请教！ 逻辑回归代价函数输出nan问题

这个代价函数cost输出nan什么情况，没看出哪里有问题

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import scipy.optimize as opt


path ='./ex2data1.txt'
data = pd.read_csv(path, header=None, names=['Exam 1', 'Exam 2', 'Admitted'])
# print(data.head())

positive = data[data['Admitted'].isin([1])]
negative = data[data['Admitted'].isin([0])]

fig, ax = plt.subplots(figsize=(12,8))
ax.scatter(positive['Exam 1'], positive['Exam 2'], s=50, c='b', marker='o', label='Admitted')
ax.scatter(negative['Exam 1'], negative['Exam 2'], s=50, c='r', marker='x', label='Not Admitted')
ax.legend()
ax.set_xlabel('Exam 1 Score')
ax.set_ylabel('Exam 2 Score')
plt.show()


def sigmoid(z):
    return 1 / (1 + np.exp(-z))


def cost(theta, X, y):
    theta = np.matrix(theta)
    X = np.matrix(X)
    y = np.matrix(y)
    first = np.multiply(-y, np.log(sigmoid(X * theta.T)))
    second = np.multiply((1 - y), np.log(1 - sigmoid(X * theta.T)))
    return np.sum(first - second) / (len(X))

# 加一列常数列
data.insert(0, 'Ones', 1)

# 初始化X，y，θ
cols = data.shape[1]
X = data.iloc[:,0:cols-1]
y = data.iloc[:,cols-1:cols]
theta = np.zeros(3)

# 转换X，y的类型
X = np.array(X.values)
y = np.array(y.values)

print(cost(theta, X, y))

cost方法里 打印下first 和second 的值看看