From e96525e4ff802429b5886fd0aaf3c6f5327c74c6 Mon Sep 17 00:00:00 2001
From: "E. Almqvist" <h1g.server@gmail.com>
Date: Fri, 28 Aug 2020 21:39:02 +0200
Subject: [PATCH] Finished AI thinking

---
 lib/func.py | 28 +++++++++++++++++-----------
 main.py     |  5 ++---
 2 files changed, 19 insertions(+), 14 deletions(-)

diff --git a/lib/func.py b/lib/func.py
index 1b9b910..3f80afa 100644
--- a/lib/func.py
+++ b/lib/func.py
@@ -21,25 +21,31 @@ class AIlib:
     def genRandomMatrix( x:int, y:int, min: float=0.0, max: float=1.0 ): # generate a matrix with x, y dimensions with random values from min-max in it
         return np.random.rand(x, y)
 
-    def think( inp:np.matrix, weights:list, bias:list, layerIndex: int=0 ): # recursive thinking, hehe
+    def think( inp:np.array, weights:list, bias:list, layerIndex: int=0 ): # recursive thinking, hehe
         # the length of weights and bias should be the same
         # if not then the neural net is flawed/incorrect
-        maxLayer = len(weights)
-        biasLen = len(bias)
-        if( maxLayer != len(bias) ):
+        maxLayer = len(weights) - 1
+        biasLen = len(bias) - 1
+        if( maxLayer != biasLen ):
             print("Neural Network Error: Length of weights and bias are not equal.")
-            print("Weights: ${maxLayer}, Bias: ${biasLen}")
+            print( "Weights: " + str(maxLayer) + " Bias: " + str(biasLen) )
             exit()
+
         try:
+            print("Think " + str(layerIndex))
             weightedInput = np.dot( weights[layerIndex], inp ) # dot multiply the input and the weights
-            layer = np.add( weightedInput, bias[layerIndex] ) # add the biases
+            layer = AIlib.sigmoid( np.add(weightedInput, bias[layerIndex]) ) # add the biases
 
-            if( layerIndex >= maxLayer ):
-                return layer
+            print(layer)
+            print("\n")
+
+            if( layerIndex < maxLayer ):
+                return AIlib.think( layer, weights, bias, layerIndex + 1 )
             else:
-                print("New think " + str(layerIndex + 1))
-                AIlib.think( layer, weights, bias, layerIndex + 1 )
-        except ValueError as err:
+                return layer
+
+        except (ValueError, IndexError) as err:
             print("\n---------")
             print( "Error: " + str(err) )
             print( "Layer index: " + str(layerIndex) )
+            print( "Max layer index: " + str(maxLayer) )
diff --git a/main.py b/main.py
index 244559e..d8253fa 100755
--- a/main.py
+++ b/main.py
@@ -23,9 +23,8 @@ class rgb(object):
 
     def think(self, inp:np.array):
         res = ai.think( inp, self.weights, self.bias )
-        print( "Result: " + str(res) )
-        # print(self.weights)
-        # print(self.bias)
+        print("\n-Result-")
+        print(res)
 
 def init(): # init func
     bot = rgb()