# 3D Streamtube Plots in Python

How to make 3D streamtube plots in Python with Plotly.

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Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

### Introduction¶

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.

### Basic Streamtube Plot¶

In [1]:
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()


### Starting Position and Segments¶

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.

In [2]:
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()


### Tube color and diameter¶

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.

In [3]:
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.flatten()
y = y.flatten()
z = z.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()


#### Reference¶

See https://plotly.com/python/reference/streamtube/ for more information and chart attribute options!

### What About Dash?¶

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

from dash import Dash, dcc, html

app = Dash()
app.layout = html.Div([
dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter