landlab.graph.voronoi.voronoi

class DelaunayGraph[source]

Bases: Graph

Graph of a voronoi grid.

Examples

>>> from landlab.graph import DelaunayGraph

Create a voronoi grid.

Parameters:

nodes (tuple of array_like) – Coordinates of every node. First y, then x.

Examples

>>> from landlab.graph import DelaunayGraph
>>> node_x = [0.0, 1.0, 2.0, 0.9, 1.9, 2.9]
>>> node_y = [0, 0, 0, 2, 2, 2]
>>> graph = DelaunayGraph((node_y, node_x), sort=True)
>>> graph.x_of_node
array([0. ,  1. ,  2. ,  0.9,  1.9,  2.9])
>>> graph.y_of_node
array([0.,  0.,  0.,  2.,  2.,  2.])
>>> graph.nodes_at_link
array([[0, 1], [1, 2],
       [0, 3], [1, 3], [1, 4], [2, 4], [2, 5],
       [3, 4], [4, 5]])
>>> graph.links_at_node
array([[ 0,  2, -1, -1], [ 1,  4,  3,  0], [ 6,  5,  1, -1],
       [ 7,  2,  3, -1], [ 8,  7,  4,  5], [ 8,  6, -1, -1]])
>>> graph.links_at_patch
array([[3, 2, 0], [5, 4, 1], [7, 3, 4], [8, 5, 6]])
>>> graph.nodes_at_patch
array([[3, 0, 1], [4, 1, 2], [4, 3, 1], [5, 4, 2]])
__init__(node_y_and_x, max_node_spacing=None, sort=False, perimeter_links=None)[source]

Create a voronoi grid.

Parameters:

nodes (tuple of array_like) – Coordinates of every node. First y, then x.

Examples

>>> from landlab.graph import DelaunayGraph
>>> node_x = [0.0, 1.0, 2.0, 0.9, 1.9, 2.9]
>>> node_y = [0, 0, 0, 2, 2, 2]
>>> graph = DelaunayGraph((node_y, node_x), sort=True)
>>> graph.x_of_node
array([0. ,  1. ,  2. ,  0.9,  1.9,  2.9])
>>> graph.y_of_node
array([0.,  0.,  0.,  2.,  2.,  2.])
>>> graph.nodes_at_link
array([[0, 1], [1, 2],
       [0, 3], [1, 3], [1, 4], [2, 4], [2, 5],
       [3, 4], [4, 5]])
>>> graph.links_at_node
array([[ 0,  2, -1, -1], [ 1,  4,  3,  0], [ 6,  5,  1, -1],
       [ 7,  2,  3, -1], [ 8,  7,  4,  5], [ 8,  6, -1, -1]])
>>> graph.links_at_patch
array([[3, 2, 0], [5, 4, 1], [7, 3, 4], [8, 5, 6]])
>>> graph.nodes_at_patch
array([[3, 0, 1], [4, 1, 2], [4, 3, 1], [5, 4, 2]])
__new__(**kwargs)
property adjacent_nodes_at_node

Get adjacent nodes.

Examples

>>> from landlab.graph import Graph

First, a simple example with no diagonals.

>>> node_x, node_y = [0, 0, 0, 1, 1, 1, 2, 2, 2], [0, 1, 2, 0, 1, 2, 0, 1, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> graph = Graph((node_y, node_x), links=links, sort=True)
>>> graph.adjacent_nodes_at_node
array([[ 1,  3, -1, -1],
       [ 2,  4,  0, -1],
       [ 5,  1, -1, -1],
       [ 4,  6,  0, -1],
       [ 5,  7,  3,  1],
       [ 8,  4,  2, -1],
       [ 7,  3, -1, -1],
       [ 8,  6,  4, -1],
       [ 7,  5, -1, -1]])

Next, we add the diagonal from node 0 to node 4.

>>> node_x, node_y = [0, 0, 0, 1, 1, 1, 2, 2, 2], [0, 1, 2, 0, 1, 2, 0, 1, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
...     (0, 4),
... )
>>> graph = Graph((node_y, node_x), links=links, sort=True)
>>> graph.adjacent_nodes_at_node
array([[ 1,  4,  3, -1, -1],
       [ 2,  4,  0, -1, -1],
       [ 5,  1, -1, -1, -1],
       [ 4,  6,  0, -1, -1],
       [ 5,  7,  3,  0,  1],
       [ 8,  4,  2, -1, -1],
       [ 7,  3, -1, -1, -1],
       [ 8,  6,  4, -1, -1],
       [ 7,  5, -1, -1, -1]])

Get the angle of each link.

Examples

>>> import numpy as np
>>> from landlab.graph import Graph
>>> node_x, node_y = ([0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1])
>>> links = ((0, 1), (1, 2), (0, 3), (1, 4), (2, 5), (3, 4), (4, 5))
>>> graph = Graph((node_y, node_x), links=links)
>>> graph.angle_of_link * 180.0 / np.pi
array([ 0.,  0., 90., 90., 90.,  0.,  0.])
property area_of_patch

Get the area of each patch.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1, 2, 2, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> patches = ((0, 3, 5, 2), (1, 4, 6, 3))
>>> graph = Graph((node_y, node_x), links=links, patches=patches)
>>> graph.area_of_patch
array([1.,  1.])
property ds
freeze()

Freeze the graph by making arrays read-only.

classmethod from_dict(meta)
classmethod from_netcdf(fname)
property frozen

Get the length of links.

Examples

>>> import numpy as np
>>> from landlab.graph import UniformRectilinearGraph
>>> graph = UniformRectilinearGraph((2, 3), spacing=(1, 2))
>>> graph.length_of_link
array([2., 2., 1., 1., 1., 2., 2.])

Return link directions into each node.

A value of 1 indicates a link points toward a given node, while a value of -1 indicates a link points away from a node.

Returns:

Link directions relative to the nodes of a grid. The shape of the matrix will be number of nodes by the maximum number of links per node. A zero indicates no link at this position.

Return type:

(n_nodes, max_links_per_node) ndarray of int

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1, 2, 2, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> graph = Graph((node_y, node_x), links=links)
>>> graph.link_dirs_at_node
array([[-1, -1,  0,  0], [-1, -1,  1,  0], [-1,  1,  0,  0],
       [-1, -1,  1,  0], [-1, -1,  1,  1], [-1,  1,  1,  0],
       [-1,  1,  0,  0], [-1,  1,  1,  0], [ 1,  1,  0,  0]],
      dtype=int8)

Get links touching a node.

Examples

>>> from landlab.graph import Graph
>>> node_x = [0, 1, 2, 0, 1, 2, 0, 1, 2]
>>> node_y = [0, 0, 0, 1, 1, 1, 2, 2, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> graph = Graph((node_y, node_x), links=links)
>>> graph.links_at_node
array([[ 0,  2, -1, -1], [ 1,  3,  0, -1], [ 4,  1, -1, -1],
       [ 5,  7,  2, -1], [ 6,  8,  5,  3], [ 9,  6,  4, -1],
       [10,  7, -1, -1], [11, 10,  8, -1], [11,  9, -1, -1]])

Get the links that define a patch.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1, 2, 2, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> patches = ((0, 3, 5, 2), (1, 4, 6, 3))
>>> graph = Graph((node_y, node_x), links=links, patches=patches, sort=True)
>>> graph.links_at_patch
array([[3, 5, 2, 0],
       [4, 6, 3, 1]])
classmethod load(source)
merge(dual, node_at_cell=None, nodes_at_face=None)

Get the middle of links.

Examples

>>> import numpy as np
>>> from landlab.graph import UniformRectilinearGraph
>>> graph = UniformRectilinearGraph((2, 3), spacing=(1, 2))
>>> graph.midpoint_of_link
array([[1. , 0. ], [3. , 0. ],
       [0. , 0.5], [2. , 0.5], [4. , 0.5],
       [1. , 1. ], [3. , 1. ]])
property ndim

Get nodes at link head.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1, 2, 2, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> graph = Graph((node_y, node_x), links=links)
>>> graph.node_at_link_head
array([1, 2, 3, 4, 5, 4, 5, 6, 7, 8, 7, 8])

Get nodes at link tail.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1, 2, 2, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> graph = Graph((node_y, node_x), links=links)
>>> graph.node_at_link_tail
array([0, 1, 0, 1, 2, 3, 4, 3, 4, 5, 6, 7])
property node_x
property node_y
property nodes

Get identifier for each node.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1]
>>> graph = Graph((node_y, node_x))
>>> graph.nodes
array([0, 1, 2, 3, 4, 5])

Get nodes at either end of links.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1, 2, 2, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> graph = Graph((node_y, node_x), links=links)
>>> graph.nodes_at_link
array([[0, 1], [1, 2],
       [0, 3], [1, 4], [2, 5],
       [3, 4], [4, 5],
       [3, 6], [4, 7], [5, 8],
       [6, 7], [7, 8]])
property nodes_at_patch

Get the nodes that define a patch.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = ([0, 1, 2, 0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1, 2, 2, 2])
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> patches = ((0, 3, 5, 2), (1, 4, 6, 3))
>>> graph = Graph((node_y, node_x), links=links, patches=patches, sort=True)
>>> graph.nodes_at_patch
array([[4, 3, 0, 1],
       [5, 4, 1, 2]])

Get nodes at link head.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1, 2, 2, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> graph = Graph((node_y, node_x), links=links)
>>> graph.number_of_links == 12
True
property number_of_nodes

Get total number of nodes.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1]
>>> graph = Graph((node_y, node_x))
>>> graph.number_of_nodes == 6
True
property number_of_patches

Get the number of patches.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1, 2, 2, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> patches = ((0, 3, 5, 2), (1, 4, 6, 3))
>>> graph = Graph((node_y, node_x), links=links, patches=patches)
>>> graph.number_of_patches == 2
True

Get the patches on either side of each link.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = ([0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1])
>>> links = ((0, 1), (1, 2), (0, 3), (1, 4), (2, 5), (3, 4), (4, 5))
>>> patches = ((0, 3, 5, 2), (1, 4, 6, 3))
>>> graph = Graph((node_y, node_x), links=links, patches=patches)
>>> graph.patches_at_link
array([[ 0, -1], [ 1, -1],
       [ 0, -1], [ 0,  1], [ 1, -1],
       [ 0, -1], [ 1, -1]])
property patches_at_node

Get the patches that touch each node.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = ([0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1])
>>> links = ((0, 1), (1, 2), (0, 3), (1, 4), (2, 5), (3, 4), (4, 5))
>>> patches = ((0, 3, 5, 2), (1, 4, 6, 3))
>>> graph = Graph((node_y, node_x), links=links, patches=patches, sort=True)
>>> graph.patches_at_node
array([[ 0, -1], [ 1,  0], [ 1, -1],
       [ 0, -1], [ 0,  1], [ 1, -1]])
property perimeter_nodes

Get nodes on the convex hull of a Graph.

Examples

>>> import numpy as np
>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1]
>>> graph = Graph((node_y, node_x))
>>> np.sort(graph.perimeter_nodes)
array([0, 2, 3, 5])
sort()

Sort graph elements.

thaw()

Thaw the graph by making arrays writable.

thawed()
to_dict()
to_json()
to_netcdf(*args, **kwds)

Write graph contents to a netCDF file.

See xarray.Dataset.to_netcdf for a complete list of parameters. Below are only the most common.

Parameters:
  • path (str, optional) – Path to which to save this graph.

  • mode ({'w', 'a'}, optional) – Write (‘w’) or append (‘a’) mode. If mode=’w’, any existing file at this location will be overwritten.

  • format ({'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_64BIT', 'NETCDF3_CLASSIC'}, optional) –

    File format for the resulting netCDF file:

    • NETCDF4: Data is stored in an HDF5 file, using netCDF4 API features.

    • NETCDF4_CLASSIC: Data is stored in an HDF5 file, using only netCDF 3 compatible API features.

    • NETCDF3_64BIT: 64-bit offset version of the netCDF 3 file format, which fully supports 2+ GB files, but is only compatible with clients linked against netCDF version 3.6.0 or later.

    • NETCDF3_CLASSIC: The classic netCDF 3 file format. It does not handle 2+ GB files very well.

    All formats are supported by the netCDF4-python library. scipy.io.netcdf only supports the last two formats.

    The default format is NETCDF4 if you are saving a file to disk and have the netCDF4-python library available. Otherwise, xarray falls back to using scipy to write netCDF files and defaults to the NETCDF3_64BIT format (scipy does not support netCDF4).

Make arrays to store the unit vectors associated with each link.

For each link, the x and y components of the link’s unit vector (that is, the link’s x and y dimensions if it were shrunk to unit length but retained its orientation).

Examples

The example below is a seven-node hexagonal grid, with six nodes around the perimeter and one node (#3) in the interior. There are four horizontal links with unit vector (1,0), and 8 diagonal links with unit vector (+/-0.5, +/-sqrt(3)/2) (note: sqrt(3)/2 ~ 0.866).

>>> from landlab.graph import TriGraph
>>> graph = TriGraph((3, 2), spacing=2.0, node_layout="hex", sort=True)
>>> np.round(graph.unit_vector_at_link[:, 0], decimals=5)
array([ 1. , -0.5,  0.5, -0.5,  0.5,  1. ,  1. ,  0.5, -0.5,  0.5, -0.5,
        1. ])
>>> np.round(graph.unit_vector_at_link[:, 1], decimals=5)
array([0.     , 0.86603, 0.86603, 0.86603, 0.86603, 0.     ,
       0.     , 0.86603, 0.86603, 0.86603, 0.86603, 0.     ])
property unit_vector_at_node

Get a unit vector for each node.

Examples

>>> from landlab.graph import UniformRectilinearGraph
>>> graph = UniformRectilinearGraph((3, 3))
>>> graph.unit_vector_at_node
array([[1., 1.],
       [2., 1.],
       [1., 1.],
       [1., 2.],
       [2., 2.],
       [1., 2.],
       [1., 1.],
       [2., 1.],
       [1., 1.]])
>>> from landlab.graph import TriGraph
>>> graph = TriGraph((3, 2), spacing=2.0, node_layout="hex", sort=True)
>>> unit_vector_at_node = np.round(graph.unit_vector_at_node, decimals=5)
>>> unit_vector_at_node[:, 0]
array([2., 2., 2., 4., 2., 2., 2.])
>>> unit_vector_at_node[:, 1]
array([1.73205, 1.73205, 1.73205, 3.4641 , 1.73205, 1.73205, 1.73205])
property x_of_node

Get x-coordinate of node.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1]
>>> graph = Graph((node_y, node_x))
>>> graph.x_of_node
array([0., 1., 2., 0., 1., 2.])
property xy_of_node

Get x and y-coordinates of node.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1]
>>> graph = Graph((node_y, node_x))
>>> graph.xy_of_node[:, 0]
array([0., 1., 2., 0., 1., 2.])
>>> graph.xy_of_node[:, 1]
array([0., 0., 0., 1., 1., 1.])
property xy_of_patch

Get the centroid of each patch.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1, 2, 2, 2]
>>> links = (
...     (0, 1),
...     (1, 2),
...     (0, 3),
...     (1, 4),
...     (2, 5),
...     (3, 4),
...     (4, 5),
...     (3, 6),
...     (4, 7),
...     (5, 8),
...     (6, 7),
...     (7, 8),
... )
>>> patches = ((0, 3, 5, 2), (1, 4, 6, 3))
>>> graph = Graph((node_y, node_x), links=links, patches=patches)
>>> graph.xy_of_patch
array([[0.5, 0.5],
       [1.5, 0.5]])
property y_of_node

Get y-coordinate of node.

Examples

>>> from landlab.graph import Graph
>>> node_x, node_y = [0, 1, 2, 0, 1, 2], [0, 0, 0, 1, 1, 1]
>>> graph = Graph((node_y, node_x))
>>> graph.y_of_node
array([0., 0., 0., 1., 1., 1.])