wccsom {wccsom}R Documentation

Mapping spectra with self-organising maps

Description

Self-organising maps for mapping high-dimensional spectra or patterns to 2D; instead of Euclidean distance, the weighted cross correlation (WCC) similarity measure is used. Modelled after the SOM function in package 'class'. wccsom takes 'continous' patterns, i.e. datapoints are equidistant.

Usage

wccsom(data, grid=somgrid(), rlen = 100, alpha = c(0.05, 0.01),
       radius = quantile(nhbrdist, 0.7), init, nhbrdist, trwidth = 20,
       toroidal = FALSE, FineTune = TRUE, keep.data = TRUE)

Arguments

data Spectra or patterns to be mapped: a matrix, with each row representing a compound.
grid A grid for the representatives: see 'somgrid'.
rlen the number of times the complete data set will be presented to the network.
alpha a vector of two numbers indicating the amount of change. Default is to decline linearly from 0.05 to 0.01 over rlen updates.
radius the initial radius of the neighbourhood to be used for each update: the decrease is exponential over rlen updates in such a way that after one-third of the updates only the winning unit is updated. The default is to start with a value that covers 2/3 of all units.
init the initial representatives, represented as a matrix. If missing, chosen (without replacement) randomly from 'data'.
nhbrdist optionally, the distance matrix for the units.
trwidth width of the triangle function used in the WCC measure, given in the number of data points.
toroidal if TRUE, then the edges of the map are joined. Note that in a toroidal hexagonal map, the number of rows must be even.
FineTune apply kmeans for fine-tuning the codebook vectors.
keep.data store training data and their mapping in the network.

Value

an object of class '"wccsom"' with components

grid the grid, an object of class '"somgrid"'.
changes vector of mean average deviations from code vectors
codes a matrix of code vectors.
trwdth the triangle width used for the WCC measure
acors autocorrelations of the code vectors.
toroidal setting of parameter 'toroidal'.
FineTune setting of parameter 'FineTune'.
unit.classif mapping of training data: a vector of unit numbers. Only if keep.data equals TRUE.
wccs WCC values of all training data, compared to the best matching codebook vector. Only if keep.data equals TRUE.
data.acors WAC values for training data. Only if keep.data equals TRUE.

Author(s)

Ron Wehrens

References

R. Wehrens, W.J. Melssen, L.M.C. Buydens and R. de Gelder. Representing Structural Databases in a Self-Organising Map. Acta Cryst. B61, 548-557, 2005.

See Also

SOM, plot.wccsom, wccxyf, wcc

Examples

data(cepha)
gr <- somgrid(3,3, "hexagonal")
set.seed(7)
x <- wccsom(cepha$patterns, grid=gr, trwidth=20, rlen=100)

[Package wccsom version 1.2.3 Index]