def test_timestep_after(self):
sos_model = SosModel('test')
sos_model.timesteps = [2010, 2011, 2012]
assert sos_model.timestep_after(2010) == 2011
assert sos_model.timestep_after(2011) == 2012
assert sos_model.timestep_after(2012) is None
assert sos_model.timestep_after(2013) is None
def test_timestep_before(self):
sos_model = SosModel('test')
sos_model.timesteps = [2010, 2011, 2012]
assert sos_model.timestep_before(2010) is None
assert sos_model.timestep_before(2011) == 2010
assert sos_model.timestep_before(2012) == 2011
assert sos_model.timestep_before(2013) is None
def test_data_not_present(self, sos_model_dict, sector_model):
"""Raise a NotImplementedError if an input is defined but no dependency links
it to a data source
"""
sos_model_dict['scenario_dependencies'] = []
sos_model_dict['model_dependencies'] = []
with raises(NotImplementedError):
SosModel.from_dict(sos_model_dict, [sector_model])
def test_scenario_model_not_provided(self, sos_model_dict, sector_model,
economic_model):
"""Error on scenario not provided
"""
with raises(SmifDataMismatchError) as ex:
SosModel.from_dict(sos_model_dict, [sector_model, economic_model])
assert "SectorModel or ScenarioModel source `climate` required by " + \
"dependency `climate (precipitation) - water_supply (precipitation)` " + \
"was not provided by the builder" in str(ex.value)
def test_scenario_variant_not_present(self, sos_model_dict, scenario_model,
economic_model):
"""Error on sector model not provided
"""
with raises(SmifDataMismatchError) as ex:
SosModel.from_dict(sos_model_dict,
[scenario_model, economic_model])
assert "SectorModel or ScenarioModel sink `water_supply` required " + \
"by dependency `economic_model (gva) - water_supply (rGVA)` " + \
"was not provided by the builder" in str(ex.value)
def test_get_model_sets(self, get_sector_model):
regions = Mock()
regions.name = 'test_regions'
intervals = Mock()
intervals.name = 'test_intervals'
elec_scenario = ScenarioModel('scenario')
elec_scenario.add_output('output', regions, intervals, 'unit')
SectorModel = get_sector_model
energy_model = SectorModel('model')
energy_model.add_input('input', regions, intervals, 'unit')
energy_model.add_dependency(elec_scenario, 'output', 'input')
sos_model = SosModel('energy_sos_model')
sos_model.add_model(energy_model)
sos_model.add_model(elec_scenario)
sos_model.check_dependencies()
actual = sos_model._get_model_sets_in_run_order()
expected = ['scenario', 'model']
for model, name in zip(actual, expected):
assert model.name == name
def sos_model(sector_model, scenario_model, economic_model):
"""SosModel with one scenario and one sector model
"""
model = SosModel('test_sos_model')
model.add_model(scenario_model)
model.add_model(economic_model)
model.add_model(sector_model)
model.add_dependency(scenario_model, 'precipitation', sector_model,
'precipitation')
model.add_dependency(economic_model, 'gva', sector_model, 'rGVA')
return model
def test_simplest_case(self, get_scenario):
"""One scenario only
"""
elec_scenario = get_scenario
sos_model = SosModel('simple')
sos_model.add_model(elec_scenario)
actual = sos_model.simulate(2010)
expected = {
'electricity_demand_scenario': {
'electricity_demand_output': np.array([[123]])
}
}
assert actual == expected
def test_hanging_inputs(self, get_sector_model):
"""
sos_model_high
sos_model_lo
-> em
"""
SectorModel = get_sector_model
energy_model = SectorModel('energy_sector_model')
input_metadata = {
'name': 'electricity_demand_input',
'spatial_resolution': Mock(),
'temporal_resolution': Mock(),
'units': 'unit'
}
energy_model._inputs = MetadataSet([input_metadata])
sos_model_lo = SosModel('lower')
sos_model_lo.add_model(energy_model)
expected = Metadata(input_metadata['name'],
input_metadata['spatial_resolution'],
input_metadata['temporal_resolution'],
input_metadata['units'])
assert energy_model.free_inputs.names == ['electricity_demand_input']
assert sos_model_lo.free_inputs.names == ['electricity_demand_input']
sos_model_high = SosModel('higher')
sos_model_high.add_model(sos_model_lo)
actual = sos_model_high.free_inputs['electricity_demand_input']
assert actual == expected
def test_simple_graph(self, get_sector_model):
regions = Mock()
regions.name = 'test_regions'
intervals = Mock()
intervals.name = 'test_intervals'
SectorModel = get_sector_model
elec_scenario = ScenarioModel('scenario')
elec_scenario.add_output('output', regions, intervals, 'unit')
energy_model = SectorModel('model')
energy_model.add_input('input', regions, intervals, 'unit')
energy_model.add_dependency(elec_scenario, 'output', 'input')
sos_model = SosModel('energy_sos_model')
sos_model.add_model(energy_model)
sos_model.add_model(elec_scenario)
# Builds the dependency graph
sos_model.check_dependencies()
graph = sos_model.dependency_graph
assert energy_model in graph
assert elec_scenario in graph
assert list(graph.edges()) == [(elec_scenario, energy_model)]
def test_undefined_unit_conversion(self, sos_model_dict, sector_model,
scenario_model, economic_model):
"""Error on invalid dependency
"""
sector_model.inputs['precipitation'] = Spec(name='precipitation',
dims=['LSOA'],
coords={'LSOA': [1, 2, 3]},
dtype='float',
unit='incompatible')
with raises(ValueError) as ex:
SosModel.from_dict(sos_model_dict,
[sector_model, scenario_model, economic_model])
assert "ml!=incompatible" in str(ex.value)
def test_construct(self, sos_model_dict, scenario_model, sector_model,
economic_model):
"""Constructing from config of the form::
{
'name': 'sos_model_name',
'description': 'friendly description of the sos model',
'dependencies': [
{
'source': str (Model.name),
'source_output': str (Metadata.name),
'sink': str (Model.name),
'sink_output': str (Metadata.name)
}
]
}
With list of child SectorModel/ScenarioModel instances passed in alongside.
"""
sos_model = SosModel.from_dict(
sos_model_dict, [scenario_model, sector_model, economic_model])
assert isinstance(sos_model, SosModel)
assert list(sos_model.scenario_models) == [scenario_model]
assert isinstance(sos_model.get_model('climate'), ScenarioModel)
assert sos_model.sector_models == [sector_model, economic_model] or \
sos_model.sector_models == [economic_model, sector_model]
assert isinstance(sos_model.get_model('economic_model'), SectorModel)
assert isinstance(sos_model.get_model('water_supply'), SectorModel)
def test_loop(self, get_energy_sector_model, get_water_sector_model):
"""Fails because no functionality to deal with loops
"""
energy_model = get_energy_sector_model
water_model = get_water_sector_model
sos_model = SosModel('energy_water_model')
water_model.add_dependency(energy_model, 'fluffiness', 'fluffyness')
energy_model.add_dependency(water_model, 'electricity_demand',
'electricity_demand_input')
sos_model.add_model(water_model)
sos_model.add_model(energy_model)
assert energy_model.model_inputs.names == ['electricity_demand_input']
assert water_model.model_inputs.names == ['fluffyness']
assert sos_model.model_inputs.names == []
assert energy_model.free_inputs.names == []
assert water_model.free_inputs.names == []
assert sos_model.free_inputs.names == []
sos_model.check_dependencies()
graph = sos_model.dependency_graph
assert (water_model, energy_model) in graph.edges()
assert (energy_model, water_model) in graph.edges()
modelset = ModelSet([water_model, energy_model], sos_model)
actual = modelset.guess_results(water_model, 2010, {})
expected = {'electricity_demand': np.array([1.])}
# assert actual == expected
sos_model.max_iterations = 100
results = sos_model.simulate(2010)
expected = np.array([[0.13488114]], dtype=np.float)
actual = results['energy_sector_model']['fluffiness']
np.testing.assert_allclose(actual, expected, rtol=1e-5)
expected = np.array([[0.16469004]], dtype=np.float)
actual = results['water_supply_model']['electricity_demand']
np.testing.assert_allclose(actual, expected, rtol=1e-5)
def test_parameter_passing_into_models(self, get_empty_sector_model):
"""Tests that policy values for global parameters are passed to all
models, and policy values only passed into the intended models.
"""
sos_model_param = {
'name': 'sos_model_param',
'description': 'A global parameter passed to all contained models',
'absolute_range': (0, 100),
'suggested_range': (3, 10),
'default_value': 3,
'units': '%'
}
sos_model = SosModel('global')
sos_model.add_parameter(sos_model_param)
sector_model = get_empty_sector_model('source_model')
# Patch the sector model so that it returns the calling arguments
sector_model.simulate = lambda _, y: {'sm1': y}
sos_model.add_model(sector_model)
sector_model.add_parameter({
'name': 'sector_model_param',
'description': 'Some meaningful text',
'absolute_range': (0, 100),
'suggested_range': (3, 10),
'default_value': 3,
'units': '%'
})
sector_model_2 = get_empty_sector_model('another')
sector_model_2.simulate = lambda _, y: {'sm2': y}
sos_model.add_model(sector_model_2)
data = {
'global': {
'sos_model_param': 999
},
'source_model': {
'sector_model_param': 123
}
}
assert sos_model.simulate(2010, data) == \
{'sm1': {'sector_model_param': 123, 'sos_model_param': 999},
'sm2': {'sos_model_param': 999}}
def test_loop(self, get_energy_sector_model, get_water_sector_model):
"""Fails because no functionality to deal with loops
"""
energy_model = get_energy_sector_model
water_model = get_water_sector_model
sos_model = SosModel('energy_water_model')
water_model.add_dependency(energy_model, 'fluffiness', 'fluffyness')
energy_model.add_dependency(water_model, 'electricity_demand',
'electricity_demand_input')
sos_model.add_model(water_model)
sos_model.add_model(energy_model)
assert energy_model.inputs.names == ['electricity_demand_input']
assert water_model.inputs.names == ['fluffyness']
assert sos_model.inputs.names == []
assert energy_model.free_inputs.names == []
assert water_model.free_inputs.names == []
assert sos_model.free_inputs.names == []
sos_model.check_dependencies()
graph = sos_model.dependency_graph
assert (water_model, energy_model) in graph.edges()
assert (energy_model, water_model) in graph.edges()
sos_model.max_iterations = 100
data_handle = get_data_handle(sos_model)
results = sos_model.simulate(data_handle)
expected = np.array([[0.13488114]], dtype=np.float)
actual = results.get_results('fluffiness', model_name='energy_sector_model',
modelset_iteration=35)
np.testing.assert_allclose(actual, expected, rtol=1e-5)
expected = np.array([[0.16469004]], dtype=np.float)
actual = results.get_results('electricity_demand', model_name='water_supply_model',
modelset_iteration=35)
np.testing.assert_allclose(actual, expected, rtol=1e-5)
def test_add_parameters(self, get_empty_sector_model):
sos_model = SosModel('global')
sos_model_param = {
'name': 'sos_model_param',
'description': 'A global parameter passed to all contained models',
'absolute_range': (0, 100),
'suggested_range': (3, 10),
'default_value': 3,
'units': '%'
}
sos_model.add_parameter(sos_model_param)
expected = sos_model_param
assert sos_model.parameters['sos_model_param'].as_dict() == expected
assert sos_model.parameters.names == ['sos_model_param']
sector_model = get_empty_sector_model('source_model')
sector_model.add_parameter({
'name': 'sector_model_param',
'description': 'Required for the sectormodel',
'absolute_range': (0, 100),
'suggested_range': (3, 10),
'default_value': 3,
'units': '%'
})
sos_model.add_model(sector_model)
# SosModel contains only its own parameters
assert 'sos_model_param' in sos_model.parameters.names
# SectorModel has its own ParameterList, gettable by param name
assert 'sector_model_param' in sector_model.parameters.names
def get_sos_model_object(get_sector_model_object, get_scenario_model_object):
sos_model = SosModel('test_sos_model')
sector_model = get_sector_model_object
scenario_model = get_scenario_model_object
sos_model.add_model(sector_model)
sos_model.add_model(scenario_model)
sos_model.timesteps = scenario_model.timesteps
sector_model.add_dependency(scenario_model, 'raininess', 'raininess')
return sos_model
def test_simplest_case(self, get_scenario):
"""One scenario only
"""
elec_scenario = get_scenario
sos_model = SosModel('simple')
sos_model.add_model(elec_scenario)
data_handle = get_data_handle(sos_model)
sos_model.simulate(data_handle)
def test_add_dependency(self, empty_sector_model):
"""Add models, connect via dependency
"""
spec = Spec(name='hourly_value',
dims=['hours'],
coords={'hours': range(24)},
dtype='int')
sink_model = copy(empty_sector_model)
sink_model.add_input(spec)
source_model = copy(empty_sector_model)
source_model.add_output(spec)
sos_model = SosModel('test')
sos_model.add_model(source_model)
sos_model.add_model(sink_model)
sos_model.add_dependency(source_model, 'hourly_value', sink_model,
'hourly_value')
def test_get_model_sets(self, get_sector_model):
SectorModel = get_sector_model
elec_scenario = ScenarioModel('scenario')
elec_scenario.add_output('output', Mock(), Mock(), 'unit')
elec_scenario.add_data(np.array([[[123]]]), [2010])
energy_model = SectorModel('model')
energy_model.add_input('input', Mock(), Mock(), 'unit')
energy_model.add_dependency(elec_scenario, 'output', 'input')
sos_model = SosModel('energy_sos_model')
sos_model.add_model(energy_model)
sos_model.add_model(elec_scenario)
sos_model.check_dependencies()
actual = sos_model._get_model_sets_in_run_order()
expected = ['scenario', 'model']
for model, name in zip(actual, expected):
assert model.name == name
def test_topological_sort(self, get_sector_model):
SectorModel = get_sector_model
elec_scenario = ScenarioModel('scenario')
elec_scenario.add_output('output', Mock(), Mock(), 'unit')
elec_scenario.add_data(np.array([[[123]]]), [2010])
energy_model = SectorModel('model')
energy_model.add_input('input', Mock(), Mock(), 'unit')
energy_model.add_dependency(elec_scenario, 'output', 'input')
sos_model = SosModel('energy_sos_model')
sos_model.add_model(energy_model)
sos_model.add_model(elec_scenario)
sos_model.check_dependencies()
graph = sos_model.dependency_graph
actual = networkx.topological_sort(graph, reverse=False)
assert actual == [elec_scenario, energy_model]
def test_simulate_data_not_present(self, get_sector_model):
SectorModel = get_sector_model
"""Raise a NotImplementedError if an input is defined but no dependency links
it to a data source
"""
sos_model = SosModel('test')
model = SectorModel('test_model')
model.add_input('input', Mock(), Mock(), 'units')
sos_model.add_model(model)
data_handle = get_data_handle(sos_model)
with raises(NotImplementedError):
sos_model.simulate(data_handle)
def test_sector_model_one_input(self, get_energy_sector_model,
get_scenario):
elec_scenario = get_scenario
energy_model = get_energy_sector_model
energy_model.add_dependency(elec_scenario,
'electricity_demand_output',
'electricity_demand_input')
sos_model = SosModel('blobby')
sos_model.add_model(elec_scenario)
sos_model.add_model(energy_model)
data_handle = get_data_handle(sos_model)
results = sos_model.simulate(data_handle)
expected = np.array([[100.737]])
actual = results.get_results('fluffiness', 'energy_sector_model')
np.testing.assert_allclose(actual, expected, rtol=1e-5)
def test_topological_sort(self, get_sector_model):
regions = Mock()
regions.name = 'test_regions'
intervals = Mock()
intervals.name = 'test_intervals'
SectorModel = get_sector_model
elec_scenario = ScenarioModel('scenario')
elec_scenario.add_output('output', regions, intervals, 'unit')
energy_model = SectorModel('model')
energy_model.add_input('input', regions, intervals, 'unit')
energy_model.add_dependency(elec_scenario, 'output', 'input')
sos_model = SosModel('energy_sos_model')
sos_model.add_model(energy_model)
sos_model.add_model(elec_scenario)
sos_model.check_dependencies()
graph = sos_model.dependency_graph
actual = list(networkx.topological_sort(graph))
assert actual == [elec_scenario, energy_model]
def test_simple_graph(self, get_sector_model):
SectorModel = get_sector_model
elec_scenario = ScenarioModel('scenario')
elec_scenario.add_output('output', Mock(), Mock(), 'unit')
elec_scenario.add_data(np.array([[[123]]]), [2010])
energy_model = SectorModel('model')
energy_model.add_input('input', Mock(), Mock(), 'unit')
energy_model.add_dependency(elec_scenario, 'output', 'input')
sos_model = SosModel('energy_sos_model')
sos_model.add_model(energy_model)
sos_model.add_model(elec_scenario)
# Builds the dependency graph
sos_model.check_dependencies()
graph = sos_model.dependency_graph
assert energy_model in graph
assert elec_scenario in graph
assert graph.edges() == [(elec_scenario, energy_model)]
def test_add_parameters(self, get_empty_sector_model):
sos_model_param = {
'name': 'sos_model_param',
'description': 'A global parameter passed to all contained models',
'absolute_range': (0, 100),
'suggested_range': (3, 10),
'default_value': 3,
'units': '%'
}
sos_model = SosModel('global')
sos_model.add_parameter(sos_model_param)
expected = dict(sos_model_param, **{'parent': sos_model})
assert sos_model.parameters == {
'global': {
'sos_model_param': expected
}
}
assert sos_model.parameters['global'].names == ['sos_model_param']
sector_model = get_empty_sector_model('source_model')
sector_model.add_parameter({
'name': 'sector_model_param',
'description': 'Required for the sectormodel',
'absolute_range': (0, 100),
'suggested_range': (3, 10),
'default_value': 3,
'units': '%'
})
sos_model.add_model(sector_model)
# SosModel contains ParameterList objects in a nested dict by model name
assert 'global' in sos_model.parameters
assert 'sos_model_param' in sos_model.parameters['global'].names
# SosModel parameter attribute holds references to contained
# model parameters keyed by model name
assert 'source_model' in sos_model.parameters
assert 'sector_model_param' in sos_model.parameters['source_model']
# SectorModel has a ParameterList, gettable by param name
assert 'sector_model_param' in sector_model.parameters.names
assert 'source_model' in sos_model.parameters
assert 'sector_model_param' in sos_model.parameters['source_model']
def test_dependencies_fields(self, sos_model_dict, scenario_model,
sector_model, economic_model):
"""Compose dependencies from scenario- and model- fields
"""
sos_model_dict['scenario_dependencies'] = [{
'source': 'climate',
'source_output': 'precipitation',
'sink_input': 'precipitation',
'sink': 'water_supply',
'timestep': 'CURRENT'
}, {
'source': 'climate',
'source_output': 'reservoir_level',
'sink_input': 'reservoir_level',
'sink': 'water_supply',
'timestep': 'CURRENT'
}]
sos_model_dict['model_dependencies'] = [{
'source': 'economic_model',
'source_output': 'gva',
'sink_input': 'rGVA',
'sink': 'water_supply',
'timestep': 'CURRENT'
}, {
'source': 'water_supply',
'source_output': 'reservoir_level',
'sink_input': 'reservoir_level',
'sink': 'water_supply',
'timestep': 'PREVIOUS'
}]
sos_model = SosModel.from_dict(
sos_model_dict, [scenario_model, sector_model, economic_model])
actual = sos_model.as_dict()
TestCase().assertCountEqual(actual['scenario_dependencies'],
sos_model_dict['scenario_dependencies'])
TestCase().assertCountEqual(actual['model_dependencies'],
sos_model_dict['model_dependencies'])
def get_sos_model_with_model_dependency():
sos_model = SosModel('test_sos_model')
ws = WaterSupplySectorModel('water_supply')
ws.inputs = [{
'name': 'raininess',
'spatial_resolution': 'LSOA',
'temporal_resolution': 'annual',
'units': 'ml'
}]
ws.outputs = [{
'name': 'water',
'spatial_resolution': 'LSOA',
'temporal_resolution': 'annual',
'units': 'Ml'
}, {
'name': 'cost',
'spatial_resolution': 'LSOA',
'temporal_resolution': 'annual',
'units': 'million GBP'
}]
ws.interventions = [{
"name": "water_asset_a",
"location": "oxford"
}, {
"name": "water_asset_b",
"location": "oxford"
}, {
"name": "water_asset_c",
"location": "oxford"
}]
sos_model.add_model(ws)
ws2 = WaterSupplySectorModel('water_supply_2')
ws2.inputs = [{
'name': 'water',
'spatial_resolution': 'LSOA',
'temporal_resolution': 'annual',
'units': 'Ml'
}]
ws2.add_dependency(ws, 'water', 'water')
sos_model.add_model(ws2)
return sos_model
def test_add_dependency(self, get_empty_sector_model):
regions = Mock()
regions.name = 'test_regions'
intervals = Mock()
intervals.name = 'test_intervals'
units = 'test_units'
sink_model = get_empty_sector_model('sink_model')
sink_model.add_input('input_name', regions, intervals, units)
source_model = get_empty_sector_model('source_model')
source_model.add_output('output_name', regions, intervals, units)
sink_model.add_dependency(source_model, 'output_name', 'input_name')
sos_model = SosModel('test')
sos_model.add_model(source_model)
sos_model.add_model(sink_model)
def test_sector_model_one_input(self, get_energy_sector_model,
get_scenario):
elec_scenario = get_scenario
energy_model = get_energy_sector_model
energy_model.add_dependency(elec_scenario, 'electricity_demand_output',
'electricity_demand_input')
sos_model = SosModel('blobby')
sos_model.add_model(elec_scenario)
sos_model.add_model(energy_model)
actual = sos_model.simulate(2010)
expected = {
'energy_sector_model': {
'fluffiness': np.array([[100.737]])
},
'electricity_demand_scenario': {
'electricity_demand_output': np.array([[123]])
}
}
assert actual == expected
