Skip to main content

Digital waveform and protocol reverse engineering toolkit with IEEE-compliant measurements

Project description

TraceKit

Version Python License IEEE

Python signal analysis toolkit for oscilloscope and logic analyzer data

TraceKit provides IEEE-compliant waveform analysis, protocol decoding, and spectral measurements in a single unified framework. Designed for engineers who need scriptable, automatable signal analysis with industry-standard accuracy.


Key Capabilities

  • Waveform Measurements - Rise/fall time, frequency, duty cycle, overshoot (IEEE 181-2011)
  • Protocol Decoders - UART, SPI, I2C, CAN, CAN-FD, 1-Wire, LIN, JTAG, SWD, I2S, USB, HDLC, Manchester, FlexRay
  • Spectral Analysis - FFT, PSD, THD, SNR, SINAD, ENOB, spectrograms, wavelets (IEEE 1241-2010)
  • Signal Integrity - Jitter decomposition, eye diagrams, S-parameter analysis, TDR (IEEE 2414-2020)
  • File Format Support - Tektronix WFM, Rigol, Sigrok, VCD, PCAP, TDMS, WAV, CSV, HDF5, Touchstone
  • Power Analysis - AC/DC power, efficiency, ripple, SOA testing, power factor
  • EMC Compliance - CISPR/FCC/CE limit mask testing with automated reporting

Quick Start

Installation

# Using uv (recommended)
uv pip install tracekit

# From source
git clone https://github.com/lair-click-bats/tracekit.git
cd tracekit
uv pip install -e ".[dev]"

Basic Usage

import tracekit as tk

# Load and measure
trace = tk.load("capture.wfm")
print(f"Rise time: {tk.rise_time(trace):.2e} s")
print(f"Frequency: {tk.frequency(trace):.2f} Hz")

# Spectral analysis
freq, mag = tk.fft(trace)
print(f"THD: {tk.thd(trace):.1f} dB")
print(f"SNR: {tk.snr(trace):.1f} dB")

# Protocol decoding
uart_packets = tk.decode_uart(trace, baudrate=115200)
spi_frames = tk.decode_spi(trace, clock_pin=0, mosi_pin=1)

# Filtering and math
filtered = tk.low_pass(trace, cutoff=1e6)
derivative = tk.differentiate(trace)

Core Features

Signal Measurements

IEEE-compliant measurements for characterization and validation:

# Amplitude measurements
vpp = tk.amplitude(trace)       # Peak-to-peak voltage
rms = tk.rms(trace)             # RMS value
mean = tk.mean(trace)           # DC offset

# Timing measurements (IEEE 181-2011)
rise = tk.rise_time(trace)      # 10-90% rise time
fall = tk.fall_time(trace)      # 90-10% fall time
freq = tk.frequency(trace)      # Signal frequency
duty = tk.duty_cycle(trace)     # Duty cycle percentage

# Signal quality
overshoot = tk.overshoot(trace)
undershoot = tk.undershoot(trace)

Protocol Decoding

Decode embedded protocols directly from captured waveforms:

# Serial protocols
uart = tk.decode_uart(trace, baudrate=115200)
spi = tk.decode_spi(trace, clock_pin=0, mosi_pin=1, miso_pin=2)
i2c = tk.decode_i2c(trace, scl_pin=0, sda_pin=1)

# Automotive protocols
can = tk.decode_can(trace, bitrate=500000)
can_fd = tk.decode_can_fd(trace, bitrate=500000, data_bitrate=2000000)
lin = tk.decode_lin(trace)

# Debug protocols
jtag = tk.decode_jtag(trace)
swd = tk.decode_swd(trace)

Spectral Analysis

Comprehensive frequency-domain analysis with IEEE 1241-2010 compliance:

# FFT and power spectral density
freq, magnitude = tk.fft(trace, window="hann")
freq, psd = tk.psd(trace, method="welch")

# ADC quality metrics
snr = tk.snr(trace)          # Signal-to-noise ratio
thd = tk.thd(trace)          # Total harmonic distortion
sinad = tk.sinad(trace)      # Signal-to-noise and distortion
enob = tk.enob(trace)        # Effective number of bits
sfdr = tk.sfdr(trace)        # Spurious-free dynamic range

# Time-frequency analysis
spectrogram = tk.spectrogram(trace)

Signal Filtering

Complete filter library with design tools:

# Convenience filters
filtered = tk.low_pass(trace, cutoff=1e6)
filtered = tk.high_pass(trace, cutoff=100)
filtered = tk.band_pass(trace, low=1e3, high=1e6)
filtered = tk.notch_filter(trace, center=60, q=30)  # Remove 60 Hz

# Filter design
filter_obj = tk.design_filter("butterworth", order=4, cutoff=1e6)

Power Analysis

Characterize power electronics and supplies:

# Power measurements
power = tk.instantaneous_power(v_trace, i_trace)
avg_power = tk.average_power(v_trace, i_trace)
energy = tk.energy(v_trace, i_trace, duration=1e-3)

# AC power
pf = tk.power_factor(v_trace, i_trace)
apparent = tk.apparent_power(v_trace, i_trace)
reactive = tk.reactive_power(v_trace, i_trace)

# Power supply analysis
ripple_pp, ripple_rms = tk.ripple(trace)
eff = tk.efficiency(v_in, i_in, v_out, i_out)

Signal Integrity

High-speed digital validation and characterization:

# Jitter measurements (IEEE 2414-2020)
from tracekit.analyzers import jitter
tie = jitter.calculate_tie(trace)
period_jitter = jitter.period_jitter(trace)
rj, dj = jitter.decompose_jitter(trace)

# Eye diagram
from tracekit.analyzers.eye import generate_eye_diagram
eye = generate_eye_diagram(trace, bit_rate=1e9)

# Component analysis
impedance = tk.extract_impedance(tdr_trace)
z0 = tk.characteristic_impedance(trace)
delay = tk.propagation_delay(trace)

Advanced Features

Exploratory Analysis

Analyze unknown or undocumented signals:

from tracekit.exploratory import unknown, fuzzy

# Detect binary field boundaries in data
fields = unknown.detect_binary_fields(data)

# Fuzzy pattern matching with bit errors
from tracekit.exploratory.sync import fuzzy_sync_search
matches = fuzzy_sync_search(data, pattern=0xAA55, max_errors=2)

Auto-Inference

Automatic signal classification and protocol detection:

# Classify signal type
signal_type = tk.classify_signal(trace)

# Detect protocol automatically
protocol = tk.detect_protocol(trace)
print(f"Detected: {protocol.name} (confidence: {protocol.confidence:.0%})")

# Get analysis recommendations
recommendations = tk.recommend_analyses(trace)

Streaming and Lazy Loading

Handle large files efficiently:

# Lazy loading for huge files
trace = tk.load("huge_capture.wfm", lazy=True)
print(f"Length: {len(trace)} samples")  # Metadata only, no data loaded

# Streaming analysis
for chunk in tk.load_trace_chunks("huge.wfm", chunk_size=1_000_000):
    process(chunk)

Pipelines

Compose analysis workflows functionally:

from tracekit import Pipeline, pipe

# Build reusable pipelines
analysis = Pipeline([
    tk.low_pass(cutoff=1e6),
    tk.rise_time,
    tk.frequency,
])

results = analysis(trace)

Session Management

Annotate and save analysis state:

session = tk.Session()
session.load_trace("capture.wfm")
session.annotate(time=1.5e-6, text="Glitch detected")
session.save("debug_session.tks")

File Format Support

Format Extension Description
Tektronix WFM .wfm Tektronix oscilloscopes
Rigol WFM .wfm Rigol oscilloscopes
Sigrok .sr Sigrok/PulseView captures
VCD .vcd Value Change Dump (digital)
PCAP .pcap, .pcapng Network packet captures
TDMS .tdms NI LabVIEW
WAV .wav Audio waveforms
Touchstone .s1p, .s2p, etc. S-parameter data
CSV .csv Generic time-series
HDF5 .h5, .hdf5 Scientific data format
NumPy .npz NumPy arrays

Reporting

Generate professional reports in multiple formats:

report = tk.generate_report(
    trace,
    measurements=["rise_time", "frequency", "thd"],
    format="html",  # or "pdf", "json"
)
report.save("analysis_report.html")

Built-in Templates: default, compliance, characterization, debug, production, comparison


EMC Compliance Testing

Test against regulatory limit masks:

# Check CISPR compliance
result = tk.check_compliance(
    spectrum,
    mask="CISPR22_ClassB",
    detector="quasi_peak"
)

# Generate compliance report
report = tk.generate_compliance_report(result, format="pdf")

Supported Standards: CISPR 22/32, FCC Part 15, MIL-STD-461


IEEE Standards Compliance

TraceKit implements measurements according to IEEE standards:

Standard Domain Measurements
IEEE 181-2011 Pulse measurements Rise/fall time, slew rate
IEEE 1057-2017 Digitizer characterization Timing analysis
IEEE 1241-2010 ADC testing SNR, SINAD, ENOB, THD, SFDR
IEEE 2414-2020 Jitter measurements TIE, period jitter, RJ/DJ
IEEE 1459 Power measurements Power quality analysis
IEC 61000-4-7 Power quality Harmonics analysis

Development

# Install with dev dependencies
uv sync

# Run tests
uv run pytest tests/unit -v

# Lint and format
uv run ruff check src/ tests/
uv run ruff format src/ tests/

# Type check
uv run mypy src/

See CONTRIBUTING.md for development guidelines.


Documentation


License

MIT License - See LICENSE for details.


Links

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tracekit-0.1.1.tar.gz (99.5 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tracekit-0.1.1-py3-none-any.whl (1.4 MB view details)

Uploaded Python 3

File details

Details for the file tracekit-0.1.1.tar.gz.

File metadata

  • Download URL: tracekit-0.1.1.tar.gz
  • Upload date:
  • Size: 99.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.15 {"installer":{"name":"uv","version":"0.9.15","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for tracekit-0.1.1.tar.gz
Algorithm Hash digest
SHA256 8aaa27fa2fc8b2ba37e6ff0589a76db144d99eab06363b109599e2f89ca1dcb1
MD5 3c64d466b749a3ae36c48b639ea9db0d
BLAKE2b-256 49ff52c94d61fbb76d92dec42b8d15d0e91ae2c4b215bdedebc5f211f2d15ec9

See more details on using hashes here.

File details

Details for the file tracekit-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: tracekit-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 1.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.15 {"installer":{"name":"uv","version":"0.9.15","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for tracekit-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 413ff4bbfe56b79581a47bc11b5a6046116cbc3a987e5ef0c9a3ff005bd7ae91
MD5 6ddb8e2ac78bce4ddebf8851c3c815d8
BLAKE2b-256 fef18b5c6ffcec4565035ff1c4307f385702d459addefb7223d051390239f7e1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page