## Not run:
# library(intubate)
# library(magrittr)
# library(lattice)
#
# ## barchart
# ## Original function to interface
# barchart(yield ~ variety | site, data = barley,
# groups = year, layout = c(1,6), stack = TRUE,
# auto.key = list(space = "right"),
# ylab = "Barley Yield (bushels/acre)",
# scales = list(x = list(rot = 45)))
#
# ## The interface reverses the order of data and formula
# ntbt_barchart(data = barley, yield ~ variety | site,
# groups = year, layout = c(1,6), stack = TRUE,
# auto.key = list(space = "right"),
# ylab = "Barley Yield (bushels/acre)",
# scales = list(x = list(rot = 45)))
#
# ## so it can be used easily in a pipeline.
# barley %>%
# ntbt_barchart(yield ~ variety | site,
# groups = year, layout = c(1,6), stack = TRUE,
# auto.key = list(space = "right"),
# ylab = "Barley Yield (bushels/acre)",
# scales = list(x = list(rot = 45)))
#
# ## bwplot
# ## Original function to interface
# bwplot(voice.part ~ height, data = singer, xlab = "Height (inches)")
#
# ## The interface reverses the order of data and formula
# ntbt_bwplot(data = singer, voice.part ~ height, xlab = "Height (inches)")
#
# ## so it can be used easily in a pipeline.
# singer %>%
# ntbt_bwplot(voice.part ~ height, xlab = "Height (inches)")
#
# ## cloud
# ## Original function to interface
# cloud(Sepal.Length ~ Petal.Length * Petal.Width | Species, data = iris,
# screen = list(x = -90, y = 70), distance = .4, zoom = .6)
#
# ## The interface reverses the order of data and formula
# ntbt_cloud(data = iris, Sepal.Length ~ Petal.Length * Petal.Width | Species,
# screen = list(x = -90, y = 70), distance = .4, zoom = .6)
#
# ## so it can be used easily in a pipeline.
# iris %>%
# ntbt_cloud(Sepal.Length ~ Petal.Length * Petal.Width | Species,
# screen = list(x = -90, y = 70), distance = .4, zoom = .6)
#
# ## contourplot
# grid <- with(
# environmental,
# {
# ozo.m <- loess((ozone^(1/3)) ~ wind * temperature * radiation,
# parametric = c("radiation", "wind"), span = 1, degree = 2)
# w.marginal <- seq(min(wind), max(wind), length.out = 50)
# t.marginal <- seq(min(temperature), max(temperature), length.out = 50)
# r.marginal <- seq(min(radiation), max(radiation), length.out = 4)
# wtr.marginal <- list(wind = w.marginal, temperature = t.marginal,
# radiation = r.marginal)
# ret <- expand.grid(wtr.marginal)
# ret[, "fit"] <- c(predict(ozo.m, ret))
# ret
# })
#
# ## Original function to interface
# contourplot(fit ~ wind * temperature | radiation, data = grid,
# cuts = 10, region = TRUE,
# xlab = "Wind Speed (mph)",
# ylab = "Temperature (F)",
# main = "Cube Root Ozone (cube root ppb)")
#
# ## The interface reverses the order of data and formula
# ntbt_contourplot(data = grid, fit ~ wind * temperature | radiation,
# cuts = 10, region = TRUE,
# xlab = "Wind Speed (mph)",
# ylab = "Temperature (F)",
# main = "Cube Root Ozone (cube root ppb)")
#
# ## so it can be used easily in a pipeline.
# grid %>%
# ntbt_contourplot(fit ~ wind * temperature | radiation,
# cuts = 10, region = TRUE,
# xlab = "Wind Speed (mph)",
# ylab = "Temperature (F)",
# main = "Cube Root Ozone (cube root ppb)")
#
# ## densityplot
# ## Original function to interface
# densityplot(~ height | voice.part, data = singer, layout = c(2, 4),
# xlab = "Height (inches)", bw = 5)
#
# ## The interface reverses the order of data and formula
# ntbt_densityplot(data = singer, ~ height | voice.part, layout = c(2, 4),
# xlab = "Height (inches)", bw = 5)
#
# ## so it can be used easily in a pipeline.
# singer %>%
# ntbt_densityplot(~ height | voice.part, layout = c(2, 4),
# xlab = "Height (inches)", bw = 5)
#
# ## dotplot
# ## Original function to interface
# dotplot(variety ~ yield | site, data = barley, groups = year,
# key = simpleKey(levels(barley$year), space = "right"),
# xlab = "Barley Yield (bushels/acre) ",
# aspect=0.5, layout = c(1,6), ylab=NULL)
#
# ## The interface reverses the order of data and formula
# ntbt_dotplot(data = barley, variety ~ yield | site, groups = year,
# key = simpleKey(levels(barley$year), space = "right"),
# xlab = "Barley Yield (bushels/acre) ",
# aspect=0.5, layout = c(1,6), ylab=NULL)
#
# ## so it can be used easily in a pipeline.
# barley %>%
# ntbt_dotplot(variety ~ yield | site, groups = year,
# key = simpleKey(levels(barley$year), space = "right"),
# xlab = "Barley Yield (bushels/acre) ",
# aspect=0.5, layout = c(1,6), ylab=NULL)
#
# ## histogram
# ## Original function to interface
# histogram(~ height | voice.part, data = singer,
# xlab = "Height (inches)", type = "density",
# panel = function(x, ...) {
# panel.histogram(x, ...)
# panel.mathdensity(dmath = dnorm, col = "black",
# args = list(mean=mean(x),sd=sd(x)))
# })
#
# ## The interface reverses the order of data and formula
# ntbt_histogram(data = singer, ~ height | voice.part,
# xlab = "Height (inches)", type = "density",
# panel = function(x, ...) {
# panel.histogram(x, ...)
# panel.mathdensity(dmath = dnorm, col = "black",
# args = list(mean=mean(x),sd=sd(x)))
# })
#
# ## so it can be used easily in a pipeline.
# singer %>%
# ntbt_histogram(~ height | voice.part,
# xlab = "Height (inches)", type = "density",
# panel = function(x, ...) {
# panel.histogram(x, ...)
# panel.mathdensity(dmath = dnorm, col = "black",
# args = list(mean=mean(x),sd=sd(x)))
# })
#
# ## levelplot
# x <- seq(pi/4, 5 * pi, length.out = 100)
# y <- seq(pi/4, 5 * pi, length.out = 100)
# r <- as.vector(sqrt(outer(x^2, y^2, "+")))
# grid <- expand.grid(x = x, y = y)
# grid$z <- cos(r^2) * exp(-r/(pi^3))
#
# ## Original function to interface
# levelplot(z ~ x*y, grid, cuts = 50, scales = list(log = "e"), xlab = "",
# ylab = "", main = "Weird Function", sub = "with log scales",
# colorkey = FALSE, region = TRUE)
#
# ## The interface reverses the order of data and formula
# ntbt_levelplot(grid, z ~ x*y, cuts = 50, scales = list(log = "e"), xlab = "",
# ylab = "", main = "Weird Function", sub = "with log scales",
# colorkey = FALSE, region = TRUE)
#
# ## so it can be used easily in a pipeline.
# grid %>%
# ntbt_levelplot(z ~ x*y, cuts = 50, scales = list(log = "e"), xlab = "",
# ylab = "", main = "Weird Function", sub = "with log scales",
# colorkey = FALSE, region = TRUE)
#
# ## oneway
# ## Original function to interface
# fit <- oneway(height ~ voice.part, data = singer, spread = 1)
# rfs(fit, aspect = 1)
#
# ## The interface reverses the order of data and formula
# fit <- ntbt_oneway(data = singer, height ~ voice.part, spread = 1)
# rfs(fit, aspect = 1)
#
# ## so it can be used easily in a pipeline.
# singer %>%
# ntbt_oneway(height ~ voice.part, spread = 1) %>%
# rfs(aspect = 1)
#
# ## parallelplot
# ## Original function to interface
# parallelplot(~iris[1:4], iris, groups = Species,
# horizontal.axis = FALSE, scales = list(x = list(rot = 90)))
#
# ## The interface reverses the order of data and formula
# ntbt_parallelplot(iris, ~iris[1:4], groups = Species,
# horizontal.axis = FALSE, scales = list(x = list(rot = 90)))
#
# ## so it can be used easily in a pipeline.
# iris %>%
# ntbt_parallelplot(~iris[1:4], groups = Species,
# horizontal.axis = FALSE, scales = list(x = list(rot = 90)))
#
# ## qq
# ## Original function to interface
# qq(voice.part ~ height, data = singer, aspect = 1,
# subset = (voice.part == "Bass 2" | voice.part == "Tenor 1"))
#
# ## The interface reverses the order of data and formula
# ntbt_qq(data = singer, voice.part ~ height, aspect = 1,
# subset = (voice.part == "Bass 2" | voice.part == "Tenor 1"))
#
# ## so it can be used easily in a pipeline.
# singer %>%
# ntbt_qq(voice.part ~ height, aspect = 1,
# subset = (voice.part == "Bass 2" | voice.part == "Tenor 1"))
#
# ## qqmath
# ## Original function to interface
# qqmath(~ height | voice.part, data = singer, aspect = "xy",
# prepanel = prepanel.qqmathline,
# panel = function(x, ...) {
# panel.qqmathline(x, ...)
# panel.qqmath(x, ...)
# })
#
# ## The interface reverses the order of data and formula
# ntbt_qqmath(data = singer, ~ height | voice.part, aspect = "xy",
# prepanel = prepanel.qqmathline,
# panel = function(x, ...) {
# panel.qqmathline(x, ...)
# panel.qqmath(x, ...)
# })
#
# ## so it can be used easily in a pipeline.
# singer %>%
# ntbt_qqmath(~ height | voice.part, aspect = "xy",
# prepanel = prepanel.qqmathline,
# panel = function(x, ...) {
# panel.qqmathline(x, ...)
# panel.qqmath(x, ...)
# })
#
# ## splom
# super.sym <- trellis.par.get("superpose.symbol")
#
# ## Original function to interface
# splom(~ iris[1:4], data = iris, groups = Species,
# panel = panel.superpose,
# key = list(title = "Three Varieties of Iris",
# columns = 3,
# points = list(pch = super.sym$pch[1:3],
# col = super.sym$col[1:3]),
# text = list(c("Setosa", "Versicolor", "Virginica"))))
# splom(~ iris[1:3] | Species, data = iris,
# layout=c(2,2), pscales = 0,
# varnames = c("Sepal\nLength", "Sepal\nWidth", "Petal\nLength"),
# page = function(...) {
# ltext(x = seq(.6, .8, length.out = 4),
# y = seq(.9, .6, length.out = 4),
# labels = c("Three", "Varieties", "of", "Iris"),
# cex = 2)
# })
#
# ## The interface reverses the order of data and formula
# ntbt_splom(data = iris, ~ iris[1:4], groups = Species,
# panel = panel.superpose,
# key = list(title = "Three Varieties of Iris",
# columns = 3,
# points = list(pch = super.sym$pch[1:3],
# col = super.sym$col[1:3]),
# text = list(c("Setosa", "Versicolor", "Virginica"))))
# ntbt_splom(data = iris, ~ iris[1:3] | Species,
# layout=c(2,2), pscales = 0,
# varnames = c("Sepal\nLength", "Sepal\nWidth", "Petal\nLength"),
# page = function(...) {
# ltext(x = seq(.6, .8, length.out = 4),
# y = seq(.9, .6, length.out = 4),
# labels = c("Three", "Varieties", "of", "Iris"),
# cex = 2)
# })
#
# ## so it can be used easily in a pipeline.
# iris %>%
# ntbt_splom(~ iris[1:4], groups = Species,
# panel = panel.superpose,
# key = list(title = "Three Varieties of Iris",
# columns = 3,
# points = list(pch = super.sym$pch[1:3],
# col = super.sym$col[1:3]),
# text = list(c("Setosa", "Versicolor", "Virginica"))))
# iris %>%
# ntbt_splom(~ iris[1:3] | Species,
# layout=c(2,2), pscales = 0,
# varnames = c("Sepal\nLength", "Sepal\nWidth", "Petal\nLength"),
# page = function(...) {
# ltext(x = seq(.6, .8, length.out = 4),
# y = seq(.9, .6, length.out = 4),
# labels = c("Three", "Varieties", "of", "Iris"),
# cex = 2)
# })
#
# ## stripplot
# ## Original function to interface
# stripplot(voice.part ~ jitter(height), data = singer, aspect = 1,
# jitter.data = TRUE, xlab = "Height (inches)")
#
# ## The interface reverses the order of data and formula
# ntbt_stripplot(data = singer, voice.part ~ jitter(height), aspect = 1,
# jitter.data = TRUE, xlab = "Height (inches)")
#
# ## so it can be used easily in a pipeline.
# singer %>%
# ntbt_stripplot(voice.part ~ jitter(height), aspect = 1,
# jitter.data = TRUE, xlab = "Height (inches)")
#
# ## tmd
# ## Original function to interface
# tmd(Sepal.Length + Sepal.Width ~ Petal.Length + Petal.Width | Species,
# data = iris, scales = "free", layout = c(2, 2),
# auto.key = list(x = .6, y = .7, corner = c(0, 0)))
#
# ## The interface reverses the order of data and formula
# ntbt_tmd(data = iris,
# Sepal.Length + Sepal.Width ~ Petal.Length + Petal.Width | Species,
# scales = "free", layout = c(2, 2),
# auto.key = list(x = .6, y = .7, corner = c(0, 0)))
#
# ## so it can be used easily in a pipeline.
# iris %>%
# ntbt_tmd(Sepal.Length + Sepal.Width ~ Petal.Length + Petal.Width | Species,
# scales = "free", layout = c(2, 2),
# auto.key = list(x = .6, y = .7, corner = c(0, 0)))
#
#
# ## wireframe
# g <- expand.grid(x = 1:10, y = 5:15, gr = 1:2)
# g$z <- log((g$x^g$gr + g$y^2) * g$gr)
#
# ## Original function to interface
# wireframe(z ~ x * y, data = g, groups = gr,
# scales = list(arrows = FALSE),
# drape = TRUE, colorkey = TRUE,
# screen = list(z = 30, x = -60))
#
# ## The interface reverses the order of data and formula
# ntbt_wireframe(data = g, z ~ x * y, groups = gr,
# scales = list(arrows = FALSE),
# drape = TRUE, colorkey = TRUE,
# screen = list(z = 30, x = -60))
#
# ## so it can be used easily in a pipeline.
# g %>%
# ntbt_wireframe(z ~ x * y, groups = gr,
# scales = list(arrows = FALSE),
# drape = TRUE, colorkey = TRUE,
# screen = list(z = 30, x = -60))
#
# ## xyplot
# ## Original function to interface
# xyplot(Sepal.Length + Sepal.Width ~ Petal.Length + Petal.Width | Species,
# data = iris, scales = "free", layout = c(2, 2),
# auto.key = list(x = .6, y = .7, corner = c(0, 0)))
#
# ## The interface reverses the order of data and formula
# ntbt_xyplot(data = iris,
# Sepal.Length + Sepal.Width ~ Petal.Length + Petal.Width | Species,
# scales = "free", layout = c(2, 2),
# auto.key = list(x = .6, y = .7, corner = c(0, 0)))
#
# ## so it can be used easily in a pipeline.
# iris %>%
# ntbt_xyplot(Sepal.Length + Sepal.Width ~ Petal.Length + Petal.Width | Species,
# scales = "free", layout = c(2, 2),
# auto.key = list(x = .6, y = .7, corner = c(0, 0)))
#
# ## End(Not run)
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