inst/app/help.R
In sigbertklinke/smvgraph: Visualization and Clustering of Data in a Shiny App
#' huglawurza
#' @description A dummy function for importing all packages.
#' @return nothing
#' @import graphics
#' @import lattice
#' @import stat
#' @import smvgraph
#' @import car
#' @import aplpack
#' @import stats
#' @import sm
#' @import vioplot
#' @import MASS
#' @import fmsb
#' @import scagnostics
#' @import psych
#' @import dbscan
#' @import mclust
#' @export
#' @examples
#' huglawurza()
huglawurza <- function() {
if (FALSE) {
# Formula method
barplot(GNP ~ Year, data = longley)
barplot(cbind(Employed, Unemployed) ~ Year, data = longley)
## 3rd form of formula - 2 categories :
op <- par(mfrow = 2:1, mgp = c(3,1,0)/2, mar = .1+c(3,3:1))
summary(d.Titanic <- as.data.frame(Titanic))
barplot(Freq ~ Class + Survived, data = d.Titanic,
subset = Age == "Adult" & Sex == "Male",
main = "barplot(Freq ~ Class + Survived, *)", ylab = "# {passengers}", legend.text = TRUE)
# Corresponding table :
(xt <- xtabs(Freq ~ Survived + Class + Sex, d.Titanic, subset = Age=="Adult"))
# Alternatively, a mosaic plot :
mosaicplot(xt[,,"Male"], main = "mosaicplot(Freq ~ Class + Survived, *)", color=TRUE)
par(op)
# Default method
require(grDevices) # for colours
tN <- table(Ni <- stats::rpois(100, lambda = 5))
r <- barplot(tN, col = rainbow(20))
#- type = "h" plotting *is* 'bar'plot
lines(r, tN, type = "h", col = "red", lwd = 2)
barplot(tN, space = 1.5, axisnames = FALSE,
sub = "barplot(..., space= 1.5, axisnames = FALSE)")
barplot(VADeaths, plot = FALSE)
barplot(VADeaths, plot = FALSE, beside = TRUE)
mp <- barplot(VADeaths) # default
tot <- colMeans(VADeaths)
text(mp, tot + 3, format(tot), xpd = TRUE, col = "blue")
barplot(VADeaths, beside = TRUE,
col = c("lightblue", "mistyrose", "lightcyan",
"lavender", "cornsilk"),
legend.text = rownames(VADeaths), ylim = c(0, 100))
title(main = "Death Rates in Virginia", font.main = 4)
hh <- t(VADeaths)[, 5:1]
mybarcol <- "gray20"
mp <- barplot(hh, beside = TRUE,
col = c("lightblue", "mistyrose",
"lightcyan", "lavender"),
legend.text = colnames(VADeaths), ylim = c(0,100),
main = "Death Rates in Virginia", font.main = 4,
sub = "Faked upper 2*sigma error bars", col.sub = mybarcol,
cex.names = 1.5)
segments(mp, hh, mp, hh + 2*sqrt(1000*hh/100), col = mybarcol, lwd = 1.5)
stopifnot(dim(mp) == dim(hh)) # corresponding matrices
mtext(side = 1, at = colMeans(mp), line = -2,
text = paste("Mean", formatC(colMeans(hh))), col = "red")
# Bar shading example
barplot(VADeaths, angle = 15+10*1:5, density = 20, col = "black",
legend.text = rownames(VADeaths))
title(main = list("Death Rates in Virginia", font = 4))
# Border color
barplot(VADeaths, border = "dark blue") % lwd = 2 << not passed
%notyet barplot(VADeaths, inside = FALSE, main = "barplot(*, inside = FALSE)")
# Log scales (not much sense here)
barplot(tN, col = heat.colors(12), log = "y")
barplot(tN, col = gray.colors(20), log = "xy")
# Legend location
barplot(height = cbind(x = c(465, 91) / 465 * 100,
y = c(840, 200) / 840 * 100,
z = c(37, 17) / 37 * 100),
beside = FALSE,
width = c(465, 840, 37),
col = c(1, 2),
legend.text = c("A", "B"),
args.legend = list(x = "topleft"))
}
if (FALSE) {
# Formula method
barplot(GNP ~ Year, data = longley)
barplot(cbind(Employed, Unemployed) ~ Year, data = longley)
## 3rd form of formula - 2 categories :
op <- par(mfrow = 2:1, mgp = c(3,1,0)/2, mar = .1+c(3,3:1))
summary(d.Titanic <- as.data.frame(Titanic))
barplot(Freq ~ Class + Survived, data = d.Titanic,
subset = Age == "Adult" & Sex == "Male",
main = "barplot(Freq ~ Class + Survived, *)", ylab = "# {passengers}", legend.text = TRUE)
# Corresponding table :
(xt <- xtabs(Freq ~ Survived + Class + Sex, d.Titanic, subset = Age=="Adult"))
# Alternatively, a mosaic plot :
mosaicplot(xt[,,"Male"], main = "mosaicplot(Freq ~ Class + Survived, *)", color=TRUE)
par(op)
# Default method
require(grDevices) # for colours
tN <- table(Ni <- stats::rpois(100, lambda = 5))
r <- barplot(tN, col = rainbow(20))
#- type = "h" plotting *is* 'bar'plot
lines(r, tN, type = "h", col = "red", lwd = 2)
barplot(tN, space = 1.5, axisnames = FALSE,
sub = "barplot(..., space= 1.5, axisnames = FALSE)")
barplot(VADeaths, plot = FALSE)
barplot(VADeaths, plot = FALSE, beside = TRUE)
mp <- barplot(VADeaths) # default
tot <- colMeans(VADeaths)
text(mp, tot + 3, format(tot), xpd = TRUE, col = "blue")
barplot(VADeaths, beside = TRUE,
col = c("lightblue", "mistyrose", "lightcyan",
"lavender", "cornsilk"),
legend.text = rownames(VADeaths), ylim = c(0, 100))
title(main = "Death Rates in Virginia", font.main = 4)
hh <- t(VADeaths)[, 5:1]
mybarcol <- "gray20"
mp <- barplot(hh, beside = TRUE,
col = c("lightblue", "mistyrose",
"lightcyan", "lavender"),
legend.text = colnames(VADeaths), ylim = c(0,100),
main = "Death Rates in Virginia", font.main = 4,
sub = "Faked upper 2*sigma error bars", col.sub = mybarcol,
cex.names = 1.5)
segments(mp, hh, mp, hh + 2*sqrt(1000*hh/100), col = mybarcol, lwd = 1.5)
stopifnot(dim(mp) == dim(hh)) # corresponding matrices
mtext(side = 1, at = colMeans(mp), line = -2,
text = paste("Mean", formatC(colMeans(hh))), col = "red")
# Bar shading example
barplot(VADeaths, angle = 15+10*1:5, density = 20, col = "black",
legend.text = rownames(VADeaths))
title(main = list("Death Rates in Virginia", font = 4))
# Border color
barplot(VADeaths, border = "dark blue") % lwd = 2 << not passed
%notyet barplot(VADeaths, inside = FALSE, main = "barplot(*, inside = FALSE)")
# Log scales (not much sense here)
barplot(tN, col = heat.colors(12), log = "y")
barplot(tN, col = gray.colors(20), log = "xy")
# Legend location
barplot(height = cbind(x = c(465, 91) / 465 * 100,
y = c(840, 200) / 840 * 100,
z = c(37, 17) / 37 * 100),
beside = FALSE,
width = c(465, 840, 37),
col = c(1, 2),
legend.text = c("A", "B"),
args.legend = list(x = "topleft"))
}
if (FALSE) {
## boxplot on a formula:
boxplot(count ~ spray, data = InsectSprays, col = "lightgray")
# *add* notches (somewhat funny here <--> warning "notches .. outside hinges"):
boxplot(count ~ spray, data = InsectSprays,
notch = TRUE, add = TRUE, col = "blue")
boxplot(decrease ~ treatment, data = OrchardSprays, col = "bisque",
log = "y")
## horizontal=TRUE, switching y <--> x :
boxplot(decrease ~ treatment, data = OrchardSprays, col = "bisque",
log = "x", horizontal=TRUE)
rb <- boxplot(decrease ~ treatment, data = OrchardSprays, col = "bisque")
title("Comparing boxplot()s and non-robust mean +/- SD")
mn.t <- tapply(OrchardSprays$decrease, OrchardSprays$treatment, mean)
sd.t <- tapply(OrchardSprays$decrease, OrchardSprays$treatment, sd)
xi <- 0.3 + seq(rb$n)
points(xi, mn.t, col = "orange", pch = 18)
arrows(xi, mn.t - sd.t, xi, mn.t + sd.t,
code = 3, col = "pink", angle = 75, length = .1)
## boxplot on a matrix:
mat <- cbind(Uni05 = (1:100)/21, Norm = rnorm(100),
`5T` = rt(100, df = 5), Gam2 = rgamma(100, shape = 2))
boxplot(mat) # directly, calling boxplot.matrix()
## boxplot on a data frame:
df. <- as.data.frame(mat)
par(las = 1) # all axis labels horizontal
boxplot(df., main = "boxplot(*, horizontal = TRUE)", horizontal = TRUE)
## Using 'at = ' and adding boxplots -- example idea by Roger Bivand :
boxplot(len ~ dose, data = ToothGrowth,
boxwex = 0.25, at = 1:3 - 0.2,
subset = supp == "VC", col = "yellow",
main = "Guinea Pigs' Tooth Growth",
xlab = "Vitamin C dose mg",
ylab = "tooth length",
xlim = c(0.5, 3.5), ylim = c(0, 35), yaxs = "i")
boxplot(len ~ dose, data = ToothGrowth, add = TRUE,
boxwex = 0.25, at = 1:3 + 0.2,
subset = supp == "OJ", col = "orange")
legend(2, 9, c("Ascorbic acid", "Orange juice"),
fill = c("yellow", "orange"))
## With less effort (slightly different) using factor *interaction*:
boxplot(len ~ dose:supp, data = ToothGrowth,
boxwex = 0.5, col = c("orange", "yellow"),
main = "Guinea Pigs' Tooth Growth",
xlab = "Vitamin C dose mg", ylab = "tooth length",
sep = ":", lex.order = TRUE, ylim = c(0, 35), yaxs = "i")
## more examples in help(bxp)
}
if (FALSE) {
}
if (FALSE) {
}
if (FALSE) {
sigbertklinke/smvgraph documentation built on Dec. 10, 2022, 9:13 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
#' huglawurza
#' @description A dummy function for importing all packages.
#' @return nothing
#' @import graphics
#' @import lattice
#' @import stat
#' @import smvgraph
#' @import car
#' @import aplpack
#' @import stats
#' @import sm
#' @import vioplot
#' @import MASS
#' @import fmsb
#' @import scagnostics
#' @import psych
#' @import dbscan
#' @import mclust
#' @export
#' @examples
#' huglawurza()
huglawurza <- function() {
if (FALSE) {
# Formula method
barplot(GNP ~ Year, data = longley)
barplot(cbind(Employed, Unemployed) ~ Year, data = longley)
## 3rd form of formula - 2 categories :
op <- par(mfrow = 2:1, mgp = c(3,1,0)/2, mar = .1+c(3,3:1))
summary(d.Titanic <- as.data.frame(Titanic))
barplot(Freq ~ Class + Survived, data = d.Titanic,
subset = Age == "Adult" & Sex == "Male",
main = "barplot(Freq ~ Class + Survived, *)", ylab = "# {passengers}", legend.text = TRUE)
# Corresponding table :
(xt <- xtabs(Freq ~ Survived + Class + Sex, d.Titanic, subset = Age=="Adult"))
# Alternatively, a mosaic plot :
mosaicplot(xt[,,"Male"], main = "mosaicplot(Freq ~ Class + Survived, *)", color=TRUE)
par(op)
# Default method
require(grDevices) # for colours
tN <- table(Ni <- stats::rpois(100, lambda = 5))
r <- barplot(tN, col = rainbow(20))
#- type = "h" plotting *is* 'bar'plot
lines(r, tN, type = "h", col = "red", lwd = 2)
barplot(tN, space = 1.5, axisnames = FALSE,
sub = "barplot(..., space= 1.5, axisnames = FALSE)")
barplot(VADeaths, plot = FALSE)
barplot(VADeaths, plot = FALSE, beside = TRUE)
mp <- barplot(VADeaths) # default
tot <- colMeans(VADeaths)
text(mp, tot + 3, format(tot), xpd = TRUE, col = "blue")
barplot(VADeaths, beside = TRUE,
col = c("lightblue", "mistyrose", "lightcyan",
"lavender", "cornsilk"),
legend.text = rownames(VADeaths), ylim = c(0, 100))
title(main = "Death Rates in Virginia", font.main = 4)
hh <- t(VADeaths)[, 5:1]
mybarcol <- "gray20"
mp <- barplot(hh, beside = TRUE,
col = c("lightblue", "mistyrose",
"lightcyan", "lavender"),
legend.text = colnames(VADeaths), ylim = c(0,100),
main = "Death Rates in Virginia", font.main = 4,
sub = "Faked upper 2*sigma error bars", col.sub = mybarcol,
cex.names = 1.5)
segments(mp, hh, mp, hh + 2*sqrt(1000*hh/100), col = mybarcol, lwd = 1.5)
stopifnot(dim(mp) == dim(hh)) # corresponding matrices
mtext(side = 1, at = colMeans(mp), line = -2,
text = paste("Mean", formatC(colMeans(hh))), col = "red")
# Bar shading example
barplot(VADeaths, angle = 15+10*1:5, density = 20, col = "black",
legend.text = rownames(VADeaths))
title(main = list("Death Rates in Virginia", font = 4))
# Border color
barplot(VADeaths, border = "dark blue") % lwd = 2 << not passed
%notyet barplot(VADeaths, inside = FALSE, main = "barplot(*, inside = FALSE)")
# Log scales (not much sense here)
barplot(tN, col = heat.colors(12), log = "y")
barplot(tN, col = gray.colors(20), log = "xy")
# Legend location
barplot(height = cbind(x = c(465, 91) / 465 * 100,
y = c(840, 200) / 840 * 100,
z = c(37, 17) / 37 * 100),
beside = FALSE,
width = c(465, 840, 37),
col = c(1, 2),
legend.text = c("A", "B"),
args.legend = list(x = "topleft"))
}
if (FALSE) {
# Formula method
barplot(GNP ~ Year, data = longley)
barplot(cbind(Employed, Unemployed) ~ Year, data = longley)
## 3rd form of formula - 2 categories :
op <- par(mfrow = 2:1, mgp = c(3,1,0)/2, mar = .1+c(3,3:1))
summary(d.Titanic <- as.data.frame(Titanic))
barplot(Freq ~ Class + Survived, data = d.Titanic,
subset = Age == "Adult" & Sex == "Male",
main = "barplot(Freq ~ Class + Survived, *)", ylab = "# {passengers}", legend.text = TRUE)
# Corresponding table :
(xt <- xtabs(Freq ~ Survived + Class + Sex, d.Titanic, subset = Age=="Adult"))
# Alternatively, a mosaic plot :
mosaicplot(xt[,,"Male"], main = "mosaicplot(Freq ~ Class + Survived, *)", color=TRUE)
par(op)
# Default method
require(grDevices) # for colours
tN <- table(Ni <- stats::rpois(100, lambda = 5))
r <- barplot(tN, col = rainbow(20))
#- type = "h" plotting *is* 'bar'plot
lines(r, tN, type = "h", col = "red", lwd = 2)
barplot(tN, space = 1.5, axisnames = FALSE,
sub = "barplot(..., space= 1.5, axisnames = FALSE)")
barplot(VADeaths, plot = FALSE)
barplot(VADeaths, plot = FALSE, beside = TRUE)
mp <- barplot(VADeaths) # default
tot <- colMeans(VADeaths)
text(mp, tot + 3, format(tot), xpd = TRUE, col = "blue")
barplot(VADeaths, beside = TRUE,
col = c("lightblue", "mistyrose", "lightcyan",
"lavender", "cornsilk"),
legend.text = rownames(VADeaths), ylim = c(0, 100))
title(main = "Death Rates in Virginia", font.main = 4)
hh <- t(VADeaths)[, 5:1]
mybarcol <- "gray20"
mp <- barplot(hh, beside = TRUE,
col = c("lightblue", "mistyrose",
"lightcyan", "lavender"),
legend.text = colnames(VADeaths), ylim = c(0,100),
main = "Death Rates in Virginia", font.main = 4,
sub = "Faked upper 2*sigma error bars", col.sub = mybarcol,
cex.names = 1.5)
segments(mp, hh, mp, hh + 2*sqrt(1000*hh/100), col = mybarcol, lwd = 1.5)
stopifnot(dim(mp) == dim(hh)) # corresponding matrices
mtext(side = 1, at = colMeans(mp), line = -2,
text = paste("Mean", formatC(colMeans(hh))), col = "red")
# Bar shading example
barplot(VADeaths, angle = 15+10*1:5, density = 20, col = "black",
legend.text = rownames(VADeaths))
title(main = list("Death Rates in Virginia", font = 4))
# Border color
barplot(VADeaths, border = "dark blue") % lwd = 2 << not passed
%notyet barplot(VADeaths, inside = FALSE, main = "barplot(*, inside = FALSE)")
# Log scales (not much sense here)
barplot(tN, col = heat.colors(12), log = "y")
barplot(tN, col = gray.colors(20), log = "xy")
# Legend location
barplot(height = cbind(x = c(465, 91) / 465 * 100,
y = c(840, 200) / 840 * 100,
z = c(37, 17) / 37 * 100),
beside = FALSE,
width = c(465, 840, 37),
col = c(1, 2),
legend.text = c("A", "B"),
args.legend = list(x = "topleft"))
}
if (FALSE) {
## boxplot on a formula:
boxplot(count ~ spray, data = InsectSprays, col = "lightgray")
# *add* notches (somewhat funny here <--> warning "notches .. outside hinges"):
boxplot(count ~ spray, data = InsectSprays,
notch = TRUE, add = TRUE, col = "blue")
boxplot(decrease ~ treatment, data = OrchardSprays, col = "bisque",
log = "y")
## horizontal=TRUE, switching y <--> x :
boxplot(decrease ~ treatment, data = OrchardSprays, col = "bisque",
log = "x", horizontal=TRUE)
rb <- boxplot(decrease ~ treatment, data = OrchardSprays, col = "bisque")
title("Comparing boxplot()s and non-robust mean +/- SD")
mn.t <- tapply(OrchardSprays$decrease, OrchardSprays$treatment, mean)
sd.t <- tapply(OrchardSprays$decrease, OrchardSprays$treatment, sd)
xi <- 0.3 + seq(rb$n)
points(xi, mn.t, col = "orange", pch = 18)
arrows(xi, mn.t - sd.t, xi, mn.t + sd.t,
code = 3, col = "pink", angle = 75, length = .1)
## boxplot on a matrix:
mat <- cbind(Uni05 = (1:100)/21, Norm = rnorm(100),
`5T` = rt(100, df = 5), Gam2 = rgamma(100, shape = 2))
boxplot(mat) # directly, calling boxplot.matrix()
## boxplot on a data frame:
df. <- as.data.frame(mat)
par(las = 1) # all axis labels horizontal
boxplot(df., main = "boxplot(*, horizontal = TRUE)", horizontal = TRUE)
## Using 'at = ' and adding boxplots -- example idea by Roger Bivand :
boxplot(len ~ dose, data = ToothGrowth,
boxwex = 0.25, at = 1:3 - 0.2,
subset = supp == "VC", col = "yellow",
main = "Guinea Pigs' Tooth Growth",
xlab = "Vitamin C dose mg",
ylab = "tooth length",
xlim = c(0.5, 3.5), ylim = c(0, 35), yaxs = "i")
boxplot(len ~ dose, data = ToothGrowth, add = TRUE,
boxwex = 0.25, at = 1:3 + 0.2,
subset = supp == "OJ", col = "orange")
legend(2, 9, c("Ascorbic acid", "Orange juice"),
fill = c("yellow", "orange"))
## With less effort (slightly different) using factor *interaction*:
boxplot(len ~ dose:supp, data = ToothGrowth,
boxwex = 0.5, col = c("orange", "yellow"),
main = "Guinea Pigs' Tooth Growth",
xlab = "Vitamin C dose mg", ylab = "tooth length",
sep = ":", lex.order = TRUE, ylim = c(0, 35), yaxs = "i")
## more examples in help(bxp)
}
if (FALSE) {
}
if (FALSE) {
}
if (FALSE) {
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