DjsZddlmZddlmZddlZddlmZddlZddlZddl Z ddl Z ddl mZddlmZmZGdd Zd Zd d d dddddZdZ ddZddZddZdZ ddZd dZ d!dZd"dZy)#) FUTURE_STACK)lzipN)reduce) SimpleTable) fmt_latexfmt_txtcteZdZdZdZdZdZdZ ddZddZ ddZ d Z dd Z dd Z d ZdZddZy )SummarycJg|_g|_g|_d|_d|_y)NF)tablessettings extra_txttitle _merge_latexselfs ^C:\Crop_Prediction\Backend\crop-ai-system\venv\Lib\site-packages\statsmodels/iolib/summary2.py__init__zSummary.__init__s&   !c"|jSN)as_textrs r__str__zSummary.__str__s||~rcXtt|dz|jzdzS)Nz """ z """)strtyperrs r__repr__zSummary.__repr__s%4:*T\\^;gEErc"|jS)z$Display as HTML in IPython notebook.)as_htmlrs r _repr_html_zSummary._repr_html_s||~rc"|jS)z9Display as LaTeX when converting IPython notebook to PDF.)as_latexrs r _repr_latex_zSummary._repr_latex_"s}}rc~||||d}|jj||jj|y)a Add the contents of a DataFrame to summary table Parameters ---------- df : DataFrame header : bool Reproduce the DataFrame column labels in summary table index : bool Reproduce the DataFrame row labels in summary table float_format : str Formatting to float data columns align : str Data alignment (l/c/r) indexheader float_formatalignN)r appendr)rdfr'r(r)r*rs radd_dfzSummary.add_df&s:$#f$05B 2 X&rcZtj|}|j|dd||y)aAdd the contents of a Numpy array to summary table Parameters ---------- array : numpy array (2D) float_format : str Formatting to array if type is float align : str Data alignment (l/c/r) Fr&N)pd DataFramer-)rarrayr*r)tables r add_arrayzSummary.add_array=s. U# Eu!-U  z"Summary.add_dict..fs299aV#4rr*N) keys _formattervaluesr7r1rshapevstacksplitrr3) rdncolsr*r)r:r>valsdatapads radd_dictzSummary.add_dictMs 67VVX> 1l+>>56XXZ@ 1l+@@xxT4() ::a=5 A %4::a=501C99dBHHSRH:-=$>?@Dxxe$4d; t5)?@s C?Dc:|jj|y)zAppend a note to the bottom of the summary table. In ASCII tables, the note will be wrapped to table width. Notes are not indented. N)rr+)rstrings radd_textzSummary.add_textis f%rNct|tr||_y|<|jjj }|t vr t |}d|z|_yd|_y)aInsert a title on top of the summary table. If a string is provided in the title argument, that string is printed. If no title string is provided but a results instance is provided, statsmodels attempts to construct a useful title automatically. Nz Results: r5) isinstancerrmodel __class____name__ _model_types)rrresultsrOs r add_titlezSummary.add_titleosU eS !DJ" //88L((/E(50  rct|||j}t|}|||_|||d<|j |d|j |||j ||y)aLTry to construct a basic summary instance. Parameters ---------- results : Model results instance alpha : float significance level for the confidence intervals (optional) float_format: str Float formatting for summary of parameters (optional) title : str Title of the summary table (optional) xname : list[str] of length equal to the number of parameters Names of the independent variables (optional) yname : str Name of the dependent variable (optional) )alphause_tNDependent Variable:lr=)r))rrS)summary_paramsrW summary_modelr'rIr-rT) rrSrVr)rxnameynameparaminfos radd_basezSummary.add_basesn&we7==IW%  EK  */D& ' d# & E 5 UG4rc|j}|j}|j}|j}t ||\}}}|dz}t ||||} | D cgc]} | j } } dj| } | jd} || d<| j|dj| } |4|}t||kr&dt|dz t|dz z z|z}nd}|D cgc]} tj| |} } | D cgc]} dj| } } dj| } dj|| | g} | Scc} wcc} wcc} w)z%Generate ASCII Summary Table = r r5)r rrr_measure_tables_simple_tablesrjoinrCr+leninttextwrapwrap)rr rrrpad_col pad_indexwidest rule_equal simple_tablesr:tabtxtouts rrzSummary.as_textsW== NN %4VX%F"Fc\ &vx)L $12qqyy{22iiniioA :iin  E5zF"c&1*s5zA~"=>>FE1:;Ax}}Q';;%()tyy|))iiniiS)* +3<)sE6EE$cX|j}|j}t||}|Dcgc]}|j}}dj |}|j Dcgc]}|j dd}}dj |}dj ||g} | Scc}wcc}w)z$Generate HTML Summary Table rcz
)r rrgr rhrreplace) rr rrqr:rrsttemp_txtrsrts rr zSummary.as_htmls==&vx8 $12qqyy{22iin9=H2BJJtY/HHnnX&nnc3Z( 3Is B"!B'c|j}|j}|j}| d|zdz}nd}d|zdz}t||}|Dcgc]}|j }}dj |}d}|j rtj|d|}d|||d f} d j | } d j |j} | d z| z} | Scc}w) zGenerate LaTeX Summary Table Parameters ---------- label : str Label of the summary table that can be referenced in a latex document (optional) z \caption{}z \caption{}z\label{z z8\\hline\n\\hline\n\\end{tabular}\n\\begin{tabular}{.*}\nz \\midrule\nz \begin{table}z \end{table}rcz \newline z \bigskip ) r rrrgas_latex_tabularrhrresubr) rlabelr rrrqr:rr to_replace non_captionedrsrts rr#zSummary.as_latexs==    5(3.E!EU"S(&vx8 -:;q!!#;;kk#A    &&^S9C(%^K  -0 ""4>>2o-3 !.time_now%s&##%||,--rcB|jjjSr)rOrPrQr:s rr<zsummary_model..*sqww0099rzModel:cB|jjjSr)family__classrQrs rr<zsummary_model..+sahh&6&6&?&?rz Model Family:cV|jjjjSr)rlinkrPrQrs rr<zsummary_model..,sqxx}}'>'>'G'GrzLink Function:c.|jjSr)rO endog_namesrs rr<zsummary_model..-sAGG,?,?rrXzDate:c d|jzSNz%#6d)nobsrs rr<zsummary_model../s&166/rzNo. Observations:c d|jzSr)df_modelrs rr<zsummary_model..0s&1::"5rz Df Model:c d|jzSr)df_residrs rr<zsummary_model..1sfqzz&9rz Df Residuals:c |jdS)N converged mle_retvalsrs rr<zsummary_model..2s1==#=rz Converged:c |jdS)N iterationsrrs rr<zsummary_model..3s l(CrzNo. Iterations:c|jSr)methodrs rr<zsummary_model..4s rzMethod:c |jdS)Nnorm fit_optionsrs rr<zsummary_model..5sammF3rzNorm:c |jdS)N scale_estrrs rr<zsummary_model..6sAMM+$>rz Scale Est.:c |jdS)Ncovrrs rr<zsummary_model..7s1==#7rz Cov. Type:r5z (uncentered)c d|jzSNz%#8.3f)rsquaredrs rr<zsummary_model..:s1::8Mr R-squared:c d|jzSr) rsquared_adjrs rr<zsummary_model..;sX=VrzAdj. R-squaredc d|jzSr) prsquaredrs rr<zsummary_model..<s(Q[[*@rzPseudo R-squared:c d|jzSNz%8.4f)aicrs rr<zsummary_model..=Wquu_rzAIC:c d|jzSr)bicrs rr<zsummary_model..>rrzBIC:c d|jzSNz%#8.5g)llfrs rr<zsummary_model..?s155(8rzLog-Likelihood:c d|jzSr)llnullrs rr<zsummary_model..@sAHH!4rzLL-Null:c d|jzSr) llr_pvaluers rr<zsummary_model..AsX %<rz LLR p-value:c d|jzSr)deviancers rr<zsummary_model..Bs(QZZ"7rz Deviance:c d|jzSNz%#6.3g) pearson_chi2rs rr<zsummary_model..Csh&?rz Pearson chi2:c d|jzS)Nz%#8.4g)fvaluers rr<zsummary_model..DsX%8rz F-statistic:c d|jzSr)f_pvaluers rr<zsummary_model..EsHqzz,ArzProb (F-statistic):c d|jzSr)scalers rr<zsummary_model..Fsx!''1rzScale:) k_constantitemsAttributeErrorKeyErrorNotImplementedError)rSrr_ rsquared_typertkeyfuncs rr[r[ s . D9DN?DGD "?D DM 9D 5D9D=DCD (DO3DM>D7D!,,B/M.MD} $s *+3VD M )C /0 @D ,DL,DL8D 4D   s C++DDc t|tr |\}}}} } } nA|j}|j}|j} |j } |j |} tj||| | gj} tj| | g} tj| } |r/dddddt|dz ztd|dz z dzg| _n.ddd d dt|dz ztd|dz z dzg| _|s( |jj j"| _| S|| _| S#t&$r|jj(| _Y| SwxYw) axcreate a summary table of parameters from results instance Parameters ---------- res : results instance some required information is directly taken from the result instance yname : {str, None} optional name for the endogenous variable, default is "y" xname : {list[str], None} optional names for the exogenous variables, default is "var_xx" alpha : float significance level for the confidence intervals use_t : bool indicator whether the p-values are based on the Student-t distribution (if True) or on the normal distribution (if False) skip_header : bool If false (default), then the header row is added. If true, then no header row is added. float_format : str float formatting options (e.g. ".3g") Returns ------- params_table : SimpleTable instance zCoef.zStd.Err.tzP>|t|[rer]zzP>|z|)rNtupleparamsbsetvaluespvaluesconf_intr7r1Tr8r/r0rcolumnsrOrG param_namesr'r exog_names) rSr]r\rVrW skip_headerr)rrrrrrGs rrZrZRsd:'5!;B8gwkk////##E* 88VS'73 4 6 6D 99dH% &D << D S'c%!)n,c!eai-.@3.FH  S'c%!)n,c!eai-.@3.FH   2 ++77DJ K K  2 11DJ K  2s %D==$E%$E%ct|}|jddD]}||jfd||<d|jdddfzdz|jdddf<|r|jdddfdk}|j||jd fd z|j||jd f<|jdddfd k}|j||jd fd z|j||jd f<|jdddfd k}|j||jd fd z|j||jd f<|jddddf}|j dit }|rt|d tj}t|dtj}tj||d} | jjr-| jfd} tj|| gd }tj|}t!|j"j$g|_|S)z.s L1,<r(r)g?r*rg{Gz?rr)rr5)zR-squared Adj.r5c|zSrrrs rr<z_col_params..s L1$4r)axisr)rZrapplyiloclocstackrgetattrr7nanr/Seriesnotnullanyconcatr0rrOr) resultr)stars include_r2rescolidxrrr2s ` r _col_paramsrs  C{{2A>s8>>"<=C>388AqD>)C/CHHQTN hhq!tnr!'*wwsCKKN/B'Cc'IS[[^#$hhq!tns"'*wwsCKKN/B'Cc'IS[[^#$hhq!tns"'*wwsCKKN/B'Cc'IS[[^#$ ((1bqb5/C #)) #l #C6:rvv6v~rvv> YY80<>? ::<   45B))S"IA.C ,,s Cv||//01CK JrcP|i}g}g}|D]B}t||tr |j||||j|Dt j t |jj|i|}|S#t$r|jdYgwxYw)z!Stack model info in a column r5)r') rNdictr+rr/r0rrOr)r info_dictrtr'rs r _col_infors C E  ilD )   JJ|y|F+ ,  Q ,,FLL445s;5 IC J   JJrN sBB%$B%ctt|t|k(r|Sddlm}|t}g}|D])}||xxdz cc<|j |dz||z+|S)Nr) defaultdictIrd)riset collectionsrrr+) list_of_namesr name_counterr(_names r _make_uniquer"sq 3} #m"44's#L F9Us" eckL$7789 Mrc 6 t|ts|g}|Dcgc]}t||||} }|r t|} n&t| Dcgc]}|jdc}} t t | D]} | | g| | _d} t| dj} | ddD])}|jD]}|| vs| j|+dD]3}|| vs| j|| jt | |5t| | }|j| }|r|jjdj}tj |j#}|j$|dk(jj}|Dcgc] }||vs| }}|Dcgc] }||vs| }}||z}|jjdDcgc]}||vr| }}||z }|r|D]}|j||j|d}g}|jjd} t d| j&ddD]b} |j| | | dz| j&dkr | | | | dzk(r|jd L|j| | dzd||_|rH|Dcgc]<}t)||j+|j,j.j0|>} }n$|Dcgc]}t)|t3|d d} }t5| t| Dcgc]}|jdc}D] \}}|g|_t| | }tj6t9j:||g}|j|_tj<|jj|jjz|_|}|j?d }tA}d |_!|jE|d d |jGd|r|jGd|Scc}wcc}wcc}wcc}wcc}wcc}wcc}wcc}w)a@ Summarize multiple results instances side-by-side (coefs and SEs) Parameters ---------- results : statsmodels results instance or list of result instances float_format : str, optional float format for coefficients and standard errors Default : '%.4f' model_names : list[str], optional Must have same length as the number of results. If the names are not unique, a roman number will be appended to all model names stars : bool print significance stars info_dict : dict, default None dict of functions to be applied to results instances to retrieve model info. To use specific information for different models, add a (nested) info_dict with model name as the key. Example: `info_dict = {"N":lambda x:(x.nobs), "R2": ..., "OLS":{ "R2":...}}` would only show `R2` for OLS regression models, but additionally `N` for all other results. Default : None (use the info_dict specified in result.default_model_infos, if this property exists) regressor_order : list[str], optional list of names of the regressors in the desired order. All regressors not specified will be appended to the end of the list. drop_omitted : bool, optional Includes regressors that are not specified in regressor_order. If False, regressors not specified will be appended to end of the list. If True, only regressors in regressor_order will be included. include_r2 : bool, optional Includes R2 and adjusted R2 in the summary table. )rr)rrc,|j|dddS)NouterT)how right_index left_index)merger9s rmergzsummary_col..merg swwqg4DwIIrrNrre)levelr5default_model_infosTrY)r(r*zStandard errors in parentheses.z* p<.1, ** p<.05, ***p<.01)$rNlistrr"rrrir'r+removeinsertrreindexget_level_valuestolistr/r  value_countsrrArgetrOrPrQrzipr0r7rBIndexfillnar rr-rL)rSr) model_namesrrregressor_order drop_omittedrr:colscolnamesrr*r'rrspecialsummvarnamesvcordered unordered new_orderotheruorr,namer_datsmrys r summary_colrIsxJ gt $)9@ A34 \#- / AD A ,t ._s 1l ;rct|SrrQrs rr<z$_df_to_simpletable..asZ<%@rrdr)headersstubsltx_fmttxt_fmtlatex data_aligns header_alignrstable_dec_abovetable_dec_belowheader_dec_belowrcolsep)copymaprapplymaprr2rr'rjrrr7r1rr output_formats)r,r*r)r(r'rZr[r\rmrnrGr:rSrTrws ` r_df_to_simpletablerbZs '')CBgg;<#&;;#5#5#78a3q688 8; 8H8H8JK1Q#i.3..KK$'88AqD>3a&3y>C#773A RXXc]G5& 9B05Bg}-16Bg~..3Be]+2ABe./2ABe./3CBe/0),s7Q;/?)?BeX& I+ Bll@AB9L3s#F$G:!G 3!G$GGc  g}|r|ddnd}|dgt|z}|dgt|z}t|D]D\}}||d}||d} ||d} |jt|| || |||||F|S)Nrr)rr'r(r*)r*r)r(r'rmrn)ri enumerater+rb) r rrmrnrqr)rvr'r(r*s rrgrgxsM2:8A;~.L#F #C#f+% &!I1 G$!X& G$/=I7=U8? :CA, H I I r)NNrTFr)rTFr)rrFNrFT)r) rrTT-Nrfrrr)statsmodels.compat.pandasrstatsmodels.compat.pythonrr functoolsrr|rknumpyr7pandasr/r2rtableformattingrr r rfrRr[rZrrr"rIr?rbrgrrrrms2* /iiX+402?/,11  /dFJ399z$N* EJAFwtCGHLBC<r