code: def fitresult():
      """Return a ModelResult after fitting a randomized Gaussian data set."""
      x = np.linspace(0, 12, 601)
      data = gaussian(x, amplitude=36.4, center=6.70, sigma=0.88)
      data = data + np.random.normal(x.size, scale=3.2)
  
      model = GaussianModel()
      params = model.make_params(amplitude=50, center=5, sigma=2)
  
      params["amplitude"].min = 1
      params["amplitude"].max = 100.0
      params["sigma"].min = 0
      params["sigma"].brute_step = 0.001
  
      result = model.fit(data, params, x=x)
      return result
  
imports: import numpy
  import pytest
  import lmfit
  from lmfit import Minimizer, Parameters, ci_report, conf_interval, fit_report, report_ci, report_fit
  from lmfit.lineshapes import gaussian
  from lmfit.models import GaussianModel
  from lmfit.printfuncs import alphanumeric_sort, correl_table, fitreport_html_table, getfloat_attr, gformat
label_desc: Use image node_id 2 for calling a global function with example usage: fitresult() and returns: result