What does replacement mean in numpy.random.choice?
Question:
Here explains the function numpy.random.choice. However, I am confused about the third parameter replace. What is it? And in which case will it be useful? Thanks!
Answers:
It controls whether the sample is returned to the sample pool. If you want only unique samples then this should be false.
You can use it when you want sample some elements from a list, and meanwhile you want the elements no repeat, then you can set the “replace=False“.
eg.
from numpy import random as rd
ary = list(range(10))
# usage
In[18]: rd.choice(ary, size=8, replace=False)
Out[18]: array([0, 5, 9, 8, 2, 1, 6, 3]) # no repeated elements
In[19]: rd.choice(ary, size=8, replace=True)
Out[19]: array([4, 9, 8, 5, 4, 1, 1, 9]) # elements may be repeated
Here explains the function numpy.random.choice. However, I am confused about the third parameter replace. What is it? And in which case will it be useful? Thanks!
It controls whether the sample is returned to the sample pool. If you want only unique samples then this should be false.
You can use it when you want sample some elements from a list, and meanwhile you want the elements no repeat, then you can set the “replace=False“.
eg.
from numpy import random as rd
ary = list(range(10))
# usage
In[18]: rd.choice(ary, size=8, replace=False)
Out[18]: array([0, 5, 9, 8, 2, 1, 6, 3]) # no repeated elements
In[19]: rd.choice(ary, size=8, replace=True)
Out[19]: array([4, 9, 8, 5, 4, 1, 1, 9]) # elements may be repeated