!g* dZddlZddlZddlmZddlmZejde fde fde fde fd e fd e fd e fd e fgZ ejd Z ee jej e Zedej%dj'ede fde fde fde fd e fd e fd e fd e ffDcic]\}}|d||dfc}}Zdj-Ze ddeDcgc] }e|d c}fZej ej%dZedej'eeddfZeeDcic]\}}|edd|f|e|dgc}}Zd7dZdZdZeedddfZdgZ e D]Z!eee!dee!d<dgZ"e"D]=Z!eejFee!ddee!ddfedjIe!<?ejFeedddfejJejddffZ&edddfZ'ee'e&jPZ)ee)jTee)jVdZ,dZ-dZ.ee,e.e)zee-e.e)zedejFeejJejddffZ/ee'e/jPZ0ee0jTee0jVee-e.e0zedejFedddfejJejddffZ1ee'e1jPZ2ee2jTee2jVee-e.e2zdZ3dZ4ejjjmde4d f!jod"e fd#e fd$e fd%e fgZ8ejjjse4df!jod&e fd'e fgZ:ejvjxj{e8e:fd()Z>ej~e4dfe>Z@e8jjD] ZBe8eBe@eB< e:jjD] ZBe:eBe@eB<  e3d*e@\ZCZAe3d+e@\ZCZAejeADcgc]}eC| c}ZFeFj'dd,ejjjse4!zzZGeeGeFjPZHeeHjTee-e.eHzd-ZIejeId.eADcgc]}eC| c}ZFeFj'dd,ejjjse4!zzZGeeGeFjPZHeeHjTee-e.eHzejd e d/d(0Z ed1e jjDcgc]}e j"|j'!c}e j"joeJZKeKjd2eMe jjj%dZNe eNddfjZPeePjeePje3d3eP\ZQZRejeIdeRDcgc]}eQ| c}ZSePd ZTeeTeSjPZUeeUjTee-e.eUzee-e.e)zd4jIe jjdd2ZVe3d5eP\ZWZXejeIdeXDcgc]}eW| c}ZYePd ZZeeZeYjPZ[ee[jTee-e.e[zeXD]^Z\ed6e\ejeIe\eXDcgc]}eW| c}Z]ePd Z^ee^e]jPZ_ee-e.e_z`ycc}}wcc}wcc}}wcc}wcc}wcc}wcc}wcc}wcc}w)8z convenience functions for ANOVA type analysis with OLS Note: statistical results of ANOVA are not checked, OLS is checked but not whether the reported results are the ones used in ANOVA N)lmap)OLSbreedsexlitterpenpigagebageyz dftest3.datazrows with missing valuesz y sex ageznumber of complete observationsc|j}tj|}|r|dddf|k(jtS|dddf|k(jtddddfS)z|convert array of categories to dummy variables by default drops dummy variable for last category uses ravel, 1d onlyN)ravelnpuniqueastypeint)x returnallgroupss n/var/www/dash_apps/app1/venv/lib/python3.12/site-packages/statsmodels/sandbox/regression/ols_anova_original.py data2dummyr4sh  A YYq\F!T' f$,,S11!T' f$,,S1!CRC%88ctjtt|j }||dddddfk(j dj jtddddfS)zcreates product dummy variables from 2 columns of 2d array drops last dummy variable, but not from each category singular with simple dummy variable but not with constant quickly written, no safeguards Nr) rrrtupletolistallTrr)rrs rdata2proddummyr ?s^YYtE188:. /F vaQh  $ $R ( * * 1 1# 6q"u ==rcV|jdk(r |dddf}t|d}||zS)zcreate dummy continuous variable Parameters ---------- x1 : 1d array label or group array x2 : 1d array (float) continuous variable Notes ----- useful for group specific slope coefficients in regression r NT)r)ndimr)x1x2dummys rdata2groupcontr&Ns2 ww!| $Z rT *E 2:r)rr aW ANOVA statistics (model sum of squares excludes constant) Source DF Sum Squares Mean Square F Value Pr > F Model %(df_model)i %(ess)f %(mse_model)f %(fvalue)f %(f_pvalue)f Error %(df_resid)i %(ssr)f %(mse_resid)f CTotal %(nobs)i %(uncentered_tss)f %(mse_total)f R squared %(rsquared)f a] ANOVA statistics (model sum of squares includes constant) Source DF Sum Squares Mean Square F Value Pr > F Model %(df_model)i %(ssmwithmean)f %(mse_model)f %(fvalue)f %(f_pvalue)f Error %(df_resid)i %(ssr)f %(mse_resid)f CTotal %(nobs)i %(uncentered_tss)f %(mse_total)f R squared %(rsquared)f ci}|j|jgd}|D]}t||||<|jj|d<|j |j z |d<|S)zjupdate regression results dictionary with ANOVA specific statistics not checked for completeness ) df_modeldf_residessssruncentered_tss mse_model mse_resid mse_totalfvaluef_pvaluersquarednobs ssmwithmean)update__dict__getattrmodelr5r.r-)resad anova_attrkeys r anovadictr?sp BIIcllJ$#s#3$BvJ**SWW4B} Irzusing sex onlyzusing age onlyci}g}|jD]}|dk(r7tj|jd|d<|j d@d|vr||||<|j |^|dddk(r7|jdd}t ||||<|j ||ddd k(r|jddjd }t tj||d||df|d j|<|j d j|&|ddd k(ro|jddjd }t||d||d|d j|<|j d j|td ||fS)aconvert string formula to data dictionary ss : str * I : add constant * varname : for simple varnames data is used as is * F:varname : create dummy variables for factor varname * P:varname1*varname2 : create product dummy variables for varnames * G:varname1*varname2 : create product between factor and continuous variable data : dict or structured array data set, access of variables by name as in dictionaries Returns ------- vars : dictionary dictionary of variables with converted dummy variables names : list list of names, product (P:) and grouped continuous variables (G:) have name by joining individual names sorted according to input Examples -------- >>> xx, n = form2design('I a F:b P:c*d G:c*f', testdata) >>> xx.keys() ['a', 'b', 'const', 'cf', 'cd'] >>> n ['const', 'a', 'b', 'cd', 'cf'] Notes ----- with sorted dict, separate name list would not be necessary Irconst:Nr(zF:r zP:*r'zG:zunknown expression in formula) splitronesshapeappendrr c_joinr& ValueError)ssdatavarsnamesitemvs r form2designrRsH D E > 3;GGDJJqM2DM LL ! 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