centum.accounting

Functions

aggregate_volume(da_volume[, freq])	Aggregate volume data over time.
check_crs_consistent(ds1, ds2)	Check if CRS is defined and consistent between two rioxarray-enabled datasets.
check_dimensions_consistent(ds1, ds2)	Check if dimensions and time coordinates are consistent between two xarray Datasets.
check_nan_mask_t0_consistent(ds1, ds2[, ...])	Check if NaN mask at the first time step is spatially consistent between two datasets for the given pair of variables.
check_nb_of_nan_over_time(ds[, variable])
check_time_consistent(ds1, ds2)	Check if both datasets have a 'time' coordinate and that they are identical.
compute_net_irrigation(ds_baseline, ds_eo[, ...])	Compute net irrigation as the difference between ETa baseline and ETa EO.
compute_pixel_area(da)	Compute the approximate area (m²) of each pixel based on coordinate spacing.
compute_water_accounting(ds[, variable, freq])	Compute water accounting volumes and mean ETa aggregated by time frequency.
et_mm_day_to_m3_day(da_etha, pixel_area_m2)	Convert ETa from mm/day to volume m³/day per pixel.
plot_monthly_et(monthly_ds[, var])	Plot spatially averaged monthly ETa.

Classes

Accounting(ds_baseline, ds_EO[, variable, ...])