snp2le: S-Parameter To Lumped Element Netlist Converter

(c) 2026 Simon Dorrer

Institute for Integrated Circuits and Quantum Computing (IICQC), Johannes Kepler University (JKU), Linz, Austria

[!IMPORTANT] The converter (GUI and CLI) runs anywhere with Python ≥ 3.10, see Install below. Running the exported netlists in a testbench additionally needs Xschem plus Ngspice and/or VACASK. The easiest way to get all of them is the IIC-OSIC-TOOLS container. Since tag 2026.07, snp2le has been installed directly in the IIC-OSIC-TOOLS container.

Description

snp2le turns a Touchstone .sNp S-parameter file (for example from an AWS Palace EM simulation) into an equivalent lumped-element netlist for Ngspice (Berkeley SPICE3) and VACASK (Spectre syntax). An EM-extracted structure can then be co-simulated at circuit level, without re-running the field solve.

It offers two conversion philosophies:

• Universal (any N-port). Vector-fits the S-parameters with scikit-rf VectorFitting, optionally enforces passivity, and synthesises a passive macromodel of R, C and controlled sources. It works for any structure and port count, and is electrically exact but not physically interpretable.
• Structure-specific. Fits a known physical topology, so every component maps to reality (series L, shunt C, coupling k, and so on) at a chosen extraction frequency. See Available structures.

A single dialect-agnostic Circuit IR drives both netlist backends and the on-screen schematic, so the outputs always agree. The code is split into a pure-Python, Qt-free snp2le.core (fully unit-tested) and a thin PySide6 snp2le.gui, both driven by one entry point, engine.convert(state, net).

The snp2le GUI converting a band-pass filter (BPF) S-parameter file into a lumped-element netlist.

Plot view: loaded data (grey) vs extracted model (blue) vs imported testbench simulation (red).

Directory Structure

• 📄 pyproject.toml packaging metadata, dependencies and the snp2le entry point
• 📄 MANIFEST.in source-distribution manifest (bundles the examples and assets)
• 📄 requirements.txt runtime dependencies (mirrors pyproject.toml)
• 📁 snp2le/ the application package (pip-installable)
  • 📄 __init__.py package version
  • 📄 __main__.py single entry point (snp2le opens the GUI, snp2le -b runs the CLI)
  • 📄 app.py GUI launcher
  • 📄 cli.py command-line interface
  • 📁 core/ pure Python, Qt-free, all the maths
    • 📄 engine.py convert(state, net) returns Results, the single entry point
    • 📄 io.py load Touchstone (scikit-rf), parse Ngspice result tables
    • 📄 units.py engineering-notation parse and format
    • 📄 ir.py dialect-agnostic Circuit IR (element list and couplings)
    • 📄 netlist.py render the IR to Ngspice (SPICE3) and VACASK (Spectre)
    • 📄 universal.py vector-fit passive macromodel
    • 📄 mna.py rebuild N-port S-parameters from an RLC IR (model overlay)
    • 📄 dc.py DC operating-point (singularity) check for the macromodel
    • 📄 state.py ConverterState and Results dataclasses
    • 📄 xschem.py headless Xschem netlist and simulate commands
    • 📁 structures/ physical extractors, one file per topology
      • 📄 base.py, inductor_pi.py, mim_cap.py, tline.py
      • 📄 wilkinson.py, balun.py, branchline.py
      • 📄 __init__.py registry (the GUI dropdown and CLI auto-discover it)
  • 📁 gui/ PySide6, no maths
    • 📄 main_window.py the controller
    • 📄 top_bar.py load, mode, structure, options, simulator, run
    • 📄 design_view.py result, element values, tolerances, schematic, netlist
    • 📄 plot_view.py four S-parameter or extracted-parameter plots
    • 📄 help_dialog.py, style.py, widgets.py, and more
    • 📁 assets/ logos (svg and png), snp2le.ico
  • 📁 examples/ Touchstone .sNp sample files (BPF, inductor, balun, BLC, WPD, and more)
• 📁 tests/ pytest suite (test_core.py)
• 📁 doc/ architecture.md and screenshots (in fig/)
• 📁 testbenches/xschem/ BPF testbenches (Ngspice and VACASK) plus postprocess eval scripts
• 📁 netlist/ exported lumped-element netlists
  • 📁 spice/ Ngspice (.spice)
  • 📁 spectre/ VACASK (.inc) plus syntax_cheatsheet.inc
• 📁 schematic/xschem/ DUT symbol (bpf_le.sym) and xschemrc
• 📁 sim_data/ simulation results, imported and overlaid on the plots
• 📄 README.md, 📄 LICENSE (Apache-2.0), 📄 CITATION.cff

How to Use

Install

From PyPI:

pip install snp2le
# or, for an isolated install with its own command on PATH:
pipx install snp2le

From source (for development), an editable install pulls in every dependency:

git clone https://github.com/iic-jku/snp2le.git
cd snp2le

python -m venv .venv
# Windows:        .venv\Scripts\activate
# macOS / Linux:  source .venv/bin/activate

pip install -e .

Run the GUI

snp2le              # after installing (pip / pipx)
python -m snp2le    # from the repo root of a source checkout, no install needed

A bundled example is preloaded on first run. More live in snp2le/examples/.

[!NOTE] Start it as a module (python -m snp2le), not python snp2le/app.py. The launcher imports the snp2le package, which Python only finds when it is run as a module from the repo root (or after pip install).

Typical workflow

1. Load a Touchstone .sNp file from the top bar. The header shows the port count and frequency range.
2. Choose a mode. Universal (set Max order and Enforce passivity) or Structure-specific (pick a structure and set the extraction frequency). Some structures expose an extra option such as Stages, Isolation R or Resistive loss.
3. Inspect the result, element values, per-element tolerances at the extraction frequency, the drawn schematic, and the generated netlist in the Design & Schematic view.
4. Compare the loaded data (grey) against the extracted model (blue) in the Plot view (up to four traces, magnitude and phase).
5. Export the netlist. Export Ngspice writes a .spice file and Export VACASK writes an .inc file. The .SUBCKT is named after the file, so a testbench that instantiates it resolves the include.

[!TIP] The Help button in the top bar opens a full in-app guide to every control.

Run a testbench (simulate)

Drop the exported subcircuit into an Xschem testbench, then run it from the GUI:

1. Load .sch. Pick the testbench. The Simulator auto-selects from the file name (a name ending in _ngspice.sch selects Ngspice or _vacask.sch selects VACASK) and can be overridden.
2. Run Simulation. Both simulators netlist and simulate through Xschem and write their result to sim_data/, which is imported and overlaid on the plots automatically. The button turns green on success or red on failure. On failure the dialog shows the simulator log.
3. Show output. Tick it to show the simulator's console and plot windows. Leave it unticked to run quietly. The result is imported either way.

[!NOTE] A simulator (Xschem plus Ngspice and/or VACASK) is only needed for this step. The conversion and export themselves are pure Python.

Run the tests

pytest               # from the repo root

CLI Overview

The same engine is available headlessly for Makefiles and batch use, through the -b (batch) flag:

snp2le -b list-structures
snp2le -b convert <file.sNp> [options]

From a source checkout without installing, use python -m snp2le -b ... in place of snp2le -b.

convert options

Examples

# universal macromodel to an Ngspice netlist
snp2le -b convert coupler.s4p --mode universal --order 12 -o coupler.spice

# structure extraction at 7 GHz, both dialects, print values and tolerances
snp2le -b convert ind.s2p --mode structure --structure inductor-pi \
    --fext 7GHz --format both --values --tolerances

# convert the BPF, run its Xschem testbench, and show data vs model vs sim plots
snp2le -b convert snp2le/examples/bpf_ihp-sg13g2.s2p \
    --mode universal --order 13 -o netlist/spice/bpf_le.spice \
    --simulate testbenches/xschem/bpf_le_tb_acsp_ngspice.sch --plot

[!NOTE] --simulate and --plot need Xschem (and a display for --plot). They print a clear message and skip if Xschem is not on PATH.

Available structures

New structures plug in by subclassing snp2le.core.structures.base.Structure and registering them in snp2le/core/structures/__init__.py. They then appear in the GUI dropdown and the CLI automatically.

Cite This Work

@misc{2026_snp2le,
  author = {Dorrer, Simon},
  month = july,
  year = {2026},
  title = {{GitHub Repository for snp2le: A S-Parameter To Lumped Element Netlist Converter}},
  url = {https://github.com/iic-jku/snp2le},
  doi = {10.5281/zenodo.21189545}
}

Acknowledgements

• The structure-specific extractors (inductor, MIM capacitor, RLGC line) were inspired by Volker Mühlhaus' lumpedmodel.
• The passivity-enforcement strategy for the universal macromodel was adapted from the COBRA project.
• Vector fitting is provided by scikit-rf.

License

Licensed under the Apache License 2.0, see LICENSE.