(BUGFIX) cleaning up for tests

Author: lachlangrose

LoopStructural/interpolators/structured_grid.py

@@ -40,24 +40,6 @@ def barycentre(self):
         return self.cell_centres(np.arange(self.n_elements))
 
 
-
-    def update_property(self, propertyname, values):
-        """[summary]
-
-        [extended_summary]
-
-        Parameters
-        ----------
-        propertyname : [type]
-            [description]
-        values : [type]
-            [description]
-        """
-        if values.shape[0] == self.n_nodes:
-            self.properties[propertyname] = values
-        if values.shape[0] == self.n_elements:
-            self.cell_properties[propertyname] = values
-
     def cell_centres(self, global_index):
         """[summary]
 

LoopStructural/interpolators/structured_tetra.py

@@ -41,8 +41,6 @@ def __init__(self, origin = [0,0,0], nsteps = [10,10,10], step_vector = [1,1,1])
             [1,0,3,5]
         ])
         self.ntetra = self.n_cells * 5
-        self.properties = {}
-        self.property_gradients = {}
         self.n_elements = self.ntetra
         self.cg = None
 
@@ -125,7 +123,6 @@ def evaluate_gradient(self, pos, property_array):
         values = np.zeros(pos.shape)
         values[:] = np.nan
         vertices, element_gradients, tetras, inside = self.get_tetra_gradient_for_location(pos)
-        vertex_vals = self.properties[prop][tetras]
         #grads = np.zeros(tetras.shape)
         values[inside,:] = (element_gradients[inside,:,:]*property_array[tetras[inside,None,:]]).sum(2)
         length = np.sum(values[inside,:],axis=1)

LoopStructural/modelling/core/geological_model.py

@@ -158,7 +158,7 @@ def __init__(self, origin, maximum, rescale=True, nsteps=(40, 40, 40),
         self.bounding_box /= self.scale_factor
         self.support = {}
         self.reuse_supports = reuse_supports
-        if reuse_supports:
+        if self.reuse_supports:
             logger.warning("Supports are shared between geological features \n"
                                 "this may cause unexpected behaviour and should only\n"
                                 "be use by advanced users")
@@ -484,7 +484,7 @@ def get_interpolator(self, interpolatortype='PLI', nelements=1e5,
             # number of steps is the length of the box / step vector
             nsteps = np.ceil((bb[1, :] - bb[0, :]) / step_vector).astype(int)
             # create a structured grid using the origin and number of steps
-            if reuse_supports:
+            if self.reuse_supports:
                 mesh_id = 'mesh_{}'.format(nelements)
                 mesh = self.support.get(mesh_id,
                                         TetMesh(origin=bb[0, :], nsteps=nsteps,

tests/unit_tests/interpolator/test_discrete_supports.py

@@ -20,14 +20,12 @@ def test_create_structured_grid_origin_nsteps():
 
 def test_evaluate_value():
     grid = StructuredGrid()
-    grid.update_property('X',grid.nodes[:,0])
     assert np.sum(grid.barycentre()[:,0] - 
-    grid.evaluate_value(grid.barycentre(),'X')) ==0
+    grid.evaluate_value(grid.barycentre(),grid.nodes[:,0])) ==0
 
 def test_evaluate_gradient():
     grid = StructuredGrid()
-    grid.update_property('Y',grid.nodes[:,1])
-    vector = np.mean(grid.evaluate_gradient(grid.barycentre(),'Y'),axis=0)
+    vector = np.mean(grid.evaluate_gradient(grid.barycentre(),grid.nodes[:,1]),axis=0)
     # vector/=np.linalg.norm(vector)
     assert np.sum(vector-np.array([0,grid.step_vector[1],0])) == 0
 
@@ -76,13 +74,11 @@ def test_create_tetmesh_origin_nsteps():
 
 def test_evaluate_value_tetmesh():
     grid = TetMesh()
-    grid.update_property('X',grid.nodes[:,0])
     assert np.sum(grid.barycentre()[:,0] - 
-    grid.evaluate_value(grid.barycentre(),'X')) ==0
+    grid.evaluate_value(grid.barycentre(),grid.nodes[:,0])) ==0
 
 def test_evaluate_gradient_tetmesh():
     grid = TetMesh()
-    grid.update_property('Y',grid.nodes[:,1])
-    vector = np.mean(grid.evaluate_gradient(grid.barycentre(),'Y'),axis=0)
+    vector = np.mean(grid.evaluate_gradient(grid.barycentre(),grid.nodes[:,1]),axis=0)
     # vector/=np.linalg.norm(vector)
     assert np.sum(vector-np.array([0,grid.step_vector[1],0])) == 0