def QA_util_time_gap(time, gap, methods, type_):
'分钟线回测的时候的gap'
min_len = int(240 / int(str(type_).split('min')[0]))
day_gap = math.ceil(gap / min_len)
if methods in ['>', 'gt']:
data = pd.concat([pd.DataFrame(QA_util_make_min_index(day, type_)) for day in trade_date_sse[trade_date_sse.index(str(datetime.datetime.strptime(
time, '%Y-%m-%d %H:%M:%S').date())):trade_date_sse.index(str(datetime.datetime.strptime(time, '%Y-%m-%d %H:%M:%S').date())) + day_gap+1]]).reset_index()
return np.asarray(data[data[0] > time].head(gap)[0].apply(lambda x: str(x))).tolist()[-1]
elif methods in ['>=', 'gte']:
data = pd.concat([pd.DataFrame(QA_util_make_min_index(day, type_)) for day in trade_date_sse[trade_date_sse.index(str(datetime.datetime.strptime(
time, '%Y-%m-%d %H:%M:%S').date())):trade_date_sse.index(str(datetime.datetime.strptime(time, '%Y-%m-%d %H:%M:%S').date())) + day_gap+1]]).reset_index()
return np.asarray(data[data[0] >= time].head(gap)[0].apply(lambda x: str(x))).tolist()[-1]
elif methods in ['<', 'lt']:
data = pd.concat([pd.DataFrame(QA_util_make_min_index(day, type_)) for day in trade_date_sse[trade_date_sse.index(str(datetime.datetime.strptime(
time, '%Y-%m-%d %H:%M:%S').date())) - day_gap:trade_date_sse.index(str(datetime.datetime.strptime(time, '%Y-%m-%d %H:%M:%S').date()))+1]]).reset_index()
return np.asarray(data[data[0] < time].tail(gap)[0].apply(lambda x: str(x))).tolist()[0]
elif methods in ['<=', 'lte']:
data = pd.concat([pd.DataFrame(QA_util_make_min_index(day, type_)) for day in trade_date_sse[trade_date_sse.index(str(datetime.datetime.strptime(
time, '%Y-%m-%d %H:%M:%S').date())) - day_gap:trade_date_sse.index(str(datetime.datetime.strptime(time, '%Y-%m-%d %H:%M:%S').date()))+1]]).reset_index()
return np.asarray(data[data[0] <= time].tail(gap)[0].apply(lambda x: str(x))).tolist()[0]
elif methods in ['==', '=', 'eq']:
return time
def QA_util_time_gap(time, gap, methods, type_):
"""
explanation:
分钟线回测的时候的gap, 按交易日往前往后推
params:
* time ->
含义:时间
类型:int
参数支持: []
* gap ->
含义: gap
类型:float
参数支持: []
* methods ->
含义:方向
类型:str
参数支持: [">", "gt",">=", "gte", "<", "lt", "<=", "lte"]
* type_ ->
含义: 周期
类型: str
参数支持: ["xmin"]
"""
min_len = int(240 / int(str(type_).split('min')[0]))
day_gap = math.ceil(gap / min_len)
if methods in ['>', 'gt']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
):trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + day_gap + 1]
]
).reset_index()
return np.asarray(
data[data[0] > time].head(gap)[0].apply(lambda x: str(x))
).tolist()[-1]
elif methods in ['>=', 'gte']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
):trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + day_gap + 1]
]
).reset_index()
return np.asarray(
data[data[0] >= time].head(gap)[0].apply(lambda x: str(x))
).tolist()[-1]
elif methods in ['<', 'lt']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) - day_gap:trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + 1]
]
).reset_index()
return np.asarray(
data[data[0] < time].tail(gap)[0].apply(lambda x: str(x))
).tolist()[0]
elif methods in ['<=', 'lte']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
type_))
for day in trade_date_sse[trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) - day_gap:trade_date_sse.index(
str(
datetime.datetime.strptime(time,
'%Y-%m-%d %H:%M:%S').date()
)
) + 1]
]
).reset_index()
return np.asarray(
data[data[0] <= time].tail(gap)[0].apply(lambda x: str(x))
).tolist()[0]
elif methods in ['==', '=', 'eq']:
return time