add tests

src/cabinetry/visualize/plot_result.py

@@ -166,6 +166,16 @@ def ranking(
     else:
         layout = None  # pragma: no cover  # layout set after figure creation instead
 
+    if impacts_method not in ["np_shift", "covariance", "auxdata_shift"]:
+        raise ValueError(
+            f"The impacts method {impacts_method} provided is not supported."
+            + " Valid options are (np_shift, covariance, auxdata_shift)"
+        )
+    if impacts_method == "auxdata_shift":
+        raise NotImplementedError(
+            "Plotting impacts computed by shifting auxiliary data is not supported yet."
+        )
+
     impacts_color_map = {
         "np_shift": ["C0", "C5"],
         "covariance": ["#2CA02C", "#98DF8A"],
@@ -207,7 +217,7 @@ def ranking(
     y_pos = np.arange(num_pars)[::-1]
 
     pre_up, pre_down = None, None
-    if impacts_method == "np_shifts":
+    if impacts_method == "np_shift":
         # pre-fit up
         pre_up = ax_impact.barh(
             y_pos,

tests/cli/test_cli.py

@@ -203,6 +203,7 @@ def test_fit(mock_utils, mock_fit, mock_pulls, mock_corrmat, tmp_path):
         np.asarray([[0.8]]),
         np.asarray([[1.1]]),
         np.asarray([[0.9]]),
+        impacts_method="np_shift",
     ),
     autospec=True,
 )

tests/fit/test_fit_results_containers.py

@@ -30,7 +30,14 @@ def test_RankingResults():
     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
+        bestfit,
+        uncertainty,
+        labels,
+        prefit_up,
+        prefit_down,
+        postfit_up,
+        postfit_down,
+        impacts_method="np_shift",
     )
     assert np.allclose(ranking_results.bestfit, bestfit)
     assert np.allclose(ranking_results.uncertainty, uncertainty)
@@ -39,6 +46,7 @@ def test_RankingResults():
     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 ranking_results.impacts_method, "np_shift"
 
 
 def test_ScanResults():

tests/visualize/test_visualize.py

@@ -510,10 +510,11 @@ def test_ranking(mock_draw):
         impact_prefit_down,
         impact_postfit_up,
         impact_postfit_down,
+        impacts_method="np_shift",
     )
     folder_path = "tmp"
 
-    figure_path = pathlib.Path(folder_path) / "ranking.pdf"
+    figure_path = pathlib.Path(folder_path) / "ranking_np_shift.pdf"
     bestfit_expected = np.asarray([0.1, 1.2])
     uncertainty_expected = np.asarray([0.8, 0.2])
     labels_expected = ["modeling", "staterror_a"]
@@ -530,7 +531,11 @@ def test_ranking(mock_draw):
     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[1] == {"figure_path": figure_path, "close_figure": True}
+    assert mock_draw.call_args[1] == {
+        "figure_path": figure_path,
+        "close_figure": True,
+        "impacts_method": "np_shift",
+    }
 
     # maximum parameter amount specified, do not close figure, do not save figure
     _ = visualize.ranking(
@@ -548,7 +553,44 @@ def test_ranking(mock_draw):
     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[1] == {"figure_path": None, "close_figure": False}
+    assert mock_draw.call_args[1] == {
+        "figure_path": None,
+        "close_figure": False,
+        "impacts_method": "np_shift",
+    }
+
+    # maximum parameter amount specified, do not close figure, do not save figure
+    # covariance impacts
+    ranking_results = fit.RankingResults(
+        bestfit,
+        uncertainty,
+        labels,
+        impact_prefit_up,
+        impact_prefit_down,
+        impact_postfit_up,
+        impact_postfit_down,
+        impacts_method="covariance",
+    )
+    _ = visualize.ranking(
+        ranking_results,
+        figure_folder=folder_path,
+        max_pars=1,
+        close_figure=False,
+        save_figure=False,
+    )
+    assert mock_draw.call_count == 3
+    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[1] == {
+        "figure_path": None,
+        "close_figure": False,
+        "impacts_method": "covariance",
+    }
 
 
 @mock.patch(

tests/visualize/test_visualize_plot_result.py

@@ -89,17 +89,50 @@ def test_ranking(tmp_path):
         impact_postfit_up,
         impact_postfit_down,
         figure_path=fname,
+        impacts_method="np_shift",
     )
     # large tolerance needed here, possibly related to lack of set_tight_layout usage
     assert (
-        compare_images("tests/visualize/reference/ranking.png", str(fname), 50) is None
+        compare_images("tests/visualize/reference/ranking_np_shift.png", str(fname), 50)
+        is None
     )
 
     # compare figure returned by function
     fname = tmp_path / "fig_from_return.png"
     fig.savefig(fname)
     assert (
-        compare_images("tests/visualize/reference/ranking.png", str(fname), 50) is None
+        compare_images("tests/visualize/reference/ranking_np_shift.png", str(fname), 50)
+        is None
+    )
+
+    fname = tmp_path / "fig_cov.png"
+    fig = plot_result.ranking(
+        bestfit,
+        uncertainty,
+        labels,
+        impact_prefit_up,
+        impact_prefit_down,
+        impact_postfit_up,
+        impact_postfit_down,
+        figure_path=fname,
+        impacts_method="covariance",
+    )
+    # large tolerance needed here, possibly related to lack of set_tight_layout usage
+    assert (
+        compare_images(
+            "tests/visualize/reference/ranking_covariance.png", str(fname), 50
+        )
+        is None
+    )
+
+    # compare figure returned by function
+    fname = tmp_path / "fig_cov_from_return.png"
+    fig.savefig(fname)
+    assert (
+        compare_images(
+            "tests/visualize/reference/ranking_covariance.png", str(fname), 50
+        )
+        is None
     )
 
     # do not save figure, but close it
@@ -116,6 +149,39 @@ def test_ranking(tmp_path):
         )
         assert mock_close_safe.call_args_list == [((fig, None, True), {})]
 
+    with pytest.raises(
+        ValueError,
+        match="The impacts method wrong_method provided is not supported."
+        + " Valid options are \\(np_shift, covariance, auxdata_shift\\)",
+    ):
+        plot_result.ranking(
+            bestfit,
+            uncertainty,
+            labels,
+            impact_prefit_up,
+            impact_prefit_down,
+            impact_postfit_up,
+            impact_postfit_down,
+            close_figure=True,
+            impacts_method="wrong_method",
+        )
+    with pytest.raises(
+        NotImplementedError,
+        match="Plotting impacts computed by shifting auxiliary data is not "
+        + "supported yet.",
+    ):
+        plot_result.ranking(
+            bestfit,
+            uncertainty,
+            labels,
+            impact_prefit_up,
+            impact_prefit_down,
+            impact_postfit_up,
+            impact_postfit_down,
+            close_figure=True,
+            impacts_method="auxdata_shift",
+        )
+
     plt.close("all")