旋转点集后，寻找5个最共线点的算法返回错误结果

我有一个包含15个不同x、y坐标点的点集，想找出其中5个最接近共线的点（无需完全共线，只要是所有5点组合中最接近共线的）。

当前实现步骤 #

• 使用itertools.combinations生成所有可能的5点组合
• 遍历每一组5点组合
• 计算第一个点到其他点的斜率
• 计算第一个斜率与其他斜率的绝对差
• 求和所有差值
• 比较所有组合的差值和，返回和最小的组合

该算法存在问题：在points_0deg点集上工作正常，但将同一点集旋转80度得到points_80deg后，算法会错误地识别红点为最共线点，而非绿点。

相关代码 #

import itertools

points_0deg = [[818.5, 395.5], [688.5, 586.5], [556.5, 448.5], [819.5, 779.5], [657.5, 892.5], [558.5, 727.5],
               [658.5, 278.5], [453.5, 279.5], [426.5, 588.5], [877.5, 589.5], [458.5, 893.5], [301.5, 403.5],
               [296.5, 774.5], [241.5, 583.5], [558.5, 585.5]]
points_80deg = [[498.5, 397.5], [665.5, 558.5], [505.5, 665.5], [356.5, 533.5], [781.5, 711.5], [876.5, 463.5],
                [958.5, 641.5], [619.5, 816.5], [700.5, 373.5], [925.5, 838.5], [414.5, 906.5], [322.5, 737.5],
                [580.5, 998.5], [776.5, 975.5], [640.5, 687.5]]


def check_collinear(points):
    x1, y1 = points[0]

    slope = []
    for point in points[1:]:
        x, y = point
        slope.append((y - y1) / (x - x1) if (x - x1) != 0 else float('inf'))

    diff = []
    for val in slope[1:]:
        diff.append(abs(slope[0] - val))

    return sum(diff)


def find_most_collinear(points):
    combinations = list(itertools.combinations(points, 5))
    collinear_points = None
    min_sum = float('inf')
    for comb in combinations:
        s = check_collinear(comb)
        if s <= min_sum:
            min_sum = s
            collinear_points = comb
    return collinear_points


if __name__ == '__main__':
    print(find_most_collinear(points_0deg))
    print(find_most_collinear(points_80deg))

内容的提问来源于stack exchange，提问作者user3662357