working timeseries

cyclus · Aug 5, 2019 · 79989af · 79989af
1 parent 5ba8b3c
commit 79989af
Showing 1 changed file with 24 additions and 7 deletions.
diff --git a/cymetric/metrics.py b/cymetric/metrics.py
@@ -409,7 +409,7 @@ def annual_electricity_generated_by_agent(elec):
 del _egdeps, _egschema
 
 # Usage
-_egdeps = ['Metadata', 'TimeList', 'AgentEntry']
+_egdeps = ['Metadata', 'TimeList', 'AgentEntry', 'TimeSeriesPower', 'TimeSeriesEnrichmentSWU', 'TimeSeriesThroughput']
 
 _egschema = [
     ('SimId', ts.UUID),
@@ -420,14 +420,14 @@ def annual_electricity_generated_by_agent(elec):
     ]
 
 @metric(name='Usage', depends=_egdeps, schema=_egschema)
-def usage_by_agent(metadata, time, agents_entry):
+def usage_by_agent(metadata, time, agents_entry, power, SWU, throughput_ts):
     """
     """
 
     deployment = metadata[ metadata['Type'] == "deployment" ]
     decom = metadata[ metadata['Type'] == "decommission" ]
     timestep = metadata[ metadata['Type'] == "timestep" ]
-    throughput = metadata[ metadata['Type'] == "throughput" ]
+    throughput_meta = metadata[ metadata['Type'] == "throughput" ]
 
 
     # Deployement
@@ -441,10 +441,11 @@ def usage_by_agent(metadata, time, agents_entry):
                                         'Keyword': _tmp.Keyword, 
                                         'Value':_tmp.Value.astype(float)}, 
                                   columns=['SimId', 'AgentId', 'Time', 'Keyword', 'Value'])
-
+    rtn = deployment_use.copy() 
 
     # Decommision
     decom_agent = agents_entry[agents_entry['AgentId'].isin(decom['AgentId'])]
+    decom_agent = decom_agent.reset_index(drop=True)
     decom_agent['ExitTime'] = decom_agent['EnterTime'] + decom_agent['Lifetime']
     _tmp = pd.merge(decom[['SimId', 'AgentId','Keyword', 'Value']], decom_agent, on=['SimId', 'AgentId'])
     decom_use = pd.DataFrame(data={'SimId': _tmp.SimId, 
@@ -453,9 +454,11 @@ def usage_by_agent(metadata, time, agents_entry):
                                    'Keyword': _tmp.Keyword, 
                                    'Value':_tmp.Value.astype(float)}, 
                              columns=['SimId', 'AgentId', 'Time', 'Keyword', 'Value'])
-
+    rtn = pd.concat([rtn, decom_use], ignore_index=True)
+
     # TimeStep
     timestep_agent = agents_entry[agents_entry['AgentId'].isin(timestep['AgentId'])]
+    timestep_agent = timestep_agent.reset_index(drop=True)
     timestep_agent['ExitTime'] = timestep_agent['EnterTime'] + timestep_agent['Lifetime']
     timestep_tmp = pd.DataFrame(data={'SimId': _tmp.SimId, 
                                       'AgentId': _tmp.AgentId, 
@@ -473,9 +476,23 @@ def usage_by_agent(metadata, time, agents_entry):
                           row['Keyword'],
                           row['Value']))
     timestep_use = pd.DataFrame(time_step_data, columns=['SimId', 'AgentId', 'Time', 'Keyword', 'Value'])
-
-    rtn = pd.concat([deployment_use, decom_use, timestep_use], ignore_index=True)
+    rtn = pd.concat([rtn, timestep_use], ignore_index=True) 
 
+    def get_throughput_timeseries(throughput_df, throughput_meta):
+        if throughput_df is not None:
+            _tmp = pd.merge(throughput_meta[['SimId', 'AgentId','Keyword', 'Value']], throughput_df, on=['SimId', 'AgentId'])
+            _tmp['Value_y'] = _tmp.Value_x.astype(float)*_tmp.Value_y
+            _tmp.drop(columns=['Value_x'], inplace=True)
+            _tmp.rename(columns={"Value_y": "Value"}, inplace=True)
+            return _tmp
+        else:
+            return pd.DataFrame()
+
+    rtn = pd.concat([rtn, get_throughput_timeseries(power, throughput_meta)], ignore_index=True)
+    rtn = pd.concat([rtn, get_throughput_timeseries(SWU, throughput_meta)], ignore_index=True)
+    rtn = pd.concat([rtn, get_throughput_timeseries(throughput_ts, throughput_meta)], ignore_index=True)
+
+
     return rtn
 
 del _egdeps, _egschema