Make minor formatting edits

openfold/features/np/data_pipeline.py

@@ -62,7 +62,7 @@ class DataPipeline:
     """Runs the alignment tools and assembles the input features."""
 
     def __init__(self,
-                 jackhammer_binary_path: str,
+         jackhmmer_binary_path: str,
          hhblits_binary_path: str,
          hhsearch_binary_path: str,
          uniref90_database_path: str,
@@ -79,12 +79,12 @@ class DataPipeline:
         """Constructs a feature dict for a given FASTA file."""
         self._use_small_bfd = use_small_bfd
         self.jackhmmer_uniref90_runner = jackhmmer.Jackhmmer(
-            binary_path=jackhammer_binary_path,
+            binary_path=jackhmmer_binary_path,
             database_path=uniref90_database_path
         )
         if use_small_bfd:
             self.jackhmmer_small_bfd_runner = jackhmmer.Jackhmmer(
-                binary_path=jackhammer_binary_path,
+                binary_path=jackhmmer_binary_path,
                 database_path=small_bfd_database_path
             )
         else:
@@ -93,7 +93,7 @@ class DataPipeline:
                 databases=[bfd_database_path, uniclust30_database_path]
             )
         self.jackhmmer_mgnify_runner = jackhmmer.Jackhmmer(
-            binary_path=jackhammer_binary_path,
+            binary_path=jackhmmer_binary_path,
             database_path=mgnify_database_path
         )
         self.hhsearch_pdb70_runner = hhsearch.HHSearch(

openfold/utils/affine_utils.py

@@ -198,7 +198,7 @@ class T:
         denom = torch.sqrt(sum((c * c for c in e0)) + eps)
         e0 = [c / denom for c in e0]
         dot = sum((c1 * c2 for c1, c2 in zip(e0, e1)))
-        e1 = [c1 - c2 * dot for c1, c2 in zip(e1, e0)]
+        e1 = [c2 - c1 * dot for c1, c2 in zip(e0, e1)]
         denom = torch.sqrt(sum((c * c for c in e1)) + eps)
         e1 = [c / denom for c in e1]
         e2 = [

run_pretrained_alphafold.py

@@ -63,10 +63,11 @@ def main(args):
         max_hits=MAX_TEMPLATE_HITS,
         kalign_binary_path=args.kalign_binary_path,
         release_dates_path=None,
-        obsolete_pdbs_path=args.obsolete_pdbs_path)
+        obsolete_pdbs_path=args.obsolete_pdbs_path
+    )
 
     data_processor = data_pipeline.DataPipeline(
-        jackhammer_binary_path=args.jackhmmer_binary_path,
+        jackhmmer_binary_path=args.jackhmmer_binary_path,
         hhblits_binary_path=args.hhblits_binary_path,
         hhsearch_binary_path=args.hhsearch_binary_path,
         uniref90_database_path=args.uniref90_database_path,
@@ -94,16 +95,11 @@ def main(args):
     print("Collecting data...")
     feature_dict = data_processor.process(
         input_fasta_path=args.fasta_path, msa_output_dir=msa_output_dir)
-    # Output the features
-    features_output_path = os.path.join(output_dir_base, 'features.pkl')
-    with open(features_output_path, 'wb') as f:
-        pickle.dump(feature_dict, f, protocol=4)
 
     print("Generating features...")
-    processed_feature_dict = feature_processor.process_features(feature_dict, random_seed)
-
-    with open(os.path.join(output_dir_base, 'processed_feats.pkl'), 'wb') as f:
-        pickle.dump(processed_feature_dict, f, protocol=4)
+    processed_feature_dict = feature_processor.process_features(
+        feature_dict, random_seed
+    )
 
     print("Executing model...")
     batch = processed_feature_dict
@@ -209,7 +205,8 @@ if __name__ == "__main__":
     parser.add_argument(
         '--kalign_binary_path', type=str, default='/usr/bin/kalign'
     )
-    parser.add_argument('--uniref90_database_path', type=str, default=None, required=True
+    parser.add_argument(
+        '--uniref90_database_path', type=str, default=None, required=True
     )
     parser.add_argument(
         '--mgnify_database_path', type=str, default=None, required=True