Worked on graphing class

src/database/matplotlib_graph.py

@@ -7,20 +7,12 @@ class Matplotlib_Graph:
 
     def __init__(self, database):
         self.database = database
-
-
-    def make_plot(self, type_of_plot, size, X, Y):
-        """Create the plot"""
-
-        # 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)
+        self.type_of_plot = plt.plot
+        self.size = [6,6]
+        self.xlabel = None
+        self.ylabel = None
+        self.title = None
+        self.yscale = "linear"
 
 
     def generation_total_fitness(self, type_of_plot = "line", size = [6,6]):
@@ -33,14 +25,26 @@ class Matplotlib_Graph:
         X = list(range(0, generations))
 
         # Query for Y data
-        Y = self.database.get_generation_total_fitness()
+        Y_list = self.database.get_generation_total_fitness()
 
-        self.make_plot(type_of_plot, size, X, Y)
+        # Set the y scale
+        plt.yscale(self.yscale)
+
+        if(self.yscale == "log"):
+            # If using log then the values have to be positive numbers
+            Y  =  [abs(ele) for ele in Y_list]
+
+        # Setup data
+        plt.figure(figsize = self.size)
+        self.type_of_plot(X,Y_list)
 
         # x and y labels
-        plt.xlabel('Generation')
-        plt.ylabel('Generation Total Fitness')
-        plt.title('Relationship Between Generations and Generation Total Fitness')
+        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()
@@ -56,15 +60,26 @@ class Matplotlib_Graph:
         X = list(range(0, generations))
 
         # Query for Y data
-        Y = self.database.get_highest_chromosome()
+        Y_list = self.database.get_highest_chromosome()
 
-        self.make_plot(type_of_plot, size, X, Y)
+        # Set the y scale
+        plt.yscale(self.yscale)
+
+        if(self.yscale == "log"):
+            # If using log then the values have to be positive numbers
+            Y  =  [abs(ele) for ele in Y_list]
+
+        # Setup data
+        plt.figure(figsize = self.size)
+        self.type_of_plot(X,Y_list)
 
         # x and y labels
-        plt.xlabel('Generation')
-        plt.ylabel('Generation Highest Fitness Chromosome')
-        plt.title('Relationship Between Generations and Highest Value Chromosome')
-
+        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()
 
@@ -79,14 +94,45 @@ class Matplotlib_Graph:
         X = list(range(0, generations))
 
         # Query for Y data
-        Y = self.database.get_lowest_chromosome()
+        Y_list = self.database.get_lowest_chromosome()
 
-        self.make_plot(type_of_plot, size, X, Y)
+        # Set the y scale
+        plt.yscale(self.yscale)
+
+        if(self.yscale == "log"):
+            # If using log then the values have to be positive numbers
+            Y  =  [abs(ele) for ele in Y_list]
+
+        # Setup data
+        plt.figure(figsize = self.size)
+        self.type_of_plot(X,Y_list)
 
         # x and y labels
-        plt.xlabel('Generation')
-        plt.ylabel('Generation Highest Fitness Chromosome')
-        plt.title('Relationship Between Generations and Lowest Value Chromosome')
-
+        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()
+
+    # Getter and setters
+    @property
+    def type_of_plot(self):
+        return self._type_of_plot
+
+
+    @type_of_plot.setter
+    def type_of_plot(self, value_input):
+
+        # Defults type of ploting functions
+        if(value_input  == "line"):
+            self._type_of_plot = plt.plot
+        elif(value_input == "scatter"):
+            self._type_of_plot = plt.scatter
+        elif(value_input == "bar"):
+            self._type_of_plot = plt.bar
+        else:
+            # If its none of the defaults then use what the user provided.
+            self._type_of_plot = value_input

src/structure/population.py

@@ -1,7 +1,8 @@
 class Population:
 
     def __init__(self, chromosome_list = None):
-        """Intiialize the population with fitness of value None, and a set of chromosomes dependant on user-passed parameter"""
+        """Intiialize the population with fitness of value None, and a
+        set of chromosomes dependant on user-passed parameter"""
 
         if chromosome_list is None:
           self.chromosome_list = []
@@ -14,6 +15,8 @@ class Population:
 
 
     def update(self):
+        """Sets all the population variables to what they should be at
+        the end of the generation """
         self.set_chromosome_list(self.next_population)
         self.reset_mating_pool()
         self.reset_next_population()
@@ -70,7 +73,9 @@ class Population:
 
 
     def add_chromosome(self, chromosome, index = None):
-        """Adds a chromosome to the population at the input index, defaulted to the end of the chromosome set"""
+        """Adds a chromosome to the population at the input index, defaulted
+         to the end of the chromosome set"""
+
         if index is None:
             index = self.size()
         self.chromosome_list.insert(index, chromosome)