landlab.grid.structured_quad package

Submodules

landlab.grid.structured_quad.c_faces module

landlab.grid.structured_quad.cells module

class StructuredQuadCellGrid(shape)

Bases: object

node_at_cell

number_of_cell_columns

number_of_cell_rows

number_of_cells

number_of_vertices_at_cell(cell)

shape

cell_id_at_nodes(shape, bad=-1)

Cell ID at each node.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

ndarray :

ID of cell associated with each node.

Examples

>>> from landlab.grid.structured_quad.cells import cell_id_at_nodes
>>> cell_id_at_nodes((4, 5), bad=-1) 
array([[-1, -1, -1, -1, -1],
       [-1,  0,  1,  2, -1],
       [-1,  3,  4,  5, -1],
       [-1, -1, -1, -1, -1]])

cell_ids(shape)

IDs of all cells.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

ndarray :

ID of node associated with each cell.

Examples

>>> from landlab.grid.structured_quad.cells import cell_ids
>>> cell_ids((3, 4))
array([[0, 1]])

node_id_at_cells(shape)

Node ID at each cell.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

ndarray :

ID of node associated with each cell.

Examples

>>> from landlab.grid.structured_quad.cells import node_id_at_cells
>>> node_id_at_cells((3, 4))
array([[5, 6]])

number_of_cells(shape)

Number of cells is a structured quad grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

int :

Number of cells in the grid.

Examples

>>> from landlab.grid.structured_quad.cells import number_of_cells
>>> number_of_cells((3, 4))
2

shape_of_cells(shape)

Shape of cells in a structured quad grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

int :

Shape of cells in grid.

Examples

>>> from landlab.grid.structured_quad.cells import shape_of_cells
>>> shape_of_cells((3, 4))
(1, 2)

landlab.grid.structured_quad.cfuncs module

landlab.grid.structured_quad.faces module

face_at_link(shape, bad_index_value=-1)

Get face for each link of a grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Examples

>>> from landlab.grid.structured_quad.faces import face_at_link
>>> face_at_link((4, 5), bad_index_value=-1)
...     
array([-1, -1, -1, -1, -1,  0,  1,  2, -1,
        3,  4,  5,  6, -1,  7,  8,  9, -1,
       10, 11, 12, 13, -1, 14, 15, 16, -1,
       -1, -1, -1, -1])

link_at_face(shape)

Get the link at each face.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Notes

The algorithm is based on the following considerations:

1. To get the link ID associated with a face ID, we start with the face ID and add something to it.
2. Face 0 crosses the second vertical link. The first NC-1 links are horizontal, and run along the bottom of the grid. Then there’s a vertical link on the lower-left side of the grid. Thus the link that crosses face 0 will be ID number NC, where NC is the number of cols.
3. The offset between face ID and link ID increases by 1 every time we finish a row of horizontal faces (NC-2 of them) with vertical links, and again when we finish a row of vertical faces (NC-1 of them) with horizontal links. Together, a “row” of horizontal and vertical faces makes up 2NC-3 faces; this is the variable “fpr” (for “faces per row”) below.
4. The quantity 2 * (face_ids // fpr) increases by 2 for every “full” (horizontal plus vertical) row of faces.
5. The quantity ((face_ids % fpr) >= (NC-2)) increases by 1 every time we shift from a horizontal to a vertical row of faces (because each “full row” has NC-2 horizontal faces, then NC-1 vertical ones.)
6. So, to find the offset, we add the “basic” offset, NC, to the “full row” offset, 2*(face_ids//fpr), and the “mid-row” offset, ((face_ids % fpr)>=(NC-2)).

Examples

>>> from landlab.grid.structured_quad.faces import link_at_face
>>> link_at_face((3, 5)) 
array([  5,  6,  7,
         9, 10, 11, 12,
        14, 15, 16])

number_of_faces(shape)

Number of faces in a structured quad grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

int :

Number of faces in grid.

Examples

>>> from landlab.grid.structured_quad.faces import number_of_faces
>>> number_of_faces((3, 4))
7

landlab.grid.structured_quad.links module

class StructuredQuadLinkGrid(shape)

Bases: landlab.grid.unstructured.links.LinkGrid

active_link_ids(shape, node_status)

Get active links.

Parameters:

shape : tuple of int

Shape of grid of nodes.

node_status : array_link

Status of nodes in grid.

Returns:

ndarray :

Links IDs at the active links.

Examples

>>> from landlab.grid import RasterModelGrid
>>> from landlab.grid.structured_quad.links import active_link_ids

>>> rmg = RasterModelGrid((3, 4))
>>> rmg.set_closed_boundaries_at_grid_edges(True, True, True, True)

>>> status = rmg.status_at_node
>>> status 
array([4, 4, 4, 4,
       4, 0, 0, 4,
       4, 4, 4, 4], dtype=int8)

>>> active_link_ids((3, 4), status)
array([8])

bottom_edge_horizontal_ids(shape)

Link IDs of bottom edge horizontal links.

Parameters:

shape : tuple of int

Shape of grid, given as (rows, columns) of nodes.

Returns:

ndarray :

Link IDs of bottom edge horizontal links. Length is (rmg.number_of_columns-1)

Examples

The following example uses this grid:

*--27-->*--28-->*--29-->*--30-->*

*--18-->*--19-->*--20-->*--21-->*

*---9-->*--10-->*--11-->*--12-->*

*---0-->*---1-->*---2-->*---3-->*

Note

Only horizontal links are shown.

* indicates nodes

Numeric values correspond to the horizontal IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import (
...     bottom_edge_horizontal_ids)
>>> rmg = RasterModelGrid(4, 5)
>>> shape = rmg.shape
>>> bottom_edge_horizontal_ids(shape)
array([0, 1, 2, 3])

bottom_edge_vertical_ids(shape)

Link IDs of bottom edge vertical links.

Parameters:

shape : tuple of int

Shape of grid, given as (rows, columns) of nodes.

Returns:

ndarray :

Link IDs of bottom edge vertical links. Length is (rmg.number_of_columns)

Examples

The following example uses this grid:

 *       *       *       *       *
 ^       ^       ^       ^       ^
22      23      24      25      26
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
13      14      15      16      17
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
 4       5       6       7       8
 |       |       |       |       |
 *       *       *       *       *

Note

Only vertical links are shown.

* indicates nodes

Numeric values correspond to the vertical IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import bottom_edge_vertical_ids
>>> rmg = RasterModelGrid(4, 5)
>>> shape = rmg.shape
>>> bottom_edge_vertical_ids(shape)
array([4, 5, 6, 7, 8])

d4_horizontal_active_link_neighbors(shape, horizontal_ids, bad_index_value=-1)

returns IDs of all 4 horizontal link neighbors.

Parameters:

shape : tuple of int

Shape of grid of nodes.

horizontal_ids : array of int

Array of all horizontal link ids - must be of len(horizontal_links)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray

Array of 4 horizontal link neighbors for a given link ID. Returned in [E, N, W, S]. Returns array for only ACTIVE horizontal links.

Examples

Sample grid, giving neighbors for link ID 20:

*------>*------>*------>*------>*

*------>*--19-->*--20-->*------>*

*------>*--10-->*--11-->*------>*

*------>*------>*------>*------>*

Note

Only horizontal links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the horizontal ACTIVE_LINK IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid((4, 5))
>>> rmg.set_closed_boundaries_at_grid_edges(True, True, True, True)
>>> active_ids = active_link_ids(rmg.shape, rmg.status_at_node)
>>> horizontal_ids = horizontal_active_link_ids(
...     rmg.shape, active_ids)
>>> d4_horizontal_active_link_neighbors(rmg.shape, horizontal_ids)
array([[11, 19, -1, -1],
       [-1, 20, 10, -1],
       [20, -1, -1, 10],
       [-1, -1, 19, 11]])

d4_horizontal_link_neighbors(shape, horizontal_ids, bad_index_value=-1)

IDs of all 4 horizontal link neighbors.

Parameters:

shape : tuple of int

Shape of grid of nodes.

horizontal_ids : array of int

Array of all horizontal link ids - must be of len(horizontal_links)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Array of 4 horizontal link neighbors for a given link ID. Returned in [E, N, W, S].

Examples

Sample grid, giving neighbors for link ID 10:

*------>*------>*------>*------>*

*------>*--19-->*------>*------>*

*---9-->*--10-->*--11-->*------>*

*------>*---1-->*------>*------>*

Note

Only horizontal links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the horizontal IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid(4, 5)
>>> horizontal_links = horizontal_link_ids(rmg.shape).flatten()
>>> d4_horizontal_link_neighbors(rmg.shape, horizontal_links)
array([[ 1,  9, -1, -1],
       [ 2, 10,  0, -1],
       [ 3, 11,  1, -1],
       [-1, 12,  2, -1],
       [10, 18, -1,  0],
       [11, 19,  9,  1],
       [12, 20, 10,  2],
       [-1, 21, 11,  3],
       [19, 27, -1,  9],
       [20, 28, 18, 10],
       [21, 29, 19, 11],
       [-1, 30, 20, 12],
       [28, -1, -1, 18],
       [29, -1, 27, 19],
       [30, -1, 28, 20],
       [-1, -1, 29, 21]])

d4_vertical_active_link_neighbors(shape, vertical_ids, bad_index_value=-1)

IDs of all 4 vertical link neighbors.

Parameters:

shape : tuple of int

Shape of grid of nodes.

vertical_active_ids : array of int

Array of all vertical link ids - must be of len(vertical_links)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Array of 4 vertical link neighbors for a given ACTIVE link ID. Returned in [E, N, W, S].

Examples

The following example uses this grid:

 *       *       *       *       *
 ^       ^       ^       ^       ^
22      23      24      25      26
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
13      14      15      16      17
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
 4       5       6       7       8
 |       |       |       |       |
 *       *       *       *       *

Note

Only vertical links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the vertical IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import (active_link_ids,
...     vertical_active_link_ids, d4_vertical_active_link_neighbors)
>>> rmg = RasterModelGrid(4, 5)
>>> active_link_ids = active_link_ids(rmg.shape, rmg.status_at_node)
>>> vertical_active_ids = vertical_active_link_ids(
...     rmg.shape, active_link_ids)
>>> d4_vertical_active_link_neighbors(rmg.shape, vertical_active_ids)
array([[ 6, 14, -1, -1],
       [ 7, 15,  5, -1],
       [-1, 16,  6, -1],
       [15, 23, -1,  5],
       [16, 24, 14,  6],
       [-1, 25, 15,  7],
       [24, -1, -1, 14],
       [25, -1, 23, 15],
       [-1, -1, 24, 16]])

d4_vertical_link_neighbors(shape, vertical_ids, bad_index_value=-1)

IDs of all 4 vertical link neighbors.

Parameters:

shape : tuple of int

Shape of grid of nodes.

vertical_ids : array of int

Array of all vertical link ids - MUST BE ARRAY OF LEN(VERTICAL_LINKS)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Array of 4 vertical link neighbors for a given link ID. Returned in [E, N, W, S].

Examples

The following example uses this grid:

 *       *       *       *       *
 ^       ^       ^       ^       ^
22      23      24      25      26
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
13      14      15      16      17
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
 4       5       6       7       8
 |       |       |       |       |
 *       *       *       *       *

Note

Only vertical links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the vertical IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid(4, 5)
>>> vertical_ids = vertical_link_ids(rmg.shape)
>>> d4_vertical_link_neighbors(rmg.shape, vertical_ids)
array([[ 5, 13, -1, -1],
       [ 6, 14,  4, -1],
       [ 7, 15,  5, -1],
       [ 8, 16,  6, -1],
       [-1, 17,  7, -1],
       [14, 22, -1,  4],
       [15, 23, 13,  5],
       [16, 24, 14,  6],
       [17, 25, 15,  7],
       [-1, 26, 16,  8],
       [23, -1, -1, 13],
       [24, -1, 22, 14],
       [25, -1, 23, 15],
       [26, -1, 24, 16],
       [-1, -1, 25, 17]])

fixed_link_ids(shape, node_status)

ID of fixed links.

Parameters:

shape : tuple of int

Shape of grid of nodes.

node_status : array_link

Status of nodes in grid.

Returns:

ndarray :

Links IDs at the active links.

Examples

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import fixed_link_ids
>>> import numpy as np
>>> rmg = RasterModelGrid(4, 5)
>>> z = np.arange(0, rmg.number_of_nodes)
>>> s = np.arange(0, rmg.number_of_links)
>>> rmg.at_node['topographic__elevation'] = z
>>> rmg.at_link['topographic__slope'] = s
>>> rmg.set_fixed_link_boundaries_at_grid_edges(True, True, True, True)
>>> rmg.status_at_node 
array([2, 2, 2, 2, 2,
       2, 0, 0, 0, 2,
       2, 0, 0, 0, 2,
       2, 2, 2, 2, 2], dtype=int8)
>>> fixed_link_ids(rmg.shape, rmg.status_at_node)
array([ 5,  6,  7,  9, 12, 18, 21, 23, 24, 25])

horizontal_active_link_ids(shape, active_ids, bad_index_value=-1)

ID of horizontal active links.

Parameters:

shape : tuple of int

Shape of grid of nodes.

active_ids : array of int

Array of all active link ids

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs at the HORIZONTAL active links. Length of number_of_horizontal_links.

Examples

The following example uses this grid:

*---I-->*---I-->*---I-->*---I-->*
^       ^       ^       ^       ^
I       I       I       I       I
|       |       |       |       |
*---I-->o--24-->o--25-->o---I-->*
^       ^       ^       ^       ^
I       V       V       V       I
|       |       |       |       |
*---I-->o--20-->o--21-->o---I-->*
^       ^       ^       ^       ^
I       I       I       I       I
|       |       |       |       |
*---I-->*---I-->*---I-->*---I-->*

Note

* indicates the nodes that are set to CLOSED_BOUNDARY

o indicates the nodes that are set to CORE_NODE

I indicates the links that are set to INACTIVE_LINK

V indicates vertical active ids, which are ignored by this function.

Numeric values correspond to the horizontal ACTIVE_LINK ID.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import (active_link_ids,
...     horizontal_active_link_ids)

>>> rmg = RasterModelGrid(4, 5)
>>> rmg.set_closed_boundaries_at_grid_edges(True, True, True, True)

>>> status = rmg.status_at_node
>>> status 
array([4, 4, 4, 4, 4,
       4, 0, 0, 0, 4,
       4, 0, 0, 0, 4,
       4, 4, 4, 4, 4], dtype=int8)
>>> active_ids = active_link_ids((4,5), status)

>>> horizontal_active_link_ids((4,5), active_ids)
...     
array([-1, -1, -1, -1,
       -1, 10, 11, -1,
       -1, 19, 20, -1,
       -1, -1, -1, -1])

horizontal_east_link_neighbor(shape, horizontal_ids, bad_index_value=-1)

IDs of east, horizontal link neighbor.

Parameters:

shape : tuple of int

Shape of grid of nodes.

horizontal_ids : array of int

Array of all horizontal link ids - must be of len(horizontal_links)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs of east horizontal neighbor links. Length of number_of_horizontal_links.

Examples

The following example uses this grid:

*--27-->*--28-->*--29-->*--30-->*

*--18-->*--19-->*--20-->*--21-->*

*---9-->*--10-->*--11-->*--12-->*

*---0-->*---1-->*---2-->*---3-->*

Note

Only horizontal links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the horizontal ACTIVE_LINK IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid(4, 5)
>>> horizontal_links = horizontal_link_ids(rmg.shape).flatten()
>>> horizontal_east_link_neighbor(rmg.shape, horizontal_links)
array([ 1,  2,  3, -1, 10, 11, 12, -1, 19, 20, 21, -1, 28, 29, 30, -1])

horizontal_fixed_link_ids(shape, fixed_ids, bad_index_value=-1)

ID of horizontal fixed links.

Parameters:

shape : tuple of int

Shape of grid of nodes.

fixed_ids : array of int

Array of all fixed link ids

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs at the HORIZONTAL fixed links. Length of number_of_horizontal_links.

Examples

The following example uses this grid:

*---I-->*---I-->*---I-->*---I-->*
^       ^       ^       ^       ^
I       V       V       V       I
|       |       |       |       |
*--18-->o------>o------>o--21-->*
^       ^       ^       ^       ^
I       V       V       V       I
|       |       |       |       |
*---9-->o------>o------>o--12-->*
^       ^       ^       ^       ^
I       V       V       V       I
|       |       |       |       |
*---I-->*---I-->*---I-->*---I-->*

Note

* indicates the nodes that are set to FIXED_VALUE_BOUNDARY

o indicates the nodes that are set to CORE_NODE

I indicates the links that are set to INACTIVE_LINK

V indicates vertical ids, which are ignored by this function

H indicates horizontal ACTIVE_LINK ids, which are ignored by this function

Numeric values correspond to the horizontal FIXED_LINK ID.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import (fixed_link_ids,
...     horizontal_fixed_link_ids)
>>> import numpy

>>> rmg = RasterModelGrid(4, 5)
>>> rmg.at_node['topographic__elevation'] = numpy.arange(
...     0, rmg.number_of_nodes)
>>> rmg.at_link['topographic__slope'] = numpy.arange(
...     0, rmg.number_of_links)

>>> rmg.set_fixed_link_boundaries_at_grid_edges(True, True, True, True)
>>> status = rmg.status_at_node
>>> status 
array([2, 2, 2, 2, 2,
       2, 0, 0, 0, 2,
       2, 0, 0, 0, 2,
       2, 2, 2, 2, 2], dtype=int8)

>>> fixed_ids = fixed_link_ids((4, 5), status)
>>> horizontal_fixed_link_ids((4, 5), fixed_ids)
...     
array([-1, -1, -1, -1,
        9, -1, -1, 12,
       18, -1, -1, 21,
       -1, -1, -1, -1])

horizontal_link_ids(shape)

Horizontal links in a structured quad grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

(M, N) ndarray :

Array of link IDs.

Examples

>>> from landlab.grid.structured_quad.links import horizontal_link_ids
>>> horizontal_link_ids((3, 4))
array([[ 0,  1,  2],
       [ 7,  8,  9],
       [14, 15, 16]])

horizontal_north_link_neighbor(shape, horizontal_ids, bad_index_value=-1)

ID of north, horizontal link neighbor.

Parameters:

shape : tuple of int

Shape of grid of nodes.

horizontal_ids : array of int

Array of all horizontal link ids - must be of len(horizontal_links)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs of north horizontal neighbor links. Length of number_of_horizontal_links.

Examples

The following example uses this grid:

*--27-->*--28-->*--29-->*--30-->*

*--18-->*--19-->*--20-->*--21-->*

*---9-->*--10-->*--11-->*--12-->*

*---0-->*---1-->*---2-->*---3-->*

Note

Only horizontal links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the horizontal ACTIVE_LINK IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid(4, 5)
>>> horizontal_links = horizontal_link_ids(rmg.shape).flatten()
>>> horizontal_north_link_neighbor(rmg.shape, horizontal_links)
array([ 9, 10, 11, 12, 18, 19, 20, 21, 27, 28, 29, 30, -1, -1, -1, -1])

horizontal_south_link_neighbor(shape, horizontal_ids, bad_index_value=-1)

ID of south horizontal link neighbor.

Parameters:

shape : tuple of int

Shape of grid of nodes.

horizontal_ids : array of int

Array of all horizontal link ids must be of len(horizontal_links).

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs of south horizontal neighbor links. Length of number_of_horizontal_links.

Examples

The following example uses this grid:

*--27-->*--28-->*--29-->*--30-->*

*--18-->*--19-->*--20-->*--21-->*

*---9-->*--10-->*--11-->*--12-->*

*---0-->*---1-->*---2-->*---3-->*

Note

Only horizontal links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the horizontal IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid(4, 5)
>>> horizontal_links = horizontal_link_ids(rmg.shape).flatten()
>>> horizontal_south_link_neighbor(rmg.shape, horizontal_links)
array([-1, -1, -1, -1,  0,  1,  2,  3,  9, 10, 11, 12, 18, 19, 20, 21])

horizontal_west_link_neighbor(shape, horizontal_ids, bad_index_value=-1)

ID of west, horizontal link neighbor.

Parameters:

shape : tuple of int

Shape of grid of nodes.

horizontal_ids : array of int

Array of all horizontal link ids - must be of len(horizontal_links)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs of west horizontal neighbor links. Length of number_of_horizontal_links.

Examples

The following example uses this grid:

*--27-->*--28-->*--29-->*--30-->*

*--18-->*--19-->*--20-->*--21-->*

*---9-->*--10-->*--11-->*--12-->*

*---0-->*---1-->*---2-->*---3-->*

Note

Only horizontal links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the horizontal IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid(4, 5)
>>> horizontal_links = horizontal_link_ids(rmg.shape).flatten()
>>> horizontal_west_link_neighbor(rmg.shape, horizontal_links)
array([-1,  0,  1,  2, -1,  9, 10, 11, -1, 18, 19, 20, -1, 27, 28, 29])

is_active_link(shape, node_status)

Link IDs of active links.

Parameters:

shape : tuple of int

Shape of grid of nodes.

node_status : array_link

Status of nodes in grid.

Returns:

ndarray :

Links IDs at the active links.

Examples

>>> from landlab.grid.structured_quad.nodes import (
...     status_with_perimeter_as_boundary)
>>> from landlab.grid.structured_quad.links import is_active_link
>>> status = status_with_perimeter_as_boundary((3, 4))
>>> status 
array([[4, 4, 4, 4],
       [4, 0, 0, 4],
       [4, 4, 4, 4]])
>>> is_active_link((3, 4), status) 
array([False, False, False,
       False, False, False, False,
       False, True, False,
       False, False, False, False,
       False, False, False], dtype=bool)

is_diagonal_link(shape, links)

Test if a link is diagonal.

Parameters:

shape : tuple of int

Shape of grid of nodes.

links : array of int

Array of link ids to test.

Returns:

ndarray of bool

True for links that are diagonal.

Examples

>>> from landlab.grid.structured_quad.links import (is_diagonal_link,
...     number_of_links)
>>> import numpy as np
>>> shape = (3, 4)
>>> links = np.array([0, 3, 16, 17])
>>> is_diagonal_link(shape, links) 
array([False, False, False,  True], dtype=bool)

is_fixed_link(shape, node_status)

ID of active links.

Parameters:

shape : tuple of int

Shape of grid of nodes.

node_status : array_link

Status of nodes in grid.

Returns:

ndarray :

Links IDs at the active links.

Examples

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import is_fixed_link
>>> import numpy as np

>>> rmg = RasterModelGrid((4, 5))
>>> z = np.arange(0, rmg.number_of_nodes)
>>> s = np.arange(0, rmg.number_of_links)
>>> rmg.at_node['topographic__elevation'] = z
>>> rmg.at_link['topographic__slope'] = s

>>> rmg.set_fixed_link_boundaries_at_grid_edges(True, True, True, True)
>>> rmg.status_at_node 
array([2, 2, 2, 2, 2,
       2, 0, 0, 0, 2,
       2, 0, 0, 0, 2,
       2, 2, 2, 2, 2], dtype=int8)

>>> is_fixed_link(rmg.shape, rmg.status_at_node)
array([False, False, False, False, False,  True,  True,  True, False,
        True, False, False,  True, False, False, False, False, False,
        True, False, False,  True, False,  True,  True,  True, False,
       False, False, False, False], dtype=bool)

is_horizontal_link(shape, links)

Test if a link is horizontal.

Parameters:

shape : tuple of int

Shape of grid of nodes.

links : array of int

Array of link ids to test.

Returns:

ndarray of bool

True for links that are horizontal.

Examples

>>> from landlab.grid.structured_quad.links import (is_horizontal_link,
...     number_of_links)
>>> import numpy as np
>>> shape = (3, 4)
>>> links = np.arange(number_of_links(shape))
>>> is_horizontal_link(shape, links) 
array([ True,  True,  True, False, False, False, False,
        True,  True,  True, False, False, False, False,
        True,  True,  True], dtype=bool)

is_vertical_link(shape, links)

Test if links are vertical.

Parameters:

shape : tuple of int

Shape of grid of nodes.

links : array of int

Array of link ids to test.

Returns:

ndarray of bool

True for links that are vertical.

Examples

>>> from landlab.grid.structured_quad.links import (is_vertical_link,
...     number_of_links)
>>> import numpy as np
>>> shape = (3, 4)
>>> links = np.arange(number_of_links(shape))
>>> is_vertical_link(shape, links) 
array([False, False, False,  True,  True,  True,  True,
       False, False, False,  True,  True,  True,  True,
       False, False, False], dtype=bool)

left_edge_horizontal_ids(shape)

Link IDs of left edge horizontal links.

Parameters:

shape : tuple of int

Shape of grid, given as (rows, columns) of nodes.

Returns:

ndarray :

Link IDs of left edge horizontal links. Length is (rmg.number_of_rows)

Examples

The following example uses this grid:

*--27-->*--28-->*--29-->*--30-->*

*--18-->*--19-->*--20-->*--21-->*

*---9-->*--10-->*--11-->*--12-->*

*---0-->*---1-->*---2-->*---3-->*

Note

Only horizontal links are shown.

* indicates nodes

Numeric values correspond to the horizontal IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import left_edge_horizontal_ids
>>> rmg = RasterModelGrid(4, 5)
>>> shape = rmg.shape
>>> left_edge_horizontal_ids(shape)
array([ 0,  9, 18, 27])

left_edge_vertical_ids(shape)

Link IDs of left edge vertical links.

Parameters:

shape : tuple of int

Shape of grid, given as (rows, columns) of nodes.

Returns:

ndarray :

Link IDs of left edge vertical links. Length is (rmg.number_of_rows - 1)

Examples

The following example uses this grid:

 *       *       *       *       *
 ^       ^       ^       ^       ^
22      23      24      25      26
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
13      14      15      16      17
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
 4       5       6       7       8
 |       |       |       |       |
 *       *       *       *       *

Note

Only vertical links are shown.

* indicates nodes

Numeric values correspond to the vertical IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import left_edge_vertical_ids
>>> rmg = RasterModelGrid(4, 5)
>>> shape = rmg.shape
>>> left_edge_vertical_ids(shape)
array([ 4, 13, 22])

link_dirs_at_node(shape)

Construct a matrix of link directions at each node.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

(N, 4) ndarray of int

Array of link directions.

Examples

>>> from landlab.grid.structured_quad.links import link_dirs_at_node
>>> link_dirs_at_node((4, 3)) 
array([[-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]])

links_at_node(shape)

Get link ids for each node.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

(N, 4) ndarray of int

Array of link ids.

Examples

>>> from landlab.grid.structured_quad.links import links_at_node
>>> links_at_node((4, 3)) 
array([[ 0,  2, -1, -1], [ 1,  3,  0, -1], [-1,  4,  1, -1],
       [ 5,  7, -1,  2], [ 6,  8,  5,  3], [-1,  9,  6,  4],
       [10, 12, -1,  7], [11, 13, 10,  8], [-1, 14, 11,  9],
       [15, -1, -1, 12], [16, -1, 15, 13], [-1, -1, 16, 14]])

neighbors_at_link(shape, links)

Get neighbor links.

Examples

>>> import numpy as np
>>> from landlab.grid.structured_quad.links import neighbors_at_link

>>> neighbors_at_link((3, 2), np.arange(7)) 
array([[-1,  3, -1, -1],
       [ 2,  4, -1, -1], [-1,  5,  1, -1],
       [-1,  6, -1,  0],
       [ 5,  7, -1,  1], [-1, -1,  4,  2],
       [-1, -1, -1,  3]])

node_id_at_link_end(shape)

Node ID at end of links.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

ndarray :

Node IDs at end of links.

Examples

>>> from landlab.grid.structured_quad.links import node_id_at_link_end
>>> node_id_at_link_end((3, 4)) 
array([ 1, 2, 3,
        4, 5, 6, 7,
        5, 6, 7,
        8, 9, 10, 11,
        9, 10, 11])

node_id_at_link_start(shape)

Node ID at start of links.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

ndarray :

Node IDs at start of links.

Examples

>>> from landlab.grid.structured_quad.links import node_id_at_link_start
>>> node_id_at_link_start((3, 4)) 
array([ 0, 1, 2,
        0, 1, 2, 3,
        4, 5, 6,
        4, 5, 6, 7,
        8, 9, 10])

node_in_link_ids(shape)

Links entering each node.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

tuple :

Tuple of array of link IDs as (vertical_links, horizontal_links).

Examples

>>> from landlab.grid.structured_quad.links import node_in_link_ids
>>> (links, offset) = node_in_link_ids((3, 4))
>>> links
array([ 0,  1,  2,  3,  4,  7,  5,  8,  6,  9, 10, 11, 14, 12, 15, 13, 16])
>>> offset
array([ 0,  0,  1,  2,  3,  4,  6,  8, 10, 11, 13, 15, 17])

The links entering the 1st, 5th, and last node. The first node does not have any links entering it.

>>> offset[0] == offset[1]
True
>>> for link in [4, 11]: links[offset[link]:offset[link + 1]]
array([3])
array([13, 16])

node_link_ids(shape)

Link IDs for links entering and leaving each node.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

tuple :

Tuple of array of link IDs and offsets into link array.

Examples

>>> from landlab.grid.structured_quad.links import node_link_ids
>>> (links, offset) = node_link_ids((3, 4))
>>> links
array([ 0,  3,  1,  4,  0,  2,  5,  1,  6,  2,
        7, 10,  3,  8, 11,  7,  4,  9, 12,  8,  5, 13,  9,  6,
       14, 10, 15, 14, 11, 16, 15, 12, 16, 13])
>>> offset
array([ 0,  2,  5,  8, 10, 13, 17, 21, 24, 26, 29, 32, 34])

The links attached to node 0

>>> links[offset[0]:offset[1]]
array([0, 3])

The links attached to node 5

>>> links[offset[5]:offset[6]]
array([ 8, 11,  7,  4])

node_out_link_ids(shape)

Links leaving each node.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

tuple :

Tuple of array of link IDs as (vertical_links, horizontal_links).

Examples

>>> from landlab.grid.structured_quad.links import node_out_link_ids
>>> (links, offset) = node_out_link_ids((3, 4))
>>> links
array([ 3,  0,  4,  1,  5,  2,  6, 10,  7, 11,  8, 12,  9, 13, 14, 15, 16])
>>> offset
array([ 0,  2,  4,  6,  7,  9, 11, 13, 14, 15, 16, 17, 17])

The links leaving the 1st, 8th, and last node. The last node does not have any links leaving it.

>>> offset[11] == offset[12]
True
>>> for link in [0, 7]: links[offset[link]:offset[link + 1]]
array([3, 0])
array([13])

nth_horizontal_link(shape, links)

Convert link ID to horizontal link ID.

Parameters:

shape : tuple of int

Shape of grid of nodes.

links : array of int

Array of link ids to test.

Returns:

ndarray of int

The link ID as the nth horizontal links.

Examples

>>> from landlab.grid.structured_quad.links import nth_horizontal_link
>>> shape = (3, 4)
>>> nth_horizontal_link(shape, 16)
8
>>> nth_horizontal_link(shape, (1, 7, 8))
array([1, 3, 4])

nth_vertical_link(shape, links)

Convert link ID to vertical link ID.

Parameters:

shape : tuple of int

Shape of grid of nodes.

links : array of int

Array of link ids to test.

Returns:

ndarray of int

The link ID as the nth vertical links.

Examples

>>> from landlab.grid.structured_quad.links import nth_vertical_link
>>> shape = (3, 4)
>>> nth_vertical_link(shape, 4)
1
>>> nth_vertical_link(shape, (3, 4, 11))
array([0, 1, 5])

number_of_horizontal_links(shape)

Number of horizontal links in a structured quad grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

int :

Number of horizontal links in grid.

Examples

>>> from landlab.grid.structured_quad.links import (
...     number_of_horizontal_links)
>>> number_of_horizontal_links((3, 4))
9

number_of_in_links_per_node(shape)

Number of links entering each node.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

ndarray :

Array of number of in-links per node.

Examples

>>> from landlab.grid.structured_quad.links import (
...     number_of_in_links_per_node)
>>> number_of_in_links_per_node((3, 4))
array([[0, 1, 1, 1],
       [1, 2, 2, 2],
       [1, 2, 2, 2]])

number_of_links(shape)

Number of links in a structured quad grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

int :

Number of links in grid.

Examples

>>> from landlab.grid.structured_quad.links import number_of_links
>>> number_of_links((3, 4))
17

number_of_links_per_node(shape)

Number of links touching each node.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

ndarray :

Array of number of links per node.

Examples

>>> from landlab.grid.structured_quad.links import (
...     number_of_links_per_node, number_of_in_links_per_node,
...     number_of_out_links_per_node)
>>> number_of_links_per_node((3, 4))
array([[2, 3, 3, 2],
       [3, 4, 4, 3],
       [2, 3, 3, 2]])
>>> (number_of_in_links_per_node((3, 4)) +
...  number_of_out_links_per_node((3, 4)))
array([[2, 3, 3, 2],
       [3, 4, 4, 3],
       [2, 3, 3, 2]])

number_of_out_links_per_node(shape)

Number of links leaving each node.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

ndarray :

Array of number of out-links per node.

Examples

>>> from landlab.grid.structured_quad.links import (
...     number_of_out_links_per_node)
>>> number_of_out_links_per_node((3, 4))
array([[2, 2, 2, 1],
       [2, 2, 2, 1],
       [1, 1, 1, 0]])

number_of_vertical_links(shape)

Number of vertical links in a structured quad grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

int :

Number of vertical links in grid.

Examples

>>> from landlab.grid.structured_quad.links import number_of_vertical_links
>>> number_of_vertical_links((3, 4))
8

right_edge_horizontal_ids(shape)

IDs of right edge horizontal links.

Parameters:

shape : tuple of int

Shape of grid, given as (rows, columns) of nodes.

Returns:

ndarray :

Link IDs of left edge horizontal links. Length is (rmg.number_of_rows)

Examples

The following example uses this grid:

*--27-->*--28-->*--29-->*--30-->*

*--18-->*--19-->*--20-->*--21-->*

*---9-->*--10-->*--11-->*--12-->*

*---0-->*---1-->*---2-->*---3-->*

Note

Only horizontal links are shown.

* indicates nodes

Numeric values correspond to the horizontal IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import (
...     right_edge_horizontal_ids)
>>> rmg = RasterModelGrid(4, 5)
>>> shape = rmg.shape
>>> right_edge_horizontal_ids(shape)
array([ 3, 12, 21, 30])

right_edge_vertical_ids(shape)

Link IDs of right edge vertical links.

Parameters:

shape : tuple of int

Shape of grid, given as (rows, columns) of nodes.

Returns:

ndarray :

Link IDs of left edge vertical links. Length is (rmg.number_of_rows - 1)

Examples

The following example uses this grid:

 *       *       *       *       *
 ^       ^       ^       ^       ^
22      23      24      25      26
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
13      14      15      16      17
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
 4       5       6       7       8
 |       |       |       |       |
 *       *       *       *       *

Note

Only vertical links are shown.

* indicates nodes

Numeric values correspond to the vertical IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import right_edge_vertical_ids
>>> rmg = RasterModelGrid(4, 5)
>>> shape = rmg.shape
>>> right_edge_vertical_ids(shape)
array([ 8, 17, 26])

shape_of_horizontal_links(shape)

Shape of horizontal link grid.

Number of rows and columns of horizontal links that connect nodes in a structured grid of quadrilaterals.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

tuple of int :

Shape of the horizontal links in grid.

Examples

>>> from landlab.grid.structured_quad.links import (
...     shape_of_horizontal_links)
>>> shape_of_horizontal_links((3, 4))
(3, 3)

shape_of_vertical_links(shape)

Shape of vertical link grid.

Number of rows and columns of vertical links that connect nodes in a structured grid of quadrilaterals.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

tuple of int :

Shape of the vertical links in grid.

Examples

>>> from landlab.grid.structured_quad.links import shape_of_vertical_links
>>> shape_of_vertical_links((3, 4))
(2, 4)

top_edge_horizontal_ids(shape)

IDs of top edge horizontal links.

Parameters:

shape : tuple of int

Shape of grid, given as (rows, columns) of nodes.

Returns:

ndarray :

Link IDs of top edge horizontal links. Length is (rmg.number_of_columns - 1)

Examples

The following example uses this grid:

*--27-->*--28-->*--29-->*--30-->*

*--18-->*--19-->*--20-->*--21-->*

*---9-->*--10-->*--11-->*--12-->*

*---0-->*---1-->*---2-->*---3-->*

Note

Only horizontal links are shown.

* indicates nodes

Numeric values correspond to the horizontal IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import top_edge_horizontal_ids
>>> rmg = RasterModelGrid(4, 5)
>>> shape = rmg.shape
>>> top_edge_horizontal_ids(shape)
array([27, 28, 29, 30])

top_edge_vertical_ids(shape)

Link IDs of top edge vertical links.

Parameters:

shape : tuple of int

Shape of grid, given as (rows, columns) of nodes.

Returns:

ndarray :

Link IDs of top edge vertical links. Length is (rmg.number_of_columns)

Examples

The following example uses this grid:

 *       *       *       *       *
 ^       ^       ^       ^       ^
22      23      24      25      26
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
13      14      15      16      17
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
 4       5       6       7       8
 |       |       |       |       |
 *       *       *       *       *

Note

Only vertical links are shown.

* indicates nodes

Numeric values correspond to the vertical IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import top_edge_vertical_ids
>>> rmg = RasterModelGrid(4, 5)
>>> shape = rmg.shape
>>> top_edge_vertical_ids(shape)
array([22, 23, 24, 25, 26])

vertical_active_link_ids(shape, active_ids, bad_index_value=-1)

ID of vertical active links.

Parameters:

shape : tuple of int

Shape of grid of nodes.

active_ids : array of int

Array of all active link ids

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs at the VERTICAL active links. Length of number_of_vertical_links.

Examples

The following example uses this grid:

*---I-->*---I-->*---I-->*---I-->*
^       ^       ^       ^       ^
I       I       I       I       I
|       |       |       |       |
*---I-->o---H-->o---H-->o---I-->*
^       ^       ^       ^       ^
I       6       7       8       I
|       |       |       |       |
*---I-->o---H-->o---H-->o---I-->*
^       ^       ^       ^       ^
I       I       I       I       I
|       |       |       |       |
*---I-->*---I-->*---I-->*---I-->*

Note

* indicates the nodes that are set to CLOSED_BOUNDARY

o indicates the nodes that are set to CORE_NODE

I indicates the links that are set to INACTIVE_LINK

H indicates horizontal active ids, which are ignored by this function

Numeric values correspond to the vertical ACTIVE_LINK IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import (active_link_ids,
...     vertical_active_link_ids)

>>> rmg = RasterModelGrid((4, 5))
>>> active_ids = active_link_ids((4, 5), rmg.status_at_node)
>>> active_ids 
array([ 5,  6,  7,
        9, 10, 11, 12,
       14, 15, 16,
       18, 19, 20, 21,
       23, 24, 25])

>>> vertical_active_link_ids((4, 5), active_ids)
...     
array([-1,  5,  6,  7, -1,
       -1, 14, 15, 16, -1,
       -1, 23, 24, 25, -1])

>>> rmg.set_closed_boundaries_at_grid_edges(True, True, True, True)
>>> status = rmg.status_at_node
>>> active_ids = active_link_ids((4, 5), status)
>>> vertical_active_link_ids((4, 5), active_ids)
...     
array([-1, -1, -1, -1, -1,
       -1, 14, 15, 16, -1,
       -1, -1, -1, -1, -1])

vertical_east_link_neighbor(shape, vertical_ids, bad_index_value=-1)

Link IDs of east, vertical link neighbor.

Parameters:

shape : tuple of int

Shape of grid of nodes.

vertical_ids : array of int

Array of all vertical link ids - MUST BE ARRAY OF LEN(VERTICAL_LINKS)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs of east vertical neighbor links. Length of number_of_vertical_links.

Examples

The following example uses this grid:

 *       *       *       *       *
 ^       ^       ^       ^       ^
22      23      24      25      26
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
13      14      15      16      17
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
 4       5       6       7       8
 |       |       |       |       |
 *       *       *       *       *

Note

Only vertical links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the vertical IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid(4, 5)
>>> vertical_links = vertical_link_ids(rmg.shape)
>>> vertical_east_link_neighbor(rmg.shape, vertical_links)
...     
array([ 5,  6,  7,  8, -1,
       14, 15, 16, 17, -1,
       23, 24, 25, 26, -1])

vertical_fixed_link_ids(shape, fixed_ids, bad_index_value=-1)

ID of vertical fixed links.

Parameters:

shape : tuple of int

Shape of grid of nodes.

fixed_ids : array of int

Array of all fixed link ids

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs at the VERTICAL fixed links. Length of number_of_vertical_links.

Examples

The following example uses this grid:

*---I-->*---I-->*---I-->*---I-->*
^       ^       ^       ^       ^
I      23      24      25       I
|       |       |       |       |
*---H-->o---H-->o---H-->o---H-->*
^       ^       ^       ^       ^
I       V       V       V       I
|       |       |       |       |
*---H-->o---H-->o---H-->o---H-->*
^       ^       ^       ^       ^
I       5       6       7       I
|       |       |       |       |
*---I-->*---I-->*---I-->*---I-->*

Note

* indicates the nodes that are set to FIXED_GRADIENT_BOUNDARY

o indicates the nodes that are set to CORE_NODE

I indicates the links that are set to INACTIVE_LINK

H indicates horizontal active and fixed links, which are ignored by this function.

V indicates vertical active ids, which are ignored by this function.

Numeric values correspond to the vertical FIXED_LINK IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import (fixed_link_ids,
...     vertical_fixed_link_ids)
>>> import numpy

>>> rmg = RasterModelGrid((4, 5))
>>> rmg.at_node['topographic__elevation'] = numpy.arange(
...     0, rmg.number_of_nodes)
>>> rmg.at_link['topographic__slope'] = numpy.arange(
...     0, rmg.number_of_links)
>>> rmg.set_fixed_link_boundaries_at_grid_edges(True, True, True, True)

>>> status = rmg.status_at_node
>>> status 
array([2, 2, 2, 2, 2,
       2, 0, 0, 0, 2,
       2, 0, 0, 0, 2,
       2, 2, 2, 2, 2], dtype=int8)
>>> fixed_ids = fixed_link_ids((4, 5), status)

>>> vertical_fixed_link_ids((4,5), fixed_ids)
...     
array([-1,  5,  6,  7, -1,
       -1, -1, -1, -1, -1,
       -1, 23, 24, 25, -1])

vertical_link_ids(shape)

Vertical links in a structured quad grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

(M, N) ndarray :

Array of link IDs.

Examples

>>> from landlab.grid.structured_quad.links import vertical_link_ids
>>> vertical_link_ids((3, 4))
array([[ 3,  4,  5,  6],
       [10, 11, 12, 13]])

vertical_north_link_neighbor(shape, vertical_ids, bad_index_value=-1)

Link IDs of north, vertical link neighbor.

Parameters:

shape : tuple of int

Shape of grid of nodes.

vertical_ids : array of int

Array of all vertical link ids- MUST BE ARRAY OF LEN(VERTICAL_LINKS)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs of north vertical neighbor links. Length of number_of_vertical_links.

Examples

The following example uses this grid:

 *       *       *       *       *
 ^       ^       ^       ^       ^
22      23      24      25      26
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
13      14      15      16      17
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
 4       5       6       7       8
 |       |       |       |       |
 *       *       *       *       *

Note

Only vertical links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the vertical IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid(4, 5)
>>> vertical_ids = vertical_link_ids(rmg.shape)
>>> vertical_north_link_neighbor(rmg.shape, vertical_ids)
...     
array([13, 14, 15, 16, 17,
       22, 23, 24, 25, 26,
       -1, -1, -1, -1, -1])

vertical_south_link_neighbor(shape, vertical_ids, bad_index_value=-1)

Link IDs of south, vertical link neighbor.

Parameters:

shape : tuple of int

Shape of grid of nodes.

vertical_ids : array of int

Array of all vertical link ids - MUST BE ARRAY OF LEN(VERTICAL_LINKS)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs of south vertical neighbor links. Length of number_of_vertical_links.

Examples

The following example uses this grid:

 *       *       *       *       *
 ^       ^       ^       ^       ^
22      23      24      25      26
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
13      14      15      16      17
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
 4       5       6       7       8
 |       |       |       |       |
 *       *       *       *       *

Note

Only vertical links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the vertical IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid((4, 5))
>>> vertical_links = vertical_link_ids(rmg.shape)
>>> vertical_south_link_neighbor(rmg.shape, vertical_links)
...     
array([-1, -1, -1, -1, -1,
        4,  5,  6,  7,  8,
        13, 14, 15, 16, 17])

vertical_west_link_neighbor(shape, vertical_ids, bad_index_value=-1)

Link IDs of west, vertical link neighbor.

Parameters:

shape : tuple of int

Shape of grid of nodes.

vertical_ids : array of int

Array of all vertical link ids- MUST BE ARRAY OF LEN(VERTICAL_LINKS)

bad_index_value: int, optional

Value assigned to inactive indicies in the array.

Returns:

ndarray :

Link IDs of west vertical neighbor links. Length of number_of_vertical_links.

Examples

The following example uses this grid:

 *       *       *       *       *
 ^       ^       ^       ^       ^
22      23      24      25      26
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
13      14      15      16      17
 |       |       |       |       |
 *       *       *       *       *
 ^       ^       ^       ^       ^
 4       5       6       7       8
 |       |       |       |       |
 *       *       *       *       *

Note

Only vertical links are shown. When no neighbor is found, bad_index_value is returned.

* indicates nodes

Numeric values correspond to the vertical IDs.

>>> from landlab import RasterModelGrid
>>> from landlab.grid.structured_quad.links import *
>>> rmg = RasterModelGrid(4, 5)
>>> vertical_links = vertical_link_ids(rmg.shape)
>>> vertical_west_link_neighbor(rmg.shape, vertical_links)
...     
array([-1,  4,  5,  6,  7,
       -1, 13, 14, 15, 16,
       -1, 22, 23, 24, 25])

landlab.grid.structured_quad.nodes module

bottom_iter(shape)

Iterator for the bottom perimeter nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

bottom_top_iter(shape)

Iterator for the bottom and top perimeter nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Examples

>>> import numpy as np
>>> from landlab.grid.structured_quad.nodes import bottom_top_iter
>>> np.fromiter(bottom_top_iter((4, 3)), dtype=np.int)
array([ 0,  1,  2,  9, 10, 11])

corners(shape)

IDs of corner nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

(4, ) ndarray :

IDs of the corner nodes.

Examples

>>> from landlab.grid.structured_quad.nodes import corners
>>> corners((3, 4))
array([ 0,  3,  8, 11])

interior_nodes(shape)

IDs of interior nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

(M, N) ndarray :

IDs of the interior nodes.

Examples

>>> from landlab.grid.structured_quad.nodes import interior_nodes
>>> interior_nodes((3, 4))
array([[5, 6]])
>>> interior_nodes((4, 5))
array([[ 6,  7,  8],
       [11, 12, 13]])

left_iter(shape)

Iterator for the left perimeter nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

left_right_iter(shape, stop) left_right_iter(shape, start, stop[, step])

Iterator for left and right perimeter nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

start : int, optional

Start row.

stop : int, optional

Stop row.

step : int, optional

Interval between rows.

Examples

>>> import numpy as np
>>> from landlab.grid.structured_quad.nodes import left_right_iter
>>> np.fromiter(left_right_iter((4, 3)), dtype=np.int)
array([ 0,  2,  3,  5,  6,  8,  9, 11])
>>> np.fromiter(left_right_iter((4, 3), 2), dtype=np.int)
array([0, 2, 3, 5])
>>> np.fromiter(left_right_iter((4, 3), 2, 4), dtype=np.int)
array([ 6,  8,  9, 11])
>>> np.fromiter(left_right_iter((4, 3), 1, 4, 2), dtype=np.int)
array([ 3,  5,  9, 11])

node_ids(shape)

IDs of nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

ndarray :

IDs of the nodes.

Examples

>>> from landlab.grid.structured_quad.nodes import node_ids
>>> node_ids((3, 4))
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])

number_of_core_nodes(shape)

Number of core nodes is a structured quad grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

int :

Number of core nodes in the grid.

Examples

>>> from landlab.grid.structured_quad.nodes import number_of_core_nodes
>>> number_of_core_nodes((3, 4))
2

number_of_nodes(shape)

Number of nodes is a structured quad grid.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

int :

Number of nodes in the grid.

Examples

>>> from landlab.grid.structured_quad.nodes import number_of_nodes
>>> number_of_nodes((3, 4))
12

perimeter(shape)

Perimeter nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Returns:

ndarray :

IDs of the perimeter nodes.

Examples

>>> from landlab.grid.structured_quad.nodes import perimeter
>>> perimeter((3, 4))
array([ 0,  1,  2,  3,  4,  7,  8,  9, 10, 11])

perimeter_iter(shape)

Iterator for all perimeter nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

Examples

>>> import numpy as np
>>> from landlab.grid.structured_quad.nodes import perimeter_iter
>>> np.fromiter(perimeter_iter((4, 3)), dtype=np.int)
array([ 0,  1,  2,  3,  5,  6,  8,  9, 10, 11])

right_iter(shape)

Iterator for the right perimeter nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

status_with_perimeter_as_boundary(shape, node_status=4)

Node status for a grid whose boundary is along its perimeter.

Parameters:

shape : tuple of int

Shape of grid of nodes.

node_status : int or array_lik of int, optional

Status of nodes on grid perimeter.

Returns:

ndarray :

Node status for grid.

Examples

>>> from landlab.grid.structured_quad.nodes import status_with_perimeter_as_boundary
>>> status_with_perimeter_as_boundary((3, 4))
array([[4, 4, 4, 4],
       [4, 0, 0, 4],
       [4, 4, 4, 4]])
>>> status_with_perimeter_as_boundary((3, 4), node_status=-1)
array([[-1, -1, -1, -1],
       [-1,  0,  0, -1],
       [-1, -1, -1, -1]])

top_iter(shape)

Iterator for the top perimeter nodes.

Parameters:

shape : tuple of int

Shape of grid of nodes.

landlab.grid.structured_quad.rectilinear module

class RasterGrid(shape, spacing=1.0, origin=0.0)

Bases: landlab.grid.structured_quad.rectilinear.UniformRectilinearGrid

Parameters:

shape : tuple

Shape of the grid in nodes.

spacing : float, optional

Spacing between rows and columns.

origin : tuple, optional

Coordinates of grid origin.

Examples

>>> from landlab.grid.structured_quad.rectilinear import RasterGrid
>>> grid = RasterGrid((4, 5), spacing=2, origin=(-1, 1))
>>> grid.number_of_nodes
20

#>>> grid.number_of_core_nodes 6 >>> grid.number_of_node_rows 4 >>> grid.number_of_node_columns 5 >>> grid.nodes_at_corners_of_grid array([ 0, 4, 15, 19]) >>> grid.number_of_cells 6 >>> grid.node_row_coord array([-1., 1., 3., 5.]) >>> grid.node_col_coord array([ 1., 3., 5., 7., 9.])

class RectilinearGrid(coord)

Bases: landlab.grid.structured_quad.structured.StructuredQuadGrid

Parameters:

coord : tuple

Coordinates of node rows and node columns.

Examples

>>> import numpy as np
>>> from landlab.grid.structured_quad.rectilinear import RectilinearGrid
>>> (y, x) = np.arange(4.), np.arange(5.)
>>> grid = RectilinearGrid((y, x))
>>> grid.number_of_nodes
20
>>> grid.number_of_node_rows
4
>>> grid.number_of_node_columns
5
>>> grid.nodes_at_corners_of_grid
array([ 0,  4, 15, 19])
>>> grid.number_of_cells
6
>>> grid.node_row_coord
array([ 0.,  1.,  2.,  3.])
>>> grid.node_col_coord
array([ 0.,  1.,  2.,  3.,  4.])

coord

Node row and column coordinates.

node_col_coord

node_row_coord

class UniformRectilinearGrid(shape, spacing=(1.0, 1.0), origin=(0.0, 0.0))

Bases: landlab.grid.structured_quad.rectilinear.RectilinearGrid

Parameters:

shape : tuple

Shape of the grid in nodes.

spacing : tuple, optional

Spacing between rows and columns.

origin : tuple, optional

Coordinates of grid origin.

Examples

>>> from landlab.grid.structured_quad.rectilinear import UniformRectilinearGrid
>>> grid = UniformRectilinearGrid((4, 5), spacing=(2, 3), origin=(-1, 1))
>>> grid.number_of_nodes
20

#>>> grid.number_of_core_nodes 6 >>> grid.number_of_node_rows 4 >>> grid.number_of_node_columns 5 >>> grid.nodes_at_corners_of_grid array([ 0, 4, 15, 19]) >>> grid.number_of_cells 6 >>> grid.node_row_coord array([-1., 1., 3., 5.]) >>> grid.node_col_coord array([ 1., 4., 7., 10., 13.])

dx

Spacing between columns of grid nodes.

dy

Spacing between rows of grid nodes.

spacing

Spacing of rows and columns of grid nodes.

landlab.grid.structured_quad.structured module

Examples

>>> import numpy as np
>>> from landlab.grid.structured_quad.structured import StructuredQuadGrid
>>> (y, x) = np.meshgrid(np.arange(4.), np.arange(5.), indexing='ij')
>>> grid = StructuredQuadGrid((y, x))
>>> grid.number_of_nodes
20

>>> grid.number_of_node_rows == 4
True
>>> grid.number_of_node_columns == 5
True
>>> grid.nodes_at_corners_of_grid
array([ 0,  4, 15, 19])
>>> grid.number_of_cells
6

class StructuredQuadGrid(node_coord, shape=None, axis_name=None, axis_units=None, links=True, cells=True, node_status=None)

Bases: landlab.grid.unstructured.base.BaseGrid

Parameters:

node_coord : tuple

Coordinates of all grid nodes.

shape : tuple, optional

Shape of the grid of nodes.

corner_nodes

Note

This method is deprecated as of Landlab version 1.0.

Use nodes_at_corners_of_grid() instead.

nodes_at_corners_of_grid

Nodes in grid corners.

Return the IDs to the corner nodes of the grid, sorted by ID.

Returns:

(4, ) ndarray

Array of corner node IDs.

Examples

>>> import numpy as np
>>> from landlab.grid.structured_quad.structured import StructuredQuadGrid
>>> (x, y) = np.meshgrid(np.arange(4.), np.arange(5.), indexing='ij')
>>> grid = StructuredQuadGrid((x, y))
>>> grid.nodes_at_corners_of_grid
array([ 0,  4, 15, 19])

number_of_node_columns

Number of node columns.

Returns the number of columns, including boundaries.

number_of_node_rows

Number of node rows.

Returns the number of rows, including boundaries.

shape

Shape of the grid as rows, columns.

Module contents