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()
class PybarFEI4Histogrammer(Transceiver):
def setup_transceiver(self):
self.set_bidirectional_communication(
) # We want to be able to change the histogrammmer settings
def setup_interpretation(self):
self.histograming = PyDataHistograming()
self.histograming.set_no_scan_parameter()
self.histograming.create_occupancy_hist(True)
self.histograming.create_rel_bcid_hist(True)
self.histograming.create_tot_hist(True)
self.histograming.create_tdc_hist(True)
# Variables
self.n_readouts = 0
self.readout = 0
self.fps = 0 # data frames per second
self.hps = 0 # hits per second
self.eps = 0 # events per second
self.plot_delay = 0
self.total_hits = 0
self.total_events = 0
self.updateTime = time.time()
# Histogrammes from interpretation stored for summing
self.tdc_counters = None
self.error_counters = None
self.service_records_counters = None
self.trigger_error_counters = None
def deserialze_data(self, data):
return jsonapi.loads(data, object_hook=utils.json_numpy_obj_hook)
def interpret_data(self, data):
# Meta data is directly forwarded to the receiver, only hit data and event counters are histogramed
if 'meta_data' in data[0][1]: # 0 for frontend index, 1 for data dict
meta_data = data[0][1]['meta_data']
now = time.time()
recent_total_hits = meta_data['n_hits']
recent_total_events = meta_data['n_events']
recent_fps = 1.0 / (now - self.updateTime) # calculate FPS
recent_hps = (recent_total_hits -
self.total_hits) / (now - self.updateTime)
recent_eps = (recent_total_events -
self.total_events) / (now - self.updateTime)
self.updateTime = now
self.total_hits = recent_total_hits
self.total_events = recent_total_events
self.fps = self.fps * 0.7 + recent_fps * 0.3
self.hps = self.hps + (recent_hps - self.hps) * 0.3 / self.fps
self.eps = self.eps + (recent_eps - self.eps) * 0.3 / self.fps
meta_data.update({
'fps': self.fps,
'hps': self.hps,
'total_hits': self.total_hits,
'eps': self.eps,
'total_events': self.total_events
})
return [data[0][1]]
self.readout += 1
if self.n_readouts != 0: # 0 for infinite integration
if self.readout % self.n_readouts == 0:
self.histograming.reset()
self.tdc_counters = np.zeros_like(self.tdc_counters)
self.error_counters = np.zeros_like(self.error_counters)
self.service_records_counters = np.zeros_like(
self.service_records_counters)
self.trigger_error_counters = np.zeros_like(
self.trigger_error_counters)
self.readouts = 0
interpreted_data = data[0][1]
self.histograming.add_hits(interpreted_data['hits'])
# Sum up interpreter histograms
if self.tdc_counters is not None:
self.tdc_counters += interpreted_data['tdc_counters']
else:
self.tdc_counters = interpreted_data['tdc_counters'].copy(
) # Copy needed to give ownage to histogrammer
if self.error_counters is not None:
self.error_counters += interpreted_data['error_counters']
else:
self.error_counters = interpreted_data['error_counters'].copy(
) # Copy needed to give ownage to histogrammer
if self.service_records_counters is not None:
self.service_records_counters += interpreted_data[
'service_records_counters']
else:
self.service_records_counters = interpreted_data[
'service_records_counters'].copy(
) # Copy needed to give ownage to histogrammer
if self.trigger_error_counters is not None:
self.trigger_error_counters += interpreted_data[
'trigger_error_counters']
else:
self.trigger_error_counters = interpreted_data[
'trigger_error_counters'].copy(
) # Copy needed to give ownage to histogrammer
histogrammed_data = {
'occupancy': self.histograming.get_occupancy(),
'tot_hist': self.histograming.get_tot_hist(),
'tdc_counters': self.tdc_counters,
'error_counters': self.error_counters,
'service_records_counters': self.service_records_counters,
'trigger_error_counters': self.trigger_error_counters,
'rel_bcid_hist': self.histograming.get_rel_bcid_hist()
}
return [histogrammed_data]
def serialze_data(self, data):
return jsonapi.dumps(data, cls=utils.NumpyEncoder)
def handle_command(self, command):
if command[0] == 'RESET': # Reset command to reset the histograms
self.histograming.reset()
self.tdc_counters = np.zeros_like(self.tdc_counters)
self.error_counters = np.zeros_like(self.error_counters)
self.service_records_counters = np.zeros_like(
self.service_records_counters)
self.trigger_error_counters = np.zeros_like(
self.trigger_error_counters)
else:
self.n_readouts = int(command[0])
class PybarFEI4Histogrammer(Transceiver):
def setup_transceiver(self):
self.set_bidirectional_communication() # We want to be able to change the histogrammmer settings
def setup_interpretation(self):
self.histograming = PyDataHistograming()
self.histograming.set_no_scan_parameter()
self.histograming.create_occupancy_hist(True)
self.histograming.create_rel_bcid_hist(True)
self.histograming.create_tot_hist(True)
self.histograming.create_tdc_hist(True)
# Variables
self.n_readouts = 0
self.readout = 0
self.fps = 0 # data frames per second
self.hps = 0 # hits per second
self.eps = 0 # events per second
self.plot_delay = 0
self.total_hits = 0
self.total_events = 0
self.updateTime = time.time()
# Histogrammes from interpretation stored for summing
self.tdc_counters = None
self.error_counters = None
self.service_records_counters = None
self.trigger_error_counters = None
def deserialze_data(self, data):
return jsonapi.loads(data, object_hook=utils.json_numpy_obj_hook)
def interpret_data(self, data):
if 'meta_data' in data[0][1]: # Meta data is directly forwarded to the receiver, only hit data, event counters are histogramed; 0 from frontend index, 1 for data dict
meta_data = data[0][1]['meta_data']
now = time.time()
recent_total_hits = meta_data['n_hits']
recent_total_events = meta_data['n_events']
recent_fps = 1.0 / (now - self.updateTime) # calculate FPS
recent_hps = (recent_total_hits - self.total_hits) / (now - self.updateTime)
recent_eps = (recent_total_events - self.total_events) / (now - self.updateTime)
self.updateTime = now
self.total_hits = recent_total_hits
self.total_events = recent_total_events
self.fps = self.fps * 0.7 + recent_fps * 0.3
self.hps = self.hps + (recent_hps - self.hps) * 0.3 / self.fps
self.eps = self.eps + (recent_eps - self.eps) * 0.3 / self.fps
meta_data.update({'fps': self.fps, 'hps': self.hps, 'total_hits': self.total_hits, 'eps': self.eps, 'total_events': self.total_events})
return [data[0][1]]
self.readout += 1
if self.n_readouts != 0: # = 0 for infinite integration
if self.readout % self.n_readouts == 0:
self.histograming.reset()
self.tdc_counters = np.zeros_like(self.tdc_counters)
self.error_counters = np.zeros_like(self.error_counters)
self.service_records_counters = np.zeros_like(self.service_records_counters)
self.trigger_error_counters = np.zeros_like(self.trigger_error_counters)
self.readouts = 0
interpreted_data = data[0][1]
self.histograming.add_hits(interpreted_data['hits'])
# Sum up interpreter histograms
if self.tdc_counters is not None:
self.tdc_counters += interpreted_data['tdc_counters']
else:
self.tdc_counters = interpreted_data['tdc_counters'].copy() # Copy needed to give ownage to histogrammer
if self.error_counters is not None:
self.error_counters += interpreted_data['error_counters']
else:
self.error_counters = interpreted_data['error_counters'].copy() # Copy needed to give ownage to histogrammer
if self.service_records_counters is not None:
self.service_records_counters += interpreted_data['service_records_counters']
else:
self.service_records_counters = interpreted_data['service_records_counters'].copy() # Copy needed to give ownage to histogrammer
if self.trigger_error_counters is not None:
self.trigger_error_counters += interpreted_data['trigger_error_counters']
else:
self.trigger_error_counters = interpreted_data['trigger_error_counters'].copy() # Copy needed to give ownage to histogrammer
histogrammed_data = {
'occupancy': self.histograming.get_occupancy(),
'tot_hist': self.histograming.get_tot_hist(),
'tdc_counters': self.tdc_counters,
'error_counters': self.error_counters,
'service_records_counters': self.service_records_counters,
'trigger_error_counters': self.trigger_error_counters,
'rel_bcid_hist': self.histograming.get_rel_bcid_hist()
}
return [histogrammed_data]
def serialze_data(self, data):
return jsonapi.dumps(data, cls=utils.NumpyEncoder)
def handle_command(self, command):
if command[0] == 'RESET':
self.histograming.reset()
self.tdc_counters = np.zeros_like(self.tdc_counters)
self.error_counters = np.zeros_like(self.error_counters)
self.service_records_counters = np.zeros_like(self.service_records_counters)
self.trigger_error_counters = np.zeros_like(self.trigger_error_counters)
else:
self.n_readouts = int(command[0])
class ThresholdBaselineTuning(Fei4RunBase):
'''Threshold Baseline Tuning
Tuning the FEI4 to the lowest possible threshold (GDAC and TDAC). Feedback current will not be tuned.
NOTE: In case of RX errors decrease the trigger frequency (= increase trigger_rate_limit)
NOTE: To increase the TDAC range, decrease TdacVbp.
'''
_default_run_conf = {
"occupancy_limit": 0, # occupancy limit, when reached the TDAC will be decreased (increasing threshold). 0 will mask any pixel with occupancy greater than zero
"scan_parameters": [('Vthin_AltFine', (120, None)), ('Step', 60)], # the Vthin_AltFine range, number of steps (repetition at constant Vthin_AltFine)
"increase_threshold": 5, # increasing the global threshold (Vthin_AltFine) after tuning
"disabled_pixels_limit": 0.01, # limit of disabled pixels, fraction of all pixels
"use_enable_mask": False, # if True, enable mask from config file anded with mask (from col_span and row_span), if False use mask only for enable mask
"n_triggers": 10000, # total number of trigger sent to FE
"trigger_rate_limit": 500, # artificially limiting the trigger rate, in BCs (25ns)
"trig_count": 0, # FE-I4 trigger count, number of consecutive BCs, 0 means 16, from 0 to 15
"col_span": [1, 80], # column range (from minimum to maximum value). From 1 to 80.
"row_span": [1, 336], # row range (from minimum to maximum value). From 1 to 336.
}
def configure(self):
if self.trig_count == 0:
self.consecutive_lvl1 = (2 ** self.register.global_registers['Trig_Count']['bitlength'])
else:
self.consecutive_lvl1 = self.trig_count
self.abs_occ_limit = int(self.occupancy_limit * self.n_triggers * self.consecutive_lvl1)
if self.abs_occ_limit <= 0:
logging.info('Any noise hit will lead to an increased pixel threshold.')
else:
logging.info('The pixel threshold of any pixel with an occpancy >%d will be increased' % self.abs_occ_limit)
commands = []
commands.extend(self.register.get_commands("ConfMode"))
# TDAC
tdac_max = 2 ** self.register.pixel_registers['TDAC']['bitlength'] - 1
self.register.set_pixel_register_value("TDAC", tdac_max)
commands.extend(self.register.get_commands("WrFrontEnd", same_mask_for_all_dc=False, name="TDAC"))
mask = make_box_pixel_mask_from_col_row(column=self.col_span, row=self.row_span)
# Enable
if self.use_enable_mask:
self.register.set_pixel_register_value("Enable", np.logical_and(mask, self.register.get_pixel_register_value("Enable")))
else:
self.register.set_pixel_register_value("Enable", mask)
commands.extend(self.register.get_commands("WrFrontEnd", same_mask_for_all_dc=False, name="Enable"))
# Imon
self.register.set_pixel_register_value('Imon', 1)
commands.extend(self.register.get_commands("WrFrontEnd", same_mask_for_all_dc=True, name='Imon'))
# C_High
self.register.set_pixel_register_value('C_High', 0)
commands.extend(self.register.get_commands("WrFrontEnd", same_mask_for_all_dc=True, name='C_High'))
# C_Low
self.register.set_pixel_register_value('C_Low', 0)
commands.extend(self.register.get_commands("WrFrontEnd", same_mask_for_all_dc=True, name='C_Low'))
# Registers
# self.register.set_global_register_value("Trig_Lat", self.trigger_latency) # set trigger latency
self.register.set_global_register_value("Trig_Count", self.trig_count) # set number of consecutive triggers
commands.extend(self.register.get_commands("WrRegister", name=["Trig_Count"]))
commands.extend(self.register.get_commands("RunMode"))
self.register_utils.send_commands(commands)
self.interpreter = PyDataInterpreter()
self.histogram = PyDataHistograming()
self.interpreter.set_trig_count(self.trig_count)
self.interpreter.set_warning_output(False)
self.histogram.set_no_scan_parameter()
self.histogram.create_occupancy_hist(True)
def scan(self):
scan_parameter_range = [self.register.get_global_register_value("Vthin_AltFine"), 0]
if self.scan_parameters.Vthin_AltFine[0]:
scan_parameter_range[0] = self.scan_parameters.Vthin_AltFine[0]
if self.scan_parameters.Vthin_AltFine[1]:
scan_parameter_range[1] = self.scan_parameters.Vthin_AltFine[1]
steps = 1
if self.scan_parameters.Step:
steps = self.scan_parameters.Step
lvl1_command = self.register.get_commands("LV1")[0] + self.register.get_commands("zeros", length=self.trigger_rate_limit)[0]
self.total_scan_time = int(lvl1_command.length() * 25 * (10 ** -9) * self.n_triggers)
preselected_pixels = invert_pixel_mask(self.register.get_pixel_register_value('Enable')).sum()
disabled_pixels_limit_cnt = int(self.disabled_pixels_limit * self.register.get_pixel_register_value('Enable').sum())
disabled_pixels = 0
self.last_reg_val = deque([None] * self.increase_threshold, maxlen=self.increase_threshold + 1)
self.last_step = deque([None] * self.increase_threshold, maxlen=self.increase_threshold + 1)
self.last_good_threshold = deque([None] * self.increase_threshold, maxlen=self.increase_threshold + 1)
self.last_good_tdac = deque([None] * self.increase_threshold, maxlen=self.increase_threshold + 1)
self.last_good_enable_mask = deque([None] * self.increase_threshold, maxlen=self.increase_threshold + 1)
self.last_occupancy_hist = deque([None] * self.increase_threshold, maxlen=self.increase_threshold + 1)
self.last_occupancy_mask = deque([None] * self.increase_threshold, maxlen=self.increase_threshold + 1)
for reg_val in range(scan_parameter_range[0], scan_parameter_range[1] - 1, -1):
if self.stop_run.is_set():
break
logging.info('Scanning Vthin_AltFine %d', reg_val)
commands = []
commands.extend(self.register.get_commands("ConfMode"))
self.register.set_global_register_value("Vthin_AltFine", reg_val) # set number of consecutive triggers
commands.extend(self.register.get_commands("WrRegister", name=["Vthin_AltFine"]))
# setting FE into RunMode
commands.extend(self.register.get_commands("RunMode"))
self.register_utils.send_commands(commands)
step = 0
while True:
if self.stop_run.is_set():
break
self.histogram.reset()
step += 1
logging.info('Step %d / %d at Vthin_AltFine %d', step, steps, reg_val)
logging.info('Estimated scan time: %ds', self.total_scan_time)
with self.readout(Vthin_AltFine=reg_val, Step=step, reset_sram_fifo=True, fill_buffer=True, clear_buffer=True, callback=self.handle_data):
got_data = False
start = time()
self.register_utils.send_command(lvl1_command, repeat=self.n_triggers, wait_for_finish=False, set_length=True, clear_memory=False)
while not self.stop_run.wait(0.1):
if self.register_utils.is_ready:
if got_data:
self.progressbar.finish()
logging.info('Finished sending %d triggers', self.n_triggers)
break
if not got_data:
if self.fifo_readout.data_words_per_second() > 0:
got_data = True
logging.info('Taking data...')
self.progressbar = progressbar.ProgressBar(widgets=['', progressbar.Percentage(), ' ', progressbar.Bar(marker='*', left='|', right='|'), ' ', progressbar.Timer()], maxval=self.total_scan_time, poll=10, term_width=80).start()
else:
try:
self.progressbar.update(time() - start)
except ValueError:
pass
# Use fast C++ hit histogramming to save time
raw_data = np.ascontiguousarray(data_array_from_data_iterable(self.fifo_readout.data), dtype=np.uint32)
self.interpreter.interpret_raw_data(raw_data)
self.interpreter.store_event() # force to create latest event
self.histogram.add_hits(self.interpreter.get_hits())
occ_hist = self.histogram.get_occupancy()[:, :, 0]
# noisy pixels are set to 1
occ_mask = np.zeros(shape=occ_hist.shape, dtype=np.dtype('>u1'))
occ_mask[occ_hist > self.abs_occ_limit] = 1
tdac_reg = self.register.get_pixel_register_value('TDAC')
decrease_pixel_mask = np.logical_and(occ_mask > 0, tdac_reg > 0)
disable_pixel_mask = np.logical_and(occ_mask > 0, tdac_reg == 0)
enable_reg = self.register.get_pixel_register_value('Enable')
enable_mask = np.logical_and(enable_reg, invert_pixel_mask(disable_pixel_mask))
if np.logical_and(occ_mask > 0, enable_reg == 0).sum():
logging.warning('Received data from disabled pixels')
# disabled_pixels += disable_pixel_mask.sum() # can lead to wrong values if the enable reg is corrupted
disabled_pixels = invert_pixel_mask(enable_mask).sum() - preselected_pixels
if disabled_pixels > disabled_pixels_limit_cnt:
logging.info('Limit of disabled pixels reached: %d (limit %d)... stopping scan' % (disabled_pixels, disabled_pixels_limit_cnt))
break
else:
logging.info('Increasing threshold of %d pixel(s)', decrease_pixel_mask.sum())
logging.info('Disabling %d pixel(s), total number of disabled pixel(s): %d', disable_pixel_mask.sum(), disabled_pixels)
tdac_reg[decrease_pixel_mask] -= 1
self.register.set_pixel_register_value('TDAC', tdac_reg)
self.register.set_pixel_register_value('Enable', enable_mask)
commands = []
commands.extend(self.register.get_commands("ConfMode"))
commands.extend(self.register.get_commands("WrFrontEnd", same_mask_for_all_dc=False, name='TDAC'))
commands.extend(self.register.get_commands("WrFrontEnd", same_mask_for_all_dc=False, name='Enable'))
commands.extend(self.register.get_commands("RunMode"))
self.register_utils.send_commands(commands)
if occ_mask.sum() == 0 or step == steps or decrease_pixel_mask.sum() < disabled_pixels_limit_cnt:
self.last_reg_val.appendleft(reg_val)
self.last_step.appendleft(step)
self.last_good_threshold.appendleft(self.register.get_global_register_value("Vthin_AltFine"))
self.last_good_tdac.appendleft(self.register.get_pixel_register_value("TDAC"))
self.last_good_enable_mask.appendleft(self.register.get_pixel_register_value("Enable"))
self.last_occupancy_hist.appendleft(occ_hist.copy())
self.last_occupancy_mask.appendleft(occ_mask.copy())
break
else:
logging.info('Found %d noisy pixels... repeat tuning step for Vthin_AltFine %d', occ_mask.sum(), reg_val)
if disabled_pixels > disabled_pixels_limit_cnt or scan_parameter_range[1] == reg_val:
break
def analyze(self):
self.register.set_global_register_value("Vthin_AltFine", self.last_good_threshold[self.increase_threshold])
self.register.set_pixel_register_value('TDAC', self.last_good_tdac[self.increase_threshold])
self.register.set_pixel_register_value('Enable', self.last_good_enable_mask[0]) # use enable mask from the lowest point to mask bad pixels
# write configuration to avaoid high current states
commands = []
commands.extend(self.register.get_commands("ConfMode"))
commands.extend(self.register.get_commands("WrRegister", name=["Vthin_AltFine"]))
commands.extend(self.register.get_commands("WrFrontEnd", same_mask_for_all_dc=False, name="TDAC"))
commands.extend(self.register.get_commands("WrFrontEnd", same_mask_for_all_dc=False, name="Enable"))
self.register_utils.send_commands(commands)
with AnalyzeRawData(raw_data_file=self.output_filename, create_pdf=True) as analyze_raw_data:
analyze_raw_data.create_source_scan_hist = True
analyze_raw_data.interpreter.set_warning_output(False)
analyze_raw_data.interpret_word_table()
analyze_raw_data.interpreter.print_summary()
analyze_raw_data.plot_histograms()
plot_occupancy(self.last_occupancy_hist[self.increase_threshold].T, title='Noisy Pixels at Vthin_AltFine %d Step %d' % (self.last_reg_val[self.increase_threshold], self.last_step[self.increase_threshold]), filename=analyze_raw_data.output_pdf)
plot_fancy_occupancy(self.last_occupancy_hist[self.increase_threshold].T, filename=analyze_raw_data.output_pdf)
plot_occupancy(self.last_occupancy_mask[self.increase_threshold].T, title='Occupancy Mask at Vthin_AltFine %d Step %d' % (self.last_reg_val[self.increase_threshold], self.last_step[self.increase_threshold]), z_max=1, filename=analyze_raw_data.output_pdf)
plot_fancy_occupancy(self.last_occupancy_mask[self.increase_threshold].T, filename=analyze_raw_data.output_pdf)
plot_three_way(self.last_good_tdac[self.increase_threshold].T, title='TDAC at Vthin_AltFine %d Step %d' % (self.last_reg_val[self.increase_threshold], self.last_step[self.increase_threshold]), x_axis_title="TDAC", filename=analyze_raw_data.output_pdf, maximum=31, bins=32)
plot_occupancy(self.last_good_tdac[self.increase_threshold].T, title='TDAC at Vthin_AltFine %d Step %d' % (self.last_reg_val[self.increase_threshold], self.last_step[self.increase_threshold]), z_max=31, filename=analyze_raw_data.output_pdf)
plot_occupancy(self.last_good_enable_mask[self.increase_threshold].T, title='Intermediate Enable Mask at Vthin_AltFine %d Step %d' % (self.last_reg_val[self.increase_threshold], self.last_step[self.increase_threshold]), z_max=1, filename=analyze_raw_data.output_pdf)
plot_fancy_occupancy(self.last_good_enable_mask[self.increase_threshold].T, filename=analyze_raw_data.output_pdf)
plot_occupancy(self.last_good_enable_mask[0].T, title='Final Enable Mask at Vthin_AltFine %d Step %d' % (self.last_reg_val[0], self.last_step[0]), z_max=1, filename=analyze_raw_data.output_pdf)
plot_fancy_occupancy(self.last_good_enable_mask[0].T, filename=analyze_raw_data.output_pdf)