lexer: New functions for parsing real numbers in specified ranges.

[pspp] / src / language / stats / logistic.c

diff --git a/src/language/stats/logistic.c b/src/language/stats/logistic.c
index 66a4111c7f88a54dea4671f4f104f119e16ba062..75f1d2a13fb4f6a439fb0a6e4428b3cc3a45cec1 100644 (file)
--- a/src/language/stats/logistic.c
+++ b/src/language/stats/logistic.c
@@ -227,7 +227,7 @@ predictor_value (const struct ccase *c,
 {
   /* Values of the scalar predictor variables */
   if (index < n_x)
-    return case_data (c, x[index])->f;
+    return case_num (c, x[index]);
 
   /* Coded values of categorical predictor variables (or interactions) */
   if (cats && index - n_x  < categoricals_df_total (cats))
@@ -242,7 +242,7 @@ predictor_value (const struct ccase *c,
 
 
 /*
-  Return the probability beta_hat (that is the estimator logit(y) )
+  Return the probability beta_hat (that is the estimator logit(y))
   corresponding to the coefficient estimator for case C
 */
 static double
@@ -321,7 +321,7 @@ hessian (const struct lr_spec *cmd,
     }
   casereader_destroy (reader);
 
-  if ( max_w < cmd->min_epsilon)
+  if (max_w < cmd->min_epsilon)
     {
       *converged = true;
       msg (MN, _("All predicted values are either 1 or 0"));
@@ -418,7 +418,7 @@ frq_update  (const void *aux1 UNUSED, void *aux2 UNUSED,
 }
 
 static void
-frq_destroy (const void *aux1 UNUSED, void *aux2 UNUSED, void *user_data UNUSED)
+frq_destroy (const void *aux1 UNUSED, void *aux2 UNUSED, void *user_data)
 {
   free (user_data);
 }
@@ -478,7 +478,7 @@ initial_pass (const struct lr_spec *cmd, struct lr_result *res, struct casereade
       double weight = dict_get_case_weight (cmd->dict, c, &res->warn_bad_weight);
       const union value *depval = case_data (c, cmd->dep_var);
 
-      if (var_is_value_missing (cmd->dep_var, depval, cmd->exclude))
+      if (var_is_value_missing (cmd->dep_var, depval) & cmd->exclude)
        {
          missing = true;
        }
@@ -486,7 +486,7 @@ initial_pass (const struct lr_spec *cmd, struct lr_result *res, struct casereade
       for (v = 0; v < cmd->n_indep_vars; ++v)
        {
          const union value *val = case_data (c, cmd->indep_vars[v]);
-         if (var_is_value_missing (cmd->indep_vars[v], val, cmd->exclude))
+         if (var_is_value_missing (cmd->indep_vars[v], val) & cmd->exclude)
            {
              missing = true;
              break;
@@ -509,7 +509,7 @@ initial_pass (const struct lr_spec *cmd, struct lr_result *res, struct casereade
        }
       else if (!v1set)
        {
-         if ( !value_equal (&res->y0, depval, width))
+         if (!value_equal (&res->y0, depval, width))
            {
              value_clone (&res->y1, depval, width);
              v1set = true;
@@ -520,7 +520,7 @@ initial_pass (const struct lr_spec *cmd, struct lr_result *res, struct casereade
          if (! value_equal (&res->y0, depval, width)
              &&
              ! value_equal (&res->y1, depval, width)
-             )
+       )
            {
              msg (ME, _("Dependent variable's values are not dichotomous."));
               case_unref (c);
@@ -640,7 +640,7 @@ run_lr (const struct lr_spec *cmd, struct casereader *input,
   work.hessian = gsl_matrix_calloc (work.beta_hat->size, work.beta_hat->size);
 
   /* Start the Newton Raphson iteration process... */
-  for( i = 0 ; i < cmd->max_iter ; ++i)
+  for(i = 0 ; i < cmd->max_iter ; ++i)
     {
       double min, max;
       gsl_vector *v ;
@@ -669,7 +669,7 @@ run_lr (const struct lr_spec *cmd, struct casereader *input,
 
        gsl_vector_minmax (delta, &min, &max);
 
-       if ( fabs (min) < cmd->bcon && fabs (max) < cmd->bcon)
+       if (fabs (min) < cmd->bcon && fabs (max) < cmd->bcon)
          {
            msg (MN, _("Estimation terminated at iteration number %d because parameter estimates changed by less than %g"),
                 i + 1, cmd->bcon);
@@ -697,8 +697,8 @@ run_lr (const struct lr_spec *cmd, struct casereader *input,
 
 
 
-  if ( ! converged)
-    msg (MW, _("Estimation terminated at iteration number %d because maximum iterations has been reached"), i );
+  if (! converged)
+    msg (MW, _("Estimation terminated at iteration number %d because maximum iterations has been reached"), i);
 
 
   output_model_summary (&work, initial_log_likelihood, log_likelihood);
@@ -883,7 +883,7 @@ cmd_logistic (struct lexer *lexer, struct dataset *ds)
                        }
                      lr.confidence = lex_number (lexer);
                      lex_get (lexer);
-                     if ( ! lex_force_match (lexer, T_RPAREN))
+                     if (! lex_force_match (lexer, T_RPAREN))
                        {
                          lex_error (lexer, NULL);
                          goto error;
@@ -917,7 +917,7 @@ cmd_logistic (struct lexer *lexer, struct dataset *ds)
                        }
                      lr.bcon = lex_number (lexer);
                      lex_get (lexer);
-                     if ( ! lex_force_match (lexer, T_RPAREN))
+                     if (! lex_force_match (lexer, T_RPAREN))
                        {
                          lex_error (lexer, NULL);
                          goto error;
@@ -928,14 +928,14 @@ cmd_logistic (struct lexer *lexer, struct dataset *ds)
                {
                  if (lex_force_match (lexer, T_LPAREN))
                    {
-                     if (! lex_force_int (lexer))
+                     if (! lex_force_int_range (lexer, "ITERATE", 0, INT_MAX))
                        {
                          lex_error (lexer, NULL);
                          goto error;
                        }
                      lr.max_iter = lex_integer (lexer);
                      lex_get (lexer);
-                     if ( ! lex_force_match (lexer, T_RPAREN))
+                     if (! lex_force_match (lexer, T_RPAREN))
                        {
                          lex_error (lexer, NULL);
                          goto error;
@@ -953,7 +953,7 @@ cmd_logistic (struct lexer *lexer, struct dataset *ds)
                        }
                      lr.lcon = lex_number (lexer);
                      lex_get (lexer);
-                     if ( ! lex_force_match (lexer, T_RPAREN))
+                     if (! lex_force_match (lexer, T_RPAREN))
                        {
                          lex_error (lexer, NULL);
                          goto error;
@@ -971,7 +971,7 @@ cmd_logistic (struct lexer *lexer, struct dataset *ds)
                        }
                      lr.min_epsilon = lex_number (lexer);
                      lex_get (lexer);
-                     if ( ! lex_force_match (lexer, T_RPAREN))
+                     if (! lex_force_match (lexer, T_RPAREN))
                        {
                          lex_error (lexer, NULL);
                          goto error;
@@ -982,20 +982,13 @@ cmd_logistic (struct lexer *lexer, struct dataset *ds)
                {
                  if (lex_force_match (lexer, T_LPAREN))
                    {
-                     if (! lex_force_num (lexer))
-                       {
-                         lex_error (lexer, NULL);
-                         goto error;
-                       }
+                      if (!lex_force_num_range_closed (lexer, "CUT", 0, 1))
+                        goto error;
+
                      cp = lex_number (lexer);
 
-                     if (cp < 0 || cp > 1.0)
-                       {
-                         msg (ME, _("Cut point value must be in the range [0,1]"));
-                         goto error;
-                       }
                      lex_get (lexer);
-                     if ( ! lex_force_match (lexer, T_RPAREN))
+                     if (! lex_force_match (lexer, T_RPAREN))
                        {
                          lex_error (lexer, NULL);
                          goto error;
@@ -1312,7 +1305,7 @@ output_model_summary (const struct lr_result *res,
   double entries[] = {
     -2 * log_likelihood,
     cox,
-    cox / ( 1.0 - exp(initial_log_likelihood * (2 / res->cc)))
+    cox / (1.0 - exp(initial_log_likelihood * (2 / res->cc)))
   };
   for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
     pivot_table_put2 (table, i, 0, pivot_value_new_number (entries[i]));