diff --git a/R/calcRiskHeatMap.R b/R/calcRiskHeatMap.R
index 821e6b46e6e605e8a0e5c0a2a9294fb24f343dc1..35a5b79f1ed69b96fd90e99be253304bed712230 100644
--- a/R/calcRiskHeatMap.R
+++ b/R/calcRiskHeatMap.R
@@ -2,26 +2,33 @@ calcRiskHeatMap <- function(con, ruleset, station, level, lake) {
iObjective <- which(objectives$station == station & objectives$level == level)
cdfs <- tbl(con, "CDFs")
ruleset <- as.character(ruleset)
- cdf <- cdfs %>%
- filter(id_ruleset == {{ ruleset }},
+ cdf <- cdfs %>%
+ filter(id_ruleset == {{ ruleset }},
id_objective == {{ iObjective }},
- id_lake == {{ lake }}) %>%
+ id_lake == {{ lake }}) %>%
collect()
cdf$id_cal_day <- as.factor(cdf$id_cal_day)
- discretStorage <- seq(0, rvgest::lakes[lake, "max"] - rvgest::lakes[lake, "min"], 1) * 1E6
- listDiscretProbs <- lapply(unique(cdf$id_cal_day), function(x) {
- dataLength <- length(which(cdf$id_cal_day == x))
+ cdf$V <- cdf$V / 1E6 # -> hm3
+ if(!objectives$flood[iObjective]) cdf$prob <- 1 - cdf$prob
+ discretStorage <- seq(0, rvgest::lakes[lake, "max"] - rvgest::lakes[lake, "min"], 1)
+ caldays <- unique(cdf$id_cal_day)
+ listDiscretProbs <- lapply(seq.int(length(caldays)), function(i) {
+ calday <- caldays[i]
+ dataLength <- length(which(cdf$id_cal_day == calday))
if(dataLength > 1) {
- l <- approx(cdf$V[cdf$id_cal_day == x], cdf$prob[cdf$id_cal_day == x], discretStorage, rule = 2)
- data.frame(day = x, V = l$x, prob = l$y)
+ l <- approx(cdf$V[cdf$id_cal_day == calday], cdf$prob[cdf$id_cal_day == calday], discretStorage, rule = 2)
+ data.frame(julian = i, day = calday, V = l$x, prob = round(l$y, digits = 1))
} else if(dataLength == 1){
- data.frame(day = x, V = discretStorage, prob = 0)
+ data.frame(julian = i, day = calday, V = discretStorage, prob = 0)
} else {
warning("No data for lake", lake, " at ", station, " for objective ", level)
}
})
# if(length(listDiscretProbs) == 365) {
- return(do.call(rbind, listDiscretProbs))
+ df <- do.call(rbind, listDiscretProbs)
+ df$V <- round(df$V + rvgest::lakes[lake, "min"])
+ df$julian <- 1:nrow(df)
+ return(df)
# } else {
# return(NULL)
# }
diff --git a/R/getObjectiveStorage.R b/R/getObjectiveStorage.R
index 92d0b20decb25392b843111e13e75e41bcef223e..8dea4afee6d6806d954122bc1ede5e3dc9f8879f 100644
--- a/R/getObjectiveStorage.R
+++ b/R/getObjectiveStorage.R
@@ -3,22 +3,26 @@
#' @param date [Date] (default current date)
#'
#' @return Named [numeric] vector with objective storage for each reservoir
-#' @export
#'
#' @examples
#' getObjectiveStorage()
getObjectiveStorage <- function(date = Sys.Date()) {
+ date_julian <- which(format(date, "%m%d") == objectiveStorageCurves$day)
+ objectiveStorageCurves[date_julian, -1]
+}
+
+getObjectiveStoragePivots <- function() {
pivots <- list(
- data.frame(mmdd = c('1101', '0201', '0301', '0701'),
- S = c(24.5, 84., 130., 170.)),
- data.frame(mmdd = c('1108', '1208', '0208', '0408', '0708'),
- S = c(18.7, 40., 95., 175., 207.8)),
data.frame(mmdd = c('1101', '1231', '0131', '0701'),
S = c(12.3, 34., 50., 80.)),
+ data.frame(mmdd = c('1108', '1208', '0208', '0408', '0708'),
+ S = c(18.7, 40., 95., 175., 207.8)),
+ data.frame(mmdd = c('1101', '0201', '0301', '0701'),
+ S = c(24.5, 84., 130., 170.)),
data.frame(mmdd = c('1101', '0101', '0201', '0301', '0701'),
S = c(25, 100, 170, 260, 350))
)
- names(pivots) <- c("AUBE", "SEINE", "YONNE","MARNE")
+ names(pivots) <- rvgest::lakes$name
caldays <- format(seq(as.Date("2001-01-01"), as.Date("2001-12-31"), 1), "%m%d")
pivots <- lapply(pivots, function(x) {
# sort array by date
@@ -31,9 +35,28 @@ getObjectiveStorage <- function(date = Sys.Date()) {
x$julian[nrow(x)] <- x$julian[nrow(x)] + 365
x
})
- date_julian <- which(format(date, "%m%d") == caldays)
- unlist(lapply(pivots, function(x) {
- approx(x$julian, x$S, date_julian)$y
- }))
}
+objectiveStoragePivots <- getObjectiveStoragePivots()
+
+getObjectiveStorageCurve <- function(lake) {
+ caldays <- format(seq(as.Date("2001-01-01"), as.Date("2001-12-31"), 1), "%m%d")
+ data.frame(day = as.factor(format(seq(as.Date("2001-01-01"), as.Date("2001-12-31"), 1), "%m%d")),
+ S = sapply(seq.int(365), function(i) {
+ approx(objectiveStoragePivots[[lake]]$julian, objectiveStoragePivots[[lake]]$S, i)$y
+ }))
+}
+
+getObjectiveStorageCurves <- function() {
+ l <- lapply(rvgest::lakes$name, function(lake) {
+ df <- getObjectiveStorageCurve(lake)
+ names(df)[2] <- lake
+ df
+ })
+ df <- do.call(cbind, l)
+ df <- df[, c(1, 2 * seq.int(nrow(rvgest::lakes)))]
+ df$julian = seq(365)
+ return(df)
+}
+
+objectiveStorageCurves <- getObjectiveStorageCurves()
diff --git a/R/mod_instant_risk_overview.R b/R/mod_instant_risk_overview.R
index 6bedd3815eaae30692af14994fabd0476ca558f1..29f756ce5dbcb9e8f0270489c81e6e8c58e1240f 100644
--- a/R/mod_instant_risk_overview.R
+++ b/R/mod_instant_risk_overview.R
@@ -4,9 +4,9 @@
#'
#' @param id,input,output,session Internal parameters for {shiny}.
#'
-#' @noRd
+#' @noRd
#'
-#' @importFrom shiny NS tagList
+#' @importFrom shiny NS tagList
mod_instant_risk_overview_ui <- function(id){
ns <- NS(id)
choices <- seq(length(rvgest::rulesets$rules))
@@ -30,7 +30,7 @@ mod_instant_risk_overview_ui <- function(id){
lapply(seq.int(nrow(rvgest::lakes)), function(i) {
column(width = 3,
sliderInput(ns(paste0("V", i)),
- label = rvgest::lakes$name[i],
+ label = paste(rvgest::lakes$name[i], "lake (hm3)"),
value = round(getObjectiveStorage()[rvgest::lakes$name[i]]),
min = rvgest::lakes$min[i],
max = rvgest::lakes$max[i]))
@@ -39,17 +39,17 @@ mod_instant_risk_overview_ui <- function(id){
# tableOutput(ns("table"))
plotOutput(ns("plot"))
)
-
+
}
-
+
#' instant_risk_overview Server Function
#'
-#' @noRd
+#' @noRd
#' @import ggplot2
mod_instant_risk_overview_server <- function(id, con) {
moduleServer(id, function(input, output, session){
ns <- session$ns
-
+
df <- reactive({
storages <- c(input$V1, input$V2, input$V3, input$V4)
names(storages) <- lakes$name
@@ -64,10 +64,10 @@ mod_instant_risk_overview_server <- function(id, con) {
coord_flip())
})
}
-
+
## To be copied in the UI
# mod_instant_risk_overview_ui("instant_risk_overview_ui_1")
-
+
## To be copied in the server
# mod_instant_risk_overview_server("instant_risk_overview_ui_1")
-
+
diff --git a/R/mod_one_objective_focus.R b/R/mod_one_objective_focus.R
index adb59261be88e702c8eaec078e777e57520c5f13..7637aeb555e5904529ac64dc95b54d07b419b0c3 100644
--- a/R/mod_one_objective_focus.R
+++ b/R/mod_one_objective_focus.R
@@ -4,9 +4,9 @@
#'
#' @param id,input,output,session Internal parameters for {shiny}.
#'
-#' @noRd
+#' @noRd
#'
-#' @importFrom shiny NS tagList
+#' @importFrom shiny NS tagList
#' @importFrom rvgest objectives
mod_one_objective_focus_ui <- function(id){
ns <- NS(id)
@@ -50,10 +50,10 @@ mod_one_objective_focus_ui <- function(id){
uiOutput(ns("plots"))
)
}
-
+
#' one_objective_focus Server Functions
#'
-#' @noRd
+#' @noRd
mod_one_objective_focus_server <- function(id, con){
moduleServer( id, function(input, output, session){
ns <- session$ns
@@ -66,18 +66,21 @@ mod_one_objective_focus_server <- function(id, con){
dfDiscretProbs <- calcRiskHeatMap(con, input$ruleset, objective$station, objective$level, lake)
if(!is.null(dfDiscretProbs)) {
breaks <- sapply(iBreaks, function(x) levels(dfDiscretProbs$day)[x])
- p <- ggplot(dfDiscretProbs, aes(x = day, y = V / 1e6)) +
+ objCurve <- data.frame(day = objectiveStorageCurves$day, V = round(objectiveStorageCurves[[lake]]))
+ objCurve <- objCurve[seq.int(1, 365,3),]
+ p <- ggplot(dfDiscretProbs, aes(x = day, y = V)) +
geom_tile(aes(fill = prob)) +
scale_fill_continuous(low = "green", high = "red", name = "Failure probability") +
+ geom_point(data = objCurve, color = "black", size = 1, shape = 21, fill = "grey") +
ggtitle(paste("Lake", lake)) +
scale_x_discrete("Calendar days", breaks = breaks, labels = labels) +
scale_y_continuous(name="Reservoir storage (hm3)")
output[[paste("plot", lake, sep = "_")]] <- renderPlot({p},width = 640, height = 280)
}
})
-
+
})
-
+
output$plots <- renderUI({
objective <- rvgest::objectives[rvgest::objectives$station == input$station & rvgest::objectives$level == input$level,]
plot_output_list <- lapply(objective$lakes[[1]]$name, function(lake) {
@@ -88,9 +91,9 @@ mod_one_objective_focus_server <- function(id, con){
})
})
}
-
+
## To be copied in the UI
# mod_one_objective_focus_ui("one_objective_focus_ui_1")
-
+
## To be copied in the server
# mod_one_objective_focus_server("one_objective_focus_ui_1")
diff --git a/irmara.Rproj b/irmara.Rproj
index 941b140502cfad76fdfd6d280f44ffea1add174f..d6ac4c76e4bfb47378cab32482586fb4088a07e6 100644
--- a/irmara.Rproj
+++ b/irmara.Rproj
@@ -12,6 +12,9 @@ Encoding: WINDOWS-1252
RnwWeave: Sweave
LaTeX: pdfLaTeX
+AutoAppendNewline: Yes
+StripTrailingWhitespace: Yes
+
BuildType: Package
PackageUseDevtools: Yes
PackageInstallArgs: --no-multiarch --with-keep.source
diff --git a/vignettes/debugging/HeatMap.Rmd b/vignettes/debugging/HeatMap.Rmd
new file mode 100644
index 0000000000000000000000000000000000000000..bb9fd52325a002ef23791a98b9781544b796906c
--- /dev/null
+++ b/vignettes/debugging/HeatMap.Rmd
@@ -0,0 +1,59 @@
+---
+title: "Untitled"
+author: "David Dorchies"
+date: "24/04/2021"
+output: html_document
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = TRUE)
+```
+
+# Setup
+
+```{r cars}
+library(irmara)
+library(ggplot2)
+con <- DBI::dbConnect(RSQLite::SQLite(), dbname = irmara:::app_sys("cdf", "Qgen_5000y_unbiased_median.sqlite"))
+objectiveStorageCurves <- irmara:::objectiveStorageCurves
+```
+
+#
+
+```{r}
+ruleset <- 1
+iObjective <- 1
+objective <- rvgest::objectives[iObjective,]
+lake <- objective$lakes[[1]]$name[1]
+```
+
+```{r}
+objCurve <- data.frame(day = objectiveStorageCurves$day, V = round(objectiveStorageCurves[[lake]]))
+objCurve <- objCurve[seq.int(1, 365,3),]
+head(objCurve)
+```
+
+
+```{r}
+indexMonths <- c(1,31,28,31,30,31,30,31,31,30,31,30)
+labels <- unlist(strsplit("JFMAMJJASOND", NULL))
+iBreaks <- sapply(seq.int(12), function(i) sum(indexMonths[1:i]))
+```
+
+```{r}
+dfDiscretProbs <- irmara:::calcRiskHeatMap(con, ruleset, objective$station, objective$level, lake)
+breaks <- sapply(iBreaks, function(x) levels(dfDiscretProbs$day)[x])
+head(dfDiscretProbs)
+```
+
+```{r}
+p <- ggplot(dfDiscretProbs, aes(x = day, y = V)) +
+ geom_tile(aes(fill = prob)) +
+ scale_fill_continuous(low = "green", high = "red", name = "Failure probability") +
+ geom_point(data = objCurve, color = "black", size = 1, shape = 21, fill = "grey") +
+ ggtitle(paste("Lake", lake)) +
+ scale_x_discrete("Calendar days", breaks = breaks, labels = labels) +
+ scale_y_continuous(name="Reservoir storage (hm3)")
+p
+```
+