A measure computed from a Dataset
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_results conditional attribute.
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 conditional attribute.
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.
Available conditional attributes:
(Conditional attributes enabled by default suffixed with +)
null_dist : instance of distribution estimator
auto_train : bool
force_train : bool
enable_ca : None or list of str
disable_ca : None or list of str
space: str, optional :
postproc : Node instance, optional
descr : str
Return Null Distribution estimator
Stores the probability of a measure under the NULL hypothesis
Stores the t-score corresponding to null_prob under assumption of Normal distribution