Overview
This issue will track repetitive components that can be modularised.
1. Updating of reactiveValues()
Either updating numeric values (a):
observeEvent(input$optsCostUnit, {
costs$unit <- as.numeric(input$optsCostUnit)
}, ignoreNULL = TRUE)
Inputs unit, pool, cluster, and period all share:
numericInput(inputId = ns(X), label, value = isolate(Y), min = 1e-6, step = 0.5)
And the UI, to make a module pair, is the above.
2. For processOther():
observeEvent(input$optsPrevalence, {
design_opts$prev <- processOther(input, "optsPrevalence")
}, ignoreNULL = TRUE)
3. Validation
Where mod_ui = The error text displayed and mod_server = maybe
reactiveValues(
exists = FALSE,
valid = FALSE
)
where the validation logic should req(exists) to avoid propogating NULL etc.
4. numericInput with "Other"
e.g. Prevalence, Correlation, Sensitivity, Specificity
Overview
This issue will track repetitive components that can be modularised.
1. Updating ofreactiveValues()(numerics)boundNumericInput() andsaveNumericInput`processOther()numericInputwith "Other"1. Updating of
reactiveValues()Either updating numeric values (a):
Inputs unit, pool, cluster, and period all share:
numericInput(inputId = ns(X), label, value = isolate(Y), min = 1e-6, step = 0.5)And the UI, to make a module pair, is the above.
2. For
processOther():3. Validation
Where mod_ui = The error text displayed and mod_server = maybe
where the validation logic should req(exists) to avoid propogating NULL etc.
4.
numericInputwith "Other"e.g. Prevalence, Correlation, Sensitivity, Specificity