IR-e6ddlZddlZddlZddlmZddlmZddgZdZ dZ d Z Gd d Z Gd de Z Gd de ZdS)N)AstropyUserWarning)get_index_by_names TableGroups ColumnGroupsc|d5t||cdddS#1swxYwYdS)Ndiscard_on_copy) index_mode_table_group_by)tablekeyss 4lib/python3.11/site-packages/astropy/table/groups.pytable_group_byrs   + , ,,,ud++,,,,,,,,,,,,,,,,,,s 377cddlm}ddlm}t |t r|f}t |t tfr|D]V}|jvrtd|j r2tj |j rtd|dWfd|Dd }t|}d }nt |tj|frd|}t#|t#kr=td t#|t#d }d}n/t'd t)||st ||r ||} ||}n|d}d } n9#t&$r,|}t/jdv} YnwxYw||}tjd g|dd |d dkd gf} tj| } | sBt7| d d| dd D]!\} } || | "|}|| d d}t ||r ||jd<t=|| ||_|S)a2 Get groups for ``table`` on specified ``keys``. Parameters ---------- table : `Table` Table to group keys : str, list of str, `Table`, or Numpy array Grouping key specifier Returns ------- grouped_table : Table object with groups attr set accordingly rrepresent_mixins_as_columnsTablezTable does not have key column zMissing values in key column z are not allowedc g|] }| Sr).0keyr s r z#_table_group_by..5s%A%A%ASeCj%A%A%AF)copyTz9Input keys array length {} does not match table length {}NzHKeys input must be string, list, tuple, Table or numpy array, but got {} mergesort)kind)DarwinWindowsgrouped_by_table_colsindicesr ) serializerr r isinstancestrlisttuplecolnames ValueErrormaskednpanymask __class__rndarraylenformat TypeErrortype sorted_dataargsortplatformsystem concatenate flatnonzerozipsortmetar_groups)r r rrname table_keys table_indexr!idx_sort stable_sortdiffsr#i0i1outout_keyss` rr r su766666$w$u &&    D5>)) !K4!K!KLLL| uT{'7 8 8  LDLLL __%A%A%A%AD%A%A%A_NN )55 $ D2:u- . .  z??c%jj ( (KRR OOSZZ   % V ] ]T       =:j%88=00<<  E  ""..00HH!)){);;H EEE%%''o''/DD EH%J NTFJqrrNj"o$EvN O OEnU##G #'#2#, 44 # #FB RUO " " " " //%/ * *C'#2#,'H(E""G1F -.c7BBBCK Js/G3HHcddlm}ddlm}t ||r||}|}t |t jstdt|t|t|kr=td t|t|| }||}t jdg|dd|ddkdgf}t j|}|||}t#||||dd |_|S) a> Get groups for ``column`` on specified ``keys``. Parameters ---------- column : Column object Column to group keys : Table or Numpy array of same length as col Grouping key specifier Returns ------- grouped_column : Column object with groups attr set accordingly rrrz(Keys input must be numpy array, but got z:Input keys array length {} does not match column length {}TNr r")r$rr rr%as_arrayr,r0r3r4r1r*r2r6r9r:r/rr>)columnr rrrBrDr#rGs rcolumn_group_byrLysp766666$**400}} dBJ ' 'QO4::OOPPP 4yyCKK H O OD 3v;;     ||~~H >D NTFDHSbS $9D6B C CEnU##G   6(+ , ,CsG$wss|:LMMMCK JrcJeZdZdZedZdZdZeZdZ dZ dZ dS) BaseGroupsa4 A class to represent groups within a table of heterogeneous data. - ``keys``: key values corresponding to each group - ``indices``: index values in parent table or column corresponding to group boundaries - ``aggregate()``: method to create new table by aggregating within groups cHt|tr|jn|jSN)r%r parent_column parent_tableselfs rparentzBaseGroups.parents&#-T<"@"@ WD  dFW rcd|_|SNr) _iter_indexrSs r__iter__zBaseGroups.__iter__s rc|j}|t|jdz kr<|j||j|dz}}|xjdz c_|j||StNr)rXr1r#rU StopIteration)rTiirErFs rnextzBaseGroups.nextsj   DL!!A% % %\"%t|BF';B    !  ;r"u% % rc|j}t|ttjfrD|j||j|dz}}|||}|jj||j_n|jdd|jdd}} ||||} }n"#t$r} td| d} ~ wwxYwtj t|t} t|| D] \}}d| ||< || }|jj||j_tjdgtj| |z g|j_|S)Nrr zHIndex item for groups attribute must be a slice, numpy mask or int arraydtypeTr)rUr%intr,integerr#groupsr _keys Exceptionr3zerosr1boolr;r9cumsum_indices) rTitemrUrErFrGindices0indices1i0si1serrr.s r __getitem__zBaseGroups.__getitem__se dS"*- . . N\$'dQh)?BB-C%}1$7CJ  !%crc!2DL4DhH #D>8D>S   .  8CKKt444Dc3-- # #B"RU ,C%}1$7CJ "$.1#rys7K7K1L"M"MCJ  s B B<'B77B<c2d|jjd|jdS)N)r/__name__r#rSs r__repr__zBaseGroups.__repr__s"D4>*DDT\DDDDrc0t|jdz Sr[)r1r#rSs r__len__zBaseGroups.__len__s4<  1$$rN) ru __module__ __qualname____doc__propertyrUrYr^__next__rqrvrxrrrrNrNs  X    H4EEE%%%%%rrNcNeZdZddZedZedZdZdZdS)rNcR||_|jj|_||_||_dSrP)rQinforRrjre)rTrQr#r s r__init__zColumnGroups.__init__s**).;  rc|jr|jjjS|j(t jdt |jgS|jSrW)rRrdr#rjr,arrayr1rQrSs rr#zColumnGroups.indicessN   %$+3 3}$xC(:$;$; <===}$rc@|jr|jjjS|jSrP)rRrdr rerSs rr zColumnGroups.keyss&   $+0 0: rc Pddlm}|jdd|jdd}}|jt |}t d}t ju}t ju} |sh|s|s|rb|r;t j |t j |jz } nT|r t j  |} n/t j fdt||D} | } nK#t$r>} t!djjjj| | d} ~ wwxYw| j} dD]7} t+| | t-j| (#t.$rY4wxYw| S)Nr) MaskedColumnr reduceatc<g|]\}}||Srr)rrErFfuncpar_cols rrz*ColumnGroups.aggregate..s/ R R R&"bgben!5!5 R R Rrz/Cannot aggregate column '{}' with type '{}': {})r?unitr2 descriptionr=)rKrr#rQr%hasattrr,summeanaddrdiffrr;r/rfr3r2rr?rasetattrgetattrAttributeError)rTrrrnror+rsum_case mean_casevalsrGrpout_infoattrrs ` @r aggregatezColumnGroups.aggregates((((((<$dl122&6S$G\224,,26>BGO   Tx T8 Ty T76??7C88274<;P;PPDD&!v==#66DDx R R R R RCSMM R R RSS##D))CC   AHHL%w|'93   8E  D $ d(C(CDDDD!     s++B.D E"$9EE"1$F F#"F#ctjt|t}t |D]\}}||||<||S)a Filter groups in the Column based on evaluating function ``func`` on each group sub-table. The function which is passed to this method must accept one argument: - ``column`` : `Column` object It must then return either `True` or `False`. As an example, the following will select all column groups with only positive values:: def all_positive(column): if np.any(column < 0): return False return True Parameters ---------- func : function Filter function Returns ------- out : Column New column with the aggregated rows. r`)r,emptyr1rh enumerate)rTrr.i group_columns rfilterzColumnGroups.filter%sV6xD ...( ) )OA|d<((DGGDzrNN) ruryrzrr|r#r rrrrrrrs} %%X%X"""HrcdeZdZddZedZedZdZdZedZ dS) rNc0||_||_||_dSrP)rRrjre)rTrRr#r s rrzTableGroups.__init__Hs(  rcvt|jdidd}|r |jjndS)z^ Return the names of columns in the parent table that were used for grouping. r=r!Fr)rr getr))rTr!s r key_colnameszTableGroups.key_colnamesMsD!( 62 > > B B #U! ! &;Bty!!Brcn|j(tjdt|jgS|jSrW)rjr,rr1rRrSs rr#zTableGroups.indices[s2 = 8QD$5 6 6788 8= rc|jdd}g}|j}|jD]}|jj|jvr||}n_ |jj |}n>#t$r1}tj t|tYd}~d}~wwxYw|||||jS)a Aggregate each group in the Table into a single row by applying the reduction function ``func`` to group values in each column. Parameters ---------- func : function Function that reduces an array of values to a single value Returns ------- out : Table New table with the aggregated rows. Nr )r=)r#rRcolumnsvaluesrr?rtakerdrr3warningswarnr&rappendr/r=)rTrrnout_colsrRcolnew_colrps rrzTableGroups.aggregatebsl3B3( '..00 % %Cx} 111((3--!ho77==GG M#c((,>???HHHH OOG $ $ $ $%%h\5F%GGGsA>> B9'B44B9ctjt|t}|j}t |D]\}}|||||<||S)a Filter groups in the Table based on evaluating function ``func`` on each group sub-table. The function which is passed to this method must accept two arguments: - ``table`` : `Table` object - ``key_colnames`` : tuple of column names in ``table`` used as keys for grouping It must then return either `True` or `False`. As an example, the following will select all table groups with only positive values in the non-key columns:: def all_positive(table, key_colnames): colnames = [name for name in table.colnames if name not in key_colnames] for colname in colnames: if np.any(table[colname] < 0): return False return True Parameters ---------- func : function Filter function Returns ------- out : Table New table with the aggregated rows. r`)r,rr1rhrr)rTrr.rr group_tables rrzTableGroups.filters`<xD ...( 'oo 6 6NA{d; 55DGGDzrc|jSrP)rerSs rr zTableGroups.keyss zrr) ruryrzrr|rr#rrr rrrrrGs  C CX C!!X! H H HD###JXr)r7rnumpyr,astropy.utils.exceptionsrindexr__all__rr rLrNrrrrrrs777777%%%%%% . ),,, aaaH,,,^<%<%<%<%<%<%<%<%~]]]]]:]]]@ddddd*dddddr