code: def testSplineModel():
      x = np.linspace(0, 25, 501)
      y = (
          gaussian(x, amplitude=10, center=16.2, sigma=0.8)
          + 3
          + 0.03 * x
          + np.sin(x / 4)
      )
  
      model = GaussianModel(prefix="peak_")
      params = model.make_params(amplitude=8, center=16, sigma=1)
  
      knot_xvals = np.array([1, 3, 5, 7, 9, 11, 13, 19, 21, 23, 25])
  
      bkg = SplineModel(prefix="bkg_", xknots=knot_xvals)
      params.update(bkg.guess(y, x))
  
      model = model + bkg
  
      pars = dict(peak_amplitude=10, peak_center=16.2, peak_sigma=0.8)
      check_fit(model, params, x, y, pars, noise_scale=0.05)
  
file_path: lmfit-py/tests/test_models.py
imports: import numpy
  import lmfit
  from lmfit.lineshapes import gaussian
  from lmfit.models import GaussianModel, SplineModel
label_desc: Use image node_id 10 for calling a global function with example usage: testSplineModel() without return types