pysmithchart

pysmithchart

pysmithchart is a Python library that provides high-quality Smith charts for RF and microwave engineering applications. Built as a native extension to matplotlib, it enables reproducible analysis and publication-ready visualization of reflection coefficients, impedances, and admittances commonly encountered in transmission-line theory, antenna characterization, and network analysis.

Smith charts remain a foundational tool in RF engineering, and this library is designed to support both instructional use and research workflows. By integrating directly with matplotlib’s projection system, pysmithchart enables familiar plotting syntax while offering fine-grained control of chart geometry, grid styling, interpolation, and layout.

This project originated from pySmithPlot by Paul Staerke. It has been completely rewritten so any issues are not his.

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Features

• Seamless matplotlib integration — implemented as a projection; compatible with standard plotting workflows

• Support for common RF quantities — reflection coefficients, impedances, admittances, and S-parameters

• Configurable analytical grids — control spacing, style, and precision of constant-R and constant-X curves

• Interpolation utilities — optional smoothing and resampling of complex-valued datasets

• Custom marker rotation — useful for frequency-indexed trajectories and multi-point measurement data

• Publication-quality output — full control over fonts, colors, annotations, and line styling

Installation

Using pip:

pip install pysmithchart

Using conda:

conda install -c conda-forge pysmithchart

Quick Start

Reflection Coefficients (S-Parameters)

import matplotlib.pyplot as plt
from pysmithchart import R_DOMAIN

S = [0.5 + 0.3j, -0.2 - 0.1j]

plt.figure(figsize=(6, 6))
plt.subplot(1, 1, 1, projection="smith")
plt.plot(S, domain=R_DOMAIN, marker='o', markersize=10, label='S₁₁')
plt.legend()
plt.title('Reflection Coefficients')
plt.show()

Normalized Impedance Example

import matplotlib.pyplot as plt
import pysmithchart

ZL = [30 + 30j, 50 + 50j, 100 + 100j]

sc = {"grid.Z.minor_enable":True}
plt.figure(figsize=(6, 6))
ax = plt.subplot(1, 1, 1, projection="smith", Z0=200, **sc)
plt.plot(ZL, "b-o", markersize=10, label='Load Impedance')
plt.legend()
plt.title('Impedances with Z₀ = 200Ω')
plt.show()

Documentation

Comprehensive documentation, including the API reference, tutorials, theoretical background, and worked examples, is available at:

https://pysmithchart.readthedocs.io

A live, browser-based environment powered by JupyterLite is available for experimentation without installation:

https://scottprahl.github.io/pysmithchart/

License

pysmithchart is released under the BSD-3 Clause License.

Citation

If you use pysmithchart in academic or technical work, please cite:

Prahl, S. (2026). pysmithchart: A Python module for Smith charts (Version 0.6.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.8370821

BibTeX

@software{pygrin_prahl_2026,
  author    = {Scott Prahl},
  title     = {pysmithchart: A Python module for Smith charts},
  year      = {2026},
  version   = {0.6.0},
  doi       = {10.5281/zenodo.8370821},
  url       = {https://github.com/scottprahl/pygrin},
  publisher = {Zenodo}
}

Getting Started

• Quickstart
  • Create a Smith chart axis
  • Changing the default characteristic impedance
  • Adding labels with ax.text()
• Smith chart domains
  • Domain quick reference
  • How to set the domain
  • A single physical load shown four ways
  • What about ax.text() and ax.annotate()?
• Admittance Smith Charts
  • Simplified Interface
  • 1. Basic Admittance Chart
  • 2. Admittance Chart with Minor Grid
  • 3. Fancy Mode (Adaptive Clipping)
  • 4. Fancy Mode with Minor Grid
  • 5. Customized Admittance Grid Colors
  • 6. Dual Grid: Impedance + Admittance
  • 7. Standard vs Fancy Mode Comparison
  • 8. Different Division Settings
  • 9. Practical Example: Parallel RC Circuit

How-To Guides

• Plotting data on a Smith chart
  • ax.plot() vs ax.scatter()
  • What inputs does plot() accept?
  • Points vs lines in plot() (format strings, markers, and line styles)
  • Marker control with ax.scatter()
  • Traces: plotting a sweep
  • ax.text() vs ax.annotate()
  • Plotting in Γ (reflection coefficient)
  • 5. Plotting with normalized impedance (NORM_Z_DOMAIN)
• VSWR and circles on the Smith chart
  • VSWR and \(|\Gamma|\)
  • Reading VSWR on the horizontal axis
  • VSWR circles with pysmithchart
  • The same circles shown in Γ coordinates
  • VSWR for a point
• Rotations and transmission lines
  • 1. Rotation in the \(\Gamma\) plane (R_DOMAIN)
  • Half-wavelength periodicity
  • The same motion in impedance coordinates (Z_DOMAIN)
  • Rotate “toward generator” vs “toward load”
  • Quarter-wave transformer example
• Arrow Support in Smith Charts
  • Basic Arrow Usage with ax.plot()
  • Custom Arrow Styles
  • Arrow Size Control
  • Arrows on Constant Resistance Circles
  • Arrows on Constant Reactance Arcs
  • Admittance Arrows
  • Arrows on VSWR Circles
  • Arrows on Matching Paths
• Impedance Matching: Practical Design Examples at 1 GHz
  • Key Formulas
  • Quarter-Wave Transformer to match resistive load
  • Example 2: Single-Stub Matching (Series)
  • Example 3: Single-Stub Matching (Shunt)
  • Example 4: L-Network Matching (Series-Shunt)
  • Example 5: Double-Stub Matching
• Customize grid, colors, and tick labels
  • Recommended configuration pattern
  • 1. Default grid and ticks
  • 2. Enable/disable major and minor grids (reusable config)
  • 3. Changing grid colors
  • 3a. Styling the outer boundary (Smith-circle frame)
  • 3b. Using alpha to emphasize major vs minor grids
  • 4. Changing the number of major divisions (tick locations)
  • 5. Minor grid density
  • 6. “Fancy” grid style
  • 7. Tick-label formatting and precision
  • Summary

API

Changelog

changelog

Versions

• CHANGELOG