§  ãh`ãór—dZddlZddlmZddlmZmZmZddl m Z ddl m Z m Z Gd„d eeee ¬ ¦«ZdS) z)Principal Component Analysis Base ClasseséN)Úlinalgé)Ú BaseEstimatorÚTransformerMixinÚClassNamePrefixFeaturesOutMixin)Úcheck_is_fitted)ÚABCMetaÚabstractmethodcóX—eZdZdZd„Zd„Zed d„¦«Zd„Zd„Z e d„¦«Z dS) Ú_BasePCAzwBase class for PCA methods. Warning: This class should not be used directly. Use derived classes instead. cóT—|j}|j}|jr+|tj|dd…tjf¦«z}tj||jz d¦«}tj|j |z|¦«}|j ddt|¦«dz…xx|jz cc<|S)asCompute data covariance with the generative model. ``cov = components_.T * S**2 * components_ + sigma2 * eye(n_features)`` where S**2 contains the explained variances, and sigma2 contains the noise variances. Returns ------- cov : array of shape=(n_features, n_features) Estimated covariance of data. Nçé) Ú components_Úexplained_variance_ÚwhitenÚnpÚsqrtÚnewaxisÚmaximumÚnoise_variance_ÚdotÚTÚflatÚlen)ÚselfrÚexp_varÚ exp_var_diffÚcovs úW/var/www/html/Sam_Eipo/venv/lib/python3.11/site-packages/sklearn/decomposition/_base.pyÚget_covariancez_BasePCA.get_covariances©€ðÔ&ˆ ØÔ*ˆØ Œ;ð HØ%­¬°¸¸¸½2¼:¸ Ô0FÑ(GÔ(GÑGˆKÝ”z '¨DÔ,@Ñ"@À#ÑFÔFˆ ÝŒf[”] \Ñ1°;Ñ?Ô?ˆØ Œ•C˜‘H”H˜q‘LÐ!Ð!Ô! TÔ%9Ñ9Ð!Ð!Ñ!؈ ócóJ—|jjd}|jdkrtj|¦«|jz Stj|jdd¬¦«r&tj|  ¦«¦«S|j}|j }|j r+|tj |dd…tj f¦«z}tj||jz d¦«}tj||j¦«|jz }|jddt%|¦«dz…xxd|z z cc<tj|jtjtj|¦«|¦«¦«}||jdz z}|jddt%|¦«dz…xxd|jz z cc<|S)a8Compute data precision matrix with the generative model. Equals the inverse of the covariance but computed with the matrix inversion lemma for efficiency. Returns ------- precision : array, shape=(n_features, n_features) Estimated precision of data. rrr)ÚatolNgð?r)rÚshapeÚ n_components_rÚeyerÚiscloserÚinvr!rrrrrrrrr)rÚ n_featuresrrrÚ precisions r Ú get_precisionz_BasePCA.get_precision1s€ðÔ%Ô+¨AÔ.ˆ ð Ô  Ò "Ð "Ý”6˜*Ñ%Ô%¨Ô(<Ñ<Ð <å Œ:dÔ*¨C°cÐ :Ñ :Ô :ð 5Ý”:˜d×1Ò1Ñ3Ô3Ñ4Ô4Ð 4ðÔ&ˆ ØÔ*ˆØ Œ;ð HØ%­¬°¸¸¸½2¼:¸ Ô0FÑ(GÔ(GÑGˆKÝ”z '¨DÔ,@Ñ"@À#ÑFÔFˆ Ý”F˜;¨ ¬ Ñ6Ô6¸Ô9MÑMˆ ØŒÐ,Ð,#˜i™.œ.¨1Ñ,Ð,Ð-Ð-Ô-°°|Ñ1CÑCÐ-Ð-Ñ-Ý”F˜;œ=­"¬&µ´¸IÑ1FÔ1FÈ Ñ*TÔ*TÑUÔUˆ ØtÔ+¨QÑ.Ð/Ñ/ˆ ØŒÐ,Ð,#˜i™.œ.¨1Ñ,Ð,Ð-Ð-Ô-°°tÔ7KÑ1KÑKÐ-Ð-Ñ-ØÐr"Ncó—dS)a¢Placeholder for fit. Subclasses should implement this method! Fit the model with X. Parameters ---------- X : array-like of shape (n_samples, n_features) Training data, where `n_samples` is the number of samples and `n_features` is the number of features. Returns ------- self : object Returns the instance itself. N©)rÚXÚys r Úfitz _BasePCA.fitRs€€€r"có&—t|¦«| |tjtjgd¬¦«}|j ||jz }tj||jj¦«}|j r|tj |j ¦«z}|S)azApply dimensionality reduction to X. X is projected on the first principal components previously extracted from a training set. Parameters ---------- X : array-like of shape (n_samples, n_features) New data, where `n_samples` is the number of samples and `n_features` is the number of features. Returns ------- X_new : array-like of shape (n_samples, n_components) Projection of X in the first principal components, where `n_samples` is the number of samples and `n_components` is the number of the components. F)ÚdtypeÚreset) rÚ_validate_datarÚfloat64Úfloat32Úmean_rrrrrr)rr/Ú X_transformeds r Ú transformz_BasePCA.transformds†€õ$ ˜ÑÔÐà × Ò  ­"¬*µb´jÐ)AÈÐ Ñ OÔ OˆØ Œ:Ð !ØD”J‘ˆAÝœ˜q $Ô"2Ô"4Ñ5Ô5ˆ Ø Œ;ð ?Ø RœW TÔ%=Ñ>Ô>Ñ >ˆMØÐr"cóô—|jrPtj|tj|jdd…tjf¦«|jz¦«|jzStj||j¦«|jzS)açTransform data back to its original space. In other words, return an input `X_original` whose transform would be X. Parameters ---------- X : array-like of shape (n_samples, n_components) New data, where `n_samples` is the number of samples and `n_components` is the number of components. Returns ------- X_original array-like of shape (n_samples, n_features) Original data, where `n_samples` is the number of samples and `n_features` is the number of features. Notes ----- If whitening is enabled, inverse_transform will compute the exact inverse operation, which includes reversing whitening. N)rrrrrrrr8)rr/s r Úinverse_transformz_BasePCA.inverse_transform€sv€ð, Œ;ð <å”ØÝ”G˜DÔ4°Q°Q°Q½¼ °]ÔCÑDÔDÀtÔGWÑWñôð”*ñ ð õ”6˜!˜TÔ-Ñ.Ô.°´Ñ;Ð ;r"có&—|jjdS)z&Number of transformed output features.r)rr%)rs r Ú_n_features_outz_BasePCA._n_features_out¡s€ðÔÔ% aÔ(Ð(r")N) Ú__name__Ú __module__Ú __qualname__Ú__doc__r!r,r r1r:r<Úpropertyr>r.r"r r r s—€€€€€ððð ððð*ðððBð ð ð ñ„^ð ð"ððð8<ð<ð<ðBð)ð)ñ„Xð)ð)ð)r"r )Ú metaclass)rBÚnumpyrÚscipyrÚbaserrrÚutils.validationrÚabcr r r r.r"r úrJsÀðØ/Ð/ðÐÐÐØÐÐÐÐÐàSÐSÐSÐSÐSÐSÐSÐSÐSÐSØ.Ð.Ð.Ð.Ð.Ð.Ø'Ð'Ð'Ð'Ð'Ð'Ð'Ð'ðQ)ðQ)ðQ)ðQ)ðQ)Ø#Ð%5°}ÐPWðQ)ñQ)ôQ)ðQ)ðQ)ðQ)r"