Skip to main content

Logical Graph Builder that can be used for various problems that can be modeled as a graph data structure

Project description

coopgraph

Logical Graph Builder that can be used for various problems that can be modeled as a graph data structure

An Example:

from Graphs import Graph, Node
from dataStructs import Vector2

a = Node(name='A', pos=Vector2(0, 0))
b = Node(name='B', pos=Vector2(3, 3))
c = Node(name='C', pos=Vector2(2, 0))
d = Node(name='D', pos=Vector2(2, 1))
e = Node(name='E', pos=Vector2(3, 4))
f = Node(name='F', pos=Vector2(5, 5))


g = { a: [d],
      b: [c],
      c: [b, d, e],
      d: [a, c],
      e: [c, f],
      f: []
    }

graph = Graph(g)

The graph structure can then be used to perform various graph-related analysis:

Two find nodes that have no outbound connections

print(graph.find_isolated_vertices())

To find the shortest path between two nodes

print(graph.astar(a, e))

Note that for astar calculation, edges can be enabled or disabled against one or more disablers. This is useful for implementing temporary criteria in:

edges_to_disable = [value for key, value in graph.edges()][:3]

graph.disable_edges(edges_to_disable, "myDisabler")
path = graph.astar(a, e)
graph.disable_edges(edges_to_disable, "myDisabler")

you can also ignore disablers directly by passing a list of disabler names to the astar() method

edges_to_disable = [value for key, value in graph.edges()][:3]
graph.disable_edges(edges_to_disable, "myIngoredDisabler")

ignored = ["myIngoredDisabler"]
path = graph.astar(a, e, ignored_disablers=ignored)

An astar() call can also include custom g and h functions that allow for better control of the astar algorithm

def g(node1 Node, node2: Node) -> float:
    if node1.pos - node2.pos > 10:
        return 1
    else
        return .5

def h(node1 Node, node2: Node) -> float:
    if node1.pos - node2.pos > 10:
        return 100
    else
        return -100

path = graph.astar(a, e, g_func=g, h_func=h)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

coopgraph-1.9.tar.gz (16.8 kB view details)

Uploaded Source

Built Distribution

coopgraph-1.9-py3-none-any.whl (19.3 kB view details)

Uploaded Python 3

File details

Details for the file coopgraph-1.9.tar.gz.

File metadata

  • Download URL: coopgraph-1.9.tar.gz
  • Upload date:
  • Size: 16.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.9.6

File hashes

Hashes for coopgraph-1.9.tar.gz
Algorithm Hash digest
SHA256 b86ba60d464755289fde923bbe68eaf75f959cdfd1633e729f91632dace84c32
MD5 d0c276f37ee35ae971513609590d0a23
BLAKE2b-256 5a918836281cd595f3cce1e4d9807514bab3b40f2eb2dedec46cfa78fcd6a93c

See more details on using hashes here.

File details

Details for the file coopgraph-1.9-py3-none-any.whl.

File metadata

  • Download URL: coopgraph-1.9-py3-none-any.whl
  • Upload date:
  • Size: 19.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.9.6

File hashes

Hashes for coopgraph-1.9-py3-none-any.whl
Algorithm Hash digest
SHA256 76bdde5f2aa2b135ef82459f36e82ba2cc04ebae5b6b60cbd144193c5a5d6061
MD5 f12f5f93d41a998c086d9fd32793c7f6
BLAKE2b-256 92f14fdcaef7e142b9d419f0cf5398018b9a63f3c84ec7b819ddf601409546ec

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page