# source: https://raw.githubusercontent.com/markvdeursen/freqrade-strategies/1268af050e6aa3688b58cded1d6aa3e51ac3626c/ichimoku_strategy.py
from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
from technical.indicators import ichimoku

import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib

class Github_markvdeursen_freqrade_strategies__ichimoku_strategy__20240211_102906(IStrategy):
    """
    Github_markvdeursen_freqrade_strategies__ichimoku_strategy__20240211_102906 Strategy
    """

    minimal_roi = {
        "90": 0.04,
        "60": 0.05,
        "30": 0.06
    }

    # Optimal timeframe for the strategy
    timeframe = '5m'

    # trailing stoploss
    stoploss = -0.015
    trailing_stop = True
    trailing_stop_positive = 0.01
    trailing_stop_positive_offset = 0.02
    trailing_only_offset_is_reached = True

    # run "populate_indicators" only for new candle
    ta_on_candle = False

    # Experimental settings (configuration will overide these if set)
    use_exit_signal = True
    exit_profit_only = True
    ignore_roi_if_buy_signal = False

    # Optional order type mapping
    order_types = {
        'buy': 'limit',
        'sell': 'limit',
        'stoploss': 'market',
        'stoploss_on_exchange': False
    }

    plot_config = {
        'main_plot': {
            'senkou_a': {'color': 'green'},
            'senkou_b': {'color': 'red'},
            'tenkan': {'color': 'orange'},
            'kijun': {'color': 'blue'},
        },
        'subplots': {
            "Moving Avarages": {
            },
            "RSI": {
                'rsi': {'color': 'red'},
            }
        }
    }

    def informative_pairs(self):
        """
        """

        # return [(f"{self.config['stake_currency']}/USDT", self.timeframe)]
        return []

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        """

        ichi = ichimoku(dataframe)
        dataframe['tenkan'] = ichi['tenkan_sen']
        dataframe['kijun'] = ichi['kijun_sen']
        dataframe['senkou_a'] = ichi['senkou_span_a']
        dataframe['senkou_b'] = ichi['senkou_span_b']
        dataframe['cloud_green'] = ichi['cloud_green']
        dataframe['cloud_red'] = ichi['cloud_red']
        dataframe['cloud'] = dataframe['senkou_a'] - dataframe['senkou_b']

        return dataframe

    # Implementeer de koop- en verkooplogica
    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        (dataframe['close'] > dataframe['senkou_a']) &
        
        
        """
        # Fine-tune de kooplogica voor Bitcoin
        dataframe.loc[
            (dataframe['tenkan'] > dataframe['kijun']) & # Tekan-sen (Conversion line) boven Kijun-sen (Base line)
            (dataframe['close'] > dataframe['cloud_green']) & # Boven de cloud
            (dataframe['close'] > dataframe['senkou_a']) &
            (dataframe['volume'] > dataframe['volume'].rolling(window=20).mean()),  # Koop als het volume boven het gemiddelde ligt
            'enter_long'
        ] = 1

        # Plot een groene driehoek voor koopbeslissingen
        dataframe.loc[dataframe['enter_long'] == 1, 'buy_marker'] = dataframe['close']
        
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # Fine-tune de verkooplogica voor Bitcoin
        dataframe.loc[
            (dataframe['tenkan'] < dataframe['kijun']) &
            (dataframe['close'] < dataframe['cloud']) &
            (dataframe['close'] < dataframe['senkou_a']) &
            (dataframe['volume'] > dataframe['volume'].rolling(window=20).mean()),  # Verkoop als het volume boven het gemiddelde ligt
            'exit_long'
        ] = 1

        # Plot een rode driehoek voor verkoopbeslissingen
        dataframe.loc[dataframe['exit_long'] == 1, 'sell_marker'] = dataframe['close']
        
        return dataframe

    # def populate_sell_trend_short(self, dataframe, metadata):
    #     dataframe.loc[dataframe['sell_signal'] == 1, 'sell_marker_short'] = dataframe['close']
    #     dataframe.loc[dataframe['tenkan'] < dataframe['kijun'], 'tenkan_sen_short'] = dataframe['tenkan']
    #     dataframe.loc[dataframe['kijun_sen'] < dataframe['tenkan_sen'], 'kijun_sen_short'] = dataframe['kijun']
    #     dataframe.loc[dataframe['senkou_a'] < dataframe['senkou_b'], 'senkou_span_a_short'] = dataframe['senkou_a']
    #     dataframe.loc[dataframe['senkou_b'] < dataframe['senkou_a'], 'senkou_span_b_short'] = dataframe['senkou_b']
    #     dataframe.loc[dataframe['cloud'] < 0, 'cloud_top_short'] = dataframe['senkou_a']
    #     dataframe.loc[dataframe['cloud'] < 0, 'cloud_bottom_short'] = dataframe['senkou_b']

    #     return dataframe