Dont train if we are already perfect

caliGraph.py

@@ -831,8 +831,8 @@ def train(gamma = 1, full=True):
     books = loadBooksFromDB()
     bestWeights = copy.copy(weights)
     mse, gradient = evaluateFitness(books)
+    delta = sum(gradient[g]**2 for g in gradient)
     best_mse = mse
-    delta = 1
     stagLen = 0
 
     while gamma > 1.0e-06 and delta > 1.0e-06:
@@ -854,6 +854,7 @@ def train(gamma = 1, full=True):
         if stagLen == 3 or mse > 100:
             for wt in weights:
                 weights[wt] = random.random()
+    print('Done.')
 
 def saveWeights(weights):
     with open('neuralWeights.json', 'w') as f: