mirror of
https://github.com/logos-blockchain/logos-blockchain-simulations.git
synced 2026-01-06 23:23:08 +00:00
118 lines
3.8 KiB
Python
118 lines
3.8 KiB
Python
from typing import List, Dict, Any, Tuple
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import numpy as np
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np.random.seed(42)
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import pandas as pd
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import tqdm
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from simulation_parameters import SimulationParameters
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from tx_fees_models import Block, Blockchain, MemPool, TransactionFeeMechanism, \
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EIP1559, StableFee, Transaction, create_demand
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def _generate_random_bool(p_true=0.5):
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return np.random.choice([True, False], p=(p_true, 1.-p_true), size=1)[0]
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def run_simulation(params: SimulationParameters) -> Tuple[pd.DataFrame, pd.DataFrame]:
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blockchain:Dict[str,Blockchain] = {
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"EIP": Blockchain(),
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"StableFee": Blockchain()
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}
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mempool:Dict[str, MemPool] = {
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"EIP": MemPool(),
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"StableFee": MemPool()
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}
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tf_models:dict[str, TransactionFeeMechanism] = {
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"EIP": EIP1559(),
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"StableFee": StableFee()
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}
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df_stats:Dict[str, pd.DataFrame] = {
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"EIP": pd.DataFrame(
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0,
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columns=["demand_size", "num_tx", "price", "tot_paid"],
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index=range(params.num_blocks)
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),
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"StableFee": pd.DataFrame(
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0,
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columns=["demand_size", "num_tx", "price", "tot_paid"],
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index=range(params.num_blocks)
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)
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}
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pbar = tqdm.tqdm(total=params.num_blocks)
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for b in range(params.num_blocks):
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# transactions are created with random values
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demand_size:int = np.random.choice(params.demand_sizes, p=params.demand_probabilities, size=1)[0]
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demand:List[Transaction] = create_demand(
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demand_size,
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fee_cap_range=params.fee_cap_range,
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max_tip_pct=params.max_tip_pct,
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variable_gas=True
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)
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stop_below_gas_limit:bool = _generate_random_bool(params.probability_stop_below_gas_limit)
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scale_block_size = np.random.uniform(
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params.scale_block_size_limits[0], params.scale_block_size_limits[1]
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)
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for chain, pool, tfm, stats in zip(
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blockchain.values(), mempool.values(), tf_models.values(), df_stats.values()
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):
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scaled_demand:List[Transaction] = tfm.scale_demand(demand)
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# transactions are added to the mempool
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pool.add_txs(scaled_demand)
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# transactions are selected from the mempool based on the gas premium
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selected_transactions, to_be_purged_transactions = tfm.select_transactions(
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pool,
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stop_below_gas_limit=stop_below_gas_limit,
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scale_block_size=scale_block_size,
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purge_after=params.purge_after
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)
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# selected transactions are added to the blockchain
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chain.add_block(Block(selected_transactions))
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# the price is updated based on the selected transactions
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tfm.update_price(chain)
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# base fee is updated for the next round
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stats.loc[b, "demand_size"] = demand_size
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stats.loc[b, "num_tx"] = len(selected_transactions)
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stats.loc[b, "price"] = tfm.get_current_price()
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stats.loc[b, "tot_paid"] = tfm.total_paid_fees(selected_transactions)
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# clear the mempool
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pool.remove_txs(selected_transactions)
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pool.remove_txs(to_be_purged_transactions)
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pbar.update(1)
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pbar.close()
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df_stats_merged = pd.concat(
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[df_stats[mechanism].add_suffix("_" + mechanism) for mechanism in df_stats.keys()],
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axis=1
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)
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df_chain_stats:Dict[str,pd.DataFrame] = {
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"EIP": blockchain["EIP"].compute_stats(),
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"StableFee": blockchain["StableFee"].compute_stats()
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}
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df_chain_stats_merged = pd.concat(
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[df_chain_stats[mechanism].add_suffix("_" + mechanism) for mechanism in df_stats.keys()],
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axis=1
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)
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return df_stats_merged, df_chain_stats_merged
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