hydromodpy.core.metrics.goodness_of_fit

Hydrological efficiency and error metrics.

Pure NumPy functions consumed by calibration, comparison, and display. All metrics drop NaN-aligned pairs and return float (not np.float64) so they round-trip cleanly through JSON and DuckDB.

References

• Nash, J. E., Sutcliffe, J. V. (1970). Journal of Hydrology, 10(3), 282-290.

• Gupta, H. V., et al. (2009). Journal of Hydrology, 377(1-2), 80-91.

• Moriasi, D. N., et al. (2007). Trans. ASABE, 50(3), 885-900. (PBIAS)

Functions

align(sim, obs)	Drop entries where either sim or obs is NaN.
bias(sim, obs)	Mean signed error (sim - obs).
correlation(sim, obs)	Pearson correlation coefficient.
kge(sim, obs)	Kling-Gupta Efficiency (2009) and its decomposition.
log_nse(sim, obs, *[, eps])	NSE on log-transformed series; rejects negative values.
mae(sim, obs)	Mean absolute error.
nse(sim, obs)	Nash-Sutcliffe Efficiency.
pbias(sim, obs)	Percent bias: 100 × Σ(obs - sim) / Σ(obs).
rmse(sim, obs)	Root-mean-square error.