def test_multi_poly_lookup():
# A simple quad grid
nodes = np.array([
[0.0, 0.0], #0
[0.0, 2.0], #1
[2.0, 0.0], #2
[2.0, 2.0], #3
[4.0, 0.0], #4
[4.0, 2.0], #5
[6.0, 0.0], #6
[6.0, 2.0], #7
[0.0, 4.0], #8
[2.0, 4.0], #9
[4.0, 4.0], #10
[6.0, 4.0] #11
])
faces = np.array([[0, 8, 9, 5, 2], [9, 11, 7, 5, -1], [4, 7, 6, -1, -1]],
dtype=np.intc)
tree = CellTree(nodes, faces, num_buckets=2, cells_per_leaf=1)
point = np.array([1., 1.]) # in POLY 1
result = tree.locate(point)
assert result == 0
point[0] = 5.0 # tri 2
result = tree.locate(point)
assert result == 2
point[1] = 3.0
result = tree.locate(point)
assert result == 1
point[0] = -1.0 # out of grid
result = tree.locate(point)
assert result == -1
def test_multi_poly_lookup():
# A simple quad grid
nodes = np.array(
[
[0.0, 0.0], # 0
[0.0, 2.0], # 1
[2.0, 0.0], # 2
[2.0, 2.0], # 3
[4.0, 0.0], # 4
[4.0, 2.0], # 5
[6.0, 0.0], # 6
[6.0, 2.0], # 7
[0.0, 4.0], # 8
[2.0, 4.0], # 9
[4.0, 4.0], # 10
[6.0, 4.0], # 11
]
)
faces = np.array([[0, 8, 9, 5, 2], [9, 11, 7, 5, -1], [4, 7, 6, -1, -1]], dtype=np.intc)
tree = CellTree(nodes, faces, num_buckets=2, cells_per_leaf=1)
point = np.array([1.0, 1.0]) # in POLY 1
result = tree.locate(point)
assert result == 0
point[0] = 5.0 # tri 2
result = tree.locate(point)
assert result == 2
point[1] = 3.0
result = tree.locate(point)
assert result == 1
point[0] = -1.0 # out of grid
result = tree.locate(point)
assert result == -1
def test_triangle_lookup():
tree = CellTree(nodes, faces)
point = np.array([1., 1.]) # in triangle 1
result = tree.locate(point)
assert result == 0
point[0] = 2.0 # tri 2
result = tree.locate(point)
assert result == 1
point[0] = -1.0 # out of grid
result = tree.locate(point)
assert result == -1
def test_triangle_lookup():
tree = CellTree(nodes, faces)
point = np.array([1.0, 1.0]) # in triangle 1
result = tree.locate(point)
assert result == 0
point[0] = 2.0 # tri 2
result = tree.locate(point)
assert result == 1
point[0] = -1.0 # out of grid
result = tree.locate(point)
assert result == -1
def test_build_tree_from_coords():
"""
this tests using a structured grid with cell coordinates
converting it to a flattened grid with nodes and cells
defined as indexes to those nodes
as much as anything else, this surves as example code for how to do that.
"""
x, y = curv_grid(n_x=3,
n_y=3,
center=(0.0, 0.0),
min_radius=9.0,
max_radius=18.0,
angle=np.pi / 4.0
)
nodes, faces = nodes_from_coords(x, y)
# these range from (30., 20.) to (31.1, 21.1)
tree = CellTree(nodes, faces)
# try to find some points
# points outside the domain:
result = tree.locate([(0.0, 0.0),
(19.0, 5.0),
(17.0, -1.0),
(9.0, 10.0),
],
)
assert np.all(result == -1)
# points inside the domain
result = tree.locate([(10.0, 1.0),
(9.0, 3.0),
(8.0, 6.0),
(13.0, 1.0),
(12.0, 4.0),
(11.0, 7.0),
(16.0, 1.0),
(15.0, 8.0),
(13.0, 11.0),
]
)
assert np.array_equal(result, [0, 1, 2, 3, 4, 5, 6, 7, 8])
def test_multipoint():
tree = CellTree(nodes21, faces21)
points = [
(4.2, 3.0),
(7.7, 13.5),
(3.4, 7.000000001),
(7.0, 5.0), # out of bounds points
(8.66, 10.99),
(7.3, 0.74),
(2.5, 5.5),
(9.8, 12.3),
]
correct_indexes = (1, 20, 7, -1, -1, -1, -1, -1)
ind = tree.locate(points)
assert np.array_equal(ind, correct_indexes)
def test_multipoint():
tree = CellTree(nodes21, faces21)
points = [
(4.2, 3.0),
(7.7, 13.5),
(3.4, 7.000000001),
(7.0, 5.0), # out of bounds points
(8.66, 10.99),
(7.3, 0.74),
(2.5, 5.5),
(9.8, 12.3),
]
correct_indexes = (1, 20, 7, -1, -1, -1, -1, -1)
ind = tree.locate(points)
assert np.array_equal(ind, correct_indexes)
def test_poly_lookup():
# A simple quad grid
nodes = np.array([
[0.0, 0.0], #0
[0.0, 2.0], #1
[2.0, 0.0], #2
[2.0, 2.0], #3
[4.0, 0.0], #4
[4.0, 2.0], #5
[6.0, 0.0], #6
[6.0, 2.0], #7
[0.0, 4.0], #8
[2.0, 4.0], #9
[4.0, 4.0], #10
[6.0, 4.0] #11
])
#quads
faces1 = np.array([
[0, 2, 3, 1],
[4, 6, 7, 5],
], dtype=np.intc)
#Pentas
faces2 = np.array([
[0, 8, 9, 5, 2],
[9, 11, 6, 2, 5],
], dtype=np.intc)
tree1 = CellTree(nodes, faces1, num_buckets=2, cells_per_leaf=1)
point = np.array([1., 1.]) # in triangle 1
result = tree1.locate(point)
assert result == 0
point[0] = 5.0 # tri 2
result = tree1.locate(point)
assert result == 1
point[0] = -1.0 # out of grid
result = tree1.locate(point)
assert result == -1
tree2 = CellTree(nodes, faces2, num_buckets=2, cells_per_leaf=1)
point = np.array([1., 2.]) # in triangle 1
result = tree2.locate(point)
assert result == 0
point[0] = 5.0 # tri 2
result = tree2.locate(point)
assert result == 1
point[0] = -1.0 # out of grid
result = tree2.locate(point)
assert result == -1
def test_poly_lookup():
# A simple quad grid
nodes = np.array(
[
[0.0, 0.0], # 0
[0.0, 2.0], # 1
[2.0, 0.0], # 2
[2.0, 2.0], # 3
[4.0, 0.0], # 4
[4.0, 2.0], # 5
[6.0, 0.0], # 6
[6.0, 2.0], # 7
[0.0, 4.0], # 8
[2.0, 4.0], # 9
[4.0, 4.0], # 10
[6.0, 4.0], # 11
]
)
# quads
faces1 = np.array([[0, 2, 3, 1], [4, 6, 7, 5]], dtype=np.intc)
# Pentas
faces2 = np.array([[0, 8, 9, 5, 2], [9, 11, 6, 2, 5]], dtype=np.intc)
tree1 = CellTree(nodes, faces1, num_buckets=2, cells_per_leaf=1)
point = np.array([1.0, 1.0]) # in triangle 1
result = tree1.locate(point)
assert result == 0
point[0] = 5.0 # tri 2
result = tree1.locate(point)
assert result == 1
point[0] = -1.0 # out of grid
result = tree1.locate(point)
assert result == -1
tree2 = CellTree(nodes, faces2, num_buckets=2, cells_per_leaf=1)
point = np.array([1.0, 2.0]) # in triangle 1
result = tree2.locate(point)
assert result == 0
point[0] = 5.0 # tri 2
result = tree2.locate(point)
assert result == 1
point[0] = -1.0 # out of grid
result = tree2.locate(point)
assert result == -1
