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Gymnasium/gym/spaces/multi_binary.py
2021-07-28 20:26:34 -04:00

58 lines
1.5 KiB
Python

import numpy as np
from .space import Space
class MultiBinary(Space):
"""
An n-shape binary space.
The argument to MultiBinary defines n, which could be a number or a `list` of numbers.
Example Usage:
>> self.observation_space = spaces.MultiBinary(5)
>> self.observation_space.sample()
array([0,1,0,1,0], dtype =int8)
>> self.observation_space = spaces.MultiBinary([3,2])
>> self.observation_space.sample()
array([[0, 0],
[0, 1],
[1, 1]], dtype=int8)
"""
def __init__(self, n):
self.n = n
if type(n) in [tuple, list, np.ndarray]:
input_n = n
else:
input_n = (n,)
super(MultiBinary, self).__init__(input_n, np.int8)
def sample(self):
return self.np_random.randint(low=0, high=2, size=self.n, dtype=self.dtype)
def contains(self, x):
if isinstance(x, list) or isinstance(x, tuple):
x = np.array(x) # Promote list to array for contains check
if self.shape != x.shape:
return False
return ((x == 0) | (x == 1)).all()
def to_jsonable(self, sample_n):
return np.array(sample_n).tolist()
def from_jsonable(self, sample_n):
return [np.asarray(sample) for sample in sample_n]
def __repr__(self):
return "MultiBinary({})".format(self.n)
def __eq__(self, other):
return isinstance(other, MultiBinary) and self.n == other.n