som_clas: Self-Organizing Maps classification

In synoptReg: Synoptic Climate Classification and Spatial Regionalization of Environmental Data

Description

som_clas allows to perform a SOM synoptic classification

Usage

som_clas(
  x,
  xdim,
  ydim,
  iter = 2000,
  alpha = c(0.05, 0.01),
  dist.fcts = "euclidean",
  mode = "online",
  cores = 1,
  norm = T
)

Arguments

x	data.frame. A data.frame with the following variables: lon, lat, time, value, anom_value. See tidy_nc.
xdim	Integer. X dimension of the grid. See somgrid from kohonen package.
ydim	Integer. Y dimension of the grid. See somgrid from kohonen package.
iter	integer. Number of iterations.
alpha	vector. learning rate. See som from kohonen package for details.
dist.fcts	character. vector of distance functions to be used for the individual data layers. See som from kohonen package for details.
mode	carachter. type of learning algorithm. Default "on-line". See kohonen package for details.
cores	Integer. Parallel processing only available for "pbatch" algorithm.
norm	logical. Default TRUE. norm = TRUE is recommended for classifying two ore more variables.

Value

A list with:

• A data.frame containing the dates and the weather types.

• A data frame containing the gridded data grouped by circulation types.

• An object of class kohonen with all the components returned by the function som

References

Wehrens, R. and BuydenL. (2007) Self- and Super-organizing Maps in R: The kohonen Package Journal of Statistical Software, 21(5), 1 - 19.

See Also

tidy_nc

Examples

# Load data
data(z500)
# Tidying our atmospheric variables (500 hPa geopotential height).
z500_tidy <- tidy_nc(x = list(z500),
             name_vars = c("z500"))

# SOM classification
som_cl <- som_clas(z500_tidy, xdim = 4, ydim = 4, iter = 200)

synoptReg documentation built on April 22, 2021, 1:06 a.m.