Make gradient_rotation stashable. Interpolate in air in place

Author: domfournier

simpeg_drivers/components/models.py

@@ -637,10 +637,9 @@ def _get_value(self, model: float | NumericData) -> np.ndarray:
         if isinstance(model, NumericData):
             model = self.obj_2_mesh(model, self.driver.inversion_mesh.entity)
             model = (self.driver.inversion_mesh.permutation @ model).astype(model.dtype)
-        else:
+        elif isinstance(model, int | float):
             nc = self.driver.inversion_mesh.mesh.n_cells
-            if isinstance(model, int | float):
-                model *= np.ones(nc)
+            model *= np.ones(nc)
 
         return model
 

simpeg_drivers/options.py

@@ -17,6 +17,7 @@
 
 import numpy as np
 from geoapps_utils.base import Options
+from geoapps_utils.utils.numerical import weighted_average
 from geoh5py.data import (
     BooleanData,
     DataAssociationEnum,
@@ -29,7 +30,6 @@
 from geoh5py.objects import DrapeModel, Grid2D, Octree, Points
 from geoh5py.objects.surveys.electromagnetics.base import BaseEMSurvey
 from geoh5py.ui_json import InputFile
-from geoh5py.ui_json.utils import fetch_active_workspace
 from pydantic import (
     AliasChoices,
     BaseModel,
@@ -285,6 +285,8 @@ class ModelOptions(BaseModel):
     y_norm: float | FloatData | None = 2.0
     z_norm: float | FloatData = 2.0
 
+    _gradient_orientations: np.ndarray | None = None
+
     @property
     def gradient_direction(self) -> np.ndarray:
         if self.gradient_orientations is None:
@@ -306,12 +308,20 @@ def gradient_orientations(self) -> tuple(float, float):
         and clockwise from horizontal for dip.
         """
 
-        if self.gradient_rotation is not None:
+        if self._gradient_orientations is None and self.gradient_rotation is not None:
             orientations = direction_and_dip(self.gradient_rotation)
 
-            return np.deg2rad(orientations)
+            angles = np.deg2rad(orientations)
+            # Deal with aircells here
+            orientations = weighted_average(
+                self.gradient_rotation.parent.centroids,
+                self.gradient_rotation.parent.centroids,
+                [angles[:, 0], angles[:, 1]],
+            )
+
+            self._gradient_orientations = np.vstack(orientations).T
 
-        return None
+        return self._gradient_orientations
 
 
 class ConductivityModelOptions(ModelOptions):