def print_yr_summary(datafile):
data = f.filter_thisyr(
f.load_candles(datafile))
samplesizes = f.get_sample_sizes(
f.get_interday_summary(data, f.classify_month))
bearbull = f.get_bearbull_summary(data)
for bb in f.BEARBULL_KEYS:
print("**** {key} ****".format(key=bb))
f.print_complete_summary(bearbull.get(bb, []), [f.Summaries.MONTHS], samplesizes)
if __name__ == '__main__':
logging.basicConfig(filename="/tmp/retracement.log",
filemode='w',
format='%(asctime)s,%(msecs)d %(name)s %(levelname)s' +
'%(message)s line:%(lineno)d',
datefmt='%H:%M:%S',
level=logging.DEBUG)
# years = [2016, 2017, 2018]
years = [2018]
# ltf data
datafile_ltf = sys.argv[1]
data_ltf = f.filter(f.load_candles(datafile_ltf), f.filter_year, years)
# day data
datafile_d = sys.argv[2]
data_d = weekday(f.filter(f.load_candles(datafile_d), f.filter_year,
years))
# profile bearish days
beardates = dates(f.filter(data_d, f.filter_bearish, True)) # , False)
bearbuckets = retracement(f.BearBull.BEARISH, data_ltf, beardates)
print_buckets(bearbuckets)
# profile bullish days
bulldates = dates(f.filter(data_d, f.filter_bullish, True)) # , False)
bullbuckets = retracement(f.BearBull.BULLISH, data_ltf, bulldates)
print_buckets(bullbuckets)
item1 = item
continue
delta = abs(item1.close - item.close)
day = item.time.weekday()
print(item.high, item.low)
price, cnt = buckets.get(day, (0., 0))
price += delta
cnt += 1
buckets[day] = (price, cnt)
for day in buckets:
price, cnt = buckets[day]
ave = price / cnt
buckets[day] = (price, cnt, ave)
return buckets
if __name__ == '__main__':
# years = [2013, 2014, 2015, 2016, 2017, 2018]
years = [2018]
# data
datafile = sys.argv[1]
data = f.filter(f.load_candles(datafile), f.filter_year, years)
print(process(data))
self.wick_item = item
elif self.wick_high and high < self.wick_high - DELTA or self.wick_low and low + DELTA:
self.store_result(success)
wick_success += 1
return (wick_success, success), (wick_fails, fails)
if __name__ == '__main__':
logging.basicConfig(
filename="/tmp/rangebreaks.log",
filemode='w',
format='%(asctime)s,%(msecs)d %(name)s %(levelname)s' +
'%(message)s line:%(lineno)d',
datefmt='%H:%M:%S',
level=logging.DEBUG)
# years = [2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018]
years = [2018]
# day data
datafile = sys.argv[1]
data = f.filter(
f.load_candles(datafile),
f.filter_year,
years)
(wick_success, success), (wick_fails, fails) = Wicks().process(data)
print(wick_success)
print(wick_fails)
low_ = None
data_idx += 1
return within, total
if __name__ == '__main__':
logging.basicConfig(
filename="/tmp/rangebreaks.log",
filemode='w',
format='%(asctime)s,%(msecs)d %(name)s %(levelname)s' +
'%(message)s line:%(lineno)d',
datefmt='%H:%M:%S',
level=logging.DEBUG)
years = [2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018]
# years = [2018]
# day data
datafile_d = sys.argv[1]
data_d = f.filter(
f.load_candles(datafile_d),
f.filter_year,
years)
within, total = rangebreaks(data_d)
pc = within * 100.0 / total
print("Ranges maintained: {within}/{total}, {pc:.2f}%".format(
within=within, total=total, pc=pc))
elif trend_m == f.BearBull.BULLISH and item.low < bull_low:
low = bull_low = item.low
elif trend_m == f.BearBull.BEARISH and item.high > high:
high = item.high
elif trend_m == f.BearBull.BULLISH and item.low < low:
low = item.low
if dayofweek == 'Friday':
close = item.close
bear_pc = (bear_high_cnt * 100.) / bear_cnt if bear_cnt else 100
bear_result = "BEARISH WEEKS: M-T/ HIGH: {num}/{tot} {pc:.2f}%".format(
num=bear_high_cnt, tot=bear_cnt, pc=bear_pc)
print(bear_result)
bull_pc = (bull_low_cnt * 100.) / bull_cnt if bull_cnt else 100
bull_result = "BULLISH WEEKS: M-T/ LOW: {num}/{tot} {pc:.2f}%".format(
num=bull_low_cnt, tot=bull_cnt, pc=bull_pc)
print(bull_result)
if __name__ == '__main__':
data = f.filter(
f.load_candles(sys.argv[1]),
f.filter_year,
#[2013, 2014, 2015, 2016, 2017, 2018])
[2018])
week_highlow(data, False)
period=period, pair=pair),
filemode='w',
format='%(asctime)s,%(msecs)d %(name)s %(levelname)s' +
'%(message)s line:%(lineno)d',
datefmt='%H:%M:%S',
level=logging.DEBUG)
# years = [2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018]
#
# years = [2018]
years = [2013, 2014, 2015, 2016, 2017, 2018]
# data
data = f.filter(
f.load_candles(datafile_p),
f.filter_year,
years)
# # day data
# if period == '1_D':
# data_d = data
# else:
# data_d = f.filter(
# f.load_candles(datafile_d),
# f.filter_year,
# years)
# emas, emal = Touches.ema(data_d)
emas = emal = None
winners_max = 0