o eRh V@sddlZddlZddlZddlZddlmZddlZddlm Z ddl Z ddl Z ddl mZddlmZddlmZmZddlmZz ddlmZdZWn eyWd ZYnwzddlZdZWn eykd ZYnwd d Zd d Ze jdddddZ ese jddZ!deiZ"erOe#ee$rOz"ddl%Z%e"&de%ie'e%j(e)dkre*de%j+ddWn e*yYnwzddl,Z,e"&de,ie,-eWn e*yYnwz ddl.Z.e"&de.iWn e*yYnwz!ddl/Z0e"&de0jie0j1&dde0j1&de02edWn e*yYnwe3dvrOe4eZ5d e5vr2nz d!d"e5DZ"Wne6yNd#e"7Z8e9e8wde"vrVd$Ze j:;d%e"<Z=e j:j>ed&d'Z?d(d)Z@e jd*d+ZAe jd,d-ZBdEd/d0ZCe jDEejFGeHd1e jIjJd2ddd3e jIjJd4ddddeKe jLd5ejMNd6d4ZOe jIPeOeredFd7d8ZQeQe_ReSgd9e_Tej(d:krejT&eSgd;gd<e_Ud=d=d>d?d@dAe_VeSdBge_WdCgdDie_Xde_YdSdS)GN)contextmanager) get_fpu_mode)FPUModeChangeWarning)SCIPY_ARRAY_API SCIPY_DEVICE)_pep440) dt_configTFcCs|dd|dd|ddzddl}Wnty'|ddYnwzddlm}Wnty?|ddYnw|dd |dd tsb|dd |dd |dd dSdS)Nmarkerszslow: Tests that are very slow.zHxslow: mark test as extremely slow (not run unless explicitly requested)z8xfail_on_32bit: mark test as failing on 32-bit platformsrz.timeout: mark a test for a non-default timeout)parse_durationz8fail_slow: mark a test for a non-default timeout failurezskip_xp_backends(backends, reason=None, np_only=False, cpu_only=False, exceptions=None): mark the desired skip configuration for the `skip_xp_backends` fixture.zxfail_xp_backends(backends, reason=None, np_only=False, cpu_only=False, exceptions=None): mark the desired xfail configuration for the `xfail_xp_backends` fixture.zOparallel_threads(n): run the given test function in parallel using `n` threads.z8thread_unsafe: mark the test function as single-threadedzCiterations(n): run the given test function `n` times in each thread)addinivalue_linepytest_timeout Exceptionpytest_fail_slowr PARALLEL_RUN_AVAILABLE)configr r rP/home/air/sanwanet/backup_V2/venv/lib/python3.10/site-packages/scipy/conftest.pypytest_configuresV   rc Cs|d}|dur'z ttjdd}Wn tyd}Ynw|s'td|d}|durCt dj dkrCt d |j dt |}|tjz dd lm}d }Wn tycd}Ynw|rz ttjd }WntyYWddSwtd std}t||d}z||ddWn tyYWddSwWddSWddSWddS1swYdS)Nxslow SCIPY_XSLOW0Fz@very slow test; set environment variable SCIPY_XSLOW=1 to run itxfail_on_32bitrz&Fails on our 32-bit test platform(s): )threadpool_limitsTPYTEST_XDIST_WORKER_COUNTOMP_NUM_THREADSblas)user_api)get_closest_markerintosenvironget ValueErrorpytestskipnpintpitemsizexfailargsnptsuppress_warningsfilter PytestUnraisableExceptionWarning threadpoolctlrr KeyErrorgetenv cpu_countmax) itemmarkvsuprHAS_THREADPOOLCTLxdist_worker_countmax_openmp_threadsthreads_per_workerrrrpytest_runtest_setupIsT            "r>function)scopeautouseccsFt}dVt}||kr!tjd|dd|ddtdddSdS)z9 Check FPU mode was not changed during the test. NzFPU mode changed from z#xz to z during the testr)category stacklevel)rwarningswarnr)requestold_modenew_moderrrcheck_fpu_modezs rIcCsdS)Nrrrrrrnum_parallel_threadssrJnumpyarray_api_strictz2.0z'array-api-strict must be >= version 2.0z2023.12) api_versiontorchcupy jax.numpyjax_enable_x64jax_default_device)1trueallcCsi|]}|t|qSr)xp_available_backends).0backendrrr srYz!'--array-api-backend' must be in cudaxpzsTest involves masked arrays, object arrays, or other types that are not valid input when `SCIPY_ARRAY_API` is used.reasoncCs|j|dj}t|dkrtd|t|j|d}g}i}|D]J}|jdr=d|d<|jdg|d<n|jdrU|dsUd|d<|jdg|d<t|jdkrq|jd}| ||j d i||jiq'||fS) z%A helper for {skip,xfail}_xp_backends _xp_backendsrzmultiple backends: np_onlyT exceptionscpu_onlyrNr) keywordsr,lenr%listnode iter_markerskwargsr$appendupdate)rF skip_or_xfailargs_r backendsrgmarkerrXrrr_backends_kwargs_from_requests(      rncC2d|jvrdSt|dd\}}t|||dddS)askip_xp_backends(backend=None, reason=None, np_only=False, cpu_only=False, exceptions=None) Skip a decorated test for the provided backend, or skip a category of backends. See ``skip_or_xfail_backends`` docstring for details. Note that, contrary to ``skip_or_xfail_backends``, the ``backend`` and ``reason`` arguments are optional single strings: this function only skips a single backend at a time. To skip multiple backends, provide multiple decorators. skip_xp_backendsNr'rjrbrnskip_or_xfail_xp_backendsr[rFrlrgrrrrps rpcCro)axfail_xp_backends(backend=None, reason=None, np_only=False, cpu_only=False, exceptions=None) xfail a decorated test for the provided backend, or xfail a category of backends. See ``skip_or_xfail_backends`` docstring for details. Note that, contrary to ``skip_or_xfail_backends``, the ``backend`` and ``reason`` arguments are optional single strings: this function only xfails a single backend at a time. To xfail multiple backends, provide multiple decorators. xfail_xp_backendsNr+rqrrrtrrrrus rur'c Cstt|}|dd}|dd}|dg}|d}r&td|d|r,|r,d}|r6|s6|s6td|r^|d d }t|tsMt|d krMtd |jd kr\|j|vr\||ddS|rd}|durhgn|}trt dkr|jdkrd|vr||dn5|jdkrd|vrd| dj j vr||dn|jdkrd|vr| d D] } d| jvr||dq|durt|D]\} } |j| kr|| d }|sd| }||dqdSdS)an Skip based on the ``skip_xp_backends`` or ``xfail_xp_backends`` marker. See the "Support for the array API standard" docs page for usage examples. Parameters ---------- backends : tuple Backends to skip/xfail, e.g. ``("array_api_strict", "torch")``. These are overriden when ``np_only`` is ``True``, and are not necessary to provide for non-CPU backends when ``cpu_only`` is ``True``. For a custom reason to apply, you should pass a dict ``{'reason': '...'}`` to a keyword matching the name of the backend. reason : str, optional A reason for the skip/xfail in the case of ``np_only=True``. If unprovided, a default reason is used. Note that it is not possible to specify a custom reason with ``cpu_only``. np_only : bool, optional When ``True``, the test is skipped/xfailed for all backends other than the default NumPy backend. There is no need to provide any ``backends`` in this case. To specify a reason, pass a value to ``reason``. Default: ``False``. cpu_only : bool, optional When ``True``, the test is skipped/xfailed on non-CPU devices. There is no need to provide any ``backends`` in this case, but any ``backends`` will also be skipped on the CPU. Default: ``False``. exceptions : list, optional A list of exceptions for use with ``cpu_only`` or ``np_only``. This should be provided when delegation is implemented for some, but not all, non-CPU/non-NumPy backends. skip_or_xfail : str ``'skip'`` to skip, ``'xfail'`` to xfail. r_Frar`reasonsz.provide a single `reason=` kwarg; got reasons=z insteadz<`exceptions` is only valid alongside `cpu_only` or `np_only`r]z#do not run with non-NumPy backends.rz8please provide a singleton `reason` when using `np_only`rKr\NzTno array-agnostic implementation or delegation available for this backend and devicecpurOrNrrPz#do not run with array API backend: )getattrr&r$r% isinstancestrrc__name__rremptydevicetypedevices device_kind enumerate) r[rlrgrjr_rar`rvr]dirXrrrrssT #              rsz .hypothesisnondeterministic)namedeadline print_blob deterministic)rrrdatabase derandomizesuppress_health_checkSCIPY_HYPOTHESIS_PROFILEc cst}ddg}|D] }ttdd||<q gd}|D] }ttd||<qddlm}d d g}|D] }t|jd d||<q1gd }|D] }ttd||<qCttd dtdtdtd|jdd}||t d} ddl m } ddl } | U| j dt2|r|j|vrtjdi||jdVn|r|j| vrdVn tdtdVWdn1swYWddSWddS1swYdS)zmTemporarily turn (almost) all warnings to errors. Filter out known warnings which we allow. zscipy.linalg.normzscipy.ndimage.center_of_masszdivide by zero)rBmessage)zscipy.signal.cwtzscipy.signal.morletzscipy.signal.morlet2zscipy.signal.rickerzscipy.integrate.simpsonzscipy.interpolate.interp2dzscipy.linalg.kron)rBr) integratezscipy.special.ellip_normalzscipy.special.ellip_harm_2zThe occurrence of roundoff)zscipy.stats.anderson_ksampzscipy.stats.kurtosistestzscipy.stats.normaltestscipy.sparse.linalg.normzExited at iterationzthe matrix subclass is not)rrBz"The maximum number of subdivisions)rz linalg.rstz stats.rstscipy.signal.normalize)_fixed_default_rngNignoreerror)r)dictRuntimeWarningDeprecationWarningscipyrIntegrationWarning UserWarningPendingDeprecationWarningrisetscipy._lib._utilrrKrandomseedrDcatch_warningsrfilterwarnings simplefilterWarning) testknown_warningsdivide_by_zeror deprecatedr integration_wuser_wdctlegitrr(rrrwarnings_errors_and_rngsf         "r)zscipy.linalg.LinAlgErrorzscipy.fftpack.fftshiftzscipy.fftpack.ifftshiftzscipy.fftpack.fftfreqzscipy.special.sinczscipy.optimize.show_optionsrrz$scipy.io.matlab.MatlabObject.stridesz"scipy.io.matlab.MatlabObject.dtypez"scipy.io.matlab.MatlabOpaque.dtypez$scipy.io.matlab.MatlabOpaque.stridesz&scipy.io.matlab.MatlabFunction.stridesz$scipy.io.matlab.MatlabFunction.dtype2)zscipy.io.hb_readzscipy.io.hb_writez)scipy.sparse.csgraph.connected_componentsz&scipy.sparse.csgraph.depth_first_orderz"scipy.sparse.csgraph.shortest_pathz#scipy.sparse.csgraph.floyd_warshallzscipy.sparse.csgraph.dijkstraz!scipy.sparse.csgraph.bellman_fordzscipy.sparse.csgraph.johnsonzscipy.sparse.csgraph.yenz(scipy.sparse.csgraph.breadth_first_orderz*scipy.sparse.csgraph.reverse_cuthill_mckeez$scipy.sparse.csgraph.structural_rankz*scipy.sparse.csgraph.construct_dist_matrixz%scipy.sparse.csgraph.reconstruct_pathzscipy.ndimage.value_indiceszscipy.stats.mstats.describe) zscipy.stats.distributionszscipy.optimize.cython_optimizez scipy.testzscipy.show_configzscipy/special/_precomputez#scipy/interpolate/_interpnd_info.pyzscipy/_lib/array_api_compatzscipy/_lib/highszscipy/_lib/unuranzscipy/_lib/_gcutils.pyzscipy/_lib/doccer.pyzscipy/_lib/_uarrayzReST parser limitationz__cinit__ unexpected argumentznan in scalar_powerzintegration warning)zND_regular_grid.rstzextrapolation_examples.rstzsampling_pinv.rstzsampling_srou.rstzprobability_distributions.rstzintegrate.nquad(func,zio.rst)z octave_a.matzoctave_cells.matzoctave_struct.mat)r')N)Zjsonr"rDtempfile contextlibrrKr( numpy.testingtestingr-r& hypothesisscipy._lib._fpumoderscipy._lib._testutilsrscipy._lib._array_apirr scipy._librscipy_doctest.conftestr HAVE_SCPDTModuleNotFoundErrorpytest_run_parallelrr rr>fixturerIrJrVryrzrLriparse __version__Version ImportErrorset_array_api_strict_flagsrNset_default_devicerO jax.numpyjaxrrlowerloadsSCIPY_ARRAY_API_r2keysmsgr%r7 parametrizevaluesarray_api_compatibleskipifskip_xp_invalid_argrnrprurs configurationset_hypothesis_home_dirpathjoin gettempdirsettingsregister_profilerd HealthCheckr#r$r load_profileruser_context_mgrrskiplistpytest_extra_ignorepytest_extra_xfail pseudocodelocal_resources strict_checkrrrrs        * 1            V  Q