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constants.py
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constants.py
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UNIVARIATE_DATASET_NAMES_2018 = ['ACSF1', 'Adiac', 'ArrowHead', 'Beef', 'BeetleFly', 'BirdChicken', 'BME', 'Car', 'CBF',
'Chinatown', 'ChlorineConcentration', 'CinCECGtorso', 'Coffee',
'Computers', 'CricketX', 'CricketY', 'CricketZ', 'Crop', 'DiatomSizeReduction',
'DistalPhalanxOutlineAgeGroup', 'DistalPhalanxOutlineCorrect', 'DistalPhalanxTW',
'Earthquakes', 'ECG200', 'ECG5000', 'ECGFiveDays', 'ElectricDevices', 'EOGHorizontalSignal',
'EOGVerticalSignal','EthanolLevel', 'FaceAll', 'FaceFour', 'FacesUCR', 'FiftyWords', 'FISH',
'FordA', 'FordB', 'FreezerRegularTrain', 'FreezerSmallTrain', 'GunPoint', 'GunPointAgeSpan',
'GunPointMaleVersusFemale', 'GunPointOldVersusYoung', 'Ham', 'HandOutlines', 'Haptics',
'Herring', 'HouseTwenty', 'InlineSkate', 'InsectEPGRegularTrain', 'InsectEPGSmallTrain',
'InsectWingbeatSound', 'ItalyPowerDemand','LargeKitchenAppliances', 'Lightning2', 'Lightning7',
'MALLAT', 'Meat', 'MedicalImages', 'MiddlePhalanxOutlineAgeGroup', 'MiddlePhalanxOutlineCorrect',
'MiddlePhalanxTW', 'MixedShapesSmallTrain', 'MoteStrain', 'NonInvasiveFetalECGThorax1',
'NonInvasiveFetalECGThorax2', 'OliveOil', 'OSULeaf', 'PhalangesOutlinesCorrect', 'Phoneme',
'PigAirwayPressure','PigArtPressure','PigCVP', 'Plane', 'PowerCons', 'ProximalPhalanxOutlineAgeGroup',
'ProximalPhalanxOutlineCorrect', 'ProximalPhalanxTW', 'RefrigerationDevices', 'Rock',
'ScreenType', 'SemgHandGenderCh2', 'SemgHandMovementCh2','SemgHandSubjectCh2', 'ShapeletSim',
'ShapesAll', 'SmallKitchenAppliances', 'SmoothSubspace', 'SonyAIBORobotSurface1',
'SonyAIBORobotSurface2', 'StarLightCurves', 'Strawberry', 'SwedishLeaf', 'Symbols',
'SyntheticControl', 'ToeSegmentation1', 'ToeSegmentation2', 'Trace', 'TwoLeadECG',
'TwoPatterns', 'UMD', 'UWaveGestureLibraryAll', 'uWaveGestureLibraryX', 'uWaveGestureLibraryY',
'uWaveGestureLibraryZ', 'wafer', 'Wine', 'WordSynonyms', 'Worms', 'WormsTwoClass', 'yoga']
CLASSIFIERS = ['teacher', 'StudentAlone']
#CLASSIFIERS = ['Student']
ARCHIVE_NAMES = ['UCRArchive_2018']
dataset_names_for_archive = {'UCRArchive_2018': UNIVARIATE_DATASET_NAMES_2018}
EPOCHS = 2000
ITERATIONS = 5 # nb of random runs for random initializations
ITERATIONS_STUDENT_ALONE = 5 # nb of random runs for random initializations
ITERATIONS_STUDENT = 5
BEST_TEACHER_ONLY = True
# If true, be sure to have copied the best teacher results in best_teacher folder using
# the script 'copy_best_teacher.py'
#ALPHALIST = [i/100 for i in range(0, 101, 1)]
ALPHALIST = [0.1]
TEMPERATURELIST = [10]
PATH_DATA = "../../UCRArchive_2018"
PATH_OUT = "."
FILTERS = [64, 32, 28, 24, 20, 16, 12, 8, 4]
FILTERS2 = [128, 64, 56, 48, 40, 32, 24, 16, 8]
LAYERS = 3
SEPARABLE_CONV = False