added realplot to tornadopage in VolumetricAnalysis

CHANGELOG.md

@@ -6,6 +6,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [UNRELEASED] - YYYY-MM-DD
 
+### Added
+- [#845](https://github.com/equinor/webviz-subsurface/pull/845) - Added realization plot colored by sensitivity to tornado tab in `VolumetricAnalysis`. 
+
 ### Changed
 - [#844](https://github.com/equinor/webviz-subsurface/pull/844) - `SeismicMisfit` improvements. Data ranges now follows selected attribute. User defined zooms are now kept during callbacks. New option in slice plot to show individual realizations. Prettyfied all hoverdata. New colorscales. Polygons sorted by name in drop down selector.
 

webviz_subsurface/_components/tornado/_tornado_bar_chart.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Union
 
 import pandas as pd
 import plotly.graph_objects as go
@@ -18,7 +18,7 @@ def __init__(
         plotly_theme: Dict[str, Any],
         figure_height: Optional[int] = None,
         label_options: str = "detailed",
-        locked_si_prefix: Optional[int] = None,
+        locked_si_prefix: Optional[Union[int, str]] = None,
         number_format: str = "",
         unit: str = "",
         spaced: bool = True,
@@ -29,14 +29,14 @@ def __init__(
         sensitivity_color_map: dict = None,
     ) -> None:
         self._tornadotable = tornado_data.tornadotable
-        self._realtable = self.make_points(tornado_data.real_df)
+        self._realtable = tornado_data.real_df
         self._reference_average = tornado_data.reference_average
         self._plotly_theme = plotly_theme
         self._number_format = number_format
         self._unit = unit
         self._spaced = spaced
         self._locked_si_prefix = locked_si_prefix
-        self._locked_si_prefix_relative: Optional[int]
+        self._locked_si_prefix_relative: Optional[Union[str, int]]
         self._scale = tornado_data.scale
         self._use_true_base = use_true_base
         self._show_reference = show_reference
@@ -59,26 +59,6 @@ def create_color_list(self, sensitivities: list) -> list:
             else self._plotly_theme["layout"]["colorway"]
         )
 
-    def make_points(self, realdf: pd.DataFrame) -> pd.DataFrame:
-        dfs = []
-        for sensname in self._tornadotable["sensname"].unique():
-            for case in ["high", "low"]:
-                df = realdf.loc[
-                    realdf["REAL"].isin(
-                        self._tornadotable[self._tornadotable["sensname"] == sensname][
-                            f"{case}_reals"
-                        ].iloc[0]
-                    )
-                ].copy()
-                df["sensname"] = sensname
-                df["case"] = case
-                dfs.append(df)
-        return (
-            pd.concat(dfs)
-            if dfs
-            else pd.DataFrame(columns=["REAL", "sensname", "case"])
-        )
-
     @property
     def figure_height(self) -> Optional[int]:
         """Set height of figure as a function of number of senscases(bars)"""

webviz_subsurface/_components/tornado/_tornado_data.py

@@ -1,5 +1,6 @@
 from typing import Dict, List, Union
 
+import numpy as np
 import pandas as pd
 
 
@@ -23,7 +24,7 @@ def __init__(
         if cutbyref:
             self._cut_sensitivities_by_ref()
         self._sort_sensitivities_by_max()
-        self._real_df = dframe[["REAL", "VALUE"]]
+        self._real_df = self._create_real_df(dframe)
 
     def _validate_input(self, dframe: pd.DataFrame) -> None:
         for col in self.REQUIRED_COLUMNS:
@@ -43,6 +44,29 @@ def _validate_input(self, dframe: pd.DataFrame) -> None:
         if dframe.loc[dframe["SENSNAME"].isin([self._reference])].empty:
             raise ValueError(f"Reference SENSNAME {self._reference} not in input data")
 
+    def _create_real_df(self, dframe: pd.DataFrame) -> pd.DataFrame:
+        """Make dataframe with value and case info per realization"""
+        realdf = dframe[self.REQUIRED_COLUMNS].rename(
+            columns={"SENSNAME": "sensname", "SENSCASE": "senscase"}
+        )
+
+        sensitivities = self._tornadotable["sensname"].unique()
+        realdf = realdf.loc[realdf["sensname"].isin(sensitivities)]
+
+        for val in self.low_high_realizations_list.values():
+            for case in ["high", "low"]:
+                casemask = realdf["REAL"].isin(val[f"real_{case}"])
+                realdf.loc[casemask, "case"] = case
+
+        mc_mask = realdf["SENSTYPE"] == "mc"
+        realdf["casetype"] = np.where(mc_mask, "mc", realdf["case"])
+        realdf["sensname_case"] = np.where(
+            mc_mask,
+            realdf["sensname"],
+            realdf[["sensname", "senscase"]].agg("--".join, axis=1),
+        )
+        return realdf
+
     @property
     def real_df(self) -> pd.DataFrame:
         return self._real_df

webviz_subsurface/_components/tornado/_tornado_table.py

@@ -1,4 +1,6 @@
-from typing import Dict, List
+from typing import Dict, List, Union
+
+from dash.dash_table.Format import Format
 
 from ._tornado_data import TornadoData
 
@@ -9,10 +11,13 @@ class TornadoTable:
     def __init__(
         self,
         tornado_data: TornadoData,
+        use_si_format: bool = True,
+        precision: int = 4,
     ) -> None:
         self._table = tornado_data.tornadotable.copy()
         self.scale = tornado_data.scale
-
+        self._use_si_format = use_si_format
+        self._precision = precision
         self._table["low_reals"] = self._table["low_reals"].apply(lambda x: str(len(x)))
         self._table["high_reals"] = self._table["high_reals"].apply(
             lambda x: str(len(x))
@@ -31,21 +36,24 @@ def __init__(
             inplace=True,
         )
 
+    def set_column_format(self, col: str) -> Union[dict, Format]:
+        if "%" in col:
+            return {"specifier": ".1f"}
+        if self._use_si_format:
+            return {
+                "locale": {"symbol": ["", ""]},
+                "specifier": f"$.{self._precision}s",
+            }
+        return Format(precision=self._precision)
+
     @property
     def columns(self) -> List[Dict]:
         return [
             {
                 "name": col,
                 "id": col,
                 "type": "numeric",
-                "format": {
-                    "locale": {"symbol": ["", ""]},
-                    "specifier": "$.4s",
-                }
-                if not "%" in col
-                else {
-                    "specifier": ".1f",
-                },
+                "format": self.set_column_format(col),
             }
             for col in [
                 "Response",