lwbgt
lwbgt is a stable, low-level C/FFI computational kernel for Liljegren outdoor
WBGT. Derived from the Liljegren WBGT v1.1 C implementation, it preserves the
original scalar ABI and documented numerical behaviour while removing
demonstrably repeated or dead work. It is intended to be embedded as a
numerical backend by higher-level scientific packages, services, and
high-throughput data pipelines.
Python is an official, dependency-free ctypes binding to that same native
kernel. Install a self-contained binary wheel with pip install lwbgt. Input
units are explicit in field names and are never converted implicitly. The
package intentionally does not add dataframe/xarray models, meteorological
preprocessing, classifications, advisory policy, or alternate WBGT methods.
For those higher-level workflows, consider
pywbgt or
thermofeel.
Release status: v0.3.0. v0.1.0 is the frozen scalar-compatibility release. Its complete permitted optimization set measures 1.316× on the primary GCC 13 benchmark and 1.289× in the GCC 16.2 container. The v0.2.0 position-independent static build measures 1.249× on the GCC 13 host. All three results exceed the mandatory 1.20× gate with exact compatibility. These are narrowly supported throughput measurements on the documented environments and workloads, not broader portability claims.
It is not affiliated with or endorsed by the original authors, UChicago Argonne, or the U.S. Department of Energy.
This distribution contains a modified Liljegren WBGT v1.1 derivative. Binary and source redistributions must retain the UChicago Argonne/Department of Energy acknowledgement in NOTICE and comply with LICENSING.md.
Python installation and quick start
python -m pip install lwbgt
from lwbgt import Input, calculate, esat
weather = Input(
year=2024, month=4, day=15, hour=14, minute=30,
gmt_offset_hours=8, averaging_minutes=60, urban=1,
latitude_deg_north=1.3521, longitude_deg_east=103.8198,
solar_w_m2=742.0, pressure_hpa=1008.4,
air_temperature_c=32.1, relative_humidity_percent=68.0,
wind_speed_m_s=2.8, wind_height_m=10.0,
vertical_temperature_difference_c=-0.4,
)
result = calculate(weather)
assert result.status == 0
print(result.wbgt_c)
print(esat(273.15, phase=0))
Batch calculation uses the native serial batch entry point rather than a Python loop:
from lwbgt import calculate_batch
results = calculate_batch([weather, weather])
Input and Result are immutable typed records. Their complete field names,
units, solver status, and -9999 failure convention map directly to ABI v1;
see ABI.md. No third-party
Python runtime dependency is required.
Purpose
lwbgt owns the numerical Liljegren calculation, stable C/FFI contracts,
reproducible compatibility evidence, and low-level static/shared-library
distribution. Higher-level callers own table and dataframe APIs,
meteorological data ingestion, unit conversion beyond the documented ABI,
missing-data policy, additional domain validation, classification and advisory
systems, orchestration and parallelism, and application-specific defaults.
This narrow boundary is intentional.
Applications / research pipelines
|
Python / R / Julia / services
|
lwbgt
|
Liljegren WBGT numerical model
When to use lwbgt
Use lwbgt when you need a stable C or FFI Liljegren backend; behaviour
anchored to the original Liljegren C implementation; an embedded WBGT kernel
for another package or service; high-volume calculation with preprocessing
kept outside the kernel; or an auditable, reference-compatible numerical
backend within the documented compatibility scope.
When not to use lwbgt directly
A higher-level package is more appropriate when the primary requirement is dataframe-oriented ergonomics, automatic weather-data preprocessing, policy or heat-risk classifications, a batteries-included Python/R/Julia API, or GPU/JAX execution.
Native build and install
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build --parallel
ctest --test-dir build --output-on-failure
cmake --install build --prefix /desired/prefix
The build produces liblwbgt.a and a versioned shared library and installs
lwbgt.h, CMake package metadata, and pkg-config metadata. Core compilation is
GNU89 with -fno-fast-math -ffp-contract=off -fno-strict-aliasing; LTO and
architecture-specific flags are not enabled. GCC, Clang/AppleClang, and MinGW
GCC are supported; MSVC cannot compile the preserved K&R source.
Installed CMake consumers can select lwbgt::static or lwbgt::shared after
find_package(lwbgt CONFIG REQUIRED).
Supported API and compatibility contract
ABI.md defines the authoritative layouts, units, error behavior, concurrency rules, symbol surface, and compatibility policy.
The legacy calc_wbgt and esat declarations in include/lwbgt.h remain the
permanent scalar compatibility ABI. Scalar floating-point arguments use
double at the ABI boundary because the original K&R float parameters undergo
default argument promotion; output pointers remain float *.
The v1 FFI ABI adds fixed-layout lwbgt_input_v1 and lwbgt_output_v1
structures and lwbgt_calc_batch_v1. The batch call executes scalar calls in
input order. It returns the supplied wind as the effective 2-m wind when no
height conversion is needed, avoiding the legacy scalar routine's untouched
output-pointer behavior. It performs no allocation, retains no caller pointers,
and introduces no domain validation, clamping, unit conversion, or
missing-value policy beyond inherited scalar behaviour. Input and output arrays
must not overlap. Independent calls using separate buffers are thread-safe; a
single batch call is serial.
The shared library exports only calc_wbgt, esat, and
lwbgt_calc_batch_v1. The static archive retains global helper symbols inherited
from the source implementation; they remain unsupported implementation details.
The exported-symbol review is recorded in tests/API.md.
The maintained Python package and minimal R and Julia examples demonstrate the intended integration pattern: higher-level packages can bind the stable ABI while owning their user-facing policies. The R and Julia examples are tested interoperability examples, not registry packages, and no compatibility claim is made for third-party wrappers.
The exact upstream source is retained unmodified at
upstream/wbgt.c.original. src/wbgt.c is the modified derivative maintained
by Yifei/HeatStressDev. HeatStressBench's frozen liljegren-c target remains
the oracle and is not replaced or relabelled.
Numerical provenance and the exact-compatibility scope are documented in ABI.md, UPSTREAM.md, and the retained test evidence.
For matched compilers and floating-point flags, the acceptance policy is exact
32-bit equality for return status, estimated wind speed, Tg, Tnwb, Tpsy,
WBGT, and esat. The deterministic 454-case suite produces the same
087532603ebd6d3addad5bec4d99290eb3f1a9ed82bdfb141d5e9708194235ff
probe hash with GCC 13.3.0 and GCC 16.2.0.
Evidence
| Environment | Exact result | Median overall speedup | Release gate |
|---|---|---|---|
| Linux x86-64, GCC 13.3.0 | bit-identical | 1.316× | passed |
| Linux x86-64 container, GCC 16.2.0 | bit-identical | 1.289× | passed |
| Linux x86-64, GCC 13.3.0, v0.2.0 PIC build | bit-identical | 1.249× | passed |
Every v0.1.0 benchmark cohort exceeds 1.25×. The v0.2.0 PIC build passes the
unchanged overall and per-cohort gates, with a 1.210× slowest measured cohort.
Detailed host results, hardware, flags, datasets, warm-up, CPU-affinity policy,
repetitions, medians, and dispersion are under benchmarks/. HeatStressBench
adapter evidence is under tests/.
Licence and provenance
Project-authored files are licensed under Apache-2.0. The retained upstream source and modified derivative remain under the UChicago Argonne Liljegren WBGT v1.1 terms. LICENSING.md defines the file-level boundary and redistribution requirements.
UPSTREAM.md records the repository, pinned commit, blob, import date, and
relationship to HeatStressBench. The complete upstream source licence is in
LICENSES/LicenseRef-UChicago-Argonne-WBGT-1.1.txt; the required
Argonne/Department of Energy acknowledgement is in NOTICE.
Explicit non-goals
This release adds no high-level dataframe/xarray API, unit conversion, meteorological ingestion, dew-point policy, classification thresholds, alternate solver, precision change, new physics, cache, parallelism, OpenMP, SIMD, GPU path, or fast-math mode.
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