# Terminology#

This document builds on Xarray’s glossary. We strongly recommend reading the Xarray Terminology document before reading this document. The UGRID Conventions are also a recommended read.

- Grid
A representation of a larger geometric domain by smaller discrete cells. “Mesh” is used somewhat interchangeabely.

- Structured Grid
Structured grids arrange cells in a simple (

`n_row, n_column)`

array. Structured grids are identified by regular connectivity: every cell has the same number of neighbors, with the exception of boundaries. Each cross-section has the same number of cells, even though the cell shape and size may differ arbitrarily (non-equidistant spacing). Cells are quadrilateral (four sides) in 2D. Cell to cell connectivity is implicit and can be directly derived from row defined from the row and column numbers.- Unstructured Grid
In contrast to a structured grid, connectivity for an unstructured grid is irregular and has to be defined explicitly. The primary benefit of unstructured grids are possibilities for local refinement. Another benefit is that arbitrary geometries can be easily represented. Unstructured grids generally arrange cells in a flat (

`n_cell,`

) array and separate arrays are used to store the cell locations. “Unstructured mesh” or “flexible mesh” are used interchangeably.- Topology
In these pages, short for “grid topology”. Grid topology refers to the location and connectivity of the grid cells and its constituent parts (nodes, edges). More broadly it also refers to any connectivity information with respect to a grid.

- UGRID
Conventions for specifying the topology of unstructured grids. The focus of the UGRID conventions is environmental applications and it builds on the Climate & Forecast (CF) Metadata Conventions. Data stored according to the UGRID conventions is thus nearly always written to Unidata Network Common Data Form (NetCDF) files, but the convention applies to the data and metadata: they can be written to any sufficiently rich file format (e.g. Zarr).

- Node
A point, a coordinate pair (x, y): the most basic element of the topology. “Vertex” is used interchangeably.

- Edge
A line or curve bounded by two nodes.

- Face
A plane or surface enclosed by a set of edges. “Cell” is used somewhat interchangeably; “polygon” also, but to a lesser degree.

- Sparse Array
A sparse matrix or sparse array is a matrix in which most elements are zero. For efficiency reasons, sparse matrices are commonly stored in special data structures, storing only the non-zero values. A straightforward storage scheme is Coordinate list (COO) or triplet format: for every non-zero value, three values are stored:

`(row_index, column_index, value)`

. In the Python data ecosystem, these data structures are provided by SciPy; in these pages, “sparse array” or “sparse matrix” refers specifically to data stored in one of these Scipy objects.- Dense Array
Contrast with “sparse array”: a dense array is an array in which all values – including zeros or fill values – are stored. In these pages, “dense array” refers to “ordinary” NumPy arrays.

- Adjacency List
A list describing which features of the grid (e.g. faces) are associated with each other (e.g. nodes, or the neighboring faces). This can be stored as a list of lists for a grid, a rectangular array for regular connectivity, or a “ragged array” for irregular connectivity. In the UGRID conventions, both regular and irregular connectivity is stored in (dense) rectangular arrays; ragged arrays are represented by rectangular arrays partially filled with a fill value.

- Adjacency Matrix
An alternative to adjacency lists is an adjacency matrix, which is a matrix in which the row and column numbers correspond to the element numbers and wherein the cell value contains a Boolean value denoting connectivity (

`True`

,`1`

) or not (`False`

,`0`

); such a matrix can be efficiently stored as a sparse matrix.- Face node connectivity
An index array of integers. For every face, a list of index values indicating which members of the list of nodes form its (exterior) edges. According to UGRID conventions, this data is stored in a (dense) rectangular array with explicit fill values of the shape

`(n_face, n_max_nodes_per_face`

). For a grid consisting of exclusively triangles,`n_max_nodes_per_face == 3`

and no fill value is required; for an exclusively quadrilateral grid`n_max_nodes_per_face == 4`

; the fill value is only used for mixed grids (e.g. triangles and quandrilaterals). The numbering of the faces is implicit in the first index (row number) of the array; we would collect the index values for the first face as follows:`face_node_connectivity[0]`

.- Edge node connectivity
An index arrray of integers. For every edge, a list of index value indicating which two members of the list of nodes bound a curve or line. This data is stored in a (dense) rectangular array of the shape

`(n_edge, 2)`

. The numbering of the edges is implicit in the first index (row number) of the array. Refer to the UGRID Conventions for an exhaustive description of connectivities.