def test_random_gnm_directed(self):
graph = retworkx.directed_gnm_random_graph(20, 100)
self.assertEqual(len(graph), 20)
self.assertEqual(len(graph.edges()), 100)
# with other arguments equal, same seed results in same graph
graph_s1 = retworkx.directed_gnm_random_graph(20, 100, seed=10)
graph_s2 = retworkx.directed_gnm_random_graph(20, 100, seed=10)
self.assertEqual(graph_s1.edge_list(), graph_s2.edge_list())
def test_random_gnm_directed_empty_graph(self):
graph = retworkx.directed_gnm_random_graph(20, 0)
self.assertEqual(len(graph), 20)
self.assertEqual(len(graph.edges()), 0)
# passing a seed when passing zero edges has no effect
graph = retworkx.directed_gnm_random_graph(20, 0, 44)
self.assertEqual(len(graph), 20)
self.assertEqual(len(graph.edges()), 0)
def test_random_gnm_directed_complete_graph(self):
n = 20
max_m = n * (n - 1)
# passing the max edges for the passed number of nodes
graph = retworkx.directed_gnm_random_graph(n, max_m)
self.assertEqual(len(graph), n)
self.assertEqual(len(graph.edges()), max_m)
# passing m > the max edges n(n-1) still returns the max edges
graph = retworkx.directed_gnm_random_graph(n, max_m + 1)
self.assertEqual(len(graph), n)
self.assertEqual(len(graph.edges()), max_m)
# passing a seed when passing max edges has no effect
graph = retworkx.directed_gnm_random_graph(n, max_m, 55)
self.assertEqual(len(graph), n)
self.assertEqual(len(graph.edges()), max_m)
def setup(self, num_nodes, num_edges):
random.seed(42)
self.graph = retworkx.directed_gnm_random_graph(num_nodes, num_edges)
for x in self.graph.node_indexes():
self.graph[x] = x
for edge in self.graph.edge_indices():
self.graph.update_edge_by_index(edge, random.randint(1, 10000))
def setup(self, num_nodes, num_edges, remove_nodes):
random.seed(12345)
self.graph_func = retworkx.digraph_adjacency_matrix
self.graph = retworkx.directed_gnm_random_graph(num_nodes,
num_edges,
seed=4242)
for edge in self.graph.edge_indices():
self.graph.update_edge_by_index(edge, random.randint(0, 20000))
def test_weight_fn_raises(self):
path = os.path.join(tempfile.gettempdir(), "fail.txt")
graph = retworkx.directed_gnm_random_graph(5, 4)
def weight_fn(edge):
raise KeyError
self.addCleanup(os.remove, path)
with self.assertRaises(KeyError):
graph.write_edge_list(path, weight_fn=weight_fn)
def test_random_gnm_directed_invalid_num_edges(self):
with self.assertRaises(ValueError):
retworkx.directed_gnm_random_graph(23, -5)
def test_invalid_return_type_weight_fn(self):
path = os.path.join(tempfile.gettempdir(), "fail.txt")
graph = retworkx.directed_gnm_random_graph(5, 4)
self.addCleanup(os.remove, path)
with self.assertRaises(TypeError):
graph.write_edge_list(path, weight_fn=lambda _: 4.5)
import os
import tempfile
from typing import Sized
from PIL import Image
import pydot
import retworkx as rx
import igraph as ig
import numpy as np
G: rx.PyDiGraph = rx.directed_gnm_random_graph(1000, 2000, None)
components: list = rx.strongly_connected_components(G)
largest_component: Sized = max(components, key=len)
H: rx.PyGraph = G.subgraph(largest_component)
# have to fix pydot error
"""
dot = pydot.graph_from_dot_data(G.to_dot())[0]
with tempfile.TemporaryDirectory() as tmpdirname:
tmp_path = os.path.join(tmpdirname, 'dag.png')
dot.write_png(tmp_path)
image = Image.open(tmp_path)
os.remove(tmp_path)
image
"""
n1: np.ndarray = rx.digraph_adjacency_matrix(G, None)
g: ig.Graph = ig.Graph.Weighted_Adjacency(n1.tolist())
ig.plot(g)
def setup(self, num_nodes, num_edges):
self.graph = retworkx.directed_gnm_random_graph(num_nodes,
num_edges,
seed=4242423)