Changeset 1195 for framspy

Timestamp:

02/01/23 22:58:25 (22 months ago)

Author:

Maciej Komosinski

Message:

Cosmetic

Location:

framspy

Files:

• FramsticksEvolution.py (modified) (4 diffs)
• README.txt (modified) (1 diff)
• evolalg/base/experiment_niching_abc.py (modified) (1 diff)
• frams-test.py (modified) (1 diff)

framspy/FramsticksEvolution.py

@@ -21 +21 @@
 
 
-def frams_evaluate(frams_cli, individual):
+def frams_evaluate(frams_lib, individual):
         BAD_FITNESS = [-1] * len(OPTIMIZATION_CRITERIA)  # fitness of -1 is intended to discourage further propagation of this genotype via selection ("this genotype is very poor")
         genotype = individual[0]  # individual[0] because we can't (?) have a simple str as a deap genotype/individual, only list of str.
-        data = frams_cli.evaluate([genotype])
+        data = frams_lib.evaluate([genotype])
         # print("Evaluated '%s'" % genotype, 'evaluation is:', data)
         valid = True
@@ -47 +47 @@
 
 
-def frams_crossover(frams_cli, individual1, individual2):
+def frams_crossover(frams_lib, individual1, individual2):
         geno1 = individual1[0]  # individual[0] because we can't (?) have a simple str as a deap genotype/individual, only list of str.
         geno2 = individual2[0]  # individual[0] because we can't (?) have a simple str as a deap genotype/individual, only list of str.
-        individual1[0] = frams_cli.crossOver(geno1, geno2)
-        individual2[0] = frams_cli.crossOver(geno1, geno2)
+        individual1[0] = frams_lib.crossOver(geno1, geno2)
+        individual2[0] = frams_lib.crossOver(geno1, geno2)
         return individual1, individual2
 
 
-def frams_mutate(frams_cli, individual):
-        individual[0] = frams_cli.mutate([individual[0]])[0]  # individual[0] because we can't (?) have a simple str as a deap genotype/individual, only list of str.
+def frams_mutate(frams_lib, individual):
+        individual[0] = frams_lib.mutate([individual[0]])[0]  # individual[0] because we can't (?) have a simple str as a deap genotype/individual, only list of str.
         return individual,
 
 
-def frams_getsimplest(frams_cli, genetic_format, initial_genotype):
-        return initial_genotype if initial_genotype is not None else frams_cli.getSimplest(genetic_format)
+def frams_getsimplest(frams_lib, genetic_format, initial_genotype):
+        return initial_genotype if initial_genotype is not None else frams_lib.getSimplest(genetic_format)
 
 
-def prepareToolbox(frams_cli, OPTIMIZATION_CRITERIA, tournament_size, genetic_format, initial_genotype):
+def prepareToolbox(frams_lib, 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"
 
         toolbox = base.Toolbox()
-        toolbox.register("attr_simplest_genotype", frams_getsimplest, frams_cli, genetic_format, initial_genotype)  # "Attribute generator"
+        toolbox.register("attr_simplest_genotype", frams_getsimplest, frams_lib, genetic_format, initial_genotype)  # "Attribute generator"
         # (failed) struggle to have an individual which is a simple str, not a list of str
         # toolbox.register("individual", tools.initRepeat, creator.Individual, toolbox.attr_frams)
@@ -78 +78 @@
         toolbox.register("individual", tools.initRepeat, creator.Individual, toolbox.attr_simplest_genotype, 1)
         toolbox.register("population", tools.initRepeat, list, toolbox.individual)
-        toolbox.register("evaluate", frams_evaluate, frams_cli)
-        toolbox.register("mate", frams_crossover, frams_cli)
-        toolbox.register("mutate", frams_mutate, frams_cli)
+        toolbox.register("evaluate", frams_evaluate, frams_lib)
+        toolbox.register("mate", frams_crossover, frams_lib)
+        toolbox.register("mutate", frams_mutate, frams_lib)
         if len(OPTIMIZATION_CRITERIA) <= 1:
                 toolbox.register("select", tools.selTournament, tournsize=tournament_size)
@@ -90 +90 @@
 def parseArguments():
         parser = argparse.ArgumentParser(description='Run this program with "python -u %s" if you want to disable buffering of its output.' % sys.argv[0])
-        parser.add_argument('-path', type=ensureDir, required=True, help='Path to Framsticks CLI without trailing slash.')
-        parser.add_argument('-lib', required=False, help='Library name. If not given, "frams-objects.dll" or "frams-objects.so" is assumed depending on the platform.')
+        parser.add_argument('-path', type=ensureDir, required=True, help='Path to Framsticks library without trailing slash.')
+        parser.add_argument('-lib', required=False, help='Library name. If not given, "frams-objects.dll" (or .so or .dylib) is assumed depending on the platform.')
         parser.add_argument('-sim', required=False, default="eval-allcriteria.sim", help="The name of the .sim file with settings for evaluation, mutation, crossover, and similarity estimation. If not given, \"eval-allcriteria.sim\" is assumed by default. Must be compatible with the \"standard-eval\" expdef. If you want to provide more files, separate them with a semicolon ';'.")
 

framspy/README.txt

@@ -5 +5 @@
 
 "frams.py" is the most fundamental file. It allows to access Framsticks script
-objects in Python. You will find detailed descriptions in the source of this file.
+objects in Python. You will find detailed descriptions in the source of this file,
+but since this file is only responsible for buidling the low-level bridge between
+Framsticks and Python, understanding and modifying it should not be necessary.
 
 "frams-test.py" uses "frams.py" and tests the connection between Python
 and the native Framsticks library by performing a number of simple yet diversified
-operations,  so you should run it first to ensure everything works correctly. 
+operations, so you should run it first to ensure everything works correctly.
+This file can also be treated as a set of examples and demonstrations on how to access
+Framsticks genotypes, the simulation, body parts, neurons, etc.
 Again, read the comments in the source for more information.
 
-"FramsticksLib.py" uses "frams.py" and provides a few fundamental building blocks
+"FramsticksLib.py" uses "frams.py" and provides a few fundamental, high-level building blocks
 for optimization: functions to mutate, crossover, evaluate a solution, etc.
 

framspy/evolalg/base/experiment_niching_abc.py

@@ -193 +193 @@
                             help="What normalization use for dissimilarity matrix, max (default}, sum and none")
         parser.add_argument("-knn",type= int, default= 0,
-                        help="Nearest neighbors parameter for local novelty/niching, if knn==0 global is performed.Default:0")
+                        help="Nearest neighbors parameter for local novelty/niching, if knn==0 global is performed. Default: 0")
         return parser 
         

framspy/frams-test.py

@@ -106 +106 @@
 
 matrix = np.zeros((20, 20, 20), dtype=int)  # 3D matrix, "voxels"
-m = frams.ModelGeometry.forModel(frams.Model.newFromString(geno));
-m.geom_density = 20;
+m = frams.ModelGeometry.forModel(frams.Model.newFromString(geno))
+m.geom_density = 20
 for p in m.voxels():
         # print('%f %f %f ' % (p.x._value(), p.y._value(), p.z._value()))