mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-08-07 03:57:45 +00:00
Yuante Li
56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
import pickle
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from pathlib import Path
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import pandas as pd
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import qlib
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from mlflow.entities import ViewType
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from mlflow.tracking import MlflowClient
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qlib.init()
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from qlib.workflow import R
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# here is the documents of the https://qlib.readthedocs.io/en/latest/component/recorder.html
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# TODO: list all the recorder and metrics
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# Assuming you have already listed the experiments
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experiments = R.list_experiments()
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# Iterate through each experiment to find the latest recorder
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experiment_name = None
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latest_recorder = None
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for experiment in experiments:
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recorders = R.list_recorders(experiment_name=experiment)
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for recorder_id in recorders:
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if recorder_id is not None:
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experiment_name = experiment
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recorder = R.get_recorder(recorder_id=recorder_id, experiment_name=experiment)
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end_time = recorder.info["end_time"]
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try:
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# Check if the recorder has a valid end time
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if end_time is not None:
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if latest_recorder is None or end_time > latest_recorder.info["end_time"]:
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latest_recorder = recorder
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else:
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print(f"Warning: Recorder {recorder_id} has no valid end time")
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except Exception as e:
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print(f"Error: {e}")
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# Check if the latest recorder is found
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if latest_recorder is None:
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print("No recorders found")
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else:
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print(f"Latest recorder: {latest_recorder}")
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# Load the specified file from the latest recorder
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metrics = pd.Series(latest_recorder.list_metrics())
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output_path = Path(__file__).resolve().parent / "qlib_res.csv"
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metrics.to_csv(output_path)
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print(f"Output has been saved to {output_path}")
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ret_data_frame = latest_recorder.load_object("portfolio_analysis/report_normal_1day.pkl")
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ret_data_frame.to_pickle("ret.pkl")
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