damage_simulation.py 文件源码

def _tipping_point_update(self, tmp, consump, peak_temp_interval=30.0):
        """Determine whether a tipping point has occurred, if so reduce consumption for 
        all periods after this date.
        """
        draws = tmp.shape[0]
        disaster = self._disaster_simulation()
        disaster_cons = self._disaster_cons_simulation()
        period_lengths = self.tree.decision_times[1:] - self.tree.decision_times[:-1]

        tmp_scale = np.maximum(self.peak_temp, tmp)
        ave_prob_of_survival = 1.0 - np.square(tmp / tmp_scale) 
        prob_of_survival = ave_prob_of_survival**(period_lengths / peak_temp_interval)
        # this part may be done better, this takes a long time to loop over
        res = prob_of_survival < disaster
        rows, cols = np.nonzero(res)
        row, count = np.unique(rows, return_counts=True)
        first_occurance = zip(row, cols[np.insert(count.cumsum()[:-1],0,0)])
        for pos in first_occurance:
            consump[pos[0], pos[1]:] *= np.exp(-disaster_cons[pos[0]])
        return consump