Crate spaces

Set/space primitives for defining machine learning problems.

spaces provides set/space primitives to be used for defining properties of machine learning problems. Traits such as Space, and it's derivatives, may be used to define state/action spaces, for example. Mappings between different spaces may also be defined using traits such as Surjection to streamline many common preprocessing and type conversion tasks.

Modules

discrete	Discrete spaces module.
real	Real spaces module.

Structs

Empty	A space filled with... nothing.
Equipartition	Finite, uniformly partitioned interval.
Interval	Generalisation of a interval.
PairSpace	2-dimensional heterogeneous space.
ProductSpace	N-dimensional homogeneous space.
TwoSpace	2-dimensional homogeneous space.

Enums

Card	Measure of the cardinality (#) of a set.
Dim	Measure of the dimensionality of the elements of a set.

Traits

BoundedSpace	Trait for defining spaces with at least one finite bound.
FiniteSpace	Trait for defining spaces containing a finite set of values.
Intersection	Trait for types that can be combined in the form of an intersection.
Space	Trait for defining geometric spaces.
Surjection	Trait for types that implement a mapping from values of one set onto another.
Union	Trait for types that can be combined in the form of a union.