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Cleaned code and added functions to graph

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This commit is contained in:
danielwilczak101
2020-11-13 01:43:15 -05:00
parent efb69f88ea
commit 2cfb840198
2 changed files with 42 additions and 24 deletions
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52
src/database/matplotlib_graph.py
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@ -4,7 +4,8 @@ import matplotlib.pyplot as plt
class Matplotlib_Graph: class Matplotlib_Graph:
"""Prebuilt graphing functions to make visual represention of fitness data.""" """Prebuilt graphing functions to make visual represention of fitness data."""
type_of_plot_dict = { # Common graphing functions
type_of_graph_dict = {
'line' : plt.plot, 'line' : plt.plot,
'scatter' : plt.scatter, 'scatter' : plt.scatter,
'bar' : plt.bar 'bar' : plt.bar
@ -12,7 +13,10 @@ class Matplotlib_Graph:
def __init__(self, database): def __init__(self, database):
self.database = database self.database = database
self.type_of_plot = 'line' self.type_of_graph = 'line'
self.x = None
self.y = None
self.yscale = "linear"
def generation_total_fitness(self): def generation_total_fitness(self):
@ -22,12 +26,16 @@ class Matplotlib_Graph:
generations = self.database.get_total_generations() generations = self.database.get_total_generations()
# Create the generations list - [0,1,2,etc] # Create the generations list - [0,1,2,etc]
X = list(range(0, generations)) self.x = list(range(0, generations))
# Query for Y data # Query for Y data
Y = self.database.get_generation_total_fitness() self.y = self.database.get_generation_total_fitness()
self.type_of_plot(X, Y) if self.yscale == "log":
# If using log then the values have to be positive numbers
self.y = [abs(ele) for ele in self.y]
self.type_of_graph(self.x, self.y)
plt.xlabel('Generation') plt.xlabel('Generation')
plt.ylabel('Generation Total Fitness') plt.ylabel('Generation Total Fitness')
plt.title('Relationship Between Generations and Generation Total Fitness') plt.title('Relationship Between Generations and Generation Total Fitness')
@ -40,12 +48,16 @@ class Matplotlib_Graph:
generations = self.database.get_total_generations() generations = self.database.get_total_generations()
# Create the generations list - [0,1,2,etc] # Create the generations list - [0,1,2,etc]
X = list(range(0, generations)) self.x = list(range(0, generations))
# Query for Y data # Query for Y data
Y = self.database.get_highest_chromosome() self.y = self.database.get_highest_chromosome()
self.type_of_plot(X, Y) if self.yscale == "log":
# If using log then the values have to be positive numbers
self.y = [abs(ele) for ele in self.y]
self.type_of_graph(self.x, self.y)
plt.xlabel('Generation') plt.xlabel('Generation')
plt.ylabel('Highest Fitness') plt.ylabel('Highest Fitness')
plt.title('Relationship Between Generations and Highest Fitness') plt.title('Relationship Between Generations and Highest Fitness')
@ -58,12 +70,16 @@ class Matplotlib_Graph:
generations = self.database.get_total_generations() generations = self.database.get_total_generations()
# Create the generations list - [0,1,2,etc] # Create the generations list - [0,1,2,etc]
X = list(range(0, generations)) self.x = list(range(0, generations))
# Query for Y data # Query for Y data
Y = self.database.get_lowest_chromosome() self.y = self.database.get_lowest_chromosome()
self.type_of_plot(X, Y) if self.yscale == "log":
# If using log then the values have to be positive numbers
self.y = [abs(ele) for ele in self.y]
self.type_of_graph(self.x, self.y)
plt.xlabel('Generation') plt.xlabel('Generation')
plt.ylabel('Lowest Fitness') plt.ylabel('Lowest Fitness')
plt.title('Relationship Between Generations and Lowest Fitness') plt.title('Relationship Between Generations and Lowest Fitness')
@ -71,13 +87,13 @@ class Matplotlib_Graph:
# Getter and setters # Getter and setters
@property @property
def type_of_plot(self): def type_of_graph(self):
return self._type_of_plot return self._type_of_graph
@type_of_plot.setter @type_of_graph.setter
def type_of_plot(self, _type_of_plot): def type_of_graph(self, value_input):
if _type_of_plot in self.type_of_plot_dict.keys(): if value_input in self.type_of_graph_dict.keys():
self._type_of_plot = self.type_of_plot_dict[_type_of_plot] self._type_of_graph = self.type_of_graph_dict[value_input]
else: else:
self._type_of_plot = _type_of_plot self._type_of_plot = value_input

14
src/run_testing.py
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@ -1,8 +1,7 @@
import EasyGA import EasyGA
import random
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
# Create the Genetic algorithm # Create the genetic algorithm
ga = EasyGA.GA() ga = EasyGA.GA()
# Create 25 chromosomes each with 10 genes and 200 generations # Create 25 chromosomes each with 10 genes and 200 generations
@ -10,13 +9,16 @@ ga.population_size = 100
ga.chromosome_length = 10 ga.chromosome_length = 10
ga.generation_goal = 150 ga.generation_goal = 150
# Evolve the genetic algorithm
ga.evolve() ga.evolve()
# Print generation and population
ga.print_generation()
ga.print_population() ga.print_population()
# Plot the data from the genetic algorithm
plt.figure(figsize = [6, 6]) plt.figure(figsize = [6, 6])
ga.graph.highest_value_chromosome() # Change this so it doesn't make its own figure or show ga.graph.highest_value_chromosome() # Change this so it doesn't make its own figure or show
plt.xlabel('days passed') # override the xlabel plt.xlabel('My datas generations') # override the xlabel
plt.ylabel('products sold that day') # override the ylabel plt.ylabel('How well the fitness is') # override the ylabel
plt.title('Efficiency over time') # override the title plt.title('My GA fitness x generations') # override the title
plt.show() plt.show()