def temoa_setup(self):
"""This function prepares the model to be solved.
Inputs:
model -- the model object
config_filename -- config filename, non-blank if called from the UI
There are three possible ways to call the model:
1. python temoa_model/ /path/to/data_files
2. python temoa_model/ --config=/path/to/config/file
3. function call from the UI
This function discerns which way the model was called and process the
inputs accordingly.
"""
if self.config_filename == '': # Called from the command line
self.options, config_flag = parse_args()
if config_flag == 1: # Option 2 (using config file)
self.options.path_to_lp_files = self.options.path_to_logs + sep + "lp_files"
TempfileManager.tempdir = self.options.path_to_lp_files
else: # Must be Option 1 (no config file)
pass
else: # Config file already specified, so must be an interface call
available_solvers, default_solver = get_solvers()
temoa_config = TemoaConfig(d_solver=default_solver)
temoa_config.build(config=self.config_filename)
self.options = temoa_config
self.temp_lp_dest = '/srv/thirdparty/temoa/data_files/'
self.options.path_to_lp_files = self.options.path_to_logs + sep + "lp_files"
TempfileManager.tempdir = self.options.path_to_lp_files
def parse_args():
"""Parse arguments specfied from command line or in config file."""
import argparse, sys
import os, re
from os.path import dirname, abspath
available_solvers, default_solver = get_solvers()
parser = argparse.ArgumentParser()
parser.prog = path.basename(argv[0].strip('/'))
parser.add_argument(
'dot_dat',
type=str,
nargs='*',
help='AMPL-format data file(s) with which to create a model instance. '
'e.g. "data.dat"')
parser.add_argument(
'--path_to_logs',
help=
'Path to where debug logs will be generated by default. See folder debug_logs in data_files.',
action='store',
dest='path_to_logs',
default=re.sub('temoa_model$', 'data_files', dirname(
abspath(__file__))) + os.sep + "debug_logs")
parser.add_argument(
'--config',
help='Path to file containing configuration information.',
action='store',
dest='config',
default=None)
parser.add_argument(
'--solver',
help=
"Which backend solver to use. See 'pyomo --help-solvers' for a list "
'of solvers with which Pyomo can interface. The list shown here is '
'what Pyomo can currently find on this system. [Default: {}]'.format(
default_solver),
action='store',
choices=sorted(available_solvers),
dest='solver',
default=default_solver)
options = parser.parse_args()
options.neos = False
# Can't specify keeping the LP file without config file, so set this
# attribute to false
options.keepPyomoLP = False
# If the user specifies the config flag, then call TemoaConfig and overwrite
# the argument parser above.
if options.config:
config_flag = 1 #flag indicates config file was used.
try:
temoa_config = TemoaConfig(d_solver=default_solver)
temoa_config.build(config=options.config)
SE.write(repr(temoa_config))
options = temoa_config
SE.write('\nPlease press enter to continue or Ctrl+C to quit.\n')
#raw_input() # Give the user a chance to confirm input
if options.abort_temoa:
return
except KeyboardInterrupt:
SE.write('\n\nUser requested quit. Exiting Temoa ...\n')
raise SystemExit()
else:
config_flag = 0 #flag indicates config file was not used.
s_choice = str(options.solver).upper()
SE.write('Notice: Using the {} solver interface.\n'.format(s_choice))
SE.flush()
SE.write(
"Continue Operation? [Press enter to continue or CTRL+C to abort]\n")
SE.flush()
try: #make compatible with Python 2.7 or 3
raw_input() # Give the user a chance to confirm input
except:
input()
return options, config_flag
def solve_ef(p_model, p_data, dummy_temoa_options=None):
"""
solve_ef(p_model, p_data) -> objective value of the extensive form
Solves the model in stochastic mode.
p_model -> string, the path to the model file (ReferenceModel.py).
p_data -> string, the path to the directory of data for the stochastic
mdoel, where ScenarioStructure.dat should resides.
Returns a float point number of the value of objective function for the
stochastic program model.
"""
options = ScenarioTreeManagerClientSerial.register_options()
if os.path.basename(p_model) == 'ReferenceModel.py':
options.model_location = os.path.dirname(p_model)
else:
sys.stderr.write(
'\nModel file should be ReferenceModel.py. Exiting...\n')
sys.exit(1)
options.scenario_tree_location = p_data
# using the 'with' block will automatically call
# manager.close() and gracefully shutdown
with ScenarioTreeManagerClientSerial(options) as manager:
manager.initialize()
ef_instance = create_ef_instance(manager.scenario_tree,
verbose_output=options.verbose)
ef_instance.dual = Suffix(direction=Suffix.IMPORT)
with SolverFactory('cplex') as opt:
ef_result = opt.solve(ef_instance)
# Write to database
if dummy_temoa_options:
sys.path.append(options.model_location)
from pformat_results import pformat_results
from temoa_config import TemoaConfig
temoa_options = TemoaConfig()
temoa_options.config = dummy_temoa_options.config
temoa_options.keepPyomoLP = dummy_temoa_options.keepPyomoLP
temoa_options.saveTEXTFILE = dummy_temoa_options.saveTEXTFILE
temoa_options.path_to_db_io = dummy_temoa_options.path_to_db_io
temoa_options.saveEXCEL = dummy_temoa_options.saveEXCEL
ef_result.solution.Status = 'feasible' # Assume it is feasible
for s in manager.scenario_tree.scenarios:
ins = s._instance
temoa_options.scenario = s.name
temoa_options.dot_dat = [
os.path.join(options.scenario_tree_location,
s.name + '.dat')
]
temoa_options.output = os.path.join(
options.scenario_tree_location, dummy_temoa_options.output)
msg = '\nStoring results from scenario {} to database.\n'.format(
s.name)
sys.stderr.write(msg)
formatted_results = pformat_results(ins, ef_result,
temoa_options)
ef_instance.solutions.store_to(ef_result)
ef_obj = value(ef_instance.EF_EXPECTED_COST.values()[0])
return ef_obj