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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def allan_variance(data, dt, tmax=10):
 """Calculate Allan variance. Args: data (np.ndarray):
 Input data. dt (float):
 Time between each data. tmax (float):
 Maximum time. Returns: vk (np.ndarray):
 Frequency. allanvar (np.ndarray):
 Allan variance. """

    allanvar = []
    nmax = len(data) if len(data) < tmax / dt else int(tmax / dt)
    for i in range(1, nmax+1):
        databis = data[len(data) % i:]
        y = databis.reshape(len(data)//i, i).mean(axis=1)
        allanvar.append(((y[1:] - y[:-1])**2).mean() / 2)
    return dt * np.arange(1, nmax+1), np.array(allanvar)