def test_singletonblock_noindextemplate(self):
st_model = CreateConcreteTwoStageScenarioTreeModel(1)
st_model.StageVariables['Stage1'].add("b1")
st_model.StageDerivedVariables['Stage1'].add("b2")
st_model.NodeVariables['RootNode'].add("b3")
st_model.NodeDerivedVariables['RootNode'].add("b4")
st_model.StageCost['Stage1'] = "FirstStageCost"
st_model.StageCost['Stage2'] = "SecondStageCost"
scenario_tree = ScenarioTree(scenariotreeinstance=st_model)
self.assertEqual(len(scenario_tree.stages), 2)
self.assertEqual(len(scenario_tree.nodes), 2)
self.assertEqual(len(scenario_tree.scenarios), 1)
model = self._get_block_model()
scenario_tree.linkInInstances({'Scenario1': model})
root = scenario_tree.findRootNode()
self.assertEqual(len(root._variable_ids), 12)
self.assertEqual(len(root._standard_variable_ids), 6)
self.assertEqual(len(root._derived_variable_ids), 6)
for name in ("b1.x", "b2.x", "b3.x", "b4.x"):
for index in [None]:
self.assertEqual(
(name,index) in root._name_index_to_id, True)
for name in ("b1.X", "b2.X", "b3.X", "b4.X"):
for index in model.s:
self.assertEqual(
(name,index) in root._name_index_to_id, True)
def _generate_base_scenario_tree(self, model, variable_stage_assignments):
stage_cost_annotation = locate_annotations(model,
PySP_StageCostAnnotation,
max_allowed=1)
if len(stage_cost_annotation) == 0:
raise ValueError("Reference model is missing stage cost "
"annotation: %s" %
(PySP_StageCostAnnotation.__name__))
else:
assert len(stage_cost_annotation) == 1
stage_cost_annotation = stage_cost_annotation[0][1]
stage_cost_assignments = ComponentMap(
stage_cost_annotation.expand_entries())
stage1_cost = None
stage2_cost = None
for cdata, stagenum in stage_cost_assignments.items():
if stagenum == 1:
stage1_cost = cdata
elif stagenum == 2:
stage2_cost = cdata
if stage1_cost is None:
raise ValueError("Missing stage cost annotation for time stage: 1")
if stage2_cost is None:
raise ValueError("Missing stage cost annotation for time stage: 2")
assert stage1_cost != stage2_cost
#
# Create a dummy 1-scenario scenario tree
#
stm = CreateAbstractScenarioTreeModel()
stm.Stages.add('Stage1')
stm.Stages.add('Stage2')
stm.Nodes.add('RootNode')
stm.Nodes.add('LeafNode')
stm.Scenarios.add('ReferenceScenario')
stm = stm.create_instance()
stm.NodeStage['RootNode'] = 'Stage1'
stm.ConditionalProbability['RootNode'] = 1.0
stm.NodeStage['LeafNode'] = 'Stage2'
stm.Children['RootNode'].add('LeafNode')
stm.Children['LeafNode'].clear()
stm.ConditionalProbability['LeafNode'] = 1.0
stm.ScenarioLeafNode['ReferenceScenario'] = 'LeafNode'
stm.StageCost['Stage1'] = stage1_cost.name
stm.StageCost['Stage2'] = stage2_cost.name
for var, (stagenum, derived) in variable_stage_assignments.items():
stagelabel = 'Stage' + str(stagenum)
if not derived:
stm.StageVariables[stagelabel].add(var.name)
else:
stm.StageDerivedVariables[second_stage].add(var.name)
scenario_tree = ScenarioTree(scenariotreeinstance=stm)
scenario_tree.linkInInstances(
{'ReferenceScenario': self.reference_model})
return scenario_tree
def test_indexedvar_noindextemplate(self):
st_model = CreateConcreteTwoStageScenarioTreeModel(1)
st_model.StageVariables['Stage1'].add("x")
st_model.StageDerivedVariables['Stage1'].add("y")
st_model.NodeVariables['RootNode'].add("z")
st_model.NodeDerivedVariables['RootNode'].add("q")
st_model.StageCost['Stage1'] = "FirstStageCost"
st_model.StageCost['Stage2'] = "SecondStageCost"
scenario_tree = ScenarioTree(scenariotreeinstance=st_model)
self.assertEqual(len(scenario_tree.stages), 2)
self.assertEqual(len(scenario_tree.nodes), 2)
self.assertEqual(len(scenario_tree.scenarios), 1)
model = ConcreteModel()
model.s = Set(initialize=[1, 2, 3])
model.x = Var(model.s)
model.y = Var(model.s)
model.z = Var(model.s)
model.q = Var(model.s)
model.FirstStageCost = Expression(expr=0.0)
model.SecondStageCost = Expression(expr=0.0)
model.obj = Objective(expr=0.0)
scenario_tree.linkInInstances({'Scenario1': model})
root = scenario_tree.findRootNode()
self.assertEqual(len(root._variable_ids), 12)
self.assertEqual(len(root._standard_variable_ids), 6)
self.assertEqual(len(root._derived_variable_ids), 6)
for name in ("x", "y", "z", "q"):
for index in model.s:
self.assertEqual((name, index) in root._name_index_to_id, True)
def test_indexedblock_wildcardtemplate(self):
st_model = CreateConcreteTwoStageScenarioTreeModel(1)
st_model.StageVariables['Stage1'].add("B1[*]")
st_model.StageDerivedVariables['Stage1'].add("B2[*]")
st_model.NodeVariables['RootNode'].add("B3[*]")
st_model.NodeDerivedVariables['RootNode'].add("B4[*]")
st_model.StageCost['Stage1'] = "FirstStageCost"
st_model.StageCost['Stage2'] = "SecondStageCost"
scenario_tree = ScenarioTree(scenariotreeinstance=st_model)
self.assertEqual(len(scenario_tree.stages), 2)
self.assertEqual(len(scenario_tree.nodes), 2)
self.assertEqual(len(scenario_tree.scenarios), 1)
model = self._get_block_model()
scenario_tree.linkInInstances({'Scenario1': model})
root = scenario_tree.findRootNode()
self.assertEqual(len(root._variable_ids), 24)
self.assertEqual(len(root._standard_variable_ids), 12)
self.assertEqual(len(root._derived_variable_ids), 12)
for name in ("B1[1].x", "B1[2].x", "B2[1].x", "B2[2].x", "B3[1].x",
"B3[2].x", "B4[1].x", "B4[2].x"):
for index in [None]:
self.assertEqual((name, index) in root._name_index_to_id, True)
for name in ("B1[1].X", "B1[2].X", "B2[1].X", "B2[2].X", "B3[1].X",
"B3[2].X", "B4[1].X", "B4[2].X"):
for index in model.s:
self.assertEqual((name, index) in root._name_index_to_id, True)
def test_singletonvar_wildcardtemplate(self):
st_model = CreateConcreteTwoStageScenarioTreeModel(1)
st_model.StageVariables['Stage1'].add("x[*]")
st_model.StageDerivedVariables['Stage1'].add("y[*]")
st_model.NodeVariables['RootNode'].add("z[*]")
st_model.NodeDerivedVariables['RootNode'].add("q[*]")
st_model.StageCost['Stage1'] = "FirstStageCost"
st_model.StageCost['Stage2'] = "SecondStageCost"
scenario_tree = ScenarioTree(scenariotreeinstance=st_model)
self.assertEqual(len(scenario_tree.stages), 2)
self.assertEqual(len(scenario_tree.nodes), 2)
self.assertEqual(len(scenario_tree.scenarios), 1)
model = ConcreteModel()
model.x = Var()
model.y = Var()
model.z = Var()
model.q = Var()
model.FirstStageCost = Expression(expr=0.0)
model.SecondStageCost = Expression(expr=0.0)
model.obj = Objective(expr=0.0)
scenario_tree.linkInInstances({'Scenario1': model})
root = scenario_tree.findRootNode()
self.assertEqual(len(root._variable_ids), 4)
self.assertEqual(len(root._standard_variable_ids), 2)
self.assertEqual(len(root._derived_variable_ids), 2)
for name in ("x", "y", "z", "q"):
for index in [None]:
self.assertEqual(
(name,index) in root._name_index_to_id, True)
def test_singletonvar_wildcardtemplate(self):
st_model = CreateConcreteTwoStageScenarioTreeModel(1)
st_model.StageVariables['Stage1'].add("x[*]")
st_model.StageDerivedVariables['Stage1'].add("y[*]")
st_model.NodeVariables['RootNode'].add("z[*]")
st_model.NodeDerivedVariables['RootNode'].add("q[*]")
st_model.StageCost['Stage1'] = "FirstStageCost"
st_model.StageCost['Stage2'] = "SecondStageCost"
scenario_tree = ScenarioTree(scenariotreeinstance=st_model)
self.assertEqual(len(scenario_tree.stages), 2)
self.assertEqual(len(scenario_tree.nodes), 2)
self.assertEqual(len(scenario_tree.scenarios), 1)
model = ConcreteModel()
model.x = Var()
model.y = Var()
model.z = Var()
model.q = Var()
model.FirstStageCost = Expression(expr=0.0)
model.SecondStageCost = Expression(expr=0.0)
model.obj = Objective(expr=0.0)
scenario_tree.linkInInstances({'Scenario1': model})
root = scenario_tree.findRootNode()
self.assertEqual(len(root._variable_ids), 4)
self.assertEqual(len(root._standard_variable_ids), 2)
self.assertEqual(len(root._derived_variable_ids), 2)
for name in ("x", "y", "z", "q"):
for index in [None]:
self.assertEqual((name, index) in root._name_index_to_id, True)
def test_singletonblock_noindextemplate(self):
st_model = CreateConcreteTwoStageScenarioTreeModel(1)
st_model.StageVariables['Stage1'].add("b1")
st_model.StageDerivedVariables['Stage1'].add("b2")
st_model.NodeVariables['RootNode'].add("b3")
st_model.NodeDerivedVariables['RootNode'].add("b4")
st_model.StageCost['Stage1'] = "FirstStageCost"
st_model.StageCost['Stage2'] = "SecondStageCost"
scenario_tree = ScenarioTree(scenariotreeinstance=st_model)
self.assertEqual(len(scenario_tree.stages), 2)
self.assertEqual(len(scenario_tree.nodes), 2)
self.assertEqual(len(scenario_tree.scenarios), 1)
model = self._get_block_model()
scenario_tree.linkInInstances({'Scenario1': model})
root = scenario_tree.findRootNode()
self.assertEqual(len(root._variable_ids), 12)
self.assertEqual(len(root._standard_variable_ids), 6)
self.assertEqual(len(root._derived_variable_ids), 6)
for name in ("b1.x", "b2.x", "b3.x", "b4.x"):
for index in [None]:
self.assertEqual((name, index) in root._name_index_to_id, True)
for name in ("b1.X", "b2.X", "b3.X", "b4.X"):
for index in model.s:
self.assertEqual((name, index) in root._name_index_to_id, True)
def test_indexedvar_noindextemplate(self):
st_model = CreateConcreteTwoStageScenarioTreeModel(1)
st_model.StageVariables['Stage1'].add("x")
st_model.StageDerivedVariables['Stage1'].add("y")
st_model.NodeVariables['RootNode'].add("z")
st_model.NodeDerivedVariables['RootNode'].add("q")
st_model.StageCost['Stage1'] = "FirstStageCost"
st_model.StageCost['Stage2'] = "SecondStageCost"
scenario_tree = ScenarioTree(scenariotreeinstance=st_model)
self.assertEqual(len(scenario_tree.stages), 2)
self.assertEqual(len(scenario_tree.nodes), 2)
self.assertEqual(len(scenario_tree.scenarios), 1)
model = ConcreteModel()
model.s = Set(initialize=[1,2,3])
model.x = Var(model.s)
model.y = Var(model.s)
model.z = Var(model.s)
model.q = Var(model.s)
model.FirstStageCost = Expression(expr=0.0)
model.SecondStageCost = Expression(expr=0.0)
model.obj = Objective(expr=0.0)
scenario_tree.linkInInstances({'Scenario1': model})
root = scenario_tree.findRootNode()
self.assertEqual(len(root._variable_ids), 12)
self.assertEqual(len(root._standard_variable_ids), 6)
self.assertEqual(len(root._derived_variable_ids), 6)
for name in ("x", "y", "z", "q"):
for index in model.s:
self.assertEqual(
(name,index) in root._name_index_to_id, True)
def _generate_base_scenario_tree(self, model, variable_stage_assignments):
stage_cost_annotation = locate_annotations(
model,
PySP_StageCostAnnotation,
max_allowed=1)
if len(stage_cost_annotation) == 0:
raise ValueError("Reference model is missing stage cost "
"annotation: %s" % (PySP_StageCostAnnotation.__name__))
else:
assert len(stage_cost_annotation) == 1
stage_cost_annotation = stage_cost_annotation[0][1]
stage_cost_assignments = ComponentMap(
stage_cost_annotation.expand_entries())
stage1_cost = None
stage2_cost = None
for cdata, stagenum in stage_cost_assignments.items():
if stagenum == 1:
stage1_cost = cdata
elif stagenum == 2:
stage2_cost = cdata
if stage1_cost is None:
raise ValueError("Missing stage cost annotation for time stage: 1")
if stage2_cost is None:
raise ValueError("Missing stage cost annotation for time stage: 2")
assert stage1_cost != stage2_cost
#
# Create a dummy 1-scenario scenario tree
#
stm = CreateAbstractScenarioTreeModel()
stm.Stages.add('Stage1')
stm.Stages.add('Stage2')
stm.Nodes.add('RootNode')
stm.Nodes.add('LeafNode')
stm.Scenarios.add('ReferenceScenario')
stm = stm.create_instance()
stm.NodeStage['RootNode'] = 'Stage1'
stm.ConditionalProbability['RootNode'] = 1.0
stm.NodeStage['LeafNode'] = 'Stage2'
stm.Children['RootNode'].add('LeafNode')
stm.Children['LeafNode'].clear()
stm.ConditionalProbability['LeafNode'] = 1.0
stm.ScenarioLeafNode['ReferenceScenario'] = 'LeafNode'
stm.StageCost['Stage1'] = stage1_cost.name
stm.StageCost['Stage2'] = stage2_cost.name
for var, (stagenum, derived) in variable_stage_assignments.items():
stagelabel = 'Stage'+str(stagenum)
if not derived:
stm.StageVariables[stagelabel].add(var.name)
else:
stm.StageDerivedVariables[second_stage].add(var.name)
scenario_tree = ScenarioTree(scenariotreeinstance=stm)
scenario_tree.linkInInstances(
{'ReferenceScenario': self.reference_model})
return scenario_tree
def test_two_stage_custom_names(self):
G = networkx.DiGraph()
G.add_node("R", label="Root")
G.add_node("C1", label="Child1")
G.add_edge("R", "C1", weight=0.8)
G.add_node("C2", label="Child2")
G.add_edge("R", "C2", weight=0.2)
model = ScenarioTreeModelFromNetworkX(
G,
edge_probability_attribute='weight',
node_name_attribute='label',
stage_names=['T1', 'T2'],
scenario_names={
'C1': 'S1',
'C2': 'S2'
})
self.assertEqual(sorted(list(model.Stages)), sorted(['T1', 'T2']))
self.assertEqual(sorted(list(model.Nodes)),
sorted(['Root', 'Child1', 'Child2']))
self.assertEqual(sorted(list(model.Children['Root'])),
sorted(['Child1', 'Child2']))
self.assertEqual(sorted(list(model.Children['Child1'])), sorted([]))
self.assertEqual(sorted(list(model.Children['Child2'])), sorted([]))
self.assertEqual(sorted(list(model.Scenarios)), sorted(['S1', 'S2']))
self.assertEqual(model.ConditionalProbability['Root'], 1.0)
self.assertEqual(model.ConditionalProbability['Child1'], 0.8)
self.assertEqual(model.ConditionalProbability['Child2'], 0.2)
model.StageCost['T1'] = 'c1'
model.StageCost['T2'] = 'c2'
model.StageVariables['T1'].add('x')
ScenarioTree(scenariotreeinstance=model)
def test_bundles(self):
G = networkx.DiGraph()
G.add_node("r")
for i in range(4):
G.add_node("u" + str(i), bundle=i % 2)
G.add_edge("r", "u" + str(i))
model = ScenarioTreeModelFromNetworkX(G,
edge_probability_attribute=None)
self.assertEqual(sorted(list(model.Stages)),
sorted(["Stage1", "Stage2"]))
self.assertEqual(sorted(list(model.Nodes)),
sorted(["r", "u0", "u1", "u2", "u3"]))
self.assertEqual(sorted(list(model.Children["r"])),
sorted(["u0", "u1", "u2", "u3"]))
for i in range(4):
self.assertEqual(sorted(list(model.Children["u" + str(i)])),
sorted([]))
self.assertEqual(sorted(list(model.Scenarios)),
sorted(["u0", "u1", "u2", "u3"]))
self.assertEqual(model.ConditionalProbability["r"], 1.0)
for i in range(4):
self.assertEqual(model.ConditionalProbability["u" + str(i)], 0.25)
self.assertEqual(model.Bundling.value, True)
self.assertEqual(list(model.Bundles), [0, 1])
for k, bundle_name in enumerate(model.Bundles):
self.assertEqual(list(model.BundleScenarios[bundle_name]),
["u" + str(i) for i in range(4) if i % 2 == k])
model.StageCost["Stage1"] = "c1"
model.StageCost["Stage2"] = "c2"
model.StageVariables["Stage1"].add("x")
ScenarioTree(scenariotreeinstance=model)
def test_two_stage_custom_names(self):
G = networkx.DiGraph()
G.add_node("R", label="Root")
G.add_node("C1", label="Child1", scenario="S1")
G.add_edge("R", "C1", probability=0.8)
G.add_node("C2", label="Child2", scenario="S2")
G.add_edge("R", "C2", probability=0.2)
model = ScenarioTreeModelFromNetworkX(
G,
edge_probability_attribute="probability",
node_name_attribute="label",
stage_names=["T1", "T2"],
scenario_name_attribute="scenario")
self.assertEqual(sorted(list(model.Stages)), sorted(["T1", "T2"]))
self.assertEqual(sorted(list(model.Nodes)),
sorted(["Root", "Child1", "Child2"]))
self.assertEqual(sorted(list(model.Children["Root"])),
sorted(["Child1", "Child2"]))
self.assertEqual(sorted(list(model.Children["Child1"])), sorted([]))
self.assertEqual(sorted(list(model.Children["Child2"])), sorted([]))
self.assertEqual(sorted(list(model.Scenarios)), sorted(["S1", "S2"]))
self.assertEqual(model.ConditionalProbability["Root"], 1.0)
self.assertEqual(model.ConditionalProbability["Child1"], 0.8)
self.assertEqual(model.ConditionalProbability["Child2"], 0.2)
model.StageCost["T1"] = "c1"
model.StageCost["T2"] = "c2"
model.StageVariables["T1"].add("x")
self.assertEqual(model.Bundling.value, False)
self.assertEqual(list(model.Bundles), [])
self.assertEqual(len(model.BundleScenarios), 0)
ScenarioTree(scenariotreeinstance=model)
def test_two_stage(self):
G = networkx.DiGraph()
G.add_node("Root")
G.add_node("Child1")
G.add_edge("Root", "Child1", weight=0.8)
G.add_node("Child2")
G.add_edge("Root", "Child2", weight=0.2)
model = ScenarioTreeModelFromNetworkX(G)
self.assertEqual(sorted(list(model.Stages)),
sorted(["Stage1", "Stage2"]))
self.assertEqual(sorted(list(model.Nodes)),
sorted(["Root", "Child1", "Child2"]))
self.assertEqual(sorted(list(model.Children["Root"])),
sorted(["Child1", "Child2"]))
self.assertEqual(sorted(list(model.Children["Child1"])), sorted([]))
self.assertEqual(sorted(list(model.Children["Child2"])), sorted([]))
self.assertEqual(sorted(list(model.Scenarios)),
sorted(["Child1", "Child2"]))
self.assertEqual(model.ConditionalProbability["Root"], 1.0)
self.assertEqual(model.ConditionalProbability["Child1"], 0.8)
self.assertEqual(model.ConditionalProbability["Child2"], 0.2)
model.StageCost["Stage1"] = "c1"
model.StageCost["Stage2"] = "c2"
model.StageVariables["Stage1"].add("x")
self.assertEqual(model.Bundling.value, False)
self.assertEqual(list(model.Bundles), [])
self.assertEqual(len(model.BundleScenarios), 0)
ScenarioTree(scenariotreeinstance=model)
def test_two_stage(self):
G = networkx.DiGraph()
G.add_node("Root")
G.add_node("Child1")
G.add_edge("Root", "Child1", probability=0.8)
G.add_node("Child2")
G.add_edge("Root", "Child2", probability=0.2)
model = ScenarioTreeModelFromNetworkX(G)
self.assertEqual(sorted(list(model.Stages)),
sorted(['Stage1', 'Stage2']))
self.assertEqual(sorted(list(model.Nodes)),
sorted(['Root', 'Child1', 'Child2']))
self.assertEqual(sorted(list(model.Children['Root'])),
sorted(['Child1', 'Child2']))
self.assertEqual(sorted(list(model.Children['Child1'])), sorted([]))
self.assertEqual(sorted(list(model.Children['Child2'])), sorted([]))
self.assertEqual(sorted(list(model.Scenarios)),
sorted(['Scenario_uChild1', 'Scenario_uChild2']))
self.assertEqual(model.ConditionalProbability['Root'], 1.0)
self.assertEqual(model.ConditionalProbability['Child1'], 0.8)
self.assertEqual(model.ConditionalProbability['Child2'], 0.2)
model.StageCost['Stage1'] = 'c1'
model.StageCost['Stage2'] = 'c2'
model.StageVariables['Stage1'].add('x')
ScenarioTree(scenariotreeinstance=model)
def test_two_stage_more_node_attributes(self):
G = networkx.DiGraph()
G.add_node("Root", cost="c1", variables=["x"], derived_variables=["y"])
G.add_node("Child1",
cost="c2",
variables=["q"],
derived_variables=["z"])
G.add_edge("Root", "Child1", weight=0.8)
G.add_node("Child2",
cost="c2",
variables=["q"],
derived_variables=["z"])
G.add_edge("Root", "Child2", weight=0.2)
model = ScenarioTreeModelFromNetworkX(G)
self.assertEqual(sorted(list(model.Stages)),
sorted(["Stage1", "Stage2"]))
self.assertEqual(sorted(list(model.Nodes)),
sorted(["Root", "Child1", "Child2"]))
self.assertEqual(sorted(list(model.Children["Root"])),
sorted(["Child1", "Child2"]))
self.assertEqual(sorted(list(model.Children["Child1"])), sorted([]))
self.assertEqual(sorted(list(model.Children["Child2"])), sorted([]))
self.assertEqual(sorted(list(model.Scenarios)),
sorted(["Child1", "Child2"]))
self.assertEqual(model.ConditionalProbability["Root"], 1.0)
self.assertEqual(model.ConditionalProbability["Child1"], 0.8)
self.assertEqual(model.ConditionalProbability["Child2"], 0.2)
# FIXME: #300 on GitHub
self.assertEqual(model.StageCost["Stage1"]._value, None)
self.assertEqual(list(model.StageVariables["Stage1"]), [])
self.assertEqual(list(model.StageDerivedVariables["Stage1"]), [])
self.assertEqual(model.NodeCost["Root"].value, "c1")
self.assertEqual(list(model.NodeVariables["Root"]), ["x"])
self.assertEqual(list(model.NodeDerivedVariables["Root"]), ["y"])
# FIXME: #300 on GitHub
self.assertEqual(model.StageCost["Stage2"]._value, None)
self.assertEqual(list(model.StageVariables["Stage2"]), [])
self.assertEqual(list(model.StageDerivedVariables["Stage2"]), [])
self.assertEqual(model.NodeCost["Child1"].value, "c2")
self.assertEqual(list(model.NodeVariables["Child1"]), ["q"])
self.assertEqual(list(model.NodeDerivedVariables["Child1"]), ["z"])
self.assertEqual(model.NodeCost["Child2"].value, "c2")
self.assertEqual(list(model.NodeVariables["Child2"]), ["q"])
self.assertEqual(list(model.NodeDerivedVariables["Child2"]), ["z"])
self.assertEqual(model.Bundling.value, False)
self.assertEqual(list(model.Bundles), [])
self.assertEqual(len(model.BundleScenarios), 0)
ScenarioTree(scenariotreeinstance=model)
def test_unbalanced(self):
G = networkx.DiGraph()
G.add_node("R")
G.add_node("0")
G.add_node("1")
G.add_edge("R", "0")
G.add_edge("R", "1")
G.add_node("00")
G.add_node("01")
G.add_edge("0", "00")
G.add_edge("0", "01")
model = ScenarioTreeModelFromNetworkX(
G,
edge_probability_attribute=None)
self.assertEqual(
sorted(list(model.Stages)),
sorted(["Stage1", "Stage2", "Stage3"]))
self.assertEqual(
sorted(list(model.Nodes)),
sorted(["R","0","1","00","01"]))
self.assertEqual(
sorted(list(model.Children["R"])),
sorted(["0", "1"]))
self.assertEqual(
sorted(list(model.Children["0"])),
sorted(["00","01"]))
self.assertEqual(
sorted(list(model.Children["1"])),
sorted([]))
self.assertEqual(
sorted(list(model.Children["00"])),
sorted([]))
self.assertEqual(
sorted(list(model.Children["01"])),
sorted([]))
self.assertEqual(
sorted(list(model.Scenarios)),
sorted(["00", "01", "1"]))
self.assertEqual(model.ConditionalProbability["R"], 1.0)
self.assertEqual(model.ConditionalProbability["0"], 0.5)
self.assertEqual(model.ConditionalProbability["1"], 0.5)
self.assertEqual(model.ConditionalProbability["00"], 0.5)
self.assertEqual(model.ConditionalProbability["01"], 0.5)
model.StageCost["Stage1"] = "c1"
model.StageCost["Stage2"] = "c2"
model.StageCost["Stage3"] = "c3"
model.StageVariables["Stage1"].add("x")
model.StageVariables["Stage2"].add("x")
self.assertEqual(model.Bundling.value, False)
self.assertEqual(list(model.Bundles), [])
self.assertEqual(len(model.BundleScenarios), 0)
ScenarioTree(scenariotreeinstance=model)
def test_indexedblock_wildcardtemplate(self):
st_model = CreateConcreteTwoStageScenarioTreeModel(1)
st_model.StageVariables['Stage1'].add("B1[*]")
st_model.StageDerivedVariables['Stage1'].add("B2[*]")
st_model.NodeVariables['RootNode'].add("B3[*]")
st_model.NodeDerivedVariables['RootNode'].add("B4[*]")
st_model.StageCost['Stage1'] = "FirstStageCost"
st_model.StageCost['Stage2'] = "SecondStageCost"
scenario_tree = ScenarioTree(scenariotreeinstance=st_model)
self.assertEqual(len(scenario_tree.stages), 2)
self.assertEqual(len(scenario_tree.nodes), 2)
self.assertEqual(len(scenario_tree.scenarios), 1)
model = self._get_block_model()
scenario_tree.linkInInstances({'Scenario1': model})
root = scenario_tree.findRootNode()
self.assertEqual(len(root._variable_ids), 24)
self.assertEqual(len(root._standard_variable_ids), 12)
self.assertEqual(len(root._derived_variable_ids), 12)
for name in ("B1[1].x", "B1[2].x",
"B2[1].x", "B2[2].x",
"B3[1].x", "B3[2].x",
"B4[1].x", "B4[2].x"):
for index in [None]:
self.assertEqual(
(name,index) in root._name_index_to_id, True)
for name in ("B1[1].X", "B1[2].X",
"B2[1].X", "B2[2].X",
"B3[1].X", "B3[2].X",
"B4[1].X", "B4[2].X"):
for index in model.s:
self.assertEqual(
(name,index) in root._name_index_to_id, True)
def test_multi_stage(self):
G = networkx.balanced_tree(3, 2, networkx.DiGraph())
model = ScenarioTreeModelFromNetworkX(G,
edge_probability_attribute=None)
self.assertEqual(sorted(list(model.Stages)),
sorted(['Stage1', 'Stage2', 'Stage3']))
self.assertEqual(sorted(list(model.Nodes)),
sorted([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]))
self.assertEqual(sorted(list(model.Children[0])), sorted([1, 2, 3]))
self.assertEqual(sorted(list(model.Children[1])), sorted([4, 5, 6]))
self.assertEqual(sorted(list(model.Children[2])), sorted([7, 8, 9]))
self.assertEqual(sorted(list(model.Children[3])), sorted([10, 11, 12]))
self.assertEqual(sorted(list(model.Children[4])), sorted([]))
self.assertEqual(sorted(list(model.Children[5])), sorted([]))
self.assertEqual(sorted(list(model.Children[6])), sorted([]))
self.assertEqual(sorted(list(model.Children[7])), sorted([]))
self.assertEqual(sorted(list(model.Children[8])), sorted([]))
self.assertEqual(sorted(list(model.Children[9])), sorted([]))
self.assertEqual(sorted(list(model.Children[10])), sorted([]))
self.assertEqual(sorted(list(model.Children[11])), sorted([]))
self.assertEqual(sorted(list(model.Children[12])), sorted([]))
self.assertEqual(
sorted(list(model.Scenarios)),
sorted([
'Scenario_u4', 'Scenario_u5', 'Scenario_u6', 'Scenario_u7',
'Scenario_u8', 'Scenario_u9', 'Scenario_u10', 'Scenario_u11',
'Scenario_u12'
]))
self.assertEqual(model.ConditionalProbability[0], 1.0)
self.assertAlmostEqual(model.ConditionalProbability[1], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[2], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[3], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[4], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[5], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[6], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[7], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[8], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[9], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[10], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[11], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[12], 1.0 / 3)
model.StageCost['Stage1'] = 'c1'
model.StageCost['Stage2'] = 'c2'
model.StageCost['Stage3'] = 'c3'
model.StageVariables['Stage1'].add('x')
model.StageVariables['Stage2'].add('y')
model.StageVariables['Stage3'].add('y')
ScenarioTree(scenariotreeinstance=model)
def test_multi_stage(self):
G = networkx.balanced_tree(3, 2, networkx.DiGraph())
model = ScenarioTreeModelFromNetworkX(G,
edge_probability_attribute=None)
self.assertEqual(sorted(list(model.Stages)),
sorted(["Stage1", "Stage2", "Stage3"]))
self.assertEqual(sorted(list(model.Nodes)),
sorted([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]))
self.assertEqual(sorted(list(model.Children[0])), sorted([1, 2, 3]))
self.assertEqual(sorted(list(model.Children[1])), sorted([4, 5, 6]))
self.assertEqual(sorted(list(model.Children[2])), sorted([7, 8, 9]))
self.assertEqual(sorted(list(model.Children[3])), sorted([10, 11, 12]))
self.assertEqual(sorted(list(model.Children[4])), sorted([]))
self.assertEqual(sorted(list(model.Children[5])), sorted([]))
self.assertEqual(sorted(list(model.Children[6])), sorted([]))
self.assertEqual(sorted(list(model.Children[7])), sorted([]))
self.assertEqual(sorted(list(model.Children[8])), sorted([]))
self.assertEqual(sorted(list(model.Children[9])), sorted([]))
self.assertEqual(sorted(list(model.Children[10])), sorted([]))
self.assertEqual(sorted(list(model.Children[11])), sorted([]))
self.assertEqual(sorted(list(model.Children[12])), sorted([]))
self.assertEqual(sorted(list(model.Scenarios)),
sorted([4, 5, 6, 7, 8, 9, 10, 11, 12]))
self.assertEqual(model.ConditionalProbability[0], 1.0)
self.assertAlmostEqual(model.ConditionalProbability[1], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[2], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[3], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[4], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[5], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[6], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[7], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[8], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[9], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[10], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[11], 1.0 / 3)
self.assertAlmostEqual(model.ConditionalProbability[12], 1.0 / 3)
model.StageCost["Stage1"] = "c1"
model.StageCost["Stage2"] = "c2"
model.StageCost["Stage3"] = "c3"
model.StageVariables["Stage1"].add("x")
model.StageVariables["Stage2"].add("y")
model.StageVariables["Stage3"].add("y")
self.assertEqual(model.Bundling.value, False)
self.assertEqual(list(model.Bundles), [])
self.assertEqual(len(model.BundleScenarios), 0)
ScenarioTree(scenariotreeinstance=model)
def test_unbalanced(self):
G = networkx.DiGraph()
G.add_node('R')
G.add_node('0')
G.add_node('1')
G.add_edge('R', '0')
G.add_edge('R', '1')
G.add_node('00')
G.add_node('01')
G.add_edge('0', '00')
G.add_edge('0', '01')
model = ScenarioTreeModelFromNetworkX(G,
edge_probability_attribute=None)
self.assertEqual(sorted(list(model.Stages)),
sorted(['Stage1', 'Stage2', 'Stage3']))
self.assertEqual(sorted(list(model.Nodes)),
sorted(['R', '0', '1', '00', '01']))
self.assertEqual(sorted(list(model.Children['R'])), sorted(['0', '1']))
self.assertEqual(sorted(list(model.Children['0'])),
sorted(['00', '01']))
self.assertEqual(sorted(list(model.Children['1'])), sorted([]))
self.assertEqual(sorted(list(model.Children['00'])), sorted([]))
self.assertEqual(sorted(list(model.Children['01'])), sorted([]))
self.assertEqual(
sorted(list(model.Scenarios)),
sorted(['Scenario_u00', 'Scenario_u01', 'Scenario_u1']))
self.assertEqual(model.ConditionalProbability['R'], 1.0)
self.assertEqual(model.ConditionalProbability['0'], 0.5)
self.assertEqual(model.ConditionalProbability['1'], 0.5)
self.assertEqual(model.ConditionalProbability['00'], 0.5)
self.assertEqual(model.ConditionalProbability['01'], 0.5)
model.StageCost['Stage1'] = 'c1'
model.StageCost['Stage2'] = 'c2'
model.StageCost['Stage3'] = 'c3'
model.StageVariables['Stage1'].add('x')
model.StageVariables['Stage2'].add('x')
ScenarioTree(scenariotreeinstance=model)
def generate_scenario_tree(self,
downsample_fraction=1.0,
include_scenarios=None,
bundles=None,
random_bundles=None,
random_seed=None,
verbose=True):
scenario_tree_model = self._scenario_tree_model
if scenario_tree_model is not None:
if has_networkx and \
isinstance(scenario_tree_model, networkx.DiGraph):
scenario_tree_model = \
ScenarioTreeModelFromNetworkX(scenario_tree_model)
else:
assert isinstance(scenario_tree_model, (_BlockData, Block)), \
str(scenario_tree_model)+" "+str(type(scenario_tree_model))
if bundles is not None:
if isinstance(bundles, six.string_types):
if scenario_tree_model is None:
raise ValueError("A bundles file can not be used when the "
"scenario tree input was not a Pyomo "
"model or ScenarioStructure.dat file.")
logger.debug("attempting to locate bundle file for input: %s" %
(bundles))
# we interpret the scenario bundle specification in one of
# two ways. if the supplied name is a file, it is used
# directly. otherwise, it is interpreted as the root of a
# file with a .dat suffix to be found in the instance
# directory.
orig_input = bundles
if not bundles.endswith(".dat"):
bundles = bundles + ".dat"
bundles = os.path.expanduser(bundles)
if not os.path.exists(bundles):
if self.data_directory() is None:
raise ValueError(
"Could not locate bundle .dat file from input "
"'%s'. Path does not exist and there is no data "
"directory to search in." % (orig_input))
bundles = os.path.join(self.data_directory(), bundles)
if not os.path.exists(bundles):
raise ValueError("Could not locate bundle .dat file "
"from input '%s' as absolute path or "
"relative to data directory: %s" %
(orig_input, self.data_directory()))
if verbose:
print("Scenario tree bundle specification filename=%s" %
(bundles))
scenario_tree_model = scenario_tree_model.clone()
scenario_tree_model.Bundling = True
scenario_tree_model.Bundling._constructed = False
scenario_tree_model.Bundling._data.clear()
scenario_tree_model.Bundles.clear()
scenario_tree_model.Bundles._constructed = False
scenario_tree_model.Bundles._data.clear()
scenario_tree_model.BundleScenarios.clear()
scenario_tree_model.BundleScenarios._constructed = False
scenario_tree_model.BundleScenarios._data.clear()
scenario_tree_model.load(bundles)
#
# construct the scenario tree
#
if scenario_tree_model is not None:
scenario_tree = ScenarioTree(
scenariotreeinstance=scenario_tree_model,
scenariobundlelist=include_scenarios)
else:
assert self._scenario_tree is not None
if include_scenarios is None:
scenario_tree = copy.deepcopy(self._scenario_tree)
else:
# note: any bundles will be lost
if self._scenario_tree.contains_bundles():
raise ValueError("Can not compress a scenario tree that "
"contains bundles")
scenario_tree = self._scenario_tree.make_compressed(
include_scenarios, normalize=True)
# compress/down-sample the scenario tree, if requested
if (downsample_fraction is not None) and \
(downsample_fraction < 1.0):
scenario_tree.downsample(downsample_fraction, random_seed, verbose)
#
# create bundles from a dict, if requested
#
if bundles is not None:
if not isinstance(bundles, six.string_types):
if verbose:
print("Adding bundles to scenario tree from "
"user-specified dict")
if scenario_tree.contains_bundles():
if verbose:
print("Scenario tree already contains bundles. "
"All existing bundles will be removed.")
for bundle in list(scenario_tree.bundles):
scenario_tree.remove_bundle(bundle.name)
for bundle_name in bundles:
scenario_tree.add_bundle(bundle_name, bundles[bundle_name])
#
# create random bundles, if requested
#
if (random_bundles is not None) and \
(random_bundles > 0):
if bundles is not None:
raise ValueError("Cannot specify both random "
"bundles and a bundles specification")
num_scenarios = len(scenario_tree._scenarios)
if random_bundles > num_scenarios:
raise ValueError("Cannot create more random bundles "
"than there are scenarios!")
if verbose:
print("Creating " + str(random_bundles) +
" random bundles using seed=" + str(random_seed))
scenario_tree.create_random_bundles(random_bundles, random_seed)
scenario_tree._scenario_instance_factory = self
return scenario_tree
def generate_scenario_tree(self,
downsample_fraction=1.0,
include_scenarios=None,
bundles=None,
random_bundles=None,
random_seed=None):
scenario_tree_instance = self._scenario_tree_instance
if bundles is not None:
if isinstance(bundles, string_types):
bundles_file_path = None
# we interpret the scenario bundle specification in one of
# two ways. if the supplied name is a file, it is used
# directly. otherwise, it is interpreted as the root of a
# file with a .dat suffix to be found in the instance
# directory.
if os.path.exists(os.path.expanduser(bundles)):
bundles_file_path = \
os.path.expanduser(bundles)
else:
bundles_file_path = \
os.path.join(self._scenario_tree_directory,
bundles+".dat")
if self._verbose:
if bundles_file_path is not None:
print("Scenario tree bundle specification filename="
+bundles_file_path)
scenario_tree_instance = scenario_tree_instance.clone()
scenario_tree_instance.Bundling._constructed = False
scenario_tree_instance.Bundles._constructed = False
scenario_tree_instance.BundleScenarios._constructed = False
scenario_tree_instance.load(bundles_file_path)
#
# construct the scenario tree
#
scenario_tree = ScenarioTree(scenariotreeinstance=scenario_tree_instance,
scenariobundlelist=include_scenarios)
# compress/down-sample the scenario tree, if requested
if (downsample_fraction is not None) and \
(downsample_fraction < 1.0):
scenario_tree.downsample(downsample_fraction,
random_seed,
self._verbose)
#
# create bundles from a dict, if requested
#
if bundles is not None:
if not isinstance(bundles, string_types):
if self._verbose:
print("Adding bundles to scenario tree from user-specified dict")
if scenario_tree.contains_bundles():
if self._verbose:
print("Scenario tree already contains bundles. All existing "
"bundles will be removed.")
for bundle in list(scenario_tree.bundles):
scenario_tree.remove(bundle.name)
for bundle_name in bundles:
scenario_tree.add_bundle(bundle_name, bundles[bundle_name])
#
# create random bundles, if requested
#
if (random_bundles is not None) and \
(random_bundles > 0):
if bundles is not None:
raise ValueError("Cannot specify both random "
"bundles and a bundles specification")
num_scenarios = len(scenario_tree._scenarios)
if random_bundles > num_scenarios:
raise ValueError("Cannot create more random bundles "
"than there are scenarios!")
print("Creating "+str(random_bundles)+
" random bundles using seed="
+str(random_seed))
scenario_tree.create_random_bundles(self._scenario_tree_instance,
random_bundles,
random_seed)
scenario_tree._scenario_instance_factory = self
return scenario_tree
def generate_scenario_tree(self,
downsample_fraction=1.0,
include_scenarios=None,
bundles=None,
random_bundles=None,
random_seed=None,
verbose=True):
scenario_tree_model = self._scenario_tree_model
if scenario_tree_model is not None:
if has_networkx and \
isinstance(scenario_tree_model, networkx.DiGraph):
scenario_tree_model = \
ScenarioTreeModelFromNetworkX(scenario_tree_model)
else:
assert isinstance(scenario_tree_model, (_BlockData, Block)), \
str(scenario_tree_model)+" "+str(type(scenario_tree_model))
if bundles is not None:
if isinstance(bundles, six.string_types):
if scenario_tree_model is None:
raise ValueError(
"A bundles file can not be used when the "
"scenario tree input was not a Pyomo "
"model or ScenarioStructure.dat file.")
logger.debug("attempting to locate bundle file for input: %s"
% (bundles))
# we interpret the scenario bundle specification in one of
# two ways. if the supplied name is a file, it is used
# directly. otherwise, it is interpreted as the root of a
# file with a .dat suffix to be found in the instance
# directory.
orig_input = bundles
if not bundles.endswith(".dat"):
bundles = bundles+".dat"
bundles = os.path.expanduser(bundles)
if not os.path.exists(bundles):
if self.data_directory() is None:
raise ValueError(
"Could not locate bundle .dat file from input "
"'%s'. Path does not exist and there is no data "
"directory to search in." % (orig_input))
bundles = os.path.join(self.data_directory(), bundles)
if not os.path.exists(bundles):
raise ValueError("Could not locate bundle .dat file "
"from input '%s' as absolute path or "
"relative to data directory: %s"
% (orig_input, self.data_directory()))
if verbose:
print("Scenario tree bundle specification filename=%s"
% (bundles))
scenario_tree_model = scenario_tree_model.clone()
scenario_tree_model.Bundling = True
scenario_tree_model.Bundling._constructed = False
scenario_tree_model.Bundles.clear()
scenario_tree_model.Bundles._constructed = False
scenario_tree_model.BundleScenarios.clear()
scenario_tree_model.BundleScenarios._constructed = False
scenario_tree_model.load(bundles)
#
# construct the scenario tree
#
if scenario_tree_model is not None:
scenario_tree = ScenarioTree(scenariotreeinstance=scenario_tree_model,
scenariobundlelist=include_scenarios)
else:
assert self._scenario_tree is not None
if include_scenarios is None:
scenario_tree = copy.deepcopy(self._scenario_tree)
else:
# note: any bundles will be lost
if self._scenario_tree.contains_bundles():
raise ValueError(
"Can not compress a scenario tree that "
"contains bundles")
scenario_tree = self._scenario_tree.make_compressed(
include_scenarios,
normalize=True)
# compress/down-sample the scenario tree, if requested
if (downsample_fraction is not None) and \
(downsample_fraction < 1.0):
scenario_tree.downsample(downsample_fraction,
random_seed,
verbose)
#
# create bundles from a dict, if requested
#
if bundles is not None:
if not isinstance(bundles, six.string_types):
if verbose:
print("Adding bundles to scenario tree from "
"user-specified dict")
if scenario_tree.contains_bundles():
if verbose:
print("Scenario tree already contains bundles. "
"All existing bundles will be removed.")
for bundle in list(scenario_tree.bundles):
scenario_tree.remove_bundle(bundle.name)
for bundle_name in bundles:
scenario_tree.add_bundle(bundle_name,
bundles[bundle_name])
#
# create random bundles, if requested
#
if (random_bundles is not None) and \
(random_bundles > 0):
if bundles is not None:
raise ValueError("Cannot specify both random "
"bundles and a bundles specification")
num_scenarios = len(scenario_tree._scenarios)
if random_bundles > num_scenarios:
raise ValueError("Cannot create more random bundles "
"than there are scenarios!")
if verbose:
print("Creating "+str(random_bundles)+
" random bundles using seed="
+str(random_seed))
scenario_tree.create_random_bundles(random_bundles,
random_seed)
scenario_tree._scenario_instance_factory = self
return scenario_tree