Changeset 1191

Timestamp:

12/11/22 16:07:08 (16 months ago)

Author:

Maciej Komosinski

Message:

Cosmetic

File:

• framspy/FramsticksEvolution.py (modified) (3 diffs)

framspy/FramsticksEvolution.py

@@ -64 +64 @@
 
 
-def prepareToolbox(frams_cli, tournament_size, genetic_format, initial_genotype):
+def prepareToolbox(frams_cli, OPTIMIZATION_CRITERIA, tournament_size, genetic_format, initial_genotype):
         creator.create("FitnessMax", base.Fitness, weights=[1.0] * len(OPTIMIZATION_CRITERIA))
         creator.create("Individual", list, fitness=creator.FitnessMax)  # would be nice to have "str" instead of unnecessary "list of str"
@@ -134 +134 @@
 
 
-if __name__ == "__main__":
+def main():
+        global parsed_args, OPTIMIZATION_CRITERIA  # needed in frams_evaluate(), so made global to avoid passing as arguments
+
         # random.seed(123)  # see FramsticksLib.DETERMINISTIC below, set to True if you want full determinism
         FramsticksLib.DETERMINISTIC = False  # must be set before FramsticksLib() constructor call
         parsed_args = parseArguments()
         print("Argument values:", ", ".join(['%s=%s' % (arg, getattr(parsed_args, arg)) for arg in vars(parsed_args)]))
-
         OPTIMIZATION_CRITERIA = parsed_args.opt.split(",")
         framsLib = FramsticksLib(parsed_args.path, parsed_args.lib, parsed_args.sim.split(";"))
-
-        toolbox = prepareToolbox(framsLib, parsed_args.tournament, '1' if parsed_args.genformat is None else parsed_args.genformat, parsed_args.initialgenotype)
-
+        toolbox = prepareToolbox(framsLib, OPTIMIZATION_CRITERIA, parsed_args.tournament, '1' if parsed_args.genformat is None else parsed_args.genformat, parsed_args.initialgenotype)
         pop = toolbox.population(n=parsed_args.popsize)
         hof = tools.HallOfFame(parsed_args.hof_size)
@@ -152 +151 @@
         stats.register("min", np.min)
         stats.register("max", np.max)
-
         pop, log = algorithms.eaSimple(pop, toolbox, cxpb=parsed_args.pxov, mutpb=parsed_args.pmut, ngen=parsed_args.generations, stats=stats, halloffame=hof, verbose=True)
         print('Best individuals:')
         for ind in hof:
                 print(ind.fitness, '\t-->\t', ind[0])
-
         if parsed_args.hof_savefile is not None:
                 save_genotypes(parsed_args.hof_savefile, OPTIMIZATION_CRITERIA, hof)
+
+
+if __name__ == "__main__":
+        main()