CdUddlmZddlZddlZddlZddlmZmZddlmZddl m Z ddl m Z ddl ZddlmZddlmZmZmZmZmZmZdd lmZdd lmZdd lmZdd lmZdd l m!Z!m"Z"m#Z#GddZ$dIdZ%GddZ&dZ'dJdZ(dZ)dZ*dZ+dZ,dZ-dZ.dddddZ/ iZ0de1d <e Z2d!Z3 e3d"Z4e3d#Z5e3d$Z6e3d%Z7e3d&Z8e3d'Z9e3d(Z:e3d)Z;e3d*Z<e3d+Z=e3d,Z>e3d-Z?e3d.Z@e3d/ZAe3d0ZBe3d1ZCe3d2ZDe3d3ZEe3d4ZFe3d5ZGe3d6ZHe3d7ZIe3d8ZJe3d9ZKe3d:ZLe3d:ZMe3d;ZNe3d<ZOe3d=ZPe3d>ZQe3d?ZRe3d@ZSe3dAZTe3dBZUe3dCZVe3dDZWe3dEZXe3dFZYe3dGZZe3dHZ[dS)K) annotationsN)chainproduct)Integral)getitem)Lock)array_creation_dispatch)Arrayasarraybroadcast_shapes broadcast_tonormalize_chunksslices_from_chunks)arange) asarray_safe)tokenize)HighLevelGraph) derived_fromrandom_state_datatypenamecH eZdZdZdZdZedZedZe e j j dd6d Z e e j j dd6d Ze e j j dd6d Ze e j j d d7dZe e j j dd8dZe e j j dd6dZe e j j dd8dZe e j j dd6dZe e j j dd9dZe e j j dd6dZe e j j ddde jdd fdZe e j j dd9dZe e j j dd9dZe e j j dd9dZe e j j dd6dZe e j j dd6dZe e j j d d:d Ze e j j dd6d!Ze e j j dd6d"Z e e j j dd6d#Z!e e j j dd9d$Z"e e j j dd6d%Z#e e j j dd&Z$e e j j dd8d'Z%e e j j dd6d(Z&e e j j dde j'dd fd)Z e e j j dd8d*Z(e e j j dd6d+Z)e e j j dd6d,Z*e e j j dd6d-Z+e e j j dd6d.Z,e e j j dd6d/Z-e e j j dd6d0Z.e e j j dd9d1Z/e e j j dd6d2Z0e e j j dd6d3Z1e e j j dd6d4Z2e e j j dd6d5Z3dS); Generatora Container for the BitGenerators. ``Generator`` exposes a number of methods for generating random numbers drawn from a variety of probability distributions and serves as a replacement for ``RandomState``. The main difference between the two is that ``Generator`` relies on an additional ``BitGenerator`` to manage state and generate the random bits, which are then transformed into random values from useful distributions. The default ``BitGenerator`` used by ``Generator`` is ``PCG64``. The ``BitGenerator`` can be changed by passing an instantiated ``BitGenerator`` to ``Generator``. The function :func:`dask.array.random.default_rng` is the recommended way to instantiate a ``Generator``. .. warning:: No Compatibility Guarantee. ``Generator`` does not provide a version compatibility guarantee. In particular, as better algorithms evolve the bit stream may change. Parameters ---------- bit_generator : BitGenerator BitGenerator to use as the core generator. Notes ----- In addition to the distribution-specific arguments, each ``Generator`` method takes a keyword argument `size` that defaults to ``None``. If `size` is ``None``, then a single value is generated and returned. If `size` is an integer, then a 1-D array filled with generated values is returned. If `size` is a tuple, then an array with that shape is filled and returned. The Python stdlib module `random` contains pseudo-random number generator with a number of methods that are similar to the ones available in ``Generator``. It uses Mersenne Twister, and this bit generator can be accessed using ``MT19937``. ``Generator``, besides being Dask-aware, has the advantage that it provides a much larger number of probability distributions to choose from. All ``Generator`` methods are identical to ``np.random.Generator`` except that they also take a `chunks=` keyword argument. ``Generator`` does not guarantee parity in the generated numbers with any third party library. In particular, numbers generated by `Dask` and `NumPy` will differ even if they use the same seed. Examples -------- >>> from numpy.random import PCG64 >>> from dask.array.random import Generator >>> rng = Generator(PCG64()) >>> rng.standard_normal().compute() # doctest: +SKIP array(0.44595957) # random See Also -------- default_rng : Recommended constructor for `Generator`. np.random.Generator c||_dSN)_bit_generator)self bit_generators 1lib/python3.11/site-packages/dask/array/random.py__init__zGenerator.__init__^s+cR|jj}|d|jjjzdzz }|S)N()) __class____name__r)r_strs r__str__zGenerator.__str__as.~& d)3<z#Generator.choice..s. A ABs2ww A A A A A Ar c 8i|]\}}}|t||fS) _choice_rng) rWkbitgenr:r?axisrHreplaceshuffles r z$Generator.choice..sB   64  VQgq$H   r  dependenciesmeta) _choice_validate_paramslistr_spawn_bitgensrrUrziprfrom_collectionsr )rr?r:r`rHr_rar;rfrdsizesbitgensnamekeysdskgraphs ` ```` rchoicezGenerator.choice~s0( $D!T7AtV L L      Wf%&& !4c%jjAA$x T61gq$( (  vB A A& A A ABBB        #&tWe#<#<    /c UUUUD&t4444r ?c &t|d|f||d|SN exponentialr9r<rscaler:r;rAs rrvzGenerator.exponential2 - -1&  DJ   r c (t|d||f||d|SNfr9r<rdfnumdfdenr:r;rAs rr|z Generator.f%$UEVVVVvVVVr c (t|d||f||d|SNgammar9r<rshaperxr:r;rAs rrzGenerator.gamma4 '5% .26  EK   r c &t|d|f||d|SN geometricr9r<rrHr:r;rAs rrzGenerator.geometric#$ QST&SSFSSSr c (t|d||f||d|SNgumbelr9r<rlocrxr:r;rAs rrzGenerator.gumbel4 (C -1&  DJ   r c *t|d|||f||d|SNhypergeometricr9r<rngoodnbadnsampler:r;rAs rrzGenerator.hypergeometric?             r Fc ,t|d|f|||||d|S)Nintegers)highr:dtypeendpointr;r<)rlowrr:rrr;rAs rrzGenerator.integerssD           r c (t|d||f||d|SNlaplacer9r<rs rrzGenerator.laplace4 )S% .26  EK   r c (t|d||f||d|SNlogisticr9r<rs rrzGenerator.logistic4 *c5 /3F  FL   r c (t|d||f||d|SN lognormalr9r<rmeansigmar:r;rAs rrzGenerator.lognormal4 +tU 15f  HN   r c &t|d|f||d|SN logseriesr9r<rs rrzGenerator.logseriesrr c Ht|d||f||t|ffd|SN multinomialr:r; extra_chunksr=rUrrGpvalsr:r;rAs rrzGenerator.multinomialJ     u::-)      r marginalsc *t|d||f|||d|S)Nmultivariate_hypergeometric)r:methodr;r<)rcolorsrr:rr;rAs rrz%Generator.multivariate_hypergeometricsA  )          r c (t|d||f||d|SNnegative_binomialr9r<rFs rrzGenerator.negative_binomial5 %q! 26v  IO   r c (t|d||f||d|SNnoncentral_chisquarer9r<rrNnoncr:r;rAs rrzGenerator.noncentral_chisquare5 ("d 9=f  PV   r c *t|d|||f||d|SN noncentral_fr9r<rr~rrr:r;rAs rrzGenerator.noncentral_f6 .% ;?  RX   r c (t|d||f||d|SNnormalr9r<rs rrzGenerator.normal%rr c &t|d|f||d|SNparetor9r<rr?r:r;rAs rrzGenerator.pareto+#$!P$vPPPPPr c(ddlm}|jdkrtdt |t jrt|d}|jt|}t|j ||||S)Nr shuffle_slicecupyz`Generator.permutation` not supported for cupy-backed Generator objects. Use the 'numpy' array backend to call `dask.array.random.default_rng`, or pass in `numpy.random.PCG64()`.r5r;) dask.array.slicingrr-NotImplementedError isinstancenumbersNumberrr1rU_shufflerrxrindexs r permutationzGenerator.permutation/s444444   ' '%+  a ( ( )q(((A $$SVV,,$e,,,}Q&&&r c &t|d|f||d|SNpoissonr9r<rlamr:r;rAs rrzGenerator.poissonB#$ 3ST&SSFSSSr c &t|d|f||d|SNpowerr9r<rs rrzGenerator.powerF#$OfOOOOOr c (t|df||||d|S)Nrandom)r:routr;r<)rr:rrr;rAs rrzGenerator.randomJs4 ( !%UF  NT   r c &t|d|f||d|SNrayleighr9r<rws rrzGenerator.rayleighP#$ EVVVVvVVVr c $t|df||d|SNstandard_cauchyr9r<rr:r;rAs rrzGenerator.standard_cauchyT"$ 1VVVVvVVVr c $t|df||d|SNstandard_exponentialr9r<rs rrzGenerator.standard_exponentialX1 ( /3F  FL   r c &t|d|f||d|SNstandard_gammar9r<rrr:r;rAs rrzGenerator.standard_gamma^3 "E 04V  GM   r c $t|df||d|SNstandard_normalr9r<rs rrzGenerator.standard_normaldrr c &t|d|f||d|SN standard_tr9r<rMs rr zGenerator.standard_th#$ bUtFUUfUUUr c *t|d|||f||d|SN triangularr9r<rleftmoderightr:r;rAs rrzGenerator.triangularl6 ,dE 8>@,,, ;;X; ;;X; \")%!444RRR54R\")%!444VVV54V\")%!444UUU54U\")%!444  "5"5"554"5H\")%!444   54 \")%!444WWW54W\")%!444   54 \")%!444TTT54T\")%!444   54 \")%!444    54  \")%!444 h   54 ,\")%!444   54 \")%!444   54 \")%!444   54 \")%!444TTT54T\")%!444    54  \")%!444EK    54  \")%!444   54 \")%!444   54 \")%!444   54 \")%!444   54 \")%!444QQQ54Q\")%!444''54'$\")%!444TTT54T\")%!444PPP54P\")%!444bjd6   54 \")%!444WWW54W\")%!444WWW54W\")%!444   54 \")%!444   54 \")%!444WWW54W\")%!444VVV54V\")%!444   54 \")%!444   54 \")%!444   54 \")%!444YYY54Y\")%!444RRR54R\")%!444OOO54OOOr rct|drt|St|tr|St|drt|jStt j|S)af Construct a new Generator with the default BitGenerator (PCG64). Parameters ---------- seed : {None, int, array_like[ints], SeedSequence, BitGenerator, Generator}, optional A seed to initialize the `BitGenerator`. If None, then fresh, unpredictable entropy will be pulled from the OS. If an ``int`` or ``array_like[ints]`` is passed, then it will be passed to `SeedSequence` to derive the initial `BitGenerator` state. One may also pass in a `SeedSequence` instance. Additionally, when passed a `BitGenerator`, it will be wrapped by `Generator`. If passed a `Generator`, it will be returned unaltered. Returns ------- Generator The initialized generator object. Notes ----- If ``seed`` is not a `BitGenerator` or a `Generator`, a new `BitGenerator` is instantiated. This function does not manage a default global instance. Examples -------- ``default_rng`` is the recommended constructor for the random number class ``Generator``. Here are several ways we can construct a random number generator using ``default_rng`` and the ``Generator`` class. Here we use ``default_rng`` to generate a random float: >>> import dask.array as da >>> rng = da.random.default_rng(12345) >>> print(rng) Generator(PCG64) >>> rfloat = rng.random().compute() >>> rfloat array(0.86999885) >>> type(rfloat) Here we use ``default_rng`` to generate 3 random integers between 0 (inclusive) and 10 (exclusive): >>> import dask.array as da >>> rng = da.random.default_rng(12345) >>> rints = rng.integers(low=0, high=10, size=3).compute() >>> rints array([2, 8, 7]) >>> type(rints[0]) Here we specify a seed so that we have reproducible results: >>> import dask.array as da >>> rng = da.random.default_rng(seed=42) >>> print(rng) Generator(PCG64) >>> arr1 = rng.random((3, 3)).compute() >>> arr1 array([[0.91674416, 0.91098667, 0.8765925 ], [0.30931841, 0.95465607, 0.17509458], [0.99662814, 0.75203348, 0.15038118]]) If we exit and restart our Python interpreter, we'll see that we generate the same random numbers again: >>> import dask.array as da >>> rng = da.random.default_rng(seed=42) >>> arr2 = rng.random((3, 3)).compute() >>> arr2 array([[0.91674416, 0.91098667, 0.8765925 ], [0.30931841, 0.95465607, 0.17509458], [0.99662814, 0.75203348, 0.15038118]]) See Also -------- np.random.default_rng capsuler)hasattrrrrr default_bit_generator)seeds r default_rngr=swdtY- D) $ $-  ' '-+,,, ,B4HH I IIr c eZdZdZd4dZedZd5dZee j j dd6d Z ee j j dd6d Z ee j j dd6d Zeje5ee j j dd7d Zdddn #1swxYwYee j j dd8dZee j j dd6dZee j j dd8dZee j j dd6dZee j j dd9dZee j j dd6dZee j j dd9dZee j j dd9dZee j j dd9dZee j j dd6dZee j j dd6dZee j j dd6dZee j j dd6dZee j j dd6dZ ee j j dd9dZ!ee j j dd6dZ"ee j j dd Z#ee j j dd8d!Z$ee j j dd6d"Z%ee j j dd:d$Z&ee j j dd;d%Z'ee j j dd6d&Z(e(Z ee j j dd8d'Z)ee j j dd6d(Z*ee j j dd6d)Z+ee j j dd6d*Z,ee j j dd6d+Z-ee j j dd6d,Z.ee j j dd6d-Z/ee j j dd6d.Z0ee j j dd9d/Z1ee j j dd6d0Z2ee j j dd6d1Z3ee j j dd6d2Z4ee j j dd6d3Z5dS)< RandomStatea Mersenne Twister pseudo-random number generator This object contains state to deterministically generate pseudo-random numbers from a variety of probability distributions. It is identical to ``np.random.RandomState`` except that all functions also take a ``chunks=`` keyword argument. Parameters ---------- seed: Number Object to pass to RandomState to serve as deterministic seed RandomState: Callable[seed] -> RandomState A callable that, when provided with a ``seed`` keyword provides an object that operates identically to ``np.random.RandomState`` (the default). This might also be a function that returns a ``mkl_random``, or ``cupy.random.RandomState`` object. Examples -------- >>> import dask.array as da >>> state = da.random.RandomState(1234) # a seed >>> x = state.normal(10, 0.1, size=3, chunks=(2,)) >>> x.compute() array([10.01867852, 10.04812289, 9.89649746]) See Also -------- np.random.RandomState Ncxtj||_| tjn||_dSr)r5rr? _numpy_stater _RandomState)rr<r?s rrzRandomState.__init__ s9I11$773>3F # / /K r ct|jdd}tj|Sr))rrBr+r/r0)rr-s rr1zRandomState._backends8!!23399#>>qA &}555r c:|j|dSr)rAr<)rr<s rr<zRandomState.seeds t$$$$$r r2r3r5c (t|d||f||d|Sr7r<r>s rr8zRandomState.betarBr c (t|d||f||d|SrDr<rFs rrEzRandomState.binomialrIr c &t|d|f||d|SrKr<rMs rrLzRandomState.chisquare"rOr Tc t||d|\}}}}}tt|} tt | |j} dt | ||z} t| ggd|DR} fdt| | | D} tj | | |}t|| ||S)NrrQc3NK|] }tt|V!dSrrSrVs rrYz%RandomState.choice..;s.$E$EU3r77^^$E$E$E$E$E$Er c 4i|]\}}}|t||fSr[) _choice_rs)rWr]stater:r?rHr`s rrbz&RandomState.choice..<s>"AudJq$;r rcre) rgrhrrrUrArrjrrkr )rr?r:r`rHr;r_rfrdrl state_datarnrorprqs ` `` rrrzRandomState.choice(s)(aw1fMM &)**E*3u::t7HIIJ(8D&!Wa,,DD6F$E$Ef$E$E$EFFFD&)$ E&B&BC #3c Ef4888 8r rsc &t|d|f||d|Srur<rws rrvzRandomState.exponentialFryr c (t|d||f||d|Sr{r<r}s rr|z RandomState.fLrr c (t|d||f||d|Srr<rs rrzRandomState.gammaPrr c &t|d|f||d|Srr<rs rrzRandomState.geometricVrr rc (t|d||f||d|Srr<rs rrzRandomState.gumbelZrr c *t|d|||f||d|Srr<rs rrzRandomState.hypergeometric`rr c (t|d||f||d|Srr<rs rrzRandomState.laplacemrr c (t|d||f||d|Srr<rs rrzRandomState.logisticsrr c (t|d||f||d|Srr<rs rrzRandomState.lognormalyrr c &t|d|f||d|Srr<rs rrzRandomState.logseriesrr c Ht|d||f||t|ffd|Srrrs rrzRandomState.multinomialrr c (t|d||f||d|Srr<rFs rrzRandomState.negative_binomialrr c (t|d||f||d|Srr<rs rrz RandomState.noncentral_chisquarerr c *t|d|||f||d|Srr<rs rrzRandomState.noncentral_frr c (t|d||f||d|Srr<rs rrzRandomState.normalrr c &t|d|f||d|Srr<rs rrzRandomState.paretorr cddlm}t|tjrt |d}t jt|}|j ||||S)Nrrr5r) rrrrrrr5rUrArars rrzRandomState.permutationsx444444 a ( ( )q(((A #a&&!! !!%(((}Q&&&r c &t|d|f||d|Srr<rs rrzRandomState.poissonrr c &t|d|f||d|Srr<rs rrzRandomState.powerrr lc *t|d||f|||d|S)Nrandint)r:r;rr<)rrrr:r;rrAs rrczRandomState.randints6 )S$ -1&  QW   r c (t|d||f||d|S)Nrandom_integersr9r<rs rrezRandomState.random_integerss5 #S$ 59&  LR   r c $t|df||d|S)N random_sampler9r<rs rrgzRandomState.random_samples!$Td6TTVTTTr c &t|d|f||d|Srr<rws rrzRandomState.rayleighrr c $t|df||d|Srr<rs rrzRandomState.standard_cauchyrr c $t|df||d|Srr<rs rrz RandomState.standard_exponentialrr c &t|d|f||d|Srr<rs rrzRandomState.standard_gammarr c $t|df||d|Srr<rs rrzRandomState.standard_normalrr c &t|d|f||d|Sr r<rMs rr zRandomState.standard_tr r c $t|df||d|S)Ntomaxintr9r<rs rrozRandomState.tomaxints!$ OfOOOOOr c *t|d|||f||d|Srr<rs rrzRandomState.triangularrr c (t|d||f||d|Srr<rs rrzRandomState.uniformrr c (t|d||f||d|Srr<rs rrzRandomState.vonmisesr r c (t|d||f||d|Sr"r<r$s rr#zRandomState.waldr%r c &t|d|f||d|Sr'r<rs rr(zRandomState.weibullr)r c &t|d|f||d|Sr+r<rs rr,zRandomState.zipf r-r )NNrr.)NTNr5r/r0)NNr5ra)NNr5)6r%r1r2r3rr4r1r<rr5rr?r8rErL contextlibsuppressAttributeErrorrrrvr|rrrrrrrrrrrrrrrrrrcrergrrrrrr rorrrr#r(r,r[r rr?r?s' >    66X6 %%%%\")'A666RRR76R\")'A666VVV76V\")'A666UUU76U  ^ , ,99 bi+ : : : 9 9 9 ; : 9999999999999999@\")'A666   76 \")'A666WWW76W\")'A666   76 \")'A666TTT76T\")'A666   76 \")'A666    76  \")'A666   76 \")'A666   76 \")'A666   76 \")'A666TTT76T\")'A666    76  \")'A666   76 \")'A666   76 \")'A666   76 \")'A666   76 \")'A666QQQ76Q\")'A666''76'\")'A666TTT76T\")'A666PPP76P\")'A666   76 \")'A666   76 \")'A666UUU76UF\")'A666WWW76W\")'A666WWW76W\")'A666   76 \")'A666   76 \")'A666WWW76W\")'A666VVV76V\")'A666PPP76P\")'A666   76 \")'A666   76 \")'A666   76 \")'A666YYY76Y\")'A666RRR76R\")'A666OOO76OOOs "B;;B?B?r?ct|dd}tj|}|j|Sr))rr+r/r0rr=)r^ backend_name backend_libs r_rng_from_bitgenr|sKF##))#..q1L),77K   ) )& 1 11r c|j}t|}||_t|}|||S)N)r_)rLtyper|ra)rrr_rMrLs rrrsJ$J'D''))M$M ] + +E === & &&r cXj|}fd|D}|S)Nc@g|]}t|Sr[)r~)rWr<r^s r z"_spawn_bitgens.."s)444d|tF||D!!444r ) _seed_seqspawn)r^ n_bitgensseedsrms` rriri s7   " "9 - -E4444e444G Nr ct|tjjr ||}t |}t ||}||d|i|S)z$Apply random module method with seedr:)rr5r SeedSequencer|getattr)rngfuncnamer^r:argsrAfuncs r_apply_random_funcr&s\&")011V 6 " "C 3 ! 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