climpred.options.set_options

class climpred.options.set_options(**kwargs)

Set options for climpred in a controlled context. Analogous to xarray.set_options(**option).

Currently supported options:

• seasonality

  • Attribute to group dimension groupby(f"{dim}.{seasonality}"").

    Used in reference=climatology and remove_bias().

  • Allowed: ["dayofyear", "weekofyear", "month", "season"]

  • Default: dayofyear.

• warn_for_failed_PredictionEnsemble_xr_call

  • Raise UserWarning when PredictionEnsemble.xr_call,

    e.g. .sel(lead=[1]) fails on one of the datasets.

  • Allowed: [True, False]

  • Default: True

• warn_for_rename_to_climpred_dims

  • Raise UserWarning when dimensions are renamed to CLIMPRED_DIMS when

    PredictionEnsemble is instantiated.

  • Allowed: [True, False]

  • Default: True

• warn_for_init_coords_int_to_annual

  • Raise UserWarning when init coordinate is of type integer and gets

    converted to annual cftime_range when PredictionEnsemble is instantiated.

  • Allowed: [True, False]

  • Default: True

• climpred_warnings

  • Overwrites all options containing "*warn*".

  • Allowed: [True, False]

  • Default: True

Examples

You can use set_options either as a context manager:

>>> kw = dict(metric='mse', comparison='e2o', dim='init',
...           alignment='same_verifs', reference='climatology')
>>> with climpred.set_options(seasonality='month'):
...     HindcastEnsemble.verify(**kw).SST.sel(skill='climatology')
<xarray.DataArray 'SST' (lead: 10)>
array([0.03712573, 0.03712573, 0.03712573, 0.03712573, 0.03712573,
       0.03712573, 0.03712573, 0.03712573, 0.03712573, 0.03712573])
Coordinates:
  * lead     (lead) int32 1 2 3 4 5 6 7 8 9 10
    skill    <U11 'climatology'

Or to set global options:

>>> climpred.set_options(seasonality='month')  
<climpred.options.set_options object at 0x...>

__init__(**kwargs)

Methods

__init__(**kwargs)