蟒蛇,麻木
有没有更紧凑的方法来操作数组元素,而不必使用标准的 for 循环。?
例如,考虑下面的函数:
filterData(A):
B = numpy.zeros(len(A));
B[0] = (A[0] + A[1])/2.0;
for i in range(1, len(A)):
B[i] = (A[i]-A[i-1])/2.0;
return B;
Numpy 有一个diff 运算符,适用于 numpy 数组和 Python 原生数组。您可以将代码重写为:
def filterData(A):
B = numpy.zeros(len(A));
B[1:] = np.diff( A )/2.0
B[0] = (A[0] + A[1])/2.0;
return B
还有numpy.ediff1d
,它允许您使用to_end
andto_begin
参数显式地预先或附加到差异,例如:
>>> import numpy as np
>>> a = np.arange(10.)
>>> diff = np.ediff1d(a,to_begin = a[:2].sum()) / 2.
>>> diff
array([ 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5])
>>> diff.size
10