def generate_caveman_graph(
number_of_cliques: int, size_of_cliques: int, random_weights: bool = False, seed: Optional[int] = None
):
graph = _generate_caveman_graph(
number_of_cliques, size_of_cliques, random_weights, seed
)
save_graph(graph, "graph.json")
def generate_ladder_graph(
length_of_ladder: int, random_weights: bool = False, seed: Optional[int] = None
):
graph = _generate_ladder_graph(
length_of_ladder, random_weights, seed
)
save_graph(graph, "graph.json")
def generate_complete_graph(
number_of_nodes: int, random_weights: bool = False, seed: Optional[int] = None
):
graph = _generate_random_graph_erdos_renyi(
number_of_nodes, 1.0, random_weights, seed
)
save_graph(graph, "graph.json")
def generate_complete_graph(number_of_nodes: int,
random_weights: bool = False,
seed: Union[str, int] = "None"):
if seed == "None":
seed = None
graph = _generate_random_graph_erdos_renyi(number_of_nodes, 1.0,
random_weights, seed)
save_graph(graph, "graph.json")
def generate_barbell_graph(
number_of_vertices_complete_graph: int, random_weights: bool = False,
seed: Optional[int] = None
):
graph = _generate_barbell_graph(
number_of_vertices_complete_graph, random_weights, seed
)
save_graph(graph, "graph.json")
def generate_random_regular_graph(
number_of_nodes: int,
degree: int,
random_weights: bool = False,
seed: Optional[int] = None,
):
graph = _generate_random_regular_graph(number_of_nodes, degree,
random_weights, seed)
save_graph(graph, "graph.json")
def generate_random_graph_erdos_renyi(
number_of_nodes: int,
edge_probability: float,
random_weights: bool = False,
seed: Optional[int] = None,
):
graph = _generate_random_graph_erdos_renyi(
number_of_nodes, edge_probability, random_weights, seed
)
save_graph(graph, "graph.json")
def generate_random_regular_graph(
number_of_nodes: int,
degree: int,
random_weights: bool = False,
seed: Union[str, int] = "None",
):
if seed == "None":
seed = None
graph = _generate_random_regular_graph(number_of_nodes, degree,
random_weights, seed)
save_graph(graph, "graph.json")
def generate_barbell_graph(
number_of_vertices_complete_graph: int,
sampler_specs: Optional[Specs] = None,
seed: Optional[int] = None,
):
graph = zquantum.core.graph.generate_barbell_graph(
number_of_vertices_complete_graph,
_make_sampler(sampler_specs),
seed,
)
save_graph(graph, "graph.json")
def generate_ladder_graph(
length_of_ladder: int,
sampler_specs: Optional[Specs] = None,
seed: Optional[int] = None,
):
graph = zquantum.core.graph.generate_ladder_graph(
length_of_ladder,
_make_sampler(sampler_specs),
seed,
)
save_graph(graph, "graph.json")
def generate_complete_graph(
number_of_nodes: int,
sampler_specs: Optional[Specs] = None,
seed: Optional[int] = None,
):
graph = zquantum.core.graph.generate_random_graph_erdos_renyi(
number_of_nodes,
1.0,
_make_sampler(sampler_specs),
seed,
)
save_graph(graph, "graph.json")
def generate_random_graph_erdos_renyi(
number_of_nodes: int,
edge_probability: float,
random_weights: bool = False,
seed: Union[str, int] = "None",
):
if seed == "None":
seed = None
graph = _generate_random_graph_erdos_renyi(number_of_nodes,
edge_probability,
random_weights, seed)
save_graph(graph, "graph.json")
def generate_caveman_graph(
number_of_cliques: int,
size_of_cliques: int,
sampler_specs: Optional[Specs] = None,
seed: Optional[int] = None,
):
graph = zquantum.core.graph.generate_caveman_graph(
number_of_cliques,
size_of_cliques,
_make_sampler(sampler_specs),
seed,
)
save_graph(graph, "graph.json")
def generate_random_regular_graph(
number_of_nodes: int,
degree: int,
sampler_specs: Optional[Specs] = None,
seed: Optional[int] = None,
):
graph = zquantum.core.graph.generate_random_regular_graph(
number_of_nodes,
degree,
_make_sampler(sampler_specs),
seed,
)
save_graph(graph, "graph.json")
def test_graph_io(self):
# Given
G = nx.Graph()
G.add_edges_from([(1, 2), (2, 3), (1, 3)])
# When
save_graph(G, "Graph.json")
G2 = load_graph("Graph.json")
# Then
self.assertTrue(compare_graphs(G, G2))
os.remove("Graph.json")
def generate_graph_from_specs(graph_specs: Dict):
graph_specs_dict = json.loads(graph_specs)
graph = _generate_graph_from_specs(graph_specs_dict)
save_graph(graph, "graph.json")
def generate_graph_from_specs(graph_specs: str):
graph_specs_dict = json.loads(graph_specs)
graph = zquantum.core.graph.generate_graph_from_specs(graph_specs_dict)
save_graph(graph, "graph.json")
