3D scatter plot
mohammad yasir roll no 151 (DS)
2023-12-17
R Markdown
#Basic 3D scatter plots
##library("scatterplot3d") # loaddata(iris)
head(iris)## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa# Example data
x <- c(1, 2, 3, 4, 5)
y <- c(2, 3, 4, 5, 6)
z <- c(3, 4, 5, 6, 7)
# Check if lengths are equal
if (length(x) == length(y) && length(y) == length(z)) {
# Plot the scatterplot
library(scatterplot3d)
scatterplot3d(x, y, z, main="3D Scatterplot")
} else {
# Print an error message if lengths differ
stop("Lengths of 'x', 'y', and 'z' must be the same.")
}
scatterplot3d(iris[,1:3])
scatterplot3d(iris[,1:3], angle = 55)
Change the main title and axis labels
scatterplot3d(iris[,1:3],
main="3D Scatter Plot",
xlab = "Sepal Length (cm)",
ylab = "Sepal Width (cm)",
zlab = "Petal Length (cm)")
# Change the shape and the color of points
scatterplot3d(iris[,1:3], pch = 16, color="steelblue")
Change point shapes by groups
shapes = c(16, 17, 18)
shapes <- shapes[as.numeric(iris$Species)]
scatterplot3d(iris[,1:3], pch = shapes)
# Change point colors by groups
colors <- c("#999999", "#E69F00", "#56B4E9")
colors <- colors[as.numeric(iris$Species)]
scatterplot3d(iris[,1:3], pch = 16, color=colors)
# Change the global appearance of the graph
Remove the box around the plot
scatterplot3d(iris[,1:3], pch = 16, color = colors,
grid=TRUE, box=FALSE)
Add grids on the different factes of scatterplot3d graphics:
# 1. Source the function
source('http://www.sthda.com/sthda/RDoc/functions/addgrids3d.r')
# 2. 3D scatter plot
scatterplot3d(iris[, 1:3], pch = 16, grid=FALSE, box=FALSE)
# 3. Add grids
addgrids3d(iris[, 1:3], grid = c("xy", "xz", "yz"))
Add bars
scatterplot3d(iris[,1:3], pch = 16, type="h",
color=colors)
# Add legends
Specify the legend position using xyz.convert()
s3d <- scatterplot3d(iris[,1:3], pch = 16, color=colors)
legend(s3d$xyz.convert(7.5, 3, 4.5), legend = levels(iris$Species),
col = c("#999999", "#E69F00", "#56B4E9"), pch = 16)
Specify the legend position using keywords
# "right" position
s3d <- scatterplot3d(iris[,1:3], pch = 16, color=colors)
legend("right", legend = levels(iris$Species),
col = c("#999999", "#E69F00", "#56B4E9"), pch = 16)
# Use the argument inset
s3d <- scatterplot3d(iris[,1:3], pch = 16, color=colors)
legend("right", legend = levels(iris$Species),
col = c("#999999", "#E69F00", "#56B4E9"), pch = 16, inset = 0.1)
# "bottom" position
s3d <- scatterplot3d(iris[,1:3], pch = 16, color=colors)
legend("bottom", legend = levels(iris$Species),
col = c("#999999", "#E69F00", "#56B4E9"), pch = 16)
# Customize the legend position
# Custom point shapes
s3d <- scatterplot3d(iris[,1:3], pch = shapes)
legend("bottom", legend = levels(iris$Species),
pch = c(16, 17, 18),
inset = -0.25, xpd = TRUE, horiz = TRUE)
# Custom colors
s3d <- scatterplot3d(iris[,1:3], pch = 16, color=colors)
legend("bottom", legend = levels(iris$Species),
col = c("#999999", "#E69F00", "#56B4E9"), pch = 16,
inset = -0.25, xpd = TRUE, horiz = TRUE)
# Custom shapes/colors
s3d <- scatterplot3d(iris[,1:3], pch = shapes, color=colors)
legend("bottom", legend = levels(iris$Species),
col = c("#999999", "#E69F00", "#56B4E9"),
pch = c(16, 17, 18),
inset = -0.25, xpd = TRUE, horiz = TRUE)
# Add point labels
scatterplot3d(iris[,1:3], pch = 16, color=colors)
text(s3d$xyz.convert(iris[, 1:3]), labels = rownames(iris),
cex= 0.7, col = "steelblue")
# Add regression plane and supplementary points
data(trees)
head(trees)## Girth Height Volume
## 1 8.3 70 10.3
## 2 8.6 65 10.3
## 3 8.8 63 10.2
## 4 10.5 72 16.4
## 5 10.7 81 18.8
## 6 10.8 83 19.73D scatter plot with the regression plane:
# 3D scatter plot
s3d <- scatterplot3d(trees, type = "h", color = "blue",
angle=55, pch = 16)
# Add regression plane
my.lm <- lm(trees$Volume ~ trees$Girth + trees$Height)
s3d$plane3d(my.lm)
# Add supplementary points
s3d$points3d(seq(10, 20, 2), seq(85, 60, -5), seq(60, 10, -10),
col = "red", type = "h", pch = 8)
## Install plot3D package
#install.packages("plot3D")Load plot3D package
library("plot3D")## Warning: package 'plot3D' was built under R version 4.3.2Prepare the data
data(iris)
head(iris)## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosaBasic scatter plot
scatter3D(x, y, z, clab = c("Sepal", "Width (cm)"))
scatter3D(x, y, z, colvar = NULL, col = "blue",
pch = 19, cex = 0.5)
# Change the type of the box around the plot
# full box
scatter3D(x, y, z, bty = "f", colkey = FALSE, main ="bty= 'f'")
# back panels and grid lines are visible
scatter3D(x, y, z, bty = "b2", colkey = FALSE, main ="bty= 'b2'" )
# grey background with white grid lines
scatter3D(x, y, z, bty = "g", colkey = FALSE, main ="bty= 'g'")
# User defined
scatter3D(x, y, z, pch = 18, bty = "u", colkey = FALSE,
main ="bty= 'u'", col.panel ="steelblue", expand =0.4,
col.grid = "darkblue")
# Color palettes
# gg.col: ggplot2 like color
scatter3D(x, y, z, bty = "g", pch = 18, col = gg.col(100))
# ramp.col: custom palettes
scatter3D(x, y, z, bty = "g", pch = 18,
col = ramp.col(c("blue", "yellow", "red")) )
# Change the color by groups
scatter3D(x, y, z, bty = "g", pch = 18,
col.var = as.integer(iris$Species),
col = c("#1B9E77", "#D95F02", "#7570B3"),
pch = 18, ticktype = "detailed",
colkey = list(at = c(2, 3, 4), side = 1,
addlines = TRUE, length = 0.5, width = 0.5,
labels = c("setosa", "versicolor", "virginica")) )
# Change the position of the legend
# Bottom colkey
scatter3D(x, y, z, bty = "g",
colkey = list(side = 1, length = 0.5))
# 3D viewing direction
scatter3D(x, y, z, theta = 15, phi = 20)
scatter3D(x, y, z, phi = 0, bty ="g")
# Titles and axis labels
scatter3D(x, y, z, pch = 18, theta = 20, phi = 20,
main = "Iris data", xlab = "Sepal.Length",
ylab ="Petal.Length", zlab = "Sepal.Width")
# Tick marks and labels
scatter3D(x, y, z, phi = 0, bty = "g",
pch = 20, cex = 2, ticktype = "detailed")
# Add points and text to an existing plot
# Create a scatter plot
scatter3D(x, y, z, phi = 0, bty = "g",
pch = 20, cex = 2, ticktype = "detailed")
# Add another point (black color)
scatter3D(x = 7, y = 3, z = 3.5, add = TRUE, colkey = FALSE,
pch = 18, cex = 3, col = "black")
Line plots
# type ="l" for lines only
scatter3D(x, y, z, phi = 0, bty = "g", type = "l",
ticktype = "detailed", lwd = 4)
# type ="b" for both points and lines
scatter3D(x, y, z, phi = 0, bty = "g", type = "b",
ticktype = "detailed", pch = 20,
cex = c(0.5, 1, 1.5))
# type ="h" for vertical lines
scatter3D(x, y, z, phi = 0, bty = "g", type = "h",
ticktype = "detailed", pch = 19, cex = 0.5)
# Add confidence interval
# Confidence interval
CI <- list(z = matrix(nrow = length(x),
data = rep(0.1, 2*length(x))))
head(CI$z)## [,1] [,2]
## [1,] 0.1 0.1
## [2,] 0.1 0.1
## [3,] 0.1 0.1
## [4,] 0.1 0.1
## [5,] 0.1 0.1# 3D Scatter plot with CI
scatter3D(x, y, z, phi = 0, bty = "g", col = gg.col(100),
pch = 18, CI = CI)
# 3D fancy Scatter plot with small dots on basal plane
# Add small dots on basal plane and on the depth plane
scatter3D_fancy <- function(x, y, z,..., colvar = z)
{
panelfirst <- function(pmat) {
XY <- trans3D(x, y, z = rep(min(z), length(z)), pmat = pmat)
scatter2D(XY$x, XY$y, colvar = colvar, pch = ".",
cex = 2, add = TRUE, colkey = FALSE)
XY <- trans3D(x = rep(min(x), length(x)), y, z, pmat = pmat)
scatter2D(XY$x, XY$y, colvar = colvar, pch = ".",
cex = 2, add = TRUE, colkey = FALSE)
}
scatter3D(x, y, z, ..., colvar = colvar, panel.first=panelfirst,
colkey = list(length = 0.5, width = 0.5, cex.clab = 0.75))
}Fancy scatter plot:
scatter3D_fancy(x, y, z, pch = 16,
ticktype = "detailed", theta = 15, d = 2,
main = "Iris data", clab = c("Petal", "Width (cm)") )
# Regression plane
data(mtcars)
head(mtcars[, 1:6])## mpg cyl disp hp drat wt
## Mazda RX4 21.0 6 160 110 3.90 2.620
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
## Datsun 710 22.8 4 108 93 3.85 2.320
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215
## Hornet Sportabout 18.7 8 360 175 3.15 3.440
## Valiant 18.1 6 225 105 2.76 3.460# x, y, z variables
x <- mtcars$wt
y <- mtcars$disp
z <- mtcars$mpg
# Compute the linear regression (z = ax + by + d)
fit <- lm(z ~ x + y)
# predict values on regular xy grid
grid.lines = 26
x.pred <- seq(min(x), max(x), length.out = grid.lines)
y.pred <- seq(min(y), max(y), length.out = grid.lines)
xy <- expand.grid( x = x.pred, y = y.pred)
z.pred <- matrix(predict(fit, newdata = xy),
nrow = grid.lines, ncol = grid.lines)
# fitted points for droplines to surface
fitpoints <- predict(fit)
# scatter plot with regression plane
scatter3D(x, y, z, pch = 18, cex = 2,
theta = 20, phi = 20, ticktype = "detailed",
xlab = "wt", ylab = "disp", zlab = "mpg",
surf = list(x = x.pred, y = y.pred, z = z.pred,
facets = NA, fit = fitpoints), main = "mtcars")
data(USArrests)
with(USArrests, text3D(Murder, Assault, Rape,
labels = rownames(USArrests), colvar = UrbanPop,
col = gg.col(100), theta = 60, phi = 20,
xlab = "Murder", ylab = "Assault", zlab = "Rape",
main = "USA arrests", cex = 0.6,
bty = "g", ticktype = "detailed", d = 2,
clab = c("Urban","Pop"), adj = 0.5, font = 2))
# text3D and scatter3D
# Plot texts
with(USArrests, text3D(Murder, Assault, Rape,
labels = rownames(USArrests), colvar = UrbanPop,
col = gg.col(100), theta = 60, phi = 20,
xlab = "Murder", ylab = "Assault", zlab = "Rape",
main = "USA arrests", cex = 0.6,
bty = "g", ticktype = "detailed", d = 2,
clab = c("Urban","Pop"), adj = 0.5, font = 2))
# Add points
with(USArrests, scatter3D(Murder, Assault, Rape - 1,
colvar = UrbanPop, col = gg.col(100),
type = "h", pch = ".", add = TRUE))
# Zoom near origin: choose suitable ranges
plotdev(xlim = c(0, 10), ylim = c(40, 150),
zlim = c(7, 25))
hist3D (x = 1:5, y = 1:4, z = VADeaths,
bty = "g", phi = 20, theta = -60,
xlab = "", ylab = "", zlab = "", main = "VADeaths",
col = "#0072B2", border = "black", shade = 0.8,
ticktype = "detailed", space = 0.15, d = 2, cex.axis = 1e-9)
# Use text3D to label x axis
text3D(x = 1:5, y = rep(0.5, 5), z = rep(3, 5),
labels = rownames(VADeaths),
add = TRUE, adj = 0)
# Use text3D to label y axis
text3D(x = rep(1, 4), y = 1:4, z = rep(0, 4),
labels = colnames(VADeaths),
add = TRUE, adj = 1)
scatter2D: 2D scatter plot
# x, y coordinates
set.seed(1234)
x <- sort(rnorm(10))
y <- runif(10)
# Variable for coloring points
col.v <- sqrt(x^2 + y^2) Basic 2D scatter plot:
scatter2D(x, y, colvar = col.v, pch = 16, bty ="n",
type ="b")
# 2D scatter plot with confidence interval:
# Confidence interval for x variable only
CI <- list()
CI$x <- matrix(nrow = length(x), data = c(rep(0.25, 2*length(x))))
scatter2D(x, y, colvar = col.v, pch = 16, bty ="n", cex = 1.5,
CI = CI, type = "b")
# Confidence interval for both x and y variables
CI$y <- matrix (nrow = length(y), data = c(rep(0.05, 2*length(y))))
CI$col <- "black"
scatter2D(x, y, colvar = col.v, pch = 16, bty ="n", cex = 1.5,
CI = CI, type ="b")
CI$y[c(2,4,8,10), ] <- NA # Some points have no CI
CI$x[c(2,4,8,10), ] <- NA # Some points have no CI
CI$alen <- 0.02 # increase arrow head
scatter2D(x, y, colvar = col.v, pch = 16, bty ="n", cex = 1.5,
CI = CI, type ="b")
# text2D
# Only text
with(USArrests, text2D(x = Murder, y = Assault + 5, colvar = Rape,
xlab = "Murder", ylab = "Assault", clab = "Rape",
main = "USA arrests", labels = rownames(USArrests), cex = 0.6,
adj = 0.5, font = 2))
# text with point
with(USArrests, text2D(x = Murder, y = Assault + 5, colvar = Rape,
xlab = "Murder", ylab = "Assault", clab = "Rape",
main = "USA arrests", labels = rownames(USArrests), cex = 0.6,
adj = 0.5, font = 2))
with(USArrests, scatter2D(x = Murder, y = Assault, colvar = Rape,
pch = 16, add = TRUE, colkey = FALSE))
2D arrows:
3D rectangle
rect3D(x0 = 0, y0 = 0.5, z0 = 0, x1 = 1, z1 = 5,
ylim = c(0, 1), bty = "g", facets = TRUE,
border = "red", col ="#7570B3", alpha=0.5,
lwd = 2, phi = 20)
# 2D rectangle:
rect2D(x0 = runif(3), y0 = runif(3),
x1 = runif(3), y1 = runif(3), colvar = 1:3,
alpha = 0.4, lwd = 2, main = "rect2D")
Install and load required packages
#install.packages(c("rgl", "car"))library("car")## Warning: package 'car' was built under R version 4.3.2## Loading required package: carDataPrepare the data
data(iris)
head(iris)## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa#rgl.postscript("plot.pdf",fmt="pdf")Install the RGL package
#install.packages("rgl")Load the RGL package
library("rgl")## Warning: package 'rgl' was built under R version 4.3.2Prepare the data
data(iris)
head(iris)## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa