Remove variables assigned to but never used.

[pspp] / src / language / stats / quick-cluster.c

diff --git a/src/language/stats/quick-cluster.c b/src/language/stats/quick-cluster.c
index 9adcc64243a70c50539909304f758d09488a4020..bc66cce795caf06932ed3da6269b306bd0a6cd52 100644 (file)
--- a/src/language/stats/quick-cluster.c
+++ b/src/language/stats/quick-cluster.c
@@ -1,5 +1,5 @@
 /* PSPP - a program for statistical analysis.
-   Copyright (C) 2011 Free Software Foundation, Inc.
+   Copyright (C) 2011, 2012 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
@@ -46,6 +46,13 @@
 #define _(msgid) gettext (msgid)
 #define N_(msgid) msgid
 
+enum missing_type
+  {
+    MISS_LISTWISE,
+    MISS_PAIRWISE,
+  };
+
+
 struct qc
 {
   const struct variable **vars;
@@ -55,6 +62,9 @@ struct qc
   int maxiter;                 /* Maximum iterations (Given by the user) */
 
   const struct variable *wv;   /* Weighting variable. */
+
+  enum missing_type missing_type;
+  enum mv_class exclude;
 };
 
 /* Holds all of the information for the functions.  int n, holds the number of
@@ -174,18 +184,18 @@ static int
 kmeans_get_nearest_group (struct Kmeans *kmeans, struct ccase *c, const struct qc *qc)
 {
   int result = -1;
-  double x;
   int i, j;
-  double dist;
-  double mindist;
-  mindist = INFINITY;
+  double mindist = INFINITY;
   for (i = 0; i < qc->ngroups; i++)
     {
-      dist = 0;
+      double dist = 0;
       for (j = 0; j < qc->n_vars; j++)
        {
-         x = case_data (c, qc->vars[j])->f;
-         dist += pow2 (gsl_matrix_get (kmeans->centers, i, j) - x);
+         const union value *val = case_data (c, qc->vars[j]);
+         if ( var_is_value_missing (qc->vars[j], val, qc->exclude))
+           continue;
+
+         dist += pow2 (gsl_matrix_get (kmeans->centers, i, j) - val->f);
        }
       if (dist < mindist)
        {
@@ -200,28 +210,28 @@ kmeans_get_nearest_group (struct Kmeans *kmeans, struct ccase *c, const struct q
 static void
 kmeans_recalculate_centers (struct Kmeans *kmeans, const struct casereader *reader, const struct qc *qc)
 {
-  casenumber i;
+  casenumber i = 0;
   int v, j;
-  double x, curval;
   struct ccase *c;
-  struct ccase *c_index;
-  struct casereader *cs;
-  struct casereader *cs_index;
-  int index;
 
-  i = 0;
-  cs = casereader_clone (reader);
-  cs_index = casereader_clone (kmeans->index_rdr);
+  struct casereader *cs = casereader_clone (reader);
+  struct casereader *cs_index = casereader_clone (kmeans->index_rdr);
 
   gsl_matrix_set_all (kmeans->centers, 0.0);
   for (; (c = casereader_read (cs)) != NULL; case_unref (c))
     {
       double weight = qc->wv ? case_data (c, qc->wv)->f : 1.0;
-      c_index = casereader_read (cs_index);
-      index = case_data_idx (c_index, 0)->f;
+      struct ccase *c_index = casereader_read (cs_index);
+      int index = case_data_idx (c_index, 0)->f;
       for (v = 0; v < qc->n_vars; ++v)
        {
-         x = case_data (c, qc->vars[v])->f * weight;
+         const union value *val = case_data (c, qc->vars[v]);
+         double x = val->f * weight;
+         double curval;
+
+         if ( var_is_value_missing (qc->vars[v], val, qc->exclude))
+           continue;
+
          curval = gsl_matrix_get (kmeans->centers, index, v);
          gsl_matrix_set (kmeans->centers, index, v, curval + x);
        }
@@ -279,6 +289,7 @@ kmeans_calculate_indexes_and_check_convergence (struct Kmeans *kmeans, const str
       struct ccase *index_case_new = case_create (kmeans->proto);
       int bestindex = kmeans_get_nearest_group (kmeans, c, qc);
       double weight = qc->wv ? case_data (c, qc->wv)->f : 1.0;
+      assert (bestindex < kmeans->num_elements_groups->size);
       kmeans->num_elements_groups->data[bestindex] += weight;
       if (kmeans->index_rdr)
        {
@@ -379,11 +390,10 @@ static void
 quick_cluster_show_centers (struct Kmeans *kmeans, bool initial, const struct qc *qc)
 {
   struct tab_table *t;
-  int nc, nr, heading_columns, currow;
+  int nc, nr, currow;
   int i, j;
   nc = qc->ngroups + 1;
   nr = qc->n_vars + 4;
-  heading_columns = 1;
   t = tab_create (nc, nr);
   tab_headers (t, 0, nc - 1, 0, 1);
   currow = 0;
@@ -487,6 +497,8 @@ cmd_quick_cluster (struct lexer *lexer, struct dataset *ds)
   const struct dictionary *dict = dataset_dict (ds);
   qc.ngroups = 2;
   qc.maxiter = 2;
+  qc.missing_type = MISS_LISTWISE;
+  qc.exclude = MV_ANY;
 
   if (!parse_variables_const (lexer, dict, &qc.vars, &qc.n_vars,
                              PV_NO_DUPLICATE | PV_NUMERIC))
@@ -494,9 +506,37 @@ cmd_quick_cluster (struct lexer *lexer, struct dataset *ds)
       return (CMD_FAILURE);
     }
 
-  if (lex_match (lexer, T_SLASH))
+  while (lex_token (lexer) != T_ENDCMD)
     {
-      if (lex_match_id (lexer, "CRITERIA"))
+      lex_match (lexer, T_SLASH);
+
+      if (lex_match_id (lexer, "MISSING"))
+       {
+         lex_match (lexer, T_EQUALS);
+         while (lex_token (lexer) != T_ENDCMD
+                && lex_token (lexer) != T_SLASH)
+           {
+             if (lex_match_id (lexer, "LISTWISE") || lex_match_id (lexer, "DEFAULT"))
+               {
+                 qc.missing_type = MISS_LISTWISE;
+               }
+             else if (lex_match_id (lexer, "PAIRWISE"))
+               {
+                 qc.missing_type = MISS_PAIRWISE;
+               }
+             else if (lex_match_id (lexer, "INCLUDE"))
+               {
+                 qc.exclude = MV_SYSTEM;
+               }
+             else if (lex_match_id (lexer, "EXCLUDE"))
+               {
+                 qc.exclude = MV_ANY;
+               }
+             else
+               goto error;
+           }     
+       }
+      else if (lex_match_id (lexer, "CRITERIA"))
        {
          lex_match (lexer, T_EQUALS);
          while (lex_token (lexer) != T_ENDCMD
@@ -536,6 +576,13 @@ cmd_quick_cluster (struct lexer *lexer, struct dataset *ds)
 
     while (casegrouper_get_next_group (grouper, &group))
       {
+       if ( qc.missing_type == MISS_LISTWISE )
+         {
+           group  = casereader_create_filter_missing (group, qc.vars, qc.n_vars,
+                                                    qc.exclude,
+                                                    NULL,  NULL);
+         }
+
        kmeans = kmeans_create (&qc);
        kmeans_cluster (kmeans, group, &qc);
        quick_cluster_show_results (kmeans, &qc);