unienv_interface.space.spaces.dynamic_box¶
DynamicBoxSpace(backend: ComputeBackend[BArrayType, BDeviceType, BDtypeType, BRNGType], low: Union[int, float, BArrayType], high: Union[int, float, BArrayType], shape_low: Sequence[int], shape_high: Sequence[int], dtype: BDtypeType, device: Optional[BDeviceType] = None, fill_value: Union[int, float] = 0)
Bases: Space[BArrayType, BDeviceType, BDtypeType, BRNGType]
property
¶
low: BArrayType
Broadcasted lower bounds at the space's broadcast shape.
For a dynamic box there is no single fixed shape — only a range
[shape_low, shape_high] per axis. The stored _low/_high
arrays are broadcastable to self._broadcast_shape (shape_low
with size 1 on every dynamic axis, i.e. axes where
shape_low != shape_high). This property returns the bounds
broadcast to that _broadcast_shape, mirroring BoxSpace.low
(which broadcasts to self.shape). Comparisons against data of any
in-range shape broadcast correctly because dynamic axes carry size 1
here. Use get_low(shape) / get_high(shape) to materialize the
bounds at a specific concrete shape.
property
¶
high: BArrayType
Broadcasted upper bounds at the space's broadcast shape.
See low for the rationale behind the chosen shape.
property
¶
shape: tuple[int, ...] | None
Return the shape of the space as an immutable property.
staticmethod
¶
pad_array_on_axis(backend: ComputeBackend[BArrayType, BDeviceType, BDtypeType, BRNGType], data: BArrayType, axis: int, target_size: int, fill_value: Union[int, float] = 0) -> BArrayType
staticmethod
¶
get_array_axis_length(backend: ComputeBackend[BArrayType, BDeviceType, BDtypeType, BRNGType], data: BArrayType, axis: int, fill_value: Union[int, float] = 0) -> int
staticmethod
¶
unpad_array_on_axis(backend: ComputeBackend[BArrayType, BDeviceType, BDtypeType, BRNGType], data: BArrayType, axis: int, fill_value: Union[int, float] = 0) -> BArrayType
to(backend: Optional[ComputeBackend] = None, device: Optional[Union[BDeviceType, Any]] = None) -> Union[DynamicBoxSpace[BArrayType, BDeviceType, BDtypeType, BRNGType], DynamicBoxSpace]
sample(rng: BRNGType) -> Tuple[BRNGType, BArrayType]
Generates a single random sample inside the Box.
In creating a sample of the box, each coordinate is sampled (independently) from a distribution that is chosen according to the form of the interval:
- :math:
[a, b]: uniform distribution - :math:
[a, \infty): shifted exponential distribution - :math:
(-\infty, b]: shifted negative exponential distribution - :math:
(-\infty, \infty): normal distribution
Returns:
| Type | Description |
|---|---|
Tuple[BRNGType, BArrayType]
|
A sampled value from the Box |
pad_data(data: BArrayType, start_axis: Optional[int] = None, end_axis: Optional[int] = None) -> BArrayType
Pad the data to the maximum shape of this space.
unpad_data(data: BArrayType, start_axis: Optional[int] = None, end_axis: Optional[int] = None) -> BArrayType
Unpad the data to the minimum shape of this space.
shape_contains(shape: Sequence[int]) -> bool
Check if the shape is within the bounds of this space.
clip(x: BArrayType) -> BArrayType
Clip the values of x to be within the bounds of this space.
get_repr(abbreviate: bool = False, include_backend: bool = True, include_device: bool = True, include_dtype: bool = True) -> str
is_subspaceeq(other: Any) -> bool
Return whether this dynamic box is a non-strict subspace of other (⊆).
True iff other is a DynamicBoxSpace on the same backend with
equal dtype, self's shape range is contained within other's
(other.shape_low <= self.shape_low and
self.shape_high <= other.shape_high per dimension, inf-aware via
plain integer comparison), and the value bounds of self are
contained within other's. The value-bounds check is performed by
broadcasting both spaces' bounds to a common shape (the elementwise
maximum of the two shape_high vectors along each axis, restricted
to axes where the two ranges overlap) via get_low/get_high.
.. note::
This class exposes get_low/get_high but no low/high
properties, even though __eq__ and contains reference
self.low/self.high. This implementation deliberately avoids
self.low/self.high and uses get_low/get_high
instead; the pre-existing bug in __eq__/contains is left
untouched per scope.
data_to(data: BArrayType, backend: Optional[ComputeBackend] = None, device: Optional[Union[BDeviceType, Any]] = None) -> Union[BArrayType, Any]
Convert data to another backend.
is_subspace(other: Space) -> bool
Return whether this space is a STRICT subspace of other (self ⊂ other).
Defined uniformly for all spaces as::
self.is_subspace(other) ⟺ self.is_subspaceeq(other) and not other.is_subspaceeq(self)
I.e. self ⊆ other holds but other ⊆ self does not, so self
is a PROPER (strict) subspace of other. This is the ⊂ relation
versus the non-strict ⊆ provided by :meth:is_subspaceeq.
This definition is used instead of relying on __eq__ because some
space classes only have identity __eq__; defining strict
containment via the symmetric non-strict check works uniformly for all
classes regardless of their __eq__ implementation.
For structurally-distinct-but-mutually-containing spaces (which should
not occur under the strict dtype/shape policies enforced by the
per-class is_subspaceeq implementations) this degrades gracefully
to False: if both self.is_subspaceeq(other) and
other.is_subspaceeq(self) hold, the two spaces are considered
equivalent and neither is a STRICT subspace of the other.
If either side's is_subspaceeq is not implemented (the base
:meth:is_subspaceeq raises NotImplementedError), the exception
propagates to the caller — it is NOT swallowed into False so that
callers can tell that the comparison is unsupported.
Note: controller-required-space checks should typically use
:meth:is_subspaceeq (a controller's required space may exactly equal
the env space, in which case the strict is_subspace would return
False).
staticmethod
¶
abbr_device(spaces: Iterable[Space[Any, _SpaceBDeviceT, _SpaceBDTypeT, _SpaceBDRNGT]]) -> Optional[_SpaceBDeviceT]
Return the shared device across spaces, or None if mixed/empty.