mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-07-29 00:17:44 +00:00
Xu Yang
e0a24fb46f
* ignore result csv file * fix app scripts * rename taskgenerator to developer and generate to develop * fix a config bug in coder * fix a small bug in factor coder evaluators * remove a single logger in factor coder evaluators * fix a small bug in model coder main.py * rename Implementation to Workspace * move the prepare the inject_code into FBWorkspace to align all the behavior * fix a small bug in model feedback * remove debug lines for multi processing and simplify evaluators multi proc * add a copy function to workspace to freeze the workspace && add config prefix to speed up debugging * make hypothesisgen a abc class * use Qlib***Experiment * fix a small bug * rename Imp to Ws * rename sub_implementations to sub_workspace_list * fix a bug in feedback not presented as content in prompts * move proposal pys to proposal folder * reformat the folder * align factor and model qlib workspace and use template to handle the workspace * add a filter to evoagent to filter out false evo * align multi_proc_n into RDAGENT seeting * handle when runner gets empty experiment * fix logger merge remaining problems * fix black and isort automatically
56 lines
1.9 KiB
Python
56 lines
1.9 KiB
Python
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 list its recorders and metrics
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experiment_name = None
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for experiment in experiments:
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print(f"Experiment: {experiment}")
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recorders = R.list_recorders(experiment_name=experiment)
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# print(recorders)
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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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print(f"Recorder ID: {recorder_id}")
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recorder = R.get_recorder(recorder_id=recorder_id, experiment_name=experiment)
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metrics = recorder.list_metrics()
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print(f"Metrics: {metrics}")
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# TODO: get the latest recorder
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recorder_list = R.list_recorders(experiment_name="workflow")
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end_times = {key: value.info['end_time'] for key, value in recorder_list.items()}
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sorted_end_times = dict(sorted(end_times.items(), key=lambda item: item[1], reverse=True))
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latest_recorder_id = next(iter(sorted_end_times))
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print(f"Latest recorder ID: {latest_recorder_id}")
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latest_recorder = R.get_recorder(experiment_name=experiment_name, recorder_id=latest_recorder_id)
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print(f"Latest recorder: {latest_recorder}")
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pred_df = latest_recorder.load_object("pred.pkl")
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print("pred_df", pred_df)
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ic_df = latest_recorder.load_object("sig_analysis/ic.pkl")
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print("ic_df: ", ic_df)
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ric_df = latest_recorder.load_object("sig_analysis/ric.pkl")
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print("ric_df: ", ric_df)
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print("list_metrics: ", latest_recorder.list_metrics())
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print("IC: ", latest_recorder.list_metrics()["IC"])
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print("ICIR: ", latest_recorder.list_metrics()["ICIR"])
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print("Rank IC: ", latest_recorder.list_metrics()["Rank IC"])
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print("Rank ICIR: ", latest_recorder.list_metrics()["Rank ICIR"])
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