Spaces:
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Running
style: move attribute types to after docstring
Browse files- pysr/sr.py +15 -15
pysr/sr.py
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@@ -183,21 +183,6 @@ VALID_OPTIMIZER_ALGORITHMS = ["BFGS", "NelderMead"]
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class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
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equations_: Optional[Union[pd.DataFrame, List[pd.DataFrame]]]
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n_features_in_: int
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feature_names_in_: ArrayLike[str]
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display_feature_names_in_: ArrayLike[str]
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X_units_: Optional[ArrayLike[str]]
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y_units_: Optional[Union[str, ArrayLike[str]]]
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nout_: int
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selection_mask_: Optional[NDArray[np.bool_]]
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tempdir_: Path
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equation_file_: Union[str, Path]
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julia_state_stream_: Optional[NDArray[np.uint8]]
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julia_options_stream_: Optional[NDArray[np.uint8]]
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equation_file_contents_: Optional[List[pd.DataFrame]]
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show_pickle_warnings_: bool
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"""
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High-performance symbolic regression algorithm.
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@@ -679,6 +664,21 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
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```
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"""
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def __init__(
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self,
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model_selection: Literal["best", "accuracy", "score"] = "best",
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class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
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"""
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High-performance symbolic regression algorithm.
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```
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"""
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equations_: Optional[Union[pd.DataFrame, List[pd.DataFrame]]]
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n_features_in_: int
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feature_names_in_: ArrayLike[str]
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display_feature_names_in_: ArrayLike[str]
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X_units_: Optional[ArrayLike[str]]
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y_units_: Optional[Union[str, ArrayLike[str]]]
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nout_: int
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selection_mask_: Optional[NDArray[np.bool_]]
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tempdir_: Path
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equation_file_: Union[str, Path]
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julia_state_stream_: Optional[NDArray[np.uint8]]
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julia_options_stream_: Optional[NDArray[np.uint8]]
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equation_file_contents_: Optional[List[pd.DataFrame]]
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show_pickle_warnings_: bool
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def __init__(
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self,
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model_selection: Literal["best", "accuracy", "score"] = "best",
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