teal_slice {teal.slice}

Specify single filter

Description

Create a teal_slice object that holds complete information on filtering one variable. Check out teal_slice-utilities functions for working with teal_slice object.

Usage

teal_slice(
  dataname,
  varname,
  id,
  expr,
  choices = NULL,
  selected = NULL,
  keep_na = NULL,
  keep_inf = NULL,
  fixed = FALSE,
  anchored = FALSE,
  multiple = TRUE,
  title = NULL,
  ...
)

Arguments

dataname

(character(1)) name of data set

varname

(character(1)) name of variable

id

(character(1)) identifier of the filter. Must be specified when expr is set. When varname is specified then id is set to "{dataname} {varname}" by default.

expr

(character(1)) string providing a logical expression. Must be a valid R expression which can be evaluated in the context of the data set. For a data.frame var == "x" is sufficient, but MultiAssayExperiment::subsetByColData requires dataname prefix, e.g. data$var == "x".

choices

(vector) optional, specifies allowed choices; When specified it should be a subset of values in variable denoted by varname; Type and size depends on variable type. Factors are coerced to character.

selected

(vector) optional, specifies selected values from choices; Type and size depends on variable type. Factors are coerced to character.

keep_na

(logical(1)) optional flag specifying whether to keep missing values

keep_inf

(logical(1)) optional flag specifying whether to keep infinite values

fixed

(logical(1)) flag specifying whether to fix this filter state (forbid setting state)

anchored

(logical(1)) flag specifying whether to lock this filter state (forbid removing and inactivating)

multiple

(logical(1)) optional flag specifying whether more than one value can be selected; only applicable to ChoicesFilterState and LogicalFilterState

title

(character(1)) optional title of the filter. Ignored when varname is set.

...

additional arguments which can be handled by extensions of teal.slice classes.

Details

teal_slice object fully describes filter state and can be used to create, modify, and delete a filter state. A teal_slice contains a number of common fields (all named arguments of teal_slice), some of which are mandatory, but only dataname and either varname or expr must be specified, while the others have default values.

Setting any of the other values to NULL means that those properties will not be modified (when setting an existing state) or that they will be determined by data (when creating new a new one). Entire object is FilterState class member and can be accessed with FilterState$get_state().

A teal_slice can come in two flavors:

1. teal_slice_var - this describes a typical interactive filter that refers to a single variable, managed by the FilterState class. This class is created when varname is specified. The object retains all fields specified in the call. id can be created by default and need not be specified.

2. teal_slice_expr - this describes a filter state that refers to an expression, which can potentially include multiple variables, managed by the FilterStateExpr class. This class is created when expr is specified. dataname and anchored are retained, fixed is set to TRUE, id becomes mandatory, title remains optional, while other arguments are disregarded.

A teal_slice can be passed FilterState/FilterStateExpr constructors to instantiate an object. It can also be passed to FilterState$set_state to modify the state. However, once a FilterState is created, only the mutable features can be set with a teal_slice: selected, keep_na and keep_inf.

Special consideration is given to two fields: fixed and anchored. These are always immutable logical flags that default to FALSE. In a FilterState instantiated with fixed = TRUE the features selected, keep_na, keep_inf cannot be changed. Note that a FilterStateExpr is always considered to have fixed = TRUE. A FilterState instantiated with anchored = TRUE cannot be removed.

Value

A teal.slice object. Depending on whether varname or expr was specified, the resulting teal_slice also receives class teal_slice_var or teal_slice_expr, respectively.

Filters in SumarizedExperiment and MultiAssayExperiment objects

To establish a filter on a column in a data.frame, dataname and varname are sufficient. MultiAssayExperiment objects can be filtered either on their colData slot (which contains subject information) or on their experiments, which are stored in the experimentList slot. For filters referring to colData no extra arguments are needed. If a filter state is created for an experiment, that experiment name must be specified in the experiment argument. Furthermore, to specify filter for an SummarizedExperiment one must also set arg ("subset" or "select", arguments in the subset() function for SummarizedExperiment) in order to determine whether the filter refers to the SE's rowData or colData.

Note

Date time objects of POSIX*t classes are printed as strings after converting to UTC timezone.

See Also

teal_slices, is.teal_slice, as.teal_slice, as.list.teal_slice, print.teal_slice, format.teal_slice

Examples

x1 <- teal_slice(
  dataname = "data",
  id = "Female adults",
  expr = "SEX == 'F' & AGE >= 18",
  title = "Female adults"
)
x2 <- teal_slice(
  dataname = "data",
  varname = "var",
  choices = c("F", "M", "U"),
  selected = "F",
  keep_na = TRUE,
  keep_inf = TRUE,
  fixed = FALSE,
  anchored = FALSE,
  multiple = TRUE,
  id = "Gender",
  extra_arg = "extra"
)

is.teal_slice(x1)
as.list(x1)
as.teal_slice(list(dataname = "a", varname = "var"))
format(x1)
format(x1, show_all = TRUE, trim_lines = FALSE)
print(x1)
print(x1, show_all = TRUE, trim_lines = FALSE)