online_attacks/online_algorithms/stochastic_optimistic.py [34:50]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    def reset(self):
        super().reset()
        self.R = []
        self.sampling_phase = True

    def action(self, value: float, index: int):
        if self.sampling_phase:
            self.R.append([value, index])
            self.R.sort(key=lambda tup: tup[0], reverse=True)  # sorts in place
            self.R = self.R[: self.k]

            if index >= self.threshold:
                self.sampling_phase = False
        else:
            num_picked = len(self.S)
            num_left_to_pick = self.k - num_picked
            num_samples_left = self.N - index
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



online_attacks/online_algorithms/stochastic_single_ref.py [109:125]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    def reset(self):
        super().reset()
        self.R = []
        self.sampling_phase = True

    def action(self, value: float, index: int):
        if self.sampling_phase:
            self.R.append([value, index])
            self.R.sort(key=lambda tup: tup[0], reverse=True)  # sorts in place
            self.R = self.R[: self.k]

            if index >= self.threshold:
                self.sampling_phase = False
        else:
            num_picked = len(self.S)
            num_left_to_pick = self.k - num_picked
            num_samples_left = self.N - index
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -