typo fix, get corpus for each trial

model_training/evaluate_model_helpers.py

@@ -26,7 +26,7 @@ def _extract_transcription(input):
         trans += chr(input[c])
     return trans
 
-def load_h5py_file(file_path):
+def load_h5py_file(file_path, b2txt_csv_df):
     data = {
         'neural_features': [],
         'n_time_steps': [],
@@ -36,7 +36,8 @@ def load_h5py_file(file_path):
         'sentence_label': [],
         'session': [],
         'block_num': [],
-        'trial_num': []
+        'trial_num': [],
+        'corpus': [],
     }
     # Open the hdf5 file for that day
     with h5py.File(file_path, 'r') as f:
@@ -57,6 +58,11 @@ def load_h5py_file(file_path):
             block_num = g.attrs['block_num']
             trial_num = g.attrs['trial_num']
 
+            # match this trial up with the csv to get the corpus name
+            year, month, day = session.split('.')[1:]
+            date = f'{year}-{month}-{day}'
+            row = b2txt_csv_df[(b2txt_csv_df['Date'] == date) & (b2txt_csv_df['Block number'] == block_num)]
+            corpus_name = row['Corpus'].values[0]
 
             data['neural_features'].append(neural_features)
             data['n_time_steps'].append(n_time_steps)
@@ -67,6 +73,7 @@ def load_h5py_file(file_path):
             data['session'].append(session)
             data['block_num'].append(block_num)
             data['trial_num'].append(trial_num)
+            data['corpus'].append(corpus_name)
     return data
 
 def rearrange_speech_logits_pt(logits):