Please help to convert to work on Futures dataset

Sheikh

Hello @support,
I was wondering if I can request your assistance in converting the code below to work on the Futures dataset. (I omitted & changed a few things to not reveal the true strategy. But this is the basic idea.)
It currently works on the Crypto dataset.
I'm posting the crypto version as the attempts I made to convert it to work on Futures are a big mess.
Basically, I changed the load_data and competition type to futures and removed the markets = ['BTC'] line.
I also removed from the output: dims=['asset'], coords=dict(asset=markets)
But still no luck getting it to run on Futures.
Can you take a look pls when you have a moment.
Thanks.

import xarray as xr
import numpy as np
import qnt.data as qndata
import qnt.backtester as qnbt
import qnt.ta as qnta

def load_data(period):
    data = qndata.cryptofutures_load_data(tail=period)
    return data

def strategy(data, state):
    markets = ['BTC']
    
    zthreshold =  2.0
    lookback_trading_days = 20
    
    close = data.sel(field='close')
    last_close = close.isel(time=-1)
    high = data.sel(field='high')
    low = data.sel(field='low')
    # state may be null, so define a default value
    prev_output = state
    if prev_output is None:
        prev_output = xr.zeros_like(last_close)
    s1 = close[-lookback_trading_days:]
    # Compute mean of the spread up to now
    mvavg = np.mean(np.log(s1))
    # Compute stdev of the spread up to now
    stdev = np.std(np.log(s1))
    # Compute current spread
    current_spread = np.log(s1[-1])
    # Compute z-score
    zscore = (current_spread - mvavg) / stdev if stdev > 0 else 0
    
    output = prev_output
    if prev_output == [1] and zscore[-1] <= -zthreshold:
        output = [0]
    elif prev_output == [-1] and zscore[-1] >= -zthreshold:
        output = [0]
    elif zscore[-1] <= zthreshold:
        output = [1]
    elif zscore[-1] >= -zthreshold:
        output = [-1]
    else:
        output = prev_output
    return xr.DataArray(output, dims=['asset'], coords=dict(asset=markets)), output

weights, state = qnbt.backtest(
    competition_type="cryptofutures",  
    lookback_period=200,  # lookback in calendar days
    start_date= "2014-01-01",
    strategy=strategy,
    analyze=True,
    build_plots=True,
    collect_all_states=False # if it is False, then the function returns the last state, otherwise - all states
)

support

@sheikh Thanks, could you post the log you see on the notebook when the code fails? Thank you!