94 lines
2.9 KiB
Python
94 lines
2.9 KiB
Python
"""Cross-check the ApsisRS rain coefficients against ITU-R P.838-3.
|
|
|
|
Reads the values written by ``cargo run -p apsis-rs --features rf --example
|
|
dump_rain`` and recomputes each one with the ``itur`` package, which
|
|
implements the recommendation directly.
|
|
|
|
The script needs no network access.
|
|
|
|
Usage:
|
|
|
|
pixi run python validation/python/atmosphere/check_rain.py [path]
|
|
|
|
Exit status is zero when every value agrees within tolerance and one
|
|
otherwise.
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
import csv
|
|
import sys
|
|
from pathlib import Path
|
|
|
|
from itur.models.itu838 import _ITU838_3_
|
|
|
|
# The implementation reproduces the reference to about twelve significant
|
|
# digits. The Rust output is written with twelve decimal places, which limits
|
|
# the comparison for the smallest coefficients, so the tolerance is set to
|
|
# one part in ten to the eighth.
|
|
RELATIVE_TOLERANCE = 1e-8
|
|
|
|
DEFAULT_INPUT = Path("validation/data/expected/rust_rain.csv")
|
|
|
|
|
|
def read_rows(path: Path) -> list[dict[str, str]]:
|
|
"""Reads the CSV rows."""
|
|
with path.open(newline="") as handle:
|
|
reader = csv.DictReader(handle)
|
|
return [row for row in reader if row.get("frequency_ghz")]
|
|
|
|
|
|
def main(argv: list[str]) -> int:
|
|
path = Path(argv[1]) if len(argv) > 1 else DEFAULT_INPUT
|
|
if not path.exists():
|
|
print(f"missing input file: {path}", file=sys.stderr)
|
|
print(
|
|
"generate it with: cargo run -p apsis-rs --features rf "
|
|
"--example dump_rain > " + str(path),
|
|
file=sys.stderr,
|
|
)
|
|
return 2
|
|
|
|
rows = read_rows(path)
|
|
if not rows:
|
|
print("input file has no data rows", file=sys.stderr)
|
|
return 2
|
|
|
|
model = _ITU838_3_()
|
|
worst_k = 0.0
|
|
worst_alpha = 0.0
|
|
worst_at = None
|
|
|
|
for row in rows:
|
|
frequency = float(row["frequency_ghz"])
|
|
elevation = float(row["elevation_deg"])
|
|
polarisation = float(row["polarisation_deg"])
|
|
k, alpha = model.rain_specific_attenuation_coefficients(
|
|
frequency, elevation, polarisation
|
|
)
|
|
k = float(k)
|
|
alpha = float(alpha)
|
|
|
|
k_error = abs(float(row["k"]) - k) / k
|
|
alpha_error = abs(float(row["alpha"]) - alpha) / abs(alpha)
|
|
if k_error > worst_k or alpha_error > worst_alpha:
|
|
worst_at = (frequency, elevation, polarisation)
|
|
worst_k = max(worst_k, k_error)
|
|
worst_alpha = max(worst_alpha, alpha_error)
|
|
|
|
print(f"combinations compared: {len(rows)}")
|
|
print(f"worst relative k: {worst_k:.3e}")
|
|
print(f"worst relative alpha: {worst_alpha:.3e}")
|
|
print(f"worst combination: {worst_at}")
|
|
print(f"tolerance: {RELATIVE_TOLERANCE:.3e} relative")
|
|
|
|
if worst_k <= RELATIVE_TOLERANCE and worst_alpha <= RELATIVE_TOLERANCE:
|
|
print("result: pass")
|
|
return 0
|
|
print("result: FAIL")
|
|
return 1
|
|
|
|
|
|
if __name__ == "__main__":
|
|
raise SystemExit(main(sys.argv))
|