code: from petabtests import *
  from petab.C import *
  import petab
  
  import pandas as pd
  
  
  test_id = 15
  
  # problem --------------------------------------------------------------------
  
  model = DEFAULT_SBML_FILE
  
  condition_df = pd.DataFrame(data={
      CONDITION_ID: ['c0'],
  }).set_index([CONDITION_ID])
  
  measurement_df = pd.DataFrame(data={
      OBSERVABLE_ID: ['obs_a', 'obs_a'],
      SIMULATION_CONDITION_ID: ['c0', 'c0'],
      TIME: [0, 10],
      MEASUREMENT: [0.7, 0.1],
      NOISE_PARAMETERS: ['noise', 'noise']
  })
  
  observable_df = pd.DataFrame(data={
      OBSERVABLE_ID: ['obs_a'],
      OBSERVABLE_FORMULA: ['A'],
      NOISE_FORMULA: ['noiseParameter1_obs_a']
  }).set_index([OBSERVABLE_ID])
  
  parameter_df = pd.DataFrame(data={
      PARAMETER_ID: ['a0', 'b0', 'k1', 'k2', 'noise'],
      PARAMETER_SCALE: [LIN] * 5,
      LOWER_BOUND: [0] * 5,
      UPPER_BOUND: [10] * 5,
      NOMINAL_VALUE: [1, 0, 0.8, 0.6, 5],
      ESTIMATE: [1] * 5,
  }).set_index(PARAMETER_ID)
  
  
  # solutions ------------------------------------------------------------------
  
  simulation_df = measurement_df.copy(deep=True).rename(
      columns={MEASUREMENT: SIMULATION})
  simulation_df[SIMULATION] = [analytical_a(t, 1, 0, 0.8, 0.6)
                               for t in simulation_df[TIME]]
  
  chi2 = petab.calculate_chi2(
      measurement_df, simulation_df, observable_df, parameter_df)
  
  llh = petab.calculate_llh(
      measurement_df, simulation_df, observable_df, parameter_df)
  print(llh)
  
apis: pandas.DataFrame