fix

mhcflurry/select_allele_specific_models_command.py

@@ -442,13 +442,13 @@ def model_select(allele):
         unselected_score_function = (
             unselected_accuracy_scorer.score_function(allele))
 
-        unselected_score = unselected_score_function(predictor)
-        scrambled_predictor = ScrambledPredictor(predictor)
         additional_metadata = {}
+        unselected_score = unselected_score_function(
+            predictor, additional_metadata_out=additional_metadata)
+        scrambled_predictor = ScrambledPredictor(predictor)
         scrambled_scores = numpy.array([
             unselected_score_function(
-                scrambled_predictor,
-                additional_metadata_out=additional_metadata)
+                scrambled_predictor)
             for _ in range(unselected_accuracy_scorer_samples)
         ])
         unselected_score_scrambled_mean = scrambled_scores.mean()
@@ -779,8 +779,7 @@ class MassSpecModelSelector(object):
 
                 # We additionally compute AUC score.
                 additional_metadata_out["score_mass_spec_AUC"] = roc_auc_score(
-                    self.df[allele].values,
-                    -1 * predictions)
+                    self.df[allele].values, -1 * predictions)
             return ppv * multiplier
 
         summary = "mass-spec (%d hits / %d decoys)" % (total_hits, total_decoys)

test/test_train_and_related_commands.py

@@ -105,7 +105,7 @@ def run_and_check_with_model_selection(n_jobs=1):
         deepcopy(HYPERPARAMETERS[0]),
         deepcopy(HYPERPARAMETERS[0]),
     ]
-    hyperparameters[-1]["max_epochs"] = 0
+    hyperparameters[-1]["max_epochs"] = 10
     with open(hyperparameters_filename, "w") as fd:
         json.dump(hyperparameters, fd)
 
@@ -153,9 +153,9 @@ def run_and_check_with_model_selection(n_jobs=1):
         result.allele_to_allele_specific_models["HLA-A*03:01"][
             0].hyperparameters["max_epochs"], 500)
 
-    #print("Deleting: %s" % models_dir1)
-    #print("Deleting: %s" % models_dir2)
-    #shutil.rmtree(models_dir1)
+    print("Deleting: %s" % models_dir1)
+    print("Deleting: %s" % models_dir2)
+    shutil.rmtree(models_dir1)
 
 
 if os.environ.get("KERAS_BACKEND") != "theano":