TypeError: ne peut pas calculer la valeur d'un tableau de paramètres

Question

J'ai créé un modèle abstrait simple et je voulais pré-résoudre it.Here est mon modèle jusqu'à présent:

from __future__ import division 

from pyomo.environ import * 
from pyomo.opt import SolverFactory 

model=AbstractModel() 

opt=SolverFactory('ipopt') 

#Sets 
model.i=Set(initialize=['conv','effic','hybrid','elec'],ordered=True,doc='car types') 
model.iter=RangeSet(0,1000) 
model.ir=Set(within=model.iter,ordered=True) 
model.j=Set(initialize=model.i) 

#Parameter initialize 

def lamda_init(model): 
    return model.lamdalo 

def mu_init(model): 
    return model.mulo 

def shares_init(model,i): 
    return model.base[i] 

def cost_init(model,i): 
    return model.pr[i]+ model.lamda*model.em[i]+ model.mu(1-model.type[i]) 

#Parameters 
model.pr=Param(model.i,initialize= {'conv':12,'effic':15,'hybrid':25,'elec':45},mutable=True,doc='levelized cost of  car EUR per 100km') 
model.base=Param(model.i,initialize= {'conv':0.80,'effic':0.07,'hybrid':0.10,'elec':0.03},mutable=True,doc='shares of car types in base year') 
model.em=Param(model.i,initialize={'conv':10,'effic':5,'hybrid':1,'elec':0},mutable=True,doc='emissions kgCO2 per 100km') 
model.type=Param(model.i,initialize={'conv':0,'effic':0,'hybrid':0,'elec':1},mutable=True,doc='compliance with promoted car type') 
model.gamma=Param(initialize=-2.5,mutable=True,doc='exponent of discrete choice') 
model.lamdalo=Param(initialize=0,mutable=True,doc='min dual value of emission constraint measured as additional cost') 
model.lamda=Param(initialize=lamda_init,mutable=True,doc='dual value of emission constraint measured as additional cost') 
model.lamdaup=Param(initialize=1000,mutable=True,doc='max dual value of emission constraint measured as additional cost') 
model.mulo=Param(initialize=0,mutable=True,doc='dual value of desired car type measured as additional cost') 
model.mu=Param(initialize=mu_init,mutable=True,doc='dual value of desired car type measured as additional cost') 
model.muup=Param(initialize=1000,mutable=True,doc='dual value of desired car type measured as additional cost') 
model.CO2goal=Param(initialize=0.9,mutable=True,doc='target of emissions') 
model.cargoal=Param(initialize=0.50,mutable=True,doc='target of share of promoted car type') 
model.CO2perf=Param(mutable=True,doc='performance for emissions') 
model.carperf=Param(mutable=True,doc='performance in terms of share of promoted car type') 
model.count=Param(mutable=True,doc='counter of model runs -iterations') 
model.count1=Param(mutable=True) 
model.count2=Param(mutable=True) 
model.conv=Param(mutable=True,doc='convergence criterion') 
model.tolerance=Param(initialize=10**-3,mutable=True,doc='tolerance of convergence') 
model.maxiter=Param(initialize=200,mutable=True) 
model.report=dict() 

#Variables 
model.shares=Var(model.i,initialize=shares_init,within=NonNegativeReals,doc='shares of technologies') 
model.cost=Var(model.i,initialize=cost_init,within=NonNegativeReals,doc='generalized unit cost') 


def eqobj_rule(model): 
    return 0 
model.obj=Objective(rule=eqobj_rule,doc='dummy objective') 

def eq1_rule(model,i): 
    return model.shares[i]==model.base[i]*model.cost[i]**model.gamma/sum(model.base[j]*model.cost[j]**model.gamma for j in model.j) 

model.eq1=Constraint(model.i,rule=eq1_rule) 

def eq2_rule(model,i): 
    return model.cost[i]==model.pr[i]+model.lamda*model.em[i]+model.mu*(1-model.type[i]) 
model.eq2=Constraint(model.i,rule=eq2_rule) 

model.count=0 
model.conv=1000 
instance=model.create_instance() 

for i in instance.iter: 
    if i==instance.count: 
     instance.ir.add(i) 
    else: 
     pass 

results= opt.solve(instance) 

Mais quand je le lance la erreur suivante se produit:

TypeError         Traceback (most recent call last) 
<ipython-input-92-5dc9cea3a41f> in <module>() 
    75 display(instance) 
    76 
---> 77 results= opt.solve(instance) 
    78 
    79 def twocarpolicies_sub(model): 

C:\Users\irini\Anaconda2\lib\site-packages\pyomo\opt\base\solvers.pyc in  solve(self, *args, **kwds) 
    579    initial_time = time.time() 
    580 
--> 581    self._presolve(*args, **kwds) 
    582 
    583    presolve_completion_time = time.time() 

C:\Users\irini\Anaconda2\lib\site-  packages\pyomo\solvers\plugins\solvers\ASL.pyc in _presolve(self, *args, **kwds) 
    176    self._instance = args[0] 
    177    xfrm = TransformationFactory('mpec.nl') 
--> 178    xfrm.apply_to(self._instance) 
    179    if  len(self._instance._transformation_data['mpec.nl'].compl_cuids) == 0: 
    180     # There were no complementarity conditions 

C:\Users\irini\Anaconda2\lib\site-packages\pyomo\core\base\plugin.pyc in apply_to(self, model, **kwds) 
    328   if not hasattr(model, '_transformation_data'): 
    329    model._transformation_data = TransformationData() 
--> 330   self._apply_to(model, **kwds) 
    331 
    332  def create_using(self, model, **kwds): 

C:\Users\irini\Anaconda2\lib\site-packages\pyomo\mpec\plugins\mpec4.pyc in  _apply_to(self, instance, **kwds) 
    42   free_vars = {} 
    43   id_list = [] 
---> 44   for vdata in instance.component_data_objects(Var,  active=True, sort=SortComponents.deterministic): 
    45    id_list.append(id(vdata)) 
    46    free_vars[id(vdata)] = vdata 

C:\Users\irini\Anaconda2\lib\site-packages\pyomo\core\base\block.pyc in  component_data_objects(self, ctype, active, sort, descend_into, descent_order) 
    1198     sort=sort, 
    1199     descend_into=descend_into, 
-> 1200     descent_order=descent_order) 
    1201   else: 
    1202    block_generator = (self,) 

C:\Users\irini\Anaconda2\lib\site-packages\pyomo\core\base\block.pyc in block_data_objects(self, active, sort, descend_into, descent_order) 
    1269         active=active, 
    1270         sort=sort, 
-> 1271         traversal=descent_order) 
    1272 
    1273  def _tree_iterator(self, 

C:\Users\irini\Anaconda2\lib\site-packages\pyomo\core\base\block.pyc in _tree_iterator(self, ctype, active, sort, traversal) 
    1289   if active is not None and self.active != active: 
    1290    return().__iter__() 
-> 1291   if self.parent_component().type() not in ctype: 
    1292    return().__iter__() 
    1293 

C:\Users\irini\Anaconda2\lib\site-packages\pyomo\core\base\param.pyc in __call__(self, exception) 
    927   if exception: 
    928   msg = 'Cannot compute the value of an array of parameters' 
--> 929   raise TypeError(msg) 
    930 
    931 register_component(Param, "Parameter data that is used to define a model instance.") 

TypeError: Cannot compute the value of an array of parameters 

Je ne sais pas dans quelle partie du modèle il se réfère. Est-ce que quelqu'un sait pourquoi?

Answer 1

Ceci est un subtil: type s'avère être une méthode standard sur tous les composants Pyomo (y compris AbstractModel). Lorsque vous déclarez une type Param:

model.type=Param(model.i,initialize={'conv':0,'effic':0,'hybrid':0,'elec':1},mutable=True,doc='compliance with promoted car type') 

vous remplacez implicitement cette méthode avec votre Param. Cela provoque à son tour des problèmes lorsque le code suivant utilise le modèle, en supposant que toutes les méthodes normales existent.

La solution est de ne pas déclarer un composant de modèle type.

Pour être complet, la liste actuelle des méthodes définies pour le modèle (ou bloc) que vous devez éviter impérieuses sont:

['PseudoMap', '_DEFAULT_INDEX_CHECKING_ENABLED', '__class__', '__contains__', '__deepcopy__', 
'__delattr__', '__dict__', '__doc__', '__format__', '__getattribute__', '__getitem__', 
'__getstate__', '__hash__', '__init__', '__iter__', '__len__', '__module__', '__new__', 
'__pickle_slots__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__setstate__', 
'__sizeof__', '__slots__', '__str__', '__subclasshook__', '__weakref__', '_active', 
'_add_temporary_set', '_bfs_iterator', '_component', '_component_data_iter', 
'_component_typemap', '_construct_temporary_set', '_constructed', '_ctypes', '_data', 
'_decl', '_decl_order', '_default', '_flag_vars_as_stale', '_implicit_subsets', '_index', 
'_initialize_component', '_load_model_data', '_name', '_options', '_parent', 
'_postfix_dfs_iterator', '_pprint', '_prefix_dfs_iterator', '_processUnhashableIndex', 
'_rule', '_suppress_ctypes', '_tree_iterator', '_tuplize', '_type', 'activate', 'active', 
'active_blocks', 'active_component_data', 'active_components', 'add_component', 'all_blocks', 
'all_component_data', 'all_components', 'block_data_objects', 'clear', 'clear_suffix_value', 
'clone', 'cname', 'collect_ctypes', 'component', 'component_data_iterindex', 
'component_data_objects', 'component_map', 'component_objects', 'compute_statistics', 
'config', 'construct', 'contains_component', 'create', 'create_instance', 'deactivate', 
'del_component', 'dim', 'display', 'doc', 'find_component', 'fix_all_vars', 
'get_suffix_value', 'getname', 'id_index_map', 'index', 'index_set', 'is_constructed', 
'is_indexed', 'items', 'iteritems', 'iterkeys', 'itervalues', 'keys', 'load', 'local_name', 
'model', 'name', 'nconstraints', 'nobjectives', 'nvariables', 'parent_block', 
'parent_component', 'pprint', 'preprocess', 'preprocessor_ep', 'reclassify_component_type', 
'reconstruct', 'root_block', 'set_suffix_value', 'set_value', 'solutions', 'statistics', 
'to_dense_data', 'to_string', 'transform', 'type', 'unfix_all_vars', 'valid_model_component', 
'valid_problem_types', 'values', 'write']