code: def opts(debug=False):
      """
      Return a dictionary of parameters to pass to
      brainiak.factoranalysis.htfa.HTFA
  
      inputs:
        debug: set to True (default) to generate a quick test fit and False to
               generate a (slower) more accurate fit.
      """
      if debug:
          return {
              "K": 10,
              "max_global_iter": 3,
              "max_local_iter": 3,
              "voxel_ratio": 0.1,
              "tr_ratio": 0.1,
              "max_voxel_scale": 0.1,
              "max_tr_scale": 0.1,
              "verbose": True,
          }
      else:
          return {
              "K": 50,
              "max_global_iter": 10,
              "max_local_iter": 5,
              "voxel_ratio": 0.1,
              "tr_ratio": 0.1,
              "max_voxel_scale": 0.25,
              "max_tr_scale": 0.25,
              "verbose": True,
          }
  
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 1 for calling a global function with example usage: opts(debug) and returns: dict, dict