In [1]:

    

import matplotlib.pyplot as plt
import networkx as nx
import pandas as pd
import numpy as np

from genome import Genome

%matplotlib inline


    

In [2]:

    

X = np.array([[0,0],[0,1],[1,0],[1,1]], dtype=np.float16)
Y = np.array([[0],[1],[1],[0]], dtype=np.float16) 
data = X,Y


    

In [3]:

    

class Visualize(object):
    '''
    Mutate Visualization: Using PyGraphViz and Dot Syntax
    '''

    def __init__(self, GENOME):
        self.nodes, self.connections = GENOME
        
    def create(self):
        '''
        Create a directed graph from a Genome (Genotype)
        '''
        
        # Capture a List of Lists for in/out connections
        connectionList = self.connections[['in','out']].values.tolist()
        connectionList = [tuple(aList) for aList in connectionList]
        
        return connectionList

        # Cluster nodes by type
        #sensorNodes = self.nodes.loc[self.nodes.type == ("sensor"),("node")].values.tolist()
        #hiddenNodes = self.nodes.loc[self.nodes.type == ("hidden"),("node")].values.tolist()
        #outputNodes = self.nodes.loc[self.nodes.type == ("output"),("node")].values.tolist()

        # Create the dot syntax map
        #graphString = ("digraph {")
        #for ix,ele in enumerate(connectionList):
        #    graphString += (str(ele[0]) + "->" + str(ele[1]) + ";")
        #graphString += ("}")

        # Create the Graph
        #G = nx.Graph(graphString, strict=False, directed=False, rankdir='LR')
        #G.node_attr['shape']='circle'
        #G.add_subgraph(sensorNodes, name='cluster_sensors', label="Sensor Nodes", rank="same")
        #G.add_subgraph(hiddenNodes, name='cluster_hidden', label="Hidden Nodes")
        #G.add_subgraph(outputNodes, name='cluster_output', label="Output Nodes", rank="same")
        
        #imageResult = G.draw(format='png', prog='dot')

        #return imageResult


    

In [4]:

    

options = {'node_color': 'black',
           'edge_color': 'blue',
           #'with_labels': True, 
           #'font_weight': 'bold',
           'node_size': 1,
           #'arrows': True,
           'width': 0.025}


    

In [5]:

    

g = Genome(data)
GENOME = g.create()
v = Visualize(GENOME)
G = nx.Graph()
G.add_edges_from(v.create())
nx.draw(G, **options)


    

In [6]:

    

for _ in range(1000):
    g.mutate(GENOME)
v = Visualize(GENOME)
G = nx.Graph()
G.add_edges_from(v.create())
nx.draw(G, **options)


    

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