qmt-python/STOA.py at main · cloudsthere/qmt-python · GitHub

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#coding:gbk

import numpy as np
import pandas
import math
import time
import datetime

def init(ContextInfo):
	ContextInfo.stock = ContextInfo.stockcode + '.' + ContextInfo.market
	ContextInfo.set_universe([ContextInfo.stock])
	ContextInfo.month = '00'
	ContextInfo.STOA = 0.0


def handlebar(ContextInfo):
	try:
		d = ContextInfo.barpos
		lastdate = timetag_to_datetime(ContextInfo.get_bar_timetag(d - 1), '%Y%m%d')
		date = timetag_to_datetime(ContextInfo.get_bar_timetag(d), '%Y%m%d')
		time_region = str(get_days_before_lastdate(date, 35*12))
		vt_list = ContextInfo.get_market_data(fields=['volume'],stock_code=[ContextInfo.stock],start_time=time_region,end_time=date)
		vt_list_index_reverse = vt_list.index.tolist()
		vt_list_index_reverse.reverse()
		vt_list_array = [vt_list['volume'][vt_list_index_reverse[k]] for k in range(252)]
		circulating_capital_frame = ContextInfo.get_financial_data(['CAPITALSTRUCTURE.circulating_capital'], [ContextInfo.stock],time_region,date)
		cc_list_index_reverse = circulating_capital_frame.index.tolist()
		cc_list_index_reverse.reverse()
		cc_list_array = [circulating_capital_frame['circulating_capital'][cc_list_index_reverse[k]] for k in range(252)]
		total_stom = 0.0
		for i in range(12):
			d_index = d-i*21
			per_date = timetag_to_datetime(ContextInfo.get_bar_timetag(d_index), '%Y%m%d')
			per_stom = get_STOM(ContextInfo,  vt_list_array[i*21:(i+1)*21], cc_list_array[i*21:(i+1)*21])
			total_stom += math.exp(per_stom)
			print("total_stom_i", i, total_stom)
		ContextInfo.STOA = math.log(float(total_stom/12))
	except:
		pass
	ContextInfo.paint('STOA', ContextInfo.STOA, -1, 0)

def get_STOM(ContextInfo, vt_list_one=[], cc_list_one=[]):
	stom_total = 0.0
	for i in range(21):
		if cc_list_one[i] :
			stom_total += float(vt_list_one[i] / cc_list_one[i])
	return stom_total


def get_days_before_lastdate(lastdate, n=0):
	'''
	date format = "YYYY-MM-DD HH:MM:SS"
	'''
	last_date = datetime.datetime.strptime(lastdate, '%Y%m%d')
	if(n<0):
		return datetime.datetime(now.year, now.month, now.day, now.hour, now.minute, now.second)
	else:
		n_days_before = last_date - datetime.timedelta(days=n)
	return datetime.datetime(n_days_before.year, n_days_before.month, n_days_before.day).strftime('%Y%m%d')