随机数 与 线性变换

import numpy as np
import random

def creatData():
    # how many 2-demention vector do you want
    numberOfVectors = 2
    # the linear transform you want 
    # (should be a 3*2)
    matmuler = [[3,2],[2,1],[2,1]]
    # additional move you wnat  (weights)
    # [a, b] = [88, 88]
    
    x = []
    i = 0
    while i < numberOfVectors:
       x.append(random.uniform(0.,0.5))
       i = i + 1
       
    y = []
    i = 0
    while i < numberOfVectors:
       y.append(random.uniform(0.,0.5))
       i = i + 1
       
    mat = [x,y]
    
    result = np.matmul(matmuler, mat) 
    # + [a, b]
    
    # c = 0
    # c = np.dot(matmuler, mat)
    
    def sigmoid(x):
        # TODO: Implement sigmoid function
        return 1/(1 + np.exp(-x))
    
    for i in range(len(result)):
        for j in range(len(result[0])):
            result[i][j] = sigmoid(result[i][j]) 
            
    del x, y, i, j, mat, matmuler
    return result
result = creatData()
print("moudle runing")

1. sigmoid，ML常用激活函数
2. for i in range(len(list)) 很好的二维数列遍历方法