def get_phmd(self, dataset):
return lz(bdd=['PHMD'], **self.__base__(dataset))
def get_vr(self, dataset):
self.__compute_train_and_test__()
return lz(bdd=['VR'], **self.__base__(dataset),
repetitions=self.params['repetitions'], subset=self.params['subset'], xpdesign=self.params['xpdesign'])
def get_bi2015b(self, dataset):
return lz(bdd=['bi2015b'], **self.__base__(dataset, subject=self.__compute_paired_subject()),
pair=self.__compute_subjects__(dataset), session=self.__compute_session_2015b__())
def get_alpha(self, dataset):
return lz(bdd=['alpha'], **self.__base__(dataset))
def get_bi2015a(self, dataset):
return lz(bdd=['bi2015a'], **self.__base__(dataset),
session=self.__compute_session_2015a__())
def get_bi2014b(self, dataset):
return lz(bdd=['bi2014b'], **self.__base__(dataset, subject=self.__compute_paired_subject()),
pair=self.__compute_subjects__(dataset), xpdesign=['cola', 'solo'])
def get_bi2014a(self, dataset):
return lz(bdd=['bi2014a'], **self.__base__(dataset))
def get_bi2013(self, dataset):
return lz(bdd=['bi2013'], **self.__base__(dataset),
session=self.__compute_session_2013__(),
nonadaptive=self.params['nonadaptive'], adaptive=self.params['adaptive'],
training=self.params['training'], online=self.params['online'])
def get_bi2012(self, dataset):
return lz(bdd=['bi2012'], **self.__base__(dataset), training=self.params['training'])