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ReduceToLowLand = function(BestMatchingUnits,GeneralizedUmatrix,Data=NULL,Cls=NULL,Key=NULL,LowLimit,Force=FALSE){
# wenn zuviele BM dann werden die Auf die LowLandBM reduziert
# BestMatchingUnits = ReduceToLowLand(BestMatchingUnits,GeneralizedUmatrix)
# [BestMatchingUnits,Data,Cls,Key,LowLandInd] = ReduceToLowLand(BestMatchingUnits,GeneralizedUmatrix,Data,Cls,Key,LowLimit)
#
# INPUT
# BestMatchingUnits(1:n,1:n,1:n) BestMatchingUnits =[BMkey, BMLineCoords, BMColCoords]
# GeneralizedUmatrix(1:l,1:c) U-Matrix heights in Matrix form
#
# OPTIONAL
# Data(1:n,1:d) data cases in lines, variables in Columns or [] or 0
# Cls(1:n) a possible classif( ication of the data or [] or 0
# Key(1:n) the keys of the data or [] or 0
# LowLimit GeneralizedUmatrix heights up to this are considered to lie in the low lands
# default: LowLimit = prctile(Uheights,80)
# nur die 80# tiefsten
# Force ==TRUE: Always perform reduction
#
# OUTPUT
# LowLandBM the unique BestMatchingUnits in the low lands of an u-Matrix
# LowLandInd index such that UniqueBM = BestMatchingUnits(UniqueInd,]
#
# LowLandData Data reduced to LowLand: LowLandData = Data(LowLandInd,]
# LowLandCls Cls reduced to LowLand: LowLandCls = Cls(LowLandInd)
# LowLandKey Key reduced to LowLand: LowLandKey = Key(LowLandInd)
# ALU 2021 in matlab, MCT reimplemented in R
# DEFAULTS
# BestMatchingUnits,GeneralizedUmatrix,Data,Cls,Key,LowLimit
# 1 2 3 4 5 6
if(is.null(Data)) {
Data = BestMatchingUnits[, 1]*0
}
# init Output to zeros(n,1)
if (is.null(Cls)) {
Cls = BestMatchingUnits[, 1]*0
}
# init Output to zeros(n,1)
if (is.null(Key)) {
Key = BestMatchingUnits[, 1]*0
}
# alle U-hoehen
if (missing(LowLimit)) {
Uheights = Uheights4Data(BestMatchingUnits, GeneralizedUmatrix)$Uheights
LowLimit = quantile(Uheights,
p = 80 / 100,
type = 5,
na.rm = TRUE)
}
# init Output to zeros(n,1)
#print(LowLimit)
# nur die 80# tiefsten
V=dim(GeneralizedUmatrix)
l = V[1]
c = V[2]
AnzNeuronen = l*c
# anzahl Neuronen
BMKey = BestMatchingUnits[, 1]
AnzBM = length(BMKey)
# soviele BM
if (AnzBM > AnzNeuronen |isTRUE(Force)) {
# reduktion noetig
# 'NOTE: BestMatchingUnits reduced to Lowlands!' # ansage!
V = LowLand(BestMatchingUnits = BestMatchingUnits,
GeneralizedUmatrix = GeneralizedUmatrix,
Data = Data, Cls = Cls, Key = Key, LowLimit = LowLimit)
BestMatchingUnitsOut = V$LowLandBM
LowLandInd = V$LowLandInd
DataOut = V$LowLandData
ClsOut = V$LowLandCls
KeyOut = V$LowLandKey
LowLimit = V$LowLimit
# reduktion auf LowLands
} else{
LowLandInd = c(1:AnzBM)
BestMatchingUnitsOut=BestMatchingUnits
DataOut=Data
ClsOut=Cls
KeyOut=Key
message("No Reduction performed")
# keine Reduktion
}
V=list(BestMatchingUnitsOut, DataOut, ClsOut, KeyOut, LowLandInd,LowLimit)
names(V) = c('BestMatchingUnits', 'Data', 'Cls', 'Key', 'LowLandInd','LowLimit')
return(V
)
}
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