z i(>SrSSKJr SSKrSSKJr "SS\5rg)zQuasidistribution class)sqrtN)ProbDistributionc^\rSrSrSr\R "S5rSrS U4Sjjr S Sjr SSjr Sr \ S 5rS rS rU=r$)QuasiDistributionz7A dict-like class for representing quasi-probabilities.z^[01]+$c>X lX0lSUlU(Ga[[ UR 555n[ U[5(a5[[[UR 5555S- UlGO"[ U[5(GaURS5(dURS5(acUR5VVs0sHupV[US5U_M nnn[[[UR 5555S- UlO}URRU5(aG[SU55UlUR5VVs0sHupV[US5U_M nnnO[!S5e[#S5e[$TU]MU5 gs snnfs snnf) aBuilds a quasiprobability distribution object. .. note:: The quasiprobability values might include floating-point errors. ``QuasiDistribution.__repr__`` rounds using :meth:`numpy.round` and the parameter ``ndigits`` can be manipulated with the class attribute ``__ndigits__``. The default is ``15``. Parameters: data (dict): Input quasiprobability data. Where the keys represent a measured classical value and the value is a float for the quasiprobability of that result. The keys can be one of several formats: * A hexadecimal string of the form ``"0x4a"`` * A bit string e.g. ``'0b1011'`` or ``"01011"`` * An integer shots (int): Number of shots the distribution was derived from. stddev_upper_bound (float): An upper bound for the standard deviation Raises: TypeError: If the input keys are not a string or int ValueError: If the string format of the keys is incorrect r0x0bc38# UHn[U5v M g7fN)len).0keys [/home/james-whalen/.local/lib/python3.13/site-packages/qiskit/result/distributions/quasi.py -QuasiDistribution.__init__..Ls(BTcSTszThe input keys are not a valid string format, must either be a hex string prefixed by '0x' or a binary string optionally prefixed with 0bz9Input data's keys are of invalid type, must be str or intN)shots_stddev_upper_bound _num_bitsnextiterkeys isinstanceintrbinmaxstr startswithitems_bitstring_regexsearch ValueError TypeErrorsuper__init__)selfdatarstddev_upper_bound first_keyrvalue __class__s rr(QuasiDistribution.__init__ sb6 #5  T$))+./I)S))"%STYY[)9%:!;a!?Is++''--1E1Ed1K1KAEN:3CQK.DN&)S-=)>%?!%CDN**11)<<%((BT(B%BDNAEN:3CQK.DND$6  [\\ !OOs F;8Gc~[[UR5SS95n[U5n0nSnSnUR5H;upxXU- -n U S:aXX- nUS-nXhU-- nM$XeU- XS- -- nX'XS- -XG'M= U(a [ X@R 5[ U54$[ X@R 5$)aTakes a quasiprobability distribution and maps it to the closest probability distribution as defined by the L2-norm. Parameters: return_distance (bool): Return the L2 distance between distributions. Returns: ProbDistribution: Nearest probability distribution. float: Euclidean (L2) distance of distributions. Notes: Method from Smolin et al., Phys. Rev. Lett. 108, 070502 (2012). c US$)Nr)items rDQuasiDistribution.nearest_probability_distribution..gs$q')rrr)dictsortedr"rrrr) r)return_distance sorted_probs num_elems new_probsbetadiffrvaltemps r nearest_probability_distribution2QuasiDistribution.nearest_probability_distributionXsF4::<5IJK  %  $**,HC ))Dax Q c ! )d.>??!-!2T5E!E - #Izz:DJF F ::66r6cUc UROUnUR5VVs0sH!up4[US5RU5U_M# snn$s snnf)aNBuild a quasi-probabilities dictionary with binary string keys Parameters: num_bits (int): number of bits in the binary bitstrings (leading zeros will be padded). If None, a default value will be used. If keys are given as integers or strings with binary or hex prefix, the default value will be derived from the largest key present. If keys are given as bitstrings without prefix, the default value will be derived from the largest key length. Returns: dict: A dictionary where the keys are binary strings in the format ``"0110"`` b)rr"formatzfill)r)num_bitsnrr-s rbinary_probabilities&QuasiDistribution.binary_probabilitiesysK'.DNNHCG::<P.>??R^_``_s A )rrr)NN)Fr)__name__ __module__ __qualname____firstlineno____doc__recompiler#rUr(rArIrNpropertyr+rV__static_attributes__ __classcell__)r.s@rrrsRAzz*-K6p7BQ$@((aar6r)r\mathrr] probabilityrr7rr2r6rrds# )@a@ar6