📅  最后修改于: 2020-06-01 12:06:26             🧑  作者: Mango
numpy.full_like(a,fill_value,dtype = None,order =’K’,subok = True):返回形状和类型与给定数组相同的新数组。
shape:行数
order:C_contiguous或F_contiguous
dtype:[可选,float(默认))返回数组的数据类型。
subok:[bool,可选]使a的子类与否
返回值:
ndarray
# Python编程说明numpy.full_like方法
import numpy as geek
x = geek.arange(10, dtype = int).reshape(2, 5)
print("x before full_like : \n", x)
# using full_like
print("\nx after full_like : \n", geek.full_like(x, 10.0))
y = geek.arange(10, dtype = float).reshape(2, 5)
print("\n\ny before full_like : \n", x)
# using full_like
print("\ny after full_like : \n", geek.full_like(y, 0.01))
输出:
full_like之前的x:
[[0 1 2 3 4]
[5 6 7 8 9]]
full_like之前的x:
[[10 10 10 10 10]
[10 10 10 10 10]]
y full_like之前的y:
[[0 1 2 3 4]
[5 6 7 8 9]]全像
后y:
[[0.01 0.01 0.01 0.01 0.01]
[0.01 0.01 0.01 0.01 0.01]]