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| import numpy as np | |
| class TemporalConsistencyModel: | |
| """ | |
| Simple temporal smoothing model to capture flicker and irregular changes. | |
| Works as a moving average + penalty for inconsistent transitions. | |
| """ | |
| def __init__(self, window=5, alpha=0.7): | |
| self.window = window | |
| self.alpha = alpha | |
| self.history = [] | |
| def update(self, score): | |
| self.history.append(score) | |
| if len(self.history) > self.window: | |
| self.history.pop(0) | |
| smoothed = np.mean(self.history) | |
| # penalize high oscillations | |
| flicker_penalty = np.std(self.history) | |
| final = (self.alpha * smoothed) - (0.5 * flicker_penalty) | |
| return np.clip(final, 0, 1) | |
| ####################################################################################################################################################3 | |