Bivariate normals in R

bivariate_normals.R

## install.packages(ggplot)
## install.packages(viridis)
## install.packages(ggthemes)

library(ggplot2)
library(viridis)
library(ggthemes)

## Build data
data <- list()
l <- 10000
data$x <- rnorm(l, mean=1, sd=1)
data$y <- rnorm(l, mean=1, sd=1)

f <- function(x,y){
  return(sin(x*y))
}

for(i in c(1:l)){
  data$color <- c(data$color,f(data$x[i], data$y[i]))
}

View(data)
data <- as.data.frame(data)
View(data)

## Simple plot
ggplot(data, aes(x=x,y=y)) +
  geom_point(aes(colour=color))

## Minimally more complicated plot

ggplot(data, aes(x=x,y=y)) +
  geom_point(aes(colour=color))+
  labs(color = "Legend Title\n")+
  scale_color_viridis() 

## Styled plot

title_text = "Blabitty blah blah"
subtitle_text = "By looking at this plot, I agree to give my immortal soul to Nuño Sempere"
label_x_axis = "label x axis"
label_y_axis = "label y axis"
label_color_legend = "label legend"
ggplot(data, aes(x=x,y=y)) +
  geom_point(aes(colour=color))+
  theme_tufte() + 
  labs(
    title=title_text,
    subtitle=subtitle_text,
    x=label_x_axis, 
    y=label_y_axis,
    color=label_color_legend
  ) +
  theme(
    plot.title = element_text(hjust = 0.5),
    plot.subtitle = element_text(hjust = 0.5),
    legend.position="right",
    legend.box="horizontal",
    axis.text.x=element_text(angle=60, hjust=1),
  ) +
  scale_color_viridis() 

# Saving plots
## Saving the last plot
getwd() ## Working directory on which the file will be saved. Can be changed with setwd("/your/directory")
setwd("/home/loki/Documents/temp") ## or somewhere like that
height = 5
width = height*1.05 ## floor(height*(1+sqrt(5))/2)
ggsave("alexplot.png", width=width, height=height)

Result looks like:

To get a rotation

angle_in_degrees = 60
angle_in_radians = (angle_in_degrees/360)*(2*pi)
for(i in c(1:l)){
  y_old = data$y[i]
  x_old = data$x[i]
  x_new = x_old * cos(angle_in_radians) - y_old * sin(angle_in_radians)
  y_new = x_old * sin(angle_in_radians) + y_old * cos(angle_in_radians)
  data$x[i] = x_new
  data$y[i] = y_new
  data$color <- c(data$color,f(data$x[i], data$y[i]))
}