old_contents: import os
  import pytest
  import pandas as pd
  from glob import glob
  import numpy as np
  
  from gypsy import DATA_DIR
  from gypsy.forward_simulation import simulate_forwards_df
  
  
  TEST_FILES = glob(os.path.join(DATA_DIR, 'forward_simulation_files', '*.csv'))
  TEST_FILES = [(item) for item in TEST_FILES]
  CHART_FILES = glob(os.path.join(DATA_DIR, 'output', 'comparisons*.csv'))
  CHART_FILES = [(item) for item in CHART_FILES]
  
  
  @pytest.mark.parametrize("test_file", TEST_FILES)
  def test_compare_forward_simulation(test_file):
      input_df = pd.read_csv(test_file)
      expected_data_path = os.path.join(
          DATA_DIR, 'output',
          'comparisons_{}'.format(os.path.basename(test_file))
      )
  
      plot_id = str(int(input_df.loc[0, 'PlotID']))
  
      result = simulate_forwards_df(input_df, simulation_choice='yes')[plot_id]
      expected = pd.read_csv(expected_data_path, index_col=0)
  
      assert isinstance(result, pd.DataFrame)
      assert np.allclose(
          expected.values.astype(np.float64), result.values.astype(np.float64),
          equal_nan=True
      )
  
      # regenerate output files
      # result.to_csv(expected_data_path)
  
new_contents: import os
  import pytest
  import pandas as pd
  from glob import glob
  import numpy as np
  
  from gypsy import DATA_DIR
  from gypsy.forward_simulation import simulate_forwards_df
  
  
  TEST_FILES = glob(os.path.join(DATA_DIR, 'forward_simulation_files', '*.csv'))
  TEST_FILES = [(item) for item in TEST_FILES]
  CHART_FILES = glob(os.path.join(DATA_DIR, 'output', 'comparisons*.csv'))
  CHART_FILES = [(item) for item in CHART_FILES]
  
  
  @pytest.mark.parametrize("test_file", TEST_FILES)
  def test_compare_forward_simulation(test_file):
      input_df = pd.read_csv(test_file)
      expected_data_path = os.path.join(
          DATA_DIR, 'output',
          'comparisons_{}'.format(os.path.basename(test_file))
      )
  
      plot_id = str(int(input_df.loc[0, 'PlotID']))
  
      result = simulate_forwards_df(input_df, simulation_choice='yes')[plot_id]
      expected = pd.read_csv(expected_data_path, index_col=0)
  
      assert isinstance(result, pd.DataFrame)
      assert np.testing.assert_allclose(
          expected.values, result.values,
          rtol=0, atol=1e-4,
          equal_nan=True
      )
  
      # regenerate output files
      # result.to_csv(expected_data_path)
  
subject: Revise tests to use np.testing.assert_allclose