Dj|ndZddlZddlZddlmZddlmZhdZdZ dZ dZ d Z d Z d Zd Zd ZdZy)z Arg validation for auto-arima calls. This allows us to test validation more directly without having to fit numerous combinations of models. N)metrics)ModelFitWarning>aicbicoobaicchqicc|dk(r|S|S)zCA more concise way to handle the default behavior of with_interceptauto)with_interceptdefaults ^C:\Crop_Prediction\Backend\crop-ai-system\venv\Lib\site-packages\pmdarima/arima/_validation.pyauto_interceptrs c|tvrtd|dt|dk(r|dk(rd}tjd|S)z0Check whether the information criterion is validz0auto_arima not defined for information_criteria=z&. Valid information criteria include: rrrzoinformation_criterion cannot be 'oob' with out_of_sample_size = 0. Falling back to information criterion = aic.)VALID_CRITERIA ValueErrorwarningswarn)information_criterionout_of_sample_sizes rcheck_information_criterionrsWN21>CD D %*<*A % E F ! rc|r|SiS)zReturn kwargs or an empty dict. We often pass named kwargs (like `sarimax_kwargs`) as None by default. This is to avoid a mutable default, which can bite you in unexpected ways. This will return a kwarg-compatible value. r )kwargss r check_kwargsr*s Ircv|dkr|s|dkr td|s|dkDrtjd|zd}|S)z+Check the value of M (seasonal periodicity)rz"m must be a positive integer (> 0)z-m (%i) set for non-seasonal fit. Setting to 0)rrr)mseasonals rcheck_mr!6sC A(q1u=>>  q5 MMIAM N  HrcH|r|dk7rd}tjd|z|S)zPotentially update the n_jobs parameter We can't run in parallel with the stepwise algorithm. This checks ``n_jobs`` w.r.t. stepwise and will warn. rz`stepwise model cannot be fit in parallel (n_jobs=%i). Falling back to stepwise parameter search.)rr)stepwisen_jobss r check_n_jobsr%Ds3 FaK CEKL M Mrc|tj}|td|z|dkrtd|z||krtd|d|||fS)z2Ensure starting points and ending points are validzstart_%s cannot be Nonerzstart_%s must be positivemax_z must be >= start_)npinfr)stmxargnames rcheck_start_max_valuesr-Qs^ z VV z2W<== Av4w>?? Bw'JKK r6MrcR|yt|ttfr t|S|ryy)zCheck the value of tracerr) isinstanceintbool)traces r check_tracer3^s+ }%#t%5z  rct|tr;|dk(rtjS|dk(rtjS t t|St|stdt|z|S#t $rtd|zwxYw)a;Get a scoring metric by name, or passthrough a callable Parameters ---------- metric : str or callable A name of a scoring metric, or a custom callable function. If it is a callable, it must adhere to the signature:: def func(y_true, y_pred) Note that the ARIMA model selection seeks to MINIMIZE the score, and it is up to the user to ensure that scoring methods that return maximizing criteria (i.e., ``r2_score``) are wrapped in a function that will return the negative value of the score. msemaez#'%s' is not a valid scoring method.zG`metric` must be a valid scoring method, or a callable, but got type=%s) r/strrmean_squared_errormean_absolute_errorgetattrAttributeErrorrcallable TypeErrortype)metrics rget_scoring_metricr@js &# U?-- - U?.. . M7F+ + F 46:6lCD D M MBVKL L Ms A00Bc|dk\rtjdty||zdkDs|dkDrtjdtyy)zWarn for large values of DzqHaving more than one seasonal differences is not recommended. Please consider using only one seasonal difference.zvHaving 3 or more differencing operations is not recommended. Please consider reducing the total number of differences.N)rrr)dDs r warn_for_DrEsJAv -.= ? Qa!e /0? Ar)__doc__numpyr(rsklearnrpmdarima.warningsrrrrrr!r%r-r3r@rEr rrrJsN -7!"       "J Ar