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")