refactor: 🔥 cleaning up p2 interpolator

Author: Lachlan Grose

LoopStructural/interpolators/_p2interpolator.py

@@ -156,46 +156,7 @@ def add_norm_constraints(self, w=1.0):
 
         pass
 
-    def add_gradient_orthogonal_constraint(self, points, vector, w=1.0, B=0):
-        """
-        constraints scalar field to be orthogonal to a given vector
-
-        Parameters
-        ----------
-        position
-        normals
-        w
-        B
-
-        Returns
-        -------
-
-        """
-        pass
-        # if points.shape[0] > 0:
-        #     vertices, element_gradients, tetras, inside = self.support.get_tetra_gradient_for_location(points[:,:3])
-        #     #e, inside = self.support.elements_for_array(points[:, :3])
-        #     #nodes = self.support.nodes[self.support.elements[e]]
-        #     vector /= np.linalg.norm(vector,axis=1)[:,None]
-        #     vecs = vertices[:, 1:, :] - vertices[:, 0, None, :]
-        #     vol = np.abs(np.linalg.det(vecs))  # / 6
-        #     # d_t = self.support.get_elements_gradients(e)
-        #     norm = np.linalg.norm(element_gradients, axis=2)
-        #     element_gradients /= norm[:, :, None]
-
-        #     A = np.einsum('ij,ijk->ik', vector, element_gradients)
-
-        #     A *= vol[:, None]
-
-        #     gi = np.zeros(self.support.n_nodes).astype(int)
-        #     gi[:] = -1
-        #     gi[self.region] = np.arange(0, self.nx).astype(int)
-        #     w /= 3
-        #     idc = gi[tetras]
-        #     B = np.zeros(idc.shape[0])+B
-        #     outside = ~np.any(idc == -1, axis=1)
-        #     self.add_constraints_to_least_squares(A[outside, :] * w,
-        #                                           B[outside], idc[outside, :])
+     
 
     def add_value_constraints(self, w=1.0):
         points = self.get_value_constraints()