Smith Charts in Python

How to make Smith Charts with plotly.

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.

New in v5.4

A Smith Chart is a specialized chart for visualizing complex numbers: numbers with both a real and imaginary part.

Smith Charts with Plotly Graph Objects¶

In [1]:

import plotly.graph_objects as go

fig = go.Figure(go.Scattersmith(imag=[0.5, 1, 2, 3], real=[0.5, 1, 2, 3]))
fig.show()

Smith Chart Subplots and Styling¶

In [2]:

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scattersmith(
    imag=[1],
    real=[1],
    marker_symbol='x',
    marker_size=30,
    marker_color="green",
    subplot="smith1"
))

fig.add_trace(go.Scattersmith(
    imag=[1],
    real=[1],
    marker_symbol='x',
    marker_size=30,
    marker_color="pink",
    subplot="smith2"
))

fig.update_layout(
    smith=dict(
        realaxis_gridcolor='red',
        imaginaryaxis_gridcolor='blue',
        domain=dict(x=[0,0.45])
    ),
    smith2=dict(
        realaxis_gridcolor='blue',
        imaginaryaxis_gridcolor='red',
        domain=dict(x=[0.55,1])
    )
)

fig.update_smiths(bgcolor="lightgrey")

fig.show()

Reference¶

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

In [ ]:

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