0b99c0035092a7d93a8cb;hpb=7878e5e2f2d1045bba2483ab9a752ceae50086f3;p=pspp diff --git a/src/language/stats/binomial.c b/src/language/stats/binomial.c index bc87a94da3..f2ae51513e 100644 --- a/src/language/stats/binomial.c +++ b/src/language/stats/binomial.c @@ -1,5 +1,5 @@ /* PSPP - a program for statistical analysis. - Copyright (C) 2006, 2009 Free Software Foundation, Inc. + Copyright (C) 2006, 2009, 2010, 2011, 2014 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 @@ -15,37 +15,34 @@ along with this program. If not, see . */ #include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include - -#include -#include - -#include "binomial.h" -#include "freq.h" - -#include "xalloc.h" - -#include "gettext.h" -#define _(msgid) gettext (msgid) - -#include +#include "language/stats/binomial.h" +#include #include #include -#include +#include "data/case.h" +#include "data/casereader.h" +#include "data/dataset.h" +#include "data/dictionary.h" +#include "data/format.h" +#include "data/value-labels.h" +#include "data/value.h" +#include "data/variable.h" +#include "language/stats/freq.h" +#include "libpspp/assertion.h" +#include "libpspp/compiler.h" +#include "libpspp/message.h" +#include "libpspp/misc.h" +#include "output/pivot-table.h" + +#include "gl/xalloc.h" +#include "gl/minmax.h" -#include +#include "gettext.h" +#define N_(msgid) msgid +#define _(msgid) gettext (msgid) static double calculate_binomial_internal (double n1, double n2, double p); @@ -63,8 +60,8 @@ static double calculate_binomial (double n1, double n2, double p) { const double n = n1 + n2; - const bool test_reversed = (n1 / n > p ) ; - if ( test_reversed ) + const bool test_reversed = (n1 / n > p) ; + if (test_reversed) { p = 1 - p ; swap (&n1, &n2); @@ -81,7 +78,7 @@ calculate_binomial_internal (double n1, double n2, double p) double sig1tailed = gsl_cdf_binomial_P (n1, p, n1 + n2); - if ( p == 0.5 ) + if (p == 0.5) return sig1tailed > 0.5 ? 1.0 :sig1tailed * 2.0; return sig1tailed ; @@ -90,15 +87,15 @@ calculate_binomial_internal (double n1, double n2, double p) static bool do_binomial (const struct dictionary *dict, struct casereader *input, - const struct binomial_test *bst, - struct freq_mutable *cat1, - struct freq_mutable *cat2, + const struct one_sample_test *ost, + struct freq *cat1, + struct freq *cat2, enum mv_class exclude - ) + ) { + const struct binomial_test *bst = UP_CAST (ost, const struct binomial_test, parent); bool warn = true; - const struct one_sample_test *ost = (const struct one_sample_test *) bst; struct ccase *c; for (; (c = casereader_read (input)) != NULL; case_unref (c)) @@ -106,38 +103,38 @@ do_binomial (const struct dictionary *dict, int v; double w = dict_get_case_weight (dict, c, &warn); - for (v = 0 ; v < ost->n_vars ; ++v ) + for (v = 0 ; v < ost->n_vars ; ++v) { const struct variable *var = ost->vars[v]; double value = case_num (c, var); - if (var_is_num_missing (var, value, exclude)) + if (var_is_num_missing (var, value) & exclude) continue; if (bst->cutpoint != SYSMIS) { - if ( cat1[v].value.f >= value ) + if (cat1[v].values[0].f >= value) cat1[v].count += w; else cat2[v].count += w; } else { - if ( SYSMIS == cat1[v].value.f ) + if (SYSMIS == cat1[v].values[0].f) { - cat1[v].value.f = value; + cat1[v].values[0].f = value; cat1[v].count = w; } - else if ( cat1[v].value.f == value ) + else if (cat1[v].values[0].f == value) cat1[v].count += w; - else if ( SYSMIS == cat2[v].value.f ) + else if (SYSMIS == cat2[v].values[0].f) { - cat2[v].value.f = value; + cat2[v].values[0].f = value; cat2[v].count = w; } - else if ( cat2[v].value.f == value ) + else if (cat2[v].values[0].f == value) cat2[v].count += w; - else if ( bst->category1 == SYSMIS) + else if (bst->category1 == SYSMIS) msg (ME, _("Variable %s is not dichotomous"), var_get_name (var)); } } @@ -155,12 +152,11 @@ binomial_execute (const struct dataset *ds, bool exact UNUSED, double timer UNUSED) { - int v; const struct dictionary *dict = dataset_dict (ds); - const struct binomial_test *bst = (const struct binomial_test *) test; - const struct one_sample_test *ost = (const struct one_sample_test*) test; + const struct one_sample_test *ost = UP_CAST (test, const struct one_sample_test, parent); + const struct binomial_test *bst = UP_CAST (ost, const struct binomial_test, parent); - struct freq_mutable *cat[2]; + struct freq *cat[2]; int i; assert ((bst->category1 == SYSMIS) == (bst->category2 == SYSMIS) || bst->cutpoint != SYSMIS); @@ -174,99 +170,85 @@ binomial_execute (const struct dataset *ds, value = bst->category2; cat[i] = xnmalloc (ost->n_vars, sizeof *cat[i]); - for (v = 0; v < ost->n_vars; v++) + for (size_t v = 0; v < ost->n_vars; v++) { - cat[i][v].value.f = value; + cat[i][v].values[0].f = value; cat[i][v].count = 0; } } - if (do_binomial (dataset_dict (ds), input, bst, cat[0], cat[1], exclude)) + if (do_binomial (dataset_dict (ds), input, ost, cat[0], cat[1], exclude)) { - const struct variable *wvar = dict_get_weight (dict); - const struct fmt_spec *wfmt = wvar ? - var_get_print_format (wvar) : & F_8_0; - - struct tab_table *table = tab_create (7, ost->n_vars * 3 + 1); - - tab_dim (table, tab_natural_dimensions, NULL, NULL); - - tab_title (table, _("Binomial Test")); - - tab_headers (table, 2, 0, 1, 0); - - tab_box (table, TAL_1, TAL_1, -1, TAL_1, - 0, 0, tab_nc (table) - 1, tab_nr(table) - 1 ); - - for (v = 0 ; v < ost->n_vars; ++v) + struct pivot_table *table = pivot_table_create (N_("Binomial Test")); + pivot_table_set_weight_var (table, dict_get_weight (dict)); + + pivot_dimension_create ( + table, PIVOT_AXIS_COLUMN, N_("Statistics"), + N_("Category"), + N_("N"), PIVOT_RC_COUNT, + N_("Observed Prop."), PIVOT_RC_OTHER, + N_("Test Prop."), PIVOT_RC_OTHER, + (bst->p == 0.5 + ? N_("Exact Sig. (2-tailed)") + : N_("Exact Sig. (1-tailed)")), PIVOT_RC_SIGNIFICANCE); + + pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Groups"), + N_("Group 1"), N_("Group 2"), N_("Total")); + + struct pivot_dimension *variables = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Variables")); + + for (size_t v = 0; v < ost->n_vars; ++v) { - double n_total, sig; - struct string catstr[2]; const struct variable *var = ost->vars[v]; - ds_init_empty (&catstr[0]); - ds_init_empty (&catstr[1]); + int var_idx = pivot_category_create_leaf ( + variables->root, pivot_value_new_variable (var)); - if ( bst->cutpoint != SYSMIS) - { - ds_put_format (&catstr[0], "<= %g", bst->cutpoint); - } + /* Category. */ + if (bst->cutpoint != SYSMIS) + pivot_table_put3 ( + table, 0, 0, var_idx, + pivot_value_new_user_text_nocopy ( + xasprintf ("<= %.*g", DBL_DIG + 1, bst->cutpoint))); else + for (int i = 0; i < 2; i++) + pivot_table_put3 ( + table, 0, i, var_idx, + pivot_value_new_var_value (var, cat[i][v].values)); + + double n_total = cat[0][v].count + cat[1][v].count; + double sig = calculate_binomial (cat[0][v].count, cat[1][v].count, + bst->p); + struct entry { - var_append_value_name (var, &cat[0][v].value, &catstr[0]); - var_append_value_name (var, &cat[1][v].value, &catstr[1]); + int stat_idx; + int group_idx; + double x; + } + entries[] = { + /* N. */ + { 1, 0, cat[0][v].count }, + { 1, 1, cat[1][v].count }, + { 1, 2, n_total }, + /* Observed Prop. */ + { 2, 0, cat[0][v].count / n_total }, + { 2, 1, cat[1][v].count / n_total }, + { 2, 2, 1.0 }, + /* Test Prop. */ + { 3, 0, bst->p }, + /* Significance. */ + { 4, 0, sig } + }; + for (size_t i = 0; i < sizeof entries / sizeof *entries; i++) + { + const struct entry *e = &entries[i]; + pivot_table_put3 (table, e->stat_idx, e->group_idx, + var_idx, pivot_value_new_number (e->x)); } - - 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")); - tab_text (table, 1, 2 + v * 3, TAB_LEFT, _("Group2")); - tab_text (table, 1, 3 + v * 3, TAB_LEFT, _("Total")); - - /* Test Prop */ - tab_double (table, 5, 1 + v * 3, TAB_NONE, bst->p, NULL); - - /* Category labels */ - tab_text (table, 2, 1 + v * 3, TAB_NONE, ds_cstr (&catstr[0])); - tab_text (table, 2, 2 + v * 3, TAB_NONE, ds_cstr (&catstr[1])); - - /* Observed N */ - tab_double (table, 3, 1 + v * 3, TAB_NONE, cat[0][v].count, wfmt); - tab_double (table, 3, 2 + v * 3, TAB_NONE, cat[1][v].count, wfmt); - - n_total = cat[0][v].count + cat[1][v].count; - tab_double (table, 3, 3 + v * 3, TAB_NONE, n_total, wfmt); - - /* Observed Proportions */ - tab_double (table, 4, 1 + v * 3, TAB_NONE, - cat[0][v].count / n_total, NULL); - tab_double (table, 4, 2 + v * 3, TAB_NONE, - cat[1][v].count / n_total, NULL); - - tab_double (table, 4, 3 + v * 3, TAB_NONE, - (cat[0][v].count + cat[1][v].count) / n_total, NULL); - - /* Significance */ - sig = calculate_binomial (cat[0][v].count, cat[1][v].count, bst->p); - tab_double (table, 6, 1 + v * 3, TAB_NONE, sig, NULL); - - ds_destroy (&catstr[0]); - ds_destroy (&catstr[1]); } - 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_format (table, 6, 0, TAB_CENTER, - _("Exact Sig. (%d-tailed)"), - bst->p == 0.5 ? 2 : 1); - - tab_vline (table, TAL_2, 2, 0, tab_nr (table) -1); - tab_submit (table); + pivot_table_submit (table); } for (i = 0; i < 2; i++)