Fixing local predictions when no input_fields are defined

bigml/ensemble.py

@@ -131,6 +131,7 @@ def __init__(self, ensemble,
         self.importance = {}
         query_string = ONLY_MODEL
         no_check_fields = False
+        self.input_fields = []
         if isinstance(ensemble, list):
             if all([isinstance(model, Model) for model in ensemble]):
                 models = ensemble
@@ -144,6 +145,7 @@ def __init__(self, ensemble,
                     raise ValueError('Failed to verify the list of models.'
                                      ' Check your model id values: %s' %
                                      str(exc))
+
         else:
             ensemble = self.get_ensemble_resource(ensemble)
             self.resource_id = get_ensemble_id(ensemble)
@@ -166,7 +168,7 @@ def __init__(self, ensemble,
                 self.objective_id = ensemble['object'].get("objective_field")
                 query_string = EXCLUDE_FIELDS
                 no_check_fields = True
-        self.input_fields = ensemble['object'].get('input_fields')
+            self.input_fields = ensemble['object'].get('input_fields')
 
         number_of_models = len(models)
         if max_models is None:

bigml/modelfields.py

@@ -154,8 +154,14 @@ def __init__(self, fields, objective_id=None, data_locale=None,
                 self.inverted_fields = invert_dictionary(fields)
                 self.fields = {}
                 self.fields.update(fields)
-                if not self.input_fields:
-                    self.input_fields = self.fields.keys()
+                if not (hasattr(self, "input_fields") and self.input_fields):
+                    self.input_fields = [field_id for field_id, field in \
+                        sorted( \
+                        [(field_id, field) for field_id,
+                         field in self.fields.items()],
+                        key=lambda(x): x[1].get("column_number"))
+                        if not self.objective_id or
+                        field_id != self.objective_id]
                 self.model_fields = {}
                 self.model_fields.update(
                     dict([(field_id, field) for field_id, field in \