eCerto_R6Class {eCerto} | R Documentation |
A reactive class based on an R6 object.
Description
Builds a class, which allows only restricted access to the
contained 'reactiveValues'. Elements should be accessed via getValue()
.
Possible advantages are that (1) structure of 'reactiveValues' is clear
from the beginning (no function like "addVariable" should exist!) and that
(2) functions to calculate the mean or plot current data can be implemented
here directly.
General access to data object (so data object can maybe get changed without that much code edit)
Returns element. If 'key' is used, reactivity not working correctly.
Preferable way for calling getValue(df, key)
, see example
Usage
setValue(df, key, value)
getValue(df, key = NULL)
Arguments
df |
An object of class R6. |
key |
Key value within R6 object 'df'. |
value |
Value to set. |
Value
Nothing. The R6 object is updated automatically.
Value of 'key' from 'df'.
Active bindings
cur_an
Set or return the current analyte (reactiveVal) via an active binding.
Methods
Public methods
Method new()
Write the (reactive) value of element 'keys' from list 'l'.
Usage
eCerto$new(rv)
Arguments
rv
'reactiveValues' object.
Returns
A new 'eCerto' object.
Method get()
Read the value of field element of R6 object.
Usage
eCerto$get(keys = NULL)
Arguments
keys
Name of list element.
Returns
Current value of field.
Method set()
Set element of R6 object defined by 'keys' to new value.
Usage
eCerto$set(keys = NULL, value)
Arguments
keys
Name(s) of list element.
value
New value.
Returns
New value of element (invisible).
Method c_plot()
Plot the certification data either provided by the user or from the private slot of self.
Usage
eCerto$c_plot(data, annotate_id = FALSE, filename_labels = FALSE)
Arguments
data
data.frame containing columns 'value', 'Lab' and 'L_flt' for a specific analyte.
annotate_id
T/F to overlay the plot with ID as text if column 'ID' is present.
filename_labels
T/F to use imported file names as labels on x-axes.
Returns
A plot.
Method c_lab_means()
Compute the analyte means for a data set filtered for a specific analyte.
Usage
eCerto$c_lab_means(data)
Arguments
data
data.frame containing columns 'analyte', 'value', 'Lab', 'S_flt' and 'L_flt'.
Returns
A data.frame of lab means.
Method c_analytes()
Return analyte names currently in apm.
Usage
eCerto$c_analytes()
Returns
A named character vector.
Method c_lab_codes()
Return lab codes currently in C data.
Usage
eCerto$c_lab_codes()
Returns
A named character vector.
Method a_p()
Return currently specified values of a type for all analytes.
Usage
eCerto$a_p( val = c("precision", "precision_export", "pooling", "confirmed", "unit", "name") )
Arguments
val
A character value indicating the item of the apm list to be extracted
Returns
A named vector.
Method e_present()
Return modules with existing data.
Usage
eCerto$e_present()
Returns
A named logical vector.
Method c_fltData()
Filter the full data set for a specific analyte and remove all 'S_flt' but keep 'L_flt'.
Usage
eCerto$c_fltData(recalc = FALSE)
Arguments
recalc
If TRUE triggers a recalculation and returns current object if FALSE..
Returns
A data.frame with filtered data of a single analyte.
Method clone()
The objects of this class are cloneable with this method.
Usage
eCerto$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
Examples
if (interactive()) {
# establish new Shiny session and new eCerto object
ShinySession <- shiny::MockShinySession$new()
test <- eCerto::eCerto$new()
# view current value stored in specific eCerto slot and register observer
shiny::isolate(eCerto::getValue(test, c("Certification", "data")))
shiny::observeEvent(eCerto::getValue(test, c("Certification", "data")), {
message("Certification$data changed:", eCerto::getValue(test, "Certification")$data)
})
# change value of specific eCerto slot and flush reactivity to trigger observer
shiny::isolate(eCerto::setValue(test, c("Certification", "data"), 5))
ShinySession$flushReact()
shiny::isolate(eCerto::getValue(test, c("Certification", "data")))
}
tmp <- eCerto$new()
shiny::isolate(tmp$c_plot())
shiny::isolate(tmp$c_lab_means())
tmp$c_analytes()
tmp$c_lab_codes()
tmp$a_p()
tmp$a_p("pooling")
ca <- shiny::isolate(tmp$cur_an)
tmp$a_p("pooling")[ca]
shiny::isolate(tmp$e_present())
tmp$c_fltData()
shiny::isolate(tmp$cur_an <- "Fe")
shiny::isolate(tmp$cur_an)
tmp$c_fltData()
x <- shiny::isolate(eCerto::getValue(tmp, c("General", "apm")))
x[[shiny::isolate(tmp$cur_an)]][["lab_filter"]] <- "L2"
shiny::isolate(eCerto::setValue(tmp, c("General", "apm"), x))
tmp$c_fltData()
tmp$c_fltData(recalc = TRUE)
# Only run examples in interactive R sessions
if (interactive()) {
rv <- eCerto$new(init_rv())
setValue(rv, c("Certification", "data"), 5)
getValue(rv, c("Certification", "data")) # is 5?
setValue(rv, c("General", "user"), "Franz")
getValue(rv, c("General", "user"))
}