class_docstr: Benchmarks using minimize() and least-squares
code: def time_minimize_withnan(self):
      np.random.seed(201)
      x = np.linspace(0, 15, 601)
      x[53] = np.nan
  
      data = 5.0 * np.sin(2 * x - 0.1) * np.exp(
          -x * x * 0.025
      ) + np.random.normal(size=len(x), scale=0.3)
      params = Parameters()
      params.add("amp", value=1, min=0, max=100)
      params.add("decay", value=0.0, min=0, max=10)
      params.add("shift", value=0.0, min=-np.pi / 2.0, max=np.pi / 2)
      params.add("omega", value=1.0, min=0, max=10)
  
      return minimize(
          obj_func, params, args=(x, data), nan_policy="omit"
      )
  
file_path: lmfit-py/asv_benchmarking/benchmarks/benchmarks.py
imports: from copy import deepcopy
  import numpy
  from lmfit import Minimizer, Parameters, conf_interval, minimize
label_desc: Use image node_id 3 for calling the MinimizeSuite obj's underlying member method code with example usage: obj.time_minimize_withnan() and returns: minimize