我由于某种原因无法理解此异常。这是非常复杂的，我的np.array v来自哪里，但这是发生异常时的代码：

print v, type(v)

for val in v:
    print val, type(val)

print "use isfinte() with astype(float64): "
np.isfinite(v.astype("float64"))

print "use isfinite() as usual: "
try:
    np.isfinite(v)
except Exception,e:
    print e

这给出以下输出：

[6.4441947744288255 7.2246449651781788 4.1028442021807656
 4.8832943929301189] <type 'numpy.ndarray'>

6.44419477443 <type 'numpy.float64'>
7.22464496518 <type 'numpy.float64'>
4.10284420218 <type 'numpy.float64'>
4.88329439293 <type 'numpy.float64'>

np.isfinte() with astype(float64): 
[ True  True  True  True]

np.isfinte() as usual: 
ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

我不了解TypeError。所有元素都是np.float64，应该没问题。也许是个错误？有时只会发生此错误，但找不到数组之间的差异。始终具有相同的类型。

提前致谢。

编辑：工作示例：

数据结构如上所述。

import pandas as pd
import numpy as np


def forward_estim(H,end):

    old_idx = H.index
    new_idx = pd.period_range(old_idx[-1],end,freq=old_idx.freq)

    H_estim = pd.DataFrame(columns=["A","B","C","D"],index=new_idx)

    H_chg = H.values[1:]-H.values[:-1]
    mean_ = H_chg.mean()
    std_  = H_chg.std()

    H_estim.ix[0] = H.ix[-1]

    for i in range(1,len(H_estim)):
        H_estim.A[i] = H_estim.A[i-1] + mean_ + std_/2
        H_estim.B[i] = H_estim.B[i-1] + mean_ + std_
        H_estim.C[i] = H_estim.C[i-1] + mean_ - std_
        H_estim.D[i] = H_estim.D[i-1] + mean_ - std_/2

    return H_estim.ix[1:]


H_idx = pd.period_range("2010-01-01","2012-01-01",freq="A")
print H_idx

H = pd.Series(np.array([2.3,3.0,2.9]),index=H_idx)
print H

H_estim = forward_estim(H,"2014-01-01")
print H_estim

np.isfinite(H_estim.values.astype("float64"))
print "This works!"

np.isfinite(H_estim.values)
print "This does not work!"

使用以下命令在此处运行：

MacOsX Mavericks，Python 2.7.6，numpy 1.8.1，pandas 0.13.1