Merge pull request #104 from AllenNeuralDynamics/han_softwarename_to_stimulus_epochs

add querying "dynamic-foraging-task" from stimulus_epochs

Author: hanhou

code/util/fetch_data_docDB.py

@@ -114,15 +114,19 @@ def fetch_dynamic_foraging_data(client):
     # let's directly query the software name
     logger.warning("fetching 'dynamic foraging' in software name...")
     software_name_results = client.retrieve_docdb_records(
-        filter_query={"session.data_streams.software.name": "dynamic-foraging-task",
-                      "name": {"$not": {"$regex": ".*processed.*"}}, # only raw data
-                      },
-        paginate_batch_size=500
-    )              
+        filter_query={
+            "$or": [
+                {"session.data_streams.software.name": "dynamic-foraging-task"},
+                {"session.stimulus_epochs.software.name": "dynamic-foraging-task"},
+            ],
+            "name": {"$not": {"$regex": ".*processed.*"}},  # only raw data
+        },
+        paginate_batch_size=500,
+    )
     logger.warning(f"found {len(software_name_results)} results")
 
-    # there are more from the past that didn't specify modality correctly. 
-    # until this is fixed, need to guess by asset name 
+    # there are more from the past that didn't specify modality correctly.
+    # until this is fixed, need to guess by asset name
     logger.warning("fetching FIP records by name...")
     name_FIP_results = client.retrieve_docdb_records(
         filter_query={"name": {"$regex": "^FIP.*"}},
@@ -134,32 +138,32 @@ def fetch_dynamic_foraging_data(client):
     unique_results_by_id = {**{ r['_id']: r for r in software_name_results }, **{ r['_id']: r for r in name_FIP_results }}
     results = list(unique_results_by_id.values())
     logger.warning(f"found {len(results)} unique results")
-        
+
     # make a dataframe
     records_df = pd.DataFrame.from_records([map_record_to_dict(d) for d in results ])
-    
+
     # PREVIOUSLY, there are some sessions uploaded twice in two different locations.
     # let's filter out the ones in aind-ophys-data, a deprecated location
-    # this is no longer a problem-- so I'm taking off the drop but keeping the dupe check on. 
+    # this is no longer a problem-- so I'm taking off the drop but keeping the dupe check on.
     dup_df = records_df[records_df.duplicated('session_name',keep=False)]
     dup_df = dup_df[dup_df.session_loc.str.contains("aind-ophys-data")]
     if len(dup_df):
         logger.warning('duplicated entries found, please fix')
     # records_df = records_df.drop(dup_df.index.values)
-    
+
     # let's get processed results too
     logger.warning("fetching processed results...")
     processed_results = client.retrieve_docdb_records(filter_query={
         "name": {"$regex": "^behavior_.*processed_.*"}
     }) 
-    
+
     # converting to a dictionary
     processed_results_by_name = { r['name']: r for r in processed_results }  
-        
+
     # adding two columns to our master dataframe - result name and result s3 location
     records_df['processed_session_name'] = records_df.session_name.apply(lambda x: find_result(x, processed_results_by_name).get('name'))
     records_df['processed_session_loc'] = records_df.session_name.apply(lambda x: find_result(x, processed_results_by_name).get('location'))
-    # get external_links, strip it down to the string 
+    # get external_links, strip it down to the string
     co_data_asset_id_processed = records_df.session_name.apply(lambda x: find_result(x, processed_results_by_name).get('external_links'))
     records_df['processed_CO_dataID'] = strip_dict_for_id(co_data_asset_id_processed)
     records_df['CO_dataID'] = strip_dict_for_id(records_df['CO_dataID'])