def generate_one_tsp_problem()

in src/streamlit_demo.py [0:0]

• 29 lines of code
• 3 McCabe index (conditional complexity)

def generate_one_tsp_problem(neighbors = 0.20,
                             num_nodes=10):
    dataset_path = None
    batch_size = 1
    accumulation_steps = 80
    num_samples = 1
    knn_strat = 'percentage'
    
    dataset = TSP.make_dataset(
        filename=dataset_path,
        batch_size=batch_size,
        num_samples=num_samples,
        min_size=num_nodes,
        max_size=num_nodes,
        neighbors=neighbors,
        knn_strat=knn_strat,
        supervised=False
    )
    dataloader = DataLoader(dataset,
                        batch_size=batch_size,
                        shuffle=False,
                        num_workers=0)
    # transform data
    data = []
    for bat_idx, bat in enumerate(dataloader):
        input = {}
        input["nodes"] = bat["nodes"].tolist()
        data.append(input)
    for record in data:
        record["neighbors"] = neighbors
    return data