debugging optimizer

da/tools/pipeline.py

@@ -160,10 +160,13 @@ def SampleState(DaCycle,Samples,StateVector, ObservationOperator):
 
         msg     = header+".....Ensemble Kalman Filter at lag %d"% (int(lag)+1,)           ; logging.info(msg) 
 
+        if lag>0: print StateVector.EnsembleMembers[0][0].ModelSample.Data.getvalues('obs')
+
         StateVector = SampleOneCycle(DaCycle,Samples,StateVector, ObservationOperator,lag)
 
         print StateVector.EnsembleMembers[0][0].ModelSample.Data.getvalues('obs')
 
+
     # Optionally, post-processing of the model output can be added that deals for instance with
     # sub-sampling of time series, vertical averaging, etc.