wccsom: Mapping spectra with self-organising maps

In wccsom: SOM Networks for Comparing Patterns with Peak Shifts

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)

wccsom documentation built on May 30, 2017, 12:52 a.m.