Dj<PdZddlZddlZddlmZddlmZddl m Z GddZ y)z? SARIMAX parameters class. Author: Chad Fulton License: BSD-3 N) Polynomial) is_invertible)validate_basicceZdZdZdZedZejdZedZejdZedZ e jdZ ed Z e jd Z ed Z e jd Z ed Z e jdZ edZ e jdZ edZejdZedZejdZedZejdZedZedZedZejdZedZedZedZedZdZd Zd!Zy")# SARIMAXParamsac SARIMAX parameters. Parameters ---------- spec : SARIMAXSpecification Specification of the SARIMAX model. Attributes ---------- spec : SARIMAXSpecification Specification of the SARIMAX model. exog_names : list of str Names associated with exogenous parameters. ar_names : list of str Names associated with (non-seasonal) autoregressive parameters. ma_names : list of str Names associated with (non-seasonal) moving average parameters. seasonal_ar_names : list of str Names associated with seasonal autoregressive parameters. seasonal_ma_names : list of str Names associated with seasonal moving average parameters. param_names :list of str Names of all model parameters. k_exog_params : int Number of parameters associated with exogenous variables. k_ar_params : int Number of parameters associated with (non-seasonal) autoregressive lags. k_ma_params : int Number of parameters associated with (non-seasonal) moving average lags. k_seasonal_ar_params : int Number of parameters associated with seasonal autoregressive lags. k_seasonal_ma_params : int Number of parameters associated with seasonal moving average lags. k_params : int Total number of model parameters. cD||_|j|_|j|_|j|_|j|_|j |_|j |_|j|_|j|_|j|_ |j|_ |j|_ |j|_ |jtj|jtj zd|_d|_y)NT) allow_infnan)spec exog_namesar_namesma_namesseasonal_ar_namesseasonal_ma_names param_names k_exog_params k_ar_params k_ma_paramsk_seasonal_ar_paramsk_seasonal_ma_paramsk_params split_paramsnpzerosnan _params_split_params)selfr s `C:\Crop_Prediction\Backend\crop-ai-system\venv\Lib\site-packages\statsmodels\tsa\arima\params.py__init__zSARIMAXParams.__init__8s //    !%!7!7!%!7!7++!//++++$($=$=!$($=$=!  ".. HHT]] #bff ,4/A c |jdS)z7(array) Parameters associated with exogenous variables. exog_paramsrrs rr"zSARIMAXParams.exog_paramsOs!!-00r ctj|r|g|jz}t||jd|jd<d|_y)Nzexogenous coefficientstitler")risscalarrrrrrvalues rr"zSARIMAXParams.exog_paramsTsK ;;u Gd000E,: 4%%-E-G=) r c |jdS)z1(array) Autoregressive (non-seasonal) parameters. ar_paramsr#r$s rr,zSARIMAXParams.ar_params\!!+..r ctj|r|g|jz}t||jd|jd<d|_y)NAR coefficientsr&r,)rr(rrrrr)s rr,zSARIMAXParams.ar_paramsaJ ;;u Gd...E*8 4##+<+>;' r ctj|jjdz}d|d<|jj}|j d ||<t |S)z:(Polynomial) Autoregressive (non-seasonal) lag polynomial.rr,)rrr max_ar_orderar_lagsrrrcoefixs rar_polyzSARIMAXParams.ar_polyis[xx ..23Q YY  &&{33R$r ct|tr |j}t||jj dzd}|ddk7r t dg}td|jj dzD]C}||jjvr|j|| 1||dk7s:t d||_ y)Nr2z AR polynomialr&rz*AR polynomial constant must be equal to 1.WAR polynomial includes non-zero values for lags that are excluded in the specification.) isinstancerr6rr r3 ValueErrorranger4appendr,)rr*r,is rr8zSARIMAXParams.ar_polyrs eZ (JJEudii&<&rA)rr*rAr?s rrGzSARIMAXParams.ma_polys eZ (JJEudii&<&rK)rr*rarKr?s rrczSARIMAXParams.seasonal_ar_polys II & & eZ (JJEua!dii.M.M*M&M%=? 8q=FG Gq$))99A=> 4ADII..."))5Q<-8q1u" "344  4#5r c |jdS)z+(array) Seasonal moving average parameters.seasonal_ma_paramsr#r$s rrgz SARIMAXParams.seasonal_ma_paramsrLr ctj|r|g|jz}t||jd|jd<d|_y)Nseasonal MA coefficientsr&rg)rr(rrrrr)s rrgz SARIMAXParams.seasonal_ma_paramsrOr c|jj}tjdg}|dkDrtj|jj }tj|jj tdz }|jd||<tjdtjtj|dd|dz dfgdjf}t|S)z4(Polynomial) Seasonal moving average lag polynomial.r2rrQrgrSrUrV)r rWrrYrmax_seasonal_ma_orderseasonal_ma_lagsr[rr\r]r^r_rr`s rseasonal_ma_polyzSARIMAXParams.seasonal_ma_polys II & &xx} q5xx ? ?@H$))44C@1DB--.BCHRL55BFF2::h#@$*QUAJ#7EELWYOPD$r c|jj}t|tr |j}t |d||jj zzd}|ddk7r tdg}td|jj dzD]H}||jjvr|j|||z3|||zdk7s?td||_ y)Nr2zseasonal MA polynomialr&rrerI) r rWr;rr6rrkr<r=rlr>rg)rr*rargr?s rrmzSARIMAXParams.seasonal_ma_polys II & & eZ (JJEua!dii.M.M*M&M%=@ 8q=FG Gq$))99A=> 4ADII..."))%A,7q1u" "344  4#5r c |jdS)z(float) Innovation variance.sigma2r#r$s rrpzSARIMAXParams.sigma2s!!(++r ct|jj }t||dj |j d<d|_y)Nrpr&)r[r concentrate_scaleritemrr)rparamslengths rrpzSARIMAXParams.sigma2sF4445'5 F((,,0DF 8$ r c4|j|jzS)z8(Polynomial) Reduced form autoregressive lag polynomial.)r8rcr$s rreduced_ar_polyzSARIMAXParams.reduced_ar_poly||d3333r c4|j|jzS)z8(Polynomial) Reduced form moving average lag polynomial.)rGrmr$s rreduced_ma_polyzSARIMAXParams.reduced_ma_polyrxr c|j+|jjdi|j|_|jj S)z"(array) Complete parameter vector.)rr join_paramsrcopyr$s rrtzSARIMAXParams.params$sB << 049900F43E3EFDL||  ""r cR|jj||_d|_y)N)r rrrr)s rrtzSARIMAXParams.params+s !YY33E: r chtjtj|j S)zA(bool) Are current parameter values all filled in (i.e. not NaN).)ranyisnanrtr$s r is_completezSARIMAXParams.is_complete0s#66"((4;;/000r czd} |jj|j|S#t$rd}Y|SwxYw)z>(bool) Are current parameter values valid (e.g. variance > 0).TF)r validate_paramsrtr<)rvalids ris_validzSARIMAXParams.is_valid5sF  II % %dkk 2  E  s %+ ::cVt|j|jdt|j|jdd}d}|jdkDrt |j j}|jdkDrt |jj}|xr|S)z?(bool) Is the reduced autoregressive lag poylnomial stationary.r/r&rNTr) rr,rrKrrr8r6rc)r ar_stationaryseasonal_ar_stationarys r is_stationaryzSARIMAXParams.is_stationary?s t~~t'7'7. 0t..0I0I7 9 !%   a )$,,*;*;strr"rr,rrArrKrrgr rrrpjoin)r componentss r__repr__zSARIMAXParams.__repr__{s       i#d.>.>*?? @      gDNN(;; <      gDNN(;; <  $ $   .!$"9"9:; <  $ $   .!$"9"9:; <yy**   kDKK7 8"TYYz%:::r N)__name__ __module__ __qualname____doc__rpropertyr"setterr,r8rArGrKrcrgrmrprwrzrtrrrrrrrr|r rrrs&P.11//   ^^##$//   ^^##$88    55(88    55(,, ]] 4444##  ]]1188 88" ) >;r r) rnumpyrpandasrnumpy.polynomialr statsmodels.tsa.statespace.toolsrstatsmodels.tsa.arima.toolsrrr|r rrs' ':6};};r