def _prepare_calender_cache(self):
"""preload the calendar for cache"""
# This code used the copy-on-write feature of Linux to avoid calculating the calendar multiple times in the subprocess
# This code may accelerate, but may be not useful on Windows and Mac Os
Cal.calendar(freq="1min")
get_calendar_day(freq="1min")
},
}
"""initialize qlib"""
# use yahoo_cn_1min data
QLIB_INIT_CONFIG = {**HIGH_FREQ_CONFIG, **SPEC_CONF}
print(QLIB_INIT_CONFIG)
provider_uri = QLIB_INIT_CONFIG.get("provider_uri")
if not exists_qlib_data(provider_uri):
print(f"Qlib data is not found in {provider_uri}")
GetData().qlib_data(target_dir=provider_uri,
interval="1min",
region=REG_CN)
qlib.init(**QLIB_INIT_CONFIG)
Cal.calendar(freq="1min")
get_calendar_day(freq="1min")
# get data
dataset = init_instance_by_config(task["dataset"])
xtrain, xtest = dataset.prepare(["train", "test"])
print(xtrain, xtest)
xtrain.to_csv("xtrain.csv")
dataset_backtest = init_instance_by_config(task["dataset_backtest"])
backtest_train, backtest_test = dataset_backtest.prepare(["train", "test"])
print(backtest_train, backtest_test)
# model initialization
model = init_instance_by_config(task["model"])
dataset = init_instance_by_config(task["dataset"])