[Feature] Threshold Warning + Cosmetics (#277)

Co-authored-by: Tim Lorsbach <tim@lorsba.ch>
Reviewed-on: enviPath/enviPy#277

epdb/logic.py

@@ -1489,6 +1489,7 @@ class SPathway(object):
         self.smiles_to_node: Dict[str, SNode] = dict(**{n.smiles: n for n in self.root_nodes})
         self.edges: Set["SEdge"] = set()
         self.done = False
+        self.empty_due_to_threshold = False
 
     @staticmethod
     def from_pathway(pw: "Pathway", persist: bool = True):
@@ -1601,9 +1602,24 @@ class SPathway(object):
 
                         sub.app_domain_assessment = app_domain_assessment
 
-            candidates = self.prediction_setting.expand(self, sub)
+            expansion_result = self.prediction_setting.expand(self, sub)
+
+            # We don't have any substrate, but technically we have at least one rule that triggered.
+            # If our substrate is a root node a.k.a. depth == 0 store that info in SPathway
+            if (
+                len(expansion_result["transformations"]) == 0
+                and expansion_result["rule_triggered"]
+                and sub.depth == 0
+            ):
+                self.empty_due_to_threshold = True
+
+                # Emit directly
+                if self.persist is not None:
+                    self.persist.kv["empty_due_to_threshold"] = True
+                    self.persist.save()
+
             # candidates is a List of PredictionResult. The length of the List is equal to the number of rules
-            for cand_set in candidates:
+            for cand_set in expansion_result["transformations"]:
                 if cand_set:
                     # cand_set is a PredictionResult object that can consist of multiple candidate reactions
                     for cand in cand_set:
@@ -1727,10 +1743,6 @@ class SPathway(object):
                         for queued_val in queue:
                             node_and_probs.append((queued_val, node_probs[queued_val]))
 
-                        from pprint import pprint
-
-                        pprint(node_and_probs)
-
                         # re-order the queue and only pick smiles
                         queue = [
                             n[0] for n in sorted(node_and_probs, key=lambda x: x[1], reverse=True)