code: def test_MultipleRegressionDesign_inputs():
      input_map = dict(
          covariates=dict(
              field="cov",
          ),
          explicit_mask_file=dict(
              extensions=None,
              field="masking.em",
          ),
          global_calc_mean=dict(
              field="globalc.g_mean",
              xor=["global_calc_omit", "global_calc_values"],
          ),
          global_calc_omit=dict(
              field="globalc.g_omit",
              xor=["global_calc_mean", "global_calc_values"],
          ),
          global_calc_values=dict(
              field="globalc.g_user.global_uval",
              xor=["global_calc_mean", "global_calc_omit"],
          ),
          global_normalization=dict(
              field="globalm.glonorm",
          ),
          in_files=dict(
              field="des.mreg.scans",
              mandatory=True,
          ),
          include_intercept=dict(
              field="des.mreg.incint",
              usedefault=True,
          ),
          matlab_cmd=dict(),
          mfile=dict(
              usedefault=True,
          ),
          no_grand_mean_scaling=dict(
              field="globalm.gmsca.gmsca_no",
          ),
          paths=dict(),
          spm_mat_dir=dict(
              field="dir",
          ),
          threshold_mask_absolute=dict(
              field="masking.tm.tma.athresh",
              xor=["threshold_mask_none", "threshold_mask_relative"],
          ),
          threshold_mask_none=dict(
              field="masking.tm.tm_none",
              xor=[
                  "threshold_mask_absolute",
                  "threshold_mask_relative",
              ],
          ),
          threshold_mask_relative=dict(
              field="masking.tm.tmr.rthresh",
              xor=["threshold_mask_absolute", "threshold_mask_none"],
          ),
          use_implicit_threshold=dict(
              field="masking.im",
          ),
          use_mcr=dict(),
          use_v8struct=dict(
              min_ver="8",
              usedefault=True,
          ),
          user_covariates=dict(
              field="des.mreg.mcov",
          ),
      )
      inputs = MultipleRegressionDesign.input_spec()
  
      for key, metadata in list(input_map.items()):
          for metakey, value in list(metadata.items()):
              assert getattr(inputs.traits()[key], metakey) == value
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_MultipleRegressionDesign_inputs() without return types