2 PSPP - a program for statistical analysis.
3 Copyright (C) 2012, 2013 Free Software Foundation, Inc.
5 This program is free software: you can redistribute it and/or modify
6 it under the terms of the GNU General Public License as published by
7 the Free Software Foundation, either version 3 of the License, or
8 (at your option) any later version.
10 This program is distributed in the hope that it will be useful,
11 but WITHOUT ANY WARRANTY; without even the implied warranty of
12 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13 GNU General Public License for more details.
15 You should have received a copy of the GNU General Public License
16 along with this program. If not, see <http://www.gnu.org/licenses/>.
22 #include <gsl/gsl_cdf.h>
24 #include "libpspp/assertion.h"
25 #include "libpspp/message.h"
26 #include "libpspp/pool.h"
29 #include "data/dataset.h"
30 #include "data/dictionary.h"
31 #include "data/casegrouper.h"
32 #include "data/casereader.h"
33 #include "data/casewriter.h"
34 #include "data/caseproto.h"
35 #include "data/subcase.h"
38 #include "data/format.h"
40 #include "math/interaction.h"
41 #include "math/box-whisker.h"
42 #include "math/categoricals.h"
43 #include "math/chart-geometry.h"
44 #include "math/histogram.h"
45 #include "math/moments.h"
47 #include "math/sort.h"
48 #include "math/order-stats.h"
49 #include "math/percentiles.h"
50 #include "math/tukey-hinges.h"
51 #include "math/trimmed-mean.h"
53 #include "output/charts/boxplot.h"
54 #include "output/charts/np-plot.h"
55 #include "output/charts/spreadlevel-plot.h"
56 #include "output/charts/plot-hist.h"
58 #include "language/command.h"
59 #include "language/lexer/lexer.h"
60 #include "language/lexer/value-parser.h"
61 #include "language/lexer/variable-parser.h"
63 #include "output/tab.h"
66 #define _(msgid) gettext (msgid)
67 #define N_(msgid) msgid
70 append_value_name (const struct variable *var, const union value *val, struct string *str)
72 var_append_value_name (var, val, str);
73 if ( var_is_value_missing (var, val, MV_ANY))
74 ds_put_cstr (str, _(" (missing)"));
84 /* Indices for the ex_proto member (below) */
97 /* A caseproto used to contain the data subsets under examination,
99 struct caseproto *ex_proto;
102 const struct variable **dep_vars;
105 struct interaction **iacts;
107 enum mv_class dep_excl;
108 enum mv_class fctr_excl;
110 const struct dictionary *dict;
112 struct categoricals *cats;
114 /* how many extremities to display */
123 /* The case index of the ID value (or -1) if not applicable */
129 size_t n_percentiles;
134 bool spreadlevelplot;
137 enum bp_mode boxplot_mode;
139 const struct variable *id_var;
141 const struct variable *wv;
146 /* The value of this extremity */
149 /* Either the casenumber or the value of the variable specified
150 by the /ID subcommand which corresponds to this extremity */
151 union value identity;
154 struct exploratory_stats
161 /* Most operations need a sorted reader/writer */
162 struct casewriter *sorted_writer;
163 struct casereader *sorted_reader;
165 struct extremity *minima;
166 struct extremity *maxima;
169 Minimum should alway equal mimima[0].val.
170 Likewise, maximum should alway equal maxima[0].val.
171 This redundancy exists as an optimisation effort.
172 Some statistics (eg histogram) require early calculation
178 struct trimmed_mean *trimmed_mean;
179 struct percentile *quartiles[3];
180 struct percentile **percentiles;
182 struct tukey_hinges *hinges;
184 /* The data for the NP Plots */
187 struct histogram *histogram;
189 /* The data for the box plots */
190 struct box_whisker *box_whisker;
195 /* The minimum weight */
200 /* Returns an array of (iact->n_vars) pointers to union value initialised to NULL.
201 The caller must free this array when no longer required. */
202 static const union value **
203 previous_value_alloc (const struct interaction *iact)
207 const union value **prev_val = xcalloc (iact->n_vars, sizeof (*prev_val));
209 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
210 prev_val[ivar_idx] = NULL;
215 /* Set the contents of PREV_VAL to the values of C indexed by the variables of IACT */
217 previous_value_record (const struct interaction *iact, const struct ccase *c, const union value **prev_val)
222 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
224 const struct variable *ivar = iact->vars[ivar_idx];
225 const int width = var_get_width (ivar);
226 const union value *val = case_data (c, ivar);
228 if (prev_val[ivar_idx])
229 if (! value_equal (prev_val[ivar_idx], val, width))
236 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
238 const struct variable *ivar = iact->vars[ivar_idx];
239 const union value *val = case_data (c, ivar);
241 prev_val[ivar_idx] = val;
248 show_boxplot_grouped (const struct examine *cmd, int iact_idx)
252 const struct interaction *iact = cmd->iacts[iact_idx];
253 const size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
255 for (v = 0; v < cmd->n_dep_vars; ++v)
257 double y_min = DBL_MAX;
258 double y_max = -DBL_MAX;
260 struct boxplot *boxplot;
262 ds_init_empty (&title);
264 if (iact->n_vars > 0)
267 ds_init_empty (&istr);
268 interaction_to_string (iact, &istr);
269 ds_put_format (&title, _("Boxplot of %s vs. %s"),
270 var_to_string (cmd->dep_vars[v]),
275 ds_put_format (&title, _("Boxplot of %s"), var_to_string (cmd->dep_vars[v]));
277 for (grp = 0; grp < n_cats; ++grp)
279 const struct exploratory_stats *es =
280 categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, grp);
282 if ( y_min > es[v].minimum)
283 y_min = es[v].minimum;
285 if ( y_max < es[v].maximum)
286 y_max = es[v].maximum;
289 boxplot = boxplot_create (y_min, y_max, ds_cstr (&title));
293 for (grp = 0; grp < n_cats; ++grp)
298 const struct ccase *c =
299 categoricals_get_case_by_category_real (cmd->cats, iact_idx, grp);
301 const struct exploratory_stats *es =
302 categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, grp);
304 ds_init_empty (&label);
305 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
308 const struct variable *ivar = iact->vars[ivar_idx];
309 const union value *val = case_data (c, ivar);
312 append_value_name (ivar, val, &l);
313 ds_ltrim (&l, ss_cstr (" "));
315 ds_put_substring (&label, l.ss);
316 if (ivar_idx < iact->n_vars - 1)
317 ds_put_cstr (&label, "; ");
322 boxplot_add_box (boxplot, es[v].box_whisker, ds_cstr (&label));
327 boxplot_submit (boxplot);
332 show_boxplot_variabled (const struct examine *cmd, int iact_idx)
335 const struct interaction *iact = cmd->iacts[iact_idx];
336 const size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
338 for (grp = 0; grp < n_cats; ++grp)
340 struct boxplot *boxplot;
342 double y_min = DBL_MAX;
343 double y_max = -DBL_MAX;
345 const struct ccase *c =
346 categoricals_get_case_by_category_real (cmd->cats, iact_idx, grp);
349 ds_init_empty (&title);
351 for (v = 0; v < cmd->n_dep_vars; ++v)
353 const struct exploratory_stats *es =
354 categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, grp);
356 if ( y_min > es[v].minimum)
357 y_min = es[v].minimum;
359 if ( y_max < es[v].maximum)
360 y_max = es[v].maximum;
363 if ( iact->n_vars == 0)
364 ds_put_format (&title, _("Boxplot"));
369 ds_init_empty (&label);
370 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
372 const struct variable *ivar = iact->vars[ivar_idx];
373 const union value *val = case_data (c, ivar);
375 ds_put_cstr (&label, var_to_string (ivar));
376 ds_put_cstr (&label, " = ");
377 append_value_name (ivar, val, &label);
378 ds_put_cstr (&label, "; ");
381 ds_put_format (&title, _("Boxplot of %s"),
387 boxplot = boxplot_create (y_min, y_max, ds_cstr (&title));
391 for (v = 0; v < cmd->n_dep_vars; ++v)
393 const struct exploratory_stats *es =
394 categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, grp);
396 boxplot_add_box (boxplot, es[v].box_whisker,
397 var_to_string (cmd->dep_vars[v]));
400 boxplot_submit (boxplot);
406 show_npplot (const struct examine *cmd, int iact_idx)
408 const struct interaction *iact = cmd->iacts[iact_idx];
409 const size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
413 for (v = 0; v < cmd->n_dep_vars; ++v)
416 for (grp = 0; grp < n_cats; ++grp)
418 struct chart_item *npp, *dnpp;
419 struct casereader *reader;
423 const struct ccase *c =
424 categoricals_get_case_by_category_real (cmd->cats,
427 const struct exploratory_stats *es =
428 categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, grp);
431 ds_init_cstr (&label,
432 var_to_string (cmd->dep_vars[v]));
434 if ( iact->n_vars > 0)
436 ds_put_cstr (&label, " (");
437 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
439 const struct variable *ivar = iact->vars[ivar_idx];
440 const union value *val = case_data (c, ivar);
442 ds_put_cstr (&label, var_to_string (ivar));
443 ds_put_cstr (&label, " = ");
444 append_value_name (ivar, val, &label);
445 ds_put_cstr (&label, "; ");
448 ds_put_cstr (&label, ")");
452 reader = casewriter_make_reader (np->writer);
455 npp = np_plot_create (np, reader, ds_cstr (&label));
456 dnpp = dnp_plot_create (np, reader, ds_cstr (&label));
458 if (npp == NULL || dnpp == NULL)
460 msg (MW, _("Not creating NP plot because data set is empty."));
461 chart_item_unref (npp);
462 chart_item_unref (dnpp);
466 chart_item_submit (npp);
467 chart_item_submit (dnpp);
469 casereader_destroy (reader);
477 show_spreadlevel (const struct examine *cmd, int iact_idx)
479 const struct interaction *iact = cmd->iacts[iact_idx];
480 const size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
484 /* Spreadlevel when there are no levels is not useful */
485 if (iact->n_vars == 0)
488 for (v = 0; v < cmd->n_dep_vars; ++v)
491 struct chart_item *sl;
494 ds_init_cstr (&label,
495 var_to_string (cmd->dep_vars[v]));
497 if (iact->n_vars > 0)
499 ds_put_cstr (&label, " (");
500 interaction_to_string (iact, &label);
501 ds_put_cstr (&label, ")");
504 sl = spreadlevel_plot_create (ds_cstr (&label), cmd->sl_power);
506 for (grp = 0; grp < n_cats; ++grp)
508 const struct exploratory_stats *es =
509 categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, grp);
511 double median = percentile_calculate (es[v].quartiles[1], cmd->pc_alg);
513 double iqr = percentile_calculate (es[v].quartiles[2], cmd->pc_alg) -
514 percentile_calculate (es[v].quartiles[0], cmd->pc_alg);
516 spreadlevel_plot_add (sl, iqr, median);
520 msg (MW, _("Not creating spreadlevel chart for %s"), ds_cstr (&label));
522 chart_item_submit (sl);
530 show_histogram (const struct examine *cmd, int iact_idx)
532 const struct interaction *iact = cmd->iacts[iact_idx];
533 const size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
537 for (v = 0; v < cmd->n_dep_vars; ++v)
540 for (grp = 0; grp < n_cats; ++grp)
544 const struct ccase *c =
545 categoricals_get_case_by_category_real (cmd->cats,
548 const struct exploratory_stats *es =
549 categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, grp);
553 if (es[v].histogram == NULL)
556 ds_init_cstr (&label,
557 var_to_string (cmd->dep_vars[v]));
559 if ( iact->n_vars > 0)
561 ds_put_cstr (&label, " (");
562 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
564 const struct variable *ivar = iact->vars[ivar_idx];
565 const union value *val = case_data (c, ivar);
567 ds_put_cstr (&label, var_to_string (ivar));
568 ds_put_cstr (&label, " = ");
569 append_value_name (ivar, val, &label);
570 ds_put_cstr (&label, "; ");
573 ds_put_cstr (&label, ")");
577 moments_calculate (es[v].mom, &n, &mean, &var, NULL, NULL);
580 ( histogram_chart_create (es[v].histogram->gsl_hist,
581 ds_cstr (&label), n, mean,
591 percentiles_report (const struct examine *cmd, int iact_idx)
593 const struct interaction *iact = cmd->iacts[iact_idx];
595 const int heading_columns = 1 + iact->n_vars + 1;
596 const int heading_rows = 2;
599 const size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
601 const int rows_per_cat = 2;
602 const int rows_per_var = n_cats * rows_per_cat;
604 const int nr = heading_rows + cmd->n_dep_vars * rows_per_var;
605 const int nc = heading_columns + cmd->n_percentiles;
607 t = tab_create (nc, nr);
608 tab_title (t, _("Percentiles"));
610 tab_headers (t, heading_columns, 0, heading_rows, 0);
612 /* Internal Vertical lines */
613 tab_box (t, -1, -1, -1, TAL_1,
614 heading_columns, 0, nc - 1, nr - 1);
617 tab_box (t, TAL_2, TAL_2, -1, -1,
618 0, 0, nc - 1, nr - 1);
620 tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
621 tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
623 tab_joint_text (t, heading_columns, 0,
625 TAT_TITLE | TAB_CENTER,
629 tab_hline (t, TAL_1, heading_columns, nc - 1, 1);
632 for (i = 0; i < cmd->n_percentiles; ++i)
634 tab_text_format (t, heading_columns + i, 1,
635 TAT_TITLE | TAB_CENTER,
636 _("%g"), cmd->ptiles[i]);
639 for (i = 0; i < iact->n_vars; ++i)
644 var_to_string (iact->vars[i])
652 tab_vline (t, TAL_1, heading_columns - 1, heading_rows, nr - 1);
654 for (v = 0; v < cmd->n_dep_vars; ++v)
656 const union value **prev_vals = previous_value_alloc (iact);
660 tab_hline (t, TAL_1, 0, nc - 1, heading_rows + v * rows_per_var);
663 0, heading_rows + v * rows_per_var,
664 TAT_TITLE | TAB_LEFT,
665 var_to_string (cmd->dep_vars[v])
668 for (i = 0; i < n_cats; ++i)
670 const struct ccase *c =
671 categoricals_get_case_by_category_real (cmd->cats,
674 const struct exploratory_stats *ess =
675 categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, i);
677 const struct exploratory_stats *es = ess + v;
679 int diff_idx = previous_value_record (iact, c, prev_vals);
684 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
686 const struct variable *ivar = iact->vars[ivar_idx];
687 const union value *val = case_data (c, ivar);
689 if (( diff_idx != -1 && diff_idx <= ivar_idx)
693 ds_init_empty (&str);
694 append_value_name (ivar, val, &str);
698 heading_rows + v * rows_per_var + i * rows_per_cat,
699 TAT_TITLE | TAB_LEFT,
707 if ( diff_idx != -1 && diff_idx < iact->n_vars)
709 tab_hline (t, TAL_1, 1 + diff_idx, nc - 1,
710 heading_rows + v * rows_per_var + i * rows_per_cat
714 tab_text (t, heading_columns - 1,
715 heading_rows + v * rows_per_var + i * rows_per_cat,
716 TAT_TITLE | TAB_LEFT,
717 gettext (ptile_alg_desc [cmd->pc_alg]));
719 tukey_hinges_calculate (es->hinges, hinges);
721 for (p = 0; p < cmd->n_percentiles; ++p)
723 tab_double (t, heading_columns + p,
724 heading_rows + v * rows_per_var + i * rows_per_cat,
726 percentile_calculate (es->percentiles[p], cmd->pc_alg),
729 if (cmd->ptiles[p] == 25.0)
731 tab_double (t, heading_columns + p,
732 heading_rows + v * rows_per_var + i * rows_per_cat + 1,
737 else if (cmd->ptiles[p] == 50.0)
739 tab_double (t, heading_columns + p,
740 heading_rows + v * rows_per_var + i * rows_per_cat + 1,
745 else if (cmd->ptiles[p] == 75.0)
747 tab_double (t, heading_columns + p,
748 heading_rows + v * rows_per_var + i * rows_per_cat + 1,
756 tab_text (t, heading_columns - 1,
757 heading_rows + v * rows_per_var + i * rows_per_cat + 1,
758 TAT_TITLE | TAB_LEFT,
759 _("Tukey's Hinges"));
770 descriptives_report (const struct examine *cmd, int iact_idx)
772 const struct interaction *iact = cmd->iacts[iact_idx];
774 const int heading_columns = 1 + iact->n_vars + 2;
775 const int heading_rows = 1;
778 size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
780 const int rows_per_cat = 13;
781 const int rows_per_var = n_cats * rows_per_cat;
783 const int nr = heading_rows + cmd->n_dep_vars * rows_per_var;
784 const int nc = 2 + heading_columns;
786 t = tab_create (nc, nr);
787 tab_title (t, _("Descriptives"));
789 tab_headers (t, heading_columns, 0, heading_rows, 0);
791 /* Internal Vertical lines */
792 tab_box (t, -1, -1, -1, TAL_1,
793 heading_columns, 0, nc - 1, nr - 1);
796 tab_box (t, TAL_2, TAL_2, -1, -1,
797 0, 0, nc - 1, nr - 1);
799 tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
800 tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
803 tab_text (t, heading_columns, 0, TAB_CENTER | TAT_TITLE,
806 tab_text (t, heading_columns + 1, 0, TAB_CENTER | TAT_TITLE,
809 for (i = 0; i < iact->n_vars; ++i)
814 var_to_string (iact->vars[i])
818 for (v = 0; v < cmd->n_dep_vars; ++v)
820 const union value **prev_val = previous_value_alloc (iact);
824 tab_hline (t, TAL_1, 0, nc - 1, heading_rows + v * rows_per_var);
827 0, heading_rows + v * rows_per_var,
828 TAT_TITLE | TAB_LEFT,
829 var_to_string (cmd->dep_vars[v])
832 for (i = 0; i < n_cats; ++i)
834 const struct ccase *c =
835 categoricals_get_case_by_category_real (cmd->cats,
838 const struct exploratory_stats *ess =
839 categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, i);
841 const struct exploratory_stats *es = ess + v;
843 const int diff_idx = previous_value_record (iact, c, prev_val);
845 double m0, m1, m2, m3, m4;
848 moments_calculate (es->mom, &m0, &m1, &m2, &m3, &m4);
850 tval = gsl_cdf_tdist_Qinv ((1.0 - cmd->conf) / 2.0, m0 - 1.0);
852 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
854 const struct variable *ivar = iact->vars[ivar_idx];
855 const union value *val = case_data (c, ivar);
857 if (( diff_idx != -1 && diff_idx <= ivar_idx)
861 ds_init_empty (&str);
862 append_value_name (ivar, val, &str);
866 heading_rows + v * rows_per_var + i * rows_per_cat,
867 TAT_TITLE | TAB_LEFT,
875 if ( diff_idx != -1 && diff_idx < iact->n_vars)
877 tab_hline (t, TAL_1, 1 + diff_idx, nc - 1,
878 heading_rows + v * rows_per_var + i * rows_per_cat
884 heading_rows + v * rows_per_var + i * rows_per_cat,
890 1 + iact->n_vars + 2,
891 heading_rows + v * rows_per_var + i * rows_per_cat,
895 1 + iact->n_vars + 3,
896 heading_rows + v * rows_per_var + i * rows_per_cat,
897 0, calc_semean (m2, m0), 0);
901 heading_rows + v * rows_per_var + i * rows_per_cat + 1,
903 _("%g%% Confidence Interval for Mean"),
908 1 + iact->n_vars + 1,
909 heading_rows + v * rows_per_var + i * rows_per_cat + 1,
915 1 + iact->n_vars + 2,
916 heading_rows + v * rows_per_var + i * rows_per_cat + 1,
917 0, m1 - tval * calc_semean (m2, m0), 0);
921 1 + iact->n_vars + 1,
922 heading_rows + v * rows_per_var + i * rows_per_cat + 2,
928 1 + iact->n_vars + 2,
929 heading_rows + v * rows_per_var + i * rows_per_cat + 2,
930 0, m1 + tval * calc_semean (m2, m0), 0);
935 heading_rows + v * rows_per_var + i * rows_per_cat + 3,
941 1 + iact->n_vars + 2,
942 heading_rows + v * rows_per_var + i * rows_per_cat + 3,
944 trimmed_mean_calculate (es->trimmed_mean),
949 heading_rows + v * rows_per_var + i * rows_per_cat + 4,
955 1 + iact->n_vars + 2,
956 heading_rows + v * rows_per_var + i * rows_per_cat + 4,
958 percentile_calculate (es->quartiles[1], cmd->pc_alg),
964 heading_rows + v * rows_per_var + i * rows_per_cat + 5,
970 1 + iact->n_vars + 2,
971 heading_rows + v * rows_per_var + i * rows_per_cat + 5,
976 heading_rows + v * rows_per_var + i * rows_per_cat + 6,
982 1 + iact->n_vars + 2,
983 heading_rows + v * rows_per_var + i * rows_per_cat + 6,
988 heading_rows + v * rows_per_var + i * rows_per_cat + 7,
994 1 + iact->n_vars + 2,
995 heading_rows + v * rows_per_var + i * rows_per_cat + 7,
1002 heading_rows + v * rows_per_var + i * rows_per_cat + 8,
1008 1 + iact->n_vars + 2,
1009 heading_rows + v * rows_per_var + i * rows_per_cat + 8,
1016 heading_rows + v * rows_per_var + i * rows_per_cat + 9,
1022 1 + iact->n_vars + 2,
1023 heading_rows + v * rows_per_var + i * rows_per_cat + 9,
1025 es->maxima[0].val - es->minima[0].val,
1030 heading_rows + v * rows_per_var + i * rows_per_cat + 10,
1032 _("Interquartile Range")
1037 1 + iact->n_vars + 2,
1038 heading_rows + v * rows_per_var + i * rows_per_cat + 10,
1040 percentile_calculate (es->quartiles[2], cmd->pc_alg) -
1041 percentile_calculate (es->quartiles[0], cmd->pc_alg),
1049 heading_rows + v * rows_per_var + i * rows_per_cat + 11,
1055 1 + iact->n_vars + 2,
1056 heading_rows + v * rows_per_var + i * rows_per_cat + 11,
1060 1 + iact->n_vars + 3,
1061 heading_rows + v * rows_per_var + i * rows_per_cat + 11,
1062 0, calc_seskew (m0), 0);
1066 heading_rows + v * rows_per_var + i * rows_per_cat + 12,
1072 1 + iact->n_vars + 2,
1073 heading_rows + v * rows_per_var + i * rows_per_cat + 12,
1077 1 + iact->n_vars + 3,
1078 heading_rows + v * rows_per_var + i * rows_per_cat + 12,
1079 0, calc_sekurt (m0), 0);
1089 extremes_report (const struct examine *cmd, int iact_idx)
1091 const struct interaction *iact = cmd->iacts[iact_idx];
1093 const int heading_columns = 1 + iact->n_vars + 2;
1094 const int heading_rows = 1;
1095 struct tab_table *t;
1097 size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
1099 const int rows_per_cat = 2 * cmd->disp_extremes;
1100 const int rows_per_var = n_cats * rows_per_cat;
1102 const int nr = heading_rows + cmd->n_dep_vars * rows_per_var;
1103 const int nc = 2 + heading_columns;
1105 t = tab_create (nc, nr);
1106 tab_title (t, _("Extreme Values"));
1108 tab_headers (t, heading_columns, 0, heading_rows, 0);
1110 /* Internal Vertical lines */
1111 tab_box (t, -1, -1, -1, TAL_1,
1112 heading_columns, 0, nc - 1, nr - 1);
1114 /* External Frame */
1115 tab_box (t, TAL_2, TAL_2, -1, -1,
1116 0, 0, nc - 1, nr - 1);
1118 tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
1119 tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
1123 tab_text (t, heading_columns, 0, TAB_CENTER | TAT_TITLE,
1124 var_to_string (cmd->id_var));
1126 tab_text (t, heading_columns, 0, TAB_CENTER | TAT_TITLE,
1129 tab_text (t, heading_columns + 1, 0, TAB_CENTER | TAT_TITLE,
1132 for (i = 0; i < iact->n_vars; ++i)
1137 var_to_string (iact->vars[i])
1141 for (v = 0; v < cmd->n_dep_vars; ++v)
1143 const union value **prev_val = previous_value_alloc (iact);
1147 tab_hline (t, TAL_1, 0, nc - 1, heading_rows + v * rows_per_var);
1150 0, heading_rows + v * rows_per_var,
1152 var_to_string (cmd->dep_vars[v])
1155 for (i = 0; i < n_cats; ++i)
1158 const struct ccase *c =
1159 categoricals_get_case_by_category_real (cmd->cats, iact_idx, i);
1161 const struct exploratory_stats *ess =
1162 categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, i);
1164 const struct exploratory_stats *es = ess + v;
1166 int diff_idx = previous_value_record (iact, c, prev_val);
1168 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
1170 const struct variable *ivar = iact->vars[ivar_idx];
1171 const union value *val = case_data (c, ivar);
1173 if (( diff_idx != -1 && diff_idx <= ivar_idx)
1177 ds_init_empty (&str);
1178 append_value_name (ivar, val, &str);
1182 heading_rows + v * rows_per_var + i * rows_per_cat,
1183 TAT_TITLE | TAB_LEFT,
1191 if ( diff_idx != -1 && diff_idx < iact->n_vars)
1193 tab_hline (t, TAL_1, 1 + diff_idx, nc - 1,
1194 heading_rows + v * rows_per_var + i * rows_per_cat
1199 heading_columns - 2,
1200 heading_rows + v * rows_per_var + i * rows_per_cat,
1205 tab_hline (t, TAL_1, heading_columns - 2, nc - 1,
1206 heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes
1210 heading_columns - 2,
1211 heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes,
1215 for (e = 0 ; e < cmd->disp_extremes; ++e)
1218 heading_columns - 1,
1219 heading_rows + v * rows_per_var + i * rows_per_cat + e,
1224 /* The casenumber */
1228 heading_rows + v * rows_per_var + i * rows_per_cat + e,
1230 &es->maxima[e].identity,
1236 heading_rows + v * rows_per_var + i * rows_per_cat + e,
1238 es->maxima[e].identity.f,
1242 heading_columns + 1,
1243 heading_rows + v * rows_per_var + i * rows_per_cat + e,
1246 var_get_print_format (cmd->dep_vars[v]));
1250 heading_columns - 1,
1251 heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes + e,
1256 /* The casenumber */
1260 heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes + e,
1262 &es->minima[e].identity,
1268 heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes + e,
1270 es->minima[e].identity.f,
1274 heading_columns + 1,
1275 heading_rows + v * rows_per_var + i * rows_per_cat + cmd->disp_extremes + e,
1278 var_get_print_format (cmd->dep_vars[v]));
1289 summary_report (const struct examine *cmd, int iact_idx)
1291 const struct interaction *iact = cmd->iacts[iact_idx];
1293 const int heading_columns = 1 + iact->n_vars;
1294 const int heading_rows = 3;
1295 struct tab_table *t;
1297 const struct fmt_spec *wfmt = cmd->wv ? var_get_print_format (cmd->wv) : &F_8_0;
1299 size_t n_cats = categoricals_n_count (cmd->cats, iact_idx);
1301 const int nr = heading_rows + n_cats * cmd->n_dep_vars;
1302 const int nc = 6 + heading_columns;
1304 t = tab_create (nc, nr);
1305 tab_title (t, _("Case Processing Summary"));
1307 tab_headers (t, heading_columns, 0, heading_rows, 0);
1309 /* Internal Vertical lines */
1310 tab_box (t, -1, -1, -1, TAL_1,
1311 heading_columns, 0, nc - 1, nr - 1);
1313 /* External Frame */
1314 tab_box (t, TAL_2, TAL_2, -1, -1,
1315 0, 0, nc - 1, nr - 1);
1317 tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
1318 tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
1320 tab_joint_text (t, heading_columns, 0,
1321 nc - 1, 0, TAB_CENTER | TAT_TITLE, _("Cases"));
1324 heading_columns + 1, 1,
1325 TAB_CENTER | TAT_TITLE, _("Valid"));
1328 heading_columns + 2, 1,
1329 heading_columns + 3, 1,
1330 TAB_CENTER | TAT_TITLE, _("Missing"));
1333 heading_columns + 4, 1,
1334 heading_columns + 5, 1,
1335 TAB_CENTER | TAT_TITLE, _("Total"));
1337 for (i = 0; i < 3; ++i)
1339 tab_text (t, heading_columns + i * 2, 2, TAB_CENTER | TAT_TITLE,
1341 tab_text (t, heading_columns + i * 2 + 1, 2, TAB_CENTER | TAT_TITLE,
1345 for (i = 0; i < iact->n_vars; ++i)
1350 var_to_string (iact->vars[i])
1355 for (v = 0; v < cmd->n_dep_vars; ++v)
1358 const union value **prev_values = previous_value_alloc (iact);
1361 tab_hline (t, TAL_1, 0, nc - 1, heading_rows + v * n_cats);
1364 0, heading_rows + n_cats * v,
1366 var_to_string (cmd->dep_vars[v])
1370 for (i = 0; i < n_cats; ++i)
1373 const struct exploratory_stats *es;
1375 const struct ccase *c =
1376 categoricals_get_case_by_category_real (cmd->cats,
1380 int diff_idx = previous_value_record (iact, c, prev_values);
1382 if ( diff_idx != -1 && diff_idx < iact->n_vars - 1)
1383 tab_hline (t, TAL_1, 1 + diff_idx, nc - 1,
1384 heading_rows + n_cats * v + i );
1386 for (ivar_idx = 0; ivar_idx < iact->n_vars; ++ivar_idx)
1388 const struct variable *ivar = iact->vars[ivar_idx];
1389 const union value *val = case_data (c, ivar);
1391 if (( diff_idx != -1 && diff_idx <= ivar_idx)
1395 ds_init_empty (&str);
1396 append_value_name (ivar, val, &str);
1399 1 + ivar_idx, heading_rows + n_cats * v + i,
1400 TAT_TITLE | TAB_LEFT,
1410 es = categoricals_get_user_data_by_category_real (cmd->cats, iact_idx, i);
1413 total = es[v].missing + es[v].non_missing;
1415 heading_columns + 0,
1416 heading_rows + n_cats * v + i,
1423 heading_columns + 1,
1424 heading_rows + n_cats * v + i,
1427 100.0 * es[v].non_missing / total
1432 heading_columns + 2,
1433 heading_rows + n_cats * v + i,
1439 heading_columns + 3,
1440 heading_rows + n_cats * v + i,
1443 100.0 * es[v].missing / total
1446 heading_columns + 4,
1447 heading_rows + n_cats * v + i,
1452 /* This can only be 100% can't it? */
1454 heading_columns + 5,
1455 heading_rows + n_cats * v + i,
1458 100.0 * (es[v].missing + es[v].non_missing)/ total
1464 tab_hline (t, TAL_1, heading_columns, nc - 1, 1);
1465 tab_hline (t, TAL_1, heading_columns, nc - 1, 2);
1470 /* Attempt to parse an interaction from LEXER */
1471 static struct interaction *
1472 parse_interaction (struct lexer *lexer, struct examine *ex)
1474 const struct variable *v = NULL;
1475 struct interaction *iact = NULL;
1477 if ( lex_match_variable (lexer, ex->dict, &v))
1479 iact = interaction_create (v);
1481 while (lex_match (lexer, T_BY))
1483 if (!lex_match_variable (lexer, ex->dict, &v))
1485 interaction_destroy (iact);
1488 interaction_add_variable (iact, v);
1490 lex_match (lexer, T_COMMA);
1498 create_n (const void *aux1, void *aux2 UNUSED)
1502 const struct examine *examine = aux1;
1503 struct exploratory_stats *es = pool_calloc (examine->pool, examine->n_dep_vars, sizeof (*es));
1504 struct subcase ordering;
1505 subcase_init (&ordering, 0, 0, SC_ASCEND);
1507 for (v = 0; v < examine->n_dep_vars; v++)
1509 es[v].sorted_writer = sort_create_writer (&ordering, examine->ex_proto);
1510 es[v].sorted_reader = NULL;
1512 es[v].mom = moments_create (MOMENT_KURTOSIS);
1513 es[v].cmin = DBL_MAX;
1515 es[v].maximum = -DBL_MAX;
1516 es[v].minimum = DBL_MAX;
1519 subcase_destroy (&ordering);
1524 update_n (const void *aux1, void *aux2 UNUSED, void *user_data,
1525 const struct ccase *c, double weight)
1528 const struct examine *examine = aux1;
1529 struct exploratory_stats *es = user_data;
1531 for (v = 0; v < examine->n_dep_vars; v++)
1533 struct ccase *outcase ;
1534 const struct variable *var = examine->dep_vars[v];
1535 const double x = case_data (c, var)->f;
1537 if (var_is_value_missing (var, case_data (c, var), examine->dep_excl))
1539 es[v].missing += weight;
1543 outcase = case_create (examine->ex_proto);
1545 if (x > es[v].maximum)
1548 if (x < es[v].minimum)
1551 es[v].non_missing += weight;
1553 moments_pass_one (es[v].mom, x, weight);
1555 /* Save the value and the ID to the writer */
1556 assert (examine->id_idx != -1);
1557 case_data_rw_idx (outcase, EX_VAL)->f = x;
1558 value_copy (case_data_rw_idx (outcase, EX_ID),
1559 case_data_idx (c, examine->id_idx), examine->id_width);
1561 case_data_rw_idx (outcase, EX_WT)->f = weight;
1565 if (es[v].cmin > weight)
1566 es[v].cmin = weight;
1568 casewriter_write (es[v].sorted_writer, outcase);
1573 calculate_n (const void *aux1, void *aux2 UNUSED, void *user_data)
1576 const struct examine *examine = aux1;
1577 struct exploratory_stats *es = user_data;
1579 for (v = 0; v < examine->n_dep_vars; v++)
1582 casenumber imin = 0;
1584 struct casereader *reader;
1587 if (examine->histogramplot)
1590 double bin_width = fabs (es[v].minimum - es[v].maximum)
1591 / (1 + log2 (es[v].cc))
1595 histogram_create (bin_width, es[v].minimum, es[v].maximum);
1598 es[v].sorted_reader = casewriter_make_reader (es[v].sorted_writer);
1599 es[v].sorted_writer = NULL;
1601 imax = casereader_get_case_cnt (es[v].sorted_reader);
1603 es[v].maxima = pool_calloc (examine->pool, examine->calc_extremes, sizeof (*es[v].maxima));
1604 es[v].minima = pool_calloc (examine->pool, examine->calc_extremes, sizeof (*es[v].minima));
1605 for (i = 0; i < examine->calc_extremes; ++i)
1607 value_init_pool (examine->pool, &es[v].maxima[i].identity, examine->id_width) ;
1608 value_init_pool (examine->pool, &es[v].minima[i].identity, examine->id_width) ;
1611 for (reader = casereader_clone (es[v].sorted_reader);
1612 (c = casereader_read (reader)) != NULL; case_unref (c))
1614 const double val = case_data_idx (c, EX_VAL)->f;
1615 const double wt = case_data_idx (c, EX_WT)->f;
1617 moments_pass_two (es[v].mom, val, wt);
1619 if (es[v].histogram)
1620 histogram_add (es[v].histogram, val, wt);
1622 if (imin < examine->calc_extremes)
1625 for (x = imin; x < examine->calc_extremes; ++x)
1627 struct extremity *min = &es[v].minima[x];
1629 value_copy (&min->identity, case_data_idx (c, EX_ID), examine->id_width);
1635 if (imax < examine->calc_extremes)
1639 for (x = imax; x < imax + 1; ++x)
1641 struct extremity *max;
1643 if (x >= examine->calc_extremes)
1646 max = &es[v].maxima[x];
1648 value_copy (&max->identity, case_data_idx (c, EX_ID), examine->id_width);
1652 casereader_destroy (reader);
1654 if (examine->calc_extremes > 0)
1656 assert (es[v].minima[0].val == es[v].minimum);
1657 assert (es[v].maxima[0].val == es[v].maximum);
1661 const int n_os = 5 + examine->n_percentiles;
1662 struct order_stats **os ;
1663 es[v].percentiles = pool_calloc (examine->pool, examine->n_percentiles, sizeof (*es[v].percentiles));
1665 es[v].trimmed_mean = trimmed_mean_create (es[v].cc, 0.05);
1667 os = xcalloc (n_os, sizeof *os);
1668 os[0] = &es[v].trimmed_mean->parent;
1670 es[v].quartiles[0] = percentile_create (0.25, es[v].cc);
1671 es[v].quartiles[1] = percentile_create (0.5, es[v].cc);
1672 es[v].quartiles[2] = percentile_create (0.75, es[v].cc);
1674 os[1] = &es[v].quartiles[0]->parent;
1675 os[2] = &es[v].quartiles[1]->parent;
1676 os[3] = &es[v].quartiles[2]->parent;
1678 es[v].hinges = tukey_hinges_create (es[v].cc, es[v].cmin);
1679 os[4] = &es[v].hinges->parent;
1681 for (i = 0; i < examine->n_percentiles; ++i)
1683 es[v].percentiles[i] = percentile_create (examine->ptiles[i] / 100.00, es[v].cc);
1684 os[5 + i] = &es[v].percentiles[i]->parent;
1687 order_stats_accumulate_idx (os, n_os,
1688 casereader_clone (es[v].sorted_reader),
1694 if (examine->boxplot)
1696 struct order_stats *os;
1698 es[v].box_whisker = box_whisker_create (es[v].hinges,
1699 EX_ID, examine->id_var);
1701 os = &es[v].box_whisker->parent;
1702 order_stats_accumulate_idx (&os, 1,
1703 casereader_clone (es[v].sorted_reader),
1707 if (examine->npplot)
1709 double n, mean, var;
1710 struct order_stats *os;
1712 moments_calculate (es[v].mom, &n, &mean, &var, NULL, NULL);
1714 es[v].np = np_create (n, mean, var);
1716 os = &es[v].np->parent;
1718 order_stats_accumulate_idx (&os, 1,
1719 casereader_clone (es[v].sorted_reader),
1727 cleanup_exploratory_stats (struct examine *cmd)
1730 for (i = 0; i < cmd->n_iacts; ++i)
1733 const size_t n_cats = categoricals_n_count (cmd->cats, i);
1735 for (v = 0; v < cmd->n_dep_vars; ++v)
1738 for (grp = 0; grp < n_cats; ++grp)
1741 const struct exploratory_stats *es =
1742 categoricals_get_user_data_by_category_real (cmd->cats, i, grp);
1744 struct order_stats *os = &es[v].hinges->parent;
1745 struct statistic *stat = &os->parent;
1746 stat->destroy (stat);
1748 for (q = 0; q < 3 ; q++)
1750 os = &es[v].quartiles[q]->parent;
1752 stat->destroy (stat);
1755 for (q = 0; q < cmd->n_percentiles ; q++)
1757 os = &es[v].percentiles[q]->parent;
1759 stat->destroy (stat);
1762 os = &es[v].trimmed_mean->parent;
1764 stat->destroy (stat);
1766 os = &es[v].np->parent;
1770 stat->destroy (stat);
1773 statistic_destroy (&es[v].histogram->parent);
1774 moments_destroy (es[v].mom);
1776 casereader_destroy (es[v].sorted_reader);
1784 run_examine (struct examine *cmd, struct casereader *input)
1788 struct casereader *reader;
1790 struct payload payload;
1791 payload.create = create_n;
1792 payload.update = update_n;
1793 payload.calculate = calculate_n;
1794 payload.destroy = NULL;
1796 cmd->wv = dict_get_weight (cmd->dict);
1799 = categoricals_create (cmd->iacts, cmd->n_iacts,
1800 cmd->wv, cmd->dep_excl, cmd->fctr_excl);
1802 categoricals_set_payload (cmd->cats, &payload, cmd, NULL);
1804 if (cmd->id_var == NULL)
1806 struct ccase *c = casereader_peek (input, 0);
1808 cmd->id_idx = case_get_value_cnt (c);
1809 input = casereader_create_arithmetic_sequence (input, 1.0, 1.0);
1814 /* Remove cases on a listwise basis if requested */
1815 if ( cmd->missing_pw == false)
1816 input = casereader_create_filter_missing (input,
1823 for (reader = input;
1824 (c = casereader_read (reader)) != NULL; case_unref (c))
1826 categoricals_update (cmd->cats, c);
1828 casereader_destroy (reader);
1829 categoricals_done (cmd->cats);
1831 for (i = 0; i < cmd->n_iacts; ++i)
1833 summary_report (cmd, i);
1835 if (cmd->disp_extremes > 0)
1836 extremes_report (cmd, i);
1838 if (cmd->n_percentiles > 0)
1839 percentiles_report (cmd, i);
1843 switch (cmd->boxplot_mode)
1846 show_boxplot_grouped (cmd, i);
1849 show_boxplot_variabled (cmd, i);
1857 if (cmd->histogramplot)
1858 show_histogram (cmd, i);
1861 show_npplot (cmd, i);
1863 if (cmd->spreadlevelplot)
1864 show_spreadlevel (cmd, i);
1866 if (cmd->descriptives)
1867 descriptives_report (cmd, i);
1870 cleanup_exploratory_stats (cmd);
1871 categoricals_destroy (cmd->cats);
1876 cmd_examine (struct lexer *lexer, struct dataset *ds)
1879 bool nototals_seen = false;
1880 bool totals_seen = false;
1882 struct interaction **iacts_mem = NULL;
1883 struct examine examine;
1884 bool percentiles_seen = false;
1886 examine.missing_pw = false;
1887 examine.disp_extremes = 0;
1888 examine.calc_extremes = 0;
1889 examine.descriptives = false;
1890 examine.conf = 0.95;
1891 examine.pc_alg = PC_HAVERAGE;
1892 examine.ptiles = NULL;
1893 examine.n_percentiles = 0;
1894 examine.id_idx = -1;
1895 examine.id_width = 0;
1896 examine.id_var = NULL;
1897 examine.boxplot_mode = BP_GROUPS;
1899 examine.ex_proto = caseproto_create ();
1901 examine.pool = pool_create ();
1903 /* Allocate space for the first interaction.
1904 This is interaction is an empty one (for the totals).
1905 If no totals are requested, we will simply ignore this
1908 examine.n_iacts = 1;
1909 examine.iacts = iacts_mem = pool_zalloc (examine.pool, sizeof (struct interaction *));
1910 examine.iacts[0] = interaction_create (NULL);
1912 examine.dep_excl = MV_ANY;
1913 examine.fctr_excl = MV_ANY;
1914 examine.histogramplot = false;
1915 examine.npplot = false;
1916 examine.boxplot = false;
1917 examine.spreadlevelplot = false;
1918 examine.sl_power = 0;
1920 examine.dict = dataset_dict (ds);
1922 /* Accept an optional, completely pointless "/VARIABLES=" */
1923 lex_match (lexer, T_SLASH);
1924 if (lex_match_id (lexer, "VARIABLES"))
1926 if (! lex_force_match (lexer, T_EQUALS) )
1930 if (!parse_variables_const (lexer, examine.dict,
1931 &examine.dep_vars, &examine.n_dep_vars,
1932 PV_NO_DUPLICATE | PV_NUMERIC))
1935 if (lex_match (lexer, T_BY))
1937 struct interaction *iact = NULL;
1940 iact = parse_interaction (lexer, &examine);
1945 pool_nrealloc (examine.pool, iacts_mem,
1947 sizeof (*iacts_mem));
1949 iacts_mem[examine.n_iacts - 1] = iact;
1956 while (lex_token (lexer) != T_ENDCMD)
1958 lex_match (lexer, T_SLASH);
1960 if (lex_match_id (lexer, "STATISTICS"))
1962 lex_match (lexer, T_EQUALS);
1964 while (lex_token (lexer) != T_ENDCMD
1965 && lex_token (lexer) != T_SLASH)
1967 if (lex_match_id (lexer, "DESCRIPTIVES"))
1969 examine.descriptives = true;
1971 else if (lex_match_id (lexer, "EXTREME"))
1974 if (lex_match (lexer, T_LPAREN))
1976 extr = lex_integer (lexer);
1980 msg (MW, _("%s may not be negative. Using default value (%g)."), "EXTREME", 5.0);
1985 if (! lex_force_match (lexer, T_RPAREN))
1988 examine.disp_extremes = extr;
1990 else if (lex_match_id (lexer, "NONE"))
1993 else if (lex_match (lexer, T_ALL))
1995 if (examine.disp_extremes == 0)
1996 examine.disp_extremes = 5;
2000 lex_error (lexer, NULL);
2005 else if (lex_match_id (lexer, "PERCENTILES"))
2007 percentiles_seen = true;
2008 if (lex_match (lexer, T_LPAREN))
2010 while (lex_is_number (lexer))
2012 double p = lex_number (lexer);
2014 if ( p <= 0 || p >= 100.0)
2017 _("Percentiles must lie in the range (0, 100)"));
2021 examine.n_percentiles++;
2023 xrealloc (examine.ptiles,
2024 sizeof (*examine.ptiles) *
2025 examine.n_percentiles);
2027 examine.ptiles[examine.n_percentiles - 1] = p;
2030 lex_match (lexer, T_COMMA);
2032 if (!lex_force_match (lexer, T_RPAREN))
2036 lex_match (lexer, T_EQUALS);
2038 while (lex_token (lexer) != T_ENDCMD
2039 && lex_token (lexer) != T_SLASH)
2041 if (lex_match_id (lexer, "HAVERAGE"))
2043 examine.pc_alg = PC_HAVERAGE;
2045 else if (lex_match_id (lexer, "WAVERAGE"))
2047 examine.pc_alg = PC_WAVERAGE;
2049 else if (lex_match_id (lexer, "ROUND"))
2051 examine.pc_alg = PC_ROUND;
2053 else if (lex_match_id (lexer, "EMPIRICAL"))
2055 examine.pc_alg = PC_EMPIRICAL;
2057 else if (lex_match_id (lexer, "AEMPIRICAL"))
2059 examine.pc_alg = PC_AEMPIRICAL;
2061 else if (lex_match_id (lexer, "NONE"))
2063 examine.pc_alg = PC_NONE;
2067 lex_error (lexer, NULL);
2072 else if (lex_match_id (lexer, "TOTAL"))
2076 else if (lex_match_id (lexer, "NOTOTAL"))
2078 nototals_seen = true;
2080 else if (lex_match_id (lexer, "MISSING"))
2082 lex_match (lexer, T_EQUALS);
2084 while (lex_token (lexer) != T_ENDCMD
2085 && lex_token (lexer) != T_SLASH)
2087 if (lex_match_id (lexer, "LISTWISE"))
2089 examine.missing_pw = false;
2091 else if (lex_match_id (lexer, "PAIRWISE"))
2093 examine.missing_pw = true;
2095 else if (lex_match_id (lexer, "EXCLUDE"))
2097 examine.dep_excl = MV_ANY;
2099 else if (lex_match_id (lexer, "INCLUDE"))
2101 examine.dep_excl = MV_SYSTEM;
2103 else if (lex_match_id (lexer, "REPORT"))
2105 examine.fctr_excl = MV_NEVER;
2107 else if (lex_match_id (lexer, "NOREPORT"))
2109 examine.fctr_excl = MV_ANY;
2113 lex_error (lexer, NULL);
2118 else if (lex_match_id (lexer, "COMPARE"))
2120 lex_match (lexer, T_EQUALS);
2121 if (lex_match_id (lexer, "VARIABLES"))
2123 examine.boxplot_mode = BP_VARIABLES;
2125 else if (lex_match_id (lexer, "GROUPS"))
2127 examine.boxplot_mode = BP_GROUPS;
2131 lex_error (lexer, NULL);
2135 else if (lex_match_id (lexer, "PLOT"))
2137 lex_match (lexer, T_EQUALS);
2139 while (lex_token (lexer) != T_ENDCMD
2140 && lex_token (lexer) != T_SLASH)
2142 if (lex_match_id (lexer, "BOXPLOT"))
2144 examine.boxplot = true;
2146 else if (lex_match_id (lexer, "NPPLOT"))
2148 examine.npplot = true;
2150 else if (lex_match_id (lexer, "HISTOGRAM"))
2152 examine.histogramplot = true;
2154 else if (lex_match_id (lexer, "SPREADLEVEL"))
2156 examine.spreadlevelplot = true;
2157 examine.sl_power = 0;
2158 if (lex_match (lexer, T_LPAREN))
2160 examine.sl_power = lex_integer (lexer);
2163 if (! lex_force_match (lexer, T_RPAREN))
2167 else if (lex_match_id (lexer, "NONE"))
2169 examine.histogramplot = false;
2170 examine.npplot = false;
2171 examine.boxplot = false;
2173 else if (lex_match (lexer, T_ALL))
2175 examine.histogramplot = true;
2176 examine.npplot = true;
2177 examine.boxplot = true;
2181 lex_error (lexer, NULL);
2184 lex_match (lexer, T_COMMA);
2187 else if (lex_match_id (lexer, "CINTERVAL"))
2189 if ( !lex_force_num (lexer))
2192 examine.conf = lex_number (lexer);
2195 else if (lex_match_id (lexer, "ID"))
2197 lex_match (lexer, T_EQUALS);
2199 examine.id_var = parse_variable_const (lexer, examine.dict);
2203 lex_error (lexer, NULL);
2209 if ( totals_seen && nototals_seen)
2211 msg (SE, _("%s and %s are mutually exclusive"),"TOTAL","NOTOTAL");
2215 /* If totals have been requested or if there are no factors
2216 in this analysis, then the totals need to be included. */
2217 if ( !nototals_seen || examine.n_iacts == 1)
2219 examine.iacts = &iacts_mem[0];
2224 examine.iacts = &iacts_mem[1];
2225 interaction_destroy (iacts_mem[0]);
2229 if ( examine.id_var )
2231 examine.id_idx = var_get_case_index (examine.id_var);
2232 examine.id_width = var_get_width (examine.id_var);
2235 examine.ex_proto = caseproto_add_width (examine.ex_proto, 0); /* value */
2236 examine.ex_proto = caseproto_add_width (examine.ex_proto, examine.id_width); /* id */
2237 examine.ex_proto = caseproto_add_width (examine.ex_proto, 0); /* weight */
2240 if (examine.disp_extremes > 0)
2242 examine.calc_extremes = examine.disp_extremes;
2245 if (examine.descriptives && examine.calc_extremes == 0)
2247 /* Descriptives always displays the max and min */
2248 examine.calc_extremes = 1;
2251 if (percentiles_seen && examine.n_percentiles == 0)
2253 examine.n_percentiles = 7;
2254 examine.ptiles = xcalloc (examine.n_percentiles,
2255 sizeof (*examine.ptiles));
2257 examine.ptiles[0] = 5;
2258 examine.ptiles[1] = 10;
2259 examine.ptiles[2] = 25;
2260 examine.ptiles[3] = 50;
2261 examine.ptiles[4] = 75;
2262 examine.ptiles[5] = 90;
2263 examine.ptiles[6] = 95;
2266 assert (examine.calc_extremes >= examine.disp_extremes);
2268 struct casegrouper *grouper;
2269 struct casereader *group;
2272 grouper = casegrouper_create_splits (proc_open (ds), examine.dict);
2273 while (casegrouper_get_next_group (grouper, &group))
2274 run_examine (&examine, group);
2275 ok = casegrouper_destroy (grouper);
2276 ok = proc_commit (ds) && ok;
2279 caseproto_unref (examine.ex_proto);
2281 for (i = 0; i < examine.n_iacts; ++i)
2282 interaction_destroy (examine.iacts[i]);
2283 free (examine.ptiles);
2284 free (examine.dep_vars);
2285 pool_destroy (examine.pool);
2290 caseproto_unref (examine.ex_proto);
2291 examine.iacts = iacts_mem;
2292 for (i = 0; i < examine.n_iacts; ++i)
2293 interaction_destroy (examine.iacts[i]);
2294 free (examine.dep_vars);
2295 free (examine.ptiles);
2296 pool_destroy (examine.pool);