Updated database ad graph functions.

This commit is contained in:
danielwilczak101
2020-11-07 01:54:37 -05:00
parent 05b8fd06fa
commit 918c4f4d5e
3 changed files with 115 additions and 16 deletions

View File

@ -110,3 +110,40 @@ class database:
query_data = cur.fetchone()
return query_data[0]
def get_generation_total_fitness(self):
"""Get each generations total fitness sum from the database """
query_data = self.query_all("SELECT SUM(fitness) FROM data GROUP BY generation;")
# Format the fitness data into one list
formated_query_data = [i[0] for i in query_data]
return formated_query_data
def get_total_generations(self):
"""Get the total generations from the database"""
query_data = self.query_one_item("SELECT COUNT(DISTINCT generation) FROM data;")
return query_data
def get_highest_chromosome(self):
"""Get the highest fitness of each generation"""
query_data = self.query_all("select fitness, max(fitness) from data group by generation")
# Format the fitness data into one list
formated_query_data = [i[0] for i in query_data]
return formated_query_data;
def get_lowest_chromosome(self):
"""Get the lowest fitness of each generation"""
query_data = self.query_all("select fitness, min(fitness) from data group by generation")
# Format the fitness data into one list
formated_query_data = [i[0] for i in query_data]
return formated_query_data;

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@ -5,27 +5,30 @@ from database import database
from sqlite3 import Error
class graph:
""" """
"""Prebuilt graphing functions to make visual represention of fitness data."""
def scatter(ga):
"""Show a scatter plot of the database information."""
def generation_total_fitness(ga,type_of_plot = "line",size = [6,6]):
"""Show a plot of generation by generation total fitness."""
# Query the X data
generations = ga.database.query_one_item("SELECT COUNT(DISTINCT generation) FROM data;")
generations = ga.database.get_total_generations()
# Create the generations array
# Create the generations list - [0,1,2,etc]
X = list(range(0, generations))
#Query the Y data
Y_data = ga.database.query_all("SELECT SUM(fitness) FROM data GROUP BY generation;")
# Format the Y data so we can use it to plot
Y = [i[0] for i in Y_data]
# Query for Y data
Y = ga.database.get_generation_total_fitness()
# Set the plot size
plt.figure(figsize=[5, 5])
plt.figure(figsize=size)
if(type_of_plot == "line"):
plt.plot(X,Y)
elif(type_of_plot == "scatter"):
plt.scatter(X,Y)
elif(type_of_plot == "bar"):
plt.bar(X,Y)
plt.scatter(X,Y)
# x and y labels
plt.xlabel('Generation')
plt.ylabel('Generation Total Fitness')
@ -34,6 +37,63 @@ class graph:
# Show the plot
plt.show()
def highest_value_chromosome(ga,type_of_plot = "line",size = [6,6]):
"""Generation by Max value chromosome """
def line(ga):
pass
# Query the X data
generations = ga.database.get_total_generations()
# Create the generations list - [0,1,2,etc]
X = list(range(0, generations))
# Query for Y data
Y = ga.database.get_highest_chromosome()
# Set the plot size
plt.figure(figsize=size)
if(type_of_plot == "line"):
plt.plot(X,Y)
elif(type_of_plot == "scatter"):
plt.scatter(X,Y)
elif(type_of_plot == "bar"):
plt.bar(X,Y)
# x and y labels
plt.xlabel('Generation')
plt.ylabel('Generation Highest Fitness Chromosome')
plt.title('Relationship Between Generations and Highest Value Chromosome')
# Show the plot
plt.show()
def lowest_value_chromosome(ga,type_of_plot = "line",size = [6,6]):
"""Generation by Min value Chromosome """
# Query the X data
generations = ga.database.get_total_generations()
# Create the generations list - [0,1,2,etc]
X = list(range(0, generations))
# Query for Y data
Y = ga.database.get_lowest_chromosome()
# Set the plot size
plt.figure(figsize=size)
if(type_of_plot == "line"):
plt.plot(X,Y)
elif(type_of_plot == "scatter"):
plt.scatter(X,Y)
elif(type_of_plot == "bar"):
plt.bar(X,Y)
# x and y labels
plt.xlabel('Generation')
plt.ylabel('Generation Highest Fitness Chromosome')
plt.title('Relationship Between Generations and Lowest Value Chromosome')
# Show the plot
plt.show()

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@ -5,7 +5,7 @@ import random
ga = EasyGA.GA()
# Create 25 chromosomes each with 10 genes and 200 generations
ga.population_size = 25
ga.population_size = 100
ga.chromosome_length = 10
ga.generation_goal = 150
@ -18,4 +18,6 @@ ga.target_fitness_type = 'min'
ga.evolve()
ga.graph.scatter(ga)
ga.print_population()
ga.graph.lowest_value_chromosome(ga)