def test_hardsweep_with_1_ind_array_and_1_dep_array():
"""
...
This works as expected.
"""
@setter(('repetition', '#', 'numeric'))
def repetition_param(repetition):
"""
The purpose of this setter is to simulate a qcodes parameter without
the need of importing it
"""
pass
n_pts = 7
time_vals = numpy.random.rand(n_pts)
magn_vals = numpy.random.rand(n_pts)
@hardsweep(ind=[("time", "us", "array")],
dep=[("magn", "V", "array")])
def measure_with_alazar():
return time_vals, magn_vals
so = sweep(repetition_param, [1])(
measure_with_alazar()
)
sweep_output = list(so)
assert isinstance(sweep_output, list)
assert 1 == len(sweep_output)
assert {'repetition', 'time', 'magn'} == set(sweep_output[0].keys())
assert 1 == sweep_output[0]['repetition']
assert numpy.allclose(magn_vals, sweep_output[0]['magn'])
assert numpy.allclose(time_vals, sweep_output[0]['time'])
def test_hardsweep_with_1_ind_numeric_and_1_dep_numeric():
"""
...
This works as expected.
"""
@setter(('repetition', '#', 'numeric'))
def repetition_param(repetition):
"""
The purpose of this setter is to simulate a qcodes parameter without
the need of importing it
"""
pass
n_pts = 7
time_vals = numpy.random.rand(n_pts)
magn_vals = numpy.random.rand(n_pts)
@hardsweep(ind=[("time", "us")],
dep=[("magn", "V")])
def measure_with_alazar():
return time_vals, magn_vals
so = sweep(repetition_param, [1])(
measure_with_alazar()
)
sweep_output = list(so)
assert isinstance(sweep_output, list)
assert n_pts == len(sweep_output)
expected_output = [{'repetition': 1, 'magn': m_val, 'time': t_val}
for t_val, m_val in zip(time_vals, magn_vals)]
assert expected_output == sweep_output
def test_hardsweep_with_1_ind_numeric_and_1_dep_array():
"""
...
This works as expected
"""
@setter(('repetition', '#', 'numeric'))
def repetition_param(repetition):
pass
n_pts = 7
time_val = 42
magn_vals = numpy.random.rand(n_pts)
@hardsweep(ind=[("time", "us")], # 'numeric'
dep=[("magn", "V", "array")])
def measure_with_alazar():
return time_val, magn_vals
so = sweep(repetition_param, [1])(
measure_with_alazar()
)
sweep_output = list(so)
assert isinstance(sweep_output, list)
assert 1 == len(sweep_output)
assert 1 == sweep_output[0]['repetition']
assert numpy.allclose(magn_vals, sweep_output[0]['magn'])
assert time_val == sweep_output[0]['time']
def test_hardsweep_with_2_ind_array_and_2_dep_array():
"""
...
This works as expected
"""
@setter(('repetition', '#', 'numeric'))
def repetition_param(repetition):
pass
n_pts = 7
time_vals = numpy.random.rand(n_pts)
space_vals = numpy.random.rand(n_pts)
magn_vals = numpy.random.rand(n_pts)
phas_vals = numpy.random.rand(n_pts)
@hardsweep(ind=[("time", "us", "array"), ("space", "nm", "array")],
dep=[("magn", "V", "array"), ("phas", "V", "array")])
def measure_with_alazar():
ind_vals = numpy.vstack((time_vals, space_vals))
dep_vals = numpy.vstack((magn_vals, phas_vals))
return ind_vals, dep_vals
so = sweep(repetition_param, [1])(
measure_with_alazar()
)
sweep_output = list(so)
assert isinstance(sweep_output, list)
assert 1 == len(sweep_output)
assert {'repetition', 'time', 'magn', 'phas', 'space'} \
== set(sweep_output[0].keys())
assert 1 == sweep_output[0]['repetition']
assert numpy.allclose(magn_vals, sweep_output[0]['magn'])
assert numpy.allclose(phas_vals, sweep_output[0]['phas'])
assert numpy.allclose(space_vals, sweep_output[0]['space'])
assert numpy.allclose(time_vals, sweep_output[0]['time'])
def test_hardsweep_with_2_ind_numeric_and_2_dep_numeric():
"""
...
This works as expected
"""
@setter(('repetition', '#', 'numeric'))
def repetition_param(repetition):
pass
n_pts = 7
time_vals = numpy.random.rand(n_pts)
space_vals = numpy.random.rand(n_pts)
magn_vals = numpy.random.rand(n_pts)
phas_vals = numpy.random.rand(n_pts)
@hardsweep(ind=[("time", "us"), ("space", "nm")],
dep=[("magn", "V"), ("phas", "V")])
def measure_with_alazar():
ind_vals = numpy.vstack((time_vals, space_vals))
dep_vals = numpy.vstack((magn_vals, phas_vals))
return ind_vals, dep_vals
so = sweep(repetition_param, [1])(
measure_with_alazar()
)
sweep_output = list(so)
assert isinstance(sweep_output, list)
expected_output = [{'repetition': 1,
'time': t_val, 'magn': m_val,
'phas': p_val, 'space': s_val}
for t_val, s_val, m_val, p_val
in zip(time_vals, space_vals, magn_vals, phas_vals)]
assert expected_output == sweep_output