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April 23, 2023 01:09
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Code to generate wallpaper (bivariate normal distribution)
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rm(list=ls()) | |
setwd("/home/wviechtb/misc/wallpapers/bivariate_normal") | |
library(mvtnorm) | |
library(ellipse) | |
### specify the correlation for the bivariate normal distribution | |
rho <- 0.4 | |
### number of points for x and y at which to evaluate the density of the bivariate normal distribution | |
n <- 501 | |
sigma <- matrix(c(1,rho,rho,1), nrow=2) | |
x <- seq(-3.5, 3.5, length=n) | |
y <- seq(-3.5, 3.5, length=n) | |
z <- matrix(NA, nrow=n, ncol=n) | |
for (i in seq_along(x)) { | |
for (j in seq_along(y)) { | |
z[i,j] <- dmvnorm(c(x[i],y[j]), sigma=sigma) | |
} | |
} | |
z[z <= .001] <- 0 | |
jpeg("bivariate_normal_2.jpg", width=2732, height=1536, quality=100, bg="gray10", type="cairo") | |
### bivariate normal surface | |
par(mar=c(6,0,6,0)) | |
nrz <- nrow(z) | |
ncz <- ncol(z) | |
cols <- colorRampPalette(c(rgb(36,36,36,maxColorValue=255), "gray60")) | |
nbcol <- 10000 | |
color <- cols(nbcol) | |
zfacet <- z[-1, -1] + z[-1, -ncz] + z[-nrz, -1] + z[-nrz, -ncz] | |
facetcol <- cut(zfacet, nbcol) | |
col <- color[facetcol] | |
val <- .136 | |
col[c(zfacet) <= .001] <- rgb(val,val,val) | |
sav <- persp(x, y, z, theta=0, phi=25, r=100, d=1, box=FALSE, col=col, border=NA, expand=0.4, ltheta=-125, lphi=-10, shade=.3) | |
### add pdf text | |
text(0, 0.006, col="gray70", pos=1, cex=2.6, | |
expression(frac(1, 2 ~ pi ~ sigma[x] ~ sigma[y] ~ sqrt(1 - rho^2)) ~ | |
exp ~ bgroup("[", -frac(1,2*(1-rho^2)) ~ bgroup("(", frac((x-mu[x])^2, sigma[x]^2) ~ + ~ | |
frac((y-mu[y])^2, sigma[y]^2) ~ - ~ | |
frac(2 ~ rho ~ (x-mu[x]) ~ (y-mu[y]), sigma[x] ~ sigma[y]), | |
")"), | |
"]") | |
) | |
) | |
dev.off() |
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