mirror of
https://github.com/webclinic017/drift.git
synced 2026-07-28 03:08:01 +00:00
Daniel Szemerey
3084f5e271
* refr: Took out main primary and secondary loops and data processing. * feat: Tidied the code up. * feat: Saving models and results now works in a type safe way. * fix: There was error in the saving function. * chore: Took out some remaining comments. * fix: Fixed the previous data checking process. * feat: Fixed model selection method. I will continue the inference after we merged. Co-authored-by: Daniel Szemerey <szemereydaniel@gmail.com>
39 lines
1.1 KiB
Python
39 lines
1.1 KiB
Python
import pandas as pd
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from models.base import Model
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# | Reporting
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# |
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class Single_Model:
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def __init__(self, model_name:str, model_over_time:list[Model]):
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self.model_name: str = model_name
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self.model_over_time: list[Model] = model_over_time
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class Training_Step:
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def __init__(self, level:str):
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self.level:str = level
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self.base: list[Single_Model] = []
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self.metalabeling: list[list[Single_Model]] = []
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class Asset():
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def __init__(self, ticker:str, primary: Training_Step, secondary: Training_Step):
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self.name:str = ticker
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self.primary:Training_Step = primary
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self.secondary:Training_Step = secondary
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class Reporting:
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def __init__(self):
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self.results:pd.DataFrame = pd.DataFrame()
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self.all_predictions:pd.DataFrame = pd.DataFrame()
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self.all_probabilities:pd.DataFrame = pd.DataFrame()
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self.all_assets:list[Asset] = []
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def get_results(self)->tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame, list[Asset]]:
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return self.results, self.all_predictions, self.all_probabilities, self.all_assets
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