iSSKrSSKrSSKrSSKJrJr SSKJrJrJ r J r J r J r J r JrJr SSKrSSKJr SSKJrJr SSKJrJrJrJrJrJrJrJ r J!r!J"r"J#r#J$r$J%r%J&r'J(r(J)r* SSK+J,r- SSK.J/r/ SS K0J1r1 SS K2J3r3 SS K4J5r5 SS K6J7r7 SS K8J9r9J:r:J;r;Jr> SSK?J@r@ S\AS\AS\4SjrB\(a SSKCJDrDJErE O \B"SS5rE\B"SS5rF\B"SS5rG\B"SS5rH/SQrISrJ\K"S\RRS5SS 55S!:rN\>"S"S#9SSSSSSSSSSSSS$. S%\RS&\R\AS-S'\QS(\QS-S)\Q\R-S-S*\Q\R-S-S+\SS-S,\SS-S-\SS-S.\SS-S/\SS-S0\7S1\7S-S\R\4S2jj5rT"S3S4\R5rUSS5jrV\ "S6S7S89rW\ "S9S:S89rX\SSS;S<.S%\ S=\RS=4S>\Q\R\Q-\-\R\-S?\R\\\A\4-S-S@\R\S-SA\SSSB4 SCjj5rY\SSS;S<.S%\W\R\W-S>\Q\R\Q-\-\R\-S?\R\\\A\4-S-S@\R\S-SA\SSSD4 SEjj5rY\>"S"S#9SSS;S<.S%\W\R\W-S>\Q\R\Q-\-\R\-S?\R\\\A\4-S-S@\R\S-SA\SSSD4 SFjj5rY\>"5S\R\R4SGj5rZSH\;S\;4SIjr[\[S\RSJ4SKj5r\SLr]\SMSN.SO\ASP\ SQS\RSR4SSjj5r^\SMSN.SO\ASP\ STS\RSU4SVjj5r^\SMSN.SO\ASP\ SWS\RSX4SYjj5r^\SMSN.SO\ASP\ SZS\RS[4S\jj5r^\SMS]S^.SO\ASP\\ S]S\RS_4S`jj5r^\[SMS]S^.SO\ASP\ S]\\ S]-S\RS_4Sajj5r^\SMSN.SO\ASP\ SQS\RSb4Scjj5r_\SMSN.SO\ASP\ STS\RSd4Sejj5r_\SMSN.SO\ASP\ SWS\RSf4Sgjj5r_\SMSN.SO\ASP\ SZS\RSh4Sijj5r_\SMS]S^.SO\ASP\\ S]S\RSj4Skjj5r_\[SMS]S^.SO\ASP\ S]\\ S]-S\RSj4Sljj5r_\SMSN.SO\ASP\ STS\RSm4Snjj5r`\SMSN.SO\ASP\ SWS\RSo4Spjj5r`\SMSN.SO\ASP\ SZS\RSq4Srjj5r`\SMSN.SO\ASP\ SsS\RSt4Sujj5r`\SMSvS^.SO\ASP\\ SwS\RSx4Syjj5r`\[SMSvS^.SO\ASP\ Sw\\ Sw-S\RSx4Szjj5r`\SMSN.SO\ASP\ SZS\RS{4S|jj5ra\SMSN.SO\ASP\ SsS\RS}4S~jj5ra\SMSN.SO\ASP\ SS\RS4Sjj5ra\SMSS^.SO\ASP\\ SS\RS4Sjj5ra\[SMSS^.SO\ASP\ S\\ S-S\RS4Sjj5ra\/S5rb\[SSSMS.S\AS\ASO\AS\RS4Sjj5rc\[SSSMS.S\AS\ASO\AS\RS4Sjj5rd\[SMSSTS.SO\AS\QS\QS\RS4Sjj5re\[SMSSTS.SO\AS\QS\QS\RS4Sjj5rfSrg\[\Z"54SSS;S.S\R\RS'\QS(\QS\SS\R\R4 Sjjj5rh\>"5\Z"54SSS.S\R\RS\QS\QS-S\R\R4Sjjj5ri\1"\*5S5r)S\*RS3\)lj\1"\'5S5r&S\'RS3\&lj\SSSS.S>\S\QS\QS-S\ S;S\ S;S\R\ \K\ S4-4 Sjj5rk\SSSSS.S>\S\QS\QS-S\ S;S\ S"S\R\!\K\!S4-4 Sjj5rk\SSS.S>\S\QS\QS-S\ S"S\ S;S\R\\K\S4-4 Sjj5rk\SSSS.S>\S\QS\QS-S\ S"S\ S"S\R\\K\S4-4 Sjj5rk\>"5SSS;S"S.S>\S\QS\QS-S\SS\SS\R\4 Sjj5rk\ "S\RS89rm\\""5S.S>\S\R\SS4Sjj5rn\\""5S.S>\S\R\S%SSS4Sjj5rn\>"5\""5\R"\Q5S.S>\S\R\S%SSS4Sjj5rnSroSrpS\q\9S\R\9S-4Sjrrg)N)MappingSequence) TYPE_CHECKINGAnyLiteralTypeVarUnioncastget_args get_originoverload) strategies)HypothesisExceptionInvalidArgument)_BIENDIM_MAX BasicIndexBasicIndexStrategyBroadcastableShapesShape_BIENoEllipsis_BIENoEllipsisNoNewaxis _BIENoNewaxis array_shapesbroadcastable_shapescheck_argumentcheck_valid_dimsmutually_broadcastable_shapes order_checkvalid_tuple_axes)utils)check_function)proxies) check_type)unwrap_strategies)Real)ExMappedStrategyTcheck_strategy)defines_strategy)note_deprecationmod_name attr_namereturncxSU;de[R"U5n[X!S5$![a gf=f)N.) importlib import_modulegetattr ImportError)r-r.mods U/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/hypothesis/extra/numpy.py _try_importr8AsD i  %%h/st,, s !, 99) DTypeLikeNDArrayz numpy.typingr: ArrayLikeznumpy._typing._nested_sequence_NestedSequenceznumpy._typing._array_like_SupportsArray)r array_dtypesrarrays basic_indicesboolean_dtypesrbyte_string_dtypescomplex_number_dtypesdatetime64_dtypesfloating_dtypes from_dtypeinteger_array_indicesinteger_dtypesr nested_dtypes scalar_dtypestimedelta64_dtypesunicode_string_dtypesunsigned_integer_dtypesr ) YMDhmsmsusnspsfsasc#8# UHn[U5v M g7fN)int.0xs r7 r`nsG)FAQ)Fsr1)T)force_reusable_values) alphabetmin_sizemax_size min_value max_value allow_nanallow_infinityallow_subnormal exclude_min exclude_max min_magnitude max_magnitudedtypererfrgrhrirjrkrlrmrnrorpc ^^[[RTS5 [5R 5V Vs0sHupU S:wdM UcMX_M snn mTR bVTR bITR Vs/sHn[TR US40TD6PM! nn[R"U6$TRbTRunn[UUTS9$UU4SjnTRS:Xa[R"5nGO2TRS:XaN[R"S/S[[ S [#S TR$-S 550U"S S SSSSS5D6nGOTRS:XaL[R&"S/S[[ S[#S TR$-S550U"SSSSS5D6nGOxTRS;aBTR$=(d Sn[R("S/0U"SUS9D6R+S5nGO&TRS:Xa2U"SSS TR$--S- S9n[R,"S/0UD6nGOTRS :Xa6SS TR$-S- -n[R,"S/0U"U*US- S9D6nGOTRS!:XaxTR$=(d SS"-=(d Sn[.(aS#T;a[R0"5TS#'[R2"S/0U"S#SUS9D6R+S$5nGOTRS%;aS&TR4;a6[R6"TR4R9S&5S'SS'5nO[R:"[<5nUS(La/[R,"S)S*5[R6"S+5-nO[R,"S,S*5n[R>"TR@UU5nO8TRS-:Xa[RB"[D5$[GS.T35eURITR@5$s snn fs snf)0aCreates a strategy which can generate any value of the given dtype. Compatible parameters are passed to the inferred strategy function while inapplicable ones are ignored. This allows you, for example, to customise the min and max values, control the length or contents of strings, or exclude non-finite numbers. This is particularly useful when kwargs are passed through from :func:`arrays` which allow a variety of numeric dtypes, as it seamlessly handles the ``width`` or representable bounds for you. rqNr)elementsc >1SkRU5(de[T5RU5HnST<SUSTU<SX<3nXcM URS5(aXTU:a[ US-5eURS5(dMgXTU:dMt[ US -5e UR TR 5VVs0sHupEX@;dXA;dMXE_M snn5 U$s snnf) zDUpdate default args to the strategy with user-supplied keyword args.>rgrirhzdtype z requires =z to be %s min_)zat leastmax_)zat most) issupersetset intersection startswithrupdateitems)argskwkeymsgkvrqkwargss r7 compat_kwfrom_dtype..compat_kws5@@DDDDv;++B/C5):cU!F3K?*RWKXCw">>&))bgs .C)# *=>>^^F++&+0E)# *<== 0 FLLNKNDAai17414NKL Ls C< ,C< bfwidth @rrhrirjrkrlrmrnc)rrrrorp)Sarf)rgcUSSS:g$)Nrs r7from_dtype..safourarb)rhriiUrecUSSS:g$)Nrrrs r7rrsafnrrRrO[rFllNaTlOzNo strategy inference for r)%r$nprqlocalsr}namesfieldsrFsttuplessubdtyper?kindbooleansfloatsr rminitemsizecomplex_numbersbinaryfilterintegersNP_FIXED_UNICODE characterstextstrjustsplit sampled_fromTIME_RESOLUTIONSbuildstype from_typeobjectrmap)rqrerfrgrhrirjrkrlrmrnrorprrnamesubssubtypeshaperresultroverflowreselemsrs` @r7rFrFqs6rxx(%x~~/ R/tq1>)TFYzHEFMM %  s  aA4F.G!.K L"r" s U^^+a/0VyH9ST UV s NN'aA-5   & 8!#F: P9ZhOPWW $  z ! %)) ''%))//#.r23B78C //"23C E !KK)4rwwu~EEKK i8E5::uc2 s ||F## :5'BCC ::ejj !!{S Us Q QQ&Q#cB^\rSrSrU4SjrSrSS.SjrSrSrU=r $) ArrayStrategyc>[TU]5 [U5UlX@l[ [ R"U55UlX0l Xl XPl URS;Ul g)N)rV)super__init__tuplerfillr\rprod array_sizerqelement_strategyuniquer_check_elements)selfrrrqrr __class__s r7rArrayStrategy.__init__sS 5\  bggen- 0 $zz;rc SUR<SURSUR<SUR<SUR<S3 $)NzArrayStrategy(z, shape=z, dtype=z, fill=z , unique=))rrrqrr)rs r7__repr__ArrayStrategy.__repr__sJT225Xdjj\JZZN'$))i a Q rFrcXXU'UR =(a XU:g=(a X:HnU(aU(a URO URnURRS:XafS[U5s=:=(a- [R"UR5R:Os nU(a[S US US X#<S 35e[SU<SU<SUR<SX#<S[X#5<S3 5eg![a;n[SU<S[US[U55SUR<S35UeSnAff=f![ a;n[SU<S[US[U55<SUR<35UeSnAff=f![ a S nNf=f)NzCould not add element=z of rqz to array of z- - possible mismatch of time units in dtypes?z%Internal error when checking element=rrFzGenerated subnormal float z from strategy z resulted in zx, probably as a result of NumPy being built with flush-to-zero compiler options. Consider passing allow_subnormal=False.zGenerated array element z from cannot be represented as dtype z - instead it becomes z (type zc). Consider using a more precise strategy, for example passing the `width` argument to `floats()`.) TypeErrorrr4rrqr Exceptionrrrrabsrfinfotiny) rvalridxrerr elem_changedstrategy is_subnormals r7 set_elementArrayStrategy.set_elements  3K //UC#;4FU3:L $(tyyd.C.CHzz#%)#$s3x#K#K"((4::2F2K2K#KL  )4SE#*M&+A11"*3'|D((, ~5K;/fk):(=>!! ) % !(t3c34M<<""OQ    &7wd3c36m<<"$   "!)$)L)sAD %E-AF E6E  E F6FF F)(F)cSUR;a)[R"URURS9$URRS;=(a URR S:Hn[R"UR U(a[O URS9nURR(aUR(al[R"URUR UR SS9n[URU55HupVUR!XcU5 M GO[#[%U55H.nUR!URUR5X55 M0 GOF[&R("USUR [+SUR -[-S[.R0"UR 555S 9n[R2"UR S5n[55n UR75(aUR9SUR S - 5nX(dUR;5 MOUR!URUR5X55 UR(a-X5U ;aUR;5 MU R=X55 S X'UR75(aMUR?5(a[R"S U(a[O URS9n UR!URUR5U SSS 9 U(aU RAUR5n U Sn UR(a-[RB"U 5n U (d[GS U <35e[RH"X8U 5 U(a\URAUR5n X:gnUR?5(a&[GSX><SUR<SX<S35eU nURKUR5RM5nURNbeU$![Da S n Nf=f)Nr)rqr)rrr)rrqT)rfrgrg? )rfrg average_sizerbFrz,Cannot fill unique array with non-NaN value zArray elements rz - instead they become zk. Use a more precise strategy, e.g. without trailing null bytes, as this will be an error future versions.)(rrzerosrqrrrrris_emptyrrlistsr enumeratedrawrrangelencumanyrmaxmathsqrtfullrymore draw_integerrejectaddanyastypeisnanrrputmaskreshapecopybase)rdataunsized_string_dtyperrrrrs needs_fillseen one_element fill_valueis_nanoutmismatchs r7do_drawArrayStrategy.do_draw4s{  ?88$**DJJ? ? JJOO . K4::3F3F!3K //3GTZZ  99   {{))!__!__  &dii&67DA$$Q28s6{+A$$TYYt/D/D%EvQ,ww!$//)DIIdoo67 H$7J5D--//%%a1)<=!}OO%  4+@+@!A6M;;yD( ) HHVY' % --//~~!hh-A6tzz   499!5{AD Q'"-"4"4TZZ"@K(^ ;;'!#*!5"-J:.Y 6{; -- +C}H||~~%%f&6%9: $ ~-D}'(UU F +002{{""" 5%'!&'s Q,, Q;:Q;)rrrqrrrr) __name__ __module__ __qualname____firstlineno__rrrr__static_attributes__ __classcell__)rs@r7rrs$< 5:4lxxrrcUc4U(dUR(d[R"5nU$UnU$[X#(aUS3OS5 U$)Nz.fillr)has_reusable_valuesrnothingr*)rsrrrs r7fill_forrsM | 55::= 0, a tuple of such integers, or a strategy that generates such values. * ``elements`` is a strategy for generating values to put in the array. If it is None a suitable value will be inferred based on the dtype, which may give any legal value (including eg NaN for floats). If a mapping, it will be passed as ``**kwargs`` to ``from_dtype()`` * ``fill`` is a strategy that may be used to generate a single background value for the array. If None, a suitable default will be inferred based on the other arguments. If set to :func:`~hypothesis.strategies.nothing` then filling behaviour will be disabled entirely and every element will be generated independently. * ``unique`` specifies if the elements of the array should all be distinct from one another. Note that in this case multiple NaN values may still be allowed. If fill is also set, the only valid values for it to return are NaN values (anything for which :obj:`numpy:numpy.isnan` returns True. So e.g. for complex numbers ``nan+1j`` is also a valid fill). Note that if ``unique`` is set to ``True`` the generated values must be hashable. Arrays of specified ``dtype`` and ``shape`` are generated for example like this: .. code-block:: pycon >>> import numpy as np >>> arrays(np.int8, (2, 3)).example() array([[-8, 6, 3], [-6, 4, 6]], dtype=int8) >>> arrays(np.float, 3, elements=st.floats(0, 1)).example() array([ 0.88974794, 0.77387938, 0.1977879 ]) Array values are generated in two parts: 1. Some subset of the coordinates of the array are populated with a value drawn from the elements strategy (or its inferred form). 2. If any coordinates were not assigned in the previous step, a single value is drawn from the ``fill`` strategy and is assigned to all remaining places. You can set :func:`fill=nothing() ` to disable this behaviour and draw a value for every element. If ``fill=None``, then it will attempt to infer the correct behaviour automatically. If ``unique`` is ``True``, no filling will occur by default. Otherwise, if it looks safe to reuse the values of elements across multiple coordinates (this will be the case for any inferred strategy, and for most of the builtins, but is not the case for mutable values or strategies built with flatmap, map, composite, etc) then it will use the elements strategy as the fill, else it will default to having no fill. Having a fill helps Hypothesis craft high quality examples, but its main importance is when the array generated is large: Hypothesis is primarily designed around testing small examples. If you have arrays with hundreds or more elements, having a fill value is essential if you want your tests to run in reasonable time. UnionTypec3`# UH$n[[R"U55v M& g7fr[)rFrrq)r^ds r7r`arrays..s L^Jrxx{33^s,.c>[UTTTTS9$Nr!r?)r(rsrrrs r7rarrays..'sfQtFSrc>[TUTTTS9$r+r,)rSrqrsrrs r7rr-+sfUAtFSrrrz[{}]c>[UTTTS9$)N)rrrr,)r(rrrs r7rr-9s6!5tF#Srrsforce_has_reusable_valuesFTc3B# UHn[U[5v M g7fr[ isinstancer\r^rSs r7r`r)Hs .1Jq#  zDArray shape must be integer in each dimension, provided shape was {})rsrr)!rr4typesrr rone_of__args__r3SearchStrategyflatmaprrqrrrrrrformatrFr*r%r(packmapped_strategyr0r\rrallrr)rqrrsrr unwrappeds````` r7r?r?sR E{wuk68>rc [R"[5[5[ 5[ 5[ 5[5[55$)z@Return a strategy that can return any non-flexible scalar dtype.) rr7rArHrMrErCrDrKrrr7rJrJPs? 99! rstratcJ^[5[T5U4Sj55nU$)NcN>T"U0UD6R[R5$r[)rrrq)r~rrAs r7inner%defines_dtype_strategy..inner_s$d%f%))"((33r)r+r#)rArDs` r7defines_dtype_strategyrF^s+ U^44 Lrznp.dtype[np.bool_]c.[R"S5$)z%Return a strategy for boolean dtypes.?)rrrrr7rArAgs 773<rc.^Sn[X4;SUU5 Tbz[U[5(aU4n[US5 [[U4SjU55SUT5 [SU55(a[ UVs1sHoUS-iM sn5n[ R "U5nSU;aUS- nUS :Xa=URS U-R5URS U-R5-$URX0-R5$s snf) N)rHz)Unknown endianness: was {}, must be in {}z+Dtype must have at least one possible size.c3,># UH oT;v M g7fr[r)r^rS valid_sizess r7r` dtype_factory..{s0%Q[ %sz7Invalid sizes: was {} must be an item or sequence in {}c3B# UHn[U[5v M g7fr[r2r4s r7r`rNs15az!S!!5r5rz{}rHrJrK) rr3r\r>sortedrrrr;)rsizesrM endianness valid_endianrSrAs ` r7 dtype_factoryrTms'L"3   eS ! !HEuKL 0%0 0 E    151 1 1E2EqFE23E OOE "E 4  Syy#*,,- 3::M:M0NNN 99j'// 00 3s<DrH)rRrRrQrznp.dtype[np.uint8]cgr[rrRrQs r7rMrM /2rrznp.dtype[np.uint16]cgr[rrVs r7rMrM 03rrznp.dtype[np.uint32]cgr[rrVs r7rMrMrYrrznp.dtype[np.uint64]cgr[rrVs r7rMrMrYrrrrrrVz!np.dtype[np.unsignedinteger[Any]]cgr[rrVs r7rMrMs >Arc[SUSU5$)abReturn a strategy for unsigned integer dtypes. endianness may be ``<`` for little-endian, ``>`` for big-endian, ``=`` for native byte order, or ``?`` to allow either byte order. This argument only applies to dtypes of more than one byte. sizes must be a collection of integer sizes in bits. The default (8, 16, 32, 64) covers the full range of sizes. rr\rTrVs r7rMrMs( e_j AArznp.dtype[np.int8]cgr[rrVs r7rHrHs .1rznp.dtype[np.int16]cgr[rrVs r7rHrHrWrznp.dtype[np.int32]cgr[rrVs r7rHrHrWrznp.dtype[np.int64]cgr[rrVs r7rHrHrWrznp.dtype[np.signedinteger[Any]]cgr[rrVs r7rHrHs ?z RRrznp.dtype[np.str_]c b[SSX5 [S[[XS-55SU5$)aReturn a strategy for generating unicode string dtypes, of various lengths and byteorder. While Hypothesis' string strategies can generate empty strings, string dtypes with length 0 indicate that size is still to be determined, so the minimum length for string dtypes is 1. rrbrNrrs r7rLrLrrc[5nUHDtp#[U[5(dMURU5(a gUR U5 MF g)NFT)ryr3rrzr|)lsr title_and_name_s r7#_no_title_is_name_of_a_titled_fieldrsJ 5D  ne , ,  00 KK ' ! r)rfrgallow_subarrayssubtype_strategyrc [SSX5 [R"SS5RSR5[R "SS9-n[R "U[R"XD5RS55n[R"XP5nU(a"U[R"XP[SSS 95-n[R"UUUS S 4S 9R[5$) zmReturn a strategy for generating array (compound) dtypes, with members drawn from the given subtype strategy.sizerzf{}rb)rfcUSUS:g$Nrrbr)rVs r7rarray_dtypes..sber!unrra)max_dimsmax_sidecL[US[5(aUS$USS$)Nrr3rr(s r7rr(j1s33ad@1a@rcL[US[5(aUS$USS$rrrs r7rrrr)rsrfrg unique_by) rrrrr;rr7rrrrr)rrfrgr field_names name_titlesrss r7r>r>s8.++a%))%,,7"''1:MMK)) ++223LMK*,;)QHBII <Q+O   88 A @   f 01 2rr) max_leaves max_itemsizerrcX^[R"USUS9RU4Sj5$)a(Return the most-general dtype strategy. Elements drawn from this strategy may be simple (from the subtype_strategy), or several such values drawn from :func:`array_dtypes` with ``allow_subarrays=True``. Subdtypes in an array dtype may be nested to any depth, subject to the max_leaves argument. c[USS9$)NT)r)r>)r_s r7rnested_dtypes.. s ,q$7r)rc8>TSL=(d URT:*$r[)r)r(rs r7rr s|t+Iqzz\/IIr)r recursiver)rrrs `r7rIrIs- <<7  f IJ Krc[U0UD6$r[)_valid_tuple_axesr~rs r7r r s d -f --rz Return a strategy for generating permissible tuple-values for the ``axis`` argument for a numpy sequential function (e.g. :func:`numpy:numpy.sum`), given an array of the specified dimensionality. z c[U0UD6$r[)_mutually_broadcastable_shapesrs r7rrs )4 :6 ::ra **Use with Generalised Universal Function signatures** A :doc:`universal function ` (or ufunc for short) is a function that operates on ndarrays in an element-by-element fashion, supporting array broadcasting, type casting, and several other standard features. A :doc:`generalised ufunc ` operates on sub-arrays rather than elements, based on the "signature" of the function. Compare e.g. :obj:`numpy.add() ` (ufunc) to :obj:`numpy.matmul() ` (gufunc). To generate shapes for a gufunc, you can pass the ``signature`` argument instead of ``num_shapes``. This must be a gufunc signature string; which you can write by hand or access as e.g. ``np.matmul.signature`` on generalised ufuncs. In this case, the ``side`` arguments are applied to the 'core dimensions' as well, ignoring any frozen dimensions. ``base_shape`` and the ``dims`` arguments are applied to the 'loop dimensions', and if necessary, the dimensionality of each shape is silently capped to respect the 32-dimension limit. The generated ``result_shape`` is the real result shape of applying the gufunc to arrays of the generated ``input_shapes``, even where this is different to broadcasting the loop dimensions. gufunc-compatible shapes shrink their loop dimensions as above, towards omitting optional core dimensions, and smaller-size core dimensions. .. code-block:: pycon >>> # np.matmul.signature == "(m?,n),(n,p?)->(m?,p?)" >>> for _ in range(3): ... mutually_broadcastable_shapes(signature=np.matmul.signature).example() BroadcastableShapes(input_shapes=((2,), (2,)), result_shape=()) BroadcastableShapes(input_shapes=((3, 4, 2), (1, 2)), result_shape=(3, 4)) BroadcastableShapes(input_shapes=((4, 2), (1, 2, 3)), result_shape=(4, 3)) .)min_dimsr allow_newaxisrrrallow_ellipsiscgr[rrrrrrs r7r@r@Ksr)rrrrcgr[rrs r7r@r@Xs DGr)rrcgr[rrs r7r@r@cs FIr)rrrcgr[rrs r7r@r@ns25rc [[US5 [[SU55SU<S35 [[US5 [[US5 [[ US5 U[ U5:a"U(d[SUS [ U5S 3S S S 9 [US5 UcHU(a'[[[ U5U5S-[5nO\[[ U5[5nOB[[ US5 U[ U5:a"U(d[SUS [ U5S 3S S S 9 [US5 [SSX5 [UUUUUSS9$)aReturn a strategy for :doc:`basic indexes ` of arrays with the specified shape, which may include dimensions of size zero. It generates tuples containing some mix of integers, :obj:`python:slice` objects, ``...`` (an ``Ellipsis``), and ``None``. When a length-one tuple would be generated, this strategy may instead return the element which will index the first axis, e.g. ``5`` instead of ``(5,)``. * ``shape`` is the shape of the array that will be indexed, as a tuple of positive integers. This must be at least two-dimensional for a tuple to be a valid index; for one-dimensional arrays use :func:`~hypothesis.strategies.slices` instead. * ``min_dims`` is the minimum dimensionality of the resulting array from use of the generated index. When ``min_dims == 0``, scalars and zero-dimensional arrays are both allowed. * ``max_dims`` is the maximum dimensionality of the resulting array, defaulting to ``len(shape) if not allow_newaxis else max(len(shape), min_dims) + 2``. * ``allow_newaxis`` specifies whether ``None`` is allowed in the index. * ``allow_ellipsis`` specifies whether ``...`` is allowed in the index. rc3Z# UH!n[U[5=(a US:v M# g7frNr2r]s r7r` basic_indices..s# 95aJq#  )16 )5)+shape=z3, but all dimensions must be non-negative integers.rrrz min_dims=z is larger than len(shape)=zZ, but allow_newaxis=False makes it impossible for an indexing operation to add dimensions.z 2021-09-15F)since has_codemodrarz max_dims=dimsrT)rrrrallow_fewer_indices_than_dims)r$rrr>boolr\rr,rrrrrrrs r7r@r@ysUDueW% 95 99 5(EFt^%56t]O4sHj)#e*]z!>> from numpy import array >>> x = array([-0, -1, -2, -3, -4]) >>> ind = (array([[4, 0], [0, 1]]),) # a tuple containing a 2D integer-array >>> x[ind] # the resulting array is commensurate with the indexing array(s) array([[-4, 0], [0, -1]]) Note that this strategy does not accommodate all variations of so-called 'advanced indexing', as prescribed by NumPy's nomenclature. Combinations of basic and advanced indexes are too complex to usefully define in a standard strategy; we leave application-specific strategies to the user. Advanced-boolean indexing can be defined as ``arrays(shape=..., dtype=bool)``, and is similarly left to the user. rc3Z# UH!n[U[5=(a US:v M# g7frr2r]s r7r`(integer_array_indices..s#BEqjC(2QU2Errz* must be a non-empty tuple of integers > 0rzdtype=z must be an integer dtypec ^>[TU[R"T(aU*OSUS- 5S9$)Nrrb)rqrrs)r?rr) index_shaperrqsigneds r7 array_for(integer_array_indices..array_fors.[[&$aB  rcB>^[R"UU4SjT56$)Nc36># UHnT"TU5v M g7fr[r)r^rrrs r7r`:integer_array_indices....!s'WQV +t(D(DQVs)rr)rrrs`r7r'integer_array_indices..!sBII'WQV'WXr) r$rrr>r*r issubdtypeinteger signedintegerr:)rrrqrrs` `@@r7rGrGs`ueW% B#BEBB 5(<=<0 eRZZ(VUH4M*N]]5""2"2 3F    X rc8[USS5nU(a[U5[[S[55[4;aY[ U5S:Xde[ US[5(a+USR[R:Xde[nU$USnU$)Nr8rr&rbr) r4rr6rr rr3r __bound__rgenericr)rq dtype_argss r7 _unpack_dtyper%s B/Jd5k'%fh*OQV)WW:!### jmW - -a=**bjj8 88E LqME LrcD[U5S::aU(a[US5O[nO[U5S:Xde[US5nU[La [5$[ U5[ [ S[55[4;aU$[R"U5$)Nrbrrar&) rrrrJrr4r6rr rrq)r~rqs r7_dtype_from_argsr3s 4yA~+/ d1g&C4yA~~d1g& | e VX>F F 88E?rthingc [R"[R"5[R"5[R"5[R "5[R "5[R"5/5n[R"[R"5[R"5[R"5[R "5[R "5[R"5R[R5/5nU[R:XaB[R"[5[5[5[!5[#55$U[$:Xa[R"U[R&"[R("U5[R*S9[R&"[R,"[R.5[R*S95$[1U[25(aR[5U[R65(a3[R"U5nUR8S;a [;U5$S$[=U5nUcUn[?U5nU[@:XGa[CU5S::deU(a[R,"US5OUn[R"[R("U5[R&"[R*"5[R*5[R&"[R*"U5[R*5[R&"[R*"Xf5[R*55$U[RDRF[R.[H4;a[KU5n[MU[OSS95$g)zCalled by st.from_type to try to infer a strategy for thing using numpy. If we can infer a numpy-specific strategy for thing, we return that; otherwise, we return None. )extendOVNrbrra)r)(rr7rrrrrrrbytesisasciirrqrJrBrLr>rIr;rrrrndarrayr3r issubclassrrrFr r r<rtypingr:r=rr?r)r base_stratsbase_strats_asciirqoriginr~ base_strats r7 _from_typerDs)) KKM KKM IIK    GGI IIK   K KKM KKM IIK    GGI IIK  u}} -    yy O  ! # N O    yy  LL"34RYY G LLbjj1")) D  %:eRZZ#@#@$)JJd$:z% DD  F ~ E?D  4yA~~.2R\\$q'* yy HHZ LLbii 0 LL:. : LL::BII F   "))##RZZ@@ &e\1566 r))sr2rr6collections.abcrrrrrrrr r r r r numpyr hypothesisrrhypothesis.errorsrrhypothesis.extra._array_helpersrrrrrrrrrrrrrrrrr rhypothesis.internal.conjecturer!rhypothesis.internal.coverager"hypothesis.internal.reflectionr#hypothesis.internal.validationr$$hypothesis.strategies._internal.lazyr%'hypothesis.strategies._internal.numbersr&*hypothesis.strategies._internal.strategiesr'r(r)r*%hypothesis.strategies._internal.utilsr+hypothesis.utils.deprecationr,rr8 numpy.typingr9r:r;r<r=__all__rr __version__rrrqr9r\floatrrFrrrPr r?rJrFrArTrMrHrErCr~rDrKrBrLrr>rI__doc__r@rrrGrrrrrrr7rsV -   'B$7725B8 C9###//.)4G  4 >@QR8:JK 0VG)=)=c)B2A)FGG7R-/3$($(!"&#'##!%x" 88x"$t+x" x" Dj x" U{T! x"U{T!x"d{x"4Kx"D[x"x"x"x"$;x"sx".x"vB%%D C{# C|$ CG*. *  1 1- @@ A* ""3' '% /"2C2CE2J J*$wsCx'884? *  C 4 ' *  *%* * CG*. , r  # #, ""3' '% /"2C2CE2J J,$wsCx'884? ,  C 4 ' ,  ,', ,- CG*. x? r  # #x? 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