def test_missing_spectra_and_nums_frequency(self, ids, shifts, tol):
"""Test that an error is raised if both, spectra
and nums_frequency are missing."""
with pytest.raises(ValueError,
match="Either nums_frequency or spectra"):
_prepare_jobs(ids,
nums_frequency=None,
spectra=None,
shifts=shifts,
atol=tol)
def test_with_nums_frequency(self, ids, spectra, nums_frequency, tol):
"""Test the prepared jobs when using nums_frequency."""
"""Test ``_prepare_jobs`` with a large variety of test cases (cheap)."""
ids_, recon_fn, jobs, need_f0 = _prepare_jobs(
ids,
nums_frequency,
None,
None,
atol=tol,
)
# Check ids
if ids is None:
assert self.nested_dict_ids_match(nums_frequency, ids_)
else:
assert self.ids_match(ids, ids_)
# Check function to use for 1D reconstructions
assert recon_fn == _reconstruct_equ
# Check reconstruction jobs to be run
assert self.nested_dict_ids_match(jobs, ids_)
for _id, _jobs in jobs.items():
for idx, job in _jobs.items():
if nums_frequency[_id][idx] == 0:
assert job is None
continue
assert list(job.keys()) == ["num_frequency"]
assert job["num_frequency"] == nums_frequency[_id][idx]
# always need fun at zero if equidistant reconstruction is performed
assert need_f0
def test_with_spectra(self, ids, spectra, tol):
"""Test the prepared jobs when using spectra and shifts."""
ids_, recon_fn, jobs, need_f0 = _prepare_jobs(
ids,
nums_frequency=None,
spectra=spectra,
shifts=None,
atol=tol,
)
if ids is None:
assert self.nested_dict_ids_match(spectra, ids_)
else:
assert self.ids_match(ids, ids_)
# Check function to use for 1D reconstructions
assert recon_fn == _reconstruct_gen
# Check reconstruction jobs to be run
assert self.nested_dict_ids_match(jobs, ids_)
# Check all job details
for _id, _jobs in jobs.items():
for idx, job in _jobs.items():
if len(spectra[_id][idx]) == 1:
assert job is None
continue
assert list(job.keys()) == ["shifts", "spectrum"]
assert job["shifts"] is None
assert job["spectrum"] == spectra[_id][idx]
assert need_f0
def test_with_spectra_and_shifts(self, ids, spectra, shifts, tol):
"""Test the prepared jobs when using spectra and shifts."""
ids_, recon_fn, jobs, need_f0 = _prepare_jobs(
ids,
nums_frequency=None,
spectra=spectra,
shifts=shifts,
atol=tol,
)
if ids is None:
assert self.nested_dict_ids_match(spectra, ids_)
else:
assert self.ids_match(ids, ids_)
# Check function to use for 1D reconstructions
assert recon_fn == _reconstruct_gen
# Check reconstruction jobs to be run
assert self.nested_dict_ids_match(jobs, ids_)
# Check all job details
for _id, _jobs in jobs.items():
for idx, job in _jobs.items():
if len(spectra[_id][idx]) == 1:
assert job is None
continue
assert list(job.keys()) == ["shifts", "spectrum"]
assert job["shifts"] == shifts[_id][idx]
assert job["spectrum"] == spectra[_id][idx]
# sometimes need fun at zero if general reconstruction is performed
_all_shifts = chain.from_iterable(
[
sum(
[
__shifts
for par_idx, __shifts in _shifts.items()
if id_ in ids_ and par_idx in ids_[id_]
],
[],
)
for id_, _shifts in shifts.items()
],
)
assert need_f0 == any(np.isclose(_shift, 0.0, atol=tol, rtol=0) for _shift in _all_shifts)