Files
MESO/reWeight.R
2022-04-07 09:10:15 +01:00

133 lines
4.0 KiB
R

modules::import(magrittr)
reWeightLayer <- function(nestedLayerTib, fudge=1) {
for (idx in 1:nrow(nestedLayerTib)) {
#print(nestedLayerTib$data[idx])
thisData <- nestedLayerTib$data[idx][[1]]
#Calculate the overall depletion rate
#depRate <- ifelse(thisData$values<0, -thisData$values, 0)
#Re-adjust those weightings in line with the number applied
survived <- 1
grown <- 1
for (depIdx in 1:nrow(thisData)) {
if (thisData$values[depIdx]<0) survived <- survived * (1 + thisData$values[depIdx]) else
grown <- (1-thisData$values[depIdx]) * grown
}
#Update the edge weightings to reflect the combined depletion on the BA from each of the edges
effDepRate <- survived - 1
effGrowthRate <- 1-grown
#print(effDepRate)
if (sum(thisData$values)==0) newValues <- rep(0, length(thisData$values)) else
newValues <- round(thisData$values/sum(thisData$values)*(effDepRate+effGrowthRate), digits=3)
#print(paste(idx, paste(newValues, collapse=",")))
nestedLayerTib$data[idx][[1]]$values <- newValues / fudge
}
return(nestedLayerTib %>% tidyr::unnest(cols=c(data)))
}
assignWeights <- function(
edgesTib,
incode,
outcode,
value) {
for (idx in 1:length(incode)) {
ref <- intersect(which(edgesTib$input == incode[idx]),
which(edgesTib$output == outcode[idx]))
utils::str(ref)
if (length(ref)>1) stop("Error has occurred with multiple edges between two nodes")
print(paste(ref, edgesTib$values[ref], value[idx]))
edgesTib$values[ref] <- value[idx]
#Set the appropriate values
}
return(edgesTib)
}
reWeightModel <- function(thisNet, pressStatus) {
print("About to recalc p - ba")
#what is the depletion factor for each of the pressures applied to the BA?
p_on <- pressStatus %>%
dplyr::filter(status=="On") %>%
dplyr::left_join(thisNet$nodes, by=c("code"="code")) %>%
dplyr::left_join(thisNet$edges, by=c("code"="input")) %>%
dplyr::mutate(values=values * 0.9)
print("before")
print(sum(p_on$values))
p_on <- p_on %>%
dplyr::rename(presscode=code) %>%
dplyr::rename(ba_code=output) %>%
dplyr::select(presscode, layer, ba_code, values) %>%
tidyr::nest(data=c(presscode, values))
newP <- reWeightLayer(p_on, fudge=1)
print("About to recalc ba - op")
#Repeat for the linkage between ba and op
bas <- unique(newP$ba_code)
ba_impacted <- thisNet$nodes %>%
dplyr::filter(code %in% bas) %>%
dplyr::left_join(thisNet$edges, by=c("code"="input")) %>%
tidyr::drop_na() %>%
dplyr::rename(ba_code=code) %>%
dplyr::select(layer, output, ba_code, values) %>%
dplyr::rename(op_code=output) %>%
tidyr::nest(data=c(ba_code, values))
newBA <- reWeightLayer(ba_impacted, fudge=4)
print("About to recalc op - es")
#Repeat for the linkage between op and es
ops <- unique(newBA$op_code)
op_impacted <- thisNet$nodes %>%
dplyr::filter(code %in% ops) %>%
dplyr::left_join(thisNet$edges, by=c("code"="input")) %>%
dplyr::rename(op_code=code) %>%
tidyr::drop_na() %>%
dplyr::select(layer, output, op_code, values) %>%
dplyr::rename(es_code=output) %>%
tidyr::nest(data=c(op_code, values))
newOP <- reWeightLayer(op_impacted, fudge=2)
#Check for any more links through the system
print("About to recalc es - es")
ess <- unique(newOP$es_code)
es_impacted <- thisNet$nodes %>%
dplyr::filter(code %in% ess) %>%
dplyr::left_join(thisNet$edges, by=c("code"="input")) %>%
dplyr::rename(es_code=code) %>%
tidyr::drop_na() %>%
dplyr::select(layer, output, es_code, values) %>%
dplyr::rename(lo_code=output) %>%
tidyr::nest(data=c(lo_code, values))
newES <- reWeightLayer(es_impacted, fudge=4)
incode <- c(newP$presscode, newBA$ba_code, newOP$op_code, newES$es_code)
outcode <- c(newP$ba_code, newBA$op_code, newOP$es_code, newES$lo_code)
value <- c(newP$values, newBA$values, newOP$values, newES$values)
thisNet$edges <- assignWeights(thisNet$edges, incode, outcode, value)
print("exitting reweighting process")
return(thisNet)
}