B q\6@sddlZddlZddlZddlmZddlmZddgZddZ d d Z d d Z Gd ddZ Gddde Z Gddde ZdS)N)get_index_by_names)AstropyUserWarning TableGroups ColumnGroupsc Cs |d t||SQRXdS)NZdiscard_on_copy)Z index_mode_table_group_by)tablekeysr 3lib/python3.7/site-packages/astropy/table/groups.pytable_group_bys r cs4ddlm}ddlm}t|tr(|f}t|ttfrxH|D]@}|jkrXt d |j r3sz#_table_group_by..F)copyTz;Input keys array length {0} does not match table length {1}NzIKeys input must be string, list, tuple, Table or numpy array, but got {0}Z mergesort)Zkind)ZDarwinZWindowsgrouped_by_table_cols)indicesr ) rr serializer isinstancestrlisttuplecolnames ValueErrorformatmaskednpanymask __class__rndarraylen TypeErrortypeZ sorted_dataargsortplatformsystem concatenate flatnonzerozipsortmetar_groups)rr r rnameZ table_keysZ table_indexridx_sortZ stable_sortdiffsri0i1outZout_keysr )rr rsX          ( $  rcCsddlm}ddlm}t||r2||}|}t|tjsPtd t |t |t |krxt d t |t || }||}tdg|dd|ddkdgf}t|}|||}t||||ddd |_|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 r)r )rz+Keys input must be numpy array, but got {0}z)rr"__name__r)r;r r r __repr__szBaseGroups.__repr__cCst|jdS)Nr)r$r)r;r r r __len__szBaseGroups.__len__N) rL __module__ __qualname____doc__propertyr<r>r@__next__rKrMrNr r r r r8s r8c@s>eZdZd ddZeddZeddZdd Zd d ZdS) rNcCs||_|j|_||_||_dS)N)r9r:rGrD)r;r9rr r r r __init__szColumnGroups.__init__cCs8|jr|jjjS|jdkr.tdt|jgS|jSdS)Nr)r:rCrrGrarrayr$r9)r;r r r rs   zColumnGroups.indicescCs|jr|jjjS|jSdS)N)r:rCr rD)r;r r r r s zColumnGroups.keysc s ddlm}|jdd|jdd}}|jt|}td}tjk}tjk}yl|s|sj|sj|r|rtj |t |j} q|rtj |} n t fddt ||D} Wn,tk rtdjjjjYnXj| jjjjjjjjjjd} | S) Nr) MaskedColumnrreduceatcs g|]\}}||qSr r )rr3r4)funcpar_colr r rsz*ColumnGroups.aggregate..z-Cannot aggregate column '{0}' with type '{1}')datar0 descriptionunitrr.)r6rVrr9rhasattrrsumZmeanaddrWZdiffrUr,rEr%rinfor0rAr"r[r\r.) r;rXrVrIrJrrWZsum_caseZ mean_caseZvalsr5r )rXrYr aggregates4     $ zColumnGroups.aggregatecCs<tjt|td}x t|D]\}}||||<qW||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. )rA)remptyr$rF enumerate)r;rXr!iZ group_columnr r r filterszColumnGroups.filter)NN) rLrOrPrTrRrr rarer r r r rs    c@sJeZdZdddZeddZeddZdd Zd d Zed d Z dS)rNcCs||_||_||_dS)N)r:rGrD)r;r:rr r r r rT4szTableGroups.__init__cCs&t|jdidd}|r"|jjSdS)z^ Return the names of columns in the parent table that were used for grouping. r.rFr )getattrr getr)r;rr r r key_colnames9s zTableGroups.key_colnamescCs(|jdkrtdt|jgS|jSdS)Nr)rGrrUr$r:)r;r r r rEs zTableGroups.indicesc Cs|jdd|jdd}}g}|j}x||jD]n}|jj|jkrR||}nFy|j |}Wn4t k r}zt t |tw4Wdd}~XYnX||q4W|j||jdS)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. Nrr)r.)rr:columnsvaluesr`r0rhZtakerCrar%warningswarnrrappendr"r.) r;rXrIrJZout_colsr:colZnew_colerrr r r raLs zTableGroups.aggregatecCsDtjt|td}|j}x"t|D]\}}|||||<q"W||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. )rA)rrbr$rFrhrc)r;rXr!rhrdZ group_tabler r r reos zTableGroups.filtercCs|jS)N)rD)r;r r r r szTableGroups.keys)NN) rLrOrPrTrRrhrrarer r r r r r3s   #%)r(rkZnumpyrindexrZastropy.utils.exceptionsr__all__r rr7r8rrr r r r s  \-9\