Add mean in tornado table VolumetricAnalysis (#1297)

equinor · Aug 19, 2024 · 04b4aab · 04b4aab
1 parent c7b388a
commit 04b4aab
Show file tree

Hide file tree

Showing 4 changed files with 14 additions and 2 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -8,6 +8,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [UNRELEASED] - YYYY-MM-DD
 
+### Added
+- [#1297](https://github.com/equinor/webviz-subsurface/pull/1297) - Added mean for mc sensitivities in the tornadotable in `VolumetricAnalysis`.
+
+## [0.2.30] - 2024-06-10
+
 ### Added
 - [#1293](https://github.com/equinor/webviz-subsurface/pull/1293) - Added automatic calculation of `STOIIP_TOTAL` / `GIIP_TOTAL` in `VolumetricAnalysis`.
 

diff --git a/setup.py b/setup.py
@@ -14,7 +14,7 @@
     "pytest-xdist",
     "pytest-forked",
     "selenium>=3.141",
-    "types-pkg-resources",
+    "types-setuptools",
     "types-pyyaml",
 ]
 

diff --git a/webviz_subsurface/_components/tornado/_tornado_data.py b/webviz_subsurface/_components/tornado/_tornado_data.py
@@ -25,6 +25,9 @@ def __init__(
             self._cut_sensitivities_by_ref()
         self._sort_sensitivities_by_max()
         self._real_df = self._create_real_df(dframe)
+        self.mean_per_mc_sens = (
+            dframe[dframe["SENSTYPE"] == "mc"].groupby("SENSNAME")["VALUE"].mean()
+        )
 
     def _validate_input(self, dframe: pd.DataFrame) -> None:
         for col in self.REQUIRED_COLUMNS:

diff --git a/webviz_subsurface/plugins/_volumetric_analysis/controllers/tornado_controllers.py b/webviz_subsurface/plugins/_volumetric_analysis/controllers/tornado_controllers.py
@@ -359,12 +359,16 @@ def create_tornado_table(
         use_si_format=use_si_format,
         precision=4 if use_si_format else 3,
     )
+    mean_col = "Mean (mc)"
     table_data = tornado_table.as_plotly_table
     for data in table_data:
-        data["Reference"] = tornado_data.reference_average
+        data[mean_col] = tornado_data.mean_per_mc_sens.get(data["Sensitivity"])
         if group is not None:
             data[subplots] = group
 
     columns = create_table_columns(columns=[subplots]) if subplots is not None else []
     columns.extend(tornado_table.columns)
+    columns.insert(
+        -3, create_table_columns(columns=[mean_col], use_si_format=[mean_col])[0]
+    )
     return table_data, columns