# 3D Axes in Julia

How to format axes of 3d plots in Julia with Plotly.

### Range of axes

3D figures have an attribute in layout called scene, which contains attributes such as xaxis, yaxis and zaxis parameters, in order to set the range, title, ticks, color etc. of the axes.

using PlotlyJS

N = 70
layout = Layout(
scene=attr(
xaxis=attr(
nticks=4,
range=[-100,100]
),
yaxis=attr(
nticks=4,
range=[-50,100]
),
zaxis=attr(
nticks=4,
range=[-100,100]
),
),
width=700,
margin=attr(
r=20,
l=10,
b=10,
t=10
),
)

plot(mesh3d(
x=(70 .* randn(N)),
y=(55 .* randn(N)),
z=(40 .* randn(N)),
color="rgba(244,22,100,0.6)"
),
layout,
)

### Fixed Ratio Axes

using PlotlyJS

N = 50

fig = make_subplots(rows=2, cols=2, specs=fill(Spec(kind="scene"), 2, 2))

relayout!(
fig,
# fix the ratio in the top left subplot to be a cube
scene_aspectmode="cube",
# manually force the z-axis to appear twice as big as the other two
scene2=attr(aspectmode="manual", aspectratio=attr(x=1, y=1, z=2)),
# draw axes in proportion to the proportion of their ranges
scene3_aspectmode="data",
# automatically produce something that is well proportioned using "data" as the default
scene4_aspectmode="auto",
)

for i in 1:2, j in 1:2
fig,
mesh3d(
x=(60 .* randn(N)),
y=(25 .* randn(N)),
z=(40 .* randn(N)),
opacity=0.5,
),
row=i, col=j
)
end

fig

### Set Axes Title

using PlotlyJS
# Define random surface
N = 50
trace1 = mesh3d(x=(60 .* randn(N)),
y=(25 .* randn(N)),
z=(40 .* randn(N)),
opacity=0.5,
color="yellow"
)
trace2 = mesh3d(x=(70 .* randn(N)),
y=(55 .* randn(N)),
z=(30 .* randn(N)),
opacity=0.5,
color="pink"
)

layout = Layout(scene = attr(
xaxis_title="X AXIS TITLE",
yaxis_title="Y AXIS TITLE",
zaxis_title="Z AXIS TITLE"),
width=700,
margin=attr(r=20, b=10, l=10, t=10))

plot([trace1, trace2], layout)

### Ticks Formatting

using PlotlyJS
# Define random surface
N = 50
trace = mesh3d(x=(60 .* randn(N)),
y=(25 .* randn(N)),
z=(40 .* randn(N)),
opacity=0.5,
color="rgba(100,22,200,0.5)"
)

# Different types of customized ticks
layout = Layout(scene = attr(
xaxis = attr(
ticktext= ["TICKS","MESH","PLOTLY","JULIA"],
tickvals= [0,50,75,-50]),
yaxis = attr(
nticks=5, tickfont=attr(
color="green",
size=12,
family="Old Standard TT, serif",),
ticksuffix="#"),
zaxis = attr(
nticks=4, ticks="outside",
tick0=0, tickwidth=4),),
width=700,
margin=attr(r=10, l=10, b=10, t=10)
)

plot(trace, layout)

### Background and Grid Color

using PlotlyJS

N = 50
trace = mesh3d(x=(30 .* randn(N)),
y=(25 .* randn(N)),
z=(30 .* randn(N)),
opacity=0.5)

# xaxis.backgroundcolor is used to set background color
layout = Layout(scene = attr(
xaxis = attr(
backgroundcolor="rgb(200, 200, 230)",
gridcolor="white",
showbackground=true,
zerolinecolor="white",),
yaxis = attr(
backgroundcolor="rgb(230, 200,230)",
gridcolor="white",
showbackground=true,
zerolinecolor="white"),
zaxis = attr(
backgroundcolor="rgb(230, 230,200)",
gridcolor="white",
showbackground=true,
zerolinecolor="white",),),
width=700,
margin=attr(
r=10, l=10,
b=10, t=10)
)
plot(trace, layout)

### Disabling tooltip spikes

By default, guidelines originating from the tooltip point are drawn. It is possible to disable this behaviour with the showspikes parameter. In this example we only keep the z spikes (projection of the tooltip on the x-y plane). Hover on the data to show this behaviour.

using PlotlyJS

N = 50
trace = mesh3d(x=(30 .* randn(N)),
y=(25 .* randn(N)),
z=(30 .* randn(N)),
opacity=0.5)
layout = Layout(scene=attr(xaxis_showspikes=false,
yaxis_showspikes=false))

plot(trace, layout)