def __init__(self, **kwargs):
""" @param verbosity: Verbosity level
@param mutationVariate: Variate used for mutation. Defaults to None
@param mutation: Defaults to EvolinoSubMutation
"""
Filter.__init__(self)
ap = KWArgsProcessor(self, kwargs)
ap.add( 'verbosity', default=0 )
ap.add( 'mutationVariate', default=None )
ap.add( 'mutation', default=EvolinoSubMutation() )
if self.mutationVariate is not None:
self.mutation.mutationVariate = self.mutationVariate
def __init__(self, evolino_network, dataset, **kwargs):
""" @param evolino_network: an instance of NetworkWrapper()
@param dataset: The evaluation dataset
@param evalfunc: Compares output to target values and returns a scalar, denoting the fitness.
Defaults to -mse(output, target).
@param wtRatio: Float array of two values denoting the ratio between washout and training length.
Defaults to [1,2]
@param verbosity: Verbosity level. Defaults to 0
"""
Filter.__init__(self)
ap = KWArgsProcessor(self, kwargs)
ap.add( 'verbosity', default=0 )
ap.add( 'evalfunc', default=lambda output, target: -Validator.MSE(output, target) )
ap.add( 'wtRatio', default=array([1,2], float) )
self.network = evolino_network
self.dataset = dataset
self.max_fitness = -Infinity
def __init__(self):
Filter.__init__(self)
def __init__(self, **kwargs):
""" @param **kwargs: will be forwarded to the EvolinoSubReproduction constructor
"""
Filter.__init__(self)
self._kwargs = kwargs
def __init__(self):
Filter.__init__(self)
self.nParents = None
self.sub_selection = EvolinoSubSelection()