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:type ql: float
:param qh: the higher quantile of the corridor
:type qh: float
:param isabs: should the absolute differences be taken?
:type isabs: bool
:param f_agg: the aggregator function that is applied to the differences in the bin
:type f_agg: str, name of a numpy function (e.g. mean, var, std, median)
:return: the value of this feature
:rtype: float
"""
if ql is None or qh is None or isabs is None or f_agg is None:
f_agg = 'mean'
isabs = True
qh = 0.2
ql = 0.0
quantile = feature_calculators.change_quantiles(x, ql, qh, isabs, f_agg)
logging.debug("change_quantiles by tsfresh calculated")
return quantile
def function(x):
return change_quantiles(x,
ql=self.ql,
qh=self.qh,
isabs=self.isabs,
f_agg=self.f_agg)