#Number of simulations and chunk-size
sN <- 265
sM <- 10
#Line from 0 to 1 will be divided into 40 bins
bin <- seq(0 + (1 / 40) / 2, 1 - (1 / 40) / 2, 1 / 40)
bincnt <- rep(0, 40)
#Vertical distance between dots
icr <- 0.01
printx <- NULL
printy <- NULL
for (i in 1:sN) {
if (i < 15)
sMI <- 1
if (i > 14)
sMI <- sM
sim <- runif(sMI)
Sys.sleep(0.1)
pointx <- rep(0, sMI)
pointy <- rep(0, sMI)
for (j in 1:sMI) {
idx <- sim[j] %/% (1 / 40) + 1
pointx[j] <- bin[idx]
pointy[j] <- bincnt[idx] + 1
pointy[j] <- max(icr, (pointy[j] * icr) %% 1) %% 1
bincnt[idx] <- bincnt[idx] + 1
}
printx <- c(printx, pointx)
printy <- c(printy, pointy)
plot(
seq(0, 1, 0.01),
dunif(seq(0, 1, 0.01)),
type = "l",
xlab = "value",
ylab = "Uniform density",
ylim = c(0, 1.2),
col = "red",
lwd = 5
)
points(printx, printy, pch = 20)
}
#Procedure repeated with Gaussian distribution
sN <- 365
sM <- 5
#Line from -3 to 3 divided into 100 bins
bin <- seq(-3 + (6 / 100) / 2, 3 - (6 / 100) / 2, 6 / 100)
bincnt <- rep(0, 100)
icr <- 0.01
printx <- NULL
printy <- NULL
for (i in 1:sN) {
if (i < 15)
sMI <- 1
if (i > 14)
sMI <- sM
sim <- rnorm(sMI)
Sys.sleep(0.1)
for (j in 1:sMI) {
idx <- (3 + sim[j]) %/% (6 / 100)
if (idx > 0 & idx < 101) {
pointx <- bin[idx]
pointy <- bincnt[idx] + 1
pointy <- max(icr, (pointy * icr) %% 1) %% 1
printx <- c(printx, pointx)
printy <- c(printy, pointy)
bincnt[idx] <- bincnt[idx] + 1
}
}
plot(
seq(-3, 3, 0.01),
dnorm(seq(-3, 3, 0.01)),
type = "l",
xlab = "value",
ylab = "Gaussian density",
ylim = c(0, 0.5),
col = "red",
lwd = 5
)
points(printx, printy, pch = 20)
}
getwd()
setwd("C:/plots")
getwd()
#Procedure repeated with Gaussian distribution
sN <- 365
sM <- 5
#Line from -3 to 3 divided into 100 bins
bin <- seq(-3 + (6 / 100) / 2, 3 - (6 / 100) / 2, 6 / 100)
bincnt <- rep(0, 100)
#install.packages("animation")
#library(animation)
#ani.record(reset = TRUE)
icr <- 0.01
printx <- NULL
printy <- NULL
png("GaussianDensity%03d.png")
for (i in 1:sN) {
if (i < 15)
sMI <- 1
if (i > 14)
sMI <- sM
sim <- rnorm(sMI)
Sys.sleep(0.1)
for (j in 1:sMI) {
idx <- (3 + sim[j]) %/% (6 / 100)
if (idx > 0 & idx < 101) {
pointx <- bin[idx]
pointy <- bincnt[idx] + 1
pointy <- max(icr, (pointy * icr) %% 1) %% 1
printx <- c(printx, pointx)
printy <- c(printy, pointy)
bincnt[idx] <- bincnt[idx] + 1
}
}
plot(
seq(-3, 3, 0.01),
dnorm(seq(-3, 3, 0.01)),
type = "l",
xlab = "value",
ylab = "Gaussian density",
ylim = c(0, 0.5),
col = "red",
lwd = 5
)
points(printx, printy, pch = 20)
}
dev.off()
#oopts = ani.options(interval = 0.1)
#ani.replay()
#install.packages("R2SWF")
library(R2SWF)
output = image2swf(sprintf("GaussianDensity%03d.png", 1:365), interval = 0.05)
swf2html(output)
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