init

neuron.py

@@ -0,0 +1,39 @@
+import random
+import math
+
+class Neuron:
+    def __init__(self):
+        self.bias = random.uniform(-1.0, 1.0)
+        self.in_ = []
+        self.out_ = []
+        self.value = 0.0
+
+    def connect_in(self, connection):
+        self.in_.append(connection)
+
+    def connect_out(self, connection):
+        self.out_.append(connection)
+
+    def calc(self, input_val=None):
+        if input_val is not None:
+            self.value = input_val
+        else:
+            z = self.bias
+            for connection in self.in_:
+                z += connection.value * connection.weight
+            
+            z = max(-500, min(500, z)) 
+            self.value = 1.0 / (1.0 + math.exp(-z))
+
+        for connection in self.out_:
+            connection.transfer(self.value)
+
+    def adjust(self, error:float, learning_rate:float = 0.1):
+        derivative = self.value * (1.0 - self.value)
+        
+        delta = error * derivative
+
+        self.bias += learning_rate * delta
+
+        for connection in self.in_:
+            connection.adjust(delta, learning_rate)