3D Cone Plots in Python
How to make 3D Cone plots in Python with Plotly.
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A cone plot is the 3D equivalent of a 2D quiver plot, i.e., it represents a 3D vector field using cones to represent the direction and norm of the vectors. 3-D coordinates are given by x
, y
and z
, and the coordinates of the vector field by u
, v
and w
.
Basic 3D Cone¶
In [1]:
import plotly.graph_objects as go
fig = go.Figure(data=go.Cone(x=[1], y=[1], z=[1], u=[1], v=[1], w=[0]))
fig.update_layout(scene_camera_eye=dict(x=-0.76, y=1.8, z=0.92))
fig.show()
Multiple 3D Cones¶
In [2]:
import plotly.graph_objects as go
fig = go.Figure(data=go.Cone(
x=[1, 2, 3],
y=[1, 2, 3],
z=[1, 2, 3],
u=[1, 0, 0],
v=[0, 3, 0],
w=[0, 0, 2],
sizemode="absolute",
sizeref=2,
anchor="tip"))
fig.update_layout(
scene=dict(domain_x=[0, 1],
camera_eye=dict(x=-1.57, y=1.36, z=0.58)))
fig.show()
3D Cone Lighting¶
In [3]:
import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Cone(x=[1,] * 3, name="base"))
fig.add_trace(go.Cone(x=[2,] * 3, opacity=0.3, name="opacity:0.3"))
fig.add_trace(go.Cone(x=[3,] * 3, lighting_ambient=0.3, name="lighting.ambient:0.3"))
fig.add_trace(go.Cone(x=[4,] * 3, lighting_diffuse=0.3, name="lighting.diffuse:0.3"))
fig.add_trace(go.Cone(x=[5,] * 3, lighting_specular=2, name="lighting.specular:2"))
fig.add_trace(go.Cone(x=[6,] * 3, lighting_roughness=1, name="lighting.roughness:1"))
fig.add_trace(go.Cone(x=[7,] * 3, lighting_fresnel=2, name="lighting.fresnel:2"))
fig.add_trace(go.Cone(x=[8,] * 3, lightposition=dict(x=0, y=0, z=1e5),
name="lighting.position x:0,y:0,z:1e5"))
fig.update_traces(y=[1, 2, 3], z=[1, 1, 1],
u=[1, 2, 3], v=[1, 1, 2], w=[4, 4, 1],
hoverinfo="u+v+w+name",
showscale=False)
fig.update_layout(scene=dict(aspectmode="data",
camera_eye=dict(x=0.05, y=-2.6, z=2)),
margin=dict(t=0, b=0, l=0, r=0))
fig.show()
3D Cone Vortex¶
In [4]:
import plotly.graph_objects as go
import pandas as pd
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/vortex.csv")
fig = go.Figure(data = go.Cone(
x=df['x'],
y=df['y'],
z=df['z'],
u=df['u'],
v=df['v'],
w=df['w'],
colorscale='Blues',
sizemode="absolute",
sizeref=40))
fig.update_layout(scene=dict(aspectratio=dict(x=1, y=1, z=0.8),
camera_eye=dict(x=1.2, y=1.2, z=0.6)))
fig.show()
Sizemode¶
Earlier examples use sizemode="absolute"
when adjusting the cone size scaling with sizeref
. sizemode
also supports raw
(new in 5.21) and scaled
.
In [5]:
import plotly.graph_objects as go
import pandas as pd
df = pd.read_csv(
"https://raw.githubusercontent.com/plotly/datasets/master/cone_plot_data.csv"
)
fig = go.Figure(
data=go.Cone(
x=df["x"],
y=df["y"],
z=df["z"],
u=df["u"],
v=df["v"],
w=df["w"],
sizemode="raw",
sizeref=0.1,
colorscale="Portland",
cmin=0,
cmax=80,
hoverinfo="u+v+w+text",
text="-> wind <-",
),
layout=dict(
width=900, height=600, scene=dict(camera=dict(eye=dict(x=1.2, y=0, z=0.6)))
),
)
fig.show()