Scenario Creation

In addition to model-based parameter estimation, parmest can create scenarios for use in optimization under uncertainty. To do this, one first creates an Estimator object, then a ScenarioCreator object, which has methods to add ParmestScen scenario objects to a ScenarioSet object, which can write them to a csv file or output them via an iterator method.

This example is in the semibatch subdirectory of the examples directory in the file It creates a csv file with scenarios that correspond one-to-one with the experiments used as input data. It also creates a few scenarios using the bootstrap methods and outputs prints the scenarios to the screen, accessing them via the ScensItator a print

#  ___________________________________________________________________________
#  Pyomo: Python Optimization Modeling Objects
#  Copyright (c) 2008-2022
#  National Technology and Engineering Solutions of Sandia, LLC
#  Under the terms of Contract DE-NA0003525 with National Technology and
#  Engineering Solutions of Sandia, LLC, the U.S. Government retains certain
#  rights in this software.
#  This software is distributed under the 3-clause BSD License.
#  ___________________________________________________________________________

import json
from os.path import join, abspath, dirname
import pyomo.contrib.parmest.parmest as parmest
from pyomo.contrib.parmest.examples.semibatch.semibatch import generate_model
import pyomo.contrib.parmest.scenariocreator as sc

def main():
    # Vars to estimate in parmest
    theta_names = ['k1', 'k2', 'E1', 'E2']

    # Data: list of dictionaries
    data = [] 
    file_dirname = dirname(abspath(str(__file__)))
    for exp_num in range(10):
        fname = join(file_dirname, 'exp'+str(exp_num+1)+'.out')
        with open(fname,'r') as infile:
            d = json.load(infile)

    pest = parmest.Estimator(generate_model, data, theta_names)

    scenmaker = sc.ScenarioCreator(pest, "ipopt")

    # Make one scenario per experiment and write to a csv file
    output_file = "scenarios.csv"
    experimentscens = sc.ScenarioSet("Experiments")
    # Use the bootstrap to make 3 scenarios and print
    bootscens = sc.ScenarioSet("Bootstrap")
    scenmaker.ScenariosFromBoostrap(bootscens, 3)
    for s in bootscens.ScensIterator():
        print("{}, {}".format(, s.probability))
        for n,v in s.ThetaVals.items():
            print("   {}={}".format(n, v))

if __name__ == "__main__":


This example may produce an error message your version of Ipopt is not based on a good linear solver.