class_docstr: The problem of fitting the sum of exponentials with linear and
  quadratic degrees to data, [1]_.
  
  Number of variables --- 11, number of residuals --- 65, no bounds.
  
  .. [1] Brett M. Averick et al. "The MINPACK-2 Test Problem Collection",
         p. 27
class_docstr_tok: ["The","problem","of","fitting","the","sum","of","exponentials","with","linear","and","quadratic","degrees","to","data",",","[","1","]","_",".","Number","of","variables","--","-","11",",","number","of","residuals","--","-","65",",","no","bounds",".","..","[","1","]","Brett","M.","Averick","et","al",".","``","The","MINPACK-2","Test","Problem","Collection","''",",","p.","27"]
code: def __init__(self, x0):
      super().__init__(11, 65, 4.013772e-02, x0)
      self.t = np.arange(self.m, dtype=float) * 1e-1
      self.y = np.array(
          [
              1.366,
              1.191,
              1.112,
              1.013,
              9.91e-1,
              8.85e-1,
              8.31e-1,
              8.47e-1,
              7.86e-1,
              7.25e-1,
              7.46e-1,
              6.79e-1,
              6.08e-1,
              6.55e-1,
              6.16e-1,
              6.06e-1,
              6.02e-1,
              6.26e-1,
              6.51e-1,
              7.24e-1,
              6.49e-1,
              6.49e-1,
              6.94e-1,
              6.44e-1,
              6.24e-1,
              6.61e-1,
              6.12e-1,
              5.58e-1,
              5.33e-1,
              4.95e-1,
              5.0e-1,
              4.23e-1,
              3.95e-1,
              3.75e-1,
              3.72e-1,
              3.91e-1,
              3.96e-1,
              4.05e-1,
              4.28e-1,
              4.29e-1,
              5.23e-1,
              5.62e-1,
              6.07e-1,
              6.53e-1,
              6.72e-1,
              7.08e-1,
              6.33e-1,
              6.68e-1,
              6.45e-1,
              6.32e-1,
              5.91e-1,
              5.59e-1,
              5.97e-1,
              6.25e-1,
              7.39e-1,
              7.1e-1,
              7.29e-1,
              7.2e-1,
              6.36e-1,
              5.81e-1,
              4.28e-1,
              2.92e-1,
              1.62e-1,
              9.8e-2,
              5.4e-2,
          ]
      )
  
imports: import inspect
  import sys
  import numpy
  from numpy.polynomial.chebyshev import Chebyshev
  from scipy.integrate import odeint
label_desc: Use image node_id 1 to create a new GaussianFitting object from inherited base classes: LSQBenchmarkProblem with example: obj = GaussianFitting(x0)