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better 2D docs

tags/v0.1.1
hrbrmstr 8 years ago
parent
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fb4de66649
  1. 2
      DESCRIPTION
  2. 27
      R/geom_bkde.r
  3. 34
      R/geom_bkde2d.r
  4. 4
      README.md
  5. BIN
      README_figs/README-unnamed-chunk-4-10.png
  6. 16
      man/geom_bkde.Rd
  7. 43
      man/geom_bkde2d.Rd
  8. 23
      man/stat_bkde2d.Rd

2
DESCRIPTION

@ -1,6 +1,6 @@
Package: ggalt
Title: Extra Geoms, Stats and Coords for 'ggplot2'
Version: 0.0.2.9003
Version: 0.0.2.9004
Authors@R: c(person("Bob", "Rudis", email = "bob@rudis.net", role = c("aut", "cre")))
Description: A package contains additional geoms, coords and stats for the revamped (late 2015) version of ggplot2.
Depends: R (>= 3.0.0), ggplot2 (>= 1.0.1.9003)

27
R/geom_bkde.r

@ -24,8 +24,9 @@
#' @inheritParams ggplot2::geom_point
#' @export
geom_bkde <- function(mapping = NULL, data = NULL, stat = "bkde",
position = "identity", bandwidth, range.x=NULL, show.legend = NA, inherit.aes = TRUE,
...) {
position = "identity", bandwidth=NULL, range.x=NULL,
show.legend = NA, inherit.aes = TRUE,
...) {
layer(
data = data,
@ -45,18 +46,21 @@ geom_bkde <- function(mapping = NULL, data = NULL, stat = "bkde",
#' @usage NULL
#' @export
GeomBkde <- ggproto("GeomBkde", GeomArea,
default_aes = aes(colour = NA, fill = "grey20", size = 0.5, linetype = 1, alpha = NA)
default_aes = aes(colour = NA, fill = "grey20", size = 0.5,
linetype = 1, alpha = NA)
)
#' @param bandwidth the kernel bandwidth smoothing parameter. see
#' \code{\link[KernSmooth]{bkde}} for details
#' \code{\link[KernSmooth]{bkde}} for details. If \code{NULL},
#' it will be computed for you but will most likely not yield optimal
#' results.
#' @param kernel character string which determines the smoothing kernel. see
#' \code{\link[KernSmooth]{bkde}} for details
#' @param canonical logical flag: if TRUE, canonically scaled kernels are used.
#' see \code{\link[KernSmooth]{bkde}} for details
#' @param gridsize the number of equally spaced points at which to estimate the
#' density. see \code{\link[KernSmooth]{bkde}} for details
#' density. see \code{\link[KernSmooth]{bkde}} for details.
#' @param range.x vector containing the minimum and maximum values of x at which
#' to compute the estimate. see \code{\link[KernSmooth]{bkde}} for details
#' @param truncate logical flag: if TRUE, data with x values outside the range
@ -80,8 +84,10 @@ GeomBkde <- ggproto("GeomBkde", GeomArea,
#' ggplot(geyser, aes(x=duration)) +
#' geom_bkde(bandwidth=0.25)
stat_bkde <- function(mapping = NULL, data = NULL, geom = "area",
position = "stack", kernel="normal", canonical=FALSE, bandwidth, gridsize=410,
range.x=NULL, truncate=TRUE, show.legend = NA, inherit.aes = TRUE, ...) {
position = "stack", kernel="normal", canonical=FALSE,
bandwidth = NULL, gridsize=410, range.x=NULL,
truncate=TRUE, show.legend = NA, inherit.aes = TRUE,
...) {
layer(
data = data,
@ -114,9 +120,12 @@ StatBkde <- ggproto("StatBkde", Stat,
default_aes = aes(y = ..density.., fill = NA),
compute_group = function(data, scales, kernel="normal", canonical=FALSE,
bandwidth, gridsize=410, range.x, truncate=TRUE) {
bandwidth=NULL, gridsize=410, range.x=NULL,
truncate=TRUE) {
if (is.null(bandwidth)) bandwidth <- KernSmooth::dpik(data$x)
if (missing(range.x) | is.null(range.x)) range.x <- range(data$x)
if (is.null(range.x)) range.x <- range(data$x)
compute_bkde(data$x, kernel=kernel, canonical=canonical,
bandwidth=bandwidth, gridsize=gridsize, range.x=range.x,

34
R/geom_bkde2d.r

@ -29,7 +29,7 @@
#' d + stat_bkde2d(bandwidth=c(0.5, 0.5), geom = "point",
#' aes(size = ..density..), contour = FALSE)
geom_bkde2d <- function(mapping = NULL, data = NULL, stat = "bkde2d",
position = "identity", bandwidth, range.x=NULL,
position = "identity", bandwidth=NULL, range.x=NULL,
lineend = "butt", contour=TRUE,
linejoin = "round", linemitre = 1,
show.legend = NA,
@ -63,16 +63,35 @@ GeomBkde2d <- ggproto("GeomBkde2d", GeomPath,
)
#' 2D density
#' Contours from a 2d density estimate.
#'
#' @export
#' Perform a 2D kernel density estimation using \code{bkde2D} and display the
#' results with contours. This can be useful for dealing with overplotting
#'
#' @param bandwidth the kernel bandwidth smoothing parameter. see
#' \code{\link[KernSmooth]{bkde2D}} for details. If \code{NULL},
#' it will be computed for you but will most likely not yield optimal
#' results. see \code{\link[KernSmooth]{bkde2D}} for details
#' @param gridsize vector containing the number of equally spaced points in each
#' direction over which the density is to be estimated. see
#' \code{\link[KernSmooth]{bkde2D}} for details
#' @param range.x a list containing two vectors, where each vector contains the
#' minimum and maximum values of x at which to compute the estimate for
#' each direction. see \code{\link[KernSmooth]{bkde2D}} for details
#' @param truncate logical flag: if TRUE, data with x values outside the range
#' specified by range.x are ignored. see \code{\link[KernSmooth]{bkde2D}}
#' for details
#' @param contour If \code{TRUE}, contour the results of the 2d density
#' estimation
#' @section Computed variables:
#' Same as \code{\link{stat_contour}}
#' @seealso \code{\link{geom_contour}} for contour drawing geom,
#' \code{\link{stat_sum}} for another way of dealing with overplotting
#' @rdname geom_bkde2d
#' @export
stat_bkde2d <- function(mapping = NULL, data = NULL, geom = "density2d",
position = "identity", contour = TRUE,
bandwidth, grid_size=c(51, 51), range.x=NULL,
bandwidth=NULL, grid_size=c(51, 51), range.x=NULL,
truncate=TRUE, show.legend = NA,
inherit.aes = TRUE, ...) {
layer(
@ -104,10 +123,15 @@ StatBkde2d <- ggproto("StatBkde2d", Stat,
required_aes = c("x", "y"),
compute_group = function(data, scales, contour=TRUE, bandwidth,
compute_group = function(data, scales, contour=TRUE, bandwidth=NULL,
grid_size=c(51, 51), range.x=NULL,
truncate=TRUE) {
if (is.null(bandwidth)) {
bandwidth <- c(KernSmooth::dpik(data$x),
KernSmooth::dpik(data$y))
}
if (is.null(range.x)) {
x_range <- range(data$x)
y_range <- range(data$y)

4
README.md

@ -39,7 +39,7 @@ library(ggalt)
# current verison
packageVersion("ggalt")
#> [1] '0.0.2.9003'
#> [1] '0.0.2.9004'
set.seed(1492)
dat <- data.frame(x=c(1:10, 1:10, 1:10),
@ -173,7 +173,7 @@ library(ggalt)
library(testthat)
date()
#> [1] "Tue Sep 8 21:26:18 2015"
#> [1] "Tue Sep 8 21:44:34 2015"
test_dir("tests/")
#> testthat results ========================================================================================================

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16
man/geom_bkde.Rd

@ -6,13 +6,13 @@
\title{Display a smooth density estimate.}
\usage{
geom_bkde(mapping = NULL, data = NULL, stat = "bkde",
position = "identity", bandwidth, range.x = NULL, show.legend = NA,
inherit.aes = TRUE, ...)
position = "identity", bandwidth = NULL, range.x = NULL,
show.legend = NA, inherit.aes = TRUE, ...)
stat_bkde(mapping = NULL, data = NULL, geom = "area",
position = "stack", kernel = "normal", canonical = FALSE, bandwidth,
gridsize = 410, range.x = NULL, truncate = TRUE, show.legend = NA,
inherit.aes = TRUE, ...)
position = "stack", kernel = "normal", canonical = FALSE,
bandwidth = NULL, gridsize = 410, range.x = NULL, truncate = TRUE,
show.legend = NA, inherit.aes = TRUE, ...)
}
\arguments{
\item{mapping}{Set of aesthetic mappings created by \code{\link{aes}} or
@ -28,7 +28,9 @@ defined at the top level of the plot.}
a call to a position adjustment function.}
\item{bandwidth}{the kernel bandwidth smoothing parameter. see
\code{\link[KernSmooth]{bkde}} for details}
\code{\link[KernSmooth]{bkde}} for details. If \code{NULL},
it will be computed for you but will most likely not yield optimal
results.}
\item{range.x}{vector containing the minimum and maximum values of x at which
to compute the estimate. see \code{\link[KernSmooth]{bkde}} for details}
@ -63,7 +65,7 @@ the default plot specification, e.g. \code{\link{borders}}.}
see \code{\link[KernSmooth]{bkde}} for details}
\item{gridsize}{the number of equally spaced points at which to estimate the
density. see \code{\link[KernSmooth]{bkde}} for details}
density. see \code{\link[KernSmooth]{bkde}} for details.}
\item{truncate}{logical flag: if TRUE, data with x values outside the range
specified by range.x are ignored. see \code{\link[KernSmooth]{bkde}}

43
man/geom_bkde2d.Rd

@ -2,12 +2,18 @@
% Please edit documentation in R/geom_bkde2d.r
\name{geom_bkde2d}
\alias{geom_bkde2d}
\alias{stat_bkde2d}
\title{Contours from a 2d density estimate.}
\usage{
geom_bkde2d(mapping = NULL, data = NULL, stat = "bkde2d",
position = "identity", bandwidth, range.x = NULL, lineend = "butt",
contour = TRUE, linejoin = "round", linemitre = 1, show.legend = NA,
inherit.aes = TRUE, ...)
position = "identity", bandwidth = NULL, range.x = NULL,
lineend = "butt", contour = TRUE, linejoin = "round", linemitre = 1,
show.legend = NA, inherit.aes = TRUE, ...)
stat_bkde2d(mapping = NULL, data = NULL, geom = "density2d",
position = "identity", contour = TRUE, bandwidth = NULL,
grid_size = c(51, 51), range.x = NULL, truncate = TRUE,
show.legend = NA, inherit.aes = TRUE, ...)
}
\arguments{
\item{mapping}{Set of aesthetic mappings created by \code{\link{aes}} or
@ -25,8 +31,20 @@ layer, as a string.}
\item{position}{Position adjustment, either as a string, or the result of
a call to a position adjustment function.}
\item{bandwidth}{the kernel bandwidth smoothing parameter. see
\code{\link[KernSmooth]{bkde2D}} for details. If \code{NULL},
it will be computed for you but will most likely not yield optimal
results. see \code{\link[KernSmooth]{bkde2D}} for details}
\item{range.x}{a list containing two vectors, where each vector contains the
minimum and maximum values of x at which to compute the estimate for
each direction. see \code{\link[KernSmooth]{bkde2D}} for details}
\item{lineend}{Line end style (round, butt, square)}
\item{contour}{If \code{TRUE}, contour the results of the 2d density
estimation}
\item{linejoin}{Line join style (round, mitre, bevel)}
\item{linemitre}{Line mitre limit (number greater than 1)}
@ -50,9 +68,24 @@ the default plot specification, e.g. \code{\link{borders}}.}
default \code{stat} associated with the layer.
\item Other arguments passed on to the stat.
}}
\item{truncate}{logical flag: if TRUE, data with x values outside the range
specified by range.x are ignored. see \code{\link[KernSmooth]{bkde2D}}
for details}
\item{gridsize}{vector containing the number of equally spaced points in each
direction over which the density is to be estimated. see
\code{\link[KernSmooth]{bkde2D}} for details}
}
\description{
Contours from a 2d density estimate.
Perform a 2D kernel density estimation using \code{bkde2D} and display the
results with contours. This can be useful for dealing with overplotting
}
\section{Computed variables}{
Same as \code{\link{stat_contour}}
}
\examples{
m <- ggplot(faithful, aes(x = eruptions, y = waiting)) +
@ -80,4 +113,8 @@ d + stat_bkde2d(bandwidth=c(0.5, 0.5), geom = "raster",
d + stat_bkde2d(bandwidth=c(0.5, 0.5), geom = "point",
aes(size = ..density..), contour = FALSE)
}
\seealso{
\code{\link{geom_contour}} for contour drawing geom,
\code{\link{stat_sum}} for another way of dealing with overplotting
}

23
man/stat_bkde2d.Rd

@ -1,23 +0,0 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/geom_bkde2d.r
\name{stat_bkde2d}
\alias{stat_bkde2d}
\title{2D density}
\usage{
stat_bkde2d(mapping = NULL, data = NULL, geom = "density2d",
position = "identity", contour = TRUE, bandwidth, grid_size = c(51, 51),
range.x = NULL, truncate = TRUE, show.legend = NA, inherit.aes = TRUE,
...)
}
\arguments{
\item{contour}{If \code{TRUE}, contour the results of the 2d density
estimation}
}
\description{
2D density
}
\section{Computed variables}{
Same as \code{\link{stat_contour}}
}
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