schola.core.spaces.binary.MultiBinarySpace

class schola.core.spaces.binary.MultiBinarySpace(n)[source]

Bases: MultiBinary, UnrealSpace

A Space representing a vector of binary values.

Parameters:

n (int) – The number of binary values in the space.

shape

The shape of the space.

Type:

Tuple[int]

n

The number of binary values in the space.

Type:

int

See also

gymnasium.spaces.MultiBinary

The gym space object that this class is analogous to.

proto_spaces.BinarySpace

The protobuf representation of this space.

Methods

__init__(n)	Constructor of MultiBinary space.
contains(x)	Return boolean specifying if x is a valid member of this space.
fill_proto(msg, values)	Convert a python representation of point in this space to a protobuf message.
from_jsonable(sample_n)	Convert a JSONable data type to a batch of samples from this space.
from_proto(message)	Create a Space Object from a protobuf representation.
is_empty_definition(message)	Returns True iff this space has magnitude 0.
merge(*spaces)	Merge multiple MultiBinarySpaces into a single space.
process_data(msg)	Convert a protobuf message corresponding to a point in this space to a pythonic representation.
sample([mask])	Generates a single random sample from this space.
seed([seed])	Seed the PRNG of this space and possibly the PRNGs of subspaces.
to_jsonable(sample_n)	Convert a batch of samples from this space to a JSONable data type.
to_normalized()	Cannot normalize a binary space, so return self.

Attributes

is_np_flattenable	Checks whether this space can be flattened to a spaces.Box.
np_random	Lazily seed the PRNG since this is expensive and only needed if sampling from this space.
shape	Has stricter type than gym.Space – never None.

__init__(n)[source]

Constructor of MultiBinary space.

Parameters:

• n (int) – This will fix the shape of elements of the space. It can either be an integer (if the space is flat) or some sort of sequence (tuple, list or np.ndarray) if there are multiple axes.

• seed – Optionally, you can use this argument to seed the RNG that is used to sample from the space.

fill_proto(msg, values)[source]

Convert a python representation of point in this space to a protobuf message. Mutates msg with the result.

Parameters:

• msg (proto_points.FundamentalPoint) – The protobuf message to fill.

• value (Any) – The pythonic representation of the point.

classmethod from_proto(message)[source]

Create a Space Object from a protobuf representation.

Parameters:

message (proto_space) – The protobuf message to convert.

Returns:

The Space subclass created from the protobuf message

Return type:

UnrealSpace

classmethod is_empty_definition(message)[source]

Returns True iff this space has magnitude 0.

Parameters:

message (proto_space) – The protobuf message to check for emptiness.

Returns:

True iff the space is empty.

Return type:

bool

classmethod merge(*spaces)[source]

Merge multiple MultiBinarySpaces into a single space.

Parameters:

*spaces (List[MultiBinarySpace]) – The spaces to merge.

Returns:

The merged space.

Return type:

MultiBinarySpace

Raises:

TypeError – If any of the spaces are not MultiBinarySpaces.

Examples

Copied!

>>> merged_space = MultiBinarySpace.merge(MultiBinarySpace(3), MultiBinarySpace(4))
>>> merged_space.n
7

process_data(msg)[source]

Convert a protobuf message corresponding to a point in this space to a pythonic representation.

Parameters:

msg (proto_points.FundamentalPoint) – The protobuf message to convert.

Returns:

The pythonic representation of the point.

Return type:

np.ndarray

proto_space

alias of BinarySpace

to_normalized()[source]

Cannot normalize a binary space, so return self.