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pre-release tm_g_bivariate document update #660

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Feb 26, 2024
Merged

pre-release tm_g_bivariate document update #660

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d15f77d
updating tm_g_bivariate documentation
kartikeyakirar Feb 21, 2024
d946251
merge back from pre-release
kartikeyakirar Feb 23, 2024
5b7323a
remove return statment
kartikeyakirar Feb 23, 2024
a2ed571
adding tags
kartikeyakirar Feb 23, 2024
a183c9c
removing whitelines
kartikeyakirar Feb 23, 2024
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155 changes: 69 additions & 86 deletions R/tm_g_bivariate.R
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Original file line number Diff line number Diff line change
@@ -1,50 +1,55 @@
#' Univariate and bivariate visualizations
#' @md
#' Univariate and bivariate visualizations module
#'
#' Module enables the creation of univariate and bivariate plots,
#' facilitating the exploration of data distributions and relationships between two variables.
#'
#' This is a general module to visualize 1 & 2 dimensional data.
#'
#' @note
#' For more examples, please see the vignette "Using bivariate plot" via
#' `vignette("using-bivariate-plot", package = "teal.modules.general")`.
#'
#' @inheritParams teal::module
#' @inheritParams shared_params
#' @param x (`data_extract_spec` or `list` of multiple `data_extract_spec`)
#' Variable names selected to plot along the x-axis by default. Variable can be numeric, factor or character.
#' No empty selections are allowed!
#' Variable names selected to plot along the x-axis by default.
#' Can be numeric, factor or character.
#' No empty selections are allowed.
#' @param y (`data_extract_spec` or `list` of multiple `data_extract_spec`)
#' Variable names selected to plot along the y-axis by default. Variable can be numeric, factor or character.
#' @param use_density optional, (`logical`) value for whether density (`TRUE`) is plotted or
#' frequency (`FALSE`). Defaults to frequency (`FALSE`).
#' @param row_facet optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
#' Variables for row facetting.
#' @param col_facet optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
#' Variables for col facetting.
#' @param facet optional, (`logical`) to specify whether the facet encodings `ui` elements are toggled
#' on and shown to the user by default. Defaults to `TRUE` if either `row_facet` or `column_facet`
#' are supplied.
#' Variable names selected to plot along the y-axis by default.
#' Can be numeric, factor or character.
#' @param use_density (`logical`, optional) Indicates whether to plot density (`TRUE`) or frequency (`FALSE`).
#' Defaults to frequency (`FALSE`).
#' @param row_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
#' Variables for row facetting.
#' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
#' Variables for column facetting.
#' @param facet (`logical`, optional) to specify whether the facet encodings `ui` elements are toggled
#' on and shown to the user by default. Defaults to `TRUE` if either `row_facet` or `column_facet`
#' are supplied.
#' @param color_settings (`logical`) Whether coloring, filling and size should be applied
#' and `UI` tool offered to the user.
#' @param color optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
#' Variables selected for the outline color inside the coloring settings.
#' It will be applied when `color_settings` is set to `TRUE`.
#' @param fill optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
#' Variables selected for the fill color inside the coloring settings.
#' It will be applied when `color_settings` is set to `TRUE`.
#' @param size optional, (`data_extract_spec` or `list` of multiple `data_extract_spec`)
#' Variables selected for the size of `geom_point` plots inside the coloring settings.
#' It will be applied when `color_settings` is set to `TRUE`.
#' @param free_x_scales optional, (`logical`) Whether X scaling shall be changeable.
#' Does not allow scaling to be changed by default (`FALSE`).
#' @param free_y_scales optional, (`logical`) Whether Y scaling shall be changeable.
#' Does not allow scaling to be changed by default (`FALSE`).
#' @param swap_axes optional, (`logical`) Whether to swap X and Y axes. Defaults to `FALSE`.
#' @param color (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
#' Variables selected for the outline color inside the coloring settings.
#' It will be applied when `color_settings` is set to `TRUE`.
#' @param fill (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
#' Variables selected for the fill color inside the coloring settings.
#' It will be applied when `color_settings` is set to `TRUE`.
#' @param size (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
#' Variables selected for the size of `geom_point` plots inside the coloring settings.
#' It will be applied when `color_settings` is set to `TRUE`.
#' @param free_x_scales (`logical`, optional) Whether X scaling shall be changeable.
#' Does not allow scaling to be changed by default (`FALSE`).
#' @param free_y_scales (`logical`, optional) Whether Y scaling shall be changeable.
#' Does not allow scaling to be changed by default (`FALSE`).
#' @param swap_axes (`logical`, optional) Whether to swap X and Y axes. Defaults to `FALSE`.
#'
#' @details
#' This is a general module to visualize 1 & 2 dimensional data.
#'
#' @note
#' For more examples, please see the vignette "Using bivariate plot" via
#' `vignette("using-bivariate-plot", package = "teal.modules.general")`.
#'
#' @export
#' @return Object of class `teal_module` to be used in `teal` applications.
#'
#' @examples
#' # Bivariate plot of selected variable (AGE) against selected (SEX)
#' library(teal.widgets)
#'
#' data <- teal_data()
#' data <- within(data, {
#' library(nestcolor)
Expand All @@ -54,48 +59,48 @@
#' datanames(data) <- datanames
#' join_keys(data) <- default_cdisc_join_keys[datanames]
#'
#' app <- teal::init(
#' app <- init(
#' data = data,
#' modules = teal::modules(
#' teal.modules.general::tm_g_bivariate(
#' x = teal.transform::data_extract_spec(
#' modules = modules(
#' tm_g_bivariate(
#' x = data_extract_spec(
#' dataname = "ADSL",
#' select = teal.transform::select_spec(
#' select = select_spec(
#' label = "Select variable:",
#' choices = teal.transform::variable_choices(data[["ADSL"]]),
#' choices = variable_choices(data[["ADSL"]]),
#' selected = "AGE",
#' fixed = FALSE
#' )
#' ),
#' y = teal.transform::data_extract_spec(
#' y = data_extract_spec(
#' dataname = "ADSL",
#' select = teal.transform::select_spec(
#' select = select_spec(
#' label = "Select variable:",
#' choices = teal.transform::variable_choices(data[["ADSL"]]),
#' choices = variable_choices(data[["ADSL"]]),
#' selected = "SEX",
#' multiple = FALSE,
#' fixed = FALSE
#' )
#' ),
#' row_facet = teal.transform::data_extract_spec(
#' row_facet = data_extract_spec(
#' dataname = "ADSL",
#' select = teal.transform::select_spec(
#' select = select_spec(
#' label = "Select variable:",
#' choices = teal.transform::variable_choices(data[["ADSL"]]),
#' choices = variable_choices(data[["ADSL"]]),
#' selected = "ARM",
#' fixed = FALSE
#' )
#' ),
#' col_facet = teal.transform::data_extract_spec(
#' col_facet = data_extract_spec(
#' dataname = "ADSL",
#' select = teal.transform::select_spec(
#' select = select_spec(
#' label = "Select variable:",
#' choices = teal.transform::variable_choices(data[["ADSL"]]),
#' choices = variable_choices(data[["ADSL"]]),
#' selected = "COUNTRY",
#' fixed = FALSE
#' )
#' ),
#' ggplot2_args = teal.widgets::ggplot2_args(
#' ggplot2_args = ggplot2_args(
#' labs = list(subtitle = "Plot generated by Bivariate Module")
#' )
#' )
Expand All @@ -104,6 +109,10 @@
#' if (interactive()) {
#' shinyApp(app$ui, app$server)
#' }
#'
#'
#' @export
#'
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tm_g_bivariate <- function(label = "Bivariate Plots",
x,
y,
Expand Down Expand Up @@ -225,6 +234,7 @@ tm_g_bivariate <- function(label = "Bivariate Plots",
)
}

# UI function for the bivariate module.
ui_g_bivariate <- function(id, ...) {
args <- list(...)
is_single_dataset_value <- teal.transform::is_single_dataset(
Expand Down Expand Up @@ -365,7 +375,7 @@ ui_g_bivariate <- function(id, ...) {
)
}


# Server function for the bivariate module.
srv_g_bivariate <- function(id,
data,
reporter,
Expand Down Expand Up @@ -646,15 +656,10 @@ srv_g_bivariate <- function(id,
})
}


#' Get Substituted ggplot call
#'
#' @noRd
#'
#' @examples
#'
#' bivariate_plot_call("ANL", "BAGE", "RACE", "numeric", "factor")
#' bivariate_plot_call("ANL", "BAGE", character(0), "numeric", "NULL")
#' @keywords internal
bivariate_plot_call <- function(data_name,
x = character(0),
y = character(0),
Expand Down Expand Up @@ -711,28 +716,10 @@ substitute_q <- function(x, env) {


#' Create ggplot part of plot call
#'
#' Due to the type of the x and y variable the plot type is chosen
#'
#' @noRd
#'
#' @examples
#' bivariate_ggplot_call("numeric", "NULL")
#' bivariate_ggplot_call("numeric", "NULL", freq = FALSE)
#'
#' bivariate_ggplot_call("NULL", "numeric")
#' bivariate_ggplot_call("NULL", "numeric", freq = FALSE)
#'
#' bivariate_ggplot_call("NULL", "factor")
#' bivariate_ggplot_call("NULL", "factor", freq = FALSE)
#'
#' bivariate_ggplot_call("factor", "NULL")
#' bivariate_ggplot_call("factor", "NULL", freq = FALSE)
#'
#' bivariate_ggplot_call("numeric", "numeric")
#' bivariate_ggplot_call("numeric", "factor")
#' bivariate_ggplot_call("factor", "numeric")
#' bivariate_ggplot_call("factor", "factor")
#' @keywords internal
bivariate_ggplot_call <- function(x_class = c("NULL", "numeric", "integer", "factor", "character", "logical"),
y_class = c("NULL", "numeric", "integer", "factor", "character", "logical"),
freq = TRUE,
Expand Down Expand Up @@ -913,19 +900,14 @@ bivariate_ggplot_call <- function(x_class = c("NULL", "numeric", "integer", "fac
plot_call <- reduce_plot_call(plot_call, quote(coord_flip()))
}

return(plot_call)
plot_call
}


#' Create facet call
#'
#' @noRd
#'
#' @examples
#'
#' facet_ggplot_call(LETTERS[1:3])
#' facet_ggplot_call(NULL, LETTERS[23:26])
#' facet_ggplot_call(LETTERS[1:3], LETTERS[23:26])
#' @keywords internal
facet_ggplot_call <- function(row_facet = character(0),
col_facet = character(0),
free_x_scales = FALSE,
Expand Down Expand Up @@ -955,7 +937,8 @@ facet_ggplot_call <- function(row_facet = character(0),
call("facet_grid", rows = call_fun_dots("vars", row_facet), scales = scales)
}
}

#' @noRd
#' @keywords internal
coloring_ggplot_call <- function(colour,
fill,
size,
Expand Down
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