o i9@sddlZddlmZddlmZmZddlZddlm Z ddl m Z ddl m Z d d Zd d ZeGd ddeZGdddZGdddZGdddZeZeeeeddZd&ddZd&ddZddZddZdd ZGd!d"d"Zdd#d$d%ZdS)'Nwraps)Protocolruntime_checkable)issparse) get_config) available_ifc Cs>zt|WSty}z td|d|d|d}~ww)zCheck library is installed.zSetting output container to 'z ' requires z to be installedN) importlib import_module ImportError)libraryexcrh/var/www/html/eduruby.in/lip-sync/lip-sync-env/lib/python3.10/site-packages/sklearn/utils/_set_output.pycheck_library_installeds rcCs*t|rz|WStyYdSw|SN)callable Exceptioncolumnsrrr get_columnss rc@s8eZdZUeed<d ddZddZddZd d Zd S) ContainerAdapterProtocol container_libFcCdS)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'z)ContainerAdapterProtocol.create_containercCr)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_containerCr!z/ContainerAdapterProtocol.is_supported_containercCr)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_columnsQr!z'ContainerAdapterProtocol.rename_columnscCr)aStack containers horizontally (column-wise). Parameters ---------- Xs : list of containers List of containers to stack. Returns ------- stacked_Xs : container Stacked containers. Nr)rXsrrrhstackbr!zContainerAdapterProtocol.hstackN)F) __name__ __module__ __qualname__str__annotations__r r#r%r'rrrrr#s   rc@2eZdZdZd ddZddZddZd d Zd S) PandasAdapterpandasTcCs|td}t|}|rt||js2t||jr|j}nt||j|jfr'|j}nd}|j||| d}|dur<|||S|S)Nr/)indexcopy)rr isinstance DataFramer0ZSeriesr%)rrrrrpdr0rrrr ts  zPandasAdapter.create_containercCtd}t||jS)Nr/rr2r3)rr"r4rrrr# z$PandasAdapter.is_supported_containercC ||_|Srrr$rrrr%zPandasAdapter.rename_columnscCtd}|j|ddS)Nr/r )Zaxisrconcat)rr&r4rrrr'zPandasAdapter.hstackNTr(r)r*rr r#r%r'rrrrr.qs   r.c@r-) PolarsAdapterpolarsTcCs`td}t|}t|tjr|n|}|rt||js$|j||ddS|dur.|||S|S)NrArow)ZschemaZorient)rrr2npZndarraytolistr3r%)rrrrrplrrrr s zPolarsAdapter.create_containercCr5)NrAr6)rr"rErrrr#r7z$PolarsAdapter.is_supported_containercCr8rrr$rrrr%r9zPolarsAdapter.rename_columnscCr:)NrA horizontal)howr;)rr&rErrrr'r=zPolarsAdapter.hstackNr>r?rrrrr@s    r@c@s(eZdZddZeddZddZdS)ContainerAdaptersManagercCs i|_dSr)adaptersrrrr__init__s z!ContainerAdaptersManager.__init__cCsdht|jBS)Ndefault)setrIrJrrrsupported_outputssz*ContainerAdaptersManager.supported_outputscCs||j|j<dSr)rIr)radapterrrrregistersz!ContainerAdaptersManager.registerN)r(r)r*rKpropertyrNrPrrrrrHs   rHc Cs^|jjdd}ztj|WSty.}zttj}td|d|d|d}~ww)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_MANAGERrIKeyErrorlistkeys ValueError) container module_namerZavailable_adaptersrrr_get_adapter_from_containers  r\cCs0t||d}ztj|WStyYdSw)zGet container adapter.denseN)_get_output_configrUrIrV)method estimator dense_configrrr_get_container_adapters   rbcCs\t|di}||vr||}nt|d}tj}||vr*tdt|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 r])getattrrrUrNrYsorted)r_r`Zest_sklearn_output_configrarNrrrr^s  r^cCsbt||}|ddkst|s|S|d}t|r#td|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. r]rLzmThe 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) r^_auto_wrap_is_configuredrrY capitalizerUrIr get_feature_names_out)r_ data_to_wrapZoriginal_inputr`Z output_configrarOrrr_wrap_data_with_container s  rkcstfdd}|S)z@Wrapper used by `_SetOutputMixin` to automatically wrap methods.csr||g|Ri|}t|tr2t|d||g|ddR}tt|dr0t||S|St|||S)Nrr _make)r2tuplerkhasattrtyperl)rr"argskwargsrjZ return_tuplefr_rrwrapped:s  z$_wrap_method_output..wrappedr)rsr_rtrrrr_wrap_method_output7srucCs 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_keysri transform)rerMrn)r`auto_wrap_output_keysrrrrgNs rgcs8eZdZdZdfdd 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. rwc stjdi|t|ts|dustd|dur t|_dSddd}t|_|D](\}}t||r:||vr;q-|j |||j vrGq-t t |||}t |||q-dS)Nz6auto_wrap_output_keys must be None or a tuple of keys.rw)rw fit_transformr)super__init_subclass__r2rmrYrMrvitemsrnadd__dict__ruresetattr)clsrxrqZ method_to_keyr_keyZwrapped_methodrSrrr}es*  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. Nrcrw)rnrc)rrwrrr set_outputs   z_SetOutputMixin.set_output)rz) r(r)r*__doc__r}r rgr __classcell__rrrrry[s   ryrzcCsJt|dp t|do |du}|sdSt|dstd|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. rwr{NrzUnable to configure output for z' because `set_output` is not available.rz)rnrYr)r`rwZset_output_for_transformrrr_safe_set_outputs    rr)r functoolsrtypingrrnumpyrCZ scipy.sparser_configrZ _available_ifr rrrr.r@rHrUrPr\rbr^rkrurgryrrrrrs2      M*    #. M