schola.core.spaces.discrete.DiscreteSpace

class schola.core.spaces.discrete.DiscreteSpace(n)[source]

Bases: Discrete, UnrealSpace

A Space representing a single discrete value.

Parameters:

n (int) – The number of discrete values in the space. e.g. space is one value in interval [0,n]

n

The number of discrete values in the space.

Type:

int

See also

gymnasium.spaces.Discrete

The gym space object that this class is analogous to.

proto_spaces.DiscreteSpace

The protobuf representation of this space.

Methods

__init__(n)	Constructor of Discrete space.
contains(x)	Return boolean specifying if x is a valid member of this space.
fill_proto(msg, value)	Convert a python representation of point in this space to a protobuf message.
from_jsonable(sample_n)	Converts a list of json samples to a list of np.int64.
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 DiscreteSpaces 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)	Converts a list of samples to a list of ints.
to_normalized()	Returns a normalized version of the space.

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	Return the shape of the space as an immutable property.

__init__(n)[source]

Constructor of Discrete space.

This will construct the space \(\{\text{start}, …, \text{start} + n – 1\}\).

Parameters:

• n (int) – The number of elements of this space.

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

• start (int) – The smallest element of this space.

fill_proto(msg, value)[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 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 DiscreteSpaces into a single space.

Parameters:

*spaces (List[Union[DiscreteSpace, MultiDiscreteSpace]]) – The spaces to merge.

Returns:

The merged space.

Return type:

MultiDiscreteSpace

Raises:

TypeError – If any of the spaces are not Discrete or MultiDiscrete.

See also

merge_discrete_like_spaces

Merge multiple Discrete or MultiDiscrete spaces into a single MultiDiscrete space.

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 DiscreteSpace

to_normalized()[source]

Returns a normalized version of the space. Is a noop if a space subclass does not implement to_normalized.

Returns:

The normalized space.

Return type:

UnrealSpace