]h6!SrSSKJr SSKJrJrJrJr SSKr SSK r SSK J r SSKJr SSKJr SS KJr SS KJr "S S 5rg) zCContainer for the results of running autodiff variational inference) OrderedDict)DictOptionalTupleUnionN)Method)scan_variational_csv) get_logger)InferenceMetadata)RunSetc p\rSrSrSrS\SS4SjrS\4SjrS\S\ \ R\ 44S jr S \SS4S jr\S\4S j5r\S\\S 44Sj5r\S\ 4Sj5r\S\ R4Sj5r\S\R.4Sj5r\S\\\ R44Sj5r\S\4Sj5rSS.S\S\\S\ \ R\ 44SjjrSS.S\\S\\\ \ R\ 444Sjjr \S\ R4Sj5r!\S\R.4Sj5r"SS\\SS4Sjjr#Sr$g) CmdStanVBzb Container for outputs from CmdStan variational run. Created by :meth:`CmdStanModel.variational`. runsetreturnNcUR[R:Xd$[SR UR55eXlUR URS5 g)zInitialize object.zEWrong runset method, expecting variational inference, found method {}rN)methodr VARIATIONAL ValueErrorformatr_set_variational_attrs csv_files)selfrs gC:\Users\julio\OneDrive\Documentos\Trabajo\Ideas Frescas\venv\Lib\site-packages\cmdstanpy/stanfit/vb.py__init__CmdStanVB.__init__sT}} 2 22""(&"7   ##F$4$4Q$78c\SRURRURRRR S/S95nSRUSR URR5SR URR55nU$)NzCmdStanVB: model={}{}r)cmdz#{} csv_file: {} output_file: {}z ) rrmodel_args method_argscomposejoinr stdout_files)rreprs r__repr__CmdStanVB.__repr__!s&-- KK  t{{00<<DDQBDO ;AA  KK -- . KK 00 1   rattrcURS5(a[SU35eURU5$![an[UR6eSnAff=f)z)Synonymous with ``fit.stan_variable(attr)_zUnknown variable name N) startswithAttributeError stan_variablerargs)rr*es r __getattr__CmdStanVB.__getattr__-sY ??3   #9$!@A A *%%d+ + * !&&) ) *s7 AAA sample_csv_0c[U5n[U5UlUSUlUSUlUSUlUSUlg)N column_namesetavariational_meanvariational_sample)r r _metadata _column_names_eta_variational_mean_variational_sample)rr4metas rr CmdStanVB._set_variational_attrs7sL#L1*40.2>.B; -12D-E/34H/I rc,[UR5$)z Total number of information items returned by sampler. Includes approximation information and names of model parameters and computed quantities. )lenr;rs rcolumnsCmdStanVB.columns@s4%%&&r.cUR$)z Names of information items returned by sampler for each draw. Includes approximation information and names of model parameters and computed quantities. )r;rCs rr6CmdStanVB.column_namesIs!!!rcUR$)z# Step size scaling parameter 'eta' )r<rCs rr7 CmdStanVB.etaRs yyrcUR$)z2 Returns inferred parameter means as numpy array. )r=rCs rvariational_params_npCmdStanVB.variational_params_npYs %%%rcV[R"UR/URS9$)z7 Returns inferred parameter means as pandas DataFrame. rD)pd DataFramer=r6rCs rvariational_params_pdCmdStanVB.variational_params_pd`s$ ||T334d>O>OPPrcT[[URUR55$)z)Returns inferred parameter means as Dict.)rzipr6r=rCs rvariational_params_dict!CmdStanVB.variational_params_dictgs"3t00$2H2HIJJrcUR$)z Returns object which contains CmdStan configuration as well as information about the names and structure of the inference method and model output variables. )r:rCs rmetadataCmdStanVB.metadatals~~rmeanvarr[cUc[5RS5 SnU(a URnO URnURR UR U5nURS:XdURS:Xa0U(a[5RS5 UR5$U$![aD [SUS3SRURR R55-5ef=f) a Return a numpy.ndarray which contains the estimates for the for the named Stan program variable where the dimensions of the numpy.ndarray match the shape of the Stan program variable, with a leading axis added for the number of draws from the variational approximation. * If the variable is a scalar variable, the return array has shape ( draws, ). * If the variable is a vector, the return array has shape ( draws, len(vector)) * If the variable is a matrix, the return array has shape ( draws, size(dim 1), size(dim 2) ) * If the variable is an array with N dimensions, the return array has shape ( draws, size(dim 1), ..., size(dim N)) This functionaltiy is also available via a shortcut using ``.`` - writing ``fit.a`` is a synonym for ``fit.stan_variable("a")`` :param var: variable name :param mean: if True, return the variational mean. Otherwise, return the variational sample. The default behavior will change in a future release to return the variational sample. See Also -------- CmdStanVB.stan_variables CmdStanMCMC.stan_variable CmdStanMLE.stan_variable CmdStanPathfinder.stan_variable CmdStanGQ.stan_variable CmdStanLaplace.stan_variable zThe default behavior of CmdStanVB.stan_variable() will change in a future release to return the variational sample, rather than the mean. To maintain the current behavior, pass the argument mean=TrueT)r zThe default behavior of CmdStanVB.stan_variable(mean=True) will change in a future release to always return a numpy.ndarray, even for scalar variables.zUnknown variable name: z Available variables are z, ) r warningr=r>r: stan_varsextract_reshapeshapeitemKeyErrorrr%keys)rr\r[drawsouts rr/CmdStanVB.stan_variableusL < L  D **E,,E "nn66s;KKCyyB#))t"3L((0 xxz!J )#/++))DNN4499;<=  sA7B:8B::ADcf0nURRHnURX1S9X#'M U$)a5 Return a dictionary mapping Stan program variables names to the corresponding numpy.ndarray containing the inferred values. See Also -------- CmdStanVB.stan_variable CmdStanMCMC.stan_variables CmdStanMLE.stan_variables CmdStanGQ.stan_variables CmdStanPathfinder.stan_variables CmdStanLaplace.stan_variables rZ)r:r`r/)rr[resultnames rstan_variablesCmdStanVB.stan_variabless7 NN,,D--d->FL- rcUR$)z6Returns the set of approximate posterior output draws.)r>rCs rr9CmdStanVB.variational_samples'''rcT[R"URURS9$)zN Returns the set of approximate posterior output draws as a pandas DataFrame. rN)rOrPr>r6rCs rvariational_sample_pdCmdStanVB.variational_sample_pds! ||D44d>O>OPPrdirc:URRU5 g)a/ Move output CSV files to specified directory. If files were written to the temporary session directory, clean filename. E.g., save 'bernoulli-201912081451-1-5nm6as7u.csv' as 'bernoulli-201912081451-1.csv'. :param dir: directory path See Also -------- stanfit.RunSet.save_csvfiles cmdstanpy.from_csv N)r save_csvfiles)rrss rruCmdStanVB.save_csvfiless !!#&r)r;r<r:r=r>r)N)%__name__ __module__ __qualname____firstlineno____doc__r rstrr(rnpndarrayfloatr2rpropertyintrDrr6r7rKrOrPrQrrUr rXrboolr/rlr9rqru__static_attributes__r^rrrrs  9v9$9 # **bjj%.?(@*J3J4J'''"eCHo""U &rzz&& Qr||QQ Kc2::o)>KK+37II!)$I rzz5 !IX)-~ c5U*++ ,*(BJJ((Qr||QQ'#'$''rr)r{ collectionsrtypingrrrrnumpyr}pandasrOcmdstanpy.cmdstan_argsrcmdstanpy.utilsr cmdstanpy.utils.loggingr rXr rr rr^rrrs2I#//)0.'_'_'r