Mariner Backtesting - TA-LIB Vector Arithmetic Substraction

SUB

 real = SUB(high, low)

Plot

$Vector Arithmetic Substraction$

Working Example

 from cloudquant.interfaces import Strategy
from collections import OrderedDict
import ktgfunc
import talib

class WE_SUB(Strategy):

    def on_start(self, md, order, service, account):
        # symbol and timestamp
        print(self.symbol + ":  " + service.time_to_string(service.system_time))
        daily_bars = md.bar.daily(start=-100)
        high = daily_bars.high
        low = daily_bars.low
        real = talib.SUB(high, low)

        # get the date values
        dates = service._context.market._storage.market_hours.keys()
        dateList = []
        for date in dates:
           dateList.append(str(date.strftime('%Y-%m-%d')))
        dates = sorted(dateList, reverse=True)[1:101]
        dates.sort()

        dict = OrderedDict()
        dict['date'] = dates
        dict['high'] = high
        dict['low'] = low
        dict['real'] = real
        symbol = 'SUB: ' + self.symbol
        print ktgfunc.talib_table(symbol, 1, dict)

Console

MSFT:  2017-02-09 09:30:00.000000

SUB: MSFT
	Input	Output
date	high	low	real
2016-09-16	57.24	56.37	0.87
2016-09-19	57.36	56.47	0.89
2016-09-20	56.97	56.37	0.60
2016-09-21	57.46	56.70	0.76
2016-09-22	57.61	57.24	0.37
2016-09-23	57.52	56.99	0.53
2016-09-26	56.76	56.45	0.31
2016-09-27	57.67	56.30	1.37
2016-09-28	57.67	57.28	0.39
2016-09-29	57.78	56.83	0.95
2016-09-30	57.38	56.96	0.43
2016-10-03	57.16	56.68	0.49
2016-10-04	57.21	56.59	0.62
2016-10-05	57.57	56.88	0.70
2016-10-06	57.47	56.90	0.58
2016-10-07	57.59	57.03	0.56
2016-10-10	58.00	57.48	0.52
2016-10-11	57.63	56.51	1.12
2016-10-12	56.89	56.02	0.86
2016-10-13	56.92	55.94	0.98
2016-10-14	57.35	56.74	0.62
2016-10-17	57.07	56.49	0.59
2016-10-18	57.56	57.02	0.53
2016-10-19	57.45	57.01	0.44
2016-10-20	57.13	56.28	0.85
2016-10-21	60.04	59.09	0.96
2016-10-24	60.59	59.53	1.06
2016-10-25	60.96	60.39	0.57
2016-10-26	60.79	60.06	0.73
2016-10-27	60.42	59.69	0.74
2016-10-28	60.11	59.18	0.93
2016-10-31	60.01	59.52	0.50
2016-11-01	59.62	58.85	0.76
2016-11-02	59.53	58.90	0.63
2016-11-03	59.24	58.71	0.53
2016-11-04	58.88	58.13	0.75
2016-11-07	60.11	59.38	0.74
2016-11-08	60.37	59.75	0.63
2016-11-09	60.18	58.80	1.38
2016-11-10	60.08	57.24	2.84
2016-11-11	58.72	57.62	1.10
2016-11-14	58.68	56.90	1.79
2016-11-15	59.49	58.31	1.18
2016-11-16	59.66	54.27	5.39
2016-11-17	60.95	59.97	0.99
2016-11-18	61.14	60.30	0.84
2016-11-21	60.97	60.42	0.55
2016-11-22	61.26	60.81	0.45
2016-11-23	61.10	60.25	0.85
2016-11-25	60.53	60.13	0.40
2016-11-28	61.02	60.21	0.81
2016-11-29	61.41	60.52	0.89
2016-11-30	61.18	60.22	0.97
2016-12-01	60.15	58.94	1.22
2016-12-02	59.47	58.80	0.67
2016-12-05	60.58	59.56	1.02
2016-12-06	60.46	59.80	0.66
2016-12-07	61.38	59.80	1.58
2016-12-08	61.58	60.84	0.74
2016-12-09	61.99	61.12	0.87
2016-12-12	62.30	61.72	0.58
2016-12-13	63.42	62.24	1.18
2016-12-14	63.45	62.53	0.92
2016-12-15	63.15	62.30	0.85
2016-12-16	62.95	62.12	0.83
2016-12-19	63.77	62.42	1.35
2016-12-20	63.80	63.03	0.77
2016-12-21	63.70	63.12	0.58
2016-12-22	64.10	63.40	0.69
2016-12-23	63.54	62.80	0.74
2016-12-27	64.07	63.21	0.86
2016-12-28	63.40	62.83	0.57
2016-12-29	63.20	62.73	0.47
2016-12-30	62.99	62.03	0.96
2017-01-03	62.84	62.12	0.72
2017-01-04	62.75	62.12	0.63
2017-01-05	62.66	62.03	0.63
2017-01-06	63.15	62.04	1.11
2017-01-09	63.08	62.54	0.54
2017-01-10	63.07	62.28	0.79
2017-01-11	63.23	62.43	0.80
2017-01-12	63.40	61.95	1.45
2017-01-13	62.87	62.35	0.52
2017-01-17	62.70	62.03	0.67
2017-01-18	62.70	62.12	0.58
2017-01-19	62.98	62.19	0.78
2017-01-20	62.82	62.37	0.45
2017-01-23	63.12	62.57	0.55
2017-01-24	63.74	62.94	0.80
2017-01-25	64.10	63.45	0.65
2017-01-26	64.54	63.55	0.99
2017-01-27	65.91	64.89	1.02
2017-01-30	65.79	64.80	0.99
2017-01-31	65.15	64.26	0.89
2017-02-01	64.62	63.47	1.15
2017-02-02	63.41	62.75	0.66
2017-02-03	63.70	63.07	0.63
2017-02-06	63.65	63.14	0.51
2017-02-07	63.78	63.23	0.55
2017-02-08	63.81	63.22	0.59