神经网络 感知机 Perceptron python实现

import numpy as np
import matplotlib.pyplot as plt 
import math

def create_data(w1=3,w2=-7,b=4,seed=1,size=30):
    np.random.seed(seed)
    w = np.array([w1,w2])
    x1 = np.arange(0,size)
    v = np.random.normal(loc=0,scale=5,size=size)
    x2 = v - (b+w[0]*x1)/(w[1]*1.0)
    y_train=[]
    x_train = np.array(zip(x1,x2))
    for item in v:
        if item >=0:
            y_train.append(1)
        else:
            y_train.append(-1)
    y_train = np.array(y_train)
    return x_train,y_train

def SGD(x_train,y_train):
    alpha=0.01
    w,b=np.array([0,0]),0
    c,i=0,0
    while i0:
            ax1.scatter(x_train[i,0],x_train[i,1],c="r",marker='o')
        else:
            ax1.scatter(x_train[i,0],x_train[i,1],c="b",marker="^")
    plt.show()

if __name__ == '__main__':
    w1,w2,b=3,-7,4
    size=50
    x_train,y_train=create_data(w1,w2,b,1,size)
    w_estimate,b_estimate=SGD(x_train,y_train)
    test_and_show(w1,w2,b,size,w_estimate,b_estimate,x_train,y_train)

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