text: """ get_clusters_edit_data.py: a callable Python script that runs get_clusters.py, but with
  user-defined Python arrays instead of FITS filenames."""
  
  import sys
  from sc_classifier import parser
  from sc_classifier.utils import test_dataset_3d
  from get_clusters_from_file import main
  
  def get_parser():
      """ Add some arguments relating to files & smoothing to the default SpatialColorClassifier
          parser """
      p = parser()
      p.add_argument('-P', '--n_pca', dest='n_pca', type=int, default=3,
                     help="Number of PCA modes to keep")
      p.add_argument('-p', '--pca', dest="pca", action="store_true",
                     help="Run a PCA on the spectral dimension of a data cube")
      p.add_argument('-g', '--grow', dest="grow", action="store_true",
                     help="'Grow' the segmentation map to cover unclustered pixels")
      p.add_argument('-m', '--maxpool', dest="maxpool", action="store_true",
                     help="Run a maxpool algorithm to denoise segmentation map")
      p.add_argument('-o', dest="output_file", type=str,
                     help="Output filename for diagnostic image")
      return p
  
  
  if __name__ == '__main__':
      # Get a parser and parse command-line arguments
      p = get_parser()
      kwargs = p.parse_args(sys.argv[1:]).__dict__
      # Change the 'filename' arg to be a dataset of your choice
      kwargs['filename'] = test_dataset_3d()
      # run the clustering
      main(**kwargs)
  