Dj ddlZddlZddlZddlmZGddeejZGddeejZ y) N)BaseTransformerc$eZdZdZdfd ZxZS)BaseExogTransformerz-A base class for exogenous array transformerscXtt| ||\}}| |s td||fS)zCheck the endog and exog arraysz(X must be non-None for exog transformers)superr _check_y_X ValueError)selfyX null_allowed __class__s dC:\Crop_Prediction\Backend\crop-ai-system\venv\Lib\site-packages\pmdarima/preprocessing/exog/base.pyr zBaseExogTransformer._check_y_X s7($:1a@1 9\GH H!t )F)__name__ __module__ __qualname____doc__r __classcell__)rs@rrr s7rr) metaclasscPeZdZdZddZej dZdZdZ d dZ y) BaseExogFeaturizerzTransformers that create new exog features from the endog or exog array Parameters ---------- prefix : str or None, optional (default=None) The feature prefix Nc||_yN)prefix)r rs r__init__zBaseExogFeaturizer.__init__s  rcy)z6Get the feature prefix for when exog is a pd.DataFrameN)r s r _get_prefixzBaseExogFeaturizer._get_prefix rc|j}t|jdDcgc] }d||fz c}Scc}w)Nz%s_%i)r rangeshape)r r pfxis r_get_feature_namesz%BaseExogFeaturizer._get_feature_names$s: ,1!''!*,=>q3(">>>s<c|t|tjrt|tjstjj|}|j ||_|Gt j|jdx|_ |_ tj||gdS|St j||gS)z!H-stack dataframes or np.ndarraysrr#)axis) isinstancepd DataFrame from_recordsr(columnsnparanger%indexconcathstack)r r featuress r _safe_hstackzBaseExogFeaturizer._safe_hstack(s 9 1bll3h 5<<44X> $66x@H },.99QWWQZ+@@(.yy!XQ77Oyy!X''rc y)aiTransform the new array Apply the transformation to the array after learning the training set's characteristics in the ``fit`` method. The transform method for featurizers behaves slightly differently in that the ``n_periods` may be required to extrapolate for periods in the future. Parameters ---------- y : array-like or None, shape=(n_samples,) The endogenous (time-series) array. X : array-like or None, shape=(n_samples, n_features) An array of additional covariates. n_periods : int, optional (default=0) The number of periods in the future to forecast. If ``n_periods`` is 0, will compute the features for the training set. ``n_periods`` corresponds to the number of samples that will be returned. **kwargs : keyword args Keyword arguments required by the transform function. Returns ------- y : array-like or None The transformed y array X : array-like or None The transformed X array Nr)r r r n_periodskwargss r transformzBaseExogFeaturizer.transform=r!rr)Nr) rrrrrabcabstractmethodr r(r6r:rrrrrs7 EE?(*  rr) pandasr,numpyr0r;baserABCMetarrrrrrAs: "/S[[H , H r