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Changed constructor of ParameterRegion to take a valuation. 

Use ParameterRegion.create_from_string() to initialize a region from string.
refactoring
Matthias Volk 6 years ago
parent
3606edfa96
commit
3bf516f08e
4 changed files with 84 additions and 13 deletions
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  1. 5
      CHANGELOG.md
  2. 18
      src/pars/pla.cpp
  3. 21
      tests/pars/test_parametric.py
  4. 53
      tests/pars/test_pla.py

5
CHANGELOG.md
View File

@ -4,6 +4,11 @@ Changelog
Version 1.3.x
-------------
### Version 1.3.1 (under development)
- Changed constructor of `ParameterRegion` to take a valuation instead of string.
Use `ParameterRegion.create_from_string()` to create a region from string.
### Version 1.3.0 (2019/01)
Requires storm version >= 1.3.0 and pycarl version >= 2.0.3
- Adaptions to changes in Storm

18
src/pars/pla.cpp
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@ -73,13 +73,23 @@ void define_pla(py::module& m) {
// Region
py::class_<Region, std::shared_ptr<Region>>(m, "ParameterRegion", "Parameter region")
.def("__init__", [](Region &instance, std::string const& regionString, std::set<Region::VariableType> const& variables) -> void {
new (&instance) Region(storm::api::parseRegion<storm::RationalFunction>(regionString, variables));
})
.def("__init__", [](Region &instance, std::map<Region::VariableType, std::pair<Region::CoefficientType, Region::CoefficientType>> valuation) -> void {
Region::Valuation lowerValuation;
Region::Valuation upperValuation;
for (auto const& val : valuation) {
lowerValuation[val.first] = val.second.first;
upperValuation[val.first] = val.second.second;
}
new (&instance) Region(lowerValuation, upperValuation);
}, "Create region from valuation of var -> (lower_bound, upper_bound)", py::arg("valuation"))
.def_static("create_from_string", [](std::string const& regionString, std::set<Region::VariableType> const& variables) -> Region {
return storm::api::parseRegion<storm::RationalFunction>(regionString, variables);
}, "Create region from string", py::arg("region_string"), py::arg("variables"))
.def_property_readonly("area", &Region::area, "Get area")
.def("__str__", &streamToString<Region>)
;
// RegionModelChecker
py::class_<RegionModelChecker, std::shared_ptr<RegionModelChecker>> regionModelChecker(m, "RegionModelChecker", "Region model checker via paramater lifting");
regionModelChecker.def("check_region", &checkRegion, "Check region", py::arg("environment"), py::arg("region"), py::arg("hypothesis") = storm::modelchecker::RegionResultHypothesis::Unknown, py::arg("initialResult") = storm::modelchecker::RegionResult::Unknown, py::arg("sampleVertices") = false)
.def("get_bound", &getBoundAtInit, "Get bound", py::arg("environment"), py::arg("region"), py::arg("maximise")= true)

21
tests/pars/test_parametric.py
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@ -135,3 +135,24 @@ class TestParametric:
model, formula = stormpy.pars.simplify_model(model, formula)
assert model.nr_states == 17
assert model.nr_transitions == 50
def test_region(self):
program = stormpy.parse_prism_program(get_example_path("pdtmc", "brp16_2.pm"))
prop = "P<=0.84 [F s=5 ]"
formulas = stormpy.parse_properties_for_prism_program(prop, program)
model = stormpy.build_parametric_model(program, formulas)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
assert region.area == stormpy.RationalRF(1) / stormpy.RationalRF(25)
for par in parameters:
if par.name == "pL":
pL = par
elif par.name == "pK":
pK = par
else:
assert False
dec = stormpy.RationalRF(100)
region_valuation = {pL: (stormpy.RationalRF(70) / dec, stormpy.RationalRF(90) / dec), pK: (stormpy.RationalRF(75) / dec, stormpy.RationalRF(95) / dec)}
region = stormpy.pars.ParameterRegion(region_valuation)
assert region.area == stormpy.RationalRF(1) / stormpy.RationalRF(25)

53
tests/pars/test_pla.py
View File

@ -21,14 +21,49 @@ class TestPLA:
checker = stormpy.pars.create_region_checker(env, model, formulas[0].raw_formula)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
result = checker.check_region(env, region)
assert result == stormpy.pars.RegionResult.ALLSAT
region = stormpy.pars.ParameterRegion("0.4<=pL<=0.65,0.75<=pK<=0.95", parameters)
result = checker.check_region(env, region, stormpy.pars.RegionResultHypothesis.UNKNOWN,
stormpy.pars.RegionResult.UNKNOWN, True)
region = stormpy.pars.ParameterRegion.create_from_string("0.4<=pL<=0.65,0.75<=pK<=0.95", parameters)
result = checker.check_region(env, region, stormpy.pars.RegionResultHypothesis.UNKNOWN, stormpy.pars.RegionResult.UNKNOWN, True)
assert result == stormpy.pars.RegionResult.EXISTSBOTH
region = stormpy.pars.ParameterRegion("0.1<=pL<=0.73,0.2<=pK<=0.715", parameters)
region = stormpy.pars.ParameterRegion.create_from_string("0.1<=pL<=0.73,0.2<=pK<=0.715", parameters)
result = checker.check_region(env, region)
assert result == stormpy.pars.RegionResult.ALLVIOLATED
def test_pla_region_valuation(self):
program = stormpy.parse_prism_program(get_example_path("pdtmc", "brp16_2.pm"))
prop = "P<=0.84 [F s=5 ]"
formulas = stormpy.parse_properties_for_prism_program(prop, program)
model = stormpy.build_parametric_model(program, formulas)
assert model.nr_states == 613
assert model.nr_transitions == 803
assert model.model_type == stormpy.ModelType.DTMC
assert model.has_parameters
env = stormpy.Environment()
checker = stormpy.pars.create_region_checker(env, model, formulas[0].raw_formula)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
for par in parameters:
if par.name == "pL":
pL = par
elif par.name == "pK":
pK = par
else:
assert False
region_valuation = dict()
region_valuation[pL] = (stormpy.RationalRF(0.7), stormpy.RationalRF(0.9))
region_valuation[pK] = (stormpy.RationalRF(0.75), stormpy.RationalRF(0.95))
region = stormpy.pars.ParameterRegion(region_valuation)
result = checker.check_region(env, region)
assert result == stormpy.pars.RegionResult.ALLSAT
region_valuation[pL] = (stormpy.RationalRF(0.4), stormpy.RationalRF(0.65))
region = stormpy.pars.ParameterRegion(region_valuation)
result = checker.check_region(env, region, stormpy.pars.RegionResultHypothesis.UNKNOWN, stormpy.pars.RegionResult.UNKNOWN, True)
assert result == stormpy.pars.RegionResult.EXISTSBOTH
region_valuation[pK] = (stormpy.RationalRF(0.2), stormpy.RationalRF(0.715))
region_valuation[pL] = (stormpy.RationalRF(0.1), stormpy.RationalRF(0.73))
region = stormpy.pars.ParameterRegion(region_valuation)
result = checker.check_region(env, region)
assert result == stormpy.pars.RegionResult.ALLVIOLATED
@ -42,7 +77,7 @@ class TestPLA:
checker = stormpy.pars.create_region_checker(env, model, formulas[0].raw_formula)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
result = checker.get_bound(env, region, True)
assert math.isclose(float(result.constant_part()), 0.8369631383670559, rel_tol=1e-6)
result_vec = checker.get_bound_all_states(env, region, True)
@ -60,7 +95,7 @@ class TestPLA:
checker.specify(env, model, formulas[0].raw_formula)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
result = checker.get_bound(env, region, True)
assert math.isclose(float(result.constant_part()), 0.8369631383670559, rel_tol=1e-6)
@ -75,7 +110,7 @@ class TestPLA:
checker.specify(env, model, formulas[0].raw_formula, allow_model_simplification=False)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
result = checker.get_bound(env, region, True)
assert math.isclose(float(result.constant_part()), 0.836963056082918, rel_tol=1e-6)
@ -90,7 +125,7 @@ class TestPLA:
checker.specify(env, model, formulas[0].raw_formula, allow_model_simplification=False)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
result_vec = checker.get_bound_all_states(env, region, True)
assert len(result_vec.get_values()) == model.nr_states
assert math.isclose(result_vec.at(model.initial_states[0]), 0.836963056082918, rel_tol=1e-6)
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