partial fix of bug 19819

[pspp-builds.git] / src / language / stats / regression.q

diff --git a/src/language/stats/regression.q b/src/language/stats/regression.q
index 7baaef9109f9a1a66a71c82e687c828deaa3df16..37b3b48dd214444468d92ae31070123b70bde5f8 100644 (file)
--- a/src/language/stats/regression.q
+++ b/src/language/stats/regression.q
@@ -27,7 +27,6 @@
 #include "regression-export.h"
 #include <data/case.h>
 #include <data/casefile.h>
-#include <data/cat-routines.h>
 #include <data/category.h>
 #include <data/dictionary.h>
 #include <data/missing-values.h>
@@ -565,7 +564,7 @@ regression_trns_pred_proc (void *t_, struct ccase *c,
   pspp_linreg_cache *model;
   union value *output = NULL;
   const union value **vals = NULL;
-  struct variable **vars = NULL;
+  const struct variable **vars = NULL;
 
   assert (trns != NULL);
   model = trns->c;
@@ -605,7 +604,7 @@ regression_trns_resid_proc (void *t_, struct ccase *c,
   union value *output = NULL;
   const union value **vals = NULL;
   const union value *obs = NULL;
-  struct variable **vars = NULL;
+  const struct variable **vars = NULL;
 
   assert (trns != NULL);
   model = trns->c;
@@ -790,7 +789,7 @@ reg_print_categorical_encoding (FILE * fp, pspp_linreg_cache * c)
 
       for (j = 0; j < n_categories; j++)
        {
-         union value *val = cat_subscript_to_value (j, varlist[i]);
+         const union value *val = cat_subscript_to_value (j, varlist[i]);
          fprintf (fp, "%s.values[%d] = \"%s\";\n\t",
                   var_get_name (varlist[i]), j,
                   var_get_value_name (varlist[i], val));
@@ -1067,7 +1066,7 @@ get_n_indep (const struct variable *v)
        }
       i++;
     }
-  return result;
+  return (result == 0) ? 1 : result;
 }
 
 /*
@@ -1088,13 +1087,18 @@ prepare_data (int n_data, int is_missing_case[],
   j = 0;
   for (i = 0; i < n_variables; i++)
     {
-      if (!is_depvar (i, depvar))
+      /*
+       The second condition ensures the program will run even if
+       there is only one variable to act as both explanatory and
+       response.
+       */
+      if ((!is_depvar (i, depvar)) || (n_variables == 1))
        {
          indep_vars[j] = v_variables[i];
          j++;
          if (var_is_alpha (v_variables[i]))
            {
-             /* Make a place to hold the binary vectors 
+             /* Make a place to hold the binary vectors
                 corresponding to this variable's values. */
              cat_stored_values_create (v_variables[i]);
            }
@@ -1222,12 +1226,12 @@ run_regression (const struct ccase *first,
       n_data = prepare_data (n_cases, is_missing_case, indep_vars,
                             cmd.v_dependent[k],
                             (const struct casefile *) cf, mom);
-      if (n_data > 0)
+      if ((n_data > 0) && (n_indep > 0))
        {
          Y = gsl_vector_alloc (n_data);
-         
          X =
-           design_matrix_create (n_indep, (const struct variable **) indep_vars,
+           design_matrix_create (n_indep,
+                                 (const struct variable **) indep_vars,
                                  n_data);
          for (i = 0; i < X->m->size2; i++)
            {
@@ -1238,16 +1242,16 @@ run_regression (const struct ccase *first,
          models[k]->indep_std = gsl_vector_alloc (X->m->size2);
          models[k]->depvar = (const struct variable *) cmd.v_dependent[k];
          /*
-           For large data sets, use QR decomposition.
-         */
+            For large data sets, use QR decomposition.
+          */
          if (n_data > sqrt (n_indep) && n_data > REG_LARGE_DATA)
            {
              models[k]->method = PSPP_LINREG_SVD;
            }
-         
+
          /*
-           The second pass fills the design matrix.
-         */
+            The second pass fills the design matrix.
+          */
          row = 0;
          for (r = casefile_get_reader (cf, NULL); casereader_read (r, &c);
               case_destroy (&c))
@@ -1259,28 +1263,29 @@ run_regression (const struct ccase *first,
                  for (i = 0; i < n_variables; ++i)     /* Iterate over the
                                                           variables for the
                                                           current case.
-                                                       */
+                                                        */
                    {
                      val = case_data (&c, v_variables[i]);
                      /*
-                       Independent/dependent variable separation. The
-                       'variables' subcommand specifies a varlist which contains
-                       both dependent and independent variables. The dependent
-                       variables are specified with the 'dependent'
-                       subcommand, and maybe also in the 'variables' subcommand. 
-                       We need to separate the two.
-                     */
+                        Independent/dependent variable separation. The
+                        'variables' subcommand specifies a varlist which contains
+                        both dependent and independent variables. The dependent
+                        variables are specified with the 'dependent'
+                        subcommand, and maybe also in the 'variables' subcommand. 
+                        We need to separate the two.
+                      */
                      if (!is_depvar (i, cmd.v_dependent[k]))
                        {
                          if (var_is_alpha (v_variables[i]))
                            {
                              design_matrix_set_categorical (X, row,
-                                                            v_variables[i], val);
+                                                            v_variables[i],
+                                                            val);
                            }
                          else
                            {
-                             design_matrix_set_numeric (X, row, v_variables[i],
-                                                        val);
+                             design_matrix_set_numeric (X, row,
+                                                        v_variables[i], val);
                            }
                        }
                    }
@@ -1290,20 +1295,20 @@ run_regression (const struct ccase *first,
                }
            }
          /*
-           Now that we know the number of coefficients, allocate space
-           and store pointers to the variables that correspond to the
-           coefficients.
-         */
+            Now that we know the number of coefficients, allocate space
+            and store pointers to the variables that correspond to the
+            coefficients.
+          */
          coeff_init (models[k], X);
-         
+
          /* 
             Find the least-squares estimates and other statistics.
-         */
+          */
          pspp_linreg ((const gsl_vector *) Y, X->m, &lopts, models[k]);
          compute_moments (models[k], mom, X, n_variables);
          subcommand_statistics (cmd.a_statistics, models[k]);
          subcommand_export (cmd.sbc_export, models[k]);
-         
+
          gsl_vector_free (Y);
          design_matrix_destroy (X);
          free (indep_vars);