# Source code for rising.random.discrete

```
from functools import partial
from itertools import combinations
from random import choices as sample_with_replacement
from random import sample as sample_without_replacement
from typing import List, Sequence
from rising.random.abstract import AbstractParameter
__all__ = ["DiscreteParameter", "DiscreteCombinationsParameter"]
[docs]def combinations_all(data: Sequence) -> List:
"""
Return all combinations of all length for given sequence
Args:
data: sequence to get combinations of
Returns:
List: all combinations
"""
comb = []
for r in range(1, len(data) + 1):
comb.extend(combinations(data, r=r))
return comb
[docs]class DiscreteParameter(AbstractParameter):
"""
Samples parameters from a discrete population with or without
replacement
"""
def __init__(
self, population: Sequence, replacement: bool = False, weights: Sequence = None, cum_weights: Sequence = None
):
"""
Args:
population : the parameter population to sample from
replacement : whether or not to sample with replacement
weights : relative sampling weights
cum_weights : cumulative sampling weights
"""
super().__init__()
if replacement:
sample_fn = partial(sample_with_replacement, weights=weights, cum_weights=cum_weights)
else:
if weights is not None or cum_weights is not None:
raise ValueError("weights and cum_weights should only be specified if " "replacement is set to True!")
sample_fn = sample_without_replacement
self.sample_fn = sample_fn
self.population = population
[docs] def sample(self, n_samples: int) -> list:
"""
Samples from the discrete internal population
Args:
n_samples : the number of elements to sample
Returns:
list: the sampled values
"""
return self.sample_fn(population=self.population, k=n_samples)
[docs]class DiscreteCombinationsParameter(DiscreteParameter):
"""
Sample parameters from an extended population which consists of all
possible combinations of the given population
"""
def __init__(self, population: Sequence, replacement: bool = False):
"""
Args:
population : population to build combination of
replacement : whether or not to sample with replacement
"""
population = combinations_all(population)
super().__init__(population=population, replacement=replacement)
```