In the R Shiny code below there are two user input tables: parentTbl
and childTbl
. Both are generated using rhandsontable
. The user can input two "Y" values into the parentTbl
input table which in the full code applies these Y variables over time window "W". Values in parentTbl
flow downstream into a group of two linked and detailed user input tables called “childTbl
”. The user can optionally enter values into any one of the two childTbl
user input tables. In childTbl
the user can alter the variable Y at time period "X" by inserting new rows via right mouse click and entering values into the added rows of the rhandsontable
. Regardless of which table the user inputs values into, whether parentTbl
or childTbl
or both or none, values flow from parentTbl
to childTbl
to a calculation model (not shown). Note that the first row of parentTbl
is directly linked to and corresponds to childTbl
“Var_A”, the second row of parentTbl is directly linked to and corresponds to childTbl
“Var_B”. Basically, childTbl
allows the user the explode the values input into parentTbl
.
Variable "W" for time window (per the slider input$periods
) serves as the outer perimeter for variable X in the childTbl
.
If the user has built up a childTbl
(without changing input$periods
) and then enters a new value into the corresponding row of the parentTbl
, then the associated childTbl
correctly resets as shown in the 1st image below.
If the user has built up a childTbl
and then changes input$periods
to a value less than the value in an X column of a childTbl
, then those childTbl
rows are automatically and correctly deleted as shown in the 2nd image below.
However, if the user has built up a childTbl
and then changes input$periods
, then the corresponding childTbl
no longer resets upon a change to parentTbl
as shown in the 3rd image below.
How do I make this reset mechanism upon a parentTbl
input take precedence over all other observers and operations in all scenarios? Changing a parentTbl
value should always reset the corresponding childTbl
, and only that childTbl
and not all the childTbl
tables. While not losing any other functionality, such as resetting only the childTbl
associated with the parentTbl
row that is modified by user input and deleting only those childTbl
rows where its X value > value of new input$periods
.
Here it the reduced code, I left in many print()
statements for reactive variable tracking making the code look longer than it need be:
library(rhandsontable)
library(shiny)
testVars <- c("Var_A","Var_B")
dft_vals <- c(18, 6)
names(dft_vals) <- testVars
ui <-
fluidPage(
sliderInput("periods", "Time window (W):", min = 1, max = 60 * 2, value = 60),
h5(strong("Variable (Y) over window (W):")),
rHandsontableOutput("parentTbl"),
uiOutput("childTbl")
)
server <- function(input,output,session)({
parentVars <- lapply(testVars, function(var) reactiveValues(data = dft_vals[var]))
grpInputs <- reactiveValues(tables = list())
output$parentTbl <- renderRHandsontable({
rhandsontable(
data.frame(Inputs = sapply(parentVars, function(x) x$data)),
readOnly = FALSE,
colHeaders = NULL,
rowHeaders = testVars,
contextMenu = FALSE
)
})
observeEvent(input$parentTbl, {
newValues <- hot_to_r(input$parentTbl)$Inputs
for (i in 1:2) {
if (parentVars[[i]]$data != newValues[i]) {
print(paste("Row ID:", testVars[i], "New Value:", newValues[i]))
grpInputs$tbl[[testVars[i]]] <- data.frame(X = 1, Y = newValues[i])
}
parentVars[[i]]$data <- newValues[i]
}
})
observe({
print("Contents of parentVars:")
for (i in 1:length(parentVars)){print(parentVars[[i]]$data)}
print("Contents of grpInputs:")
print(reactiveValuesToList(grpInputs))
})
# Below block eliminates child table rows where column X > input$periods
observeEvent(input$periods, {
lapply(testVars, function(varInputId) {
if (!is.null(grpInputs$tbl[[varInputId]])) {
updated_tbl <- grpInputs$tbl[[varInputId]]
updated_tbl <- subset(updated_tbl, X <= input$periods)
grpInputs$tbl[[varInputId]] <- updated_tbl
output[[varInputId]] <- renderRHandsontable({
rhandsontable(updated_tbl, contextMenu = TRUE, rowHeaders = FALSE) %>%
hot_validate_numeric(col = 1, min = 1, max = input$periods)
})
}
})
})
# Below block builds child X/Y tables
lapply(1:2, function(i) {
varInputId <- testVars[i]
output[[varInputId]] <- renderRHandsontable({
df <- data.frame(X = 1, Y = parentVars[[i]]$data)
rhandsontable(df, contextMenu = TRUE, minRows = 1, rowHeaders = FALSE) %>%
hot_validate_numeric(col = 1, min = 1, max = input$periods)
})
})
output$childTbl <- renderUI({
lapply(1:2, function(i) {
varInputId <- testVars[i]
list(
h5(strong(paste("Adjust ", varInputId, " (Y) at time X:"))),
rHandsontableOutput(varInputId)
)
})
})
# Below keeps childTbl from resetting due to change in input$periods
observe({
lapply(1:2, function(i) {
varInputId <- testVars[i]
if (!is.null(input[[varInputId]])) {
grpInputs$tbl[[i]] <- tryCatch({
hot_to_r(input[[varInputId]])
}, error = function(e) {
grpInputs$tbl[[i]]
})
names(grpInputs$tbl)[i] <- varInputId
}
})
})
})
shinyApp(ui = ui, server = server)
I didn't know about the priority parameter for observers, that is a very handy feature. Thank you ismirsehregal! However, I was able to resolve the issue by changing the logic. I now update the corresponding childTbl
within the observeEvent(input$parentTbl, {...})
block when the parentTbl
values change. This ensures that when a value is updated in parentTbl
, the corresponding childTbl
is also updated. Here is the corrected code:
library(rhandsontable)
library(shiny)
testVars <- c("Var_A","Var_B")
dft_vals <- c(18, 6)
names(dft_vals) <- testVars
ui <-
fluidPage(
sliderInput("periods", "Time window (W):", min = 1, max = 60 * 2, value = 60),
h5(strong("Variable (Y) over window (W):")),
rHandsontableOutput("parentTbl"),
uiOutput("childTbl")
)
server <- function(input,output,session)({
parentVars <- lapply(testVars, function(var) reactiveValues(data = dft_vals[var]))
grpInputs <- reactiveValues(tables = list())
output$parentTbl <- renderRHandsontable({
rhandsontable(
data.frame(Inputs = sapply(parentVars, function(x) x$data)),
readOnly = FALSE,
colHeaders = NULL,
rowHeaders = testVars,
contextMenu = FALSE
)
})
observeEvent(input$parentTbl, {
newValues <- hot_to_r(input$parentTbl)$Inputs
for (i in 1:2) {
if (parentVars[[i]]$data != newValues[i]) {
parentVars[[i]]$data <- newValues[i]
# Update the corresponding childTbl
child_var <- testVars[i]
child_data <- data.frame(X = 1, Y = parentVars[[i]]$data)
output[[child_var]] <- renderRHandsontable({
rhandsontable(child_data, contextMenu = TRUE, minRows = 1, rowHeaders = FALSE) %>%
hot_validate_numeric(col = 1, min = 1, max = input$periods)
})
}
}
})
# Below block eliminates child table rows where column X > input$periods
observeEvent(input$periods, {
lapply(testVars, function(varInputId) {
if (!is.null(grpInputs$tbl[[varInputId]])) {
updated_tbl <- grpInputs$tbl[[varInputId]]
updated_tbl <- subset(updated_tbl, X <= input$periods)
grpInputs$tbl[[varInputId]] <- updated_tbl
output[[varInputId]] <- renderRHandsontable({
rhandsontable(updated_tbl, contextMenu = TRUE, rowHeaders = FALSE) %>%
hot_validate_numeric(col = 1, min = 1, max = input$periods)
})
}
})
})
# Below block builds child X/Y tables
lapply(1:2, function(i) {
varInputId <- testVars[i]
output[[varInputId]] <- renderRHandsontable({
df <- data.frame(X = 1, Y = parentVars[[i]]$data)
rhandsontable(df, contextMenu = TRUE, minRows = 1, rowHeaders = FALSE) %>%
hot_validate_numeric(col = 1, min = 1, max = input$periods)
})
})
output$childTbl <- renderUI({
lapply(1:2, function(i) {
varInputId <- testVars[i]
list(
h5(strong(paste("Adjust ", varInputId, " (Y) at time X:"))),
rHandsontableOutput(varInputId)
)
})
})
# Below keeps childTbl from resetting due to change in input$periods
observe({
lapply(1:2, function(i) {
varInputId <- testVars[i]
if (!is.null(input[[varInputId]])) {
grpInputs$tbl[[i]] <- tryCatch({
hot_to_r(input[[varInputId]])
}, error = function(e) {
grpInputs$tbl[[i]]
})
names(grpInputs$tbl)[i] <- varInputId
}
})
})
})
shinyApp(ui = ui, server = server)