Python API¶
Use these functions when you need fine-grained control beyond the CLI.
Quick example¶
from cross_sensor_cal import merge_duckdb
merge_duckdb(["parquet/a.parquet","parquet/b.parquet"], "merged/all.parquet")
Brightness correction entry point¶
apply_brightness_correction(cube, mask=None, method='percentile_match', ...)¶
Normalizes per-band brightness for hyperspectral cubes before BRDF/topo stages. The docstring walks through the affine model, parameter choices, and examples. Use it when you need to harmonise tiles prior to the full pipeline; the QA JSON will surface the per-band gain/offsets when this stage runs.
Cross-Sensor Calibration public package surface.
_PLOT_EXPORTS = (make_micasense_vs_landsat_panels.__name__, make_sensor_vs_neon_panels.__name__)
module-attribute
¶
__all__ = sorted(set(__all__ + (['apply_brightness_correction', load_brightness_coefficients.__name__] + list(_PLOT_EXPORTS))))
module-attribute
¶
__version__ = '2.2.0'
module-attribute
¶
__getattr__(name)
¶
load_brightness_coefficients(system_pair='landsat_to_micasense')
¶
Load brightness coefficients for a given system pair.
Parameters¶
system_pair : str Key identifying the pair of systems, e.g. "landsat_to_micasense".
Returns¶
dict[int, float] Mapping from 1-based band index to brightness coefficient (percent).
Notes¶
- Values are stored in percent (e.g., -7.3959 means "reduce by 7.3959%").