metrust 0.4.4

Rust-powered MetPy-compatible calculation layer with optional GPU acceleration

metrust

MetPy-compatible calculation layer, powered by Rust.

150/150 metpy.calc functions implemented natively, plus 36 extras. Often faster on real-world workflows. Verified against MetPy on SounderPy, MetPy Cookbook examples, and synthetic global grids.

# The only change: swap the import
from metrust.calc import cape_cin, potential_temperature, vorticity
from metrust.units import units

Installation

pip install metrust

Optional GPU acceleration for supported calculations:

pip install "metrust[gpu]"

For plotting, xarray accessor, or Level2File (forwarded to MetPy):

pip install metrust metpy

What It Does

metrust implements every function in metpy.calc with a Rust backend compiled via PyO3. The Python API now matches MetPy's public metpy.calc signatures and is designed for MetPy-compatible units, return types, and runtime behavior on the shared calculation surface:

import numpy as np
from metrust.calc import (
    cape_cin, parcel_profile, bunkers_storm_motion,
    storm_relative_helicity, significant_tornado_parameter,
    vorticity, divergence, advection,
)
from metrust.units import units

# Sounding analysis (same API as MetPy)
p = np.array([1000, 925, 850, 700, 500, 300]) * units.hPa
T = np.array([25, 20, 15, 5, -15, -40]) * units.degC
Td = np.array([20, 15, 10, -5, -25, -50]) * units.degC

prof = parcel_profile(p, T[0], Td[0])
cape, cin = cape_cin(p, T, Td, prof)  # MetPy parcel_profile form works

# Grid kinematics with xarray (dx/dy inferred from lat/lon coords)
vort = vorticity(u_xarray, v_xarray)  # spherical metric corrections included
div = divergence(u_xarray, v_xarray)

Optional GPU Backend

Current users do not need to change anything. metrust stays on the Rust CPU backend by default.

When met-cu is installed, you can opt in explicitly:

import metrust.calc as mcalc

mcalc.set_backend("gpu")
theta = mcalc.potential_temperature(pressure, temperature)

with mcalc.use_backend("cpu"):
    theta_cpu = mcalc.potential_temperature(pressure, temperature)

The GPU backend currently targets the overlap where met-cu is already strong and verified:

• potential_temperature
• equivalent_potential_temperature
• dewpoint
• vorticity
• frontogenesis
• q_vector
• compute_cape_cin
• compute_srh
• compute_shear
• compute_pw
• composite_reflectivity_from_hydrometeors

Eligible dispatch currently focuses on scalar thermo plus uniform 2-D Cartesian grid workloads. Latitude/longitude-derived spacing, map-scale corrections, and other projection-aware cases fall back to the Rust CPU backend.

metrust still returns the same Pint/NumPy-facing API surface. Unsupported cases automatically stay on the Rust CPU path.

Speed

Benchmarked on real-world workflows (v0.3.3, validated by Codex against MetPy):

Workflow	Speedup	Notes
MetPy Cookbook sounding analysis	6.0x	Full severe weather stack
MetPy Cookbook 500 hPa grid	6.1x	Vorticity, smoothing, advection
MetPy Cookbook Q-vectors	6.1x	Q-vector divergence
SounderPy compute-heavy subset	29.7x	Thermo + wind + severe params
MetPy isentropic example	2.3x	Isentropic interpolation + Montgomery
Vorticity/divergence (global grid)	2.3x	Spherical corrections on 721x1440

Current replay-harness snapshot from benches/bench_workflows.py on Windows 11 / Python 3.13.7: sounding 2.16x, grid diagnostics 8.53x, xarray workflow 1.46x.

Three-Way Benchmark: MetPy vs Rust vs CUDA

Real HRRR model output (40 isobaric levels, 1059 × 1799 grid, ~1.9 M points). RTX 5090, python tests/benchmark_gpu.py.

Scalar Thermodynamics (2D: 1059×1799)

Function	MetPy	Rust	CUDA	Rust/MetPy	CUDA/Rust
potential_temperature ★	11.2 ms	13.0 ms	7.9 ms	0.9x	1.6x
equiv_potential_temperature ★	303.1 ms	16.5 ms	9.1 ms	18x	1.8x
dewpoint ★	33.6 ms	10.8 ms	8.8 ms	3.1x	1.2x
saturation_vapor_pressure	66.7 ms	8.2 ms	—	8.1x	—
saturation_mixing_ratio	78.6 ms	13.7 ms	—	5.7x	—
dewpoint_from_rh	110.3 ms	7.6 ms	—	14x	—
rh_from_dewpoint	138.7 ms	10.9 ms	—	13x	—
virtual_temperature	31.1 ms	19.7 ms	—	1.6x	—
mixing_ratio	11.6 ms	8.5 ms	—	1.4x	—
wet_bulb_temperature	>10 min	26.9 ms	—	—	—

Grid Kinematics (2D: 1059×1799)

Function	MetPy	Rust	CUDA	Rust/MetPy	CUDA/Rust
vorticity ★	98.3 ms	92.8 ms	9.3 ms	1.1x	10x
divergence	96.1 ms	91.2 ms	—	1.1x	—
frontogenesis ★	733.0 ms	339.4 ms	12.2 ms	2.2x	28x
q_vector ★	390.3 ms	310.1 ms	10.8 ms	1.3x	29x
advection	161.8 ms	87.7 ms	—	1.8x	—

1D Sounding (40 levels, single column)

Function	MetPy	Rust	Rust/MetPy
parcel_profile	5.5 ms	0.074 ms	74x
cape_cin	1.4 ms	0.254 ms	5.4x
lcl	0.118 ms	0.065 ms	1.8x
lfc	6.7 ms	0.107 ms	62x
el	6.6 ms	0.112 ms	59x
precipitable_water	2.1 ms	0.057 ms	36x

Grid Composites (3D: 40×1059×1799 → 2D) — MetPy has no grid equivalents

Function	Rust	CUDA	CUDA/Rust
compute_cape_cin ★	2.96 s	674.5 ms	4.4x
compute_srh ★	223.5 ms	135.8 ms	1.6x
compute_shear ★	190.4 ms	166.5 ms	1.1x
compute_pw ★	191.6 ms	107.9 ms	1.8x
composite_refl_hydrometeors ★	154.2 ms	232.2 ms	0.7x

Summary

	MetPy	Rust	CUDA
Scalar thermo (×10)	785 ms	136 ms	26 ms
Grid kinematics (×5)	1.48 s	921 ms	32 ms
1D sounding (×6)	22 ms	0.67 ms	—
Grid composites (×5)	—	3.72 s	1.32 s
★ GPU-eligible total	—	4.50 s	1.37 s (3.3x)

★ = dispatches to CUDA when set_backend("gpu"). All other functions stay on Rust CPU regardless of backend setting.

Array Throughput

1M elements, 32-core Ryzen, rayon parallel:

Function	Time	Throughput
potential_temperature	1.8 ms	550 M/s
wet_bulb_temperature	7.3 ms	137 M/s
wind_speed	1.5 ms	660 M/s

Numerical Parity

Verified on the MetPy OUN 2011-05-22 12Z test sounding:

Metric	Difference from MetPy
CAPE	+4.0 J/kg
MUCAPE	+7.6 J/kg
SRH (0-1 km)	+0.3 m^2/s^2
Critical angle	+0.2 deg
Bunkers RM	+0.02 m/s
STP	+0.01
Montgomery streamfunction	corr 1.0000
Isentropic pressure	7e-13 hPa diff
Vorticity (global lat/lon)	corr 1.0000

Uses MetPy-exact physical constants (Rd, Cp, Lv, epsilon), MetPy's CAPE integration formula (g * dTv/Tv * dz), pressure-weighted Bunkers algorithm, Newton solver for isentropic interpolation, and spherical metric tensor corrections for lat/lon grid kinematics.

Coverage

• 150/150 metpy.calc functions (100% coverage)
• 36 extras not in MetPy (grid composites, fire weather indices, etc.)
• 28 Rust array bindings with rayon parallelism and GIL release
• Pint application registry shared with MetPy (no cross-registry errors)
• xarray support with coordinate inference and shape preservation

What's Not Native

These forward to MetPy when installed:

• metrust.plots (matplotlib-based plotting)
• metrust.xarray (xarray accessor)
• metrust.io.Level2File (NEXRAD Level II)

Core metrust.calc stays native Rust by default with no required MetPy dependency. The shared calc surface now stays on native metrust implementations even when MetPy is installed. The optional met-cu backend is an explicit accelerator, not a requirement.

End-to-end replay benchmarks for sounding, grid, and xarray workflows live in benches/bench_workflows.py and the published docs page workflow-benchmarks.md.

Examples

See examples/ for complete drop-in demos:

• cookbook_sounding.py — MetPy Cookbook sounding analysis
• cookbook_500hpa_grid.py — MetPy Cookbook 500 hPa vorticity advection
• sounderpy_dropin.py — SounderPy-style full sounding pipeline

Testing

cargo test --workspace          # 1,186 Rust tests
python -m pytest tests/ -q      # 30 Python tests (including MetPy compatibility regression)

Documentation

Full docs at fahrenheitresearch.github.io/metrust-py, including:

• API reference for all 186 functions
• Beginner tutorials (Weather 101, soundings, grids, recipes)
• Migration guide from MetPy
• Performance benchmarks

License

MIT