code: def test_reshape_loco_string_contig(spark):
      df = pd.read_csv(
          "test-data/wgr/ridge-regression/level1YHatLoco.csv",
          dtype={"contigName": "str"},
      ).set_index(["sample_id", "contigName"])
      reshaped = glow.wgr.reshape_for_gwas(spark, df)
      assert reshaped.count() == 12
      assert reshaped.columns == ["contigName", "label", "values"]
      pt_list = (
          reshaped.where('label = "sim100" and contigName = "1"')
          .head()
          .values
      )
      expected = df.xs("1", level="contigName")["sim100"].to_numpy()
      assert np.allclose(expected, np.array(pt_list))
  
imports: import numpy
  import pandas
  import pytest
  import glow
label_desc: Use image node_id 3 for calling a global function with example usage: test_reshape_loco_string_contig(spark) without return types