jupyter | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
In streamtube plots, attributes include x
, y
, and z
, which set the coordinates of the vector field, and u
, v
, and w
, which set the x, y, and z components of the vector field. Additionally, you can use starts
to determine the streamtube's starting position.
import plotly.graph_objects as go
fig = go.Figure(data=go.Streamtube(x=[0, 0, 0], y=[0, 1, 2], z=[0, 0, 0],
u=[0, 0, 0], v=[1, 1, 1], w=[0, 0, 0]))
fig.show()
By default, streamlines are initialized in the x-z plane of minimal y value. You can change this behaviour by providing directly the starting points of streamtubes.
import plotly.graph_objects as go
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/streamtube-wind.csv').drop(['Unnamed: 0'],axis=1)
fig = go.Figure(data=go.Streamtube(
x = df['x'],
y = df['y'],
z = df['z'],
u = df['u'],
v = df['v'],
w = df['w'],
starts = dict(
x = [80] * 16,
y = [20,30,40,50] * 4,
z = [0,0,0,0,5,5,5,5,10,10,10,10,15,15,15,15]
),
sizeref = 0.3,
colorscale = 'Portland',
showscale = False,
maxdisplayed = 3000
))
fig.update_layout(
scene = dict(
aspectratio = dict(
x = 2,
y = 1,
z = 0.3
)
),
margin = dict(
t = 20,
b = 20,
l = 20,
r = 20
)
)
fig.show()
The color of tubes is determined by their local norm, and the diameter of the field by the local divergence of the vector field.
In all cases below the norm is proportional to z**2
but the direction of the vector is different, resulting in a different divergence field.
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import numpy as np
x, y, z = np.mgrid[0:10, 0:10, 0:10]
x = x.T.flatten()
y = y.T.flatten()
z = z.T.flatten()
u = np.zeros_like(x)
v = np.zeros_like(y)
w = z**2
fig = make_subplots(rows=1, cols=3, specs=[[{'is_3d': True}, {'is_3d': True}, {'is_3d':True}]])
fig.add_trace(go.Streamtube(x=x, y=y, z=z, u=u, v=v, w=w), 1, 1)
fig.add_trace(go.Streamtube(x=x, y=y, z=z, u=w, v=v, w=u), 1, 2)
fig.add_trace(go.Streamtube(x=x, y=y, z=z, u=u, v=w, w=v), 1, 3)
fig.update_layout(scene_camera_eye=dict(x=2, y=2, z=2),
scene2_camera_eye=dict(x=2, y=2, z=2),
scene3_camera_eye=dict(x=2, y=2, z=2))
fig.show()
See https://plot.ly/python/reference/ for more information and chart attribute options!