def test_FilterBankMotorImagery_paradigm(self):
# can work with filter bank
paradigm = FilterBankMotorImagery()
dataset = FakeDataset(paradigm='imagery')
X, labels, metadata = paradigm.get_data(dataset, subjects=[1])
# X must be a 4D Array
self.assertEqual(len(X.shape), 4)
self.assertEqual(X.shape[-1], 6)
def test_FilterBankMotorImagery_paradigm(self):
# can work with filter bank
paradigm = FilterBankMotorImagery()
dataset = FakeDataset(paradigm="imagery")
X, labels, metadata = paradigm.get_data(dataset, subjects=[1])
# X must be a 4D Array
self.assertEqual(len(X.shape), 4)
self.assertEqual(X.shape[-1], 6)
# should return epochs
epochs, _, _ = paradigm.get_data(dataset, subjects=[1], return_epochs=True)
self.assertIsInstance(epochs, BaseEpochs)
def test_filter_bank_mi(self):
# can work with filter bank
paradigm = FilterBankMotorImagery()
dataset = FakeDataset()
X, labels, metadata = paradigm.get_data(dataset, subjects=[1])
# X must be a 3D Array
self.assertEquals(len(X.shape), 4)
self.assertEquals(X.shape[-1], 6)
# can work with filter bank
paradigm = FilterBankLeftRightImagery()
dataset = FakeDataset(event_list=['left_hand', 'right_hand'])
X, labels, metadata = paradigm.get_data(dataset, subjects=[1])
# X must be a 3D Array
self.assertEquals(len(X.shape), 4)
self.assertEquals(X.shape[-1], 6)
############################################################################### # Paradigm object can also return the list of all dataset compatible. here # it will return the list all the imagery datasets from the moabb. compatible_datasets = paradigm.datasets print([dataset.code for dataset in compatible_datasets]) ############################################################################### # FilterBank MotorImagery # ----------------------- # # FilterBankMotorImagery is the same paradigm, but with a different # preprocessing. In this case, it apply a bank of 6 bandpass filter on the data # before concatenating the output. paradigm = FilterBankMotorImagery() print(paradigm.__doc__) ############################################################################### # therefore, the output X is a 4D array, with trial x channel x time x filter X, y, metadata = paradigm.get_data(dataset=dataset, subjects=subjects) print(X.shape) ############################################################################### # LeftRight MotorImagery # ---------------------- # # LeftRightImagery is a variation over the BaseMotorImagery paradigm,