class_docstr: Finds and removes flat channels.
  
  Attributes
  ----------
  channels_ : ndarray, shape (n_good_channels)
      The indices of the non-flat channels.
class_docstr_tok: ["Finds","and","removes","flat","channels",".","Attributes","--","--","--","--","--","channels_",":","ndarray",",","shape","(","n_good_channels",")","The","indices","of","the","non-flat","channels","."]
docstr: Find flat channels.
  
  Parameters
  ----------
  X : ndarray, shape (n_matrices, n_channels, n_times)
      Multi-channel time-series.
  y : None
      Not used, here for compatibility with sklearn API.
  
  Returns
  -------
  X : ndarray, shape (n_matrices, n_good_channels, n_times)
      Multi-channel time-series without flat channels.
docstr_tok: ["Find","flat","channels",".","Parameters","--","--","--","--","--","X",":","ndarray",",","shape","(","n_matrices",",","n_channels",",","n_times",")","Multi-channel","time-series",".","y",":","None","Not","used",",","here","for","compatibility","with","sklearn","API",".","Returns","--","--","--","-","X",":","ndarray",",","shape","(","n_matrices",",","n_good_channels",",","n_times",")","Multi-channel","time-series","without","flat","channels","."]
code: def fit(self, X, y=None):
      """Find flat channels.
  
      Parameters
      ----------
      X : ndarray, shape (n_matrices, n_channels, n_times)
          Multi-channel time-series.
      y : None
          Not used, here for compatibility with sklearn API.
  
      Returns
      -------
      X : ndarray, shape (n_matrices, n_good_channels, n_times)
          Multi-channel time-series without flat channels.
      """
      std = np.mean(np.std(X, axis=2) ** 2, 0)
      self.channels_ = np.where(std)[0]
      return self
  
file_path: pyRiemann/pyriemann/channelselection.py
imports: import numpy
  from sklearn.base import BaseEstimator, TransformerMixin
  from .utils.distance import distance
  from .classification import MDM
label_desc: Use image node_id 1 for calling the FlatChannelRemover obj's underlying member method code with example usage: obj.fit(X, y) and returns: self