code: def test_unpartitioned_standard_scaler(self):
      ls = StandardScalarScaler(
          "score", None, "new_score", 1.0, use_pandas=False
      )
  
      df = self.create_sample_dataframe()
      model = ls.fit(df)
      new_df = model.transform(df)
  
      assert new_df.count() == df.count()
  
      new_scores = new_df.toPandas()["new_score"]
  
      assert new_scores.to_numpy().mean() == 0.0
      assert abs(new_scores.to_numpy().std() - 1.0) < 0.0001
  
file_path: SynapseML/core/src/test/python/synapsemltest/cyber/feature/test_scalers.py
imports: import unittest
  from typing import Type
  from pyspark.sql import functions, types
  from synapse.ml.cyber.feature import LinearScalarScaler, StandardScalarScaler
  from synapsemltest.cyber.explain_tester import ExplainTester
  from synapsemltest.spark import *
label_desc: Use image node_id 4 for calling the TestScalers obj's underlying member method code with example usage: obj.test_unpartitioned_standard_scaler() without return types