landlab.graph.hex.dual_hex

class DualHexGraph[source]

Bases: DualGraph, TriGraph

Graph of a structured grid of triangles.

Examples

>>> import numpy as np
>>> from landlab.graph import DualHexGraph

>>> graph = DualHexGraph((3, 2), node_layout="hex")
>>> graph.number_of_nodes
7
>>> graph.number_of_corners
6

>>> np.round(graph.y_of_node * 2.0 / np.sqrt(3))
array([0., 0., 1., 1., 1., 2., 2.])
>>> graph.x_of_node
array([0.5, 1.5, 0. , 1. , 2. , 0.5, 1.5])

Create a structured grid of triangles.

Parameters:

  • shape (tuple of int) – Number of rows and columns of the hex grid. The first value is the number of nodes in the first column and the second the number of nodes in the first column.

  • spacing (float, optional) – Length of links.

  • xy_of_lower_left (tuple of float, optional) – Coordinates of lower-left corner of the grid.

  • orientation ({'horizontal', 'vertical'}) – Specify if triangles should be laid out in rows or columns.

  • node_layout ({'rect', 'hex'}) – Specify the overall layout of the nodes. Use rect for the layout to approximate a rectangle and hex for a hexagon.

__init__(shape, spacing=1.0, xy_of_lower_left=(0.0, 0.0), orientation='horizontal', node_layout='rect', sort=False)[source]

Create a structured grid of triangles.

Parameters:

  • shape (tuple of int) – Number of rows and columns of the hex grid. The first value is the number of nodes in the first column and the second the number of nodes in the first column.

  • spacing (float, optional) – Length of links.

  • xy_of_lower_left (tuple of float, optional) – Coordinates of lower-left corner of the grid.

  • orientation ({'horizontal', 'vertical'}) – Specify if triangles should be laid out in rows or columns.

  • node_layout ({'rect', 'hex'}) – Specify the overall layout of the nodes. Use rect for the layout to approximate a rectangle and hex for a hexagon.

__new__(**kwargs)
property adjacent_corners_at_corner

Get adjacent corners.

See also

adjacent_nodes_at_node

property adjacent_faces_at_face
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]])
property angle_of_face

Get the angle of each face.

See also

angle_of_link

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_cell

Get the area of each cell.

See also

area_of_patch

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 cell_at_node
property cells_at_corner

Get the cells that touch each corner.

See also

patches_at_node

property cells_at_face

Get the cells on either side of each face.

See also

patches_at_link

property corner_at_face_head

Get corners at face head.

See also

node_at_link_head

property corner_at_face_tail

Get corners at face tail.

See also

node_at_link_tail

property corner_at_patch
property corner_layout
property corner_x
property corner_y
property corners

Get identifier for each corner.

See also

nodes

property corners_at_bottom_edge

Get corners along the bottom edge.

See also

nodes_at_bottom_edge

property corners_at_cell

Get the corners that define a cell.

See also

nodes_at_patch

property corners_at_face

Get corners at either end of faces.

See also

nodes_at_link

property corners_at_left_edge

Get corners along the left edge.

See also

nodes_at_left_edge

property corners_at_right_edge

Get corners along the right edge.

See also

nodes_at_right_edge

property corners_at_top_edge

Get corners along the top edge.

See also

nodes_at_top_edge

property ds
property dual
property face_dirs_at_corner

Return face directions into each corner.

See also

link_dirs_at_node

property faces_at_cell

Get the faces that define a cell.

See also

links_at_patch

property faces_at_corner

Get faces touching a corner.

See also

links_at_node

freeze()

Freeze the graph by making arrays read-only.

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

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)
property midpoint_of_face

Get the middle of faces.

See also

midpoint_of_link

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
property node_at_cell

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_layout
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])
property nodes_at_bottom_edge

Get nodes along the bottom edge.

Examples

>>> import numpy as np
>>> from landlab.graph import TriGraph
>>> graph = TriGraph((3, 4), node_layout="rect")
>>> graph.nodes_at_bottom_edge
array([0, 1, 2, 3])
property nodes_at_face
property nodes_at_left_edge

Get nodes along the left edge.

Examples

>>> import numpy as np
>>> from landlab.graph import TriGraph
>>> graph = TriGraph((3, 4), node_layout="rect")
>>> graph.nodes_at_left_edge
array([0, 4, 8])

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]])
property nodes_at_right_edge

Get nodes along the right edge.

Examples

>>> import numpy as np
>>> from landlab.graph import TriGraph
>>> graph = TriGraph((3, 4), node_layout="rect")
>>> graph.nodes_at_right_edge
array([ 3,  7, 11])
property nodes_at_top_edge

Get nodes along the top edge.

Examples

>>> import numpy as np
>>> from landlab.graph import TriGraph
>>> graph = TriGraph((3, 4), node_layout="rect")
>>> graph.nodes_at_top_edge
array([ 8,  9, 10, 11])
property number_of_cells

Get the number of cells.

See also

number_of_patches

property number_of_corners

Get total number of corners.

See also

number_of_nodes

property number_of_faces

Get corners at face head.

See also

number_of_links

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
property orientation
property orientation_of_face

Return array of face orientation codes (one value per face).

See also

orientation_of_link

Return array of link orientation codes (one value per link).

Orientation codes are defined by LinkOrientation; 1 = E, 2 = ENE, 4 = NNE, 8 = N, 16 = NNW, 32 = ESE (using powers of 2 allows for future applications that might want additive combinations).

Examples

>>> from landlab import HexModelGrid
>>> import numpy as np
>>> grid = HexModelGrid((3, 2))
>>> grid.orientation_of_link
array([ 1, 16,  4, 16,  4,  1,  1,  4, 16,  4, 16,  1], dtype=uint8)
>>> grid = HexModelGrid((2, 3), orientation="vertical")
>>> grid.orientation_of_link
array([32,  2,  8,  2, 32,  8,  8, 32,  2,  8,  2, 32], dtype=uint8)
property parallel_faces_at_face

Return similarly oriented faces connected to each face.

See also

parallel_links_at_link

Return similarly oriented links connected to each link.

Return IDs of links of the same orientation that are connected to each given link’s tail or head node.

The data structure is a numpy array of shape (n_links, 2) containing the IDs of the “tail-wise” (connected to tail node) and “head-wise” (connected to head node) links, or -1 if the link is inactive (e.g., on the perimeter) or it has no attached parallel neighbor in the given direction.

For instance, consider a 3x3 hex, in which link IDs are as shown:

    o---17--o---18--o
   / .     / .     / .
  11 12   13  14  15  16
 /     . /     . /     .
o---8---o---9---o---10--o
 .     / .     / .     /
  2   3   4   5   6   7
   . /     . /     . /
    o---0---o---1---o

Here’s a mapping of the tail-wise and head-wise links, where there are valid parallel links:

    o-------o-------o
   / .     / .     / .
  /   .   /   .   /   .
 /     4 3     6 5     .
o-----9-o-8--10-o-9-----o
 .    13 12   15 14    /
  .   /   .   /   .   /
   . /     . /     . /
    o-------o-------o

The corresponding data structure would be mostly filled with -1, but for the 11 active links, it would look like:

3: [[-1, 13],
4:  [-1, 12],
5:  [-1, 15],
6:  [-1, 14],
8:  [-1,  9],
9:  [ 8, 10],
10: [ 9, -1],
12: [ 4, -1],
13: [ 3, -1],
14: [ 6, -1],
15: [ 5, -1]]

Examples

>>> from landlab import HexModelGrid
>>> grid = HexModelGrid((3, 3))
>>> pll = grid.parallel_links_at_link
>>> pll[3:16]
array([[-1, 13],
       [-1, 12],
       [-1, 15],
       [-1, 14],
       [-1, -1],
       [-1,  9],
       [ 8, 10],
       [ 9, -1],
       [-1, -1],
       [ 4, -1],
       [ 3, -1],
       [ 6, -1],
       [ 5, -1]])
property patch_at_corner

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_corners
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])
property shape
sort()

Sort graph elements.

property spacing
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).

property unit_vector_at_corner

Get a unit vector for each corner.

See also

unit_vector_at_node

property unit_vector_at_face

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

See also

unit_vector_at_link

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_corner

Get x-coordinate of corner.

See also

x_of_node

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_cell

Get the centroid of each cell.

See also

xy_of_patch

property xy_of_corner

Get x and y-coordinates of corner.

See also

xy_of_node

property xy_of_face
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_corner

Get y-coordinate of corner.

See also

y_of_node

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.])