class PybarFEI4(Transceiver):
def setup_interpretation(self):
self.interpreter = PyDataInterpreter()
self.interpreter.set_warning_output(False)
def deserialze_data(self, data): # According to pyBAR data serilization
try:
self.meta_data = jsonapi.loads(data)
except ValueError:
try:
dtype = self.meta_data.pop('dtype')
shape = self.meta_data.pop('shape')
if self.meta_data:
try:
raw_data_array = np.frombuffer(
buffer(data), dtype=dtype).reshape(shape)
return raw_data_array
except (
KeyError, ValueError
): # KeyError happens if meta data read is omitted; ValueError if np.frombuffer fails due to wrong sha
return None
except AttributeError: # Happens if first data is not meta data
return None
return {'meta_data': self.meta_data}
def interpret_data(self, data):
if isinstance(
data[0][1],
dict): # Meta data is omitted, only raw data is interpreted
# Add info to meta data
data[0][1]['meta_data'].update({
'n_hits':
self.interpreter.get_n_hits(),
'n_events':
self.interpreter.get_n_events()
})
return [data[0][1]]
self.interpreter.interpret_raw_data(data[0][1])
interpreted_data = {
'hits':
self.interpreter.get_hits(),
'tdc_counters':
self.interpreter.get_tdc_counters(),
'error_counters':
self.interpreter.get_error_counters(),
'service_records_counters':
self.interpreter.get_service_records_counters(),
'trigger_error_counters':
self.interpreter.get_trigger_error_counters()
}
self.interpreter.reset_histograms(
) # For the summing of histograms the histogrammer converter is used
return [interpreted_data]
def serialze_data(self, data):
return jsonapi.dumps(data, cls=utils.NumpyEncoder)
class PybarFEI4(Transceiver):
def setup_interpretation(self):
self.interpreter = PyDataInterpreter()
self.interpreter.set_warning_output(False)
def deserialze_data(self, data): # According to pyBAR data serilization
try:
self.meta_data = jsonapi.loads(data)
except ValueError:
try:
dtype = self.meta_data.pop('dtype')
shape = self.meta_data.pop('shape')
if self.meta_data:
try:
raw_data_array = np.frombuffer(buffer(data), dtype=dtype).reshape(shape)
return raw_data_array
except (KeyError, ValueError): # KeyError happens if meta data read is omitted; ValueError if np.frombuffer fails due to wrong sha
return None
except AttributeError: # Happens if first data is not meta data
return None
return {'meta_data': self.meta_data}
def interpret_data(self, data):
if isinstance(data[0][1], dict): # Meta data is omitted, only raw data is interpreted
# Add info to meta data
data[0][1]['meta_data'].update({'n_hits': self.interpreter.get_n_hits(), 'n_events': self.interpreter.get_n_events()})
return [data[0][1]]
self.interpreter.interpret_raw_data(data[0][1])
interpreted_data = {
'hits': self.interpreter.get_hits(),
'tdc_counters': self.interpreter.get_tdc_counters(),
'error_counters': self.interpreter.get_error_counters(),
'service_records_counters': self.interpreter.get_service_records_counters(),
'trigger_error_counters': self.interpreter.get_trigger_error_counters()
}
self.interpreter.reset_histograms() # For the summing of histograms the histogrammer converter is used
return [interpreted_data]
def serialze_data(self, data):
return jsonapi.dumps(data, cls=utils.NumpyEncoder)
class DataWorker(QtCore.QObject):
run_start = QtCore.pyqtSignal()
run_config_data = QtCore.pyqtSignal(dict)
global_config_data = QtCore.pyqtSignal(dict)
filename = QtCore.pyqtSignal(dict)
interpreted_data = QtCore.pyqtSignal(dict)
meta_data = QtCore.pyqtSignal(dict)
finished = QtCore.pyqtSignal()
def __init__(self):
QtCore.QObject.__init__(self)
self.integrate_readouts = 1
self.n_readout = 0
self._stop_readout = Event()
self.setup_raw_data_analysis()
self.reset_lock = Lock()
def setup_raw_data_analysis(self):
self.interpreter = PyDataInterpreter()
self.histogram = PyDataHistograming()
self.interpreter.set_warning_output(False)
self.histogram.set_no_scan_parameter()
self.histogram.create_occupancy_hist(True)
self.histogram.create_rel_bcid_hist(True)
self.histogram.create_tot_hist(True)
self.histogram.create_tdc_hist(True)
try:
self.histogram.create_tdc_distance_hist(True)
self.interpreter.use_tdc_trigger_time_stamp(True)
except AttributeError:
self.has_tdc_distance = False
else:
self.has_tdc_distance = True
def connect(self, socket_addr):
self.socket_addr = socket_addr
self.context = zmq.Context()
self.socket_pull = self.context.socket(zmq.SUB) # subscriber
self.socket_pull.setsockopt(zmq.SUBSCRIBE,
'') # do not filter any data
self.socket_pull.connect(self.socket_addr)
def on_set_integrate_readouts(self, value):
self.integrate_readouts = value
def reset(self):
with self.reset_lock:
self.histogram.reset()
self.interpreter.reset()
self.n_readout = 0
def analyze_raw_data(self, raw_data):
self.interpreter.interpret_raw_data(raw_data)
self.histogram.add_hits(self.interpreter.get_hits())
def process_data(
self
): # infinite loop via QObject.moveToThread(), does not block event loop
while (not self._stop_readout.wait(0.01)
): # use wait(), do not block here
with self.reset_lock:
try:
meta_data = self.socket_pull.recv_json(flags=zmq.NOBLOCK)
except zmq.Again:
pass
else:
name = meta_data.pop('name')
if name == 'ReadoutData':
data = self.socket_pull.recv()
# reconstruct numpy array
buf = buffer(data)
dtype = meta_data.pop('dtype')
shape = meta_data.pop('shape')
data_array = np.frombuffer(buf,
dtype=dtype).reshape(shape)
# count readouts and reset
self.n_readout += 1
if self.integrate_readouts != 0 and self.n_readout % self.integrate_readouts == 0:
self.histogram.reset()
# we do not want to reset interpreter to keep the error counters
# self.interpreter.reset()
# interpreted data
self.analyze_raw_data(data_array)
if self.integrate_readouts == 0 or self.n_readout % self.integrate_readouts == self.integrate_readouts - 1:
interpreted_data = {
'occupancy':
self.histogram.get_occupancy(),
'tot_hist':
self.histogram.get_tot_hist(),
'tdc_counters':
self.interpreter.get_tdc_counters(),
'tdc_distance':
self.interpreter.get_tdc_distance()
if self.has_tdc_distance else np.zeros(
(256, ), dtype=np.uint8),
'error_counters':
self.interpreter.get_error_counters(),
'service_records_counters':
self.interpreter.get_service_records_counters(
),
'trigger_error_counters':
self.interpreter.get_trigger_error_counters(),
'rel_bcid_hist':
self.histogram.get_rel_bcid_hist()
}
self.interpreted_data.emit(interpreted_data)
# meta data
meta_data.update({
'n_hits':
self.interpreter.get_n_hits(),
'n_events':
self.interpreter.get_n_events()
})
self.meta_data.emit(meta_data)
elif name == 'RunConf':
self.run_config_data.emit(meta_data)
elif name == 'GlobalRegisterConf':
trig_count = int(meta_data['conf']['Trig_Count'])
self.interpreter.set_trig_count(trig_count)
self.global_config_data.emit(meta_data)
elif name == 'Reset':
self.histogram.reset()
self.interpreter.reset()
self.run_start.emit()
elif name == 'Filename':
self.filename.emit(meta_data)
self.finished.emit()
def stop(self):
self._stop_readout.set()
