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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 sum_of_reoccurring_values(x):
 """ Returns the sum of all values, that are present in the time series more than once. :param x: the time series to calculate the feature of :type x: numpy.ndarray :return: the value of this feature :return type: float """

    unique, counts = np.unique(x, return_counts=True)
    counts[counts < 2] = 0
    counts[counts > 1] = 1
    return np.sum(counts * unique)