def test_two_lines_no_snap(self):
p = np.array([[0, 1, 0.5, 0.5], [0, 0, 1e-3, 1]])
e = np.array([[0, 2], [1, 3]])
tol = 1e-4
p_new = cg.snap_points_to_segments(p, e, tol)
assert np.allclose(p_new, p)
def test_snapping_3d(self):
p = np.array([[0, 1, 0.5, 0.5], [0, 0, 1e-3, 1], [0, 1, 0.5, 1]])
e = np.array([[0, 2], [1, 3]])
tol = 1e-2
p_new = cg.snap_points_to_segments(p, e, tol)
p_known = np.array([[0, 1, 0.5, 0.5], [0, 0, 0, 1], [0, 1, 0.5, 1]])
assert np.allclose(p_new, p_known)
def test_single_point_no_snap(self):
p = np.array([[0, 1], [0, 0]])
e = np.array([[0], [1]])
tol = 1e-4
p_snap = np.array([[0.5], [1e-3]])
p_new = cg.snap_points_to_segments(p, e, tol, p_snap)
assert np.allclose(p_snap, p_new)
def test_vertex_snaps(self):
p = np.array([[0, 1, 0., 0.], [0, 0, 1e-3, 1]])
e = np.array([[0, 2], [1, 3]])
tol = 1e-2
p_new = cg.snap_points_to_segments(p, e, tol)
p_known = np.array([[0, 1, 0., 0.], [0, 0, 0, 1]])
self.assertTrue(np.allclose(p_new, p_known))
def create(conforming, tol=1e-4):
csv_folder = "./"
csv_file = "example_4_outcrop.csv"
pts, edges = importer.lines_from_csv(csv_folder + csv_file)
# A tolerance of 1 seems to be sufficient to recover the T-intersections, but
# I might have missed some, though, so take a look at the network and modify
# if necessary.
snap_pts = cg.snap_points_to_segments(pts, edges, tol=1)
extrusion_kwargs = {}
extrusion_kwargs["tol"] = tol
extrusion_kwargs["exposure_angle"] = np.pi / 4.0 * np.ones(edges.shape[1])
# Added an option not to include the points on the exposed surface. This
# reduces cell refinement somewhat, but setting it True should also be okay
extrusion_kwargs["outcrop_consistent"] = True
fractures = extrusion.fractures_from_outcrop(snap_pts, edges,
**extrusion_kwargs)
network = FractureNetwork(fractures, tol=tol)
# network.to_vtk(folder_export+"network.vtu")
bounding_box = {
"xmin": -800,
"xmax": 600,
"ymin": 100,
"ymax": 1500,
"zmin": -100,
"zmax": 1000,
}
network.impose_external_boundary(bounding_box,
truncate_fractures=True,
keep_box=False)
mesh_kwargs = {}
h = 30
mesh_kwargs["mesh_size"] = {
"mode": "weighted", # 'distance'
"value": h,
"bound_value": h,
"tol": tol,
}
if conforming:
# Change h_ideal and h_min at will here, but I ran into trouble with h_min < 1.
gb = meshing.dfn(network, conforming=True, h_ideal=100, h_min=5)
else:
# Switch conforming=True to get conforming meshes
gb = meshing.dfn(network,
conforming=False,
**mesh_kwargs,
keep_geo=True)
gb.remove_nodes(lambda g: g.dim == 0)
gb.compute_geometry()
gb.assign_node_ordering()
return gb
def test_single_point_snap(self):
p = np.array([[0, 1], [0, 0]])
e = np.array([[0], [1]])
tol = 1e-4
p_snap = np.array([[0.5], [1e-5]])
p_new = cg.snap_points_to_segments(p, e, tol, p_snap)
p_known = np.array([[0.5], [0]])
self.assertTrue(np.allclose(p_known, p_new, rtol=1e-8))