src.delaunay#

Functions

`get_decomposition`(topo[, xnp, ynp, padding])	Partitions a lat-lon domain into a number of coarser but regularly spaced points that comprises the vertices of the Delaunay triangles.
`get_land_cells`(tri, topo[, height_tol, ...])	Land cell selector based on how much of a grid cell contains topography of a certain elevation.

src.delaunay.get_decomposition(topo, xnp=11, ynp=6, padding=0)#

Partitions a lat-lon domain into a number of coarser but regularly spaced points that comprises the vertices of the Delaunay triangles.

Parameters#

topoarray-like: 2D topography data
xnpint, optional: number of points in the first horizontal direction, by default 11
ynpint, optional: number of points in the second horizontal direction, by default 6
paddingint, optional: number of grid points to include as a boundary (padded) region, by default 0

scipy.spatial.qhull.Delaunay instance: scipy Delaunary triangulation instance

src.delaunay.get_land_cells(tri, topo, height_tol=0.5, percent_tol=0.95)#

Land cell selector based on how much of a grid cell contains topography of a certain elevation.

triscipy.spatial.qhull.Delaunay instance: scipy Delaunay triangulation instance containing tuples of the three vertice coordinates of a triangle
topoarray-like: 2D topographic data
height_tolfloat, optional: elevation above height_tol are considered as land, by default 0.5 [m]
percent_tolfloat, optional: cut-off percentage of topography in the given grid cell below height_tol. By default 0.95, i.e., at least 5% of the grid cell has to be above heigh_tol to be considered a land cell.