h2&ddlmZddlmZddlmZddlmZddlm Z dd d Z dd Z d Z d Z dZGddZdddZdS)wraps)issparse) get_config)check_pandas_support) available_ifN)indexc(t|rtdt|r |}n#t$rd}YnwxYwt d}t ||jr |||_|S||||dS)aACreate a Pandas DataFrame. If `data_to_wrap` is a DataFrame, then the `columns` and `index` will be changed inplace. If `data_to_wrap` is a ndarray, then a new DataFrame is created with `columns` and `index`. Parameters ---------- data_to_wrap : {ndarray, dataframe} Data to be wrapped as pandas dataframe. columns : callable, ndarray, or None The column names or a callable that returns the column names. The callable is useful if the column names require some computation. If `columns` is a callable that raises an error, `columns` will have the same semantics as `None`. If `None` and `data_to_wrap` is already a dataframe, then the column names are not changed. If `None` and `data_to_wrap` is **not** a dataframe, then columns are `range(n_features)`. index : array-like, default=None Index for data. `index` is ignored if `data_to_wrap` is already a DataFrame. Returns ------- dataframe : DataFrame Container with column names or unchanged `output`. z+Pandas output does not support sparse data.Nz$Setting output container to 'pandas'F)r columnscopy)r ValueErrorcallable Exceptionr isinstance DataFramer ) data_to_wrapr r pds a/var/www/html/services/rag-service/venv/lib/python3.11/site-packages/sklearn/utils/_set_output.py_wrap_in_pandas_containerr sD HFGGG giiGG   GGG  D E EB, --  #*L  << E7< O OOs : A A ct|di}||vr ||}nt|d}|dvrtd|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_output>pandasdefaultz0output config must be 'default' or 'pandas' got dense)getattrrr)method estimatorest_sklearn_output_config dense_configs r_get_output_configr#?s|(!( 3KR P P ***08 !||v$6$6$67 000 M| M M    \ ""ct||}|ddkst|s|Sd}||r|jnd}t|||jS)aWrap output with container based on an estimator's or global config. Parameters ---------- method : {"transform"} Estimator's method to get container output for. data_to_wrap : {ndarray, dataframe} Data to wrap with container. original_input : {ndarray, dataframe} Original input of function. estimator : estimator instance Estimator with to get the output configuration from. Returns ------- output : {ndarray, dataframe} If the output config is "default" or the estimator is not configured for wrapping return `data_to_wrap` unchanged. If the output config is "pandas", return `data_to_wrap` as a pandas DataFrame. rrcddl}t|drEt|dr5 |jd}n#t$rYdSwxYwt ||jSdS)zvReturn True if the X is a pandas dataframe. This is is backport from 1.4 in 1.3.1 for compatibility. rNr ilocrF)syshasattrmodulesKeyErrorrr)Xr(rs r _is_pandas_dfz0_wrap_data_with_container.._is_pandas_dfs|  1i  /WQ%7%7 / [*   uu a.. .us 4 AAN)rr r )r#_auto_wrap_is_configuredr rget_feature_names_out)rroriginal_inputr output_configr-r s r_wrap_data_with_containerr2as2'vy99MW**2J92U2U*"%2M.$A$A KN tE $!/   r$c@tfd}|S)z@Wrapper used by `_SetOutputMixin` to automatically wrap methods.c6||g|Ri|}t|tret|d||g|ddR}tt |dr"t ||S|St|||S)Nrr_make)rtupler2r)typer5)selfr,argskwargsr return_tuplefrs rwrappedz$_wrap_method_output..wrappedsqq24222622 lE * * *&,q/1dKKabb!L tL))733 >L))// === (q$GGGr$r)r<rr=s`` r_wrap_method_outputr>sA 1XXHHHHHXH Nr$cdt|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)rsetr))r auto_wrap_output_keyss rr.r.s? $I/OQTQVQVWW 233 1 0 0r$cReZdZdZdfd ZeedddZxZS)_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. rAc tjdi|t|ts|t d|t |_dSddd}t |_|D]m\}}t||r||vr|j |||j vr>tt|||}t|||ndS)Nz6auto_wrap_output_keys must be None or a tuple of keys.rA)rA fit_transform)super__init_subclass__rr6rrBr@itemsr)add__dict__r>rsetattr)clsrCr: method_to_keyrkeywrapped_method __class__s rrKz!_SetOutputMixin.__init_subclass__s$!!++F+++ ,e 4 4 W8M8UUVV V (14C . F%(  .1UU*(..00 1 1KFC3'' 36K+K+K  . 2 23 7 7 7S\))0f1E1EsKKN C 0 0 0 0 1 1r$NcP||St|dsi|_||jd<|S)aDSet output container. See :ref:`sphx_glr_auto_examples_miscellaneous_plot_set_output.py` for an example on how to use the API. Parameters ---------- transform : {"default", "pandas"}, default=None Configure output of `transform` and `fit_transform`. - `"default"`: Default output format of a transformer - `"pandas"`: DataFrame output - `None`: Transform configuration is unchanged Returns ------- self : estimator instance Estimator instance. NrrA)r)r)r8rAs r set_outputz_SetOutputMixin.set_outputs<*  Kt566 -*,D '3<#K0 r$)rF) __name__ __module__ __qualname____doc__rKr r.rV __classcell__)rTs@rrErEs|111111@\*++&*,+r$rErFct|dpt|do|du}|sdSt|dstd|d||S)aSafely 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"}, 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. rArHNrVzUnable to configure output for z' because `set_output` is not available.rF)r)rrV)r rAset_output_for_transforms r_safe_set_outputr^s0  ;'' " 9o . . " T ! $  9l + +  i         )  4 44r$)N) functoolsr scipy.sparser_configrr _available_ifr rr#r2r>r.rEr^rIr$rrds!!!!!! """"""''''''  2P2P2P2P2Pj####D444n.   FFFFFFFFR.2&5&5&5&5&5&5&5r$