`sTopology`

is supposed to define the topology of a 2D map grid.
The topological shape can be either a supra-hexagonal grid or a
hexagonal/rectangle sheet. It returns an object of "sTopol" class,
containing: the total number of hexagons/rectangles in the grid, the
grid xy-dimensions, the grid lattice, the grid shape, and the 2D
coordinates of all hexagons/rectangles in the grid. The 2D coordinates
can be directly used to measure distances between any pair of lattice
hexagons/rectangles.

1 2 |

`data` |
a data frame or matrix of input data |

`xdim` |
an integer specifying x-dimension of the grid |

`ydim` |
an integer specifying y-dimension of the grid |

`nHex` |
the number of hexagons/rectangles in the grid |

`lattice` |
the grid lattice, either "hexa" for a hexagon or "rect" for a rectangle |

`shape` |
the grid shape, either "suprahex" for a supra-hexagonal grid or "sheet" for a hexagonal/rectangle sheet |

an object of class "sTopol", a list with following components:

`nHex`

: the total number of hexagons/rectanges in the grid. It is not always the same as the input nHex (if any); see "Note" below for the explaination`xdim`

: x-dimension of the grid`ydim`

: y-dimension of the grid`lattice`

: the grid lattice`shape`

: the grid shape`coord`

: a matrix of nHex x 2, with each row corresponding to the coordinates of a hexagon/rectangle in the 2D map grid`call`

: the call that produced this result

The output of nHex depends on the input arguments and grid shape:

How the input parameters are used to determine nHex is taken priority in the following order: "xdim & ydim" > "nHex" > "data"

If both of xdim and ydim are given,

*nHex=xdim*ydim*for the "sheet" shape,*r=(min(xdim,ydim)+1)/2*for the "suprahex" shapeIf only data is input,

*nHex=5*sqrt(dlen)*, where dlen is the number of rows of the input dataWith nHex in hand, it depends on the grid shape:

For "sheet" shape, xy-dimensions of sheet grid is determined according to the square root of the two biggest eigenvalues of the input data

For "suprahex" shape, see

`sHexGrid`

for calculating the grid radius r. The xdim (and ydim) is related to r via*xdim=2*r-1*

`sHexGrid`

, `visHexMapping`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
# For "suprahex" shape
sTopol <- sTopology(xdim=3, ydim=3, lattice="hexa", shape="suprahex")
# Error: "The suprahex shape grid only allows for hexagonal lattice"
# sTopol <- sTopology(xdim=3, ydim=3, lattice="rect", shape="suprahex")
# For "sheet" shape with hexagonal lattice
sTopol <- sTopology(xdim=3, ydim=3, lattice="hexa", shape="sheet")
# For "sheet" shape with rectangle lattice
sTopol <- sTopology(xdim=3, ydim=3, lattice="rect", shape="sheet")
# By default, nHex=19 (i.e., r=3; xdim=ydim=5) for "suprahex" shape
sTopol <- sTopology(shape="suprahex")
# By default, xdim=ydim=5 (i.e., nHex=25) for "sheet" shape
sTopol <- sTopology(shape="sheet")
# Determine the topolopy of a supra-hexagonal grid based on input data
# 1) generate an iid normal random matrix of 100x10
data <- matrix(rnorm(100*10,mean=0,sd=1), nrow=100, ncol=10)
# 2) from this input matrix, determine nHex=5*sqrt(nrow(data))=50,
# but it returns nHex=61, via "sHexGrid(nHex=50)", to make sure a supra-hexagonal grid
sTopol <- sTopology(data=data, lattice="hexa", shape="suprahex")
# visualise a supre-hexagonal grid
visHexMapping(sTopol,mappingType="indexes")
``` |

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