U /e9-@sddlZddlZddlmZddlmZmZmZm Z m Z m Z m Z m Z ddlmZddlmZddlmZddlmZmZeeejfeje eejfejeeejfeje eejfeje ejjejjeeejfeeejjee ejd3d d Z eejjd4d d Z!e ejjd5ddZ"e #de#de #de #dddZ$e #de#dddZ%e #de#de #de #dddZ&e #de#dddZ'ddZ(e ejjddZ)e eejfd d!Z*d"d#Z+e,d$d%d&Z-e eejfd'd(Z.d)d*Z/Gd+d,d,eZ0Gd-d.d.e0Z1ed/d0e0d1d2Z2e23d0e1dS)6N)chunk)concatenate_lookup divide_lookup einsum_lookup empty_lookupnannumel_lookup numel_lookuppercentile_lookuptensordot_lookup)divide) ma_divide _percentile)CreationDispatchDaskBackendEntrypointlinearcCs t|||SNr )aqmethodr7/tmp/pip-unpacked-wheel-dbjnr7gq/dask/array/backends.py percentilesrcCs`tjj||d}dd|D}tdd|Dr8td|r\t|}t|dkr\|d|_|S) N)axiscSsg|]}t|dr|jqS) fill_value)hasattrr).0irrr &s z _concatenate..css|]}t|tjVqdSr) isinstancenpndarray)rfrrr 'sz_concatenate..zADask doesn't support masked array's with non-scalar `fill_value`sr)r ma concatenateany ValueErroruniquelenr)ZarraysroutZ fill_valuesrrr _concatenate#s   r,cs8z t|Wn2tk r>tt| dttd|Yn X|\zt}tWntk rzgd}YnXzt}tWntk rgd}YnX|j|j}|j|j}d}||krd}nlt|D]b}||kr d}qF|dkr(||7<|dkr||7<q|sTtdfddt|D} | } d} D]} | | 9} qzd| f} fd d| D}fd dt|D} | }d} D]} | | 9} q| df}fd d| D}||  | }|| |}t j ||}| ||S) Nrr$TFzshape-mismatch for sumcsg|]}|kr|qSrrrk)axes_arrrasz_tensordot..csg|] }|qSrrrr)as_rrrgscsg|]}|kr|qSrrr.)axes_brrriscsg|] }|qSrrr2)bsrrros) iter TypeErrorlistranger*shapendimr(Z transposeZreshaper r%dot)rbaxesnanbZndaZndbequalr/notinZ newaxes_aZN2rZ newshape_aZoldaZ newaxes_bZ newshape_bZoldbatZbtresr)r3r0r4r5r _tensordot3sj       rEcupycszddlddlm}tjjtjj|jt t jt t jt tjfdd}dS)Nr)r cs$|dd|ddj||S)NZcastingorder)popeinsum)argskwargsrFrr _cupy_einsums  z#register_cupy.._cupy_einsum)rFdask.array.dispatchr rregisterr!r&r tensordotrr_numel_arrayliker _nannumelr)r rMrrLr register_cupyws  rSZcupyxc szddlm}zddlmmWn,tk rL}ztd|W5d}~XYnXdfdd }t||t|tdS)Nr)spmatrixhstackvstackz>Stacking of sparse arrays requires at least CuPy version 8.0.0cs4|dkr|S|dkr |Sd|}t|dS)Nrr$zECan only concatenate cupy sparse matrices for axis in {0, 1}. Got %s)r(LrmsgrUrr_concat_cupy_sparsesz+register_cupyx.._concat_cupy_sparse)r) Zcupyx.scipy.sparserTrVrW ImportErrorrrOr _tensordot_scipy_sparse)rTer[rrUrregister_cupyxs  r_sparsecCsHddl}t|j|jt|j|jt|jtt |jt dS)Nr) r`rrOZCOOr&r rPr_numel_ndarrayr_nannumel_sparse)r`rrrregister_sparses rcscipycs:ddldfdd }tjj|tjjtdS)Nrcs<|dkrj|S|dkr(j|Sd|}t|dS)Nrr$zFCan only concatenate scipy sparse matrices for axis in {0, 1}. Got %s)r`rWrVr(rXrdrrr,s  z+register_scipy_sparse.._concatenate)r)Z scipy.sparserrOr`rTr r])r,rrerregister_scipy_sparses rfcCs|j|jkrdksntt|dt|dkrBdksHnt|d\}|d\}|dkrl|dkspt|j||j|kst|dkr|dkr|j|S|dkr|dkr|j|jS|dkr|dkr||S|dkr|dkr||jSdS)Nr-rr$)rr$)r;AssertionErrorr*r:T)rr=r>Za_axisZb_axisrrrr]s*    r]cKstjt|f|S)z'Numel implementation for masked arrays.)rsumr Z ones_likexrKrrr _numel_maskedsrlcKst|fddi|S)zJNumel implementation for arrays that want to return numel of type ndarray.coerce_np_ndarrayT_numelrjrrrrasracKst|fddi|S)zKNumel implementation for arrays that want to return numel of the same type.rmFrnrjrrrrQsrQ)rmc s,|j|dd}|dd|dtj}dkrtj|d}|dkrN|S|rjtjdt||dStj||dt|d Stt t fsgt fd d D}|d krt fd d t tD}n t fdd t tD}|rt tj||d|Stj||||d SdS)a  A reduction to count the number of elements. This has an additional kwarg in coerce_np_ndarray, which determines whether to ensure that the resulting array is a numpy.ndarray, or whether we allow it to be other array types via `np.full_like`. keepdimsFrNdtype)rq)r$)r:rrq)r:rqc3s|]}|VqdSrrrZdim)r:rrr# sz_numel..Tc3s"|]}|kr|ndVqdS)r$Nrrrrr:rrr#sc3s|]}|kr|VqdSrrrrrsrrr#s)r:getr Zfloat64prodfullr*Z full_likertupler8mathr9Z broadcast_toarray)rkrmrKrprqruZ new_shaperrsrros,    rocKstjt|f|S)z;A reduction to count the number of elements, excluding nans)rrir isnanrjrrrrRsrRcKs"t|f|}t|dr|S|S)a  A reduction to count the number of elements in a sparse array, excluding nans. This will in general result in a dense matrix with an unpredictable fill value. So make it official and convert it to dense. https://github.com/dask/dask/issues/7169 todense)rRrr{)rkrKnrrrrb s rbc@seZdZdZeddZedddddZeddddd Zedddd d Z edddd d Z eddddddZ dS)ArrayBackendEntrypointzjDask-Array version of ``DaskBackendEntrypoint`` See Also -------- NumpyBackendEntrypoint cCstdS)zReturn the backend-specific RandomState class For example, the 'numpy' backend simply returns ``numpy.random.RandomState``. NNotImplementedErrorselfrrr RandomState6sz"ArrayBackendEntrypoint.RandomStateN)rqmetacKstdS)ztCreate an array of ones Returns a new array having a specified shape and filled with ones. Nr~r:rqrrKrrrones?szArrayBackendEntrypoint.onescKstdS)zvCreate an array of zeros Returns a new array having a specified shape and filled with zeros. Nr~rrrrzerosHszArrayBackendEntrypoint.zeroscKstdS)z`Create an empty array Returns an uninitialized array having a specified shape. Nr~rrrremptyQszArrayBackendEntrypoint.emptycKstdS)zCreate a uniformly filled array Returns a new array having a specified shape and filled with fill_value. Nr~)r:rrqrrKrrrrvYszArrayBackendEntrypoint.fullr$cKstdS)zCreate an ascending or descending array Returns evenly spaced values within the half-open interval ``[start, stop)`` as a one-dimensional array. Nr~)startstopsteprqrrKrrrarangebszArrayBackendEntrypoint.arange)Nr$) __name__ __module__ __qualname____doc__propertyr staticmethodrrrrvrrrrrr}.s r}c@seZdZeddZdS)NumpyBackendEntrypointcCstjjSr)r randomrrrrrrmsz"NumpyBackendEntrypoint.RandomStateN)rrrrrrrrrrlsrrynumpyarray_creation_dispatch) module_namedefaultZentrypoint_classname)r)r)r-)4rxrr Z dask.arrayrrNrrrrrrr r Zdask.array.numpy_compatr Z np_divider Zdask.array.percentilerZ dask.backendsrrrOobjectr!r&rPrIrr%Z masked_arrayrr,rEZ register_lazyrSr_rcrfr]rlrarQboolrorRrbr}rrZregister_backendrrrrsn (         C      ( >