def compute_whdr(self, r, delta=0.10):

        error_sum = 0.0
        weight_sum = 0.0

        for c in self.comparisons:
            point1 = self.id_to_points[c['point1']]
            point2 = self.id_to_points[c['point2']]
            darker = c['darker']
            weight = c['darker_score']

            if not point1['opaque'] or not point2['opaque']:
                continue
            if weight < 0 or weight is None:
                raise ValueError("Invalid darker_score: %s" % weight)
            if darker not in ('1', '2', 'E'):
                raise ValueError("Invalid darker: %s" % darker)

            l1 = np.mean(r[
                int(point1['y'] * r.shape[0]),
                int(point1['x'] * r.shape[1]),
                ...])
            l2 = np.mean(r[
                int(point2['y'] * r.shape[0]),
                int(point2['x'] * r.shape[1]),
                ...])

            l1 = max(l1, 1e-10)
            l2 = max(l2, 1e-10)

            if l2 / l1 > 1.0 + delta:
                alg_darker = '1'
            elif l1 / l2 > 1.0 + delta:
                alg_darker = '2'
            else:
                alg_darker = 'E'

            if darker != alg_darker:
                error_sum += weight
            weight_sum += weight

        if weight_sum:
            return error_sum / weight_sum
        else:
            return None
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dataset/ETHPy150Open seanbell/intrinsic/bell2014/judgements.py/HumanReflectanceJudgements.compute_whdr--crossover with--dataset/ETHPy150Open DataDog/dogapi/src/dogapi/http/events.py/EventApi.comment