run_simulator.py

import pandas as pd
import sys, os, json
from lnsimulator.ln_utils import preprocess_json_file
import lnsimulator.simulator.transaction_simulator as ts

data_dir = "../ln_data/"
max_threads = 2

def run_experiment(edges, parameter_file, output_dir):
    if not os.path.exists(output_dir):
        os.makedirs(output_dir)

    print("\n# 2. Load parameters")
    with open(parameter_file) as f:
        params = json.load(f)
    print(params)

    amount = params["amount"]
    count = params["count"]
    epsilon = params["epsilon"]
    drop_disabled = params["drop_disabled"]
    drop_low_cap = params["drop_low_cap"]
    with_depletion = params["with_depletion"]
    find_alternative_paths = True

    print("\n# 3. Load meta data")
    node_meta = pd.read_csv("%s/1ml_meta_data.csv" % data_dir)
    providers = list(node_meta["pub_key"])

    print("\n# 4. Simulation")
    simulator = ts.TransactionSimulator(edges, providers, amount, count, epsilon=epsilon, drop_disabled=drop_disabled, drop_low_cap=drop_low_cap, with_depletion=with_depletion)
    transactions = simulator.transactions
    shortest_paths, alternative_paths, all_router_fees, _ = simulator.simulate(weight="total_fee", with_node_removals=find_alternative_paths, max_threads=max_threads)
    total_income, total_fee = simulator.export(output_dir)
    
    print("\n# 5. Analyze optimal base fee for nodes")
    if find_alternative_paths:
        opt_fees_df, p_altered = ts.calc_optimal_base_fee(shortest_paths, alternative_paths, all_router_fees)
        opt_fees_df.to_csv("%s/opt_fees.csv" % output_dir, index=False)
    print("\ndone")

if __name__ == "__main__":
    if len(sys.argv) == 5:
        input_type = sys.argv[1]
        print("# 1. Load LN graph data")
        if input_type == "raw":
            json_file = sys.argv[2]
            directed_edges = preprocess_json_file(json_file)
        elif input_type == "preprocessed":
            snapshot_id = int(sys.argv[2])
            snapshots = pd.read_csv("%s/ln_edges.csv" % data_dir)
            directed_edges = snapshots[snapshots["snapshot_id"]==snapshot_id]
        else:
            raise ValueError("The first arguments must be 'raw' or 'preprocessed'!")
        parameter_file = sys.argv[3]
        output_folder = sys.argv[4]
        run_experiment(directed_edges, parameter_file, output_folder)
    else:
        print("You must support 4 input arguments:")
        print("   run_simulator.py raw <json_file_path> <parameter_file> <output_folder>")
        print("OR")
        print("   run_simulator.py preprocessed <snapshot_id (int)> <parameter_file> <output_folder>")