Changeset 1306 for framspy/evolalg

Timestamp:

05/13/24 03:59:10 (8 months ago)

Author:

Maciej Komosinski

Message:

Introduced symbolic names for dissimilarity estimation methods

Location:

framspy/evolalg

Files:

• base/experiment_niching_abc.py (modified) (2 diffs)
• tests/test_diferent_settings.py (modified) (3 diffs)

framspy/evolalg/base/experiment_niching_abc.py

@@ -10 +10 @@
 from .experiment_abc import ExperimentABC
 from .remove_diagonal import remove_diagonal
+from FramsticksLib import DissimMethod  # since the descendant ExperimentFramsNiching class does not introduce any Framsticks-specific dissimilarity methods, all of them must be known here (in ExperimentNiching)
 
 
@@ -189 +190 @@
     def get_args_for_parser():
         parser = ExperimentABC.get_args_for_parser()
-        parser.add_argument("-dissim",type= int, default=1,
-                   help="Dissimilarity measure type. Available: -3:freq, -2:dens, -1:Leven, 1:frams-struct (default}, 2:frams-descr")
+        parser.add_argument("-dissim", type = lambda arg: DissimMethod[arg], choices = DissimMethod,
+                   default=DissimMethod.PHENE_STRUCT_OPTIM,
+                   help="Dissimilarity measure type. Available: " + str(DissimMethod._member_names_))
         parser.add_argument("-fit",type= str, default="raw",
                         help="Fitness type, availible types: niching, novelty, knn_niching (local), knn_novelty (local), nsga2, nslc and raw (default)")

framspy/evolalg/tests/test_diferent_settings.py

@@ -3 +3 @@
 import numpy as np
 
-from FramsticksLib import FramsticksLib
+from FramsticksLib import FramsticksLib, DissimMethod
 
 from ..frams_base.experiment_frams_niching import ExperimentFramsNiching
@@ -14 +14 @@
 
 
-GENERATIONS = 10 
+GENERATIONS = 10
 
 SETTINGS_TO_TEST_NUMERIC = {
@@ -47 +47 @@
     'hof_size': [0, 10],
     'normalize': ['none', 'max', 'sum'],
-    'dissim': [-2, -1, 1, 2],
+    'dissim': [DissimMethod.GENE_LEVENSHTEIN, DissimMethod.PHENE_STRUCT_OPTIM, DissimMethod.PHENE_DESCRIPTORS, DissimMethod.PHENE_DENSITY_FREQ],
     'fit': ['niching', 'novelty', 'nsga2', 'nslc', 'raw'],
     'genformat': ['1'],