sInitial {supraHex} | R Documentation

## Function to initialise a sInit object given a topology and input data

### Description

`sInitial` is supposed to initialise an object of class "sInit" given a topology and input data. As a matter of fact, it initialises the codebook matrix (in input high-dimensional space). The return object inherits the topology information (i.e., a "sTopol" object from `sTopology`), along with initialised codebook matrix and method used.

### Usage

    sInitial(data, sTopol, init = c("linear", "uniform", "sample"), seed =
    825)

### Arguments

`data` | a data frame or matrix of input data
`sTopol` | an object of class "sTopol" (see `sTopology`)
`init` | an initialisation method. It can be one of "uniform", "sample" and "linear" initialisation methods
`seed` | an integer specifying the seed

### Value

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

- `nHex`: the total number of hexagons/rectanges in the grid

- `xdim`: x-dimension of the grid

- `ydim`: y-dimension of the grid

- `r`: the hypothetical radius 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

- `init`: an initialisation method

- `codebook`: a codebook matrix of nHex x ncol(data), with each row corresponding to a prototype vector in input high-dimensional space

- `call`: the call that produced this result

### Note

The initialisation methods include:

- "uniform": the codebook matrix is uniformly initialised via randomly taking any values within the interval [min, max] of each column of input data

- "sample": the codebook matrix is initialised via randomly sampling/selecting input data

- "linear": the codebook matrix is linearly initialised along the first two greatest eigenvectors of input data

### See Also

`sTopology`

### Examples

    # 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")

    # 3) initialise the codebook matrix using different mehtods
    # 3a) using "uniform" method
    sI_uniform <- sInitial(data=data, sTopol=sTopol, init="uniform")
    # 3b) using "sample" method
    # sI_sample <- sInitial(data=data, sTopol=sTopol, init="sample")
    # 3c) using "linear" method
    # sI_linear <- sInitial(data=data, sTopol=sTopol, init="linear")

[Package supraHex version 1.32.0 Index]