np.power(x1,x2)

最新推荐文章于 2024-09-17 10:17:06 发布

转载最新推荐文章于 2024-09-17 10:17:06 发布 · 1.3k 阅读

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#power #python

本文详细介绍了NumPy库中幂运算函数np.power的使用方法，包括参数解释、返回值说明及多个实例演示，展示了如何利用该函数进行数组元素级的幂运算。

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power(x1, x2, /, out=None, *, where=True, casting=‘same_kind’, order=‘K’, dtype=None, subok=True
[, signature, extobj])

First array elements raised to powers from second array, element-wise.

Raise each base in `x1` to the positionally-corresponding power in
`x2`.  `x1` and `x2` must be broadcastable to the same shape. Note that an
integer type raised to a negative integer power will raise a ValueError.

Parameters
----------
x1 : array_like
The bases.
x2 : array_like
The exponents.
out : ndarray, None, or tuple of ndarray and None, optional
A location into which the result is stored. If provided, it must have
a shape that the inputs broadcast to. If not provided or `None`,
a freshly-allocated array is returned. A tuple (possible only as a
keyword argument) must have length equal to the number of outputs.
where : array_like, optional
Values of True indicate to calculate the ufunc at that position, values
of False indicate to leave the value in the output alone.
**kwargs
For other keyword-only arguments, see the
:ref:`ufunc docs <ufuncs.kwargs>`.

Returns
-------
y : ndarray
The bases in `x1` raised to the exponents in `x2`.

See Also
--------
float_power : power function that promotes integers to float

Examples
--------
Cube each element in a list.

>>> x1 = range(6)
>>> x1
[0, 1, 2, 3, 4, 5]
>>> np.power(x1, 3)
array([  0,   1,   8,  27,  64, 125])

Raise the bases to different exponents.

>>> x2 = [1.0, 2.0, 3.0, 3.0, 2.0, 1.0]
>>> np.power(x1, x2)
array([  0.,   1.,   8.,  27.,  16.,   5.])

The effect of broadcasting.

>>> x2 = np.array([[1, 2, 3, 3, 2, 1], [1, 2, 3, 3, 2, 1]])
>>> x2
array([[1, 2, 3, 3, 2, 1],
[1, 2, 3, 3, 2, 1]])
>>> np.power(x1, x2)
array([[ 0,  1,  8, 27, 16,  5],
[ 0,  1,  8, 27, 16,  5]])