class_docstr: Compute power spectral density (PSD) using a multi-taper method.
  
  Parameters
  ----------
  sfreq : float
      The sampling frequency.
  fmin : float
      The lower frequency of interest.
  fmax : float
      The upper frequency of interest.
  bandwidth : float
      The bandwidth of the multi taper windowing function in Hz.
  adaptive : bool
      Use adaptive weights to combine the tapered spectra into PSD
      (slow, use n_jobs >> 1 to speed up computation).
  low_bias : bool
      Only use tapers with more than 90%% spectral concentration within
      bandwidth.
  n_jobs : int
      Number of parallel jobs to use (only used if adaptive=True).
  %(normalization)s
  %(verbose)s
  
  See Also
  --------
  mne.time_frequency.psd_array_multitaper
  mne.io.Raw.compute_psd
  mne.Epochs.compute_psd
  mne.Evoked.compute_psd
docstr: Compute power spectral density (PSD) using a multi-taper method.
  
  Parameters
  ----------
  epochs_data : array, shape (n_epochs, n_channels, n_times)
      The data.
  
  Returns
  -------
  psd : array, shape (n_signals, n_freqs) or (n_freqs,)
      The computed PSD.
docstr_tok: ["Compute","power","spectral","density","(","PSD",")","using","a","multi-taper","method",".","Parameters","--","--","--","--","--","epochs_data",":","array",",","shape","(","n_epochs",",","n_channels",",","n_times",")","The","data",".","Returns","--","--","--","-","psd",":","array",",","shape","(","n_signals",",","n_freqs",")","or","(","n_freqs",",",")","The","computed","PSD","."]
code: def transform(self, epochs_data):
      """Compute power spectral density (PSD) using a multi-taper method.
  
      Parameters
      ----------
      epochs_data : array, shape (n_epochs, n_channels, n_times)
          The data.
  
      Returns
      -------
      psd : array, shape (n_signals, n_freqs) or (n_freqs,)
          The computed PSD.
      """
      if not isinstance(epochs_data, np.ndarray):
          raise ValueError(
              "epochs_data should be of type ndarray (got %s)."
              % type(epochs_data)
          )
      psd, _ = psd_array_multitaper(
          epochs_data,
          sfreq=self.sfreq,
          fmin=self.fmin,
          fmax=self.fmax,
          bandwidth=self.bandwidth,
          adaptive=self.adaptive,
          low_bias=self.low_bias,
          normalization=self.normalization,
          n_jobs=self.n_jobs,
      )
      return psd
  
imports: import numpy
  from .._fiff.pick import _pick_data_channels, _picks_by_type, _picks_to_idx, pick_info, pick_types
  from ..cov import _check_scalings_user
  from ..filter import filter_data
  from ..time_frequency import psd_array_multitaper
  from ..utils import _check_option, _validate_type, fill_doc, verbose
  from .base import BaseEstimator
  from .mixin import TransformerMixin
label_desc: Use image node_id 3 for calling the PSDEstimator obj's underlying member method code with example usage: obj.transform(epochs_data) and returns: psd