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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 find_anomalies(errors, index, z_range=(0, 10)):
 """Find sequences of values that are anomalous. We first find the ideal threshold for the set of errors that we have, and then find the sequences of values that are above this threshold. Lastly, we compute a score proportional to the maximum error in the sequence, and finally return the index pairs that correspond to each sequence, along with its score. """


    threshold = find_threshold(errors, z_range)
    sequences = find_sequences(errors, threshold)

    anomalies = list()
    denominator = errors.mean() + errors.std()
    for start, stop in sequences:
        max_error = errors[start:stop + 1].max()
        score = (max_error - threshold) / denominator
        anomalies.append([index[start], index[stop], score])

    return np.asarray(anomalies)