--- a/dataset.py	Thu May 22 19:08:46 2008 -0400
+++ b/dataset.py	Fri May 23 12:22:54 2008 -0400
@@ -245,8 +245,7 @@
             if n_batches is not None:
                 ds_nbatches = min(n_batches,ds_nbatches)
             if fieldnames:
-                if not dataset.hasFields(*fieldnames):
-                    raise ValueError('field not present', fieldnames)
+                assert dataset.hasFields(*fieldnames)
             else:
                 self.fieldnames=dataset.fieldNames()
             self.iterator = self.dataset.minibatches_nowrap(self.fieldnames,self.minibatch_size,
@@ -970,16 +969,7 @@
         for fieldname, fieldcolumns in self.fields_columns.items():
             if type(fieldcolumns) is int:
                 assert fieldcolumns>=0 and fieldcolumns<data_array.shape[1]
-
-                if 0:
-                    #I changed this because it didn't make sense to me,
-                    # and it made it more difficult to write my learner.
-                    # If it breaks stuff, let's talk about it.
-                    # - James 22/05/2008
-                    self.fields_columns[fieldname]=[fieldcolumns]
-                else:
-                    self.fields_columns[fieldname]=fieldcolumns
-
+                self.fields_columns[fieldname]=[fieldcolumns]
             elif type(fieldcolumns) is slice:
                 start,step=None,None
                 if not fieldcolumns.start: