X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;ds=sidebyside;f=src%2Flanguage%2Fstats%2Foneway.c;h=6756882d33fb28a7fd8559a31c76a6cfe86bb799;hb=b3e38130c172738f79f180fb4d459e4d5d2d88a6;hp=ce4f016d99063acabf0dd71abab6d36245229aa3;hpb=2fc70481c7621ee4d51f986c53c4add4ec6cc57d;p=pspp diff --git a/src/language/stats/oneway.c b/src/language/stats/oneway.c index ce4f016d99..6756882d33 100644 --- a/src/language/stats/oneway.c +++ b/src/language/stats/oneway.c @@ -20,6 +20,11 @@ #include #include +#include +#include +#include +#include + #include #include @@ -94,6 +99,21 @@ struct oneway_spec struct ll_list contrast_list; }; + +/* Workspace variable for each dependent variable */ +struct per_var_ws +{ + struct covariance *cov; + + double sst; + double sse; + double ssa; + + int n_groups; + + double cc; +}; + struct oneway_workspace { /* The number of distinct values of the independent variable, when all @@ -103,10 +123,12 @@ struct oneway_workspace /* A hash table containing all the distinct values of the independent variable */ struct hsh_table *group_hash; + + struct per_var_ws *vws; }; /* Routines to show the output tables */ -static void show_anova_table (const struct oneway_spec *); +static void show_anova_table (const struct oneway_spec *, const struct oneway_workspace *); static void show_descriptives (const struct oneway_spec *, const struct dictionary *dict); static void show_homogeneity (const struct oneway_spec *); @@ -288,13 +310,25 @@ run_oneway (const struct oneway_spec *cmd, struct casereader *input, const struct dataset *ds) { + int v; struct taint *taint; struct dictionary *dict = dataset_dict (ds); struct casereader *reader; struct ccase *c; + const struct variable *wv = dict_get_weight (dict); struct oneway_workspace ws; + ws.vws = xmalloc (cmd->n_vars * sizeof (*ws.vws)); + + for (v = 0; v < cmd->n_vars; ++v) + { + ws.vws[v].cov = covariance_2pass_create (1, &cmd->vars[v], + 1, &cmd->indep_var, + wv, cmd->exclude); + ws.vws[v].cc = 0; + } + c = casereader_peek (input, 0); if (c == NULL) { @@ -322,6 +356,7 @@ run_oneway (const struct oneway_spec *cmd, input = casereader_create_filter_weight (input, dict, NULL, NULL); reader = casereader_clone (input); + for (; (c = casereader_read (reader)) != NULL; case_unref (c)) { size_t i; @@ -338,6 +373,13 @@ run_oneway (const struct oneway_spec *cmd, for (i = 0; i < cmd->n_vars; ++i) { + { + struct per_var_ws *pvw = &ws.vws[i]; + + pvw->cc += weight; + covariance_accumulate_pass1 (pvw->cov, c); + } + const struct variable *v = cmd->vars[i]; const union value *val = case_data (c, v); @@ -393,6 +435,34 @@ run_oneway (const struct oneway_spec *cmd, } casereader_destroy (reader); + reader = casereader_clone (input); + for ( ; (c = casereader_read (reader) ); case_unref (c)) + { + int i; + for (i = 0; i < cmd->n_vars; ++i) + { + struct per_var_ws *pvw = &ws.vws[i]; + covariance_accumulate_pass2 (pvw->cov, c); + } + } + casereader_destroy (reader); + + for (v = 0; v < cmd->n_vars; ++v) + { + struct per_var_ws *pvw = &ws.vws[v]; + gsl_matrix *cm = covariance_calculate_unnormalized (pvw->cov); + const struct categoricals *cats = covariance_get_categoricals (pvw->cov); + + pvw->sst = gsl_matrix_get (cm, 0, 0); + + reg_sweep (cm, 0); + + pvw->sse = gsl_matrix_get (cm, 0, 0); + + pvw->ssa = pvw->sst - pvw->sse; + + pvw->n_groups = categoricals_total (cats); + } postcalc (cmd); @@ -517,7 +587,7 @@ output_oneway (const struct oneway_spec *cmd, struct oneway_workspace *ws) if (cmd->stats & STATS_HOMOGENEITY) show_homogeneity (cmd); - show_anova_table (cmd); + show_anova_table (cmd, ws); if (ll_count (&cmd->contrast_list) > 0) @@ -541,7 +611,7 @@ output_oneway (const struct oneway_spec *cmd, struct oneway_workspace *ws) /* Show the ANOVA table */ static void -show_anova_table (const struct oneway_spec *cmd) +show_anova_table (const struct oneway_spec *cmd, const struct oneway_workspace *ws) { size_t i; int n_cols =7; @@ -570,21 +640,13 @@ show_anova_table (const struct oneway_spec *cmd) for (i = 0; i < cmd->n_vars; ++i) { - struct group_statistics *totals = &group_proc_get (cmd->vars[i])->ugs; - struct hsh_table *group_hash = group_proc_get (cmd->vars[i])->group_hash; - struct hsh_iterator g; - struct group_statistics *gs; - double ssa = 0; - const char *s = var_to_string (cmd->vars[i]); - - for (gs = hsh_first (group_hash, &g); - gs != 0; - gs = hsh_next (group_hash, &g)) - { - ssa += pow2 (gs->sum) / gs->n; - } + const struct per_var_ws *pvw = &ws->vws[i]; + struct group_proc *gp = group_proc_get (cmd->vars[i]); + const double df1 = pvw->n_groups - 1; + const double df2 = pvw->cc - pvw->n_groups; + const double msa = pvw->ssa / df1; - ssa -= pow2 (totals->sum) / totals->n; + const char *s = var_to_string (cmd->vars[i]); tab_text (t, 0, i * 3 + 1, TAB_LEFT | TAT_TITLE, s); tab_text (t, 1, i * 3 + 1, TAB_LEFT | TAT_TITLE, _("Between Groups")); @@ -594,44 +656,35 @@ show_anova_table (const struct oneway_spec *cmd) if (i > 0) tab_hline (t, TAL_1, 0, n_cols - 1, i * 3 + 1); - { - struct group_proc *gp = group_proc_get (cmd->vars[i]); - const double sst = totals->ssq - pow2 (totals->sum) / totals->n; - const double df1 = gp->n_groups - 1; - const double df2 = totals->n - gp->n_groups; - const double msa = ssa / df1; - - gp->mse = (sst - ssa) / df2; + gp->mse = (pvw->sst - pvw->ssa) / df2; - /* Sums of Squares */ - 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); + /* Sums of Squares */ + tab_double (t, 2, i * 3 + 1, 0, pvw->ssa, NULL); + tab_double (t, 2, i * 3 + 3, 0, pvw->sst, NULL); + tab_double (t, 2, i * 3 + 2, 0, pvw->sse, NULL); - /* Degrees of freedom */ - 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); + /* Degrees of freedom */ + 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, pvw->cc - 1, 4, 0); - /* Mean Squares */ - tab_double (t, 4, i * 3 + 1, TAB_RIGHT, msa, NULL); - tab_double (t, 4, i * 3 + 2, TAB_RIGHT, gp->mse, NULL); + /* Mean Squares */ + 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_double (t, 5, i * 3 + 1, 0, F, NULL); + /* The F value */ + tab_double (t, 5, i * 3 + 1, 0, F, NULL); - /* The significance */ - tab_double (t, 6, i * 3 + 1, 0, gsl_cdf_fdist_Q (F, df1, df2), NULL); - } + /* The significance */ + tab_double (t, 6, i * 3 + 1, 0, gsl_cdf_fdist_Q (F, df1, df2), NULL); } } - tab_title (t, _("ANOVA")); tab_submit (t); }