回调函数

%load_ext autoreload
%autoreload 2

在预测步骤中使用的工具函数。

from utilsforecast.compat import DataFrame
from utilsforecast.processing import (
    assign_columns,
    drop_index_if_pandas,
    vertical_concat
)

class SaveFeatures:
    """保存每个时间戳的特征。"""
    def __init__(self):
        self._inputs = []

    def __call__(self, new_x):
        self._inputs.append(new_x)
        return new_x

    def get_features(self, with_step: bool = False) -> DataFrame:
        """Retrieves the input features for every timestep
        
        Parameters
        ----------
        with_step : bool
            Add a column indicating the step
        
        Returns
        -------
        pandas or polars DataFrame
            DataFrame with input features
        """
        if not self._inputs:
            raise ValueError(
                'Inputs list is empty. '
                'Call `predict` using this callback as before_predict_callback'
            )
        if with_step:
            dfs = [assign_columns(df, 'step', i) for i, df in enumerate(self._inputs)]
        else:
            dfs = self._inputs
        res = vertical_concat(dfs, match_categories=False)
        res = drop_index_if_pandas(res)
        return res

from nbdev import show_doc

show_doc(SaveFeatures)

---

SaveFeatures

 SaveFeatures ()

Saves the features in every timestamp.

show_doc(SaveFeatures.get_features)

---

SaveFeatures.get_features

 SaveFeatures.get_features (with_step:bool=False)

Retrieves the input features for every timestep

	Type	Default	Details
with_step	bool	False	Add a column indicating the step
Returns	Union		DataFrame with input features

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