mirror of
https://github.com/NicolasBohn/NexQuant.git
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Linlang
faa2fb03ad
* fix isort & black & toml-sort & sphinx error * fix ci error * fix ci error * add comments * Update Makefile * change sphinx build command * add auto-lint * add black args * format with black * Auto Linting document * fix ci error --------- Co-authored-by: you-n-g <you-n-g@users.noreply.github.com> Co-authored-by: Young <afe.young@gmail.com>
43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
import os
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import pickle
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import time
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from pathlib import Path
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from pprint import pprint
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from rdagent.app.qlib_rd_loop.conf import PROP_SETTING
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from rdagent.components.benchmark.conf import BenchmarkSettings
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from rdagent.components.benchmark.eval_method import FactorImplementEval
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from rdagent.core.scenario import Scenario
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from rdagent.core.utils import import_class
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from rdagent.log import rdagent_logger as logger
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from rdagent.scenarios.qlib.experiment.factor_experiment import QlibFactorScenario
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from rdagent.scenarios.qlib.factor_experiment_loader.json_loader import (
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FactorTestCaseLoaderFromJsonFile,
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)
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# 1.read the settings
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bs = BenchmarkSettings()
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# 2.read and prepare the eval_data
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test_cases = FactorTestCaseLoaderFromJsonFile().load(bs.bench_data_path)
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# 3.declare the method to be tested and pass the arguments.
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scen: Scenario = import_class(PROP_SETTING.factor_scen)()
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generate_method = import_class(bs.bench_method_cls)(scen=scen)
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# 4.declare the eval method and pass the arguments.
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eval_method = FactorImplementEval(
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method=generate_method,
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test_cases=test_cases,
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scen=scen,
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catch_eval_except=True,
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test_round=bs.bench_test_round,
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)
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# 5.run the eval
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res = eval_method.eval()
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# 6.save the result
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logger.log_object(res)
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