Betaflight closed-loop chirp / blackbox analysis core — decoder, FRF/Bode, step response, spectral, HTML report.

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Project description

betaflight-chirp-core

The compute core for Betaflight closed-loop chirp / blackbox analysis: decode a .bbl/.bfl, estimate the frequency response (FRF/Bode), step response and noise spectrum, and render a self-contained HTML report.

betaflight-chirp-core knows nothing about MCP, HTTP, Docker, the CLI or the filesystem. Input: bytes. Output: objects + HTML.

Install

pip install betaflight-chirp-core

Or pin an exact commit straight from git:

pip install "betaflight-chirp-core @ git+https://github.com/SebGalina/betaflight-chirp-core@v0.1.5"

Usage

from betaflight_chirp_core import decode, analyse_log, build_report, run

# low-level: decode -> analyse -> render, step by step
df, fs, config = decode(open("log.bbl", "rb").read())
# df: decoded frames (pandas)   fs: loop/log rate (Hz)   config: PID/filter settings
a_pass = analyse_log(df, fs, config)        # one log  -> one self-contained pass dict
html   = build_report([a_pass])             # passes   -> self-contained HTML report

# single call: decode + analyse + report in one shot
result = run(open("log.bbl", "rb").read())
result.metrics       # == result.raw["axes"] — per-axis indicators, render as-is
result.report_html   # the self-contained HTML report (a full <html> string)
result.raw           # the complete pass dict (see Output below)

Importing the package is light: numpy/scipy/pandas load lazily, only when an analysis runs. from betaflight_chirp_core import decoder stays stdlib-only, so decode-only callers pull no heavy deps.

Output

Four return surfaces, from raw to ready-to-render:

Call	Returns	Is
`decode(bytes)`	`(df, fs, config)`	pandas frames, log rate (Hz), header tune dict
`analyse_log(df,…)`	pass dict	one log → all indicators (below)
`build_report(passes)`	`str`	one self-contained `<html>` page
`run(bytes)`	`AnalysisResult`	`.metrics` (= `raw["axes"]`), `.report_html`, `.raw` (pass dict)

The pass dict

analyse_log() / result.raw — one self-contained analysis of one log:

{
  "timestamp":   "2026-06-12T09:00:00",   # ISO, when analysed
  "file":        "log.bbl",
  "sample_rate_hz": 8000,                  # loop/log rate
  "input_col":   "debug[3]",               # FRF input column (chirp setpoint channel)
  "band_hz":     [1.0, 1000.0],            # analysed frequency band [fmin, fmax]
  "throttle_max": 1850,                    # peak flying throttle (or None)
  "config":      {…},                      # PID / filter settings parsed from the header
  "axes":        {"roll": {…}, "pitch": {…}, "yaw": {…}},   # per-axis, see below
  "tune_score":  {"overall": 76.0, "grade": "B", "axes": {"roll": {"score": …, "subs": {…}}}},
  "throttle_map":   {…},                   # resonance vs throttle (heatmap payload)
  "noise_spectrum": {…},                   # gyro PSD raw vs filtered (see below)
  "spectrogram":    {…},                   # chirp sweep time×freq (heatmap payload)
  "synthesis":      [{"fr": "...", "en": "..."}, …],   # plain-language read, bilingual
  "filter_suggestions": [ … ],             # filter change hints (only when config present)
  "noise_suggestions":  [ … ],             # noise/peak hints
}

Per axis (axes["roll"] etc.) — the Bode + step + verdict for one axis:

{
  "band_hz": [1.0, 1000.0], "n_samples": 48000,
  "freq": [...], "gain_db": [...], "phase_deg": [...], "coherence": [...],  # Bode curves
  "peaks": [ … ],                          # gain-resonance peaks in band
  "crossover_hz": 32.0,                    # 0 dB crossover
  "phase_margin_deg": 41.0, "phase_margin_unc_deg": 6.0,
  "ms": 4.8, "f_ms_hz": 70.0, "pm_guaranteed_deg": 34.0,   # peak sensitivity (robustness)
  "step": {                                # setpoint→gyro step response
    "t_ms": [...], "y": [...], "y_lo": [...], "y_hi": [...],
    "metrics": {"overshoot_pct": 12.0, "rise_ms": 18.0, "delay_ms": 3.0,
                "settle_ms": 60.0, "peak": 1.12},
  },
  "diagnosis": [ … ], "step_diagnosis": [ … ],   # short verdict strings
}

tune_score.grade is an A–F letter (A ≥ 85 … F < 40); overall is the mean of the per-axis scores. noise_spectrum carries freqs, raw_db/filt_db curves (0 dB = raw broadband floor) and a peaks list with above_floor_db / resid_db (filtered residual) / atten_db (raw→filtered cut) per peak.

Array fields (freq, gain_db, *_db, …) are JSON-ready (rounded floats), so the whole pass dict serialises straight to a front-end or a history store. For the exact nested fields, read analysis/chirp.py:build_pass.

Layout

Module	Role
`decoder.py`	pure-Python `.bbl` frame decoder (stdlib only)
`signal.py`	`decode_dataframe` (bytes → frames), `sample_rate`, `active_mask`
`config.py`	PID / filter settings parsed from the header
`analysis/`	chirp (FRF/Bode), spectral, step response
`report.py`	self-contained HTML report (inlines the renderer assets)
`report_assets/`	shared report renderer (`chirp_report.{js,css}` + glossary/strings JSON) — inlined by `report.py`, mountable by a web front

Develop

pip install -e ".[test]"
pytest

Tests run on .bbl fixtures in tests/data/. One GPS-free log (8.bbl) ships so the suite runs out of the box; drop your own logs there for more coverage. Every other .bbl/.bfl is git-ignored — never commit a real flight log, it carries GPS home-point coordinates (only 8.bbl is whitelisted, after verifying it has no GPS frame).

License

Apache-2.0.

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sgalina

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0.1.7

Jun 15, 2026

This version

0.1.6

Jun 12, 2026

0.1.5

Jun 12, 2026

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betaflight-chirp-core 0.1.6

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