use new event in primal dual recipe (#1160)

* use new event in primal dual recipe

* typo

* Supress warning from expecetd-to-fail test

* remove forgotten assert

Author: Joao-Dionisio

src/pyscipopt/recipes/primal_dual_evolution.py

@@ -15,31 +15,24 @@ class GapEventhdlr(Eventhdlr):
 
         def eventinit(self): # we want to collect best primal solutions and best dual solutions
             self.model.catchEvent(SCIP_EVENTTYPE.BESTSOLFOUND, self)
-            self.model.catchEvent(SCIP_EVENTTYPE.LPSOLVED, self)
-            self.model.catchEvent(SCIP_EVENTTYPE.NODESOLVED, self)
-            
+            self.model.catchEvent(SCIP_EVENTTYPE.DUALBOUNDIMPROVED, self)
 
         def eventexec(self, event):
             # if a new best primal solution was found, we save when it was found and also its objective
             if event.getType() == SCIP_EVENTTYPE.BESTSOLFOUND:
                 self.model.data["primal_log"].append([self.model.getSolvingTime(), self.model.getPrimalbound()])
 
-            if not self.model.data["dual_log"]:
-                self.model.data["dual_log"].append([self.model.getSolvingTime(), self.model.getDualbound()])
-            
-            if self.model.getObjectiveSense() == "minimize":
-                if self.model.isGT(self.model.getDualbound(), self.model.data["dual_log"][-1][1]):
-                    self.model.data["dual_log"].append([self.model.getSolvingTime(), self.model.getDualbound()])
-            else:
-                if self.model.isLT(self.model.getDualbound(), self.model.data["dual_log"][-1][1]):
-                    self.model.data["dual_log"].append([self.model.getSolvingTime(), self.model.getDualbound()])
-                    
+            if event.getType() == SCIP_EVENTTYPE.DUALBOUNDIMPROVED:
+                self.model.data["dual_log"].append([self.model.getSolvingTime(), self.model.getDualbound()])                    
 
     if not hasattr(model, "data") or model.data==None:
         model.data = {}
 
-    model.data["primal_log"] = []
-    model.data["dual_log"] = []
+    model.data.update({
+            'primal_log': [],
+            'dual_log': []
+            })
+
     hdlr = GapEventhdlr()
     model.includeEventhdlr(hdlr, "gapEventHandler", "Event handler which collects primal and dual solution evolution")
 

tests/test_relax.py

@@ -47,6 +47,7 @@ def test_relaxator():
 class EmptyRelaxator(Relax):
     pass
 
+@pytest.mark.filterwarnings("ignore::pytest.PytestUnraisableExceptionWarning")
 def test_empty_relaxator():
     m = Model()
     m.setPresolve(SCIP_PARAMSETTING.OFF)
@@ -64,9 +65,8 @@ def test_empty_relaxator():
 
     m.setObjective(x1 + x0)
 
-    with pytest.raises(Exception):
-        with pytest.raises(AssertionError):
-            m.optimize()
+    with pytest.raises(Exception, match="SCIP"):
+        m.optimize()
 
 def test_relax():
     model = random_mip_1()