U Gv f_ @sddlmZddlZddlZddlZddlZddlmZddlZddl Z ddl m Z m Z m Z mZddlZe eejfZe eejejfZe re e eejjejjfZede ejjejjfdZzddlmZWn"ek rGdd d ZYnXdAd d ZdBd d ZeddfddZ ddZ!ddZ"eedddZ#ddZ$dCddZ%dDddZ&ed d!d"d#d$d%d&d'gZ'd(d)Z(Gd*d+d+Z)Gd,d-d-Z*dEd/d0Z+edFd2d3Z,dGd4d5Z-d6d7Z.dHd8d9Z/dId;d<Z0dJd=d>Z1d?d@Z2dS)K)contextmanagerN) namedtuple)OptionalUnion TYPE_CHECKINGTypeVar GeneratorType)bound) Generatorc@s eZdZdS)r N)__name__ __module__ __qualname__rr4/tmp/pip-unpacked-wheel-96ln3f52/scipy/_lib/_util.pyr sr c st|dkr,|dkr$tdq>> import numpy as np >>> a, b = np.array([1, 2, 3, 4]), np.array([5, 6, 7, 8]) >>> def f(a, b): ... return a*b >>> _lazywhere(a > 2, (a, b), f, np.nan) array([ nan, nan, 21., 32.]) Notice, it assumes that all `arrays` are of the same shape, or can be broadcasted together. Nz%One of (fillvalue, f2) must be given.z)Only one of (fillvalue, f2) can be given.rc3s|]}t|VqdSNnpextract.0Zarrcondrr Bsz_lazywhere..cSsg|] }|jjqSrdtypecharrarrr Csz_lazywhere..Z fill_valuerc3s|]}t|VqdSrrrrrrrGs) rasarray ValueErrornanbroadcast_arraystuple mintypecodefullshapeplace) rarraysf fillvaluef2argstemptcodeoutrrr _lazywhere$s"  r2c stj|}tdd|D}tjt|d||d}t||D]T\}tdkrZqBt|d\}tfdd|D}t|||qB|S)aZ 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 -------- >>> import numpy as np >>> 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|] }|jjqSrrrrrrrjsz_lazyselect..rr Fc3s|]}t|VqdSrrrrrrrpsz_lazyselect..) rr$r&r'r(zipallr%r)) ZcondlistZ choicelistr*defaultr0r1func_r/rrr _lazyselectMs r8CcCst|}|dkr|j}t|ds(|f}ttj||j}t ||dtj }|j dd|}|dkrt||}||||ddd}tj ||||d}| d|S)zAllocate a new ndarray with aligned memory. Primary use case for this currently is working around a f2py issue in NumPy 1.9.1, where dtype.alignment is such that np.zeros() does not necessarily create arrays aligned up to it. N__len__rdatar)order)rr alignmenthasattr functoolsreduceoperatormulitemsizeemptyZuint8Z__array_interface__ndarrayfill)r(rr=Zalignsizebufoffsetr;rrr_aligned_zerosus   rKcCs(|jdk r$|j|jjdkr$|S|S)zReturn an array equivalent to the input array. If the input array is a view of a much larger array, copy its contents to a newly allocated array. Otherwise, return the input unchanged. N)baserHcopy)arrayrrr _prune_arraysrPcCsd}|D] }||9}q|S)z Product of a sequence of numbers. Faster than np.prod for short lists like array shapes, and does not overflow if using Python integers. rr)iterableproductxrrrprods rT)nreturncCs|dkrtt|StjS)zlCompute the factorial and return as a float Returns infinity when result is too large for a double )floatmath factorialrinf)rUrrrfloat_factorialsr\cCsd|dks|tjkrtjjjSt|tjtjfr:tj|St|tjjtjj frT|St d|dS)a`Turn `seed` into a `np.random.RandomState` instance. Parameters ---------- seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional If `seed` is None (or `np.random`), the `numpy.random.RandomState` singleton is used. If `seed` is an int, a new ``RandomState`` instance is used, seeded with `seed`. If `seed` is already a ``Generator`` or ``RandomState`` instance then that instance is used. Returns ------- seed : {`numpy.random.Generator`, `numpy.random.RandomState`} Random number generator. Nz=%r cannot be used to seed a numpy.random.RandomState instance) rrandommtrand_rand isinstancenumbersIntegralinteger RandomStater r"seedrrrcheck_random_states  rgTFc Cs|s$ddl}|j|r$d}t||s|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|] }|jtjjtjjfkr|jqSr)kindinspect ParameterPOSITIONAL_OR_KEYWORDPOSITIONAL_ONLYrsrprrrrJs  z*getfullargspec_no_self..cSs g|]}|jtjjkr|jqSr)r|r}r~VAR_POSITIONALrsrrrrrOsrNcSs g|]}|jtjjkr|jqSr)r|r}r~ VAR_KEYWORDrsrrrrrTscss.|]&}|jtjjkr|j|jk r|jVqdSr)r|r}r~rr5rErrrrrYs z)getfullargspec_no_self..cSs g|]}|jtjjkr|jqSr)r|r}r~ KEYWORD_ONLYrsrrrrr^scSs0i|](}|jtjjkr|j|jk r|j|jqSr)r|r}r~rr5rErsrrrr bs  z*getfullargspec_no_self..cSs"i|]}|j|jk r|j|jqSr) annotationrErsrrrrres )r} signature parametersvaluesr%ru) r6sigr.rvrwrxry kwdefaultsr{rrrgetfullargspec_no_self4s4  rc@s eZdZdZddZddZdS)_FunctionWrapperz? Object to wrap user's function, allowing picklability cCs||_|dkrgn||_dSrr+r.)selfr+r.rrr__init__osz_FunctionWrapper.__init__cCs|j|f|jSrr)rrSrrr__call__ssz_FunctionWrapper.__call__N)r r r __doc__rrrrrrrksrc@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. If `pool` is a map-like callable that follows the same calling sequence as the built-in map function, then this callable is used for parallelization. rcCsd|_t|_d|_t|r*||_|j|_nvddlm}t|dkr\||_|jj|_d|_nDt|dkrjn6t|dkr|t|d|_|jj|_d|_ntddS) NFr)Poolr<Tr)Z processeszUNumber of workers specified must be -1, an int >= 1, or an object with a 'map' method) poolmap_mapfunc _own_poolcallablemultiprocessingrint RuntimeError)rrrrrrrs$       zMapWrapper.__init__cCs|Srrrrrr __enter__szMapWrapper.__enter__cCs|jr|jdSr)rr terminaterrrrrszMapWrapper.terminatecCs|jr|jdSr)rrjoinrrrrrszMapWrapper.joincCs|jr|jdSr)rrcloserrrrrszMapWrapper.closecCs|jr|j|jdSr)rrrr)rexc_type exc_value tracebackrrr__exit__s zMapWrapper.__exit__c Cs@z|||WStk r:}ztd|W5d}~XYnXdS)Nz;The map-like callable must be of the form f(func, iterable))rrq)rr6rQerrrrs zMapWrapper.__call__N)r) r r r rrrrrrrrrrrrrws rint64cCst|tr|j|||||dS|dkr0tjjj}|rn|dkrP|j|d||dS|dk rn|j||d||dS|j||||dSdS)al Return random integers from low (inclusive) to high (exclusive), or if endpoint=True, low (inclusive) to high (inclusive). 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. )highrHrendpointNr)rHr)rrHr)r`r Zintegersrr]r^r_randint)genlowrrHrrrrr rng_integerss,   r !E^1cuBnc#s6tjj|ffdd tj_z dVW5tj_XdS)z0Context with a fixed np.random.default_rng seed.cs|SrrreZorig_funrrz$_fixed_default_rng..N)rr]Z default_rngrerrr_fixed_default_rngs  rcCs,tj||d}|r(|dk r(tj||d}|S)z argmin with a `keepdims` parameter. See https://github.com/numpy/numpy/issues/8710 If axis is not None, a.shape[axis] must be greater than 0. axisN)rZargminZ expand_dims)rkeepdimsrresrrr_argmin s rcCs$tt||dd}tj|||dS)a Return the first non-nan value along the given axis. If a slice is all nan, nan is returned for that slice. The shape of the return value corresponds to ``keepdims=True``. Examples -------- >>> import numpy as np >>> nan = np.nan >>> a = np.array([[ 3., 3., nan, 3.], [ 1., nan, 2., 4.], [nan, nan, 9., -1.], [nan, 5., 4., 3.], [ 2., 2., 2., 2.], [nan, nan, nan, nan]]) >>> _first_nonnan(a, axis=0) array([[3., 3., 2., 3.]]) >>> _first_nonnan(a, axis=1) array([[ 3.], [ 1.], [ 9.], [ 5.], [ 2.], [nan]]) Trrr)rrisnanZtake_along_axis)rrrrrrr _first_nonnansrcCs|dkr$|jdkrdS|}d}nF|j}||dkrj|d|d|||dd}tj|dtdSt||d}||kt|Bj||dS) a Determine if the values along an axis are all the same. nan values are ignored. `a` must be a numpy array. `axis` is assumed to be normalized; that is, 0 <= axis < a.ndim. For an axis of length 0, the result is True. That is, we adopt the convention that ``allsame([])`` is True. (There are no values in the input that are different.) `True` is returned for slices that are all nan--not because all the values are the same, but because this is equivalent to ``allsame([])``. Examples -------- >>> import numpy as np >>> a = np.array([[ 3., 3., nan, 3.], [ 1., nan, 2., 4.], [nan, nan, 9., -1.], [nan, 5., 4., 3.], [ 2., 2., 2., 2.], [nan, nan, nan, nan]]) >>> _nan_allsame(a, axis=1, keepdims=True) array([[ True], [False], [False], [False], [ True], [ True]]) NrT)rrr rr) rHravelr(rr'boolrrr4)rrrZshpZa0rrr _nan_allsame:s"  $ r propagatec Cst|tjsd}dddg}||kr>tdddd|Dt|jtjr|r~tjd d d t t |}W5QRXqt | }nJt|jt rd}| D](}tt|tjrt |rd }qqnd}|r|dkrtd ||fS) NFrraiseZomitznan_policy must be one of {%s}z, css|]}d|VqdS)z'%s'Nr)rsrrrrpsz _contains_nan..ignore)invalidZoverTzThe input contains nan values)r`rrFr"rrlrrmZerrstatersumanyobjectrtypenumber)rZ nan_policyZ use_summationZpoliciesZ contains_nanelrrr _contains_nanjs,    rcsfdd}|S)a Generate decorator for backward-compatible keyword renaming. Apply the decorator generated by `_rename_parameter` to functions with a recently renamed parameter to maintain backward-compatibility. After decoration, the function behaves as follows: If only the new parameter is passed into the function, behave as usual. If only the old parameter is passed into the function (as a keyword), raise a DeprecationWarning if `dep_version` is provided, and behave as usual otherwise. If both old and new parameters are passed into the function, raise a DeprecationWarning if `dep_version` is provided, and raise the appropriate TypeError (function got multiple values for argument). Parameters ---------- old_name : str Old name of parameter new_name : str New name of parameter dep_version : str, optional Version of SciPy in which old parameter was deprecated in the format 'X.Y.Z'. If supplied, the deprecation message will indicate that support for the old parameter will be removed in version 'X.Y+2.Z' Notes ----- Untested with functions that accept *args. Probably won't work as written. cs tfdd}|S)Nc s|krrfd}tt|dd|d<d|}dddd|d }tj|tdd|krjd d }t|| |<||S) N.rrLzUse of keyword argument `z!` is deprecated and replaced by `z`. Support for `z` will be removed in SciPy ) stacklevelz2() got multiple values for argument now known as ``) splitstrrrwarningswarnDeprecationWarningr rqpop)r.kwargsZ end_versionmessage) dep_versionfunnew_nameold_namerrwrappers  z5_rename_parameter..decorator..wrapper)r@wraps)rrrrr)rr decoratorsz$_rename_parameter..decoratorr)rrrrrrr_rename_parameters rcs(|jj}fdd||D}|S)Ncs g|]}tjt|qSr)rr]r r)rZchild_ssbgrrrsz_rng_spawn..)Z_bit_generatorZ _seed_seqspawn)rngZ n_childrenssZ child_rngsrrr _rng_spawns  r)NN)r)TFFFF)N)NNrF)r)FN)F)rT)N)3 contextlibrr@rBrra collectionsrr}rYtypingrrrrZnumpyrrrcZ IntNumberrXZfloatingZ DecimalNumberr]r rdZSeedTyperZ numpy.random ImportErrorr2r8rKrPrTr\rgrortrurrrrrrrrrrrrrrrsr      ) (    8 )7 J @  0 7