pymgrid.utils.space.ModuleSpace#

class pymgrid.utils.space.ModuleSpace(unnormalized_low, unnormalized_high, normalized_bounds=(0, 1), clip_vals=True, shape=None, dtype=<class 'numpy.float64'>, seed=None, verbose=False)[source]#

Methods

`clip`(val, *[, low, high, space, normalized])	Clip a value into a lower and upper bound.
`contains`(x)	Check if x is a valid member of the space.
`denormalize`(val)
`from_jsonable`(sample_n)	Convert a JSONable data type to a batch of samples from this space.
`inner_clip`(val, space)
`normalize`(val)
`sample`([normalized])	Randomly sample an element of 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.

Attributes

`is_np_flattenable`	Checks whether this space can be flattened to a `spaces.Box`.
`normalized`
`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.
`unnormalized`