def __calcSamplingWeights__()

in mapillary_sls/datasets/msls.py [0:0]

• 15 lines of code
• 9 McCabe index (conditional complexity)

    def __calcSamplingWeights__(self):

        # length of query
        N = len(self.qIdx)

        # initialize weights
        self.weights = np.ones(N)

        # weight higher if from night or sideways facing
        if len(self.night) != 0:
            self.weights[self.night] += N / len(self.night)
        if len(self.sideways) != 0:
            self.weights[self.sideways] += N / len(self.sideways)

        # print weight information
        print("#Sideways [{}/{}]; #Night; [{}/{}]".format(len(self.sideways), N, len(self.night), N))
        print("Forward and Day weighted with {:.4f}".format(1))
        if len(self.night) != 0:
            print("Forward and Night weighted with {:.4f}".format(1 + N/len(self.night)))
        if len(self.sideways) != 0:
            print("Sideways and Day weighted with {:.4f}".format( 1 + N/len(self.sideways)))
        if len(self.sideways) != 0 and len(self.night) != 0:
            print("Sideways and Night weighted with {:.4f}".format(1 + N/len(self.night) + N/len(self.sideways)))