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from unittest.case import TestCase
import unittest
import pandas as pd
import numpy as np
from datetime import datetime
from qlib import init
from qlib.config import C
from qlib.log import TimeInspector
from qlib.constant import REG_CN, REG_US, REG_TW
from qlib.utils.time import cal_sam_minute as cal_sam_minute_new, get_min_cal, CN_TIME, US_TIME, TW_TIME
from qlib.utils.data import guess_horizon
REG_MAP = {REG_CN: CN_TIME, REG_US: US_TIME, REG_TW: TW_TIME}
def cal_sam_minute(x: pd.Timestamp, sam_minutes: int, region: str):
"""
Sample raw calendar into calendar with sam_minutes freq, shift represents the shift minute the market time
- open time of stock market is [9:30 - shift*pd.Timedelta(minutes=1)]
- mid close time of stock market is [11:29 - shift*pd.Timedelta(minutes=1)]
- mid open time of stock market is [13:00 - shift*pd.Timedelta(minutes=1)]
- close time of stock market is [14:59 - shift*pd.Timedelta(minutes=1)]
"""
# TODO: actually, this version is much faster when no cache or optimization
day_time = pd.Timestamp(x.date())
shift = C.min_data_shift
region_time = REG_MAP[region]
open_time = (
day_time
+ pd.Timedelta(hours=region_time[0].hour, minutes=region_time[0].minute)
- shift * pd.Timedelta(minutes=1)
)
close_time = (
day_time
+ pd.Timedelta(hours=region_time[-1].hour, minutes=region_time[-1].minute)
- shift * pd.Timedelta(minutes=1)
)
if region_time == CN_TIME:
mid_close_time = (
day_time
+ pd.Timedelta(hours=region_time[1].hour, minutes=region_time[1].minute - 1)
- shift * pd.Timedelta(minutes=1)
)
mid_open_time = (
day_time
+ pd.Timedelta(hours=region_time[2].hour, minutes=region_time[2].minute)
- shift * pd.Timedelta(minutes=1)
)
else:
mid_close_time = close_time
mid_open_time = open_time
if open_time <= x <= mid_close_time:
minute_index = (x - open_time).seconds // 60
elif mid_open_time <= x <= close_time:
minute_index = (x - mid_open_time).seconds // 60 + 120
else:
raise ValueError("datetime of calendar is out of range")
minute_index = minute_index // sam_minutes * sam_minutes
if 0 <= minute_index < 120 or region_time != CN_TIME:
return open_time + minute_index * pd.Timedelta(minutes=1)
elif 120 <= minute_index < 240:
return mid_open_time + (minute_index - 120) * pd.Timedelta(minutes=1)
else:
raise ValueError("calendar minute_index error, check `min_data_shift` in qlib.config.C")
class TimeUtils(TestCase):
@classmethod
def setUpClass(cls):
init()
def test_cal_sam_minute(self):
# test the correctness of the code
random_n = 1000
regions = [REG_CN, REG_US, REG_TW]
def gen_args(cal: List):
for time in np.random.choice(cal, size=random_n, replace=True):
sam_minutes = np.random.choice([1, 2, 3, 4, 5, 6])
dt = pd.Timestamp(
datetime(
2021,
month=3,
day=3,
hour=time.hour,
minute=time.minute,
second=time.second,
microsecond=time.microsecond,
)
)
args = dt, sam_minutes
yield args
for region in regions:
cal_time = get_min_cal(region=region)
for args in gen_args(cal_time):
assert cal_sam_minute(*args, region) == cal_sam_minute_new(*args, region=region)
# test the performance of the code
args_l = list(gen_args(cal_time))
with TimeInspector.logt():
for args in args_l:
cal_sam_minute(*args, region=region)
with TimeInspector.logt():
for args in args_l:
cal_sam_minute_new(*args, region=region)
class DataUtils(TestCase):
@classmethod
def setUpClass(cls):
init()
def test_guess_horizon(self):
label = ["Ref($close, -2) / Ref($close, -1) - 1"]
result = guess_horizon(label)
assert result == 2
label = ["Ref($close, -5) / Ref($close, -1) - 1"]
result = guess_horizon(label)
assert result == 5
label = ["Ref($close, -1) / Ref($close, -1) - 1"]
result = guess_horizon(label)
assert result == 1
if __name__ == "__main__":
unittest.main()
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