B 0d I @sddlmZddlZddlZddlZddlZddlZddlmZddl Z ddl Z ddl m Z m Z mZmZddlZe eejfZe eejejfZere e eejjejjfZede ejjejjfdZyddlmZWn"ek rGdd d ZYnXd4d d Zd5d d Z eddfddZ!ddZ"ddZ#eedddZ$GdddZ%ddZ&d6ddZ'd7d d!Z(ed"d#d$d%d&d'd(d)gZ)d*d+Z*Gd,d-d-Z+d8d/d0Z,ed9d2d3Z-dS):)contextmanagerN) namedtuple)OptionalUnion TYPE_CHECKINGTypeVar GeneratorType)bound) Generatorc@s eZdZdS)r N)__name__ __module__ __qualname__rrB/var/www/html/venv/lib/python3.7/site-packages/scipy/_lib/_util.pyr !sr c st|dkr,|dkr$tdq>> a, b = np.array([1, 2, 3, 4]), np.array([5, 6, 7, 8]) >>> def f(a, b): ... return a*b >>> _lazywhere(a > 2, (a, b), f, np.nan) array([ nan, nan, 21., 32.]) Notice, it assumes that all `arrays` are of the same shape, or can be broadcasted together. Nz%One of (fillvalue, f2) must be given.z)Only one of (fillvalue, f2) can be given.rc3s|]}t|VqdS)N)npextract).0arr)condrr Bsz_lazywhere..cSsg|] }|jjqSr)dtypechar)rarrr Csz_lazywhere..) fill_valuerc3s|]}t|VqdS)N)rr)rr)rrrrGs) rasarray ValueErrornanbroadcast_arraystuple mintypecodefullshapeplace) rarraysf fillvaluef2argstemptcodeoutr)rr _lazywhere%s"  r-c stj|}tdd|D}tjt|d||d}xrtt|D]b}||||}tdkrlqFt|d\}tfdd|D} t ||| qFW|S)a? Mimic `np.select(condlist, choicelist)`. Notice, it assumes that all `arrays` are of the same shape or can be broadcasted together. All functions in `choicelist` must accept array arguments in the order given in `arrays` and must return an array of the same shape as broadcasted `arrays`. Examples -------- >>> x = np.arange(6) >>> np.select([x <3, x > 3], [x**2, x**3], default=0) array([ 0, 1, 4, 0, 64, 125]) >>> _lazyselect([x < 3, x > 3], [lambda x: x**2, lambda x: x**3], (x,)) array([ 0., 1., 4., 0., 64., 125.]) >>> a = -np.ones_like(x) >>> _lazyselect([x < 3, x > 3], ... [lambda x, a: x**2, lambda x, a: a * x**3], ... (x, a), default=np.nan) array([ 0., 1., 4., nan, -64., -125.]) cSsg|] }|jjqSr)rr)rrrrrrisz_lazyselect..r)rrFc3s|]}t|VqdS)N)rr)rr)rrrrpsz_lazyselect..) rrr!r"r#rangelenallr r$) ZcondlistZ choicelistr%defaultr+r,indexfunc_r*r)rr _lazyselectMs r5CcCst|}|dkr|j}t|ds(|f}ttj||j}t ||dtj }|j dd|}|dkrt||}||||ddd}tj ||||d}| d|S)zAllocate a new ndarray with aligned memory. Primary use case for this currently is working around a f2py issue in NumPy 1.9.1, where dtype.alignment is such that np.zeros() does not necessarily create arrays aligned up to it. N__len__rdatar)order)rrZ alignmenthasattr functoolsreduceoperatormulitemsizeemptyZuint8Z__array_interface__Zndarrayfill)r#rr:alignsizebufoffsetr8rrr_aligned_zerosus   rGcCs(|jdk r$|j|jjdkr$|S|S)zReturn an array equivalent to the input array. If the input array is a view of a much larger array, copy its contents to a newly allocated array. Otherwise, return the input unchanged. N)baserDcopy)arrayrrr _prune_arraysrLcCsd}x|D] }||9}q W|S)z Product of a sequence of numbers. Faster than np.prod for short lists like array shapes, and does not overflow if using Python integers. rr)iterableproductxrrrprods  rP)nreturncCs|dkrtt|StjS)zlCompute the factorial and return as a float Returns infinity when result is too large for a double )floatmath factorialrinf)rQrrrfloat_factorialsrXc@s(eZdZdZddZddZddZdS) DeprecatedImporta3 Deprecated import with redirection and warning. Examples -------- Suppose you previously had in some module:: from foo import spam If this has to be deprecated, do:: spam = DeprecatedImport("foo.spam", "baz") to redirect users to use "baz" module instead. cCs(||_||_t|jtj|j|_dS)N) _old_name _new_name __import__sysmodules_mod)selfZold_module_nameZnew_module_namerrr__init__s zDeprecatedImport.__init__cCs t|jS)N)dirr_)r`rrr__dir__szDeprecatedImport.__dir__cCs$td|j|jftt|j|S)Nz'Module %s is deprecated, use %s instead)warningswarnrZr[DeprecationWarninggetattrr_)r`namerrr __getattr__s zDeprecatedImport.__getattr__N)r r r __doc__rarcrirrrrrYsrYcCs|dks|tjkrtjjjSt|tjtjfr:tj|St|tjjrL|Syt|tjj r`|SWnt k rvYnXt d|dS)amTurn `seed` into a `np.random.RandomState` instance. Parameters ---------- seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional If `seed` is None (or `np.random`), the `numpy.random.RandomState` singleton is used. If `seed` is an int, a new ``RandomState`` instance is used, seeded with `seed`. If `seed` is already a ``Generator`` or ``RandomState`` instance then that instance is used. Returns ------- seed : {`numpy.random.Generator`, `numpy.random.RandomState`} Random number generator. Nz=%r cannot be used to seed a numpy.random.RandomState instance) rrandommtrand_rand isinstancenumbersIntegralinteger RandomStater AttributeErrorr)seedrrrcheck_random_states  ruTFc Cs|s$ddl}|j|r$d}t||sr2 TypeErrorr)krhminimumrrr _validate_int/sr FullArgSpecr)varargsvarkwdefaults kwonlyargskwonlydefaults annotationsc Cst|}dd|jD}dd|jD}|r>|dnd}dd|jD}|rb|dnd}tdd|jDpd}d d|jD}d d |jD}d d |jD}t||||||pd|S) asinspect.getfullargspec replacement using inspect.signature. If func is a bound method, do not list the 'self' parameter. Parameters ---------- func : callable A callable to inspect Returns ------- fullargspec : FullArgSpec(args, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations) NOTE: if the first argument of `func` is self, it is *not*, I repeat *not*, included in fullargspec.args. This is done for consistency between inspect.getargspec() under Python 2.x, and inspect.signature() under Python 3.x. cSs(g|] }|jtjjtjjgkr|jqSr)kindinspect ParameterPOSITIONAL_OR_KEYWORDPOSITIONAL_ONLYrh)rprrrrts z*getfullargspec_no_self..cSs g|]}|jtjjkr|jqSr)rrrVAR_POSITIONALrh)rrrrrrysrNcSs g|]}|jtjjkr|jqSr)rrr VAR_KEYWORDrh)rrrrrr~scss.|]&}|jtjjkr|j|jk r|jVqdS)N)rrrrr1rA)rrrrrrsz)getfullargspec_no_self..cSs g|]}|jtjjkr|jqSr)rrr KEYWORD_ONLYrh)rrrrrrscSs0i|](}|jtjjkr|j|jk r|j|jqSr)rrrrr1rArh)rrrrr sz*getfullargspec_no_self..cSs"i|]}|j|jk r|j|jqSr) annotationrArh)rrrrrrs)r signature parametersvaluesr r) r3sigr)rrrr kwdefaultsrrrrgetfullargspec_no_self]s  rc@sJeZdZdZdddZddZddZd d Zd d Zd dZ ddZ dS) MapWrapperav Parallelisation wrapper for working with map-like callables, such as `multiprocessing.Pool.map`. Parameters ---------- pool : int or map-like callable If `pool` is an integer, then it specifies the number of threads to use for parallelization. If ``int(pool) == 1``, then no parallel processing is used and the map builtin is used. If ``pool == -1``, then the pool will utilize all available CPUs. 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Replaces `RandomState.randint` (with endpoint=False) and `RandomState.random_integers` (with endpoint=True). Return random integers from the "discrete uniform" distribution of the specified dtype. If high is None (the default), then results are from 0 to low. Parameters ---------- gen : {None, np.random.RandomState, np.random.Generator} Random number generator. If None, then the np.random.RandomState singleton is used. low : int or array-like of ints Lowest (signed) integers to be drawn from the distribution (unless high=None, in which case this parameter is 0 and this value is used for high). high : int or array-like of ints If provided, one above the largest (signed) integer to be drawn from the distribution (see above for behavior if high=None). If array-like, must contain integer values. size : array-like 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. dtype : {str, dtype}, optional Desired dtype of the result. All dtypes are determined by their name, i.e., 'int64', 'int', etc, so byteorder is not available and a specific precision may have different C types depending on the platform. The default value is np.int_. endpoint : bool, optional If True, sample from the interval [low, high] instead of the default [low, high) Defaults to False. Returns ------- out: int or ndarray of ints size-shaped array of random integers from the appropriate distribution, or a single such random int if size not provided. )highrDrendpointNr)rDr)rrDr)rnr Zintegersrrkrlrmrandint)genlowrrDrrrrr rng_integerss,   r !E^1cuBnc#s6tjj|ffdd tj_z dVWdtj_XdS)z0Context with a fixed np.random.default_rng seed.cs|S)Nr)rt)orig_funrr"z$_fixed_default_rng..N)rrkZ default_rng)rtr)rr_fixed_default_rngs  r)NN)r)TFFFF)N)NNrF)r). contextlibrr<r>r]rdro collectionsrrrUtypingrrrrnumpyrrrqZ IntNumberrTZfloatingZ DecimalNumberrkr rrZSeedTyperZ numpy.random ImportErrorr-r5rGrLrPrXrYrur{rrrrrrrrrrsT     ( (  $% 6 ) 7J ?