The MONET Stats package provides first-class Xarray accessors to enable seamless integration with the Pangeo ecosystem. These accessors allow you to perform statistical analyses directly on xarray.DataArray and xarray.Dataset objects using the .monet_stats namespace.
The MonetDataArrayAccessor (available via da.monet_stats) provides methods for common time-series and spatial analyses, as well as a comprehensive suite of verification metrics.
The accessor provides direct access to many common verification metrics. These methods typically take an obs DataArray as their first argument and an optional dim parameter.
Example usage:
rmse = mod_da.monet_stats.rmse(obs_da, dim="time")
pearson_r = mod_da.monet_stats.pearsonr(obs_da)
Available metrics include:
mae, rmse, mb, ioa, crmse, mdnb, nmse, mnb, mne, nse, fac2, rmslepearsonr, r2, kge, cccnmb, fb, mg, vghss, ets, csi, pod, far, fbi, tss, bss_binary, bsThe verify method allows for efficient computation of multiple metrics at once, returning an xarray.Dataset.
metrics_ds = mod_da.monet_stats.verify(obs_da, dim="time")
The bundle includes: MAE, RMSE, MB, R (Pearson), IOA, NMB, MNB, MNE, NSE, R2, and FAC2.
::: monet_stats.accessor.MonetDataArrayAccessor
The MonetDatasetAccessor (available via ds.monet_stats) provides methods for calculating summary statistics and performing analyses across multiple variables in a dataset.
::: monet_stats.accessor.MonetDatasetAccessor