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