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92
Parses.R
92
Parses.R
@@ -40,7 +40,7 @@ buildExpr <- function(pressStatus) {
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}
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expr<-substr(expr, 1, nchar(expr)-2)
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expr<-paste0(expr, ')')
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return(expr)
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}
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@@ -55,14 +55,14 @@ parseScenario <- function(press, prefix = 'p') {
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cat('Duplicated pressure node names found')
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print(pressNodes[duplicated(pressNames)])
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}
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return(list(
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timeSeq=press,
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nodes=data.frame(name = pressNames,
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code=paste0(prefix, seq(1:length(pressNames))),
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growth = coefs[,'growth'],
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confidence=coefs[,'confidence'],
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layer=coefs[,'layer'],
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timeSeq=press,
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nodes=data.frame(name = pressNames,
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code=paste0(prefix, seq(1:length(pressNames))),
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growth = coefs[,'growth'],
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confidence=coefs[,'confidence'],
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layer=coefs[,'layer'],
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stringsAsFactors = FALSE),
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edges=data.frame(input=NULL, output=NULL, impact=NULL)
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))
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@@ -75,7 +75,7 @@ getInitial <- function(string, letter) {
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split <- function(cell) {
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params <- unlist(strsplit(cell, ','))
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values <- rep(0, length(states))
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for (n in 1:length(params)) {
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kvp <- unlist(strsplit(params[n], '='))
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ref <- match(getInitial(trimws(kvp[1])), getInitial(states))
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@@ -106,11 +106,11 @@ buildGraph <- function(model, desc) {
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#model contains the following
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# node table, edge table
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#descriptor (desc) contains:
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#inputCode - the top layer of the model
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#outputCodes - all subsequent layers to be included in the model
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inputNodes <- model$nodes$code[which(startsWith(model$nodes$code, desc$inputCode))]
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inputText <- paste0("[", inputNodes, "]", collapse ="")
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@@ -128,19 +128,19 @@ buildGraph <- function(model, desc) {
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edges <- paste0(edges, paste0("[", outNodes[idx], "|", substr(inputsStr, start=1, stop=(nchar(inputsStr)-1)), "]"))
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#Make the coefficient of the distribution
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coefVal <- setNames(c(model$nodes$growth[nodeRef], model$edges$values[rows]),
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coefVal <- setNames(c(model$nodes$growth[nodeRef], model$edges$values[rows]),
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c("(Intercept)", model$edges$input[rows])
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)
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#str(coefVal)
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outDist[[idx]] <- list(coef = coefVal,
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outDist[[idx]] <- list(coef = coefVal,
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sd = model$nodes$confidence[nodeRef])
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}
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print('about to build network')
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print(paste0(inputText, edges))
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net <- model2network(paste0(inputText, edges), debug=TRUE)
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print('network build successful')
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inDist <- vector(mode="list", length=length(inputNodes))
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@@ -153,19 +153,19 @@ buildGraph <- function(model, desc) {
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allDists = as.list(setNames(c(inDist, outDist), c(inputNodes, outNodes)))
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cfit = custom.fit(net, allDists)
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cat('about to calculate sample distributions')
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print(outNodes)
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sampleDists <- cpdist(cfit, nodes = outNodes, evidence = TRUE, n = 10000, method = "lw")
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summDists <- summary(sampleDists)
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#stdDev <- sd(sampleDists)
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print('sample distribution build successful')
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model$edges$input <- model$nodes$name[match(model$edges$input, model$nodes$code)]
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model$edges$output <- model$nodes$name[match(model$edges$output, model$nodes$code)]
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return(
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list(
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nodes = model$nodes,
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@@ -180,10 +180,10 @@ buildGraph <- function(model, desc) {
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getValidNodes <- function(mapping, prevOutputs, prefix) {
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#Find row id for input nodes, internal and published
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inputNodes <- mapping[2:nrow(mapping),1]
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#check that all input nodes are in the previous table
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inputNodes <- delNA(mapping[mapping[,"Node.Type"] == 'input', "Nodes"])
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if (length(inputNodes)>0) {
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@@ -192,27 +192,27 @@ getValidNodes <- function(mapping, prevOutputs, prefix) {
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print(inputNodes[!inputNodes %in% prevOutputs$name])
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}
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} else print('Invalid sheet - table must have at least one input row containing names from previous table')
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#Check the row headings concur with previous names
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validInputs <- delNA(inputNodes[which(unique(inputNodes) %in% prevOutputs$name)])
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if (length(validInputs)==0) print('Invalid sheet - table must have at least one input row containing names from previous table')
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inputInts <- delNA(inputNodes[mapping$Node.Type!='link'])
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if (sum(duplicated(inputInts))>0) {
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cat('Duplicated input node names found')
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print(inputNodes[duplicated(inputNodes)])
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}
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outNodes <- delNA(colnames(mapping)[FIRST_NODE_COL:ncol(mapping)])
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if (sum(duplicated(outNodes))>0) {
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cat('Duplicated output node names found')
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print(outNodes[duplicated(outNodes)])
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}
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#check that all internal nodes are in the columns
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intNodes <- delNA(mapping[mapping[,"Node.Type"] == 'internal', "Nodes"])
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if (length(intNodes)>0) {
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@@ -221,17 +221,17 @@ getValidNodes <- function(mapping, prevOutputs, prefix) {
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print(intNodes[!intNodes %in% outNodes])
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}
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}
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coefs <- matrix(data=NA, nrow=length(outNodes), ncol=3, dimnames=list(NULL, c('growth', 'confidence', 'layer')))
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for (idx in 1:length(outNodes)) {
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col <- match(outNodes[idx], colnames(mapping))
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coefs[idx,] <- as.numeric(split(mapping[1, col]))[match(c('growth', 'confidence', 'layer'), states)]
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}
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print(coefs)
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return(data.frame(
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code=c(prevOutputs$code, paste0(prefix, seq(1:length(outNodes)))),
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code=c(prevOutputs$code, paste0(prefix, seq(1:length(outNodes)))),
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name=c(prevOutputs$name, outNodes),
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growth=c(prevOutputs$growth, coefs[,"growth"]),
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confidence=c(prevOutputs$confidence, coefs[,"confidence"]),
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@@ -248,17 +248,17 @@ getValidEdges <- function(mapping, nodeDF, prevEdge=NULL, prefix) {
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str(nodeDF)
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edgeCols <- c('inputNode', 'outputNode', 'impact')
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edgeM <- matrix(data=NA, nrow=0, ncol=length(edgeCols), dimnames=list(NULL, edgeCols))
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#to start let just get the statements and print them out....
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for (col in FIRST_NODE_COL:ncol(mapping)) {
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count=0
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for (row in 2:nrow(mapping)) {
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if (!is.na(mapping[row, col])) {
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edgeM <- rbind(edgeM,
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c(getCode(mapping[row, 1], nodeDF),
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getCode(colnames(mapping)[col], nodeDF),
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edgeM <- rbind(edgeM,
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c(getCode(mapping[row, 1], nodeDF),
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getCode(colnames(mapping)[col], nodeDF),
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split(mapping[row,col])[match('impact', states)]
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)
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)
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@@ -285,10 +285,10 @@ getValidEdges <- function(mapping, nodeDF, prevEdge=NULL, prefix) {
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}
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parseMapping <- function(mapping, prevOutputs, prefix) {
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mapping <- mapping[,-1]
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mapping[,1] <- cleanTitles(mapping[,1])
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nodeDF <- getValidNodes(mapping, prevOutputs$nodes, prefix)
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edgeDF <- getValidEdges(mapping, nodeDF, prevEdge=prevOutputs$edges, prefix)
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@@ -302,32 +302,32 @@ parseMapping <- function(mapping, prevOutputs, prefix) {
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parseSheet <- function(fName) {
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#get sheet names
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print(paste('starting sheet load', fName))
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if (file.exists(fName)) {
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names <- openxlsx::getSheetNames(fName)
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if (length(names)>0) {
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sheets <- sort(delNA(match(names, mappings)))
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cat('starting sheet parse')
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print(sheets)
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if (sum(sheets==refs)==length(refs)) {
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#read all mapping tables
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scenario <- parseScenario(readXL(fName,mappings[1], startRow=1), prefix='p')
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p_ba <- parseMapping(readXL(fName,mappings[2], startRow=1), scenario, prefix='ba')
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p_op <- parseMapping(readXL(fName,mappings[3], startRow=1), p_ba, prefix='op')
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p_es <- parseMapping(readXL(fName,mappings[4], startRow=1), p_op, prefix='es')
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#print('building graphs')
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#p_baNet <- buildGraph(p_ba, desc=list(inputCode='p', outputCodes='ba'))
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#p_opNet <- buildGraph(p_op, desc=list(inputCode='p', outputCodes=c('ba', 'op')))
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#p_esNet <- buildGraph(p_es, desc=list(inputCode='p', outputCodes=c('ba', 'op', 'es')))
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print('sheet load completed')
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return(
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#list(
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