Add tests for univariate missfits and boxplot representations

- Formatting ert-style.json
equinor · Dec 14, 2020 · e38be15 · e38be15
1 parent 81aa449
commit e38be15
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Showing 3 changed files with 47 additions and 8 deletions.
diff --git a/ertviz/assets/ert-style.json b/ertviz/assets/ert-style.json
@@ -90,11 +90,16 @@
             "marker": null
         }
     },
-    "figure":{
-        "layout" : {
-            "hovermode":"closest",
-            "uirevision":true,
-            "margin": {"l": 5, "b": 5, "t": 5, "r": 5},
+    "figure": {
+        "layout": {
+            "hovermode": "closest",
+            "uirevision": true,
+            "margin": {
+                "l": 5,
+                "b": 5,
+                "t": 5,
+                "r": 5
+            },
             "autosize": true
         }
     }

diff --git a/ertviz/controllers/observation_response_controller.py b/ertviz/controllers/observation_response_controller.py
@@ -37,8 +37,6 @@ def _create_misfits_plot(response, selected_realizations, color):
         realizations,
         [],
         dict(
-            xaxis={"title": "Index"},
-            yaxis={"title": "Unit TODO"},
             hovermode="closest",
             uirevision=True,
         ),

diff --git a/tests/plots/test_controller.py b/tests/plots/test_controller.py
@@ -7,10 +7,13 @@
     _get_realizations_plots,
     _get_realizations_statistics_plots,
 )
+from ertviz.controllers.observation_response_controller import (
+    _get_univariate_misfits_boxplots,
+)
 from ertviz.controllers.ensemble_selector_controller import _construct_graph
 from ertviz.data_loader import get_ensembles
 from ertviz.models import EnsembleModel
-from ertviz.models import HistogramPlotModel, MultiHistogramPlotModel
+from ertviz.models import HistogramPlotModel, MultiHistogramPlotModel, BoxPlotModel
 import ertviz.assets as assets
 
 
@@ -125,3 +128,36 @@ def test_multi_histogram_plot_representation():
         assert plot.data[idx].autobinx == False
         assert plot.data[idx].marker.color == colors_dict[ensemble_name]
         assert plot.data[idx].name == ensemble_name
+
+
+def test_univariate_misfits_boxplot_representation():
+    data = np.random.rand(200).reshape(-1, 20)
+    missfits_df = pd.DataFrame(data=data, index=range(10), columns=range(20))
+    missfits_df["x_axis"] = np.arange(10)
+    plots = _get_univariate_misfits_boxplots(
+        missfits_df.copy(), assets.ERTSTYLE["ensemble-selector"]["color_wheel"][0]
+    )
+
+    assert len(plots) == 10
+    for id_plot, plot in enumerate(plots):
+        np.testing.assert_equal(0.3, plot.repr.jitter)
+        np.testing.assert_equal("all", plot.repr.boxpoints)
+        x_pos = int(missfits_df["x_axis"][id_plot])
+        name = f"Misfits@{x_pos}"
+        assert name == plot.repr.name
+
+
+def test_boxplot_representation():
+    data = np.random.rand(10)
+    data_df = pd.DataFrame(data=data, index=range(10))
+
+    plot = BoxPlotModel(
+        x_axis=[5],
+        y_axis=data_df.values,
+        name="Boxplot@Location5",
+        color=assets.ERTSTYLE["ensemble-selector"]["color_wheel"][0],
+    )
+    plot = plot.repr
+    np.testing.assert_equal(plot.y.flatten(), data)
+    assert plot.boxpoints == "all"
+    assert plot.name == "Boxplot@Location5"