numpy.prod

numpy.prod(a, axis=None, dtype=None, out=None, keepdims=)

返回给定轴上的数组元素的乘积。

Parameters:

a : array_like
Input data.
axis : None or int or tuple of ints, optional
Axis or axes along which a product is performed. The default, axis=None, will calculate the product of all the elements in the input array. If axis is negative it counts from the last to the first axis.
New in version 1.7.0.
If axis is a tuple of ints, a product is performed on all of the axes specified in the tuple instead of a single axis or all the axes as before.
dtype : dtype, optional
The type of the returned array, as well as of the accumulator in which the elements are multiplied. The dtype of a is used by default unless a has an integer dtype of less precision than the default platform integer. In that case, if a is signed then the platform integer is used while if a is unsigned then an unsigned integer of the same precision as the platform integer is used.
out : ndarray, optional
Alternative output array in which to place the result. It must have the same shape as the expected output, but the type of the output values will be cast if necessary.
keepdims : bool, optional
If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
If the default value is passed, then keepdims will not be passed through to the prod method of sub-classes of ndarray, however any non-default value will be. If the sub-classes sum method does not implement keepdims any exceptions will be raised.
Returns:
product_along_axis : ndarray, see dtype parameter above.
An array shaped as a but with the specified axis removed. Returns a reference to out if specified.

Notes:
当使用整数类型时，算术是模块化的，在溢出时不会产生错误。 这意味着，在32位平台上：

>>> x = np.array([536870910, 536870910, 536870910, 536870910])
>>> np.prod(x)  # random
16

空阵列的产物是元素1:

>>> np.prod([])
1.0

Examples:
默认情况下，计算所有元素的乘积:

In [1]: import numpy as np

In [2]: np.prod([1.,2.])
Out[2]: 2.0

即使输入数组是二维的:

In [3]: np.prod([[1.,2.],[3.,4.]])
Out[3]: 24.0

但是我们也可以指定要乘以的轴:

In [4]: np.prod([[1.,2.],[3.,4.]], axis=1)
Out[4]: array([ 2., 12.])

如果x的类型是无符号的，那么输出类型是无符号整数:

>>> x = np.array([1, 2, 3], dtype=np.uint8)
>>> np.prod(x).dtype == np.uint
True

如果x是有符号整数类型，那么输出类型是默认的有符号整数:

>>> x = np.array([1, 2, 3], dtype=np.int8)
>>> np.prod(x).dtype == int
True