def test_load_2dsoftsweep_known_shape(experiment):
N = 1
m = qc.Measurement(exp=experiment)
m.register_custom_parameter('x', unit='cm')
m.register_custom_parameter('y')
# check that unused parameters don't mess with
m.register_custom_parameter('foo')
dd_expected = DataDict(x=dict(values=np.array([]), unit='cm'),
y=dict(values=np.array([])))
for n in range(N):
m.register_custom_parameter(f'z_{n}', setpoints=['x', 'y'])
dd_expected[f'z_{n}'] = dict(values=np.array([]), axes=['x', 'y'])
dd_expected.validate()
shape = (3, 3)
m.set_shapes({'z_0': shape})
with m.run() as datasaver:
for result in testdata.generate_2d_scalar_simple(*shape, N):
row = [(k, v) for k, v in result.items()] + [('foo', 1)]
datasaver.add_result(*row)
dd_expected.add_data(**result)
dd_expected['x']['values'] = dd_expected['x']['values'].reshape(*shape)
dd_expected['y']['values'] = dd_expected['y']['values'].reshape(*shape)
dd_expected['z_0']['values'] = dd_expected['z_0']['values'].reshape(*shape)
# retrieve data as data dict
ddict = ds_to_datadict(datasaver.dataset)
assert ddict == dd_expected
def from_dataset(cls, ds, gate_name, freq_name, magnitude_name, phase_name):
meshgrid = datadict_to_meshgrid(ds_to_datadict(ds))
return cls.from_meshgrid(meshgrid, gate_name, freq_name, magnitude_name, phase_name)