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Cleaned up code

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SimpleArt
2020-11-12 16:15:34 -05:00
parent df422c6478
commit 4bd8d0a908
1 changed files with 35 additions and 65 deletions
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100
src/database/matplotlib_graph.py
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@ -5,10 +5,10 @@ class Matplotlib_Graph:
"""Prebuilt graphing functions to make visual represention of fitness data."""
type_of_plot_dict = {
'line' : plt.plot,
'scatter' : plt.scatter,
'bar' : plt.bar
}
'line' : plt.plot,
'scatter' : plt.scatter,
'bar' : plt.bar
}
def __init__(self, database):
self.database = database
@ -20,7 +20,28 @@ class Matplotlib_Graph:
self.yscale = "linear"
def generation_total_fitness(self, type_of_plot = "line", size = [6,6]):
def plt_setup(self, X, Y, yscale, xlabel, ylabel, title, type_of_plot, size):
"""Setup for plt"""
if yscale == "log":
# If using log then the values have to be positive numbers
Y = [abs(ele) for ele in Y]
# Setup data
plt.figure(figsize = size)
plt.yscale(self.yscale)
type_of_plot(X, Y)
# labels
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title)
# Show the plot
plt.show()
def generation_total_fitness(self):
"""Show a plot of generation by generation total fitness."""
# Query the X data
@ -30,31 +51,12 @@ class Matplotlib_Graph:
X = list(range(0, generations))
# Query for Y data
Y_data = self.database.get_generation_total_fitness()
Y = self.database.get_generation_total_fitness()
if(self.yscale == "log"):
# If using log then the values have to be positive numbers
Y = [abs(ele) for ele in Y_data]
Y_data = Y
# Setup data
plt.figure(figsize = self.size)
plt.yscale(self.yscale)
self.type_of_plot(X,Y_data)
# x and y labels
if(self.xlabel == None):
plt.xlabel('Generation')
if(self.ylabel == None):
plt.ylabel('Generation Total Fitness')
if(self.title == None):
plt.title('Relationship Between Generations and Generation Total Fitness')
# Show the plot
plt.show()
self.plt_setup(X, Y, self.yscale, 'Generation', 'Generation Total Fitness', 'Relationship Between Generations and Generation Total Fitness', self.type_of_plot, self.size)
def highest_value_chromosome(self, type_of_plot = "line", size = [6,6]):
def highest_value_chromosome(self):
"""Generation by Max value chromosome """
# Query the X data
@ -64,30 +66,12 @@ class Matplotlib_Graph:
X = list(range(0, generations))
# Query for Y data
Y_data = self.database.get_highest_chromosome()
Y = self.database.get_highest_chromosome()
if(self.yscale == "log"):
# If using log then the values have to be positive numbers
Y = [abs(ele) for ele in Y_data]
Y_data = Y
# Setup data
plt.figure(figsize = self.size)
plt.yscale(self.yscale)
self.type_of_plot(X,Y_data)
# x and y labels
if(self.xlabel == None):
plt.xlabel('Generation')
if(self.ylabel == None):
plt.ylabel('Generation Total Fitness')
if(self.title == None):
plt.title('Relationship Between Generations and Generation Total Fitness')
# Show the plot
plt.show()
self.plt_setup(X, Y, self.yscale, 'Generation', 'Highest Fitness', 'Relationship Between Generations and Highest Fitness', self.type_of_plot, self.size)
def lowest_value_chromosome(self, type_of_plot = "line", size = [6,6]):
def lowest_value_chromosome(self):
"""Generation by Min value Chromosome """
# Query the X data
@ -99,27 +83,13 @@ class Matplotlib_Graph:
print(X)
# Query for Y data
Y_data = self.database.get_lowest_chromosome()
Y = self.database.get_lowest_chromosome()
if(self.yscale == "log"):
# If using log then the values have to be positive numbers
Y = [abs(ele) for ele in Y_data]
Y_data = Y
Y = [abs(ele) for ele in Y]
# Setup data
plt.figure(figsize = self.size)
plt.yscale(self.yscale)
self.type_of_plot(X,Y_data)
# Default x and y labels
if(self.xlabel == None):
plt.xlabel('Generation')
if(self.ylabel == None):
plt.ylabel('Generation Total Fitness')
if(self.title == None):
plt.title('Relationship Between Generations and Generation Total Fitness')
# Show the plot
plt.show()
self.plt_setup(X, Y, self.yscale, 'Generation', 'Lowest Fitness', 'Relationship Between Generations and Lowest Fitness', self.type_of_plot, self.size)
# Getter and setters