def test_overhead(self):
print "Testing overhead..."
#import cProfile
#import StringIO
#import pstats
for num_timesteps in self.num_timesteps:
for num_nodes in self.num_nodes:
#pr = cProfile.Profile(timer=self.timer)
#pr.enable()
print "%s timesteps * %s nodes" % (num_timesteps, num_nodes)
#Create a simulator object which will be run.
s = Simulator()
#Set the timesteps of the simulator.
timesteps = range(num_timesteps)
s.set_timesteps(timesteps)
#Create the network with initial data
n = Network(name="example network %s nodes %s timesteps" %
(num_nodes, num_timesteps))
for node_num in range(num_nodes):
n.add_node(
DummyNode(x=node_num,
y=node_num,
name="Node number %s" % node_num))
#Set the simulator's network to this network.
s.network = n
#Create an instance of the deficit allocation engine.
empty_engine = EmptyEngine(n)
#add the engine to the simulator
s.add_engine(empty_engine)
t = time.time()
#start the simulator
s.start()
self.result_matrix[num_timesteps][num_nodes] = (time.time() -
t)
#pr.disable()
#s = StringIO.StringIO()
#sortby = 'cumulative'
#ps = pstats.Stats(pr, stream=s).sort_stats(sortby)
#ps.print_stats()
#with open('profile_%s_%s.txt' % (num_timesteps, num_nodes), 'w') as profile_result:
# profile_result.write(s.getvalue())
overhead_result = open('overhead_result.json', 'w')
overhead_result.write(json.dumps(self.result_matrix))
def test_overhead(self):
print("Testing overhead...")
#import cProfile
#import StringIO
#import pstats
for num_timesteps in self.num_timesteps:
for num_nodes in self.num_nodes:
#pr = cProfile.Profile(timer=self.timer)
#pr.enable()
print("%s timesteps * %s nodes"%(num_timesteps, num_nodes))
#Create a simulator object which will be run.
s = Simulator()
#Set the timesteps of the simulator.
timesteps = range(num_timesteps)
s.set_timesteps(timesteps)
#Create the network with initial data
n = Network(name="example network %s nodes %s timesteps"%(num_nodes, num_timesteps))
for node_num in range(num_nodes):
n.add_node(DummyNode(x=node_num, y=node_num, name="Node number %s"%node_num))
#Set the simulator's network to this network.
s.network = n
#Create an instance of the deficit allocation engine.
empty_engine = EmptyEngine(n)
#add the engine to the simulator
s.add_engine(empty_engine)
t = time.time()
#start the simulator
s.start()
self.result_matrix[num_timesteps][num_nodes] = (time.time()-t)
#pr.disable()
#s = StringIO.StringIO()
#sortby = 'cumulative'
#ps = pstats.Stats(pr, stream=s).sort_stats(sortby)
#ps.print_stats()
#with open('profile_%s_%s.txt' % (num_timesteps, num_nodes), 'w') as profile_result:
# profile_result.write(s.getvalue())
overhead_result = open('overhead_result.json', 'w')
overhead_result.write(json.dumps(self.result_matrix))
def test_engine_error(self):
""" Test an engine can raises a non-StopIteration error.
"""
s = Simulator(max_iterations=5)
s.network = Network("Iteration test network")
s.add_engine(TypeErrorEngine(None, error_on_iteration=1))
s.add_engine(CountEngine(None))
s.timesteps = [0, ]
with self.assertRaises(TypeError):
s.start()
def test_engine_iteration(self):
""" Test setting the global number of iterations in a simulator. """
s = Simulator(max_iterations=5)
s.network = Network("Iteration test network")
engine = CountEngine(None)
s.add_engine(engine)
s.timesteps = [0, ]
s.start()
assert engine.iteration == 5
assert engine.run_count == 5
def test_default_iteration(self):
""" Test that the default simulation `max_iterations` is one. """
s = Simulator()
s.network = Network("Iteration test network")
engine = CountEngine(None)
s.add_engine(engine)
s.timesteps = [0, ]
s.start()
assert engine.iteration == 1
assert engine.run_count == 1
def test_engine_iteration(self):
""" Test setting the global number of iterations in a simulator. """
s = Simulator(max_iterations=5)
s.network = Network("Iteration test network")
engine = CountEngine(None)
s.add_engine(engine)
s.timesteps = [
0,
]
s.start()
assert engine.iteration == 5
assert engine.run_count == 5
def test_default_iteration(self):
""" Test that the default simulation `max_iterations` is one. """
s = Simulator()
s.network = Network("Iteration test network")
engine = CountEngine(None)
s.add_engine(engine)
s.timesteps = [
0,
]
s.start()
assert engine.iteration == 1
assert engine.run_count == 1
def test_engine_error(self):
""" Test an engine can raises a non-StopIteration error.
"""
s = Simulator(max_iterations=5)
s.network = Network("Iteration test network")
s.add_engine(TypeErrorEngine(None, error_on_iteration=1))
s.add_engine(CountEngine(None))
s.timesteps = [
0,
]
with self.assertRaises(TypeError):
s.start()
def test_dict_overwrite(self):
"""
Test to ensure that dictionaries and other objects contained in history
are not overwritten by maintaining references to the same objects.
"""
print("Testing...")
network = Network("History Test Network")
network.add_node(HistoryTestNode(x=0, y=0, name="Test Node"))
s = Simulator()
s.network = network
s.timesteps = ['a', 'b', 'c']
s.start()
assert s.network.nodes[0]._history['property_dict'] == [{'test': 'a'}, {'test': 'b'}, {'test': 'c'}]
def test_engine_stopping_iteration(self):
""" Test an engine terminating iteration
The engine must raise a `StopIteration` exception.
"""
s = Simulator(max_iterations=5)
s.network = Network("Iteration test network")
stopper_engine = StopperEngine(None, stop_on_iteration=2)
s.add_engine(stopper_engine)
engine = CountEngine(None)
s.add_engine(engine)
s.timesteps = [0, ]
s.start()
assert engine.iteration == 1
assert engine.run_count == 1
assert stopper_engine.iteration == 2
def test_engine_stopping_iteration(self):
""" Test an engine terminating iteration
The engine must raise a `StopIteration` exception.
"""
s = Simulator(max_iterations=5)
s.network = Network("Iteration test network")
stopper_engine = StopperEngine(None, stop_on_iteration=2)
s.add_engine(stopper_engine)
engine = CountEngine(None)
s.add_engine(engine)
s.timesteps = [
0,
]
s.start()
assert engine.iteration == 1
assert engine.run_count == 1
assert stopper_engine.iteration == 2
def test_dict_overwrite(self):
"""
Test to ensure that dictionaries and other objects contained in history
are not overwritten by maintaining references to the same objects.
"""
print("Testing...")
network = Network("History Test Network")
network.add_node(HistoryTestNode(x=0, y=0, name="Test Node"))
s = Simulator()
s.network = network
s.timesteps = ['a', 'b', 'c']
s.start()
assert s.network.nodes[0]._history['property_dict'] == [{
'test': 'a'
}, {
'test': 'b'
}, {
'test': 'c'
}]
link4._max_flow = {0: 220.0, 1: 250.0, 2: 200.0, 3: 230.0, 4: 240.0, 5: 250.0}
link5._max_flow = {0: 30.0, 1: 40.0, 2: 20.0, 3: 30.0, 4: 30.0, 5: 10.0}
# Define network
network = WaterResourcesSystem(name='Priority based')
network.add_nodes(SR, IRR, URB, J1, In, Out)
network.add_links(link1, link2, link3, link4, link5)
# Run simulation
simulation = Simulator()
simulation.set_timesteps(timesteps)
simulation.network = network
engine = PriorityBased(network)
simulation.add_engine(engine)
simulation.start()
import seaborn
import matplotlib.pyplot as plt
plt.figure(1)
plt.subplot(2, 5, 1)
plt.plot(simulation.network.nodes[0]._history['S'])
plt.title('SR storage')
l3._upper_flow = flow_upper_matrix['l3'] l3._cost=flow_cost_matrix['l3'] l4 = RiverSection(name="l4", start_node=jn1, end_node=endpt) l4._flow_multiplier = flow_mult_matrix["l4"] l4._lower_flow = flow_lower_matrix['l4'] l4._upper_flow = flow_upper_matrix['l4'] l4._cost=flow_cost_matrix['l4'] #When adding these links to the network, the network's nodes will be updated also #with the link added to the starting node's 'out links' and the ending node's 'in links' n.add_links(l1, l2, l3, l4) #Set the network on the simulator s.network = n #Create an instance of the pyomo allocator engine. allocator = PyomoAllocation(n) #add the engine to the simulator. Multiple engines can be added here. The #engines will be run sequentially based on the order they were added to the #simulator s.add_engine(allocator) #start the simulator s.start() total_deficit = 0
'oct': 100.0,
'nov': 100.0,
'dec': 100.0,
}
# Network
network = ReservoirSystem(name="Allocation in a river system")
network.add_nodes(J1,J2,J3,J4,J5,J6,J7,U1,F1,F2,F3,F4,E1)
network.add_links(J1_J2,J2_J3,J2_J4,J3_U1,J3_F4,J4_J5,J5_J6,J6_J7,J7_E1,J5_F1,J6_F2,J7_F3
)
network.timestep = 86400 * 30 # one month
# Simulation
simulation = Simulator()
simulation.set_timesteps(timesteps)
simulation.network = network
engine = SimpleRouting(network)
simulation.add_engine(engine)
simulation.start()
for node in simulation.network.nodes:
print("%s: %s"%(node.name, node._history['inflow'][0]))
simulation.network.plot('inflow')
#Citrus farms and vegetable farms are demand nodes. They use the water supplied
#by the reservoir.
irr1 = CitrusFarm(x=1, y=2, name="I1")
irr2 = CitrusFarm(x=10, y=20, name="I2")
irr3 = VegetableFarm(x=100, y=200, name="I3")
n.add_nodes(sr1, irr1, irr2, irr3)
#Create some links
n.add_link(RiverSection(name="rs1", start_node=sr1, end_node=irr1))
n.add_link(RiverSection(name="rs2", start_node=sr1, end_node=irr2))
n.add_link(RiverSection(name="rs3", start_node=sr1, end_node=irr3))
#Set the simulator's network to this network.
s.network = n
#Add some institutions (loosely based on the Jordan project)
mow = WaterDepartment("Jordan Ministry of Water")
mow.add_nodes(sr1)
jva = IrrigationDecisionMaker("Jordan Valley Authority")
jva.add_nodes(irr1, irr2, irr3)
n.add_institutions(mow, jva)
#Create an instance of the deficit allocation engine.
allocator = DeficitAllocation(n)
#add the engine to the simulator
s.add_engine(allocator)
def run_simulation(diversion_pos, discharge_data, draw=False, queue=None):
"""Run the simulation based on a given position of diversion nodes.
A fixed river network structure is assumed here.
N1
|
N2 N4
| |
N3 N5
\ /
N6
|
N7 N9
| |
N8 N10
| /
N11
|
N12
"""
N1 = RiverNode(x=0, y=7, name='N1')
N1.dQdx = copy.deepcopy(discharge_data['N1'])
N2 = RiverNode(x=0, y=6, name='N2')
N2.dQdx = copy.deepcopy(discharge_data['N2'])
N3 = RiverNode(x=0, y=5, name='N3')
N3.dQdx = copy.deepcopy(discharge_data['N3'])
N4 = RiverNode(x=2, y=6, name='N4')
N4.dQdx = copy.deepcopy(discharge_data['N4'])
N5 = RiverNode(x=2, y=5, name='N5')
N5.dQdx = copy.deepcopy(discharge_data['N5'])
N6 = RiverNode(x=1, y=4, name='N6')
N6.dQdx = copy.deepcopy(discharge_data['N6'])
N7 = RiverNode(x=1, y=3, name='N7')
N7.dQdx = copy.deepcopy(discharge_data['N7'])
N8 = RiverNode(x=1, y=2, name='N8')
N8.dQdx = copy.deepcopy(discharge_data['N8'])
N9 = RiverNode(x=3, y=3, name='N9')
N9.dQdx = copy.deepcopy(discharge_data['N9'])
N10 = RiverNode(x=3, y=2, name='N10')
N10.dQdx = copy.deepcopy(discharge_data['N10'])
N11 = RiverNode(x=2, y=1, name='N11')
N11.dQdx = copy.deepcopy(discharge_data['N11'])
N12 = RiverNode(x=2, y=0, name='N12')
N12.dQdx = copy.deepcopy(discharge_data['N12'])
node_dict = {
0: N1,
1: N2,
2: N3,
3: N4,
4: N5,
5: N6,
6: N7,
7: N8,
8: N9,
9: N10,
10: N11,
11: N12
}
# Add a diversion node based on the position parameter
div_node = Diversion(x=node_dict[diversion_pos].x,
y=node_dict[diversion_pos].y,
name='Diversion')
div_node.dQdx = node_dict[diversion_pos].dQdx
div_node.demand = 0.5
node_dict[diversion_pos] = div_node
L1 = GenericLink(start_node=node_dict[0], end_node=node_dict[1], name='L1')
L2 = GenericLink(start_node=node_dict[1], end_node=node_dict[2], name='L2')
L3 = GenericLink(start_node=node_dict[2], end_node=node_dict[5], name='L3')
L4 = GenericLink(start_node=node_dict[3], end_node=node_dict[4], name='L4')
L5 = GenericLink(start_node=node_dict[4], end_node=node_dict[5], name='L5')
L6 = GenericLink(start_node=node_dict[5], end_node=node_dict[6], name='L6')
L7 = GenericLink(start_node=node_dict[6], end_node=node_dict[7], name='L7')
L8 = GenericLink(start_node=node_dict[7],
end_node=node_dict[10],
name='L8')
L9 = GenericLink(start_node=node_dict[8], end_node=node_dict[9], name='L9')
L10 = GenericLink(start_node=node_dict[9],
end_node=node_dict[10],
name='L10')
L11 = GenericLink(start_node=node_dict[10],
end_node=node_dict[11],
name='L11')
river_network = RiverNetwork(name='River network with diversion')
river_network.add_nodes(*node_dict.values())
river_network.add_links(L1, L2, L3, L4, L5, L6, L7, L8, L9, L10, L11)
if draw:
river_network.draw(block=False)
routing = Routing(river_network)
simulation = Simulator()
simulation.network = river_network
simulation.add_engine(routing)
simulation.set_timesteps([1])
simulation.start()
if queue is None:
return simulation.network.discharge
else:
queue.put(simulation.network.discharge)