From 0c426bac8d34d85b6154fd580d1248e44310f767 Mon Sep 17 00:00:00 2001
From: whohensee <106775295+whohensee@users.noreply.github.com>
Date: Tue, 15 Oct 2024 08:37:31 -0700
Subject: [PATCH] Changes from review

---
 models/deepscore.py    | 25 -------------------------
 pipeline/data_store.py | 13 +++----------
 2 files changed, 3 insertions(+), 35 deletions(-)

diff --git a/models/deepscore.py b/models/deepscore.py
index 2f5dea95..7f4e4d34 100644
--- a/models/deepscore.py
+++ b/models/deepscore.py
@@ -120,31 +120,6 @@ def from_measurements(measurements, provenance=None, **kwargs):
 
         return score
 
-    def evaluate_scores(self):
-        """Evaluate the ML/DL score for the associated measurement, using the 
-        appropriate algorithm.
-        """
-        # consider doing cases or another solution, for now just if-else block
-
-        algo = Provenance.get( self.provenance_id ).parameters['algorithm']
-
-        if algo == 'random':
-            self.score = np.random.default_rng().random()
-            self.algorithm = algo
-
-        elif algo == 'allperfect':
-            self.score = 1.0
-            self.algorithm = algo
-        
-        elif algo in DeepscoreAlgorithmConverter.dict_inverse:
-            raise NotImplementedError(f"algorithm {algo} isn't yet implemented")
-        
-        else:
-            raise ValueError(f"{algo} is not a valid ML algorithm.")
-        
-        return None
-    
-
     def get_upstreams(self, session=None):
         """Get the measurements that was used to make this deepscore. """
         with SmartSession(session) as session:
diff --git a/pipeline/data_store.py b/pipeline/data_store.py
index dfac1bab..42a2c41a 100644
--- a/pipeline/data_store.py
+++ b/pipeline/data_store.py
@@ -1668,19 +1668,12 @@ def get_scores(self, provenance=None, reload=False, session=None):
         
         # sort the scores so the list order matches measurements
         if scores is not None and len(scores) > 0:
+
             if len(scores) != len(self.measurements):
                 raise RuntimeError(f"get_scores found {len(scores)} scores for {len(self.measurements)} measurements")
+            
             m_ids = [str(m.id) for m in self.measurements]
-            sorted_scores = [None]*len(self.scores)
-            for score in scores:
-                idx = m_ids.index(str(score.measurements_id))
-                sorted_scores[idx] = score
-
-            if not all(scores):  # check if any None still remain
-                raise RuntimeError(f"get_scores did not replace all None values when sorting list")
-
-            scores = sorted_scores
-            self.scores = scores  # update the order in ds to be sorted too.
+            scores.sort( key=lambda x: m_ids.index( str(x.measurements_id) ) )
 
         return scores