code: def test_second_level_voxelwise_attribute_errors(attribute):
      """Tests that an error is raised when trying to access
      voxelwise attributes before fitting the model, before
      computing a contrast, and when not setting
      ``minimize_memory`` to ``True``.
      """
      shapes = (SHAPE,)
      mask, fmri_data, _ = generate_fake_fmri_data_and_design(shapes)
      model = SecondLevelModel(mask_img=mask, minimize_memory=False)
  
      with pytest.raises(ValueError, match="The model has no results."):
          getattr(model, attribute)
  
      Y = fmri_data * 4
      X = pd.DataFrame([[1]] * 4, columns=["intercept"])
      model.fit(Y, design_matrix=X)
  
      with pytest.raises(ValueError, match="The model has no results."):
          getattr(model, attribute)
      with pytest.raises(ValueError, match="attribute must be one of"):
          model._get_voxelwise_model_attribute("foo", True)
  
      model = SecondLevelModel(mask_img=mask, minimize_memory=True)
      model.fit(Y, design_matrix=X)
      model.compute_contrast()
  
      with pytest.raises(
          ValueError, match="To access voxelwise attributes"
      ):
          getattr(model, attribute)
  
imports: import os
  from pathlib import Path
  import numpy
  import pandas
  import pytest
  from nibabel import Nifti1Image, load
  from numpy.testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from scipy import stats
  from nilearn._utils import testing
  from nilearn._utils.data_gen import generate_fake_fmri_data_and_design, write_fake_bold_img, write_fake_fmri_data_and_design
  from nilearn.glm.first_level import FirstLevelModel, run_glm
  from nilearn.glm.second_level import SecondLevelModel, non_parametric_inference
  from nilearn.glm.second_level.second_level import _check_confounds, _check_design_matrix, _check_effect_maps, _check_first_level_contrast, _check_input_as_first_level_model, _check_output_type, _check_second_level_input, _infer_effect_maps, _process_second_level_input_as_dataframe, _process_second_level_input_as_firstlevelmodels, _sort_input_dataframe
  from nilearn.image import concat_imgs, get_data, new_img_like, smooth_img
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 35 for calling a global function with example usage: test_second_level_voxelwise_attribute_errors(attribute) without return types