def __init__(self,
configuration,
data_queue,
symbol_pipe,
loglevel='INFO'):
self.data_queue = data_queue
self.symbol_pipe = symbol_pipe
utils.setup_logging(loglevel)
logging.info("Initialize converter mananager with configuration in %s",
configuration)
self.configuration = utils.parse_config_file(configuration)
def start_converter(self):
current_path = os.path.dirname(
os.path.dirname(os.path.abspath(__file__)))
conv_utils.setup_logging('INFO')
cm = ConverterManager(configuration=current_path + os.sep +
'tpx3_monitor.yaml',
data_queue=self.data_queue,
symbol_pipe=self.pipe_dest_conn)
self.converter_process = Process(target=cm.start,
name='TPX3 Converter')
self.pipe_source_conn.send(True)
self.converter_process.start()
def __init__(self,
configuration,
path,
loglevel='INFO',
delay=0.1,
kind='Test',
name='Undefined'):
utils.setup_logging(loglevel)
logging.info("Initialize producer simulation mananager")
self.configuration = utils.parse_config_file(configuration)
self.data_file = path
self.loglevel = loglevel
self.delay = delay
self.kind = kind
self.name = name
def run(
self
): # The receiver loop running in extra process; is called after start() method
utils.setup_logging(self.loglevel)
logging.debug("Start %s producer %s at %s", self.kind, self.name,
self.backend_address)
self.setup_producer_device()
while not self.exit.wait(0.02):
self.send_data()
## Close connections
self.sender.close()
self.context.term()
logging.debug("Close %s producer %s at %s", self.kind, self.name,
self.backend_address)
def __init__(self,
frontend,
kind,
data_queue,
symbol_pipe,
name='Undefined',
max_buffer=None,
loglevel='INFO',
**kwarg):
multiprocessing.Process.__init__(self)
self.kind = kind # kind of transeiver (e.g. forwarder)
self.frontend_address = frontend # socket facing a data publisher
# Maximum number of input messages buffered, otherwise data omitted
self.max_buffer = max_buffer
self.name = name # name of the DAQ/device
# Std. setting is unidirectional frondend communication
self.frontend_socket_type = zmq.SUB
self.data_queue = data_queue
self.symbol_pipe = symbol_pipe
self.run_data_queue_symbol = True
if 'max_cpu_load' in kwarg:
logging.warning(
'The parameter max_cpu_load is deprecated! Use max_buffer!')
self.config = kwarg
# Determine how many frontends the converter has
# just one frontend socket given
if not isinstance(self.frontend_address, list):
self.frontend_address = [self.frontend_address]
self.n_frontends = 1
else:
self.n_frontends = len(self.frontend_address)
self.exit = multiprocessing.Event() # exit signal
self.loglevel = loglevel
utils.setup_logging(self.loglevel)
logging.debug("Initialize %s converter %s with frontends %s ",
self.kind, self.name, self.frontend_address)
def setup_interpretation(self):
''' Objects defined here are available in interpretation process '''
utils.setup_logging(self.loglevel)
self.chunk_size = self.config.get('chunk_size', 1000000)
# Init result hists
self.reset_hists()
# Number of readouts to integrate
self.int_readouts = 0
# Variables for meta data time calculations
self.ts_last_readout = 0. # Time stamp last readout
self.hits_last_readout = 0. # Number of hits
self.events_last_readout = 0. # Number of events in last chunk
self.fps = 0. # Readouts per second
self.hps = 0. # Hits per second
self.eps = 0. # Events per second
self.ext_trg_num = -1 # external trigger number
def __init__(self,
backend,
data_file,
delay=0.1,
kind='Test',
name='Undefined',
loglevel='INFO'):
multiprocessing.Process.__init__(self)
self.backend_address = backend
self.name = name # name of the DAQ/device
self.kind = kind
self.delay = delay
self.data_file = data_file
self.loglevel = loglevel
self.exit = multiprocessing.Event() # exit signal
utils.setup_logging(loglevel)
logging.debug("Initialize %s producer %s at %s", self.kind, self.name,
self.backend_address)
def run(self): # the Receiver loop run in extra process
utils.setup_logging(self.loglevel)
self._setup_transceiver()
self.setup_interpretation()
process = psutil.Process(self.ident) # access this process info
self.cpu_load = 0.
fe_thread = threading.Thread(target=self.recv_data)
fe_thread.start()
logging.debug("Start %s transceiver %s", self.kind, self.name)
while not self.exit.wait(0.01):
if self.raw_data.empty():
continue
else:
raw_data = self.raw_data.get_nowait()
actual_cpu_load = process.cpu_percent()
# Filter cpu load by running mean since it changes rapidly;
# cpu load spikes can be filtered away since data queues up
# through ZMQ
self.cpu_load = 0.90 * self.cpu_load + 0.1 * actual_cpu_load
# Check if already too many messages queued up then omit data
if not self.max_buffer or self.max_buffer > self.raw_data.qsize():
self.interpret_data(raw_data)
else:
logging.warning(
'Converter cannot keep up, omitting data for interpretation!'
)
self.fe_stop.set()
fe_thread.join()
# Close connections
for actual_frontend in self.frontends:
actual_frontend[1].close()
self.context.term()
logging.debug("Close %s transceiver %s", self.kind, self.name)
