(BUGFIX) if you try and access a feature that does

not exist it will print an error
Removing attempts to build better frames

Author: lachlangrose

LoopStructural/modelling/core/geological_model.py

@@ -1341,6 +1341,7 @@ def get_feature_by_name(self, feature_name):
         if feature_index > -1:
             return self.features[feature_index]
         else:
+            logger.error("{} does not exist!".format(feature_name))
             return None
 
     def evaluate_feature_value(self, feature_name, xyz, scale=True):

LoopStructural/modelling/features/structural_frame_builder.py

@@ -162,18 +162,18 @@ def build(self, w1=1., w2=1., w3=1., frame=StructuralFrame, **kwargs):
             gy_const_norm = kwargs.get('gy_const_norm',0.)
 
             ## bit of an ugly hack, adding in norm constraints for the norm we are forcing
-            if gz_feature is not None: 
-                tmp = CrossProductGeologicalFeature('tmp',gx_feature,gz_feature)
-                self.builders[1].add_orthogonal_feature(tmp,10.,step=step,B=1)
-                # gy_feature.value_feature = fold.fold frame[0]
-                # vector = feature.evaluate_gradient(self.builders[1].interpolator.support.barycentre())
-                # vector /= np.linalg.norm(vector,axis=1)[:,None]
-                # element_idx = np.arange(self.builders[1].interpolator.support.n_elements)
-                # np.random.shuffle(element_idx)
-                # norm_pts = np.hstack([self.builders[1].interpolator.support.barycentre()[element_idx[::step],:],vector[element_idx[::step],:],np.ones((vector[element_idx[::step],:].shape[0],1))])
-
-                # self.builders[1].interpolator.set_normal_constraints(norm_pts)
-                self.builders[1].data_added=True
+            # if gz_feature is not None: 
+            #     tmp = CrossProductGeologicalFeature('tmp',gx_feature,gz_feature)
+            #     self.builders[1].add_orthogonal_feature(tmp,10.,step=step,B=1)
+            #     # gy_feature.value_feature = fold.fold frame[0]
+            #     # vector = feature.evaluate_gradient(self.builders[1].interpolator.support.barycentre())
+            #     # vector /= np.linalg.norm(vector,axis=1)[:,None]
+            #     # element_idx = np.arange(self.builders[1].interpolator.support.n_elements)
+            #     # np.random.shuffle(element_idx)
+            #     # norm_pts = np.hstack([self.builders[1].interpolator.support.barycentre()[element_idx[::step],:],vector[element_idx[::step],:],np.ones((vector[element_idx[::step],:].shape[0],1))])
+
+            #     # self.builders[1].interpolator.set_normal_constraints(norm_pts)
+            #     self.builders[1].data_added=True
 
             gy_feature = self.builders[1].build(regularisation=regularisation[1],**kwargs)