code: def test_regression_fit_transform(spark):
      indexdf = spark.read.parquet(
          f"{data_root}/groupedIDs.snappy.parquet"
      )
      level1df = spark.read.parquet(
          f"{data_root}/level1BlockedGT.snappy.parquet"
      ).limit(5)
      group2ids = __get_sample_blocks(indexdf)
  
      regressor = RidgeRegression(
          level1df,
          std_labeldf,
          group2ids,
          add_intercept=False,
          alphas=alphas,
      )
      yhatdf = regressor.fit_transform()
      fit_transform_df = regressor.fit_transform()
  
      assert fit_transform_df.equals(yhatdf)
  
imports: from glow.wgr.ridge_reduction import *
  from glow.wgr.ridge_regression import *
  from glow.wgr.ridge_udfs import *
  from glow.wgr.model_functions import _fill_na_and_standardize
  import numpy
  import pandas
  from pyspark.sql.functions import *
  import math
label_desc: Use image node_id 16 for calling a global function with example usage: test_regression_fit_transform(spark) without return types