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mirror of https://github.com/microsoft/qlib.git synced 2026-07-04 11:30:57 +08:00

fix OPDT_backtest bugs

This commit is contained in:
Mingzhe Han
2021-02-24 13:44:20 +08:00
parent 1f28044d84
commit e6dfccce2f
4 changed files with 12 additions and 13 deletions

View File

@@ -89,8 +89,8 @@ and finally start our OPD method.
python main.py --config=example/OPD/config.yml
```
### Citation
You are more than welcome to cite our paper:
## Citation
You are more than welcome to citetmu our paper:
```
@inproceedings{fang2021universal,
title={Universal Trading for Order Execution with Oracle Policy Distillation},

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@@ -71,24 +71,22 @@ class RuleObs(BaseObs):
if time == -1:
predictions += [0.0] * size
else:
predictions += df.iloc[size * time : size * (time + 1)].reshape(-1).tolist()
predictions += df[size * time : size * (time + 1)].reshape(-1).tolist()
elif feature["type"] == "daily":
predictions += df.reshape(-1)[:size].tolist()
elif feature["type"] == "range":
# if feature.startswith('oracle'):
# predictions += df.iloc[:, (time + 1) : size + (time + 1)].reshape(-1).tolist()
if time == -1:
predictions += [0.0] * size
else:
predictions += df.iloc[time : size + time].reshape(-1).tolist()
predictions += df[time : size + time].reshape(-1).tolist()
elif feature["type"] == "interval":
if len(df.iloc[interval * size : (interval + 1) * size].reshape(-1)) == size:
predictions += df.iloc[interval * size : (interval + 1) * size].reshape(-1).tolist()
if len(df[interval * size : (interval + 1) * size].reshape(-1)) == size:
predictions += df[interval * size : (interval + 1) * size].reshape(-1).tolist()
else:
predictions += [0.0] * size
elif feature["type"] == "step":
if len(df.iloc[size * (time + 1) : size * (time + 2)].reshape(-1)) == size:
predictions += df.iloc[size * (time + 1) : size * (time + 2)].reshape(-1).tolist()
if len(df[size * (time + 1) : size * (time + 2)].reshape(-1)) == size:
predictions += df[size * (time + 1) : size * (time + 2)].reshape(-1).tolist()
else:
predictions += [0.0] * size

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@@ -52,7 +52,7 @@ def w_order(f, start, end):
all_path = os.path.join(data_path, "order/all/")
if not os.path.exists(all_path):
os.makedirs(all_path)
order_test.to_pickle(all_path + f[:-9] + '.target')
order.to_pickle(all_path + f[:-9] + '.target')
return 0
res = Parallel(n_jobs=64)(delayed(w_order)(f, 0, 239) for f in os.listdir(in_dir))

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@@ -6,13 +6,14 @@ feature_path = os.path.join(data_path, 'feature/teacher/')
if not os.path.exists(feature_path):
os.makedirs(feature_path)
log_file = os.path.join(os.environ.get('OUTPUT_DIR'),'example/OPDT_b/0/test/')
log_file = os.path.join(os.environ.get('OUTPUT_DIR'),'example/OPDT_b/test/')
files = os.listdir(log_file)
for f in files:
if f.endswith(".log"):
df = pd.read_pickle(log_file + f)
df['datetime'] = df.index.get_level_values(1).map(lambda x: x[1])
#df['datetime'] = df.index.get_level_values(1).map(lambda x: x[1])
df['datetime'] = df.index.get_level_values(1)
df.set_index('datetime', append=True, drop=True, inplace=True)
action = df['action']
action = action.reset_index(level=1, drop=True)