code: def test_confidence_sigma_vs_prob(data, pars):
      """Calculate confidence by specifying sigma or probability."""
      minimizer = lmfit.Minimizer(residual, pars, fcn_args=(data))
      out = minimizer.leastsq()
  
      ci_sigma_None = lmfit.conf_interval(minimizer, out, sigmas=None)
      ci_sigmas = lmfit.conf_interval(minimizer, out, sigmas=[1, 2, 3])
      ci_1sigma = lmfit.conf_interval(minimizer, out, sigmas=[1])
      ci_probs = lmfit.conf_interval(
          minimizer, out, sigmas=[0.68269, 0.9545, 0.9973]
      )
  
      assert ci_sigma_None == ci_sigmas
      assert_allclose(
          ci_sigmas["a"][0][1], ci_probs["a"][0][1], rtol=0.01
      )
      assert_allclose(
          ci_sigmas["b"][2][1], ci_probs["b"][2][1], rtol=0.01
      )
      assert len(ci_1sigma["a"]) == 3
      assert len(ci_probs["a"]) == 7
  
imports: import copy
  import numpy
  from numpy.testing import assert_allclose
  import pytest
  from scipy.stats import f
  import lmfit
label_desc: Use image node_id 9 for calling a global function with example usage: test_confidence_sigma_vs_prob(data, pars) without return types