Python: 感知机学习算法原始形式

from numpy import *
import numpy as np
import matplotlib.pyplot as plt
import time
plt.ion()
plt.autoscale(enable=True, tight=False)
dataFn = "data.dat>"
def drawSpLine(w, b):
    plt.plot([-b/w[0] if w[1]==0 else 0, 10 if w[0]==0 else -b/w[0]], [10 if w[1]==0 else -b/w[1], -b/w[1] if w[0]==0 else 0])
    plt.draw()
    plt.show()
with open(dataFn) as inFile:
    data = inFile.readlines()
    d = np.loadtxt(data)
    for row in d:
        if row[0]==1:
            plt.plot(row[1], row[2], 'ro')
        else:
            plt.plot(row[1], row[2], 'bo')
    plt.draw()
    plt.show()
    time.sleep(1)
w = ones(2)
b = random.randint(10)
eta = 1
print w
print b
drawSpLine(w, b)
time.sleep(1)
while True:
    isConv = True
    for row in d:
        if row[0]*(dot(np.transpose(w), np.transpose(row[1:])) + b) <= 0:
            w = w + eta * row&#91;0&#93; * row&#91;1:&#93;
            b = b + eta * row&#91;0&#93;
            print w, b
            drawSpLine(w, b)
            time.sleep(1)
            isConv = False
            break
    if isConv:
        print "Converged.>"
        break
print "w>", w
print "b>", b
plt.show(block=True) 

1    1   1
1   2   1
1   1   2
-1  4   2
-1  4   3
-1  3   3

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