code: def test_main(self):
      lexicon_df = pd.DataFrame(
          {
              "activation": {
                  "a": 1.3846,
                  "abandon": 2.375,
                  "abandoned": 2.1,
                  "abandonment": 2.0,
                  "abated": 1.3333,
              },
              "imagery": {
                  "a": 1.0,
                  "abandon": 2.4,
                  "abandoned": 3.0,
                  "abandonment": 1.4,
                  "abated": 1.2,
              },
              "pleasantness": {
                  "a": 2.0,
                  "abandon": 1.0,
                  "abandoned": 1.1429,
                  "abandonment": 1.0,
                  "abated": 1.6667,
              },
          }
      )
  
      with self.assertRaises(AssertionError):
          FeatsFromScoredLexicon(3)
      feats_from_scored_lexicon = FeatsFromScoredLexicon(lexicon_df)
      self.assertEqual(
          set(
              feats_from_scored_lexicon.get_top_model_term_lists().keys()
          ),
          set(["activation", "imagery", "pleasantness"]),
      )
      features = feats_from_scored_lexicon.get_doc_metadata(
          whitespace_nlp_with_sentences("I abandoned a wallet.")
      )
      np.testing.assert_almost_equal(
          features[["activation", "imagery", "pleasantness"]],
          np.array([1.74230, 2.00000, 1.57145]),
      )
  
imports: from unittest import TestCase
  import numpy
  import pandas
  from scattertext import whitespace_nlp_with_sentences
  from scattertext.features.FeatsFromScoredLexicon import FeatsFromScoredLexicon
label_desc: Use image node_id 1 for calling the TestFeatsFromScoredLexicon obj's underlying member method code with example usage: obj.test_main() without return types