Moddus · May 18, 2015 09:48 · May 18, 2015
diff --git a/perzeptron.py b/perzeptron.py
@@ -0,0 +1,48 @@
+import numpy as np
+
+class Perzeptron:
+
+    def __init__(self, t, my, d,  maxiter, sign):
+        self.t = t
+        self.my = my
+        self.maxiter = maxiter
+        self.sign = sign
+        self.w = np.mat([[-self.t],[1],[1]]) 
+        self.d = d
+
+    def delta(self, x, d):
+        return self.my*(d-self.calculate(x))
+
+    def calculate(self, x):
+        return self.sign(float(self.w.T * x))
+
+    def training(self, data):
+        itercount = 0
+        while(self.maxiter != itercount):
+            itercount += 1
+            for i in range(data.shape[0]):
+                xi = data[i].T
+                delta = self.delta(xi, self.d[i])
+                self.w += delta * xi
+
+def lineare(x):
+    c = 2
+    r = 0
+    if x > c:
+        r = 1
+    elif x < -c:
+        r = 0
+    else:
+        r = 1/(2*c)*(x+c)
+    return r
+
+def fermi(x):
+    return 1 / (1 + np.exp(-x))
+
+def tanh(x):
+    return (1 + np.tanh(x))/2
+
+def hart(x):
+    if x >= 0:
+        return 1
+    return 0
diff --git a/run.py b/run.py
@@ -0,0 +1,17 @@
+#!/usr/bin/env python3
+
+from perzeptron import *
+
+data = np.mat([[1, 0, 0],[1, 0, 1], [1, 1, 0], [1, 1, 1]])
+
+result_OR = np.array([0, 1, 1, 1])
+result_AND = np.array([0, 0, 0, 1])
+result_XOR = np.array([0, 1, 1, 0])
+
+p = Perzeptron(0.5, 0.1, result_OR, 10000, lineare)
+p.training(data)
+print(p.calculate(data[0].T))
+print(p.calculate(data[1].T))
+print(p.calculate(data[2].T))
+print(p.calculate(data[3].T))
+print(p.w)
diff --git a/test_perzeptron.py b/test_perzeptron.py
@@ -0,0 +1,34 @@
+import numpy as py
+from perzeptron import *
+
+data = np.mat([[1, 0, 0],[1, 0, 1], [1, 1, 0], [1, 1, 1]])
+
+result_OR = np.array([0, 1, 1, 1])
+result_AND = np.array([0, 0, 0, 1])
+result_XOR = np.array([0, 1, 1, 0])
+
+t = 0.5
+my = 0.1
+iter = 1000
+eps = 0.01
+
+def isBetween(v,r):
+    return v >= r - eps and v <= r + eps
+
+def test_or_perzeptron():
+    p = Perzeptron(t, my, result_OR, iter, lineare)
+    p.training(data)
+
+    assert isBetween(p.calculate(data[0].T), 0) == True
+    assert isBetween(p.calculate(data[1].T), 1) == True
+    assert isBetween(p.calculate(data[2].T), 1) == True
+    assert isBetween(p.calculate(data[3].T), 1) == True
+
+def test_and_perzeptron():
+    p = Perzeptron(t, my, result_AND, iter, lineare)
+    p.training(data)
+
+    assert isBetween(p.calculate(data[0].T), 0) == True
+    assert isBetween(p.calculate(data[1].T), 0) == True
+    assert isBetween(p.calculate(data[2].T), 0) == True
+    assert isBetween(p.calculate(data[3].T), 1) == True
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