Merge pull request #187 from ahmedfgad/github-actions

GitHub Actions Workflows and new additions

Author: ahmedfgad

.github/workflows/main.yml

@@ -0,0 +1,37 @@
+name: Testing PyGAD using PyTest
+
+on:
+  push:
+    branches:
+      - github-actions
+      # - master
+
+jobs:
+  job_id_1:
+    runs-on: ubuntu-latest
+    name: PyTest Workflow Job
+
+    steps:
+      - name: Checkout Pre-Built Action
+        uses: actions/checkout@v3
+
+      - name: Setup Python 3.10
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.10' 
+
+      - name: Build PyGAD from the Repository
+        run: |
+          python3 -m pip install --upgrade build
+          python3 -m build
+
+      - name: Install PyGAD after Building the .whl File
+        run: |
+          find ./dist/*.whl | xargs pip install
+
+      - name: Install PyTest
+        run: pip install pytest
+
+      - name: Run the Tests by Calling PyTest
+        run: |
+          pytest

example.py renamed to examples/example.py

@@ -119,4 +119,4 @@ def fitness_func(ga_instance, solution, solution_idx):
     matplotlib.pyplot.scatter(cluster_x, cluster_y)
     matplotlib.pyplot.scatter(cluster_centers[cluster_idx, 0], cluster_centers[cluster_idx, 1], linewidths=5)
 matplotlib.pyplot.title("Clustering using PyGAD")
-matplotlib.pyplot.show()
+matplotlib.pyplot.show()

example_clustering_2.py renamed to examples/example_clustering_2.py

@@ -71,4 +71,4 @@ def mutation_func(offspring, ga_instance):
                        mutation_type=mutation_func)
 
 ga_instance.run()
-ga_instance.plot_fitness()
+ga_instance.plot_fitness()

example_clustering_3.py renamed to examples/example_clustering_3.py

@@ -0,0 +1,41 @@
+import pygad
+import numpy
+
+"""
+All the callback functions/methods in PyGAD have limits in the number of arguments passed.
+For example, the fitness function accepts only 3 arguments:
+    1. The pygad.GA instance.
+    2. The solution(s).
+    3. The index (indices) of the passed solution(s).
+If it is necessary to pass extra arguments to the fitness function, for example, then follow these steps:
+    1. Create a wrapper function that accepts only the number of arguments meeded by PyGAD.
+    2. Define the extra arguments in the body of the wrapper function.
+    3. Create an inner fitness function inside the wrapper function with whatever extra arguments needed.
+    4. Call the inner fitness function from the wrapper function while passing the extra arguments.
+
+This is an example that passes a list ([10, 20, 30]) to the inner fitness function. The list has 3 numbers.
+A number is randomly selected from the list and added to the calculated fitness.
+"""
+
+function_inputs = [4,-2,3.5,5,-11,-4.7]
+desired_output = 44
+
+def fitness_func_wrapper(ga_instanse, solution, solution_idx):
+    def fitness_func(ga_instanse, solution, solution_idx, *args):
+        output = numpy.sum(solution*function_inputs)
+        output += numpy.random.choice(args)
+        fitness = 1.0 / (numpy.abs(output - desired_output) + 0.000001)
+        return fitness
+    args = [10, 20, 30]
+    fitness = fitness_func(ga_instanse, solution, solution_idx, *args)
+    return fitness
+
+ga_instance = pygad.GA(num_generations=3,
+                       num_parents_mating=5,
+                       fitness_func=fitness_func_wrapper,
+                       sol_per_pop=10,
+                       num_genes=len(function_inputs),
+                       suppress_warnings=True)
+
+ga_instance.run()
+ga_instance.plot_fitness()

example_custom_operators.py renamed to examples/example_custom_operators.py

@@ -0,0 +1,4 @@
+from .cnn import *
+
+__version__ = "1.0.0"
+