reASITIC

A clean-room Python re-implementation of [ASITIC][asitic] — the planar RF inductor analysis tool originally developed at UC Berkeley by Ali M. Niknejad in 1999. The library exposes geometry builders, partial- inductance / Q / resistance / S-parameter / Pi-model analyses, and CIF / GDS / Sonnet / SPICE / FastHenry / Touchstone exports.

A clean-room Python re-implementation of the 1999 UC Berkeley ASITIC RF-spiral inductor analysis tool, faithful to the original but powered by NumPy / SciPy and a strict, fully type-annotated codebase.

🚀 Try reASITIC in your browser — no install   full Python + NumPy + SciPy + the reasitic wheel via Pyodide

User guide

Reference

Quick install

pip install reASITIC          # base library
pip install reASITIC[plot]    # + matplotlib for plotting helpers

At-a-glance

import reasitic

tech = reasitic.parse_tech_file("BiCMOS.tek")
sp = reasitic.square_spiral(
    "L1", length=170, width=10, spacing=3, turns=2,
    tech=tech, metal="m3",
)
print(f"L = {reasitic.compute_self_inductance(sp):.3f} nH")
print(f"R = {reasitic.compute_ac_resistance(sp, tech, 2.4):.3f} Ω")
print(f"Q = {reasitic.metal_only_q(sp, tech, 2.4):.1f}")

Feature surface

  • 117 / 117 original REPL commands

  • 669 unit / integration / regression tests, 90 % line coverage

  • 643 / 643 identified C functions covered (100 %) — see milestone

  • mypy --strict clean across the entire public surface

  • Greenhouse + Grover partial-inductance summation with filament-level current-crowding, Wheeler skin effect, substrate eddy correction

  • Sommerfeld Green’s-function substrate model, FFT-accelerated coupling grid

  • 2-port Y/Z/S algebra, π / π3 / π4 / πX extraction, 3-port reduction, Touchstone v1 reader/writer

  • Geometry builders (10): square / polygon / wire / ring / via / transformer / 3D-transformer / symmetric-square / balun / capacitor

  • Round-trip CIF / Sonnet / SPICE / FastHenry / Tek / Tek 4014 exports

  • SLSQP-driven OptSq / OptPoly / OptArea / OptSymSq / BatchOpt

  • JSON-based session persistence, full-binary cross-validation harness

Indices