def test_graph_is_frozen():
graph = UniformRectilinearGraph((3, 4))
assert_array_equal(
graph.nodes_at_link,
[
[0, 1],
[1, 2],
[2, 3],
[0, 4],
[1, 5],
[2, 6],
[3, 7],
[4, 5],
[5, 6],
[6, 7],
[4, 8],
[5, 9],
[6, 10],
[7, 11],
[8, 9],
[9, 10],
[10, 11],
],
)
with raises(ValueError):
graph.nodes_at_link[0] = [1, 0]
def test_graph_can_thaw():
graph = UniformRectilinearGraph((3, 4))
assert_array_equal(
graph.nodes_at_link,
[
[0, 1],
[1, 2],
[2, 3],
[0, 4],
[1, 5],
[2, 6],
[3, 7],
[4, 5],
[5, 6],
[6, 7],
[4, 8],
[5, 9],
[6, 10],
[7, 11],
[8, 9],
[9, 10],
[10, 11],
],
)
with graph.thawed():
graph.nodes_at_link[0] = [1, 0]
assert_array_equal(
graph.nodes_at_link,
[
[1, 0],
[1, 2],
[2, 3],
[0, 4],
[1, 5],
[2, 6],
[3, 7],
[4, 5],
[5, 6],
[6, 7],
[4, 8],
[5, 9],
[6, 10],
[7, 11],
[8, 9],
[9, 10],
[10, 11],
],
)
def dataset_from_bmi_uniform_rectilinear(bmi, grid_id):
from landlab.graph import UniformRectilinearGraph
rank = bmi.get_grid_rank(grid_id)
shape = bmi.get_grid_shape(grid_id)
spacing = bmi.get_grid_spacing(grid_id)
origin = bmi.get_grid_origin(grid_id)
if rank < 1 or rank > 3:
raise ValueError('uniform rectilinear grids must be rank 1, 2, or 3')
attrs=OrderedDict([
('cf_role', 'grid_topology'),
('long_name',
'Topology data of {rank}D structured quadrilateral'.format(rank=rank)),
('topology_dimension', rank),
('node_coordinates', ' '.join(coordinate_names(rank))),
('node_dimensions', ' '.join(index_names(rank))),
('node_spacing', 'node_spacing'),
('node_origin', 'node_origin'),
('type', 'structured_quad'),
])
dataset = xr.Dataset(
{'mesh': xr.DataArray(data=grid_id, attrs=attrs),
'node_shape': xr.DataArray(data=shape, dims=('rank', )),
'node_spacing': xr.DataArray(data=spacing, dims=('rank', )),
'node_origin': xr.DataArray(data=origin, dims=('rank', )),
})
coords = []
for dim in range(rank):
coords.append(np.arange(shape[dim], dtype=float) * spacing[dim] +
origin[dim])
coords_at_node = np.meshgrid(*coords, indexing='ij')
for axis, name in enumerate(COORDINATE_NAMES[-rank:]):
dataset = dataset.update({
'node_' + name: xr.DataArray(
data=coords_at_node[axis].reshape(-1), dims=('n_node', ),
attrs={'standard_name': name, 'units': 'm'})
})
if rank == 2:
graph = UniformRectilinearGraph(shape, spacing=spacing, origin=origin)
dataset = dataset.update({
'face_node_connectivity': xr.DataArray(
data=graph.nodes_at_patch.reshape((-1 ,)),
dims=('n_vertices', ),
attrs={'standard_name': 'Face-node connectivity'})
})
dataset = dataset.update({
'face_node_offset': xr.DataArray(
data=np.arange(1, graph.number_of_patches + 1, dtype=np.int32) * 4,
dims=('n_faces', ),
attrs={'standard_name': 'Offset to face-node connectivity'})
})
return dataset
def test_nodes():
graphs = (
UniformRectilinearGraph((3, 4)),
StructuredQuadGraph((
[[0.0, 0.0, 0.0, 0.0], [1.0, 1.0, 1.0, 1.0], [2.0, 2.0, 2.0, 2.0]],
[[0.0, 1.0, 2.0, 3.0], [0.0, 1.0, 2.0, 3.0], [0.0, 1.0, 2.0, 3.0]],
)),
RectilinearGraph(([0.0, 1.0, 2.0], [0.0, 1.0, 2.0, 3.0])),
)
for graph in graphs:
assert_array_equal(graph.nodes,
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])
with raises(ValueError):
graph.nodes[0, 0] = 99
def __init__(self, *args):
super(UniformRectilinear, self).__init__(*args)
if self.ndim < 1 or self.ndim > 3:
raise ValueError(
"uniform_rectangular grid must be rank 1, 2, or 3")
shape = self.bmi.grid_shape(self.grid_id)
spacing = self.bmi.grid_spacing(self.grid_id)
origin = self.bmi.grid_origin(self.grid_id)
self.metadata = OrderedDict([
("cf_role", "grid_topology"),
(
"long_name",
"Topology data of {}D structured quadrilateral".format(
self.ndim),
),
("topology_dimension", self.ndim),
("node_coordinates", " ".join(coordinate_names(self.ndim))),
("node_dimensions", " ".join(index_names(self.ndim))),
("node_spacing", "node_spacing"),
("node_origin", "node_origin"),
("type", self.grid_type),
])
self.set_mesh()
self.set_shape(shape)
self.set_spacing(spacing)
self.set_origin(origin)
grid_coords = []
for dim in range(self.ndim):
grid_coords.append(
np.arange(shape[dim], dtype=float) * spacing[dim] +
origin[dim])
self.set_nodes_rectilinear(grid_coords)
graph = UniformRectilinearGraph(shape, spacing=spacing, origin=origin)
self.set_connectivity(data=graph.nodes_at_patch.reshape((-1, )))
self.set_offset(
data=np.arange(1, graph.number_of_patches + 1, dtype=np.int32) * 4)
def test_link_dirs_at_node_raster():
graph = UniformRectilinearGraph((4, 3))
assert_array_equal(
graph.link_dirs_at_node,
[
[-1, -1, 0, 0],
[-1, -1, 1, 0],
[0, -1, 1, 0],
[-1, -1, 0, 1],
[-1, -1, 1, 1],
[0, -1, 1, 1],
[-1, -1, 0, 1],
[-1, -1, 1, 1],
[0, -1, 1, 1],
[-1, 0, 0, 1],
[-1, 0, 1, 1],
[0, 0, 1, 1],
],
)
assert graph.link_dirs_at_node.dtype == np.int8
def dataset_from_bmi_uniform_rectilinear(bmi, grid_id):
from landlab.graph import UniformRectilinearGraph
rank = bmi.get_grid_ndim(grid_id)
shape = bmi.get_grid_shape(grid_id)
spacing = bmi.get_grid_spacing(grid_id)
origin = bmi.get_grid_origin(grid_id)
if rank < 1 or rank > 3:
raise ValueError("uniform rectilinear grids must be rank 1, 2, or 3")
attrs = OrderedDict(
[
("cf_role", "grid_topology"),
(
"long_name",
"Topology data of {rank}D structured quadrilateral".format(rank=rank),
),
("topology_dimension", rank),
("node_coordinates", " ".join(coordinate_names(rank))),
("node_dimensions", " ".join(index_names(rank))),
("node_spacing", "node_spacing"),
("node_origin", "node_origin"),
("type", "structured_quad"),
]
)
dataset = xr.Dataset(
{
"mesh": xr.DataArray(data=grid_id, attrs=attrs),
"node_shape": xr.DataArray(data=shape, dims=("rank",)),
"node_spacing": xr.DataArray(data=spacing, dims=("rank",)),
"node_origin": xr.DataArray(data=origin, dims=("rank",)),
}
)
coords = []
for dim in range(rank):
coords.append(np.arange(shape[dim], dtype=float) * spacing[dim] + origin[dim])
coords_at_node = np.meshgrid(*coords, indexing="ij")
for axis, name in enumerate(COORDINATE_NAMES[-rank:]):
dataset = dataset.update(
{
"node_"
+ name: xr.DataArray(
data=coords_at_node[axis].reshape(-1),
dims=("node",),
attrs={"standard_name": name, "units": "m"},
)
}
)
if rank == 2:
graph = UniformRectilinearGraph(shape, spacing=spacing, origin=origin)
dataset = dataset.update(
{
"face_node_connectivity": xr.DataArray(
data=graph.nodes_at_patch.reshape((-1,)),
dims=("vertex",),
attrs={"standard_name": "Face-node connectivity"},
)
}
)
dataset = dataset.update(
{
"face_node_offset": xr.DataArray(
data=np.arange(1, graph.number_of_patches + 1, dtype=np.int32) * 4,
dims=("face",),
attrs={"standard_name": "Offset to face-node connectivity"},
)
}
)
return dataset