Cd)ddlmZddlZddlmZddlmZddlmZddl Z ddl m Z ddl mZddlmZdd lmZdd lmZdd lmZee jdd ZdZdZddZddZdS)) annotationsN)Iterator)wraps)Number)merge)Array) _numpy_122) percentile)tokenize)HighLevelGraphlinearct|}t|sd|fSt|trt|}|jjdkrRt |jj||}ddl }|j ||jj |jj |fSt|jjdkr'ddl }t||j|jfr|j}t'j|jt&jr||}|d}t ||||j}|ddkr+t1|d||d<||fSt'j|jt&jsd}t ||||fS)Ncategory)methodrDatetimeTZDtypei8nearest)len isinstancerlistdtypename np_percentilecatcodespandas Categorical from_codes categoriesorderedtype__name__SeriesIndexvaluesnp issubdtype datetime64viewastypeminnumber)aqrnresultpdr%a2s 5lib/python3.11/site-packages/dask/array/percentile.py _percentiler4s AA q66Qw!X GGw|z!!qu{Af===~((1CQW_UUWXXX AG}}!222 a")RX. / / A }QWbm,, [[  r1V444;;FLII Q4199F1Ivzz||44F1Iqy =") , , Af - - -q 00cPddlm}|}|||S)NrTDigest)crickr8update)r-r8ts r3_tdigest_chunkr<1s3 AHHQKKK Hr5cddlm}|}|j|tj||dz S)Nrr7gY@)r9r8rr&arrayquantile)qsdigestsr8r;s r3_percentiles_from_tdigestrB:sN A AGW 8AJJrEz** + ++r5defaultc ddlmddlm}m}gd}|vrt jdt}d|vr6trt jdt| d|r$td| |j d kstd t|tr|g}|||| }t!||}|j} t%j| t$jr|g| || d z j} ||| } ||vrt+d||dkrdkrt%j| t$jst%j| t$jreddlm} | ddd|zfdt3|D} d|z} | dft6|t9| fi}nt%j|d ddd<d|zfdt3|D} d|z} | dft<|gt?|j dzt9| fi}tC| |} tEj#| | |g}tI|| t?|ff| S)!uApproximate percentile of 1-D array Parameters ---------- a : Array q : array_like of float Percentile or sequence of percentiles to compute, which must be between 0 and 100 inclusive. method : {'linear', 'lower', 'higher', 'midpoint', 'nearest'}, optional The interpolation method to use when the desired percentile lies between two data points ``i < j``. Only valid for ``method='dask'``. - 'linear': ``i + (j - i) * fraction``, where ``fraction`` is the fractional part of the index surrounded by ``i`` and ``j``. - 'lower': ``i``. - 'higher': ``j``. - 'nearest': ``i`` or ``j``, whichever is nearest. - 'midpoint': ``(i + j) / 2``. .. versionchanged:: 2022.1.0 This argument was previously called "interpolation" internal_method : {'default', 'dask', 'tdigest'}, optional What internal method to use. By default will use dask's internal custom algorithm (``'dask'``). If set to ``'tdigest'`` will use tdigest for floats and ints and fallback to the ``'dask'`` otherwise. .. versionchanged:: 2022.1.0 This argument was previously called “method”. interpolation : str, optional Deprecated name for the method keyword argument. .. deprecated:: 2022.1.0 See Also -------- numpy.percentile : Numpy's equivalent Percentile function r)percentile_lookup) array_safemeta_from_array)rCdasktdigestzJIn Dask 2022.1.0, the `method=` argument was renamed to `internal_method=` interpolationzXIn Dask 2022.1.0, the `interpolation=` argument to percentile was renamed to `method= ` z0percentile() got an unexpected keyword argument z+Percentiles only implemented for 1-d arrayslike)rrM?)rz"`internal_method=` must be one of rIr )import_requiredr9z=crick is a required dependency for using the t-digest method.zpercentile_tdigest_chunk-c.i|]\}}|ft|fS)r<).0ikeyrs r3 zpercentile..s5   17CT1I,   r5zpercentile_tdigest-constant)modedzpercentile_chunk-c(i|]\}}|f|fSrQrQ)rRrSrTr4calc_qrrs r3rUzpercentile..s<   31I S&&9   r5z percentile-) dependencies)chunksmeta)%dask.array.dispatchrEdask.array.utilsrFrGwarningswarn FutureWarningr pop TypeErrorkeysndimNotImplementedErrorrrr rr&r'integer ValueErrorfloating dask.utilsrO enumerate __dask_keys__rBsortedpadmerge_percentilesrr]rr from_collectionsr)r-r.rinternal_methodkwargsrFrGallowed_internal_methodstokenrr^rOdskname2dsk2graphr4r[rs ` @@@r3r r CsREDDDDD<<<<<<<<=== ))) X    !&    M    O,,   Nv{{}} N N    6Q;;!"OPPP!V C 1??1--...A Q6 " "E GE }UBJ''SBe//!2D2DEEEKR ?1E * * *D666 K1I K K   9$$ h   ]5"+ . . 24-rz2R2R  /..... T   +U2    ;DQ__EVEV;W;W   &- 66#;;GH 1:...r "U*       #AOO$5$566    % AJ!3qx{+++s    T  C  +E3aS I I IE Ayl > > >>r5lowerTc ddlm}t|trt |}|||}t t t|}t |}| t |\}}t |}t t dt |||D}|sF|rtdtj t|ddz tj S|\}}}|dj j dkrTt||d |D|||}ddl} | j||dj|djStj|dj tjsd }t|t|ks t|t|krtd g} t ||D]w\} } tj|t|  } tj|| | d| d d<| d| d<| | z} | | xtj|}|tj| |}tj|}tj||}tj||}tj|}|||}|t;|z}|dkrtj|||}n%tj||d}tj||dd z }tj |t|d z |tj ||}tj!||}|dkr ||}n|dkr ||}n|dkrd||||zz}nk|d krVtj"|||z }tj"|||z }||k}|}||||<||}ntd|S)aCombine several percentile calculations of different data. Parameters ---------- finalq : numpy.array Percentiles to compute (must use same scale as ``qs``). qs : sequence of :class:`numpy.array`s Percentiles calculated on different sets of data. vals : sequence of :class:`numpy.array`s Resulting values associated with percentiles ``qs``. Ns : sequence of integers The number of data elements associated with each data set. method : {'linear', 'lower', 'higher', 'midpoint', 'nearest'} Specify the interpolation method to use to calculate final percentiles. For more information, see :func:`numpy.percentile`. Examples -------- >>> finalq = [10, 20, 30, 40, 50, 60, 70, 80] >>> qs = [[20, 40, 60, 80], [20, 40, 60, 80]] >>> vals = [np.array([1, 2, 3, 4]), np.array([10, 11, 12, 13])] >>> Ns = [100, 100] # Both original arrays had 100 elements >>> merge_percentiles(finalq, qs, vals, Ns=Ns) array([ 1, 2, 3, 4, 10, 11, 12, 13]) r)rFrLNc$g|] \}}}||||fSrQrQ)rRr.valNs r3 z%merge_percentiles..s)GGG91c1QGAsA;GGGr5zNo non-trivial arrays foundrcg|] }|j SrQ)r)rRvs r3rz%merge_percentiles..s///Q///r5rz3qs, vals, and Ns parameters must be the same length)shaperKr left)siderightr{highermidpointrNzVinterpolation method can only be 'linear', 'lower', 'higher', 'midpoint', or 'nearest')#r`rFrrrmapziprjr&fullrnanrrrqrrrrr r'r, empty_likediffappend concatenateargsorttakecumsumsuminterp searchsortedminimummaximumabs)finalqr@valsrNs raise_on_nanrFLr0r1countsr.rcount combined_valscombined_counts sort_order combined_q desired_qrvrrr{upperlower_residualupper_residualmaskindexs r3rqrqse:,+++++&(##f ZV , , ,F c$mm  B ::D z:b bB SGGBb0A0AGGG HIIA /  <:;; ;ws2a5zzA~rv...LBb Aw}Z''" B//$///\   ~((a1CT!W_UUU =a 2 2 4yyCGGs2ww#b''11NOOOFB 1 fCFF333GJJqqt44455abb Q4a   eN4((M j!7!7mLLLOM**JGM:66Mgoz::O?++JZ] 3 3 3FR I Yy*m < <z96BBB IGDDDqH 4]++a/666 4'' 4'' W  u%BB x  u%BB z ! ! e,}U/CCDBB y VJu$5 $ABBNVJu$5 $ABBN!N2DE+E$Ku%BB5  Ir5)r )r rC)r{NT) __future__rracollections.abcr functoolsrnumbersrnumpyr&tlzrdask.array.corerdask.array.numpy_compatr r r dask.baser dask.highlevelgraphr r4r<rBrqrQr5r3rsV""""""$$$$$$!!!!!!......??????......r}1111<   ,,,A?A?A?A?Hqqqqqqr5