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 readvstime(
delay: float,
timeout: float,
*param_meas: qcnd.ParamMeasT,
exp: Experiment = None,
use_threads=False,
enter_actions: qcnd.ActionsT = (),
exit_actions: qcnd.ActionsT = (),
additional_setpoints=tuple(),
):
meas = Measurement(exp=exp)
timer = ElapsedTimeParameter("time")
all_setpoint_params = (timer, ) + tuple(s for s in additional_setpoints)
measured_parameters = list(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
qcnd._register_parameters(meas, all_setpoint_params)
qcnd._register_parameters(meas,
param_meas,
setpoints=all_setpoint_params,
shapes=None)
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)
timer.reset_clock()
while True:
time.sleep(delay)
datasaver.add_result(
(timer, timer.get()),
*qcnd._process_params_meas(param_meas,
use_threads=use_threads),
*additional_setpoints_data)
if (timeout - timer.get()) < 0.005:
break
dataset = datasaver.dataset
return dataset
def field_sweep_ps120(
field_param,
start: float,
stop: float,
delay: float,
*param_meas: qcnd.ParamMeasT,
exp: Experiment = None,
use_threads=False,
enter_actions: qcnd.ActionsT = (),
exit_actions: qcnd.ActionsT = (),
additional_setpoints=tuple(),
):
# get instrument for field param
magnet = field_param.instrument
# timer param
timer = ElapsedTimeParameter("time")
# add field to measured params
param_meas = list(param_meas)
param_meas.append(field_param)
measured_parameters = list(param for param in param_meas
if isinstance(param, _BaseParameter))
all_setpoint_params = (timer, ) + tuple(s for s in additional_setpoints)
if (len(measured_parameters) > 2) or (use_threads == True):
use_threads = True
elif (use_threads == False):
use_threads = False
else:
use_threads = False
meas = Measurement(exp=exp)
qcnd._register_parameters(meas, all_setpoint_params)
qcnd._register_parameters(meas,
param_meas,
setpoints=all_setpoint_params,
shapes=None)
qcnd._register_actions(meas, enter_actions, exit_actions)
with qcnd._catch_keyboard_interrupts() as interrupted, \
meas.run(write_in_background=True) as datasaver:
magnet.field_blocking(start)
additional_setpoints_data = qcnd._process_params_meas(
additional_setpoints)
timer.reset_clock()
magnet.field_non_blocking(stop)
while magnet.ramp_status() != magnet._GET_STATUS_RAMP[0]:
time.sleep(delay)
datasaver.add_result(
(timer, timer.get()),
*qcnd._process_params_meas(param_meas,
use_threads=use_threads),
*additional_setpoints_data)
dataset = datasaver.dataset
return dataset
def field_sweep_ami_2d(
field_param,
xarray,
delayx,
param_sety,
yarray,
delayy,
*param_meas: qcnd.ParamMeasT,
exp: Experiment = None,
use_threads=False,
enter_actions: qcnd.ActionsT = (),
exit_actions: qcnd.ActionsT = (),
additional_setpoints=tuple(),
):
# get instrument for field param
magnet = field_param.instrument
# add field to measured params
all_setpoint_params = (
param_sety,
field_param,
) + 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
elif (use_threads == False):
use_threads = False
else:
use_threads = False
try:
loop_shape = tuple(
1 for _ in additional_setpoints) + (len(yarray), 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
meas = Measurement(exp=exp)
qcnd._register_parameters(meas, all_setpoint_params)
qcnd._register_parameters(meas,
param_meas,
setpoints=all_setpoint_params,
shapes=None)
qcnd._register_actions(meas, enter_actions, exit_actions)
inner_loop_params = (field_param, ) + param_meas
inner_loop_dict = {k.name: [] for k in inner_loop_params}
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_pointy in yarray:
param_sety.set(set_pointy)
time.sleep(delayy)
magnet.set_field(xarray[0], block=True)
magnet.set_field(xarray[-1], block=False)
while magnet.ramping_state() == 'ramping':
time.sleep(delayx)
for param, val in qcnd._process_params_meas(
inner_loop_params, use_threads=use_threads):
inner_loop_dict[param.name].append(val)
datasaver.add_result(
(param_sety, [set_pointy] * len(xarray)),
*_bin_results_to_fit_shape(field_param, xarray,
inner_loop_params, inner_loop_dict),
*additional_setpoints_data,
)
dataset = datasaver.dataset
return dataset
def do2d(
param_setx,
xarray,
delayx,
param_sety,
yarray,
delayy,
*param_meas: qcnd.ParamMeasT,
enter_actions: qcnd.ActionsT = (),
exit_actions: qcnd.ActionsT = (),
before_inner_actions: qcnd.ActionsT = (),
after_inner_actions: qcnd.ActionsT = (),
exp: Optional[Experiment] = None,
use_threads: Optional[bool] = None,
additional_setpoints: Sequence[qcnd.ParamMeasT] = tuple(),
):
meas = Measurement(exp=exp)
all_setpoint_params = (
param_sety,
param_setx,
) + 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
elif (use_threads == False):
use_threads = False
else:
use_threads = False
try:
loop_shape = tuple(
1 for _ in additional_setpoints) + (len(yarray), 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)
param_setx.post_delay = 0.0
param_sety.post_delay = 0.0
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_pointy in yarray:
param_setx.set(xarray[0])
param_sety.set(set_pointy)
time.sleep(delayy)
for action in before_inner_actions:
action()
for set_pointx in xarray:
param_setx.set(set_pointx)
time.sleep(delayx)
datasaver.add_result(
(param_sety, set_pointy), (param_setx, set_pointx),
*qcnd._process_params_meas(param_meas,
use_threads=use_threads),
*additional_setpoints_data)
for action in after_inner_actions:
action()
dataset = datasaver.dataset
return dataset
def do1d_repeat_twoway(
param_setx,
xarray,
delayx,
num_repeats,
delayy,
*param_meas: qcnd.ParamMeasT,
enter_actions: qcnd.ActionsT = (),
exit_actions: qcnd.ActionsT = (),
before_inner_actions: qcnd.ActionsT = (),
after_inner_actions: qcnd.ActionsT = (),
exp: Optional[Experiment] = None,
use_threads: Optional[bool] = None,
additional_setpoints: Sequence[qcnd.ParamMeasT] = tuple(),
):
if (not _is_monotonic(xarray)) or (not _is_monotonic(yarray)):
warn('Sweep array is not monotonic. This is pretty weird. Reconsider.')
meas = Measurement(exp=exp)
param_county = CountParameter("repeat")
all_setpoint_params = (
param_county,
param_setx,
) + 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) + (num_repeats, 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)
param_setx.post_delay = 0.0
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 i in range(num_repeats):
y = param_county.get()
if y % 2 == 0:
xsetpoints = xarray
else:
xsetpoints = xarray[::-1]
param_setx.set(xsetpoints[0])
time.sleep(delayy)
for action in before_inner_actions:
action()
for set_pointx in xsetpoints:
param_setx.set(set_pointx)
time.sleep(delayx)
datasaver.add_result(
(param_county, y), (param_setx, set_pointx),
*qcnd._process_params_meas(param_meas,
use_threads=use_threads),
*additional_setpoints_data)
for action in after_inner_actions:
action()
dataset = datasaver.dataset
return dataset