REGRESSION: Implement /ORIGIN subcommand.

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

diff --git a/src/language/stats/factor.c b/src/language/stats/factor.c
index ae42d406a6d9b17cead82e7cb2276e978c3ffda3..c1ce93aaec3fbbcce445875187862b6e4e607a37 100644 (file)
--- a/src/language/stats/factor.c
+++ b/src/language/stats/factor.c
@@ -1005,7 +1005,7 @@ iterate_factor_matrix (const gsl_matrix *r, gsl_vector *communalities, gsl_matri
 
 static bool run_factor (struct dataset *ds, const struct cmd_factor *factor);
 
-static void do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata);
+static bool do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata);
 
 
 
@@ -1467,6 +1467,12 @@ cmd_factor (struct lexer *lexer, struct dataset *ds)
   if (factor.n_vars < 2)
     msg (MW, _("Factor analysis on a single variable is not useful."));
 
+  if (factor.n_vars < 1)
+    {
+      msg (ME, _("Factor analysis without variables is not possible."));
+      goto error;
+    }
+
   if (matrix_reader)
     {
       struct idata *id = idata_alloc (factor.n_vars);
@@ -1554,14 +1560,14 @@ the_communality (const gsl_matrix *evec, const gsl_vector *eval, int n, int n_fa
 
 /* Return the communality of variable N, calculated to N_FACTORS */
 static double
-communality (struct idata *idata, int n, int n_factors)
+communality (const struct idata *idata, int n, int n_factors)
 {
   return the_communality (idata->evec, idata->eval, n, n_factors);
 }
 
 
 static void
-show_scree (const struct cmd_factor *f, struct idata *idata)
+show_scree (const struct cmd_factor *f, const struct idata *idata)
 {
   struct scree *s;
   const char *label ;
@@ -1646,7 +1652,7 @@ show_communalities (const struct cmd_factor * factor,
 
 
 static void
-show_factor_matrix (const struct cmd_factor *factor, struct idata *idata, const char *title, const gsl_matrix *fm)
+show_factor_matrix (const struct cmd_factor *factor, const struct idata *idata, const char *title, const gsl_matrix *fm)
 {
   int i;
 
@@ -1739,7 +1745,8 @@ show_factor_matrix (const struct cmd_factor *factor, struct idata *idata, const
 
 
 static void
-show_explained_variance (const struct cmd_factor * factor, struct idata *idata,
+show_explained_variance (const struct cmd_factor * factor,
+                        const struct idata *idata,
                         const gsl_vector *initial_eigenvalues,
                         const gsl_vector *extracted_eigenvalues,
                         const gsl_vector *rotated_loadings)
@@ -2190,7 +2197,7 @@ do_factor (const struct cmd_factor *factor, struct casereader *r)
   struct idata *idata = idata_alloc (factor->n_vars);
 
   idata->cvm = covariance_1pass_create (factor->n_vars, factor->vars,
-                                             factor->wv, factor->exclude);
+                                       factor->wv, factor->exclude, true);
 
   for ( ; (c = casereader_read (r) ); case_unref (c))
     {
@@ -2220,9 +2227,15 @@ do_factor (const struct cmd_factor *factor, struct casereader *r)
   casereader_destroy (r);
 }
 
-static void
+static bool
 do_factor_by_matrix (const struct cmd_factor *factor, struct idata *idata)
 {
+  if (!idata->mm.cov && !idata->mm.corr)
+    {
+      msg (ME, _("The dataset has no complete covariance or correlation matrix."));
+      return false;
+    }
+
   if (idata->mm.cov && !idata->mm.corr)
     idata->mm.corr = correlation_from_covariance (idata->mm.cov, idata->mm.var_matrix);
   if (idata->mm.corr && !idata->mm.cov)