From ada270aa3c9a28d1931e7cd42c1599e63c7dca8b Mon Sep 17 00:00:00 2001
From: jebus <lorsbach@envipath.com>
Date: Wed, 12 Aug 2026 21:01:41 +1200
Subject: [PATCH] [Fix] Canonicalize SMILES when checking overlaps in
 smiles_covered_by (#443)

Co-authored-by: Tim Lorsbach <tim@lorsba.ch>
Reviewed-on: https://git.envipath.com/enviPath/enviPy/pulls/443
---
 utilities/chem.py | 26 ++++++++++++++++++--------
 utilities/ml.py   | 30 ++++++++++++++++++------------
 2 files changed, 36 insertions(+), 20 deletions(-)

diff --git a/utilities/chem.py b/utilities/chem.py
index cbfba09e..476b450b 100644
--- a/utilities/chem.py
+++ b/utilities/chem.py
@@ -68,6 +68,8 @@ class PredictionResult(object):
 
 
 class FormatConverter(object):
+    tautomer_enumerator = rdMolStandardize.TautomerEnumerator()
+
     @staticmethod
     def mass(smiles):
         return Descriptors.MolWt(FormatConverter.from_smiles(smiles))
@@ -240,8 +242,9 @@ class FormatConverter(object):
             Chem.RemoveStereochemistry(res_mol)
 
         if canonicalize_tautomers:
-            te = rdMolStandardize.TautomerEnumerator()  # idem
-            res_mol = te.Canonicalize(res_mol)
+            tautomers = FormatConverter.tautomer_enumerator.Enumerate(res_mol)
+            if len(tautomers) >= 1:
+                res_mol = FormatConverter.tautomer_enumerator.PickCanonical(tautomers)
 
         return Chem.MolToSmiles(res_mol, kekuleSmiles=True)
 
@@ -389,7 +392,7 @@ class FormatConverter(object):
                                 prods.append(p)
 
                         except ValueError as e:
-                            logger.error(f"Sanitizing and converting failed:\n{e}")
+                            logger.debug(f"Sanitizing and converting failed:\n{e}")
                             continue
 
                     if len(prods):
@@ -397,7 +400,8 @@ class FormatConverter(object):
                         pss.add(ps)
 
         except Exception as e:
-            logger.error(f"Applying {smirks} on {smiles} failed:\n{e}")
+            logger.debug(f"Applying {smirks} on {smiles} failed:\n{e}")
+            pass
 
         return list(pss)
 
@@ -482,8 +486,10 @@ class FormatConverter(object):
         if standardize:
             for smi in l_smiles:
                 try:
-                    smi = FormatConverter.standardize(
-                        smi, remove_stereo=True, canonicalize_tautomers=canonicalize_tautomers
+                    smi = FormatConverter.canonicalize(
+                        FormatConverter.standardize(
+                            smi, remove_stereo=True, canonicalize_tautomers=canonicalize_tautomers
+                        )
                     )
                 except Exception:
                     # :shrug:
@@ -497,8 +503,12 @@ class FormatConverter(object):
         if standardize:
             for smi in r_smiles:
                 try:
-                    smi = FormatConverter.standardize(
-                        smi, remove_stereo=True, canonicalize_tautomers=canonicalize_tautomers
+                    smi = FormatConverter.canonicalize(
+                        FormatConverter.standardize(
+                            smi,
+                            remove_stereo=True,
+                            canonicalize_tautomers=canonicalize_tautomers,
+                        )
                     )
                 except Exception:
                     # :shrug:
diff --git a/utilities/ml.py b/utilities/ml.py
index 06e80dcf..a633ee2e 100644
--- a/utilities/ml.py
+++ b/utilities/ml.py
@@ -238,9 +238,11 @@ class RuleBasedDataset(Dataset):
     ):
         if feat_funcs is None:
             feat_funcs = [FormatConverter.maccs]
-        _structures = set()  # Get all the structures
+
+        _structures = set()
         for r in reactions:
             _structures.update(r.educts.all())
+
             if not educts_only:
                 _structures.update(r.products.all())
 
@@ -282,17 +284,14 @@ class RuleBasedDataset(Dataset):
                     if key not in triggered:
                         continue
 
-                    # standardize products from reactions for comparison
-                    standardized_products = []
-                    for cs in r.products.all():
-                        smi = cs.smiles
-                        try:
-                            smi = FormatConverter.standardize(smi, remove_stereo=True)
-                        except Exception:
-                            logger.debug(f"Standardizing SMILES failed for {smi}")
-                        standardized_products.append(smi)
-                    if len(set(standardized_products).difference(triggered[key])) == 0:
+                    if FormatConverter.smiles_covered_by(
+                        [prod.smiles for prod in r.products.all()],
+                        list(triggered[key]),
+                        standardize=True,
+                        canonicalize_tautomers=True,
+                    ):
                         observed.add(key)
+
         feat_columns = []
         for feat_func in feat_funcs:
             if isinstance(feat_func, Descriptor):
@@ -301,6 +300,7 @@ class RuleBasedDataset(Dataset):
                 feats = feat_func(compounds[0].smiles)
             start_i = len(feat_columns)
             feat_columns.extend([f"feature_{start_i + i}" for i, _ in enumerate(feats)])
+
         ds_columns = (
             ["structure_id"]
             + feat_columns
@@ -334,7 +334,9 @@ class RuleBasedDataset(Dataset):
                     obs.append(None)
                 else:
                     obs.append(0)
+
             rows.append([str(comp.uuid)] + feats + trig + obs)
+
         ds = RuleBasedDataset(len(applicable_rules), ds_columns, data=rows)
         return ds
 
@@ -680,9 +682,13 @@ class RelativeReasoning:
 
     def predict(self, X):
         res = np.zeros((len(X), (self.end_index + 1 - self.start_index)))
+        immutable_res = np.zeros((len(X), (self.end_index + 1 - self.start_index)))
 
         # Loop through all instances
         for inst_idx, inst in enumerate(X):
+            for i, t in enumerate(inst[self.start_index : self.end_index + 1]):
+                immutable_res[inst_idx][i] = t
+
             # Loop through all "triggered" features
             for i, t in enumerate(inst[self.start_index : self.end_index + 1]):
                 # Set label
@@ -696,7 +702,7 @@ class RelativeReasoning:
                             if i2 in self.winmap.get(i, []):
                                 # if thatat rule also triggered, it dominated the current
                                 # set label to 0
-                                if X[inst_idx][i2]:
+                                if immutable_res[inst_idx][i2]:
                                     res[inst_idx][i] = 0
 
         return res