Precommit not working.

.Rbuildignore

@@ -1,8 +1,5 @@
 .graphics
 ^.*\.Rproj$
 ^\.Rproj\.user$
-^\.pre-commit-config\.yaml$
-^renv$
-^renv\.lock$
 demo/
 dev/

DESCRIPTION

@@ -17,7 +17,7 @@ License: All rights reserved.
 Encoding: UTF-8
 LazyData: true
 VignetteBuilder: knitr
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Suggests:
     knitr,
     rmarkdown,

NAMESPACE

@@ -8,4 +8,5 @@ export(stat_shade_ranges)
 export(theme_dereck_dark)
 export(theme_dereck_light)
 import(data.table)
+import(ggplot2)
 importFrom(ggplot2,'%+replace%')

R/dmplot.R

@@ -0,0 +1,3 @@
+#' @import ggplot2
+#' @import data.table
+NULL

R/stat_movingaverages.R

@@ -1,4 +1,3 @@
-
 # df <- data.table::fread("data/kucoin_prices.csv")
 
 StatMovingAverage <- ggplot2::ggproto(
@@ -32,62 +31,62 @@ StatMovingAverage <- ggplot2::ggproto(
 
 #' @title Moving averages `ggplot2` layer
 #' @author Dereck Mezquita
-#' 
-#' @description 
+#'
+#' @description
 #' `stat_movingaverages` is a `ggplot2` layer that allows you to plot moving averages on a `ggplot2` plot either by providing the column names `ggplot2::aes` of the previously calculated metrics.
-#' 
+#'
 #' You are free to use whatever algorithm you desire; the result will be two line plots one for a short moving average and one for a long moving average.
-#' 
+#'
 #' To use this layer provide `ggplot2::aes` values for `x` (datetime x-axis) and `short` and `long` (y-axis).
-#' 
+#'
 #' See examples for more details.
 #'
 #' @param mapping A `ggplot2::aes` object (required - default `NULL`).
 #' @param data A `data.table` object (required - default `NULL`).
 #' @param linewidth A `numeric` vector of length one; the width of the line (optional - default `1.75`).
 #' @param alpha A `numeric` vector of length one; the alpha of the line (optional - default `0.75`).
 #' @param colour A named or unnamed `list` with three elements "short" and "long". These are the colours for the short and long moving averages (optional - default `list(short = "red", long = "blue")`).
-#' 
+#'
 #' @section Aesthetics:
 #' \code{stat_movingaverages} understands the following aesthetics (required aesthetics are in bold):
 #' \itemize{
 #'   \item \strong{x} -- datetime (x-axis)
 #'   \item \strong{short} -- the values for the short moving average (y-axis).
 #'   \item \strong{long} -- the values for the long moving average (y-axis)
 #' }
-#' 
+#'
 #' @details
-#' 
+#'
 #' This is a `ggplot2` extension; it is used with the `+` operator for adding a layer to a `ggplot2` object.
 #'
 #' @return A `ggplot2::layer` object.
 #'
 #' @examples
-#' 
+#'
 #' # get some financial data
 #' # kucoin is private package - you can use any data source
 #' ticker <- "BTC/USDT"
-#' 
+#'
 #' dt <- kucoin::get_market_data(
 #'     symbols = ticker,
 #'     from = "2022-11-28 15:29:43 EST", # lubridate::now() - lubridate::days(7),
-#'     to = "2022-12-05 15:29:31 EST",# lubridate::now(),
+#'     to = "2022-12-05 15:29:31 EST", # lubridate::now(),
 #'     frequency = "1 hour"
 #' )
-#' 
+#'
 #' dt
-#' 
+#'
 #' # we need a function that calculates the indicator for us
 #' # typically I like to write my own functions in C++; in this case we will use TTR's
 #' # the stat expects a named list to be returned - we redefine ttr
 #' ema <- function(close, n = 2, wilder = TRUE) {
 #'     return(as.list(as.data.frame(TTR::EMA(close, n = n, wilder = wilder))))
 #' }
-#' 
+#'
 #' # calculate the short and long moving averages
 #' dt[, ema_short := ema(close, n = 10, wilder = TRUE)]
 #' dt[, ema_long := ema(close, n = 50, wilder = TRUE)]
-#' 
+#'
 #' dt |>
 #'     ggplot2::ggplot(ggplot2::aes(
 #'         x = datetime,
@@ -117,7 +116,7 @@ StatMovingAverage <- ggplot2::ggproto(
 #'         axis.text.x = ggplot2::element_text(angle = 75, vjust = 0.925, hjust = 0.975),
 #'         panel.grid.minor = ggplot2::element_blank()
 #'     )
-#' 
+#'
 #' @export
 
 stat_movingaverages <- function(
@@ -134,8 +133,7 @@ stat_movingaverages <- function(
         short = "yellow",
         long = "purple"
     ),
-    ...
-) {
+    ...) {
     list(
         ggplot2::layer(
             stat = StatMovingAverage,
@@ -187,5 +185,3 @@ stat_movingaverages <- function(
 #     # allows user to choose which values to use for calculations
 #     # accepts wilder as an additional argument
 #     stat_movingaverages(ggplot2::aes(y = close), FUN = TTR::SMA)
-
-

R/stat_shade_ranges.R

@@ -1,4 +1,9 @@
-
+#' StatShadedDateRange
+#'
+#' @rdname ggplot2-ggproto
+#' @format NULL
+#' @usage NULL
+#' @export
 StatShadedDateRange <- ggplot2::ggproto(
     "StatShadedDateRange",
     ggplot2::Stat,
@@ -66,32 +71,50 @@ StatShadedDateRange <- ggplot2::ggproto(
 )
 
 
-#' @title Shaded Date Ranges `ggplot2` layer
-#' @author Dereck Mezquita
+#' Shaded Date Ranges ggplot2 layer
 #'
-#' @param mapping A `ggplot2::aes` object (required - default `NULL`).
-#' @param data A `data.table` object (required - default `NULL`).
-#' @param ... Additional arguments passed to `ggplot2::layer`.
+#' This function creates a ggplot2 layer that shades date ranges based on grouped data.
+#' It's particularly useful for highlighting specific periods in time series data.
 #'
-#' @details
+#' @param mapping Set of aesthetic mappings created by \code{\link[ggplot2]{aes}}.
+#'   Must include `x` for dates and `group` for categorizing ranges.
+#' @param data The data to be displayed in this layer. If NULL, the default,
+#'   the data is inherited from the plot data as specified in the call to \code{\link[ggplot2]{ggplot}}.
+#' @param geom The geometric object to use display the data. Default is "linerange".
+#' @param position Position adjustment, either as a string, or the result of a call to a position adjustment function. Default is "identity".
+#' @param na.rm If FALSE, the default, missing values are removed with a warning.
+#'   If TRUE, missing values are silently removed.
+#' @param show.legend logical. Should this layer be included in the legends?
+#'   NA, the default, includes if any aesthetics are mapped.
+#' @param inherit.aes If FALSE, overrides the default aesthetics,
+#'   rather than combining with them.
+#' @param ... Other arguments passed on to \code{\link[ggplot2]{layer}}.
+#'   These are often aesthetics, used to set an aesthetic to a fixed value.
 #'
-#' This is a `ggplot2` extension; it is used with the `+` operator for adding a layer to a `ggplot2` object.
-#' 
-#' You can set the colour by fill aesthetic with a column.
+#' @return A ggplot2 layer object.
 #'
-#' @return A `ggplot2::layer` object.
-#' 
 #' @examples
 #' \dontrun{
-#' dt |>
-#'    ggplot2::ggplot(ggplot2::aes(x = datetime)) +
-#'    ggplot2::geom_line(ggplot2::aes(y = close), linewidth = 1.5, colour = "white") +
-#'    plots$stat_shade_ranges(ggplot2::aes(group = call, fill = call), alpha = 0.25) +
-#'    ggplot2::scale_color_manual(
-#'        name = "call",
-#'        values = c("buy" = "green", "sell" = "red", "none" = "gray"),
-#'        aesthetics = "fill"
-#'   )
+#' library(ggplot2)
+#' library(data.table)
+#'
+#' # Create sample data
+#' dt <- data.table(
+#'     datetime = seq(as.POSIXct("2023-01-01"), as.POSIXct("2023-12-31"), by = "day"),
+#'     close = runif(365, 100, 200),
+#'     call = sample(c("buy", "sell", "none"), 365, replace = TRUE, prob = c(0.3, 0.3, 0.4))
+#' )
+#'
+#' # Create plot with shaded ranges
+#' ggplot(dt, aes(x = datetime)) +
+#'     geom_line(aes(y = close), linewidth = 1.5, colour = "white") +
+#'     stat_shade_ranges(aes(group = call, fill = call), alpha = 0.25) +
+#'     scale_fill_manual(
+#'         name = "Call",
+#'         values = c("buy" = "green", "sell" = "red", "none" = "gray")
+#'     ) +
+#'     theme_minimal() +
+#'     labs(title = "Stock Price with Buy/Sell Signals", x = "Date", y = "Price")
 #' }
 #'
 #' @export
@@ -103,8 +126,7 @@ stat_shade_ranges <- function(
     na.rm = TRUE,
     show.legend = NA,
     inherit.aes = TRUE,
-    ...
-) {
+    ...) {
     list(
         ggplot2::layer(
             stat = StatShadedDateRange,
@@ -120,4 +142,4 @@ stat_shade_ranges <- function(
             )
         )
     )
-}
+}

R/theme_dereck.R

@@ -10,7 +10,7 @@
 #'     ggplot2::ggplot(ggplot2::aes(x = Sepal.Length, y = Sepal.Width)) +
 #'     ggplot2::geom_point(ggplot2::aes(color = Species, shape = Species)) +
 #'     ggplot2::labs(title = "Iris data", subtitle = "Classic data", x = "Sepal Length", y = "Sepal Width") +
-#'     ggplot2::facet_grid(~ Species) +
+#'     ggplot2::facet_grid(~Species) +
 #'     dmplot::theme_dereck_light()
 #'
 #' data.frame(year = time(nhtemp), tmps = as.matrix(nhtemp)) |>
@@ -24,20 +24,16 @@ theme_dereck_light <- function(base_size = 11, base_family = "") {
     ggplot2::theme_bw(base_size = base_size, base_family = base_family) %+replace% ggplot2::theme(
         plot.title = ggplot2::element_text(face = "bold", hjust = 1, margin = ggplot2::margin(0, 0, 5, 0, unit = "pt")), # 0.5 centres when position is set to "plot"
         plot.subtitle = ggplot2::element_text(hjust = 1, vjust = 0.015, margin = ggplot2::margin(0, 0, 5, 0, unit = "pt")),
-
         panel.background = ggplot2::element_blank(),
         # panel.border = ggplot2::element_rect(color = "#afafaf", fill = NA),
         axis.line = ggplot2::element_blank(),
         panel.border = ggplot2::element_blank(),
-
         panel.grid.minor = ggplot2::element_line(color = "#454545", size = 0.135, linetype = "dotted"),
         panel.grid.major = ggplot2::element_line(color = "#aaaaaa", size = 0.175, linetype = "longdash"),
 
         # axis.line = ggplot2::element_line(color = "#afafaf"),
         axis.ticks = ggplot2::element_line(color = "#aaaaaa"),
-
         strip.background = ggplot2::element_rect(fill = "white", colour = "#676767"),
-
         legend.position = "bottom",
         legend.title = ggplot2::element_text(vjust = 0.85) # adjust title position higher to key when bottom
     )
@@ -55,7 +51,7 @@ theme_dereck_light <- function(base_size = 11, base_family = "") {
 #'     ggplot2::ggplot(ggplot2::aes(x = Sepal.Length, y = Sepal.Width)) +
 #'     ggplot2::geom_point(ggplot2::aes(color = Species, shape = Species)) +
 #'     ggplot2::labs(title = "Iris data", subtitle = "Classic data", x = "Sepal Length", y = "Sepal Width") +
-#'     ggplot2::facet_grid(~ Species) +
+#'     ggplot2::facet_grid(~Species) +
 #'     dmplot::theme_dereck_dark()
 #'
 #' data.frame(year = time(nhtemp), tmps = as.matrix(nhtemp)) |>
@@ -74,23 +70,20 @@ theme_dereck_dark <- function(base_size = 12, base_family = "") {
         # panel.border = ggplot2::element_rect(color = "#afafaf", fill = NA),
         axis.line = ggplot2::element_blank(),
         panel.border = ggplot2::element_blank(),
-
         panel.grid.minor = ggplot2::element_line(color = "white", size = 0.135, linetype = "dotted"),
         panel.grid.major = ggplot2::element_line(color = "#aaaaaa", size = 0.175, linetype = "longdash"),
 
         # axis.line = ggplot2::element_line(color = "#afafaf"),
         axis.ticks = ggplot2::element_line(color = "#aaaaaa"),
-
         strip.background = ggplot2::element_rect(fill = "white", colour = "#676767"),
-
         legend.position = "bottom",
         legend.title = ggplot2::element_text(vjust = 0.85), # adjust title position higher to key when bottom
 
         # dark theme configs
         plot.background = ggplot2::element_rect(fill = "#333333"),
         panel.background = ggplot2::element_rect(fill = "#1E1E1E"),
-        legend.background = ggplot2::element_rect(fill = "#252526"), # 
+        legend.background = ggplot2::element_rect(fill = "#252526"), #
         text = ggplot2::element_text(colour = "#CFCFCF"),
         axis.text = ggplot2::element_text(colour = "#CFCFCF")
     )
-}
+}