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qlib/examples/trade/teacher_feature.py

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Python

import pandas as pd
import os
data_path = '../data/'
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/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)
df.set_index('datetime', append=True, drop=True, inplace=True)
action = df['action']
action = action.reset_index(level=1, drop=True)
action.index = action.index.map(lambda x: (x[0], x[1], x[2].time()))
action = action.unstack().iloc[:, ::30] * 2
action = action.fillna(0)
train_action = action.astype("int")
final = train_action
final.to_pickle(feature_path + f[:-4] + '.pkl')