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Hl$({ H; IVBHZE1 {L= H QP A;B HLHRp VP A=@9HL MH I/u IGLP0H H5Z H9p HA H HH- HHCH;  Mu H;( Lt$(E H; 0HSBHJE1H $ uLcqL= p VP A; LLH$IDH QP A=29M IM I/u IGLP0L赑HHbH蚑Hh I9E(FH~IHI HB Mm(H H9HU H H HH HY HAH5 HH $HH H $HHHHV HHu HAHP0H H V H9H H= H HL5) M` IFH5 LHH HIHH IHuIFH $LP0H $LH $L)謎H $HI HD$]H $LL$HI LHH $kH $HI H H5] H9p HD H HL-0 M IEH5 H $LHH H $IM ImH59 LLHL$L $EL $HL$ I)rHLLH $(H $HIH)uH$HAHP0L $I.uIFL $LP0L $I/uIGL $LP0L $L $L $HHS HEH@H(HALHH H9C HHH $IH $IH)u HAHP0M\ Imu IELP0HmHEHLP0fH H5 H9pHy HHHe HLHCH5 HHHIMH+ԈHHHEH@H(I$HCL`H I9FHLMIH+MI/IEHmHEHLP0I,$Mf29(P@$@9-@$@HCHP0HCHP0NI$LHI$uID$LP0HtHmu HEHP0H8H[]A\A]A^A_DIGLP0IEHm@HL-HQDLH I<DH H9G1H E11E11H8։$E11D$$E111D$E11E1Ht$H+uHCLL$HHL$P0LL$HL$HtH)uHALL$HP0LL$MtI.uIFLL$LP0LL$MtImuIELL$LP0LL$MtI)u IALP0T$4$H 5H=!,Ht/HmtH1M^I$1HI$)E@M8I,$ (HEH1P0MPfDH= H" H5# NIfDH=Y 4I@I^HM~HII.IUHL&H+H(HCHP0f.Ht$(LNHfDE1E11E1$ D$H= H: H5; vHfDH= \H@LsML{IIH+=IU LLNI.I[IFLP0LfHt$(H~I-fD$%D$E1E111-fH= ćIM$E1D$E1E11H1E11G#IHI$ME1D$E111HE1E1fDIHIGLL$LHL$P0LL$HL$wfIFLP0HCHP0IELL$LH $P0LL$H $_IAH $LP0H $wLJ1 uI~Ht$(AHDLB1 uH{Ht$(AIIE1$eD$HH=$HI$E1D$E1E11H1E1fD胆HHIE1E1E111$HD$gE1E11$D$@H=q H H5 ^HifDH=I DHO@#IjE11$D$z$,#@IME1E11E1$HD$INHMM~HII.uIFH $LP0H $HHLH $H $IH)HAHP0DD$$IE1E1E111HLE1D$$@$9E1E11D$1Uf.H= Hz H5{ ƇHfDE1E11$CD$@D$$3@IE1E1E11$ED$&fDCH $HaH=9 4H@E11$PD$zH= H H5 IUfDH= I;@賅HVME1E1E1$RD$`E1$UD$IME1E1$WHD$E1$\D$I$cE1D$HIE1$^D$HH= H| H5} H $H $I0I$`D$H訄H $I8H= H $H $IH ME11H5rH8IE11E1$HD$E1$jD$HD$IE1E1HC H5H8tHE11$HL$HD$E11L$D$>L{MILkIIEH+uHCH $HP0H $HLLH $ I/H $IIGH $LP0H $1ɺAH1ɺAIHH__int__ returned non-int (type %.200s). The ability to return an instance of a strict subclass of int is deprecated, and may be removed in a future version of Python.__%.4s__ returned non-%.4s (type %.200s)%.200s.%.200s is not a type object%.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject%s.%s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject%.200s does not export expected C variable %.200sC variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)%.200s does not export expected C function %.200sC function %.200s.%.200s has wrong signature (expected %.500s, got %.500s) while calling a Python objectNULL result without error in PyObject_CallInterpreter change detected - this module can only be loaded into one interpreter per process.__annotations__ must be set to a dict object__kwdefaults__ must be set to a dict object__defaults__ must be set to a tuple objectfunction's dictionary may not be deletedsetting function's dictionary to a non-dict__qualname__ must be set to a string object__name__ must be set to a string objectcan't convert negative value to uint32_tvalue too large to convert to uint32_tmetaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its basesUnexpected format string character: '%c'join() result is too long for a Python string%s() got multiple values for keyword argument '%U'%.200s() keywords must be strings%s() got an unexpected keyword argument '%U'calling %R should have returned an instance of BaseException, not %Rraise: exception class must be a subclass of BaseExceptionBuffer dtype mismatch, expected %s%s%s but got %sBuffer dtype mismatch, expected '%s' but got %s in '%s.%s'Expected a dimension of size %zu, got %zuExpected %d dimensions, got %dPython does not define a standard format string size for long double ('g')..Buffer dtype mismatch; next field is at offset %zd but %zd expectedBig-endian buffer not supported on little-endian compilerBuffer acquisition: Expected '{' after 'T'Cannot handle repeated arrays in format stringDoes not understand character buffer dtype format string ('%c')Expected a dimension of size %zu, got %dExpected a comma in format string, got '%c'Expected %d dimension(s), got %dUnexpected end of format string, expected ')'Buffer has wrong number of dimensions (expected %d, got %d)Item size of buffer (%zd byte%s) does not match size of '%s' (%zd byte%s)%.200s() takes no arguments (%zd given)%.200s() takes exactly one argument (%zd given)Bad call flags in __Pyx_CyFunction_Call. METH_OLDARGS is no longer supported!%.200s() takes no keyword argumentsobject of type 'NoneType' has no len()hasattr(): attribute name must be stringnumpy.random.bit_generator.__pyx_unpickle_SeedlessSeedSequence__set_state__pyx_unpickle_SeedlessSeedSequence%.200s() takes %.8s %zd positional argument%.1s (%zd given)numpy.random.bit_generator.__pyx_unpickle_SeedlessSeedSequencenumpy.random.bit_generator.ISpawnableSeedSequence.spawnnumpy.random.bit_generator.__defaults__numpy.random.bit_generator.ISeedSequence.generate_statenumpy.random.bit_generator.SeedlessSeedSequence.__setstate_cython__numpy.random.bit_generator.SeedlessSeedSequence.spawnnumpy.random.bit_generator.SeedlessSeedSequence.generate_statenumpy.random.bit_generator.SeedSequence.n_children_spawned.__get__numpy.random.bit_generator.SeedSequence.pool_size.__get__numpy.random.bit_generator.SeedSequence.state.__get__numpy.random.bit_generator.SeedSequence.spawnnumpy.random.bit_generator.SeedSequence.__repr__Out of bounds on buffer access (axis %d)numpy.random.bit_generator.SeedSequence.mix_entropynumpy.random.bit_generator.BitGenerator.cffi.__get__numpy.random.bit_generator.BitGenerator.ctypes.__get__numpy.random.bit_generator.BitGenerator.state.__set__numpy.random.bit_generator.BitGenerator.state.__get__numpy.random.bit_generator.BitGenerator._benchmarknumpy.random.bit_generator.BitGenerator.random_rawnumpy.random.bit_generator.BitGenerator.__reduce__numpy.random.bit_generator.BitGenerator.__setstate__numpy.random.bit_generator.BitGenerator.__getstate__Unable to initialize pickling for %s'NoneType' object is not subscriptablenumpy.random.bit_generator.__pyx_unpickle_SeedSequence__set_statenumpy.random.bit_generator.__pyx_unpickle_SeedSequencenumpy.random.bit_generator.SeedSequence.__setstate_cython__numpy.random.bit_generator.SeedlessSeedSequence.__reduce_cython__numpy.random.bit_generator._int_to_uint32_arrayCannot convert %.200s to %.200snumpy.random.bit_generator.SeedSequence.__init__numpy.random.bit_generator.SeedSequence.__reduce_cython__%.200s object is not an iteratornumpy.random.bit_generator.SeedSequence.generate_stateModule 'bit_generator' has already been imported. Re-initialisation is not supported.compiletime version %s of module '%.100s' does not match runtime version %sShared Cython type %.200s is not a type objectShared Cython type %.200s has the wrong size, try recompilingPyObject *(bitgen_t *, PyObject *, Py_ssize_t, PyObject *)PyObject *(bitgen_t *, PyObject *, PyObject *, PyObject *)_ARRAY_API is not PyCapsule objectmodule compiled against ABI version 0x%x but this version of numpy is 0x%xmodule compiled against API version 0x%x but this version of numpy is 0x%xFATAL: module compiled as unknown endianFATAL: module compiled as little endian, but detected different endianness at runtimeinit numpy.random.bit_generatornumpy.random.bit_generator._coerce_to_uint32_arraynumpy.random.bit_generator.BitGenerator.__init__numpy.random.bit_generator.SeedSequence.get_assembled_entropynumpy.random.bit_generator.SeedlessSeedSequence A seed sequence for BitGenerators with no need for seed state. See Also -------- SeedSequence, ISeedSequence numpy.random.bit_generator.SeedlessSequencenumpy.random.bit_generator.SeedSequence SeedSequence(entropy=None, *, spawn_key=(), pool_size=4) SeedSequence mixes sources of entropy in a reproducible way to set the initial state for independent and very probably non-overlapping BitGenerators. Once the SeedSequence is instantiated, you can call the `generate_state` method to get an appropriately sized seed. Calling `spawn(n) ` will create ``n`` SeedSequences that can be used to seed independent BitGenerators, i.e. for different threads. Parameters ---------- entropy : {None, int, sequence[int]}, optional The entropy for creating a `SeedSequence`. spawn_key : {(), sequence[int]}, optional A third source of entropy, used internally when calling `SeedSequence.spawn` pool_size : {int}, optional Size of the pooled entropy to store. Default is 4 to give a 128-bit entropy pool. 8 (for 256 bits) is another reasonable choice if working with larger PRNGs, but there is very little to be gained by selecting another value. n_children_spawned : {int}, optional The number of children already spawned. Only pass this if reconstructing a `SeedSequence` from a serialized form. Notes ----- Best practice for achieving reproducible bit streams is to use the default ``None`` for the initial entropy, and then use `SeedSequence.entropy` to log/pickle the `entropy` for reproducibility: >>> sq1 = np.random.SeedSequence() >>> sq1.entropy 243799254704924441050048792905230269161 # random >>> sq2 = np.random.SeedSequence(sq1.entropy) >>> np.all(sq1.generate_state(10) == sq2.generate_state(10)) True numpy.random.bit_generator.BitGenerator BitGenerator(seed=None) Base Class for generic BitGenerators, which provide a stream of random bits based on different algorithms. Must be overridden. Parameters ---------- seed : {None, int, array_like[ints], SeedSequence}, 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 ~`numpy.random.SeedSequence` to derive the initial `BitGenerator` state. One may also pass in a `SeedSequence` instance. Attributes ---------- lock : threading.Lock Lock instance that is shared so that the same BitGenerator can be used in multiple Generators without corrupting the state. Code that generates values from a bit generator should hold the bit generator's lock. See Also -------- SeedSequence Get or set the PRNG state The base BitGenerator.state must be overridden by a subclass Returns ------- state : dict Dictionary containing the information required to describe the state of the PRNG ctypes interface Returns ------- interface : namedtuple Named tuple containing ctypes wrapper * state_address - Memory address of the state struct * state - pointer to the state struct * next_uint64 - function pointer to produce 64 bit integers * next_uint32 - function pointer to produce 32 bit integers * next_double - function pointer to produce doubles * bitgen - pointer to the bit generator struct CFFI interface Returns ------- interface : namedtuple Named tuple containing CFFI wrapper * state_address - Memory address of the state struct * state - pointer to the state struct * next_uint64 - function pointer to produce 64 bit integers * next_uint32 - function pointer to produce 32 bit integers * next_double - function pointer to produce doubles * bitgen - pointer to the bit generator struct __pyx_capi____loader__loader__file__origin__package__parent__path__submodule_search_locationsintan integer is requiredname '%U' is not definedcannot import name %Sendunparseable format string'complex double''signed char''unsigned char''short''unsigned short''int''unsigned int''long''unsigned long''long long''unsigned long long''double''complex long double''bool''char''complex float''float'a structPython objecta pointera string'long double'buffer dtypenumpy/random/bit_generator.c%s (%s:%d)stringsourceexactlytupleExpected %.16s, got %.200sspawnbit_generator.pyxat leastat mostgenerate_statebit_generator.pxd__del___benchmarkrandom_raw__pyx_unpickle_SeedSequence__init__Missing type object%d.%d%snumpy.random.bit_generator_cython_0_29_21builtinscython_runtime__builtins__4294967296numpyflatiterbroadcastndarraygenericnumberunsignedintegerinexactcomplexfloatingflexiblecharacterufuncnumpy.random._commondoubleLEGACY_POISSON_LAM_MAXuint64_tMAXSIZEPyObject *(bitgen_t *)prepare_cffiprepare_ctypesnumpy.core._multiarray_umath_ARRAY_API_ARRAY_API not found_ARRAY_API is NULL pointer__init__.pxdnumpy.import_arrayBitGeneratorcython_function_or_method__reduce____module__func_doc__doc__func_name__name____qualname____self__func_dict__dict__func_globals__globals__func_closure__closure__func_code__code__func_defaults__defaults____kwdefaults____annotations____reduce_cython____setstate_cython__entropyspawn_keypool_sizepooln_children_spawned_seed_seqlockcapsule__getstate____setstate___coerce_to_uint32_array_int_to_uint32_arraynpy_uint32кккl4 ,Ll\|\dtTD4$D4$TR\\R\\\\\RR\\R\\llR\\\\\\\\\\\\\\\\*4>\>>**\\*\\\**\*(((((((((((((((((((((((((((((((((( TT TTTTT<,TTTTTTTTTTTTTTTTTTTT LTd<,TTTTT T ` P$DX0pp/$ CIX4 r\;|;7T; :?h?7??gA\ABA{AA00010203040506070809101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899 Abstract base class for seed sequences that can spawn. seedless SeedSequences cannot generate statenumpy.core.umath failed to importThe size of the entropy pool should be at least SeedSequence expects int or sequence of ints for entropy not {}Not implemented in base BitGeneratorIncompatible checksums (%s vs 0xf88304a = (entropy, n_children_spawned, pool, pool_size, spawn_key))Incompatible checksums (%s vs 0xd41d8cd = ())BitGenerator is a base class and cannot be instantizednumpy.core.multiarray failed to import Coerce an input to a uint32 array. If a `uint32` array, pass it through directly. If a non-negative integer, then break it up into `uint32` words, lowest bits first. If a string starting with "0x", then interpret as a hex integer, as above. If a string of decimal digits, interpret as a decimal integer, as above. If a sequence of ints or strings, interpret each element as above and concatenate. Note that the handling of `int64` or `uint64` arrays are not just straightforward views as `uint32` arrays. If an element is small enough to fit into a `uint32`, then it will only take up one `uint32` element in the output. This is to make sure that the interpretation of a sequence of integers is the same regardless of numpy's default integer type, which differs on different platforms. Parameters ---------- x : int, str, sequence of int or str Returns ------- seed_array : uint32 array Examples -------- >>> import numpy as np >>> from numpy.random.bit_generator import _coerce_to_uint32_array >>> _coerce_to_uint32_array(12345) array([12345], dtype=uint32) >>> _coerce_to_uint32_array('12345') array([12345], dtype=uint32) >>> _coerce_to_uint32_array('0x12345') array([74565], dtype=uint32) >>> _coerce_to_uint32_array([12345, '67890']) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.uint32)) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.int64)) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array([12345, 0x10deadbeef, 67890, 0xdeadbeef]) array([ 12345, 3735928559, 16, 67890, 3735928559], dtype=uint32) >>> _coerce_to_uint32_array(1234567890123456789012345678901234567890) array([3460238034, 2898026390, 3235640248, 2697535605, 3], dtype=uint32) BitGenerator base class and SeedSequence used to seed the BitGenerators. SeedSequence is derived from Melissa E. O'Neill's C++11 `std::seed_seq` implementation, as it has a lot of nice properties that we want. https://gist.github.com/imneme/540829265469e673d045 http://www.pcg-random.org/posts/developing-a-seed_seq-alternative.html The MIT License (MIT) Copyright (c) 2015 Melissa E. O'Neill Copyright (c) 2019 NumPy Developers Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. Abstract base class for seed sequences. ``BitGenerator`` implementations should treat any object that adheres to this interface as a seed sequence. See Also -------- SeedSequence, SeedlessSeedSequence __pyx_unpickle_SeedlessSeedSequence_coerce_to_uint32_array (line 88)only support uint32 or uint64expected non-negative integerISpawnableSeedSequence.spawnISeedSequence.generate_statenumpy.random.bit_generator__pyx_unpickle_SeedSequenceunrecognized seed string_coerce_to_uint32_arrayISpawnableSeedSequenceseed must be integer n_children_spawned=SeedlessSeedSequence_int_to_uint32_arrayNotImplementedErrorn_children_spawnedcline_in_traceback__bit_generator_ctorbit_generator.pyxSeedlessSequence__setstate_cython____pyx_PickleErrordummy_threadinggenerate_stateabstractmethod__reduce_cython__bit_generatorISeedSequencestringsource__pyx_checksumSystemRandomSeedSequenceBitGenerator spawn_key= pool_size=getrandbitsconcatenatePickleErrorImportErrorstartswith__pyx_vtable____pyx_resultn_childrenValueErrorDECIMAL_REthreadingspawn_key__reduce_ex____pyx_statepool_size__metaclass__itertools entropy=TypeError__setstate__registerrandbits__qualname____pyx_typepickle__getstate__errstatesubseqssecrets__prepare__n_wordsentropycompileupdateuint64uint32__reduce__random_pickleoutput__module__method__import__ignoreformatastypezerosstatespawnrangenumpymatchdtypecyclearrayview__test__sizeselfseedover__name____main____dict__copybaseLocksys__new____doc__cntarr__all__abc ABC[0-9]+À 0L 0@P`pЃp<PdЄxpЅ,0@\x@@P@Tp @Dp `p @ 0 `l ` p P l P ` ``0<`PР|@pPppLL  hp<X0t  \ 0l @ 0P0p`()`1 2H@ T\@Px`DzRx $P%FJ w?;*3$"Dx}`D | H 4`} ADD  CAG K CAI ~ ~ ~ ~ ~ ~`D| H 4~ADD b CAA K CAA P, d( x$14PAAD0M AAK O AAG H+YAdP  , @TyeDGpL3YYpA\ d ~A| C j F 7AU J V< ,$8lBAA  CBC Txh)AcP)BEH D(D0GxHfA\0D(A BBB8z*{BEE G(A0](C BBBQA^ I h 4HAi N V X'A P v$|Q*SADA JAAD|*BEE L(D0A8B@8C0A(B BBBD7+BEE L(D0A8B@8C0A(B BBBL4HBBB A(A0p (A BBBA Y (A BBBH @BEB D(D0G@p 0A(A BBBH 8^+BHD D(GPm(A ABB\( BBE D(A0O (D BBBI K (D BBBK (A EBB8dO,bBEA A(A0N(D ABB4uBDD W GBF AAB4UBDD s GBJ AAB0-xAAD0g AAB DAA8D<BBB D(D0&(A BBByDE G P|Db J |Db J Do E hDo E o܈hDo E o(0,iAD z AH  AH 8\1,BBE A(C0p(A BBB$4MAU J \ D LHR,:BEE E(A0A8B@8D0A(B BBBD @-BEE E(D0D8DP8D0A(B BBB(T -DBKC pAB 1 ȉ  ĉtbH LBBB J(A0C8D` 8D0A(B BBBG d [BEE B(A0D8H] 8A0A(B BBBF  8F0A(B BBBA Dt sCA e DBN AABDh \ @hBBE B(D0A8G@WHJPGXC`AhBpI@o 8D0A(B BBBF  P0 QA^ I hP L(d mADG e DAJ ( LpADD ^ DAD  yeDG  QBB B(A0A8G`H`H 8A0A(B BBBF L 8F0A(B BBBE \ 8F0A(B BBBA H ؛^BEI B(G0K8G`q 8D0A(B BBBG T ,ADM AAG A FAH O AAG lHRA4( ĢAAG \ DAF N DAE \` hBBI D(D0 (D ABBD N (D ABBI \ (C DBBI L ,BBA A(D@ (D ABBF ~ (G ABBF LjBED A(GP (D ABBC n (D ABBI `BBE A(D0G@t 0D(A BBBL  0D(A BBBA V 0D(A BBBG D 0D(A BBBI ԫpBBB B(D0C8Fp 8A0A(B BBBL O 8A0A(B BBBG xTAABAAAAAIp 8A0A(B BBBF `BBB B(A0A8D@ 8D0A(B BBBH t 8C0A(B BBBH Ĵf BFB A(A0G` 0A(A BBBA JhVp_hF` 0A(A BBBH hWp_hA`NhVp`hG`d|BFA A(D@f (A ABBA IHVP_HF@\ (C ABBE HWP_HA@4AID M AAC s CAI djBFA A(DP (A ABBA iXD`kXFP\ (C ABBJ IXW`_XAPDu G s E L(BDI D0w  AABB X  AABD s  CABG XBBA A(D@ (C ABBC ]HHPYHF@\ (C ABBH PLID Q K lID R J HBBE B(A0A8D@ 8D0A(B BBBG H BBB B(F0A8G`E 8D0A(B BBBH L | BBE B(A0A8D 8D0A(B BBBB LpBBB B(D0A8G1 8A0A(B BBBA LAG Y AF AG Y AF 8$}BBA A(D0 (F ABBJ 8DhRBBA A(D0 (C ABBF dBBB D(D0DPkXH`YXFP\ 0C(A BBBF  0A(A BBBJ XBBA D(D@`HLP`HF@^ (D ABBJ L (D ABBK XDBBJ A(A0D@ 0D(A BBBD  0D(A BBBD gDo E c E  iD b J t`>KBA A(G0 (A ABBD B (F ABBC D (G ABBH F0$T8!daAA ~AAH|t!BEE B(A0A8DP8D0A(B BBBdBBB B(A0A8D@\ 8D0A(B BBBI  8C0A(B BBBE 0<f BFB A(A0G` 0A(A BBBA JhVp_hF` 0A(A BBBH hWp_hA`NhVp`hG`( Du G s E H BBE B(A0A8DP 8D0A(B BBBE 8 LBHD D(D0s (D ABBF H\jBDB B(A0D8D`  8D0A(B BBBG \#BBB E(A0A8DHYFf 8A0A(B BBBH H$7BBB B(A0D8DP 8D0A(B BBBC XT?|BBB E(A0D8DkHYF^ 8D0A(B BBBG X! BBBB B(A0D8GS HBFFAAAAANLHBFFAAAAANLHEFFAAAAANBQEFFAAAAANWQBFFAAAAANPQBFFAAAAAN58A0A(B BBBH PYBBB B(A0D8D` 8D0A(B BBBF lXr& BBB B(A0A8G`p 8A0A(B BBBE yhHpYhF`a 8A0A(B BBBE HzBBB E(A0A8Dp\ 8D0A(B BBBF ` \"   [ `\"\"o0 `"X 8P 1 oooo\"[[[[[\\&\6\F\V\f\v\\\\\\\\\]]&]6]F]V]f]v]]]]]]]]]^^&^6^F^V^f^v^^^^^^^^^__&_6_F_V_f_v_________``&`6`F`V`f`v`````````aa&a6aFaVafavaaaaaaaaabb&b6bFbVbfbvbbbbbbbbbcc&c6cUsed in tests random_raw(self, size=None) Return randoms as generated by the underlying BitGenerator Parameters ---------- size : int or tuple of ints, optional Output shape. If the given shape is, e.g., ``(m, n, k)``, then ``m * n * k`` samples are drawn. Default is None, in which case a single value is returned. output : bool, optional Output values. Used for performance testing since the generated values are not returned. Returns ------- out : uint or ndarray Drawn samples. Notes ----- This method directly exposes the the raw underlying pseudo-random number generator. All values are returned as unsigned 64-bit values irrespective of the number of bits produced by the PRNG. See the class docstring for the number of bits returned. spawn(n_children) Spawn a number of child `SeedSequence` s by extending the `spawn_key`. Parameters ---------- n_children : int Returns ------- seqs : list of `SeedSequence` s generate_state(n_words, dtype=np.uint32) Return the requested number of words for PRNG seeding. A BitGenerator should call this method in its constructor with an appropriate `n_words` parameter to properly seed itself. Parameters ---------- n_words : int dtype : np.uint32 or np.uint64, optional The size of each word. This should only be either `uint32` or `uint64`. Strings (`'uint32'`, `'uint64'`) are fine. Note that requesting `uint64` will draw twice as many bits as `uint32` for the same `n_words`. This is a convenience for `BitGenerator`s that express their states as `uint64` arrays. Returns ------- state : uint32 or uint64 array, shape=(n_words,) spawn(n_children) Spawn a number of child `SeedSequence` s by extending the `spawn_key`. Parameters ---------- n_children : int Returns ------- seqs : list of `SeedSequence` s generate_state(n_words, dtype=np.uint32) Return the requested number of words for PRNG seeding. A BitGenerator should call this method in its constructor with an appropriate `n_words` parameter to properly seed itself. Parameters ---------- n_words : int dtype : np.uint32 or np.uint64, optional The size of each word. This should only be either `uint32` or `uint64`. Strings (`'uint32'`, `'uint64'`) are fine. Note that requesting `uint64` will draw twice as many bits as `uint32` for the same `n_words`. This is a convenience for `BitGenerator`s that express their states as `uint64` arrays. Returns ------- state : uint32 or uint64 array, shape=(n_words,) Coerce an input to a uint32 array. If a `uint32` array, pass it through directly. If a non-negative integer, then break it up into `uint32` words, lowest bits first. If a string starting with "0x", then interpret as a hex integer, as above. If a string of decimal digits, interpret as a decimal integer, as above. If a sequence of ints or strings, interpret each element as above and concatenate. Note that the handling of `int64` or `uint64` arrays are not just straightforward views as `uint32` arrays. If an element is small enough to fit into a `uint32`, then it will only take up one `uint32` element in the output. This is to make sure that the interpretation of a sequence of integers is the same regardless of numpy's default integer type, which differs on different platforms. Parameters ---------- x : int, str, sequence of int or str Returns ------- seed_array : uint32 array Examples -------- >>> import numpy as np >>> from numpy.random.bit_generator import _coerce_to_uint32_array >>> _coerce_to_uint32_array(12345) array([12345], dtype=uint32) >>> _coerce_to_uint32_array('12345') array([12345], dtype=uint32) >>> _coerce_to_uint32_array('0x12345') array([74565], dtype=uint32) >>> _coerce_to_uint32_array([12345, '67890']) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.uint32)) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.int64)) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array([12345, 0x10deadbeef, 67890, 0xdeadbeef]) array([ 12345, 3735928559, 16, 67890, 3735928559], dtype=uint32) >>> _coerce_to_uint32_array(1234567890123456789012345678901234567890) array([3460238034, 2898026390, 3235640248, 2697535605, 3], dtype=uint32) p"p"ȩ"""""p"`"P"Ш"""""""ب""("""(""3  @@`({"{" |" 0M X  c l t @ ~ @   0 0 0 0 @ @ P P pp 0" 2("%2 "2"*"A". 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