code: def test_unpartitioned_min_max_scaler(self):
      ls = LinearScalarScaler(
          "score", None, "new_score", 5, 9, use_pandas=False
      )
  
      df = self.create_sample_dataframe().cache()
      model = ls.fit(df)
      new_df = model.transform(df).cache()
  
      assert new_df.count() == df.count()
  
      assert (
          0
          == new_df.filter(
              f.col("name").cast(t.IntegerType())
              != f.col("new_score").cast(t.IntegerType()),
          ).count()
      )
  
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 2 for calling the TestScalers obj's underlying member method code with example usage: obj.test_unpartitioned_min_max_scaler() without return types