nrel.hive.dispatcher.instruction_generator.instruction_generator_ops

Module Contents

Classes

InstructionGenerationResult

Typed version of namedtuple.

Functions

generate_instructions(→ InstructionGenerationResult)

applies a set of InstructionGenerators to the SimulationState;

valid_station_for_vehicle(...)

only allows vehicles to use stations where the membership is correct

instruct_vehicles_to_dispatch_to_station(...)

a helper function to set n vehicles to charge at a station

get_nearest_valid_station_distance(...)

a helper function to find the distance between a vehicle and the closest valid station

Attributes

log

i_map

nrel.hive.dispatcher.instruction_generator.instruction_generator_ops.log[source]
nrel.hive.dispatcher.instruction_generator.instruction_generator_ops.i_map: immutables.Map[nrel.hive.dispatcher.instruction.instructions.VehicleId, List[nrel.hive.dispatcher.instruction.instructions.Instruction]]
class nrel.hive.dispatcher.instruction_generator.instruction_generator_ops.InstructionGenerationResult[source]

Bases: NamedTuple

Typed version of namedtuple.

Usage in Python versions >= 3.6:

class Employee(NamedTuple):
    name: str
    id: int

This is equivalent to:

Employee = collections.namedtuple('Employee', ['name', 'id'])

The resulting class has an extra __annotations__ attribute, giving a dict that maps field names to types. (The field names are also in the _fields attribute, which is part of the namedtuple API.) Alternative equivalent keyword syntax is also accepted:

Employee = NamedTuple('Employee', name=str, id=int)

In Python versions <= 3.5 use:

Employee = NamedTuple('Employee', [('name', str), ('id', int)])
instruction_stack: immutables.Map[nrel.hive.dispatcher.instruction.instructions.VehicleId, nrel.hive.dispatcher.instruction.instructions.Tuple[nrel.hive.dispatcher.instruction.instructions.Instruction, Ellipsis]]
updated_instruction_generators: nrel.hive.dispatcher.instruction.instructions.Tuple[nrel.hive.dispatcher.instruction_generator.instruction_generator.InstructionGenerator, Ellipsis] = ()
apply_instruction_generator(instruction_generator: nrel.hive.dispatcher.instruction_generator.instruction_generator.InstructionGenerator, simulation_state: nrel.hive.dispatcher.instruction.instructions.SimulationState, environment: nrel.hive.dispatcher.instruction.instructions.Environment) → InstructionGenerationResult[source]

generates instructions from one of the InstructionGenerators; each of these instructions are added to the stack for the appropriate vehicle id;

Parameters:

  • instruction_generator – an InstructionGenerator to apply to the SimulationState

  • simulation_state – the current simulation state

  • environment – the simulation environment

Returns:

the updated accumulator

add_driver_instructions(simulation_state, environment)[source]

drivers are given a chance to optionally generate instructions; each of these instructions are added to the stack for the appropriate vehicle id;

Parameters:

  • simulation_state – the current simulation state

  • environment – the simulation environment

Returns:

nrel.hive.dispatcher.instruction_generator.instruction_generator_ops.generate_instructions(instruction_generators: nrel.hive.dispatcher.instruction.instructions.Tuple[nrel.hive.dispatcher.instruction_generator.instruction_generator.InstructionGenerator, Ellipsis], simulation_state: nrel.hive.dispatcher.instruction.instructions.SimulationState, environment: nrel.hive.dispatcher.instruction.instructions.Environment) → InstructionGenerationResult[source]

applies a set of InstructionGenerators to the SimulationState; each time an instruction is generated it gets added to a stack (per vehicle id); the last instruction to be added gets popped and executed; thus, the order of instruction generation matters as the last instruction generated (per vehicle) gets executed;

Parameters:

  • instruction_generators – a tuple of instruction generators

  • simulation_state – the simulation state

  • environment – the simulation environment

Returns:

the instructions generated for this time step (0 to many instructions per vehicle)

nrel.hive.dispatcher.instruction_generator.instruction_generator_ops.valid_station_for_vehicle(vehicle: nrel.hive.model.vehicle.vehicle.Vehicle, env: nrel.hive.dispatcher.instruction.instructions.Environment) → Callable[[nrel.hive.model.station.station.Station], bool][source]

only allows vehicles to use stations where the membership is correct and the fuel type is correct :param vehicle: the vehicle :param env: simulation environment :return: valid station function

nrel.hive.dispatcher.instruction_generator.instruction_generator_ops.instruct_vehicles_to_dispatch_to_station(n: int, max_search_radius_km: float, vehicles: nrel.hive.dispatcher.instruction.instructions.Tuple[nrel.hive.model.vehicle.vehicle.Vehicle, Ellipsis], simulation_state: nrel.hive.dispatcher.instruction.instructions.SimulationState, environment: nrel.hive.dispatcher.instruction.instructions.Environment, target_soc: nrel.hive.util.units.Ratio, charging_search_type: nrel.hive.dispatcher.instruction_generator.charging_search_type.ChargingSearchType) → nrel.hive.dispatcher.instruction.instructions.Tuple[nrel.hive.dispatcher.instruction.instructions.Instruction, Ellipsis][source]

a helper function to set n vehicles to charge at a station

Parameters:

  • n – how many vehicles to charge at the base

  • max_search_radius_km – the max kilometers to search for a station

  • vehicles – the list of vehicles to consider

  • simulation_state – the simulation state

  • environment – the simulation environment

  • target_soc – when ranking alternatives, use this target SoC value

  • charging_search_type – the type of search to conduct

Returns:

instructions for vehicles to charge at stations

nrel.hive.dispatcher.instruction_generator.instruction_generator_ops.get_nearest_valid_station_distance(max_search_radius_km: float, vehicle: nrel.hive.model.vehicle.vehicle.Vehicle, geoid: nrel.hive.util.typealiases.GeoId, simulation_state: nrel.hive.dispatcher.instruction.instructions.SimulationState, environment: nrel.hive.dispatcher.instruction.instructions.Environment, target_soc: nrel.hive.util.units.Ratio, charging_search_type: nrel.hive.dispatcher.instruction_generator.charging_search_type.ChargingSearchType) → nrel.hive.util.units.Kilometers[source]

a helper function to find the distance between a vehicle and the closest valid station

Parameters:

  • max_search_radius_km – the max kilometers to search for a station

  • vehicle – the vehicle to consider

  • geoid – the geoid of the origin

  • simulation_state – the simulation state

  • environment – the simulation environment

  • target_soc – when ranking alternatives, use this target SoC value

  • charging_search_type – the type of search to conduct

Returns:

the distance in km to the nearest valid station