class_docstr: Convolve time series with a kernel window.
  
  Parameters
  ----------
  window : str, tuple, or list, optional
      The type of kernal window used for the convolution.
  
      - If str or tuple, it is a window type that can be passed to
        `scipy.signal.get_window`. See
        https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.get_window.html
        for more details.
      - If list, it is a list of such object. The type of a kernel window
        convolved with a time series is randomly sampled from this list.
  
      Default: "hann".
  
  size : int, list, tuple, optional
      Length of kernel windows.
  
      - If int, all series are convolved with windows of the same length.
      - If list, each series is convolved with a window with a size sampled
        from the list randomly.
      - If 2-tuple, each series is convolved with a window with a size sampled
        from the interval randomly.
  
      Default: 7.
  
  per_channel : bool, optional
      Whether to sample a kernel window for each channel in a time series or
      to use the same window for all channels in a time series. Only used if
      the kernel window is not deterministic. Default: False.
  
  repeats : int, optional
      The number of times a series is augmented. If greater than one, a series
      will be augmented so many times independently. This parameter can also
      be set by operator `*`. Default: 1.
  
  prob : float, optional
      The probability of a series is augmented. It must be in (0.0, 1.0]. This
      parameter can also be set by operator `@`. Default: 1.0.
  
  seed : int, optional
      The random seed. Default: None.
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code: def window(self) -> Union[str, Tuple, List[Union[str, Tuple]]]:
      return self._window
  
file_path: tsaug/src/tsaug/_augmenter/convolve.py
imports: from typing import List, Optional, Tuple, Union
  import numpy
  from scipy.ndimage.filters import convolve1d
  from scipy.signal import get_window
  from .base import _Augmenter, _default_seed
label_desc: Use image node_id 3 for calling the Convolve obj's underlying member method code with example usage: obj.window() and returns: self