# source: https://raw.githubusercontent.com/viktors1982/trading/e2fba2a4608c6bd6d1ca7e117c80cad2f692dec1/freqtrade/strategies/LuxOSC.py # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement # flake8: noqa: F401 # --- Do not remove these libs --- import numpy as np # noqa import pandas as pd # noqa from pandas import DataFrame from freqtrade.strategy import IStrategy from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter # -------------------------------- # Add your lib to import here import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib def LUX_SuperTrendOscillator(dtloc, source = 'close', length = 6, mult = 9, smooth = 72): """ // This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) https://creativecommons.org/licenses/by-nc-sa/4.0/ // © LuxAlgo https://www.tradingview.com/script/dVau7zqn-LUX-SuperTrend-Oscillator/ :return: List of tuples in the format (osc, signal, histogram) translated for freqtrade: viksal1982 viktors.s@gmail.com """ def_proc_name = '_LUX_SuperTrendOscillator' atrcol = 'atr' + def_proc_name hl2col = 'hl2' + def_proc_name upcol = 'up' + def_proc_name dncol = 'dn' + def_proc_name uppercol = 'upper' + def_proc_name lowercol = 'lower' + def_proc_name trendcol = 'trend' + def_proc_name sptcol = 'spt' + def_proc_name osc1col = 'osc1' + def_proc_name osc2col = 'osc2' + def_proc_name osccol = 'osc' + def_proc_name alphacol = 'alpha' + def_proc_name amacol = 'ama' + def_proc_name histcol = 'hist' + def_proc_name dtS = dtloc.copy().fillna(0) dtS[atrcol] = ta.ATR(dtloc, timeperiod = length) * mult dtS[hl2col] = (dtS['high'] + dtS['low'] )/2 dtS[upcol] = dtS[hl2col] + dtS[atrcol] dtS[dncol] = dtS[hl2col] - dtS[atrcol] def calc_upper(dfr, init=0): global calc_Lux_STO_upper global calc_Lux_STO_src if init == 1: calc_Lux_STO_upper = 0.0 calc_Lux_STO_src = 0.0 return if calc_Lux_STO_src < calc_Lux_STO_upper: calc_Lux_STO_upper = min(dfr[upcol], calc_Lux_STO_upper) else: calc_Lux_STO_upper = dfr[upcol] calc_Lux_STO_src = dfr[source] return calc_Lux_STO_upper calc_upper(None, init=1) dtS[uppercol] = dtS.apply(calc_upper, axis = 1) def calc_lower(dfr, init=0): global calc_Lux_STO_lower global calc_Lux_STO_src if init == 1: calc_Lux_STO_lower = 0.0 calc_Lux_STO_src = 0.0 return if calc_Lux_STO_src > calc_Lux_STO_lower: calc_Lux_STO_lower= max(dfr[dncol], calc_Lux_STO_lower) else: calc_Lux_STO_lower = dfr[dncol] calc_Lux_STO_src = dfr[source] return calc_Lux_STO_lower calc_lower(None, init=1) dtS[lowercol] = dtS.apply(calc_lower, axis = 1) def calc_trend(dfr, init=0): global calc_Lux_STO_trend global calc_Lux_STO_lower global calc_Lux_STO_upper if init == 1: calc_Lux_STO_trend = 0.0 calc_Lux_STO_lower = 0.0 calc_Lux_STO_upper = 0.0 return if dfr[source] > calc_Lux_STO_upper: calc_Lux_STO_trend = 1 elif dfr[source] < calc_Lux_STO_lower: calc_Lux_STO_trend = 0 calc_Lux_STO_upper = dfr[uppercol] calc_Lux_STO_lower = dfr[lowercol] return calc_Lux_STO_trend calc_trend(None, init=1) dtS[trendcol] = dtS.apply(calc_trend, axis = 1) dtS[sptcol] = dtS[trendcol] * dtS[lowercol] + (1-dtS[trendcol] ) * dtS[uppercol] dtS[osc1col] = (dtS[source] - dtS[sptcol]) / (dtS[uppercol] - dtS[lowercol]) dtS[osc2col] = np.where(dtS[osc1col] < 1, dtS[osc1col], 1 ) dtS[osccol] = np.where(dtS[osc2col] > -1, dtS[osc2col], -1) dtS[alphacol] = dtS[osccol].pow(2)/length def calc_ama(dfr, init=0): global calc_Lux_STO_ama if init == 1: calc_Lux_STO_ama = 0.0 return calc_Lux_STO_ama = calc_Lux_STO_ama + dfr[alphacol] * (dfr[osccol] - calc_Lux_STO_ama) return calc_Lux_STO_ama calc_ama(None, init=1) dtS[amacol] = dtS.apply(calc_ama, axis = 1) dtS[histcol] = ta.EMA((dtS[osccol]- dtS[amacol]),timeperiod = smooth) return dtS[osccol] * 100, dtS[amacol] * 100 , dtS[histcol] * 100, dtS[sptcol] class Github_viktors1982_trading__LuxOSC__20220718_143423(IStrategy): INTERFACE_VERSION = 2 # Buy hyperspace params: buy_params = { "cross_buy": -100, "length_buy": 6, "mult_buy": 9, "smooth_buy": 72, } # Sell hyperspace params: sell_params = { "cross_sell": 50, } length_buy = IntParameter(2, 100, default= int(buy_params['length_buy']), space='buy') mult_buy = IntParameter(2, 100, default= int(buy_params['mult_buy']), space='buy') smooth_buy = IntParameter(2, 100, default= int(buy_params['smooth_buy']), space='buy') cross_buy = IntParameter(-100, 100, default= int(buy_params['cross_buy']), space='buy') cross_sell = IntParameter(-100, 100, default= int(sell_params['cross_sell']), space='sell') stoploss = -0.99 # Trailing stoploss trailing_stop = False timeframe = '5m' custom_info = {} process_only_new_candles = False use_sell_signal = True sell_profit_only = False ignore_roi_if_buy_signal = False startup_candle_count: int = 30 # Optional order type mapping. order_types = { 'buy': 'limit', 'sell': 'limit', 'stoploss': 'market', 'stoploss_on_exchange': False } # Optional order time in force. order_time_in_force = { 'buy': 'gtc', 'sell': 'gtc' } plot_config = { # Main plot indicators (Moving averages, ...) 'main_plot': { 'supertrend': {'color': 'green'}, }, 'subplots': { # Subplots - each dict defines one additional plot "OSC": { 'osc': {'color': 'blue'}, 'signal': {'color': 'orange'}, 'histogram': {'color': 'green'}, } } } def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['osc'], dataframe['signal'] , dataframe['histogram'], dataframe['supertrend'] = LUX_SuperTrendOscillator(dataframe, length = int(self.length_buy.value), mult = int(self.mult_buy.value), smooth = int(self.smooth_buy.value)) return dataframe def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (qtpylib.crossed_above(dataframe['osc'], int(self.cross_buy.value))) & (dataframe['supertrend'] > dataframe['close'] ) & (dataframe['volume'] > 0) ), 'buy'] = 1 return dataframe def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (qtpylib.crossed_below(dataframe['osc'], int(self.cross_sell.value))) & (dataframe['volume'] > 0) ), 'sell'] = 1 return dataframe