diff --git a/src/aind_dynamic_foraging_basic_analysis/metrics/trial_metrics.py b/src/aind_dynamic_foraging_basic_analysis/metrics/trial_metrics.py
index ee29713..2dfdd41 100644
--- a/src/aind_dynamic_foraging_basic_analysis/metrics/trial_metrics.py
+++ b/src/aind_dynamic_foraging_basic_analysis/metrics/trial_metrics.py
@@ -16,6 +16,7 @@
 
 LEFT, RIGHT, IGNORE = 0, 1, 2
 
+
 def compute_trial_metrics(nwb):
     """
     Computes trial by trial metrics
@@ -41,7 +42,6 @@ def compute_trial_metrics(nwb):
 
     df_trials = nwb.df_trials.copy()
 
-
     # --- Add reward-related columns ---
     df_trials["reward"] = False
     df_trials.loc[
@@ -147,7 +147,6 @@ def compute_trial_metrics(nwb):
                     df_trials.loc[i, "n_valid_licks_right"] = 0
                     df_trials.loc[i, "n_valid_licks_all"] = 0
 
-
     df_trials["RESPONDED"] = [x in [0, 1] for x in df_trials["animal_response"].values]
     # Rolling fraction of goCues with a response
     df_trials["response_rate"] = (
@@ -191,7 +190,6 @@ def compute_trial_metrics(nwb):
     ]
     df_trials = df_trials.drop(columns=drop_cols)
 
-
     return df_trials
 
 
@@ -291,5 +289,4 @@ def compute_bias(nwb):
     df_trials["bias_ci_lower"] = df_trials["bias_ci_lower"].bfill().ffill()
     df_trials["bias_ci_upper"] = df_trials["bias_ci_upper"].bfill().ffill()
 
-
     return df_trials