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Published
20 hours ago •
microsoft
microsoft
Fix: QlibDataLoader drops the cols added by inst_processor
Fix: QlibDataLoader drops the cols added by inst_processor
Description
When inst_processor creates new columns, the QlibDataLoader drops them.
Motivation and Context
How Has This Been Tested?
- [ ] Pass the test by running:
pytest qlib/tests/test_all_pipeline.pyunder upper directory ofqlib. - [ ] If you are adding a new feature, test on your own test scripts.
Screenshots of Test Results (if appropriate):
- Pipeline test:
- Your own tests:
Types of changes
- [ X] Fix bugs
- [ ] Add new feature
- [ ] Update documentation
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-- Thanks.
Xu Li, Shanghai, China
@xu-li Could you please add any tests for it? (It fails in previous version and success in current version)
Thanks.
The test pipeline seems to be broken already on Mac. See the output below. I am on 6295939346bfe619fe6eef5ffbe7c9252c3c9b09.
Am I doing something wrong?
% git rev-parse HEAD
6295939346bfe619fe6eef5ffbe7c9252c3c9b09
% pytest tests/test_all_pipeline.py
================================================================================================= test session starts ==================================================================================================
platform darwin -- Python 3.8.16, pytest-7.2.1, pluggy-1.0.0
rootdir: /XXXXXX/tests, configfile: pytest.ini
collected 3 items
tests/test_all_pipeline.py .F. [100%]
======================================================================================================= FAILURES =======================================================================================================
_____________________________________________________________________________________________ TestAllFlow.test_1_backtest ______________________________________________________________________________________________
self = <test_all_pipeline.TestAllFlow testMethod=test_1_backtest>
@pytest.mark.slow
def test_1_backtest(self):
analyze_df = backtest_analysis(TestAllFlow.PRED_SCORE, TestAllFlow.RID, self.URI_PATH)
> self.assertGreaterEqual(
analyze_df.loc(axis=0)["excess_return_with_cost", "annualized_return"].values[0],
0.05,
"backtest failed",
)
E AssertionError: -0.09994674991447777 not greater than or equal to 0.05 : backtest failed
tests/test_all_pipeline.py:166: AssertionError
------------------------------------------------------------------------------------------------- Captured stdout call -------------------------------------------------------------------------------------------------
'The following are analysis results of benchmark return(1day).'
risk
mean 0.000477
std 0.012295
annualized_return 0.113561
information_ratio 0.598699
max_drawdown -0.370479
'The following are analysis results of the excess return without cost(1day).'
risk
mean -0.000417
std 0.012286
annualized_return -0.099245
information_ratio -0.523614
max_drawdown -0.503287
'The following are analysis results of the excess return with cost(1day).'
risk
mean -0.000420
std 0.012286
annualized_return -0.099947
information_ratio -0.527307
max_drawdown -0.503838
'The following are analysis results of indicators(1day).'
value
ffr 1.0
pa 0.0
pos 0.0
risk
excess_return_without_cost mean -0.000417
std 0.012286
annualized_return -0.099245
information_ratio -0.523614
max_drawdown -0.503287
excess_return_with_cost mean -0.000420
std 0.012286
annualized_return -0.099947
information_ratio -0.527307
max_drawdown -0.503838
------------------------------------------------------------------------------------------------- Captured stderr call -------------------------------------------------------------------------------------------------
[73260:MainThread](2023-02-06 20:06:05,082) INFO - qlib.timer - [log.py:128] - Time cost: 71.856s | Loading data Done
[73260:MainThread](2023-02-06 20:06:06,395) INFO - qlib.timer - [log.py:128] - Time cost: 0.359s | DropnaLabel Done
[73260:MainThread](2023-02-06 20:06:10,730) INFO - qlib.timer - [log.py:128] - Time cost: 4.335s | CSZScoreNorm Done
[73260:MainThread](2023-02-06 20:06:10,759) INFO - qlib.timer - [log.py:128] - Time cost: 5.677s | fit & process data Done
[73260:MainThread](2023-02-06 20:06:10,760) INFO - qlib.timer - [log.py:128] - Time cost: 77.534s | Init data Done
[73260:MainThread](2023-02-06 20:06:10,789) INFO - qlib.backtest caller - [__init__.py:93] - Create new exchange
[73260:MainThread](2023-02-06 20:06:39,242) WARNING - qlib.online operator - [exchange.py:219] - $close field data contains nan.
[73260:MainThread](2023-02-06 20:06:39,244) WARNING - qlib.online operator - [exchange.py:219] - $close field data contains nan.
[73260:MainThread](2023-02-06 20:06:39,247) WARNING - qlib.online operator - [exchange.py:226] - factor.day.bin file not exists or factor contains `nan`. Order using adjusted_price.
[73260:MainThread](2023-02-06 20:06:39,247) WARNING - qlib.online operator - [exchange.py:228] - trade unit 100 is not supported in adjusted_price mode.
[73260:MainThread](2023-02-06 20:06:44,264) WARNING - qlib.BaseExecutor - [executor.py:121] - `common_infra` is not set for <qlib.backtest.executor.SimulatorExecutor object at 0x141f05160>
backtest loop: 100%|██████████| 871/871 [00:10<00:00, 82.92it/s]
[73260:MainThread](2023-02-06 20:06:55,254) INFO - qlib.workflow - [record_temp.py:505] - Portfolio analysis record 'port_analysis_1day.pkl' has been saved as the artifact of the Experiment 1
[73260:MainThread](2023-02-06 20:06:55,272) INFO - qlib.workflow - [record_temp.py:530] - Indicator analysis record 'indicator_analysis_1day.pkl' has been saved as the artifact of the Experiment 1
This is the bug that I am trying to fix:
import pandas as pd
import qlib
from qlib.data import D
from qlib.data.inst_processor import InstProcessor
qlib.init()
class MyInstProcessor(InstProcessor):
def __init__(self) -> None:
super().__init__()
def __call__(self, df: pd.DataFrame, instrument, *args, **kwargs):
if df.empty:
return df
df['MyNewFeature'] = 1
return df
df = D.features(['SH601216'], ['$close'], start_time='2020-05-01', end_time='2020-05-10',
inst_processors=[MyInstProcessor()])
# Before fix:
# $close
# instrument datetime
# SH601216 2020-05-06 1.318379
# 2020-05-07 1.304631
# 2020-05-08 1.309334
# After fix:
# $close MyNewFeature
# instrument datetime
# SH601216 2020-05-06 1.318379 1
# 2020-05-07 1.304631 1
# 2020-05-08 1.309334 1
print(df)
from qlib.data.dataset.loader import QlibDataLoader
qdl_config = {
'feature': (['$close'], ['Close']),
'label': (['$close / Ref($close, 10)'], ['RET10'])
}
qdl = QlibDataLoader(config=qdl_config, inst_processor={'feature': [MyInstProcessor()]})
df = qdl.load(instruments=['sh600519'], start_time='20190101', end_time='20190105')
# Before fix:
# feature label
# Close RET10
# datetime instrument
# 2019-01-02 sh600519 72.881897 1.014326
# 2019-01-03 sh600519 71.789268 0.998409
# 2019-01-04 sh600519 73.249367 1.041884
# After fix:
# feature label
# Close MyNewFeature RET10
# datetime instrument
# 2019-01-02 sh600519 72.881897 1 1.014326
# 2019-01-03 sh600519 71.789268 1 0.998409
# 2019-01-04 sh600519 73.249367 1 1.041884
print(df)
