Hallucinate a progress bar of sorts for the heat calculations

Nifty

graphs/data/fitHeat/calc.py

@@ -121,7 +121,12 @@ def _get_cycle_time_s(mod):
     return avg_time_ms / 1000.0
 
 
-def get_first_burnout_samples(fit, rack_slot, max_time_s, iterations):
+def has_burnout_samples(fit, rack_slot, max_time_s, iterations):
+    cache_key = (getattr(fit, "ID", None), int(rack_slot), max_time_s, iterations)
+    return cache_key in _burnout_samples_cache
+
+
+def get_first_burnout_samples(fit, rack_slot, max_time_s, iterations, progress_cb=None):
     """
     Monte Carlo simulation of time until the first module in the given rack burns out.
     Returns a list of burnout times (seconds). If no burnout happens before max_time_s,
@@ -178,7 +183,7 @@ def get_first_burnout_samples(fit, rack_slot, max_time_s, iterations):
 
     samples = []
 
-    for _ in range(iterations):
+    for i in range(iterations):
         hp = list(base_hp)
         dead = [hp_val <= 0 for hp_val in hp]
         online_counts = dict(base_online_counts)
@@ -280,6 +285,11 @@ def get_first_burnout_samples(fit, rack_slot, max_time_s, iterations):
 
         samples.append(sample_time)
 
+        if progress_cb is not None:
+            # progress_cb should return True to continue, False to cancel
+            if not progress_cb(i + 1):
+                break
+
     _burnout_samples_cache[cache_key] = samples
     return samples
 

graphs/data/fitHeat/getter.py

@@ -20,7 +20,8 @@
 
 from eos.const import FittingSlot
 from graphs.data.base import SmoothPointGetter
-from .calc import get_first_burnout_samples, get_rack_heat_value
+import wx
+from .calc import get_first_burnout_samples, get_rack_heat_value, has_burnout_samples
 
 
 class _BaseTime2RackHeatGetter(SmoothPointGetter):
@@ -64,9 +65,41 @@ class _BaseTime2BurnoutCdfGetter(SmoothPointGetter):
             iterations = self._iterations
         if iterations <= 0:
             iterations = self._iterations
-        samples = get_first_burnout_samples(
-            fit=fit, rack_slot=self.rack_slot, max_time_s=max_sim_time, iterations=iterations
-        )
+        samples = None
+        # Show a progress dialog only on cache miss for expensive runs
+        if iterations >= 1000 and not has_burnout_samples(fit, self.rack_slot, max_sim_time, iterations):
+            app = wx.GetApp()
+            parent = app.GetTopWindow() if app is not None else None
+            dlg = wx.ProgressDialog(
+                "Computing burnout CDF",
+                "Running overheating simulations...",
+                maximum=iterations,
+                parent=parent,
+                style=wx.PD_APP_MODAL | wx.PD_ELAPSED_TIME | wx.PD_AUTO_HIDE,
+            )
+
+            def progress_cb(done):
+                # dlg.Update returns (continue, skip)
+                cont, _ = dlg.Update(done)
+                return cont
+
+            try:
+                samples = get_first_burnout_samples(
+                    fit=fit,
+                    rack_slot=self.rack_slot,
+                    max_time_s=max_sim_time,
+                    iterations=iterations,
+                    progress_cb=progress_cb,
+                )
+            finally:
+                dlg.Destroy()
+        else:
+            samples = get_first_burnout_samples(
+                fit=fit,
+                rack_slot=self.rack_slot,
+                max_time_s=max_sim_time,
+                iterations=iterations,
+            )
         xs = []
         ys = []
         if not samples:
@@ -98,7 +131,10 @@ class _BaseTime2BurnoutCdfGetter(SmoothPointGetter):
         if iterations <= 0:
             iterations = self._iterations
         samples = get_first_burnout_samples(
-            fit=fit, rack_slot=self.rack_slot, max_time_s=max_sim_time, iterations=iterations
+            fit=fit,
+            rack_slot=self.rack_slot,
+            max_time_s=max_sim_time,
+            iterations=iterations,
         )
         if not samples:
             return 0.0