#!/usr/bin/env python
# coding: utf-8
import numpy as np
from ..probabilistic_models import UniBin
from ._generation_init import GenInit
[docs]class UniBinGenInit(GenInit):
"""
Initial generation simulator based on the probabilistic model of univariate binary probabilities.
"""
def __init__(self, n_variables: int, means_vector: np.array = np.empty(0)):
"""
:param n_variables: Number of variables.
:param means_vector: Array of means to initialize the item.
:type means_vector: np.array
"""
super().__init__(n_variables)
if len(means_vector) == 0:
self.means_vector = np.array([0.5] * self.n_variables)
else:
self.means_vector = means_vector
self.pm = UniBin(list(range(self.n_variables)), lower_bound=0, upper_bound=1) # dismiss bounds
self.pm.pm = self.means_vector
self.id = 2
[docs] def sample(self, size: int) -> np.array:
"""
Sample several times the initializator.
:param size: number of samplings.
:return: array with the dataset sampled
:rtype: np.array
"""
return self.pm.sample(size)