X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Flanguage%2Fstats%2Fregression.q;h=41a23f3e2580ebd9a9aac6ff289b89803c6f8da2;hb=bd17d2af982332ee1791998361b1ac6731fe14fa;hp=32ac1815ea95c42d471ba3a4c280469a14a36113;hpb=f5d9f9911bd04682a7edfb48521a12202e561e0a;p=pspp-builds.git

diff --git a/src/language/stats/regression.q b/src/language/stats/regression.q
index 32ac1815..41a23f3e 100644
--- a/src/language/stats/regression.q
+++ b/src/language/stats/regression.q
@@ -150,7 +150,7 @@ reg_stats_r (pspp_linreg_cache * c)
   adjrsq = 1.0 - (1.0 - rsq) * (c->n_obs - 1.0) / (c->n_obs - c->n_indeps);
   std_error = sqrt (pspp_linreg_mse (c));
   t = tab_create (n_cols, n_rows, 0);
-  tab_dim (t, tab_natural_dimensions);
+  tab_dim (t, tab_natural_dimensions, NULL);
   tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1);
   tab_hline (t, TAL_2, 0, n_cols - 1, 1);
   tab_vline (t, TAL_2, 2, 0, n_rows - 1);
@@ -193,7 +193,7 @@ reg_stats_coeff (pspp_linreg_cache * c)
 
   t = tab_create (n_cols, n_rows, 0);
   tab_headers (t, 2, 0, 1, 0);
-  tab_dim (t, tab_natural_dimensions);
+  tab_dim (t, tab_natural_dimensions, NULL);
   tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1);
   tab_hline (t, TAL_2, 0, n_cols - 1, 1);
   tab_vline (t, TAL_2, 2, 0, n_rows - 1);
@@ -290,7 +290,7 @@ reg_stats_anova (pspp_linreg_cache * c)
   assert (c != NULL);
   t = tab_create (n_cols, n_rows, 0);
   tab_headers (t, 2, 0, 1, 0);
-  tab_dim (t, tab_natural_dimensions);
+  tab_dim (t, tab_natural_dimensions, NULL);
 
   tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1);
 
@@ -315,9 +315,9 @@ reg_stats_anova (pspp_linreg_cache * c)
 
 
   /* Degrees of freedom */
-  tab_text (t, 3, 1, TAB_RIGHT | TAT_PRINTF, "%g", c->dfm);
-  tab_text (t, 3, 2, TAB_RIGHT | TAT_PRINTF, "%g", c->dfe);
-  tab_text (t, 3, 3, TAB_RIGHT | TAT_PRINTF, "%g", c->dft);
+  tab_text_format (t, 3, 1, TAB_RIGHT, "%g", c->dfm);
+  tab_text_format (t, 3, 2, TAB_RIGHT, "%g", c->dfe);
+  tab_text_format (t, 3, 3, TAB_RIGHT, "%g", c->dft);
 
   /* Mean Squares */
   tab_double (t, 4, 1, TAB_RIGHT, msm, NULL);
@@ -381,7 +381,7 @@ reg_stats_bcov (pspp_linreg_cache * c)
   n_rows = 2 * (c->n_indeps + 1);
   t = tab_create (n_cols, n_rows, 0);
   tab_headers (t, 2, 0, 1, 0);
-  tab_dim (t, tab_natural_dimensions);
+  tab_dim (t, tab_natural_dimensions, NULL);
   tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1);
   tab_hline (t, TAL_2, 0, n_cols - 1, 1);
   tab_vline (t, TAL_2, 2, 0, n_rows - 1);
@@ -542,7 +542,7 @@ regression_trns_free (void *t_)
   Gets the predicted values.
  */
 static int
-regression_trns_pred_proc (void *t_, struct ccase *c,
+regression_trns_pred_proc (void *t_, struct ccase **c,
 			   casenumber case_idx UNUSED)
 {
   size_t i;
@@ -563,12 +563,12 @@ regression_trns_pred_proc (void *t_, struct ccase *c,
   n_vals = (*model->get_vars) (model, vars);
 
   vals = xnmalloc (n_vals, sizeof (*vals));
-  output = case_data_rw (c, model->pred);
-  assert (output != NULL);
+  *c = case_unshare (*c);
+  output = case_data_rw (*c, model->pred);
 
   for (i = 0; i < n_vals; i++)
     {
-      vals[i] = case_data (c, vars[i]);
+      vals[i] = case_data (*c, vars[i]);
     }
   output->f = (*model->predict) ((const struct variable **) vars,
 				 vals, model, n_vals);
@@ -581,7 +581,7 @@ regression_trns_pred_proc (void *t_, struct ccase *c,
   Gets the residuals.
  */
 static int
-regression_trns_resid_proc (void *t_, struct ccase *c,
+regression_trns_resid_proc (void *t_, struct ccase **c,
 			    casenumber case_idx UNUSED)
 {
   size_t i;
@@ -603,14 +603,15 @@ regression_trns_resid_proc (void *t_, struct ccase *c,
   n_vals = (*model->get_vars) (model, vars);
 
   vals = xnmalloc (n_vals, sizeof (*vals));
-  output = case_data_rw (c, model->resid);
+  *c = case_unshare (*c);
+  output = case_data_rw (*c, model->resid);
   assert (output != NULL);
 
   for (i = 0; i < n_vals; i++)
     {
-      vals[i] = case_data (c, vars[i]);
+      vals[i] = case_data (*c, vars[i]);
     }
-  obs = case_data (c, model->depvar);
+  obs = case_data (*c, model->depvar);
   output->f = (*model->residual) ((const struct variable **) vars,
 				  vals, obs, model, n_vals);
   free (vals);
@@ -688,17 +689,21 @@ subcommand_save (struct dataset *ds, int save, pspp_linreg_cache ** models)
 
       for (lc = models; lc < models + cmd.n_dependent; lc++)
 	{
-	  assert (*lc != NULL);
-	  assert ((*lc)->depvar != NULL);
-	  if (cmd.a_save[REGRESSION_SV_RESID])
-	    {
-	      reg_save_var (ds, "RES", regression_trns_resid_proc, *lc,
-			    &(*lc)->resid, n_trns);
-	    }
-	  if (cmd.a_save[REGRESSION_SV_PRED])
+	  if (*lc != NULL)
 	    {
-	      reg_save_var (ds, "PRED", regression_trns_pred_proc, *lc,
-			    &(*lc)->pred, n_trns);
+	      if ((*lc)->depvar != NULL)
+		{
+		  if (cmd.a_save[REGRESSION_SV_RESID])
+		    {
+		      reg_save_var (ds, "RES", regression_trns_resid_proc, *lc,
+				    &(*lc)->resid, n_trns);
+		    }
+		  if (cmd.a_save[REGRESSION_SV_PRED])
+		    {
+		      reg_save_var (ds, "PRED", regression_trns_pred_proc, *lc,
+				    &(*lc)->pred, n_trns);
+		    }
+		}
 	    }
 	}
     }
@@ -821,7 +826,7 @@ prepare_categories (struct casereader *input,
 		    struct moments_var *mom)
 {
   int n_data;
-  struct ccase c;
+  struct ccase *c;
   size_t i;
 
   assert (vars != NULL);
@@ -832,7 +837,7 @@ prepare_categories (struct casereader *input,
       cat_stored_values_create (vars[i]);
 
   n_data = 0;
-  for (; casereader_read (input, &c); case_destroy (&c))
+  for (; (c = casereader_read (input)) != NULL; case_unref (c))
     {
       /*
          The second condition ensures the program will run even if
@@ -841,7 +846,7 @@ prepare_categories (struct casereader *input,
        */
       for (i = 0; i < n_vars; i++)
 	{
-	  const union value *val = case_data (&c, vars[i]);
+	  const union value *val = case_data (c, vars[i]);
 	  if (var_is_alpha (vars[i]))
 	    cat_value_update (vars[i], val);
 	  else
@@ -861,39 +866,6 @@ coeff_init (pspp_linreg_cache * c, struct design_matrix *dm)
   pspp_coeff_init (c->coeff, dm);
 }
 
-/*
-  Put the moments in the linreg cache.
- */
-static void
-compute_moments (pspp_linreg_cache * c, struct moments_var *mom,
-		 struct design_matrix *dm, size_t n)
-{
-  size_t i;
-  size_t j;
-  double weight;
-  double mean;
-  double variance;
-  double skewness;
-  double kurtosis;
-  /*
-     Scan the variable names in the columns of the design matrix.
-     When we find the variable we need, insert its mean in the cache.
-   */
-  for (i = 0; i < dm->m->size2; i++)
-    {
-      for (j = 0; j < n; j++)
-	{
-	  if (design_matrix_col_to_var (dm, i) == (mom + j)->v)
-	    {
-	      moments1_calculate ((mom + j)->m, &weight, &mean, &variance,
-				  &skewness, &kurtosis);
-	      pspp_linreg_set_indep_variable_mean (c, (mom + j)->v, mean);
-	      pspp_linreg_set_indep_variable_sd (c, (mom + j)->v, sqrt (variance));
-	    }
-	}
-    }
-}
-
 static bool
 run_regression (struct casereader *input, struct cmd_regression *cmd,
 		struct dataset *ds, pspp_linreg_cache **models)
@@ -901,7 +873,7 @@ run_regression (struct casereader *input, struct cmd_regression *cmd,
   size_t i;
   int n_indep = 0;
   int k;
-  struct ccase c;
+  struct ccase *c;
   const struct variable **indep_vars;
   struct design_matrix *X;
   struct moments_var *mom;
@@ -911,13 +883,14 @@ run_regression (struct casereader *input, struct cmd_regression *cmd,
 
   assert (models != NULL);
 
-  if (!casereader_peek (input, 0, &c))
+  c = casereader_peek (input, 0);
+  if (c == NULL)
     {
       casereader_destroy (input);
       return true;
     }
-  output_split_file_values (ds, &c);
-  case_destroy (&c);
+  output_split_file_values (ds, c);
+  case_unref (c);
 
   if (!v_variables)
     {
@@ -949,16 +922,16 @@ run_regression (struct casereader *input, struct cmd_regression *cmd,
       const struct variable *dep_var;
       struct casereader *reader;
       casenumber row;
-      struct ccase c;
+      struct ccase *c;
       size_t n_data;		/* Number of valid cases. */
 
       dep_var = cmd->v_dependent[k];
       n_indep = identify_indep_vars (indep_vars, dep_var);
       reader = casereader_clone (input);
       reader = casereader_create_filter_missing (reader, indep_vars, n_indep,
-						 MV_ANY, NULL);
+						 MV_ANY, NULL, NULL);
       reader = casereader_create_filter_missing (reader, &dep_var, 1,
-						 MV_ANY, NULL);
+						 MV_ANY, NULL, NULL);
       n_data = prepare_categories (casereader_clone (reader),
 				   indep_vars, n_indep, mom);
 
@@ -974,7 +947,8 @@ run_regression (struct casereader *input, struct cmd_regression *cmd,
 	    {
 	      lopts.get_indep_mean_std[i] = 1;
 	    }
-	  models[k] = pspp_linreg_cache_alloc (X->m->size1, X->m->size2);
+	  models[k] = pspp_linreg_cache_alloc (dep_var, (const struct variable **) indep_vars,
+					       X->m->size1, n_indep);
 	  models[k]->depvar = dep_var;
 	  /*
 	     For large data sets, use QR decomposition.
@@ -988,18 +962,18 @@ run_regression (struct casereader *input, struct cmd_regression *cmd,
 	     The second pass fills the design matrix.
 	   */
 	  reader = casereader_create_counter (reader, &row, -1);
-	  for (; casereader_read (reader, &c); case_destroy (&c))
+	  for (; (c = casereader_read (reader)) != NULL; case_unref (c))
 	    {
 	      for (i = 0; i < n_indep; ++i)
 		{
 		  const struct variable *v = indep_vars[i];
-		  const union value *val = case_data (&c, v);
+		  const union value *val = case_data (c, v);
 		  if (var_is_alpha (v))
 		    design_matrix_set_categorical (X, row, v, val);
 		  else
 		    design_matrix_set_numeric (X, row, v, val);
 		}
-	      gsl_vector_set (Y, row, case_num (&c, dep_var));
+	      gsl_vector_set (Y, row, case_num (c, dep_var));
 	    }
 	  /*
 	     Now that we know the number of coefficients, allocate space