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Quiver Plots in Python

How to make a quiver plot in Python. A quiver plot displays velocity vectors a arrows.


If you're using Dash Enterprise's Data Science Workspaces, you can copy/paste any of these cells into a Workspace Jupyter notebook.
Alternatively, download this entire tutorial as a Jupyter notebook and import it into your Workspace.
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New to Plotly?

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.

Quiver plots can be made using a figure factory as detailed in this page.

Basic Quiver Plot

In [1]:
import plotly.figure_factory as ff

import numpy as np

x,y = np.meshgrid(np.arange(0, 2, .2), np.arange(0, 2, .2))
u = np.cos(x)*y
v = np.sin(x)*y

fig = ff.create_quiver(x, y, u, v)
fig.show()

Quiver Plot with Points

In [2]:
import plotly.figure_factory as ff
import plotly.graph_objects as go

import numpy as np

x,y = np.meshgrid(np.arange(-2, 2, .2),
                  np.arange(-2, 2, .25))
z = x*np.exp(-x**2 - y**2)
v, u = np.gradient(z, .2, .2)

# Create quiver figure
fig = ff.create_quiver(x, y, u, v,
                       scale=.25,
                       arrow_scale=.4,
                       name='quiver',
                       line_width=1)

# Add points to figure
fig.add_trace(go.Scatter(x=[-.7, .75], y=[0,0],
                    mode='markers',
                    marker_size=12,
                    name='points'))

fig.show()

See also

Cone plot for the 3D equivalent of quiver plots.

Reference

For more info on ff.create_quiver(), see the full function reference

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( ... )

import dash
import dash_core_components as dcc
import dash_html_components as html

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

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