sWriteData {supraHex} | R Documentation

## Function to write out the best-matching hexagons and/or cluster bases in terms of data

### Description

`sWriteData` is supposed to write out the best-matching hexagons and/or cluster bases in terms of data.

### Usage

    sWriteData(sMap, data, sBase = NULL, filename = NULL, keep.data =
    FALSE)

### Arguments

`sMap` | an object of class "sMap" or a codebook matrix
`data` | a data frame or matrix of input data
`sBase` | an object of class "sBase"
`filename` | a character string naming a filename
`keep.data` | logical to indicate whether or not to also write out the input data. By default, it sets to false for not keeping it. It is highly expensive to keep the large data sets

### Value

a data frame with following components:

- `ID`: ID for data. It inherits the rownames of data (if exists). Otherwise, it is sequential integer values starting with 1 and ending with dlen, the total number of rows of the input data

- `Hexagon_index`: the index for best-matching hexagons

- `Qerr_distance`: the quantification error (distance) for best-matching hexagons

- `Cluster_base`: optional, it is only appended when sBase is given. It stores the cluster memberships/bases

- `data`: optional, it is only appended when keep.data is true

### Note

If "filename" is not NULL, a tab-delimited text file will be also written out. If "sBase" is not NULL and comes from the "sMap" partition, then cluster bases are also appended. if "keep.data" is true, the data will be part of output.

### See Also

`sBMH`

### Examples

    # 1) generate an iid normal random matrix of 100x10
    data <- matrix( rnorm(100*10,mean=0,sd=1), nrow=100, ncol=10)

    # 2) get trained using by default setup
    sMap <- sPipeline(data=data)

    # 3) write data's BMH hitting the trained map
    output <- sWriteData(sMap=sMap, data=data, filename="sData_output.txt")

    # 4) partition the grid map into cluster bases
    sBase <- sDmatCluster(sMap=sMap, which_neigh=1,
    distMeasure="median", clusterLinkage="average")

    # 5) write data's BMH and cluster bases
    output <- sWriteData(sMap=sMap, data=data, sBase=sBase,
    filename="sData_base_output.txt")

[Package supraHex version 1.32.0 Index]