AL-get_k_random_samples

get_k_random_samples.py

def get_k_random_samples(initial_labeled_samples, X_train_full,
                         y_train_full):
    random_state = check_random_state(0)
    permutation = np.random.choice(trainset_size,
                                   initial_labeled_samples,
                                   replace=False)
    print ()
    print ('initial random chosen samples', permutation.shape),
#            permutation)
    X_train = X_train_full[permutation]
    y_train = y_train_full[permutation]
    X_train = X_train.reshape((X_train.shape[0], -1))
    bin_count = np.bincount(y_train.astype('int64'))
    unique = np.unique(y_train.astype('int64'))
    print (
        'initial train set:',
        X_train.shape,
        y_train.shape,
        'unique(labels):',
        bin_count,
        unique,
        )
    return (permutation, X_train, y_train)