climpred.metrics._mape

Contents

climpred.metrics._mape#

climpred.metrics._mape(forecast: Dataset, verif: Dataset, dim: str | List[str] | None = None, **metric_kwargs: Any) Dataset[source]#

Mean Absolute Percentage Error (MAPE).

Mean absolute error (mae) expressed as the fractional error relative to the verification data.

MAPE = \frac{1}{n} \sum \frac{|f-o|}{|o|}

Parameters:
  • forecast – Forecast.

  • verif – Verification data.

  • dim – Dimension(s) to perform metric over.

  • metric_kwargs – see xskillscore.mape()

Notes

minimum

0.0

maximum

perfect

0.0

orientation

negative

Example

>>> HindcastEnsemble.verify(
...     metric="mape", comparison="e2o", alignment="same_verifs", dim="init"
... )
<xarray.Dataset>
Dimensions:  (lead: 10)
Coordinates:
  * lead     (lead) int32 1 2 3 4 5 6 7 8 9 10
    skill    <U11 'initialized'
Data variables:
    SST      (lead) float64 1.536 1.21 1.421 1.149 ... 1.078 1.369 1.833 1.245
Attributes:
    prediction_skill_software:     climpred https://climpred.readthedocs.io/
    skill_calculated_by_function:  HindcastEnsemble.verify()
    number_of_initializations:     64
    number_of_members:             10
    alignment:                     same_verifs
    metric:                        mape
    comparison:                    e2o
    dim:                           init
    reference:                     []