Merge pull request #218 from Happy-Algorithms-League/examples/command…

…_line_args

Add command line args for example scripts

.flake8

@@ -4,3 +4,5 @@ max-line-length = 99
 max-complexity = 18
 select = B,C,E,F,W,T4,B9
 exclude = __init__.py
+per-file-ignores =
+    examples/*:E402

examples/example_differential_evo_regression.py

@@ -20,15 +20,30 @@
 
 """
 
+# The docopt str is added explicitly to ensure compatibility with
+# sphinx-gallery.
+docopt_str = """
+  Usage:
+    example_differential_evo_regression.py [--max-generations=<N>]
+
+  Options:
+    -h --help
+    --max-generations=<N>  Maximum number of generations [default: 2000]
+
+"""
+
 import functools
 
 import matplotlib.pyplot as plt
 import numpy as np
 import scipy.constants
 import torch
+from docopt import docopt
 
 import cgp
 
+args = docopt(docopt_str)
+
 # %%
 # We first define the target function. Note that this function contains
 # numeric values which are initially not available as constants to the search.
@@ -92,7 +107,7 @@ def objective(individual, seed):
 
 ea_params = {"n_offsprings": 4, "tournament_size": 1, "n_processes": 1, "k_local_search": 2}
 
-evolve_params = {"max_generations": 2000, "min_fitness": 0.0}
+evolve_params = {"max_generations": int(args["--max-generations"]), "min_fitness": 0.0}
 
 # use an uneven number of gradient steps so they can not easily
 # average out for clipped values

examples/example_evo_regression.py

@@ -6,16 +6,29 @@
 two regression tasks.
 """
 
+# The docopt str is added explicitly to ensure compatibility with
+# sphinx-gallery.
+docopt_str = """
+   Usage:
+     example_evo_regression.py [--max-generations=<N>]
+
+   Options:
+     -h --help
+     --max-generations=<N>  Maximum number of generations [default: 1000]
+"""
 
 import functools
 import warnings
 
 import matplotlib.pyplot as plt
 import numpy as np
 import scipy.constants
+from docopt import docopt
 
 import cgp
 
+args = docopt(docopt_str)
+
 # %%
 # We first define target functions. For illustration purposes, we
 # define two functions which present different levels of difficulty
@@ -123,7 +136,7 @@ def evolution(f_target):
 
     ea_params = {"n_offsprings": 10, "tournament_size": 2, "n_processes": 2}
 
-    evolve_params = {"max_generations": 1000, "min_fitness": 0.0}
+    evolve_params = {"max_generations": int(args["--max-generations"]), "min_fitness": 0.0}
 
     # create population that will be evolved
     pop = cgp.Population(**population_params, genome_params=genome_params)

examples/example_mountain_car.py

@@ -12,13 +12,25 @@
 
 """
 
+# The docopt str is added explicitly to ensure compatibility with
+# sphinx-gallery.
+docopt_str = """
+  Usage:
+    example_parametrized_nodes.py [--max-generations=<N>] [--visualize-final-champion]
+
+  Options:
+    -h --help
+    --max-generations=<N>  Maximum number of generations [default: 1500]
+    --visualize-final-champion  Create animation of final champion in the mountain car env.
+"""
 
 import functools
 import warnings
 
 import matplotlib.pyplot as plt
 import numpy as np
 import sympy
+from docopt import docopt
 
 import cgp
 
@@ -30,6 +42,8 @@
     )
 
 
+args = docopt(docopt_str)
+
 # %%
 # For more flexibility in the evolved expressions, we define two
 # constants that can be used in the expressions, with values 0.1 and
@@ -154,7 +168,7 @@ def evolve(seed):
 
     ea_params = {"n_offsprings": 4, "tournament_size": 1, "n_processes": 4}
 
-    evolve_params = {"max_generations": 1500, "min_fitness": 100.0}
+    evolve_params = {"max_generations": int(args["--max-generations"]), "min_fitness": 100.0}
 
     pop = cgp.Population(**population_params, genome_params=genome_params)
 
@@ -288,4 +302,5 @@ def f(x):
 
     plot_fitness_over_generation_index(history)
     evaluate_champion(champion)
-    # visualize_behaviour_for_evolutionary_jumps(seed, history)
+    if args["--visualize-final-champion"]:
+        visualize_behaviour_for_evolutionary_jumps(seed, history)

examples/example_parametrized_nodes.py

@@ -9,16 +9,30 @@
 
 """
 
+# The docopt str is added explicitly to ensure compatibility with
+# sphinx-gallery.
+docopt_str = """
+  Usage:
+    example_parametrized_nodes.py [--max-generations=<N>]
+
+  Options:
+    -h --help
+    --max-generations=<N>  Maximum number of generations [default: 500]
+"""
+
 import functools
 import math
 
 import matplotlib.pyplot as plt
 import numpy as np
 import scipy.constants
 import torch
+from docopt import docopt
 
 import cgp
 
+args = docopt(docopt_str)
+
 # %%
 # We first define a new node that adds two inputs then scales and
 # finally shifts the result. The scale ("w") and shift factors ("b")
@@ -99,7 +113,7 @@ def objective(individual, seed):
 
 ea_params = {"n_offsprings": 4, "tournament_size": 1, "n_processes": 2}
 
-evolve_params = {"max_generations": 500, "min_fitness": 0.0}
+evolve_params = {"max_generations": int(args["--max-generations"]), "min_fitness": 0.0}
 
 local_search_params = {"lr": 1e-3, "gradient_steps": 9}
 

requirements.txt

@@ -1 +1,2 @@
 numpy ~= 1.18.3
+docopt-ng~=0.7.2