def map_zero_one(A):
    """
    Maps a given array to the interval [0,1]
    """
    # return A
    # print("MI max and min ",A.max(),A.min())
    A_std = (A - A.min())/(A.max()-A.min())
    retval = A_std * (A.max() - A.min()) + A.min()
    return A_std
    # return softmax(A)
    # return torch.sigmoid(torch.Tensor(A)).numpy()