Fix some error handling

grade.py

@@ -56,7 +56,8 @@ def grade(grader_data,grader_config,submission,sandbox=None):
 
     #Try to determine confidence level
     try:
-        min_score=min(grader_data['score'])
+        min_score=min(numpy.asarray(grader_data['score']))
+        log.debug(grader_data['score'])
         raw_confidence=grader_data['model'].predict_proba(grader_feats)[0,(results['score']-min_score)]
         #TODO: Normalize confidence somehow here
         results['confidence']=raw_confidence

model_creator.py

@@ -94,8 +94,11 @@ def get_cv_error(clf,feats,scores):
         results['mae']=err
         results['kappa']=kappa
         results['success']=True
+    except ValueError:
+        #If this is hit, everything is fine.  It is hard to explain why the error occurs, but it isn't a big deal.
+        log.exception("Not enough classes (0,1,etc) in each cross validation fold.")
     except:
-        log.debug("Error getting cv error estimates.")
+        log.exception("Error getting cv error estimates.")
 
     return results