From 09186e524194eb5b6bb6a696261a93dc449f4a9f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?zxBIB=20Lech=C3=B3n=2CMiguel=20=28MED=20BDS=29=20EXTERNAL?= Date: Fri, 31 Jan 2025 11:11:29 +0100 Subject: [PATCH] Remove rendered man/*.Rd documentation from sources. --- .gitignore | 1 + man/HM2SVG_plot.Rd | 40 ------- man/HM2SVG_server.Rd | 58 ---------- man/apply_cat_palette_legend.Rd | 20 ---- man/bar_D3.Rd | 112 ------------------ man/boxplot_chart.Rd | 55 --------- man/boxplot_composed.Rd | 53 --------- man/bp_count_table.Rd | 25 ---- man/bp_get_closest_gen_click.Rd | 58 ---------- man/bp_listings_table.Rd | 30 ----- man/bp_significance_table.Rd | 28 ----- man/bp_subset_data.Rd | 82 ------------- man/bp_summary_table.Rd | 24 ---- man/cash-.pack_of_constants.Rd | 20 ---- man/ch_subset_data.Rd | 42 ------- man/check_selected_choices.Rd | 19 --- man/composed.Rd | 55 --------- man/compute_metric.Rd | 50 -------- man/compute_roc.Rd | 108 ------------------ man/default_lineplot_functions.Rd | 29 ----- man/dplyr_.data.Rd | 9 -- man/equal_and_mask_from_vec.Rd | 26 ----- man/fp_stats.Rd | 36 ------ man/fp_subset_data.Rd | 49 -------- man/get_dens_data.Rd | 49 -------- man/get_dens_spec.Rd | 53 --------- man/get_explore_roc_data.Rd | 50 -------- man/get_explore_roc_spec.Rd | 61 ---------- man/get_gt_summary_table.Rd | 54 --------- man/get_histo_data.Rd | 50 -------- man/get_histo_spec.Rd | 54 --------- man/get_lbl.Rd | 20 ---- man/get_lbl_robust.Rd | 20 ---- man/get_lbls.Rd | 27 ----- man/get_metric_data.Rd | 75 ------------ man/get_metric_spec.Rd | 68 ----------- man/get_quantile_data.Rd | 46 -------- man/get_raincloud_spec.Rd | 82 ------------- man/get_roc_data.Rd | 115 ------------------- man/get_roc_spec.Rd | 123 -------------------- man/get_summary_data.Rd | 100 ---------------- man/heatmap_D3.Rd | 111 ------------------ man/mock_app_boxplot.Rd | 24 ---- man/mock_app_boxplot_mm.Rd | 15 --- man/mock_app_corr_hm.Rd | 24 ---- man/mock_app_correlation_hm_mm.Rd | 12 -- man/mock_app_forest.Rd | 24 ---- man/mock_app_lineplot.Rd | 27 ----- man/mock_app_scatterplot.Rd | 24 ---- man/mock_app_scatterplotmatrix.Rd | 24 ---- man/mock_roc.Rd | 30 ----- man/mock_wfphm.Rd | 87 -------------- man/mod_boxplot.Rd | 145 ----------------------- man/mod_corr_hm.Rd | 101 ---------------- man/mod_forest.Rd | 154 ------------------------- man/mod_lineplot.Rd | 179 ----------------------------- man/mod_roc.Rd | 123 -------------------- man/mod_scatterplot.Rd | 138 ---------------------- man/mod_scatterplotmatrix.Rd | 115 ------------------- man/name_label_formatter.Rd | 19 --- man/outlier_container.Rd | 43 ------- man/outlier_selector.Rd | 47 -------- man/pack_of_constants.Rd | 46 -------- man/pal_div_palette.Rd | 25 ---- man/pal_get_cat_palette.Rd | 22 ---- man/pal_get_cont_palette.Rd | 30 ----- man/pal_get_scale_type_lim.Rd | 35 ------ man/pal_seq_palette.Rd | 25 ---- man/pal_zero_palette.Rd | 22 ---- man/parameter_UI.Rd | 15 --- man/parse_ci.Rd | 17 --- man/possibly_set_lbls.Rd | 21 ---- man/rename_with_list.Rd | 26 ----- man/resolve_or_return.Rd | 21 ---- man/rlang_assign.Rd | 11 -- man/roc_subset_data.Rd | 156 ------------------------- man/rpl_nulls_name.Rd | 21 ---- man/set_lbl.Rd | 22 ---- man/set_lbls.Rd | 21 ---- man/sp_subset_data.Rd | 76 ------------ man/spm_subset_data.Rd | 83 -------------- man/str_to_hash.Rd | 15 --- man/strip_data_pronoun.Rd | 19 --- man/subset_adsl.Rd | 44 ------- man/subset_bds_param.Rd | 75 ------------ man/swap_val_names.Rd | 18 --- man/test_disjunct_cols.Rd | 24 ---- man/test_one_cat_per_par.Rd | 43 ------- man/test_one_row_per_sbj.Rd | 32 ------ man/transformation.Rd | 67 ----------- man/transformation_utils.Rd | 36 ------ man/wfphm.Rd | 144 ----------------------- man/wfphm_hmcat.Rd | 108 ------------------ man/wfphm_hmcat_subset.Rd | 23 ---- man/wfphm_hmcont.Rd | 96 ---------------- man/wfphm_hmcont_subset.Rd | 21 ---- man/wfphm_hmpar.Rd | 172 ---------------------------- man/wfphm_hmpar_subset.Rd | 38 ------ man/wfphm_wf.Rd | 184 ------------------------------ man/wfphm_wf_apply_outliers.Rd | 20 ---- man/wfphm_wf_rename_cols.Rd | 18 --- man/wfphm_wf_subset_data_cont.Rd | 21 ---- man/wfphm_wf_subset_data_par.Rd | 77 ------------- 103 files changed, 1 insertion(+), 5531 deletions(-) delete mode 100644 man/HM2SVG_plot.Rd delete mode 100644 man/HM2SVG_server.Rd delete mode 100644 man/apply_cat_palette_legend.Rd delete mode 100644 man/bar_D3.Rd delete mode 100644 man/boxplot_chart.Rd delete mode 100644 man/boxplot_composed.Rd delete mode 100644 man/bp_count_table.Rd delete mode 100644 man/bp_get_closest_gen_click.Rd delete mode 100644 man/bp_listings_table.Rd delete mode 100644 man/bp_significance_table.Rd delete mode 100644 man/bp_subset_data.Rd delete mode 100644 man/bp_summary_table.Rd delete mode 100644 man/cash-.pack_of_constants.Rd delete mode 100644 man/ch_subset_data.Rd delete mode 100644 man/check_selected_choices.Rd delete mode 100644 man/composed.Rd delete mode 100644 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Please edit documentation in R/imod_heatmap2d_svg.R -\name{HM2SVG_plot} -\alias{HM2SVG_plot} -\title{svg heatmap plot} -\usage{ -HM2SVG_plot(data, x_desc, y_desc, z_desc, pal_fun, palette, ns) -} -\arguments{ -\item{data}{data to plot. It expects the following format: -- columns names are \code{x}, \code{y}, \code{z} and, optionally, \code{label} -- both \code{x} and \code{y} columns are factors -- There is one entry for each combination of "x" and "y" present in the dataset. -In other words, the values for each heatmap rectangle are defined explicitly, even if they are NA -- Axis labels and legend title are stored as the attribute "label" of the "x", "y" and "z" columns -- The order of records in the data frame dictates the ordering of the x/y axes in the final plot} - -\item{x_desc, y_desc, z_desc}{Indicate the absence/presence and location of the axis descriptors -(the descriptor for the x and y axes are the plot ticks; for the z axis it's the legend) -- x_desc can take the following values: "N" (north), "S" (south), NULL (absent) -- y_desc can take the following values: "W" (west), "E" (east), NULL (absent) -- z_desc can take the following values: "N", "E", "S", "W", NULL} - -\item{pal_fun}{Function that maps values on column \code{z} of \code{data} to a color in #rrggbb or #rrggbbaa format} - -\item{palette}{Vector that maps values to "z" colors. The names of the vector are hexadecimal colors encoded as -#rrggbb or #rrggbbaa (red, green, blue, alpha) and the values are the "z" values that should be -mapped to that color. -If "z" is categorical, the palette should be complete (i.e. it should offer one color per value). -If "z" is continuous, the palette should contain at least two values covering the min-max range -of possible values. If it contains more, the color of each grid rectangle will be linearly -interpolated according to where its value falls between the two surrounding provided colors.} - -\item{ns}{namespace to apply to the click events} -} -\description{ -Plot the contents of a dataframe as a heatmap, with optional legends, palette and alignment margins. None of -the parameters are reactive -} -\keyword{internal} diff --git a/man/HM2SVG_server.Rd b/man/HM2SVG_server.Rd deleted file mode 100644 index ad16fea..0000000 --- a/man/HM2SVG_server.Rd +++ /dev/null @@ -1,58 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/imod_heatmap2d_svg.R -\name{HM2SVG_server} -\alias{HM2SVG_server} -\title{Server side of ggplot-only heatmap} -\usage{ -HM2SVG_server( - id, - data, - x_desc = "S", - y_desc = "W", - z_desc = "E", - palette = NULL, - margins = list(top = 0, bottom = 0, left = 0, right = 0), - debug_gtable = FALSE -) -} -\arguments{ -\item{id}{shiny ID} - -\item{data}{data to plot. It expects the following format: -- columns names are \code{x}, \code{y}, \code{z} and, optionally, \code{label} -- both \code{x} and \code{y} columns are factors -- There is one entry for each combination of "x" and "y" present in the dataset. -In other words, the values for each heatmap rectangle are defined explicitly, even if they are NA -- Axis labels and legend title are stored as the attribute "label" of the "x", "y" and "z" columns -- The order of records in the data frame dictates the ordering of the x/y axes in the final plot} - -\item{x_desc, y_desc, z_desc}{Indicate the absence/presence and location of the axis descriptors -(the descriptor for the x and y axes are the plot ticks; for the z axis it's the legend) -- x_desc can take the following values: "N" (north), "S" (south), NULL (absent) -- y_desc can take the following values: "W" (west), "E" (east), NULL (absent) -- z_desc can take the following values: "N", "E", "S", "W", NULL} - -\item{palette}{Vector that maps values to "z" colors. The names of the vector are hexadecimal colors encoded as -#rrggbb or #rrggbbaa (red, green, blue, alpha) and the values are the "z" values that should be -mapped to that color. -If "z" is categorical, the palette should be complete (i.e. it should offer one color per value). -If "z" is continuous, the palette should contain at least two values covering the min-max range -of possible values. If it contains more, the color of each grid rectangle will be linearly -interpolated according to where its value falls between the two surrounding provided colors.} - -\item{margins}{Offset in pixels from the edges of the drawable area to the outer perimeter of the heatmap -(excluding legends and axis descriptions). It's a non-reactive list of possibly reactive "top", -"bottom", "left" and "right" numerical values.} - -\item{debug_gtable}{Activate debug mode} -} -\value{ -List of margins (Margin in pixels this plot would have if drawn in isolation encoded as -a reactiveValues object with -elements "top", "bottom", "left" and "right") and click (reactive that returns user click info) -} -\description{ -Plot the contents of a dataframe as a heatmap, with optional legends, palette and alignment margins. All -parameters can be reactive -} -\keyword{internal} diff --git a/man/apply_cat_palette_legend.Rd b/man/apply_cat_palette_legend.Rd deleted file mode 100644 index bbcf8fd..0000000 --- a/man/apply_cat_palette_legend.Rd +++ /dev/null @@ -1,20 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-palettes.R -\name{apply_cat_palette_legend} -\alias{apply_cat_palette_legend} -\title{Create an svg simple legend for a categorical palette} -\usage{ -apply_cat_palette_legend(palette, data) -} -\arguments{ -\item{palette}{} - -\item{data}{} -} -\description{ -Colors can be specified as palettes or as colors, therefore we need to cover both. -} -\details{ -TODO: Consider not passing palettes and only passing colors inside the data -} -\keyword{internal} diff --git a/man/bar_D3.Rd b/man/bar_D3.Rd deleted file mode 100644 index f943158..0000000 --- a/man/bar_D3.Rd +++ /dev/null @@ -1,112 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/imod_bar_plot_d3.R -\name{bar_D3} -\alias{bar_D3} -\alias{bar_d3_UI} -\alias{bar_d3_server} -\title{D3 bar plot} -\usage{ -bar_d3_UI(id, ...) - -bar_d3_server( - id, - data, - x_axis, - y_axis, - z_axis, - margin, - palette, - msg_func, - quiet = TRUE, - ... -) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{...}{Extra parameters that are passed to \link[r2d3:d3-shiny]{r2d3::d3Output}, \link[r2d3:d3-shiny]{r2d3::renderD3} and \link[r2d3:r2d3]{r2d3::r2d3}} - -\item{data}{\verb{[data.frame() | shiny::reactive(data.frame) | shinymeta::metaReactive(data.frame)]} - -dataframe to plot. It expects the following format: -\itemize{ -\item columns names are "x", "y", "z" and, optionally, "label" and "color" -\item There is one entry for each "x" present in the dataset. -In other words, the values for each bar are defined explicitly, even if they are NA -\item Axis labels and legend title are stored as the attribute "label" of the "x", "y" and "z" columns. (Legend title -is not implemented yet) -\item "x" is a factor. The order of the levels dictates the ordering of the x axis. -\item "z" is be a factor -\item "label" values are printed on top of each of the bars -\item If the column is included, "color" values override the color defined according to the palette paremeter. For -the entries that we do not want to override the \code{NA} value must be passed in the color column. -\item It can contain additional columns that are not used for plotting but can be used in the tooltip. -}} - -\item{x_axis, y_axis, z_axis}{\verb{[character(1) | NULL | shiny::reactive(character(1) | NULL) | shinymeta::metaReactive(character(1) | NULL)]} - -Indicate the absence/presence and location of the axis descriptors -(the descriptor for the x and y axes are the plot ticks; for the z axis it's the legend) -\itemize{ -\item x_desc can take the following values: "N" (north), "S" (south), NULL -\item y_desc can take the following values: "W" (west), "E" (east), NULL -\item z_desc can take the following values: "N", "E", "S", "W", NULL -}} - -\item{margin}{\verb{[numeric(4) | shiny::reactive(numeric(4)) | shinymeta::metaReactive(numeric(4))]} - -margin to be used on each of the sides. It must contain four entries named \code{top}, \code{bottom}, \code{left} and \code{right}} - -\item{palette}{\verb{[character(1+) | shiny::reactive(character(1+)) | shinymeta::metaReactive(character(1+))]} - -Vector that maps values to "z" colors. The names of the vector are hexadecimal colors -encoded as #rrggbb or #rrggbbaa (red, green, blue, alpha) and the values are the "z" values that -should be mapped to that color. -\itemize{ -\item the palette is complete (i.e. it should offer one color per value) -\item z values that are \code{NA} or \code{NULL} are colored in grey. -}} - -\item{msg_func}{\verb{[character(1) | shiny::reactive(numeric(1)) | shinymeta::metaReactive(numeric(1))]} - -A JS string that is evaluated in the client. The string must return -a function that receives a single parameter and returns HTML code that is placed in the tooltip. If NULL a -default tooltip is shown.} - -\item{quiet}{\verb{[logical(1) | shiny::reactive(logical(1)) | shinymeta::metaReactive(logical(1))]} - -A boolean indicating if javascript code should include debug output.} -} -\value{ -\subsection{UI}{ - -A bar plot -} - -\subsection{Server}{ - -A list with one entry: -margin: similar to the margin parameter with the minimum margins for the current plot -} - -A reactive list similar to that in the margin param, but indicating which margin is needed to safely plot -the figure. This value is only returned inside a Shiny application. -} -\description{ -Plot the contents of a dataframe as a bar plot, with optional legend, palette and alignment margins. -} -\details{ -This plot always include the value 0 as baseline. - -\emph{msg func} contains a string containing JS code. When evaluated, this string will be evaluated in the client -and must return a function that receives a single parameter. That parameter will contain a JS object with the same -fields as columns in \emph{data} for the point being hovered. -} -\section{Functions}{ -\itemize{ -\item \code{bar_d3_UI()}: UI - -\item \code{bar_d3_server()}: Server - -}} -\keyword{internal} diff --git a/man/boxplot_chart.Rd b/man/boxplot_chart.Rd deleted file mode 100644 index 9d2d962..0000000 --- a/man/boxplot_chart.Rd +++ /dev/null @@ -1,55 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_boxplot.R -\name{boxplot_chart} -\alias{boxplot_chart} -\title{ggplot for a set of faceted boxplots} -\usage{ -boxplot_chart(ds, violin, show_points, log_project_y, title_data = NULL) -} -\arguments{ -\item{ds}{\code{data.frame()} - -A dataframe as output by \link{bp_subset_data}} - -\item{violin}{\code{logical(1)} - -Shows a violin plot instead of a boxplot} - -\item{show_points}{\code{logical(1)} - -Shows individual points in the boxplot chart} - -\item{title_data}{\code{list()} - -Shows a title summarising parameter values.} -} -\value{ -A ggplot chart -} -\description{ -The chart consists of a faceted set of boxplots for biomarker data -} -\details{ -\subsection{Labels:}{ -\itemize{ -\item X axis and color aesthetic are labelled using the label atttribute from \code{main_group} column from \code{ds} -\item Y axis is labelled using the label atttribute from \code{value} column from \code{ds} -} -} - -\subsection{Aesthetics:}{ -\itemize{ -\item \code{parameter} is coded as 1st level row facets -\item \code{main_group} is coded as colors and x axis -\item \code{sub_group} is coded as 1st level column facets -\item \code{page_group} is coded as 2nd level row facets -} -} - -\subsection{Hack:}{ - -\link[shiny:brushedPoints]{shiny::nearPoints} do not manage well charts with no x aesthetic. Therefore when no \code{main_group} is present -in \code{ds} a dummy one is added. -} -} -\keyword{internal} diff --git a/man/boxplot_composed.Rd b/man/boxplot_composed.Rd deleted file mode 100644 index f7db4e4..0000000 --- a/man/boxplot_composed.Rd +++ /dev/null @@ -1,53 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_boxplot.R -\name{boxplot_composed} -\alias{boxplot_composed} -\alias{bp_get_boxplot_output} -\alias{bp_get_listings_output} -\alias{bp_get_single_listings_output} -\alias{bp_get_count_output} -\alias{bp_get_summary_output} -\alias{bp_get_significance_output} -\title{Composes data selection and charting for boxplot} -\usage{ -bp_get_boxplot_output(ds, violin, show_points, log_project_y, title_data) - -bp_get_listings_output(ds, closest_point) - -bp_get_single_listings_output(ds, closest_point, input_id) - -bp_get_count_output(ds) - -bp_get_summary_output(ds) - -bp_get_significance_output(ds) -} -\arguments{ -\item{ds}{\code{data.frame()} - -A dataframe as output by \link{bp_subset_data}} - -\item{violin}{\code{logical(1)} - -Shows a violin plot instead of a boxplot} - -\item{show_points}{\code{logical(1)} - -Shows individual points in the boxplot chart} - -\item{title_data}{\code{list()} - -Shows a title summarising parameter values.} - -\item{input_id}{Shiny ID for the single listing button} -} -\description{ -This is a set of \emph{glue} functions that in most cases follow the pattern -of receiving data, calculating data in an independent/several independent functions -} -\details{ -In some cases aesthetic or simple error validations can occur - -This set of functions is not directly tested as they are indirectly tested in the running app -} -\keyword{internal} diff --git a/man/bp_count_table.Rd b/man/bp_count_table.Rd deleted file mode 100644 index afc7406..0000000 --- a/man/bp_count_table.Rd +++ /dev/null @@ -1,25 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_boxplot.R -\name{bp_count_table} -\alias{bp_count_table} -\title{Counts the number of rows grouped by all variables except \code{subject_id} and \code{value}} -\usage{ -bp_count_table(ds) -} -\arguments{ -\item{ds}{\code{data.frame()} -A data frame to count the rows over.} -} -\value{ -\code{data.frame()} -A data frame with the counts for each group. -} -\description{ -\itemize{ -\item Counts the number of rows grouped by all variables except \code{subject_id} and \code{value}. -\item Throws an error if the Count column is present -\item The function returns a data frame with the counts for each group. -} -} -\keyword{boxplot,} -\keyword{internal} diff --git a/man/bp_get_closest_gen_click.Rd b/man/bp_get_closest_gen_click.Rd deleted file mode 100644 index 6e6e9a2..0000000 --- a/man/bp_get_closest_gen_click.Rd +++ /dev/null @@ -1,58 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_boxplot.R -\name{bp_get_closest_gen_click} -\alias{bp_get_closest_gen_click} -\alias{bp_get_closest_single_click} -\alias{bp_get_closest_double_click} -\title{Clicking helpers} -\usage{ -bp_get_closest_gen_click(ds, click) - -bp_get_closest_single_click(ds, click) - -bp_get_closest_double_click(ds, click) -} -\arguments{ -\item{ds}{\code{data.frame()} - -A data frame containing the data to be filtered.} - -\item{click}{\code{list()} - -A list containing the click information as received from the \code{Shiny} input} -} -\value{ -\code{data.frame} - -A data frame containing the closest row in \code{ds} to the click. -} -\description{ -The boxplot requires several helpers to manage the clicks. The main function is \code{bp_get_closest_gen_click}, and the -other two are specific calls for \code{click} and \code{double_click} events. -\subsection{bp_get_closest_gen_click}{ - -This function takes a dataset and a general click and returns the closest row to the click. It uses the -\link[shiny:brushedPoints]{shiny::nearPoints}. \link[shiny:brushedPoints]{shiny::nearpoints} function is not particularly well-behaved in two cases: -\itemize{ -\item The ggplot does contain several facet levels -Solved by: -Prefiltering \code{ds} manually so it only contains the rows corresponding to the clicked facet -\item The ggplot lacks an \code{x} or \code{y} aesthetic -Solved by: -In this particular case the \code{x} aesthetic correspond to the \code{CNT$MAIN_GROUP} column. If no grouping -is specified during the selection this function assumes that a dummy \code{x} aesthetic was used in \link{boxplot_chart}. -Therefore, this dummy variable is introduced as a column in \code{ds}, and \link[shiny:brushedPoints]{shiny::nearPoints} can be used. -\item The aesthetic has been defined using the \code{.data} pronoun to overcome NSE used in \link[ggplot2:ggplot]{ggplot2::ggplot} -Solved by: -Stripping \code{.data} pronouns before passing them into \link[shiny:brushedPoints]{shiny::nearPoints} -} -} - -\subsection{Specific calls:}{ - -After a click is made and a table shown, when the dataset changes, the app reaches this function in an invalid state -where \code{ds} contains the new dataset and \code{click} contains the click from the previous dataset. This usually provokes -that a 0-row dataset is returned. -} -} -\keyword{internal} diff --git a/man/bp_listings_table.Rd b/man/bp_listings_table.Rd deleted file mode 100644 index 4cdb13d..0000000 --- a/man/bp_listings_table.Rd +++ /dev/null @@ -1,30 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_boxplot.R -\name{bp_listings_table} -\alias{bp_listings_table} -\title{Subsets a data.frame based on the values of a one-rowed data.frame} -\usage{ -bp_listings_table(ds, f_ds) -} -\arguments{ -\item{ds}{\code{data.frame()} - -data.frame to be subset} - -\item{f_ds}{\code{data.frame()} - -one-rowed data.frame} -} -\value{ -\code{data.frame()} - -The subset dataset -} -\description{ -It subsets \code{ds} based on the values of \code{f_ds}. -} -\details{ -No check no names of data.frames is performed (e.g.: names in \code{f_ds} are names in \code{ds}) -} -\keyword{boxplot,} -\keyword{internal} diff --git a/man/bp_significance_table.Rd b/man/bp_significance_table.Rd deleted file mode 100644 index 111e519..0000000 --- a/man/bp_significance_table.Rd +++ /dev/null @@ -1,28 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_boxplot.R -\name{bp_significance_table} -\alias{bp_significance_table} -\title{Create a table of t-test results for pairwise comparisons for \code{main_group} in a data frame} -\usage{ -bp_significance_table(ds) -} -\arguments{ -\item{ds}{\code{data.frame()} -A data frame to be analyzed.} -} -\value{ -\code{data.frame()} -A data frame with the test results. -The returned data frame will have one row for each pairwise comparison and group, and three additional columns -\code{Test}, \code{Comparison}, and \verb{P Value}. -} -\description{ -Creates a table of t-test results for pairwise comparisons for the groups defined by \code{main_group} -groups in a data frame and values in \code{value} - -Each of the pairwise comparison is performed for each of groups defined by the columns that are not -\code{main_group}, \code{value} and \code{subject_id}. - -If no or a single data point for a group is present for a given group \code{NA} values are returned -} -\keyword{internal} diff --git a/man/bp_subset_data.Rd b/man/bp_subset_data.Rd deleted file mode 100644 index afefa63..0000000 --- a/man/bp_subset_data.Rd +++ /dev/null @@ -1,82 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_boxplot.R -\name{bp_subset_data} -\alias{bp_subset_data} -\title{Subset datasets for boxplot} -\usage{ -bp_subset_data( - cat, - cat_col, - par, - par_col, - val_col, - vis, - vis_col, - group_vect, - bm_ds, - group_ds, - subj_col -) -} -\arguments{ -\item{par, cat}{\verb{[character*ish*(n)]} - -Values from \code{par_col} and \code{cat_col} to be subset} - -\item{val_col}{\verb{[character*ish*(1)]} - -Column containing values for the parameters} - -\item{vis}{\verb{[character*ish*(1)]} - -Values from \code{vis_col} to be subset} - -\item{group_vect}{\verb{[named(character(n))]} - -Columns to be subset and renamed.} - -\item{bm_ds, group_ds}{\code{data.frame} - -data frames to be used as inputs in \link{subset_bds_param} and \link{subset_adsl}} - -\item{subj_col, par_col, cat_col, vis_col}{\verb{[character(1)]} - -Column for subject id, category, parameter and visit. All specified columns must be factors} -} -\value{ -\verb{[data.frame()]} - -The \verb{_group} columns depend on the names in \code{group_vect}\tabular{llllll}{ - \code{subject_id} \tab \code{parameter} \tab \code{value} \tab \code{main_group} \tab \code{sub_group} \tab \code{page_group} \cr - xx \tab xx \tab xx \tab xx \tab xx \tab xx \cr -} -} -\description{ -Prepares the basic input for the rest of the boxplot functions. -\itemize{ -\item \code{bm_dataset} is subset according to category, parameter and visit selection -\item \code{group_dataset} is subset according to group_selection -\item both are joined using \code{subject_col} as a common key -\item it uses a left join -} - -It is based on \code{\link[=subset_bds_param]{subset_bds_param()}} and \code{\link[=subset_adsl]{subset_adsl()}} with additional error checking. -} -\details{ -\itemize{ -\item factors from \code{bm_ds} are releveled so all extra levels not present after subsetting are dropped and are sorted -according to \code{par} and \code{cat}. Unless parameters are renamed in \code{\link[=subset_bds_param]{subset_bds_param()}} then no releveling occurs. -\item \code{group_vect} names are a subset of main_group, sub_group and page_group or empty, -otherwise a regular error is produced. -\item \code{label} attributes from \code{group_ds} and \code{bm_ds} are retained when available -} -\subsection{Shiny validation errors:}{ -\itemize{ -\item The fragment from bm contains more than row per subject, category, parameter and visit combination -\item The fragment from group contains more than row per subject -\item If \code{bm_ds} and \code{grp_ds} share column names, apart from \code{subj_col}, after internal renaming has occured -\item If the returned dataset has 0 rows -} -} -} -\keyword{internal} diff --git a/man/bp_summary_table.Rd b/man/bp_summary_table.Rd deleted file mode 100644 index b1fdbab..0000000 --- a/man/bp_summary_table.Rd +++ /dev/null @@ -1,24 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_boxplot.R -\name{bp_summary_table} -\alias{bp_summary_table} -\title{Calculates a set of summary statistics grouped by all variables except \code{subject_id} and \code{value}} -\usage{ -bp_summary_table(ds) -} -\arguments{ -\item{ds}{\code{data.frame()} -A data frame to perform the summary over.} -} -\value{ -\code{data.frame()} -A data frame with the summary statistics. -} -\description{ -\itemize{ -\item Calculates a set of summary statistics grouped by all variables except \code{subject_id} and \code{value}. -\item The summary statistics include \code{N}, \code{Mean}, \code{Median}, \code{SD}, \code{Min}, \code{Q1}, \code{Median}, \code{Q3}, \code{Max} and \verb{NA Values}. -\item \code{NA} values are ignored when calculating stats -} -} -\keyword{internal} diff --git a/man/cash-.pack_of_constants.Rd b/man/cash-.pack_of_constants.Rd deleted file mode 100644 index 0bb5f82..0000000 --- a/man/cash-.pack_of_constants.Rd +++ /dev/null @@ -1,20 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/aaa_preface.R -\name{$.pack_of_constants} -\alias{$.pack_of_constants} -\title{Extract constant from pack} -\usage{ -\method{$}{pack_of_constants}(pack, name) -} -\arguments{ -\item{pack}{pack_of_constants} - -\item{name}{target constant - -This function differs from the base list extraction method in that it avoids partial matching of keys and throws -an error if the looked-for constant is not contained within the pack.} -} -\description{ -Extract constant from pack -} -\keyword{internal} diff --git a/man/ch_subset_data.Rd b/man/ch_subset_data.Rd deleted file mode 100644 index 7c23e86..0000000 --- a/man/ch_subset_data.Rd +++ /dev/null @@ -1,42 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_corr_hm.R -\name{ch_subset_data} -\alias{ch_subset_data} -\title{Subset datasets for correlation heatmap} -\usage{ -ch_subset_data(sel, cat_col, par_col, val_col, vis_col, bm_ds, subj_col) -} -\arguments{ -\item{sel}{a data.frame with three columns CNT$CAT, CMT$PAR, CNT$VIS.} - -\item{val_col}{\verb{[character*ish*(1)]} - -Column containing values for the parameters} - -\item{bm_ds}{\code{data.frame} - -data frames to be used as inputs in \link{subset_bds_param}} - -\item{subj_col, par_col, cat_col, vis_col}{\verb{[character(1)]} - -Column for subject id, category, parameter and visit. All specified columns must be factors} -} -\value{ -\verb{[data.frame()]}\tabular{lllll}{ - \code{category} \tab \code{parameter} \tab \code{subject_id} \tab \code{value} \tab \code{visit} \cr - xx \tab xx \tab xx \tab xx \tab xx \cr -} -} -\description{ -Prepares the main data frame for the rest of the correlation heatmap functions by -subsetting \code{bm_dataset} according to the category, parameter and visit combinations -captured by the rows of the \code{sel} parameter. -} -\details{ -\itemize{ -\item factors from \code{bm_ds} are releveled so all extra levels not present after subsetting are dropped and are sorted -according to \code{par} and \code{cat}. Unless parameters are renamed in \code{\link[=subset_bds_param]{subset_bds_param()}} then no releveling occurs. -\item \code{label} attributes from \code{bm_ds} are retained when available. -} -} -\keyword{internal} diff --git a/man/check_selected_choices.Rd b/man/check_selected_choices.Rd deleted file mode 100644 index 877092a..0000000 --- a/man/check_selected_choices.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-misc.R -\name{check_selected_choices} -\alias{check_selected_choices} -\title{If selected is not contained in choices send a warning} -\usage{ -check_selected_choices(selected, choices, inputId) -} -\arguments{ -\item{selected}{selection set} - -\item{choices}{choices set} - -\item{inputId}{the inputId of the shiny element being checked} -} -\description{ -If selected is not contained in choices send a warning -} -\keyword{internal} diff --git a/man/composed.Rd b/man/composed.Rd deleted file mode 100644 index 8d5d868..0000000 --- a/man/composed.Rd +++ /dev/null @@ -1,55 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{composed} -\alias{composed} -\alias{get_roc_plot_output} -\alias{get_dens_plot_output} -\alias{get_histo_plot_output} -\alias{get_raincloud_output} -\alias{get_metrics_output} -\alias{get_gt_summary_output} -\alias{get_info_panel_output} -\title{Composed functions} -\usage{ -get_roc_plot_output(ds_list, param_as_cols, fig_size, is_sorted) - -get_dens_plot_output(ds, param_as_cols, fig_size) - -get_histo_plot_output(ds, param_as_cols, fig_size) - -get_raincloud_output(ds, param_as_cols, fig_size) - -get_metrics_output( - ds, - param_as_cols, - fig_size, - x_metrics_col, - compute_metric_fn -) - -get_gt_summary_output(ds_list, sort_alph) - -get_info_panel_output(ds) -} -\description{ -Functions that creates and output to be displayed in the app, usually, by composing data and plotting calls. -} -\section{Functions}{ -\itemize{ -\item \code{get_roc_plot_output()}: ROC plot - -\item \code{get_dens_plot_output()}: Density plot - -\item \code{get_histo_plot_output()}: Density plot - -\item \code{get_raincloud_output()}: Raincloud plot - -\item \code{get_metrics_output()}: Metrics plot - -\item \code{get_gt_summary_output()}: GT Summary - -\item \code{get_info_panel_output()}: Info Panel - -}} -\keyword{composed} -\keyword{internal} diff --git a/man/compute_metric.Rd b/man/compute_metric.Rd deleted file mode 100644 index 3a63a25..0000000 --- a/man/compute_metric.Rd +++ /dev/null @@ -1,50 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{compute_metric} -\alias{compute_metric} -\alias{assert_compute_metric_data} -\alias{compute_metric_data} -\title{Helpers for computing metric data from the subset dataset} -\usage{ -assert_compute_metric_data(r) - -compute_metric_data(predictor, response) -} -\arguments{ -\item{r}{\verb{[data.frame()]} - -dataframe resulting from compute_metric_data} - -\item{predictor}{\verb{[numeric()]} - -The scores of the predictor} - -\item{response}{\verb{[factor()]} - -The response value} -} -\value{ -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{type} \verb{[character()]}: Metric name -\item \code{y} \verb{[numeric()]}: Metric value -\item \code{score}, \code{norm_score}, \code{norm_rank} \verb{[numeric()]}: Raw, normalized, and normalized rank predictor value per group. -} - -With an attribute: -\itemize{ -\item \code{limits} \verb{[list()]}: With one entry per metric type. Each entry is a \code{numeric(2)} that contains the plotting limits for the metric. -} -} -\description{ -Helpers for computing metric data from the subset dataset -} -\section{Functions}{ -\itemize{ -\item \code{assert_compute_metric_data()}: Assert compute_metric result data.frame types are correct - -\item \code{compute_metric_data()}: Compute metric analysis - -}} diff --git a/man/compute_roc.Rd b/man/compute_roc.Rd deleted file mode 100644 index 21fd787..0000000 --- a/man/compute_roc.Rd +++ /dev/null @@ -1,108 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{compute_roc} -\alias{compute_roc} -\alias{assert_compute_roc_data} -\alias{compute_roc_data} -\title{Helpers for computing ROC data from the subset dataset} -\usage{ -assert_compute_roc_data(r, with_ci) - -compute_roc_data(predictor, response, do_bootstrap, ci_points) -} -\arguments{ -\item{r}{\verb{[list(data.frame())]} - -dataframe resulting from compute_roc_data} - -\item{with_ci}{\verb{[logical(1)]} - -Indicates if CI is included in the result} - -\item{predictor}{\verb{[numeric(n)]} - -The scores of the predictor} - -\item{response}{\verb{[factor(n)]} - -The response value} - -\item{do_bootstrap}{\verb{[logical(1)]} -Calculate confidence intervals for sensitivity and specificity} - -\item{ci_points}{\verb{[list(spec = numeric(), thr = numeric())]} -Points at which 95\% confidence intervals for sensitivity and specificity will be calculated. Depending on the entry -CI will be calculated at defined specificity points or threshold points.} -} -\value{ -\verb{[list(data.frame())]} - -A list with entries: -\subsection{\code{roc_curve}}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{specificity} \verb{[numeric()]}: Sensitivity -\item \code{sensitivity} \verb{[numeric()]}: Specificity -\item \code{threshold} \verb{[numeric()]}: Threshold -\item \code{auc} \verb{[numeric(3)]}: A numeric vector of length 3 c(LOWER AUC CI, AUC, UPPER AUC CI) -\item \code{direction} \verb{[character(1)]}: The direction of the comparisons \code{<} or \code{>} according to \code{levels} -\item \code{levels} \verb{[character(2)]}: The sorted levels of the response variable according to \code{direction} -} -} - -\subsection{\code{roc_ci}}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{ci_specificity} \verb{[numeric()]}: Specificity value -\item \code{ci_lower_specificity} \verb{[numeric()]}: Specificity lower confidence interval -\item \code{ci_upper_specificity} \verb{[numeric()]}: Specificity upper confidence interval -\item \code{ci_sensitivity} \verb{[numeric()]}: Sensitivity value -\item \code{ci_lower_sensitivity} \verb{[numeric()]}: Sensitivity lower confidence interval -\item \code{ci_upper_sensitivity} \verb{[numeric()]}: Sensitivity upper confidence interval -\item \code{threshold} \verb{[numeric()]}: Threshold -} -} - -\subsection{\code{roc_optimal_cut}}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{optimal_cut_title} \verb{[character()]}: Name of the optimal cut -\item \code{optimal_cut_specificity} \verb{[numeric()]}: Sensitivity at the optimal cut point -\item \code{optimal_cut_lower_specificity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_specificity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -\item \code{optimal_cut_sensitivity} \verb{[numeric()]}: Specificity at the optimal cut point -\item \code{optimal_cut_lower_sensitivity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_sensitivity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -\item \code{optimal_cut_threshold} \verb{[numeric()]}: Threshold of optimal cut -} -} -} -\description{ -Helpers for computing ROC data from the subset dataset -} -\details{ -\itemize{ -\item Computing CIs for sensitivity and specifity usually implies using bootstrap which can be too expensive, -therefore the option of not running calculating them when the function is invoked is included. -\item Response levels are selected alphabetically being \code{case} the first one alphabetically the comparison direction -is selected automatically by \code{\link[pROC:roc]{pROC::roc()}} and related functions. -\item CIs are expected to be 95\% CIs -} -} -\section{Functions}{ -\itemize{ -\item \code{assert_compute_roc_data()}: Assert compute_roc result data.frame types are correct - -\item \code{compute_roc_data()}: Compute ROC analysis - -}} -\keyword{compute} diff --git a/man/default_lineplot_functions.Rd b/man/default_lineplot_functions.Rd deleted file mode 100644 index ff70441..0000000 --- a/man/default_lineplot_functions.Rd +++ /dev/null @@ -1,29 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_lineplot.R -\docType{data} -\name{default_lineplot_functions} -\alias{default_lineplot_functions} -\alias{lp_mean_summary_fns} -\alias{lp_median_summary_fns} -\title{Default lineplot summary functions} -\format{ -An object of class \code{list} of length 3. - -An object of class \code{list} of length 3. -} -\usage{ -lp_mean_summary_fns - -lp_median_summary_fns -} -\description{ -Default lineplot summary functions -} -\section{Functions}{ -\itemize{ -\item \code{lp_mean_summary_fns}: Default mean functions - -\item \code{lp_median_summary_fns}: Default median functions - -}} -\keyword{datasets} diff --git a/man/dplyr_.data.Rd b/man/dplyr_.data.Rd deleted file mode 100644 index 33ba94e..0000000 --- a/man/dplyr_.data.Rd +++ /dev/null @@ -1,9 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-importFrom.R -\name{.data} -\alias{.data} -\title{.data object from dplyr} -\description{ -.data object from dplyr -} -\keyword{internal} diff --git a/man/equal_and_mask_from_vec.Rd b/man/equal_and_mask_from_vec.Rd deleted file mode 100644 index af4ba8c..0000000 --- a/man/equal_and_mask_from_vec.Rd +++ /dev/null @@ -1,26 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/common_logic.R -\name{equal_and_mask_from_vec} -\alias{equal_and_mask_from_vec} -\title{Create a mask to filter a dataframe from a named list of values} -\usage{ -equal_and_mask_from_vec(ds, fl) -} -\arguments{ -\item{ds}{\code{data.frame()} - -A dataframe} - -\item{fl}{\code{named.list()|named.atomic()} - -A named list or atomic vector} -} -\description{ -It returns a logical mask indicating which rows have all columns in the list equal to the value in the list. It only -calculates equality with a reducing function \code{&}. -} -\details{ -Any attempt to generalize this function is very likely a mistake as it is thought to be a shorthand -for a common operation. -} -\keyword{internal} diff --git a/man/fp_stats.Rd b/man/fp_stats.Rd deleted file mode 100644 index 4c9f64b..0000000 --- a/man/fp_stats.Rd +++ /dev/null @@ -1,36 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_forest.R -\name{fp_stats} -\alias{fp_stats} -\alias{pearson_correlation} -\alias{spearman_correlation} -\alias{odds_ratio} -\title{Forest plot comnputing functions} -\usage{ -pearson_correlation(a, b) - -spearman_correlation(a, b) - -odds_ratio(a, b) -} -\arguments{ -\item{a, b}{vectors to be tested} -} -\description{ -Helpers used in the forest plot to calculate statistics -} -\section{Functions}{ -\itemize{ -\item \code{pearson_correlation()}: Pearson correlation function - -Forest plot helper - -\item \code{spearman_correlation()}: Spearman correlation function - -Forest plot helper - -\item \code{odds_ratio()}: Odds ratio function - -Forest plot helper - -}} diff --git a/man/fp_subset_data.Rd b/man/fp_subset_data.Rd deleted file mode 100644 index cafe4ff..0000000 --- a/man/fp_subset_data.Rd +++ /dev/null @@ -1,49 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_forest.R -\name{fp_subset_data} -\alias{fp_subset_data} -\title{Subset datasets for correlation heatmap} -\usage{ -fp_subset_data( - cat, - cat_col, - par, - par_col, - val_col, - vis, - vis_col, - group_vect, - bm_ds, - group_ds, - subj_col -) -} -\arguments{ -\item{par, cat}{\verb{[character*ish*(n)]} - -Values from \code{par_col} and \code{cat_col} to be subset} - -\item{val_col}{\verb{[character*ish*(1)]} - -Column containing values for the parameters} - -\item{vis}{\verb{[character*ish*(1)]} - -Values from \code{vis_col} to be subset} - -\item{group_vect}{\verb{[named(character(n))]} - -Columns to be subset and renamed.} - -\item{bm_ds, group_ds}{\code{data.frame} - -data frames to be used as inputs in \link{subset_bds_param} and \link{subset_adsl}} - -\item{subj_col, par_col, cat_col, vis_col}{\verb{[character(1)]} - -Column for subject id, category, parameter and visit. All specified columns must be factors} -} -\description{ -TODO: Update this roxygen description to match the function -} -\keyword{internal} diff --git a/man/get_dens_data.Rd b/man/get_dens_data.Rd deleted file mode 100644 index 71f66e2..0000000 --- a/man/get_dens_data.Rd +++ /dev/null @@ -1,49 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_dens_data} -\alias{get_dens_data} -\title{Calculate probability density per group} -\usage{ -get_dens_data(ds) -} -\arguments{ -\item{ds}{\verb{[data.frame()]} -A dataframe} -} -\value{ -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_value} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{dens_x} \verb{[numeric()]}: Predictor parameter value. -\item \code{dens_y} \verb{[numeric()]}: Predictor parameter probability density. -} -} -\description{ -It calculates the probability density of the parameter value by groups defined by \code{predictor_parameter}, -\code{response_parameter} and, if grouped, \code{group}. -These functions is prepared to be applied over a dataset that is the output of \code{roc_subset_data()}. -} -\details{ -\link[stats:density]{stats::density} with default values is used to calculate the density -} -\section{Input dataframe}{ - - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{subject_id} \verb{[factor()]}: Subject ID -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{predictor_value} \verb{[numeric()]}: Predictor parameter Value -\item \code{response_value} \verb{[factor()]}: Response parameter Value. -} -} - -\keyword{internal} diff --git a/man/get_dens_spec.Rd b/man/get_dens_spec.Rd deleted file mode 100644 index 266cad6..0000000 --- a/man/get_dens_spec.Rd +++ /dev/null @@ -1,53 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_dens_spec} -\alias{get_dens_spec} -\title{Specification for a set of faceted probability density plots} -\usage{ -get_dens_spec(ds, param_as_cols, fig_size) -} -\arguments{ -\item{ds}{\verb{[data.frames()]} - -A dataframe} - -\item{param_as_cols}{\verb{[logical(1)]} - -Charts are faceted using parameters as columns.} - -\item{fig_size}{\verb{[numeric(1)]} - -Size in pixels for each of the charts in the facet} -} -\value{ -A \link{vegawidget} specification -} -\description{ -The chart consists of a faceted set of ROC curves plotting probability density curves for the values of -the different predictor parameters. Each facet will be grouped by the value of the response parameter. -} -\details{ -\subsection{Rows and columns:}{ -\itemize{ -\item By default, predictor parameters are displayed in rows while grouping is displayed in columns. -\item If no grouping is selected, then parameters are displayed in cols. -\item All groups corresponding to the same parameters share the same X and Y axis limits. -} -} -} -\section{Input dataframe}{ - - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_value} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{dens_x} \verb{[numeric()]}: Predictor parameter value. -\item \code{dens_y} \verb{[numeric()]}: Predictor parameter probability density. -} -} - -\keyword{internal} diff --git a/man/get_explore_roc_data.Rd b/man/get_explore_roc_data.Rd deleted file mode 100644 index ce0bf97..0000000 --- a/man/get_explore_roc_data.Rd +++ /dev/null @@ -1,50 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_explore_roc_data} -\alias{get_explore_roc_data} -\title{Prepare dataframe for auc exploration} -\usage{ -get_explore_roc_data(ds) -} -\arguments{ -\item{ds}{\verb{[data.frame()]}} -} -\value{ -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{auc} \verb{[numeric()]}: Area under the curve -\item \code{lower_CI_auc} \verb{[numeric()]}: AUC lower confidence interval -\item \code{upper_CI_auc} \verb{[numeric()]}: AUC upper confidence interval -} -} -\description{ -Removes sensitivity, specificity, and threshold and expands auc in three columns. -Removes duplicated rows. -Used on the output of \code{\link[=get_roc_data]{get_roc_data()}} -} -\details{ -It respects columns labels -} -\section{Input dataframe}{ - - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{specificity} \verb{[numeric()]}: Sensitivity -\item \code{sensitivity} \verb{[numeric()]}: Specificity -\item \code{threshold} \verb{[numeric()]}: Threshold -\item \code{auc} \verb{[numeric(3)]}: A numeric vector of length 3 c(LOWER AUC CI, AUC, UPPER AUC CI) -} -} - -\keyword{internal} diff --git a/man/get_explore_roc_spec.Rd b/man/get_explore_roc_spec.Rd deleted file mode 100644 index 7e082d7..0000000 --- a/man/get_explore_roc_spec.Rd +++ /dev/null @@ -1,61 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_explore_roc_spec} -\alias{get_explore_roc_spec} -\title{Specification for an ordered AUC value plus CI chart} -\usage{ -get_explore_roc_spec(ds, fig_size, sort_alph) -} -\arguments{ -\item{ds}{\verb{[data.frame()]} - -A data.frame} - -\item{fig_size}{\verb{[numeric(1)]} - -Size in pixels for the chart} - -\item{sort_alph}{\verb{[logical(1)]} - -Sort chart by parameter name} -} -\value{ -A \link{vegawidget} specification -} -\description{ -The chart consists of a set of points with confidence intervals representing the AUC and its confidence interval. -} -\details{ -Parameters, by default, are vertically ordered from highest to lowest AUC curve. -When grouped, parameters will be combined with the grouping variable. -} -\section{Internal checks}{ - -\subsection{Shiny validation errors:}{ -\itemize{ -\item If the number of rows returned is greater than \code{ROC_VAL$MAX_ROWS_EXPLORE} a validation error is produced. -Otherwise the chart is too large, for greater limits than \code{ROC_VAL$MAX_ROWS_EXPLORE} the session may crash. -} -} -} - -\section{Input dataframe list}{ - -\subsection{\code{ds}}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{specificity} \verb{[numeric()]}: Sensitivity -\item \code{sensitivity} \verb{[numeric()]}: Specificity -\item \code{threshold} \verb{[numeric()]}: Threshold -\item \code{auc} \verb{[numeric(3)]}: A numeric vector of length 3 c(LOWER AUC CI, AUC, UPPER AUC CI) -} -} -} - -\keyword{internal} diff --git a/man/get_gt_summary_table.Rd b/man/get_gt_summary_table.Rd deleted file mode 100644 index 0489962..0000000 --- a/man/get_gt_summary_table.Rd +++ /dev/null @@ -1,54 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_gt_summary_table} -\alias{get_gt_summary_table} -\title{GT Summary table for the area under the curve, optimal cut data and their confidence intervals} -\usage{ -get_gt_summary_table(ds, rounder = function(x) round(x, digits = 2), sort_alph) -} -\arguments{ -\item{ds}{\verb{[data.frames()]} - -A dataframe} - -\item{rounder}{\verb{[function()]} - -Single parameter function that rounds a numeric vector for rendendering} - -\item{sort_alph}{\verb{[logical(1)]} - -Sort summary table by parameter name} -} -\value{ -A \link{vegawidget} specification -} -\description{ -The table summarizes the AUC, the optimal cut data, for each parameter and grouping combination -} -\details{ -Numerical values are rounded to two decimals -} -\section{Input}{ - - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{auc} \verb{[numeric()]}: Area under the curve -\item \code{lower_CI_auc} \verb{[numeric()]}: AUC lower confidence interval -\item \code{upper_CI_auc} \verb{[numeric()]}: AUC upper confidence interval -\item \code{optimal_cut_title} \verb{[character()]}: Name of the optimal cut -\item \code{optimal_cut_specificity} \verb{[numeric()]}: Sensitivity at the optimal cut point -\item \code{optimal_cut_lower_specificity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_specificity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -\item \code{optimal_cut_sensitivity} \verb{[numeric()]}: Specificity at the optimal cut point -\item \code{optimal_cut_lower_sensitivity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_sensitivity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -} -} - -\keyword{internal} diff --git a/man/get_histo_data.Rd b/man/get_histo_data.Rd deleted file mode 100644 index 4ba3e4c..0000000 --- a/man/get_histo_data.Rd +++ /dev/null @@ -1,50 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_histo_data} -\alias{get_histo_data} -\title{Calculate binned count per group} -\usage{ -get_histo_data(ds) -} -\arguments{ -\item{ds}{\verb{[data.frame()]} -A dataframe} -} -\value{ -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_value} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{bin_start} \verb{[numeric()]}: Predictor parameter bin start. -\item \code{bin_end} \verb{[numeric()]}: Predictor parameter bin end. -\item \code{bin_count} \verb{[numeric()]}: Predictor parameter bin count. -} -} -\description{ -It calculates the binned count of the parameter value by groups defined by \code{predictor_parameter}, \code{response_parameter} and -if grouped, \code{group}. These functions is prepared to be applied over a dataset that is the output of -\code{subset_data()}. -} -\details{ -\link[graphics:hist]{graphics::hist} with default values is used to calculate the binning -} -\section{Input dataframe}{ - - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{subject_id} \verb{[factor()]}: Subject ID -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{predictor_value} \verb{[numeric()]}: Predictor parameter Value -\item \code{response_value} \verb{[factor()]}: Response parameter Value. -} -} - -\keyword{internal} diff --git a/man/get_histo_spec.Rd b/man/get_histo_spec.Rd deleted file mode 100644 index b5bbb37..0000000 --- a/man/get_histo_spec.Rd +++ /dev/null @@ -1,54 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_histo_spec} -\alias{get_histo_spec} -\title{Specification for a set of faceted histograms} -\usage{ -get_histo_spec(ds, param_as_cols, fig_size) -} -\arguments{ -\item{ds}{\verb{[data.frames()]} - -A dataframe} - -\item{param_as_cols}{\verb{[logical(1)]} - -Charts are faceted using parameters as columns.} - -\item{fig_size}{\verb{[numeric(1)]} - -Size in pixels for each of the charts in the facet} -} -\value{ -A \link{vegawidget} specification -} -\description{ -The chart consists of a faceted set of ROC curves plotting histograms for the values of the different predictor -parameters. Each facet will be grouped by the value of the response parameter. -} -\details{ -\subsection{Rows and columns:}{ -\itemize{ -\item By default, predictor parameters are displayed in rows while grouping is displayed in columns. -\item If no grouping is selected, then parameters are displayed in cols. -\item All groups corresponding to the same parameters share the same X and Y axis limits. -} -} -} -\section{Input dataframe}{ - - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{subject_id} \verb{[factor()]}: Subject ID -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{predictor_value} \verb{[numeric()]}: Predictor parameter Value -\item \code{response_value} \verb{[factor()]}: Response parameter Value. -} -} - -\keyword{internal} diff --git a/man/get_lbl.Rd b/man/get_lbl.Rd deleted file mode 100644 index 925fa2e..0000000 --- a/man/get_lbl.Rd +++ /dev/null @@ -1,20 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-label.R -\name{get_lbl} -\alias{get_lbl} -\title{Get a single label from a dataframe} -\usage{ -get_lbl(df, var) -} -\arguments{ -\item{df}{a dataframe.} - -\item{var}{from which column do we want the label} -} -\value{ -A string with the label name -} -\description{ -It will try to read the label attribute from one columns. -} -\keyword{misc} diff --git a/man/get_lbl_robust.Rd b/man/get_lbl_robust.Rd deleted file mode 100644 index e7a304c..0000000 --- a/man/get_lbl_robust.Rd +++ /dev/null @@ -1,20 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-label.R -\name{get_lbl_robust} -\alias{get_lbl_robust} -\title{Robust getter for dataframe labels} -\usage{ -get_lbl_robust(df, var) -} -\arguments{ -\item{df}{a dataframe.} - -\item{var}{a column of the dataframe} -} -\value{ -The label attribute or the name of the column if the label attribute is NULL. -} -\description{ -It returns the label of the column of a dataframe if it is not NULL. Otherwise it returns the name of the column. -} -\keyword{misc} diff --git a/man/get_lbls.Rd b/man/get_lbls.Rd deleted file mode 100644 index ded77e5..0000000 --- a/man/get_lbls.Rd +++ /dev/null @@ -1,27 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-label.R -\name{get_lbls} -\alias{get_lbls} -\alias{get_lbls_robust} -\title{Get all labels from a dataframe} -\usage{ -get_lbls(df) - -get_lbls_robust(df) -} -\arguments{ -\item{df}{a dataframe.} -} -\value{ -A named list in which name is the name of the df column and value is the label of the column. -Non-labelled columns will return NULL. In the robust version NULL is replaced by the name of the column. -} -\description{ -It will try to read the label attribute from each of the columns. -} -\section{Functions}{ -\itemize{ -\item \code{get_lbls_robust()}: robust - -}} -\keyword{misc} diff --git a/man/get_metric_data.Rd b/man/get_metric_data.Rd deleted file mode 100644 index c5ea259..0000000 --- a/man/get_metric_data.Rd +++ /dev/null @@ -1,75 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_metric_data} -\alias{get_metric_data} -\title{Compute classification metrics to groups} -\usage{ -get_metric_data(ds, compute_metric_fn) -} -\arguments{ -\item{ds}{\verb{[data.frame()]} -A dataframe} - -\item{compute_metric_fn}{\verb{[function(1)]} -A function that computes the metrics} -} -\value{ -\verb{[list()]} -A list with entries: -\subsection{\code{ds}}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{type} \verb{[character()]}: Metric name -\item \code{y} \verb{[numeric()]}: Metric value -\item \code{score}, \code{norm_score}, \code{norm_rank} \verb{[numeric()]}: Raw, normalized, and normalized rank predictor value per group. -} -} - -\subsection{\code{limits}}{ - -\verb{[list()]} - -With one entry per metric type. Each entry is a \code{numeric(2)} that contains the plotting limits for the metric. - -Additionally: -\itemize{ -\item \code{score}, \code{norm_score}, \code{norm_rank} have a \code{label} attribute \code{"Score"}, \code{"Normalized Score"} -and \code{"Normalized Rank"} respectively. -} -} -} -\description{ -It computes classification metrics over a dataset. The application is applied by groups defined by CNT_ROC$PPAR, -CNT_ROC$RPAR and, if grouped, CNT_ROC$GRP. These functions is prepared to be applied over a dataset that is the -output of \code{roc_subset_data()}. The function itself does not compute the metrics, it only applies \code{compute_metric_fn} -over the different groups. -} -\section{Input dataframe}{ - - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{subject_id} \verb{[factor()]}: Subject ID -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{predictor_value} \verb{[numeric()]}: Predictor parameter Value -\item \code{response_value} \verb{[factor()]}: Response parameter Value. -} -} - -\section{compute_metric_fn definition}{ - - -For an example of a computing function please review \code{\link[=compute_metric_data]{compute_metric_data()}}. -} - -\keyword{internal} diff --git a/man/get_metric_spec.Rd b/man/get_metric_spec.Rd deleted file mode 100644 index 347ebd4..0000000 --- a/man/get_metric_spec.Rd +++ /dev/null @@ -1,68 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_metric_spec} -\alias{get_metric_spec} -\title{Specification for a set of line plots for classification metrics} -\usage{ -get_metric_spec(ds, param_as_cols, fig_size, limits, x_col) -} -\arguments{ -\item{ds}{\verb{[data.frames()]} - -A dataframe} - -\item{param_as_cols}{\verb{[logical(1)]} - -Charts are faceted using parameters as columns.} - -\item{fig_size}{\verb{[numeric(1)]} - -Size in pixels for each of the charts in the facet} - -\item{limits}{\verb{[list()]} - -A vector as specified in the input section} - -\item{x_col}{\verb{[character(1)]} - -Column for the x axis of the graph} -} -\value{ -A \link{vegawidget} specification -} -\description{ -The chart consists of a faceted set of line and point charts. -} -\details{ -\subsection{Rows and columns:}{ -\itemize{ -\item By default, predictor parameters are displayed in rows while metrics are displayed in columns. -} -} -} -\section{Input}{ - -\subsection{\code{ds}}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{type} \verb{[character()]}: Metric name -\item \code{y} \verb{[numeric()]}: Metric value -\item \code{score}, \code{norm_score}, \code{norm_rank} \verb{[numeric()]}: Raw, normalized, and normalized rank predictor value per group. -} -} - -\subsection{\code{limits}}{ - -\verb{[list()]} - -With one entry per metric type. Each entry is a \code{numeric(2)} that contains the plotting limits for the metric. -} -} - -\keyword{internal} diff --git a/man/get_quantile_data.Rd b/man/get_quantile_data.Rd deleted file mode 100644 index 72a785e..0000000 --- a/man/get_quantile_data.Rd +++ /dev/null @@ -1,46 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_quantile_data} -\alias{get_quantile_data} -\title{Calculate quantiles per group} -\usage{ -get_quantile_data(ds) -} -\arguments{ -\item{ds}{\verb{[data.frame()]} -A dataframe} -} -\value{ -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_value} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{mean} \verb{[numeric()]}: Mean of the predictor parameter value -\item \code{q05}, \code{q25}, \code{q50}, \code{q75}, \code{q95} \verb{[numeric()]}: Quantiles of the predictor parameter value -} -} -\description{ -It calculates the quantiles \code{c(.05, .25, .50, .75, .95)} and the mean of the parameter value by groups defined by -CNT_ROC$PPAR, CNT_ROC$RPAR and, if grouped, CNT_ROC$GRP. These functions is prepared to be applied over a dataset -that is the output of \code{roc_subset_data()}. -} -\section{Input dataframe}{ - - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{subject_id} \verb{[factor()]}: Subject ID -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{predictor_value} \verb{[numeric()]}: Predictor parameter Value -\item \code{response_value} \verb{[factor()]}: Response parameter Value. -} -} - -\keyword{internal} diff --git a/man/get_raincloud_spec.Rd b/man/get_raincloud_spec.Rd deleted file mode 100644 index 19be319..0000000 --- a/man/get_raincloud_spec.Rd +++ /dev/null @@ -1,82 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_raincloud_spec} -\alias{get_raincloud_spec} -\title{Specification for a set of raincloud plots} -\usage{ -get_raincloud_spec(area_ds, quantile_ds, point_ds, param_as_cols, fig_size) -} -\arguments{ -\item{area_ds, quantile_ds, point_ds}{\verb{[data.frames()]} - -A dataframe} - -\item{param_as_cols}{\verb{[logical(1)]} - -Charts are faceted using parameters as columns.} - -\item{fig_size}{\verb{[numeric(1)]} - -Size in pixels for each of the charts in the facet} -} -\value{ -A \link{vegawidget} specification -} -\description{ -The chart consists of a faceted set of raincloud. Each facet will be grouped by the value of the response parameter. -} -\details{ -\subsection{Rows and columns:}{ -\itemize{ -\item By default, predictor parameters are displayed in rows while grouping is displayed in columns. -\item If no grouping is selected, then parameters are displayed in cols. -} -} -} -\section{Input dataframe list}{ - -\subsection{\code{area_ds}}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_value} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{dens_x} \verb{[numeric()]}: Predictor parameter value. -\item \code{dens_y} \verb{[numeric()]}: Predictor parameter probability density. -} -} - -\subsection{\code{quantile_ds}}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_value} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{mean} \verb{[numeric()]}: Mean of the predictor parameter value -\item \code{q05}, \code{q25}, \code{q50}, \code{q75}, \code{q95} \verb{[numeric()]}: Quantiles of the predictor parameter value -} -} - -\subsection{\code{point_ds}}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{subject_id} \verb{[factor()]}: Subject ID -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{predictor_value} \verb{[numeric()]}: Predictor parameter Value -\item \code{response_value} \verb{[factor()]}: Response parameter Value. -} -} -} - -\keyword{internal} diff --git a/man/get_roc_data.Rd b/man/get_roc_data.Rd deleted file mode 100644 index e47a4d4..0000000 --- a/man/get_roc_data.Rd +++ /dev/null @@ -1,115 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_roc_data} -\alias{get_roc_data} -\title{Apply ROC analysis to groups} -\usage{ -get_roc_data(ds, compute_fn, ci_points, do_bootstrap) -} -\arguments{ -\item{ds}{\verb{[data.frame()]} -A dataframe} - -\item{compute_fn}{\verb{[function(1)]} -A function that computes the ROC data} - -\item{ci_points}{\verb{[list(spec = numeric(), thr = numeric())]} -Points at which 95\% confidence intervals for sensitivity and specificity will be calculated. Depending on the entry -CI will be calculated at defined specificity points or threshold points.} - -\item{do_bootstrap}{\verb{[logical(1)]} -Calculate confidence intervals for sensitivity and specificity} -} -\value{ -\verb{[list(data.frame())]} -A list with entries: -\subsection{roc_curve}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{specificity} \verb{[numeric()]}: Sensitivity -\item \code{sensitivity} \verb{[numeric()]}: Specificity -\item \code{threshold} \verb{[numeric()]}: Threshold -\item \code{auc} \verb{[numeric(3)]}: A numeric vector of length 3 c(LOWER AUC CI, AUC, UPPER AUC CI) -} -} - -\subsection{roc_ci}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{ci_specificity} \verb{[numeric()]}: Specificity value -\item \code{ci_lower_specificity} \verb{[numeric()]}: Specificity lower confidence interval -\item \code{ci_upper_specificity} \verb{[numeric()]}: Specificity upper confidence interval -\item \code{ci_sensitivity} \verb{[numeric()]}: Sensitivity value -\item \code{ci_lower_sensitivity} \verb{[numeric()]}: Sensitivity lower confidence interval -\item \code{ci_upper_sensitivity} \verb{[numeric()]}: Sensitivity upper confidence interval -} - -CIs are only calculated when \code{do_bootstrap} is \code{TRUE} -} - -\subsection{roc_optimal_cut}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{optimal_cut_title} \verb{[character()]}: Name of the optimal cut -\item \code{optimal_cut_specificity} \verb{[numeric()]}: Sensitivity at the optimal cut point -\item \code{optimal_cut_lower_specificity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_specificity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -\item \code{optimal_cut_sensitivity} \verb{[numeric()]}: Specificity at the optimal cut point -\item \code{optimal_cut_lower_sensitivity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_sensitivity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -\item \code{optimal_cut_threshold} \verb{[numeric()]}: Threshold of the optimal cut -} - -CIs are only calculated when \code{do_bootstrap} is \code{TRUE} -} -} -\description{ -It applies an ROC analysis over a dataset. The application is applied by groups defined by \code{predictor_parameter}, -\code{response_parameter} and, if grouped, \code{group}. - -This functions is prepared to be applied over a dataset that is the output of \code{roc_subset_data()}. - -The function itself does not calculate the ROC analysis, it only applies \code{compute_fn} over the different groups. -\subsection{Input dataframe:}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{subject_id} \verb{[factor()]}: Subject ID -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{predictor_value} \verb{[numeric()]}: Predictor parameter Value -\item \code{response_value} \verb{[factor()]}: Response parameter Value. -} -} - -\subsection{compute_fn definition:}{ - -For an example of a computing function please review \code{\link[=compute_roc_data]{compute_roc_data()}}. -} -} -\details{ -If \code{compute_fn} returns an error when applied to any of the groups a dataset with NA is returned instead. -This controls side cases such as groups that contains a single observation. -} -\keyword{internal} diff --git a/man/get_roc_spec.Rd b/man/get_roc_spec.Rd deleted file mode 100644 index b1b8eb3..0000000 --- a/man/get_roc_spec.Rd +++ /dev/null @@ -1,123 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_roc_spec} -\alias{get_roc_spec} -\alias{get_roc_sorted_spec} -\title{Specification for a set of faceted ROC curves} -\usage{ -get_roc_spec(ds_list, param_as_cols, fig_size) - -get_roc_sorted_spec(ds_list, param_as_cols, fig_size) -} -\arguments{ -\item{ds_list}{\verb{[list(data.frames())]} - -A list of dataframes} - -\item{param_as_cols}{\verb{[logical(1)]} - -Charts are faceted using parameters as columns. This parameter is ignored in the sorted version.} - -\item{fig_size}{\verb{[numeric(1)]} - -Size in pixels for each of the charts in the facet} -} -\value{ -A \link{vegawidget} specification -} -\description{ -The chart consists of a faceted set of ROC curves plotting the: -} -\details{ -\itemize{ -\item ROC curves -\item The confidence intervals -\item The set of optimal cuts -} -\subsection{Rows and columns:}{ -\itemize{ -\item By default, predictor parameters are displayed in rows while grouping is displayed in columns. -\item If no grouping is selected, then parameters are displayed in cols. -\item If \verb{ds_list[[}r CNT_ROC$ROC_CI]]`` is \code{NULL} then confidence intervals are not presented. -} -} - -\subsection{Rows and columns:}{ -\itemize{ -\item Charts are ordered from left to right and top to bottom from the highest to lowest area under the curve -} -} -} -\section{Functions}{ -\itemize{ -\item \code{get_roc_sorted_spec()}: Specification for a set of sorted ROC curves - -}} -\section{Input dataframe list}{ - -\subsection{\code{ds_list}}{ - -\verb{[list(data.frame())]} -A list with entries: -} - -\subsection{roc_curve}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{specificity} \verb{[numeric()]}: Sensitivity -\item \code{sensitivity} \verb{[numeric()]}: Specificity -\item \code{threshold} \verb{[numeric()]}: Threshold -\item \code{auc} \verb{[numeric(3)]}: A numeric vector of length 3 c(LOWER AUC CI, AUC, UPPER AUC CI) -} -} - -\subsection{roc_ci}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{ci_specificity} \verb{[numeric()]}: Specificity value -\item \code{ci_lower_specificity} \verb{[numeric()]}: Specificity lower confidence interval -\item \code{ci_upper_specificity} \verb{[numeric()]}: Specificity upper confidence interval -\item \code{ci_sensitivity} \verb{[numeric()]}: Sensitivity value -\item \code{ci_lower_sensitivity} \verb{[numeric()]}: Sensitivity lower confidence interval -\item \code{ci_upper_sensitivity} \verb{[numeric()]}: Sensitivity upper confidence interval -} - -CIs are only calculated when \code{do_bootstrap} is \code{TRUE} -} - -\subsection{roc_optimal_cut}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{optimal_cut_title} \verb{[character()]}: Name of the optimal cut -\item \code{optimal_cut_specificity} \verb{[numeric()]}: Sensitivity at the optimal cut point -\item \code{optimal_cut_lower_specificity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_specificity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -\item \code{optimal_cut_sensitivity} \verb{[numeric()]}: Specificity at the optimal cut point -\item \code{optimal_cut_lower_sensitivity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_sensitivity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -\item \code{optimal_cut_threshold} \verb{[numeric()]}: Threshold of the optimal cut -} - -CIs are only calculated when \code{do_bootstrap} is \code{TRUE} -} -} - -\keyword{internal} diff --git a/man/get_summary_data.Rd b/man/get_summary_data.Rd deleted file mode 100644 index 2466055..0000000 --- a/man/get_summary_data.Rd +++ /dev/null @@ -1,100 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{get_summary_data} -\alias{get_summary_data} -\title{Prepare dataframe for summary table exploration} -\usage{ -get_summary_data(ds_list) -} -\arguments{ -\item{ds_list}{\verb{[list(data.frame)]}} -} -\value{ -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{auc} \verb{[numeric()]}: Area under the curve -\item \code{lower_CI_auc} \verb{[numeric()]}: AUC lower confidence interval -\item \code{upper_CI_auc} \verb{[numeric()]}: AUC upper confidence interval -\item \code{optimal_cut_title} \verb{[character()]}: Name of the optimal cut -\item \code{optimal_cut_specificity} \verb{[numeric()]}: Sensitivity at the optimal cut point -\item \code{optimal_cut_lower_specificity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_specificity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -\item \code{optimal_cut_sensitivity} \verb{[numeric()]}: Specificity at the optimal cut point -\item \code{optimal_cut_lower_sensitivity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_sensitivity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -} -} -\description{ -Expands auc from roc_curve in three columns and joins the dataset with roc_optimal_cut -Used on the output of \code{\link[=get_roc_data]{get_roc_data()}} -} -\section{Input dataframe list}{ - - -\verb{[list(data.frame())]} -A list with entries: -\subsection{roc_curve}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{specificity} \verb{[numeric()]}: Sensitivity -\item \code{sensitivity} \verb{[numeric()]}: Specificity -\item \code{threshold} \verb{[numeric()]}: Threshold -\item \code{auc} \verb{[numeric(3)]}: A numeric vector of length 3 c(LOWER AUC CI, AUC, UPPER AUC CI) -} -} - -\subsection{roc_ci}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{ci_specificity} \verb{[numeric()]}: Specificity value -\item \code{ci_lower_specificity} \verb{[numeric()]}: Specificity lower confidence interval -\item \code{ci_upper_specificity} \verb{[numeric()]}: Specificity upper confidence interval -\item \code{ci_sensitivity} \verb{[numeric()]}: Sensitivity value -\item \code{ci_lower_sensitivity} \verb{[numeric()]}: Sensitivity lower confidence interval -\item \code{ci_upper_sensitivity} \verb{[numeric()]}: Sensitivity upper confidence interval -} - -CIs are only calculated when \code{do_bootstrap} is \code{TRUE} -} - -\subsection{roc_optimal_cut}{ - -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter name. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{optimal_cut_title} \verb{[character()]}: Name of the optimal cut -\item \code{optimal_cut_specificity} \verb{[numeric()]}: Sensitivity at the optimal cut point -\item \code{optimal_cut_lower_specificity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_specificity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -\item \code{optimal_cut_sensitivity} \verb{[numeric()]}: Specificity at the optimal cut point -\item \code{optimal_cut_lower_sensitivity} \verb{[numeric()]}: Lower Confidence interval of sensitivity -\item \code{optimal_cut_upper_sensitivity} \verb{[numeric()]}: Upper Confidence interval of sensitivity -\item \code{optimal_cut_threshold} \verb{[numeric()]}: Threshold of the optimal cut -} - -CIs are only calculated when \code{do_bootstrap} is \code{TRUE} -} -} - -\keyword{internal} diff --git a/man/heatmap_D3.Rd b/man/heatmap_D3.Rd deleted file mode 100644 index f380c12..0000000 --- a/man/heatmap_D3.Rd +++ /dev/null @@ -1,111 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/imod_heatmap_plot_d3.R -\name{heatmap_D3} -\alias{heatmap_D3} -\alias{heatmap_d3_UI} -\alias{heatmap_d3_server} -\title{D3 heatmap plot} -\usage{ -heatmap_d3_UI(id, ...) - -heatmap_d3_server( - id, - data, - x_axis = "S", - y_axis = "W", - z_axis = "E", - margin = list(top = 0, bottom = 0, left = 0, right = 0), - palette = NULL, - quiet = TRUE, - msg_func = NULL, - ... -) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{...}{Extra parameters that are passed to \link[r2d3:d3-shiny]{r2d3::d3Output}, \link[r2d3:d3-shiny]{r2d3::renderD3} and \link[r2d3:r2d3]{r2d3::r2d3}} - -\item{data}{\verb{[data.frame() | shiny::reactive(data.frame) | shinymeta::metaReactive(data.frame)]} - -dataframe to plot. It expects the following format: -\itemize{ -\item columns names ar "x", "y", "z" and, optionally, "label" and "color" -\item There is one entry for each combination of "x" and "y" present in the dataset. -In other words, the values for each bar are defined explicitly, even if they are NA -\item Axis labels and legend title are stored as the attribute "label" of the "x", "y" and "z" columns. (Legend title -is not implemented yet) -\item "x" and "y" are factors. The order of the levels dictates the ordering of each axis. -\item "z" is a factor or a double. -\item "label" values are printed on top of each of cell -\item If the column "color" is included, its values override the color defined according to the palette parameter. For -the entries that we do not want to override the \code{NA} value must be passed in the color column. -\item It can contain additional columns that are not used for plotting but can be used in the tooltip. -}} - -\item{x_axis, y_axis, z_axis}{\verb{[character(1) | NULL | shiny::reactive(character(1) | NULL) | shinymeta::metaReactive(character(1) | NULL)]} - -Indicate the absence/presence and location of the axis descriptors -(the descriptor for the x and y axes are the plot ticks; for the z axis it's the legend) -\itemize{ -\item x_desc can take the following values: "N" (north), "S" (south), NULL -\item y_desc can take the following values: "W" (west), "E" (east), NULL -\item z_desc can take the following values: "N", "E", "S", "W", NULL -}} - -\item{margin}{\verb{[numeric(4) | shiny::reactive(numeric(4)) | shinymeta::metaReactive(numeric(4))]} - -margin to be used on each of the sides.} - -\item{palette}{\verb{[character(1+) | numeric (1+) | shiny::reactive(character(1+) | numeric (1+)) | shinymeta::metaReactive(character(1+) | numeric (1+))]} - -Vector that maps values to "z" colors. The names of the vector are hexadecimal colors -encoded as #rrggbb or #rrggbbaa (red, green, blue, alpha) and the values are the "z" values that -should be mapped to that color. -\itemize{ -\item If "z" is a factor, the palette is complete (i.e. it should offer one color per value). -\item If "z" is a double, the palette should contain at least two values covering the min-max range -of possible values. If it contains more, the color of each cell will be linearly -interpolated according to where its value falls between the two surrounding provided colors. -\item z values that are \code{NA} or \code{NULL} will always be colored in grey. -\item In all cases the same color can be mapped to several values -}} - -\item{quiet}{\verb{[logical(1) | shiny::reactive(logical(1)) | shinymeta::metaReactive(logical(1))]} - -A boolean indicating if javascript code should include debug output.} - -\item{msg_func}{\verb{[character(1) | shiny::reactive(numeric(1)) | shinymeta::metaReactive(numeric(1))]} - -A JS string that is evaluated in the client. The string must return -a function that receives a single parameter and returns HTML code that is placed in the tooltip. If NULL a -default tooltip is shown.} -} -\value{ -\subsection{UI}{ - -A heatmap plot -} - -\subsection{Server}{ - -A list with one entry: -margin: similar to the margin parameter with the minimum margins for the current plot -} -} -\description{ -Plot the contents of a dataframe as a heatmap, with optional legends, palette and alignment margins. -} -\details{ -\emph{msg func} contains a string containing JS code. When evaluated, this string will be evaluated in the client -and must return a function that receives a single parameter. That parameter will contain a JS object with the same -fields as columns in \emph{data} for the point being hovered. -} -\section{Functions}{ -\itemize{ -\item \code{heatmap_d3_UI()}: UI - -\item \code{heatmap_d3_server()}: Server - -}} -\keyword{internal} diff --git a/man/mock_app_boxplot.Rd b/man/mock_app_boxplot.Rd deleted file mode 100644 index 5bb3920..0000000 --- a/man/mock_app_boxplot.Rd +++ /dev/null @@ -1,24 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mock_boxplot.R -\name{mock_app_boxplot} -\alias{mock_app_boxplot} -\title{Mock boxplot app} -\usage{ -mock_app_boxplot( - dry_run = FALSE, - update_query_string = TRUE, - srv_defaults = list(), - ui_defaults = list() -) -} -\arguments{ -\item{dry_run}{Return parameters used in the call} - -\item{update_query_string}{automatically update query string with app state} - -\item{ui_defaults, srv_defaults}{a list of values passed to the ui/server function} -} -\description{ -Mock boxplot app -} -\keyword{mock} diff --git a/man/mock_app_boxplot_mm.Rd b/man/mock_app_boxplot_mm.Rd deleted file mode 100644 index 522ba0a..0000000 --- a/man/mock_app_boxplot_mm.Rd +++ /dev/null @@ -1,15 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mock_boxplot.R -\name{mock_app_boxplot_mm} -\alias{mock_app_boxplot_mm} -\title{Mock mm boxplot app} -\usage{ -mock_app_boxplot_mm(update_query_string = TRUE) -} -\arguments{ -\item{update_query_string}{automatically update query string with app state} -} -\description{ -Mock mm boxplot app -} -\keyword{mock} diff --git a/man/mock_app_corr_hm.Rd b/man/mock_app_corr_hm.Rd deleted file mode 100644 index 9c8478b..0000000 --- a/man/mock_app_corr_hm.Rd +++ /dev/null @@ -1,24 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mock_corr_hm.R -\name{mock_app_corr_hm} -\alias{mock_app_corr_hm} -\title{Mock corr hm app} -\usage{ -mock_app_corr_hm( - dry_run = FALSE, - update_query_string = TRUE, - srv_defaults = list(), - ui_defaults = list() -) -} -\arguments{ -\item{dry_run}{Return parameters used in the call} - -\item{update_query_string}{automatically update query string with app state} - -\item{ui_defaults, srv_defaults}{a list of values passed to the ui/server function} -} -\description{ -Mock corr hm app -} -\keyword{mock} diff --git a/man/mock_app_correlation_hm_mm.Rd b/man/mock_app_correlation_hm_mm.Rd deleted file mode 100644 index 7554fe5..0000000 --- a/man/mock_app_correlation_hm_mm.Rd +++ /dev/null @@ -1,12 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mock_corr_hm.R -\name{mock_app_correlation_hm_mm} -\alias{mock_app_correlation_hm_mm} -\title{Mock corr hm app} -\usage{ -mock_app_correlation_hm_mm() -} -\description{ -Mock corr hm app -} -\keyword{mock} diff --git a/man/mock_app_forest.Rd b/man/mock_app_forest.Rd deleted file mode 100644 index 11114d7..0000000 --- a/man/mock_app_forest.Rd +++ /dev/null @@ -1,24 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mock_forest.R -\name{mock_app_forest} -\alias{mock_app_forest} -\title{Mock forestplot app} -\usage{ -mock_app_forest( - dry_run = FALSE, - update_query_string = TRUE, - srv_defaults = list(), - ui_defaults = list() -) -} -\arguments{ -\item{dry_run}{Return parameters used in the call} - -\item{update_query_string}{automatically update query string with app state} - -\item{ui_defaults, srv_defaults}{a list of values passed to the ui/server function} -} -\description{ -Mock forestplot app -} -\keyword{mock} diff --git a/man/mock_app_lineplot.Rd b/man/mock_app_lineplot.Rd deleted file mode 100644 index b4817ae..0000000 --- a/man/mock_app_lineplot.Rd +++ /dev/null @@ -1,27 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mock_lineplot.R -\name{mock_app_lineplot} -\alias{mock_app_lineplot} -\title{Mock lineplot app} -\usage{ -mock_app_lineplot( - dry_run = FALSE, - update_query_string = TRUE, - srv_defaults = list(), - ui_defaults = list(), - data = test_data() -) -} -\arguments{ -\item{dry_run}{Return parameters used in the call} - -\item{update_query_string}{automatically update query string with app state} - -\item{ui_defaults, srv_defaults}{a list of values passed to the ui/server function} - -\item{data}{data for the mock application} -} -\description{ -Mock lineplot app -} -\keyword{mock} diff --git a/man/mock_app_scatterplot.Rd b/man/mock_app_scatterplot.Rd deleted file mode 100644 index d0aa70b..0000000 --- a/man/mock_app_scatterplot.Rd +++ /dev/null @@ -1,24 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mock_scatter.R -\name{mock_app_scatterplot} -\alias{mock_app_scatterplot} -\title{Mock scatterplot app} -\usage{ -mock_app_scatterplot( - dry_run = FALSE, - update_query_string = TRUE, - srv_defaults = list(), - ui_defaults = list() -) -} -\arguments{ -\item{dry_run}{Return parameters used in the call} - -\item{update_query_string}{automatically update query string with app state} - -\item{ui_defaults, srv_defaults}{a list of values passed to the ui/server function} -} -\description{ -Mock scatterplot app -} -\keyword{mock} diff --git a/man/mock_app_scatterplotmatrix.Rd b/man/mock_app_scatterplotmatrix.Rd deleted file mode 100644 index e3f394b..0000000 --- a/man/mock_app_scatterplotmatrix.Rd +++ /dev/null @@ -1,24 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mock_scatter_matrix.R -\name{mock_app_scatterplotmatrix} -\alias{mock_app_scatterplotmatrix} -\title{Mock matrix of scatterplots app} -\usage{ -mock_app_scatterplotmatrix( - dry_run = FALSE, - update_query_string = TRUE, - srv_defaults = list(), - ui_defaults = list() -) -} -\arguments{ -\item{dry_run}{Return parameters used in the call} - -\item{update_query_string}{automatically update query string with app state} - -\item{ui_defaults, srv_defaults}{a list of values passed to the ui/server function} -} -\description{ -Mock matrix of scatterplots app -} -\keyword{mock} diff --git a/man/mock_roc.Rd b/man/mock_roc.Rd deleted file mode 100644 index de7274b..0000000 --- a/man/mock_roc.Rd +++ /dev/null @@ -1,30 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{mock_roc} -\alias{mock_roc} -\alias{mock_roc_mm_app} -\alias{mock_roc_app} -\title{Mock functions} -\usage{ -mock_roc_mm_app( - adbm = test_roc_data()[["adbm"]], - adbin = test_roc_data()[["adbin"]], - group = test_roc_data()[["adsl"]] -) - -mock_roc_app() -} -\arguments{ -\item{adbm, adbin, group}{Datasets for the mock app} -} -\description{ -Mock functions -} -\section{Functions}{ -\itemize{ -\item \code{mock_roc_mm_app()}: Mock app running the module inside dv.manager - -\item \code{mock_roc_app()}: Mock app running the module standalone - -}} -\keyword{mock} diff --git a/man/mock_wfphm.Rd b/man/mock_wfphm.Rd deleted file mode 100644 index 06444c6..0000000 --- a/man/mock_wfphm.Rd +++ /dev/null @@ -1,87 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mock_wfphm.R -\name{mock_wfphm} -\alias{mock_wfphm} -\alias{mock_wfphm_mm_app} -\alias{mock_app_wfphm2} -\alias{mock_app_hmcat} -\alias{mock_app_hmcont} -\alias{mock_app_hmpar} -\alias{mock_app_wf} -\alias{mock_app_wfphm} -\title{Mock functions} -\usage{ -mock_wfphm_mm_app() - -mock_app_wfphm2( - dry_run = FALSE, - update_query_string = TRUE, - srv_defaults = list(), - ui_defaults = list() -) - -mock_app_hmcat( - dry_run = FALSE, - update_query_string = TRUE, - srv_args = list(), - ui_args = list() -) - -mock_app_hmcont( - dry_run = FALSE, - update_query_string = TRUE, - srv_args = list(), - ui_args = list() -) - -mock_app_hmpar( - dry_run = FALSE, - update_query_string = TRUE, - srv_args = list(), - ui_args = list() -) - -mock_app_wf( - dry_run = FALSE, - update_query_string = TRUE, - srv_args = list(), - ui_args = list() -) - -mock_app_wfphm( - dry_run = FALSE, - update_query_string = TRUE, - srv_args = list(), - ui_args = list() -) -} -\arguments{ -\item{dry_run}{Return parameters used in the call} - -\item{update_query_string}{automatically update query string with app state} - -\item{ui_defaults, srv_defaults}{a list of values passed to the ui/server function} - -\item{ui_args, srv_args}{a list of arguments passed to the ui/server function.} -} -\description{ -Mock functions -} -\section{Functions}{ -\itemize{ -\item \code{mock_wfphm_mm_app()}: Mock app running the module inside dv.manager - -\item \code{mock_app_wfphm2()}: Mock app running the waterfall plus heatmap module - -\item \code{mock_app_hmcat()}: Mock app running categorical heatmap module - -\item \code{mock_app_hmcont()}: Mock app running continuous heatmap module - -\item \code{mock_app_hmpar()}: Mock app running parameter heatmap module - -\item \code{mock_app_wf()}: Mock app running waterfall module - -\item \code{mock_app_wfphm()}: Mock app running the waterfall plus heatmap module - -}} -\keyword{mock} diff --git a/man/mod_boxplot.Rd b/man/mod_boxplot.Rd deleted file mode 100644 index 168ff5c..0000000 --- a/man/mod_boxplot.Rd +++ /dev/null @@ -1,145 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_boxplot.R -\name{mod_boxplot} -\alias{mod_boxplot} -\alias{boxplot_UI} -\alias{boxplot_server} -\alias{mod_boxplot_papo} -\title{Boxplot module} -\usage{ -boxplot_UI(id) - -boxplot_server( - id, - bm_dataset, - group_dataset, - dataset_name = shiny::reactive(character(0)), - cat_var = "PARCAT", - par_var = "PARAM", - value_vars = c("AVAL", "CHG", "PCHG"), - visit_var = "AVISIT", - subjid_var = "SUBJID", - default_cat = NULL, - default_par = NULL, - default_visit = NULL, - default_value = NULL, - default_main_group = NULL, - default_sub_group = NULL, - default_page_group = NULL, - on_sbj_click = function(x) { - } -) - -mod_boxplot( - module_id, - bm_dataset_name, - group_dataset_name, - receiver_id = NULL, - cat_var = "PARCAT", - par_var = "PARAM", - value_vars = c("AVAL", "CHG", "PCHG"), - visit_var = "AVISIT", - subjid_var = "SUBJID", - default_cat = NULL, - default_par = NULL, - default_visit = NULL, - default_value = NULL, - default_main_group = NULL, - default_sub_group = NULL, - default_page_group = NULL, - server_wrapper_func = function(x) list(subj_id = x) -) - -mod_boxplot_papo(...) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{bm_dataset, group_dataset}{\verb{[data.frame()]} - -Dataframes as described in the \verb{Input dataframes} section} - -\item{dataset_name}{\verb{[shiny::reactive(*)]} - -a reactive indicating when the dataset has possibly changed its columns} - -\item{cat_var, par_var, visit_var, }{\verb{[character(1)]} - -Columns from \code{bm_dataset} that correspond to the parameter category, parameter and visit} - -\item{value_vars}{\verb{[character(n)]} - -Columns from \code{bm_dataset} that correspond to values of the parameters} - -\item{subjid_var}{\verb{[character(1)]} - -Column corresponding to subject ID} - -\item{default_cat, default_par, default_visit, default_value, default_main_group, default_sub_group, default_page_group}{\verb{[character(1)|NULL]} - -Default values for the selectors} - -\item{on_sbj_click}{\verb{[function()]} - -Function to invoke when a subject is clicked in the single subject listing} - -\item{module_id}{\verb{[character(1)]} - -Module Shiny id} - -\item{bm_dataset_name, group_dataset_name}{\verb{[character(1)]} - -Name of the dataset} - -\item{receiver_id}{\verb{[character(1)]} - -Shiny ID of the module receiving the selected subject ID in the data listing. This ID must -be present in the app or be NULL.} - -\item{server_wrapper_func}{\verb{[function()]} - -A function that will be applied to the server returned value. Its default value will work for the current cases.} -} -\description{ -\code{mod_boxplot} is a Shiny module prepared to display data with boxplot charts with different levels of grouping. -It also includes a set of listings with information about the population, distribution and statistical comparisons. - -\figure{mod_boxplot.png} - -\subsection{Input dataframes:}{ -\subsection{bm_dataset}{ - -It expects a dataset similar to -https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192 , -1 record per subject per parameter per analysis visit. - -It must contain, at least, the columns passed in the parameters, \code{subjid_var}, \code{cat_var}, \code{par_var}, -\code{visit_var} and \code{value_vars}. The values of these variables are as described -in the CDISC standard for the variables USUBJID, PARCAT, PARAM, AVISIT and AVAL. -} - -\subsection{group_dataset}{ - -It expects a dataset with an structure similar to -https://www.cdisc.org/kb/examples/adam-subject-level-analysis-adsl-dataset-80283806 , -one record per subject. - -It must contain, at least, the column passed in the parameter, \code{subjid_var}. -} - -} -} -\details{ -\code{mod_boxplot_papo} is a deprecated function that was required to use the jumping feature in combination -with \code{dv.papo} but is no longer required. The function is still available for compatibility reasons. -} -\section{Functions}{ -\itemize{ -\item \code{boxplot_UI()}: UI - -\item \code{boxplot_server()}: Server - -\item \code{mod_boxplot_papo()}: Boxplot wrapper when its output is fed into papo module - -}} -\keyword{main} diff --git a/man/mod_corr_hm.Rd b/man/mod_corr_hm.Rd deleted file mode 100644 index 832a03b..0000000 --- a/man/mod_corr_hm.Rd +++ /dev/null @@ -1,101 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_corr_hm.R -\name{mod_corr_hm} -\alias{mod_corr_hm} -\alias{corr_hm_UI} -\alias{corr_hm_server} -\title{Correlation Heatmap module} -\usage{ -corr_hm_UI( - id, - default_cat = NULL, - default_par = NULL, - default_visit = NULL, - default_corr_method = NULL -) - -corr_hm_server( - id, - bm_dataset, - subjid_var = "SUBJID", - cat_var = "PARCAT", - par_var = "PARAM", - visit_var = "AVISIT", - value_vars = c("AVAL", "PCHG"), - default_value = NULL -) - -mod_corr_hm( - module_id, - bm_dataset_name, - subjid_var = "SUBJID", - cat_var = "PARCAT", - par_var = "PARAM", - visit_var = "AVISIT", - value_vars = "AVAL", - default_cat = NULL, - default_par = NULL, - default_visit = NULL, - default_value = NULL -) -} -\arguments{ -\item{id}{\verb{[character(1)]} - -Shiny ID} - -\item{default_cat}{Default selected categories} - -\item{default_par}{Default selected parameters} - -\item{default_visit}{Default selected visits} - -\item{default_corr_method}{Name of default correlation method} - -\item{bm_dataset}{\verb{[data.frame()]} - -An ADBM-like dataset similar in structure to the one in -\href{https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192}{this example}, -with one record per subject per parameter per analysis visit. - -It should have, at least, the columns specified by the parameters \code{subjid_var}, \code{cat_var}, -\code{par_var}, \code{visit_var} and \code{value_vars}. -The semantics of these columns are as described in the CDISC standard for variables -USUBJID, PARCAT, PARAM, AVISIT and AVAL, respectively.} - -\item{subjid_var}{\verb{[character(1)]} - -Column corresponding to the subject ID} - -\item{cat_var, par_var, visit_var}{\verb{[character(1)]} - -Columns from \code{bm_dataset} that correspond to the parameter category, parameter and visit} - -\item{value_vars}{\verb{[character(n)]} - -Columns from \code{bm_dataset} that correspond to values of the parameters} - -\item{default_value}{\verb{[character(1)|NULL]} - -Default values for the selectors} - -\item{module_id}{Shiny ID \verb{[character(1)]} - -Module identifier} - -\item{bm_dataset_name}{\verb{[character(1)]} - -Biomarker dataset name} -} -\description{ -Display a heatmap of correlation coefficients (Pearson, Spearman) along with confidence intervals -and p-values between dataset parameters over a single visit. -} -\section{Functions}{ -\itemize{ -\item \code{corr_hm_UI()}: UI - -\item \code{corr_hm_server()}: Server - -}} -\keyword{main} diff --git a/man/mod_forest.Rd b/man/mod_forest.Rd deleted file mode 100644 index 4e7cc63..0000000 --- a/man/mod_forest.Rd +++ /dev/null @@ -1,154 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_forest.R -\name{mod_forest} -\alias{mod_forest} -\alias{forest_UI} -\alias{forest_server} -\title{Forest plot module} -\usage{ -forest_UI( - id, - numeric_numeric_function_names = character(0), - numeric_factor_function_names = character(0), - default_function = NULL -) - -forest_server( - id, - bm_dataset, - group_dataset, - dataset_name = shiny::reactive(character(0)), - numeric_numeric_functions = list(), - numeric_factor_functions = list(), - subjid_var = "SUBJID", - cat_var = "PARCAT", - par_var = "PARAM", - visit_var = "AVISIT", - value_vars = c("AVAL", "PCHG"), - default_cat = NULL, - default_par = NULL, - default_visit = NULL, - default_value = NULL, - default_var = NULL, - default_group = NULL, - default_categorical_A = NULL, - default_categorical_B = NULL -) - -mod_forest( - module_id, - bm_dataset_name, - group_dataset_name, - numeric_numeric_functions = list(`Pearson Correlation` = - dv.explorer.parameter::pearson_correlation, `Spearman Correlation` = - dv.explorer.parameter::spearman_correlation), - numeric_factor_functions = list(`Odds Ratio` = dv.explorer.parameter::odds_ratio), - subjid_var = "SUBJID", - cat_var = "PARCAT", - par_var = "PARAM", - visit_var = "AVISIT", - value_vars = c("AVAL", "PCHG"), - default_cat = NULL, - default_par = NULL, - default_visit = NULL, - default_value = NULL, - default_var = NULL, - default_group = NULL, - default_categorical_A = NULL, - default_categorical_B = NULL -) -} -\arguments{ -\item{id}{\verb{[character(1)]} - -Shiny ID} - -\item{numeric_numeric_function_names, numeric_factor_function_names}{\verb{[character(1)]} - -Vectors of names of functions passed as \code{numeric_numeric_functions} and \code{numeric_factor_functions} -to \code{forest_server}} - -\item{default_function}{\verb{[character(1)]} - -Default function} - -\item{bm_dataset}{\verb{[data.frame()]} - -An ADBM-like dataset similar in structure to the one in -\href{https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192}{this example}, -with one record per subject per parameter per analysis visit. - -It should have, at least, the columns specified by the parameters \code{subjid_var}, \code{cat_var}, -\code{par_var}, \code{visit_var} and \code{value_vars}. -The semantics of these columns are as described in the CDISC standard for variables -USUBJID, PARCAT, PARAM, AVISIT and AVAL, respectively.} - -\item{group_dataset}{\verb{[data.frame()]} - -An ADSL-like dataset similar in structure to the one in -\href{https://www.cdisc.org/kb/examples/adam-subject-level-analysis-adsl-dataset-80283806}{this example}, -with one record per subject. - -It should contain, at least, the column specified by the parameter \code{subjid_var}.} - -\item{dataset_name}{\verb{[shiny::reactive(*)]} - -A reactive that indicates a possible change in the column structure of any of the two datasets} - -\item{numeric_numeric_functions, numeric_factor_functions}{\verb{[function(n)]} - -Named lists of functions. Each function needs to take two parameters and produce a list of four numbers -with the following names: -\itemize{ -\item result, CI_lower_limit, CI_upper_limit and p_value -} - -The module will offer the functions as part of its interface and will run each function if selected. - -The values returned by the functions are be captured on the output table and are also displayed -as part of the forest plot. - -\code{numeric_numeric_functions} take two numeric parameters (e.g. \code{dv.explorer.parameter::pearson_correlation}) -and \code{numeric_factor_functions} should accept a numeric first parameter and a categorical (factor) second parameter -(e.g. \code{dv.explorer.parameter::odds_ratio}).} - -\item{subjid_var}{\verb{[character(1)]} - -Column corresponding to the subject ID} - -\item{cat_var, par_var, visit_var}{\verb{[character(1)]} - -Columns from \code{bm_dataset} that correspond to the parameter category, parameter and visit} - -\item{value_vars}{\verb{[character(n)]} - -Columns from \code{bm_dataset} that correspond to values of the parameters} - -\item{default_cat, default_par, default_visit, default_value}{\verb{[character(1)|NULL]} - -Default values for the selectors} - -\item{default_var, default_group, default_categorical_A, default_categorical_B}{\verb{[character(1)|NULL]} - -Default values for the selectors} - -\item{module_id}{Shiny ID \verb{[character(1)]} - -Module identifier} - -\item{bm_dataset_name, group_dataset_name}{\verb{[character(1)]} - -Dataset names} -} -\description{ -Display a hybrid table/forest plot of arbitrary statistics (correlations, odds ratios, ...) -computed on dataset parameters over a single visit. -} -\section{Functions}{ -\itemize{ -\item \code{forest_UI()}: UI - -\item \code{forest_server()}: Server - -}} -\keyword{main} diff --git a/man/mod_lineplot.Rd b/man/mod_lineplot.Rd deleted file mode 100644 index 8e123d0..0000000 --- a/man/mod_lineplot.Rd +++ /dev/null @@ -1,179 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_lineplot.R -\name{lineplot_UI} -\alias{lineplot_UI} -\alias{lineplot_server} -\alias{mod_lineplot} -\title{Line plot module} -\usage{ -lineplot_UI(id) - -lineplot_server( - id, - bm_dataset, - group_dataset, - summary_fns = list(Mean = lp_mean_summary_fns, Median = lp_median_summary_fns), - subjid_var = "SUBJID", - cat_var = "PARCAT", - par_var = "PARAM", - visit_vars = c("AVISIT"), - cdisc_visit_vars = character(0), - value_vars = c("AVAL", "PCHG"), - additional_listing_vars = character(0), - ref_line_vars = character(0), - on_sbj_click = NULL, - default_centrality_fn = NULL, - default_dispersion_fn = NULL, - default_cat = NULL, - default_par = NULL, - default_val = NULL, - default_visit_var = NULL, - default_visit_val = NULL, - default_main_group = NULL, - default_sub_group = NULL, - default_transparency = 1, - default_y_axis_projection = "Linear" -) - -mod_lineplot( - module_id, - bm_dataset_name, - group_dataset_name, - receiver_id = NULL, - summary_fns = list(Mean = lp_mean_summary_fns, Median = lp_median_summary_fns), - subjid_var = "SUBJID", - cat_var = "PARCAT", - par_var = "PARAM", - visit_vars = c("AVISIT"), - cdisc_visit_vars = character(0), - value_vars = c("AVAL", "PCHG"), - additional_listing_vars = character(0), - ref_line_vars = character(0), - default_centrality_fn = NULL, - default_dispersion_fn = NULL, - default_cat = NULL, - default_par = NULL, - default_val = NULL, - default_visit_var = NULL, - default_visit_val = NULL, - default_main_group = NULL, - default_sub_group = NULL, - default_transparency = 1, - default_y_axis_projection = "Linear" -) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{bm_dataset}{\verb{[data.frame()]} - -An ADBM-like dataset similar in structure to the one in -\href{https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192}{this example}, -with one record per subject per parameter per analysis visit. - -It should have, at least, the columns specified by the parameters \code{subjid_var}, \code{cat_var}, -\code{par_var}, \code{visit_vars} and \code{value_vars}. -The semantics of these columns are as described in the CDISC standard for variables -USUBJID, PARCAT, PARAM, AVISIT and AVAL, respectively. - -Optional columns specified by \code{ref_line_vars} should contain the same numeric value for all -records of the same parameter.} - -\item{group_dataset}{\verb{[data.frame()]} - -An ADSL-like dataset similar in structure to the one in -\href{https://www.cdisc.org/kb/examples/adam-subject-level-analysis-adsl-dataset-80283806}{this example}, -with one record per subject. - -It should contain, at least, the column specified by the parameter \code{subjid_var}.} - -\item{summary_fns}{\verb{[list()]} - -Each element of this named list contains a summary function (e.g. a mean) and a collection of dispersion functions -(e.g. standard deviation) defining ranges around the values returned by the summary function. - -The structure of each element is then a named list with the following elements: -\itemize{ -\item \code{fn}: Function that takes a numeric vector as its sole parameter and produces a scalar number. -\item \code{dispersion}: Named list of pairs functions that return the \emph{top} and \emph{bottom} dispersion ranges. They also take -a numeric vector as input and return a single numeric scalar -\item \code{y_prefix}: Prefix that will be prepended the Y axis label of the generated plot -} - -For an example, see \code{dv.explorer.parameter::lp_mean_summary_fns}.} - -\item{subjid_var}{\verb{[character(1)]} - -Column corresponding to the subject ID} - -\item{cat_var, par_var, visit_vars}{\verb{[character(1)]} - -Columns from \code{bm_dataset} that correspond to the parameter category, parameter and visit} - -\item{cdisc_visit_vars}{\verb{[character(1)]} - -Column from \code{bm_dataset} that correspond to the parameter visit and is interpreted as a CDISC -Visit Days (skipping day 0; jumping from value -1 to value 1 in the X axis)} - -\item{value_vars}{\verb{[character(n)]} - -Columns from \code{bm_dataset} that correspond to values of the parameters} - -\item{additional_listing_vars}{\verb{[character(n)]} - -Columns from \code{bm_dataset} that will be appended to the single-subject listing} - -\item{ref_line_vars}{\verb{[character(n)]} - -Columns for \code{bm_dataset} specifying reference values for parameters} - -\item{on_sbj_click}{\verb{[function()]} - -Function to invoke when a subject is clicked in the single-subject listing} - -\item{default_cat, default_par, default_visit_var, default_main_group}{\verb{[character(1)|NULL]} - -Default values for the selectors} - -\item{default_visit_val}{\verb{list([character(n)|numeric(n)])} - -Named list of default values associated to specific \code{visit_var}s, e.g. -\code{default_visit_val = list(VISIT = c('VISIT1', 'VISIT2'), AVISITN = c(1, 2))}} - -\item{default_sub_group, default_val, default_centrality_fn, default_dispersion_fn}{\verb{[character(1)|NULL]} - -Default values for the selectors} - -\item{default_transparency}{\verb{[numeric(1)]} - -Default values for the selectors} - -\item{default_y_axis_projection}{\verb{["Linear"|"Logarithmic"]} - -Default projection for the Y axis} - -\item{module_id}{Shiny ID \verb{[character(1)]} - -Module identifier} - -\item{bm_dataset_name, group_dataset_name}{\verb{[character(1)]} - -Dataset names} - -\item{receiver_id}{\verb{[character(1)]} - -Shiny ID of the module receiving the selected subject ID in the single subject listing. This ID must -be present in the app or be NULL.} -} -\description{ -Display line plots of raw or summary data over time. Summaries include measures of central tendency -(mean, median) and optional deviation and confidence estimators. -} -\section{Functions}{ -\itemize{ -\item \code{lineplot_UI()}: UI - -\item \code{lineplot_server()}: Server - -}} -\keyword{main} diff --git a/man/mod_roc.Rd b/man/mod_roc.Rd deleted file mode 100644 index e291885..0000000 --- a/man/mod_roc.Rd +++ /dev/null @@ -1,123 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{mod_roc} -\alias{mod_roc} -\alias{roc_UI} -\alias{roc_server} -\title{ROC module} -\usage{ -roc_UI(id) - -roc_server( - id, - pred_dataset, - resp_dataset, - group_dataset, - dataset_name = shiny::reactive(character(0)), - pred_cat_var = "PARCAT", - pred_par_var = "PARAM", - pred_value_vars = c("AVAL", "PCHG"), - pred_visit_var = "AVISIT", - resp_cat_var = "PARCAT", - resp_par_var = "PARAM", - resp_value_vars = c("CHG1", "CHG2"), - resp_visit_var = "AVISIT", - subjid_var = "SUBJID", - compute_roc_fn = compute_roc_data, - compute_metric_fn = compute_metric_data -) - -mod_roc( - module_id, - pred_dataset_name, - resp_dataset_name, - group_dataset_name, - pred_cat_var = "PARCAT", - pred_par_var = "PARAM", - pred_value_vars = c("AVAL", "PCHG"), - pred_visit_var = "AVISIT", - resp_cat_var = "PARCAT", - resp_par_var = "PARAM", - resp_value_vars = c("CHG1", "CHG2"), - resp_visit_var = "AVISIT", - subjid_var = "SUBJID", - compute_roc_fn = compute_roc_data, - compute_metric_fn = compute_metric_data -) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{pred_dataset, resp_dataset, group_dataset}{\verb{[data.frame()]} - -Dataframes as described in the \verb{Input dataframes} section} - -\item{dataset_name}{\verb{[shiny::reactive(*)]} - -a reactive indicating when the dataset has possibly changed its columns} - -\item{pred_cat_var, pred_par_var, pred_visit_var, resp_cat_var, resp_par_var, resp_visit_var}{\verb{[character(1)]} - -Columns from \code{pred_dataset}/\code{resp_dataset} that correspond to the parameter category, parameter and visit} - -\item{pred_value_vars, resp_value_vars}{\verb{[character(n)]} - -Columns from \code{pred_dataset},\code{resp_dataset} that correspond to values of the parameters} - -\item{subjid_var}{\verb{[character(1)]} - -Column corresponding to subject ID} - -\item{compute_roc_fn, compute_metric_fn}{\verb{[function()]} - -Functions used to compute the ROC and metric analysis, please view the corresponding vignette for more details.} - -\item{module_id}{\verb{[character(1)]} - -Module identificator} - -\item{pred_dataset_name, resp_dataset_name, group_dataset_name}{Name of the dataset} -} -\description{ -\subsection{Input dataframes:}{ -\subsection{pred_dataset}{ - -It expects a dataset similar to -https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192 , -1 record per subject per parameter per analysis visit - -It expects, at least, the columns passed in the parameters, \code{subjid_var}, \code{pred_cat_var}, \code{pred_par_var}, -\code{pred_visit_var} and \code{pred_value_var}. The values of these variables are as described -in the CDISC standard for the variables USUBJID, PARCAT, PARAM, AVISIT and AVAL. -} - -\subsection{resp_dataset}{ - -It expects a dataset similar to -https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192 - -It expects, at least, the columns passed in the parameters, \code{subjid_var}, \code{resp_cat_var}, -\code{resp_par_var}, \code{resp_visit_var} and \code{resp_value_var}. -The values of these variables are as described -in the CDISC standard for the variables USUBJID, PARCAT, PARAM, AVISIT and AVAL. -} - -\subsection{group_dataset}{ - -It expects a dataset with an structure similar to -https://www.cdisc.org/kb/examples/adam-subject-level-analysis-adsl-dataset-80283806 , -one record per subject - -It expects to contain, at least, \code{subjid_var} -} - -} -} -\section{Functions}{ -\itemize{ -\item \code{roc_UI()}: UI - -\item \code{roc_server()}: Server - -}} -\keyword{main} diff --git a/man/mod_scatterplot.Rd b/man/mod_scatterplot.Rd deleted file mode 100644 index 6cc3cac..0000000 --- a/man/mod_scatterplot.Rd +++ /dev/null @@ -1,138 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_scatter.R -\name{mod_scatterplot} -\alias{mod_scatterplot} -\alias{scatterplot_UI} -\alias{scatterplot_server} -\title{Scatterplot module} -\usage{ -scatterplot_UI(id) - -scatterplot_server( - id, - bm_dataset, - group_dataset, - dataset_name = shiny::reactive(character(0)), - cat_var = "PARCAT", - par_var = "PARAM", - value_vars = c("AVAL", "PCHG"), - visit_var = "AVISIT", - subjid_var = "SUBJID", - default_x_cat = NULL, - default_x_par = NULL, - default_x_value = NULL, - default_x_visit = NULL, - default_y_cat = NULL, - default_y_par = NULL, - default_y_value = NULL, - default_y_visit = NULL, - default_group = NULL, - default_color = NULL, - compute_lm_cor_fn = sp_compute_lm_cor_default -) - -mod_scatterplot( - module_id, - bm_dataset_name, - group_dataset_name, - cat_var = "PARCAT", - par_var = "PARAM", - value_vars = c("AVAL", "PCHG"), - visit_var = "AVISIT", - subjid_var = "SUBJID", - default_x_cat = NULL, - default_x_par = NULL, - default_x_value = NULL, - default_x_visit = NULL, - default_y_cat = NULL, - default_y_par = NULL, - default_y_value = NULL, - default_y_visit = NULL, - default_group = NULL, - default_color = NULL, - compute_lm_cor_fn = sp_compute_lm_cor_default -) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{bm_dataset, group_dataset}{\verb{[data.frame()]} - -Dataframes as described in the \verb{Input dataframes} section} - -\item{dataset_name}{\verb{[shiny::reactive(*)]} - -a reactive indicating when the dataset has possibly changed its columns} - -\item{cat_var, par_var, visit_var}{\verb{[character(1)]} - -Columns from \code{bm_dataset} that correspond to the parameter category, parameter and visit} - -\item{value_vars}{\verb{[character(n)]} - -Columns from \code{bm_dataset} that correspond to values of the parameters} - -\item{subjid_var}{\verb{[character(1)]} - -Column corresponding to subject ID} - -\item{default_x_cat, default_x_par, default_x_visit, default_x_value, default_y_cat, default_y_par}{\verb{[character(1)|NULL]} - -Default values for the selectors} - -\item{default_y_visit, default_y_value, default_group, default_color}{\verb{[character(1)|NULL]} - -Default values for the selectors} - -\item{compute_lm_cor_fn}{\verb{[function()]} - -Function used to compute the linear regression model and correlation statistics, -please view the corresponding vignette for more details.} - -\item{module_id}{\verb{[character(1)]} - -Module Shiny id} - -\item{bm_dataset_name, group_dataset_name}{\verb{[character(1)]} - -Name of the dataset} -} -\description{ -\code{mod_scatterplot} is a Shiny module prepared to display a scatterplot of two biomarkers with different levels of -grouping. -It also includes a set of listings with information about the population and the regression and correlation -estimates. - -\figure{mod_scatterplot.png} - -\subsection{Input dataframes:}{ -\subsection{bm_dataset}{ - -It expects a dataset similar to -https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192 , -1 record per subject per parameter per analysis visit - -It expects, at least, the columns passed in the parameters, \code{subjid_var}, \code{cat_var}, \code{par_var}, -\code{visit_var} and \code{value_var}. The values of these variables are as described -in the CDISC standard for the variables USUBJID, PARCAT, PARAM, AVISIT and AVAL. -} - -\subsection{group_dataset}{ - -It expects a dataset with an structure similar to -https://www.cdisc.org/kb/examples/adam-subject-level-analysis-adsl-dataset-80283806 , -one record per subject - -It expects to contain, at least, \code{subjid_var} -} - -} -} -\section{Functions}{ -\itemize{ -\item \code{scatterplot_UI()}: UI - -\item \code{scatterplot_server()}: Server - -}} -\keyword{main} diff --git a/man/mod_scatterplotmatrix.Rd b/man/mod_scatterplotmatrix.Rd deleted file mode 100644 index 56f20c8..0000000 --- a/man/mod_scatterplotmatrix.Rd +++ /dev/null @@ -1,115 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_scatter_matrix.R -\name{mod_scatterplotmatrix} -\alias{mod_scatterplotmatrix} -\alias{scatterplotmatrix_UI} -\alias{scatterplotmatrix_server} -\title{Matrix of scatterplots module} -\usage{ -scatterplotmatrix_UI(id) - -scatterplotmatrix_server( - id, - bm_dataset, - group_dataset, - dataset_name = shiny::reactive(character(0)), - cat_var = "PARCAT", - par_var = "PARAM", - value_vars = c("AVAL", "PCHG"), - visit_var = "AVISIT", - subjid_var = "SUBJID", - default_cat = NULL, - default_par = NULL, - default_visit = NULL, - default_value = NULL, - default_main_group = NULL -) - -mod_scatterplotmatrix( - module_id, - bm_dataset_name, - group_dataset_name, - cat_var = "PARCAT", - par_var = "PARAM", - value_vars = c("AVAL", "PCHG"), - visit_var = "AVISIT", - subjid_var = "SUBJID", - default_cat = NULL, - default_par = NULL, - default_visit = NULL, - default_value = NULL, - default_main_group = NULL -) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{bm_dataset, group_dataset}{\verb{[data.frame()]} - -Dataframes as described in the \verb{Input dataframes} section} - -\item{dataset_name}{\verb{[shiny::reactive(*)]} - -a reactive indicating when the dataset has possibly changed its columns} - -\item{cat_var, par_var, visit_var, }{\verb{[character(1)]} - -Columns from \code{bm_dataset} that correspond to the parameter category, parameter and visit} - -\item{value_vars}{\verb{[character(n)]} - -Columns from \code{bm_dataset} that correspond to values of the parameters} - -\item{subjid_var}{\verb{[character(1)]} - -Column corresponding to subject ID} - -\item{default_cat, default_par, default_visit, default_value, default_main_group}{\verb{[character(1)|NULL]} - -Default values for the selectors} - -\item{module_id}{\verb{[character(1)]} - -Module Shiny id} - -\item{bm_dataset_name, group_dataset_name}{\verb{[character(1)]} - -Name of the dataset} -} -\description{ -\code{mod_scatterplotmatrix} is a Shiny module prepared to display data in a matrix of scatterplots with different levels -of grouping. It also includes correlation stats. - -\figure{mod_scatterplotmatrix.png} - -\subsection{Input dataframes:}{ -\subsection{bm_dataset}{ - -It expects a dataset similar to -https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192 , -1 record per subject per parameter per analysis visit. - -It must contain, at least, the columns passed in the parameters, \code{subjid_var}, \code{cat_var}, \code{par_var}, -\code{visit_var} and \code{value_var}. The values of these variables are as described -in the CDISC standard for the variables USUBJID, PARCAT, PARAM, AVISIT and AVAL. -} - -\subsection{group_dataset}{ - -It expects a dataset with an structure similar to -https://www.cdisc.org/kb/examples/adam-subject-level-analysis-adsl-dataset-80283806 , -one record per subject. - -It must contain, at least, the column passed in the parameter, \code{subjid_var}. -} - -} -} -\section{Functions}{ -\itemize{ -\item \code{scatterplotmatrix_UI()}: UI - -\item \code{scatterplotmatrix_server()}: Server - -}} -\keyword{main} diff --git a/man/name_label_formatter.Rd b/man/name_label_formatter.Rd deleted file mode 100644 index 30af438..0000000 --- a/man/name_label_formatter.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-label.R -\name{name_label_formatter} -\alias{name_label_formatter} -\title{Renames a list to include its value in the name} -\usage{ -name_label_formatter(l) -} -\arguments{ -\item{l}{a named list} -} -\description{ -Renames a list to include its value in the name -} -\details{ -If value and name are equal the entry name is not modified. -These lists usually come from swap_names(rpl_nulls_name(get_lbl(dataset))) -} -\keyword{internal} diff --git a/man/outlier_container.Rd b/man/outlier_container.Rd deleted file mode 100644 index a77bba6..0000000 --- a/man/outlier_container.Rd +++ /dev/null @@ -1,43 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/imod_outliers.R -\name{outlier_container} -\alias{outlier_container} -\alias{outlier_container_UI} -\alias{outlier_container_server} -\alias{mock_outlier} -\title{A container for outlier selectors} -\usage{ -outlier_container_UI(id) - -outlier_container_server(id, choices) - -mock_outlier() -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{choices}{a list with the parameters for which we want to select outliers} -} -\value{ -A reactive containing a list with as many entries as choices are selected in the selector. Each of the -entries contain a list with two entries\code{ll} and \code{ul} as described in \link{outlier_selector}. -} -\description{ -A container for outlier selectors -} -\details{ -When a choice is deselected and selected again, it will retain its previous state. -} -\section{Functions}{ -\itemize{ -\item \code{outlier_container_UI()}: UI - -\item \code{outlier_container_server()}: server - -\item \code{mock_outlier()}: mock - -}} -\seealso{ -outlier_selector -} -\keyword{internal} diff --git a/man/outlier_selector.Rd b/man/outlier_selector.Rd deleted file mode 100644 index 055dafd..0000000 --- a/man/outlier_selector.Rd +++ /dev/null @@ -1,47 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/imod_outliers.R -\name{outlier_selector} -\alias{outlier_selector} -\alias{outlier_ui} -\alias{outlier_server} -\title{Single outlier selector} -\usage{ -outlier_ui(id, label, value_ll = "", value_ul = "") - -outlier_server(id) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{label}{label for the selectors} - -\item{value_ll}{an initial value for the lower limit} - -\item{value_ul}{an initial value for the upper limit} -} -\value{ -A reactive containing a list with two entries\code{ll} and \code{ul}. It returns either NA if the box is empty or the -result of applying as.numeric to the contents of the input box. It does not return NULL values. -} -\description{ -A selector composed by two rows containing: -\itemize{ -\item a \code{label} -\item two inline \link[shiny:textInput]{shiny::textInput} boxes for the upper and lower limit of the outliers -} -} -\details{ -The UI root element is a divisor which id attribute is equal to the \code{id} parameter. So it can be used -with \link[shiny:insertUI]{shiny::insertUI} and \link[shiny:insertUI]{shiny::removeUI} functions. -} -\section{Functions}{ -\itemize{ -\item \code{outlier_ui()}: UI - -\item \code{outlier_server()}: server - -}} -\seealso{ -outlier_container -} -\keyword{internal} diff --git a/man/pack_of_constants.Rd b/man/pack_of_constants.Rd deleted file mode 100644 index 1db999e..0000000 --- a/man/pack_of_constants.Rd +++ /dev/null @@ -1,46 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/aaa_preface.R -\name{pack_of_constants} -\alias{pack_of_constants} -\title{Build a collection of named constants} -\usage{ -pack_of_constants(...) -} -\arguments{ -\item{...}{Named parameters to be collected as constants} -} -\description{ -Build a collection of named constants -} -\details{ -Shiny uses strings as IDs to link UI and server elements. E.g: -foo_UI(id = ns("foo")) ... -foo_server(id = "foo") - -This pattern makes it easy for programmers to fall on the trap of modifying one instance of the string literal "foo" -without modifying the rest and be unaware of the problem until a bug is hit. It's also easy to mistakes uses of "foo" -as an identifier from other uses (text labels, ...) when, as it's often the case, the parameter is not explicitly -named. -One easy fix consists in using global variables instead of plain string literals. In the case of the previous -example, that would mean: -ID_FOO <- "foo" -foo_UI(ns(ID_FOO)) ... -foo_server(ID_FOO) - -That simple addition makes the purpose of ID_FOO clear and also fails gracefully when not all ID_FOO instances are -updated synchronously along a codebase. It has the drawback of polluting the global namespace with identifier -variables. That's easily solved by creating a container of constants, which is the purpose of this pack_of_constants -alias. -ID <- pack_of_constants(FOO = "foo", BAR = "bar") -ID$FOO -"foo" -ID$BA -Error in \verb{$.pack_of_constants}(ID, BA) : -Pack of constants "ID" does not contain "BA" - -The pack of constants is a plain named list that enforces that all elements have unique, non-null names. -It is tagged as an S3 object to override its extraction operators. - -The use of checkmate is unnecessary, but it's a Good Library(TM) and your module should rely on it anyways -} -\keyword{internal} diff --git a/man/pal_div_palette.Rd b/man/pal_div_palette.Rd deleted file mode 100644 index 1256041..0000000 --- a/man/pal_div_palette.Rd +++ /dev/null @@ -1,25 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-palettes.R -\name{pal_div_palette} -\alias{pal_div_palette} -\title{Returns a divergent palette to use with heatmap} -\usage{ -pal_div_palette(max, neut, min, colors) -} -\arguments{ -\item{max, neut, min}{the values to be associated with the extreme and central colors} - -\item{colors}{the palette colors - -max, neut, min the values to be associated with the extreme and central colors. If the palette contains more colors, -the values are interpolated.} -} -\value{ -Vector The names of the vector are hexadecimal colors -encoded as #rrggbb or #rrggbbaa (red, green, blue, alpha) and the values are the "z" values that -should be mapped to that color. -} -\description{ -Returns a divergent palette to use with heatmap -} -\keyword{internal} diff --git a/man/pal_get_cat_palette.Rd b/man/pal_get_cat_palette.Rd deleted file mode 100644 index a1049c8..0000000 --- a/man/pal_get_cat_palette.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-palettes.R -\name{pal_get_cat_palette} -\alias{pal_get_cat_palette} -\title{Returns a categorical palette to use with heatmap} -\usage{ -pal_get_cat_palette(d, colors) -} -\arguments{ -\item{d}{a vector containing the values to be colored} - -\item{colors}{the colors to be used. They will be recycled as needed.} -} -\value{ -Vector The names of the vector are hexadecimal colors -encoded as #rrggbb or #rrggbbaa (red, green, blue, alpha) and the values are the "z" values that -should be mapped to that color. -} -\description{ -Returns a categorical palette to use with heatmap -} -\keyword{internal} diff --git a/man/pal_get_cont_palette.Rd b/man/pal_get_cont_palette.Rd deleted file mode 100644 index f928f33..0000000 --- a/man/pal_get_cont_palette.Rd +++ /dev/null @@ -1,30 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-palettes.R -\name{pal_get_cont_palette} -\alias{pal_get_cont_palette} -\title{Returns a continuous palette to use with heatmap} -\usage{ -pal_get_cont_palette( - d, - seq_pos_colors = RColorBrewer::brewer.pal(9, name = "Reds"), - seq_neg_colors = rev(RColorBrewer::brewer.pal(9, name = "Blues")), - div_colors = rev(RColorBrewer::brewer.pal(11, name = "RdBu")), - zero_color = "rgb(242, 239, 238)" -) -} -\arguments{ -\item{d}{a vector containing the values to be colored} - -\item{seq_pos_colors, seq_neg_colors, div_colors, zero_color}{a palette for sequential positive, sequential -negative, divergent or all zeroes datasets. The zero_color expects a single color, all other expect an odd number of -colors. The divergent palette central color is considered the neutral and is always associated to 0.} -} -\value{ -Vector The names of the vector are hexadecimal colors -encoded as #rrggbb or #rrggbbaa (red, green, blue, alpha) and the values are the "z" values that -should be mapped to that color. -} -\description{ -Returns a continuous palette to use with heatmap -} -\keyword{internal} diff --git a/man/pal_get_scale_type_lim.Rd b/man/pal_get_scale_type_lim.Rd deleted file mode 100644 index 3635de4..0000000 --- a/man/pal_get_scale_type_lim.Rd +++ /dev/null @@ -1,35 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-palettes.R -\name{pal_get_scale_type_lim} -\alias{pal_get_scale_type_lim} -\title{Return the type of scale and its limits} -\usage{ -pal_get_scale_type_lim(d) -} -\arguments{ -\item{d}{the data from which the scale will be inferred} -} -\value{ -A list with the entries: -\subsection{type:}{ -\itemize{ -\item divergent: It has both positive, negative and 0 values -\item seq_positive: It has positive or 0 values -\item seq_negative: It has negative or 0 values -\item seq_positive: It has positive or 0 values -\item all_zero: It has only 0 values -} -} - -\subsection{lim:}{ -\itemize{ -\item If \strong{divergent}: c(-max_abs, 0, max_abs) when max_abs is the maximum absolute value of all data -\item If \strong{seq_positive} or \strong{seq_negative}: c(min(d), max(d)) when max_abs is the maximum absolute value of all data -\item if \strong{all_zerp}: c(0,0) -} -} -} -\description{ -Inferes the type of scale and its limits based on the the data -} -\keyword{internal} diff --git a/man/pal_seq_palette.Rd b/man/pal_seq_palette.Rd deleted file mode 100644 index a444d99..0000000 --- a/man/pal_seq_palette.Rd +++ /dev/null @@ -1,25 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-palettes.R -\name{pal_seq_palette} -\alias{pal_seq_palette} -\title{A sequential palette to use with heatmap} -\usage{ -pal_seq_palette(max, min, colors) -} -\arguments{ -\item{max, min}{the values to be associated with the extreme and colors} - -\item{colors}{the palette colors - -max, min the values are associated with the extreme colors. If the palette contains more colors, -the values are interpolated.} -} -\value{ -Vector The names of the vector are hexadecimal colors -encoded as #rrggbb or #rrggbbaa (red, green, blue, alpha) and the values are the "z" values that -should be mapped to that color. -} -\description{ -A sequential palette to use with heatmap -} -\keyword{internal} diff --git a/man/pal_zero_palette.Rd b/man/pal_zero_palette.Rd deleted file mode 100644 index 9a751d1..0000000 --- a/man/pal_zero_palette.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-palettes.R -\name{pal_zero_palette} -\alias{pal_zero_palette} -\title{Returns a palette with a single color} -\usage{ -pal_zero_palette(color) -} -\arguments{ -\item{color}{the color - -The palette always return two repeated entries} -} -\value{ -Vector The names of the vector are hexadecimal colors -encoded as #rrggbb or #rrggbbaa (red, green, blue, alpha) and the values are the "z" values that -should be mapped to that color. -} -\description{ -Returns a palette with a single color -} -\keyword{internal} diff --git a/man/parameter_UI.Rd b/man/parameter_UI.Rd deleted file mode 100644 index 8418c52..0000000 --- a/man/parameter_UI.Rd +++ /dev/null @@ -1,15 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-selectors.R -\name{parameter_UI} -\alias{parameter_UI} -\title{Selectors} -\usage{ -parameter_UI(id) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} -} -\description{ -Selectors -} -\keyword{internal} diff --git a/man/parse_ci.Rd b/man/parse_ci.Rd deleted file mode 100644 index 1d1f1eb..0000000 --- a/man/parse_ci.Rd +++ /dev/null @@ -1,17 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{parse_ci} -\alias{parse_ci} -\title{Split string with ; delimiters and transform to numeric} -\usage{ -parse_ci(str) -} -\arguments{ -\item{str}{\verb{[character(1)]} - -String to be split} -} -\description{ -Split string with ; delimiters and transform to numeric -} -\keyword{internal} diff --git a/man/possibly_set_lbls.Rd b/man/possibly_set_lbls.Rd deleted file mode 100644 index b5edeec..0000000 --- a/man/possibly_set_lbls.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-label.R -\name{possibly_set_lbls} -\alias{possibly_set_lbls} -\title{Set several labels in a dataframe} -\usage{ -possibly_set_lbls(df, lbls) -} -\arguments{ -\item{df}{a dataframe.} - -\item{lbls}{a named list. Each entry will have as name the name of a given column in df and as value the expected -label of the given column. If df has no column with the name of the entry, the entry is ignored.} -} -\value{ -A dataframe with the set labels -} -\description{ -Set several labels in a dataframe -} -\keyword{internal} diff --git a/man/rename_with_list.Rd b/man/rename_with_list.Rd deleted file mode 100644 index e8e8878..0000000 --- a/man/rename_with_list.Rd +++ /dev/null @@ -1,26 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/common_logic.R -\name{rename_with_list} -\alias{rename_with_list} -\title{Rename a data frame with a list/character vector of new names} -\usage{ -rename_with_list(ds, rename_vec) -} -\arguments{ -\item{ds}{\code{data.frame()} - -A dataframe} - -\item{rename_vec}{\code{named.list()|named.character()} - -A named list or character vector with the new names} -} -\value{ -\code{data.frame()} - -Returns renamed \code{ds} -} -\description{ -The names are the old names and the values are the new names. \code{rename_vec} names not present in \code{ds} are ignored. -} -\keyword{internal} diff --git a/man/resolve_or_return.Rd b/man/resolve_or_return.Rd deleted file mode 100644 index 94a2a75..0000000 --- a/man/resolve_or_return.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-misc.R -\name{resolve_or_return} -\alias{resolve_or_return} -\title{Return the value of a reactive or regular value} -\usage{ -resolve_or_return(r) -} -\arguments{ -\item{r}{a variable which can be regular or reactive} -} -\value{ -the value of the variable or the reactive -} -\description{ -Return the value of a reactive or regular value -} -\details{ -It does not work with metaReactives. -} -\keyword{internal} diff --git a/man/rlang_assign.Rd b/man/rlang_assign.Rd deleted file mode 100644 index 630cbc4..0000000 --- a/man/rlang_assign.Rd +++ /dev/null @@ -1,11 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-importFrom.R -\name{:=} -\alias{:=} -\title{.data object from dplyr} -\description{ -.data object from dplyr - -.data object from dplyr -} -\keyword{internal} diff --git a/man/roc_subset_data.Rd b/man/roc_subset_data.Rd deleted file mode 100644 index 34eb090..0000000 --- a/man/roc_subset_data.Rd +++ /dev/null @@ -1,156 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_roc.R -\name{roc_subset_data} -\alias{roc_subset_data} -\title{Subset input datasets} -\usage{ -roc_subset_data( - pred_cat, - pred_par, - pred_val_col, - pred_visit, - resp_cat, - resp_par, - resp_val_col, - resp_visit, - group_col, - pred_ds, - resp_ds, - group_ds, - subj_col, - pred_cat_col, - pred_par_col, - pred_vis_col, - resp_cat_col, - resp_par_col, - resp_vis_col -) -} -\arguments{ -\item{pred_par, pred_cat}{\verb{[character*ish*(n)]} - -Values from \code{pred_par_col} and \code{pred_cat_col} to be subset} - -\item{pred_val_col}{\verb{[character*ish*(1)]} - -Column containing values for the predictor parameters} - -\item{pred_visit}{\verb{[character*ish*(1)]} - -Values from \code{pred_vis_col} to be subset} - -\item{resp_par, resp_cat}{\verb{[character*ish*(1)]} - -Values from \code{resp_par_col} and \code{resp_cat_col} to be subset} - -\item{resp_val_col}{\verb{[character*ish*(1)]} - -Column containing values for the response parameter} - -\item{resp_visit}{\verb{[character*ish*(1)]} - -Values from \code{resp_vis_col} to be subset} - -\item{group_col}{\verb{[character*ish*(1)]} - -Column to group the data by. \code{"None"} for no grouping.} - -\item{pred_ds, resp_ds, group_ds}{\verb{[data.frame()]} - -Data frames for predictors/responses and groupings, see section \emph{Input dataframes}} - -\item{subj_col, pred_par_col, pred_cat_col, pred_vis_col, resp_cat_col, resp_par_col, resp_vis_col}{\verb{[character(1)]} - -Column for predictor/response category/parameter/visit. \code{subj_col} must be a factor.} -} -\value{ -\verb{[data.frame()]} - -With columns: -\itemize{ -\item \code{subject_id} \verb{[factor()]}: Subject ID -\item \code{predictor_parameter} \verb{[factor()]}: Predictor parameter name. -\item \code{response_parameter} \verb{[factor()]}: Response parameter value. -\item \code{group} \verb{[factor()]}: An optional column for the grouping value (if group is specified). -\item \code{predictor_value} \verb{[numeric()]}: Predictor parameter Value -\item \code{response_value} \verb{[factor()]}: Response parameter Value. -} - -Additionally: -\itemize{ -\item \code{predictor_parameter} has a label attribute: \emph{Parameter} -\item \code{response_parameter} has a label attribute: \emph{Response} -\item \code{group} has the same label attribute as in the original dataset, if available, otherwise \code{group_col}. -} -} -\description{ -This functions prepares the basic input for the rest of dv.explorer.parameter functions. - -It subsets and joins the datasets based on the predictor/response category/parameter/visit and group selections. -} -\details{ -\itemize{ -\item All columns but \code{predictor_value} are coherced into factors if they are not factors already. -\item If at least one parameter name appears under several selected categories, -parameter names and categories will be pasted together. -\item \code{predictor_parameter} is releveled so all extra levels not present in the selection are dropped. -Levels are ordered according to \code{pred_par} as long as a parameter name appears does not appear -under more than one selected categories. -} -} -\section{Input dataframes}{ - -\subsection{pred_dataset}{ - -It expects a dataset similar to -https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192 , -1 record per subject per parameter per analysis visit - -It expects, at least, the columns passed in the parameters, -\code{subj_col}, \code{pred_cat_col}, \code{pred_par_col}, \code{pred_vis_col} and \code{pred_val}. -The values of these variables are as described -in the CDISC standard for the variables USUBJID, PARCAT, PARAM, AVISIT and AVAL. -} - -\subsection{resp_dataset}{ - -It expects a dataset similar to -https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192 - -It expects, at least, the columns passed in the parameters, -\code{subj_col}, \code{resp_cat_col}, \code{resp_par_col}, \code{resp_vis_col} and \code{resp_val}. -The values of these variables are as described -in the CDISC standard for the variables USUBJID, PARCAT, PARAM, AVISIT and AVAL. -} - -\subsection{group_dataset}{ - -It expects a dataset with an structure similar to -https://www.cdisc.org/kb/examples/adam-subject-level-analysis-adsl-dataset-80283806 , one record per subject - -It expects to contain, at least, \code{subj_col} and \code{group_col} -} -} - -\section{Internal checks}{ - -\subsection{Shiny validation errors:}{ -\itemize{ -\item After selection it checks that: -\itemize{ -\item Combination subject category parameter visit are unique for the predictor and response datasets -\item If grouped, that subject_id is unique for the selected group -\item The final selection contains at least one row -\item The response value is binary. Empty values are not considered for this check. -} -} -} - -\subsection{Warnings:}{ -\itemize{ -\item Subjects in the selection have an empty response value -} -} -} - -\keyword{internal} diff --git a/man/rpl_nulls_name.Rd b/man/rpl_nulls_name.Rd deleted file mode 100644 index b96963c..0000000 --- a/man/rpl_nulls_name.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-label.R -\name{rpl_nulls_name} -\alias{rpl_nulls_name} -\title{Replace NULL values in a list with the name of the entry} -\usage{ -rpl_nulls_name(l) -} -\arguments{ -\item{l}{a named list.} -} -\value{ -A named list. -} -\description{ -If one of the values is NULL it will be replaced with the name of the NULL entry. -} -\details{ -The input of this functions is usually the output of a \code{get_lbls} call. -} -\keyword{internal} diff --git a/man/set_lbl.Rd b/man/set_lbl.Rd deleted file mode 100644 index 3970ff1..0000000 --- a/man/set_lbl.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-label.R -\name{set_lbl} -\alias{set_lbl} -\title{Set the label attribute of a column in a data frame} -\usage{ -set_lbl(df, var, lbl) -} -\arguments{ -\item{df}{a dataframe.} - -\item{var}{a column of the dataframe} - -\item{lbl}{the label} -} -\value{ -the dataframe with the replaced label -} -\description{ -Set the label attribute of a column in a data frame -} -\keyword{misc} diff --git a/man/set_lbls.Rd b/man/set_lbls.Rd deleted file mode 100644 index 352aa05..0000000 --- a/man/set_lbls.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-label.R -\name{set_lbls} -\alias{set_lbls} -\title{Set several labels in a dataframe} -\usage{ -set_lbls(df, lbls) -} -\arguments{ -\item{df}{a dataframe.} - -\item{lbls}{a named list. Each entry will have as name the name of a given column in df and as value the expected -label of the given column.} -} -\value{ -A dataframe with the set labels -} -\description{ -Set several labels in a dataframe -} -\keyword{misc} diff --git a/man/sp_subset_data.Rd b/man/sp_subset_data.Rd deleted file mode 100644 index 9691768..0000000 --- a/man/sp_subset_data.Rd +++ /dev/null @@ -1,76 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_scatter.R -\name{sp_subset_data} -\alias{sp_subset_data} -\title{Subset datasets for scatterplot} -\usage{ -sp_subset_data( - x_cat, - y_cat, - cat_col, - x_par, - y_par, - par_col, - x_val_col, - y_val_col, - x_vis, - y_vis, - vis_col, - group_vect, - bm_ds, - group_ds, - subj_col -) -} -\arguments{ -\item{x_cat, y_cat, x_par, y_par, x_val_col, y_val_col, x_vis, y_vis}{Are similar to those without prefix in \code{\link[=subset_bds_param]{subset_bds_param()}}.} - -\item{group_vect}{\verb{[named(character(n))]} - -Columns to be subset and renamed.} - -\item{bm_ds, group_ds}{\code{data.frame} - -data frames to be used as inputs in \link{subset_bds_param} and \link{subset_adsl}} - -\item{subj_col, par_col, cat_col, vis_col}{\verb{[character(1)]} - -Column for subject id, category, parameter and visit. All specified columns must be factors} -} -\value{ -\verb{[data.frame()]} - -The \verb{_group} columns depend on the names in \code{group_vect}\tabular{lllll}{ - \code{subject_id} \tab \code{x_value} \tab \code{y_value} \tab \code{main_group} \tab \code{sub_group} \cr - xx \tab xx \tab xx \tab xx \tab xx \cr -} -} -\description{ -Prepares the basic input for the rest of the scatterplot functions. -\itemize{ -\item \code{bm_dataset} is subset according to category, parameter and visit selection for x and y val -\item \code{group_dataset} is subset according to group_selection -\item both are joined using \code{subject_col} as a common key -\item it uses a left join -} - -It is based on \code{\link[=subset_bds_param]{subset_bds_param()}} and \code{\link[=subset_adsl]{subset_adsl()}} with additional error checking. -} -\details{ -\itemize{ -\item factors from \code{bm_ds} are releveled so all extra levels not present after subsetting are dropped and are sorted -according to \code{par} and \code{cat}. Unless parameters are renamed in \code{\link[=subset_bds_param]{subset_bds_param()}} then no releveling occurs. -\item \code{group_vect} names are a subset of main_group and sub_group or empty, -otherwise a regular error is produced. -\item \code{label} attributes from \code{group_ds} and \code{bm_ds} are retained when available -} -\subsection{Shiny validation errors:}{ -\itemize{ -\item The x or y fragments from bm contains more than row per subject, category, parameter and visit combination -\item The fragment from group contains more than row per subject -\item If \code{bm_ds} and \code{grp_ds} share column names, apart from \code{subj_col}, after internal renaming has occured -\item If the returned dataset has 0 rows -} -} -} -\keyword{internal} diff --git a/man/spm_subset_data.Rd b/man/spm_subset_data.Rd deleted file mode 100644 index 37deaac..0000000 --- a/man/spm_subset_data.Rd +++ /dev/null @@ -1,83 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_scatter_matrix.R -\name{spm_subset_data} -\alias{spm_subset_data} -\title{Subset datasets for scatterplot matrix} -\usage{ -spm_subset_data( - cat, - cat_col, - par, - par_col, - val_col, - vis, - vis_col, - group_vect, - bm_ds, - group_ds, - subj_col -) -} -\arguments{ -\item{par, cat}{\verb{[character*ish*(n)]} - -Values from \code{par_col} and \code{cat_col} to be subset} - -\item{val_col}{\verb{[character*ish*(1)]} - -Column containing values for the parameters} - -\item{vis}{\verb{[character*ish*(1)]} - -Values from \code{vis_col} to be subset} - -\item{group_vect}{\verb{[named(character(n))]} - -Columns to be subset and renamed.} - -\item{bm_ds, group_ds}{\code{data.frame} - -data frames to be used as inputs in \link{subset_bds_param} and \link{subset_adsl}} - -\item{subj_col, par_col, cat_col, vis_col}{\verb{[character(1)]} - -Column for subject id, category, parameter and visit. All specified columns must be factors} -} -\value{ -\verb{[data.frame()]} - -The \verb{_group} columns depend on the names in \code{group_vect}\tabular{llll}{ - \code{PAR1} \tab \code{PAR2} \tab \code{PAR3} \tab \code{main_group} \cr - xx \tab xx \tab xx \tab xx \cr -} -} -\description{ -Prepares the basic input for the rest of the scatterplot matrix functions. -\itemize{ -\item \code{bm_dataset} is subset according to category, parameter and visit selection -\item \code{group_dataset} is subset according to group_selection -\item both are joined using \code{subject_col} as a common key -\item it uses a left join -} - -It is based on \code{\link[=subset_bds_param]{subset_bds_param()}} and \code{\link[=subset_adsl]{subset_adsl()}} with additional error checking. -} -\details{ -\itemize{ -\item factors from \code{bm_ds} are releveled so all extra levels not present after subsetting are dropped and are sorted -according to \code{par} and \code{cat}. Unless parameters are renamed in \code{\link[=subset_bds_param]{subset_bds_param()}} then no releveling occurs. -\item \code{group_vect} names are a subset of main_group or empty, -otherwise a regular error is produced. -\item \code{label} attributes from \code{group_ds} and \code{bm_ds} are retained when available -} -\subsection{Shiny validation errors:}{ -\itemize{ -\item The bm_dataset fragments from bm contains more than row per subject, category, parameter and visit combination -\item The fragment from group contains more than row per subject -\item If \code{bm_ds} and \code{grp_ds} share column names, apart from \code{subj_col}, after internal renaming has occured -\item If the returned dataset has 0 rows -\item If the returned dataset has a single parameter column -} -} -} -\keyword{internal} diff --git a/man/str_to_hash.Rd b/man/str_to_hash.Rd deleted file mode 100644 index bf91b2f..0000000 --- a/man/str_to_hash.Rd +++ /dev/null @@ -1,15 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-misc.R -\name{str_to_hash} -\alias{str_to_hash} -\title{Vectorized hash} -\usage{ -str_to_hash(object) -} -\arguments{ -\item{object}{object to be hashed} -} -\description{ -Uses digest with a fixed murmur32 algorithm and no serialization -} -\keyword{internal} diff --git a/man/strip_data_pronoun.Rd b/man/strip_data_pronoun.Rd deleted file mode 100644 index 5f743ff..0000000 --- a/man/strip_data_pronoun.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/common_logic.R -\name{strip_data_pronoun} -\alias{strip_data_pronoun} -\title{Strip ".data" pronoun from a string} -\usage{ -strip_data_pronoun(x) -} -\arguments{ -\item{x}{A character string to be processed.} -} -\value{ -A character string with the ".data" pronoun removed. -} -\description{ -This function removes the \code{.data} pronoun and the \verb{[[]]} accesor from a string using a regular expression pattern. -It works also when the .data is surrounded by \code{c()}. If there is no match the string is returned unmodified. -} -\keyword{internal} diff --git a/man/subset_adsl.Rd b/man/subset_adsl.Rd deleted file mode 100644 index 6dae88b..0000000 --- a/man/subset_adsl.Rd +++ /dev/null @@ -1,44 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/common_logic.R -\name{subset_adsl} -\alias{subset_adsl} -\title{Subsets a group dataset, usually adsl, for a group_column_selection} -\usage{ -subset_adsl(ds, group_vect, subj_col) -} -\arguments{ -\item{ds}{\verb{[data.frame()]} - -Data frame to be subset, see section \emph{Input dataframes}} - -\item{group_vect}{\verb{[named(character(n))]} - -Columns to be subset and renamed.} - -\item{subj_col}{\verb{[character(1)]} - -Column for subject id. \code{subj_col} must be a factor} -} -\value{ -\code{data.frame()}\tabular{llll}{ - \code{subject_id} \tab \code{names(group_vec)[[1]]} \tab \code{names(group_vec)[[2]]} \tab ... \cr - xx \tab xx \tab xx \tab xx \cr -} - -\itemize{ -\item When present \code{label} attribute is retained. -} -} -\description{ -Subsets a group dataset, usually adsl, for a group_column_selection -} -\section{Input dataframe}{ - - -It expects a dataset with an structure similar to -https://www.cdisc.org/kb/examples/adam-subject-level-analysis-adsl-dataset-80283806 , one record per subject - -It expects to contain, at least, \code{subj_col} and all entries in \code{group_vect} as columns -} - -\keyword{internal} diff --git a/man/subset_bds_param.Rd b/man/subset_bds_param.Rd deleted file mode 100644 index 083617a..0000000 --- a/man/subset_bds_param.Rd +++ /dev/null @@ -1,75 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/common_logic.R -\name{subset_bds_param} -\alias{subset_bds_param} -\title{Subsets a biomarker dataset for a category, parameter, visit and value selection} -\usage{ -subset_bds_param( - ds, - par, - par_col, - cat, - cat_col, - val_col, - vis, - vis_col, - subj_col -) -} -\arguments{ -\item{ds}{\code{data.frame()} - -See \emph{Input dataframe section}} - -\item{par, cat}{\verb{[character*ish*(n)]} - -Values from \code{par_col} and \code{cat_col} to be subset} - -\item{val_col}{\verb{[character*ish*(1)]} - -Column containing values for the parameters} - -\item{vis}{\verb{[character*ish*(1)]} - -Values from \code{vis_col} to be subset} - -\item{subj_col, par_col, cat_col, vis_col}{\verb{[character(1)]} - -Column for subject id, category, parameter and visit. All specified columns must be factors} -} -\value{ -\tabular{lllll}{ - \code{subject_id} \tab \code{parameter} \tab \code{category} \tab \code{visit} \tab \code{value} \cr - xx \tab xx \tab xx \tab xx \tab xx \cr -} - - -Additionally: -\itemize{ -\item When present \code{label} attributes are retained. -\item When the same parameter is repeated across different categories an error is raised -} -} -\description{ -Subsets a biomarker dataset for a category, parameter, visit and value selection -} -\details{ -\itemize{ -\item If at least one parameter name appears under several selected categories, an error is produced -} -} -\section{Input dataframe}{ - - -It expects a dataset similar to -https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192 , -1 record per subject per parameter per analysis visit - -It expects, at least, the columns passed in the parameters, -\code{subj_col}, \code{cat_col}, \code{par_col}, \code{visit_col} and \code{val_col}. -The values of these variables are as described -in the CDISC standard for the variables USUBJID, PARCAT, PARAM, AVISIT and AVAL. -} - -\keyword{data,} -\keyword{internal} diff --git a/man/swap_val_names.Rd b/man/swap_val_names.Rd deleted file mode 100644 index 086fefd..0000000 --- a/man/swap_val_names.Rd +++ /dev/null @@ -1,18 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-label.R -\name{swap_val_names} -\alias{swap_val_names} -\title{Swap names and values} -\usage{ -swap_val_names(l) -} -\arguments{ -\item{l}{a named vector or list} -} -\value{ -A vector or list with swapped names and values -} -\description{ -Swap names and values -} -\keyword{internal} diff --git a/man/test_disjunct_cols.Rd b/man/test_disjunct_cols.Rd deleted file mode 100644 index 821c80f..0000000 --- a/man/test_disjunct_cols.Rd +++ /dev/null @@ -1,24 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/common_logic.R -\name{test_disjunct_cols} -\alias{test_disjunct_cols} -\alias{need_disjunct_cols} -\title{Test has repeated cols} -\usage{ -test_disjunct_cols(ds1, ds2, ignore = NULL) - -need_disjunct_cols(..., msg) -} -\arguments{ -\item{ds1, ds2}{datframes to test} - -\item{ignore}{columns to ignore while testing} - -\item{...}{Argument forwarded to test_disjunct_cols} - -\item{msg}{Validation message} -} -\description{ -Test has repeated cols -} -\keyword{internal} diff --git a/man/test_one_cat_per_par.Rd b/man/test_one_cat_per_par.Rd deleted file mode 100644 index c394e15..0000000 --- a/man/test_one_cat_per_par.Rd +++ /dev/null @@ -1,43 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/common_logic.R, R/mod_roc.R -\name{test_one_cat_per_par} -\alias{test_one_cat_per_par} -\alias{need_one_cat_per_var} -\title{Test if a parameter only appears under one category} -\usage{ -test_one_cat_per_par(ds, cat_col, par_col) - -need_one_cat_per_var(..., msg) - -test_one_cat_per_par(ds, cat_col, par_col) -} -\arguments{ -\item{ds}{\verb{[data.frame()]} -The dataset to be tested} - -\item{cat_col}{\verb{[character(1)]} -Name of the column containing the category name} - -\item{par_col}{\verb{[character(1)]} -Name of the column containing the parameter name} - -\item{...}{arguments passed to test_one_cat_per_par} - -\item{msg}{\verb{[character(1)]} - -Validation message to be diplayed} -} -\value{ -\verb{[logical(1)]} -\code{TRUE} if a parameter appears under a single category, \code{FALSE} otherwise - -\verb{[logical(1)]} -\code{TRUE} if a parameter appears under a single category, \code{FALSE} otherwise -} -\description{ -It contains at least the subject id. It includes a need to use inside a validate body - -It contains at least the subject id -} -\keyword{helper} -\keyword{internal} diff --git a/man/test_one_row_per_sbj.Rd b/man/test_one_row_per_sbj.Rd deleted file mode 100644 index 53a9683..0000000 --- a/man/test_one_row_per_sbj.Rd +++ /dev/null @@ -1,32 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/common_logic.R -\name{test_one_row_per_sbj} -\alias{test_one_row_per_sbj} -\alias{need_one_row_per_sbj} -\title{Test if a group has a single row for the combinations of a set of grouping variables} -\usage{ -test_one_row_per_sbj(ds, subj_col, ...) - -need_one_row_per_sbj(..., msg) -} -\arguments{ -\item{ds}{\verb{[data.frame()]} -The dataset to be tested} - -\item{subj_col}{\verb{[character(1)]} -Name of the column containing the subject_id} - -\item{...}{\verb{[character(1)]} -Other column names for grouping} - -\item{msg}{\verb{[character(1)]} -Validation message} -} -\value{ -\verb{[logical(1)]} -\code{TRUE} if a single row is found, \code{FALSE} otherwise -} -\description{ -It contains at least the subject id. It includes a need version to include in a validate body. -} -\keyword{internal} diff --git a/man/transformation.Rd b/man/transformation.Rd deleted file mode 100644 index 18d3e41..0000000 --- a/man/transformation.Rd +++ /dev/null @@ -1,67 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-transformation.R -\name{transformation} -\alias{transformation} -\alias{tr_identity} -\alias{tr_z_score} -\alias{tr_gini} -\alias{tr_trunc_z_score} -\alias{tr_trunc_z_score_3_3} -\alias{tr_min_max} -\alias{tr_percentize} -\title{Transformation functions} -\usage{ -tr_identity(x) - -tr_z_score(x) - -tr_gini(x) - -tr_trunc_z_score(x, trunc_min = -3, trunc_max = 3) - -tr_trunc_z_score_3_3(x) - -tr_min_max(x) - -tr_percentize(x) -} -\arguments{ -\item{x}{a vector/list} - -\item{trunc_min}{minimum value} - -\item{trunc_max}{maximum value} -} -\value{ -a vector/list with the transformed values - -a vector/list with the transformed values - -a vector/list with the transformed values truncated at the specified cuts - -a vector/list with the transformed values truncated at the (-3, 3) cuts - -a vector/list with the transformed values - -a vector/list with the transformed values -} -\description{ -Transformation functions -} -\section{Functions}{ -\itemize{ -\item \code{tr_identity()}: Identity transformation - -\item \code{tr_z_score()}: Z score transformation - -\item \code{tr_gini()}: Gini's mean difference - -\item \code{tr_trunc_z_score()}: Truncated Z score transformation - -\item \code{tr_trunc_z_score_3_3()}: Truncated Z score transformation in the (-3, 3) range - -\item \code{tr_min_max()}: Min Max transformation - -\item \code{tr_percentize()}: Percentize transformation - -}} diff --git a/man/transformation_utils.Rd b/man/transformation_utils.Rd deleted file mode 100644 index 60e567c..0000000 --- a/man/transformation_utils.Rd +++ /dev/null @@ -1,36 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/utils-transformation.R -\name{transformation_utils} -\alias{transformation_utils} -\alias{get_tr_fun} -\alias{get_tr_apply} -\title{Transformation auxiliary functions} -\usage{ -get_tr_fun(s) - -get_tr_apply(tr) -} -\arguments{ -\item{s}{the selected transformation} - -\item{tr}{a function that has as first parameter the values to transform.} -} -\value{ -a function from \link{get_tr_apply} - -a function with the following interface \verb{function(df, group_col, val_col, ...)} where \code{...} is passed to as -extra parameters to tr -} -\description{ -Transformation auxiliary functions -} -\section{Functions}{ -\itemize{ -\item \code{get_tr_fun()}: Transformation selecting function - -\item \code{get_tr_apply()}: Transformation apply function - -Get a function that applies a transformation to a given column grouped by another column - -}} -\keyword{internal} diff --git a/man/wfphm.Rd b/man/wfphm.Rd deleted file mode 100644 index 16af93e..0000000 --- a/man/wfphm.Rd +++ /dev/null @@ -1,144 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm} -\alias{wfphm} -\alias{wfphm_UI} -\alias{wfphm_server} -\alias{mod_wfphm} -\title{Waterfall heatmap shiny module} -\usage{ -wfphm_UI(id, tr_choices = names(tr_mapper_def())) - -wfphm_server( - id, - bm_dataset, - group_dataset, - cat_var = "PARCAT1", - par_var = "PARAM", - visit_var = "AVISIT", - subjid_var = "SUBJID", - value_vars = c("AVAL", "CHG", "PCHG", "log2AVAL", "log2CHG", "log2PCHG", "log10AVAL", - "log10CHG", "log10PCHG"), - bar_group_palette = list(), - cat_palette = list(), - tr_mapper = tr_mapper_def(), - show_x_ticks = TRUE -) - -mod_wfphm( - module_id, - bm_dataset_name, - group_dataset_name, - cat_var = "PARCAT1", - par_var = "PARAM", - visit_var = "AVISIT", - subjid_var = "SUBJID", - value_vars = c("AVAL", "CHG", "PCHG", "log2AVAL", "log2CHG", "log2PCHG", "log10AVAL", - "log10CHG", "log10PCHG"), - bar_group_palette = list(), - cat_palette = list(), - tr_mapper = tr_mapper_def(), - show_x_ticks = TRUE -) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{tr_choices}{the names of the entries in tr_mapper} - -\item{bm_dataset}{\verb{[shiny::reactive(data.frame) | shinymeta::metaReactive(data.frame)]} - -It expects the following format: -\itemize{ -\item it contains, at least, the columns specified in the parameters: \code{cat_var}, \code{par_var}, \code{value_vars}, \code{visit_var} -and \code{subjid_var} -\item \code{cat_var}, \code{par_var}, \code{visit_var} and \code{subjid_var} columns are factors -\item It contains at least 1 row -}} - -\item{group_dataset}{\verb{[shiny::reactive(data.frame) | shinymeta::metaReactive(data.frame)]} - -It expects the following format: -\itemize{ -\item it contains, at least, the columns specified in the parameters: \code{subjid_var} -\item \code{subjid_var} columns is a factors -\item It contains at least 1 row -}} - -\item{cat_var, par_var, visit_var, subjid_var}{\verb{[character(1)]} - -columns used as indicated in each of the subplots} - -\item{value_vars}{\verb{[character(1+)]} - -possible colum values. If column is labelled, label will be displayed in the value menu} - -\item{bar_group_palette}{\verb{[list(palettes)]} - -list of custom palettes to apply to bar_grouping. It receives the values used for grouping and must return a DaVinci -palette. Each palette is applied when the name of the entry in the list matches the name of the column used for -grouping} - -\item{cat_palette}{\verb{[list(functions)]} - -list of functions that receive the values of the variable and returns a vector with the colors for each of the values. -Each palette is applied when the name of the entry in the list matches the name of the selected categorical -variable} - -\item{tr_mapper}{\verb{[function(1+)]} - -named vector containing a set of transformation where the name is the string shown in the selector and the value is -function to be applied according to details section.} - -\item{show_x_ticks}{\verb{[logical(1)]} - -show x ticks in the parameter heatmap} - -\item{module_id}{Shiny id} - -\item{bm_dataset_name, group_dataset_name}{The name of the dataset} -} -\value{ -\subsection{UI}{ - -The menus and plots -} - -\subsection{Server}{ - -NULL -} -} -\description{ -A module that creates the following plots with its corresponding menus: -\itemize{ -\item A waterfall \link{wfphm_wf} -\item A heatmap for categorical variables \link{wfphm_hmcat} -\item A heatmap for continuous variables \link{wfphm_hmcont} -\item A heatmap that displays a set of parameters \link{wfphm_hmpar} -} -} -\details{ -See the subsections for each of plots particularities -\subsection{X axis}{ - -All charts share the same x-axis order as defined by the value \code{sorted_x} returned by the \link{wfphm_wf}. -} - -\subsection{Margins}{ - -All four plots are aligned on their left and right sides so their x axis are also aligned. Each plot returns -their required margins and we calculate the maximum for each side and return it in the \code{margin} argument of each -plot. -} -} -\section{Functions}{ -\itemize{ -\item \code{wfphm_UI()}: UI - -\item \code{wfphm_server()}: server - -\item \code{mod_wfphm()}: dv.manager wrapper for the module - -}} -\keyword{main} diff --git a/man/wfphm_hmcat.Rd b/man/wfphm_hmcat.Rd deleted file mode 100644 index 8ed9d0d..0000000 --- a/man/wfphm_hmcat.Rd +++ /dev/null @@ -1,108 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_hmcat} -\alias{wfphm_hmcat} -\alias{wfphm_hmcat_UI} -\alias{wfphm_hmcat_server} -\title{Categorical heatmap component of WFPHM} -\usage{ -wfphm_hmcat_UI(id) - -wfphm_hmcat_server( - id, - dataset, - subjid_var, - sorted_x, - cat_palette = list(), - margin -) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{dataset}{\verb{[shiny::reactive(data.frame) | shinymeta::metaReactive(data.frame)]} - -It expects the following format: -\itemize{ -\item it contains, at least, the columns specified in the parameters: \code{subjid_var} -\item \code{subjid_var} columns is a factor -}} - -\item{subjid_var}{\verb{[character(1)]} - -column used as indicated in the details section} - -\item{sorted_x}{\verb{[factor(*) | shiny::reactive(factor(*)) | shinymeta::metaReactive(factor(*))]} - -indicates how the levels of \code{subjid_var} should be ordered in the X axis.} - -\item{cat_palette}{\verb{[list(functions)]} - -list of functions that receive the values of the variable and returns a vector with the colors for each of the values -Each palette is applied when the name of the entry in the list matches the name of the selected categorical -variable} - -\item{margin}{\verb{[numeric(4) | shiny::reactive(numeric(4)) | shinymeta::metaReactive(numeric(4))]} - -margin to be used on each of the sides. It must contain four entries named \code{top}, \code{bottom}, \code{left} and \code{right}} -} -\value{ -\subsection{UI}{ - -A heatmap plot -} - -\subsection{Server}{ - -A list with one entry: -\itemize{ -\item \code{margin}: similar to the \code{margin} parameter with the minimum margins for the current plot -} -} -} -\description{ -Presents a heatmap plot for categorical variables -} -\section{Functions}{ -\itemize{ -\item \code{wfphm_hmcat_UI()}: UI - -\item \code{wfphm_hmcat_server()}: server - -}} -\section{Data subsetting:}{ -\itemize{ -\item Allows selecting several columns from all factor or character columns, from now on \strong{category_selection}. -\itemize{ -\item Menu labelled: Discrete heatmap -} -\item Subsets the dataset to the columns \strong{category_selection}, and \code{subj_var}. -\item Pivot the dataset to a longer format such that each row have: -\itemize{ -\item column \code{x}: the value of \code{subjid_var} -\item column \code{y}: the value of a \strong{category_selection} -\item column \code{z}: the value of the \strong{category_selection} in \code{y} for the value in \code{x} -} -\item If more than one row have the same \code{x} and \code{y} an informative error indicating the plot cannot be created -is shown. -} -\subsection{X axis ordering}{ -\itemize{ -\item \code{x} levels are ordered according to \code{sorted_x} -} - -Then a call to \link{heatmap_D3} is done with the following arguments: -\itemize{ -\item \code{data} = \verb{subset dataset} (as described above) -\item \code{x_axis} = \code{NULL} -\item \code{y_axis} = \code{W} -\item \code{z_axis} = \code{E} -\item \code{margin} is the parameter passed to this same function -\item \code{palette} is hardcoded with 8 colors. After 8 categories colors are repeated -\item \code{msg_func} = NULL -\item \code{quiet} = TRUE -} -} -} - -\keyword{internal} diff --git a/man/wfphm_hmcat_subset.Rd b/man/wfphm_hmcat_subset.Rd deleted file mode 100644 index 62c5d83..0000000 --- a/man/wfphm_hmcat_subset.Rd +++ /dev/null @@ -1,23 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_hmcat_subset} -\alias{wfphm_hmcat_subset} -\title{Prepares the data for the categorical heatmap} -\usage{ -wfphm_hmcat_subset(data, selection, palette, subjid_var, sorted_x) -} -\arguments{ -\item{data}{the dataframe to be subset, commonly a subject level dataset} - -\item{selection}{the categorical columns to be selected} - -\item{palette}{a palette to be applied} - -\item{subjid_var}{the column that corresponde to the subject id} - -\item{sorted_x}{the ordered subject ids} -} -\description{ -Prepares the data for the categorical heatmap -} -\keyword{internal} diff --git a/man/wfphm_hmcont.Rd b/man/wfphm_hmcont.Rd deleted file mode 100644 index 4429ca5..0000000 --- a/man/wfphm_hmcont.Rd +++ /dev/null @@ -1,96 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_hmcont} -\alias{wfphm_hmcont} -\alias{wfphm_hmcont_UI} -\alias{wfphm_hmcont_server} -\title{Continuous heatmap component of WFPHM} -\usage{ -wfphm_hmcont_UI(id) - -wfphm_hmcont_server(id, dataset, subjid_var, sorted_x, margin) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{dataset}{\verb{[shiny::reactive(data.frame) | shinymeta::metaReactive(data.frame)]} - -It expects the following format: -\itemize{ -\item it contains, at least, the columns specified in the parameters: \code{subjid_var} -\item \code{subjid_var} columns is a factor -}} - -\item{subjid_var}{\verb{[character(1)]} - -column used as indicated in the details section} - -\item{sorted_x}{\verb{[factor(*) | shiny::reactive(factor(*)) | shinymeta::metaReactive(factor(*))]} - -indicates how the levels of \code{subjid_var} should be ordered in the X axis.} - -\item{margin}{\verb{[numeric(4) | shiny::reactive(numeric(4)) | shinymeta::metaReactive(numeric(4))]} - -margin to be used on each of the sides. It must contain four entries named \code{top}, \code{bottom}, \code{left} and \code{right}} -} -\value{ -\subsection{UI}{ - -A heatmap plot -} - -\subsection{Server}{ - -A list with one entry: -\itemize{ -\item \code{margin}: similar to the \code{margin} parameter with the minimum margins for the current plot -} -} -} -\description{ -Presents a heatmap plot for continuous variables -} -\section{Functions}{ -\itemize{ -\item \code{wfphm_hmcont_UI()}: UI - -\item \code{wfphm_hmcont_server()}: server - -}} -\section{Data subsetting:}{ -\itemize{ -\item Allows selecting several columns from all numerical columns, from now on \strong{numerical_selection}. -\itemize{ -\item Menu labelled: Continuous heatmap -} -\item Subsets the dataset to the columns \strong{numerical_selection}, and \code{subj_var}. -\item Pivot the dataset to a longer format such that each row have: -\itemize{ -\item column \code{x}: the value of \code{subjid_var} -\item column \code{y}: the value of a \strong{numerical_selection} -\item column \code{z}: the value of the \strong{numerical_selection} in \code{y} for the value in \code{x} -} -\item If more than one row have the same \code{x} and \code{y} an informative error indicating the plot cannot be created -is shown. -} -\subsection{X axis ordering}{ -\itemize{ -\item \code{x} levels are ordered according to \code{sorted_x} -} - -Then a call to \link{heatmap_D3} is done with the following arguments: -\itemize{ -\item \code{data} = \verb{subset dataset} (as described above) -\item \code{x_axis} = \code{NULL} -\item \code{y_axis} = \code{W} -\item \code{z_axis} = \code{E} -\item \code{margin} is the parameter passed to this same function -\item \code{palette} is hardcoded to \code{RColorBrewer::brewer.pal(n = 8, name = "Accent")} after 8 categories -colors are repeated -\item \code{msg_func} = NULL -\item \code{quiet} = TRUE -} -} -} - -\keyword{internal} diff --git a/man/wfphm_hmcont_subset.Rd b/man/wfphm_hmcont_subset.Rd deleted file mode 100644 index 581924c..0000000 --- a/man/wfphm_hmcont_subset.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_hmcont_subset} -\alias{wfphm_hmcont_subset} -\title{Prepares the data for the continuous heatmap} -\usage{ -wfphm_hmcont_subset(data, selection, subjid_var, sorted_x) -} -\arguments{ -\item{data}{the dataframe to be subset, commonly a subject level dataset} - -\item{selection}{the categorical columns to be selected} - -\item{subjid_var}{the column that corresponde to the subject id} - -\item{sorted_x}{the ordered subject ids} -} -\description{ -Prepares the data for the continuous heatmap -} -\keyword{internal} diff --git a/man/wfphm_hmpar.Rd b/man/wfphm_hmpar.Rd deleted file mode 100644 index 60b16ed..0000000 --- a/man/wfphm_hmpar.Rd +++ /dev/null @@ -1,172 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_hmpar} -\alias{wfphm_hmpar} -\alias{wfphm_hmpar_UI} -\alias{wfphm_hmpar_server} -\title{Parameter heatmap component of WFPHM} -\usage{ -wfphm_hmpar_UI(id, tr_choices) - -wfphm_hmpar_server( - id, - dataset, - cat_var, - par_var, - visit_var, - subjid_var, - value_vars, - sorted_x, - tr_mapper, - margin, - show_x_ticks -) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{dataset}{\verb{[shiny::reactive(data.frame) | shinymeta::metaReactive(data.frame)]} - -It expects the following format: -\itemize{ -\item it contains, at least, the columns specified in the parameters: \code{cat_var}, \code{par_var}, \code{value_vars}, \code{visit_var} -and \code{subjid_var} -\item \code{cat_var}, \code{par_var}, \code{visit_var} and \code{subjid_var} columns are factors -\item \code{value_vars} must be numeric -}} - -\item{cat_var, par_var, visit_var, subjid_var}{\verb{[character(1)]}} - -\item{value_vars}{\verb{[character(1+)]} - -possible colum values. If column is labelled, label will be displayed in the value menu} - -\item{tr_mapper}{\verb{[function(1+)]} - -named list containing a set of unary functions to transform the data. The name is the string shown in a selector and -the value is the function to be applied according to details section.} - -\item{margin}{\verb{[numeric(4) | shiny::reactive(numeric(4)) | shinymeta::metaReactive(numeric(4))]} - -margin to be used on each of the sides. It must contain four entries named \code{top}, \code{bottom}, \code{left} and \code{right}} - -\item{show_x_ticks}{\verb{[logical(1)]} - -show x ticks in the parameter heatmap} -} -\value{ -\subsection{UI}{ - -A heatmap plot -} - -\subsection{Server}{ - -A list with one entry: -\itemize{ -\item \code{margin}: similar to the \code{margin} parameter with the minimum margins for the current plot -} -} -} -\description{ -Parameter heatmap component of WFPHM -} -\details{ -\subsection{Data subsetting:}{ -\itemize{ -\item Allows selecting several values from the \code{cat_var} column, from now on \strong{cat_selection} and several values -from the \code{par_var} column from the subset of rows where \code{par_cat} is equal to \strong{cat_selection} -from now on \strong{par_selection}. -\itemize{ -\item Menu labelled: Category and Parameter -} -\item Allows selecting between the columns defined in \code{value_vars} from now on \strong{value_selection}. -\itemize{ -\item Menu labelled: Value -} -\item Allows selecting a value from \code{visit_var} column, from now on \strong{visit_selection}. -\itemize{ -\item Menu labelled: Visit -} -\item Subsets the dataset rows where: -\itemize{ -\item \code{visit_var} equal to \strong{visit_selection} -\item \code{par_var} equal to \strong{par_selection} -} -\item Subsets the dataset to \code{par_var}, \code{subj_var} and the \strong{value_selection}. -\item If more than one row have the same combination \code{subj_var} and \code{par_var} an informative error indicating the plot -cannot be created is shown. -} - -Then the dataset is prepared to be passed to \link{heatmap_D3}: -\itemize{ -\item \code{subj_var} becomes \code{x} column -\item the label attribute of \code{x} column is \verb{Subject ID} -\item \code{par_var} becomes \code{y} column -\item \code{value_selection} becomes \code{z} column -\item \code{z} becomes \code{label} column -} -} - -\subsection{Completing the dataset:}{ -\itemize{ -\item Subset dataset will be completed in the following way. All non-present combination of the original levels of \code{x} -and 'y' is are added with rows where: -\item \code{x} and \code{y} are equal to the missing combination -\item \code{z} is NA -} -} - -\subsection{Data outliers:}{ -\itemize{ -\item Allows setting two limits upper and lower for \code{y} value, values above or below in the subsetted dataset will be -considered outliers. Rows considered outliers will have the column: -\itemize{ -\item \code{label} replaced by "x" -\item \code{color} equal to "fill: white; font-weight: bold;" -} -\item Rows not considered outliers will have the column: -\itemize{ -\item \code{color} equal to NA -} -} -} - -\subsection{Data transformation:}{ -\itemize{ -\item Allows selecting between a set of functions as defined in \code{tr_mapper} from now on \strong{transformation_function}. -\itemize{ -\item Menu labelled: Transformation -} -\item This transformation is applied to the subset dataset grouped by the \code{y} column. i.e. each row of the heatmap is -transformed independently. -\item The function must be unary, and the unique argument will be the numerical values of a given row of the hetamap. -} -} - -\subsection{X axis ordering}{ -\itemize{ -\item \code{x} levels are ordered according to \code{sorted_x} -} - -Then a call to \link{heatmap_D3} is done with the following arguments: -\itemize{ -\item \code{data} = \verb{subset dataset} (as described above) -\item \code{x_axis} = \code{S} -\item \code{y_axis} = \code{W} -\item \code{z_axis} = \code{E} -\item \code{margin} is the parameter passed to this same function -\item \code{palette} is hardcoded to \code{RColorBrewer::brewer.pal(n = 8, name = "Set2")} after 8 categories colors are repeated -\item \code{msg_func} = NULL -\item \code{quiet} = TRUE -} -} -} -\section{Functions}{ -\itemize{ -\item \code{wfphm_hmpar_UI()}: UI - -\item \code{wfphm_hmpar_server()}: server - -}} -\keyword{internal} diff --git a/man/wfphm_hmpar_subset.Rd b/man/wfphm_hmpar_subset.Rd deleted file mode 100644 index 42e98f5..0000000 --- a/man/wfphm_hmpar_subset.Rd +++ /dev/null @@ -1,38 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_hmpar_subset} -\alias{wfphm_hmpar_subset} -\title{Subsets data for hmpar module} -\usage{ -wfphm_hmpar_subset( - data, - cat_selection, - cat_var, - par_selection, - par_var, - visit_selection, - visit_var, - value_var, - subjid_var, - sorted_x, - out_criteria, - scale -) -} -\arguments{ -\item{data}{the bsd param dataset} - -\item{cat_selection, par_selection, visit_selection}{the selected category, parameter and visit selections} - -\item{cat_var, par_var, visit_var, value_var, subjid_var}{the corresponding columns} - -\item{sorted_x}{the ordered subject ids} - -\item{out_criteria}{the outlier criteria} - -\item{scale}{a scaling function that will rescale the values in the heatmap} -} -\description{ -Subsets data for hmpar module -} -\keyword{internal} diff --git a/man/wfphm_wf.Rd b/man/wfphm_wf.Rd deleted file mode 100644 index b50c60f..0000000 --- a/man/wfphm_wf.Rd +++ /dev/null @@ -1,184 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_wf} -\alias{wfphm_wf} -\alias{wfphm_wf_UI} -\alias{wfphm_wf_server} -\title{Waterfall component of WFPHM} -\usage{ -wfphm_wf_UI(id) - -wfphm_wf_server( - id, - bm_dataset, - group_dataset, - cat_var, - par_var, - visit_var, - subjid_var, - value_vars, - .default_group_palette = function(x) { - pal_get_cat_palette(x, - viridisLite::viridis(length(unique(x)))) - }, - bar_group_palette = list(), - margin -) -} -\arguments{ -\item{id}{Shiny ID \verb{[character(1)]}} - -\item{cat_var, par_var, visit_var, subjid_var}{\verb{[character(1)]} - -columns used as indicated in the details section} - -\item{value_vars}{\verb{[character(1+)]} - -possible colum values. If column is labelled, label will be displayed in the value menu} - -\item{bar_group_palette}{\verb{[list(palettes)]} - -list of custom palettes to apply to bar_grouping. It receives the values used for grouping and must return a DaVinci -palette. Each palette is applied when the name of the entry in the list matches the name of the column used for -grouping} - -\item{margin}{\verb{[numeric(4) | shiny::reactive(numeric(4)) | shinymeta::metaReactive(numeric(4))]} - -margin to be used on each of the sides. It must contain four entries named \code{top}, \code{bottom}, \code{left} and \code{right}} - -\item{dataset}{\verb{[shiny::reactive(data.frame) | shinymeta::metaReactive(data.frame)]} - -It expects the following format: -\itemize{ -\item it contains, at least, the columns specified in the parameters: \code{cat_var}, \code{par_var}, \code{value_vars}, \code{visit_var} -and \code{subjid_var} -\item \code{cat_var}, \code{par_var}, \code{visit_var} and \code{subjid_var} columns are factors -}} -} -\value{ -\subsection{UI}{ - -A bar plot -} - -\subsection{Server}{ - -A list with two entries: -\itemize{ -\item \code{margin}: similar to the \code{margin} parameter with the minimum margins for the current plot -\item \code{sorted_x}: From the subsetted data the \code{x} levels sorted from high to low by \code{y} -} -} -} -\description{ -Waterfall component of WFPHM -} -\details{ -Data subsetting: -\itemize{ -\item Allows selecting a column from all factor or character columns, from now on \strong{grouping_selection}. -\itemize{ -\item Menu labelled: Grouping -} -\item Data selection for plotting can be done in two modes switched by: -\itemize{ -\item Menu labelled: Display demographic baseline information -} -} -\subsection{Mode 1:}{ -\itemize{ -\item Allows selecting a column from the set of all numerical columns, from now on \strong{value_selection}. -\itemize{ -\item Menu labelled: Value -} -\item Subsets the dataset to the columns \strong{grouping_selection}, \code{subj_var} and \strong{value_selection}. -\item Removes all repeated rows from the dataset -\item If more than one row have the same \code{subj_var} an informative error indicating the plot cannot be created -is shown. -} -} - -\subsection{Mode 2:}{ -\itemize{ -\item Allows selecting a value from the \code{cat_var} column, from now on \strong{cat_selection} and a value from the \code{par_var} -column from the subset of rows where \code{par_cat} is equal to \strong{cat_selection} from now on \strong{par_selection}. -\itemize{ -\item Menu labelled: Category and Parameter -} -\item Allows selecting between the columns defined in \code{val_var} from now on \strong{value_selection}. -\itemize{ -\item Menu labelled: Value -} -\item Allows selecting a value from \code{visit_var} column, from now on \strong{visit_selection}. -\itemize{ -\item Menu labelled: Visit -} -\item Subsets the dataset rows where: -\itemize{ -\item \code{visit_var} equal to \strong{visit_selection} -\item \code{par_var} equal to \strong{par_selection} -} -\item Subsets the dataset to the \strong{grouping_selection}, the \code{subj_var} and the \strong{value_selection}. -\item If more than one row have the same \code{subj_var} an informative error indicating the plot cannot be created -is shown. -} - -Then the dataset is prepared to be passed to \link{bar_D3}: -\itemize{ -\item \code{subj_var} becomes \code{x} column -\item \code{val_selection} becomes \code{y} column -\item the label attribute of \code{y} column is either \code{value_selection} in \emph{Mode 1} or \code{par_selection} in \emph{Mode 2} -\item \code{grouping_selection} becomes \code{z} column -\item \code{grouping_selection} becomes \code{label} column -} -} - -\subsection{Completing the dataset:}{ -\itemize{ -\item Subset dataset will be completed in the following way. If any level in \code{x} is not present in the subset -dataset, but it was present in the \code{subj_var} column in the original dataset, a row is added where \code{x} is equal to -the missing value \code{y} is NA and \code{z} is NA. -} -} - -\subsection{Data outliers:}{ -\itemize{ -\item Allows setting two limits upper and lower, values above or below in the subsetted dataset will be considered -outliers. Rows considered outliers will have the column: -\itemize{ -\item \code{label} replaced by "outlier" -\item \code{color} equal to "gray" -} -\item Rows not considered outliers will have the column: -\itemize{ -\item \code{color} equal to NA -} -} -} - -\subsection{X axis sorting}{ -\itemize{ -\item \code{x} levels are sorted from greater to lower value in \code{y} -} - -Then a call to \link{bar_D3} is done with the following arguments: -\itemize{ -\item \code{data} = \verb{subset dataset} (as described above) -\item \code{x_axis} = \code{NULL} -\item \code{y_axis} = \code{W} -\item \code{z_axis} = NULL -\item \code{margin} is the parameter passed to this same function -\item \code{palette} is hardcoded with 8 colors. After 8 categories colors are repeated -\item \code{msg_func} = NULL -\item \code{quiet} = TRUE -} -} -} -\section{Functions}{ -\itemize{ -\item \code{wfphm_wf_UI()}: UI - -\item \code{wfphm_wf_server()}: server - -}} -\keyword{internal} diff --git a/man/wfphm_wf_apply_outliers.Rd b/man/wfphm_wf_apply_outliers.Rd deleted file mode 100644 index f663e07..0000000 --- a/man/wfphm_wf_apply_outliers.Rd +++ /dev/null @@ -1,20 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_wf_apply_outliers} -\alias{wfphm_wf_apply_outliers} -\title{Color bars and changes labels to outliers} -\usage{ -wfphm_wf_apply_outliers(df, ll, ul) -} -\arguments{ -\item{df}{the dataframe where we will apply the outliers} - -\item{ll, ul}{the lower/upper value limit to consider an entry an outlier} -} -\description{ -\code{label} is replaced by \code{outlier} -} -\details{ -\code{color} is replaced by \code{gray} -} -\keyword{internal} diff --git a/man/wfphm_wf_rename_cols.Rd b/man/wfphm_wf_rename_cols.Rd deleted file mode 100644 index fe76190..0000000 --- a/man/wfphm_wf_rename_cols.Rd +++ /dev/null @@ -1,18 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_wf_rename_cols} -\alias{wfphm_wf_rename_cols} -\title{Renames wf subset columns} -\usage{ -wfphm_wf_rename_cols(df) -} -\arguments{ -\item{df}{the dataframe} -} -\description{ -column names are replaced by x y z -} -\details{ -y column label is set -} -\keyword{internal} diff --git a/man/wfphm_wf_subset_data_cont.Rd b/man/wfphm_wf_subset_data_cont.Rd deleted file mode 100644 index c6ed6ba..0000000 --- a/man/wfphm_wf_subset_data_cont.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_wf_subset_data_cont} -\alias{wfphm_wf_subset_data_cont} -\title{Subsets a subject level dataset for the waterfall heatmap} -\usage{ -wfphm_wf_subset_data_cont(val_col, color_col, group_ds, subj_col) -} -\arguments{ -\item{val_col}{the column from the group_dataset to be used} - -\item{color_col}{the column to be used for coloring/grouping} - -\item{group_ds}{the subject level dataset} - -\item{subj_col}{the subject id column} -} -\description{ -Levels in subject column are ordered with respect to value column higher to lower -} -\keyword{internal} diff --git a/man/wfphm_wf_subset_data_par.Rd b/man/wfphm_wf_subset_data_par.Rd deleted file mode 100644 index 3436721..0000000 --- a/man/wfphm_wf_subset_data_par.Rd +++ /dev/null @@ -1,77 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mod_wfphm.R -\name{wfphm_wf_subset_data_par} -\alias{wfphm_wf_subset_data_par} -\title{Subset datasets for waterfall in waterfall plus heatmap} -\usage{ -wfphm_wf_subset_data_par( - cat, - cat_col, - par, - par_col, - val_col, - vis, - vis_col, - color_col, - bm_ds, - group_ds, - subj_col -) -} -\arguments{ -\item{par, cat}{\verb{[character*ish*(n)]} - -Values from \code{par_col} and \code{cat_col} to be subset} - -\item{val_col}{\verb{[character*ish*(1)]} - -Column containing values for the parameters} - -\item{vis}{\verb{[character*ish*(1)]} - -Values from \code{vis_col} to be subset} - -\item{color_col}{the column used to color the bars} - -\item{bm_ds, group_ds}{\code{data.frame} - -data frames to be used as inputs in \link{subset_bds_param} and \link{subset_adsl}} - -\item{subj_col, par_col, cat_col, vis_col}{\verb{[character(1)]} - -Column for subject id, category, parameter and visit. All specified columns must be factors} -} -\value{ -\verb{[data.frame()]} - -The \verb{_group} columns depend on the names in \code{group_vect}\tabular{llll}{ - \code{x} \tab \code{y} \tab \code{z} \tab \code{color} \cr - xx \tab xx \tab xx \tab xx \cr -} -} -\description{ -Prepares the basic input for the rest of waterfall heatmap functions -\itemize{ -\item \code{bm_dataset} is subset according to category, parameter and visit selection -\item \code{group_dataset} is subset according to group_selection -\item both are joined using \code{subject_col} as a common key -\item it uses a full join to include the subjects that has no parameter value for that parameter visit combination -} - -It is based on \code{\link[=subset_bds_param]{subset_bds_param()}} and \code{\link[=subset_adsl]{subset_adsl()}} with additional error checking. -} -\details{ -\itemize{ -\item columns are renamed to \code{x}, \code{y}, \code{z} and \code{color} -\item \code{label} attributes from \code{group_ds} and \code{bm_ds} are retained when available -} -\subsection{Shiny validation errors:}{ -\itemize{ -\item The fragment from bm contains more than row per subject, category, parameter and visit combination -\item The fragment from group contains more than row per subject -\item If \code{bm_ds} and \code{grp_ds} share column names, apart from \code{subj_col}, after internal renaming has occured -\item If the returned dataset has 0 rows -} -} -} -\keyword{internal}