Project-wide renaming. Things seem to be mostly working.

DESCRIPTION

@@ -1,13 +1,13 @@
-Package: ggjoy
+Package: ggridges
 Type: Package
-Title: Joyplots in 'ggplot2'
-Version: 0.3.0.9000
+Title: Ridgeline plots in 'ggplot2'
+Version: 0.4.0
 Authors@R: c( 
     person("Claus O.", "Wilke", , "wilke@austin.utexas.edu", c("cre", "aut")),
-    person("RStudio", role = c("cph"), comment = "Copyright for ggplot2 code copied to ggjoy"))
-Description: Joyplots provide a convenient way of visualizing changes in distributions over 
+    person("RStudio", role = c("cph"), comment = "Copyright for ggplot2 code copied to ggridges"))
+Description: Ridgeline plots provide a convenient way of visualizing changes in distributions over 
     time or space. This package enables the creation of such plots in 'ggplot2'.
-URL: https://github.com/clauswilke/ggjoy
+URL: https://github.com/clauswilke/ggridges
 Depends:
     R (>= 3.2),
     ggplot2 (>= 2.2.0),
@@ -30,7 +30,7 @@ Suggests:
 VignetteBuilder: knitr
 Collate:
     'data.R'
-    'ggjoy.R'
+    'ggridges.R'
     'geoms.R'
     'geomsv.R'
     'geoms-gradient.R'

NAMESPACE

@@ -1,18 +1,18 @@
 # Generated by roxygen2: do not edit by hand
 
-export(GeomJoy)
-export(GeomJoy2)
-export(GeomJoyGradient)
+export(GeomDensityRidges)
+export(GeomDensityRidges2)
+export(GeomDensityRidgesGradient)
 export(GeomRidgeline)
 export(GeomRidgelineGradient)
 export(GeomVRidgeline)
 export(ScaleCyclical)
 export(StatBinline)
-export(StatJoy)
+export(StatDensityRidges)
 export(cyclical_scale)
-export(geom_joy)
-export(geom_joy2)
-export(geom_joy_gradient)
+export(geom_density_ridges)
+export(geom_density_ridges2)
+export(geom_density_ridges_gradient)
 export(geom_ridgeline)
 export(geom_ridgeline_gradient)
 export(geom_vridgeline)
@@ -23,8 +23,8 @@ export(scale_fill_cyclical)
 export(scale_linetype_cyclical)
 export(scale_size_cyclical)
 export(stat_binline)
-export(stat_joy)
-export(theme_joy)
+export(stat_density_ridges)
+export(theme_ridges)
 import(ggplot2)
 importFrom(ggplot2,Geom)
 importFrom(ggplot2,ScaleDiscrete)

NEWS

@@ -1,22 +1,6 @@
-ggjoy 0.3.0.9000
+ggridges 0.4.0
 ----------------------------------------------------------------
-- Added an option to center axis labels to `theme_joy()`.
-
-ggjoy 0.3.0
-----------------------------------------------------------------
-- Added cyclical scales that make it easy to alternate between fill colors
-  and other aesthetics.
-
-ggjoy 0.2.0
-----------------------------------------------------------------
-Numerous improvements:
-- New stat `binline` that can be used to draw histogram joyplots.
-- Various improvements in `stat_joy`. In particular, it now works properly
-  with multiple panels. It also now has parameters `from` and `to` to limit the
-  range of density estimation, just like `density()`.
-- Improvements in the vignettes
-- New geoms `geom_ridgeline_gradient` and `geom_joy_gradient` that can handle gradient fills.
-
-ggjoy 0.1.0
-----------------------------------------------------------------
-First complete implementation ready for initial release
+- Initial import of code base from ggjoy, and renaming:
+  geom_joy -> geom_density_ridges
+  stat_joy -> stat_density_ridges
+  theme_joy -> theme_ridges

R/geoms-gradient.R

@@ -1,6 +1,6 @@
-#' Plot ridgelines and joyplots with fill gradients along the x axis
+#' Plot ridgelines and ridgeline plots with fill gradients along the x axis
 #'
-#' The geoms `geom_ridgeline_gradient` and `geom_joy_gradient` work just like [`geom_ridgeline`] and [`geom_joy`] except
+#' The geoms `geom_ridgeline_gradient` and `geom_density_ridges_gradient` work just like [`geom_ridgeline`] and [`geom_density_ridges`] except
 #' that the `fill` aesthetic can vary along the x axis. Because filling with color gradients is fraught with issues,
 #' these geoms should be considered experimental. Don't use them unless you really need to. Note that due to limitations
 #' in R's graphics system, transparency (`alpha`) has to be disabled for gradient fills.
@@ -187,7 +187,7 @@ GeomRidgelineGradient <- ggproto("GeomRidgelineGradient", Geom,
     munched_poly <- ggplot2::coord_munch(coord, positions, panel_params)
 
 
-    # placing the actual grob generation into a separate function allows us to override for geom_joy2
+    # placing the actual grob generation into a separate function allows us to override for geom_density_ridges2
     self$make_group_grob(munched_line, munched_poly, aes, gradient_lwd)
   },
 
@@ -219,20 +219,20 @@ GeomRidgelineGradient <- ggproto("GeomRidgelineGradient", Geom,
 
 
 
-#' @param panel_scaling Argument only to `geom_joy_gradient`. If `TRUE`, the default, relative scaling is calculated separately
+#' @param panel_scaling Argument only to `geom_density_ridges_gradient`. If `TRUE`, the default, relative scaling is calculated separately
 #' for each panel. If `FALSE`, relative scaling is calculated globally.
 #'
 #' @rdname geom_ridgeline_gradient
 #' @importFrom ggplot2 layer
 #' @export
-geom_joy_gradient <- function(mapping = NULL, data = NULL, stat = "joy",
+geom_density_ridges_gradient <- function(mapping = NULL, data = NULL, stat = "density_ridges",
                      panel_scaling = TRUE,
                      na.rm = TRUE, gradient_lwd = 0.5, show.legend = NA, inherit.aes = TRUE, ...) {
   layer(
     data = data,
     mapping = mapping,
     stat = stat,
-    geom = GeomJoyGradient,
+    geom = GeomDensityRidgesGradient,
     position = "identity",
     show.legend = show.legend,
     inherit.aes = inherit.aes,
@@ -251,16 +251,16 @@ geom_joy_gradient <- function(mapping = NULL, data = NULL, stat = "joy",
 #' @importFrom grid gTree gList
 #' @examples
 #'
-#' # Example for `geom_joy_gradient()`
+#' # Example for `geom_density_ridges_gradient()`
 #' ggplot(lincoln_weather, aes(x = `Mean Temperature [F]`, y = `Month`, fill = ..x..)) +
-#'   geom_joy_gradient(scale = 3, rel_min_height = 0.01) +
+#'   geom_density_ridges_gradient(scale = 3, rel_min_height = 0.01) +
 #'   scale_x_continuous(expand = c(0.01, 0)) +
 #'   scale_y_discrete(expand = c(0.01, 0)) +
 #'   scale_fill_viridis(name = "Temp. [F]", option = "C") +
 #'   labs(title = 'Temperatures in Lincoln NE in 2016') +
-#'   theme_joy(font_size = 13, grid = TRUE) + theme(axis.title.y = element_blank())
+#'   theme_ridges(font_size = 13, grid = TRUE) + theme(axis.title.y = element_blank())
 #' @export
-GeomJoyGradient <- ggproto("GeomJoyGradient", GeomRidgelineGradient,
+GeomDensityRidgesGradient <- ggproto("GeomDensityRidgesGradient", GeomRidgelineGradient,
   default_aes =
     aes(color = "black",
         fill = "grey70",

R/geoms.R

@@ -2,7 +2,7 @@
 #'
 #' Plots the sum of the `y` and `height` aesthetics versus `x`, filling the area between `y` and `y + height` with a color.
 #' Thus, the data mapped onto y and onto height must be in the same units.
-#' If you want relative scaling of the heights, you can use [`geom_joy`] with `stat = "identity"`.
+#' If you want relative scaling of the heights, you can use [`geom_density_ridges`] with `stat = "identity"`.
 #'
 #' @param mapping Set of aesthetic mappings created by [`aes()`] or
 #'   [`aes_()`]. If specified and `inherit.aes = TRUE` (the
@@ -176,7 +176,7 @@ GeomRidgeline <- ggproto("GeomRidgeline", Geom,
     positions <- plyr::summarise(data, x = x, y = ymax, id = ids)
     munched_line <- ggplot2::coord_munch(coord, positions, panel_params)
 
-    # placing the actual grob generation into a separate function allows us to override for geom_joy2
+    # placing the actual grob generation into a separate function allows us to override for geom_density_ridges2
     self$make_group_grob(munched_line, munched_poly, aes)
   },
 
@@ -206,17 +206,17 @@ GeomRidgeline <- ggproto("GeomRidgeline", Geom,
 
 
 
-#' Create joyplot
+#' Create ridgeline plot
 #'
-#' `geom_joy` arranges multiple density plots in a staggered fashion, as in the cover of the famous Joy Division album Unknown Pleasures.
+#' `geom_density_ridges` arranges multiple density plots in a staggered fashion, as in the cover of the famous Joy Division album Unknown Pleasures.
 #'
 #' By default, this geom calculates densities from the point data mapped onto the x axis. If density calculation is
-#' not wanted, use `stat="identity"` or use [`geom_ridgeline`]. The difference between `geom_joy` and [`geom_ridgeline`]
-#' is that `geom_joy` will provide automatic scaling of the ridgelines (controlled by the `scale` aesthetic), whereas
+#' not wanted, use `stat="identity"` or use [`geom_ridgeline`]. The difference between `geom_density_ridges` and [`geom_ridgeline`]
+#' is that `geom_density_ridges` will provide automatic scaling of the ridgelines (controlled by the `scale` aesthetic), whereas
 #' [geom_ridgeline] will plot the data as is. Note that when you set `stat="identity"`, the `height` aesthetic must
 #' be provided.
 #'
-#' Note that the default [`stat_joy`] makes joint density estimation across all datasets. This may not generate
+#' Note that the default [`stat_density_ridges`] makes joint density estimation across all datasets. This may not generate
 #' the desired result when using faceted plots. As an alternative, you can set `stat = "density"` to use [`stat_density`].
 #' In this case, it is required to add the aesthetic mapping `height = ..density..` (see examples).
 #'
@@ -233,7 +233,7 @@ GeomRidgeline <- ggproto("GeomRidgeline", Geom,
 #' * `group` Defines the grouping. Not needed if a categorical variable is mapped onto `y`, but needed otherwise. Will typically be the same
 #' variable as is mapped to `y`.
 #' * `height` The height of each ridgeline at the respective x value. Automatically calculated and
-#' provided by [`stat_joy`] if the default stat is not changed.
+#' provided by [`stat_density_ridges`] if the default stat is not changed.
 #' * `scale` A scaling factor to scale the height of the ridgelines relative to the spacing between them.
 #' A value of 1 indicates that the maximum point of any ridgeline touches the baseline right above, assuming
 #' even spacing between baselines.
@@ -248,33 +248,33 @@ GeomRidgeline <- ggproto("GeomRidgeline", Geom,
 #' @examples
 #' # set the `rel_min_height` argument to remove tails
 #' ggplot(iris, aes(x = Sepal.Length, y = Species)) +
-#'   geom_joy(rel_min_height = 0.005) +
+#'   geom_density_ridges(rel_min_height = 0.005) +
 #'   scale_y_discrete(expand = c(0.01, 0)) +
 #'   scale_x_continuous(expand = c(0.01, 0)) +
-#'   theme_joy()
+#'   theme_ridges()
 #'
 #' # set the `scale` to determine how much overlap there is among the plots
 #' ggplot(diamonds, aes(x = price, y = cut)) +
-#'   geom_joy(scale = 4) +
+#'   geom_density_ridges(scale = 4) +
 #'   scale_y_discrete(expand=c(0.01, 0)) +
 #'   scale_x_continuous(expand=c(0.01, 0)) +
-#'   theme_joy()
+#'   theme_ridges()
 #'
 #' # the same figure with colors, and using the ggplot2 density stat
 #' ggplot(diamonds, aes(x = price, y = cut, fill = cut, height = ..density..)) +
-#'   geom_joy(scale = 4, stat = "density") +
+#'   geom_density_ridges(scale = 4, stat = "density") +
 #'   scale_y_discrete(expand = c(0.01, 0)) +
 #'   scale_x_continuous(expand = c(0.01, 0)) +
 #'   scale_fill_brewer(palette = 4) +
-#'   theme_joy() + theme(legend.position = "none")
-geom_joy <- function(mapping = NULL, data = NULL, stat = "joy",
+#'   theme_ridges() + theme(legend.position = "none")
+geom_density_ridges <- function(mapping = NULL, data = NULL, stat = "density_ridges",
                      panel_scaling = TRUE,
                      na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...) {
   layer(
     data = data,
     mapping = mapping,
     stat = stat,
-    geom = GeomJoy,
+    geom = GeomDensityRidges,
     position = "identity",
     show.legend = show.legend,
     inherit.aes = inherit.aes,
@@ -286,12 +286,12 @@ geom_joy <- function(mapping = NULL, data = NULL, stat = "joy",
   )
 }
 
-#' @rdname geom_joy
+#' @rdname geom_density_ridges
 #' @format NULL
 #' @usage NULL
 #' @importFrom grid gTree gList
 #' @export
-GeomJoy <- ggproto("GeomJoy", GeomRidgeline,
+GeomDensityRidges <- ggproto("GeomDensityRidges", GeomRidgeline,
   default_aes =
     aes(color = "black",
         fill = "grey70",
@@ -360,27 +360,27 @@ GeomJoy <- ggproto("GeomJoy", GeomRidgeline,
 )
 
 
-#' `geom_joy2` is identical to `geom_joy` except it draws closed polygons rather than ridgelines.
+#' `geom_density_ridges2` is identical to `geom_density_ridges` except it draws closed polygons rather than ridgelines.
 #'
-#' @rdname geom_joy
+#' @rdname geom_density_ridges
 #' @importFrom ggplot2 layer
 #' @export
 #' @examples
 #'
-#' # use geom_joy2() instead of geom_joy() for solid polygons
+#' # use geom_density_ridges2() instead of geom_density_ridges() for solid polygons
 #' ggplot(iris, aes(x = Sepal.Length, y = Species)) +
-#'   geom_joy2() +
+#'   geom_density_ridges2() +
 #'   scale_y_discrete(expand = c(0.01, 0)) +
 #'   scale_x_continuous(expand = c(0.01, 0)) +
-#'   theme_joy()
-geom_joy2 <- function(mapping = NULL, data = NULL, stat = "joy",
+#'   theme_ridges()
+geom_density_ridges2 <- function(mapping = NULL, data = NULL, stat = "density_ridges",
                       panel_scaling = TRUE,
                       na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...) {
   layer(
     data = data,
     mapping = mapping,
     stat = stat,
-    geom = GeomJoy2,
+    geom = GeomDensityRidges2,
     position = "identity",
     show.legend = show.legend,
     inherit.aes = inherit.aes,
@@ -392,13 +392,13 @@ geom_joy2 <- function(mapping = NULL, data = NULL, stat = "joy",
   )
 }
 
-#' @rdname geom_joy
+#' @rdname geom_density_ridges
 #' @format NULL
 #' @usage NULL
 #' @export
-GeomJoy2 <- ggproto("GeomJoy2", GeomJoy,
+GeomDensityRidges2 <- ggproto("GeomDensityRidges2", GeomDensityRidges,
   make_group_grob = function(munched_line, munched_poly, aes) {
-    ggname("geom_joy2",
+    ggname("geom_density_ridges2",
            grid::polygonGrob(
              munched_poly$x, munched_poly$y, id = munched_poly$id,
              default.units = "native",

R/geomsv.R

@@ -178,7 +178,7 @@ GeomVRidgeline <- ggproto("GeomVRidgeline", Geom,
     positions <- plyr::summarise(data, y = y, x = xmax, id = ids)
     munched_line <- ggplot2::coord_munch(coord, positions, panel_params)
 
-    # placing the actual grob generation into a separate function allows us to override for geom_joy2
+    # placing the actual grob generation into a separate function allows us to override for geom_density_ridges2
     self$make_group_grob(munched_line, munched_poly, aes)
   },
 

R/ggjoy.R → R/ggridges.R

@@ -1,6 +1,6 @@
-#' ggjoy.
+#' ggridges.
 #'
-#' @name ggjoy
+#' @name ggridges
 #' @docType package
 #' @import ggplot2
 NULL

R/scale-cyclical.R

@@ -1,6 +1,6 @@
 #' Create a discrete scale that cycles between values
 #'
-#' The readability of joyplots can often be improved by alternating between fill colors and
+#' The readability of ridgeline plots can often be improved by alternating between fill colors and
 #' other aesthetics. The various cyclical scales make it easy to create plots with this feature,
 #' simply map your grouping variable to the respective aesthetic (e.g., `fill`) and then use
 #' `scale_fill_cyclical` to define the fill colors between you want to alternate. Note that the
@@ -17,12 +17,12 @@
 #' # By default, scale_cyclical sets `guide = "none"`, i.e., no legend
 #' # is drawn
 #' ggplot(diamonds, aes(x = price, y = cut, fill = cut)) +
-#'   geom_joy(scale = 4) +
+#'   geom_density_ridges(scale = 4) +
 #'   scale_fill_cyclical(values = c("#3030D0", "#9090F0"))
 #'
 #' # However, legends can be turned on by setting `guide = "legend"`
 #' ggplot(diamonds, aes(x = price, y = cut, fill = cut)) +
-#'   geom_joy(scale = 4) +
+#'   geom_density_ridges(scale = 4) +
 #'   scale_fill_cyclical(values = c("#3030D0", "#9090F0"),
 #'                       guide = "legend", name = "Fill colors",
 #'                       labels = c("dark blue", "light blue"))
@@ -31,7 +31,7 @@
 #' ggplot(diamonds, aes(x = price, y = cut, fill = cut,
 #'                      color = cut, size = cut,
 #'                      alpha = cut, linetype = cut)) +
-#'   geom_joy(scale = 4, fill = "blue") +
+#'   geom_density_ridges(scale = 4, fill = "blue") +
 #'   scale_fill_cyclical(values = c("blue", "green")) +
 #'   scale_color_cyclical(values = c("black", "white")) +
 #'   scale_size_cyclical(values = c(2, 1)) +