IR-etdZddlZddlmZmZddlmZddlZdgZGdde Z d dZ d Z d Z d ZdS) z High-level operations for numpy structured arrays. Some code and inspiration taken from numpy.lib.recfunctions.join_by(). Redistribution license restrictions apply. N)Counter OrderedDict)SequenceTableMergeErrorceZdZdS)rN)__name__ __module__ __qualname__6lib/python3.11/site-packages/astropy/table/np_utils.pyrrsDr {col_name}_{table_name}c tjfd g}|&dttD}t D]\}}||}|jjD] } |vr |vr| nkt} | |t fd| Dr| | }|| ||<t|} d| D} | r"td | t fd|D S) a Find the column names mapping when merging the list of structured ndarrays ``arrays``. It is assumed that col names in ``common_names`` are to be merged into a single column while the rest will be uniquely represented in the output. The args ``uniq_col_name`` and ``table_names`` specify how to rename columns in case of conflicts. Returns a dict mapping each output column name to the input(s). This takes the form {outname : (col_name_0, col_name_1, ...), ... }. For key columns all of input names will be present, while for the other non-key columns the value will be (col_name_0, None, ..) or (None, col_name_1, ..) etc. c*dgtzSN)len)arrayssr z"get_col_name_map..$sD6CKK3Gr Nc2g|]}t|dzS)str).0iis r z$get_col_name_map..(s"@@@rs26{{@@@r c34K|]}|jjvVdSr)dtypenames)rothernames r z#get_col_name_map..9s-EEUtu{00EEEEEEr ) table_namecol_namec$g|] \}}|dk |Srr )rr counts r rz$get_col_name_map..Cs"RRR{tUPQ d r zgMerging column names resulted in duplicates: {}. Change uniq_col_name or table_names args to fix this.c3,K|]}||fVdSrr )rr col_name_maps r r!z#get_col_name_map..Ms-TTdl4&89TTTTTTr ) collections defaultdictranger enumeraterrappendlistpopanyformatritemsrr)r common_names uniq_col_name table_names col_name_listidxarrayr"out_nameotherscol_name_countrepeated_namesr'r s` @@r get_col_name_mapr<s*+G+G+G+GHHLM@@U3v;;-?-?@@@ ''// U % K% / /DH|##},,!((...f 3EEEEfEEEEE,33#- 4  H$$X...*.L "3 ' '' /,]++NRRn.B.B.D.DRRRN  DDJFEE   TTTTmTTTTTL r cg}|D]\}}dt||D}d|D} t|}nA#t$r4}td|d|j|d}~wwxYwd|D} t | dkrtd| } |t|}| ||| f|S) z Find the dtypes descrs resulting from merging the list of arrays' dtypes, using the column name mapping ``col_name_map``. Return a list of descrs for the output. c(g|]\}}|||Srr )rarrr s r rzget_descrs..]s%XXXdtGW3t9GWGWGWr cg|]}||Srr )rr s r rzget_descrs..`s???$d.>.>.>.>r z,The '{}' columns have incompatible types: {}rNc,h|]}|jddS)rN)shapercols r zget_descrs..os"888sy}888r rz Key columns have different shape) r1zip common_dtyperr0_incompat_typesrr.rr,) rr' out_descrsr8in_namesin_colsrrtme uniq_shapesrBs r get_descrsrNRsBJ*002244(XXc&(.C.CXXX@?(???  ))EE   ">EE!Hc1   98888 {  q !"DEE E!!  8}}H8UE23333 sA B/B  Bctjtjtjtjtjffd|D}t |dkr'd|D}td|}||_|d|D}|D]}|j j dvr d|j z|d<tj d |D}|j j S) z Use numpy to find the common dtype for a list of structured ndarray columns. Only allow columns within the following fundamental numpy data types: np.bool_, np.object_, np.number, np.character, np.void cHh|]tfdDS)c3LK|]}tjj|VdSr) issubclassrtype)rnp_typerDs r r!z)common_dtype...s1 J Jgj11 J J J J J Jr )tuple)rrDnp_typess @r rEzcommon_dtype..sG   J J J J J J JJJr rc&g|]}|jjSr )rr rCs r rz common_dtype..s999S#).999r z Columns have incompatible types cDg|]}tjd|jS)r)r)npemptyrrCs r rz common_dtype..s) 9 9 9SBHQci ( ( ( 9 9 9r )SU0rcg|] }|d S)rr )rr?s r rz common_dtype..s222c3q6222r )rYbool_object_number charactervoidrrrHrkinditemsizer7r)cols uniq_typesincompat_typesrLarrsr? arr_commonrVs @r rGrG{s"*birwGHJ :99D999QQQRR, 9 9D 9 9 9D(( 9>Z ' '3<'CF22T22233J   r c d}t|tst||D]7}t|tjr |jjt|8t|dkrtddS)Nz@`arrays` arg must be a sequence (e.g. list) of structured arraysrz,`arrays` arg must include at least one array) isinstancer TypeErrorrYndarrayrrr ValueError)rerrr7s r (_check_for_sequence_of_structured_arraysrqs LC fh ' 'nn!!%,, ! 0A0IC.. 1J 6{{aGHHHr )rN)__doc__r(rrcollections.abcrnumpyrY__all__rorr<rNrGrqr r r rvs,,,,,,,,$$$$$$       j   PT::::z&&&R   > I I I I Ir