def dijkstra2d(distance: np.array,
cost: np.array,
cardinal: Optional[int] = None,
diagonal: Optional[int] = None,
*,
edge_map: Any = None) -> None:
"""Return the computed distance of all nodes on a 2D Dijkstra grid.
`distance` is an input/output array of node distances. Is this often an
array filled with maximum finite values and 1 or more points with a low
value such as 0. Distance will flow from these low values to adjacent
nodes based the cost to reach those nodes. This array is modified
in-place.
`cost` is an array of node costs. Any node with a cost less than or equal
to 0 is considered blocked off. Positive values are the distance needed to
reach that node.
`cardinal` and `diagonal` are the cost multipliers for edges in those
directions. A value of None or 0 will disable those directions. Typical
values could be: ``1, None``, ``1, 1``, ``2, 3``, etc.
`edge_map` is a 2D array of edge costs with the origin point centered on
the array. This can be used to define the edges used from one node to
another. This parameter can be hard to understand so you should see how
it's used in the examples.
Example::
>>> import numpy as np
>>> import tcod
>>> cost = np.ones((3, 3), dtype=np.uint8)
>>> cost[:2, 1] = 0
>>> cost
array([[1, 0, 1],
[1, 0, 1],
[1, 1, 1]], dtype=uint8)
>>> dist = tcod.path.maxarray((3, 3), dtype=np.int32)
>>> dist[0, 0] = 0
>>> dist
array([[ 0, 2147483647, 2147483647],
[2147483647, 2147483647, 2147483647],
[2147483647, 2147483647, 2147483647]]...)
>>> tcod.path.dijkstra2d(dist, cost, 2, 3)
>>> dist
array([[ 0, 2147483647, 10],
[ 2, 2147483647, 8],
[ 4, 5, 7]]...)
>>> path = tcod.path.hillclimb2d(dist, (2, 2), True, True)
>>> path
array([[2, 2],
[2, 1],
[1, 0],
[0, 0]], dtype=int32)
>>> path = path[::-1].tolist()
>>> while path:
... print(path.pop(0))
[0, 0]
[1, 0]
[2, 1]
[2, 2]
`edge_map` is used for more complicated graphs. The following example
uses a 'knight move' edge map.
Example::
>>> import numpy as np
>>> import tcod
>>> knight_moves = [
... [0, 1, 0, 1, 0],
... [1, 0, 0, 0, 1],
... [0, 0, 0, 0, 0],
... [1, 0, 0, 0, 1],
... [0, 1, 0, 1, 0],
... ]
>>> dist = tcod.path.maxarray((8, 8))
>>> dist[0,0] = 0
>>> cost = np.ones((8, 8), int)
>>> tcod.path.dijkstra2d(dist, cost, edge_map=knight_moves)
>>> dist
array([[0, 3, 2, 3, 2, 3, 4, 5],
[3, 4, 1, 2, 3, 4, 3, 4],
[2, 1, 4, 3, 2, 3, 4, 5],
[3, 2, 3, 2, 3, 4, 3, 4],
[2, 3, 2, 3, 4, 3, 4, 5],
[3, 4, 3, 4, 3, 4, 5, 4],
[4, 3, 4, 3, 4, 5, 4, 5],
[5, 4, 5, 4, 5, 4, 5, 6]]...)
>>> tcod.path.hillclimb2d(dist, (7, 7), edge_map=knight_moves)
array([[7, 7],
[5, 6],
[3, 5],
[1, 4],
[0, 2],
[2, 1],
[0, 0]], dtype=int32)
`edge_map` can also be used to define a hex-grid.
See https://www.redblobgames.com/grids/hexagons/ for more info.
The following example is using axial coordinates.
Example::
hex_edges = [
[0, 1, 1],
[1, 0, 1],
[1, 1, 0],
]
.. versionadded:: 11.2
.. versionchanged:: 11.13
Added the `edge_map` parameter.
"""
dist = distance
cost = np.asarray(cost)
if dist.shape != cost.shape:
raise TypeError("distance and cost must have the same shape %r != %r" %
(dist.shape, cost.shape))
c_dist = _export(dist)
if edge_map is not None:
if cardinal is not None or diagonal is not None:
raise TypeError("`edge_map` can not be set at the same time as"
" `cardinal` or `diagonal`.")
c_edges, n_edges = _compile_cost_edges(edge_map)
_check(lib.dijkstra2d(c_dist, _export(cost), n_edges, c_edges))
else:
if cardinal is None:
cardinal = 0
if diagonal is None:
diagonal = 0
_check(lib.dijkstra2d_basic(c_dist, _export(cost), cardinal, diagonal))
def dijkstra2d(
distance: np.array,
cost: np.array,
cardinal: Optional[int],
diagonal: Optional[int],
) -> None:
"""Return the computed distance of all nodes on a 2D Dijkstra grid.
`distance` is an input/output array of node distances. Is this often an
array filled with maximum finite values and 1 or more points with a low
value such as 0. Distance will flow from these low values to adjacent
nodes based the cost to reach those nodes. This array is modified
in-place.
`cost` is an array of node costs. Any node with a cost less than or equal
to 0 is considered blocked off. Positive values are the distance needed to
reach that node.
`cardinal` and `diagonal` are the cost multipliers for edges in those
directions. A value of None or 0 will disable those directions. Typical
values could be: ``1, None``, ``1, 1``, ``2, 3``, etc.
Example:
>>> import numpy as np
>>> import tcod
>>> cost = np.ones((3, 3), dtype=np.uint8)
>>> cost[:2, 1] = 0
>>> cost
array([[1, 0, 1],
[1, 0, 1],
[1, 1, 1]], dtype=uint8)
>>> dist = tcod.path.maxarray((3, 3), dtype=np.int32)
>>> dist[0, 0] = 0
>>> dist
array([[ 0, 2147483647, 2147483647],
[2147483647, 2147483647, 2147483647],
[2147483647, 2147483647, 2147483647]]...)
>>> tcod.path.dijkstra2d(dist, cost, 2, 3)
>>> dist
array([[ 0, 2147483647, 10],
[ 2, 2147483647, 8],
[ 4, 5, 7]]...)
>>> path = tcod.path.hillclimb2d(dist, (2, 2), True, True)
>>> path
array([[2, 2],
[2, 1],
[1, 0],
[0, 0]], dtype=int32)
>>> path = path[::-1].tolist()
>>> while path:
... print(path.pop(0))
[0, 0]
[1, 0]
[2, 1]
[2, 2]
.. versionadded:: 11.2
"""
dist = distance
cost = np.asarray(cost)
if dist.shape != cost.shape:
raise TypeError("distance and cost must have the same shape %r != %r" %
(dist.shape, cost.shape))
if cardinal is None:
cardinal = 0
if diagonal is None:
diagonal = 0
_check(lib.dijkstra2d(_export(dist), _export(cost), cardinal, diagonal))