def test_nest_3d(indep_params, dep_params):
px, x, tablex = indep_params["x"]
py, y, tabley = indep_params["y"]
pz, z, tablez = indep_params["z"]
def f(vx, vy, vz):
return vx**2 + vy**2 + vz**2
pi, i, tablei = dep_params["i"]
pi.get = lambda: f(px(), py(), pz())
sweep_values_x = [0, 1, 2]
sweep_values_y = [5, 6, 7]
sweep_values_z = [8, 9, 10]
nest = Nest(Sweep(x, tablex, lambda: sweep_values_x),
Sweep(y, tabley, lambda: sweep_values_y),
Sweep(z, tablez, lambda: sweep_values_z), Measure(i, tablei))
meas = SweepMeasurement()
meas.register_sweep(nest)
interdeps = meas._interdeps
assert interdeps.dependencies == {
ParamSpecBase('i', 'numeric', '', ''):
(ParamSpecBase('x', 'numeric', '',
''), ParamSpecBase('y', 'numeric', '', ''),
ParamSpecBase('z', 'numeric', '', ''))
}
assert interdeps.inferences == {}
assert interdeps.standalones == set()
def do_experiment(experiment_name,
sweep_object,
setup=None,
cleanup=None,
station=None,
live_plot=False):
if "/" in experiment_name:
experiment_name, sample_name = experiment_name.split("/")
else:
sample_name = None
try:
experiment = load_experiment_by_name(experiment_name, sample_name)
except ValueError: # experiment does not exist yet
db_location = qcodes.config["core"]["db_location"]
DataSet(db_location)
experiment = new_experiment(experiment_name, sample_name)
def add_actions(action, callables):
if callables is None:
return
for cabble in np.atleast_1d(callables):
if not isinstance(cabble, tuple):
cabble = (cabble, ())
action(*cabble)
if live_plot:
try:
from plottr.qcodes_dataset import QcodesDatasetSubscriber
from plottr.tools import start_listener
start_listener()
except ImportError:
warn("Cannot perform live plots, plottr not installed")
live_plot = False
meas = SweepMeasurement(exp=experiment, station=station)
meas.register_sweep(sweep_object)
add_actions(meas.add_before_run, setup)
add_actions(meas.add_after_run, cleanup)
with meas.run() as datasaver:
if live_plot:
datasaver.dataset.subscribe(QcodesDatasetSubscriber(
datasaver.dataset),
state=[],
min_wait=0,
min_count=1)
for data in sweep_object:
datasaver.add_result(*data.items())
return _DataExtractor(datasaver)
def test_sweep_parameter(indep_params):
px, x, table = indep_params["x"]
sweep_values = [0, 1, 2]
parameter_sweep = Sweep(x, table, lambda: sweep_values)
meas = SweepMeasurement()
meas.register_sweep(parameter_sweep)
interdeps = meas._interdeps
assert interdeps.dependencies == {}
assert interdeps.inferences == {}
assert interdeps.standalones == {ParamSpecBase('x', 'numeric', '', '')}
def test_nest_in_chain_2_whatever(indep_params, dep_params):
px, x, tablex = indep_params["x"]
pi, i, tablei = dep_params["i"]
pj, j, tablej = dep_params["j"]
sweep_values = [0, 1, 2]
sweep_object = Nest(Sweep(x, tablex, lambda: sweep_values),
Chain(Measure(i, tablei)))
meas = SweepMeasurement()
meas.register_sweep(sweep_object)
interdeps = meas._interdeps
assert interdeps.dependencies == {
ParamSpecBase('i', 'numeric', '', ''):
(ParamSpecBase('x', 'numeric', '', ''), )
}
assert interdeps.inferences == {}
assert interdeps.standalones == set()
def test_chain_simple(indep_params):
px, x, tablex = indep_params["x"]
py, y, tabley = indep_params["y"]
sweep_values_x = [0, 1, 2]
sweep_values_y = [4, 5, 6]
parameter_sweep = Chain(Sweep(x, tablex, lambda: sweep_values_x),
Sweep(y, tabley, lambda: sweep_values_y))
meas = SweepMeasurement()
meas.register_sweep(parameter_sweep)
interdeps = meas._interdeps
assert interdeps.dependencies == {}
assert interdeps.inferences == {}
assert interdeps.standalones == {
ParamSpecBase('y', 'numeric', '', ''),
ParamSpecBase('x', 'numeric', '', '')
}
def test_interleave_1d_2d(indep_params, dep_params):
px, x, tablex = indep_params["x"]
py, y, tabley = indep_params["y"]
pi, i, tablei = dep_params["i"]
pj, j, tablej = dep_params["j"]
def f(vx):
return vx ** 2
pi.get = lambda: f(px())
def g(vx, vy):
return vx ** 2 + vy ** 2
pj.get = lambda: g(px(), py())
sweep_values_x = [0, 1, 2]
sweep_values_y = [4, 5, 6]
sweep_object = Nest(
Sweep(x, tablex, lambda: sweep_values_x),
Chain(
Measure(i, tablei),
Nest(
Sweep(y, tabley, lambda: sweep_values_y),
Measure(j, tablej)
)
)
)
meas = SweepMeasurement()
meas.register_sweep(sweep_object)
interdeps = meas._interdeps
assert interdeps.dependencies == {
ParamSpecBase('i', 'numeric', '', ''): (ParamSpecBase('x', 'numeric', '', ''),),
ParamSpecBase('j', 'numeric', '', ''): (ParamSpecBase('x', 'numeric', '', ''),
ParamSpecBase('y', 'numeric', '', ''))}
assert interdeps.inferences == {}
assert interdeps.standalones == set()
def test_nest(indep_params, dep_params):
px, x, tablex = indep_params["x"]
pi, i, tablei = dep_params["i"]
def f(value):
return value**2
pi.get = lambda: f(px())
sweep_values = [0, 1, 2]
nest = Nest(Sweep(x, tablex, lambda: sweep_values), Measure(i, tablei))
meas = SweepMeasurement()
meas.register_sweep(nest)
interdeps = meas._interdeps
assert interdeps.dependencies == {
ParamSpecBase('i', 'numeric', '', ''):
(ParamSpecBase('x', 'numeric', '', ''), )
}
assert interdeps.inferences == {}
assert interdeps.standalones == set()
