class_docstr: Store data in chunks.
code: def __init__(self, *outs, picks=None):
      for oi, out in enumerate(outs):
          if not isinstance(out, np.ndarray) or out.ndim < 1:
              raise TypeError(
                  f"outs[oi] must be >= 1D ndarray, got {out}"
              )
      self.outs = outs
      self.idx = 0
      self.picks = picks
  
file_path: mne-python/mne/_ola.py
imports: import numpy
  from scipy.signal import get_window
  from .utils import _ensure_int, logger, verbose
label_desc: Use image node_id 1 to create a new _Storer object  with example: obj = _Storer()