

def set_Xy(self, X, y):
    num_examples = X.shape[0]
    total_ratio = sum(self.ratio)
    num_train = int((((self.ratio[0] * 1.0) * num_examples) / total_ratio))
    num_valid = int((((self.ratio[1] * 1.0) * num_examples) / total_ratio))
    train_X = X[:num_train]
    train_y = y[:num_train]
    valid_X = X[num_train:(num_train + num_valid)]
    valid_y = y[num_train:(num_train + num_valid)]
    test_X = X[(num_train + num_valid):]
    test_y = y[(num_train + num_valid):]
    self.train = IterMatrix(train_X, train_y, iter_class=self.iter_class, batch_size=self.batch_size, num_batches=self.num_batches, rng=self.rng)
    if (self.ratio[1] == 0):
        self.log.warning('Valid set is empty! It is needed for early stopping and saving best model')
    self.valid = IterMatrix(valid_X, valid_y, iter_class=self.iter_class, batch_size=self.batch_size, num_batches=self.num_batches, rng=self.rng)
    if (self.ratio[2] == 0):
        self.log.warning('Test set is empty! It is needed for testing the best model')
    self.test = IterMatrix(test_X, test_y, iter_class=self.iter_class, batch_size=self.batch_size, num_batches=self.num_batches, rng=self.rng)

dataset/ETHPy150Open hycis/Pynet/pynet/datasets/dataset.py SingleBlock.set_Xy/original