code: def test_values_expr(spark, rg):
      from pyspark.sql.functions import array, lit
  
      num_samples = 5
      genotype_df = spark.range(1).withColumn("genotypes", lit(42))
      phenotype_df = pd.DataFrame(rg.random((num_samples, 5)))
      covariate_df = pd.DataFrame(rg.random((num_samples, 2)))
      array_vals = [lit(i) for i in range(num_samples)]
      results = lr.linear_regression(
          genotype_df,
          phenotype_df,
          covariate_df,
          values_column=array(*array_vals),
      )
      pandas_genotype_df = pd.DataFrame({"values": range(num_samples)})
      baseline = statsmodels_baseline(
          pandas_genotype_df, phenotype_df, covariate_df
      )
      assert regression_results_equal(
          baseline, results.drop("id").toPandas()
      )
      assert not "genotypes" in [field.name for field in results.schema]
  
imports: import functions
  import numpy
  import statsmodels.api
  import pandas
  import glow.gwas.functions
  import glow.gwas.lin_reg
  import pytest
label_desc: Use image node_id 37 for calling a global function with example usage: test_values_expr(spark, rg) without return types