update documentations

data.R
ggplot2_methods.R
methods.R
plotly_methods.R
print_method.R

Author: noriakis

NAMESPACE

@@ -39,13 +39,11 @@ S3method(unnest,tidySummarizedExperiment_nested)
 export("%>%")
 export(as_tibble)
 export(extract)
-export(ggplot)
 export(nest)
 export(pivot_longer)
 export(pivot_wider)
 export(plot_ly)
 export(separate)
-export(tbl_format_header)
 export(tidy)
 export(unite)
 export(unnest)
@@ -64,8 +62,6 @@ importFrom(SummarizedExperiment,colData)
 importFrom(SummarizedExperiment,rbind)
 importFrom(SummarizedExperiment,rowData)
 importFrom(SummarizedExperiment,rowRanges)
-importFrom(cli,cat_line)
-importFrom(cli,symbol)
 importFrom(dplyr,count)
 importFrom(dplyr,distinct)
 importFrom(dplyr,distinct_at)
@@ -128,7 +124,6 @@ importFrom(rlang,names2)
 importFrom(rlang,quo_is_null)
 importFrom(rlang,quo_name)
 importFrom(rlang,quo_squash)
-importFrom(stats,setNames)
 importFrom(stringr,regex)
 importFrom(stringr,str_detect)
 importFrom(stringr,str_replace)

R/data.R

@@ -1,16 +1,19 @@
 #' Read counts of RNA-seq samples of Pasilla knock-down by Brooks et al.
 #'
-#' A SummarizedExperiment dataset containing the transcriptome information for Drosophila Melanogaster.
+#' A SummarizedExperiment dataset containing 
+#' the transcriptome information for Drosophila Melanogaster.
 #'
 #' @format  containing 14599 features and 7 biological replicates.
 #'
 #' @source \url{https://bioconductor.org/packages/release/data/experiment/html/pasilla.html}
 #' @usage data(pasilla)
 "pasilla"
 
-#' Read counts of RNA-seq samples derived from Pasilla knock-down by Brooks et al.
+#' Read counts of RNA-seq samples derived from 
+#' Pasilla knock-down by Brooks et al.
 #'
-#' A SummarizedExperiment dataset containing the transcriptome information for Drosophila Melanogaster.
+#' A SummarizedExperiment dataset containing 
+#' the transcriptome information for Drosophila Melanogaster.
 #'
 #' @format  containing 14599 features and 7 biological replicates.
 #'

R/ggplot2_methods.R

@@ -1,68 +1,29 @@
-
-#' Create a new ggplot from a tidySummarizedExperiment object
-#'
-#'
-#' `ggplot()` initializes a ggplot object. It can be used to
-#' declare the input data frame for a graphic and to specify the
-#' set of plot aesthetics intended to be common throughout all
-#' subsequent layers unless specifically overridden.
-#'
-#' `ggplot()` is used to construct the initial plot object,
-#' and is almost always followed by `+` to add component to the
-#' plot. There are three common ways to invoke `ggplot()`:
-#'
-#'
-#' The first method is recommended if all layers use the same
-#' data and the same set of aesthetics, although this method
-#' can also be used to add a layer using data from another
-#' data frame. See the first example below. The second
-#' method specifies the default data frame to use for the plot,
-#' but no aesthetics are defined up front. This is useful when
-#' one data frame is used predominantly as layers are added,
-#' but the aesthetics may vary from one layer to another. The
-#' third method initializes a skeleton `ggplot` object which
-#' is fleshed out as layers are added. This method is useful when
-#' multiple data frames are used to produce different layers, as
-#' is often the case in complex graphics.
-#'
-#' @importFrom ggplot2 aes
-#' @importFrom ggplot2 ggplot
-#'
-#' @param .data Default dataset to use for plot. If not already a data.frame,
-#'   will be converted to one by [fortify()]. If not specified,
-#'   must be supplied in each layer added to the plot.
-#' @param mapping Default list of aesthetic mappings to use for plot.
-#'   If not specified, must be supplied in each layer added to the plot.
-#' @param ... Other arguments passed on to methods. Not currently used.
-#' @param environment DEPRECATED. Used prior to tidy evaluation.
-#'
-#' @return A ggplot
-#'
-#' @export
-#'
-#' @rdname ggplot2-methods
 #' @name ggplot
+#' @rdname ggplot
+#' @inherit ggplot2::ggplot
+#' @title Create a new \code{ggplot} from a \code{tidyseurat}
+#' @return `ggplot`
 #'
 #' @examples
-#'
 #' library(ggplot2)
-#'
-#' tidySummarizedExperiment::pasilla %>%
-#'     
-#'     tidySummarizedExperiment::ggplot(aes(sample, counts)) +
+#' data(pasilla)
+#' pasilla %>%
+#'     ggplot(aes(.sample, counts)) +
 #'     geom_boxplot()
-NULL
-
+#' 
+#' @importFrom purrr map
+#' @importFrom rlang quo_name
+#' @importFrom ggplot2 aes ggplot
 #' @export
-ggplot.SummarizedExperiment <- function(data=NULL, mapping=aes(), ..., environment=parent.frame()) {
-  
-  # Deprecation of special column names
-  if(is_sample_feature_deprecated_used(
-    data, 
-    mapping %>% unlist() %>% map(~ quo_name(.x)) %>% unlist() %>% as.character()
-  )){
-    data= ping_old_special_column_into_metadata(data)
-  }
+ggplot.SummarizedExperiment <- function(data=NULL, mapping=aes(),
+    ..., environment=parent.frame()) {
+
+    # Deprecation of special column names
+    .cols <- enquos(..., .ignore_empty="all") %>% 
+        map(~ quo_name(.x)) %>% unlist()
+    if (is_sample_feature_deprecated_used(data, .cols)) {
+        data <- ping_old_special_column_into_metadata(data)
+    }
 
     data %>%
         as_tibble() %>%

R/methods.R

@@ -1,47 +1,40 @@
 setMethod(
-    f = "show",
-    signature = "SummarizedExperiment",
-    definition = function(object) {
-        if (
-          isTRUE(x = getOption(x = "restore_SummarizedExperiment_show", default = FALSE)) |
-          
-          # If the object is a SingleCellExperiment
-          # # From BioC 3_14 SingleCellExperiment is SummarizedExperiment and 
-          # # we don't want to process with tidySummarizedExperiment
-          is(object, "SingleCellExperiment")
+    f="show",
+    signature="SummarizedExperiment",
+    definition=function(object) {
+        if (isTRUE(x=getOption(x="restore_SummarizedExperiment_show",
+            default = FALSE)) |         
+            # If the object is a SingleCellExperiment
+            # # From BioC 3_14 SingleCellExperiment is SummarizedExperiment and 
+            # # we don't want to process with tidySummarizedExperiment
+            is(object, "SingleCellExperiment")
         ) {
             f <- getMethod(
-                f = "show",
-                signature = "SummarizedExperiment",
-                where = asNamespace(ns = "SummarizedExperiment")
+                f="show",
+                signature="SummarizedExperiment",
+                where=asNamespace(ns="SummarizedExperiment")
             )
-            f(object = object)
+            f(object=object)
         } else {
             object %>%
                 print()
         }
     }
 )
 
-
 setClass("tidySummarizedExperiment", contains=c("SummarizedExperiment", "RangedSummarizedExperiment"))
 
-
-#' tidy for SummarizedExperiment
-#'
-#' @param object A SummarizedExperiment object
-#'
-#' @return A tidySummarizedExperiment object
-#' 
-#' @description 
-#' 
-#' DEPRECATED. Not needed any more.
-#'
 #' @name tidy
+#' @rdname tidy
+#' @title tidy for `Seurat`
+#'
+#' @param object A `Seurat` object.
+#' @return A `tidyseurat` object.
 #'
 #' @examples
+#' data(pasilla)
+#' pasilla %>% tidy()
 #'
-#' tidySummarizedExperiment::pasilla %>% tidy()
 #' @export
 tidy <- function(object) {
     UseMethod("tidy", object)

R/plotly_methods.R

@@ -1,144 +1,13 @@
-#' Initiate a plotly visualization
-#'
-#' This function maps R objects to [plotly.js](https://plot.ly/javascript/),
-#' an (MIT licensed) web-based interactive charting library. It provides
-#' abstractions for doing common things (e.g. mapping data values to
-#' fill colors (via `color`) or creating [animation]s (via `frame`)) and sets
-#' some different defaults to make the interface feel more 'R-like'
-#' (i.e., closer to [plot()] and [ggplot2::qplot()]).
-#'
-#' @details Unless `type` is specified, this function just initiates a plotly
-#' object with 'global' attributes that are passed onto downstream uses of
-#' [add_trace()] (or similar). A [formula] must always be used when
-#' referencing column name(s) in `data` (e.g. `plot_ly(mtcars, x=~wt)`).
-#' Formulas are optional when supplying values directly, but they do
-#' help inform default axis/scale titles
-#' (e.g., `plot_ly(x=mtcars$wt)` vs `plot_ly(x=~mtcars$wt)`)
-#'
-#' @param data A data frame (optional) or [crosstalk::SharedData] object.
-#' @param ... Arguments (i.e., attributes) passed along to the trace `type`.
-#' See [schema()] for a list of acceptable attributes for a given trace `type`
-#' (by going to `traces` -> `type` -> `attributes`). Note that attributes
-#' provided at this level may override other arguments
-#' (e.g. `plot_ly(x=1:10, y=1:10, color=I("red"), marker=list(color="blue"))`).
-#' @param type A character string specifying the trace type
-#'   (e.g. `"scatter"`, `"bar"`, `"box"`, etc).
-#' If specified, it *always* creates a trace, otherwise
-#' @param name Values mapped to the trace's name attribute. Since a trace can
-#' only have one name, this argument acts very much like `split` in that it
-#' creates one trace for every unique value.
-#' @param color Values mapped to relevant 'fill-color' attribute(s)
-#' (e.g. [fillcolor](https://plot.ly/r/reference#scatter-fillcolor),
-#' [marker.color](https://plot.ly/r/reference#scatter-marker-color),
-#' [textfont.color](https://plot.ly/r/reference/#scatter-textfont-color), etc.).
-#' The mapping from data values to color codes may be controlled using
-#' `colors` and `alpha`, or avoided altogether via [I()]
-#'   (e.g., `color=I("red")`).
-#' Any color understood by [grDevices::col2rgb()] may be used in this way.
-#' @param colors Either a colorbrewer2.org palette name
-#'   (e.g. "YlOrRd" or "Blues"),
-#' or a vector of colors to interpolate in hexadecimal "#RRGGBB" format,
-#' or a color interpolation function like `colorRamp()`.
-#' @param stroke Similar to `color`, but values are mapped to relevant 'stroke-color' attribute(s)
-#' (e.g., [marker.line.color](https://plot.ly/r/reference#scatter-marker-line-color)
-#'  and [line.color](https://plot.ly/r/reference#scatter-line-color)
-#' for filled polygons). If not specified, `stroke` inherits from `color`.
-#' @param strokes Similar to `colors`, but controls the `stroke` mapping.
-#' @param alpha A number between 0 and 1 specifying the alpha channel applied to `color`.
-#' Defaults to 0.5 when mapping to [fillcolor](https://plot.ly/r/reference#scatter-fillcolor) and 1 otherwise.
-#' @param alpha_stroke Similar to `alpha`, but applied to `stroke`.
-#' @param symbol (Discrete) values mapped to [marker.symbol](https://plot.ly/r/reference#scatter-marker-symbol).
-#' The mapping from data values to symbols may be controlled using
-#' `symbols`, or avoided altogether via [I()] (e.g., `symbol=I("pentagon")`).
-#' Any [pch] value or [symbol name](https://plot.ly/r/reference#scatter-marker-symbol) may be used in this way.
-#' @param symbols A character vector of [pch] values or [symbol names](https://plot.ly/r/reference#scatter-marker-symbol).
-#' @param linetype (Discrete) values mapped to [line.dash](https://plot.ly/r/reference#scatter-line-dash).
-#' The mapping from data values to symbols may be controlled using
-#' `linetypes`, or avoided altogether via [I()] (e.g., `linetype=I("dash")`).
-#' Any `lty` (see [par]) value or [dash name](https://plot.ly/r/reference#scatter-line-dash) may be used in this way.
-#' @param linetypes A character vector of `lty` values or [dash names](https://plot.ly/r/reference#scatter-line-dash)
-#' @param size (Numeric) values mapped to relevant 'fill-size' attribute(s)
-#' (e.g., [marker.size](https://plot.ly/r/reference#scatter-marker-size),
-#' [textfont.size](https://plot.ly/r/reference#scatter-textfont-size),
-#' and [error_x.width](https://plot.ly/r/reference#scatter-error_x-width)).
-#' The mapping from data values to symbols may be controlled using
-#' `sizes`, or avoided altogether via [I()] (e.g., `size=I(30)`).
-#' @param sizes A numeric vector of length 2 used to scale `size` to pixels.
-#' @param span (Numeric) values mapped to relevant 'stroke-size' attribute(s)
-#' (e.g.,
-#' [marker.line.width](https://plot.ly/r/reference#scatter-marker-line-width),
-#' [line.width](https://plot.ly/r/reference#scatter-line-width) for filled polygons,
-#' and [error_x.thickness](https://plot.ly/r/reference#scatter-error_x-thickness))
-#' The mapping from data values to symbols may be controlled using
-#' `spans`, or avoided altogether via [I()] (e.g., `span=I(30)`).
-#' @param spans A numeric vector of length 2 used to scale `span` to pixels.
-#' @param split (Discrete) values used to create multiple traces (one trace per value).
-#' @param frame (Discrete) values used to create animation frames.
-#' @param width Width in pixels (optional, defaults to automatic sizing).
-#' @param height Height in pixels (optional, defaults to automatic sizing).
-#' @param source a character string of length 1. Match the value of this string
-#' with the source argument in [event_data()] to retrieve the
-#' event data corresponding to a specific plot (shiny apps can have multiple plots).
-#' @author Carson Sievert
-#' @references <https://plotly-r.com/overview.html>
-#' @seealso \itemize{
-#'  \item For initializing a plotly-geo object: [plot_geo()]
-#'  \item For initializing a plotly-mapbox object: [plot_mapbox()]
-#'  \item For translating a ggplot2 object to a plotly object: [ggplotly()]
-#'  \item For modifying any plotly object: [layout()], [add_trace()], [style()]
-#'  \item For linked brushing: [highlight()]
-#'  \item For arranging multiple plots: [subplot()], [crosstalk::bscols()]
-#'  \item For inspecting plotly objects: [plotly_json()]
-#'  \item For quick, accurate, and searchable plotly.js reference: [schema()]
-#' }
-#'
-#' @return A plotly
-#'
-#' @importFrom plotly plot_ly
-#'
-#' @export
-#' @examples
+#' @name plotly
+#' @rdname plotly
+#' @inherit plotly::plot_ly
+#' @return `plotly`
 #' 
-#' # Plotly better not run
-#' print("See below examples")
+#' @examples
+#' # TODO
 #' 
-#' \dontrun{
-#' # plot_ly() tries to create a sensible plot based on the information you
-#' # give it. If you don't provide a trace type, plot_ly() will infer one.
-#' plot_ly(economics, x=~pop)
-#' plot_ly(economics, x=~date, y=~pop)
-#' # plot_ly() doesn't require data frame(s), which allows one to take
-#' # advantage of trace type(s) designed specifically for numeric matrices
-#' plot_ly(z=~volcano)
-#' plot_ly(z=~volcano, type="surface")
-#'
-#' # plotly has a functional interface: every plotly function takes a plotly
-#' # object as it's first input argument and returns a modified plotly object
-#' add_lines(plot_ly(economics, x=~date, y=~ unemploy / pop))
-#'
-#' # To make code more readable, plotly imports the pipe operator from magrittr
-#' economics %>%
-#'     plot_ly(x=~date, y=~ unemploy / pop) %>%
-#'     add_lines()
-#'
-#' # Attributes defined via plot_ly() set 'global' attributes that
-#' # are carried onto subsequent traces, but those may be over-written
-#' plot_ly(economics, x=~date, color=I("black")) %>%
-#'     add_lines(y=~uempmed) %>%
-#'     add_lines(y=~psavert, color=I("red"))
-#'
-#' # Attributes are documented in the figure reference -> https://plot.ly/r/reference
-#' # You might notice plot_ly() has named arguments that aren't in this figure
-#' # reference. These arguments make it easier to map abstract data values to
-#' # visual attributes.
-#' p <- plot_ly(iris, x=~Sepal.Width, y=~Sepal.Length)
-#' add_markers(p, color=~Petal.Length, size=~Petal.Length)
-#' add_markers(p, color=~Species)
-#' add_markers(p, color=~Species, colors="Set1")
-#' add_markers(p, symbol=~Species)
-#' add_paths(p, linetype=~Species)
-#' }
-#'
+#' @importFrom plotly plot_ly
+#' @export
 plot_ly <- function(data=data.frame(), ..., type=NULL, name=NULL,
     color=NULL, colors=NULL, alpha=NULL,
     stroke=NULL, strokes=NULL, alpha_stroke=1,
@@ -151,8 +20,8 @@ plot_ly <- function(data=data.frame(), ..., type=NULL, name=NULL,
     UseMethod("plot_ly")
 }
 
+#' @rdname plotly
 #' @export
-#'
 plot_ly.tbl_df <- function(data=data.frame(), ..., type=NULL, name=NULL,
     color=NULL, colors=NULL, alpha=NULL,
     stroke=NULL, strokes=NULL, alpha_stroke=1,
@@ -179,6 +48,7 @@ plot_ly.tbl_df <- function(data=data.frame(), ..., type=NULL, name=NULL,
         )
 }
 
+#' @rdname plotly
 #' @export
 plot_ly.SummarizedExperiment <- function(data=data.frame(), ..., type=NULL, name=NULL,
     color=NULL, colors=NULL, alpha=NULL,