Package mvpa :: Package measures :: Module base :: Class DatasetMeasure
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Class DatasetMeasure

source code


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_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.

    :Developer note:
      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.
    

Constructor information for `DatasetMeasure` class
__________________________________________________

Does nothing special.

        :Parameter:
          transformer: Functor
            This functor is called in `__call__()` to perform a final
            processing step on the to be returned dataset measure. If None,
            nothing is called
          null_dist : instance of distribution estimator
        


Documentation for base classes of `DatasetMeasure`
===================================================

Documentation for class `Stateful`
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Base class for stateful objects.

    Classes inherited from this class gain ability to provide state
    variables, accessed as simple properties. Access to state variables
    "internals" is done via states property and interface of
    `StateCollection`.

    NB This one is to replace old State base class
    TODO: rename 'descr'? -- it should simply
          be 'doc' -- no need to drag classes docstring imho.
    

Nested Classes [hide private]

Inherited from misc.state.Stateful: __metaclass__

Instance Methods [hide private]
 
__init__(self, transformer=None, null_dist=None, *args, **kwargs)
Does nothing special.
source code
 
__call__(self, dataset)
Compute measure on a given Dataset.
source code
 
_call(self, dataset)
Actually compute measure on a given Dataset.
source code
 
_postcall(self, dataset, result)
Some postprocessing on the result
source code
 
__str__(self)
str(x)
source code

Inherited from misc.state.Stateful: __getattribute__, __repr__, __setattr__, reset

Inherited from object: __delattr__, __hash__, __new__, __reduce__, __reduce_ex__

Class Variables [hide private]
  raw_result = StateVariable(enabled= False, doc= "Computed resu...
  null_prob = StateVariable(enabled= True)
Stores the probability of a measure under the NULL hypothesis
  __doc__ = enhancedDocString('DatasetMeasure', locals(), Stateful)
  _collections_template = {'states': <mvpa.misc.state.StateColle...

Inherited from misc.state.Stateful (private): _initargs

Instance Variables [hide private]
  __transformer
Functor to be called in return statement of all subclass __call__() methods.
Properties [hide private]

Inherited from misc.state.Stateful: descr

Inherited from object: __class__

Method Details [hide private]

__init__(self, transformer=None, null_dist=None, *args, **kwargs)
(Constructor)

source code 
Does nothing special.
Parameters:
  • enable_states - Names of the state variables which should be enabled additionally to default ones
  • disable_states - Names of the state variables which should be disabled
  • descr - Description of the instance
Overrides: object.__init__

__call__(self, dataset)
(Call operator)

source code 

Compute measure on a given Dataset.

Each implementation has to handle a single arguments: the source dataset.

Returns the computed measure in some iterable (list-like) container applying transformer if such is defined

_call(self, dataset)

source code 

Actually compute measure on a given Dataset.

Each implementation has to handle a single arguments: the source dataset.

Returns the computed measure in some iterable (list-like) container.

__str__(self)
(Informal representation operator)

source code 
str(x)
Overrides: object.__str__
(inherited documentation)

Class Variable Details [hide private]

raw_result

Value:
StateVariable(enabled= False, doc= "Computed results before applying a\
ny "+ "transformation algorithm")

_collections_template

Value:
{'states': <mvpa.misc.state.StateCollection object at 0x874b64c>}