import numpy as np
import pandas as pd
from itertools import combinations, product
import vectorbtpro as vbt
vbt.settings.set_theme("dark")

@vbt.chunked(  
    size=vbt.LenSizer(arg_query='fastp'),
    arg_take_spec=dict(
        data=None,
        fastp=vbt.ChunkSlicer(),
        slowp=vbt.ChunkSlicer(),
        signalp=vbt.ChunkSlicer()
    ),
    merge_func=lambda x: pd.concat(x).vbt.sort_index(),
    show_progress=True,
    chunk_len=1000  
)
def pipeline(data, fastp, slowp, signalp):  
    macd = vbt.talib("MACD").run(data.get("Close"), fastp, slowp, signalp)
    entries = macd.macd_above(0) & macd.macd_above(macd.macdsignal)  
    exits = macd.macd_below(0) | macd.macd_below(macd.macdsignal)  
    pf = vbt.Portfolio.from_signals(data, entries, exits, freq='d')
    return pf.trades.win_rate

btc_data = vbt.BinanceData.fetch(["BTCUSDT"])  
eth_data = vbt.BinanceData.fetch(["ETHUSDT"])

p = np.arange(4, 31)
fastp, slowp, signalp = zip(*product(p, p, p))  
btc_win_rates = pipeline(btc_data, fastp, slowp, signalp)  
eth_win_rates = pipeline(eth_data, fastp, slowp, signalp)
win_rates = pd.concat((btc_win_rates, eth_win_rates))  
win_rates.vbt.volume(  
    slider_level="symbol",
    trace_kwargs=dict(
        colorscale="icefire", 
        colorbar=dict(title='win_rate', tickformat='.0%'),
        cmid=0.5
    ),
).show()