numpy.ones_like(array,dtype = None,order ='K',subok = True):將給定形狀和類型的數組返回給定數組,並帶有一個,
參數:
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)
輸出:
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]
參考文獻:
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.ones_like.html
注意:
此外,這些代碼也無法在online-ID上運行。請在您的係統上運行它們以探索工作原理
相關用法
注:本文由純淨天空篩選整理自 numpy.ones_like() in Python。非經特殊聲明,原始代碼版權歸原作者所有,本譯文未經允許或授權,請勿轉載或複製。