def test_functions_available(self):
v = VDF()
self.assertEqual(v.functions_available(), ['bpr'],
'VDF class returning wrong availability')
self.assertEqual(v.apply_vdf, None, 'VDF is missing term')
self.assertEqual(v.apply_derivative, None, 'VDF is missing term')
with self.assertRaises(ValueError):
v.function = 'Cubic'
with self.assertRaises(AttributeError):
v.apply_vdf = isinstance
def test_functions_available(self):
v = VDF()
self.assertEqual(v.functions_available(), ["bpr", "conical"],
"VDF class returning wrong availability")
self.assertEqual(v.apply_vdf, None, "VDF is missing term")
self.assertEqual(v.apply_derivative, None, "VDF is missing term")
with self.assertRaises(ValueError):
v.function = "Cubic"
with self.assertRaises(AttributeError):
v.apply_vdf = isinstance
def __init__(self) -> None:
parameters = Parameters().parameters["assignment"]["equilibrium"]
self.__dict__["rgap_target"] = parameters["rgap"]
self.__dict__["max_iter"] = parameters["maximum_iterations"]
self.__dict__["vdf"] = VDF()
self.__dict__["classes"] = None # type: List[TrafficClass]
self.__dict__["algorithm"] = None # type: str
self.__dict__["vdf_parameters"] = None # type: list
self.__dict__["time_field"] = None # type: str
self.__dict__["capacity_field"] = None # type: str
self.__dict__["assignment"] = None # type: LinearApproximation
self.__dict__["capacity"] = None # type: np.ndarray
self.__dict__["free_flow_tt"] = None # type: np.ndarray
self.__dict__["total_flow"] = None # type: np.ndarray
self.__dict__["congested_time"] = None # type: np.ndarray
self.__dict__["cores"] = None # type: int
def __check_attributes(self, instance, value):
if instance == "rgap_target":
if not isinstance(value, float):
return False, value, "Relative gap needs to be a float"
if isinstance(self.assignment, LinearApproximation):
self.assignment.rgap_target = value
elif instance == "max_iter":
if not isinstance(value, int):
return False, value, "Number of iterations needs to be an integer"
if isinstance(self.assignment, LinearApproximation):
self.assignment.max_iter = value
elif instance == "vdf":
v = value.lower()
if v not in all_vdf_functions:
return False, value, f"Volume-delay function {value} is not available"
value = VDF()
value.function = v
elif instance == "classes":
if isinstance(value, TrafficClass):
value = [value]
elif isinstance(value, list):
for v in value:
if not isinstance(v, TrafficClass):
return False, value, "Traffic classes need to be proper AssignmentClass objects"
else:
raise ValueError("Traffic classes need to be proper AssignmentClass objects")
elif instance == "vdf_parameters":
if not self.__validate_parameters(value):
return False, value, f"Parameter set is not valid: {value} "
elif instance in ["time_field", "capacity_field"]:
if not isinstance(value, str):
return False, value, f"Value for {instance} is not string"
elif instance == "cores":
if not isinstance(value, int):
return False, value, f"Value for {instance} is not integer"
elif instance == "save_path_files":
if not isinstance(value, bool):
return False, value, f"Value for {instance} is not boolean"
if instance not in self.__dict__:
return False, value, f"trafficAssignment class does not have property {instance}"
return True, value, ""
def __init__(self) -> None:
parameters = Parameters().parameters["assignment"]["equilibrium"]
self.__dict__["rgap_target"] = parameters["rgap"]
self.__dict__["max_iter"] = parameters["maximum_iterations"]
self.__dict__["vdf"] = VDF()
self.__dict__["classes"] = [] # type: List[TrafficClass]
self.__dict__["algorithm"] = None # type: str
self.__dict__["vdf_parameters"] = None # type: list
self.__dict__["time_field"] = None # type: str
self.__dict__["capacity_field"] = None # type: str
self.__dict__["assignment"] = None # type: LinearApproximation
self.__dict__["capacity"] = None # type: np.ndarray
self.__dict__["free_flow_tt"] = None # type: np.ndarray
self.__dict__["total_flow"] = None # type: np.ndarray
self.__dict__["congested_time"] = None # type: np.ndarray
self.__dict__["cores"] = None # type: int
self.__dict__["procedure_id"] = uuid4().hex
self.__dict__["description"] = ""
self.__dict__["procedure_date"] = str(datetime.today())
self.__dict__["steps_below_needed_to_terminate"] = 1