code: def plot_epochs_psd(
      epochs,
      fmin=0,
      fmax=np.inf,
      tmin=None,
      tmax=None,
      proj=False,
      bandwidth=None,
      adaptive=False,
      low_bias=True,
      normalization="length",
      picks=None,
      ax=None,
      color="black",
      xscale="linear",
      area_mode="std",
      area_alpha=0.33,
      dB=True,
      estimate="auto",
      show=True,
      n_jobs=None,
      average=False,
      line_alpha=None,
      spatial_colors=True,
      sphere=None,
      exclude="bads",
      verbose=None,
  ):
      """%(plot_psd_doc)s.
  
      Parameters
      ----------
      epochs : instance of Epochs
          The epochs object.
      %(fmin_fmax_psd)s
      %(tmin_tmax_psd)s
      %(proj_psd)s
      bandwidth : float
          The bandwidth of the multi taper windowing function in Hz. The default
          value is a window half-bandwidth of 4.
      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.
      %(normalization)s
      %(picks_good_data_noref)s
      %(ax_plot_psd)s
      %(color_plot_psd)s
      %(xscale_plot_psd)s
      %(area_mode_plot_psd)s
      %(area_alpha_plot_psd)s
      %(dB_plot_psd)s
      %(estimate_plot_psd)s
      %(show)s
      %(n_jobs)s
      %(average_plot_psd)s
      %(line_alpha_plot_psd)s
      %(spatial_colors_psd)s
      %(sphere_topomap_auto)s
      exclude : list of str | 'bads'
          Channels names to exclude from being shown. If 'bads', the bad channels
          are excluded. Pass an empty list to plot all channels (including
          channels marked "bad", if any).
  
          .. versionadded:: 0.24.0
      %(verbose)s
  
      Returns
      -------
      fig : instance of Figure
          Figure with frequency spectra of the data channels.
  
      Notes
      -----
      %(notes_plot_*_psd_func)s
      """
      from ..time_frequency import Spectrum
  
      init_kw, plot_kw = _split_psd_kwargs(plot_fun=Spectrum.plot)
      return epochs.compute_psd(**init_kw).plot(**plot_kw)
  
file_path: mne-python/mne/viz/epochs.py
imports: from collections import Counter
  from copy import deepcopy
  import numpy
  from scipy.ndimage import gaussian_filter1d
  from .._fiff.meas_info import create_info
  from .._fiff.pick import _DATA_CH_TYPES_SPLIT, _VALID_CHANNEL_TYPES, _picks_to_idx
  from ..defaults import _handle_default
  from ..fixes import _sharex
  from ..utils import _check_option, fill_doc, legacy, logger, verbose, warn
  from ..utils.spectrum import _split_psd_kwargs
  from .raw import _setup_channel_selections
  from .utils import DraggableColorbar, _check_cov, _compute_scalings, _get_channel_plotting_order, _handle_decim, _handle_precompute, _make_combine_callable, _make_event_color_dict, _set_title_multiple_electrodes, _set_window_title, _setup_cmap, _setup_vmin_vmax, _validate_type, plt_show
label_desc: Use image node_id 7 for calling a global function with example usage: plot_epochs_psd(epochs, fmin, fmax, tmin, tmax, proj, bandwidth, adaptive, low_bias, normalization, picks, ax, color, xscale, area_mode, area_alpha, dB, estimate, show, n_jobs, average, line_alpha, spatial_colors, sphere, exclude, verbose) and returns: epochs