def setUp(self):
     # Radar and states generation
     self.setUp_radars_states()
     # Filter definition
     self.filter = MultipleRadarsFilterTA
     # Process noise finder definition
     self.process_noise_finder = NoiseFinderMultipleRadars(radars = self.radars,
                                                    states = self.states,
                                                    filter = self.filter)
     # Reduction of the actual list for testing purposes
     self.process_noise_finder.TO_TEST = [1.,2.,3.,4.,5.]
Exemplo n.º 2
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    print('=================================================================')
    print('=========================== ' + name +
          '-1 Radar ==========================')
    noise_finder = NoiseFinder1Radar(radar1, states, filter, nb_iterations=3)
    noise_finder.launch_benchmark()
    best_value = noise_finder.best_value()
    print(('Best value for ' + name + '-1Radar:{0}').format(best_value))
    writer.write_row(name + '-1Radar', str(best_value))

for filter in FILTERS_2_RADARS:
    name = filter.__name__[-2:]
    print('=================================================================')
    print('=========================== ' + name +
          '-2 Radars =========================')
    noise_finder = NoiseFinderMultipleRadars(radars,
                                             states,
                                             filter,
                                             nb_iterations=3)
    noise_finder.launch_benchmark()
    best_value = noise_finder.best_value()
    print(('Best value for ' + name + '-2Radars:{0}').format(best_value))
    writer.write_row(name + '-2Radars', str(best_value))

for filter in FILTERS_2_FRADARS:
    name = filter.__name__[-2:]
    print('=================================================================')
    print('========================== ' + name +
          '-2 PRadars =========================')
    noise_finder = NoiseFinderMultipleRadars(fradars,
                                             states,
                                             filter,
                                             nb_iterations=3)