#coding=utf-8
import talib as ta
import numpy as np
import pandas as pd
import kdj
import volume
import public
import ma


class Macd:

	__instance = None
	def __init__(self):
		pass

	@classmethod
	def getInstance(cls):
		if(cls.__instance == None):
			cls.__instance = Macd()
		return cls.__instance

	def myMACD(self, price, fastperiod=12, slowperiod=26, signalperiod=9):
		ewma12 = pd.ewma(price,span=fastperiod)
		ewma60 = pd.ewma(price,span=slowperiod)
		#ewma12 = ta.EMA(price, fastperiod)
		#ewma60 = ta.EMA(price, slowperiod)
		dif = ewma12-ewma60
		dea = pd.ewma(dif,span=signalperiod)
		bar = (dif-dea)*2
		return dif, dea, bar

	# 同花顺和通达信等软件中的MACD
	def MACD_CN(self, close, fastperiod, slowperiod, signalperiod) :
		dif, dea, macd = ta.MACDEXT(close, fastperiod=fastperiod, fastmatype=1, slowperiod=slowperiod, slowmatype=1, signalperiod=signalperiod, signalmatype=1)
		macd = macd * 2
		return dif, dea, macd 

	#设置macdgc gc：金叉 dc：死叉 R:最近的，A:历史所有
	def set_macd_data(self, df, type=1):
		if df is not None and df.shape[0] > 0:
			dif, dea, macd = self.myMACD(np.array(df['close']), fastperiod=12, slowperiod=26, signalperiod=9)
			#dif, dea, macd = self.MACD_CN(np.array(df['close']), fastperiod=12, slowperiod=26, signalperiod=9)
			df['dif']=pd.Series(dif,index=df.index)#DIFF
			df['dea']=pd.Series(dea,index=df.index)#DEA
			df['macd']=pd.Series(macd,index=df.index)#DIFF-DEA

			#计算macdgc、d_gc情况
			df['macd_cross'] = ''
			macd_position = df['dif'] > df['dea']
			df.loc[macd_position[(macd_position == True) & (macd_position.shift() == False)].index, 'macd_cross'] = 'gc'
			df.loc[macd_position[(macd_position == False) & (macd_position.shift() == True)].index, 'macd_cross'] = 'dc'
			#df.dropna(how='any', inplace=True)#删除所有空行值的数据
		return df

	#是否是叉
	def is_cross(self, df, index, crosstype='gc'):
		if index < 0 or index > df.shape[0]-1:
			return False
		cross_ret = {'gc':df.iloc[index]['macd_cross']=='gc', 'dc':df.iloc[index]['macd_cross']=='dc'}
		return cross_ret[crosstype]


#==============================================计算成功率=====================================

#macdgc平均涨幅，成功率
def macd_glodencross(df):
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(dflen):
		if df.iloc[i]['macd_cross'] == 'gc':
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macdgc放量平均涨幅，成功率
def macd_glodencross_volume(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and v.is_fangliang(df, i):#成交量放大:
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴上第一次gc平均涨幅，成功率
def macd_zeroup_first_glodencross(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	target = 0
	target2 = 0
	start = 0
	flag = False
	for i in xrange(0, dflen):
		if start == 0 and i+2<dflen \
				and df.iloc[i]['macd_cross'] == 'gc' \
				and df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] <= 1.5 and df.iloc[i]['dea'] > 0 \
				and df.iloc[i]['MA_60'] > df.iloc[i+1]['MA_60'] and df.iloc[i+1]['MA_60'] > df.iloc[i+2]['MA_60']:
			target = i
			start = 1
			continue
		if start == 1:
			if i - target >= 32 or df.iloc[i]['macd_cross'] == 'gc':
				start = 0
				continue
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i-target > 5:
				#target2 = i
				#if df.iloc[target]['close'] > df[target:target2]['high'].max():
				flag = True
			#if target2 != 0 and i-target2 < 21:
				#if df.iloc[i]['dif'] > 0:
					#start = 0
					#target2 = 0
					#flag = False
					#continue
			if flag:
				start = 0
				target2 = 0
				flag = False
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴上第一次gc放量平均涨幅，成功率
def macd_zeroup_first_glodencross_volume(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	if dflen < 30:
		return meettotalCount, meettotal 
	target = 0
	target2 = 0
	start = 0
	flag = False
	for i in xrange(0, dflen):
		if start == 0 and i+2<dflen \
				and df.iloc[i]['macd_cross'] == 'gc' \
				and df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] <= 1.5 and df.iloc[i]['dea'] > 0 \
				and df.iloc[i]['MA_60'] > df.iloc[i+1]['MA_60'] and df.iloc[i+1]['MA_60'] > df.iloc[i+2]['MA_60'] \
				and v.is_fangliang(df, i):
			target = i
			start = 1
			continue
		if start == 1:
			if i - target == 32 or df.iloc[i]['macd_cross'] == 'gc':
				start = 0
				continue
			if target2==0 and df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i-target > 5:
				target2 = i
				flag = True
			if target2 != 0 and i-target2 < 21:
				if df.iloc[i]['dea'] > 0:
					start = 0
					target2 = 0
					flag = False
					continue
			if flag:
				start = 0
				target2 = 0
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴上第一次gc平均涨幅，成功率
def macd_zeroup_first_glodencross_ma_duotou(df):
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	if dflen < 30:
		return meettotalCount, meettotal 
	target = 0
	start = 0
	for i in xrange(0, dflen):
		if start == 0 \
				and df.iloc[i]['macd_cross'] == 'gc' \
				and  df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] <= 1.5 and df.iloc[i]['dea'] > 0 \
				and df.iloc[i]['MA_5'] > df.iloc[i]['MA_10'] and df.iloc[i]['MA_10'] > df.iloc[i]['MA_30'] and df.iloc[i]['MA_30'] > df.iloc[i]['MA_60'] \
				and df.iloc[i]['MA_60'] > df.iloc[i+1]['MA_60']:
			target = i
			start = 1
			continue
		if start == 1:
			if i - target == 32 or df.iloc[i]['macd_cross'] == 'gc':
				start = 0
				continue
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i-target > 2:
				start = 0
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴上第一次gc平均涨幅，成功率
def macd_zeroup_first_glodencross_ma_duotou_volume(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	if dflen < 30:
		return meettotalCount, meettotal 
	target = 0
	start = 0
	for i in xrange(0, dflen):
		if start == 0 \
				and df.iloc[i]['macd_cross'] == 'gc' \
				and df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] <= 1.5 and df.iloc[i]['dea'] > 0 \
				and df.iloc[i]['MA_5'] > df.iloc[i]['MA_10'] and df.iloc[i]['MA_10'] > df.iloc[i]['MA_30'] and df.iloc[i]['MA_30'] > df.iloc[i]['MA_60'] \
				and df.iloc[i]['MA_60'] > df.iloc[i+1]['MA_60'] \
				and v.is_fangliang(df, i):
			target = i
			start = 1
			continue
		if start == 1:
			if i - target == 32 or df.iloc[i]['macd_cross'] == 'gc':
				start = 0
				continue
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i-target > 2:
				start = 0
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd dif首次突破零轴
def macd_dif_first_up_zero_succ(df):
	m_a = ma.Ma.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	target = 0
	start = 0
	for i in xrange(dflen):
		if start == 0 and i+1 < dflen \
				and df.iloc[i]['dif'] > 0 and df.iloc[i+1]['dif'] < 0 \
				and df.iloc[i]['macd'] > 0 \
				and df.iloc[i]['close'] > df.iloc[i]['MA_60']:
			target = i
			start = 1
			continue
		if start == 1:
			if m_a.ma_xielv(df, target, 'dif', 'up', 5) and m_a.ma_xielv(df, target, 'MA_60', 'down', 8):
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
			start = 0
	return meettotalCount, meettotal

#macd dif首次突破零轴
def macd_dif_first_up_zero_volume_succ(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	target = 0
	start = 0
	for i in xrange(0, dflen):
		if start == 0 and i+1 < dflen \
				and df.iloc[i]['dea'] > 0 and df.iloc[i+1]['dea'] < 0 \
				and df.iloc[i]['macd'] > 0 \
				and v.is_fangliang(df, i):
			target = i
			start = 1
			continue
		if start == 1:
			if i+1 >= dflen:
				break
			if df.iloc[i]['dea'] < df.iloc[i+1]['dea'] or df.iloc[i]['dif'] < df.iloc[i]['dea']:
				start = 0
				continue
			if i - target > 8:
				start = 0
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴下二次gc平均涨幅，成功率
def macd_zerodown_two_glodencross(df):
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	target = 0
	start = 0
	for i in xrange(0, dflen):
		if start == 0 and df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and df.iloc[i]['macd_cross'] == 'gc':
			target = i
			start = 1
			continue
		if start == 1:
			if (i-target) == 21 or df.iloc[i]['dif'] > 0 or df.iloc[i]['dea'] > 0:
				start = 0
				continue
			if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[target]['dif'] > df.iloc[i]['dif']\
					and df.iloc[target]['dea'] > df.iloc[i]['dea']:
				start = 0
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴下二次gc平均涨幅，成功率
def macd_zerodown_two_glodencross_volume(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()

	dflen = df.shape[0]
	target = 0
	start = 0
	for i in xrange(0, dflen):
		if start == 0 and df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and df.iloc[i]['macd_cross'] == 'gc':
			target = i
			start = 1
			continue
		if start == 1:
			if (i-target) == 21 or df.iloc[i]['dif'] > 0 or df.iloc[i]['dea'] > 0:
				target = 0
				start = 0
				continue
			if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[target]['dif'] > df.iloc[i]['dif']\
					and df.iloc[target]['dea'] > df.iloc[i]['dea'] and v.is_fangliang(df, i):
				target = 0
				start = 0
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴下gc平均涨幅，成功率
def macd_zerodown_glodencross(df):
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0:
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴下gc放量平均涨幅，成功率
def macd_zerodown_glodencross_volume(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[i]['dif'] < 0 and \
			df.iloc[i]['dea'] < 0 and v.is_fangliang(df, i): #成交量放大
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴上gc平均涨幅，成功率
def macd_zeroup_glodencross(df):
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[i]['dif'] >= 0 and df.iloc[i]['dea'] >= 0:
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴上gc放量平均涨幅，成功率
def macd_zeroup_glodencross_volume(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[i]['dif'] >= 0 and df.iloc[i]['dea'] >= 0 and \
				v.is_fangliang(df, i):#成交量放大:
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd kdjgc共振	
def macd_kdj_glodencross(df):
	k = kdj.Kdj.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and  k.is_cross(df, i, crosstype='gc'):
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd kdjgc共振放量
def macd_kdj_glodencross_volume(df):
	k = kdj.Kdj.getInstance()
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and k.is_cross(df, i, crosstype='gc') \
				and  v.is_fangliang(df, i):#成交量放大:
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0上 kdjgc共振	
def macd_zeroup_kdj_glodencross(df):
	k = kdj.Kdj.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[i]['dif'] >= 0 and \
						df.iloc[i]['dea'] >= 0 and k.is_cross(df, i, crosstype='gc'):
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd kdj gc共振放量
def macd_zeroup_kdj_glodencross_volume(df):
	k = kdj.Kdj.getInstance()
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc'and df.iloc[i]['dif'] >= 0 and \
						df.iloc[i]['dea'] >= 0 and k.is_cross(df, i, crosstype='gc') and v.is_fangliang(df, i):#成交量放大
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴下 kdjgc共振	
def macd_zerodown_kdj_glodencross(df):
	k = kdj.Kdj.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[i]['dif'] < 0 and \
						df.iloc[i]['dea'] < 0 and k.is_cross(df, i, crosstype='gc'):
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴下 kdjgc共振放量
def macd_zerodown_kdj_glodencross_volume(df):
	k = kdj.Kdj.getInstance()
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[i]['dif'] < 0 and \
						df.iloc[i]['dea'] < 0 and k.is_cross(df, i, crosstype='gc') and v.is_fangliang(df, i):#成交量放大:
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴附近gc平均涨幅，成功率
def macd_zeronear_glodencross(df):
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and  df.iloc[i]['dif'] < 0.06 and df.iloc[i]['dif'] > -0.05:
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd0轴附近gc放量平均涨幅，成功率
def macd_zeronear_glodencross_volume(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	for i in xrange(0, dflen):
		if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[i]['dif'] < 0.06 and \
						df.iloc[i]['dif'] > -0.05 and v.is_fangliang(df, i):#成交量放大
			meettotalCount = public.compute_succ_zf(df, i, meettotalCount, meettotal)
	return meettotalCount, meettotal

#macd高位二次gc平均涨幅，成功率
def macd_zeroup_two_glodencross(df, i, day, total):
	dflen = df.shape[0]
	if df.iloc[i]['dif'] > 0 and df.iloc[i]['dea'] > 0:
		for j in xrange(1, 22):
			if i+j < dflen:
				if df.iloc[i+j]['macd_cross'] == 'gc' and df.iloc[i+j]['dif'] > 0 and df.iloc[i+j]['dea'] > 0:
					total['totalCount'] += 1
					if (i - day) > -1:
						zf = ((df.iloc[i-day]['close'] - df.iloc[i]['close'])) / df.iloc[i]['close']*100
						total['totalRate'] += zf
						if df.iloc[i-day]['close'] > df.iloc[i]['close']:
							total['successCount'] += 1
					break

#macd高位二次gc放量平均涨幅，成功率
def macd_zeroup_two_glodencross_volume(df, i, day, total):
	dflen = df.shape[0]
	v = volume.Volume.getInstance()
	if df.iloc[i]['dif'] > 0 and df.iloc[i]['dea'] > 0:
		for j in xrange(1, 22):
			if i+j < dflen:
				if df.iloc[i+j]['macd_cross'] == 'gc' and df.iloc[i+j]['dif'] > 0 and df.iloc[i+j]['dea'] > 0:
					if v.is_fangliang(df, i):#成交量放大
						total['totalCount'] += 1
						if (i - day) > -1:
							zf = ((df.iloc[i-day]['close'] - df.iloc[i]['close'])) / df.iloc[i]['close']*100
							total['totalRate'] += zf
							if df.iloc[i-day]['close'] > df.iloc[i]['close']:
								total['successCount'] += 1
						break

#macd0轴附近二次gc平均涨幅，成功率
def macd_zeronear_two_glodencross(df, i, day, total):
	dflen = df.shape[0]
	if df.iloc[i]['dif'] < 0.06 and df.iloc[i]['dif'] > -0.05:
		for j in xrange(1, 14):
			if i+j < dflen:
				if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[i]['dif'] < 0.06 and df.iloc[i]['dif'] > -0.05:
					total['totalCount'] += 1
					if (i - day) > -1:
						zf = ((df.iloc[i-day]['close'] - df.iloc[i]['close'])) / df.iloc[i]['close']*100
						total['totalRate'] += zf
						if df.iloc[i-day]['close'] > df.iloc[i]['close']:
							total['successCount'] += 1
					break

#macd0轴附近二次gc放量平均涨幅，成功率
def macd_zeronear_two_glodencross_volume(df, i, day, total):
	dflen = df.shape[0]
	v = volume.Volume.getInstance()
	if df.iloc[i]['dif'] < 0.06 and df.iloc[i]['dif'] > -0.05:
		for j in xrange(1, 14):
			if i+j < dflen:
				if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[i]['dif'] < 0.06 and df.iloc[i]['dif'] > -0.05:
					if v.is_fangliang(df, i):#成交量放大
						total['totalCount'] += 1
						if (i - day) > -1:
							zf = ((df.iloc[i-day]['close'] - df.iloc[i]['close'])) / df.iloc[i]['close']*100
							total['totalRate'] += zf
							if df.iloc[i-day]['close'] > df.iloc[i]['close']:
								total['successCount'] += 1
						break

def macd_zeroup_redbar_decup_succ(df):
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	target = 0
	start = 0
	for i in xrange(0, dflen):
		if start == 0 and i+1 < dflen \
				and df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] <= 1.5 and df.iloc[i]['dea'] >= 0 \
				and df.iloc[i+1]['dif'] > 0 and df.iloc[i+1]['dea'] > 0 and df.iloc[i+1]['macd'] > 0 \
				and df.iloc[i]['macd'] > df.iloc[i+1]['macd']:
			target = i
			start = 1
			continue
		if start == 1:
			if i - target == 32:
				start = 0
				continue
			if i < (target+4) and (target+4) < dflen:
				if df.iloc[i]['macd'] < 0 or df.iloc[i+1]['macd'] < 0 or df.iloc[i]['macd'] > df.iloc[i+1]['macd']:
					start = 0
					continue
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i-target > 2:
				start = 0
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal

def macd_zeroup_redbar_decup_volume_succ(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	target = 0
	start = 0
	for i in xrange(0, dflen):
		if start == 0 and i+1 < dflen \
				and df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] <= 1.5 and df.iloc[i]['dea'] > 0 \
				and df.iloc[i+1]['dif'] > 0 and df.iloc[i+1]['dea'] > 0 \
				and df.iloc[i+1]['macd'] > 0 and df.iloc[i]['macd'] > df.iloc[i+1]['macd'] \
				and v.is_fangliang(df, i):
			target = i
			start = 1
			continue
		if start == 1:
			if i - target == 32:
				start = 0
				continue
			if i < (target+4) and (target+4) < dflen:
				if df.iloc[i]['macd'] < 0 or df.iloc[i+1]['macd'] < 0 or df.iloc[i]['macd'] > df.iloc[i+1]['macd']:
					start = 0
					continue
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i-target > 2:
				start = 0
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal

def macd_zeroup_redbar_decup_ma_duotou(df):
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	target = 0
	start = 0
	for i in xrange(0, dflen):
		if start == 0 and i+2 < dflen \
				and df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] <= 1.5 and df.iloc[i]['dea'] > 0 \
				and df.iloc[i+1]['dif'] > 0 and df.iloc[i+1]['dea'] > 0 and df.iloc[i+1]['macd'] > 0 and df.iloc[i]['macd'] > df.iloc[i+1]['macd'] \
				and df.iloc[i]['MA_5'] > df.iloc[i]['MA_10'] and df.iloc[i]['MA_10'] > df.iloc[i]['MA_30'] and df.iloc[i]['MA_30'] > df.iloc[i]['MA_60'] \
				and df.iloc[i]['MA_60'] >= df.iloc[i+1]['MA_60']:
			target = i
			start = 1
			continue
		if start == 1:
			if i - target == 32:
				start = 0
				continue
			if i < (target+4) and (target+4) < dflen:
				if df.iloc[i]['macd'] < 0 or df.iloc[i+1]['macd'] < 0 or df.iloc[i]['macd'] > df.iloc[i+1]['macd']:
					start = 0
					continue
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i-target > 2:
				start = 0
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal

def macd_zeroup_redbar_decup_ma_duotou_volume(df):
	v = volume.Volume.getInstance()
	meettotalCount, meettotal = public.init_succ_var()
	dflen = df.shape[0]
	target = 0
	start = 0
	for i in xrange(0, dflen):
		if start == 0 and i+1 < dflen \
				and df.iloc[i]['dif'] >= 0 and df.iloc[i]['dif'] <= 1.5 and df.iloc[i]['dea'] > 0 \
				and df.iloc[i+1]['dif'] > 0 and df.iloc[i+1]['dea'] > 0 and df.iloc[i+1]['macd'] > 0 and df.iloc[i]['macd'] > df.iloc[i+1]['macd'] \
				and df.iloc[i]['MA_5'] > df.iloc[i]['MA_10'] and df.iloc[i]['MA_10'] > df.iloc[i]['MA_30'] and df.iloc[i]['MA_30'] > df.iloc[i]['MA_60'] \
				and df.iloc[i]['MA_60'] >= df.iloc[i+1]['MA_60']\
				and v.is_fangliang(df, i):
			target = i
			start = 1
			continue
		if start == 1:
			if i - target == 32:
				start = 0
				continue
			if i < (target+4) and (target+4) < dflen:
				if df.iloc[i]['macd'] < 0 or df.iloc[i+1]['macd'] < 0 or df.iloc[i]['macd'] > df.iloc[i+1]['macd']:
					start = 0
					continue
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i-target > 2:
				start = 0
				meettotalCount = public.compute_succ_zf(df, target, meettotalCount, meettotal)
	return meettotalCount, meettotal


#=================================选股==========================================================
def macd_zeroup_first_gc(df, code):
	v = volume.Volume.getInstance()
	retcode = 0
	flag = False
	target = 0
	target2 = 0
	start = False
	dflen = df.shape[0]
	for i in xrange(dflen):
		if i==0 and i+2 < dflen \
				and df.iloc[i]['macd_cross'] == 'gc' \
				and df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] < 1.5 and df.iloc[i]['dea'] > 0 \
				and df.iloc[i]['MA_60'] > df.iloc[i+1]['MA_60'] and df.iloc[i+1]['MA_60'] > df.iloc[i+2]['MA_60']:
				#and v.is_fangliang(df, i) \
				#and df.iloc[i]['close'] > df.iloc[i]['open']:
			start = True
			target = i
			continue
		if start:
			if i-target == 32 or df.iloc[i]['macd_cross'] == 'gc':
				break
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i > 5:
				#target2 = i
				#if target2 != 0 and df[target2:target2+13][df[target2:target2+13]['dif']>0].shape[0] > 0:
					#break
				#if df.iloc[target]['high'] > df[1:target2]['high'].max():
				flag = True
			if flag:
				retcode = code
				break
	return retcode

def macd_zeroup_first_gc_volume(df, code):
	v = volume.Volume.getInstance()
	retcode = 0
	flag = False
	target = 0
	target2 = 0
	start = False
	dflen = df.shape[0]
	for i in xrange(dflen):
		if i==0 and i+2 < dflen \
				and df.iloc[i]['macd_cross'] == 'gc' \
				and df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] < 1.5 and df.iloc[i]['dea'] > 0 \
				and (df.iloc[i]['close']-df.iloc[i+1]['close'])/df.iloc[i+1]['close'] < 0.097 \
				and df.iloc[i]['MA_60'] > df.iloc[i+1]['MA_60'] and df.iloc[i+1]['MA_60'] > df.iloc[i+2]['MA_60'] \
				and v.is_fangliang(df, i):
			start = True
			target = i
			continue
		if start:
			if i-target == 32 or df.iloc[i]['macd_cross'] == 'gc':
				break
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i > 5:
				target2 = i
				flag = True
			if target2 != 0 and i - target2 < 13:
				if df.iloc[i]['dea'] > 0:
					break
			if flag:
				retcode = code
				break
	return retcode

def macd_zeroup_redbar_decup(df, code):
	retcode = 0
	flag = False
	dflen = df.shape[0]
	start = False
	target = 0
	target2 = 0
	for i in xrange(dflen):
		if i == 0 \
				and df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] < 1.5 and df.iloc[i]['dea'] > 0 \
				and df.iloc[i+1]['dif'] > 0 and df.iloc[i+1]['dea'] > 0 \
				and df.iloc[i]['macd'] > df.iloc[i+1]['macd'] \
				and (df.iloc[i]['close']-df.iloc[i+1]['close'])/df.iloc[i+1]['close'] < 0.097 \
				and df.iloc[i]['MA_60'] > df.iloc[i+1]['MA_60'] and df.iloc[i+1]['MA_60'] > df.iloc[i+2]['MA_60']:
			start = True
			target = i
			continue
		if start:
			if i-target == 32:
				break
			if i < 5:
				if df.iloc[i]['macd'] < 0 or df.iloc[i]['macd'] > df.iloc[i+1]['macd']:
					break
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i > 5:
				retcode = code
				target2 = i
				flag = True
			if target2 != 0 and i - target2 < 13:
				if df.iloc[i]['dea'] > 0:
					break
			if flag:
				retcode = code
				break
	return retcode

#macd dif首次突破零轴
def macd_dif_first_up_zero(df, code):
	m_a = ma.Ma.getInstance()
	retcode = 0
	if df.iloc[0]['dif'] > 0 and df.iloc[1]['dif'] < 0 \
	   and df.iloc[0]['macd'] > 0 \
	   and df.iloc[0]['close'] > df.iloc[0]['MA_60']:
		#if m_a.ma_xielv(df, 0, 'dif', 'up', 5) and m_a.ma_xielv(df, 0, 'MA_60', 'down', 21):
			retcode = code
	return retcode

def macd_zeroup_beaboutto_first_gc(df, code):
	retcode = 0
	dflen = df.shape[0]
	flag = False
	for i in xrange(0, 33):
		if i == 0 and df.iloc[i]['dif'] > 0 and df.iloc[i]['dif'] <= 1.5 and df.iloc[i]['dea'] > 0 and df.iloc[i]['macd'] < 0:
			flag = True
			continue
		if flag:
			if i >= dflen or df.iloc[i]['macd_cross'] == 'gc':
				break
			if i-1 < 5:
				if df.iloc[i-1]['macd'] < df.iloc[i]['macd'] or df.iloc[i-1]['macd'] > 0:
					break
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and i > 2:
				retcode = code
				break
	return retcode

def macd_zerodown_two_gc(df, code):
	dflen = df.shape[0]
	retcode = 0
	for i in xrange(0, 22):
		if i == 0 and df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0 and df.iloc[i]['macd_cross'] == 'gc':
			flag = True
		else:
			break
		if flag == True:
			if i > dflen or df.iloc[i]['dif'] > 0 or df.iloc[i]['dea'] > 0:
				break
			if df.iloc[i]['macd_cross'] == 'gc' and df.iloc[0]['dif'] > df.iloc[i]['dif']\
					and df.iloc[0]['dea'] > df.iloc[i]['dea']:
				retcode = code
				break
	return retcode

def macd_zerodown_gc(df, code, l):
	dflen = df.shape[0]
	i = 0
	if i < dflen and i+1 < dflen:
		if df.iloc[i]['macd_cross'] == 'gc' or df.iloc[i+1]['macd_cross'] == 'gc':
			if df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0:
				l.append(code)

def macd_zeroup_greenbar_dec(df, code, l):
	dflen = df.shape[0]
	if dflen > 1:
		if df.iloc[0]['dif'] > 0 and df.iloc[0]['dea'] > 0 and df.iloc[0]['macd'] > 0 and df.iloc[1]['macd'] < 0:
			flag = 1
			for i in xrange(0, 4):
				if i < dflen and i+1 < dflen:
					if df.iloc[i]['macd'] < df.iloc[i+1]['macd']:
						flag = 0
						break
				else:
					flag = 0
					break
			if flag == 1:
				l.append(code)

#macd底背离
def macd_dbl(df, code):
	retcode = 0
	dflen = df.shape[0]
	start = False
	target1 = 0
	target2 = 0
	target3 = 0
	target4 = 0
	for i in xrange(dflen):
		if i == 0 \
				and df.iloc[i]['macd_cross'] == 'gc' \
				and df.iloc[i]['dif'] < 0 and df.iloc[i]['dea'] < 0:
			start = True
			target1 = i
			continue
		if start:
			if target2 == 0 and df.iloc[i]['macd_cross'] == 'dc':
				target2 = i
				continue
			if df.iloc[i]['macd_cross'] == 'gc':
				target3 = i
				continue
			if df.iloc[i]['macd_cross'] == 'dc':
				target4 = i
				if df[target1:target2]['close'].min() > df[target3:target4]['close'].min() \
						or df[target1:target3][df[target1:target3]['dif']>0].shape[0] > 0:
					break
				if df[target1:target2]['dif'].min() > df[target3:target4]['dif'].min() \
						or df[target1:target2]['macd'].min() > df[target3:target4]['macd'].min():
					retcode = code
				break
	return retcode