code: def plot_epi(
      epi_img=None,
      cut_coords=None,
      output_file=None,
      display_mode="ortho",
      figure=None,
      axes=None,
      title=None,
      annotate=True,
      draw_cross=True,
      black_bg=True,
      colorbar=False,
      cbar_tick_format="%.2g",
      cmap=plt.cm.nipy_spectral,
      vmin=None,
      vmax=None,
      radiological=False,
      **kwargs,
  ):
      """Plot cuts of an :term:`EPI` image.
  
      By default 3 cuts: Frontal, Axial, and Lateral.
  
      Parameters
      ----------
      epi_img : a nifti-image like object or a filename, optional
          The :term:`EPI` (T2*) image.
      %(cut_coords)s
      %(output_file)s
      %(display_mode)s
      %(figure)s
      %(axes)s
      %(title)s
      %(annotate)s
      %(draw_cross)s
      %(black_bg)s
          Default=True.
      colorbar : boolean, default=False
          If True, display a colorbar on the right of the plots.
      cbar_tick_format: str, default="%%.2g" (scientific notation)
          Controls how to format the tick labels of the colorbar.
          Ex: use "%%i" to display as integers.
      %(cmap)s
          Default=`plt.cm.nipy_spectral`.
      %(vmin)s
      %(vmax)s
      %(radiological)s
  
      Returns
      -------
      display : :class:`~nilearn.plotting.displays.OrthoSlicer` or None
          An instance of the OrthoSlicer class. If ``output_file`` is defined,
          None is returned.
  
      Notes
      -----
      Arrays should be passed in numpy convention: (x, y, z) ordered.
  
      """
      display = plot_img(
          epi_img,
          cut_coords=cut_coords,
          output_file=output_file,
          display_mode=display_mode,
          figure=figure,
          axes=axes,
          title=title,
          threshold=None,
          annotate=annotate,
          draw_cross=draw_cross,
          black_bg=black_bg,
          colorbar=colorbar,
          cbar_tick_format=cbar_tick_format,
          cmap=cmap,
          vmin=vmin,
          vmax=vmax,
          radiological=radiological,
          **kwargs,
      )
      return display
  
imports: import collections.abc
  import functools
  import numbers
  import os
  import warnings
  import matplotlib
  import matplotlib.pyplot
  import numpy
  from matplotlib import gridspec
  from matplotlib.colors import LinearSegmentedColormap
  from nibabel.spatialimages import SpatialImage
  from scipy import stats
  from scipy.ndimage import binary_fill_holes
  from nilearn.image.resampling import reorder_img
  from nilearn.maskers import NiftiMasker
  from nilearn.plotting.displays import get_projector, get_slicer
  from nilearn.plotting.displays._slicers import _get_cbar_ticks
  from ..None import _utils
  from .._utils import compare_version, fill_doc
  from .._utils.extmath import fast_abs_percentile
  from .._utils.ndimage import get_border_data
  from .._utils.niimg import safe_get_data
  from .._utils.numpy_conversions import as_ndarray
  from .._utils.param_validation import check_threshold
  from ..datasets import load_mni152_template
  from ..image import get_data, iter_img, math_img, new_img_like, resample_to_img
  from ..masking import apply_mask, compute_epi_mask
  from ..signal import clean
  from .None import cm
label_desc: Use image node_id 8 for calling a global function with example usage: plot_epi(epi_img, cut_coords, output_file, display_mode, figure, axes, title, annotate, draw_cross, black_bg, colorbar, cbar_tick_format, cmap, vmin, vmax, radiological) and returns: display