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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 number_crossing_m(x, m):
 """ Calculates the number of crossings of x on m. A crossing is defined as two sequential values where the first value is lower than m and the next is greater, or vice-versa. If you set m to zero, you will get the number of zero crossings. :param x: the time series to calculate the feature of :type x: numpy.ndarray :param m: the threshold for the crossing :type m: float :return: the value of this feature :return type: int """

    if not isinstance(x, (np.ndarray, pd.Series)):
        x = np.asarray(x)
    # From https://stackoverflow.com/questions/3843017/efficiently-detect-sign-changes-in-python
    positive = x > m
    return np.where(np.bitwise_xor(positive[1:], positive[:-1]))[0].size