there may be no best model at the end of iteration

certara · Sep 22, 2023 · a3501c6 · a3501c6
1 parent f29c7cf
commit a3501c6
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Showing 2 changed files with 10 additions and 10 deletions.
diff --git a/src/darwin/algorithms/GA.py b/src/darwin/algorithms/GA.py
@@ -112,7 +112,6 @@ def run_ga(model_template: Template) -> ModelRun:
         return GlobalVars.best_run
 
     generations_no_change = 0
-    overall_best_fitness = options.crash_value
 
     # Begin evolution
     while runner.run_generation():
@@ -122,22 +121,21 @@ def run_ga(model_template: Template) -> ModelRun:
             runner.run_downhill(population)
 
         best_run = population.get_best_run()
-
         best_fitness = best_run.result.fitness
 
         log.message(f"Current generation best genome = {best_run.model.model_code.FullBinCode},"
                     f" best fitness = {best_fitness:.4f}")
 
-        best_run_overall = GlobalVars.best_run
+        best_run_overall = GlobalVars.best_run or best_run
+        overall_best_fitness = best_run_overall.result.fitness
 
         log.message(f"Best overall fitness = {best_run_overall.result.fitness:4f},"
                     f" iteration {best_run_overall.generation}, model {best_run_overall.model_num}")
 
         if best_fitness < overall_best_fitness:
+            generations_no_change = 0
             log.message(f"Better fitness found, generation = {runner.generation},"
                         f" new best fitness = {best_fitness:.4f}")
-            overall_best_fitness = best_fitness
-            generations_no_change = 0
         else:
             generations_no_change += 1
             log.message(f"No change in fitness for {generations_no_change} generations,"

diff --git a/src/darwin/algorithms/OPT.py b/src/darwin/algorithms/OPT.py
@@ -143,18 +143,20 @@ def run_skopt(model_template: Template) -> ModelRun:
 
         log.message(f"Done telling")
 
-        best_fitness = heapq.nsmallest(1, fitnesses)[0]
+        best_run = population.get_best_run()
 
-        best_run = GlobalVars.best_run
+        best_fitness = best_run.result.fitness
 
-        if best_fitness < best_run.result.fitness:
+        best_run_overall = GlobalVars.best_run or best_run
+
+        if best_fitness < best_run_overall.result.fitness:
             niter_no_change = 0
         else:
             niter_no_change += 1
 
         log.message(f"Best fitness this iteration = {best_fitness:4f}  at {time.asctime()}")
-        log.message(f"Best overall fitness = {best_run.result.fitness:4f},"
-                    f" iteration {best_run.generation}, model {best_run.model_num}")
+        log.message(f"Best overall fitness = {best_run_overall.result.fitness:4f},"
+                    f" iteration {best_run_overall.generation}, model {best_run_overall.model_num}")
 
     if options.final_downhill_search and keep_going():
         log.message(f"Starting final downhill")