TransformIf

Conditional execution of a transformer given a condition from a fittable object.

Quickstart

from sktime.transformations.compose import TransformIf

estimator = TransformIf(if_estimator, param=None, condition='bool', condition_value=None, then_trafo=None, else_trafo=None)

Parameters(6)

if_estimatorsktime estimator, must have fit

sktime estimator to fit and apply to series. this is a “blueprint” estimator, state does not change when fit is called

paramstr, optional, default = first boolean parameter of fitted if_estimator

conditionstr, optional, default = “bool”

condition that defines whether self behaves like then_est or else_est this estimator behaves like then_est iff: “bool” = if param is True “>”, “>=”, “==”, “<”, “<=”, “!=” = if param condition condition_value

condition_valuerequired for some conditions, see above; otherwise optional

then_trafosktime transformer, optional, default=``if_estimator``

transformer that this behaves as if condition is satisfied this is a “blueprint” transformer, state does not change when fit is called

else_trafosktime transformer, optional default=``Id`` (identity/no transform)

transformer that this behaves as if condition is not satisfied this is a “blueprint” transformer, state does not change when fit is called

Examples

>>> from sktime.param_est.seasonality import SeasonalityACF
>>> from sktime.transformations.compose import TransformIf
>>> from sktime.transformations.detrend import Deseasonalizer
>>> from sktime.datasets import load_airline
>>> 
>>> y = load_airline ()
>>> 
>>> seasonal = SeasonalityACF (candidate_sp = 12)
>>> deseason = Deseasonalizer (sp = 12)
>>> cond_deseason = TransformIf (seasonal, "sp", "!=", 1, deseason)
>>> y_hat = cond_deseason. fit_transform (y)