From ec1b67fc006aa133085bedb344fa0af08065d747 Mon Sep 17 00:00:00 2001
From: danielwilczak101 <44122838+danielwilczak101@users.noreply.github.com>
Date: Thu, 15 Oct 2020 01:46:13 -0400
Subject: [PATCH] Added Default for gene impl and setter example in Easy GA

---
 src/EasyGA.py      | 13 ++++++++++++-
 src/run_testing.py | 13 ++-----------
 src/test_EasyGA.py | 11 ++++++-----
 3 files changed, 20 insertions(+), 17 deletions(-)

diff --git a/src/EasyGA.py b/src/EasyGA.py
index d202507..edb60f2 100644
--- a/src/EasyGA.py
+++ b/src/EasyGA.py
@@ -27,7 +27,7 @@ class GA:
         self.chromosome_length   = 10
         self.population_size     = 10
         self.chromosome_impl     = None
-        self.gene_impl           = None
+        self.gene_impl           = lambda: random.randint(1, 10)
         self.population          = None
         self.target_fitness_type = 'maximum'
         self.update_fitness      = True
@@ -136,3 +136,14 @@ class GA:
         return sorted(chromosome_set,                                    # list to be sorted
                      key = lambda chromosome: chromosome.get_fitness(),  # by fitness
                      reverse = True)                                     # from highest to lowest fitness
+
+    # Example of how the setter error checking will look like
+    @property
+    def chromosome_length(self):
+        return self._chromosome_length
+
+    @chromosome_length.setter
+    def chromosome_length(self, value_input):
+        if(value_input == 0):
+            raise ValueError("Sorry your chromosome length must be greater then 0")
+        self._chromosome_length = value_input
diff --git a/src/run_testing.py b/src/run_testing.py
index d619f1b..96827e5 100644
--- a/src/run_testing.py
+++ b/src/run_testing.py
@@ -3,19 +3,10 @@ import EasyGA
 
 # Create the Genetic algorithm
 ga = EasyGA.GA()
-ga.population_size = 25
-ga.generation_goal = 100
-ga.gene_impl       = lambda: random.randint(1, 10)
-ga.selection_probability = 0.5
-ga.fitness_function_impl     = EasyGA.Fitness_Examples.near_5
-ga.parent_selection_impl     = EasyGA.Parent_Selection.Roulette.stochastic_selection
-ga.crossover_population_impl = EasyGA.Crossover_Methods.Population.sequential_selection
-ga.crossover_individual_impl = EasyGA.Crossover_Methods.Individual.Arithmetic.int_random
-ga.survivor_selection_impl   = EasyGA.Survivor_Selection.fill_in_best
+
+ga.chromosome_length = 0
 
 ga.evolve()
-ga.set_all_fitness()
-ga.population.sort_by_best_fitness(ga)
 
 print(f"Current Generation: {ga.current_generation}")
 ga.population.print_all()
diff --git a/src/test_EasyGA.py b/src/test_EasyGA.py
index 0d8bda7..dcc1586 100644
--- a/src/test_EasyGA.py
+++ b/src/test_EasyGA.py
@@ -5,12 +5,13 @@ import EasyGA
     # python3 -m pytest
 
 def test_chromosome_length():
-    ga = EasyGA.GA()
-    ga.chromosome_length = 100
-    ga.evolve()
+    for i in range(0,100):
+        ga = EasyGA.GA()
+        ga.chromosome_length = 100
+        ga.evolve()
 
-    """ Test to see if the actual chromosome length is the same as defined."""
-    assert ga.population.chromosome_list[0].size() == ga.chromosome_length
+        """ Test to see if the actual chromosome length is the same as defined."""
+        assert ga.population.chromosome_list[0].size() == ga.chromosome_length
 
 def test_second():