decodaitengu 1.2.0

DecoDaiTengu - dive decompression library (fork of DecoTengu)

DecoDaiTengu

A modern Python dive decompression library implementing the Bühlmann ZH-L16B/C decompression model with Erik Baker's gradient factors.

This is a modernised fork of the original DecoTengu library (v0.14.1, 2018) by Artur Wroblewski.

Features

• ZH-L16B-GF and ZH-L16C-GF models with full helium compartment support (trimix)
• Gradient factor configuration (GF low/high)
• CNS and OTU oxygen toxicity tracking
• High-level plan_dive() API for common dive planning
• Type-annotated, Python 3.10+ codebase
• Gas mix support: air, nitrox, trimix

Quick Start

pip install decodaitengu

from decodaitengu import plan_dive, Gas

# Simple air dive
result = plan_dive(depth=35, bottom_time=40, gf=(30, 85))
print(f"Runtime: {result.runtime} min")
print(f"Deco stops: {[(s.depth, s.time) for s in result.stops]}")
print(f"CNS: {result.cns_percent}%")

# Trimix dive with deco gas
result = plan_dive(
    depth=60,
    bottom_time=20,
    back_gas=Gas(21, 35),
    deco_gases=[Gas(50, 0, switch_depth=21), Gas(100, 0, switch_depth=6)],
    gf=(30, 85),
)
print(f"Runtime: {result.runtime} min")

Models

from decodaitengu import plan_dive
from decodaitengu.models import ZHL16C, ZHL16B

# ZHL-16C is the default (recommended for dive computers)
result = plan_dive(depth=40, bottom_time=25, model=ZHL16C)

# ZHL-16B available for backward compatibility
result = plan_dive(depth=40, bottom_time=25, model=ZHL16B)

Legacy API

The original DecoTengu Engine-based API has been removed. Calling decodaitengu.create() raises RuntimeError with migration instructions.

Migration from old decotengu:

# OLD (decotengu v0.x):
#   import decotengu
#   engine = decotengu.create()
#   engine.add_gas(0, 21)
#   profile = engine.calculate(35, 40)
#   list(profile)
#   print(engine.deco_table.total)

# NEW (decodaitengu v1.x):
from decodaitengu import plan_dive, Gas

result = plan_dive(depth=35, bottom_time=40, back_gas=Gas(21, 0), gf=(30, 85))
print(result.total_deco_time)

Known Differences from Other Planners

This library uses the analytically-exact Schreiner equation for tissue loading, whereas Subsurface (and many dive computers) use the Haldane equation with discrete 1-second steps. The two approaches are equivalent at constant depth but produce slightly different results during ascent/descent phases.

Key divergences from Subsurface 6.0 (ZHL-16C, GF 50/70):

Factor	Effect	Typical magnitude
Schreiner vs Haldane 1s steps	Less conservative during ascent	±1–4 min at shallow stops
Gas switch timing (free ascent)	May be more conservative	+2–4 min at 3m for multi-gas
Helium off-gassing	Extra shallow stops for trimix	+1 stop at 18m

Per-stop divergence is bounded at ≤5 minutes in integration tests. See tests/integration/reference_data.json for exact Subsurface reference values.

This library is not a certified dive planning tool. Always validate plans against established software and never dive beyond your training.

Documentation

The legacy Sphinx docs (referencing the old decotengu namespace) have been removed. API documentation will be rebuilt from the current decodaitengu package in a future release.

Development

pip install -e ".[dev]"
pre-commit install
pre-commit run --all-files
pytest
ruff check .

The pre-commit hooks intentionally run check-only commands matching CI:

ruff check decodaitengu/
ruff format --check decodaitengu/

License

GPL-3.0-or-later. See COPYING for details.

WARNING: This software is provided as-is with no warranty. Any diving using data provided by this library is at the diver's own risk.

Cheers, gully