def weekday(data):
return f.filter(data, f.filter_weekday)
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))
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))
def profile_range(trend, data, narrow):
range = profile_range_(data)
print_range(trend, "NORMAL", range)
range_narrow = profile_range_(data, narrow)
print_range(trend, "NARROW", range_narrow)
if __name__ == '__main__':
years = [2013, 2014, 2015, 2016, 2017, 2018]
# years = [2018]
# hour data
datafile_hr = sys.argv[1]
data_hr = f.filter(f.load_candles(datafile_hr), f.filter_year, years)
data_narrow = narrow_range(data_hr) # narrow_asian_range(data_hr)
# day data
datafile_d = sys.argv[2]
data_d = weekday(f.filter(f.load_candles(datafile_d), f.filter_year,
years))
# profile bearish days
beardata = f.filter(data_d, f.filter_bearish, False) # , False)
profile_range("BEARISH", beardata, data_narrow)
# profile bullish days
bulldata = f.filter(data_d, f.filter_bullish, False) # , False)
profile_range("BULLISH:", bulldata, data_narrow)
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)