code: def testQuantize():
      featureNames = ["f1", "f2", "f3"]
  
      spark = test_helpers.getOrCreateSparkSession(
          test_helpers.getCurrentMethodName()
      )
      import catboost_spark
  
      implTestQuantizeCase(
          pool_test_helpers.createSchema(
              [("features", VectorUDT()), ("label", DoubleType())],
              featureNames,
              addFeatureNamesMetadata=True,
          ),
          srcData=[
              Row(Vectors.dense(0.0, 1.0, 0.2), 0.0),
              Row(Vectors.dense(0.1, 1.1, 2.1), 1.0),
              Row(Vectors.dense(0.2, 1.2, 2.2), 1.0),
              Row(Vectors.dense(0.0, 1.1, 3.2), 0.0),
          ],
          quantizationParams=catboost_spark.QuantizationParams(),
      )
  
file_path: catboost/catboost/spark/catboost4j-spark/core/src/test/python/pool_quantization_test.py
imports: import test_helpers
  import pool_test_helpers
  from pyspark.ml.linalg import Vectors, VectorUDT
  from pyspark.sql import Row
  from pyspark.sql.types import *
label_desc: Use image node_id 2 for calling a global function with example usage: testQuantize() without return types