from datetime import timedelta
from pandas import DataFrame
from ChanEnum import Chan_FX_TYPE, Chan_KLINE_DIR, Chan_BI_DIR, Chan_SEG_DIR, Chan_ZS_DIR, Chan_BSP_DIR, Chan_BSP_TYPE, Chan_KLC_FX, Chan_MACD_STATE, Chan_PRICE_TREND, Chan_KLU_PATTERN
from ChanKLU import ChanKLU
from ChanKLC import ChanKLC
from ChanBI import ChanBI
from ChanSBI import ChanSBI
from ChanSEG import ChanSEG
from ChanZS import ChanZS
from ChanBSP import ChanBSP
import talib.abstract as ta
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, date2num
import matplotlib.patches as patches
from technical.util import resample_to_interval
from decimal import Decimal
import xgboost as xgb
import numpy as np
from ChanMACD import ChanMACD
from TF_DF import TF_DF

class ChanLun():
	def __init__(self):
		self.time3m = 3
		self.time5m = 5
		self.time10m = 10
		self.time15m = 15
		self.time30m = 30
		self.time_m_intervals = [3, 5, 10, 15, 30]
		self.time_m_symbols = ['3m', '5m', '10m', '15m', '30m']
		self.time2h = 2*60
		self.time4h = 4*60
		self.time6h = 6*60
		self.time8h = 8*60
		self.time12h = 12*60
		self.time16h = 16*60
		self.time_h_intervals = [2*60, 4*60, 6*60, 8*60, 12*60, 16*60]
		self.time_h_symbols = ['2h', '4h', '6h', '8h', '12h', '16h']
		self.time2d = 2*24*60
		self.time3d = 3*24*60
		self.time1w = 7*24*60
		self.time2w = 14*24*60
		self.time_d_intervals = [2*24*60, 3*24*60, 7*24*60, 14*24*60]
		self.time_d_symbols	 = ['2d', '3d', '1w', '2w']
		self.time2M = 2*30*24*60
		self.time3M = 3*30*24*60
		self.time6M = 6*30*24*60
		self.time1y = 12*30*24*60
		self.time_M_intervals = [2*30*24*60, 3*30*24*60, 6*30*24*60, 12*30*24*60]
		self.time_M_symbols	 = ['2M', '3M', '6M', '1y']
		self.time_symbols = ['1m', '3m', '5m', '10m', '15m', '30m', '1h', '2h', '4h', '6h', '8h', '12h', '16h', '1d', '2d', '3d', '1w', '2w', '1M', '3M', '6M', '1y']
		self.tf_df_dict = {}
		self.ema_symbols = ['1m', '3m', '5m', '10m', '15m', '30m', '1h', '2h', '4h', '6h', '8h', '12h', '16h', '1d', '2d', '3d']
		self.tf_df = TF_DF()
	def init_data(self, dataframe, intervals, timeframes):
		for index in range(0, len(intervals)):
			timeframe = timeframes[index]
			interval = intervals[index]
			self.tf_df_dict[timeframe] = TF_DF(dataframe, interval, timeframe)
	def init_dataframes(self, dataframe_m, dataframe_h, dataframe_d, dataframe_M):
		self.tf_df_dict['1m'] = TF_DF(dataframe_m, 1, '1m')
		self.init_data(dataframe_m, self.time_m_intervals, self.time_m_symbols)
		self.tf_df_dict['1h'] = TF_DF(dataframe_h, 1, '1h')
		self.init_data(dataframe_h, self.time_h_intervals, self.time_h_symbols)
		self.tf_df_dict['1d'] = TF_DF(dataframe_d, 1, '1d')
		self.init_data(dataframe_d, self.time_d_intervals, self.time_d_symbols)
		self.tf_df_dict['1M'] = TF_DF(dataframe_M, 1, '1M')
		self.init_data(dataframe_M, self.time_M_intervals, self.time_M_symbols)
	def get_ema52_dict(self):
		if len(self.tf_df_dict) > 0:
			return {key: self.tf_df_dict[key].get_ema52() for key in self.ema_symbols}
		return None
	def get_ema24_dict(self):
		if len(self.tf_df_dict) > 0:
			return {key: self.tf_df_dict[key].get_ema24() for key in self.ema_symbols}
		return None
	def get_current_klc_dict(self):
		if len(self.tf_df_dict) > 0:
			return {key: self.tf_df_dict[key].get_current_klc() for key in self.ema_symbols}
		return None
	
 
 
 
 
 	# TF_DF methods ------------------------------------------
	def get_klu_state(self, dataframe):
		return self.tf_df.get_klu_state(dataframe)
	def check_fx(self, klc):
		return self.tf_df.check_fx(klc)
	def add_indicators1(self, df):
		return self.tf_df.add_indicators(df)
	def get_bi_list(self, dataframe):
		return self.tf_df.get_bi_list(dataframe)
	def get_kl_data(self, dataframe:DataFrame):
		return self.tf_df.cal_kl_data(dataframe)
	def cal_volume_ratio(self, dataframe, window=10):
		return self.tf_df.cal_volume_ratio(dataframe, window)
	def calculate_zs(self, bi_list, seg_list):
		return self.get_zs_list(bi_list, seg_list)
	def get_seg_list(self, bi_list):
		return self.tf_df.get_seg_list(bi_list)
	def cal_trend(self, klc_list):
		return self.tf_df.cal_trend(klc_list)
	def check_top_fx(self, last_bottom, klc):
		return self.tf_df.check_top_fx(last_bottom, klc)
	def check_bottom_fx(self, last_top, klc):
		return self.tf_df.check_bottom_fx(last_top, klc)
	def cal_bi_list(self, klc_list):
		return self.tf_df.cal_bi_list(klc_list)
	def get_zs_list(self, bi_list, seg_list):
		return self.tf_df.get_zs_list(bi_list, seg_list)
	def cal_bi_zs(self, seg_list):
		return self.tf_df.cal_bi_zs(seg_list)
	def get_decimal(self, value):
		return Decimal("{:.2f}".format(value))
	def get_klc_list(self, klu_list):
		return self.tf_df.get_klc_list(klu_list)
	def get_klu_list(self, dataframe):
		return self.tf_df.cal_klu_pattern(self.get_kl_data(dataframe))