FilteredData: Class to encapsulate filtered datasets
In teal.slice: Filter Module for 'teal' Applications
FilteredData R Documentation
Class to encapsulate filtered datasets
Description
Manages filtering of all datasets in the application or module.
Details
The main purpose of this class is to provide a collection of reactive datasets,
each dataset having a filter state that determines how it is filtered.
For each dataset, get_filter_expr returns the call to filter the dataset according
to the filter state. The data itself can be obtained through get_data.
The datasets are filtered lazily, i.e. only when requested / needed in a shiny app.
By design, any dataname set through set_dataset cannot be removed because
other code may already depend on it. As a workaround, the underlying
data can be set to NULL.
The class currently supports variables of the following types within datasets:
-
choices: variable of type factor, e.g. ADSL$COUNTRY, iris$Species
zero or more options can be selected, when the variable is a factor
-
logical: variable of type logical, e.g. ADSL$TRT_FLAG
exactly one option must be selected, TRUE or FALSE
-
ranges: variable of type numeric, e.g. ADSL$AGE, iris$Sepal.Length
numerical range, a range within this range can be selected
-
dates: variable of type Date, POSIXlt
Other variables cannot be used for filtering the data in this class.
Common arguments are:
-
filtered: whether to return a filtered result or not
-
dataname: the name of one of the datasets in this FilteredData object
-
varname: one of the columns in a dataset
Methods
Public methods
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Method new()
Initialize a FilteredData object.
Usage
FilteredData$new(data_objects, join_keys = teal.data::join_keys())
Arguments
data_objects(named list)
List of data objects.
Names of the list will be used as dataname for respective datasets.
join_keys(join_keys) optional joining keys, see teal.data::join_keys().
Method datanames()
Gets datanames.
Usage
FilteredData$datanames()
Details
The datanames are returned in the order in which they must be evaluated (in case of dependencies).
Returns
Character vector.
Method get_datalabel()
Gets data label for the dataset.
Useful to display in Show R Code.
Usage
FilteredData$get_datalabel(dataname)
Arguments
dataname(character(1)) name of the dataset
Returns
Character string.
Method set_available_teal_slices()
Set list of external filter states available for activation.
Usage
FilteredData$set_available_teal_slices(x)
Arguments
x(reactive)
should return teal_slices
Details
Unlike adding new filter from the column, these filters can come with some prespecified settings.
teal_slices are wrapped in a reactive so they can be updated from elsewhere in the app.
Filters passed in x are limited to those that can be set for this FilteredData object,
i.e. they have the correct dataname and varname (waived teal_slice_fixed as they do not have varname).
List is accessible in ui/srv_active through ui/srv_available_filters.
Returns
NULL, invisibly.
Method get_available_teal_slices()
Get list of filter states available for this object.
Usage
FilteredData$get_available_teal_slices()
Details
All teal_slice objects that have been created since the beginning of the app session
are stored in one teal_slices object. This returns a subset of that teal_slices,
describing filter states that can be set for this object.
Returns
reactive that returns teal_slices.
Method get_call()
Gets a call to filter the dataset according to the filter state.
Usage
FilteredData$get_call(dataname)
Arguments
dataname(character(1)) name of the dataset
Details
It returns a call to filter the dataset only, assuming the
other (filtered) datasets it depends on are available.
Together with self$datanames() which returns the datasets in the correct
evaluation order, this generates the whole filter code, see the function
FilteredData$get_filter_code.
For the return type, note that rlang::is_expression returns TRUE on the
return type, both for base R expressions and calls (single expression,
capturing a function call).
The filtered dataset has the name given by self$filtered_dataname(dataname)
This can be used for the Show R Code generation.
Returns
A list of calls.
Method get_data()
Gets filtered or unfiltered dataset.
For filtered = FALSE, the original data set with set_data is returned including all attributes.
Usage
FilteredData$get_data(dataname, filtered = TRUE)
Arguments
dataname(character(1)) name of the dataset.
filtered(logical(1)) whether to return a filtered or unfiltered dataset.
Returns
A data object, a data.frame or a MultiAssayExperiment.
Method get_join_keys()
Get join keys between two datasets.
Usage
FilteredData$get_join_keys()
Returns
join_keys
Method get_filter_overview()
Creates filter overview table to be displayed in the application.
One row is created per dataset, according to the get_filter_overview methods
of the contained FilteredDataset objects.
Usage
FilteredData$get_filter_overview(datanames)
Arguments
datanames(character) vector of dataset names.
Returns
A data.frame listing the numbers of observations in all datasets.
Method get_keys()
Get keys for the dataset.
Usage
FilteredData$get_keys(dataname)
Arguments
dataname(character(1)) name of the dataset.
Returns
Character vector of key column names.
Method set_dataset()
Adds a dataset to this FilteredData.
Usage
FilteredData$set_dataset(data, dataname)
Arguments
data(data.frame or MultiAssayExperiment)
data to be filtered.
dataname(character(1))
the name of the dataset to be added to this object.
Details
set_dataset creates a FilteredDataset object which keeps dataset for the filtering purpose.
If this data has a parent specified in the join_keys object stored in private$join_keys
then created FilteredDataset (child) gets linked with other FilteredDataset (parent).
"Child" dataset return filtered data then dependent on the reactive filtered data of the
"parent". See more in documentation of parent argument in DataframeFilteredDataset constructor.
Returns
self, invisibly.
Method set_join_keys()
Set the join_keys.
Usage
FilteredData$set_join_keys(join_keys)
Arguments
join_keys(join_keys), see teal.data::join_keys().
Returns
self, invisibly.
Method get_filter_state()
Gets states of all contained FilterState objects.
Usage
FilteredData$get_filter_state()
Returns
A teal_slices object.
Method format()
Returns a formatted string representing this FilteredData object.
Usage
FilteredData$format(show_all = FALSE, trim_lines = TRUE)
Arguments
show_all(logical(1)) passed to format.teal_slice.
trim_lines(logical(1)) passed to format.teal_slice.
Returns
character(1) the formatted string.
Method print()
Prints this FilteredData object.
Usage
FilteredData$print(...)
Arguments
...additional arguments passed to format.
Method set_filter_state()
Sets active filter states.
Usage
FilteredData$set_filter_state(state)
Arguments
state(teal_slices)
Returns
NULL, invisibly.
Method remove_filter_state()
Removes one or more FilterState from a FilteredData object.
Usage
FilteredData$remove_filter_state(state)
Arguments
state(teal_slices)
specifying FilterState objects to remove;
teal_slices may contain only dataname and varname, other elements are ignored.
Returns
NULL, invisibly.
Method clear_filter_states()
Remove all FilterStates of a FilteredDataset or all FilterStates of a FilteredData object.
Usage
FilteredData$clear_filter_states(datanames = self$datanames(), force = FALSE)
Arguments
datanames(character)
names of datasets for which to remove all filter states.
Defaults to all datasets in this FilteredData object.
force(logical(1))
flag specifying whether to include anchored filter states.
Returns
NULL, invisibly.
Method ui_filter_panel()
top-level shiny module for the filter panel in the teal app.
Contains 1) filter overview panel, 2) filter active panel, and 3) add filters panel.
Usage
FilteredData$ui_filter_panel(id, active_datanames = self$datanames)
Arguments
id(character(1))
shiny module instance id.
active_datanames(reactive)
defining subset of self$datanames() to be displayed.
Returns
shiny.tag
Method srv_filter_panel()
Server function for filter panel.
Usage
FilteredData$srv_filter_panel(id, active_datanames = self$datanames)
Arguments
id(character(1))
shiny module instance id.
active_datanames(function or reactive)
returning datanames that should be shown on the filter panel.
Must be a subset of the datanames in this FilteredData.
If the function returns NULL (as opposed to character(0)),
the filter panel will be hidden.
Returns
NULL.
Method ui_active()
Server module responsible for displaying active filters.
Usage
FilteredData$ui_active(id, active_datanames = self$datanames)
Arguments
id(character(1))
shiny module instance id.
active_datanames(reactive)
defining subset of self$datanames() to be displayed.
Returns
shiny.tag
Method srv_active()
Server module responsible for displaying active filters.
Usage
FilteredData$srv_active(id, active_datanames = self$datanames)
Arguments
id(character(1))
shiny module instance id.
active_datanames(reactive)
defining subset of self$datanames() to be displayed.
Returns
NULL.
Method ui_overview()
Creates the UI definition for the module showing counts for each dataset
contrasting the filtered to the full unfiltered dataset.
Per dataset, it displays
the number of rows/observations in each dataset,
the number of unique subjects.
Usage
FilteredData$ui_overview(id)
Arguments
id(character(1))
shiny module instance id.
Method srv_overview()
Server function to display the number of records in the filtered and unfiltered
data.
Usage
FilteredData$srv_overview(id, active_datanames = self$datanames)
Arguments
id(character(1))
shiny module instance id.
active_datanames(reactive)
returning datanames that should be shown on the filter panel,
must be a subset of the datanames argument provided to ui_filter_panel;
if the function returns NULL (as opposed to character(0)), the filter
panel will be hidden.
Returns
NULL.
Method finalize()
Object and dependencies cleanup.
Destroy inputs and observers stored in private$session_bindings
Finalize FilteredData stored in private$filtered_datasets
Usage
FilteredData$finalize()
Returns
NULL, invisibly.
Method clone()
The objects of this class are cloneable with this method.
Usage
FilteredData$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Examples
# use non-exported function from teal.slice
FilteredData <- getFromNamespace("FilteredData", "teal.slice")
library(shiny)
datasets <- FilteredData$new(list(iris = iris, mtcars = mtcars))
# get datanames
datasets$datanames()
datasets$set_filter_state(
teal_slices(teal_slice(dataname = "iris", varname = "Species", selected = "virginica"))
)
datasets$set_filter_state(
teal_slices(teal_slice(dataname = "mtcars", varname = "mpg", selected = c(15, 20)))
)
isolate(datasets$get_filter_state())
isolate(datasets$get_call("iris"))
isolate(datasets$get_call("mtcars"))
### set_filter_state
library(shiny)
data(miniACC, package = "MultiAssayExperiment")
datasets <- FilteredData$new(list(iris = iris, mae = miniACC))
fs <- teal_slices(
teal_slice(
dataname = "iris", varname = "Sepal.Length", selected = c(5.1, 6.4),
keep_na = TRUE, keep_inf = FALSE
),
teal_slice(
dataname = "iris", varname = "Species", selected = c("setosa", "versicolor"),
keep_na = FALSE
),
teal_slice(
dataname = "mae", varname = "years_to_birth", selected = c(30, 50),
keep_na = TRUE, keep_inf = FALSE
),
teal_slice(dataname = "mae", varname = "vital_status", selected = "1", keep_na = FALSE),
teal_slice(dataname = "mae", varname = "gender", selected = "female", keep_na = TRUE),
teal_slice(
dataname = "mae", varname = "ARRAY_TYPE",
selected = "", keep_na = TRUE, experiment = "RPPAArray", arg = "subset"
)
)
datasets$set_filter_state(state = fs)
isolate(datasets$get_filter_state())
teal.slice documentation built on April 4, 2025, 12:39 a.m.
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| FilteredData | R Documentation |
Class to encapsulate filtered datasets
Description
Manages filtering of all datasets in the application or module.
Details
The main purpose of this class is to provide a collection of reactive datasets, each dataset having a filter state that determines how it is filtered.
For each dataset, get_filter_expr returns the call to filter the dataset according
to the filter state. The data itself can be obtained through get_data.
The datasets are filtered lazily, i.e. only when requested / needed in a shiny app.
By design, any dataname set through set_dataset cannot be removed because
other code may already depend on it. As a workaround, the underlying
data can be set to NULL.
The class currently supports variables of the following types within datasets:
-
choices: variable of typefactor, e.g.ADSL$COUNTRY,iris$Specieszero or more options can be selected, when the variable is a factor -
logical: variable of typelogical, e.g.ADSL$TRT_FLAGexactly one option must be selected,TRUEorFALSE -
ranges: variable of typenumeric, e.g.ADSL$AGE,iris$Sepal.Lengthnumerical range, a range within this range can be selected -
dates: variable of typeDate,POSIXltOther variables cannot be used for filtering the data in this class.
Common arguments are:
-
filtered: whether to return a filtered result or not -
dataname: the name of one of the datasets in thisFilteredDataobject -
varname: one of the columns in a dataset
Methods
Public methods
Method new()
Initialize a FilteredData object.
Usage
FilteredData$new(data_objects, join_keys = teal.data::join_keys())
Arguments
data_objects(
named list) List of data objects. Names of the list will be used asdatanamefor respective datasets.join_keys(
join_keys) optional joining keys, seeteal.data::join_keys().
Method datanames()
Gets datanames.
Usage
FilteredData$datanames()
Details
The datanames are returned in the order in which they must be evaluated (in case of dependencies).
Returns
Character vector.
Method get_datalabel()
Gets data label for the dataset.
Useful to display in Show R Code.
Usage
FilteredData$get_datalabel(dataname)
Arguments
dataname(
character(1)) name of the dataset
Returns
Character string.
Method set_available_teal_slices()
Set list of external filter states available for activation.
Usage
FilteredData$set_available_teal_slices(x)
Arguments
x(
reactive) should returnteal_slices
Details
Unlike adding new filter from the column, these filters can come with some prespecified settings.
teal_slices are wrapped in a reactive so they can be updated from elsewhere in the app.
Filters passed in x are limited to those that can be set for this FilteredData object,
i.e. they have the correct dataname and varname (waived teal_slice_fixed as they do not have varname).
List is accessible in ui/srv_active through ui/srv_available_filters.
Returns
NULL, invisibly.
Method get_available_teal_slices()
Get list of filter states available for this object.
Usage
FilteredData$get_available_teal_slices()
Details
All teal_slice objects that have been created since the beginning of the app session
are stored in one teal_slices object. This returns a subset of that teal_slices,
describing filter states that can be set for this object.
Returns
reactive that returns teal_slices.
Method get_call()
Gets a call to filter the dataset according to the filter state.
Usage
FilteredData$get_call(dataname)
Arguments
dataname(
character(1)) name of the dataset
Details
It returns a call to filter the dataset only, assuming the
other (filtered) datasets it depends on are available.
Together with self$datanames() which returns the datasets in the correct
evaluation order, this generates the whole filter code, see the function
FilteredData$get_filter_code.
For the return type, note that rlang::is_expression returns TRUE on the
return type, both for base R expressions and calls (single expression,
capturing a function call).
The filtered dataset has the name given by self$filtered_dataname(dataname)
This can be used for the Show R Code generation.
Returns
A list of calls.
Method get_data()
Gets filtered or unfiltered dataset.
For filtered = FALSE, the original data set with set_data is returned including all attributes.
Usage
FilteredData$get_data(dataname, filtered = TRUE)
Arguments
dataname(
character(1)) name of the dataset.filtered(
logical(1)) whether to return a filtered or unfiltered dataset.
Returns
A data object, a data.frame or a MultiAssayExperiment.
Method get_join_keys()
Get join keys between two datasets.
Usage
FilteredData$get_join_keys()
Returns
join_keys
Method get_filter_overview()
Creates filter overview table to be displayed in the application.
One row is created per dataset, according to the get_filter_overview methods
of the contained FilteredDataset objects.
Usage
FilteredData$get_filter_overview(datanames)
Arguments
datanames(
character) vector of dataset names.
Returns
A data.frame listing the numbers of observations in all datasets.
Method get_keys()
Get keys for the dataset.
Usage
FilteredData$get_keys(dataname)
Arguments
dataname(
character(1)) name of the dataset.
Returns
Character vector of key column names.
Method set_dataset()
Adds a dataset to this FilteredData.
Usage
FilteredData$set_dataset(data, dataname)
Arguments
data(
data.frameorMultiAssayExperiment) data to be filtered.dataname(
character(1)) the name of thedatasetto be added to this object.
Details
set_dataset creates a FilteredDataset object which keeps dataset for the filtering purpose.
If this data has a parent specified in the join_keys object stored in private$join_keys
then created FilteredDataset (child) gets linked with other FilteredDataset (parent).
"Child" dataset return filtered data then dependent on the reactive filtered data of the
"parent". See more in documentation of parent argument in DataframeFilteredDataset constructor.
Returns
self, invisibly.
Method set_join_keys()
Set the join_keys.
Usage
FilteredData$set_join_keys(join_keys)
Arguments
join_keys(
join_keys), seeteal.data::join_keys().
Returns
self, invisibly.
Method get_filter_state()
Gets states of all contained FilterState objects.
Usage
FilteredData$get_filter_state()
Returns
A teal_slices object.
Method format()
Returns a formatted string representing this FilteredData object.
Usage
FilteredData$format(show_all = FALSE, trim_lines = TRUE)
Arguments
show_all(
logical(1)) passed toformat.teal_slice.trim_lines(
logical(1)) passed toformat.teal_slice.
Returns
character(1) the formatted string.
Method print()
Prints this FilteredData object.
Usage
FilteredData$print(...)
Arguments
...additional arguments passed to
format.
Method set_filter_state()
Sets active filter states.
Usage
FilteredData$set_filter_state(state)
Arguments
state(
teal_slices)
Returns
NULL, invisibly.
Method remove_filter_state()
Removes one or more FilterState from a FilteredData object.
Usage
FilteredData$remove_filter_state(state)
Arguments
state(
teal_slices) specifyingFilterStateobjects to remove;teal_slices may contain onlydatanameandvarname, other elements are ignored.
Returns
NULL, invisibly.
Method clear_filter_states()
Remove all FilterStates of a FilteredDataset or all FilterStates of a FilteredData object.
Usage
FilteredData$clear_filter_states(datanames = self$datanames(), force = FALSE)
Arguments
datanames(
character) names of datasets for which to remove all filter states. Defaults to all datasets in thisFilteredDataobject.force(
logical(1)) flag specifying whether to include anchored filter states.
Returns
NULL, invisibly.
Method ui_filter_panel()
top-level shiny module for the filter panel in the teal app.
Contains 1) filter overview panel, 2) filter active panel, and 3) add filters panel.
Usage
FilteredData$ui_filter_panel(id, active_datanames = self$datanames)
Arguments
id(
character(1))shinymodule instance id.active_datanames(
reactive) defining subset ofself$datanames()to be displayed.
Returns
shiny.tag
Method srv_filter_panel()
Server function for filter panel.
Usage
FilteredData$srv_filter_panel(id, active_datanames = self$datanames)
Arguments
id(
character(1))shinymodule instance id.active_datanames(
functionorreactive) returningdatanamesthat should be shown on the filter panel. Must be a subset of thedatanamesin thisFilteredData. If the function returnsNULL(as opposed tocharacter(0)), the filter panel will be hidden.
Returns
NULL.
Method ui_active()
Server module responsible for displaying active filters.
Usage
FilteredData$ui_active(id, active_datanames = self$datanames)
Arguments
id(
character(1))shinymodule instance id.active_datanames(
reactive) defining subset ofself$datanames()to be displayed.
Returns
shiny.tag
Method srv_active()
Server module responsible for displaying active filters.
Usage
FilteredData$srv_active(id, active_datanames = self$datanames)
Arguments
id(
character(1))shinymodule instance id.active_datanames(
reactive) defining subset ofself$datanames()to be displayed.
Returns
NULL.
Method ui_overview()
Creates the UI definition for the module showing counts for each dataset contrasting the filtered to the full unfiltered dataset.
Per dataset, it displays the number of rows/observations in each dataset, the number of unique subjects.
Usage
FilteredData$ui_overview(id)
Arguments
id(
character(1))shinymodule instance id.
Method srv_overview()
Server function to display the number of records in the filtered and unfiltered data.
Usage
FilteredData$srv_overview(id, active_datanames = self$datanames)
Arguments
id(
character(1))shinymodule instance id.active_datanames(
reactive) returningdatanamesthat should be shown on the filter panel, must be a subset of thedatanamesargument provided toui_filter_panel; if the function returnsNULL(as opposed tocharacter(0)), the filter panel will be hidden.
Returns
NULL.
Method finalize()
Object and dependencies cleanup.
Destroy inputs and observers stored in
private$session_bindingsFinalize
FilteredDatastored inprivate$filtered_datasets
Usage
FilteredData$finalize()
Returns
NULL, invisibly.
Method clone()
The objects of this class are cloneable with this method.
Usage
FilteredData$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Examples
# use non-exported function from teal.slice
FilteredData <- getFromNamespace("FilteredData", "teal.slice")
library(shiny)
datasets <- FilteredData$new(list(iris = iris, mtcars = mtcars))
# get datanames
datasets$datanames()
datasets$set_filter_state(
teal_slices(teal_slice(dataname = "iris", varname = "Species", selected = "virginica"))
)
datasets$set_filter_state(
teal_slices(teal_slice(dataname = "mtcars", varname = "mpg", selected = c(15, 20)))
)
isolate(datasets$get_filter_state())
isolate(datasets$get_call("iris"))
isolate(datasets$get_call("mtcars"))
### set_filter_state
library(shiny)
data(miniACC, package = "MultiAssayExperiment")
datasets <- FilteredData$new(list(iris = iris, mae = miniACC))
fs <- teal_slices(
teal_slice(
dataname = "iris", varname = "Sepal.Length", selected = c(5.1, 6.4),
keep_na = TRUE, keep_inf = FALSE
),
teal_slice(
dataname = "iris", varname = "Species", selected = c("setosa", "versicolor"),
keep_na = FALSE
),
teal_slice(
dataname = "mae", varname = "years_to_birth", selected = c(30, 50),
keep_na = TRUE, keep_inf = FALSE
),
teal_slice(dataname = "mae", varname = "vital_status", selected = "1", keep_na = FALSE),
teal_slice(dataname = "mae", varname = "gender", selected = "female", keep_na = TRUE),
teal_slice(
dataname = "mae", varname = "ARRAY_TYPE",
selected = "", keep_na = TRUE, experiment = "RPPAArray", arg = "subset"
)
)
datasets$set_filter_state(state = fs)
isolate(datasets$get_filter_state())
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