def test_ranking(mock_draw):
bestfit = np.asarray([1.2, 0.1])
uncertainty = np.asarray([0.2, 0.8])
labels = ["staterror_a", "modeling"]
impact_prefit_up = np.asarray([0.1, 0.5])
impact_prefit_down = np.asarray([-0.2, -0.4])
impact_postfit_up = np.asarray([0.1, 0.4])
impact_postfit_down = np.asarray([-0.2, -0.3])
ranking_results = fit.RankingResults(
bestfit,
uncertainty,
labels,
impact_prefit_up,
impact_prefit_down,
impact_postfit_up,
impact_postfit_down,
)
folder_path = "tmp"
figure_path = pathlib.Path(folder_path) / "ranking.pdf"
bestfit_expected = np.asarray([0.1, 1.2])
uncertainty_expected = np.asarray([0.8, 0.2])
labels_expected = ["modeling", "staterror_a"]
visualize.ranking(ranking_results, figure_folder=folder_path)
assert mock_draw.call_count == 1
assert np.allclose(mock_draw.call_args[0][0], bestfit_expected)
assert np.allclose(mock_draw.call_args[0][1], uncertainty_expected)
for i_lab, label in enumerate(mock_draw.call_args[0][2]):
assert label == labels_expected[i_lab]
assert np.allclose(mock_draw.call_args[0][3], impact_prefit_up[::-1])
assert np.allclose(mock_draw.call_args[0][4], impact_prefit_down[::-1])
assert np.allclose(mock_draw.call_args[0][5], impact_postfit_up[::-1])
assert np.allclose(mock_draw.call_args[0][6], impact_postfit_down[::-1])
assert mock_draw.call_args[0][7] == figure_path
assert mock_draw.call_args[1] == {"close_figure": False}
# maximum parameter amount specified, close figure
visualize.ranking(ranking_results,
figure_folder=folder_path,
max_pars=1,
close_figure=True)
assert mock_draw.call_count == 2
assert np.allclose(mock_draw.call_args[0][0], bestfit_expected[0])
assert np.allclose(mock_draw.call_args[0][1], uncertainty_expected[0])
assert mock_draw.call_args[0][2] == labels_expected[0]
assert np.allclose(mock_draw.call_args[0][3], impact_prefit_up[1])
assert np.allclose(mock_draw.call_args[0][4], impact_prefit_down[1])
assert np.allclose(mock_draw.call_args[0][5], impact_postfit_up[1])
assert np.allclose(mock_draw.call_args[0][6], impact_postfit_down[1])
assert mock_draw.call_args[0][7] == figure_path
assert mock_draw.call_args[1] == {"close_figure": True}
# unknown plotting method
with pytest.raises(NotImplementedError, match="unknown backend: unknown"):
visualize.ranking(ranking_results,
figure_folder=folder_path,
method="unknown")
def test_RankingResults():
bestfit = np.asarray([1.0])
uncertainty = np.asarray([0.1])
labels = ["par_a"]
prefit_up = np.asarray([0.3])
prefit_down = np.asarray([-0.3])
postfit_up = np.asarray([0.2])
postfit_down = np.asarray([-0.2])
ranking_results = fit.RankingResults(bestfit, uncertainty, labels,
prefit_up, prefit_down, postfit_up,
postfit_down)
assert np.allclose(ranking_results.bestfit, bestfit)
assert np.allclose(ranking_results.uncertainty, uncertainty)
assert ranking_results.labels == labels
assert np.allclose(ranking_results.prefit_up, prefit_up)
assert np.allclose(ranking_results.prefit_down, prefit_down)
assert np.allclose(ranking_results.postfit_up, postfit_up)
assert np.allclose(ranking_results.postfit_down, postfit_down)
assert mock_pulls.call_args_list[-1] == (
(fit_results, ),
{
"figure_folder": "folder"
},
)
@mock.patch("cabinetry.visualize.ranking", autospec=True)
@mock.patch(
"cabinetry.fit.ranking",
return_value=fit.RankingResults(
np.asarray([1.0]),
np.asarray([0.1]),
["label"],
np.asarray([[1.2]]),
np.asarray([[0.8]]),
np.asarray([[1.1]]),
np.asarray([[0.9]]),
),
autospec=True,
)
@mock.patch(
"cabinetry.fit.fit",
return_value=fit.FitResults(np.asarray([1.0]), np.asarray([0.1]),
["label"], np.asarray([[1.0]]), 1.0),
autospec=True,
)
@mock.patch(
"cabinetry.model_utils.model_and_data",
return_value=("model", "data"),