How to phase out of a position with take profits levels?

[IntergalacticWaffle]

Hello, thanks for creating this library or anyone else that is answering, thanks for the help! I was wondering how to phase out of a position with take profits? Ideally I can keep using vbt.Portfolio.from_signals. I assume this has to be accomplished using: adjust_tp_func_nb=adjust_tp_func_nb, and I have accumulate set to: accumulate="RemoveOnly", which I assume means to remove as in to phase out. I can't figure out how to actually close part of the position though, whenever a tp level is hit. I have started the tp function below. I anticipate another issue being the tp levels being hit over and over before the next level is hit if that makes any sense. If you could please provide any code or if there is an easy way to accomplish this that I am missing, it would be really appreciated for some information regarding my issue. Thanks again! @polakowo

# Data gathered personally defined as df
df = 


@njit
def adjust_sl_func_nb(c, atr_array):
    sl_multiplier = 2.0
    if c.position_now > 0: # Longs
        current_profit = (c.val_price_now - c.init_price) / c.init_price
        stop_loss = (c.val_price_now - (c.val_price_now - (sl_multiplier * atr_array[c.i]))) / c.val_price_now
    elif c.position_now < 0: # Shorts
        current_profit = ((c.val_price_now - c.init_price) / c.init_price) * -1
        stop_loss = ((c.val_price_now - (c.val_price_now + (sl_multiplier * atr_array[c.i]))) / c.val_price_now) * -1
    else: # No position
        stop_loss = 1.00

    if stop_loss < 0.00: 
        stop_loss = 1.00 # Never hit

    return stop_loss, True


@njit
def adjust_tp_func_nb(c):      
    if c.position_now > 0: # Longs
        current_profit = (c.val_price_now - c.init_price) / c.init_price
        if current_profit >= 0.025:
            # sell half of position
            return
        if current_profit >= 0.05:
            # sell half of remaining half
            return        
        if current_profit >= 0.10:
            # sell remaining position
            return
    elif c.position_now < 0: # Shorts
        current_profit = ((c.val_price_now - c.init_price) / c.init_price) * -1
        if current_profit >= 0.025:
            # sell half of position
            return
        if current_profit >= 0.05:
            # sell half of remaining half
            return        
        if current_profit >= 0.10:
            # sell remaining position
            return
    else: # No position
        return 1.00 # Wont get hit


def custom_indicator(close, ema_window = 14, sma_window = 50):
    ema = talib.EMA(close, timeperiod=ema_window)
    sma = talib.SMA(close, timeperiod=sma_window)
    trend = np.where(sma > ema, -1, 0)
    trend = np.where((sma < ema), 1, trend)
    return trend

ind = vbt.IndicatorFactory(
    class_name="Combination", 
    short_name="comb", 
    input_names=["close"], 
    param_names = ["ema_window", "sma_window"], 
    output_names=["value"]).from_apply_func(custom_indicator, ema_window = 14, sma_window=50, to_2d=False)

res = ind.run(df["close"], 
    ema_window = np.arange(10, 40 + 1, step=1, dtype=int), 
    sma_window = np.arange(10, 40 + 1, step=1, dtype=int), 
    param_product = True)


entries = res.value == 1.0
exits = res.value == 0.0
short_entries = res.value == -1.0
short_exits = res.value == 0.0


# Calculate ATR using talib for SL sake
atr = talib.ATR(df["high"], df["low"], df["close"], timeperiod=14)
# Convert the result to a numpy array so it's @njit compatible
atr_for_close = atr.values


pf = vbt.Portfolio.from_signals(df["close"], 
    entries=entries, 
    exits=exits, 
    short_entries=short_entries, 
    short_exits=short_exits, 
    open=df["open"],
    high=df["high"],
    low=df["low"],
    init_cash=100000,
    fees=0.0001, 
    #slippage=0.0001,
    accumulate="RemoveOnly",
    adjust_sl_func_nb=adjust_sl_func_nb,
    adjust_sl_args=(atr_for_close),
    adjust_tp_func_nb=adjust_tp_func_nb,
    adjust_tp_args=(),
    )


returns = pf.total_return() * 100