Add NEAT to Network

main.py

@@ -11,36 +11,40 @@ def run_ai(ai, player, percentSamples, percentTraced):
   numSamples = round(percentSamples * player.size)
   numTraced = round(percentTraced * numSamples)
   numberToSelect = math.ceil(0.03 * player.size)
-  
+
   for _ in range(numSamples):
-      chosen = ai.ChooseOneToSample(player)
-      player.sample(chosen)
-  
+    chosen = ai.ChooseOneToSample(player)
+    player.sample(chosen)
+
   print(f"Sampled {len(player.sampled)} Nodes: {player.sampled}")
-  
+
   # After, calculate likelihoods
   sorted_indices = ai.getSortedIds()
-  
+
   # Find spread pattern for most likely
   for Id in sorted_indices[-numTraced:]:
-      ai.TraceSpreadPattern(player, Id)
-  
+    ai.TraceSpreadPattern(player, Id)
+
   traced = sorted_indices[-numTraced:]
-  
+
   print(f"Traced Spread Patterns For {sorted_indices[-numTraced:]}")
-  
+
   # Compare likelihoods again
   sorted_indices = ai.getSortedIds()
-  
+
   # Print 5 Top Choices (rightmost is the one it's most confident in)
-  print(f"Top Choices From AI (least confident to most confident, right being most confident): \n{sorted_indices[-numberToSelect:]}")
-
+  print(
+      f"Top Choices From AI (least confident to most confident, right being most confident): \n{sorted_indices[-numberToSelect:]}"
+  )
+
   for nodeNumber in sorted_indices[-numberToSelect:]:
     player.nodes[nodeNumber].selectedByAI = "True"
 
   return sorted_indices, traced
 
-app = Flask(__name__, template_folder = 'templates', static_folder='static')
+
+app = Flask(__name__, template_folder='templates', static_folder='static')
+
 
 @app.route('/')
 def index():
@@ -53,50 +57,59 @@ def index():
   similarityWeight = 1
   percentSamples = 0.1
   percentTraced = 0.5
-  
+
   player = p.Player(
-    size = random.randint(100, 250),
-    time = random.randint(2, 5),
-    min = random.randint(2, 4),
-    max = random.randint(3, 5),
-    percent = random.uniform(0, 0.1) # initially given
+      size=random.randint(50, 100),
+      time=random.randint(2, 5),
+      min=random.randint(2, 4),
+      max=random.randint(3, 5),
+      percent=random.uniform(0, 0.1)  # initially given
   )
 
   ai = a.Algorithm(
-    size=player.size,
+      size=player.size,
+
+      # NEAT
+      negativeEffectBias=negativeEffectBias,
+      positiveBias=positiveBias,
+      positiveEffectBias=positiveEffectBias,
+      similarityWeight=similarityWeight)
 
-    # NEAT
-    negativeEffectBias=negativeEffectBias,
-    positiveBias=positiveBias,
-    positiveEffectBias=positiveEffectBias,
-    similarityWeight=similarityWeight
-  )
-
   sorted, traced = run_ai(ai, player, percentSamples, percentTraced)
-  
+
   # Start window loop
   nodes, edges = graph.CreateGraphHTML(player, "templates/index.html")
 
-  return render_template(
-    'index.html', 
-
-    nodes=nodes, 
-    edges=edges, 
-
-    actual_p_zero=player.p_zero, 
-    sampled=str(player.sampled), 
-    sorted=sorted[-20:], 
-    traced=str(traced),
-
-    num_nodes=len(player.nodes),
-    alloted_time=player.time,
-    min=player.min_connections,
-    max=player.max_connections,
-    num_visible=player.num_visible_to_player
-  )
+  numPositive, numNegative, numUnknown = 0, 0, 0
+  for node in player.nodes:
+    if node.visibleToPlayer == False:
+      numUnknown += 1
+    elif node.state == 1: 
+      numPositive += 1
+    elif node.state == 0:
+      numNegative += 1
+
+  return render_template('index.html',
+                         nodes=nodes,
+                         edges=edges,
+                         actual_p_zero=player.p_zero,
+                         sampled=str(player.sampled),
+                         sorted=sorted[-20:],
+                         traced=str(traced),
+                         num_nodes=len(player.nodes),
+                         num_positive=numPositive,
+                         num_negative=numNegative,
+                         num_unknown=numUnknown,
+                         alloted_time=player.time,
+                         min=player.min_connections,
+                         max=player.max_connections,
+                         num_visible=player.num_visible_to_player)
+
 
 if __name__ == "__main__":  # Makes sure this is the main process
-	app.run( # Starts the site
-		host='0.0.0.0',  # EStablishes the host, required for repl to detect the site
-		port=random.randint(2000, 9000)  # Randomly select the port the machine hosts on.
-	)
+  app.run(  # Starts the site
+      host=
+      '0.0.0.0',  # EStablishes the host, required for repl to detect the site
+      port=random.randint(
+          2000, 9000)  # Randomly select the port the machine hosts on.
+  )