a hX:@sddlZddlmZddlmZmZddlZddlm Z ddl m Z ddl m Z dd lmZd d Zd d ZeGdddeZGdddZGdddZGdddZeZeeeeddZd'ddZd(ddZddZddZd d!ZGd"d#d#Zdd$d%d&ZdS))Nwraps)Protocolruntime_checkable)issparse) get_config) available_if)2_create_pandas_dataframe_from_non_pandas_containerc CsNz t|WStyH}z$td|d|d|WYd}~n d}~00dS)zCheck library is installed.zSetting output container to 'z ' requires z to be installedN) importlib import_module ImportError)libraryexcrU/var/www/html/assistant/venv/lib/python3.9/site-packages/sklearn/utils/_set_output.pycheck_library_installeds rcCs*t|r&z|WSty$YdS0|SN)callable Exceptioncolumnsrrr get_columnss  rc@s8eZdZUeed<d ddZddZddZd d Zd S) ContainerAdapterProtocol container_libFcCsdS)aCreate container from `X_output` with additional metadata. Parameters ---------- X_output : {ndarray, dataframe} Data to wrap. X_original : {ndarray, dataframe} Original input dataframe. This is used to extract the metadata that should be passed to `X_output`, e.g. pandas row index. columns : callable, ndarray, or None The column names or a callable that returns the column names. The callable is useful if the column names require some computation. If `None`, then no columns are passed to the container's constructor. inplace : bool, default=False Whether or not we intend to modify `X_output` in-place. However, it does not guarantee that we return the same object if the in-place operation is not possible. Returns ------- wrapped_output : container_type `X_output` wrapped into the container type. Nr)selfX_output X_originalrinplacerrrcreate_container(sz)ContainerAdapterProtocol.create_containercCsdS)a Return True if X is a supported container. Parameters ---------- Xs: container Containers to be checked. Returns ------- is_supported_container : bool True if X is a supported container. Nr)rXrrris_supported_containerDsz/ContainerAdapterProtocol.is_supported_containercCsdS)aQRename columns in `X`. Parameters ---------- X : container Container which columns is updated. columns : ndarray of str Columns to update the `X`'s columns with. Returns ------- updated_container : container Container with new names. Nrrr!rrrrrename_columnsRsz'ContainerAdapterProtocol.rename_columnscCsdS)aStack containers horizontally (column-wise). Parameters ---------- Xs : list of containers List of containers to stack. Returns ------- stacked_Xs : container Stacked containers. Nr)rXsrrrhstackcszContainerAdapterProtocol.hstackN)F) __name__ __module__ __qualname__str__annotations__r r"r$r&rrrrr$s  rc@s2eZdZdZd ddZddZddZd d Zd S) PandasAdapterpandasTcCsttd}t|}|r t||js\t||jr4|j}nt||jrH|j}nd}t||| d}|durp|||S|S)Nr-)r!indexcopy)rr isinstance DataFramer.r r$)rrrrrpdr.rrrr us   zPandasAdapter.create_containercCstd}t||jS)Nr-rr0r1)rr!r2rrrr"sz$PandasAdapter.is_supported_containercCs ||_|Srrr#rrrr$szPandasAdapter.rename_columnscCstd}|j|ddS)Nr-r )Zaxisrconcat)rr%r2rrrr&szPandasAdapter.hstackN)Tr'r(r)rr r"r$r&rrrrr,rs  r,c@s2eZdZdZd ddZddZddZd d Zd S) PolarsAdapterpolarsTcCs`td}t|}t|tjr$|n|}|r8t||jsH|j||ddS|dur\|||S|S)Nr8row)ZschemaZorient)rrr0npZndarraytolistr1r$)rrrrrplrrrr s zPolarsAdapter.create_containercCstd}t||jS)Nr8r3)rr!r<rrrr"sz$PolarsAdapter.is_supported_containercCs ||_|Srrr#rrrr$szPolarsAdapter.rename_columnscCstd}|j|ddS)Nr8 horizontal)howr4)rr%r<rrrr&szPolarsAdapter.hstackN)Tr6rrrrr7s  r7c@s(eZdZddZeddZddZdS)ContainerAdaptersManagercCs i|_dSr)adaptersrrrr__init__sz!ContainerAdaptersManager.__init__cCsdht|jBS)Ndefault)setr@rArrrsupported_outputssz*ContainerAdaptersManager.supported_outputscCs||j|j<dSr)r@r)radapterrrrregistersz!ContainerAdaptersManager.registerN)r'r(r)rBpropertyrErGrrrrr?s r?c Csn|jjdd}z tj|WStyh}z2ttj}td|d|d|WYd}~n d}~00dS)zGet the adapter that knows how to handle such container. See :class:`sklearn.utils._set_output.ContainerAdapterProtocol` for more details. .rzZThe container does not have a registered adapter in scikit-learn. Available adapters are: z" while the container provided is: N) __class__r(splitADAPTERS_MANAGERr@KeyErrorlistkeys ValueError) container module_namerZavailable_adaptersrrr_get_adapter_from_containers rScCs4t||d}z tj|WSty.YdS0dS)zGet container adapter.denseN)_get_output_configrLr@rM)method estimator dense_configrrr_get_container_adapters   rYcCs\t|di}||vr||}nt|d}tj}||vrTtdt|d|d|iS)aGet output config based on estimator and global configuration. Parameters ---------- method : {"transform"} Estimator's method for which the output container is looked up. estimator : estimator instance or None Estimator to get the output configuration from. If `None`, check global configuration is used. Returns ------- config : dict Dictionary with keys: - "dense": specifies the dense container for `method`. This can be `"default"` or `"pandas"`. _sklearn_output_config_outputzoutput config must be in z, got rT)getattrrrLrErPsorted)rVrWZest_sklearn_output_configrXrErrrrUs  rUcCsbt||}|ddkst|s"|S|d}t|rFtd|dtj|}|j|||jdS)aWrap output with container based on an estimator's or global config. Parameters ---------- method : {"transform"} Estimator's method to get container output for. data_to_wrap : {ndarray, dataframe} Data to wrap with container. original_input : {ndarray, dataframe} Original input of function. estimator : estimator instance Estimator with to get the output configuration from. Returns ------- output : {ndarray, dataframe} If the output config is "default" or the estimator is not configured for wrapping return `data_to_wrap` unchanged. If the output config is "pandas", return `data_to_wrap` as a pandas DataFrame. rTrCzmThe transformer outputs a scipy sparse matrix. Try to set the transformer output to a dense array or disable z- output with set_output(transform='default').r) rU_auto_wrap_is_configuredrrP capitalizerLr@r get_feature_names_out)rV data_to_wrapZoriginal_inputrWZ output_configrXrFrrr_wrap_data_with_container s   rbcstfdd}|S)z@Wrapper used by `_SetOutputMixin` to automatically wrap methods.csr||g|Ri|}t|trdt|d||g|ddR}tt|dr`t||S|St|||S)Nrr _make)r0tuplerbhasattrtyperc)rr!argskwargsraZ return_tuplefrVrrwrapped=s  z$_wrap_method_output..wrappedr)rjrVrkrrir_wrap_method_output:srlcCs t|dt}t|dod|vS)zReturn True if estimator is configured for auto-wrapping the transform method. `_SetOutputMixin` sets `_sklearn_auto_wrap_output_keys` to `set()` if auto wrapping is manually disabled. _sklearn_auto_wrap_output_keysr` transform)r\rDre)rWauto_wrap_output_keysrrrr^Qs r^cs8eZdZdZdfdd ZeeddddZZS) _SetOutputMixina\Mixin that dynamically wraps methods to return container based on config. Currently `_SetOutputMixin` wraps `transform` and `fit_transform` and configures it based on `set_output` of the global configuration. `set_output` is only defined if `get_feature_names_out` is defined and `auto_wrap_output_keys` is the default value. rnc stjfi|t|ts,|dus,td|dur@t|_dSddd}t|_|D]P\}}t||rZ||vrvqZ|j |||j vrqZt t |||}t |||qZdS)Nz6auto_wrap_output_keys must be None or a tuple of keys.rn)rn fit_transform)super__init_subclass__r0rdrPrDrmitemsreadd__dict__rlr\setattr)clsrorhZ method_to_keyrVkeyZwrapped_methodrJrrrths*  z!_SetOutputMixin.__init_subclass__NcCs*|dur |St|dsi|_||jd<|S)aSet output container. See :ref:`sphx_glr_auto_examples_miscellaneous_plot_set_output.py` for an example on how to use the API. Parameters ---------- transform : {"default", "pandas", "polars"}, default=None Configure output of `transform` and `fit_transform`. - `"default"`: Default output format of a transformer - `"pandas"`: DataFrame output - `"polars"`: Polars output - `None`: Transform configuration is unchanged .. versionadded:: 1.4 `"polars"` option was added. Returns ------- self : estimator instance Estimator instance. NrZrn)rerZ)rrnrrr set_outputs   z_SetOutputMixin.set_output)rq) r'r(r)__doc__rtr r^r| __classcell__rrr{rrp^s  rprqcCsJt|dpt|do|du}|s$dSt|ds>td|d|j|dS)a)Safely call estimator.set_output and error if it not available. This is used by meta-estimators to set the output for child estimators. Parameters ---------- estimator : estimator instance Estimator instance. transform : {"default", "pandas", "polars"}, default=None Configure output of the following estimator's methods: - `"transform"` - `"fit_transform"` If `None`, this operation is a no-op. Returns ------- estimator : estimator instance Estimator instance. rnrrNr|zUnable to configure output for z' because `set_output` is not available.rq)rerPr|)rWrnZset_output_for_transformrrr_safe_set_outputs    r)N)N) r functoolsrtypingrrnumpyr:Z scipy.sparser_configrZ _available_ifr fixesr rrrr,r7r?rLrGrSrYrUrbrlr^rprrrrrs2       M,    #. M