def _setup_collector(self):
self.sm_collector = SubMaster(['liveTracks'])
self.log_auto_df = self.op_params.get('log_auto_df')
if not isinstance(self.log_auto_df, bool):
self.log_auto_df = False
self.data_collector = DataCollector(file_path='/data/df_data',
keys=[
'v_ego', 'a_ego', 'a_lead',
'v_lead', 'x_lead', 'profile',
'time'
],
log_data=self.log_auto_df)
def __init__(self):
self.sm = SubMaster(['laneSpeed'])
self.pm = PubMaster(['dynamicCameraOffset'])
self.op_params = opParams()
self.camera_offset = self.op_params.get('camera_offset')
self.left_lane_oncoming = False # these variables change
self.right_lane_oncoming = False
self.last_left_lane_oncoming = False
self.last_right_lane_oncoming = False
self.last_oncoming_time = 0
self.i = 0.0
self._setup_static()
def main():
def get_influxdb_line(measurement: str, value: float, timestamp: datetime, tags: dict):
res = f"{measurement}"
for k, v in tags.items():
res += f",{k}={str(v)}"
res += f" value={value} {int(timestamp.timestamp() * 1e9)}\n"
return res
# open statistics socket
ctx = zmq.Context().instance()
sock = ctx.socket(zmq.PULL)
sock.bind(STATS_SOCKET)
# initialize stats directory
Path(STATS_DIR).mkdir(parents=True, exist_ok=True)
# initialize tags
tags = {
'dongleId': Params().get("DongleId", encoding='utf-8'),
'started': False,
'version': get_short_version(),
'branch': get_short_branch(),
'dirty': is_dirty(),
'origin': get_normalized_origin(),
'deviceType': HARDWARE.get_device_type(),
}
# subscribe to deviceState for started state
sm = SubMaster(['deviceState'])
last_flush_time = time.monotonic()
gauges = {}
while True:
started_prev = sm['deviceState'].started
sm.update()
# Update metrics
while True:
try:
metric = sock.recv_string(zmq.NOBLOCK)
try:
metric_type = metric.split('|')[1]
metric_name = metric.split(':')[0]
metric_value = metric.split('|')[0].split(':')[1]
if metric_type == METRIC_TYPE.GAUGE:
gauges[metric_name] = metric_value
else:
cloudlog.event("unknown metric type", metric_type=metric_type)
except Exception:
cloudlog.event("malformed metric", metric=metric)
except zmq.error.Again:
break
# flush when started state changes or after FLUSH_TIME_S
if (time.monotonic() > last_flush_time + STATS_FLUSH_TIME_S) or (sm['deviceState'].started != started_prev):
result = ""
current_time = datetime.utcnow().replace(tzinfo=timezone.utc)
tags['started'] = sm['deviceState'].started
for gauge_key in gauges:
result += get_influxdb_line(f"gauge.{gauge_key}", gauges[gauge_key], current_time, tags)
# clear intermediate data
gauges = {}
last_flush_time = time.monotonic()
# check that we aren't filling up the drive
if len(os.listdir(STATS_DIR)) < STATS_DIR_FILE_LIMIT:
if len(result) > 0:
stats_path = os.path.join(STATS_DIR, str(int(current_time.timestamp())))
with atomic_write_in_dir(stats_path) as f:
f.write(result)
else:
cloudlog.error("stats dir full")
def cputime_total(ct):
return ct.user + ct.nice + ct.system + ct.idle + ct.iowait + ct.irq + ct.softirq
def cputime_busy(ct):
return ct.user + ct.nice + ct.system + ct.irq + ct.softirq
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--mem', action='store_true')
args = parser.parse_args()
sm = SubMaster(['thermal', 'procLog'])
last_temp = 0.0
last_mem = 0.0
total_times = [0., 0., 0., 0.]
busy_times = [0., 0., 0.0, 0.]
while True:
sm.update()
if sm.updated['thermal']:
t = sm['thermal']
last_temp = np.mean([t.cpu0, t.cpu1, t.cpu2, t.cpu3]) / 10.
last_mem = t.memUsedPercent
if sm.updated['procLog']:
def main() -> NoReturn:
dongle_id = Params().get("DongleId", encoding='utf-8')
def get_influxdb_line(measurement: str, value: Union[float, Dict[str, float]], timestamp: datetime, tags: dict) -> str:
res = f"{measurement}"
for k, v in tags.items():
res += f",{k}={str(v)}"
res += " "
if isinstance(value, float):
value = {'value': value}
for k, v in value.items():
res += f"{k}={v},"
res += f"dongle_id=\"{dongle_id}\" {int(timestamp.timestamp() * 1e9)}\n"
return res
# open statistics socket
ctx = zmq.Context().instance()
sock = ctx.socket(zmq.PULL)
sock.bind(STATS_SOCKET)
# initialize stats directory
Path(STATS_DIR).mkdir(parents=True, exist_ok=True)
# initialize tags
tags = {
'started': False,
'version': get_short_version(),
'branch': get_short_branch(),
'dirty': is_dirty(),
'origin': get_normalized_origin(),
'deviceType': HARDWARE.get_device_type(),
}
# subscribe to deviceState for started state
sm = SubMaster(['deviceState'])
idx = 0
last_flush_time = time.monotonic()
gauges = {}
samples: Dict[str, List[float]] = defaultdict(list)
while True:
started_prev = sm['deviceState'].started
sm.update()
# Update metrics
while True:
try:
metric = sock.recv_string(zmq.NOBLOCK)
try:
metric_type = metric.split('|')[1]
metric_name = metric.split(':')[0]
metric_value = float(metric.split('|')[0].split(':')[1])
if metric_type == METRIC_TYPE.GAUGE:
gauges[metric_name] = metric_value
elif metric_type == METRIC_TYPE.SAMPLE:
samples[metric_name].append(metric_value)
else:
cloudlog.event("unknown metric type", metric_type=metric_type)
except Exception:
cloudlog.event("malformed metric", metric=metric)
except zmq.error.Again:
break
# flush when started state changes or after FLUSH_TIME_S
if (time.monotonic() > last_flush_time + STATS_FLUSH_TIME_S) or (sm['deviceState'].started != started_prev):
result = ""
current_time = datetime.utcnow().replace(tzinfo=timezone.utc)
tags['started'] = sm['deviceState'].started
for key, value in gauges.items():
result += get_influxdb_line(f"gauge.{key}", value, current_time, tags)
for key, values in samples.items():
values.sort()
sample_count = len(values)
sample_sum = sum(values)
stats = {
'count': sample_count,
'min': values[0],
'max': values[-1],
'mean': sample_sum / sample_count,
}
for percentile in [0.05, 0.5, 0.95]:
value = values[int(round(percentile * (sample_count - 1)))]
stats[f"p{int(percentile * 100)}"] = value
result += get_influxdb_line(f"sample.{key}", stats, current_time, tags)
# clear intermediate data
gauges.clear()
samples.clear()
last_flush_time = time.monotonic()
# check that we aren't filling up the drive
if len(os.listdir(STATS_DIR)) < STATS_DIR_FILE_LIMIT:
if len(result) > 0:
stats_path = os.path.join(STATS_DIR, f"{current_time.timestamp():.0f}_{idx}")
with atomic_write_in_dir(stats_path) as f:
f.write(result)
idx += 1
else:
cloudlog.error("stats dir full")
name = proc.name
if len(proc.cmdline):
name = proc.cmdline[0]
if len(proc.exe):
name = proc.exe + " - " + name
return name
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--mem', action='store_true')
parser.add_argument('--cpu', action='store_true')
args = parser.parse_args()
sm = SubMaster(['deviceState', 'procLog'])
last_temp = 0.0
last_mem = 0.0
total_times = [0.] * 8
busy_times = [0.] * 8
prev_proclog: Optional[capnp._DynamicStructReader] = None
prev_proclog_t: Optional[int] = None
while True:
sm.update()
if sm.updated['deviceState']:
t = sm['deviceState']
last_temp = mean(t.cpuTempC)
def _setup_collector(self):
self.sm = SubMaster(['liveTracks'])
from cereal.messaging import SubMaster
import time
sm = SubMaster(['dynamicFollowData'])
while True:
sm.update(0)
print('mpc_TR: {}'.format(sm['dynamicFollowData'].mpcTR))
time.sleep(1 / 20)
from cereal.messaging import SubMaster
sm = SubMaster(['modelV2'], poll=['modelV2'])
model_t = [
0, 0.009765625, 0.0390625, 0.087890625, 0.15625, 0.24414062, 0.3515625,
0.47851562, 0.625, 0.79101562, 0.9765625, 1.1816406, 1.40625, 1.6503906,
1.9140625, 2.1972656, 2.5, 2.8222656, 3.1640625, 3.5253906, 3.90625,
4.3066406, 4.7265625, 5.1660156, 5.625, 6.1035156, 6.6015625, 7.1191406,
7.65625, 8.2128906, 8.7890625, 9.3847656, 10
]
mpc_idxs = list(range(10))
model_t_idx = [
sorted(range(len(model_t)),
key=[abs(idx - t) for t in model_t].__getitem__)[0]
for idx in mpc_idxs
] # matches 0 to 9 interval to idx from t
# speed_curr_idx = sorted(range(len(model_t)), key=[abs(t - .1) for t in model_t].__getitem__)[0] # idx used for current speed, position still uses model_t_idx
while 1:
sm.update()
modelV2 = sm['modelV2']
if not sm.updated['modelV2'] or len(modelV2.position.x) == 0:
continue
distances, speeds, accelerations = [], [], [
] # everything is derived from x position since velocity is outputting weird values
for t in model_t_idx:
speeds.append(modelV2.velocity.x[t])
distances.append(modelV2.position.x[t])