liuyu/qlib
1
0
Fork 0
mirror of https://github.com/microsoft/qlib.git synced 2026-06-30 09:31:18 +08:00
Code Activity

modify tests.config.py

Browse Source
This commit is contained in:
lzh222333
2021-06-01 09:40:53 +00:00
parent 231bdf8608
commit 8d05cd2daf
3 changed files with 138 additions and 26 deletions
Download Patch File Download Diff File Expand all files Collapse all files

64
examples/online_srv/online_management_simulate.py
View File

@@ -5,6 +5,7 @@
This example is about how can simulate the OnlineManager based on rolling tasks.
"""
from pprint import pprint
import fire
import qlib
from qlib.model.trainer import DelayTrainerR, DelayTrainerRM, TrainerR, TrainerRM
@@ -13,7 +14,63 @@ from qlib.workflow.online.manager import OnlineManager
from qlib.workflow.online.strategy import RollingStrategy
from qlib.workflow.task.gen import RollingGen
from qlib.workflow.task.manage import TaskManager
from qlib.tests.config import CSI100_RECORD_LGB_TASK_CONFIG, CSI100_RECORD_XGBOOST_TASK_CONFIG
from qlib.tests.config import CSI100_RECORD_LGB_TASK_CONFIG_ONLINE, CSI100_RECORD_XGBOOST_TASK_CONFIG_ONLINE
data_handler_config = {
"start_time": "2018-01-01",
"end_time": "2018-10-31",
"fit_start_time": "2018-01-01",
"fit_end_time": "2018-03-31",
"instruments": "csi100",
}
dataset_config = {
"class": "DatasetH",
"module_path": "qlib.data.dataset",
"kwargs": {
"handler": {
"class": "Alpha158",
"module_path": "qlib.contrib.data.handler",
"kwargs": data_handler_config,
},
"segments": {
"train": ("2018-01-01", "2018-03-31"),
"valid": ("2018-04-01", "2018-05-31"),
"test": ("2018-06-01", "2018-09-10"),
},
},
}
record_config = [
{
"class": "SignalRecord",
"module_path": "qlib.workflow.record_temp",
},
{
"class": "SigAnaRecord",
"module_path": "qlib.workflow.record_temp",
},
]
# use lgb model
task_lgb_config = {
"model": {
"class": "LGBModel",
"module_path": "qlib.contrib.model.gbdt",
},
"dataset": dataset_config,
"record": record_config,
}
# use xgboost model
task_xgboost_config = {
"model": {
"class": "XGBModel",
"module_path": "qlib.contrib.model.xgboost",
},
"dataset": dataset_config,
"record": record_config,
}
class OnlineSimulationExample:
@@ -46,7 +103,10 @@ class OnlineSimulationExample:
tasks (dict or list[dict]): a set of the task config waiting for rolling and training
"""
if tasks is None:
tasks = [CSI100_RECORD_XGBOOST_TASK_CONFIG, CSI100_RECORD_LGB_TASK_CONFIG]
#tasks = [CSI100_RECORD_XGBOOST_TASK_CONFIG_ONLINE, CSI100_RECORD_LGB_TASK_CONFIG_ONLINE]
tasks = [task_xgboost_config, task_lgb_config]
#pprint(CSI100_RECORD_XGBOOST_TASK_CONFIG_ONLINE)
#pprint(task_xgboost_config)
self.exp_name = exp_name
self.task_pool = task_pool
self.start_time = start_time

6
examples/online_srv/rolling_online_management.py
View File

@@ -18,7 +18,7 @@ from qlib.workflow import R
from qlib.workflow.online.strategy import RollingStrategy
from qlib.workflow.task.gen import RollingGen
from qlib.workflow.online.manager import OnlineManager
from qlib.tests.config import CSI100_RECORD_XGBOOST_TASK_CONFIG, CSI100_RECORD_LGB_TASK_CONFIG
from qlib.tests.config import CSI100_RECORD_XGBOOST_TASK_CONFIG_ROLLING, CSI100_RECORD_LGB_TASK_CONFIG_ROLLING
class RollingOnlineExample:
@@ -34,9 +34,9 @@ class RollingOnlineExample:
add_tasks=None,
):
if add_tasks is None:
add_tasks = [CSI100_RECORD_LGB_TASK_CONFIG]
add_tasks = [CSI100_RECORD_LGB_TASK_CONFIG_ROLLING]
if tasks is None:
tasks = [CSI100_RECORD_XGBOOST_TASK_CONFIG]
tasks = [CSI100_RECORD_XGBOOST_TASK_CONFIG_ROLLING]
mongo_conf = {
"task_url": task_url, # your MongoDB url
"task_db_name": task_db_name, # database name

94
qlib/tests/config.py
View File

@@ -43,17 +43,29 @@ RECORD_CONFIG = [
]
def get_data_handler_config(market=CSI300_MARKET):
def get_data_handler_config(
start_time="2008-01-01",
end_time="2020-08-01",
fit_start_time="2008-01-01",
fit_end_time="2014-12-31",
instruments=CSI300_MARKET,
):
return {
"start_time": "2008-01-01",
"end_time": "2020-08-01",
"fit_start_time": "2008-01-01",
"fit_end_time": "2014-12-31",
"instruments": market,
"start_time": start_time,
"end_time": end_time,
"fit_start_time": fit_start_time,
"fit_end_time": fit_end_time,
"instruments": instruments,
}
def get_dataset_config(market=CSI300_MARKET, dataset_class=DATASET_ALPHA158_CLASS):
def get_dataset_config(
dataset_class=DATASET_ALPHA158_CLASS,
train=("2008-01-01", "2014-12-31"),
valid=("2015-01-01", "2016-12-31"),
test=("2017-01-01", "2020-08-01"),
handler_kwargs={"instruments": CSI300_MARKET},
):
return {
"class": "DatasetH",
"module_path": "qlib.data.dataset",
@@ -61,48 +73,88 @@ def get_dataset_config(market=CSI300_MARKET, dataset_class=DATASET_ALPHA158_CLAS
"handler": {
"class": dataset_class,
"module_path": "qlib.contrib.data.handler",
"kwargs": get_data_handler_config(market),
"kwargs": get_data_handler_config(**handler_kwargs),
},
"segments": {
"train": ("2008-01-01", "2014-12-31"),
"valid": ("2015-01-01", "2016-12-31"),
"test": ("2017-01-01", "2020-08-01"),
"train": train,
"valid": valid,
"test": test,
},
},
}
def get_gbdt_task(market=CSI300_MARKET):
def get_gbdt_task(dataset_kwargs={}, handler_kwargs={"instruments": CSI300_MARKET}):
return {
"model": GBDT_MODEL,
"dataset": get_dataset_config(market),
"dataset": get_dataset_config(**dataset_kwargs, handler_kwargs=handler_kwargs),
}
def get_record_lgb_config(market=CSI300_MARKET):
def get_record_lgb_config(dataset_kwargs={}, handler_kwargs={"instruments": CSI300_MARKET}):
return {
"model": {
"class": "LGBModel",
"module_path": "qlib.contrib.model.gbdt",
},
"dataset": get_dataset_config(market),
"dataset": get_dataset_config(**dataset_kwargs, handler_kwargs=handler_kwargs),
"record": RECORD_CONFIG,
}
def get_record_xgboost_config(market=CSI300_MARKET):
def get_record_xgboost_config(dataset_kwargs={}, handler_kwargs={"instruments": CSI300_MARKET}):
return {
"model": {
"class": "XGBModel",
"module_path": "qlib.contrib.model.xgboost",
},
"dataset": get_dataset_config(market),
"dataset": get_dataset_config(**dataset_kwargs, handler_kwargs=handler_kwargs),
"record": RECORD_CONFIG,
}
CSI300_DATASET_CONFIG = get_dataset_config(market=CSI300_MARKET)
CSI300_GBDT_TASK = get_gbdt_task(market=CSI300_MARKET)
CSI300_DATASET_CONFIG = get_dataset_config(handler_kwargs={"instruments": CSI300_MARKET})
CSI300_GBDT_TASK = get_gbdt_task(handler_kwargs={"instruments": CSI300_MARKET})
CSI100_RECORD_XGBOOST_TASK_CONFIG = get_record_xgboost_config(market=CSI100_MARKET)
CSI100_RECORD_LGB_TASK_CONFIG = get_record_lgb_config(market=CSI100_MARKET)
CSI100_RECORD_XGBOOST_TASK_CONFIG = get_record_xgboost_config(handler_kwargs={"instruments": CSI100_MARKET})
CSI100_RECORD_LGB_TASK_CONFIG = get_record_lgb_config(handler_kwargs={"instruments": CSI100_MARKET})
# use for rolling_online_managment.py
ROLLING_HANDLER_CONFIG = {
"start_time": "2013-01-01",
"end_time": "2020-09-25",
"fit_start_time": "2013-01-01",
"fit_end_time": "2014-12-31",
"instruments": CSI100_MARKET,
}
ROLLING_DATASET_CONFIG = {
"train": ("2013-01-01", "2014-12-31"),
"valid": ("2015-01-01", "2015-12-31"),
"test": ("2016-01-01", "2020-07-10"),
}
CSI100_RECORD_XGBOOST_TASK_CONFIG_ROLLING = get_record_xgboost_config(
dataset_kwargs=ROLLING_DATASET_CONFIG, handler_kwargs=ROLLING_HANDLER_CONFIG
)
CSI100_RECORD_LGB_TASK_CONFIG_ROLLING = get_record_lgb_config(
dataset_kwargs=ROLLING_DATASET_CONFIG, handler_kwargs=ROLLING_HANDLER_CONFIG
)
# use for online_management_simulate.py
ONLINE_HANDLER_CONFIG = {
"start_time": "2018-01-01",
"end_time": "2018-10-31",
"fit_start_time": "2018-01-01",
"fit_end_time": "2018-03-31",
"instruments": CSI100_MARKET,
}
ONLINE_DATASET_CONFIG = {
"train": ("2018-01-01", "2018-03-31"),
"valid": ("2018-04-01", "2018-05-31"),
"test": ("2018-06-01", "2018-09-10"),
}
CSI100_RECORD_XGBOOST_TASK_CONFIG_ONLINE = get_record_xgboost_config(
dataset_kwargs=ONLINE_DATASET_CONFIG, handler_kwargs=ONLINE_HANDLER_CONFIG
)
CSI100_RECORD_LGB_TASK_CONFIG_ONLINE = get_record_lgb_config(
dataset_kwargs=ONLINE_DATASET_CONFIG, handler_kwargs=ONLINE_HANDLER_CONFIG
)