]h:SSKJrJrJr SSKrSSKrSrSr Sr g))absolute_importdivisionprint_functionNc~[R"URUS:HURR5S$)a!Given the name of a regressor, return its (column) index in the `beta` matrix. Parameters ---------- m: Prophet model object, after fitting. name: Name of the regressor, as passed into the `add_regressor` function. Returns ------- The column index of the regressor in the `beta` matrix. r)npextracttrain_component_colsindex)mnames dC:\Users\julio\OneDrive\Documentos\Trabajo\Ideas Frescas\venv\Lib\site-packages\prophet/utilities.pyregressor_indexr s> :: t$)1+A+A+G+G   c*[UR5S:dS5e/nURR5Hup#URSSS2[ X54nUSS:XaX@R -US- nOXCS- nSUR - S - SSUR - S - - /n[R"XVS 9nUUSUS US[R"U5USS .nURU5 M [R"U5$) aSummarise the coefficients of the extra regressors used in the model. For additive regressors, the coefficient represents the incremental impact on `y` of a unit increase in the regressor. For multiplicative regressors, the incremental impact is equal to `trend(t)` multiplied by the coefficient. Coefficients are measured on the original scale of the training data. Parameters ---------- m: Prophet model object, after fitting. Returns ------- pd.DataFrame containing: - `regressor`: Name of the regressor - `regressor_mode`: Whether the regressor has an additive or multiplicative effect on `y`. - `center`: The mean of the regressor if it was standardized. Otherwise 0. - `coef_lower`: Lower bound for the coefficient, estimated from the MCMC samples. Only different to `coef` if `mcmc_samples > 0`. - `coef`: Expected value of the coefficient. - `coef_upper`: Upper bound for the coefficient, estimated from MCMC samples. Only different to `coef` if `mcmc_samples > 0`. rzNo extra regressors found.betaNmodeadditivestdr)qmu) regressorregressor_modecenter coef_lowercoef coef_upper) lenextra_regressorsitemsparamsry_scaleinterval_widthrquantilemeanappendpd DataFrame) r coefsrr"rr percentiles coef_boundsrecords rregressor_coefficientsr.s 4 q!! "Q &D(DD & E//557 xx?1#@ @A &>Z '))#fUm3D-'D !! !Q & Q%%%* * kk$6 "$VnTl%a.GGDM%a.    V'8* << rc^0nSHQnURS:XaURUSSX'M,[R"URU5X'MS SHMnURS:XaURUSX'M)[R"URUSS9X'MO U$)a Retrieve parameters from a trained model in the format used to initialize a new Stan model. Note that the new Stan model must have these same settings: n_changepoints, seasonality features, mcmc sampling for the retrieved parameters to be valid for the new model. Parameters ---------- m: A trained model of the Prophet class. Returns ------- A Dictionary containing retrieved parameters of m. )kr sigma_obsr)deltar)axis) mcmc_samplesr"rr&)r respnames rwarm_start_paramsr7Os C( >>Q %+A.CJ%1CJ ) # >>Q %+CJ%q9CJ # Jr) __future__rrrnumpyrpandasr(rr.r7rrr<s$A@ 1fr