Binning

class weatherbenchX.binning.Binning(bin_dim_name: str)

Binning base class.

Init.

Parameters:

bin_dim_name – Name of binning dimension.

class weatherbenchX.binning.Regions(regions: Mapping[Hashable, Tuple[Tuple[int, int], Tuple[int, int]]], bin_dim_name: str = 'region', land_sea_mask: DataArray | None = None)

Class for rectangular region binning.

Note that coordinate must be named latitude and longitude.

Init.

Parameters:

• regions – Dictionary specifying {name: ((lat_lims), (lon_lims))}.

• bin_dim_name – Name of binning dimension. Default: ‘region’

• land_sea_mask – (Optional) Boolean mask (land = True) with same latitude/longitude coordinates as the statistic. If provided, for each region will add a new land-onlybin with the name {region}_land.

class weatherbenchX.binning.ByExactCoord(coord: str, add_global_bin: bool = False)

Binning by unique coordinate values.

This will create a bin for each unique coordinate value, for example for each unique lead time in the case of sparse forecasts where lead_time is a coordinate but not a dimension.

Init.

Parameters:

• coord – Name of coordinate to bin by.

• add_global_bin – If True, add a global bin containing all data. Default: False.

class weatherbenchX.binning.ByTimeUnit(unit: str, time_dim: str, add_global_bin: bool = False)

Bin by time unit for given axis.

This uses the .dt datetime accessor in xarray, so this will only work for datetime64 coordinates.

See: https://docs.xarray.dev/en/latest/generated/xarray.core.accessor_dt.DatetimeAccessor.html

Example

` unit = 'hour' time_dim = 'init_time' ` This will aggregate together all data initialized at the same time of day, e.g. [0, 1, 2, .., 23].

Init.

Parameters:

• unit – Time unit to bin by.

• time_dim – Time dimension to bin by.

• add_global_bin – If True, add a global bin containing all data. Default: False.

class weatherbenchX.binning.ByCoordBins(dim_name: str, bin_edges: ndarray)

Binning by specified bins over a coordinate.

Init.

Parameters:

• dim_name – Name of dimension to bin by.

• bin_edges – Bin edges to bin by.

class weatherbenchX.binning.BySets(sets: Mapping[str, Sequence[Any]], coord_name: str, bin_dim_name: str | None = None, add_global_bin: bool = False)

Bin by sets of values along a coordinate.

This is, for example, useful for binning by different sets of station names.

Init.

Parameters:

• sets – Dictionary specifying sets of values to bin by.

• coord_name – Name of coordinate to bin over.

• bin_dim_name – Name of binning dimension. Default: dim_name

• add_global_bin – If True, add a global bin containing all data. Default: False.