code: def parameters():
      """Initialize a Parameters class for tests."""
      pars = lmfit.Parameters()
      pars.add(
          lmfit.Parameter(
              name="a",
              value=10.0,
              vary=True,
              min=-100.0,
              max=100.0,
              expr=None,
              brute_step=5.0,
              user_data=1,
          )
      )
      pars.add(
          lmfit.Parameter(
              name="b",
              value=0.0,
              vary=True,
              min=-250.0,
              max=250.0,
              expr="2.0*a",
              brute_step=25.0,
              user_data={"test": 123},
          )
      )
      exp_attr_values_A = ("a", 10.0, True, -100.0, 100.0, None, 5.0, 1)
      exp_attr_values_B = (
          "b",
          20.0,
          False,
          -250.0,
          250.0,
          "2.0*a",
          25.0,
          {"test": 123},
      )
      assert_parameter_attributes(pars["a"], exp_attr_values_A)
      assert_parameter_attributes(pars["b"], exp_attr_values_B)
      return pars, exp_attr_values_A, exp_attr_values_B
  
imports: from copy import copy, deepcopy
  import os
  import pickle
  import numpy
  from numpy.testing import assert_allclose
  import pytest
  import lmfit
  from lmfit.models import VoigtModel
label_desc: Use image node_id 1 for calling a global function with example usage: parameters() and returns: pars,  exp_attr_values_A,  exp_attr_values_B