def get_raw_data_from_buffer(self, filter_func=None, converter_func=None):
'''Reads local data buffer and returns raw data array.
Returns
-------
data : np.array
An array containing data words from the local data buffer.
'''
if self._is_running:
raise RuntimeError('Readout thread running')
if not self.fill_buffer:
logging.warning('Data buffer is not activated')
return [
convert_data_array(data_array_from_data_iterable(data_iterable),
filter_func=filter_func,
converter_func=converter_func)
for data_iterable in self._data_buffer
]
def scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + '.pdf')
self.close_plots = True
else:
self.close_plots = False
mask_steps = 3
enable_mask_steps = [
0
] # one mask step to increase speed, no effect on precision
cal_lvl1_command = self.register.get_commands(
"CAL")[0] + self.register.get_commands(
"zeros", length=40)[0] + self.register.get_commands(
"LV1")[0] + self.register.get_commands(
"zeros", mask_steps=mask_steps)[0]
self.write_target_charge()
for feedback_bit in self.feedback_tune_bits: # reset all GDAC bits
self.set_prmp_vbpf_bit(feedback_bit, bit_value=0)
additional_scan = True
last_bit_result = self.n_injections_feedback
tot_mean_best = 0
feedback_best = self.register.get_global_register_value("PrmpVbpf")
for feedback_bit in self.feedback_tune_bits:
if additional_scan:
self.set_prmp_vbpf_bit(feedback_bit)
logging.info(
'PrmpVbpf setting: %d, bit %d = 1' %
(self.register.get_global_register_value("PrmpVbpf"),
feedback_bit))
else:
self.set_prmp_vbpf_bit(feedback_bit, bit_value=0)
logging.info(
'PrmpVbpf setting: %d, bit %d = 0' %
(self.register.get_global_register_value("PrmpVbpf"),
feedback_bit))
scan_parameter_value = self.register.get_global_register_value(
"PrmpVbpf")
with self.readout(PrmpVbpf=scan_parameter_value):
scan_loop(self,
cal_lvl1_command,
repeat_command=self.n_injections_feedback,
mask_steps=mask_steps,
enable_mask_steps=enable_mask_steps,
enable_double_columns=None,
same_mask_for_all_dc=True,
eol_function=None,
digital_injection=False,
enable_shift_masks=self.enable_shift_masks,
disable_shift_masks=self.disable_shift_masks,
restore_shift_masks=True,
mask=None,
double_column_correction=self.pulser_dac_correction)
self.raw_data_file.append(
self.fifo_readout.data,
scan_parameters=self.scan_parameters._asdict())
tots = convert_data_array(
data_array_from_data_iterable(self.fifo_readout.data),
filter_func=is_data_record,
converter_func=get_tot_array_from_data_record_array)
mean_tot = np.mean(tots)
if np.isnan(mean_tot):
logging.error(
"No hits, ToT calculation not possible, tuning will fail")
if abs(mean_tot - self.target_tot) < abs(tot_mean_best -
self.target_tot):
tot_mean_best = mean_tot
feedback_best = self.register.get_global_register_value(
"PrmpVbpf")
logging.info('Mean ToT = %f' % mean_tot)
self.tot_array, _ = np.histogram(a=tots, range=(0, 16), bins=16)
if self.plot_intermediate_steps:
plot_tot(hist=self.tot_array,
title='ToT distribution (PrmpVbpf ' +
str(scan_parameter_value) + ')',
filename=self.plots_filename)
if abs(
mean_tot - self.target_tot
) < self.max_delta_tot and feedback_bit > 0: # abort if good value already found to save time
logging.info(
'Good result already achieved, skipping missing bits')
break
if feedback_bit > 0 and mean_tot < self.target_tot:
self.set_prmp_vbpf_bit(feedback_bit, bit_value=0)
logging.info('Mean ToT = %f < %d ToT, set bit %d = 0' %
(mean_tot, self.target_tot, feedback_bit))
if feedback_bit == 0:
if additional_scan: # scan bit = 0 with the correct value again
additional_scan = False
last_bit_result = mean_tot
self.feedback_tune_bits.append(
0) # bit 0 has to be scanned twice
else:
logging.info(
'Scanned bit 0 = 0 with %f instead of %f for scanned bit 0 = 1'
% (mean_tot, last_bit_result))
if (abs(mean_tot - self.target_tot) >
abs(last_bit_result - self.target_tot)
): # if bit 0 = 0 is worse than bit 0 = 1, so go back
self.set_prmp_vbpf_bit(feedback_bit, bit_value=1)
mean_tot = last_bit_result
logging.info('Set bit 0 = 1')
else:
logging.info('Set bit 0 = 0')
if abs(mean_tot - self.target_tot) > abs(tot_mean_best -
self.target_tot):
logging.info(
"Binary search converged to non optimal value, take best measured value instead"
)
mean_tot = tot_mean_best
self.register.set_global_register_value(
"PrmpVbpf", feedback_best)
if self.register.get_global_register_value(
"PrmpVbpf") == 0 or self.register.get_global_register_value(
"PrmpVbpf") == 254:
logging.warning('PrmpVbpf reached minimum/maximum value')
if abs(mean_tot - self.target_tot) > 2 * self.max_delta_tot:
logging.warning(
'Global feedback tuning failed. Delta ToT = %f > %f. PrmpVbpf = %d'
% (abs(mean_tot - self.target_tot), self.max_delta_tot,
self.register.get_global_register_value("PrmpVbpf")))
else:
logging.info('Tuned PrmpVbpf to %d' %
self.register.get_global_register_value("PrmpVbpf"))
self.feedback_best = self.register.get_global_register_value(
"PrmpVbpf")
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)
disabled_pixels_limit_cnt = int(self.disabled_pixels_limit * 336 * 80)
preselected_pixels = invert_pixel_mask(
self.register.get_pixel_register_value('Enable')).sum()
disabled_pixels = 0
for reg_val in range(scan_parameter_range[0],
scan_parameter_range[1] - 1, -1):
if self.stop_run.is_set():
break
self.register.create_restore_point(name=str(reg_val))
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
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):
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
self.raw_data_file.append(
self.fifo_readout.data,
scan_parameters=self.scan_parameters._asdict())
col_arr, row_arr = convert_data_array(
data_array_from_data_iterable(self.fifo_readout.data),
filter_func=is_data_record,
converter_func=get_col_row_array_from_data_record_array)
occ_hist, _, _ = np.histogram2d(col_arr,
row_arr,
bins=(80, 336),
range=[[1, 80], [1, 336]])
occ_mask = np.zeros(shape=occ_hist.shape,
dtype=np.dtype('>u1'))
# noisy pixels are set to 1
occ_mask[occ_hist > self.occupancy_limit * self.n_triggers *
self.consecutive_lvl1] = 1
# plot_occupancy(occ_hist.T, title='Occupancy', filename=self.scan_data_filename + '_noise_occ_' + str(reg_val) + '_' + str(step) + '.pdf')
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))
self.register.restore(name=str(reg_val))
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 # TODO
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.register.clear_restore_points(name=str(reg_val))
self.last_tdac_distribution = self.register.get_pixel_register_value(
'TDAC')
self.last_occupancy_hist = occ_hist.copy()
self.last_occupancy_mask = occ_mask.copy()
self.last_reg_val = reg_val
self.last_step = step
break
else:
logging.info(
'Found noisy pixels... repeat tuning step for Vthin_AltFine %d'
% (reg_val, ))
if disabled_pixels > disabled_pixels_limit_cnt:
self.last_good_threshold = self.register.get_global_register_value(
"Vthin_AltFine")
self.last_good_tdac = self.register.get_pixel_register_value(
'TDAC')
self.last_good_enable_mask = self.register.get_pixel_register_value(
'Enable')
break
def scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + '.pdf')
self.close_plots = True
else:
self.close_plots = False
enable_mask_steps = []
cal_lvl1_command = self.register.get_commands("CAL")[0] + self.register.get_commands("zeros", length=40)[0] + self.register.get_commands("LV1")[0]
self.write_target_threshold()
additional_scan = True
lastBitResult = np.zeros(shape=self.register.get_pixel_register_value("TDAC").shape, dtype=self.register.get_pixel_register_value("TDAC").dtype)
self.set_start_tdac()
self.occupancy_best = np.full(shape=(80, 336), fill_value=self.n_injections_tdac) # array to store the best occupancy (closest to Ninjections/2) of the pixel
self.tdac_mask_best = self.register.get_pixel_register_value("TDAC")
tdac_tune_bits = self.tdac_tune_bits[:]
for scan_parameter_value, tdac_bit in enumerate(tdac_tune_bits):
if additional_scan:
self.set_tdac_bit(tdac_bit)
logging.info('TDAC setting: bit %d = 1', tdac_bit)
else:
self.set_tdac_bit(tdac_bit, bit_value=0)
logging.info('TDAC setting: bit %d = 0', tdac_bit)
self.write_tdac_config()
with self.readout(TDAC=scan_parameter_value, reset_sram_fifo=True, fill_buffer=True, clear_buffer=True, callback=self.handle_data):
scan_loop(self,
command=cal_lvl1_command,
repeat_command=self.n_injections_tdac,
mask_steps=self.mask_steps,
enable_mask_steps=enable_mask_steps,
enable_double_columns=None,
same_mask_for_all_dc=self.same_mask_for_all_dc,
eol_function=None,
digital_injection=False,
enable_shift_masks=self.enable_shift_masks,
disable_shift_masks=self.disable_shift_masks,
restore_shift_masks=True,
mask=None,
double_column_correction=self.pulser_dac_correction)
occupancy_array, _, _ = np.histogram2d(*convert_data_array(data_array_from_data_iterable(self.fifo_readout.data), filter_func=logical_and(is_fe_word, is_data_record), converter_func=get_col_row_array_from_data_record_array), bins=(80, 336), range=[[1, 80], [1, 336]])
select_better_pixel_mask = abs(occupancy_array - self.n_injections_tdac / 2) <= abs(self.occupancy_best - self.n_injections_tdac / 2)
pixel_with_too_high_occupancy_mask = occupancy_array > self.n_injections_tdac / 2
self.occupancy_best[select_better_pixel_mask] = occupancy_array[select_better_pixel_mask]
if self.plot_intermediate_steps:
plot_three_way(occupancy_array.transpose(), title="Occupancy (TDAC tuning bit " + str(tdac_bit) + ")", x_axis_title='Occupancy', filename=self.plots_filename, maximum=self.n_injections_tdac)
tdac_mask = self.register.get_pixel_register_value("TDAC")
self.tdac_mask_best[select_better_pixel_mask] = tdac_mask[select_better_pixel_mask]
if tdac_bit > 0:
tdac_mask[pixel_with_too_high_occupancy_mask] = tdac_mask[pixel_with_too_high_occupancy_mask] & ~(1 << tdac_bit)
self.register.set_pixel_register_value("TDAC", tdac_mask)
if tdac_bit == 0:
if additional_scan: # scan bit = 0 with the correct value again
additional_scan = False
lastBitResult = occupancy_array.copy()
tdac_tune_bits.append(0) # bit 0 has to be scanned twice
else:
tdac_mask[abs(occupancy_array - self.n_injections_tdac / 2) > abs(lastBitResult - self.n_injections_tdac / 2)] = tdac_mask[abs(occupancy_array - self.n_injections_tdac / 2) > abs(lastBitResult - self.n_injections_tdac / 2)] | (1 << tdac_bit)
occupancy_array[abs(occupancy_array - self.n_injections_tdac / 2) > abs(lastBitResult - self.n_injections_tdac / 2)] = lastBitResult[abs(occupancy_array - self.n_injections_tdac / 2) > abs(lastBitResult - self.n_injections_tdac / 2)]
self.occupancy_best[abs(occupancy_array - self.n_injections_tdac / 2) <= abs(self.occupancy_best - self.n_injections_tdac / 2)] = occupancy_array[abs(occupancy_array - self.n_injections_tdac / 2) <= abs(self.occupancy_best - self.n_injections_tdac / 2)]
self.tdac_mask_best[abs(occupancy_array - self.n_injections_tdac / 2) <= abs(self.occupancy_best - self.n_injections_tdac / 2)] = tdac_mask[abs(occupancy_array - self.n_injections_tdac / 2) <= abs(self.occupancy_best - self.n_injections_tdac / 2)]
self.register.set_pixel_register_value("TDAC", self.tdac_mask_best) # set value for meta scan
self.write_tdac_config()
def scan(self):
self.start_condition_triggered = False # set to true if the start condition is true once
self.stop_condition_triggered = False # set to true if the stop condition is true once
self.start_at = 0.01 # if more than start_at*activated_pixel see at least one hit the precise scanning is started
self.stop_at = 0.95 # if more than stop_at*activated_pixel see the maximum numbers of injection, the scan is stopped
self.record_data = False # set to true to activate data storage, so far not everything is recorded to ease data analysis
scan_parameter_range = [0, (2 ** self.register.global_registers['PlsrDAC']['bitlength'] - 1)]
if self.scan_parameters.PlsrDAC[0]:
scan_parameter_range[0] = self.scan_parameters.PlsrDAC[0]
if self.scan_parameters.PlsrDAC[1]:
scan_parameter_range[1] = self.scan_parameters.PlsrDAC[1]
logging.info("Scanning %s from %d to %d", 'PlsrDAC', scan_parameter_range[0], scan_parameter_range[1])
self.scan_parameter_value = scan_parameter_range[0] # set to start value
self.search_distance = self.search_distance
self.data_points = 0 # counter variable to count the data points already recorded, have to be at least minimum_data_ponts
# calculate DCs to scan from the columns to ignore
enable_double_columns = range(0, 40)
if 1 in self.ignore_columns:
enable_double_columns.remove(0)
if set((78, 79, 80)).issubset(self.ignore_columns):
enable_double_columns.remove(39)
for double_column in range(1, 39):
if set((double_column * 2, (double_column * 2) + 1)).issubset(self.ignore_columns):
enable_double_columns.remove(double_column)
logging.info("Use DCs: %s", str(enable_double_columns))
self.select_arr_columns = range(0, 80)
for column in self.ignore_columns:
self.select_arr_columns.remove(column - 1)
while self.scan_parameter_value <= scan_parameter_range[1]: # scan as long as scan parameter is smaller than defined maximum
if self.stop_run.is_set():
break
commands = []
commands.extend(self.register.get_commands("ConfMode"))
self.register.set_global_register_value('PlsrDAC', self.scan_parameter_value)
commands.extend(self.register.get_commands("WrRegister", name=['PlsrDAC']))
self.register_utils.send_commands(commands)
with self.readout(PlsrDAC=self.scan_parameter_value, reset_sram_fifo=True, fill_buffer=True, clear_buffer=True, callback=self.handle_data if self.record_data else None):
cal_lvl1_command = self.register.get_commands("CAL")[0] + self.register.get_commands("zeros", length=40)[0] + self.register.get_commands("LV1")[0]
scan_loop(self, cal_lvl1_command, repeat_command=self.n_injections, use_delay=True, mask_steps=self.mask_steps, enable_mask_steps=self.enable_mask_steps, enable_double_columns=enable_double_columns, same_mask_for_all_dc=True, eol_function=None, digital_injection=False, enable_shift_masks=self.enable_shift_masks, disable_shift_masks=self.disable_shift_masks, restore_shift_masks=False, mask=invert_pixel_mask(self.register.get_pixel_register_value('Enable')) if self.use_enable_mask else None, double_column_correction=self.pulser_dac_correction)
if not self.start_condition_triggered or self.data_points > self.minimum_data_points: # speed up, only create histograms when needed. Python is much too slow here.
if not self.start_condition_triggered and not self.record_data:
logging.info('Testing for start condition: %s %d', 'PlsrDAC', self.scan_parameter_value)
if not self.stop_condition_triggered and self.record_data:
logging.info('Testing for stop condition: %s %d', 'PlsrDAC', self.scan_parameter_value)
col, row = convert_data_array(data_array_from_data_iterable(self.fifo_readout.data), filter_func=is_data_record, converter_func=get_col_row_array_from_data_record_array)
if np.any(np.logical_and(col < 1, col > 80)) or np.any(np.logical_and(row < 1, row > 336)): # filter bad data records that can happen
logging.warning('There are undefined %d data records (e.g. random data)', np.count_nonzero(np.logical_and(col < 1, col > 80)) + np.count_nonzero(np.logical_and(row < 1, row > 336)))
col, row = col[np.logical_and(col > 0, col <= 80)], row[np.logical_and(row > 0, row < 336)]
occupancy_array = hist_2d_index(col - 1, row - 1, shape=(80, 336))
self.scan_condition(occupancy_array)
# start condition is met for the first time
if self.start_condition_triggered and not self.record_data:
self.scan_parameter_value = self.scan_parameter_value - self.search_distance + self.step_size
if self.scan_parameter_value < 0:
self.scan_parameter_value = 0
logging.info('Starting threshold scan at %s %d', 'PlsrDAC', self.scan_parameter_value)
self.scan_parameter_start = self.scan_parameter_value
self.record_data = True
continue
# saving data
if self.record_data:
self.data_points = self.data_points + 1
# stop condition is met for the first time
if self.stop_condition_triggered and self.record_data:
logging.info('Stopping threshold scan at %s %d', 'PlsrDAC', self.scan_parameter_value)
break
# increase scan parameter value
if not self.start_condition_triggered:
self.scan_parameter_value = self.scan_parameter_value + self.search_distance
else:
self.scan_parameter_value = self.scan_parameter_value + self.step_size
if self.scan_parameter_value >= scan_parameter_range[1]:
logging.warning("Reached maximum of PlsrDAC range... stopping scan")
def scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + '.pdf')
self.close_plots = True
else:
self.close_plots = False
enable_mask_steps = []
cal_lvl1_command = self.register.get_commands("CAL")[0] + self.register.get_commands("zeros", length=40)[0] + self.register.get_commands("LV1")[0] + self.register.get_commands("zeros", mask_steps=self.mask_steps)[0]
self.write_target_charge()
additional_scan = True
lastBitResult = np.zeros(shape=self.register.get_pixel_register_value("FDAC").shape, dtype=self.register.get_pixel_register_value("FDAC").dtype)
self.set_start_fdac()
self.tot_mean_best = np.empty(shape=(80, 336)) # array to store the best occupancy (closest to Ninjections/2) of the pixel
self.tot_mean_best.fill(0)
self.fdac_mask_best = self.register.get_pixel_register_value("FDAC")
for scan_parameter_value, fdac_bit in enumerate(self.fdac_tune_bits):
if additional_scan:
self.set_fdac_bit(fdac_bit)
logging.info('FDAC setting: bit %d = 1', fdac_bit)
else:
self.set_fdac_bit(fdac_bit, bit_value=0)
logging.info('FDAC setting: bit %d = 0', fdac_bit)
self.write_fdac_config()
with self.readout(FDAC=scan_parameter_value, reset_sram_fifo=True, fill_buffer=True, clear_buffer=True, callback=self.handle_data):
scan_loop(self, cal_lvl1_command, repeat_command=self.n_injections_fdac, mask_steps=self.mask_steps, enable_mask_steps=enable_mask_steps, enable_double_columns=None, same_mask_for_all_dc=True, eol_function=None, digital_injection=False, enable_shift_masks=self.enable_shift_masks, disable_shift_masks=self.disable_shift_masks, restore_shift_masks=True, mask=None, double_column_correction=self.pulser_dac_correction)
col_row_tot = np.column_stack(convert_data_array(data_array_from_data_iterable(self.fifo_readout.data), filter_func=is_data_record, converter_func=get_col_row_tot_array_from_data_record_array))
tot_array = np.histogramdd(col_row_tot, bins=(80, 336, 16), range=[[1, 80], [1, 336], [0, 15]])[0]
tot_mean_array = np.average(tot_array, axis=2, weights=range(0, 16)) * sum(range(0, 16)) / self.n_injections_fdac
select_better_pixel_mask = abs(tot_mean_array - self.target_tot) <= abs(self.tot_mean_best - self.target_tot)
pixel_with_too_small_mean_tot_mask = tot_mean_array < self.target_tot
self.tot_mean_best[select_better_pixel_mask] = tot_mean_array[select_better_pixel_mask]
if self.plot_intermediate_steps:
plot_three_way(hist=tot_mean_array.transpose().transpose(), title="Mean ToT (FDAC tuning bit " + str(fdac_bit) + ")", x_axis_title='mean ToT', filename=self.plots_filename, minimum=0, maximum=15)
fdac_mask = self.register.get_pixel_register_value("FDAC")
self.fdac_mask_best[select_better_pixel_mask] = fdac_mask[select_better_pixel_mask]
if fdac_bit > 0:
fdac_mask[pixel_with_too_small_mean_tot_mask] = fdac_mask[pixel_with_too_small_mean_tot_mask] & ~(1 << fdac_bit)
self.register.set_pixel_register_value("FDAC", fdac_mask)
if fdac_bit == 0:
if additional_scan: # scan bit = 0 with the correct value again
additional_scan = False
lastBitResult = tot_mean_array.copy()
self.fdac_tune_bits.append(0) # bit 0 has to be scanned twice
else:
fdac_mask[abs(tot_mean_array - self.target_tot) > abs(lastBitResult - self.target_tot)] = fdac_mask[abs(tot_mean_array - self.target_tot) > abs(lastBitResult - self.target_tot)] | (1 << fdac_bit)
tot_mean_array[abs(tot_mean_array - self.target_tot) > abs(lastBitResult - self.target_tot)] = lastBitResult[abs(tot_mean_array - self.target_tot) > abs(lastBitResult - self.target_tot)]
self.tot_mean_best[abs(tot_mean_array - self.target_tot) <= abs(self.tot_mean_best - self.n_injections_fdac / 2)] = tot_mean_array[abs(tot_mean_array - self.target_tot) <= abs(self.tot_mean_best - self.n_injections_fdac / 2)]
self.fdac_mask_best[abs(tot_mean_array - self.target_tot) <= abs(self.tot_mean_best - self.n_injections_fdac / 2)] = fdac_mask[abs(tot_mean_array - self.target_tot) <= abs(self.tot_mean_best - self.n_injections_fdac / 2)]
self.register.set_pixel_register_value("FDAC", self.fdac_mask_best) # set value for meta scan
self.write_fdac_config()
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)
disabled_pixels_limit_cnt = int(self.disabled_pixels_limit * 336 * 80)
preselected_pixels = invert_pixel_mask(self.register.get_pixel_register_value('Enable')).sum()
disabled_pixels = 0
for reg_val in range(scan_parameter_range[0], scan_parameter_range[1] - 1, -1):
if self.stop_run.is_set():
break
self.register.create_restore_point(name=str(reg_val))
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.histograming.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 histograming 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.histograming.add_hits(self.interpreter.get_hits())
occ_hist = self.histograming.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.occupancy_limit * self.n_triggers * self.consecutive_lvl1] = 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))
self.register.restore(name=str(reg_val))
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.register.clear_restore_points(name=str(reg_val))
self.last_tdac_distribution = self.register.get_pixel_register_value('TDAC')
self.last_occupancy_hist = occ_hist.copy()
self.last_occupancy_mask = occ_mask.copy()
self.last_reg_val = reg_val
self.last_step = step
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:
self.last_good_threshold = self.register.get_global_register_value("Vthin_AltFine")
self.last_good_tdac = self.register.get_pixel_register_value('TDAC')
self.last_good_enable_mask = self.register.get_pixel_register_value('Enable')
break
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 scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + '.pdf')
self.close_plots = True
else:
self.close_plots = False
mask_steps = 3
enable_mask_steps = []
cal_lvl1_command = self.register.get_commands("CAL")[0] + self.register.get_commands("zeros", length=40)[0] + self.register.get_commands("LV1")[0] + self.register.get_commands("zeros", mask_steps=mask_steps)[0]
self.write_target_threshold()
additional_scan = True
lastBitResult = np.zeros(shape=self.register.get_pixel_register_value("TDAC").shape, dtype=self.register.get_pixel_register_value("TDAC").dtype)
self.set_start_tdac()
self.occupancy_best = np.empty(shape=(80, 336)) # array to store the best occupancy (closest to Ninjections/2) of the pixel
self.occupancy_best.fill(self.n_injections_tdac)
self.tdac_mask_best = self.register.get_pixel_register_value("TDAC")
for scan_parameter_value, tdac_bit in enumerate(self.tdac_tune_bits):
if additional_scan:
self.set_tdac_bit(tdac_bit)
logging.info('TDAC setting: bit %d = 1', tdac_bit)
else:
self.set_tdac_bit(tdac_bit, bit_value=0)
logging.info('TDAC setting: bit %d = 0', tdac_bit)
self.write_tdac_config()
with self.readout(TDAC=scan_parameter_value, reset_sram_fifo=True, fill_buffer=True, clear_buffer=True, callback=self.handle_data):
scan_loop(self, cal_lvl1_command, repeat_command=self.n_injections_tdac, mask_steps=mask_steps, enable_mask_steps=enable_mask_steps, enable_double_columns=None, same_mask_for_all_dc=True, eol_function=None, digital_injection=False, enable_shift_masks=self.enable_shift_masks, disable_shift_masks=self.disable_shift_masks, restore_shift_masks=True, mask=None, double_column_correction=self.pulser_dac_correction)
occupancy_array, _, _ = np.histogram2d(*convert_data_array(data_array_from_data_iterable(self.fifo_readout.data), filter_func=is_data_record, converter_func=get_col_row_array_from_data_record_array), bins=(80, 336), range=[[1, 80], [1, 336]])
select_better_pixel_mask = abs(occupancy_array - self.n_injections_tdac / 2) <= abs(self.occupancy_best - self.n_injections_tdac / 2)
pixel_with_too_high_occupancy_mask = occupancy_array > self.n_injections_tdac / 2
self.occupancy_best[select_better_pixel_mask] = occupancy_array[select_better_pixel_mask]
if self.plot_intermediate_steps:
plotThreeWay(occupancy_array.transpose(), title="Occupancy (TDAC tuning bit " + str(tdac_bit) + ")", x_axis_title='Occupancy', filename=self.plots_filename, maximum=self.n_injections_tdac)
tdac_mask = self.register.get_pixel_register_value("TDAC")
self.tdac_mask_best[select_better_pixel_mask] = tdac_mask[select_better_pixel_mask]
if tdac_bit > 0:
tdac_mask[pixel_with_too_high_occupancy_mask] = tdac_mask[pixel_with_too_high_occupancy_mask] & ~(1 << tdac_bit)
self.register.set_pixel_register_value("TDAC", tdac_mask)
if tdac_bit == 0:
if additional_scan: # scan bit = 0 with the correct value again
additional_scan = False
lastBitResult = occupancy_array.copy()
self.tdac_tune_bits.append(0) # bit 0 has to be scanned twice
else:
tdac_mask[abs(occupancy_array - self.n_injections_tdac / 2) > abs(lastBitResult - self.n_injections_tdac / 2)] = tdac_mask[abs(occupancy_array - self.n_injections_tdac / 2) > abs(lastBitResult - self.n_injections_tdac / 2)] | (1 << tdac_bit)
occupancy_array[abs(occupancy_array - self.n_injections_tdac / 2) > abs(lastBitResult - self.n_injections_tdac / 2)] = lastBitResult[abs(occupancy_array - self.n_injections_tdac / 2) > abs(lastBitResult - self.n_injections_tdac / 2)]
self.occupancy_best[abs(occupancy_array - self.n_injections_tdac / 2) <= abs(self.occupancy_best - self.n_injections_tdac / 2)] = occupancy_array[abs(occupancy_array - self.n_injections_tdac / 2) <= abs(self.occupancy_best - self.n_injections_tdac / 2)]
self.tdac_mask_best[abs(occupancy_array - self.n_injections_tdac / 2) <= abs(self.occupancy_best - self.n_injections_tdac / 2)] = tdac_mask[abs(occupancy_array - self.n_injections_tdac / 2) <= abs(self.occupancy_best - self.n_injections_tdac / 2)]
self.register.set_pixel_register_value("TDAC", self.tdac_mask_best) # set value for meta scan
self.write_tdac_config()
def scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + ".pdf")
self.close_plots = True
else:
self.close_plots = False
cal_lvl1_command = (
self.register.get_commands("CAL")[0]
+ self.register.get_commands("zeros", length=40)[0]
+ self.register.get_commands("LV1")[0]
+ self.register.get_commands("zeros", mask_steps=self.mask_steps_gdac)[0]
)
self.write_target_threshold()
for gdac_bit in self.gdac_tune_bits: # reset all GDAC bits
self.set_gdac_bit(gdac_bit, bit_value=0, send_command=False)
last_bit_result = self.n_injections_gdac
decreased_threshold = False # needed to determine if the FE is noisy
all_bits_zero = True
def bits_set(int_type):
int_type = int(int_type)
position = 0
bits_set = []
while int_type:
if int_type & 1:
bits_set.append(position)
position += 1
int_type = int_type >> 1
return bits_set
# calculate selected pixels from the mask and the disabled columns
select_mask_array = np.zeros(shape=(80, 336), dtype=np.uint8)
if not self.enable_mask_steps_gdac:
self.enable_mask_steps_gdac = range(self.mask_steps_gdac)
for mask_step in self.enable_mask_steps_gdac:
select_mask_array += make_pixel_mask(steps=self.mask_steps_gdac, shift=mask_step)
for column in bits_set(self.register.get_global_register_value("DisableColumnCnfg")):
logging.info("Deselect double column %d" % column)
select_mask_array[column, :] = 0
additional_scan = True
occupancy_best = 0
gdac_best = self.register_utils.get_gdac()
for gdac_bit in self.gdac_tune_bits:
if additional_scan:
self.set_gdac_bit(gdac_bit)
scan_parameter_value = (
self.register.get_global_register_value("Vthin_AltCoarse") << 8
) + self.register.get_global_register_value("Vthin_AltFine")
logging.info("GDAC setting: %d, bit %d = 1", scan_parameter_value, gdac_bit)
else:
self.set_gdac_bit(gdac_bit, bit_value=0)
scan_parameter_value = (
self.register.get_global_register_value("Vthin_AltCoarse") << 8
) + self.register.get_global_register_value("Vthin_AltFine")
logging.info("GDAC setting: %d, bit %d = 0", scan_parameter_value, gdac_bit)
with self.readout(
GDAC=scan_parameter_value,
reset_sram_fifo=True,
fill_buffer=True,
clear_buffer=True,
callback=self.handle_data,
):
scan_loop(
self,
cal_lvl1_command,
repeat_command=self.n_injections_gdac,
mask_steps=self.mask_steps_gdac,
enable_mask_steps=self.enable_mask_steps_gdac,
enable_double_columns=None,
same_mask_for_all_dc=True,
eol_function=None,
digital_injection=False,
enable_shift_masks=self.enable_shift_masks,
disable_shift_masks=self.disable_shift_masks,
restore_shift_masks=True,
mask=None,
double_column_correction=self.pulser_dac_correction,
)
occupancy_array, _, _ = np.histogram2d(
*convert_data_array(
data_array_from_data_iterable(self.fifo_readout.data),
filter_func=is_data_record,
converter_func=get_col_row_array_from_data_record_array,
),
bins=(80, 336),
range=[[1, 80], [1, 336]]
)
self.occ_array_sel_pixel = np.ma.array(
occupancy_array, mask=np.logical_not(np.ma.make_mask(select_mask_array))
) # take only selected pixel into account by creating a mask
median_occupancy = np.ma.median(self.occ_array_sel_pixel)
if abs(median_occupancy - self.n_injections_gdac / 2) < abs(occupancy_best - self.n_injections_gdac / 2):
occupancy_best = median_occupancy
gdac_best = self.register_utils.get_gdac()
if self.plot_intermediate_steps:
plot_three_way(
self.occ_array_sel_pixel.transpose(),
title="Occupancy (GDAC " + str(scan_parameter_value) + " with tuning bit " + str(gdac_bit) + ")",
x_axis_title="Occupancy",
filename=self.plots_filename,
maximum=self.n_injections_gdac,
)
if (
abs(median_occupancy - self.n_injections_gdac / 2) < self.max_delta_threshold and gdac_bit > 0
): # abort if good value already found to save time
logging.info(
"Median = %f, good result already achieved (median - Ninj/2 < %f), skipping not varied bits",
median_occupancy,
self.max_delta_threshold,
)
break
if median_occupancy == 0 and decreased_threshold and all_bits_zero:
logging.info("Chip may be noisy")
if gdac_bit > 0:
if (
median_occupancy < self.n_injections_gdac / 2
): # set GDAC bit to 0 if the occupancy is too lowm, thus decrease threshold
logging.info(
"Median = %f < %f, set bit %d = 0", median_occupancy, self.n_injections_gdac / 2, gdac_bit
)
self.set_gdac_bit(gdac_bit, bit_value=0)
decreased_threshold = True
else: # set GDAC bit to 1 if the occupancy is too high, thus increase threshold
logging.info(
"Median = %f > %f, leave bit %d = 1", median_occupancy, self.n_injections_gdac / 2, gdac_bit
)
decreased_threshold = False
all_bits_zero = False
elif gdac_bit == 0:
if additional_scan: # scan bit = 0 with the correct value again
additional_scan = False
last_bit_result = self.occ_array_sel_pixel.copy()
self.gdac_tune_bits.append(self.gdac_tune_bits[-1]) # the last tune bit has to be scanned twice
else:
last_bit_result_median = np.median(last_bit_result[select_mask_array > 0])
logging.info("Scanned bit 0 = 0 with %f instead of %f", median_occupancy, last_bit_result_median)
if abs(median_occupancy - self.n_injections_gdac / 2) > abs(
last_bit_result_median - self.n_injections_gdac / 2
): # if bit 0 = 0 is worse than bit 0 = 1, so go back
self.set_gdac_bit(gdac_bit, bit_value=1)
logging.info("Set bit 0 = 1")
self.occ_array_sel_pixel = last_bit_result
median_occupancy = np.ma.median(self.occ_array_sel_pixel)
else:
logging.info("Set bit 0 = 0")
if abs(occupancy_best - self.n_injections_gdac / 2) < abs(
median_occupancy - self.n_injections_gdac / 2
):
logging.info("Binary search converged to non optimal value, take best measured value instead")
median_occupancy = occupancy_best
self.register_utils.set_gdac(gdac_best, send_command=False)
self.gdac_best = self.register_utils.get_gdac()
if np.all((((self.gdac_best & (1 << np.arange(16)))) > 0).astype(int)[self.gdac_tune_bits[:-2]] == 1):
logging.warning("Selected GDAC bits reached maximum value")
elif np.all((((self.gdac_best & (1 << np.arange(16)))) > 0).astype(int)[self.gdac_tune_bits] == 0):
logging.warning("Selected GDAC bits reached minimum value")
if abs(median_occupancy - self.n_injections_gdac / 2) > 2 * self.max_delta_threshold:
logging.warning(
"Global threshold tuning failed. Delta threshold = %f > %f. Vthin_AltCoarse / Vthin_AltFine = %d / %d",
abs(median_occupancy - self.n_injections_gdac / 2),
self.max_delta_threshold,
self.register.get_global_register_value("Vthin_AltCoarse"),
self.register.get_global_register_value("Vthin_AltFine"),
)
else:
logging.info(
"Tuned GDAC to Vthin_AltCoarse / Vthin_AltFine = %d / %d",
self.register.get_global_register_value("Vthin_AltCoarse"),
self.register.get_global_register_value("Vthin_AltFine"),
)
self.gdac_best = self.register_utils.get_gdac()
def scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + '.pdf')
self.close_plots = True
else:
self.close_plots = False
enable_mask_steps = []
cal_lvl1_command = self.register.get_commands(
"CAL")[0] + self.register.get_commands(
"zeros", length=40)[0] + self.register.get_commands("LV1")[0]
self.write_target_charge()
additional_scan = True
lastBitResult = np.zeros(
shape=self.register.get_pixel_register_value("FDAC").shape,
dtype=self.register.get_pixel_register_value("FDAC").dtype)
self.set_start_fdac()
self.tot_mean_best = np.full(
shape=(80, 336), fill_value=0
) # array to store the best occupancy (closest to Ninjections/2) of the pixel
self.fdac_mask_best = self.register.get_pixel_register_value("FDAC")
fdac_tune_bits = self.fdac_tune_bits[:]
for scan_parameter_value, fdac_bit in enumerate(fdac_tune_bits):
if additional_scan:
self.set_fdac_bit(fdac_bit)
logging.info('FDAC setting: bit %d = 1', fdac_bit)
else:
self.set_fdac_bit(fdac_bit, bit_value=0)
logging.info('FDAC setting: bit %d = 0', fdac_bit)
self.write_fdac_config()
with self.readout(FDAC=scan_parameter_value,
reset_sram_fifo=True,
fill_buffer=True,
clear_buffer=True,
callback=self.handle_data):
scan_loop(self,
command=cal_lvl1_command,
repeat_command=self.n_injections_fdac,
mask_steps=self.mask_steps,
enable_mask_steps=enable_mask_steps,
enable_double_columns=None,
same_mask_for_all_dc=self.same_mask_for_all_dc,
eol_function=None,
digital_injection=False,
enable_shift_masks=self.enable_shift_masks,
disable_shift_masks=self.disable_shift_masks,
restore_shift_masks=True,
mask=None,
double_column_correction=self.pulser_dac_correction)
col_row_tot = np.column_stack(
convert_data_array(
data_array_from_data_iterable(self.fifo_readout.data),
filter_func=logical_and(is_fe_word, is_data_record),
converter_func=get_col_row_tot_array_from_data_record_array
))
tot_array = np.histogramdd(col_row_tot,
bins=(80, 336, 16),
range=[[1, 80], [1, 336], [0, 15]])[0]
tot_mean_array = np.average(
tot_array, axis=2, weights=range(0, 16)) * sum(range(
0, 16)) / self.n_injections_fdac
select_better_pixel_mask = abs(
tot_mean_array - self.target_tot) <= abs(self.tot_mean_best -
self.target_tot)
pixel_with_too_small_mean_tot_mask = tot_mean_array < self.target_tot
self.tot_mean_best[select_better_pixel_mask] = tot_mean_array[
select_better_pixel_mask]
if self.plot_intermediate_steps:
plot_three_way(hist=tot_mean_array.transpose().transpose(),
title="Mean ToT (FDAC tuning bit " +
str(fdac_bit) + ")",
x_axis_title='mean ToT',
filename=self.plots_filename,
minimum=0,
maximum=15)
fdac_mask = self.register.get_pixel_register_value("FDAC")
self.fdac_mask_best[select_better_pixel_mask] = fdac_mask[
select_better_pixel_mask]
if fdac_bit > 0:
fdac_mask[pixel_with_too_small_mean_tot_mask] = fdac_mask[
pixel_with_too_small_mean_tot_mask] & ~(1 << fdac_bit)
self.register.set_pixel_register_value("FDAC", fdac_mask)
if fdac_bit == 0:
if additional_scan: # scan bit = 0 with the correct value again
additional_scan = False
lastBitResult = tot_mean_array.copy()
fdac_tune_bits.append(0) # bit 0 has to be scanned twice
else:
fdac_mask[abs(tot_mean_array - self.target_tot) > abs(
lastBitResult - self.target_tot
)] = fdac_mask[abs(tot_mean_array - self.target_tot) > abs(
lastBitResult - self.target_tot)] | (1 << fdac_bit)
tot_mean_array[abs(tot_mean_array - self.target_tot) > abs(
lastBitResult - self.target_tot)] = lastBitResult[
abs(tot_mean_array -
self.target_tot) > abs(lastBitResult -
self.target_tot)]
self.tot_mean_best[
abs(tot_mean_array - self.target_tot) <= abs(
self.tot_mean_best -
self.n_injections_fdac / 2)] = tot_mean_array[
abs(tot_mean_array - self.target_tot) <= abs(
self.tot_mean_best -
self.n_injections_fdac / 2)]
self.fdac_mask_best[
abs(tot_mean_array - self.target_tot) <= abs(
self.tot_mean_best -
self.n_injections_fdac / 2)] = fdac_mask[
abs(tot_mean_array - self.target_tot) <= abs(
self.tot_mean_best -
self.n_injections_fdac / 2)]
self.register.set_pixel_register_value(
"FDAC", self.fdac_mask_best) # set value for meta scan
self.write_fdac_config()
def scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + '.pdf')
self.close_plots = True
else:
self.close_plots = False
def bits_set(int_type):
int_type = int(int_type)
position = 0
bits_set = []
while (int_type):
if (int_type & 1):
bits_set.append(position)
position += 1
int_type = int_type >> 1
return bits_set
# calculate selected pixels from the mask and the disabled columns
select_mask_array = np.zeros(shape=(80, 336), dtype=np.uint8)
if not self.enable_mask_steps_feedback:
self.enable_mask_steps_feedback = range(self.mask_steps)
for mask_step in self.enable_mask_steps_feedback:
select_mask_array += make_pixel_mask(steps=self.mask_steps,
shift=mask_step)
for column in bits_set(
self.register.get_global_register_value("DisableColumnCnfg")):
logging.info('Deselect double column %d' % column)
select_mask_array[column, :] = 0
cal_lvl1_command = self.register.get_commands(
"CAL")[0] + self.register.get_commands(
"zeros", length=40)[0] + self.register.get_commands("LV1")[0]
self.write_target_charge()
for feedback_bit in self.feedback_tune_bits: # reset all feedback bits
self.set_prmp_vbpf_bit(feedback_bit, bit_value=0)
additional_scan = True
tot_mean_best = 0.0
feedback_best = self.register.get_global_register_value("PrmpVbpf")
feedback_tune_bits = self.feedback_tune_bits[:]
for feedback_bit in feedback_tune_bits:
if additional_scan:
self.set_prmp_vbpf_bit(feedback_bit, bit_value=1)
logging.info(
'PrmpVbpf setting: %d, set bit %d = 1',
self.register.get_global_register_value("PrmpVbpf"),
feedback_bit)
else:
self.set_prmp_vbpf_bit(feedback_bit, bit_value=0)
logging.info(
'PrmpVbpf setting: %d, set bit %d = 0',
self.register.get_global_register_value("PrmpVbpf"),
feedback_bit)
scan_parameter_value = self.register.get_global_register_value(
"PrmpVbpf")
with self.readout(PrmpVbpf=scan_parameter_value,
reset_sram_fifo=True,
fill_buffer=True,
clear_buffer=True,
callback=self.handle_data):
scan_loop(self,
command=cal_lvl1_command,
repeat_command=self.n_injections_feedback,
mask_steps=self.mask_steps,
enable_mask_steps=self.enable_mask_steps_feedback,
enable_double_columns=None,
same_mask_for_all_dc=self.same_mask_for_all_dc,
eol_function=None,
digital_injection=False,
enable_shift_masks=self.enable_shift_masks,
disable_shift_masks=self.disable_shift_masks,
restore_shift_masks=True,
mask=None,
double_column_correction=self.pulser_dac_correction)
col_row_tot_array = np.column_stack(
convert_data_array(
data_array_from_data_iterable(self.fifo_readout.data),
filter_func=logical_and(is_fe_word, is_data_record),
converter_func=get_col_row_tot_array_from_data_record_array
))
occupancy_array, _, _ = np.histogram2d(col_row_tot_array[:, 0],
col_row_tot_array[:, 1],
bins=(80, 336),
range=[[1, 80], [1, 336]])
occupancy_array = np.ma.array(
occupancy_array,
mask=np.logical_not(np.ma.make_mask(select_mask_array))
) # take only selected pixel into account by creating a mask
occupancy_array = np.ma.masked_where(
occupancy_array > self.n_injections_feedback, occupancy_array)
col_row_tot_hist = np.histogramdd(col_row_tot_array,
bins=(80, 336, 16),
range=[[1, 80], [1, 336],
[0, 15]])[0]
tot_mean_array = np.average(
col_row_tot_hist, axis=2, weights=range(0, 16)) * sum(
range(0, 16)) / self.n_injections_feedback
tot_mean_array = np.ma.array(tot_mean_array,
mask=occupancy_array.mask)
# keep noisy pixels out
mean_tot = np.ma.mean(tot_mean_array)
if abs(mean_tot - self.target_tot) < abs(tot_mean_best -
self.target_tot):
tot_mean_best = mean_tot
feedback_best = self.register.get_global_register_value(
"PrmpVbpf")
logging.info('Mean ToT = %.2f', mean_tot)
tot_array = col_row_tot_array[:, 2]
self.tot_hist, _ = np.histogram(a=tot_array,
range=(0, 16),
bins=16)
if self.plot_intermediate_steps:
plot_tot(hist=self.tot_hist,
title='ToT distribution (PrmpVbpf ' +
str(scan_parameter_value) + ')',
filename=self.plots_filename)
# if abs(mean_tot - self.target_tot) < self.max_delta_tot and feedback_bit > 0: # abort if good value already found to save time
# logging.info('Good result already achieved, skipping missing bits')
# break
if feedback_bit > 0:
# TODO: if feedback is to high, no hits
if mean_tot < self.target_tot:
self.set_prmp_vbpf_bit(feedback_bit, bit_value=0)
logging.info('Mean ToT = %.2f < %.2f ToT, set bit %d = 0',
mean_tot, self.target_tot, feedback_bit)
else:
logging.info('Mean ToT = %.2f > %.2f ToT, keep bit %d = 1',
mean_tot, self.target_tot, feedback_bit)
elif feedback_bit == 0:
if additional_scan: # scan bit = 0 with the correct value again
additional_scan = False
last_mean_tot = mean_tot
last_tot_hist = self.tot_hist.copy()
feedback_tune_bits.append(
0) # bit 0 has to be scanned twice
else:
logging.info(
'Measured %.2f with bit 0 = 0 and %.2f with bit 0 = 1',
mean_tot, last_mean_tot)
if (abs(mean_tot - self.target_tot) >
abs(last_mean_tot - self.target_tot)
): # if bit 0 = 0 is worse than bit 0 = 1, so go back
logging.info('Set bit 0 = 1')
self.set_prmp_vbpf_bit(0, bit_value=1)
self.tot_hist = last_tot_hist.copy()
mean_tot = last_mean_tot
else:
logging.info('Keep bit 0 = 0')
# select best Feedback value
if abs(mean_tot - self.target_tot) > abs(tot_mean_best -
self.target_tot):
logging.info(
"Binary search converged to non-optimal value, apply best Feedback value, change PrmpVbpf from %d to %d",
self.register.get_global_register_value("PrmpVbpf"),
feedback_best)
mean_tot = tot_mean_best
self.register.set_global_register_value("PrmpVbpf", feedback_best)
self.feedback_best = self.register.get_global_register_value(
"PrmpVbpf")
if abs(mean_tot - self.target_tot) > 2 * self.max_delta_tot:
if np.all((((self.feedback_best & (1 << np.arange(
self.register.global_registers['PrmpVbpf']['bitlength'])))
) > 0).astype(int)[self.feedback_tune_bits] == 1):
if self.fail_on_warning:
raise RuntimeWarning(
'Selected Feedback bits reached maximum value')
else:
logging.warning(
'Selected Feedback bits reached maximum value')
elif np.all((((self.feedback_best & (1 << np.arange(
self.register.global_registers['PrmpVbpf']['bitlength'])))
) > 0).astype(int)[self.feedback_tune_bits] == 0):
if self.fail_on_warning:
raise RuntimeWarning(
'Selected Feedback bits reached minimum value')
else:
logging.warning(
'Selected Feedback bits reached minimum value')
else:
if self.fail_on_warning:
raise RuntimeWarning(
'Global feedback tuning failed. Delta ToT = %.2f > %.2f. PrmpVbpf = %d'
%
(abs(mean_tot - self.target_tot), self.max_delta_tot,
self.register.get_global_register_value("PrmpVbpf")))
else:
logging.warning(
'Global feedback tuning failed. Delta ToT = %.2f > %.2f. PrmpVbpf = %d',
abs(mean_tot - self.target_tot), self.max_delta_tot,
self.register.get_global_register_value("PrmpVbpf"))
else:
logging.info('Tuned PrmpVbpf to %d',
self.register.get_global_register_value("PrmpVbpf"))
def scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + '.pdf')
self.close_plots = True
else:
self.close_plots = False
cal_lvl1_command = self.register.get_commands(
"CAL")[0] + self.register.get_commands(
"zeros", length=40)[0] + self.register.get_commands("LV1")[0]
self.write_target_threshold()
scan_parameter_range = [
(2**self.register.global_registers['Vthin_AltFine']['bitlength']),
0
] # high to low
if self.scan_parameters.GDAC[0]:
scan_parameter_range[0] = self.scan_parameters.GDAC[0]
if self.scan_parameters.GDAC[1]:
scan_parameter_range[1] = self.scan_parameters.GDAC[1]
scan_parameter_range = range(scan_parameter_range[0],
scan_parameter_range[1] - 1,
self.step_size)
logging.info("Scanning %s from %d to %d", 'GDAC',
scan_parameter_range[0], scan_parameter_range[-1])
def bits_set(int_type):
int_type = int(int_type)
position = 0
bits_set = []
while (int_type):
if (int_type & 1):
bits_set.append(position)
position += 1
int_type = int_type >> 1
return bits_set
# calculate selected pixels from the mask and the disabled columns
select_mask_array = np.zeros(shape=(80, 336), dtype=np.uint8)
self.occ_array_sel_pixels_best = select_mask_array.copy()
self.occ_array_desel_pixels_best = select_mask_array.copy()
if not self.enable_mask_steps_gdac:
self.enable_mask_steps_gdac = range(self.mask_steps)
for mask_step in self.enable_mask_steps_gdac:
select_mask_array += make_pixel_mask(steps=self.mask_steps,
shift=mask_step)
for column in bits_set(
self.register.get_global_register_value("DisableColumnCnfg")):
logging.info('Deselect double column %d' % column)
select_mask_array[column, :] = 0
occupancy_best = 0.0
median_occupancy_last_step = 0.0
gdac_best = self.register_utils.get_gdac()
for gdac_scan_step, scan_parameter_value in enumerate(
scan_parameter_range):
self.register_utils.set_gdac(scan_parameter_value)
with self.readout(GDAC=scan_parameter_value,
reset_sram_fifo=True,
fill_buffer=True,
clear_buffer=True,
callback=self.handle_data):
scan_loop(self,
command=cal_lvl1_command,
repeat_command=self.n_injections_gdac,
mask_steps=self.mask_steps,
enable_mask_steps=self.enable_mask_steps_gdac,
enable_double_columns=None,
same_mask_for_all_dc=self.same_mask_for_all_dc,
eol_function=None,
digital_injection=False,
enable_shift_masks=self.enable_shift_masks,
disable_shift_masks=self.disable_shift_masks,
restore_shift_masks=True,
mask=None,
double_column_correction=self.pulser_dac_correction)
occupancy_array, _, _ = np.histogram2d(*convert_data_array(
data_array_from_data_iterable(self.fifo_readout.data),
filter_func=logical_and(is_fe_word, is_data_record),
converter_func=get_col_row_array_from_data_record_array),
bins=(80, 336),
range=[[1, 80], [1, 336]])
occ_array_sel_pixels = np.ma.array(
occupancy_array,
mask=np.logical_not(np.ma.make_mask(select_mask_array))
) # take only selected pixel into account by using the mask
occ_array_desel_pixels = np.ma.array(
occupancy_array, mask=np.ma.make_mask(select_mask_array)
) # take only de-selected pixel into account by using the inverted mask
median_occupancy = np.ma.median(occ_array_sel_pixels)
noise_occupancy = np.ma.median(occ_array_desel_pixels)
occupancy_almost_zero = np.allclose(median_occupancy, 0)
no_noise = np.allclose(noise_occupancy, 0)
if no_noise and not occupancy_almost_zero and abs(
median_occupancy - self.n_injections_gdac /
2) < abs(occupancy_best - self.n_injections_gdac / 2):
occupancy_best = median_occupancy
gdac_best = self.register_utils.get_gdac()
self.occ_array_sel_pixels_best = occ_array_sel_pixels.copy()
self.occ_array_desel_pixels_best = occ_array_desel_pixels.copy(
)
if self.plot_intermediate_steps:
plot_three_way(self.occ_array_sel_pixel.transpose(),
title="Occupancy (GDAC " +
str(scan_parameter_value) + ")",
x_axis_title='Occupancy',
filename=self.plots_filename,
maximum=self.n_injections_gdac)
if no_noise and not occupancy_almost_zero and median_occupancy >= median_occupancy_last_step and median_occupancy >= self.n_injections_gdac / 2:
break
if no_noise and not occupancy_almost_zero:
median_occupancy_last_step = median_occupancy
else:
median_occupancy_last_step = 0.0
self.register_utils.set_gdac(gdac_best, send_command=False)
median_occupancy = occupancy_best
self.gdac_best = self.register_utils.get_gdac()
if abs(median_occupancy -
self.n_injections_gdac / 2) > self.max_delta_threshold:
if np.all((((self.gdac_best & (1 << np.arange(
self.register.global_registers['Vthin_AltFine']
['bitlength'] + self.register.global_registers['Vthin_AltFine']
['bitlength'])))) > 0).astype(int) == 0):
if self.fail_on_warning:
raise RuntimeWarning(
'Selected GDAC bits reached minimum value')
else:
logging.warning('Selected GDAC bits reached minimum value')
else:
if self.fail_on_warning:
raise RuntimeWarning(
'Global threshold tuning failed. Delta threshold = %.2f > %.2f. Vthin_AltCoarse / Vthin_AltFine = %d / %d'
% (abs(median_occupancy - self.n_injections_gdac / 2),
self.max_delta_threshold,
self.register.get_global_register_value(
"Vthin_AltCoarse"),
self.register.get_global_register_value(
"Vthin_AltFine")))
else:
logging.warning(
'Global threshold tuning failed. Delta threshold = %.2f > %.2f. Vthin_AltCoarse / Vthin_AltFine = %d / %d',
abs(median_occupancy - self.n_injections_gdac / 2),
self.max_delta_threshold,
self.register.get_global_register_value(
"Vthin_AltCoarse"),
self.register.get_global_register_value(
"Vthin_AltFine"))
else:
logging.info(
'Tuned GDAC to Vthin_AltCoarse / Vthin_AltFine = %d / %d',
self.register.get_global_register_value("Vthin_AltCoarse"),
self.register.get_global_register_value("Vthin_AltFine"))
def scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + '.pdf')
self.close_plots = True
else:
self.close_plots = False
cal_lvl1_command = self.register.get_commands(
"CAL")[0] + self.register.get_commands(
"zeros", length=40)[0] + self.register.get_commands(
"LV1")[0] + self.register.get_commands(
"zeros", mask_steps=self.mask_steps_gdac)[0]
self.write_target_threshold()
for gdac_bit in self.gdac_tune_bits: # reset all GDAC bits
self.set_gdac_bit(gdac_bit, bit_value=0, send_command=False)
last_bit_result = self.n_injections_gdac
decreased_threshold = False # needed to determine if the FE is noisy
all_bits_zero = True
def bits_set(int_type):
int_type = int(int_type)
position = 0
bits_set = []
while (int_type):
if (int_type & 1):
bits_set.append(position)
position += 1
int_type = int_type >> 1
return bits_set
# calculate selected pixels from the mask and the disabled columns
select_mask_array = np.zeros(shape=(80, 336), dtype=np.uint8)
if not self.enable_mask_steps_gdac:
self.enable_mask_steps_gdac = range(self.mask_steps_gdac)
for mask_step in self.enable_mask_steps_gdac:
select_mask_array += make_pixel_mask(steps=self.mask_steps_gdac,
shift=mask_step)
for column in bits_set(
self.register.get_global_register_value("DisableColumnCnfg")):
logging.info('Deselect double column %d' % column)
select_mask_array[column, :] = 0
additional_scan = True
occupancy_best = 0
gdac_best = self.register_utils.get_gdac()
for gdac_bit in self.gdac_tune_bits:
if additional_scan:
self.set_gdac_bit(gdac_bit)
scan_parameter_value = (
self.register.get_global_register_value("Vthin_AltCoarse")
<< 8
) + self.register.get_global_register_value("Vthin_AltFine")
logging.info('GDAC setting: %d, bit %d = 1',
scan_parameter_value, gdac_bit)
else:
self.set_gdac_bit(gdac_bit, bit_value=0)
scan_parameter_value = (
self.register.get_global_register_value("Vthin_AltCoarse")
<< 8
) + self.register.get_global_register_value("Vthin_AltFine")
logging.info('GDAC setting: %d, bit %d = 0',
scan_parameter_value, gdac_bit)
with self.readout(GDAC=scan_parameter_value,
reset_sram_fifo=True,
fill_buffer=True,
clear_buffer=True,
callback=self.handle_data):
scan_loop(self,
cal_lvl1_command,
repeat_command=self.n_injections_gdac,
mask_steps=self.mask_steps_gdac,
enable_mask_steps=self.enable_mask_steps_gdac,
enable_double_columns=None,
same_mask_for_all_dc=True,
eol_function=None,
digital_injection=False,
enable_shift_masks=self.enable_shift_masks,
disable_shift_masks=self.disable_shift_masks,
restore_shift_masks=True,
mask=None,
double_column_correction=self.pulser_dac_correction)
occupancy_array, _, _ = np.histogram2d(*convert_data_array(
data_array_from_data_iterable(self.fifo_readout.data),
filter_func=is_data_record,
converter_func=get_col_row_array_from_data_record_array),
bins=(80, 336),
range=[[1, 80], [1, 336]])
self.occ_array_sel_pixel = np.ma.array(
occupancy_array,
mask=np.logical_not(np.ma.make_mask(select_mask_array))
) # take only selected pixel into account by creating a mask
median_occupancy = np.ma.median(self.occ_array_sel_pixel)
if abs(median_occupancy - self.n_injections_gdac /
2) < abs(occupancy_best - self.n_injections_gdac / 2):
occupancy_best = median_occupancy
gdac_best = self.register_utils.get_gdac()
if self.plot_intermediate_steps:
plot_three_way(self.occ_array_sel_pixel.transpose(),
title="Occupancy (GDAC " +
str(scan_parameter_value) +
" with tuning bit " + str(gdac_bit) + ")",
x_axis_title='Occupancy',
filename=self.plots_filename,
maximum=self.n_injections_gdac)
if abs(
median_occupancy - self.n_injections_gdac / 2
) < self.max_delta_threshold and gdac_bit > 0: # abort if good value already found to save time
logging.info(
'Median = %f, good result already achieved (median - Ninj/2 < %f), skipping not varied bits',
median_occupancy, self.max_delta_threshold)
break
if median_occupancy == 0 and decreased_threshold and all_bits_zero:
logging.info('Chip may be noisy')
if gdac_bit > 0:
if (
median_occupancy < self.n_injections_gdac / 2
): # set GDAC bit to 0 if the occupancy is too lowm, thus decrease threshold
logging.info('Median = %f < %f, set bit %d = 0',
median_occupancy, self.n_injections_gdac / 2,
gdac_bit)
self.set_gdac_bit(gdac_bit, bit_value=0)
decreased_threshold = True
else: # set GDAC bit to 1 if the occupancy is too high, thus increase threshold
logging.info('Median = %f > %f, leave bit %d = 1',
median_occupancy, self.n_injections_gdac / 2,
gdac_bit)
decreased_threshold = False
all_bits_zero = False
elif gdac_bit == 0:
if additional_scan: # scan bit = 0 with the correct value again
additional_scan = False
last_bit_result = self.occ_array_sel_pixel.copy()
self.gdac_tune_bits.append(
self.gdac_tune_bits[-1]
) # the last tune bit has to be scanned twice
else:
last_bit_result_median = np.median(
last_bit_result[select_mask_array > 0])
logging.info('Scanned bit 0 = 0 with %f instead of %f',
median_occupancy, last_bit_result_median)
if abs(median_occupancy - self.n_injections_gdac / 2) > abs(
last_bit_result_median - self.n_injections_gdac / 2
): # if bit 0 = 0 is worse than bit 0 = 1, so go back
self.set_gdac_bit(gdac_bit, bit_value=1)
logging.info('Set bit 0 = 1')
self.occ_array_sel_pixel = last_bit_result
median_occupancy = np.ma.median(
self.occ_array_sel_pixel)
else:
logging.info('Set bit 0 = 0')
if abs(occupancy_best - self.n_injections_gdac / 2) < abs(
median_occupancy - self.n_injections_gdac / 2):
logging.info(
"Binary search converged to non optimal value, take best measured value instead"
)
median_occupancy = occupancy_best
self.register_utils.set_gdac(gdac_best,
send_command=False)
self.gdac_best = self.register_utils.get_gdac()
if np.all((((self.gdac_best & (1 << np.arange(16)))) > 0
).astype(int)[self.gdac_tune_bits[:-2]] == 1):
logging.warning('Selected GDAC bits reached maximum value')
elif np.all((((self.gdac_best & (1 << np.arange(16)))) > 0
).astype(int)[self.gdac_tune_bits] == 0):
logging.warning('Selected GDAC bits reached minimum value')
if abs(median_occupancy -
self.n_injections_gdac / 2) > 2 * self.max_delta_threshold:
logging.warning(
'Global threshold tuning failed. Delta threshold = %f > %f. Vthin_AltCoarse / Vthin_AltFine = %d / %d',
abs(median_occupancy - self.n_injections_gdac / 2),
self.max_delta_threshold,
self.register.get_global_register_value("Vthin_AltCoarse"),
self.register.get_global_register_value("Vthin_AltFine"))
else:
logging.info(
'Tuned GDAC to Vthin_AltCoarse / Vthin_AltFine = %d / %d',
self.register.get_global_register_value("Vthin_AltCoarse"),
self.register.get_global_register_value("Vthin_AltFine"))
self.gdac_best = self.register_utils.get_gdac()
def scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + '.pdf')
self.close_plots = True
else:
self.close_plots = False
cal_lvl1_command = self.register.get_commands(
"CAL")[0] + self.register.get_commands(
"zeros", length=40)[0] + self.register.get_commands("LV1")[0]
self.write_target_threshold()
for gdac_bit in self.gdac_tune_bits: # reset all GDAC bits
self.set_gdac_bit(gdac_bit, bit_value=0, send_command=False)
def bits_set(int_type):
int_type = int(int_type)
position = 0
bits_set = []
while (int_type):
if (int_type & 1):
bits_set.append(position)
position += 1
int_type = int_type >> 1
return bits_set
# calculate selected pixels from the mask and the disabled columns
select_mask_array = np.zeros(shape=(80, 336), dtype=np.uint8)
self.occ_array_sel_pixels_best = select_mask_array.copy()
self.occ_array_desel_pixels_best = select_mask_array.copy()
if not self.enable_mask_steps_gdac:
self.enable_mask_steps_gdac = range(self.mask_steps)
for mask_step in self.enable_mask_steps_gdac:
select_mask_array += make_pixel_mask(steps=self.mask_steps,
shift=mask_step)
for column in bits_set(
self.register.get_global_register_value("DisableColumnCnfg")):
logging.info('Deselect double column %d' % column)
select_mask_array[column, :] = 0
additional_scan = True
additional_scan_ongoing = False
occupancy_best = 0.0
last_good_gdac_bit = self.gdac_tune_bits[0]
last_good_gdac_scan_step = 0
gdac_tune_bits_permutation = 0
gdac_best = self.register_utils.get_gdac()
gdac_tune_bits = self.gdac_tune_bits[:]
min_gdac_with_occupancy = None
for gdac_scan_step, gdac_bit in enumerate(gdac_tune_bits):
if additional_scan:
self.set_gdac_bit(gdac_bit, bit_value=1, send_command=True)
scan_parameter_value = (
self.register.get_global_register_value("Vthin_AltCoarse")
<< 8
) + self.register.get_global_register_value("Vthin_AltFine")
logging.info('GDAC setting: %d, set bit %d = 1',
scan_parameter_value, gdac_bit)
else:
self.set_gdac_bit(gdac_bit, bit_value=0, send_command=True)
scan_parameter_value = (
self.register.get_global_register_value("Vthin_AltCoarse")
<< 8
) + self.register.get_global_register_value("Vthin_AltFine")
logging.info('GDAC setting: %d, set bit %d = 0',
scan_parameter_value, gdac_bit)
with self.readout(GDAC=scan_parameter_value,
reset_sram_fifo=True,
fill_buffer=True,
clear_buffer=True,
callback=self.handle_data):
scan_loop(self,
command=cal_lvl1_command,
repeat_command=self.n_injections_gdac,
mask_steps=self.mask_steps,
enable_mask_steps=self.enable_mask_steps_gdac,
enable_double_columns=None,
same_mask_for_all_dc=self.same_mask_for_all_dc,
eol_function=None,
digital_injection=False,
enable_shift_masks=self.enable_shift_masks,
disable_shift_masks=self.disable_shift_masks,
restore_shift_masks=True,
mask=None,
double_column_correction=self.pulser_dac_correction)
occupancy_array, _, _ = np.histogram2d(*convert_data_array(
data_array_from_data_iterable(self.fifo_readout.data),
filter_func=logical_and(is_fe_word, is_data_record),
converter_func=get_col_row_array_from_data_record_array),
bins=(80, 336),
range=[[1, 80], [1, 336]])
occ_array_sel_pixels = np.ma.array(
occupancy_array,
mask=np.logical_not(np.ma.make_mask(select_mask_array))
) # take only selected pixel into account by using the mask
occ_array_desel_pixels = np.ma.array(
occupancy_array, mask=np.ma.make_mask(select_mask_array)
) # take only de-selected pixel into account by using the inverted mask
median_occupancy = np.ma.median(occ_array_sel_pixels)
noise_occupancy = np.ma.median(occ_array_desel_pixels)
occupancy_almost_zero = np.allclose(median_occupancy, 0)
no_noise = np.allclose(noise_occupancy, 0)
if abs(median_occupancy - self.n_injections_gdac /
2) < abs(occupancy_best - self.n_injections_gdac / 2):
occupancy_best = median_occupancy
gdac_best = self.register_utils.get_gdac()
self.occ_array_sel_pixels_best = occ_array_sel_pixels.copy()
self.occ_array_desel_pixels_best = occ_array_desel_pixels.copy(
)
if self.plot_intermediate_steps:
plot_three_way(self.occ_array_sel_pixel.transpose(),
title="Occupancy (GDAC " +
str(scan_parameter_value) +
" with tuning bit " + str(gdac_bit) + ")",
x_axis_title='Occupancy',
filename=self.plots_filename,
maximum=self.n_injections_gdac)
if not occupancy_almost_zero and no_noise:
if min_gdac_with_occupancy is None:
min_gdac_with_occupancy = self.register_utils.get_gdac()
else:
min_gdac_with_occupancy = min(
min_gdac_with_occupancy,
self.register_utils.get_gdac())
if gdac_bit > 0:
# GDAC too low, no hits
if occupancy_almost_zero and no_noise and self.register_utils.get_gdac(
) < min_gdac_with_occupancy:
logging.info(
'Median = %.2f > %.2f, GDAC possibly too low, keep bit %d = 1',
median_occupancy, self.n_injections_gdac / 2, gdac_bit)
# GDAC too high, less hits, decrease GDAC
elif no_noise and median_occupancy < (
self.n_injections_gdac / 2
): # set GDAC bit to 0 if the occupancy is too low, thus decrease threshold
try:
next_gdac_bit = gdac_tune_bits[gdac_scan_step + 1]
except IndexError:
next_gdac_bit = None
# check if new value is below lower limit
if self.gdac_lower_limit and (
next_gdac_bit is not None
and self.register_utils.get_gdac() - 2**gdac_bit +
2**next_gdac_bit < self.gdac_lower_limit) or (
next_gdac_bit is None
and self.register_utils.get_gdac() -
2**gdac_bit < self.gdac_lower_limit):
logging.info(
'Median = %.2f < %.2f, reaching lower GDAC limit, keep bit %d = 1',
median_occupancy, self.n_injections_gdac / 2,
gdac_bit)
else:
logging.info('Median = %.2f < %.2f, set bit %d = 0',
median_occupancy,
self.n_injections_gdac / 2, gdac_bit)
self.set_gdac_bit(
gdac_bit, bit_value=0, send_command=False
) # do not write, might be too low, do this in next iteration
# GDAC too low, more hits
else:
logging.info('Median = %.2f > %.2f, keep bit %d = 1',
median_occupancy, self.n_injections_gdac / 2,
gdac_bit)
elif gdac_bit == 0:
if not additional_scan_ongoing and (
(occupancy_almost_zero and no_noise) or not no_noise
) and len(self.gdac_tune_bits) > last_good_gdac_scan_step + 2:
self.set_gdac_bit(0, bit_value=0,
send_command=False) # turn off LSB
if len(
gdac_tune_bits
) == gdac_scan_step + 1 and gdac_tune_bits_permutation == 0: # min. 2 bits for bin search
self.set_gdac_bit(
last_good_gdac_bit,
bit_value=1,
send_command=False) # always enable highest bit
gdac_tune_bits.extend(
self.gdac_tune_bits[last_good_gdac_scan_step + 1:]
) # repeat all scan stept from last bit
for gdac_clear_bit in self.gdac_tune_bits[:
last_good_gdac_scan_step]:
self.set_gdac_bit(gdac_clear_bit,
bit_value=0,
send_command=False)
if 2**last_good_gdac_scan_step == 1: # last step, cleanup
last_good_gdac_bit = self.gdac_tune_bits[
last_good_gdac_scan_step + 1]
last_good_gdac_scan_step += 1
else:
gdac_tune_bits_permutation += 1
else:
gdac_tune_bits_permutation_header = map(
int,
bin(gdac_tune_bits_permutation)[2:].zfill(
last_good_gdac_scan_step))
for gdac_permutation_bit, gdac_permutation_bit_value in enumerate(
gdac_tune_bits_permutation_header):
self.set_gdac_bit(
self.gdac_tune_bits[gdac_permutation_bit],
bit_value=gdac_permutation_bit_value,
send_command=False)
gdac_tune_bits.extend(
self.gdac_tune_bits[last_good_gdac_scan_step + 1:])
if 2**last_good_gdac_scan_step > gdac_tune_bits_permutation + 1:
gdac_tune_bits_permutation += 1
else: # last step, cleanup
gdac_tune_bits_permutation = 0
last_good_gdac_bit = self.gdac_tune_bits[
last_good_gdac_scan_step + 1]
last_good_gdac_scan_step += 1
elif additional_scan: # scan bit = 0 with the correct value again
additional_scan = False
additional_scan_ongoing = True
last_occ_array_sel_pixels = occ_array_sel_pixels.copy()
last_occ_array_desel_pixels = occ_array_desel_pixels.copy()
gdac_tune_bits.append(
0) # the last tune bit has to be scanned twice
else:
additional_scan_ongoing = False
last_median_occupancy = np.ma.median(
last_occ_array_sel_pixels)
logging.info(
'Measured %.2f with bit 0 = 0 with and %.2f with bit 0 = 1',
median_occupancy, last_median_occupancy)
if abs(median_occupancy - self.n_injections_gdac / 2) > abs(
last_median_occupancy - self.n_injections_gdac / 2
): # if bit 0 = 0 is worse than bit 0 = 1, so go back
logging.info('Set bit 0 = 1')
self.set_gdac_bit(0, bit_value=1, send_command=True)
occ_array_sel_pixels = last_occ_array_sel_pixels.copy()
occ_array_desel_pixels = last_occ_array_desel_pixels.copy(
)
median_occupancy = last_median_occupancy
else:
logging.info('Keep bit 0 = 0')
# select best GDAC value
if abs(occupancy_best -
self.n_injections_gdac / 2) < abs(median_occupancy -
self.n_injections_gdac / 2):
logging.info(
"Binary search converged to non-optimal value, apply best GDAC value, change GDAC from %d to %d",
self.register_utils.get_gdac(), gdac_best)
median_occupancy = occupancy_best
self.register_utils.set_gdac(gdac_best, send_command=False)
self.gdac_best = self.register_utils.get_gdac()
if abs(median_occupancy -
self.n_injections_gdac / 2) > self.max_delta_threshold:
if np.all((((self.gdac_best & (1 << np.arange(
self.register.global_registers['Vthin_AltFine']
['bitlength'] + self.register.global_registers['Vthin_AltFine']
['bitlength'])))) > 0).astype(int)[self.gdac_tune_bits] == 1):
if self.fail_on_warning:
raise RuntimeWarning(
'Selected GDAC bits reached maximum value')
else:
logging.warning('Selected GDAC bits reached maximum value')
elif np.all((((self.gdac_best & (1 << np.arange(
self.register.global_registers['Vthin_AltFine']
['bitlength'] + self.register.global_registers['Vthin_AltFine']
['bitlength'])))) > 0).astype(int)[self.gdac_tune_bits] == 0):
if self.fail_on_warning:
raise RuntimeWarning(
'Selected GDAC bits reached minimum value')
else:
logging.warning('Selected GDAC bits reached minimum value')
else:
if self.fail_on_warning:
raise RuntimeWarning(
'Global threshold tuning failed. Delta threshold = %.2f > %.2f. Vthin_AltCoarse / Vthin_AltFine = %d / %d'
% (abs(median_occupancy - self.n_injections_gdac / 2),
self.max_delta_threshold,
self.register.get_global_register_value(
"Vthin_AltCoarse"),
self.register.get_global_register_value(
"Vthin_AltFine")))
else:
logging.warning(
'Global threshold tuning failed. Delta threshold = %.2f > %.2f. Vthin_AltCoarse / Vthin_AltFine = %d / %d',
abs(median_occupancy - self.n_injections_gdac / 2),
self.max_delta_threshold,
self.register.get_global_register_value(
"Vthin_AltCoarse"),
self.register.get_global_register_value(
"Vthin_AltFine"))
else:
logging.info(
'Tuned GDAC to Vthin_AltCoarse / Vthin_AltFine = %d / %d',
self.register.get_global_register_value("Vthin_AltCoarse"),
self.register.get_global_register_value("Vthin_AltFine"))
def scan(self):
self.start_condition_triggered = False # set to true if the start condition is true once
self.stop_condition_triggered = False # set to true if the stop condition is true once
self.start_at = 0.01 # if more than start_at*activated_pixel see at least one hit the precise scanning is started
self.stop_at = 0.95 # if more than stop_at*activated_pixel see the maximum numbers of injection, the scan is stopped
self.record_data = False # set to true to activate data storage, so far not everything is recorded to ease data analysis
scan_parameter_range = [
0, (2**self.register.global_registers['PlsrDAC']['bitlength'])
]
if self.scan_parameters.PlsrDAC[0]:
scan_parameter_range[0] = self.scan_parameters.PlsrDAC[0]
if self.scan_parameters.PlsrDAC[1]:
scan_parameter_range[1] = self.scan_parameters.PlsrDAC[1]
logging.info(
"Scanning %s from %d to %d" %
('PlsrDAC', scan_parameter_range[0], scan_parameter_range[1]))
self.scan_parameter_value = scan_parameter_range[
0] # set to start value
self.search_distance = self.search_distance
self.data_points = 0 # counter variable to count the data points already recorded, have to be at least minimum_data_ponts
# calculate DCs to scan from the columns to ignore
enable_double_columns = range(0, 40)
if 1 in self.ignore_columns:
enable_double_columns.remove(0)
if set((78, 79, 80)).issubset(self.ignore_columns):
enable_double_columns.remove(39)
for double_column in range(1, 39):
if set((double_column * 2,
(double_column * 2) + 1)).issubset(self.ignore_columns):
enable_double_columns.remove(double_column)
logging.info("Use DCs: %s" % str(enable_double_columns))
self.select_arr_columns = range(0, 80)
for column in self.ignore_columns:
self.select_arr_columns.remove(column - 1)
while self.scan_parameter_value <= scan_parameter_range[
1]: # scan as long as scan parameter is smaller than defined maximum
if self.stop_run.is_set():
break
if self.record_data:
logging.info(
"Scan step %d (%s %d)" %
(self.data_points, 'PlsrDAC', self.scan_parameter_value))
commands = []
commands.extend(self.register.get_commands("ConfMode"))
self.register.set_global_register_value('PlsrDAC',
self.scan_parameter_value)
commands.extend(
self.register.get_commands("WrRegister", name=['PlsrDAC']))
self.register_utils.send_commands(commands)
with self.readout(PlsrDAC=self.scan_parameter_value):
cal_lvl1_command = self.register.get_commands(
"CAL")[0] + self.register.get_commands(
"zeros",
length=40)[0] + self.register.get_commands("LV1")[0]
scan_loop(self,
cal_lvl1_command,
repeat_command=self.n_injections,
use_delay=True,
mask_steps=self.mask_steps,
enable_mask_steps=self.enable_mask_steps,
enable_double_columns=enable_double_columns,
same_mask_for_all_dc=True,
eol_function=None,
digital_injection=False,
enable_shift_masks=self.enable_shift_masks,
disable_shift_masks=self.disable_shift_masks,
restore_shift_masks=False,
mask=invert_pixel_mask(
self.register.get_pixel_register_value('Enable'))
if self.use_enable_mask else None,
double_column_correction=self.pulser_dac_correction)
if not self.start_condition_triggered or self.data_points > self.minimum_data_points: # speed up, only create histograms when needed. Python is much too slow here.
if not self.start_condition_triggered and not self.record_data:
logging.info('Testing for start condition: %s %d' %
('PlsrDAC', self.scan_parameter_value))
if not self.stop_condition_triggered and self.record_data:
logging.info('Testing for stop condition: %s %d' %
('PlsrDAC', self.scan_parameter_value))
col, row = convert_data_array(
data_array_from_data_iterable(self.fifo_readout.data),
filter_func=is_data_record,
converter_func=get_col_row_array_from_data_record_array)
# using self written histogrammer in C++
occupancy_array = hist_2d_index(col - 1,
row - 1,
shape=(80, 336))
# using numpy
# occupancy_array = np.histogram2d(col, row, bins=(80, 336), range=[[1, 80], [1, 336]])[0]
self.scan_condition(occupancy_array)
# start condition is met for the first time
if self.start_condition_triggered and not self.record_data:
self.scan_parameter_value = self.scan_parameter_value - self.search_distance + self.step_size
if self.scan_parameter_value < 0:
self.scan_parameter_value = 0
logging.info('Starting threshold scan at %s %d' %
('PlsrDAC', self.scan_parameter_value))
self.scan_parameter_start = self.scan_parameter_value
self.record_data = True
continue
# saving data
if self.record_data:
self.data_points = self.data_points + 1
self.raw_data_file.append(
self.fifo_readout.data,
scan_parameters=self.scan_parameters._asdict())
# stop condition is met for the first time
if self.stop_condition_triggered and self.record_data:
logging.info('Stopping threshold scan at %s %d' %
('PlsrDAC', self.scan_parameter_value))
break
# increase scan parameter value
if not self.start_condition_triggered:
self.scan_parameter_value = self.scan_parameter_value + self.search_distance
else:
self.scan_parameter_value = self.scan_parameter_value + self.step_size
if self.scan_parameter_value >= scan_parameter_range[1]:
logging.warning(
"Reached maximum of PlsrDAC range... stopping scan")
def scan(self):
if not self.plots_filename:
self.plots_filename = PdfPages(self.output_filename + '.pdf')
self.close_plots = True
else:
self.close_plots = False
enable_mask_steps = [0] # one mask step to increase speed, no effect on precision
cal_lvl1_command = self.register.get_commands("CAL")[0] + self.register.get_commands("zeros", length=40)[0] + self.register.get_commands("LV1")[0] + self.register.get_commands("zeros", mask_steps=self.mask_steps)[0]
self.write_target_charge()
for feedback_bit in self.feedback_tune_bits: # reset all GDAC bits
self.set_prmp_vbpf_bit(feedback_bit, bit_value=0)
additional_scan = True
last_bit_result = self.n_injections_feedback
tot_mean_best = 0
feedback_best = self.register.get_global_register_value("PrmpVbpf")
for feedback_bit in self.feedback_tune_bits:
if additional_scan:
self.set_prmp_vbpf_bit(feedback_bit)
logging.info('PrmpVbpf setting: %d, bit %d = 1', self.register.get_global_register_value("PrmpVbpf"), feedback_bit)
else:
self.set_prmp_vbpf_bit(feedback_bit, bit_value=0)
logging.info('PrmpVbpf setting: %d, bit %d = 0', self.register.get_global_register_value("PrmpVbpf"), feedback_bit)
scan_parameter_value = self.register.get_global_register_value("PrmpVbpf")
with self.readout(PrmpVbpf=scan_parameter_value, reset_sram_fifo=True, fill_buffer=True, clear_buffer=True, callback=self.handle_data):
scan_loop(self, cal_lvl1_command, repeat_command=self.n_injections_feedback, mask_steps=self.mask_steps, enable_mask_steps=enable_mask_steps, enable_double_columns=None, same_mask_for_all_dc=True, eol_function=None, digital_injection=False, enable_shift_masks=self.enable_shift_masks, disable_shift_masks=self.disable_shift_masks, restore_shift_masks=True, mask=None, double_column_correction=self.pulser_dac_correction)
tots = convert_data_array(data_array_from_data_iterable(self.fifo_readout.data), filter_func=is_data_record, converter_func=get_tot_array_from_data_record_array)
mean_tot = np.mean(tots)
if np.isnan(mean_tot):
logging.error("No hits, ToT calculation not possible, tuning will fail")
if abs(mean_tot - self.target_tot) < abs(tot_mean_best - self.target_tot):
tot_mean_best = mean_tot
feedback_best = self.register.get_global_register_value("PrmpVbpf")
logging.info('Mean ToT = %f', mean_tot)
self.tot_array, _ = np.histogram(a=tots, range=(0, 16), bins=16)
if self.plot_intermediate_steps:
plot_tot(hist=self.tot_array, title='ToT distribution (PrmpVbpf ' + str(scan_parameter_value) + ')', filename=self.plots_filename)
if abs(mean_tot - self.target_tot) < self.max_delta_tot and feedback_bit > 0: # abort if good value already found to save time
logging.info('Good result already achieved, skipping missing bits')
break
if feedback_bit > 0 and mean_tot < self.target_tot:
self.set_prmp_vbpf_bit(feedback_bit, bit_value=0)
logging.info('Mean ToT = %f < %d ToT, set bit %d = 0', mean_tot, self.target_tot, feedback_bit)
if feedback_bit == 0:
if additional_scan: # scan bit = 0 with the correct value again
additional_scan = False
last_bit_result = mean_tot
self.feedback_tune_bits.append(0) # bit 0 has to be scanned twice
else:
logging.info('Scanned bit 0 = 0 with %f instead of %f for scanned bit 0 = 1', mean_tot, last_bit_result)
if(abs(mean_tot - self.target_tot) > abs(last_bit_result - self.target_tot)): # if bit 0 = 0 is worse than bit 0 = 1, so go back
self.set_prmp_vbpf_bit(feedback_bit, bit_value=1)
mean_tot = last_bit_result
logging.info('Set bit 0 = 1')
else:
logging.info('Set bit 0 = 0')
if abs(mean_tot - self.target_tot) > abs(tot_mean_best - self.target_tot):
logging.info("Binary search converged to non optimal value, take best measured value instead")
mean_tot = tot_mean_best
self.register.set_global_register_value("PrmpVbpf", feedback_best)
if self.register.get_global_register_value("PrmpVbpf") == 0 or self.register.get_global_register_value("PrmpVbpf") == 254:
logging.warning('PrmpVbpf reached minimum/maximum value')
if self.fail_on_warning:
raise RuntimeWarning('PrmpVbpf reached minimum/maximum value')
if abs(mean_tot - self.target_tot) > 2 * self.max_delta_tot:
logging.warning('Global feedback tuning failed. Delta ToT = %f > %f. PrmpVbpf = %d', abs(mean_tot - self.target_tot), self.max_delta_tot, self.register.get_global_register_value("PrmpVbpf"))
if self.fail_on_warning:
raise RuntimeWarning('Global feedback tuning failed.')
else:
logging.info('Tuned PrmpVbpf to %d', self.register.get_global_register_value("PrmpVbpf"))
self.feedback_best = self.register.get_global_register_value("PrmpVbpf")
