Exemple #1
0
 def contains_training_instance(self, part):
     try:
         part = delete(part, self.fitness.exclude_from_regression, 0)
     except:
         pass
     contains, index = numpy_array_index(self.training_set, part)
     return contains
 def get_training_instance(self, part):
     contains, index = numpy_array_index(self.training_set, part)
     if self.training_set is None:
         logging.error('cannot call get_training_instance if training_set is empty')
         return False
     elif contains:
         return self.training_fitness[index]
     else :
         logging.error('cannot call get_training_instance if training_set does not contain the particle')
         return False
Exemple #3
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 def get_training_instance(self, part):
     try:
         part = delete(part, self.fitness.exclude_from_regression, 0)
     except:
         pass
     contains, index = numpy_array_index(self.training_set, part)
     if self.training_set is None:
         logging.error("cannot call get_training_instance if training_set is empty")
         return False
     elif contains:
         return self.training_fitness[index]
     else:
         logging.error("cannot call get_training_instance if training_set does not contain the particle")
         return False
Exemple #4
0
 def bitstream_was_generated(self, part):
     software_axis = [i for i, dimension in enumerate(self.fitness.designSpace) if dimension["set"] == "s"]
     pruned_training_set = delete(self.hard_regressor.get_training_set(),software_axis,1)
     pruned_part = delete([part],software_axis,1)
     contains, index = numpy_array_index(pruned_training_set, pruned_part[0])
     return contains
 def contains_training_instance(self, part):
     contains, index = numpy_array_index(self.training_set, part)
     return contains