def test_into_edges_reconnetcion_onsmall_graph_3d_higres_neighborhood(
self):
data = np.array([[[0, 0], [0, 1]], [[0, 1], [1, 1]]])
g = graph.Graph(data, (0.1, 0.2, 0.05), grid_function="nd", nsplit=2)
g.run(base_grid_vtk_fn="base_grid.vtk",
final_grid_vtk_fn="final_grid.vtk")
def test_from_edges_reconnetcion_onsmall_graph_3d_higres_neighborhood(
self):
data = np.array([
[[
1,
1,
], [
1,
0,
]],
[[
1,
0,
], [
0,
0,
]],
])
g = graph.Graph(data, (0.1, 0.2, 0.05),
grid_function="nd",
nsplit=2,
compute_msindex=True)
g.run(base_grid_vtk_fn="base_grid.vtk",
final_grid_vtk_fn="final_grid.vtk")
def test_just_two_blocks(self):
data = np.array([[[0, 1]]])
g = graph.Graph(data, (0.1, 0.2, 0.05), grid_function="nd", nsplit=2)
g.run(base_grid_vtk_fn="base_grid.vtk",
final_grid_vtk_fn="final_grid.vtk")
g
def test_into_edges_reconnetcion_on_small_graph_3d(self):
data = np.array([
[[
0,
0,
], [
0,
0,
]],
[[
0,
0,
], [
0,
1,
]],
])
g = graph.Graph(data, (0.1, 0.2, 0.05), grid_function="nd", nsplit=2)
g.run(base_grid_vtk_fn="base_grid.vtk",
final_grid_vtk_fn="final_grid.vtk")
g.edges
self.assertEqual(g.edges.shape[0], 33)
self.assertEqual(g.edges.shape[1], 2)
self.assertEqual(g.nodes.shape[0], 15)
def test_graph_3d_two_slices(self):
data = np.array([
[[0, 0, 0, 0, 1, 1, 0], [0, 1, 1, 0, 1, 0,
1], [0, 1, 1, 0, 1, 0, 0],
[1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1]],
[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0,
0], [0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1]],
])
g = graph.Graph(data, (0.1, 0.12, 0.05))
g.run()
def test_graph_3d_implementation(self):
data = np.array([[0, 0, 0, 0, 1, 1, 0], [0, 1, 1, 0, 1, 0, 1],
[0, 1, 1, 0, 1, 0, 0], [1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1]])
# g = graph.Graph(data, (0.1, 0.12), grid_function="2d", nsplit=3)
# 3d 2:0,
# diff 3d 2:6, 3:15, 4:24, 5:33 6:42 7:51
g = graph.Graph(data, (0.1, 0.12), grid_function="nd", nsplit=7)
g.run(base_grid_vtk_fn="base_grid.vtk",
final_grid_vtk_fn="final_grid.vtk")
g.lastnode
def test_graph_2d_implementation(self):
data = np.array([[0, 0, 0, 0, 1, 1, 0], [0, 1, 1, 0, 1, 0, 1],
[0, 1, 1, 0, 1, 0, 0], [1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1]])
g = graph.Graph(data, (0.1, 0.12), grid_function="2d", nsplit=7)
# g = graph.Graph(data, (0.1, 0.12), grid_function="nd", nsplit=5)
g.run(base_grid_vtk_fn="base_grid.vtk",
final_grid_vtk_fn="final_grid.vtk")
# 2d edge number diff= nsplit:(g.lastedge - g.edmax_debug)
#
# 2: 6, 3:15, 4:24
g
def test_graph_3d(self):
data = np.array([
[[0, 0, 0, 0, 0], [0, 1, 1, 0, 1], [1, 1, 1, 0, 0],
[0, 0, 0, 0, 1]],
[[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 1, 1, 0, 0],
[0, 0, 0, 0, 1]],
[[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 1, 1, 0, 0],
[0, 0, 0, 0, 1]],
])
g = graph.Graph(data, (0.1, 0.12, 0.05), grid_function="nd", nsplit=6)
# 2:-21, 3:10, 4:57 5:120 6:199
31, 47, 63, 79
16, 16, 16
g.run(base_grid_vtk_fn="base_grid.vtk",
final_grid_vtk_fn="final_grid.vtk")
g.lastnode
def test_into_maximum_edge_number(self):
# data = np.random.random([50, 50, 8])
data = np.random.random([5, 3, 3])
data = data < 0.08
# data = np.random.random_integers(0,1, [10,10,10])
g = graph.Graph(data, (0.1, 0.2, 0.05), grid_function="nd", nsplit=6)
g.run(base_grid_vtk_fn="base_grid.vtk",
final_grid_vtk_fn="final_grid.vtk")
unused_edges = g.edmax - g.lastedge
unused_nodes = g.ndmax - g.lastnode
edge_efectivity = 1 - float(unused_edges) / g.edmax
node_efectivity = 1 - float(unused_nodes) / g.ndmax
logger.info("Memory node efficiency: {} ({})".format(
node_efectivity, g.ndmax))
logger.info("Memory edge efficiency: {} ({})".format(
edge_efectivity, g.edmax))
g
def test_raise_exception_on_different_input_shapes(self):
data = np.array([
[[
1,
1,
], [
1,
0,
]],
[[
1,
0,
], [
0,
0,
]],
])
g = graph.Graph(data, (0.1, 0.2), grid_function="nd", nsplit=2)
def test_msindex_on_small_graph_3d(self):
data = np.array([[[1, 0], [0, 0]], [[0, 0], [0, 0]]])
g = graph.Graph(data, (0.1, 0.2, 0.05),
grid_function="nd",
nsplit=2,
compute_msindex=True)
g.run(base_grid_vtk_fn="base_grid.vtk",
final_grid_vtk_fn="final_grid.vtk")
self.assertEqual(g.edges.shape[0], 33)
self.assertEqual(g.edges.shape[1], 2)
self.assertEqual(g.nodes.shape[0], 15)
# msindex with low resolution should be in the beginning of data
un, counts = np.unique(g.msinds, return_counts=True)
# on this example first 7 node labeles should be used multiple timse
self.assertTrue(
(counts[:7] > 1).all(),
msg=
"on this example first 7 node labeles should be used multiple times",
)
def test_raise_exception_on_different_input_shapes(self):
data = np.array([[[1, 1], [1, 0]], [[1, 0], [0, 0]]])
with pytest.raises(ValueError) as excinfo:
g = graph.Graph(data, (0.1, 0.2), grid_function="nd", nsplit=2)