def load(self, arg, namespaces=[None], profile_memory=0, report_timing=None):
"""
Load the model with data from a file, dictionary or DataPortal object.
"""
if report_timing is not None:
deprecation_warning(
"The report_timing argument to Model.load() is deprecated. "
"Use pyomo.common.timing.report_timing() to enable reporting "
"construction timing")
if arg is None or isinstance(arg, str):
dp = DataPortal(filename=arg, model=self)
elif type(arg) is DataPortal:
dp = arg
elif type(arg) is dict:
dp = DataPortal(data_dict=arg, model=self)
elif isinstance(arg, SolverResults):
if len(arg.solution):
deprecation_warning(
"The Model.load() method is deprecated for loading "
"solutions stored in SolverResults objects. Call"
"Model.solutions.load_from().", version='4.3.11323')
self.solutions.load_from(arg)
else:
deprecation_warning(
"The Model.load() method is deprecated for loading "
"solutions stored in SolverResults objects. By default, "
"results from solvers are immediately loaded into "
"the original model instance.", version='4.3.11323')
return
else:
msg = "Cannot load model model data from with object of type '%s'"
raise ValueError(msg % str( type(arg) ))
self._load_model_data(dp,
namespaces,
profile_memory=profile_memory)
def load(self, arg, namespaces=[None], profile_memory=0):
"""
Load the model with data from a file, dictionary or DataPortal object.
"""
if arg is None or isinstance(arg, str):
dp = DataPortal(filename=arg, model=self)
elif type(arg) is DataPortal:
dp = arg
elif type(arg) is dict:
dp = DataPortal(data_dict=arg, model=self)
else:
msg = "Cannot load model model data from with object of type '%s'"
raise ValueError(msg % str(type(arg)))
self._load_model_data(dp, namespaces, profile_memory=profile_memory)
Created on Thu Dec 19 16:12:21 2019 @author: Silvia """ from __future__ import division from pyomo.opt import SolverFactory from pyomo.core import AbstractModel from pyomo.dataportal.DataPortal import DataPortal from pyomo.environ import * import pandas as pd from datetime import datetime ############ Create abstract model ########### model = AbstractModel() data = DataPortal() # ####################Define sets##################### #Name of all the nodes (primary and secondary substations) model.N = Set() data.load(filename='nodes.csv', set=model.N) #first row is not read #Allowed connections model.links = Set(dimen=2) #in the csv the values must be delimited by commas data.load(filename='links.csv', set=model.links) #Nodes are divided into two sets, as suggested in https://pyomo.readthedocs.io/en/stable/pyomo_modeling_components/Sets.html: # NodesOut[nodes] gives for each node all nodes that are connected to it via outgoing links # NodesIn[nodes] gives for each node all nodes that are connected to it via ingoing links