tickdata / fast_simulate_THE_ONE.py
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import pandas as pd
import numpy as np
import time
def simulate():
print("==================================================")
print(" PYTHON QUANT LAB: FAST SIMULATE 'THE ONE' ")
print("==================================================")
print("[1] Loading 100MB Parquet Tick Data...")
t0 = time.time()
df = pd.read_parquet(r"C:\Users\Black\Downloads\MT5EA\tick_data\ticks_100MB.parquet", columns=['time_msc', 'bid'])
df['datetime'] = pd.to_datetime(df['time_msc'], unit='ms')
df.set_index('datetime', inplace=True)
print(f" -> Loaded {len(df):,} ticks in {time.time()-t0:.2f} seconds.")
print("\n[2] Resampling Ticks to M1 Candles...")
t1 = time.time()
ohlc = df['bid'].resample('1min').ohlc()
ohlc.dropna(inplace=True)
print(f" -> Generated {len(ohlc):,} M1 candles in {time.time()-t1:.2f} seconds.")
# Thông số cấu hình
min_bodies = [30, 50, 100, 150, 200, 300, 400]
tp_pts = 400
sl_pts = 1000
print("\n[3] Quét Ma Trận (Matrix Sweep) - Chờ MT5 36 tiếng, Python làm trong 5 giây!")
print(f"Cấu hình: TP = {tp_pts} pts | SL = {sl_pts} pts (Lưu ý: Chưa tính Nhồi Lưới - Chỉ test Naked Entry)")
print("-" * 75)
print(f"{'Min_Body':<10} | {'Tổng Lệnh':<12} | {'Win Lệnh':<10} | {'Lose Lệnh':<10} | {'WinRate':<10} | {'Net P/L (Pts)':<15}")
print("-" * 75)
open_p = ohlc['open'].values
close_p = ohlc['close'].values
high_p = ohlc['high'].values
low_p = ohlc['low'].values
for mb in min_bodies:
# Vàng 2 số thập phân -> 50 points = 0.50
mb_price = mb * 0.01
tp_price = tp_pts * 0.01
sl_price = sl_pts * 0.01
# Điều kiện nổ súng (Naked Price Action)
buy_signals = (close_p - open_p) >= mb_price
sell_signals = (open_p - close_p) >= mb_price
wins = 0
losses = 0
for i in range(len(open_p)-1):
if buy_signals[i]:
entry = open_p[i+1] # Vào lệnh ở đầu nến tiếp theo
# Quét tương lai xem chạm SL hay TP trước
for j in range(i+1, min(len(open_p), i+120)): # Quét max 2 tiếng
if low_p[j] <= entry - sl_price:
losses += 1
break
elif high_p[j] >= entry + tp_price:
wins += 1
break
elif sell_signals[i]:
entry = open_p[i+1]
for j in range(i+1, min(len(open_p), i+120)):
if high_p[j] >= entry + sl_price:
losses += 1
break
elif low_p[j] <= entry - tp_price:
wins += 1
break
total = wins + losses
winrate = (wins/total*100) if total > 0 else 0
pnl = (wins * tp_pts) - (losses * sl_pts)
# Color formatting manually
pnl_str = f"+{pnl}" if pnl > 0 else f"{pnl}"
print(f"{mb:<10} | {total:<12} | {wins:<10} | {losses:<10} | {winrate:<8.2f}% | {pnl_str:<15}")
if __name__ == "__main__":
simulate()