+ LV-j/P^RIHt^RIt^RIt^RIt^RIt^RIt^RIH t ^RI H t ^RI H t Ht.ROt]P !4t]P$!4tRRltRtRtR tR tR tR^R ^R ^R^/tRtRt] !RR7]P:R44t] !RR7R4tR#))NumberN)copy_if_needed)xp_capabilities) good_sizeprev_good_sizec\V\4'dV3pVUu.uFp\P!V4NK ppV#uupi \d!pT;'gRp\ T R24ThRp?ii;i)zConvert ``x`` to an iterable sequence of int Parameters ---------- x : value, or sequence of values, convertible to int name : str, optional Name of the argument being converted, only used in the error message Returns ------- y : ``List[int]`` valuez) must be a scalar or iterable of integersN) isinstanceroperatorindex TypeError ValueError)xnameaes&& l/Volumes/fast/ai/experiments/ui-tars-smoke/.venv/lib/python3.14/site-packages/scipy/fft/_pocketfft/helper.py_iterable_of_intrsz!V DT() *1X^^A  * H + TwD6!JKLRSSTs'AAAA A2A--A2caVRJpVRJpV'g\VR4pVUu.uFqU^8dVSP,MTNK pp\;QJdV3RlV4F 'gK RM RM!V3RlV44'd \R4h\ \ V44\ V48wd \R4hV'g\VR4pV'd%\ V4\ V48wd \R 4hV'dV\ V4SP8d \R 4h\ SP\ V4, SP4p\W4UUu.uF!wreVR8XdSPV,MTNK# pppMUV'd,\SP4p\ SP4pM"VUu.uFpSPV,NK pp\;QJdR V4F 'gK RM RM !R V44'd\R V R 24h\V4\V43#uupiuuppiuupi)a Handle shape and axes arguments for N-D transforms. Returns the shape and axes in a standard form, taking into account negative values and checking for various potential errors. Parameters ---------- x : ndarray The input array. shape : int or array_like of ints or None The shape of the result. If both `shape` and `axes` (see below) are None, `shape` is ``x.shape``; if `shape` is None but `axes` is not None, then `shape` is ``numpy.take(x.shape, axes, axis=0)``. If `shape` is -1, the size of the corresponding dimension of `x` is used. axes : int or array_like of ints or None Axes along which the calculation is computed. The default is over all axes. Negative indices are automatically converted to their positive counterparts. Returns ------- shape : tuple The shape of the result as a tuple of integers. axes : list Axes along which the calculation is computed, as a list of integers. Naxesc3Z<"TF qSP8;'gV^8xK" R#5i)rN)ndim).0rrs& r *_init_nd_shape_and_axes..Ts&2TAFF{##a!e#Ts++TFz$axes exceeds dimensionality of inputzall axes must be uniqueshapezBwhen given, axes and shape arguments have to be of the same lengthz)shape requires more axes than are presentc3*"TF q^8xK R#5i)N)rss& rrrks %Qq5%sinvalid number of data points ( ) specified) rranyrlensetrangeziprlisttuple)rrrnoshapenoaxesrr sf&& r_init_nd_shape_and_axesr-/s<tmG T\F f-489Dq!eAFF *D9 32T23332T2 2 2CD D s4y>SY &67 7  0 CIU+>? ? 5zAFF" !LMM#e*,aff5D:=e:JK:J$!qBwA-:JK QWW QVV}%)*TT* s % sss %   -eWK @B B <d ##;:$L +s$I +'I Ic\VR4'g\P!V4pVP\P8Xd&\P!V\P 4#VPP R9d&\P!V\P4#VPPR4pVPR,'gRM\p\P!WVR7#)z` Convert to array with floating or complex dtype. float16 values are also promoted to float32. dtypefc=ALIGNEDT)r/copy) hasattrnpasarrayr/float16float32kindfloat64 newbyteorderflagsrarray)rr/r3s& r _asfarrayr>rs 1g   JJqMww"**zz!RZZ(( T !zz!RZZ(( GG  %Ewwy))4~D 88A ..cWJdR#\V\P4'g\VR4'dR#VPRJ#)zp Strict check for `arr` not sharing any data with `original`, under the assumption that arr = asarray(original) F __array__N)r r5ndarrayr4base)arroriginals&&r _datacopiedrFs;   h + ++0N0N 88t r?cRp\R4.VP,p\W4FNwrVVPV,V8d\^V4WF&K-\^VPV,4WF&RpKP \ V4pV'g W,R3#\ VP4p\W4F wrXWWV&K \ P!WpP4p W,W&V R3#)z5Internal auxiliary function for _raw_fft, _raw_fftnd.FNT) slicerr(rr*r)r5zerosr/) rrr must_copyr naxr axiszs &&& r _fix_shaperOsI4[M!&& EU! 772;! a EIa-EII " %LE x QWW Au#$$ GGAxAH d7Nr?cJV^8d\RV R24h\W3V34#)rr!r")rrO)rrKrMs&&&r _fix_shape_1drQs51u-aS <> > aw ''r?backwardorthoforwardc\V,pV'dV#^V, # \d\RT: R24Rhi;i)zAReturns the pypocketfft normalization mode from the norm argumentzInvalid norm value z,, should be "backward", "ortho" or "forward"N) _NORM_MAPKeyErrorr)normrTinorms&& r_normalizationrZsQ=$u0a%i0 =!$*2 238< ==s"""?cVf\\R^4#V^8d9V\)8dV^\,, pV#\RV R\) 24hV^8Xd \R4hV#)Ndefault_workersz workers value out of range; got z, must not be less than zworkers must not be zero)getattr_config _cpu_countr)workerss&r_workersras}w 1155{ zk ! q:~ %G N ?yI+,6;-9: : A344 Nr?T) out_of_scopec#"\4p\\P!V44\nRxV\nR# T\ni;i5i)alContext manager for the default number of workers used in `scipy.fft` Parameters ---------- workers : int The default number of workers to use Examples -------- >>> import numpy as np >>> from scipy import fft, signal >>> rng = np.random.default_rng() >>> x = rng.standard_normal((128, 64)) >>> with fft.set_workers(4): ... y = signal.fftconvolve(x, x) N) get_workersrar r r^r\)r` old_workerss& r set_workersrfs<(-K&x~~g'>?G. "-+s3AA A AAc$\\R^4#)zReturns the default number of workers within the current context Examples -------- >>> from scipy import fft >>> fft.get_workers() 1 >>> with fft.set_workers(4): ... fft.get_workers() 4 r\)r]r^rr?rrdrds 7-q 11r?)rrrfrd)N) numbersrr os threading contextlibnumpyr5scipy._lib._utilrscipy._lib._array_apir pypocketfftrr__all__localr^ cpu_countr_rr-r>rFrOrQrVrZracontextmanagerrfrdrr?rrts +13 H //  \\^  2@$F/( 6(1j!WaA > =  d# .$.4d# 2$ 2r?