[Fix] Compound Grouping, Identity prediction of enviFormer, Setting params (#337)

Co-authored-by: Tim Lorsbach <tim@lorsba.ch>
Reviewed-on: enviPath/enviPy#337

envipath/settings.py

@@ -311,8 +311,8 @@ DEFAULT_MODEL_PARAMS = {
     "num_chains": 10,
 }
 
-DEFAULT_MAX_NUMBER_OF_NODES = 30
+DEFAULT_MAX_NUMBER_OF_NODES = 50
-DEFAULT_MAX_DEPTH = 5
+DEFAULT_MAX_DEPTH = 8
 DEFAULT_MODEL_THRESHOLD = 0.25
 
 # Loading Plugins

epdb/legacy_api.py

@@ -1332,8 +1332,13 @@ def get_package_scenario(request, package_uuid, scenario_uuid):
         }
 
 
+@router.post("/package/{uuid:package_uuid}/scenario")
+def create_package_scenario(request, package_uuid):
+    pass
+
+
 @router.delete("/package/{uuid:package_uuid}/scenario")
-def delete_scenarios(request, package_uuid, scenario_uuid):
+def delete_scenarios(request, package_uuid):
     try:
         p = PackageManager.get_package_by_id(request.user, package_uuid)
 
@@ -1520,7 +1525,7 @@ def create_pathway(
     try:
         p = PackageManager.get_package_by_id(request.user, package_uuid)
 
-        stand_smiles = FormatConverter.standardize(pw.smilesinput.strip())
+        stand_smiles = FormatConverter.standardize(pw.smilesinput.strip(), remove_stereo=True)
 
         new_pw = Pathway.create(p, stand_smiles, name=pw.name, description=pw.description)
 
@@ -1937,7 +1942,7 @@ def get_model(request, package_uuid, model_uuid, c: Query[Classify]):
                 return 400, {"message": "Received empty SMILES"}
 
             try:
-                stand_smiles = FormatConverter.standardize(c.smiles)
+                stand_smiles = FormatConverter.standardize(c.smiles, remove_stereo=True)
             except ValueError:
                 return 400, {"message": f'"{c.smiles}" is not a valid SMILES'}
 

epdb/logic.py

@@ -1115,13 +1115,16 @@ class SettingManager(object):
         expansion_scheme: ExpansionSchemeChoice = ExpansionSchemeChoice.BFS,
     ):
         new_s = Setting()
+
         # Clean for potential XSS
         new_s.name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
         new_s.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
+
         new_s.max_nodes = max_nodes
         new_s.max_depth = max_depth
         new_s.model = model
         new_s.model_threshold = model_threshold
+        new_s.expansion_scheme = expansion_scheme
 
         new_s.save()
 

epdb/models.py

@@ -769,7 +769,7 @@ class Compound(EnviPathModel, AliasMixin, ScenarioMixin, ChemicalIdentifierMixin
             num_structs = self.structures.count()
             stand_smiles = set()
             for structure in self.structures.all():
-                stand_smiles.add(FormatConverter.standardize(structure.smiles))
+                stand_smiles.add(FormatConverter.standardize(structure.smiles, remove_stereo=True))
 
             if len(stand_smiles) != 1:
                 logger.debug(
@@ -838,7 +838,7 @@ class Compound(EnviPathModel, AliasMixin, ScenarioMixin, ChemicalIdentifierMixin
         if parsed is None:
             raise ValueError("Given SMILES is invalid")
 
-        standardized_smiles = FormatConverter.standardize(smiles)
+        standardized_smiles = FormatConverter.standardize(smiles, remove_stereo=True)
 
         # Check if we find a direct match for a given SMILES
         if CompoundStructure.objects.filter(smiles=smiles, compound__package=package).exists():
@@ -911,7 +911,7 @@ class Compound(EnviPathModel, AliasMixin, ScenarioMixin, ChemicalIdentifierMixin
         if parsed is None:
             raise ValueError("Given SMILES is invalid")
 
-        standardized_smiles = FormatConverter.standardize(smiles)
+        standardized_smiles = FormatConverter.standardize(smiles, remove_stereo=True)
 
         is_standardized = standardized_smiles == smiles
 
@@ -2011,19 +2011,23 @@ class Pathway(EnviPathModel, AliasMixin, ScenarioMixin):
             # Clean for potential XSS
             name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
 
+        is_generic_name = False
         if name is None or name == "":
             name = f"Pathway {Pathway.objects.filter(package=package).count() + 1}"
+            is_generic_name = True
 
         pw.name = name
+
         if description is not None and description.strip() != "":
             pw.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
 
         pw.predicted = predicted
 
         pw.save()
+
         try:
             # create root node
-            Node.create(pw, smiles, 0)
+            Node.create(pw, smiles, 0, name=name if not is_generic_name else None)
         except ValueError as e:
             # Node creation failed, most likely due to an invalid smiles
             # delete this pathway...
@@ -3445,10 +3449,17 @@ class EnviFormer(PackageBasedModel):
                             for smile in smi.split(".")
                         ]
                     )
+
+                    if smi in canon_smiles:
+                        logger.debug(f"Found input SMILES={smi} in prediction results. Skipping...")
+                        continue
+
                 except ValueError:  # This occurs when the predicted string is an invalid SMILES
                     logging.info(f"EnviFormer predicted an invalid SMILES: {smi}")
                     continue
+
                 res.append(PredictionResult([ProductSet([smi])], prob, None))
+
             results.append(res)
 
         return results
@@ -3587,7 +3598,7 @@ class EnviFormer(PackageBasedModel):
                     )
                 root_node = ".".join(
                     [
-                        FormatConverter.standardize(smile)
+                        FormatConverter.standardize(smile, remove_stereo=True)
                         for smile in root_node[0].default_node_label.smiles.split(".")
                     ]
                 )

epdb/tasks.py

@@ -420,7 +420,7 @@ def batch_predict(
     standardized_substrates_and_smiles = []
     for substrate in substrate_and_names:
         try:
-            stand_smiles = FormatConverter.standardize(substrate[0])
+            stand_smiles = FormatConverter.standardize(substrate[0], remove_stereo=True)
             standardized_substrates_and_smiles.append([stand_smiles, substrate[1]])
         except ValueError:
             raise ValueError(

epdb/views.py

@@ -1591,7 +1591,7 @@ def package_rule(request, package_uuid, rule_uuid):
         context = get_base_context(request)
 
         if smiles := request.GET.get("smiles", False):
-            stand_smiles = FormatConverter.standardize(smiles)
+            stand_smiles = FormatConverter.standardize(smiles, remove_stereo=True)
             res = current_rule.apply(stand_smiles)
             if len(res) > 1:
                 logger.info(
@@ -1919,7 +1919,7 @@ def package_pathways(request, package_uuid):
                 "Pathway prediction failed due to missing or empty SMILES",
             )
         try:
-            stand_smiles = FormatConverter.standardize(smiles)
+            stand_smiles = FormatConverter.standardize(smiles, remove_stereo=True)
         except ValueError:
             return error(
                 request,
@@ -2793,7 +2793,6 @@ def settings(request):
 
         return render(request, "collections/settings_paginated.html", context)
 
-        return render(request, "collections/objects_list.html", context)
     elif request.method == "POST":
         if s.DEBUG:
             for k, v in request.POST.items():
@@ -2805,15 +2804,18 @@ def settings(request):
 
         new_default = request.POST.get("prediction-setting-new-default", "off") == "on"
 
+        # min 2, max s.DEFAULT_MAX_NUMBER_OF_NODES
         max_nodes = min(
             max(
                 int(request.POST.get("prediction-setting-max-nodes", 1)),
-                s.DEFAULT_MAX_NUMBER_OF_NODES,
+                2,
             ),
             s.DEFAULT_MAX_NUMBER_OF_NODES,
         )
+
+        # min 1, max s.DEFAULT_MAX_DEPTH
         max_depth = min(
-            max(int(request.POST.get("prediction-setting-max-depth", 1)), s.DEFAULT_MAX_DEPTH),
+            max(int(request.POST.get("prediction-setting-max-depth", 1)), 1),
             s.DEFAULT_MAX_DEPTH,
         )
 
@@ -2960,7 +2962,7 @@ def jobs(request):
                 parts = pair.split(",")
 
                 try:
-                    smiles = FormatConverter.standardize(parts[0])
+                    smiles = FormatConverter.standardize(parts[0], remove_stereo=True)
                 except ValueError:
                     raise BadRequest(f"Couldn't standardize SMILES {parts[0]}!")
 

tests/test_formatconverter.py

@@ -6,5 +6,5 @@ from utilities.chem import FormatConverter
 class FormatConverterTestCase(TestCase):
     def test_standardization(self):
         smiles = "C[n+]1c([N-](C))cccc1"
-        standardized_smiles = FormatConverter.standardize(smiles)
+        standardized_smiles = FormatConverter.standardize(smiles, remove_stereo=True)
         self.assertEqual(standardized_smiles, "CN=C1C=CC=CN1C")

utilities/chem.py

@@ -474,7 +474,7 @@ class FormatConverter(object):
             for smi in l_smiles:
                 try:
                     smi = FormatConverter.standardize(
-                        smi, canonicalize_tautomers=canonicalize_tautomers
+                        smi, remove_stereo=True, canonicalize_tautomers=canonicalize_tautomers
                     )
                 except Exception:
                     # :shrug:
@@ -488,7 +488,9 @@ class FormatConverter(object):
         if standardize:
             for smi in r_smiles:
                 try:
-                    smi = FormatConverter.standardize(smi)
+                    smi = FormatConverter.standardize(
+                        smi, remove_stereo=True, canonicalize_tautomers=canonicalize_tautomers
+                    )
                 except Exception:
                     # :shrug:
                     # logger.debug(f'Standardizing SMILES failed for {smi}')