>h\SrSSKJr SSKrSSKrSSKrSSKrSSKJr SSK r SSK J r SSK JrJrJrJr SS/rS q"S S 5r\"5rS S S.rSSSS.rSrS*SjrS+SjrSrS,SjrSrSrSrSrSr Sr!Sr""SS 5r#"S!S"\#5r$S#r%\"S$S%5S-S&j5r&\"S$S%5S.S'j5r'"S(S)5r(g)/z Run x12/x13-arima specs in a subprocess from Python and curry results back into python. Notes ----- Many of the functions are called x12. However, they are also intended to work for x13. If this is not the case, it's a bug. )deprecate_kwargN)warn)Bunch)X13NotFoundError IOWarningX13Error X13Warningx13_arima_select_orderx13_arima_analysis)z x13as.exex13aszx12a.exex12a x13as_ascii x13as_htmlc\rSrSrSrSrg)_freq_to_periodcURS5(agURS5(agURS5(agg)NM QW4) startswith)selfkeys fC:\Users\julio\OneDrive\Documentos\Trabajo\Ideas Frescas\venv\Lib\site-packages\statsmodels/tsa/x13.py __getitem___freq_to_period.__getitem__ s= >>#   ^^C  ^^C !N)__name__ __module__ __qualname____firstlineno__r__static_attributes__r!r rrrsr rrr)rrlognoneauto)TFNcU(aS$S$)Nyesnor!xs rr/-sQE0D0r cUb]UR[5(aC[RR U5(d[RR U5nU(dE[SSS2qUc[R "SS5nU(d[R "SS5nO8Uc5[R "SS5nU(d[R "SS5n[HWn[RRX5n[R"U[R[RS9 Us $ g![a Mif=f)a If x12path is not given, then either x13as[.exe] or x12a[.exe] must be found on the PATH. Otherwise, the environmental variable X12PATH or X13PATH must be defined. If prefer_x13 is True, only X13PATH is searched for. If it is false, only X12PATH is searched for. NX12PATHX13PATHstdoutstderrF) endswith _binary_namesospathisdirdirnamegetenvjoin subprocess check_callPIPEOSError)x12path prefer_x13binaryx12s r _find_x12rH0sw// >>ww}}W%%ggoog.G %dd+ ?ii 2.Gii 2.G ))Ir*ii 2.Gggll7+   ! !#joo)3 :J      s3E EEc@[U5nU(d [S5eU$)Nzxx12a and x13as not found on path. Give the path, put them on PATH, or set the X12PATH or X13PATH environmental variable.)rHr)rDs r _check_x12rJUs+ G  LM M Nr c[R"SU5nSn[U5S:a[X5upX4$U"US5nSnX4$)z Takes something like (1 1 0)(0 1 1) and returns a arma order, sarma order tuple. Also accepts (1 1 0) and return arma order and (0, 0, 0) z \([0-9 ]*?\)c ~[[[[R"SSU5R S555$)Nz[()]r3 )tuplemapintresubsplitr-s rclean_clean_order..cleanes,SbffVR399#>?@@r r)rrr)rQfindalllenrO)orderrTsorders r _clean_orderr[^sY JJ .EA 5zA~E)  =eAh =r cU(aU(a [S5eU(aUSU-/nOU(aUSU-/nOX/nU(aXR/- n[R"U[R[RS9$)Nz&Cannot specify both meta and datameta.z-m z-d r5) ValueErrorr@PopenrBSTDOUT)rDspecpathoutnamemetadatametaargss rrun_specreqsp ABB )* )*"    D#-#4#4 66r cSnUSUSSUSS3- nUbUSUSSUSS3- nU$USUSSUSS3- nU$) N z maxorder = (rrMrV) z maxdiff = (zdiff = (r!)maxordermaxdiffdiffoptionss r_make_automdl_optionsrms~G hqk]!HQK=<I !1$!78I  9s A"BBBc U(dUcgSnU(aUS- nUbk[U5nUSUS3- nUSRSR[[UR R 5R5555- nUS- nU$) Nr3z regression{ z variables = (td) z user = (rhz data = ({}) rg} )ryformatr?rOstrvaluesraveltolist)tradingrwreg_specrxs r_make_regression_optionsrs t|H,, #D) l9+S11'.. IIC**,3356     H Or c$UcgSnUSUS3- nU$)Nr3z forecast{ z maxlead = (z) } r!)forecast_periods forecast_specs r_make_forecast_optionsrs+!M{#3"4G<A &' ' iilO ==3sAHHOO,=#>? @D 6 1J |#**:*:h 1#**<*>/E0/E0forecast_yearsrc < [U5n[U[R[R45(dCU bU c [ S5e[R"U[R "U [U5U S9S9n[U5nUR5nUS[US3- nU(aUS- n[XU5nUSUS3- nU[Xt5- nU[U5- nUS - nU (aU$[R"S S US 9n[R"S US 9nUR!UR#S55 UR%5 UR%5 ['UUR(SSUR(5nUR+5 UR,R/5nU (a#[1UR,R/55 [3UR(S-5n[5U5 [3UR(S-5n[3UR(S-5n[3UR(S-5nR(S-5n[6R8"UR(5 [6R8"UR(5 [EUURFS5n[EUURFS5nUURFS5nU (d[IUUUUUUS9nU$[IUUUUUUUS9nU$![:a [6R<R?UR(5(a[ASUR(3[B5 [6R<R?UR(5(a[ASUR(3[B5 GNf=f![6R8"UR(5 [6R8"UR(5 f![:a [6R<R?UR(5(a[ASUR(3[B5 [6R<R?UR(5(a[ASUR(3[B5 fff=f=f)a Perform x13-arima analysis for monthly or quarterly data. Parameters ---------- endog : array_like, pandas.Series The series to model. It is best to use a pandas object with a DatetimeIndex or PeriodIndex. However, you can pass an array-like object. If your object does not have a dates index then ``start`` and ``freq`` are not optional. maxorder : tuple The maximum order of the regular and seasonal ARMA polynomials to examine during the model identification. The order for the regular polynomial must be greater than zero and no larger than 4. The order for the seasonal polynomial may be 1 or 2. maxdiff : tuple The maximum orders for regular and seasonal differencing in the automatic differencing procedure. Acceptable inputs for regular differencing are 1 and 2. The maximum order for seasonal differencing is 1. If ``diff`` is specified then ``maxdiff`` should be None. Otherwise, ``diff`` will be ignored. See also ``diff``. diff : tuple Fixes the orders of differencing for the regular and seasonal differencing. Regular differencing may be 0, 1, or 2. Seasonal differencing may be 0 or 1. ``maxdiff`` must be None, otherwise ``diff`` is ignored. exog : array_like Exogenous variables. log : bool or None If None, it is automatically determined whether to log the series or not. If False, logs are not taken. If True, logs are taken. outlier : bool Whether or not outliers are tested for and corrected, if detected. trading : bool Whether or not trading day effects are tested for. forecast_periods : int Number of forecasts produced. The default is None. retspec : bool Whether to return the created specification file. Can be useful for debugging. speconly : bool Whether to create the specification file and then return it without performing the analysis. Can be useful for debugging. start : str, datetime Must be given if ``endog`` does not have date information in its index. Anything accepted by pandas.DatetimeIndex for the start value. freq : str Must be givein if ``endog`` does not have date information in its index. Anything accepted by pandas.DatetimeIndex for the freq value. print_stdout : bool The stdout from X12/X13 is suppressed. To print it out, set this to True. Default is False. x12path : str or None The path to x12 or x13 binary. If None, the program will attempt to find x13as or x12a on the PATH or by looking at X13PATH or X12PATH depending on the value of prefer_x13. prefer_x13 : bool If True, will look for x13as first and will fallback to the X13PATH environmental variable. If False, will look for x12a first and will fallback to the X12PATH environmental variable. If x12path points to the path for the X12/X13 binary, it does nothing. tempdir : str The path to where temporary files are created by the function. If None, files are created in the default temporary file location. Returns ------- Bunch A bunch object containing the listed attributes. - results : str The full output from the X12/X13 run. - seasadj : pandas.Series The final seasonally adjusted ``endog``. - trend : pandas.Series The trend-cycle component of ``endog``. - irregular : pandas.Series The final irregular component of ``endog``. - stdout : str The captured stdout produced by x12/x13. - spec : str, optional Returned if ``retspec`` is True. The only thing returned if ``speconly`` is True. Notes ----- This works by creating a specification file, writing it to a temporary directory, invoking X12/X13 in a subprocess, and reading the output directory, invoking exog12/X13 in a subprocess, and reading the output back in. Nz=start and freq cannot be none if endog is not a pandas object)rperiodsfreq)rztransform{function=r{z outlier{} zautomdl{zx11{ save=(d11 d12 d13) }Fz.spc)deletesuffixdir)rrutf8z.errz.outz.d11z.d12z.d13zFailed to delete resource seasadjtrend irregular)observedresultsrrrr6)rrrrrr6r)%rJ isinstancepd DataFrameSeriesr] DatetimeIndexrXrr _log_to_x12rmrrtempfileNamedTemporaryFilewriteencodeclosererowaitr6rprintrrr:removerCr;existsrrrrX13ArimaAnalysisResult)endogrirjrkrwr'outlierrrretspecspeconlyrr print_stdoutrDrEtempdirspec_objrrlftempinftempoutpr6rrrrrress rr r HsD!G ebllBII6 7 7 =DL/0 0 %r'7'7e@CE =A(CD%U+H    !D";s#3"4D 99D #Htoo 'E KKME yy*GOO<< :w / /   'ME6 eF @C Jr c \rSrSrSrSrSrg)ricc NUR5Hup#[XU5 M gN)rsetattr)rrrrs rrX13ArimaAnalysisResult.__init__ds ,,.JC Du %)r cSSKJn U"5nURSSSS9up4URR USSS9 USR S 5 UR R USSS9 USR S 5 URR US SS9 US R S 5 URR US SS9 US R S5 UR5 U$)Nr) _import_mplrrVT)sharexF)axlegendObservedzSeas. AdjustedrTrend Irregular) statsmodels.graphics.utilsr subplotsrplot set_ylabelrrr tight_layout)rr pltfigaxess rr*X13ArimaAnalysisResult.ploths:mLLAdL3  d1ge4 Q:& T!WU3 Q+, 4751 Q7# tAwu5 Q;'  r r!N)r"r#r$r%rr*r&r!r rrrcs &r r)NTr)NFF)rrVr1NNNTFNFFNNFNTN)r1r1NNNTFNNNFNTN))rstatsmodels.compat.pandasrr:r@rrQwarningsrrrstatsmodels.tools.toolsrstatsmodels.tools.sm_exceptionsrrrr __all__r9r_period_to_freqrrrHrJr[rermryrrrrrrrrr r rr!r rr8s26  )99 $%9 :. "#s#68 0"J&6$$(! @*//d(V!#56DHBG6;8