o tBh! @sddlZddlmZddlmZddlmZmZmZm Z m Z ddl Z ddl ZddlmZmZddlmZmZmZmZded ed efd d Zded ed e jfd dZdeeeffddZ ddedeedeede e d e f ddZdededeeefd e fddZ   dddZdS) N) OrderedDict) Generator)AnyDictListOptionalTuple)ArffSparseDataTypeArffContainerType)_chunk_generatorcheck_pandas_supportget_chunk_n_rows is_scalar_nan arff_datainclude_columnsreturncCstttf}ddt|D}t|d|d|dD] \}}}||vr=|d||d||d||q|S)a obtains several columns from sparse arff representation. Additionally, the column indices are re-labelled, given the columns that are not included. (e.g., when including [1, 2, 3], the columns will be relabelled to [0, 1, 2]) Parameters ---------- arff_data : tuple A tuple of three lists of equal size; first list indicating the value, second the x coordinate and the third the y coordinate. include_columns : list A list of columns to include. Returns ------- arff_data_new : tuple Subset of arff data with only the include columns indicated by the include_columns argument. cSi|]\}}||qSr.0 array_idx column_idxrrt/var/www/html/riverr-enterprise-integrations-main/venv/lib/python3.10/site-packages/sklearn/datasets/_arff_parser.py + z)_split_sparse_columns..rr )list enumeratezipappend)rr arff_data_newreindexed_columnsvalrow_idxcol_idxrrr_split_sparse_columnss"r&c Cs~t|dd}|t|f}ddt|D}tj|tjd}t|d|d|dD]\}}}||vr<|||||f<q+|S)NrcSrrrrrrrr=rz)_sparse_data_to_array..dtyperr )maxlenrnpemptyfloat64r) rrnum_obsy_shaper"yr#r$r%rrr_sparse_data_to_array6s "r1featurecCs^|ddkrtS|ddkrdS|ddks|ddvrtjS|ddkr(tjStd |) z)Map feature to dtype for pandas DataFrame data_typestringnominalcategorynumber_of_missing_values0)numericrealintegerzUnsupported feature: {})objectr+r-int64 ValueErrorformat)r2rrr_feature_to_dtypeHs   r@arff col_slice_x col_slice_yshapec Cs|d}t|trG|durtd|ddkrd}n|d|d}tjtj|d|d}|j|}|dd|f}|dd|f}||fSt|t rt ||} t |dd} | t |f} t jj| d| d| d ff| tjd }|}t||}||fStd ) af converts the arff object into the appropriate matrix type (np.array or scipy.sparse.csr_matrix) based on the 'data part' (i.e., in the liac-arff dict, the object from the 'data' key) Parameters ---------- arff : dict As obtained from liac-arff object. col_slice_x : list The column indices that are sliced from the original array to return as X data col_slice_y : list The column indices that are sliced from the original array to return as y data Returns ------- X : np.array or scipy.sparse.csr_matrix y : np.array dataNz6shape must be provided when arr['data'] is a Generatorrrr-)r(countr )rDr(z(Unexpected Data Type obtained from arff.) isinstancerr>r+fromiter itertoolschain from_iterablereshapetupler&r)r*scipysparse coo_matrixr-tocsrr1) rArBrCrDrrGrEXr0 arff_data_Xr.X_shaperrr_convert_arff_dataZs6       rVcolumns features_dictcstd}t|d}t|}t|dtstdt|d}|j|g|d}|jdd }t |} fdd |D} g} | || t |d| D]} | |j| |d| qL|j | dd } | D]'}t||}|d krd d ||D}|jj|}| |j|d d| |<qd| fS)auConvert the ARFF object into a pandas DataFrame. Parameters ---------- arff : dict As obtained from liac-arff object. columns : list Columns from dataframe to return. features_dict : dict Maps feature name to feature info from openml. Returns ------- result : tuple tuple with the resulting dataframe zfetch_openml with as_frame=True attributesrEzAarff['data'] must be a generator when converting to pd.DataFrame.rWT)deepcsg|]}|vr|qSrr)rcolrZrr sz0_convert_arff_data_dataframe..) ignore_indexr6cSs g|] }|durt|s|qSN)r)rcatrrrr]s Fcopy)r rrrHrr>next DataFrame memory_usagesumrr r concatr@apitypesCategoricalDtypeastype)rArWrXpdrY arff_columns first_rowfirst_df row_bytes chunksizecolumns_to_keepdfsrEdfcolumnr(cats_without_missingrrZr_convert_arff_data_dataframes4   rwc s|dkr0d}t|||\} | } tdkr | netdkr-| dnXdnUd} t||||\} fdd|dDfdd D} | sSnt| rgtfd d tDnt| rotd j ddkr| d n j ddkrd| | fS)Npandasr rrcs,i|]\}}t|tr|vr||qSr)rHr)rkv) data_columnstarget_columnsrrrs z%_liac_arff_parser..rYcsh|]}|vqSrr)rcol_name)nominal_attributesrr sz$_liac_arff_parser..c sJg|]!\}}ttj|dddd||dfjtddqS)Or'NrFra)r+takeasarraypoprkint)rir})r~r0rrr]s z%_liac_arff_parser..zAMix of nominal and non-nominal targets is not currently supported)rF) rwr*rVallr+hstackranyr>rDrM) arff_containeroutput_arrays_typerXr{r|rBrCrDrWframerSis_classificationr)r{r~r|r0r_liac_arff_parsersF          rr_)NNN) rJ collectionsrcollections.abcrtypingrrrrrnumpyr+ scipy.sparserOexternals._arffr r utilsr r rrr&ndarrayr1strr@rrVrwrrrrrs`   $  =  A