All dataset measures support arbitrary transformation of the measure
after it has been computed. Transformation are done by processing the
measure with a functor that is specified via the transformer keyword
argument of the constructor. Upon request, the raw measure (before
transformations are applied) is stored in the raw_result state variable.
Additionally all dataset measures support the estimation of the
probabilit(y,ies) of a measure under some distribution. Typically this will
be the NULL distribution (no signal), that can be estimated with
permutation tests. If a distribution estimator instance is passed to the
null_dist keyword argument of the constructor the respective
probabilities are automatically computed and stored in the null_prob
state variable.
For developers: All subclasses shall get all necessary parameters via
their constructor, so it is possible to get the same type of measure for
multiple datasets by passing them to the __call__() method successively.
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_postcall(self,
dataset,
result)
Some postprocessing on the result |
source code
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Inherited from misc.state.ClassWithCollections:
__getattribute__,
__new__,
__setattr__,
__str__,
reset
Inherited from object:
__delattr__,
__format__,
__hash__,
__reduce__,
__reduce_ex__,
__sizeof__,
__subclasshook__
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