146 lines
6.0 KiB
Python
146 lines
6.0 KiB
Python
import os
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import math
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import hypothesis.strategies as st
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from hypothesis import Phase, given, settings
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from parameterized import parameterized
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from collections.abc import Callable
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from typing import Any
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from opendbc.car import DT_CTRL, CanData, gen_empty_fingerprint, structs
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from opendbc.car.car_helpers import interfaces
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from opendbc.car.fingerprints import all_known_cars
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from opendbc.car.fw_versions import FW_VERSIONS, FW_QUERY_CONFIGS
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from opendbc.car.interfaces import get_interface_attr
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from opendbc.car.mock.values import CAR as MOCK
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DrawType = Callable[[st.SearchStrategy], Any]
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ALL_ECUS = {ecu for ecus in FW_VERSIONS.values() for ecu in ecus.keys()}
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ALL_ECUS |= {ecu for config in FW_QUERY_CONFIGS.values() for ecu in config.extra_ecus}
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ALL_REQUESTS = {tuple(r.request) for config in FW_QUERY_CONFIGS.values() for r in config.requests}
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MAX_EXAMPLES = int(os.environ.get('MAX_EXAMPLES', '15'))
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def get_fuzzy_car_interface_args(draw: DrawType) -> dict:
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# Fuzzy CAN fingerprints and FW versions to test more states of the CarInterface
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fingerprint_strategy = st.fixed_dictionaries({key: st.dictionaries(st.integers(min_value=0, max_value=0x800),
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st.integers(min_value=0, max_value=64)) for key in
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gen_empty_fingerprint()})
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# only pick from possible ecus to reduce search space
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car_fw_strategy = st.lists(st.sampled_from(sorted(ALL_ECUS)))
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params_strategy = st.fixed_dictionaries({
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'fingerprints': fingerprint_strategy,
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'car_fw': car_fw_strategy,
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'experimental_long': st.booleans(),
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})
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params: dict = draw(params_strategy)
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params['car_fw'] = [structs.CarParams.CarFw(ecu=fw[0], address=fw[1], subAddress=fw[2] or 0,
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request=draw(st.sampled_from(sorted(ALL_REQUESTS))))
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for fw in params['car_fw']]
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return params
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class TestCarInterfaces:
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# FIXME: Due to the lists used in carParams, Phase.target is very slow and will cause
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# many generated examples to overrun when max_examples > ~20, don't use it
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@parameterized.expand([(car,) for car in sorted(all_known_cars())] + [MOCK.MOCK])
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@settings(max_examples=MAX_EXAMPLES, deadline=None,
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phases=(Phase.reuse, Phase.generate, Phase.shrink))
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@given(data=st.data())
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def test_car_interfaces(self, car_name, data):
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CarInterface, CarController, CarState, RadarInterface = interfaces[car_name]
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args = get_fuzzy_car_interface_args(data.draw)
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car_params = CarInterface.get_params(car_name, args['fingerprints'], args['car_fw'],
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experimental_long=args['experimental_long'], docs=False)
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car_interface = CarInterface(car_params, CarController, CarState)
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assert car_params
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assert car_interface
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assert car_params.mass > 1
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assert car_params.wheelbase > 0
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# centerToFront is center of gravity to front wheels, assert a reasonable range
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assert car_params.wheelbase * 0.3 < car_params.centerToFront < car_params.wheelbase * 0.7
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assert car_params.maxLateralAccel > 0
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# Longitudinal sanity checks
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assert len(car_params.longitudinalTuning.kpV) == len(car_params.longitudinalTuning.kpBP)
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assert len(car_params.longitudinalTuning.kiV) == len(car_params.longitudinalTuning.kiBP)
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# Lateral sanity checks
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if car_params.steerControlType != structs.CarParams.SteerControlType.angle:
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tune = car_params.lateralTuning
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if tune.which() == 'pid':
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if car_name != MOCK.MOCK:
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assert not math.isnan(tune.pid.kf) and tune.pid.kf > 0
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assert len(tune.pid.kpV) > 0 and len(tune.pid.kpV) == len(tune.pid.kpBP)
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assert len(tune.pid.kiV) > 0 and len(tune.pid.kiV) == len(tune.pid.kiBP)
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elif tune.which() == 'torque':
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assert not math.isnan(tune.torque.kf) and tune.torque.kf > 0
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assert not math.isnan(tune.torque.friction) and tune.torque.friction > 0
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# Run car interface
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# TODO: use hypothesis to generate random messages
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now_nanos = 0
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CC = structs.CarControl().as_reader()
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for _ in range(10):
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car_interface.update([])
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car_interface.apply(CC, now_nanos)
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now_nanos += DT_CTRL * 1e9 # 10 ms
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CC = structs.CarControl()
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CC.enabled = True
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CC = CC.as_reader()
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for _ in range(10):
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car_interface.update([])
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car_interface.apply(CC, now_nanos)
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now_nanos += DT_CTRL * 1e9 # 10ms
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# Test radar interface
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radar_interface = RadarInterface(car_params)
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assert radar_interface
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# Run radar interface once
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radar_interface.update([])
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if not car_params.radarUnavailable and radar_interface.rcp is not None and \
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hasattr(radar_interface, '_update') and hasattr(radar_interface, 'trigger_msg'):
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radar_interface._update([radar_interface.trigger_msg])
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# Test radar fault
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if not car_params.radarUnavailable and radar_interface.rcp is not None:
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cans = [(0, [CanData(0, b'', 0) for _ in range(5)])]
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rr = radar_interface.update(cans)
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assert rr is None or len(rr.errors) > 0
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def test_interface_attrs(self):
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"""Asserts basic behavior of interface attribute getter"""
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num_brands = len(get_interface_attr('CAR'))
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assert num_brands >= 12
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# Should return value for all brands when not combining, even if attribute doesn't exist
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ret = get_interface_attr('FAKE_ATTR')
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assert len(ret) == num_brands
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# Make sure we can combine dicts
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ret = get_interface_attr('DBC', combine_brands=True)
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assert len(ret) >= 160
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# We don't support combining non-dicts
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ret = get_interface_attr('CAR', combine_brands=True)
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assert len(ret) == 0
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# If brand has None value, it shouldn't return when ignore_none=True is specified
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none_brands = {b for b, v in get_interface_attr('FINGERPRINTS').items() if v is None}
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assert len(none_brands) >= 1
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ret = get_interface_attr('FINGERPRINTS', ignore_none=True)
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none_brands_in_ret = none_brands.intersection(ret)
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assert len(none_brands_in_ret) == 0, f'Brands with None values in ignore_none=True result: {none_brands_in_ret}'
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