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server.R
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server.R
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# This is the server logic for a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com
#
#
# if (!require("pacman")) install.packages('pacman', repos='http://cran.r-project.org')
#
# pacman::p_load(shiny, ggplot2, plotly, reshape, rgdal, RColorBrewer, ggdendro, dendextend)
#
# pacman::p_load_gh("rstudio/leaflet", "cloudyr/aws.s3")
#
# library(shiny)
# library(ggplot2)
# library(plotly)
# library(leaflet)
# library(reshape)
# library(rgdal)
# library(RColorBrewer)
# library(ggdendro)
# library(dendextend)
# library(rnightlights)
# library(aws.s3)
if (!requireNamespace("shiny", quietly = TRUE))
{
stop("Pkg shiny needed for this function to work. Please install missing packages.", call. = FALSE)
}
if (!requireNamespace("dendextend", quietly = TRUE))
{
stop("Pkg dendextend needed for this function to work. Please install missing packages.", call. = FALSE)
}
if (!requireNamespace("ggdendro", quietly = TRUE))
{
stop("Pkg ggdendro needed for this function to work. Please install missing packages.", call. = FALSE)
}
if (!requireNamespace("leaflet", quietly = TRUE))
{
stop("Pkg leaflet needed for this function to work. Please install missing packages.", call. = FALSE)
}
if (!requireNamespace("plotly", quietly = TRUE))
{
stop("Pkg plotly needed for this function to work. Please install missing packages.", call. = FALSE)
}
if (!requireNamespace("RColorBrewer", quietly = TRUE))
{
stop("Pkg RColorBrewer needed for this function to work. Please install missing packages.", call. = FALSE)
}
if (!requireNamespace("reshape", quietly = TRUE))
{
stop("Pkg reshape needed for this function to work. Please install missing packages.", call. = FALSE)
}
if (!requireNamespace("rgdal", quietly = TRUE))
{
stop("Pkg rgdal needed for this function to work. Please install missing packages.", call. = FALSE)
}
options(shiny.trace=F)
shiny::shinyServer(function(input, output, session){
#Since renderUI does not like intraCountry returning NULL we init with an empty renderUI, set suspendWhenHidden = FALSE to force it to recheck intraCountry even if null
output$intraCountry <- shiny::renderUI({})
shiny::outputOptions(output, "intraCountry", suspendWhenHidden = FALSE)
#yrs <- getAllNlYears("VIIRS")
#isolate({updateTabItems(session, "inputs", "plotNightLights")})
#### reactive ctryAdmLevels ####
ctryAdmLevels <- shiny::reactive({
print(paste0("here: ctryAdmLevels"))
if (length(input$countries) != 1)
return()
temp <- data.table::fread(getCtryNlDataFnamePath(input$countries), nrows = 1, header = T)
cols <- names(temp)
cols <- cols[-grep("area_sq_km|NL_", cols)]
})
#### reactive ctryAdmLevelNames ####
ctryAdmLevelNames <- shiny::reactive({
print(paste0("here: ctryAdmLevelNames"))
countries <- input$countries
if (length(countries) != 1)
return()
hdr <- data.table::fread(getCtryNlDataFnamePath(countries), nrows = 1, header = T)
colClasses <- names(hdr)
colClasses[-grep("area_sq_km|NL_", colClasses)] <- "character"
colClasses[grep("area_sq_km|NL_", colClasses)] <- "NULL"
data <- data.table::fread(getCtryNlDataFnamePath(countries), colClasses = colClasses, header = T)
})
#### reactive ctryAdmLevels ####
ctryDataStats <- shiny::reactive({
print(paste0("here: ctryDataStats"))
if (length(input$countries) != 1)
return()
temp <- data.table::fread(getCtryNlDataFnamePath(input$countries), nrows = 1, header = T)
cols <- names(temp)
cols <- cols[grep("NL_", cols)]
stats <- unique(gsub(".*._.*._.*._", "", cols))
})
#### reactive ctryNlData ####
ctryNlData <- shiny::reactive({
print(paste0("here: ctryNlData"))
input$btnGo
countries <- shiny::isolate(input$countries)
if (length(countries)<1)
return()
ctryData <- NULL
if (length(countries) == 1)
{
ctryData <- data.table::fread(getCtryNlDataFnamePath(countries))
}
else if(length(countries) > 1) #remove subcountry admin levels
{
for (ctryCode in countries)
{
print(ctryCode)
temp <- data.table::fread(getCtryNlDataFnamePath(ctryCode))
ctryCols <- grep("country|area|NL_", names(temp))
temp <- temp[, ctryCols, with=F]
if (is.null(ctryData))
{
ctryData <- temp
}else
{
ctryData <- merge(ctryData, temp, all=TRUE)
}
}
}
return(ctryData)
})
#### reactive ctryNlDataMelted ####
ctryNlDataMelted <- shiny::reactive({
print(paste0("here: ctryNlDataMelted"))
if(is.null(ctryNlData()))
return()
ctryData <- ctryNlData()
#the nightlight cols
nlCols <- names(ctryData)[grep("NL_", names(ctryData))]
#the cols with the stats we want
statCols <- names(ctryData)[grep(paste0("NL_.*.", input$ctryStat), names(ctryData))]
#the non nightlight cols
ctryDataCols <- setdiff(names(ctryData), nlCols)
#the cols to melt by
meltMeasureVars <- statCols
#combine the non-nightlight cols and the cols with the stats we want
ctryData <- subset(ctryData, select=c(ctryDataCols, meltMeasureVars))
#
meltVarNames <- gsub("[^[:digit:]]", "", meltMeasureVars)
ctryData <- data.table::data.table(reshape2::melt(ctryData, measure.vars=meltMeasureVars))
ctryData$variable <- paste0(gsub("[^[:digit:]]","", ctryData$variable),"01")
ctryData$variable <- as.Date(ctryData$variable, format="%Y%m%d")
return(ctryData)
})
#### reactiveValues values ####
values <- shiny::reactiveValues(
a=print(paste0("here: lastUpdated")),
lastUpdated = NULL
)
output$radioStats <- shiny::renderUI({
if(length(input$countries) != 1)
return()
shiny::radioButtons(inputId = "ctryStat",
label = "Stats",
choices = ctryDataStats(),
inline = TRUE
)
})
#### observe lastUpdated ####
observe({
lapply(names(input), function(x) {
shiny::observe({
input[[x]]
values$lastUpdated <- x
})
})
})
output$intraCountry1 <- shiny::renderUI({
if(length(input$countries) != 1)
return()
shiny::radioButtons(inputId = "admLevel",
label = "Admin Level",
choices = ctryAdmLevels()
)
})
#### render UI: intraCountry ####
output$intraCountry <- shiny::renderUI({
print("here: renderUI intracountry")
countries <- input$countries
if(length(countries) != 1)
return()
ctryAdmLevels <- ctryAdmLevels()
ctryAdmLevelNames <- ctryAdmLevelNames()
if (length(ctryAdmLevelNames)>1)
elems <- lapply(2:length(ctryAdmLevels), function(lvlIdx){
lvl <- ctryAdmLevels[lvlIdx]
lvlSelect <- unique(ctryAdmLevelNames[[ctryAdmLevels[lvlIdx]]])
# a <- checkboxInput(inputId = paste0("radioAdm", lvlIdx),
# label = ctryAdmLevels[lvlIdx],
# value = FALSE
# )
b <- shiny::selectizeInput(inputId = paste0("selectAdm", lvlIdx),
label = ctryAdmLevels[lvlIdx],
choices = NULL,
selected = NULL,
multiple = TRUE
)
shiny::updateSelectizeInput(session = session,
inputId = paste0("selectAdm", lvlIdx),
choices = lvlSelect,
server = TRUE
)
b
#list(a,b)
})
})
#### observe selectAdms (intraCountry) ####
shiny::observe({
print(paste0("here: observe selectAdms"))
admLvlCtrlsNames <- names(input)
x <- admLvlCtrlsNames[grep("selectAdm", admLvlCtrlsNames)]
if(length(x)==0)
return()
admSelected <- FALSE
lowestSelected <- ""
for (i in x)
{
if (length(input[[i]]) > 0)
{
admSelected <- TRUE
lowestSelected <- gsub("[^[:digit:]]","",i)
}
}
if (!admSelected)
return()
ctryAdmLevelNames <- ctryAdmLevelNames()
ctryAdmLevelNamesFilter <- ctryAdmLevelNames
ctryAdmLevels <- ctryAdmLevels()
lvlNum <- gsub("[^[:digit:]]", "",values$lastUpdated) #gsub("[^[:digit:]]", "", x)
if(lvlNum=="")
return()
print(paste0("lastupdated:", values$lastUpdated))
print(paste0("x:", x))
print(paste0("lvlnum:", lvlNum))
#set admLevel to match the selectizeInput level
#if (length(input[[paste0("selectAdm", lvlNum)]]) > 0)
updateRadioButtons(session = session, inputId = "admLevel", selected = ctryAdmLevels[as.numeric(lowestSelected)])
multipleSelected <- FALSE
for (lvlIdx in 2:length(ctryAdmLevels))
{
lvlSelect <- ""
top10 <- ""
if (length(input[[paste0("selectAdm", lvlIdx)]]) > 1)
multipleSelected <- TRUE
if (lvlIdx < lvlNum)
{
print(paste0("lvlIdx:",lvlIdx,"lvlNum:",lvlNum))
if (length(input[[paste0("selectAdm", lvlIdx-1)]]) == 1)
{
ctryAdmLevelNamesFilter <- subset(ctryAdmLevelNamesFilter,ctryAdmLevelNamesFilter[[ctryAdmLevels[[lvlIdx-1]]]]==input[[paste0("selectAdm", lvlIdx-1)]])
lvlSelect <- unique(ctryAdmLevelNamesFilter[[ctryAdmLevels[lvlIdx]]])
}
else
{
lvlSelect <- unique(ctryAdmLevelNamesFilter[[ctryAdmLevels[lvlIdx]]])
}
#print(paste0("lvlSelect:",lvlSelect))
#print(paste0("lvlselect: ", lvlSelect))
#print(paste0("top10: ", top10))
#updateCheckboxInput(session, paste0("radioAdm", lvlIdx),value = TRUE)
shiny::updateSelectInput(session, paste0("selectAdm",lvlIdx), choices = lvlSelect, selected = input[[paste0("selectAdm",lvlIdx)]])
}
else if(lvlIdx == lvlNum)
{
print(paste0("lvlIdx:",lvlIdx,"lvlNum:",lvlNum))
if (length(input[[paste0("selectAdm", lvlIdx-1)]]) == 1)
{
ctryAdmLevelNamesFilter <- subset(ctryAdmLevelNamesFilter,ctryAdmLevelNamesFilter[[ctryAdmLevels[[lvlIdx-1]]]]==input[[paste0("selectAdm", lvlIdx-1)]])
lvlSelect <- unique(ctryAdmLevelNamesFilter[[ctryAdmLevels[lvlIdx]]])
#top10 <- if(length(lvlSelect) > 1) lvlSelect[1] else no = lvlSelect
#print(paste0("lvlselect: ", lvlSelect))
#print(paste0("top10: ", top10))
#updateCheckboxInput(session, paste0("radioAdm", lvlIdx),value = TRUE)
# if (length(input[[paste0("radioAdm", lvlIdx)]])==0)
shiny::updateSelectizeInput(session, paste0("selectAdm",lvlIdx), choices = lvlSelect, selected = input[[paste0("selectAdm",lvlIdx)]])
}else
{
shiny::updateSelectizeInput(session, paste0("selectAdm", lvlIdx), choices = NULL, selected = NULL)
}
}
else
{
print(paste0("lvlIdx:",lvlIdx,"lvlNum:",lvlNum))
if (multipleSelected)
{
shiny::updateSelectizeInput(session, paste0("selectAdm", lvlIdx), choices = "", selected = NULL)
next()
}
if(length(input[[paste0("selectAdm",lvlIdx-1)]]) == 1)
{
ctryAdmLevelNamesFilter <- subset(ctryAdmLevelNamesFilter,ctryAdmLevelNamesFilter[[ctryAdmLevels[[lvlIdx-1]]]]==input[[paste0("selectAdm", lvlIdx-1)]])
lvlSelect <- unique(ctryAdmLevelNamesFilter[[ctryAdmLevels[lvlIdx]]])
#updateCheckboxInput(session, paste0("radioAdm", lvlIdx),value = FALSE)
shiny::updateSelectizeInput(session, paste0("selectAdm", lvlIdx), choices = lvlSelect, selected = NULL)
}
else if(length(input[[paste0("selectAdm",lvlIdx-1)]]) == 0 && length(input[[paste0("selectAdm", lvlNum)]])==1)
{
lvlSelect <- unique(ctryAdmLevelNamesFilter[[ctryAdmLevels[lvlIdx]]])
shiny::updateSelectizeInput(session, paste0("selectAdm", lvlIdx), choices = lvlSelect, selected = NULL)
}
else
{
lvlSelect <- unique(ctryAdmLevelNamesFilter[[ctryAdmLevels[lvlIdx]]])
shiny::updateSelectizeInput(session, paste0("selectAdm", lvlIdx), choices = lvlSelect, selected = NULL)
}
}
}
#})
})
#})
#### sliderNlYearMonthRange ####
output$sliderNlYearMonthRange <- shiny::renderUI({
print(paste0("here: sliderNlYearMonthRange"))
ctryData <- ctryNlDataMelted()
if (is.null(ctryData))
{
shiny::sliderInput(inputId = "nlYearMonthRange",
label = "Time",
min = as.Date("2012-04-01", "%Y-%m-%d"),
max = as.Date("2016-12-31", "%Y-%m-%d"),
timeFormat = "%Y-%m",
step = 31,
value = c(as.Date("2012-01-01","%Y-%m-%d"),as.Date("2016-12-31","%Y-%m-%d"))
)
}
else
{
minDate <- min(ctryData$variable)
maxDate <- max(ctryData$variable)
shiny::sliderInput(inputId = "nlYearMonthRange",
label = "Time",
min = minDate,
max = maxDate,
timeFormat = "%Y-%m",
step = 31,
value = c(minDate, maxDate),
animate = animationOptions(interval = 2000, loop = FALSE, playButton = NULL, pauseButton = NULL)
)
}
})
#### sliderNlYearMonth ####
output$sliderNlYearMonth <- shiny::renderUI({
print(paste0("here: sliderNlYearMonth"))
ctryData <- ctryNlDataMelted()
if (is.null(ctryData))
{
shiny::sliderInput(inputId = "nlYearMonth",
label = "Time",
min = as.Date("2012-04-01", "%Y-%m-%d"),
max = as.Date("2016-12-31", "%Y-%m-%d"),
timeFormat = "%Y-%m",
step = 31,
value = as.Date("2012-04-01", "%Y-%m-%d")
)
}
else
{
minDate <- min(ctryData$variable)
maxDate <- max(ctryData$variable)
shiny::sliderInput(inputId = "nlYearMonth",
label = "Time",
min = minDate,
max = maxDate,
timeFormat = "%Y-%m",
step = 31,
value = minDate,
animate = animationOptions(interval = 10000, loop = FALSE, playButton = "Play", pauseButton = NULL)
)
}
})
####reactive hcluster####
hCluster <- shiny::reactive({
print(paste0("here: reactive hCluster"))
input$btnGo
countries <- shiny::isolate(input$countries)
if (is.null(countries))
return()
scale <- input$scale
shiny::isolate({
nlYearMonthRange <- input$nlYearMonthRange
graphType <- input$graphType
admLevel <- ctryAdmLevels()[2]
#return if the country doesn't have adm levels below country
if (is.na(admLevel))
return()
meltCtryData <- ctryNlDataMelted()
if (is.null(countries) || is.null(meltCtryData))
return()
if ("norm_area" %in% scale)
meltCtryData$value <- (meltCtryData$value)/meltCtryData$area_sq_km
#aggMeltCtryData <- aggregate(mean(value), by=list(eval(admLevel)+variable), data=meltCtryData, mean)
aggMeltCtryData <- stats::setNames(meltCtryData[,list(mean(value, na.rm = TRUE)), by = list(meltCtryData[[admLevel]], variable)], c(admLevel, "variable", "value"))
dcastFormula <- paste(paste(admLevel, collapse = " + "), "~", paste("variable", collapse = " + "))
unmeltCtryData <- data.table::dcast(aggMeltCtryData, dcastFormula, value.var='value', aggregate='mean')
d <- stats::dist(unmeltCtryData)
h <- stats::hclust(d)
h$labels <- unmeltCtryData[[admLevel]]
h
})
})
output$plotHCluster <- shiny::renderPlot({
print(paste0("here: plotHCluster"))
clusts <- hCluster()
numClusters <- input$kClusters
if (is.null(clusts))
return("Country has no adm levels")
shiny::isolate({
dendro <- stats::as.dendrogram(clusts)
cbPalette <- c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
dendro %>% dendextend::color_branches(k=numClusters, col = cbPalette) %>%
dendextend::color_labels(k=numClusters, col = cbPalette) %>%
graphics::plot(horiz=FALSE, main = "")
dendro %>% dendextend::rect.dendrogram(k=numClusters,horiz=FALSE,border = cbPalette)
})
})
####renderPlotly plotCluster####
output$plotPointsCluster <- plotly::renderPlotly({
print(paste0("here: plotPointsCluster"))
input$btnGo
countries <- shiny::isolate(input$countries)
if(length(countries) < 1)
return()
clusts <- hCluster()
if(is.null(clusts))
return()
admLevel <- ctryAdmLevels()[2]
#return if the country doesn't have adm levels below country
if (admLevel == "")
return()
numClusters <- input$kClusters
scale <- input$scale
isolate({
meltCtryData <- ctryNlDataMelted()
if ("norm_area" %in% scale)
meltCtryData$value <- (meltCtryData$value)/meltCtryData$area_sq_km
cutClusts <- stats::cutree(clusts, k=numClusters)
#ctryAvg <- aggregate(value ~ admLevel, data=meltCtryData, mean)
ctryAvg <- stats::setNames(meltCtryData[,mean(value, na.rm = TRUE), by = list(meltCtryData[[admLevel]])], c(admLevel, "value"))
cbPalette <- c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
g <- ggplot2::ggplot(data=ctryAvg, aes(x=ctryAvg[[admLevel]], y=value, col=as.factor(cutClusts)))+geom_point(size=2)+ theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) + ggplot2::scale_colour_manual(values=cbPalette)
plotly::ggplotly(g)
})
})
output$mapHCluster <- leaflet::renderLeaflet({
print(paste0("here: draw mapHCluster"))
# Use leaflet() here, and only include aspects of the map that
# won't need to change dynamically (at least, not unless the
# entire map is being torn down and recreated).
input$btnGo
countries <- shiny::isolate(input$countries)
scale <- input$scale
numClusters <- input$kClusters
shiny::isolate({
if (is.null(countries))
return()
if (length(countries) != 1)
{
renderText("Please select only one country/region")
return()
}
print("drawing leaflet cluster")
clusts <- hCluster()
cutClusts <- stats::cutree(clusts, k=numClusters)
admLevel <- ctryAdmLevels()[2]
meltCtryData <- ctryNlDataMelted()
if ("norm_area" %in% scale)
meltCtryData$value <- (meltCtryData$value)/meltCtryData$area_sq_km
ctryPoly0 <- rgdal::readOGR(getPolyFnamePath(countries), getCtryShpLyrName(countries,0))
map <- leaflet::leaflet(data=ctryPoly0) %>%
#addTiles("http://a.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}.png") %>%
leaflet::addTiles() %>%
leaflet::addWMSTiles(layerId="nlRaster", baseUrl = "http://localhost/cgi-bin/mapserv?map=nightlights_wms.map", layers = "nightlights_201204", options = WMSTileOptions(format = "image/png", transparent = TRUE, opacity=1)) %>%
leaflet::addPolygons(layerId = countries, fill = FALSE, fillColor = "#fefe40", stroke = TRUE, weight=4, smoothFactor = 0.7, opacity = 1, color="white", dashArray = "5", group = "country")
lvlCtryData <- stats::setNames(meltCtryData[,mean(value, na.rm = TRUE), by = list(meltCtryData[[admLevel]])], c(admLevel, "value"))
lvlCtryData[["rank"]] <- with(lvlCtryData, rank(-value, ties.method = 'first'))
cbPalette <- c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
pal <- cbPalette
#turn off previous layer? No point keeping it if it is hidden. Also we want to turn the current layer to transparent so that one can see through to the raster layer on hover
ctryPoly <- rgdal::readOGR(getPolyFnamePath(countries), getCtryShpLyrName(countries, 1))
ctryPoly <- sp::spTransform(ctryPoly, wgs84)
mapLabels <- sprintf(
paste0("%s:%s", "<br/>Cluster: %s", "<br/>Rad:%s", "<br/>Rank: %s/%s"),
admLevel, lvlCtryData[[1]], cutClusts, format(lvlCtryData[[2]],scientific = T,digits = 2), lvlCtryData[["rank"]], nrow(lvlCtryData)
) %>% lapply(htmltools::HTML)
map <- map %>% leaflet::addPolygons(
data = ctryPoly,
layerId = as.character(ctryPoly@data[,'NAME_1']),
fill = TRUE,
fillColor = pal[cutClusts],
fillOpacity = 0.9,
stroke = TRUE,
weight=1,
smoothFactor = 0.7,
opacity = 1,
color="white",
dashArray = "5",
group = admLevel,
highlight = leaflet::highlightOptions(
weight = 5,
color = "#666",
dashArray = "",
fillOpacity = 0,
bringToFront = TRUE),
label = mapLabels,
labelOptions = leaflet::labelOptions(
style = list("font-weight" = "normal",
padding = "3px 8px"),
textsize = "15px",
direction = "auto"
)
)
map <- map %>% leaflet::addLayersControl(overlayGroups = admLevel)
map <- map %>% leaflet::addLegend(position = "bottomright",
colors = pal[unique(cutClusts)],
labels = unique(cutClusts),
#title = "Nightlight percentiles",
title = "clusters",
opacity = 1 )
map
})
})
####renderPlotly plotTSDecomposed####
output$plotTSDecomposed <- shiny::renderPlot({
print(paste0("here: plotTSDecomposed"))
input$btnGo
countries <- shiny::isolate(input$countries)
if(length(countries) < 1)
return()
admLevel <- ctryAdmLevels()[1]
#return if the country doesn't have adm levels below country
if (admLevel == "")
return()
scale <- input$scale
shiny::isolate({
meltCtryData <- ctryNlDataMelted()
if ("norm_area" %in% scale)
meltCtryData$value <- (meltCtryData$value)/meltCtryData$area_sq_km
#ctryAvg <- aggregate(value ~ admLevel, data=meltCtryData, mean)
ctryAvg <- stats::setNames(meltCtryData[,mean(value, na.rm = TRUE), by = list(meltCtryData[[admLevel]], variable)], c(admLevel, "variable", "value"))
startYear <- lubridate::year(min(ctryAvg$variable))
startMonth <- lubridate::month(min(ctryAvg$variable))
endYear <- lubridate::year(max(ctryAvg$variable))
endMonth <- lubridate::month(max(ctryAvg$variable))
ctryDataTS <- stats::ts(ctryAvg$value, start = c(startYear,startMonth), end = c(endYear,endMonth), frequency = 12)
ctryDataTScomponents <- stats::decompose(ctryDataTS)
g <- ggplot2::autoplot(ctryDataTScomponents)
graphics::plot(ctryDataTScomponents)
})
})
####renderPlotly plotYearly####
output$plotYearly <- plotly::renderPlotly({
print(paste0("here: renderPlotYearly"))
input$btnGo
countries <- shiny::isolate(input$countries)
if (is.null(countries))
return()
scale <- input$scale
nlYearMonthRange <- input$nlYearMonthRange
graphType <- input$graphType
shiny::isolate({
ctryData <- ctryNlDataMelted()
if (is.null(countries) || is.null(ctryData))
return()
admLvlCtrlNames <- names(input)
x <- admLvlCtrlNames[grep("selectAdm", admLvlCtrlNames)]
admLvlNums <- NULL
for (i in x)
if(length(input[[i]])>0)
admLvlNums <- c(admLvlNums, i)
print(paste0("x", x))
print(paste0("admlvlnums:", admLvlNums))
#if (admLvlNum=="" && length(countries)>0)
# return()
admLvlNums <- as.numeric(gsub("[^[:digit:]]","",admLvlNums))
if (length(admLvlNums)==0)
admLvlNums <- 1
ctryAdmLevels <- ctryAdmLevels()
admLevel <- ctryAdmLevels[as.numeric(data.table::last(admLvlNums))]
print(paste0("admLevel:", admLevel))
if (!exists("admLevel") || is.null(admLevel) || length(admLevel)==0)
admLevel <- "country"
ctryData <- subset(ctryData, variable >= nlYearMonthRange[1] & variable <= nlYearMonthRange[2])
for (lvl in admLvlNums)
{
if (lvl == 1)
next()
print(paste0("lvl:",lvl))
if (length(input[[x[lvl-1]]])>0)
{
ctryData <- subset(ctryData, ctryData[[ctryAdmLevels[lvl]]] %in% input[[x[lvl-1]]])
}
}
ctryData$year <- lubridate::year(ctryData$variable)
ctryData$month <- lubridate::month(ctryData$variable)
print(paste0("ctrydata nrow:", nrow(ctryData)))
if ("norm_area" %in% scale)
ctryData$value <- (ctryData$value)/ctryData$area_sq_km
if (graphType == "boxplot")
{
if (length(countries)==1)
{
g <- ggplot2::ggplot(data=ctryData, aes(x=factor(variable), y=value, col=ctryData[[admLevel]])) + ggplot2::theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) + ggplot2::labs(col=admLevel)
}
else
{
g <- ggplot2::ggplot(data=ctryData, aes(x=factor(variable), y=value, col=country)) + ggplot2::theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) + ggplot2::labs(col=admLevel)
}
g <- g + ggplot2::geom_boxplot()# +facet_grid(.~variable)
}
else if (graphType == "line")
{
if (length(countries)==1)
{
#switched to data.table aggregation
#ctryData <- setNames(aggregate(ctryData$value, by=list(ctryData[,admLevel], ctryData[,"variable"]), mean, na.rm=T), c(admLevel, "variable", "value"))
ctryData <- stats::setNames(ctryData[,list(mean(value, na.rm = TRUE)), by = list(ctryData[[admLevel]], variable, as.factor(year), as.factor(month))], c(admLevel, "variable", "year", "month", "value"))
g <- ggplot2::ggplot(ctryData, aes(x=month, y=value, col=year, group=year))
}
else
{
#ctryData <- aggregate(value ~ country+variable, data=ctryData, mean)
#switched to data.table aggregation
ctryData <- stats::setNames(ctryData[,mean(value, na.rm = TRUE),by = list(country, variable)], c("country", "variable", "value"))
g <- ggplot2::ggplot(data=ctryData, aes(x=variable, y=value, col=country))
}
g <- g + ggplot2::geom_line() + ggplot2::geom_point() + ggplot2::geom_smooth(aes(group=1),method = "loess", weight=3) #+ theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) #+ labs(col=year)
}
else if (graphType == "histogram")
{
#ctryData <- aggregate(value ~ country+variable, data=ctryData, mean)
g <- ggplot(data=ctryData, aes(x=value))
g <- g + ggplot2::geom_histogram(aes(y=..density..), bins = 30, colour="black", fill="white") + ggplot2::geom_density(alpha=.2, fill="#FF6666") + ggplot2::facet_wrap(~ variable+country, ncol = length(countries)) # Overlay with transparent density plot
}
if ("scale_y_log" %in% scale)
g <- g + ggplot2::scale_y_log10()
if ("scale_x_log" %in% scale)
g <- g + ggplot2::scale_x_log10()
if ("norm_area" %in% scale)
g <- g + ggplot2::labs(title="Nightlight Radiances", x = "Month", y = expression(paste("Avg Rad W" %.% "Sr" ^{-1} %.% "cm" ^{-2}, "per Km" ^{2})))
else
g <- g + ggplot2::labs(title="Nightlight Radiances", x = "Month", y = expression(~Total~Rad~W %.% Sr^{-1}%.%cm^{-2}))
plotly::ggplotly(g)
})
})
#### renderPlotly plotNightLights####
output$plotNightLights <- plotly::renderPlotly({
print(paste0("here: renderPlot"))
input$btnGo
countries <- shiny::isolate(input$countries)
if (is.null(countries))
return()
scale <- input$scale
nlYearMonthRange <- input$nlYearMonthRange
graphType <- input$graphType
ctryData <- ctryNlDataMelted()
if (is.null(countries) || is.null(ctryData))
return()
admLvlCtrlNames <- names(input)
x <- admLvlCtrlNames[grep("selectAdm", admLvlCtrlNames)]
shiny::isolate({
admLvlNums <- NULL
for (i in x)
if(length(input[[i]])>0)
admLvlNums <- c(admLvlNums, i)
print(paste0("x", x))
print(paste0("admlvlnums:", admLvlNums))
#if (admLvlNum=="" && length(countries)>0)
# return()
admLvlNums <- as.numeric(gsub("[^[:digit:]]","",admLvlNums))
if (length(admLvlNums)==0)
admLvlNums <- 1
ctryAdmLevels <- ctryAdmLevels()
admLevel <- ctryAdmLevels[as.numeric(data.table::last(admLvlNums))]
print(paste0("admLevel:", admLevel))
if (!exists("admLevel") || is.null(admLevel) || length(admLevel)==0)
admLevel <- "country"
ctryData <- subset(ctryData, variable >= nlYearMonthRange[1] & variable <= nlYearMonthRange[2])
for (lvl in admLvlNums)
{
if (lvl == 1)
next()
print(paste0("lvl:",lvl))
if (length(input[[x[lvl-1]]])>0)
{
ctryData <- subset(ctryData, ctryData[[ctryAdmLevels[lvl]]] %in% input[[x[lvl-1]]])
}
}
print(paste0("ctrydata nrow:", nrow(ctryData)))
if ("norm_area" %in% scale)
ctryData$value <- (ctryData$value)/ctryData$area_sq_km
if (graphType == "boxplot")
{
if (length(countries)==1)
{
g <- ggplot2::ggplot(data=ctryData, ggplot2::aes(x=factor(variable), y=value, col=ctryData[[admLevel]])) + ggplot2::theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) + ggplot2::labs(col=admLevel)
}
else
{
g <- ggplot2::ggplot(data=ctryData, ggplot2::aes(x=factor(variable), y=value, col=country)) + ggplot2::theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) + ggplot2::labs(col=admLevel)
}
g <- g + ggplot2::geom_boxplot()# +facet_grid(.~variable)
}
else if (graphType == "line")
{
if (length(countries)==1)
{
#switched to data.table aggregation
#ctryData <- setNames(aggregate(ctryData$value, by=list(ctryData[,admLevel], ctryData[,"variable"]), mean, na.rm=T), c(admLevel, "variable", "value"))
ctryData <- stats::setNames(ctryData[,mean(value, na.rm = TRUE),by = list(ctryData[[admLevel]], variable)], c(admLevel, "variable", "value"))
g <- ggplot2::ggplot(data=ctryData, aes(x=variable, y=value, col=ctryData[[admLevel]]))
}
else
{
#ctryData <- aggregate(value ~ country+variable, data=ctryData, mean)
#switched to data.table aggregation
ctryData <- stats::setNames(ctryData[,mean(value, na.rm = TRUE),by = list(country, variable)], c("country", "variable", "value"))
g <- ggplot2::ggplot(data=ctryData, aes(x=variable, y=value, col=country))
}
g <- g+ ggplot2::geom_line() + ggplot2::geom_point()+ ggplot2::theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) + ggplot2::labs(col=admLevel)