d|dZddlZddlZddlZddlmZddlmZm Z m Z ddl m Z ddl mZmZddlmZmZmZmZmZmZmZd ZGd d ejeZdS) z"Here is defined the VLArray class.N) hdf5extension) ObjectAtom VLStringAtom VLUnicodeAtominternal_to_flavor)Leafcalc_chunksize)convert_to_np_atomconvert_to_np_atom2idx2longcorrect_byteorderSizeTypeis_idxlazyattrz1.4ceZdZdZdZedZedZedZ edZ dfd Z fd Z d Z d ZdZdZdZdZddZdZdZdZdZdZdZd dZdZdZdZxZS)!VLArrayaThis class represents variable length (ragged) arrays in an HDF5 file. Instances of this class represent array objects in the object tree with the property that their rows can have a *variable* number of homogeneous elements, called *atoms*. Like Table datasets (see :ref:`TableClassDescr`), variable length arrays can have only one dimension, and the elements (atoms) of their rows can be fully multidimensional. When reading a range of rows from a VLArray, you will *always* get a Python list of objects of the current flavor (each of them for a row), which may have different lengths. This class provides methods to write or read data to or from variable length array objects in the file. Note that it also inherits all the public attributes and methods that Leaf (see :ref:`LeafClassDescr`) already provides. .. note:: VLArray objects also support compression although compression is only performed on the data structures used internally by the HDF5 to take references of the location of the variable length data. Data itself (the raw data) are not compressed or filtered. Please refer to the `VLTypes Technical Note `_ for more details on the topic. Parameters ---------- parentnode The parent :class:`Group` object. name : str The name of this node in its parent group. atom An `Atom` instance representing the *type* and *shape* of the atomic objects to be saved. title A description for this node (it sets the ``TITLE`` HDF5 attribute on disk). filters An instance of the `Filters` class that provides information about the desired I/O filters to be applied during the life of this object. expectedrows A user estimate about the number of row elements that will be added to the growable dimension in the `VLArray` node. If not provided, the default value is ``EXPECTED_ROWS_VLARRAY`` (see ``tables/parameters.py``). If you plan to create either a much smaller or a much bigger `VLArray` try providing a guess; this will optimize the HDF5 B-Tree creation and management process time and the amount of memory used. .. versionadded:: 3.0 chunkshape The shape of the data chunk to be read or written in a single HDF5 I/O operation. Filters are applied to those chunks of data. The dimensionality of `chunkshape` must be 1. If ``None``, a sensible value is calculated (which is recommended). byteorder The byteorder of the data *on disk*, specified as 'little' or 'big'. If this is not specified, the byteorder is that of the platform. track_times Whether time data associated with the leaf are recorded (object access time, raw data modification time, metadata change time, object birth time); default True. Semantics of these times depend on their implementation in the HDF5 library: refer to documentation of the H5O_info_t data structure. As of HDF5 1.8.15, only ctime (metadata change time) is implemented. .. versionadded:: 3.4.3 .. versionchanged:: 3.0 *parentNode* renamed into *parentnode*. .. versionchanged:: 3.0 The *expectedsizeinMB* parameter has been replaced by *expectedrows*. Examples -------- See below a small example of the use of the VLArray class. The code is available in :file:`examples/vlarray1.py`:: import numpy as np import tables as tb # Create a VLArray: fileh = tb.open_file('vlarray1.h5', mode='w') vlarray = fileh.create_vlarray( fileh.root, 'vlarray1', tb.Int32Atom(shape=()), "ragged array of ints", filters=tb.Filters(1)) # Append some (variable length) rows: vlarray.append(np.array([5, 6])) vlarray.append(np.array([5, 6, 7])) vlarray.append([5, 6, 9, 8]) # Now, read it through an iterator: print('-->', vlarray.title) for x in vlarray: print('%s[%d]--> %s' % (vlarray.name, vlarray.nrow, x)) # Now, do the same with native Python strings. vlarray2 = fileh.create_vlarray( fileh.root, 'vlarray2', tb.StringAtom(itemsize=2), "ragged array of strings", filters=tb.Filters(1)) vlarray2.flavor = 'python' # Append some (variable length) rows: print('-->', vlarray2.title) vlarray2.append(['5', '66']) vlarray2.append(['5', '6', '77']) vlarray2.append(['5', '6', '9', '88']) # Now, read it through an iterator: for x in vlarray2: print('%s[%d]--> %s' % (vlarray2.name, vlarray2.nrow, x)) # Close the file. fileh.close() The output for the previous script is something like:: --> ragged array of ints vlarray1[0]--> [5 6] vlarray1[1]--> [5 6 7] vlarray1[2]--> [5 6 9 8] --> ragged array of strings vlarray2[0]--> ['5', '66'] vlarray2[1]--> ['5', '6', '77'] vlarray2[2]--> ['5', '6', '9', '88'] .. rubric:: VLArray attributes The instance variables below are provided in addition to those in Leaf (see :ref:`LeafClassDescr`). .. attribute:: atom An Atom (see :ref:`AtomClassDescr`) instance representing the *type* and *shape* of the atomic objects to be saved. You may use a *pseudo-atom* for storing a serialized object or variable length string per row. .. attribute:: flavor The type of data object read from this leaf. Please note that when reading several rows of VLArray data, the flavor only applies to the *components* of the returned Python list, not to the list itself. .. attribute:: nrow On iterators, this is the index of the current row. .. attribute:: nrows The current number of rows in the array. .. attribute:: extdim The index of the enlargeable dimension (always 0 for vlarrays). VLARRAYc|jjS)z9The NumPy ``dtype`` that most closely matches this array.)atomdtypeselfs .lib/python3.11/site-packages/tables/vlarray.pyrz VLArray.dtypesyc|jfS)zThe shape of the stored array.)nrowsrs rshapez VLArray.shapes }rc td)z The HDF5 library does not include a function to determine size_on_disk for variable-length arrays. Accessing this attribute will raise a NotImplementedError. z)size_on_disk not implemented for VLArrays)NotImplementedErrorrs r size_on_diskzVLArray.size_on_disks""MNNNrc*|S)aq The size of this array's data in bytes when it is fully loaded into memory. .. note:: When data is stored in a VLArray using the ObjectAtom type, it is first serialized using pickle, and then converted to a NumPy array suitable for storage in an HDF5 file. This attribute will return the size of that NumPy representation. If you wish to know the size of the Python objects after they are loaded from disk, you can use this `ActiveState recipe `_. )_get_memory_sizers rsize_in_memoryzVLArray.size_in_memorys"$$&&&rNTc d|_ |dux|_} ||_ ||_ ||jjd}||_ d|_ d|_ d|_ d|_ d|_ d|_ d|_ d|_ d|_ d|_ ||_ d|_ d|_ d|_ | r|t+|t,t.jfr|f} t3|}n-#t4$r t5dt7|zwxYwt9|dkrt;d|t3d|D|_t=||| ||| | dS)NEXPECTED_ROWS_VLARRAYFrzI`chunkshape` parameter must be an integer or sequence and you passed a %srz&`chunkshape` rank (length) must be 1: c34K|]}t|VdS)N)r).0ss r z#VLArray.__init__..Ls(&G&Gqx{{&G&G&G&G&G&Gr) _v_version_v_new _v_new_title_v_new_filters_v_fileparams_v_expectedrows _v_chunkshape_start_stop_step _nrowsread_startb_stopb_row_initlistarrrnrowrextdim isinstanceintnpintegertuple TypeErrortypelen ValueErrorsuper__init__) r parentnodenamertitlefilters expectedrows chunkshape byteorder_log track_timesnew __class__s rrJzVLArray.__init__s / ,, c?!&%3  %-45LML+ "D 5 5 2G . / 2 M *   A 6 M  H:)*sBJ&788 +(]  >":..  > > >*,0,<,<=>>> >:!## j$.J"1222!&&G&GJ&G&G&G!G!GD  T3"D+ 7 7 7 7 7s C++*DcVtd|_dS)Nd)rI_g_post_init_hook nrowsinbuf)rrUs rrXzVLArray._g_post_init_hookQs$ !!###rcx|j}||zdz }t|}||z}|dkrd}t|fS)z&Calculate the size for the HDF5 chunk.irr) _basesizer r)rrOelemsize expected_mb chunksizerPs r_calc_chunkshapezVLArray._calc_chunkshapeVsT>#X- 9 ";// (* ??J$$&&rc|j}t|_tjtj|jdk}|dkrtdt|ds4|j j |_ |j j |_ |j j|_n$|j |_ |j |_ |j|_|j|_|j|_|j||j|_t-d|_|j$t3|jt4j|_||j|_t|ds|j|j_ |jS)z.Create a variable length array (ragged array).rzPWhen creating VLArrays, none of the dimensions of the Atom instance can be zero.size)!r obversionr-rBsumarrayrrHhasattrbaser _atomicdtypera _atomicsizeitemsizer[rF _atomictype _atomicshaper4r_r3rrrQrsys _create_arrayr/ _v_objectidkindattrs PSEUDOATOM)rrzerodimss r _g_createzVLArray._g_creatersUy#6"(4:..!344 a<<ABB BtV$$ + $ D #y~D !Y/DNN $ D #yD !]DN9 J   %!%!6!6t7K!L!LD a[[  > !.ty#-HHDN --d.?@@tV$$ .$(IDJ !rc|\|_|_|_}d|jvr]|jj}|dkrt }n|dkrt}nt|dkrt}n_td|z|j j dddkr5|jj }|d krt }n|d krt}||_ |jS) z+Get the metadata info for an array in file.rqvlstring vlunicodeobjectz"pseudo-atom name ``%s`` not known.Nr1VLStringObject) _open_arrayrnrr4rprqrrrrHr1format_versionFLAVORr)rrroflavor1xs r_g_openzVLArray._g_opens      ?$*d&8$ 4: % %:(Dz!!#~~$$$!!!|| 84?AAA \ (! , 3 3z(H:%%#~~X%%!|| rc tjtj|jdk}|dkrdS|j}|jj}t |j}t |trt |jj}n|jjf}d}||z }||krd}nU|dkr!||d|kr|d}|dd}n.|dkr|dkr |d}ntd|d|d|d|S) z.Return the number of objects in a NumPy array.rrN)rz The object 'z&' is composed of elements with shape 'z1', which is not compatible with the atom shape ('z').) rBrcrdrrrGr@rDrH) rnparrrrr atom_shapeshapelen atomshapelendiflennobjectss r _getnobjectszVLArray._getnobjectss-6"(5;//1455 a<<1 Y_ u{## j% ( ( ty//LL)/+JLL( J  HHkkeFGGn ::QxH!""IEE 4  HMMQxHH*5:UUEEE:::OPP Prch|jjdkrtd|jz|jjS)aGet the enumerated type associated with this array. If this array is of an enumerated type, the corresponding Enum instance (see :ref:`EnumClassDescr`) is returned. If it is not of an enumerated type, a TypeError is raised. enumz)array ``%s`` is not of an enumerated type)rrorE _v_pathnamerrs rget_enumzVLArray.get_enums? 9>V # #G"./00 0y~rc||j|j}t |ds||}|j}n0 t|n#t$rtdwxYw|}t|dkr&t||}| |}nd}d}| |||xj dz c_ dS)aAdd a sequence of data to the end of the dataset. This method appends the objects in the sequence to a *single row* in this array. The type and shape of individual objects must be compliant with the atoms in the array. In the case of serialized objects and variable length strings, the object or string to append is itself the sequence. razargument is not a sequencerNr) _g_check_openr1_check_writablerretoarrayrfrGrEr r_appendr)rsequencerstatomrrs rappendzVLArray.appends  $$&&&ytV$$ ||H--HYFF >H  > > > <=== >F x==1  (&99E((//HHHE UH%%% a s #A33B c||||\|_|_|_||S)aoIterate over the rows of the array. This method returns an iterator yielding an object of the current flavor for each selected row in the array. If a range is not supplied, *all the rows* in the array are iterated upon. You can also use the :meth:`VLArray.__iter__` special method for that purpose. If you only want to iterate over a given *range of rows* in the array, you may use the start, stop and step parameters. Examples -------- :: for row in vlarray.iterrows(step=4): print('%s[%d]--> %s' % (vlarray.name, vlarray.nrow, row)) .. versionchanged:: 3.0 If the *start* parameter is provided and *stop* is None then the array is iterated from *start* to the last line. In PyTables < 3.0 only one element was returned. )_process_ranger5r6r7 _init_loop)rstartstopsteps riterrowszVLArray.iterrowssB4150C0C 411-dj$*  rcp|js.d|_|j|_d|_||S)azIterate over the rows of the array. This is equivalent to calling :meth:`VLArray.iterrows` with default arguments, i.e. it iterates over *all the rows* in the array. Examples -------- :: result = [row for row in vlarray] Which is equivalent to:: result = [row for row in vlarray.iterrows()] rr)r<r5rr6r7rrs r__iter__zVLArray.__iter__2s:&z DKDJDJ OO    rc|j|_|j|_d|_d|_t |j|jz |_dS)z)Initialization for the __iter__ iterator.TN)r5r8r9r;r<rr7r>rs rrzVLArray._init_loopOs@+{   T[4:566 rc|j|jkrd|_t|jdz|jks |jdkrZ|j|j|jzz|_| |j|j|j|_ d|_|j|_|xjdz c_|xj |jz c_ |xj|jz c_|j |jS)zGet the next element of the array during an iteration. The element is returned as a list of objects of the current flavor. Frrr) r8r6r< StopIterationr;rYr9r7r:readr=r>rs r__next__zVLArray.__next__Xs ?dj ( (DJ y1}//49q=="lTZ$/-II #yyt{DJOO  #{ IINII II #II OOtz )OO< * *rc|t|rytj|}||jkrt d|dkr ||jz }|||dzd\}}}||||dSt|trA||j |j |j \}}}||||St|ttfvst|t jr*||}||St d|)aGet a row or a range of rows from the array. If key argument is an integer, the corresponding array row is returned as an object of the current flavor. If key is a slice, the range of rows determined by it is returned as a list of objects of the current flavor. In addition, NumPy-style point selections are supported. In particular, if key is a list of row coordinates, the set of rows determined by it is returned. Furthermore, if key is an array of boolean values, only the coordinates where key is True are returned. Note that for the latter to work it is necessary that key list would contain exactly as many rows as the array has. Examples -------- :: a_row = vlarray[4] a_list = vlarray[4:1000:2] a_list2 = vlarray[[0,2]] # get list of coords a_list3 = vlarray[[0,-2]] # negative values accepted a_list4 = vlarray[numpy.array([True,...,False])] # array of bools zIndex out of rangerrInvalid index or slice: )rroperatorindexr IndexErrorrrr@slicerrrrFlistrDrBndarray_point_selection_read_coordinates)rkeyrrrcoordss r __getitem__zVLArray.__getitem__osZ8  #;; A.%%Cdj   !5666Qwwtz!"&"5"5c37A"F"F UD$99UD$//2 2 U # # A $ 3 3 38SX!/!/ E499UD$// / #YY4- ' ':c2:+F+F '**3//F))&11 1???@@ @rc t||D]b\}}||jkrtd|dkr ||jz }|}|j}t |ds||}|j}n|}t||}||}t|}| ||dzdd} t| }t||kr#tdt|d|d || dd<n6#t$r)} td |d |d | ddd | d d} ~ wwxYw| jdkr||| |ddS)z8Assign the `values` to the positions stated in `coords`.zFirst index out of rangerrarzLength of value (z,) is larger than number of elements in row ()NzValue parameter: 'z=' cannot be converted into an array object compliant vlarray[z ] row: 'z' The error was: <>)ziprrrrerrfr rr _read_arrayrGrH Exceptionra_modify) rrvaluesr>valueobject_rrrrexcs r_assign_valueszVLArray._assign_valuessvv..$ 4$ 4KD%tz!! !;<<<axx "G9D4(( ,,w//&w77E((//HD$$T4!8Q77:E5zzH5zzH$$ j>A%jjjj>Fhh"HIII J aaa J J J j;@%%:?(((CCC "IJJJ JzA~~ T5(333I$ 4$ 4sD E%$E  Ec||jt|r|g}|g}nt |t r<||j|j|j \}}}t|||}n_t|ttfvst |tjr||}nt#d||||dS)aNSet a row, or set of rows, in the array. It takes different actions depending on the type of the *key* parameter: if it is an integer, the corresponding table row is set to *value* (a record or sequence capable of being converted to the table structure). If *key* is a slice, the row slice determined by it is set to *value* (a record array or sequence of rows capable of being converted to the table structure). In addition, NumPy-style point selections are supported. In particular, if key is a list of row coordinates, the set of rows determined by it is set to value. Furthermore, if key is an array of boolean values, only the coordinates where key is True are set to values from value. Note that for the latter to work it is necessary that key list would contain exactly as many rows as the table has. .. note:: When updating the rows of a VLArray object which uses a pseudo-atom, there is a problem: you can only update values with *exactly* the same size in bytes than the original row. This is very difficult to meet with object pseudo-atoms, because :mod:`pickle` applied on a Python object does not guarantee to return the same number of bytes than over another object, even if they are of the same class. This effectively limits the kinds of objects than can be updated in variable-length arrays. Examples -------- :: vlarray[0] = vlarray[0] * 2 + 3 vlarray[99] = arange(96) * 2 + 3 # Negative values for the index are supported. vlarray[-99] = vlarray[5] * 2 + 3 vlarray[1:30:2] = list_of_rows vlarray[[1,3]] = new_1_and_3_rows rN)rr1rrr@rrrrrrangerFrrDrBrrrr)rrrrrrrs r __setitem__zVLArray.__setitem__s X  $$&&& #;; AUFGEE U # # A $ 3 3 38SX!/!/ E45$--FF #YY4- ' ':c2:+F+F '**3//FF???@@ @ FE*****rrc|||||\}}}||krg}n||||}|jt dsfd|D}n|jfd|D}|S)aGet data in the array as a list of objects of the current flavor. Please note that, as the lengths of the different rows are variable, the returned value is a *Python list* (not an array of the current flavor), with as many entries as specified rows in the range parameters. The start, stop and step parameters can be used to select only a *range of rows* in the array. Their meanings are the same as in the built-in range() Python function, except that negative values of step are not allowed yet. Moreover, if only start is specified, then stop will be set to start + 1. If you do not specify neither start nor stop, then *all the rows* in the array are selected. rac:g|]}|S) fromarray)r*arrrs r z VLArray.read..&s%AAA#$..--AAArc0g|]}t|Srr)r*rflavors rrz VLArray.read..*s$MMMc,S&99MMMr)r_process_range_readrrrer)rrrrr= outlistarrrrs @@rrz VLArray.read s"  44UD$GGtT D==GG&&udD99GytV$$ NAAAAAAAJJ[FMMMMWMMMJrc g}|D]O}||t|t|dzddP|S)z Read rows specified in `coords`.rr)rrrA)rrrowscoords rrzVLArray._read_coordinates-sW E EE KK #e**c%jj1na@@C D D D D rc t|||j|||j|| } d} ||||\}}}t d} d}t |jds|jjj}n |jj}t|||| zD]`}||| zz}||kr|}| |||d}|j d}| |||||zz }| dz } a| | _ | |fS)z2Private part of Leaf.copy() for each kind of leaf.)rMrNrOrPrRrrra)rrr) rrr3rrrerfrarrrrr)rgrouprLrrrrMrNrPrRkwargsrwrY nrowscopiednbytesatomsizestart2stop2rrs r_g_copy_with_statszVLArray._g_copy_with_stats4s8  4%-* "66udDIIdqkk ty&)) &y~*HHy~HE4 ):;;  FTJ..Et||$$6D$II!LE{1~H NN5( + + + h) )F 1 KK" rc J|d|jd|jd|jd|j S)z;This provides more metainfo in addition to standard __str__z atom = z byteorder = z nrows = z flavor = )rrQrrrs r__repr__zVLArray.__repr__YsV )~ : K  r)Nr&NNNNTT)NNN)NNr)__name__ __module__ __qualname____doc__ _c_classidrrpropertyrr"r%rJrXr_rsrrrrrrrrrrrrrrr __classcell__)rUs@rrrsppfJ XXOOXO''X'$;=,0,0(,Z7Z7Z7Z7Z7Z7x '''8) ) ) V   8###J   $$$L>:777+++.1A1A1Af'4'4'4R>+>+>+BB# # # Jrr)rrrlnumpyrBr&rrrrrrr leafr r utilsr r rrrrrrbrrrrrs'(( 9999999999&&&&&&&&&&&&&&                    G G G G G m#TG G G G G r