How to make this plot in Julia?

Specific Domains Visualization
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21

Ahh, now I got it:

using AlgebraOfGraphics, GLMakie
using Random, DataFrames
Random.seed!(123)
d = DataFrame(name = repeat(["A","B","C","D","E","F"], inner=4), 
      time=repeat([0,1,3,6], outer=6), value = rand(24));
plt = data(d)*( 
       (visual(Scatter) + visual(Lines)) * mapping(:time, :value, color = :name) + 
        visual(Makie.Text) * mapping(:time, :value, color = :name, text = :name => verbatim) 
       );
AlgebraOfGraphics.draw(plt)

billede
billede801×641 78.3 KB

Thank you for your help!

2 Likes
22

Here’s an example using Bokeh.jl. It’s quite long, because you need to be explicit about a lot of things, but I’ve been thinking about an AoG-style wrapper for it.

using DataFrames, Random, Bokeh
# OP's data
Random.seed!(123)
d = DataFrame(name = repeat(["A","B","C","D","E","F"], inner=4), 
      time=repeat([0,1,3,6], outer=6), value = rand(24));
# (optional) displays plots in the browser - omit if you are in a notebook
Bokeh.settings!(display=:browser)
# make the figure
fig = figure()
# set the axis labels
fig.x_axis.axis_label = "time"
fig.y_axis.axis_label = "value"
# (optional) by default the legend is placed inside the plot
plot!(fig, Legend; location="right")
# defines the mapping from names to colors
color = factor_cmap("name", "Set2_8", sort(unique(d.name)))
# defines the data source
source = ColumnDataSource(data=d)
# add scatter plot
plot!(fig, Scatter; x="time", y="value", source, color, size=10, legend_field="name")
# add text
plot!(fig, Bokeh.Text; x="time", y="value", text="name", source, color, text_baseline="middle", x_offset=10)
# add lines - note bokeh will not group lines for you, so you must
# group the data yourself and either make multiple `Line` plots or
# one `MultiLine` plot
w = combine(groupby(d, :name), d->(time=[d.time], value=[d.value]))
plot!(fig, MultiLine; xs="time", ys="value", source=w, color)
# show the result
display(fig)

Edit: here is the result.

image
image600×597 47.5 KB

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23

Thank you @cjdoris
I’ve heard a lot of good things about Bokeh in python, but never tried it. Great that we also have it in Julia.

1 Like
24

I just dug out my AoG-style wrapper for Bokeh: GitHub - cjdoris/Algebrokeh.jl: Statistical plotting with Bokeh.

The gist is:

# You can't use Line glyph with color mapping, so need to explicitly
# group and use the MultiLine glyph (currently).
gd = combine(groupby(d, :name), d->(time=[d.time], value=[d.value]))
# Should look familiar to AoG users!
((data(d) * (visual(Scatter) + visual(Bokeh.Text)) + data(gd) * visual(MultiLine))
 * mapping(x="time", y="value", color="name", text="name")
) |> draw |> display

image
image593×596 49.2 KB

3 Likes
25

Did you write this 300-LOC package in less then 1h?

26

Lol no I wrote the code months ago and this post prompted me to put it on GitHub :slight_smile:

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27

AoG-style wrapper for Bokeh
Wow! This is looking great!

28

It would be great for this example to be in the AofG gallery.

29

The Makie.Text part is covered by this example: https://aog.makie.org/stable/gallery/gallery/scales/prescaled_data/#Pre-scaled-data
Not sure how typical this plot actually is. What would be a good name for it?

30

You can make your code a little more concise by using visual(ScatterLines). You can also use the distributive property of mappings (that’s a matter of taste, though)

	# Version 1
	plt = data(d) * 
		mapping(:time, :value, color = :name) * (
			visual(ScatterLines) + 
			visual(Makie.Text) * mapping(text = :name => verbatim)
		)

	# Version 2 (works because ScatterLines ignores unused kwarg `text`)
	plt = data(d) * 
		mapping(:time, :value, color = :name, text = :name => verbatim) *
		(visual(ScatterLines) + visual(Makie.Text))
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