Sampling with Replacement and without Replacement in Python 📂Programing

Sampling with Replacement and without Replacement in Python

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To perform sampling with replacement/replacement in Python, one can use the np.random.choice() function of numpy.

random.choice(a, size=None, replace=True, p=None)

a: 1-dimensional array or integer
- Represents the set from which to sample. If a is an integer, sampling is done from np.arange(a).
size: An integer or a tuple of integers
- Represents the size of the output sample.
replace: Boolean
- T for sampling with replacement, F for sampling without replacement.
p: 1-dimensional array
- Represents the probabilities of each element being picked. Default is None.

(23.10.04) There is no straightforward way to do this in PyTorch.

>>> np.random.choice(5, 5, replace=False)
array([3, 1, 0, 2, 4])

>>> np.random.choice(5, 5, replace=True)
array([0, 2, 0, 2, 2])