370 lines
11 KiB
R
370 lines
11 KiB
R
|
|
modules::import(bnlearn)
|
|
modules::import(openxlsx)
|
|
modules::import(stringr)
|
|
modules::import(stats)
|
|
|
|
|
|
# Improvements needed: make the selection of first row/column of nodes programmatic
|
|
FIRST_NODE_COL <- 3
|
|
|
|
mappings <- c("TestScenario", "Map_P_BA", "Map_BA_OP", "Map_OP_ES", "Legend")
|
|
nodeTypes <- c("Input.Nodes", "Internal.Nodes", "Published.Nodes")
|
|
states <- c("impact", "confidence", "growth", "recovery", "layer")
|
|
refs <- c(1:length(mappings))
|
|
|
|
setEmpties <- function(val) {
|
|
if (is.na(val)) {
|
|
return(0)
|
|
} else {
|
|
return(val)
|
|
}
|
|
}
|
|
|
|
readXL <- function(fName, sheetN, startRow = 1) {
|
|
xl <- read.xlsx(fName, sheet = sheetN, startRow) # , rowNames = import)
|
|
return(data.frame(xl, stringsAsFactors = FALSE, row.names = NULL))
|
|
}
|
|
|
|
delNA <- function(vec) {
|
|
return(vec[!is.na(vec)])
|
|
}
|
|
|
|
buildExpr <- function(pressStatus) {
|
|
# pressStatus is a two column DF of name of pressure and status Ii.e. on or off)
|
|
MEANPRESS <- 0
|
|
expr <- "("
|
|
for (p in 1:nrow(pressStatus)) {
|
|
if (pressStatus$status[p] == "On") {
|
|
symbol <- ">="
|
|
} else {
|
|
symbol <- "<="
|
|
}
|
|
|
|
expr <- paste0(expr, "(\"", pressStatus$code[p], "\"", symbol, MEANPRESS, ") & ")
|
|
}
|
|
expr <- substr(expr, 1, nchar(expr) - 2)
|
|
expr <- paste0(expr, ")")
|
|
|
|
return(expr)
|
|
}
|
|
|
|
parseScenario <- function(press, prefix = "p") {
|
|
pressNames <- colnames(press)[2:length(colnames(press))]
|
|
coefs <- matrix(
|
|
data = NA,
|
|
nrow = length(pressNames),
|
|
ncol = 3,
|
|
dimnames = list(NULL, c("growth", "confidence", "layer"))
|
|
)
|
|
for (col in 2:ncol(press)) {
|
|
coefs[col - 1, ] <- as.numeric(split(press[1, col]))[match(c("growth", "confidence", "layer"), states)]
|
|
}
|
|
press[is.na(press)] <- 0
|
|
if (sum(duplicated(pressNames)) > 0) {
|
|
cat("Duplicated pressure node names found")
|
|
print(pressNodes[duplicated(pressNames)])
|
|
}
|
|
|
|
return(list(
|
|
timeSeq = press,
|
|
nodes = data.frame(
|
|
name = pressNames,
|
|
code = paste0(prefix, seq(1:length(pressNames))),
|
|
growth = coefs[, "growth"],
|
|
confidence = coefs[, "confidence"],
|
|
layer = coefs[, "layer"],
|
|
stringsAsFactors = FALSE
|
|
),
|
|
edges = data.frame(input = NULL, output = NULL, impact = NULL)
|
|
))
|
|
}
|
|
|
|
getInitial <- function(string, letter) {
|
|
return(tolower(substr(string, start = 1, stop = 1)))
|
|
}
|
|
|
|
split <- function(cell) {
|
|
params <- unlist(strsplit(cell, ","))
|
|
values <- rep(0, length(states))
|
|
|
|
for (n in 1:length(params)) {
|
|
kvp <- unlist(strsplit(params[n], "="))
|
|
ref <- match(getInitial(trimws(kvp[1])), getInitial(states))
|
|
|
|
if ((ref > 0) & (ref <= length(values))) {
|
|
values[ref] <- kvp[2]
|
|
} else {
|
|
print(paste("Unrecognised parameter(s):", params[n]))
|
|
}
|
|
}
|
|
|
|
return(values)
|
|
}
|
|
|
|
cleanTitles <- function(titleV) {
|
|
return(str_replace_all(titleV, c(" " = ".", "-" = "")))
|
|
}
|
|
|
|
getOutNodes <- function(codes, codeList) {
|
|
v <- vector(mode = "logical", length = length(codes))
|
|
|
|
for (idx in 1:length(codes)) {
|
|
v[idx] <- (sum(startsWith(codes[idx], codeList)) > 0)
|
|
}
|
|
|
|
return(v)
|
|
}
|
|
|
|
buildGraph <- function(model, desc) {
|
|
|
|
# model contains the following
|
|
# node table, edge table
|
|
|
|
# descriptor (desc) contains:
|
|
# inputCode - the top layer of the model
|
|
# outputCodes - all subsequent layers to be included in the model
|
|
|
|
|
|
inputNodes <- model$nodes$code[which(startsWith(model$nodes$code, desc$inputCode))]
|
|
inputText <- paste0("[", inputNodes, "]", collapse = "")
|
|
|
|
# do the internal nodes
|
|
edges <- ""
|
|
|
|
outNodes <- model$nodes$code[getOutNodes(model$nodes$code, desc$outputCodes)]
|
|
outDist <- vector(mode = "list", length = length(outNodes))
|
|
|
|
for (idx in 1:length(outNodes)) {
|
|
nodeRef <- match(outNodes[idx], model$nodes$code)
|
|
|
|
rows <- which(model$edges$output == outNodes[idx])
|
|
inputsStr <- paste0(model$edges$input[which(model$edges$output == outNodes[idx])], sep = ":", collapse = "")
|
|
edges <- paste0(edges, paste0("[", outNodes[idx], "|", substr(inputsStr, start = 1, stop = (nchar(inputsStr) - 1)), "]"))
|
|
|
|
# Make the coefficient of the distribution
|
|
coefVal <- setNames(
|
|
c(model$nodes$growth[nodeRef], model$edges$values[rows]),
|
|
c("(Intercept)", model$edges$input[rows])
|
|
)
|
|
# str(coefVal)
|
|
outDist[[idx]] <- list(coef = coefVal, sd = model$nodes$confidence[nodeRef])
|
|
}
|
|
|
|
print("Saving model prior to network modelling")
|
|
modelDefn <- paste0(inputText, edges)
|
|
save(modelDefn, file = "buildGraph.RData")
|
|
|
|
|
|
# print("about to build network")
|
|
# print(paste0(inputText, edges))
|
|
|
|
|
|
|
|
net <- model2network(paste0(inputText, edges), debug = FALSE)
|
|
|
|
print("network build successful")
|
|
|
|
inDist <- vector(mode = "list", length = length(inputNodes))
|
|
|
|
for (idx in 1:length(inputNodes)) {
|
|
inRef <- match(inputNodes[idx], model$nodes$code)
|
|
coefVal <- setNames(model$nodes$growth[inRef], "(Intercept)")
|
|
inDist[[idx]] <- list(coef = coefVal, sd = model$nodes$confidence[inRef])
|
|
}
|
|
|
|
allDists <- as.list(setNames(c(inDist, outDist), c(inputNodes, outNodes)))
|
|
|
|
# print(allDists)
|
|
cfit <- custom.fit(net, allDists)
|
|
|
|
cat("about to calculate sample distributions")
|
|
# print(outNodes)
|
|
|
|
sampleDists <- cpdist(cfit, nodes = outNodes, evidence = TRUE, n = 10000, method = "lw")
|
|
summDists <- summary(sampleDists)
|
|
# stdDev <- sd(sampleDists)
|
|
|
|
print("sample distribution build successful")
|
|
|
|
model$edges$input <- model$nodes$name[match(model$edges$input, model$nodes$code)]
|
|
model$edges$output <- model$nodes$name[match(model$edges$output, model$nodes$code)]
|
|
|
|
return(
|
|
list(
|
|
nodes = model$nodes,
|
|
edges = model$edges,
|
|
net = net,
|
|
cfit = cfit,
|
|
allDists = allDists,
|
|
summDists = summDists
|
|
)
|
|
)
|
|
}
|
|
|
|
|
|
getValidNodes <- function(mapping, prevOutputs, prefix) {
|
|
|
|
# Find row id for input nodes, internal and published
|
|
inputNodes <- mapping[2:nrow(mapping), 1]
|
|
|
|
# check that all input nodes are in the previous table
|
|
inputNodes <- delNA(mapping[mapping[, "Node.Type"] == "input", "Nodes"])
|
|
if (length(inputNodes) > 0) {
|
|
if (sum(inputNodes %in% prevOutputs$name) < length(inputNodes)) {
|
|
cat("Missing entries for input nodes in previous output columns")
|
|
print(inputNodes[!inputNodes %in% prevOutputs$name])
|
|
}
|
|
} else {
|
|
print("Invalid sheet - table must have at least one input row containing names from previous table")
|
|
}
|
|
|
|
|
|
# Check the row headings concur with previous names
|
|
validInputs <- delNA(inputNodes[which(unique(inputNodes) %in% prevOutputs$name)])
|
|
if (length(validInputs) == 0) {
|
|
print("Invalid sheet - table must have at least one input row containing names from previous table")
|
|
}
|
|
|
|
|
|
inputInts <- delNA(inputNodes[mapping$Node.Type != "link"])
|
|
|
|
if (sum(duplicated(inputInts)) > 0) {
|
|
cat("Duplicated input node names found")
|
|
print(inputNodes[duplicated(inputNodes)])
|
|
}
|
|
|
|
outNodes <- delNA(colnames(mapping)[FIRST_NODE_COL:ncol(mapping)])
|
|
if (sum(duplicated(outNodes)) > 0) {
|
|
cat("Duplicated output node names found")
|
|
print(outNodes[duplicated(outNodes)])
|
|
}
|
|
|
|
|
|
# check that all internal nodes are in the columns
|
|
intNodes <- delNA(mapping[mapping[, "Node.Type"] == "internal", "Nodes"])
|
|
if (length(intNodes) > 0) {
|
|
if (sum(intNodes %in% outNodes) < length(intNodes)) {
|
|
cat("Missing entries for internal nodes in output columns")
|
|
print(intNodes[!(intNodes %in% outNodes)])
|
|
}
|
|
}
|
|
|
|
coefs <- matrix(data = NA, nrow = length(outNodes), ncol = 3, dimnames = list(NULL, c("growth", "confidence", "layer")))
|
|
for (idx in 1:length(outNodes)) {
|
|
col <- match(outNodes[idx], colnames(mapping))
|
|
coefs[idx, ] <- as.numeric(split(mapping[1, col]))[match(c("growth", "confidence", "layer"), states)]
|
|
}
|
|
|
|
return(data.frame(
|
|
code = c(prevOutputs$code, paste0(prefix, seq(1:length(outNodes)))),
|
|
name = c(prevOutputs$name, outNodes),
|
|
growth = c(prevOutputs$growth, coefs[, "growth"]),
|
|
confidence = c(prevOutputs$confidence, coefs[, "confidence"]),
|
|
layer = c(prevOutputs$layer, coefs[, "layer"]),
|
|
stringsAsFactors = FALSE
|
|
))
|
|
}
|
|
|
|
getCode <- function(name, nodeDF) {
|
|
nodeDF$code[match(name, nodeDF$name)]
|
|
}
|
|
|
|
getValidEdges <- function(mapping, nodeDF, prevEdge = NULL, prefix) {
|
|
# utils::str(nodeDF)
|
|
|
|
# save(mapping, nodeDF, prevEdge, prefix, file="validEdges.RData")
|
|
|
|
edgeCols <- c("inputNode", "outputNode", "impact")
|
|
edgeM <- matrix(data = NA, nrow = 0, ncol = length(edgeCols), dimnames = list(NULL, edgeCols))
|
|
|
|
# to start let just get the statements and print them out....
|
|
for (col in FIRST_NODE_COL:ncol(mapping)) {
|
|
count <- 0
|
|
|
|
for (row in 2:nrow(mapping)) {
|
|
if (!is.na(mapping[row, col])) {
|
|
edgeM <- rbind(
|
|
edgeM,
|
|
c(
|
|
getCode(mapping[row, 1], nodeDF),
|
|
getCode(colnames(mapping)[col], nodeDF),
|
|
split(mapping[row, col])[match("impact", states)]
|
|
)
|
|
)
|
|
count <- count + 1
|
|
}
|
|
# if (count == 0) print(paste("No edges found for output", colnames(mapping)[col]))
|
|
}
|
|
}
|
|
if (is.null(prevEdge)) {
|
|
return(data.frame(
|
|
input = edgeM[, "inputNode"],
|
|
output = edgeM[, "outputNode"],
|
|
impact = edgeM[, "impact"],
|
|
stringsAsFactors = FALSE
|
|
))
|
|
} else {
|
|
return(data.frame(
|
|
input = c(prevEdge$input, edgeM[, "inputNode"]),
|
|
output = c(prevEdge$output, edgeM[, "outputNode"]),
|
|
impact = c(prevEdge$impact, edgeM[, "impact"]),
|
|
stringsAsFactors = FALSE
|
|
))
|
|
}
|
|
}
|
|
|
|
parseMapping <- function(mapping, prevOutputs, prefix) {
|
|
mapping <- mapping[, -1]
|
|
mapping[, 1] <- cleanTitles(mapping[, 1])
|
|
|
|
nodeDF <- getValidNodes(mapping, prevOutputs$nodes, prefix)
|
|
edgeDF <- getValidEdges(mapping, nodeDF, prevEdge = prevOutputs$edges, prefix)
|
|
|
|
# save(nodeDF, edgeDF, file="mapping.RData")
|
|
|
|
return(list(
|
|
# New structure
|
|
nodes = nodeDF,
|
|
edges = edgeDF
|
|
))
|
|
}
|
|
|
|
parseSheet <- function(fName) {
|
|
# get sheet names
|
|
|
|
print(paste("starting sheet load", fName))
|
|
|
|
if (file.exists(fName)) {
|
|
names <- openxlsx::getSheetNames(fName)
|
|
|
|
if (length(names) > 0) {
|
|
sheets <- sort(delNA(match(names, mappings)))
|
|
|
|
cat("starting sheet parse")
|
|
# print(sheets)
|
|
|
|
if (sum(sheets == refs) == length(refs)) {
|
|
# read all mapping tables
|
|
scenario <- parseScenario(readXL(fName, mappings[1], startRow = 1), prefix = "p")
|
|
p_ba <- parseMapping(readXL(fName, mappings[2], startRow = 1), scenario, prefix = "ba")
|
|
p_op <- parseMapping(readXL(fName, mappings[3], startRow = 1), p_ba, prefix = "op")
|
|
p_es <- parseMapping(readXL(fName, mappings[4], startRow = 1), p_op, prefix = "es")
|
|
legend <- readXL(fName, mappings[5], startRow = 1)
|
|
|
|
print("sheet load completed")
|
|
return(
|
|
list(
|
|
p_esMap = p_es,
|
|
legend = legend
|
|
)
|
|
)
|
|
} else {
|
|
print(paste("Sheets found include", mappings[sheets]))
|
|
cat("Missing sheets are:")
|
|
print(refs[-sheets])
|
|
}
|
|
}
|
|
}
|
|
}
|