Changeset 1140 for framspy/evolalg/examples

Timestamp:

05/08/21 20:10:15 (4 years ago)

Author:

Maciej Komosinski

Message:

Introduced a parameter for the size of the hall of fame

Location:

framspy/evolalg/examples

Files:

• niching_novelty.py (modified) (2 diffs)
• standard.py (modified) (4 diffs)

framspy/evolalg/examples/niching_novelty.py

@@ -77 +77 @@
     parser.add_argument('-max_numconnections', type=int, default=None, help="Maximum number of Neural connections. Default: no limit")
 
+    parser.add_argument('-hof_size', type=int, default=10, help="Number of genotypes in Hall of Fame. Default: 10.")
     parser.add_argument('-hof_evaluations', type=int, default=20, help="Number of final evaluations of each genotype in Hall of Fame to obtain reliable (averaged) fitness. Default: 20.")
     parser.add_argument('-checkpoint_path', required=False, default=None, help="Path to the checkpoint file")
@@ -243 +244 @@
     # -------------------------------------------------
     # Statistics
-    hall_of_fame = HallOfFameStatistics(100, "fitness_raw")  # Wrapper for halloffamae
+    hall_of_fame = HallOfFameStatistics(parsed_args.hof_size, "fitness_raw")  # Wrapper for halloffamae
     replace_with_hof = ReplaceWithHallOfFame(hall_of_fame)
     statistics_deap = StatisticsDeap([

framspy/evolalg/examples/standard.py

@@ -7 +7 @@
 # TODO extend both standard.py and steadystate.py to support >1 criteria (using DEAP's selNSGA2() and selSPEA2())
 # TODO add comments to all examples in this directory
-# TODO add to standard.py and steadystate.py evaluating each genotype in HOF N (configurable, default 10) times when the evolution ends instead of evaluating the last population as it is now in niching_novelty.py
-# TODO "debug" mode, displaying Step-based class names and their arguments so it is easy to see what happens during evolution
+# TODO add to standard.py and steadystate.py evaluating each genotype in HOF N (configurable, default 20) times when the evolution ends, as it is in niching_novelty.py
+# TODO "--debug" mode, indent nested steps (pre++, post-- of a static counter?) and print their arguments so it is easy to see what happens during evolution
 
 
@@ -43 +43 @@
                         help='optimization criteria : vertpos, velocity, distance, vertvel, lifespan, numjoints, numparts, numneurons, numconnections (or other as long as it is provided by the .sim file and its .expdef). Single or multiple criteria.')
     parser.add_argument('-lib', required=False, help="Filename of .so or .dll with the Framsticks library")
+
     parser.add_argument('-genformat', required=False, default="1",
                         help='Genetic format for the demo run, for example 4, 9, or B. If not given, f1 is assumed.')
@@ -49 +50 @@
     parser.add_argument('-generations', type=int, default=5, help="Number of generations, default 5.")
     parser.add_argument('-tournament', type=int, default=5, help="Tournament size, default 5.")
+
+    parser.add_argument('-hof_size', type=int, default=10, help="Number of genotypes in Hall of Fame. Default: 10.")
     return parser.parse_args()
 
@@ -65 +68 @@
     frams_lib = FramsticksLib(parsed_args.path, parsed_args.lib, parsed_args.sim)
 
-    hall_of_fame = HallOfFameStatistics(100, "fitness")
+    hall_of_fame = HallOfFameStatistics(parsed_args.hof_size, "fitness")
     statistics_union = UnionStep([
         hall_of_fame,