def runadmm_register_options(options=None):
if options is None:
options = PySPConfigBlock()
ADMMSolver.register_options(options)
ScenarioTreeManagerFactory.register_options(options)
safe_register_common_option(options, "verbose")
safe_register_common_option(options, "disable_gc")
safe_register_common_option(options, "profile")
safe_register_common_option(options, "traceback")
safe_register_common_option(options, "output_solver_log")
safe_register_common_option(options, "output_scenario_tree_solution")
safe_register_unique_option(
options,
"default_rho",
PySPConfigValue(
1.0,
domain=_domain_positive,
description=("The default rho value for all non-anticipative "
"variables. Default is 1.0."),
doc=None,
visibility=0),
ap_args=("-r", "--default-rho"),
ap_group=_admm_group_label)
return options
def runschuripopt_register_options(options=None):
if options is None:
options = PySPConfigBlock()
safe_register_common_option(options, "verbose")
safe_register_common_option(options, "disable_gc")
safe_register_common_option(options, "profile")
safe_register_common_option(options, "traceback")
safe_register_common_option(options, "output_scenario_tree_solution")
safe_register_common_option(options, "output_solver_log")
safe_register_common_option(options, "keep_solver_files")
safe_register_common_option(options, "symbolic_solver_labels")
ScenarioTreeManagerFactory.register_options(options)
SchurIpoptSolver.register_options(options)
# used to populate the implicit SchurIpopt options
safe_register_unique_option(
options,
"solver_options",
PySPConfigValue((),
domain=_domain_tuple_of_str_or_dict,
description=("Solver options to pass to SchurIpopt "
"(e.g., relax_integrality=yes). This "
"option can be used multiple times "
"from the command line to specify more "
"than one SchurIpopt option."),
doc=None,
visibility=0),
ap_kwds={'action': 'append'},
ap_group=_schuripopt_group_label)
return options
def runddsip_register_options(options=None):
if options is None:
options = PySPConfigBlock()
DDSIPSolver.register_options(options)
ScenarioTreeManagerFactory.register_options(options)
safe_register_common_option(options, "verbose")
safe_register_common_option(options, "disable_gc")
safe_register_common_option(options, "profile")
safe_register_common_option(options, "traceback")
safe_register_common_option(options, "output_scenario_tree_solution")
safe_register_common_option(options, "keep_solver_files")
safe_register_common_option(options, "output_solver_log")
safe_register_common_option(options, "symbolic_solver_labels")
# used to populate the implicit DDSIP options
safe_register_unique_option(
options,
"solver_options",
PySPConfigValue(
(),
domain=_domain_tuple_of_str_or_dict,
description=("Unregistered solver options that will be passed "
"to DDSIP via the config file (e.g., NODELIM=4, "
"CPLEX_1067=1). This option can be used multiple "
"times from the command line to specify more "
"than one DDSIP option."),
doc=None,
visibility=0),
ap_kwds={'action': 'append'},
ap_group=_ddsip_group_label)
return options
def runadmm_register_options(options=None):
if options is None:
options = PySPConfigBlock()
ADMMSolver.register_options(options)
ScenarioTreeManagerFactory.register_options(options)
safe_register_common_option(options,
"verbose")
safe_register_common_option(options,
"disable_gc")
safe_register_common_option(options,
"profile")
safe_register_common_option(options,
"traceback")
safe_register_common_option(options,
"output_solver_log")
safe_register_common_option(options,
"output_scenario_tree_solution")
safe_register_unique_option(
options,
"default_rho",
PySPConfigValue(
1.0,
domain=_domain_positive,
description=(
"The default rho value for all non-anticipative "
"variables. Default is 1.0."
),
doc=None,
visibility=0),
ap_args=("-r", "--default-rho"),
ap_group=_admm_group_label)
return options
def runsd_register_options(options=None):
if options is None:
options = PySPConfigBlock()
SDSolver.register_options(options)
ScenarioTreeManagerFactory.register_options(options)
safe_register_common_option(options, "verbose")
safe_register_common_option(options, "disable_gc")
safe_register_common_option(options, "profile")
safe_register_common_option(options, "traceback")
safe_register_common_option(options, "output_scenario_tree_solution")
safe_register_common_option(options, "keep_solver_files")
safe_register_common_option(options, "output_solver_log")
safe_register_common_option(options, "symbolic_solver_labels")
return options
def run_evaluate_xhat_register_options(options=None):
if options is None:
options = PySPConfigBlock()
safe_register_common_option(options,
"disable_gc")
safe_register_common_option(options,
"profile")
safe_register_common_option(options,
"traceback")
safe_register_common_option(options,
"scenario_tree_manager")
safe_register_common_option(options,
"output_scenario_tree_solution")
safe_register_common_option(options,
"solution_saver_extension")
safe_register_common_option(options,
"solution_loader_extension")
safe_register_unique_option(
options,
"disable_solution_loader_check",
PySPConfigValue(
False,
domain=bool,
description=(
"Indicates that no solution loader extension is required to "
"run this script, e.g., because the scenario tree manager "
"is somehow pre-populated with a solution."
),
doc=None,
visibility=0),
ap_group=_extension_options_group_title)
safe_register_unique_option(
options,
"output_scenario_costs",
PySPConfigValue(
None,
domain=_domain_must_be_str,
description=(
"A file name where individual scenario costs from the solution "
"will be stored. The format is determined from the extension used "
"in the filename. Recognized extensions: [.csv, .json, .yaml]"
),
doc=None,
visibility=0))
ScenarioTreeManagerFactory.register_options(options)
ScenarioTreeManagerSolverFactory.register_options(options,
options_prefix="subproblem_")
return options
def runsd(options):
"""
Construct a senario tree manager and solve it
with the SD solver.
"""
start_time = time.time()
with ScenarioTreeManagerFactory(options) as sp:
sp.initialize()
print("")
print("Running SD solver for stochastic " "programming problems")
sd = SDSolver()
sd_options = sd.extract_user_options_to_dict(options, sparse=True)
results = sd.solve(
sp,
options=sd_options,
output_solver_log=options.output_solver_log,
keep_solver_files=options.keep_solver_files,
symbolic_solver_labels=options.symbolic_solver_labels)
xhat = results.xhat
del results.xhat
print("")
print(results)
if options.output_scenario_tree_solution:
print("")
sp.scenario_tree.snapshotSolutionFromScenarios()
sp.scenario_tree.pprintSolution()
sp.scenario_tree.pprintCosts()
print("")
print("Total execution time=%.2f seconds" % (time.time() - start_time))
return 0
def runadmm(options):
"""
Construct a senario tree manager and solve it
with the ADMM solver.
"""
start_time = time.time()
with ScenarioTreeManagerFactory(options) as sp:
sp.initialize()
print("")
print("Running ADMM solver for stochastic " "programming problems")
admm = ADMMSolver()
admm_options = admm.extract_user_options_to_dict(options, sparse=True)
results = admm.solve(sp,
options=admm_options,
rho=options.default_rho,
output_solver_log=options.output_solver_log)
xhat = results.xhat
del results.xhat
print("")
print(results)
if options.output_scenario_tree_solution:
print("Final solution (scenario tree format):")
sp.scenario_tree.snapshotSolutionFromScenarios()
sp.scenario_tree.pprintSolution()
sp.scenario_tree.pprintCosts()
print("")
print("Total execution time=%.2f seconds" % (time.time() - start_time))
return 0
def runschuripopt_register_options(options=None):
if options is None:
options = PySPConfigBlock()
safe_register_common_option(options,
"verbose")
safe_register_common_option(options,
"disable_gc")
safe_register_common_option(options,
"profile")
safe_register_common_option(options,
"traceback")
safe_register_common_option(options,
"output_scenario_tree_solution")
safe_register_common_option(options,
"output_solver_log")
safe_register_common_option(options,
"keep_solver_files")
safe_register_common_option(options,
"symbolic_solver_labels")
ScenarioTreeManagerFactory.register_options(options)
SchurIpoptSolver.register_options(options)
# used to populate the implicit SchurIpopt options
safe_register_unique_option(
options,
"solver_options",
PySPConfigValue(
(),
domain=_domain_tuple_of_str_or_dict,
description=(
"Solver options to pass to SchurIpopt "
"(e.g., relax_integrality=yes). This "
"option can be used multiple times "
"from the command line to specify more "
"than one SchurIpopt option."
),
doc=None,
visibility=0),
ap_kwds={'action': 'append'},
ap_group=_schuripopt_group_label)
return options
def runddsip_register_options(options=None):
if options is None:
options = PySPConfigBlock()
DDSIPSolver.register_options(options)
ScenarioTreeManagerFactory.register_options(options)
safe_register_common_option(options,
"verbose")
safe_register_common_option(options,
"disable_gc")
safe_register_common_option(options,
"profile")
safe_register_common_option(options,
"traceback")
safe_register_common_option(options,
"output_scenario_tree_solution")
safe_register_common_option(options,
"keep_solver_files")
safe_register_common_option(options,
"output_solver_log")
safe_register_common_option(options,
"symbolic_solver_labels")
# used to populate the implicit DDSIP options
safe_register_unique_option(
options,
"solver_options",
PySPConfigValue(
(),
domain=_domain_tuple_of_str_or_dict,
description=(
"Unregistered solver options that will be passed "
"to DDSIP via the config file (e.g., NODELIM=4, "
"CPLEX_1067=1). This option can be used multiple "
"times from the command line to specify more "
"than one DDSIP option."
),
doc=None,
visibility=0),
ap_kwds={'action': 'append'},
ap_group=_ddsip_group_label)
return options
def run_evaluate_xhat_register_options(options=None):
if options is None:
options = PySPConfigBlock()
safe_register_common_option(options, "disable_gc")
safe_register_common_option(options, "profile")
safe_register_common_option(options, "traceback")
safe_register_common_option(options, "scenario_tree_manager")
safe_register_common_option(options, "output_scenario_tree_solution")
safe_register_common_option(options, "solution_saver_extension")
safe_register_common_option(options, "solution_loader_extension")
safe_register_unique_option(
options,
"disable_solution_loader_check",
PySPConfigValue(
False,
domain=bool,
description=(
"Indicates that no solution loader extension is required to "
"run this script, e.g., because the scenario tree manager "
"is somehow pre-populated with a solution."),
doc=None,
visibility=0),
ap_group=_extension_options_group_title)
safe_register_unique_option(
options, "output_scenario_costs",
PySPConfigValue(
None,
domain=_domain_must_be_str,
description=
("A file name where individual scenario costs from the solution "
"will be stored. The format is determined from the extension used "
"in the filename. Recognized extensions: [.csv, .json, .yaml]"),
doc=None,
visibility=0))
ScenarioTreeManagerFactory.register_options(options)
ScenarioTreeManagerSolverFactory.register_options(
options, options_prefix="subproblem_")
return options
def runddsip(options):
"""
Construct a senario tree manager and solve it
with the DDSIP solver.
"""
start_time = time.time()
with ScenarioTreeManagerFactory(options) as sp:
sp.initialize()
print("")
print("Running DDSIP solver for stochastic " "programming problems")
ddsip = DDSIPSolver()
# add the implicit ddsip options
solver_options = options.solver_options
if len(solver_options) > 0:
if type(solver_options) is tuple:
for name_val in solver_options:
assert "=" in name_val
name, val = name_val.split("=")
ddsip.options[name.strip()] = val.strip()
else:
for key, val in solver_options.items():
ddsip.options[key] = val
ddsip_options = ddsip.extract_user_options_to_dict(options,
sparse=True)
results = ddsip.solve(
sp,
options=ddsip_options,
output_solver_log=options.output_solver_log,
keep_solver_files=options.keep_solver_files,
symbolic_solver_labels=options.symbolic_solver_labels)
xhat = results.xhat
del results.xhat
print("")
print(results)
if options.output_scenario_tree_solution:
print("")
sp.scenario_tree.snapshotSolutionFromScenarios()
sp.scenario_tree.pprintSolution()
sp.scenario_tree.pprintCosts()
print("")
print("Total execution time=%.2f seconds" % (time.time() - start_time))
return 0
def runschuripopt(options):
"""
Construct a senario tree manager and solve it
with the SD solver.
"""
start_time = time.time()
with ScenarioTreeManagerFactory(options) as manager:
manager.initialize()
print("")
print("Running SchurIpopt solver for stochastic "
"programming problems")
schuripopt = SchurIpoptSolver()
# add the implicit schuripopt options
solver_options = options.solver_options
if len(solver_options) > 0:
if type(solver_options) is tuple:
for name_val in solver_options:
assert "=" in name_val
name, val = name_val.split("=")
schuripopt.options[name.strip()] = val.strip()
else:
for key, val in solver_options.items():
schuripopt.options[key] = val
results = schuripopt.solve(
manager,
output_solver_log=options.output_solver_log,
keep_solver_files=options.keep_solver_files,
symbolic_solver_labels=options.symbolic_solver_labels)
xhat = results.xhat
del results.xhat
print("")
print(results)
if options.output_scenario_tree_solution:
print("Final solution (scenario tree format):")
manager.scenario_tree.snapshotSolutionFromScenarios()
manager.scenario_tree.pprintSolution()
print("")
print("Total execution time=%.2f seconds" % (time.time() - start_time))
return 0
import matplotlib.pylab as plt
from pyomo.pysp.scenariotree.manager import \
ScenarioTreeManagerFactory
from pyomo.pysp.scenariotree.instance_factory import \
ScenarioTreeInstanceFactory
from gas_network_model import (pysp_instance_creation_callback,
nx_scenario_tree)
from pyomo.pysp.ef import create_ef_instance
# define and initialize the SP
instance_factory = ScenarioTreeInstanceFactory(pysp_instance_creation_callback,
nx_scenario_tree)
options = ScenarioTreeManagerFactory.register_options()
options.scenario_tree_manager = 'serial'
sp = ScenarioTreeManagerFactory(options, factory=instance_factory)
sp.initialize()
instance = create_ef_instance(sp.scenario_tree)
#instance = create_model(1.0)
print("\nHi this is PyNumero")
nlp = PyomoNLP(instance)
print("\n----------------------")
print("Problem statistics:")
print("----------------------")
print("Number of variables: {:>25d}".format(nlp.nx))
print("Number of equality constraints: {:>14d}".format(nlp.nc))
print("Number of inequality constraints: {:>11d}".format(nlp.nd))
ScenarioTreeManagerFactory from pyomo.pysp.solvers.benders import BendersAlgorithm # *** How to run this example using Pyro ***: # # To run this example using Pyro, launch the following # command in another terminal: # $ mpirun -np 1 pyomo_ns -r -n localhost : \ # -np 1 dispatch_srvr -n localhost : \ # -np 3 scenariotreeserver --pyro-host=localhost --traceback # # In this shell launch: # $ python benders_scripting.py # with sp_options.scenario_tree_manager = "pyro" sp_options = ScenarioTreeManagerFactory.register_options() # To see detailed information about options #for name in sp_options.keys(): # print(sp_options.about(name)) # To see a more compact display of options #sp_options.display() # # General options for the scenario tree manager # sp_options.scenario_tree_manager = "serial" # using absolute paths so we can automate testing # of this example examplesdir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
ScenarioTreeManagerFactory from pyomo.pysp.solvers.benders import BendersAlgorithm # *** How to run this example using Pyro ***: # # To run this example using Pyro, launch the following # command in another terminal: # $ mpirun -np 1 pyomo_ns -r -n localhost : \ # -np 1 dispatch_srvr -n localhost : \ # -np 3 scenariotreeserver --pyro-host=localhost --traceback # # In this shell launch: # $ python benders_scripting.py # with sp_options.scenario_tree_manager = "pyro" sp_options = ScenarioTreeManagerFactory.register_options() # To see detailed information about options #for name in sp_options.keys(): # print(sp_options.about(name)) # To see a more compact display of options #sp_options.display() # # General options for the scenario tree manager # sp_options.scenario_tree_manager = "serial" # using absolute paths so we can automate testing # of this example examplesdir = os.path.dirname(
def run_evaluate_xhat(options, solution_loaders=(), solution_savers=()):
import pyomo.environ
start_time = time.time()
solution_loaders = sort_extensions_by_precedence(solution_loaders)
solution_savers = sort_extensions_by_precedence(solution_savers)
with ScenarioTreeManagerFactory(options) as sp:
sp.initialize()
loaded = False
for plugin in solution_loaders:
ret = plugin.load(sp)
if not ret:
print("WARNING: Loader extension %s call did not return True. "
"This might indicate failure to load data." % (plugin))
else:
loaded = True
if (not loaded) and (not options.disable_solution_loader_check):
raise RuntimeError(
"Either no solution loader extensions were provided or "
"all solution loader extensions reported a bad return value. "
"To disable this check use the disable_solution_loader_check "
"option flag.")
with ScenarioTreeManagerSolverFactory(
sp, options, options_prefix="subproblem_") as sp_solver:
evaluate_current_node_solution(sp, sp_solver)
objective = sum(scenario.probability * \
scenario.get_current_objective()
for scenario in sp.scenario_tree.scenarios)
sp.scenario_tree.snapshotSolutionFromScenarios()
print("")
print("***********************************************"
"************************************************")
print(">>>THE EXPECTED SUM OF THE STAGE COST VARIABLES="
+str(sp.scenario_tree.findRootNode().\
computeExpectedNodeCost())+"<<<")
print("***********************************************"
"************************************************")
# handle output of solution from the scenario tree.
print("")
print("Extensive form solution:")
sp.scenario_tree.pprintSolution()
print("")
print("Extensive form costs:")
sp.scenario_tree.pprintCosts()
if options.output_scenario_tree_solution:
print("Final solution (scenario tree format):")
sp.scenario_tree.pprintSolution()
if options.output_scenario_costs is not None:
if options.output_scenario_costs.endswith('.json'):
import json
result = {}
for scenario in sp.scenario_tree.scenarios:
result[str(scenario.name)] = scenario._cost
with open(options.output_scenario_costs, 'w') as f:
json.dump(result, f, indent=2, sort_keys=True)
elif options.output_scenario_costs.endswith('.yaml'):
import yaml
result = {}
for scenario in sp.scenario_tree.scenarios:
result[str(scenario.name)] = scenario._cost
with open(options.output_scenario_costs, 'w') as f:
yaml.dump(result, f)
else:
if not options.output_scenario_costs.endswith('.csv'):
print("Unrecognized file extension. Using CSV format "
"to store scenario costs")
with open(options.output_scenario_costs, 'w') as f:
for scenario in sp.scenario_tree.scenarios:
f.write("%s,%r\n" % (scenario.name, scenario._cost))
for plugin in solution_savers:
if not plugin.save(sp):
print("WARNING: Saver extension %s call did not return True. "
"This might indicate failure to save data." % (plugin))
print("")
print("Total execution time=%.2f seconds" % (time.time() - start_time))
return 0
from pyomo.pysp.scenariotree.manager import \
ScenarioTreeManagerFactory
from pyomo.pysp.scenariotree.instance_factory import \
ScenarioTreeInstanceFactory
from gas_network_model import (pysp_instance_creation_callback,
nx_scenario_tree)
from pyomo.pysp.ef import create_ef_instance
# define and initialize the SP
instance_factory = ScenarioTreeInstanceFactory(
pysp_instance_creation_callback,
nx_scenario_tree)
options = ScenarioTreeManagerFactory.register_options()
options.scenario_tree_manager = 'serial'
sp = ScenarioTreeManagerFactory(options,
factory=instance_factory)
sp.initialize()
instance = create_ef_instance(sp.scenario_tree)
#instance = create_model(1.0)
print("\nHi this is PyNumero")
nlp = PyomoNLP(instance)
print("\n----------------------")
print("Problem statistics:")
print("----------------------")
print("Number of variables: {:>25d}".format(nlp.nx))
print("Number of equality constraints: {:>14d}".format(nlp.nc))
