def collectKPattherAndShowChart():
from earnmi.data.SWImpl import SWImpl
from vnpy.trader.constant import Exchange
from vnpy.trader.constant import Interval
sw = SWImpl()
lists = sw.getSW2List()
start = datetime(2014, 5, 1)
end = datetime(2020, 8, 17)
bars = []
limitSize = 0
chart = Chart()
for code in lists:
# for code in lists:
barList = sw.getSW2Daily(code, start, end)
indicator = Indicator(40)
preBar = None
yestodayIsMatch = False
for i in range(0, len(barList)):
bar = barList[i]
indicator.update_bar(bar)
patternValue = KPattern.encode1KAgo1(indicator)
todayIsMatch = 9 == patternValue
if todayIsMatch:
if indicator.count > 20:
chart.show(
indicator.makeBars(),
savefig=f"imgs/collectKPattherAndShowChart_{limitSize}"
)
limitSize += 1
if (limitSize > 50):
break
pass
if yestodayIsMatch:
pass
preBar = bar
yestodayIsMatch = todayIsMatch
if (limitSize > 50):
break
pass
def printKPatterMoreDetail(kPatters=[
6, 3, 17, 81, 7, 5, 4, 82, 159, 16, 28, 83, 15, 84, 18, 27, 93, 104, 158,
92, 160, 236, 157, 94, 85, 80, 14, 8, 161, 9, 29, 170, 26, 19, 38, 2, 79
]):
from earnmi.data.SWImpl import SWImpl
from vnpy.trader.constant import Exchange
from vnpy.trader.constant import Interval
sw = SWImpl()
lists = sw.getSW2List()
start = datetime(2014, 5, 1)
end = datetime(2020, 8, 17)
pct_split = [-7, -5, -3, -1.5, -0.5, 0.5, 1.5, 3, 5, 7]
pct_split = [-7, -5, -3, -1.0, 0, 1, 3, 5, 7]
pct_split = [-0.5, 0.5]
pctEncoder = FloatEncoder(pct_split)
kPattersMap = {}
for value in kPatters:
kPattersMap[value] = True
class InnerData(object):
kValue: int ##
sell_disbute = np.zeros(pctEncoder.mask()) ##卖方力量分布情况
buy_disbute = np.zeros(pctEncoder.mask()) #买方力量分布情况
pass
dataSet = {}
occurDayMap = {}
allTrayDay = 1
for code in lists:
# for code in lists:
barList = sw.getSW2Daily(code, start, end)
indicator = Indicator(40)
preBar = None
previousIsMatch = False
previousPatternVaule = None
allTrayDay = max(allTrayDay, len(barList))
for i in range(0, len(barList)):
bar = barList[i]
indicator.update_bar(bar)
patternValue = KPattern.encode1KAgo1(indicator)
todayIsMatch = False
if not patternValue is None:
todayIsMatch = kPattersMap.__contains__(patternValue)
if todayIsMatch:
dayKey = bar.datetime.year * 13 * 35 + bar.datetime.month * 13 + bar.datetime.day
occurDayMap[dayKey] = True
pass
if previousIsMatch:
innerData: InnerData = dataSet.get(previousIsMatch)
if innerData is None:
innerData = InnerData()
innerData.kValue = previousIsMatch
dataSet[previousPatternVaule] = innerData
sell_pct = 100 * ((bar.high_price + bar.close_price) / 2 -
preBar.close_price) / preBar.close_price
buy_pct = 100 * ((bar.low_price + bar.close_price) / 2 -
preBar.close_price) / preBar.close_price
innerData.buy_disbute[pctEncoder.encode(buy_pct)] += 1
innerData.sell_disbute[pctEncoder.encode(sell_pct)] += 1
pass
preBar = bar
previousIsMatch = todayIsMatch
previousPatternVaule = patternValue
print(f"所有交易日中，有意义的k线形态出现占比：%.2f%%" %
(100 * len(occurDayMap) / allTrayDay))
for kValue, dataItem in dataSet.items():
total_count1 = 0
total_count2 = 0
for cnt in dataItem.sell_disbute:
total_count1 += cnt
for cnt in dataItem.buy_disbute:
total_count2 += cnt
assert total_count1 == total_count2
assert total_count1 > 0
print(f"\n\nk:%6d, " % (kValue))
print(f" 卖方价格分布：")
for encode in range(0, len(dataItem.sell_disbute)):
occurtRate = 100 * dataItem.sell_disbute[encode] / total_count1
print(f" {pctEncoder.descriptEncdoe(encode)}：%.2f%%" %
(occurtRate))
print(f" 买方价格分布：")
for encode in range(0, len(dataItem.buy_disbute)):
occurtRate = 100 * dataItem.buy_disbute[encode] / total_count1
print(f" {pctEncoder.descriptEncdoe(encode)}：%.2f%%" %
(occurtRate))
pass
def compute_SW_KEncode_data():
from earnmi.data.SWImpl import SWImpl
sw = SWImpl()
lists = sw.getSW2List()
start = datetime(2014, 5, 1)
end = datetime(2020, 8, 17)
dataSet = {}
total_count = 0
occurKPattenDayMap = {}
kBarListTotalDay = 0
for code in lists:
#for code in lists:
barList = sw.getSW2Daily(code, start, end)
indicator = Indicator(40)
preBar = None
kBarListTotalDay = len(barList)
for bar in barList:
##先识别形态
kEncodeValue = KPattern.encode1KAgo1(indicator)
if kEncodeValue is None:
indicator.update_bar(bar)
preBar = bar
continue
total_count += 1
dataItem: CountItem = None
if dataSet.__contains__(kEncodeValue):
dataItem = dataSet[kEncodeValue]
else:
dataItem = CountItem()
dataSet[kEncodeValue] = dataItem
##第二天的收益
pct = ((bar.high_price + bar.close_price) / 2 -
preBar.close_price) / preBar.close_price
##收录当前形态
#dataItem.values.append(value)
dataItem.count_total += 1
dataItem.pct_total += pct
if pct > 0.000001:
dataItem.count_earn += 1
dataItem.pct_earn += pct
indicator.update_bar(bar)
preBar = bar
occurDayKey = preBar.datetime.year * 13 * 35 + preBar.datetime.month * 35 + preBar.datetime.day
occurKPattenDayMap[occurDayKey] = True
##打印当前形态
occur_count = 0
print(f"总共分析{total_count}个形态，识别出{len(dataSet)}个形态，有意义的形态有：")
max_succ_rate = 0
min_succ_rate = 100
ret_list = []
for key, dataItem in dataSet.items():
success_rate = 100 * dataItem.count_earn / dataItem.count_total
if dataItem.count_total < 500:
continue
if abs(int(success_rate - 50)) < 10:
continue
ret_list.append(key)
earn_pct = 100 * dataItem.pct_earn / dataItem.count_earn
if success_rate < 50:
earn_pct = 100 * (dataItem.pct_total - dataItem.pct_earn) / (
dataItem.count_total - dataItem.count_earn)
avg_pct = 100 * dataItem.pct_total / dataItem.count_total
occur_count += dataItem.count_total
occur_rate = 100 * dataItem.count_total / total_count
max_succ_rate = max(success_rate, max_succ_rate)
min_succ_rate = min(success_rate, min_succ_rate)
print(
f"{key}： total={dataItem.count_total},suc=%.2f%%,occur_rate=%.2f%%,earn_pct:%.2f%%,avg_pct:%.2f%%)"
% (success_rate, occur_rate, earn_pct, avg_pct))
total_occur_rate = 100 * occur_count / total_count
total_occur_in_day_rate = 100 * len(
occurKPattenDayMap) / kBarListTotalDay ##在所有交易日中，k线形态日出占比：
print(f"总共：occur_rate=%.2f%%, min_succ_rate=%.2f%%, max_succ_rate=%.2f%%"
f"\n所有交易日中，k线形态日出占比：%.2f%%" %
(total_occur_rate, min_succ_rate, max_succ_rate,
total_occur_in_day_rate))
print(f"{ret_list}")