def do1d(
param_set: _BaseParameter,
xarray,
delay: float,
*param_meas: qcnd.ParamMeasT,
exp: Optional[Experiment] = None,
use_threads: Optional[bool] = None,
enter_actions: qcnd.ActionsT = (),
exit_actions: qcnd.ActionsT = (),
additional_setpoints: Sequence[qcnd.ParamMeasT] = tuple(),
):
if not _is_monotonic(xarray):
warn('Sweep array is not monotonic. This is pretty weird. Reconsider.')
meas = Measurement(exp=exp)
all_setpoint_params = (param_set, ) + tuple(s
for s in additional_setpoints)
measured_parameters = tuple(param for param in param_meas
if isinstance(param, _BaseParameter))
if (len(measured_parameters) > 2) or (use_threads == True):
use_threads = True
else:
use_threads = False
try:
loop_shape = tuple(1 for _ in additional_setpoints) + (len(xarray), )
shapes: Shapes = detect_shape_of_measurement(measured_parameters,
loop_shape)
except TypeError:
warn(f"Could not detect shape of {measured_parameters} "
f"falling back to unknown shape.")
shapes = None
qcnd._register_parameters(meas, all_setpoint_params)
qcnd._register_parameters(meas,
param_meas,
setpoints=all_setpoint_params,
shapes=shapes)
qcnd._register_actions(meas, enter_actions, exit_actions)
with qcnd._catch_keyboard_interrupts() as interrupted, \
meas.run(write_in_background=True) as datasaver:
additional_setpoints_data = qcnd._process_params_meas(
additional_setpoints)
for set_point in xarray:
param_set.set(set_point)
time.sleep(delay)
datasaver.add_result(
(param_set, set_point),
*qcnd._process_params_meas(param_meas,
use_threads=use_threads),
*additional_setpoints_data)
dataset = datasaver.dataset
return dataset
def setup_parameter_from_dict(parameter: _BaseParameter,
options: Dict[str, Any]) -> None:
for attr, val in options.items():
if attr in PARAMETER_ATTRIBUTES:
# set the attributes of the parameter, that map 1 to 1
setattr(parameter, attr, val)
# extra attributes that need parsing
elif attr == 'limits':
if isinstance(val, str):
issue_deprecation_warning(
('use of a comma separated string for the limits '
'keyword'),
alternative='an array like "[lower_lim, upper_lim]"'
)
lower, upper = [float(x) for x in val.split(',')]
else:
lower, upper = val
parameter.vals = validators.Numbers(lower, upper)
elif attr == 'monitor' and val is True:
self._monitor_parameters.append(parameter)
elif attr == 'alias':
setattr(parameter.instrument, val, parameter)
elif attr == 'initial_value':
# skip value attribute so that it gets set last
# when everything else has been set up
pass
else:
log.warning(f'Attribute {attr} not recognized when '
f'instatiating parameter \"{parameter.name}\"')
if 'initial_value' in options:
parameter.set(options['initial_value'])
def _conditional_parameter_set(
parameter: _BaseParameter, value: Union[float, complex],
) -> None:
"""
Reads the cache value of the given parameter and set the parameter to
the given value if the value is different from the cache value.
"""
if value != parameter.cache.get():
parameter.set(value)
def do2d(
param_set1: _BaseParameter,
start1: float,
stop1: float,
num_points1: int,
delay1: float,
param_set2: _BaseParameter,
start2: float,
stop2: float,
num_points2: int,
delay2: float,
*param_meas: ParamMeasT,
set_before_sweep: Optional[bool] = True,
enter_actions: ActionsT = (),
exit_actions: ActionsT = (),
before_inner_actions: ActionsT = (),
after_inner_actions: ActionsT = (),
write_period: Optional[float] = None,
measurement_name: str = "",
exp: Optional[Experiment] = None,
flush_columns: bool = False,
do_plot: Optional[bool] = None,
use_threads: Optional[bool] = None,
additional_setpoints: Sequence[ParamMeasT] = tuple(),
show_progress: Optional[None] = None,
) -> AxesTupleListWithDataSet:
"""
Perform a 1D scan of ``param_set1`` from ``start1`` to ``stop1`` in
``num_points1`` and ``param_set2`` from ``start2`` to ``stop2`` in
``num_points2`` measuring param_meas at each step.
Args:
param_set1: The QCoDeS parameter to sweep over in the outer loop
start1: Starting point of sweep in outer loop
stop1: End point of sweep in the outer loop
num_points1: Number of points to measure in the outer loop
delay1: Delay after setting parameter in the outer loop
param_set2: The QCoDeS parameter to sweep over in the inner loop
start2: Starting point of sweep in inner loop
stop2: End point of sweep in the inner loop
num_points2: Number of points to measure in the inner loop
delay2: Delay after setting parameter before measurement is performed
*param_meas: Parameter(s) to measure at each step or functions that
will be called at each step. The function should take no arguments.
The parameters and functions are called in the order they are
supplied.
set_before_sweep: if True the outer parameter is set to its first value
before the inner parameter is swept to its next value.
enter_actions: A list of functions taking no arguments that will be
called before the measurements start
exit_actions: A list of functions taking no arguments that will be
called after the measurements ends
before_inner_actions: Actions executed before each run of the inner loop
after_inner_actions: Actions executed after each run of the inner loop
write_period: The time after which the data is actually written to the
database.
measurement_name: Name of the measurement. This will be passed down to
the dataset produced by the measurement. If not given, a default
value of 'results' is used for the dataset.
exp: The experiment to use for this measurement.
flush_columns: The data is written after a column is finished
independent of the passed time and write period.
additional_setpoints: A list of setpoint parameters to be registered in
the measurement but not scanned.
do_plot: should png and pdf versions of the images be saved after the
run. If None the setting will be read from ``qcodesrc.json``
use_threads: If True measurements from each instrument will be done on
separate threads. If you are measuring from several instruments
this may give a significant speedup.
show_progress: should a progress bar be displayed during the
measurement. If None the setting will be read from ``qcodesrc.json`
Returns:
The QCoDeS dataset.
"""
if do_plot is None:
do_plot = config.dataset.dond_plot
if show_progress is None:
show_progress = config.dataset.dond_show_progress
meas = Measurement(name=measurement_name, exp=exp)
all_setpoint_params = (
param_set1,
param_set2,
) + tuple(s for s in additional_setpoints)
measured_parameters = tuple(param for param in param_meas
if isinstance(param, _BaseParameter))
try:
loop_shape = tuple(
1 for _ in additional_setpoints) + (num_points1, num_points2)
shapes: Shapes = detect_shape_of_measurement(measured_parameters,
loop_shape)
except TypeError:
LOG.exception(f"Could not detect shape of {measured_parameters} "
f"falling back to unknown shape.")
shapes = None
_register_parameters(meas, all_setpoint_params)
_register_parameters(meas,
param_meas,
setpoints=all_setpoint_params,
shapes=shapes)
_set_write_period(meas, write_period)
_register_actions(meas, enter_actions, exit_actions)
original_delay1 = param_set1.post_delay
original_delay2 = param_set2.post_delay
param_set1.post_delay = delay1
param_set2.post_delay = delay2
with _catch_keyboard_interrupts() as interrupted, meas.run() as datasaver:
dataset = datasaver.dataset
additional_setpoints_data = process_params_meas(additional_setpoints)
setpoints1 = np.linspace(start1, stop1, num_points1)
for set_point1 in tqdm(setpoints1, disable=not show_progress):
if set_before_sweep:
param_set2.set(start2)
param_set1.set(set_point1)
for action in before_inner_actions:
action()
setpoints2 = np.linspace(start2, stop2, num_points2)
# flush to prevent unflushed print's to visually interrupt tqdm bar
# updates
sys.stdout.flush()
sys.stderr.flush()
for set_point2 in tqdm(setpoints2,
disable=not show_progress,
leave=False):
# skip first inner set point if `set_before_sweep`
if set_point2 == start2 and set_before_sweep:
pass
else:
param_set2.set(set_point2)
datasaver.add_result(
(param_set1, set_point1), (param_set2, set_point2),
*process_params_meas(param_meas, use_threads=use_threads),
*additional_setpoints_data)
for action in after_inner_actions:
action()
if flush_columns:
datasaver.flush_data_to_database()
param_set1.post_delay = original_delay1
param_set2.post_delay = original_delay2
return _handle_plotting(dataset, do_plot, interrupted())
def do1d(
param_set: _BaseParameter,
start: float,
stop: float,
num_points: int,
delay: float,
*param_meas: ParamMeasT,
enter_actions: ActionsT = (),
exit_actions: ActionsT = (),
write_period: Optional[float] = None,
measurement_name: str = "",
exp: Optional[Experiment] = None,
do_plot: Optional[bool] = None,
use_threads: Optional[bool] = None,
additional_setpoints: Sequence[ParamMeasT] = tuple(),
show_progress: Optional[None] = None,
) -> AxesTupleListWithDataSet:
"""
Perform a 1D scan of ``param_set`` from ``start`` to ``stop`` in
``num_points`` measuring param_meas at each step. In case param_meas is
an ArrayParameter this is effectively a 2d scan.
Args:
param_set: The QCoDeS parameter to sweep over
start: Starting point of sweep
stop: End point of sweep
num_points: Number of points in sweep
delay: Delay after setting parameter before measurement is performed
*param_meas: Parameter(s) to measure at each step or functions that
will be called at each step. The function should take no arguments.
The parameters and functions are called in the order they are
supplied.
enter_actions: A list of functions taking no arguments that will be
called before the measurements start
exit_actions: A list of functions taking no arguments that will be
called after the measurements ends
write_period: The time after which the data is actually written to the
database.
additional_setpoints: A list of setpoint parameters to be registered in
the measurement but not scanned.
measurement_name: Name of the measurement. This will be passed down to
the dataset produced by the measurement. If not given, a default
value of 'results' is used for the dataset.
exp: The experiment to use for this measurement.
do_plot: should png and pdf versions of the images be saved after the
run. If None the setting will be read from ``qcodesrc.json`
use_threads: If True measurements from each instrument will be done on
separate threads. If you are measuring from several instruments
this may give a significant speedup.
show_progress: should a progress bar be displayed during the
measurement. If None the setting will be read from ``qcodesrc.json`
Returns:
The QCoDeS dataset.
"""
if do_plot is None:
do_plot = config.dataset.dond_plot
if show_progress is None:
show_progress = config.dataset.dond_show_progress
meas = Measurement(name=measurement_name, exp=exp)
all_setpoint_params = (param_set, ) + tuple(s
for s in additional_setpoints)
measured_parameters = tuple(param for param in param_meas
if isinstance(param, _BaseParameter))
try:
loop_shape = tuple(1 for _ in additional_setpoints) + (num_points, )
shapes: Shapes = detect_shape_of_measurement(measured_parameters,
loop_shape)
except TypeError:
LOG.exception(f"Could not detect shape of {measured_parameters} "
f"falling back to unknown shape.")
shapes = None
_register_parameters(meas, all_setpoint_params)
_register_parameters(meas,
param_meas,
setpoints=all_setpoint_params,
shapes=shapes)
_set_write_period(meas, write_period)
_register_actions(meas, enter_actions, exit_actions)
original_delay = param_set.post_delay
param_set.post_delay = delay
# do1D enforces a simple relationship between measured parameters
# and set parameters. For anything more complicated this should be
# reimplemented from scratch
with _catch_keyboard_interrupts() as interrupted, meas.run() as datasaver:
dataset = datasaver.dataset
additional_setpoints_data = process_params_meas(additional_setpoints)
setpoints = np.linspace(start, stop, num_points)
# flush to prevent unflushed print's to visually interrupt tqdm bar
# updates
sys.stdout.flush()
sys.stderr.flush()
for set_point in tqdm(setpoints, disable=not show_progress):
param_set.set(set_point)
datasaver.add_result((param_set, set_point),
*process_params_meas(param_meas,
use_threads=use_threads),
*additional_setpoints_data)
param_set.post_delay = original_delay
return _handle_plotting(dataset, do_plot, interrupted())
def do2d_multi(param_slow: _BaseParameter, start_slow: float, stop_slow: float,
num_points_slow: int, delay_slow: float,
param_fast: _BaseParameter, start_fast: float, stop_fast: float,
num_points_fast: int, delay_fast: float,
lockins: Sequence[SR830],
devices_no_buffer: Iterable[Parameter] = None,
write_period: float = 1.,
threading: List[bool] = [True, True, True, True],
label: str = None,
channels: int = 0,
attempts_to_get: int = 3,
delay_fast_increase: float = 0.0
) -> Tuple[DataSet, ...]:
"""
This is a do2d to be used for a collection of SR830.
Args:
param_slow: The QCoDeS parameter to sweep over in the outer loop
start_slow: Starting point of sweep in outer loop
stop_slow: End point of sweep in the outer loop
num_points_slow: Number of points to measure in the outer loop
delay_slow: Delay after setting parameter in the outer loop
param_fast: The QCoDeS parameter to sweep over in the inner loop
start_fast: Starting point of sweep in inner loop
stop_fast: End point of sweep in the inner loop
num_points_fast: Number of points to measure in the inner loop
delay_fast: Delay after setting parameter before measurement is performed
lockins: Iterable of SR830 lockins
devices_no_buffer: Iterable of Parameters to be measured alongside the lockins
write_period: The time after which the data is actually written to the
database.
threading: For each element which are True, write_in_background, buffer_reset,
and send_trigger and get_trace will be threaded respectively
channels: Channels to get from the buffer. "0" gets both channels
attempts_to_get: Maximum number of attempts to try to get the buffer if it fails
delay_fast_increase: Amount to increase delay_fast if getting the buffer fails
"""
logger.info('Starting do2d_multi with {}'.format(num_points_slow * num_points_fast))
logger.info('write_in_background {},threading buffer_reset {},threading send_trigger {},threading get trace {}'.format(*threading))
begin_time = time.perf_counter()
for lockin in lockins:
if not isinstance(lockin, SR830):
raise ValueError('Invalid instrument. Only SR830s are supported')
lockin.buffer_SR("Trigger")
lockin.buffer_trig_mode.set('ON')
assert isinstance(param_fast, Parameter)
lockin.set_sweep_parameters(param_fast, start_fast, stop_fast, num_points_fast, label=label)
interval_slow = tqdm(np.linspace(start_slow, stop_slow, num_points_slow), position=0)
interval_slow.set_description("Slow parameter")
set_points_fast = lockins[0].sweep_setpoints
meas = Measurement()
meas.write_period = write_period
meas.register_parameter(set_points_fast)
meas.register_parameter(param_fast)
meas.register_parameter(param_slow)
param_fast.post_delay = delay_fast
param_slow.post_delay = delay_slow
traces = _datatrace_parameters(lockins, channels)
for trace in traces:
assert isinstance(trace.root_instrument, SR830)
if len(trace.label.split()) < 2:
trace.label = trace.root_instrument.name + ' ' + trace.label
meas.register_parameter(trace, setpoints=(param_slow, trace.root_instrument.sweep_setpoints))
if devices_no_buffer is not None:
meas_no_buffer = Measurement()
meas_no_buffer.write_period = write_period
meas_no_buffer.register_parameter(param_fast)
meas_no_buffer.register_parameter(param_slow)
for device in devices_no_buffer:
meas_no_buffer.register_parameter(device, setpoints=(param_slow, param_fast))
time_fast_loop = 0.0
time_set_fast = 0.0
time_buffer_reset = 0.0
time_trigger_send = 0.0
time_get_trace = 0.0
cm_datasaver = meas.run(write_in_background=threading[0])
if devices_no_buffer is not None:
cm_datasaver_no_buffer = meas_no_buffer.run(write_in_background=threading[0])
with ExitStack() as cmx:
cmx.enter_context(cm_datasaver)
datasaver = cm_datasaver.datasaver
if devices_no_buffer is not None:
cmx.enter_context(cm_datasaver_no_buffer)
datasaver_no_buffer = cm_datasaver_no_buffer.datasaver
for point_slow in interval_slow:
param_slow.set(point_slow)
data = []
data.append((param_slow, param_slow.get()))
if devices_no_buffer is not None:
data_no_buffer = []
data_no_buffer.append((param_slow, param_slow.get()))
attempts = 0
while attempts < attempts_to_get:
try:
begin_time_temp_buffer = time.perf_counter()
if threading[1]:
with concurrent.futures.ThreadPoolExecutor() as executor:
for lockin in lockins:
executor.submit(lockin.buffer_reset)
else:
for lockin in lockins:
lockin.buffer_reset()
time_buffer_reset += time.perf_counter() - begin_time_temp_buffer
begin_time_temp_fast_loop = time.perf_counter()
interval_fast = tqdm(set_points_fast.get(), position=1, leave=False)
interval_fast.set_description("Fast parameter")
for point_fast in interval_fast:
begin_time_temp_set_fast = time.perf_counter()
param_fast.set(point_fast)
time_set_fast += time.perf_counter() - begin_time_temp_set_fast
begin_time_temp_trigger = time.perf_counter()
if threading[2]:
with concurrent.futures.ThreadPoolExecutor() as executor:
for lockin in lockins:
executor.submit(lockin.send_trigger)
else:
for lockin in lockins:
lockin.send_trigger()
time_trigger_send += time.perf_counter() - begin_time_temp_trigger
if devices_no_buffer is not None:
fast = param_fast.get()
data_no_buffer.append((param_fast, fast))
for device in devices_no_buffer:
device_value = device.get()
data_no_buffer.append((device, device_value))
datasaver_no_buffer.add_result(*data_no_buffer)
time_fast_loop += time.perf_counter() - begin_time_temp_fast_loop
begin_time_temp_trace = time.perf_counter()
if threading[3]:
with concurrent.futures.ThreadPoolExecutor() as executor:
data_trace = executor.map(trace_tuble, traces)
data += list(data_trace)
else:
for trace in traces:
data.append((trace, trace.get()))
time_get_trace += time.perf_counter() - begin_time_temp_trace
data.append((set_points_fast, set_points_fast.get()))
break
except Exception as e:
logger.info('Faild to get buffer')
logger.info(e)
print(e)
attempts += 1
delay_fast += delay_fast_increase
print(attempts)
logger.info('next attempt nr. {}'.format(attempts))
logger.info('next delay_fast. {}'.format(delay_fast))
print(delay_fast)
if attempts < attempts_to_get:
log_message = 'getting the buffer failed, will try again'
print(log_message)
logger.info(log_message)
else:
log_message = 'getting the buffer failed, will go to next slow_point'
print(log_message)
logger.info(log_message)
datasaver.add_result(*data)
message = 'Have finished the measurement in {} seconds'.format(time.perf_counter()-begin_time)
logger.info(message)
message2 = 'Time used in buffer reset {}. Time used in send trigger {}. Time used in get trace {}'.format(time_buffer_reset, time_trigger_send, time_get_trace)
logger.info(message2)
logger.info('time in the fast loop {}'.format(time_fast_loop))
if devices_no_buffer is not None:
return (datasaver.dataset, datasaver_no_buffer.dataset)
else:
return (datasaver.dataset,)
def trace_tuble(trace: _BaseParameter) -> Tuple[_BaseParameter, ParamDataType]:
return (trace, trace.get())
def _attach_parameter_decorators(self,
parameter: _BaseParameter,
decorator_methods: Dict[str, Callable]):
"""Attaches @parameter decorators to a parameter
Args:
parameter: Parameter to attach decorators to
decorator_methods: Decorator methods to attach to parameter
"""
for param_attr, param_method in decorator_methods.items():
method_with_args = partial(param_method, self, parameter)
if param_attr == 'get':
parameter.get_raw = method_with_args
if parameter.wrap_get:
parameter.get = parameter._wrap_get(parameter.get_raw)
else:
parameter.get = parameter.get_raw
elif param_attr == 'set':
parameter.set_raw = method_with_args
if parameter.wrap_set:
parameter.set = parameter._wrap_set(parameter.set_raw)
else:
parameter.set = parameter.set_raw
else:
setattr(parameter, param_attr, method_with_args)
# perform a set without evaluating, which saves the value,
# ensuring that new modifications such as the set_parser are
# taken into account
if hasattr(parameter, 'set') and parameter.raw_value is not None and parameter.wrap_set:
parameter.set(copy(parameter.get_latest()), evaluate=False)
def do2d_multi(param_slow: _BaseParameter,
start_slow: float,
stop_slow: float,
num_points_slow: int,
delay_slow: float,
param_fast: _BaseParameter,
start_fast: float,
stop_fast: float,
num_points_fast: int,
delay_fast: float,
bundle: BundleLockin,
write_period: float = 1.,
threading: List[bool] = [True, True, True, True],
show_progress_bar: bool = True,
attempts_to_get: int = 3,
delay_fast_increase: float = 0.0,
label: Union[str, None] = None):
"""
This is a do2d only to be used with BundleLockin.
Args:
param_slow: The QCoDeS parameter to sweep over in the outer loop
start_slow: Starting point of sweep in outer loop
stop_slow: End point of sweep in the outer loop
num_points_slow: Number of points to measure in the outer loop
delay_slow: Delay after setting parameter in the outer loop
param_fast: The QCoDeS parameter to sweep over in the inner loop
start_fast: Starting point of sweep in inner loop
stop_fast: End point of sweep in the inner loop
num_points_fast: Number of points to measure in the inner loop
delay_fast: Delay after setting parameter before measurement is performed
write_period: The time after which the data is actually written to the
database.
threading: For each ellement which are True, write_in_background, buffer_reset,
and send_trigger and get_trace will be threaded respectively
show_progress_bar: should a progress bar be displayed during the
measurement.
attempts_to_get: nummber of attempts to get the buffer before failling
delay_fast_increase: increases the delay_fast if failling
"""
logger.info('Starting do2d_multi with {}'.format(num_points_slow *
num_points_fast))
logger.info(
'write_in_background {},threading buffer_reset {},threading send_trigger {},threading get trace {}'
.format(*threading))
begin_time = time.perf_counter()
meas = Measurement()
bundle.set_sweep_parameters(param_fast,
start_fast,
stop_fast,
num_points_fast,
label=label)
interval_slow = np.linspace(start_slow, stop_slow, num_points_slow)
meas.write_period = write_period
set_points_fast = bundle.setpoints
meas.register_parameter(set_points_fast)
param_fast.post_delay = delay_fast
meas.register_parameter(param_slow)
param_slow.post_delay = delay_slow
bundle_parameters = bundle.__dict__['parameters']
traces = [
bundle_parameters[key] for key in bundle_parameters.keys()
if 'trace' in key
]
for trace in traces:
meas.register_parameter(trace, setpoints=(param_slow, set_points_fast))
time_fast_loop = 0.0
time_set_fast = 0.0
time_buffer_reset = 0.0
time_trigger_send = 0.0
time_get_trace = 0.0
if show_progress_bar:
progress_bar = progressbar.ProgressBar(max_value=num_points_slow *
num_points_fast)
points_taken = 0
with meas.run(write_in_background=threading[0]) as datasaver:
run_id = datasaver.run_id
for point_slow in interval_slow:
param_slow.set(point_slow)
attempts = 0
while attempts < attempts_to_get:
try:
begin_time_temp_buffer = time.perf_counter()
if threading[1]:
with concurrent.futures.ThreadPoolExecutor(
) as executor:
for lockin in bundle.lockins:
executor.submit(lockin.buffer_reset)
else:
for lockin in bundle.lockins:
lockin.buffer_reset()
time_buffer_reset += time.perf_counter(
) - begin_time_temp_buffer
begin_time_temp_fast_loop = time.perf_counter()
for point_fast in set_points_fast.get():
begin_time_temp_set_fast = time.perf_counter()
param_fast.set(point_fast)
time_set_fast += time.perf_counter(
) - begin_time_temp_set_fast
begin_time_temp_trigger = time.perf_counter()
if threading[2]:
with concurrent.futures.ThreadPoolExecutor(
) as executor:
for lockin in bundle.lockins:
executor.submit(lockin.send_trigger)
else:
for lockin in bundle.lockins:
lockin.send_trigger()
if show_progress_bar and attempts == 0:
points_taken += 1
progress_bar.update(points_taken)
time_trigger_send += time.perf_counter(
) - begin_time_temp_trigger
time_fast_loop += time.perf_counter(
) - begin_time_temp_fast_loop
begin_time_temp_trace = time.perf_counter()
if threading[3]:
with concurrent.futures.ThreadPoolExecutor(
) as executor:
data = executor.map(trace_tuble, traces)
data = list(data)
else:
data = []
for trace in traces:
data.append((trace, trace.get()))
time_get_trace += time.perf_counter(
) - begin_time_temp_trace
data.append((param_slow, param_slow.get()))
data.append((set_points_fast, set_points_fast.get()))
break
except Exception as e:
print(e)
attempts += 1
delay_fast += delay_fast_increase
print(attempts)
print(delay_fast)
if attempts < attempts_to_get:
print('getting the buffer failed, will try again')
else:
print(
'getting the buffer failed, will go to next slow_point'
)
datasaver.add_result(*data)
message = 'Have finished the measurement in {} seconds. run_id {}'.format(
time.perf_counter() - begin_time, run_id)
logger.info(message)
message2 = 'Time used in buffer reset {}. Time used in send trigger {}. Time used in get trace {}'.format(
time_buffer_reset, time_trigger_send, time_get_trace)
logger.info(message2)
logger.info('time in the fast loop {}'.format(time_fast_loop))
logger.info('time setting in the fast loop {}'.format(time_set_fast))
