Standardise function titles similar to what we have in tmc

R/tm_a_pca.R

@@ -1,4 +1,4 @@
-#' Principal component analysis module
+#' `teal` module: Principal component analysis
 #'
 #' Module conducts principal component analysis (PCA) on a given dataset and offers different
 #' ways of visualizing the outcomes, including elbow plot, circle plot, biplot, and eigenvector plot.
@@ -9,12 +9,6 @@
 #' @inheritParams shared_params
 #' @param dat (`data_extract_spec` or `list` of multiple `data_extract_spec`)
 #'   specifying columns used to compute PCA.
-#' @param alpha (`numeric`, optional) Specifies point opacity.
-#' - If vector of `length == 1` then the plot points will have a fixed opacity.
-#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
-#' @param size (`numeric`, optional) Specifies point size.
-#' - If vector of `length == 1` then the plot point sizes will have a fixed size
-#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
 #' @param font_size (`numeric`, optional) Specifies font size.
 #' It controls the font size for plot titles, axis labels, and legends.
 #' - If vector of `length == 1` then the font sizes will have a fixed size.

R/tm_a_regression.R

@@ -1,4 +1,4 @@
-#' Scatterplot and regression model
+#' `teal` module: Scatterplot and regression analysis
 #'
 #' Module for visualizing regression analysis, including scatterplots and
 #' various regression diagnostics plots.
@@ -14,14 +14,6 @@
 #' Regressor variables from an incoming dataset with filtering and selecting.
 #' @param response (`data_extract_spec` or `list` of multiple `data_extract_spec`)
 #' Response variables from an incoming dataset with filtering and selecting.
-#' @param alpha (`integer(1)` or `integer(3)`, optional) Specifies point opacity.
-#' - When the length of `alpha` is one: the plot points will have a fixed opacity.
-#' - When the length of `alpha` is three: the plot points opacity are dynamically adjusted based on
-#' vector of `value`, `min`, and `max`.
-#' @param size (`integer(1)` or `integer(3)`, optional) Specifies point size.
-#' - When the length of `size` is one: the plot point sizes will have a fixed size.
-#' - When the length of `size` is three: the plot points size are dynamically adjusted based on
-#' vector of `value`, `min`, and `max`.
 #' @param default_outlier_label (`character`, optional) The default column selected to label outliers.
 #' @param default_plot_type (`numeric`, optional) Defaults to Response vs Regressor.
 #' 1. Response vs Regressor

R/tm_data_table.R

@@ -1,4 +1,4 @@
-#' Data table viewer module
+#' `teal` module: Data table viewer
 #'
 #' Module provides a dynamic and interactive way to view `data.frame`s in a `teal` application.
 #' It uses the `DT` package to display data tables in a paginated, searchable, and sortable format,

R/tm_file_viewer.R

@@ -1,4 +1,4 @@
-#' File viewer module
+#' `teal` module: File viewer
 #'
 #' The file viewer module provides a tool to view static files.
 #' Supported formats include text formats, `PDF`, `PNG` `APNG`,

R/tm_front_page.R

@@ -1,4 +1,4 @@
-#' Front page module
+#' `teal` module: Front page
 #'
 #' Creates a simple front page for `teal` applications, displaying
 #' introductory text, tables, additional `html` or `shiny` tags, and footnotes.

R/tm_g_association.R

@@ -1,4 +1,4 @@
-#' Stack plots of variables and show association with reference variable
+#' `teal` module: Stack plots of variables and show association with reference variable
 #'
 #' Module provides functionality for visualizing the distribution of variables and
 #' their association with a reference variable.

R/tm_g_bivariate.R

@@ -1,4 +1,4 @@
-#' Univariate and bivariate visualizations module
+#' `teal` module: Univariate and bivariate visualizations
 #'
 #' Module enables the creation of univariate and bivariate plots,
 #' facilitating the exploration of data distributions and relationships between two variables.

R/tm_g_distribution.R

@@ -1,4 +1,4 @@
-#' Distribution analysis module
+#' `teal` module: Distribution analysis
 #'
 #' Module is designed to explore the distribution of a single variable within a given dataset.
 #' It offers several tools, such as histograms, Q-Q plots, and various statistical tests to

R/tm_g_response.R

@@ -1,4 +1,4 @@
-#' Response plot module
+#' `teal` module: Response plot
 #'
 #' Generates a response plot for a given `response` and `x` variables.
 #' This module allows users customize and add annotations to the plot depending

R/tm_g_scatterplot.R

@@ -1,4 +1,4 @@
-#' Scatterplot module
+#' `teal` module: Scatterplot
 #'
 #' Generates a customizable scatterplot using `ggplot2`.
 #' This module allows users to select variables for the x and y axes,
@@ -22,12 +22,6 @@
 #' Specifies the variable(s) for faceting rows.
 #' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`, optional)
 #' Specifies the variable(s) for faceting columns.
-#' @param alpha (`numeric`, optional) Specifies point opacity.
-#' - If vector of `length == 1` then the plot points will have a fixed opacity.
-#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
-#' @param size (`numeric`, optional) Specifies point size.
-#' - If vector of `length == 1` then the plot point sizes will have a fixed size
-#' - while vector of `value`, `min`, and `max` allows dynamic adjustment.
 #' @param shape (`character`, optional) A character vector with the names of the
 #' shape, e.g. `c("triangle", "square", "circle")`. It defaults to `shape_names`. This is a complete list from
 #' `vignette("ggplot2-specs", package="ggplot2")`.

R/tm_g_scatterplotmatrix.R

@@ -1,4 +1,4 @@
-#' Scatterplot matrix module
+#' `teal` module: Scatterplot matrix
 #'
 #' Generates a scatterplot matrix from selected `variables` from datasets.
 #' Each plot within the matrix represents the relationship between two variables,

R/tm_missing_data.R

@@ -1,4 +1,4 @@
-#' Missing data analysis module
+#' `teal` module: Missing data analysis
 #'
 #' Module analyzes missing data in `data.frame`s to help users explore missing observations and
 #' gain insights into the completeness of their data.

R/tm_outliers.R

@@ -1,4 +1,4 @@
-#' Outliers module
+#' `teal` module: Outliers analysis
 #'
 #' Module to analyze and identify outliers using different methods
 #' such as IQR, Z-score, and Percentiles, and offers visualizations including

R/tm_t_crosstable.R

@@ -1,4 +1,4 @@
-#' Cross-table module
+#' `teal` module: Cross-table
 #'
 #' Generates a simple cross-table of two variables from a dataset with custom
 #' options for showing percentages and sub-totals.

R/tm_variable_browser.R

@@ -1,4 +1,4 @@
-#' Variable browser `teal` module
+#' `teal` module: Variable browser
 #'
 #' Module provides provides a detailed summary and visualization of variable distributions
 #' for `data.frame` objects, with interactive features to customize analysis.

R/utils.R

@@ -26,6 +26,15 @@
 #' @param post_output (`shiny.tag`, optional) Text or UI element to be displayed after the module's output,
 #' adding context or further instructions. Elements like `shiny::helpText()` are useful.
 #'
+#' @param alpha (`integer(1)` or `integer(3)`, optional) Specifies point opacity.
+#' - When the length of `alpha` is one: the plot points will have a fixed opacity.
+#' - When the length of `alpha` is three: the plot points opacity are dynamically adjusted based on
+#' vector of `value`, `min`, and `max`.
+#' @param size (`integer(1)` or `integer(3)`, optional) Specifies point size.
+#' - When the length of `size` is one: the plot point sizes will have a fixed size.
+#' - When the length of `size` is three: the plot points size are dynamically adjusted based on
+#' vector of `value`, `min`, and `max`.
+#'
 #' @return Object of class `teal_module` to be used in `teal` applications.
 #'
 #' @name shared_params