Function score

scalg.py:30–103

Analyse and score a dataset using a range based percentual proximity algorithm and calculate the linear maximum likelihood estimation. Args: source_data (list): Data set to process. weights (list): Weights corresponding to each column from the data set. 0 if lower

(source_data: list, weights: list, *args)

def score(source_data: list, weights: list, *args) -> list:
    """Analyse and score a dataset using a range based percentual proximity
    algorithm and calculate the linear maximum likelihood estimation.
    Args:
        source_data (list): Data set to process.
        weights (list): Weights corresponding to each column from the data set.
            0 if lower values have higher weight in the data set,
            1 if higher values have higher weight in the data set
    Optional args:
        "score_lists" (str): Returns a list with lists of each column scores.
        "scores" (str): Returns only the final scores.
    Raises:
        ValueError: Weights can only be either 0 or 1 (int)
    Returns:
        list: Source data with the score of the set appended at as the last element.
    """

    # getting data
    data_lists = []
    for item in source_data:
        for i, val in enumerate(item):
            try:
                data_lists[i].append(float(val))
            except IndexError:
                data_lists.append([])
                data_lists[i].append(float(val))

    # calculating price score
    score_lists = []
    for dlist, weight in zip(data_lists, weights):
        mind = min(dlist)
        maxd = max(dlist)

        score = []
        if weight == 0:
            for item in dlist:
                try:
                    score.append(1 - ((item - mind) / (maxd - mind)))
                except ZeroDivisionError:
                    score.append(1)

        elif weight == 1:
            for item in dlist:
                try:
                    score.append((item - mind) / (maxd - mind))
                except ZeroDivisionError:
                    score.append(0)

        else:
            raise ValueError("Invalid weight of %f provided" % (weight))

        score_lists.append(score)

    # return score lists
    if "score_lists" in args:
        return score_lists

    # initialize final scores