133 lines
6.5 KiB
Python
133 lines
6.5 KiB
Python
from v2realbot.utils.utils import isrising, isfalling,zoneNY, price2dec, safe_get, is_still, is_window_open, eval_cond_dict, crossed_down, crossed_up, crossed, is_pivot, json_serial, pct_diff, create_new_bars, slice_dict_lists
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from v2realbot.strategy.base import StrategyState
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from v2realbot.indicators.indicators import ema, natr, roc
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from v2realbot.strategyblocks.indicators.helpers import get_source_series, find_index_optimized
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from rich import print as printanyway
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from traceback import format_exc
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import numpy as np
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from collections import defaultdict
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#target algorithm for ML
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""""
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GOLDEN CROSS
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Target algorithm.
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if divergence of ema_slow and source is above/below threshold it labels the area as 1 or -1.
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Where
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- start is last crossing of source with ema and
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- end is the current position -1
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"""""
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def targetema(state, params, name, returns):
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try:
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funcName = "targetema"
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window_length_value = safe_get(params, "window_length_value", None)
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window_length_unit= safe_get(params, "window_length_unit", "position")
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downtrend, notrend, uptrend = safe_get(params, "output_vals", [-1,0,1])
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source = safe_get(params, "source", None)
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source_series = get_source_series(state, source, True)
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ema_slow = safe_get(params, "ema_slow", None)
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ema_slow_series = get_source_series(state, ema_slow, True)
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ema_div = safe_get(params, "ema_div", None)
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ema_div_series = get_source_series(state, ema_div)
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div_pos_threshold = safe_get(params, "div_pos_threshold", None)
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div_neg_threshold = safe_get(params, "div_neg_threshold", None)
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#mezi start a end price musi byt tento threshold
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req_min_pct_chng = float(safe_get(params, "req_min_pct_chng", 0.04)) #required PCT chng
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#kvalifikuji divergence s cenou jen vyssi nez posledni (pozor pri reverse trendu musime resetovat)
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if div_pos_threshold is not None and ema_div_series[-1] > div_pos_threshold and float(source_series[-1])>params.get("last_pos",0):
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# Finding first index where vwap is smaller than ema_slow (last cross)
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idx = np.where(source_series < ema_slow_series)[0]
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#there is no cross yet (beginning of the market)
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#TODO jeste to zbytecne protahuje tento signal az do doby protnuti (prvni signal je delsi a obcas zasahuje do konzolidace)
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if idx.size ==0:
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#if price exists lower than qualifying price
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idx = np.where(source_series*(1 + req_min_pct_chng/100) < source_series[-1])[0]
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if idx.size == 0:
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pass
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else:
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#we are qualified, oznacime
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first_idx = -len(source_series) + idx[-1]
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#fill target list with 1 from crossed point until last
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target_list = get_source_series(state, name)
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target_list[first_idx:] = [uptrend] * abs(first_idx)
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params["last_pos"] = float(source_series[-1])
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return 0, notrend
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#idx.size > 0:
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else:
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#if the value on the cross has min_pct from current price to qualify
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qual_price = source_series[idx[-1]] * (1 + req_min_pct_chng/100)
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qualified = qual_price < source_series[-1]
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if qualified:
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first_idx = -len(source_series) + idx[-1]
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#fill target list with 1 from crossed point until last
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target_list = get_source_series(state, name)
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target_list[first_idx:] = [uptrend] * abs(first_idx)
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params["last_pos"] = float(source_series[-1])
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return 0, notrend
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elif div_neg_threshold is not None and ema_div_series[-1] < div_neg_threshold and float(source_series[-1])<params.get("last_neg",99999999):
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# Finding first index where vwap is smaller than ema_slow (last cross) and price at cross must respect min PCT threshold
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idx = np.where(source_series > ema_slow_series)[0]
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#there is no cross yet (beginning of the market),
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if idx.size ==0:
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#if price exists higher than qualifying price
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idx = np.where(source_series*(1 - req_min_pct_chng/100) > source_series[-1])[0]
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if idx.size == 0:
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pass
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else:
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#we are qualified, oznacime
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first_idx = -len(source_series) + idx[-1]
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#fill target list with 1 from crossed point until last
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target_list = get_source_series(state, name)
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target_list[first_idx:] = [downtrend] * abs(first_idx)
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params["last_neg"] = float(source_series[-1])
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return 0, notrend
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#idx.size < 0:
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else:
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#porovname zda mezi aktualni cenou a cenou v crossu je dostatecna pro kvalifikaci
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qual_price = source_series[idx[-1]] * (1 - req_min_pct_chng/100)
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qualified = qual_price>source_series[-1]
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if qualified:
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first_idx = -len(source_series) + idx[-1]
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#fill target list with 1 from crossed point until last
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target_list = get_source_series(state, name)
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target_list[first_idx:] = [downtrend] * abs(first_idx)
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params["last_neg"] = float(source_series[-1])
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return 0, notrend
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#test resetujeme nejvyssi body po uplynuti 20 pozic od trendu (tim konci ochranne okno)
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# Finding the first 1 from backwards and its position
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target_numpy = get_source_series(state, name, True)
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position = np.where(target_numpy[::-1] == uptrend)[0][0] + 1
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if position % 20 == 0:
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params["last_pos"] = 0
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position = np.where(target_numpy[::-1] == downtrend)[0][0] + 1
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if position % 20 == 0:
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params["last_neg"] = 99999999
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return 0, notrend
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#pri chybe vracime explciitne notrend (muze mit jinou hodnotu nez 0)
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except Exception as e:
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state.ilog(lvl=1,e=f"IND ERROR {name} necháváme původní", message=str(e)+format_exc())
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return 0, notrend
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def add_pct(pct, value):
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"""
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Add a percentage to a value. If pct is negative it is subtracted.
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print(add_pct(1,100))
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Parameters:
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pct (float): The percentage to add (e.g., 10 for 10%).
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value (float): The original value.
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Returns:
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float: The new value after adding the percentage.
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"""
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return value * (1 + pct / 100)
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