def test_problems_from_dataset():
body = Sphere(center=(0, 0, -4), name="sphere")
body.add_translation_dof(name="Heave")
dset = xr.Dataset(coords={'omega': [0.5, 1.0, 1.5],
'radiating_dof': ["Heave"],
'body_name': ["sphere"],
'wave_direction': [0.0],
'water_depth': [np.infty]})
problems = problems_from_dataset(dset, [body])
assert RadiationProblem(body=body, omega=0.5, radiating_dof="Heave") in problems
assert len(problems) == 6
assert len([problem for problem in problems if isinstance(problem, DiffractionProblem)]) == 3
dset = xr.Dataset(coords={'omega': [0.5, 1.0, 1.5],
'wave_direction': [0.0],
'body_name': ["cube"]})
with pytest.raises(AssertionError):
problems_from_dataset(dset, [body])
shifted_body = body.translated_y(5.0, name="shifted_sphere")
dset = xr.Dataset(coords={'omega': [0.5, 1.0, 1.5],
'radiating_dof': ["Heave"],
'wave_direction': [0.0]})
problems = problems_from_dataset(dset, [body, shifted_body])
assert RadiationProblem(body=body, omega=0.5, radiating_dof="Heave") in problems
assert RadiationProblem(body=shifted_body, omega=0.5, radiating_dof="Heave") in problems
assert len(problems) == 12
def test_incomplete_test_matrix():
body = cpt.Sphere()
test_matrix = xr.Dataset(coords={
"omega": np.linspace(0, 1, 2),
})
with pytest.raises(ValueError):
problems_from_dataset(test_matrix, body)
def fill_dataset(self, dataset, bodies, **kwargs):
"""Solve a set of problems defined by the coordinates of an xarray dataset.
Parameters
----------
dataset : xarray Dataset
dataset containing the problems parameters: frequency, radiating_dof, water_depth, ...
bodies : list of FloatingBody
the bodies involved in the problems
Returns
-------
xarray Dataset
"""
attrs = {
'start_of_computation': datetime.now().isoformat(),
**self.exportable_settings
}
problems = problems_from_dataset(dataset, bodies)
if 'theta' in dataset.coords:
results = self.solve_all(problems, keep_details=True)
kochin = kochin_data_array(results, dataset.coords['theta'])
dataset = assemble_dataset(results, attrs=attrs, **kwargs)
dataset['kochin'] = kochin
else:
results = self.solve_all(problems, keep_details=False)
dataset = assemble_dataset(results, attrs=attrs, **kwargs)
return dataset
def fill_dataset(self, dataset, bodies, *, n_jobs=1, **kwargs):
"""Solve a set of problems defined by the coordinates of an xarray dataset.
Parameters
----------
dataset : xarray Dataset
dataset containing the problems parameters: frequency, radiating_dof, water_depth, ...
bodies : FloatingBody or list of FloatingBody
The body or bodies involved in the problems
They should all have different names.
n_jobs: int, optional (default: 1)
the number of jobs to run in parallel using the optional dependency `joblib`
By defaults: do not use joblib and solve sequentially.
Returns
-------
xarray Dataset
"""
attrs = {
'start_of_computation': datetime.now().isoformat(),
**self.exportable_settings
}
problems = problems_from_dataset(dataset, bodies)
if 'theta' in dataset.coords:
results = self.solve_all(problems,
keep_details=True,
n_jobs=n_jobs)
kochin = kochin_data_array(results, dataset.coords['theta'])
dataset = assemble_dataset(results, attrs=attrs, **kwargs)
dataset.update(kochin)
else:
results = self.solve_all(problems,
keep_details=False,
n_jobs=n_jobs)
dataset = assemble_dataset(results, attrs=attrs, **kwargs)
return dataset