Question

我使用numba @jit（nopython = True）定义一个函数，它将通过scipy.special调用普通的cdf函数，我收到此错误消息：

TypingError: Untyped global name 'norm'

以下是我的代码：

import numpy as np
from numba import * 
from scipy.stats import *
timelst = np.random.randn(2083)
noncovlst = np.random.randn(2083)
lst = np.random.randint(30,size=127)
lst_num = 0
lst_num = np.append(lst_num,lst)
lst_num = np.cumsum(lst_num)
n = 127
agelst = np.random.randint(16,80,127)
edulst = np.random.randint(1,28,127)
incomelst = np.random.randn(127)



@jit(nopython=True)
def lamb(now,params):
    b = params[0]
    mu = params[1]
    s = params[2]
    beta1 = params[3]
    beta3 = params[4]
    beta4 = params[5]
    beta5 = params[6]
    beta6 = params[7]
    L = 0.0

    for i in range(n):
        timez = timelst[lst_num[i]:lst_num[i+1]]
        noncov = noncovlst[lst_num[i]:lst_num[i+1]]
        timeq = timez[timez < now]
        noncovq = noncov[timez < now]
        L += (b*now + np.exp(beta3*agelst[i]+beta5*edulst[i]
                             +beta6*incomelst[i])*(norm.cdf((now-timeq-mu)/s)*np.exp(beta1*noncovq)).sum())/n
    return L

res = [2.422855,16.320364,28.984707,-9.942004,-3.118748,-0.248391,1.903728,4.126649]

输入

lamb(0.2,res)

错误消息：

TypingError: Failed at nopython (nopython frontend)
Untyped global name 'norm'

我知道drop nopython关键字可能会解决这个问题，然而，它会转换为对象模式，这会对性能造成巨大损失。

有没有更好的方法将普通的cdf纳入numba nopython模式？

使用scipy.special时出现numba错误

0 个答案: