def reset_fixed_weights()

in datasets/MixedPrioritizedSampler.py [0:0]

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

    def reset_fixed_weights(self, fixed_weights, rescale=False):
        """ Reset the manually designed weights and 
            update the whole tree accordingly.

            @rescale: rescale the fixed_weights such that 
            fixed_weights.sum() = self.fixed_scale * adaptive_weights.sum()
        """

        adaptive_weights = self.get_adaptive_weights()
        fixed_sum = fixed_weights.sum()
        if rescale and fixed_sum > 0:
            scale = self.fixed_scale * adaptive_weights.sum() / fixed_sum
            self.fixed_weights = fixed_weights * scale
        else:
            self.fixed_weights = fixed_weights
        self.update_whole(self.fixed_weights + adaptive_weights)