Geometric Data Type and Structures
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`scikit-shape` includes both explicit and implicit representations for geometries.
The explicit geometric representations are curves and triangulated domains in 2d.
The implicit geometric representations are based on labeled grids, which can be
usedto encode regions both in 2d and 3d. A specific case of labeled grids is the
phase field function which decomposes the domain into two regions, one labeled
with -1, and another labeled with +1. The following is a list of the data structures
available to encode geometries:

* :class:`skshape.geometry.curve.Curve` is used to store the discretization
representation of a simple closed curve in 2d. What is a stored is an ordered
collection (x,y) points of the nodes of the curves. Additionally, this class
includes many functions for geometric computations. For example, the unit
normals or curvature of the curve on the nodes or intermediate points can be
computed.

* :class:`skshape.geometry.curve.CurveFamily` store hierarchical collections
of :class:`skshape.geometry.curve.Curve` objects. The curves in this collection
do not intersect one another. Hence, the collection is a tree-like hierarchy,
in which a curve may be enclosed by a curve or may enclose other curves.
The :class:`skshape.geometry.curve.CurveFamily` also includes the same geometric
computation routines as the :class:`skshape.geometry.curve.Curve` class.

* :class:`skshape.geometry.domain.Domain2d` is for explicit representations of
2d domains as triangulations. It can be created by passing it the region
boundaries in the form of :class:`skshape.geometry.curve.Curve` or
:class:`skshape.geometry.curve.CurveFamily` objects. It creates and stores
the corresponding triangulations internally.

* :class:`skshape.geometry.grid.Grid2d` and :class:`skshape.geometry.grid.Grid3d`
are abstractions to represent regions embedded in image-like regular grids.

* :class:`numpy.array` is not part of `scikit-shape`, and is convenient to store
labels indicating regions of an image domain. It is used as input or output for
some of the `scikit-shape` functions. For an example, for an image with four
regions, each pixel location can be labeled with an integer 0,1,2,3, and this
labeling (i.e. segmentation) can be stored in an integer values NumPy array.