code: def test_chi_ReferenceNormHistComparer():
      hist_list = [
          "date:country",
          "date:bankrupt",
          "date:num_employees",
          "date:A_score",
          "date:A_score:num_employees",
      ]
  
      pipeline = Pipeline(
          modules=[
              JsonReader(
                  file_path=resources.data("example_histogram.json"),
                  store_key="example_hist",
              ),
              HistSplitter(
                  read_key="example_hist",
                  store_key="output_hist",
                  features=hist_list,
              ),
              ReferenceNormHistComparer(
                  reference_key="output_hist",
                  assign_to_key="output_hist",
                  store_key="comparisons",
              ),
          ]
      )
      datastore = pipeline.transform(datastore={})
  
      assert "comparisons" in datastore
      for f in [
          "A_score",
          "A_score:num_employees",
          "bankrupt",
          "country",
          "num_employees",
      ]:
          assert f in datastore["comparisons"]
  
      df = datastore["comparisons"]["A_score"]
      np.testing.assert_almost_equal(
          df["chi2"].values[0], 2.2884111855886022
      )
  
imports: import numpy
  import pandas
  import pytest
  from popmon import resources
  from popmon.analysis.apply_func import ApplyFunc
  from popmon.analysis.comparison import ExpandingNormHistComparer, ReferenceNormHistComparer, RollingNormHistComparer
  from popmon.analysis.functions import expand, expand_norm_hist_mean_cov, expanding_hist, normalized_hist_mean_cov, relative_chi_squared, roll, roll_norm_hist_mean_cov, rolling_hist
  from popmon.base import Pipeline
  from popmon.hist.hist_splitter import HistSplitter
  from popmon.io import JsonReader
label_desc: Use image node_id 10 for calling a global function with example usage: test_chi_ReferenceNormHistComparer() without return types