Fix linting on failing files updated in previous commit.

Add .flake8 config file.

.flake8

@@ -0,0 +1,2 @@
+[flake8]
+extend-ignore = E203

allensdk/brain_observatory/behavior/behavior_project_cache/project_apis/data_io/behavior_neuropixels_project_cloud_api.py

@@ -6,27 +6,28 @@
 from allensdk.brain_observatory.behavior.behavior_session import (
     BehaviorSession,
 )
+from allensdk.brain_observatory.ecephys._probe import ProbeWithLFPMeta
 from allensdk.brain_observatory.ecephys.behavior_ecephys_session import (
     BehaviorEcephysSession,
 )
-from allensdk.brain_observatory.ecephys._probe import ProbeWithLFPMeta
 from allensdk.core.dataframe_utils import (
     enforce_df_int_typing,
-    return_one_dataframe_row_only
+    return_one_dataframe_row_only,
 )
 
 INTEGER_COLUMNS = [
-    "prior_exposures_to_image_set", "ecephys_session_id", "unit_count",
-    "probe_count", "channel_count"
+    "prior_exposures_to_image_set",
+    "ecephys_session_id",
+    "unit_count",
+    "probe_count",
+    "channel_count",
 ]
 
 
 class VisualBehaviorNeuropixelsProjectCloudApi(ProjectCloudApiBase):
-
     MANIFEST_COMPATIBILITY = ["0.1.0", "10.0.0"]
 
     def _load_manifest_tables(self):
-
         self._get_ecephys_session_table()
         self._get_behavior_session_table()
         self._get_unit_table()
@@ -56,7 +57,7 @@ def get_behavior_session(
         row = return_one_dataframe_row_only(
             input_table=self._behavior_session_table,
             index_value=behavior_session_id,
-            table_name="behavior_session_table"
+            table_name="behavior_session_table",
         )
         row = row.squeeze()
         ecephys_session_id = row.ecephys_session_id
@@ -68,7 +69,7 @@ def get_behavior_session(
             row = return_one_dataframe_row_only(
                 input_table=self._ecephys_session_table,
                 index_value=ecephys_session_id,
-                table_name="ecephys_session_table"
+                table_name="ecephys_session_table",
             )
 
         file_id = str(int(row[self.cache.file_id_column]))
@@ -79,7 +80,6 @@ def get_behavior_session(
     def get_ecephys_session(
         self, ecephys_session_id: int
     ) -> BehaviorEcephysSession:
-
         """get a BehaviorEcephysSession by specifying ecephys_session_id
 
         Parameters
@@ -95,7 +95,7 @@ def get_ecephys_session(
         session_meta = return_one_dataframe_row_only(
             input_table=self._ecephys_session_table,
             index_value=ecephys_session_id,
-            table_name="ecephys_session_table"
+            table_name="ecephys_session_table",
         )
         probes_meta = self._probe_table[
             (self._probe_table["ecephys_session_id"] == ecephys_session_id)
@@ -122,10 +122,9 @@ def f():
             probe_meta = {
                 p.name: ProbeWithLFPMeta(
                     lfp_csd_filepath=make_lazy_load_filepath_function(
-                        file_id=str(int(getattr(
-                            p, self.cache.file_id_column)))
-                        ),
-                    lfp_sampling_rate=p.lfp_sampling_rate
+                        file_id=str(int(getattr(p, self.cache.file_id_column)))
+                    ),
+                    lfp_sampling_rate=p.lfp_sampling_rate,
                 )
                 for p in probes_meta.itertuples(index=False)
             }

allensdk/brain_observatory/behavior/behavior_project_cache/project_apis/data_io/behavior_project_cloud_api.py

@@ -13,17 +13,23 @@
 from allensdk.brain_observatory.behavior.behavior_session import (
     BehaviorSession,
 )
-from allensdk.core.utilities import literal_col_eval
 from allensdk.core.dataframe_utils import (
     enforce_df_int_typing,
-    return_one_dataframe_row_only
+    return_one_dataframe_row_only,
 )
+from allensdk.core.utilities import literal_col_eval
 
 COL_EVAL_LIST = ["ophys_experiment_id", "ophys_container_id", "driver_line"]
-INTEGER_COLUMNS = ["session_number", "prior_exposures_to_image_set",
-                   "ophys_session_id", "imaging_plane_group_count",
-                   "imaging_plane_group", "targeted_areas",
-                   "num_depths_per_area", "num_targeted_structures"]
+INTEGER_COLUMNS = [
+    "session_number",
+    "prior_exposures_to_image_set",
+    "ophys_session_id",
+    "imaging_plane_group_count",
+    "imaging_plane_group",
+    "targeted_areas",
+    "num_depths_per_area",
+    "num_targeted_structures",
+]
 
 
 def sanitize_data_columns(
@@ -107,17 +113,19 @@ def get_behavior_session(
         row = return_one_dataframe_row_only(
             input_table=self._behavior_session_table,
             index_value=behavior_session_id,
-            table_name="behavior_session_table"
+            table_name="behavior_session_table",
         )
         row = row.squeeze()
-        has_file_id = (not pd.isna(row[self.cache.file_id_column])
-                       and row[self.cache.file_id_column] > 0)
+        has_file_id = (
+            not pd.isna(row[self.cache.file_id_column])
+            and row[self.cache.file_id_column] > 0
+        )
         if not has_file_id:
             oeid = row.ophys_experiment_id[0]
             row = return_one_dataframe_row_only(
                 input_table=self._ophys_experiment_table,
                 index_value=oeid,
-                table_name="ophys_experiment_table"
+                table_name="ophys_experiment_table",
             )
         file_id = str(int(row[self.cache.file_id_column]))
         data_path = self._get_data_path(file_id=file_id)
@@ -141,8 +149,7 @@ def get_behavior_ophys_experiment(
         row = return_one_dataframe_row_only(
             input_table=self._ophys_experiment_table,
             index_value=ophys_experiment_id,
-            table_name="ophys_experiment_table"
-
+            table_name="ophys_experiment_table",
         )
         file_id = str(int(row[self.cache.file_id_column]))
         data_path = self._get_data_path(file_id=file_id)

allensdk/brain_observatory/behavior/behavior_project_cache/tables/util/prior_exposure_processing.py

@@ -171,6 +171,7 @@ def __get_prior_exposure_count(
     elif agg_method == "cumsum":
         df["to"] = to
         df_index_name = df.index.name
+
         def cumsum(x):
             return x.cumsum().shift(fill_value=0).astype("int64")
 
@@ -184,8 +185,7 @@ def cumsum(x):
     return counts.reindex(index)
 
 
-def add_experience_level_ophys(
-        input_df: pd.DataFrame) -> pd.DataFrame:
+def add_experience_level_ophys(input_df: pd.DataFrame) -> pd.DataFrame:
     """
     adds a column to ophys tables that contains a string
     indicating whether a session had exposure level of Familiar,
@@ -210,36 +210,34 @@ def add_experience_level_ophys(
 
     # do not modify in place
     table = input_df.copy(deep=True)
-    session_number = 'session_number' \
-        if 'session_number' in table.columns else 'session'
+    session_number = (
+        "session_number" if "session_number" in table.columns else "session"
+    )
 
     # add experience_level column with strings indicating relevant conditions
-    table['experience_level'] = 'None'
+    table["experience_level"] = "None"
 
-    session_training = table.session_type.str.startswith('TRAINING')
+    session_training = table.session_type.str.startswith("TRAINING")
     train_indices = table[session_training].index.values
-    table.loc[train_indices, 'experience_level'] = 'Training'
+    table.loc[train_indices, "experience_level"] = "Training"
 
     session_0123 = table[session_number].isin([0, 1, 2, 3])
     familiar_indices = table[session_0123].index.values
 
-    table.loc[familiar_indices, 'experience_level'] = 'Familiar'
+    table.loc[familiar_indices, "experience_level"] = "Familiar"
 
     session_456 = table[session_number].isin([4, 5, 6])
-    zero_prior_exp = (table.prior_exposures_to_image_set == 0)
+    zero_prior_exp = table.prior_exposures_to_image_set == 0
 
-    novel_indices = table[session_456
-                          & zero_prior_exp].index.values
+    novel_indices = table[session_456 & zero_prior_exp].index.values
 
-    table.loc[novel_indices, 'experience_level'] = 'Novel 1'
+    table.loc[novel_indices, "experience_level"] = "Novel 1"
 
     session_456 = table[session_number].isin([4, 5, 6])
-    nonzero_prior_exp = (table.prior_exposures_to_image_set != 0)
-    novel_gt_1_indices = table[
-                             session_456
-                             & nonzero_prior_exp].index.values
+    nonzero_prior_exp = table.prior_exposures_to_image_set != 0
+    novel_gt_1_indices = table[session_456 & nonzero_prior_exp].index.values
 
-    table.loc[novel_gt_1_indices, 'experience_level'] = 'Novel >1'
+    table.loc[novel_gt_1_indices, "experience_level"] = "Novel >1"
 
     return table