class_docstr: Drift the value of time series.
  
  The augmenter drifts the value of time series from its original values
  randomly and smoothly. The extent of drifting is controlled by the maximal
  drift and the number of drift points.
  
  Parameters
  ----------
  max_drift : float or tuple, optional
      The maximal amount of drift added to a time series.
  
      - If float, all series (all channels if `per_channel` is True) are
        drifted with the same maximum.
      - If tuple, the maximal drift added to a time series (a channel if
        `per_channel` is True) is sampled from this interval randomly.
  
      Default: 0.5.
  
  n_drift_points : int or list, optional
      The number of time points a new drifting trend is defined in a series.
  
      - If int, all series (all channels if `per_channel` is True) have the
        same number of drift points.
      - If list, the number of drift points defined in a series (a channel if
        `per_channel` is True) is sampled from this list randomly.
  
  kind : str, optional
      How the noise is added to the original time series. It must be either
      'additive' or 'multiplicative'. Default: 'additive'.
  
  per_channel : bool, optional
      Whether to sample independent drifting trends for each channel in a time
      series or to use the same drifting trends for all channels in a time
      series. Default: True.
  
  normalize : bool, optional
      Whether the drifting trend is added to the normalized time series. If
      True, each channel of a time series is normalized to [0, 1] first.
      Default: True.
  
  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 per_channel(self) -> bool:
      return self._per_channel
  
file_path: tsaug/src/tsaug/_augmenter/drift.py
imports: from typing import Callable, List, Optional, Tuple, Union
  import numpy
  from scipy.interpolate import CubicSpline
  from .base import _Augmenter, _default_seed
label_desc: Use image node_id 7 for calling the Drift obj's underlying member method code with example usage: obj.per_channel() and returns: self