code: def animate_chord(x, cthresh=0.05):
      """
      inputs:
        connectomes: a T by [((K^2 - K)/2) + K] array of per-timepoint connectomes.
                     Each timepoint's connectime is represented in a vectorized
                     format *including the diagonal* (i.e., self connections).
  
        cthresh: only show connections in the top (cthresh*100)%; default = 0.25
  
      outputs:
        hmap: a holoviews.HoloMap object containing an interactive animation
      """
      warnings.simplefilter(
          "ignore"
      )  # suppress BokehUserWarning for node colors
  
      hv.output(max_frames=x.shape[0])
      renderer = hv.renderer("bokeh")
      return hv.HoloMap(
          {
              t: mat2chord(tc.vec2mat(x[t, :]), cthresh=cthresh)
              for t in range(x.shape[0])
          },
          kdims="Time (TRs)",
      )
  
imports: import numpy
  import pandas
  import nibabel
  import nilearn
  from nilearn.input_data import NiftiMasker
  import nilearn.plotting
  import matplotlib
  import matplotlib.pyplot
  import holoviews
  import timecorr
  import os
  from brainiak.factoranalysis.htfa import HTFA
  import warnings
  import seaborn
label_desc: Use image node_id 12 for calling a global function with example usage: animate_chord(x, cthresh) and returns: hv