Auth log

Initial bayer app

Show Pack Classification

Adjusted docker compose to bayer specifics

Adjusted Dockerfile for Bayer

Adding secret flags to group, add secret pools to packages

Adjusted View for Package creation

Prep configs, added Package Create Modal

wip

More on PES

wip

wip

Wip

minor

PW interactions

API PES

wip

Make Select Widget reflect required

make required generallay available

Update UI if pathway mode is set to build

Added ais

circle adjustments

Initial Zoom, fix AD Creation

wip

auth log, bb4g fix

missing import

Added viz hint if PES is part of reaction

Add Edge check for pes

flip boolean

...

pes

Added extra

...

In / Out Edges Viz, Submitting Button Text

...

Make PES Link clickable

Return proper http response instead of error

Fixed error return, removed unused options

Fix PES Link HTML for other entities

Fixed molfile assignment, adjusted Export

Package Export/Import cycle

highlight Description links

implemented non persistent

Harmonised proposed field in Json output

Added pesLink field to PW Api output

PES Fields in API Output

removed debug

Fix Classification import, Fix PES Deserialization

underline pes link in templates

Fix alter name/desc for node, make /node /edge funcitonal

provide setting link and copy button

Implemented Compound Names / Reaction Names View Option

Unconnected Nodes

Make links thicker, reduce timeout trigger time

Show proposed info in popover

Pathway Build no stereo removal

Include probs in reaction name option viz

Detect clicks outside nodes/edges

envipath/settings.py

@@ -357,6 +357,7 @@ DEFAULT_MODEL_PARAMS = {
 DEFAULT_MAX_NUMBER_OF_NODES = 9999
 DEFAULT_MAX_DEPTH = 8
 DEFAULT_MODEL_THRESHOLD = 0.25
+BATCH_PREDICT_MAX_COMPOUNDS = 150
 
 # Loading Plugins
 PLUGINS_ENABLED = os.environ.get("PLUGINS_ENABLED", "False") == "True"

epdb/logic.py

@@ -46,7 +46,7 @@ class EPDBURLParser:
     MODEL_PATTERNS = {
         "epdb.User": re.compile(rf"^.*/user/{UUID_PATTERN}"),
         "epdb.Group": re.compile(rf"^.*/group/{UUID_PATTERN}"),
-        "epdb.Package": re.compile(rf"^.*/package/{UUID_PATTERN}"),
+        s.EPDB_PACKAGE_MODEL: re.compile(rf"^.*/package/{UUID_PATTERN}"),
         "epdb.Compound": re.compile(rf"^.*/package/{UUID_PATTERN}/compound/{UUID_PATTERN}"),
         "epdb.CompoundStructure": re.compile(
             rf"^.*/package/{UUID_PATTERN}/compound/{UUID_PATTERN}/structure/{UUID_PATTERN}"
@@ -96,7 +96,7 @@ class EPDBURLParser:
 
     def contains_package_url(self):
         return (
-            bool(self.MODEL_PATTERNS["epdb.Package"].findall(self.url))
+            bool(self.MODEL_PATTERNS[s.EPDB_PACKAGE_MODEL].findall(self.url))
             and not self.is_package_url()
         )
 
@@ -124,7 +124,7 @@ class EPDBURLParser:
             "epdb.EPModel",
             "epdb.Pathway",
             # 1st level
-            "epdb.Package",
+            s.EPDB_PACKAGE_MODEL,
             "epdb.Setting",
             "epdb.Group",
             "epdb.User",
@@ -146,7 +146,7 @@ class EPDBURLParser:
 
         hierarchy_order = [
             # 1st level
-            "epdb.Package",
+            s.EPDB_PACKAGE_MODEL,
             "epdb.Setting",
             "epdb.Group",
             "epdb.User",
@@ -1896,12 +1896,51 @@ class SPathway(object):
 
         logger.info("Update done!")
 
+    def compute_bayes_probabilities(self) -> Dict[SEdge, float]:
+        """
+        Computes Bayes-adjusted probabilities for all edges in the pathway
+        by iterating level by level from depth 0 upwards, keyed on educt depth.
+
+        Returns:
+            A dict mapping each SEdge to its Bayes-adjusted probability.
+        """
+        bayes_probs: Dict[SEdge, float] = {}
+
+        # Group edges by their educt depth
+        edges_by_depth: Dict[int, List[SEdge]] = {}
+        for edge in self.edges:
+            d = edge.educts[0].depth
+            edges_by_depth.setdefault(d, []).append(edge)
+
+        for depth in sorted(edges_by_depth.keys()):
+            for edge in edges_by_depth[depth]:
+                if depth == 0:
+                    bayes_probs[edge] = edge.probability
+                else:
+                    predecessor_edges = [e for e in self.edges if edge.educts[0] in e.products]
+
+                    if not predecessor_edges or not all(
+                        e in bayes_probs for e in predecessor_edges
+                    ):
+                        # Predecessor not computed yet (e.g. same-depth product),
+                        # fall back to raw probability
+                        bayes_probs[edge] = edge.probability
+                    else:
+                        predecessor_avg = sum(bayes_probs[e] for e in predecessor_edges) / len(
+                            predecessor_edges
+                        )
+                        bayes_probs[edge] = predecessor_avg * edge.probability
+
+        return bayes_probs
+
     def to_json(self):
         nodes = []
         edges = []
 
         idx_lookup = {}
 
+        bayes_probs = self.compute_bayes_probabilities()
+
         for i, smiles in enumerate(self.smiles_to_node):
             n = self.smiles_to_node[smiles]
             idx_lookup[smiles] = i
@@ -1922,6 +1961,7 @@ class SPathway(object):
 
             if edge.probability:
                 e["probability"] = edge.probability
+                e["multiGenProbability"] = bayes_probs[edge]
 
             edges.append(e)
 

epdb/models.py

@@ -3014,7 +3014,14 @@ class PackageBasedModel(EPModel):
 
             prec, rec = dict(), dict()
 
-            for t in np.arange(0, 1.05, 0.05):
+            thresholds = list(np.arange(0, 1.05, 0.05))
+
+            # Add specific threshold set during object creation if not already present
+            if np.float64(threshold) not in thresholds:
+                thresholds.append(np.float64(threshold))
+                thresholds.sort()
+
+            for t in thresholds:
                 temp_thresholded = (y_pred_filtered >= t).astype(int)
                 prec[f"{t:.2f}"] = precision_score(
                     y_test_filtered, temp_thresholded, zero_division=0
@@ -3024,7 +3031,14 @@ class PackageBasedModel(EPModel):
             return acc, prec, rec
 
         def evaluate_mg(model, pathways: Union[QuerySet["Pathway"] | List["Pathway"]], threshold):
-            thresholds = np.arange(0.1, 1.1, 0.1)
+            thresholds = list(np.arange(0, 1.05, 0.05))
+
+            # Add specific threshold set during object creation if not already present
+            if np.float64(threshold) not in thresholds:
+                thresholds.append(np.float64(threshold))
+                thresholds.sort()
+
+            logger.info(f"Thresholds: {thresholds}")
 
             precision = {f"{t:.2f}": [] for t in thresholds}
             recall = {f"{t:.2f}": [] for t in thresholds}
@@ -3050,7 +3064,7 @@ class PackageBasedModel(EPModel):
 
             s = Setting()
             s.model = mod
-            s.model_threshold = thresholds.min()
+            s.model_threshold = 0.0
             s.max_depth = 10
             s.max_nodes = 50
 

epdb/views.py

@@ -540,6 +540,7 @@ def batch_predict_pathway(request):
     context = get_base_context(request)
     context["title"] = "enviPath - Batch Predict Pathway"
     context["meta"]["current_package"] = context["meta"]["user"].default_package
+    context["batch_predict_max_compounds"] = s.BATCH_PREDICT_MAX_COMPOUNDS
 
     return render(request, "batch_predict_pathway.html", context)
 
@@ -1964,6 +1965,21 @@ def package_reactions(request, package_uuid):
         reaction_name = request.POST.get("reaction-name")
         reaction_description = request.POST.get("reaction-description")
         reaction_smiles = request.POST.get("reaction-smiles")
+
+        if reaction_smiles is None or reaction_smiles.strip() == "":
+            return error(
+                request,
+                "Reaction SMILES is empty / missing",
+                "No reaction SMILES provided. Please provide a SMILES for the reaction.",
+            )
+
+        if not FormatConverter.is_valid_smirks(reaction_smiles):
+            return error(
+                request,
+                "Reaction SMILES is invalid",
+                f"The provided reactions SMILES {reaction_smiles} is invalid",
+            )
+
         educts = reaction_smiles.split(">>")[0].split(".")
         products = reaction_smiles.split(">>")[1].split(".")
 

epiuclid/serializers/pathway_mapper.py

@@ -120,13 +120,6 @@ class PathwayMapper:
             )
             bundle.reference_substances.append(ref_sub)
 
-            sub = IUCLIDSubstanceData(
-                uuid=sub_uuid,
-                name=compound.name,
-                reference_substance_uuid=ref_sub_uuid,
-            )
-            bundle.substances.append(sub)
-
         if not export.compounds:
             return bundle
 
@@ -145,6 +138,16 @@ class PathwayMapper:
         if not root_compound_pks:
             return bundle
 
+        for root_pk in root_compound_pks:
+            root_sub_uuid, root_ref_uuid = seen_compounds[root_pk]
+            bundle.substances.append(
+                IUCLIDSubstanceData(
+                    uuid=root_sub_uuid,
+                    name=compound_names[root_pk],
+                    reference_substance_uuid=root_ref_uuid,
+                )
+            )
+
         edge_templates: list[tuple[UUID, frozenset[int], tuple[int, ...], tuple[UUID, ...]]] = []
         for edge in sorted(export.edges, key=lambda item: str(item.edge_uuid)):
             parent_compound_pks = sorted(

epiuclid/tests/test_api.py

@@ -70,8 +70,7 @@ class IUCLIDExportAPITest(TestCase):
             names = zf.namelist()
             self.assertIn("manifest.xml", names)
             i6d_files = [n for n in names if n.endswith(".i6d")]
-            # 2 substances + 2 ref substances + 1 ESR = 5 i6d files
+            self.assertEqual(len(i6d_files), 4)
-            self.assertEqual(len(i6d_files), 5)
 
     def test_anonymous_returns_401(self):
         self.client.logout()

epiuclid/tests/test_i6z.py

@@ -7,6 +7,11 @@ from uuid import uuid4
 
 from django.test import SimpleTestCase, tag
 
+from epapi.v1.interfaces.iuclid.dto import (
+    PathwayCompoundDTO,
+    PathwayEdgeDTO,
+    PathwayExportDTO,
+)
 from epiuclid.serializers.i6z import I6ZSerializer
 from epiuclid.serializers.pathway_mapper import (
     IUCLIDDocumentBundle,
@@ -14,9 +19,24 @@ from epiuclid.serializers.pathway_mapper import (
     IUCLIDReferenceSubstanceData,
     IUCLIDSubstanceData,
     IUCLIDTransformationProductEntry,
+    PathwayMapper,
 )
 
 
+def _unlinked_documents(manifest_xml: str) -> list[tuple[str | None, str]]:
+    ns = "http://iuclid6.echa.europa.eu/namespaces/manifest/v1"
+    root = ET.fromstring(manifest_xml)
+    base = root.findtext(f"{{{ns}}}base-document-uuid")
+    linked_targets: set[str | None] = {base}
+    docs: dict[str, str | None] = {}
+    for doc in root.findall(f".//{{{ns}}}document"):
+        uuid = doc.findtext(f"{{{ns}}}uuid")
+        docs[uuid] = doc.findtext(f"{{{ns}}}type")
+        for link in doc.findall(f"{{{ns}}}links/{{{ns}}}link"):
+            linked_targets.add(link.findtext(f"{{{ns}}}ref-uuid"))
+    return [(doc_type, uuid) for uuid, doc_type in docs.items() if uuid not in linked_targets]
+
+
 def _make_bundle() -> IUCLIDDocumentBundle:
     ref_uuid = uuid4()
     sub_uuid = uuid4()
@@ -197,3 +217,29 @@ class I6ZSerializerTest(SimpleTestCase):
             }
             self.assertIn(parent_ref_key, reference_links)
             self.assertIn(product_ref_key, reference_links)
+
+    def test_multi_compound_pathway_has_no_unlinked_documents(self):
+        compounds = [
+            PathwayCompoundDTO(pk=1, name="Root", smiles="c1ccccc1"),
+            PathwayCompoundDTO(pk=2, name="P1", smiles="CCO"),
+            PathwayCompoundDTO(pk=3, name="P2", smiles="CCN"),
+            PathwayCompoundDTO(pk=4, name="P3", smiles="CCC"),
+        ]
+        export = PathwayExportDTO(
+            pathway_uuid=uuid4(),
+            pathway_name="Regression Pathway",
+            compounds=compounds,
+            edges=[
+                PathwayEdgeDTO(edge_uuid=uuid4(), start_compound_pks=[1], end_compound_pks=[2]),
+                PathwayEdgeDTO(edge_uuid=uuid4(), start_compound_pks=[1], end_compound_pks=[3]),
+                PathwayEdgeDTO(edge_uuid=uuid4(), start_compound_pks=[2], end_compound_pks=[4]),
+            ],
+            root_compound_pks=[1],
+        )
+        bundle = PathwayMapper().map(export)
+        data = I6ZSerializer().serialize(bundle)
+
+        with zipfile.ZipFile(io.BytesIO(data)) as zf:
+            manifest_xml = zf.read("manifest.xml").decode("utf-8")
+
+        self.assertEqual(_unlinked_documents(manifest_xml), [])

epiuclid/tests/test_pathway_mapper.py

@@ -31,7 +31,7 @@ class PathwayMapperTest(SimpleTestCase):
         )
         bundle = PathwayMapper().map(export)
 
-        self.assertEqual(len(bundle.substances), 2)
+        self.assertEqual(len(bundle.substances), 1)
         self.assertEqual(len(bundle.reference_substances), 2)
         self.assertEqual(len(bundle.endpoint_study_records), 1)
 
@@ -49,8 +49,7 @@ class PathwayMapperTest(SimpleTestCase):
         )
         bundle = PathwayMapper().map(export)
 
-        # 2 unique compounds -> 2 substances, 2 ref substances
+        self.assertEqual(len(bundle.substances), 1)
-        self.assertEqual(len(bundle.substances), 2)
         self.assertEqual(len(bundle.reference_substances), 2)
         # One endpoint study record per pathway
         self.assertEqual(len(bundle.endpoint_study_records), 1)

templates/batch_predict_pathway.html

@@ -37,7 +37,8 @@
               class="text-xs text-base-content/50 border-t border-base-300 pt-3"
             >
               <strong>Format:</strong> First column = SMILES, Second column =
-              Name (headers optional) • Maximum 30 rows
+              Name (headers optional) • Maximum
+              {{ batch_predict_max_compoundss|default:150 }} rows
             </div>
           </div>
         </div>
@@ -195,8 +196,7 @@
     // Function to populate table from CSV data
     function populateTableFromCSV(csvData) {
       const lines = csvData.trim().split("\n");
-      const maxRows = 30;
+      const maxRows = Number("{{ batch_predict_max_compounds|default:150 }}");
-
       // Clear existing table
       clearTable();
 

templates/errors/error.html

@@ -51,7 +51,10 @@
               </svg>
               Go Home
             </a>
-            <button onclick="window.history.back()" class="btn btn-outline">
+            <button
+              onclick="window.location.href = document.referrer"
+              class="btn btn-outline"
+            >
               <svg
                 xmlns="http://www.w3.org/2000/svg"
                 class="mr-2 h-5 w-5"