numpy.ones_like(array,dtype = None,order ='K',subok = True):将给定形状和类型的数组返回给定数组,并带有一个,
参数:
array : array_like input subok : [optional, boolean]If true, then newly created array will be sub-class of array; otherwise, a base-class array order : C_contiguous or F_contiguous C-contiguous order in memory(last index varies the fastest) C order means that operating row-rise on the array will be slightly quicker FORTRAN-contiguous order in memory (first index varies the fastest). F order means that column-wise operations will be faster. dtype : [optional, float(byDeafult)] Data type of returned array.
返回值:
ndarray of ones having given shape, order and datatype.
# Python Programming illustrating
# numpy.ones_like method
import numpy as geek
array = geek.arange(10).reshape(5, 2)
print("Original array : \n", array)
b = geek.ones_like(array, float)
print("\nMatrix b : \n", b)
array = geek.arange(8)
c = geek.ones_like(array)
print("\nMatrix c : \n", c)
输出:
Original array : [[0 1] [2 3] [4 5] [6 7] [8 9]] Matrix b : [[ 1. 1.] [ 1. 1.] [ 1. 1.] [ 1. 1.] [ 1. 1.]] Matrix c : [1 1 1 1 1 1 1 1]
参考文献:
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.ones_like.html
注意:
此外,这些代码也无法在online-ID上运行。请在您的系统上运行它们以探索工作原理
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