8000 Static random augmentation across multiple time series · Issue #17 · arundo/tsaug · GitHub
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Static random augmentation across multiple time series #17
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@jgrss

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@jgrss

Hello,

I have a use case where I apply temporal augmentation with the same random anchor across multiple time series within a segmented object. I.e., I want certain augmentations to vary across objects, but remain constant within objects.

In TimeWarp, e.g., I've added an optional keyword argument (static_rand):

    def __init__(
         self,
         n_speed_change: int = 3,
         max_speed_ratio: Union[float, Tuple[float, float], List[float]] = 3.0,
         repeats: int = 1,
         prob: float = 1.0,
         seed: Optional[int] = _default_seed,
         static_rand: Optional[bool] = False
     ):

which is used by:

         if self.static_rand:                                                                                                                      
             anchor_values = rand.uniform(low=0.0, high=1.0, size=self.n_speed_change + 1)
             anchor_values = np.tile(anchor_values, (N, 1))
         else:
             anchor_values = rand.uniform(
                 low=0.0, high=1.0, size=(N, self.n_speed_change + 1)
             )

Thus, instead of having N time series with different random anchor_values, I generate N time series with the same anchor value.

I use this approach with TimeWarp and Drift. Would this be of any interest as a PR, or does it sound too specific?

Thanks for the nice library.

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