Cap sim now avoids optimization when running for cap graph request

eos/capSim.py

@@ -46,6 +46,10 @@ class CapSimulator:
         self.saved_changes = ()
         self.saved_changes_internal = None
 
+        # Reports if sim was stopped due to detecting stability early
+        self.optimize_repeats = True
+        self.result_optimized_repeats = None
+
     def scale_activation(self, duration, capNeed):
         for res in self.scale_resolutions:
             mod = duration % res
@@ -73,6 +77,7 @@ class CapSimulator:
         """Reset the simulator state"""
         self.state = []
         self.saved_changes_internal = {}
+        self.result_optimized_repeats = False
         mods = {}
         period = 1
         disable_period = False
@@ -175,7 +180,8 @@ class CapSimulator:
                     # history is repeating itself, so if we have more cap now than last
                     # time this happened, it is a stable setup.
                     awaitingInjectorsCounterNow = Counter(awaitingInjectors)
-                    if cap >= cap_wrap and awaitingInjectorsCounterNow == awaitingInjectorsCounterWrap:
+                    if self.optimize_repeats and cap >= cap_wrap and awaitingInjectorsCounterNow == awaitingInjectorsCounterWrap:
+                        self.result_optimized_repeats = True
                         break
                     cap_wrap = round(cap, stability_precision)
                     awaitingInjectorsCounterWrap = awaitingInjectorsCounterNow

eos/saveddata/fit.py

@@ -1284,12 +1284,16 @@ class Fit:
 
     def getCapSimData(self, startingCap):
         if startingCap not in self.__savedCapSimData:
-            self.__runCapSim(startingCap=startingCap)
+            self.__runCapSim(startingCap=startingCap, tMax=3600, optimizeRepeats=False)
         return self.__savedCapSimData[startingCap]
 
-    def __runCapSim(self, drains=None, startingCap=None):
+    def __runCapSim(self, drains=None, startingCap=None, tMax=None, optimizeRepeats=True):
         if drains is None:
             drains, nil, nil = self.__generateDrain()
+        if tMax is None:
+            tMax = 6 * 60 * 60 * 1000
+        else:
+            tMax *= 1000
         sim = capSim.CapSimulator()
         sim.init(drains)
         sim.capacitorCapacity = self.ship.getModifiedItemAttr("capacitorCapacity")
@@ -1297,10 +1301,13 @@ class Fit:
         sim.startingCapacity = startingCap = self.ship.getModifiedItemAttr("capacitorCapacity") if startingCap is None else startingCap
         sim.stagger = True
         sim.scale = False
-        sim.t_max = 6 * 60 * 60 * 1000
+        sim.t_max = tMax
         sim.reload = self.factorReload
+        sim.optimize_repeats = optimizeRepeats
         sim.run()
-        self.__savedCapSimData[startingCap] = sim.saved_changes
+        # We do not want to store partial results
+        if not sim.result_optimized_repeats:
+            self.__savedCapSimData[startingCap] = sim.saved_changes
         return sim
 
     def getRemoteReps(self, spoolOptions=None):