code: def test_TCorrMap_inputs():
      input_map = dict(
          absolute_threshold=dict(
              argstr="-Thresh %f %s",
              extensions=None,
              name_source="in_file",
              suffix="_thresh",
              xor=(
                  "absolute_threshold",
                  "var_absolute_threshold",
                  "var_absolute_threshold_normalize",
              ),
          ),
          args=dict(
              argstr="%s",
          ),
          automask=dict(
              argstr="-automask",
          ),
          average_expr=dict(
              argstr="-Aexpr %s %s",
              extensions=None,
              name_source="in_file",
              suffix="_aexpr",
              xor=("average_expr", "average_expr_nonzero", "sum_expr"),
          ),
          average_expr_nonzero=dict(
              argstr="-Cexpr %s %s",
              extensions=None,
              name_source="in_file",
              suffix="_cexpr",
              xor=("average_expr", "average_expr_nonzero", "sum_expr"),
          ),
          bandpass=dict(
              argstr="-bpass %f %f",
          ),
          blur_fwhm=dict(
              argstr="-Gblur %f",
          ),
          correlation_maps=dict(
              argstr="-CorrMap %s",
              extensions=None,
              name_source="in_file",
          ),
          correlation_maps_masked=dict(
              argstr="-CorrMask %s",
              extensions=None,
              name_source="in_file",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          expr=dict(),
          histogram=dict(
              argstr="-Hist %d %s",
              extensions=None,
              name_source="in_file",
              suffix="_hist",
          ),
          histogram_bin_numbers=dict(),
          in_file=dict(
              argstr="-input %s",
              copyfile=False,
              extensions=None,
              mandatory=True,
          ),
          mask=dict(
              argstr="-mask %s",
              extensions=None,
          ),
          mean_file=dict(
              argstr="-Mean %s",
              extensions=None,
              name_source="in_file",
              suffix="_mean",
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          out_file=dict(
              argstr="-prefix %s",
              extensions=None,
              name_source=["in_file"],
              name_template="%s_afni",
          ),
          outputtype=dict(),
          pmean=dict(
              argstr="-Pmean %s",
              extensions=None,
              name_source="in_file",
              suffix="_pmean",
          ),
          polort=dict(
              argstr="-polort %d",
          ),
          qmean=dict(
              argstr="-Qmean %s",
              extensions=None,
              name_source="in_file",
              suffix="_qmean",
          ),
          regress_out_timeseries=dict(
              argstr="-ort %s",
              extensions=None,
          ),
          seeds=dict(
              argstr="-seed %s",
              extensions=None,
              xor="seeds_width",
          ),
          seeds_width=dict(
              argstr="-Mseed %f",
              xor="seeds",
          ),
          sum_expr=dict(
              argstr="-Sexpr %s %s",
              extensions=None,
              name_source="in_file",
              suffix="_sexpr",
              xor=("average_expr", "average_expr_nonzero", "sum_expr"),
          ),
          thresholds=dict(),
          var_absolute_threshold=dict(
              argstr="-VarThresh %f %f %f %s",
              extensions=None,
              name_source="in_file",
              suffix="_varthresh",
              xor=(
                  "absolute_threshold",
                  "var_absolute_threshold",
                  "var_absolute_threshold_normalize",
              ),
          ),
          var_absolute_threshold_normalize=dict(
              argstr="-VarThreshN %f %f %f %s",
              extensions=None,
              name_source="in_file",
              suffix="_varthreshn",
              xor=(
                  "absolute_threshold",
                  "var_absolute_threshold",
                  "var_absolute_threshold_normalize",
              ),
          ),
          zmean=dict(
              argstr="-Zmean %s",
              extensions=None,
              name_source="in_file",
              suffix="_zmean",
          ),
      )
      inputs = TCorrMap.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_TCorrMap_inputs() without return types