Python的numpy.exp函数中的溢出错误 [英] Overflow Error in Python's numpy.exp function

问题描述

我想这样使用numpy.exp:

cc = np.array([
    [0.120,0.34,-1234.1]
])

print 1/(1+np.exp(-cc))

但这给了我错误:

/usr/local/lib/python2.7/site-packages/ipykernel/__main__.py:5: RuntimeWarning: overflow encountered in exp

我不明白为什么?我怎样才能解决这个问题?看来问题出在第三个数字(-1234.1)

I can't understand why? How can I fix this? It seems the problem is with third number (-1234.1)

推荐答案

正如fuglede所说，这里的问题是np.float64无法处理与exp(1234.1)一样大的数字.尝试改用np.float128:

As fuglede says, the issue here is that np.float64 can't handle a number as large as exp(1234.1). Try using np.float128 instead:

>>> cc = np.array([[0.120,0.34,-1234.1]], dtype=np.float128)
>>> cc
array([[ 0.12,  0.34, -1234.1]], dtype=float128)
>>> 1 / (1 + np.exp(-cc))
array([[ 0.52996405,  0.58419052,  1.0893812e-536]], dtype=float128)

但是请注意，使用扩展精度存在某些怪癖.它可能无法在Windows上运行；您实际上并没有获得完整的128位精度；当数字通过纯python时，您可能会失去精度.您可以在此处了解更多信息.

Note however, that there are certain quirks with using extended precision. It may not work on Windows; you don't actually get the full 128 bits of precision; and you might lose the precision whenever the number passes through pure python. You can read more about the details here.

出于大多数实际目的，您可以将1 / (1 + <a large number>)近似为零.也就是说，只要忽略警告并继续前进即可. Numpy会为您处理近似值(使用np.float64时):

For most practical purposes, you can probably approximate 1 / (1 + <a large number>) to zero. That is to say, just ignore the warning and move on. Numpy takes care of the approximation for you (when using np.float64):

>>> 1 / (1 + np.exp(-cc))
/usr/local/bin/ipython3:1: RuntimeWarning: overflow encountered in exp
  #!/usr/local/bin/python3.4
array([[ 0.52996405,  0.58419052,  0.        ]])

如果您想取消该警告，则可以使用 scipy.special.expit ，正如WarrenWeckesser在对该问题的评论中所建议的:

If you want to suppress the warning, you could use scipy.special.expit, as suggested by WarrenWeckesser in a comment to the question:

>>> from scipy.special import expit
>>> expit(cc)
array([[ 0.52996405,  0.58419052,  0.        ]])

这篇关于Python的numpy.exp函数中的溢出错误的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！