code: def test_height_and_fwhm_expression_evalution_in_builtin_models():
      """Assert models do not throw an ZeroDivisionError."""
      mod = models.GaussianModel()
      params = mod.make_params(amplitude=1.0, center=0.0, sigma=0.9)
      params.update_constraints()
  
      mod = models.LorentzianModel()
      params = mod.make_params(amplitude=1.0, center=0.0, sigma=0.9)
      params.update_constraints()
  
      mod = models.SplitLorentzianModel()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, sigma_r=1.0
      )
      params.update_constraints()
  
      mod = models.VoigtModel()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, gamma=1.0
      )
      params.update_constraints()
  
      mod = models.PseudoVoigtModel()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, fraction=0.5
      )
      params.update_constraints()
  
      mod = models.MoffatModel()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, beta=0.0
      )
      params.update_constraints()
  
      mod = models.Pearson4Model()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, expon=1.0, skew=5.0
      )
      params.update_constraints()
  
      mod = models.Pearson7Model()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, expon=1.0
      )
      params.update_constraints()
  
      mod = models.StudentsTModel()
      params = mod.make_params(amplitude=1.0, center=0.0, sigma=0.9)
      params.update_constraints()
  
      mod = models.BreitWignerModel()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, q=0.0
      )
      params.update_constraints()
  
      mod = models.LognormalModel()
      params = mod.make_params(amplitude=1.0, center=0.0, sigma=0.9)
      params.update_constraints()
  
      mod = models.DampedOscillatorModel()
      params = mod.make_params(amplitude=1.0, center=0.0, sigma=0.9)
      params.update_constraints()
  
      mod = models.DampedHarmonicOscillatorModel()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, gamma=0.0
      )
      params.update_constraints()
  
      mod = models.ExponentialGaussianModel()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, gamma=0.0
      )
      params.update_constraints()
  
      mod = models.SkewedGaussianModel()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, gamma=0.0
      )
      params.update_constraints()
  
      mod = models.SkewedVoigtModel()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, gamma=0.0, skew=0.0
      )
      params.update_constraints()
  
      mod = models.DoniachModel()
      params = mod.make_params(
          amplitude=1.0, center=0.0, sigma=0.9, gamma=0.0
      )
      params.update_constraints()
  
      mod = models.StepModel()
      for f in ("linear", "arctan", "erf", "logistic"):
          params = mod.make_params(
              amplitude=1.0, center=0.0, sigma=0.9, form=f
          )
          params.update_constraints()
  
      mod = models.RectangleModel()
      for f in ("linear", "arctan", "erf", "logistic"):
          params = mod.make_params(
              amplitude=1.0,
              center1=0.0,
              sigma1=0.0,
              center2=0.0,
              sigma2=0.0,
              form=f,
          )
          params.update_constraints()
  
      mod = models.Gaussian2dModel()
      params = mod.make_params(
          amplitude=1.0,
          centerx=0.0,
          sigmax=0.9,
          centery=0.0,
          sigmay=0.9,
      )
      params.update_constraints()
  
file_path: lmfit-py/tests/test_builtin_models.py
imports: import inspect
  import numpy
  from numpy.testing import assert_allclose
  import pytest
  from scipy.optimize import fsolve
  from lmfit import lineshapes, models
  from lmfit.models import GaussianModel
label_desc: Use image node_id 3 for calling a global function with example usage: test_height_and_fwhm_expression_evalution_in_builtin_models() without return types