tf*ddlmZddlZddlZddlmZddlmZddlm Z ddl m Z ddl Z ddlmZddlmZmZdd lmZdd lmZdd lmZdd lmZdd lmZmZdZdZdZ dZ!ddZ"y)) annotationsN)Counter)reduce)product)mul)config)Arraynormalize_chunks)meta_from_array)tokenize)flatten)HighLevelGraph)M parse_bytesa Dask's reshape only supports operations that merge or split existing dimensions evenly. For example: >>> x = da.ones((6, 5, 4), chunks=(3, 2, 2)) >>> x.reshape((3, 2, 5, 4)) # supported, splits 6 into 3 & 2 >>> x.reshape((30, 4)) # supported, merges 6 & 5 into 30 >>> x.reshape((4, 5, 6)) # unsupported, existing dimensions split unevenly To work around this you may call reshape in multiple passes, or (if your data is small enough) call ``compute`` first and handle reshaping in ``numpy`` directly. c  tdDsJtdz }t|dz }ttDcgc]}d}}tt|Dcgc]}d}}|dk\s|dk\r|||k(r|||<|||<|dz}|dz}1|}||} |dk(r d||<|dz}ni| dk(r d||<|dz}nX|| kro|dz } | dk\r=tt| |dz| kr$| dz} | dk\rtt| |dz| kr$tt| |dz| k7rt t tfdt|DrKt|dzD] }|||< |tjtt| |z||<nt| dz|dzD] }|f||< tttt| dz|dz} t| | || <tt| dz|dztfd|| D||<|dz}| dz }n|| kDr|dz } | dk\r=tt|| |dz|kr$| dz} | dk\rtt|| |dz|kr$tt|| |dz|k7rt t tt|| dz|dz t| ||<t| dz|dzD] }||f||< t fd||D|| <| dz }|dz}|dk\r|dk\rt|t|fScc}wcc}w)Nc3<K|]}t|tywN) isinstancetuple).0cs \/var/www/html/software/conda/envs/higlass/lib/python3.12/site-packages/dask/array/reshape.py z"reshape_rechunk..$s6z!U#6sr)rc3FK|]}t||k(ywr)len)riinchunksinshapes rrz"reshape_rechunk..Ds#Ea3x{#wqz1Es!c3(K|] }|z ywr)rrprods rrz"reshape_rechunk..Rs-!"D1H-c3(K|] }|z ywrr!)rrcss rrz"reshape_rechunk..fs+QAG+Qr#) allrrangerrNotImplementedError_not_implemented_messagemathr"map expand_tuplercontract_tuple)routshaperiioirresult_inchunksresult_outchunksdindoutileftchunk_reductionoleftr%r"s` ` @@rreshape_rechunkr8#s 6X6 66 6 W B X B%*3w<%89t9O9&+CM&:;;; 'R1W 2;(2, &"*2,OB #+B< R !GB !GB bk| !8"&OB  !GB QY#' R !GB 4ZFE vc7526+BCdJ  vc7526+BCdJc752623t;)*BCCE59EErAv5A)1!OA&5'/|diiXeB/07( $uqy"q&17A*1!*OA&7#)c#x BQRF7S.T"U)5huo)W&c7519rAv#>?',-&5e&<-( $ !GBB 4ZFE1*Xeb1f-E!F!L 1*Xeb1f-E!F!Lc8EBF34;)*BCCXeai"q&9:B"0"r"BOB 519b1f- 5'/{n # 5',+Q_R=P+Q&Q U #B !GB 'R1WB  !5)9#: ::I:;s M, Mc&|dk(r|Sg}|D]`}|}t||z d}|d|zk\r1|jt||t|z}|d|zk\r1|sP|j|bt|t|k(sJt |S)z >>> expand_tuple((2, 4), 2) (1, 1, 2, 2) >>> expand_tuple((2, 4), 3) (1, 1, 1, 1, 2) >>> expand_tuple((3, 4), 2) (1, 2, 2, 2) >>> expand_tuple((7, 4), 3) (2, 2, 3, 1, 1, 2) r)maxappendintsumr)chunksfactoroutrxparts rr,r,ns{ C  1v:q!1t8m JJs4y ! TNA1t8m JJqM v;#c( "" " :ct||zdk(sJg}d}|D]*}||z }||z}||z}||z}|s|j|,t|S)zReturn simple chunks tuple such that factor divides all elements Examples -------- >>> contract_tuple((2, 2, 8, 4), 4) (4, 8, 4) r)r>r<r)r?r@rAresidualchunkdivgoods rr-r-st v; 1 $$ $ CH vo6>|  JJt   :rDc J ddlm}ddlm}t t ||}|Dcgc] }|dk7s | }}t |t |kr|t |t |z dkDr tdt |dk(r|jdk(r|S||jtt|dz  t fd|D}tjt|jr!tdt!|jztt|d|jk7r td |j|k(r|St#|t |}d t%||z} |j&dk(rt)t+|j-} | fd t |zzt.j0| |fi} t d |D} t3j4| | |g } t7| | | |St |j}t |}|s1||kDr,|j9t;||z Dcic]}|dc}}t=|j||j>\}}tt|Dcgc] }tA|c}|jBjDz}|5tGtIjJd}tIjJdd}n tG|}d}||kDr|d}tMjN||dnt|rrtQ|tQ|z}g}|D]:}||dkDr|jS|||xxdzcc<*|jSd<tU||||jB|}|j9|}tWtY|jZgg|Dcgc]}t;t |c}}tWtY| gg|Dcgc]}t;t |c}}tWtY|}t]|||Dcic]\}}}|t.j0||f} }}}t3j4| | |g } t7| | ||Scc}wcc}wcc}wcc}wcc}wcc}}}w)abReshape array to new shape Parameters ---------- shape : int or tuple of ints The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions. merge_chunks : bool, default True Whether to merge chunks using the logic in :meth:`dask.array.rechunk` when communication is necessary given the input array chunking and the output shape. With ``merge_chunks==False``, the input array will be rechunked to a chunksize of 1, which can create very many tasks. limit: int (optional) The maximum block size to target in bytes. If no limit is provided, it defaults to using the ``array.chunk-size`` Dask config value. Notes ----- This is a parallelized version of the ``np.reshape`` function with the following limitations: 1. It assumes that the array is stored in `row-major order`_ 2. It only allows for reshapings that collapse or merge dimensions like ``(1, 2, 3, 4) -> (1, 6, 4)`` or ``(64,) -> (4, 4, 4)`` .. _`row-major order`: https://en.wikipedia.org/wiki/Row-_and_column-major_order When communication is necessary this algorithm depends on the logic within rechunk. It endeavors to keep chunk sizes roughly the same when possible. See :ref:`array-chunks.reshaping` for a discussion the tradeoffs of ``merge_chunks``. See Also -------- dask.array.rechunk numpy.reshape r)PerformanceWarning)sanitize_indexrz&can only specify one unknown dimensionc30K|] }|dk(rn|yw)rMNr!)rs missing_sizes rrzreshape..sDa2gl14Dsz_Array chunk size or shape is unknown. shape: %s Possible solution with x.compute_chunk_sizes()z)total size of new array must be unchangedzreshape-)rc3"K|]}|f ywrr!)rds rrzreshape..s+t+s ) dependencies)metaNzarray.chunk-sizez array.slicing.split-large-chunksTaReshaping is producing a large chunk. To accept the large chunk and silence this warning, set the option >>> with dask.config.set(**{'array.slicing.split_large_chunks': False}): ... array.reshape(shape) To avoid creating the large chunks, set the option >>> with dask.config.set(**{'array.slicing.split_large_chunks': True}): ... array.reshape(shape)Explicitly passing ``limit`` to ``reshape`` will also silence this warning >>> array.reshape(shape, limit='128 MiB')) stacklevelauto)shapelimitdtypeprevious_chunks)/dask.array.corerKdask.array.slicingrLrr+r ValueErrorndimsizerrnpisnanr>rXstrr r npartitionsnextr __dask_keys__rreshaperfrom_collectionsr rechunkr'r8r?r;rZitemsizerrgetwarningswarnrr<r listrnamezip)!rBrX merge_chunksrYrKrLrO known_sizesrTrokeydskr?graphr3r4rr outchunksmax_chunksize_in_bytessplitmsgmatching_chunks chunk_planrAx2rin_keysout_keysshapesabrPs! @rrgrgs!T31 #ne, -E#/qBw1/K/ ;#e*$ u:K( (1 ,EF F u:?qvv{H%affvc;/J&JK DeDD xxAGG  =?B177| L  c5!&DEEww% 1c%j )D E* *D}}71??,-.wE **QYYU,CD+U++//cLUD&t44 agg,C u:D C$J IIU3:%67q!t7 8)!''5!((CHi#C))DQ#a&)DEHXHXX }FJJ'9:; =tDE"% =@  MM#1a @ %h/')2DDOJ  ."3'!+%%c*#C(A-(%%f-  . )gg ( I 8 B7BGG9Ix'H!c!f 'HIJGGTFHY%GeCFm%GHIH '9% &F7:8Wf7U V V 1e1qyy!U# # VC V  + +D#RD IE id 33y0L8*EX(I%G Vs( RR R R =R3R:R)TN)# __future__rr*rl collectionsr functoolsr itertoolsroperatorrnumpyradaskrr\r r dask.array.utilsr dask.baser dask.corer dask.highlevelgraphr dask.utilsrrr)r8r,r-rgr!rDrrsQ" 3,.% H;V>.J4rD