Table of Contents¶

1 Plotting in Julia

1.1 Gadfly.jl

1.2 Plots.jl

Plotting in Julia¶

The three most popular options (as far as I know) in Julia are

Gadfly.jl
- Julia equivalent of ggplot2 in R

PyPlot.jl
- Wrapper for Python's matplotlib

Plots.jl
- Defines an unified interface for plotting
- maps arguments to different plotting "backends"
  - PyPlot, GR, PlotlyJS, and many more
- For a complete list of backends: http://docs.juliaplots.org/latest/backends/
- Mapping of attributes to backends: http://docs.juliaplots.org/latest/supported/
- First runs can be slowish. I found the GR backend fastest and most stable.

Gadfly.jl¶

To demonstrate Gadfly, we will go through an example and compare it to ggplot2.

#Pkg.add("Gadfly")

using RCall

R"""
library(ggplot2)
library(dplyr)

df <- ToothGrowth %>%
  group_by(supp, dose) %>%
  summarise(se = sd(len) / n(), len = mean(len), n = n())

ggplot(df, aes(x = dose, y = len, group = supp, color = supp)) + 
  geom_line() +
  geom_point() +
  geom_errorbar(aes(ymin = len - se, ymax = len + se), width = 0.1, alpha = 0.5,
  position = position_dodge(0.005)) +  
  scale_color_manual(values = c(VC = "skyblue", OJ = "orange")) + 
  labs(x = "Dose", y = "Tooth Length") 
"""

┌ Warning: RCall.jl: 
│ Attaching package: ‘dplyr’
│ 
│ The following objects are masked from ‘package:stats’:
│ 
│     filter, lag
│ 
│ The following objects are masked from ‘package:base’:
│ 
│     intersect, setdiff, setequal, union
│ 
└ @ RCall /Users/huazhou/.julia/packages/RCall/ffM0W/src/io.jl:113

RObject{VecSxp}

@rget df # retrieve dataframe from R to Julia workspace
using Gadfly
df[:ymin] = df[:len] - df[:se]
df[:ymax] = df[:len] + df[:se]
Gadfly.plot(df, x = :dose, y = :len, color = :supp, Geom.point,
    Guide.xlabel("Dose"), Guide.ylabel("Tooth Length"), 
    Guide.xticks(ticks = [0.5, 1.0, 1.5, 2.0]),
    Geom.line, Geom.errorbar, ymin = :ymin, ymax = :ymax, 
    Scale.color_discrete_manual("orange", "skyblue"))

┌ Info: Loading DataFrames support into Gadfly.jl
└ @ Gadfly /Users/huazhou/.julia/packages/Gadfly/09PWZ/src/mapping.jl:228

Both offer more customized options

R"""
ggplot(df, aes(x = dose, y = len, group = supp, color = supp)) + 
  geom_line() +
  geom_point() +
  geom_errorbar(aes(ymin = len - se, ymax = len + se), width = 0.1, alpha = 0.5, 
    position = position_dodge(0.005)) + 
    theme(legend.position = c(0.8,0.1), 
    legend.key = element_blank(), 
    axis.text.x = element_text(angle = 0, size = 11), 
    axis.ticks = element_blank(), 
    panel.grid.major = element_blank(), 
    legend.text=element_text(size = 11),
    panel.border = element_blank(), 
    panel.grid.minor = element_blank(), 
    panel.background = element_blank(), 
    axis.line = element_line(color = 'black',size = 0.3), 
  plot.title = element_text(hjust = 0.5)) + 
  scale_color_manual(values = c(VC = "skyblue", OJ = "orange")) + 
  labs(x = "Dose", y = "Tooth Length")
"""

RObject{VecSxp}

Gadfly.plot(df, x = :dose, y = :len, color = :supp, Geom.point,
    Guide.xlabel("Dose"), Guide.ylabel("Tooth Length"), 
    Guide.xticks(ticks = [0.5, 1.0, 1.5, 2.0]),
    Theme(panel_fill = nothing, highlight_width = 0mm, point_size = 0.5mm,
    key_position = :inside, 
    grid_line_width = 0mm, panel_stroke = colorant"black"),
    Geom.line, Geom.errorbar, ymin = :ymin, ymax = :ymax, 
    Scale.color_discrete_manual("orange", "skyblue"))

Plots.jl¶

We demonstrate Plots.jl below:

# Pkg.add("Plots")
using Plots, Random

Random.seed!(123) # set seed
x = cumsum(randn(50, 2), dims=1);

# Pkg.add("PyPlot")
pyplot()  # set the backend to PyPlot
Plots.plot(x, title="Random walk", xlab="time")

gr()   # change backend to GR
Plots.plot(x, title="Random walk", xlab="time")

gr()
@gif for i in 1:20
    Plots.plot(x -> sin(x) / (.2i), 0, i, xlim=(0, 20), ylim=(-.75, .75))
    scatter!(x -> cos(x) * .01 * i, 0, i, m=1)
end;

┌ Info: Saved animation to 
│   fn = /Users/huazhou/Documents/github.com/Hua-Zhou.github.io/teaching/biostatm280-2019spring/slides/02-juliaintro/tmp.gif
└ @ Plots /Users/huazhou/.julia/packages/Plots/47Tik/src/animation.jl:90

# Pkg.add("PlotlyJS")
plotlyjs()  # change backend to PlotlyJS
Plots.plot(x, title="Random walk", xlab="time")