Renamed nx to dof when it represents the degree of freedom of an interpolator

Author: Axel Mengelle-Nicole

LoopStructural/interpolators/_discrete_interpolator.py

@@ -42,7 +42,7 @@ def __init__(self, support, data={}, c=None, up_to_date=False):
 
         self.shape = "rectangular"
         if self.shape == "square":
-            self.B = np.zeros(self.nx)
+            self.B = np.zeros(self.dof)
         self.c_ = 0
 
         self.solver = "cg"
@@ -60,7 +60,7 @@ def __init__(self, support, data={}, c=None, up_to_date=False):
         self.non_linear_constraints = []
         self.constraints = {}
         self.interpolation_weights = {}
-        logger.info("Creating discrete interpolator with {} degrees of freedom".format(self.nx))
+        logger.info("Creating discrete interpolator with {} degrees of freedom".format(self.dof))
         self.type = InterpolatorType.BASE_DISCRETE
 
     def set_nelements(self, nelements: int) -> int:
@@ -78,7 +78,7 @@ def n_elements(self) -> int:
         return self.support.n_elements
 
     @property
-    def nx(self) -> int:
+    def dof(self) -> int:
         """Number of degrees of freedom for the interpolator
 
         Returns
@@ -125,7 +125,7 @@ def set_region(self, region=None):
         # self.region_function = region
         logger.info(
             "Cannot use region at the moment. Interpolation now uses region and has {} degrees of freedom".format(
-                self.nx
+                self.dof
             )
         )
 
@@ -175,7 +175,7 @@ def reset(self):
         """
         self.constraints = {}
         self.c_ = 0
-        self.regularisation_scale = np.ones(self.nx)
+        self.regularisation_scale = np.ones(self.dof)
         logger.info("Resetting interpolation constraints")
 
     def add_constraints_to_least_squares(self, A, B, idc, w=1.0, name="undefined"):
@@ -245,7 +245,7 @@ def add_constraints_to_least_squares(self, A, B, idc, w=1.0, name="undefined"):
         rows = np.tile(rows, (A.shape[-1], 1)).T
         self.constraints[name] = {
             'matrix': sparse.coo_matrix(
-                (A.flatten(), (rows.flatten(), idc.flatten())), shape=(n_rows, self.nx)
+                (A.flatten(), (rows.flatten(), idc.flatten())), shape=(n_rows, self.dof)
             ).tocsc(),
             'b': B.flatten(),
             'w': w,
@@ -286,7 +286,7 @@ def add_inequality_constraints_to_matrix(
         A : numpy array
             matrix of coefficients
         bounds : numpy array
-            nx3 lower, upper, 1
+            n*3 lower, upper, 1
         idc : numpy array
             index of constraints in the matrix
         Returns
@@ -296,14 +296,14 @@ def add_inequality_constraints_to_matrix(
         # map from mesh node index to region node index
         gi = np.zeros(self.support.n_nodes, dtype=int)
         gi[:] = -1
-        gi[self.region] = np.arange(0, self.nx, dtype=int)
+        gi[self.region] = np.arange(0, self.dof, dtype=int)
         idc = gi[idc]
         rows = np.arange(0, idc.shape[0])
         rows = np.tile(rows, (A.shape[-1], 1)).T
 
         self.ineq_constraints[name] = {
             'matrix': sparse.coo_matrix(
-                (A.flatten(), (rows.flatten(), idc.flatten())), shape=(rows.shape[0], self.nx)
+                (A.flatten(), (rows.flatten(), idc.flatten())), shape=(rows.shape[0], self.dof)
             ).tocsc(),
             "bounds": bounds,
         }
@@ -431,7 +431,7 @@ def add_inequality_feature(
             np.ones((value.shape[0], 1)),
             l,
             u,
-            np.arange(0, self.nx, dtype=int),
+            np.arange(0, self.dof, dtype=int),
         )
 
     def add_equality_constraints(self, node_idx, values, name="undefined"):
@@ -454,7 +454,7 @@ def add_equality_constraints(self, node_idx, values, name="undefined"):
         # map from mesh node index to region node index
         gi = np.zeros(self.support.n_nodes)
         gi[:] = -1
-        gi[self.region] = np.arange(0, self.nx)
+        gi[self.region] = np.arange(0, self.dof)
         idc = gi[node_idx]
         outside = ~(idc == -1)
 
@@ -515,7 +515,7 @@ def add_equality_block(self, A, B):
         if len(self.equal_constraints) > 0:
             ATA = A.T.dot(A)
             ATB = A.T.dot(B)
-            logger.info(f"Equality block is {self.eq_const_c} x {self.nx}")
+            logger.info(f"Equality block is {self.eq_const_c} x {self.dof}")
             # solving constrained least squares using
             # | ATA CT | |c| = b
             # | C   0  | |y|   d
@@ -540,7 +540,7 @@ def add_equality_block(self, A, B):
 
             C = sparse.coo_matrix(
                 (np.array(a), (np.array(rows), cols)),
-                shape=(self.eq_const_c, self.nx),
+                shape=(self.eq_const_c, self.dof),
                 dtype=float,
             ).tocsr()
 
@@ -557,7 +557,7 @@ def build_inequality_matrix(self):
             mats.append(c['matrix'])
             bounds.append(c['bounds'])
         if len(mats) == 0:
-            return sparse.csr_matrix((0, self.nx), dtype=float), np.zeros((0, 3))
+            return sparse.csr_matrix((0, self.dof), dtype=float), np.zeros((0, 3))
         Q = sparse.vstack(mats)
         bounds = np.vstack(bounds)
         return Q, bounds

LoopStructural/interpolators/_finite_difference_interpolator.py

@@ -160,7 +160,7 @@ def add_value_constraints(self, w=1.0):
             # print(points[inside,:].shape)
             gi = np.zeros(self.support.n_nodes, dtype=int)
             gi[:] = -1
-            gi[self.region] = np.arange(0, self.nx, dtype=int)
+            gi[self.region] = np.arange(0, self.dof, dtype=int)
             idc = np.zeros(node_idx.shape)
             idc[:] = -1
             idc[inside, :] = gi[node_idx[inside, :]]
@@ -204,7 +204,7 @@ def add_interface_constraints(self, w=1.0):
             )
             gi = np.zeros(self.support.n_nodes, dtype=int)
             gi[:] = -1
-            gi[self.region] = np.arange(0, self.nx, dtype=int)
+            gi[self.region] = np.arange(0, self.dof, dtype=int)
             idc = np.zeros(node_idx.shape).astype(int)
             idc[:] = -1
             idc[inside, :] = gi[node_idx[inside, :]]
@@ -227,11 +227,11 @@ def add_interface_constraints(self, w=1.0):
                 interface_A = np.hstack([A[mask, :][ij[:, 0], :], -A[mask, :][ij[:, 1], :]])
                 interface_idc = np.hstack([idc[mask, :][ij[:, 0], :], idc[mask, :][ij[:, 1], :]])
                 # now map the index from global to region create array size of mesh
-                # initialise as np.nan, then map points inside region to 0->nx
+                # initialise as np.nan, then map points inside region to 0->dof
                 gi = np.zeros(self.support.n_nodes).astype(int)
                 gi[:] = -1
 
-                gi[self.region] = np.arange(0, self.nx)
+                gi[self.region] = np.arange(0, self.dof)
                 interface_idc = gi[interface_idc]
                 outside = ~np.any(interface_idc == -1, axis=1)
                 self.add_constraints_to_least_squares(
@@ -266,7 +266,7 @@ def add_gradient_constraints(self, w=1.0):
             # magnitude
             gi = np.zeros(self.support.n_nodes)
             gi[:] = -1
-            gi[self.region] = np.arange(0, self.nx)
+            gi[self.region] = np.arange(0, self.dof)
             idc = np.zeros(node_idx.shape)
             idc[:] = -1
             idc[inside, :] = gi[node_idx[inside, :]]
@@ -331,7 +331,7 @@ def add_norm_constraints(self, w=1.0):
             )
             gi = np.zeros(self.support.n_nodes)
             gi[:] = -1
-            gi[self.region] = np.arange(0, self.nx)
+            gi[self.region] = np.arange(0, self.dof)
             idc = np.zeros(node_idx.shape)
             idc[:] = -1
             idc[inside, :] = gi[node_idx[inside, :]]
@@ -421,7 +421,7 @@ def add_gradient_orthogonal_constraints(
             # magnitude
             gi = np.zeros(self.support.n_nodes)
             gi[:] = -1
-            gi[self.region] = np.arange(0, self.nx)
+            gi[self.region] = np.arange(0, self.dof)
             idc = np.zeros(node_idx.shape)
             idc[:] = -1
 
@@ -472,7 +472,7 @@ def add_gradient_orthogonal_constraints(
 
     #     """
     #     # First get the global indicies of the pairs of neighbours this should be an
-    #     # Nx27 array for 3d and an Nx9 array for 2d
+    #     # N*27 array for 3d and an N*9 array for 2d
 
     #     global_indexes = self.support.neighbour_global_indexes()
 
@@ -490,7 +490,7 @@ def assemble_inner(self, operator, w, name='regularisation'):
 
         """
         # First get the global indicies of the pairs of neighbours this should be an
-        # Nx27 array for 3d and an Nx9 array for 2d
+        # N*27 array for 3d and an N*9 array for 2d
 
         global_indexes = self.support.neighbour_global_indexes()  # np.array([ii,jj]))
 
@@ -499,7 +499,7 @@ def assemble_inner(self, operator, w, name='regularisation'):
 
         gi = np.zeros(self.support.n_nodes)
         gi[:] = -1
-        gi[self.region] = np.arange(0, self.nx)
+        gi[self.region] = np.arange(0, self.dof)
         idc = gi[idc]
         inside = ~np.any(idc == -1, axis=1)  # np.ones(a.shape[0],dtype=bool)#
         # a[idc==-1] = 0

LoopStructural/interpolators/_geological_interpolator.py

@@ -96,7 +96,7 @@ def to_json(self):
         json["constraints"] = self.constraints
         json["data"] = self.data
         json["type"] = self.type
-        # json["dof"] = self.nx
+        # json["dof"] = self.dof
         json["up_to_date"] = self.up_to_date
         return json
 

LoopStructural/interpolators/_surfe_wrapper.py

@@ -203,7 +203,7 @@ def evaluate_gradient(self, evaluation_points):
         return
 
     @property
-    def nx(self):
+    def dof(self):
         return self.get_data_locations().shape[0]
     @property
     def n_elements(self)->int:

LoopStructural/interpolators/supports/_2d_base_unstructured.py

@@ -30,7 +30,7 @@ def __init__(self, elements, vertices, neighbours, aabb_nsteps=None):
             self.order = 1
         elif self.elements.shape[1] == 6:
             self.order = 2
-        self.nx = self.vertices.shape[0]
+        self.dof = self.vertices.shape[0]
         self.neighbours = neighbours
         self.minimum = np.min(self.nodes, axis=0)
         self.maximum = np.max(self.nodes, axis=0)

LoopStructural/modelling/core/geological_model.py

@@ -1670,15 +1670,15 @@ def update(self, verbose=False, progressbar=True):
         for f in self.features:
             if f.type == FeatureType.FAULT:
                 nfeatures += 3
-                total_dof += f[0].interpolator.nx * 3
+                total_dof += f[0].interpolator.dof * 3
                 continue
             if isinstance(f, StructuralFrame):
                 nfeatures += 3
-                total_dof += f[0].interpolator.nx * 3
+                total_dof += f[0].interpolator.dof * 3
                 continue
             if f.type == FeatureType.INTERPOLATED:
                 nfeatures += 1
-                total_dof += f.interpolator.nx
+                total_dof += f.interpolator.dof
                 continue
         if verbose:
             print(

LoopStructural/modelling/features/builders/_geological_feature_builder.py

@@ -452,7 +452,7 @@ def set_interpolation_geometry(self, origin, maximum, rotation=None):
         self.interpolator.support.rotation_xy = rotation
         self._up_to_date = False
 
-        while self.interpolator.nx < 100:
+        while self.interpolator.dof < 100:
             self.interpolator.support.step_vector = self.interpolator.support.step_vector * 0.9
 
     def check_interpolation_geometry(self, data, buffer=0.3):

tests/unit/interpolator/test_discrete_interpolator.py

@@ -1,5 +1,5 @@
 def test_nx(interpolator, data):
-    assert interpolator.nx == 21 * 21 * 21
+    assert interpolator.dof == 21 * 21 * 21
 
 
 def test_region(interpolator, data, region_func):