,h\$x/SQrSSKrSSKrSSKJr SSKJr SSKJ r J r Sr Sr Sr S r"S S \5rS rg) )balanced demo_data LookupFactorN) PatsyError)C) no_picklingassert_no_picklingc NURSS5n/n[U5nUH;nXnUR[SUS-5Vs/sH od<U<3PM sn5 M= [ [ R "U66n0n[ X75HupI[U 5U-X'M U$s snf)a balanced(factor_name=num_levels, [factor_name=num_levels, ..., repeat=1]) Create simple balanced factorial designs for testing. Given some factor names and the number of desired levels for each, generates a balanced factorial design in the form of a data dictionary. For example: .. ipython:: In [1]: balanced(a=2, b=3) Out[1]: {'a': ['a1', 'a1', 'a1', 'a2', 'a2', 'a2'], 'b': ['b1', 'b2', 'b3', 'b1', 'b2', 'b3']} By default it produces exactly one instance of each combination of levels, but if you want multiple replicates this can be accomplished via the `repeat` argument: .. ipython:: In [2]: balanced(a=2, b=2, repeat=2) Out[2]: {'a': ['a1', 'a1', 'a2', 'a2', 'a1', 'a1', 'a2', 'a2'], 'b': ['b1', 'b2', 'b1', 'b2', 'b1', 'b2', 'b1', 'b2']} repeat)popsortedappendrangezip itertoolsproductlist) kwargsr levelsnamesname level_countivaluesdatavalues bC:\Users\julio\OneDrive\Documentos\Trabajo\Ideas Frescas\venv\Lib\site-packages\patsy/user_util.pyrrs6ZZ! $F F 6NEl  5K!O3LM3Laq)3LMN)##V, -F D5) %[6) * K NsB" c[SSS9nUS/SQ:XdeUS/SQ:Xde[SSSS9nUS/S Q:XdeUS/S Q:Xdeg) N)abr")a1r$r$a2r%r%r#)b1b2b3r&r'r()r"r#r ) r$r$r$r%r%r%r$r$r$r%r%r%) r&r'r(r&r'r(r&r'r(r&r'r()r)rs r test_balancedr);sz a1 D 9< << < 9< << < a1Q 'D 9     9    cdURSS5nURSS5nU(a[SU<35e[5n0nUH;nUSS;aX%U'MUSS;aURU5 M.[ S U<35e [ R "[UR55[S 9n[[ R"US -U- 55nX-n [SS U0UD6n [ RRS5n [U5HnU RU S 9X'M U $)ademo_data(*names, nlevels=2, min_rows=5) Create simple categorical/numerical demo data. Pass in a set of variable names, and this function will return a simple data set using those variable names. Names whose first letter falls in the range "a" through "m" will be made categorical (with `nlevels` levels). Those that start with a "p" through "z" are numerical. We attempt to produce a balanced design on the categorical variables, repeating as necessary to generate at least `min_rows` data points. Categorical variables are returned as a list of strings. Numerical data is generated by sampling from a normal distribution. A fixed random seed is used, so that identical calls to demo_data() will produce identical results. Numerical data is returned in a numpy array. Example: .. ipython: In [1]: patsy.demo_data("a", "b", "x", "y") Out[1]: {'a': ['a1', 'a1', 'a2', 'a2', 'a1', 'a1', 'a2', 'a2'], 'b': ['b1', 'b2', 'b1', 'b2', 'b1', 'b2', 'b1', 'b2'], 'x': array([ 1.76405235, 0.40015721, 0.97873798, 2.2408932 , 1.86755799, -0.97727788, 0.95008842, -0.15135721]), 'y': array([-0.10321885, 0.4105985 , 0.14404357, 1.45427351, 0.76103773, 0.12167502, 0.44386323, 0.33367433])} nlevelsr min_rowszunexpected keyword arguments rabcdefghijklmn pqrstuvwxyzz bad name )dtypeg?r )size)r TypeErrorsetaddrnpprodrrintceilrrandom RandomStaternormal) rrr,r- numerical categoricalrbalanced_design_sizer num_rowsrrs rrr^sBjjA&Gzz*a(H VEFFIK 7& & '  !W % MM$ d45 5 774 (:(:(<#=SI C*>>? @F,H  16 1[ 1D a Ay!XX8X, " Kr*c [SSS5n[UR55/SQ:XdeUS/SQ:XdeUS/SQ:XdeUSR[R"[ 5:XdeUSR S:Xde[SS5n[UR55SS/:Xde[US5[US5s=:XaS :Xde e[[SS S 9S5S :Xde[[SSSS S 9S5S :Xde[[SSSS S S9S5S:XdeSSKnUR[[SSS5 UR[[SSSS9 g)Nr"r#x)r"r#rD)r$r$r%r%r$r$r%r%)r&r'r&r'r&r'r&r')yr. )r- r!)r-r,r__123{)asdfasdf) rrkeysr1r7floatshapelenpytestraisesrr4)d1d2rQs rtest_demo_datarUsi 3S !B "'')  // / c7F FF F c7F FF F c7==BHHUO ++ + c7==D  3 B "'') c ** * r#w<3r#w< ,1 ,, ,, , yr*3/ 0B 66 6 yc34S9 :b @@ @ yc3Q?D E KK K MM*ic7; MM)YS3M?r*c^\rSrSrSrSSjrSrSrSrSr S r S r S r S r S r\rSrg)raA simple factor class that simply looks up a named entry in the given data. Useful for programatically constructing formulas, and as a simple example of the factor protocol. For details see :ref:`expert-model-specification`. Example:: dmatrix(ModelDesc([], [Term([LookupFactor("x")])]), {"x": [1, 2, 3]}) :arg varname: The name of this variable; used as a lookup key in the passed in data dictionary/DataFrame/whatever. :arg force_categorical: If True, then treat this factor as categorical. (Equivalent to using :func:`C` in a regular formula, but of course you can't do that with a :class:`LookupFactor`. :arg contrast: If given, the contrast to use; see :func:`C`. (Requires ``force_categorical=True``.) :arg levels: If given, the categorical levels; see :func:`C`. (Requires ``force_categorical=True``.) :arg origin: Either ``None``, or the :class:`Origin` of this factor for use in error reporting. .. versionadded:: 0.2.0 The ``force_categorical`` and related arguments. NcXlX lX0lX@lXPlUR(dUb [ S5eUb [ S5egg)Nz)contrast= requires force_categorical=Truez'levels= requires force_categorical=True)_varname_force_categorical _contrast_levelsorigin ValueError)selfvarnameforce_categoricalcontrastrr]s r__init__LookupFactor.__init__sU "3!  &&# !LMM! !JKK"'r*cUR$N)rYr_s rrLookupFactor.names }}r*cRURR<SUR<S3$)N()) __class____name__rYrgs r__repr__LookupFactor.__repr__s>>22DMMBBr*c"[U[5=(ay URUR:H=(aY URUR:H=(a9 URUR:H=(a UR UR :H$rf) isinstancerrYrZr[r\r_others r__eq__LookupFactor.__eq__sm ul + . / .''5+C+CC .%//1 .  -  r*c X:X+$rfr3rrs r__ne__LookupFactor.__ne__s   r*cz[[URURURUR 45$rf)hashrrYrZr[r\rgs r__hash__LookupFactor.__hash__s5 ''    r*cg)Nrr3)r_stateeval_envs rmemorize_passes_needed#LookupFactor.memorize_passes_neededsr*cerfr3)r_r~ which_passrs rmemorize_chunkLookupFactor.memorize_chunkur*cerfr3)r_r~rs rmemorize_finishLookupFactor.memorize_finishrr*cX RnUR(a[X0RURS9nU$)N)rbr)rYrZrr[r\)r_memorize_staterrs revalLookupFactor.evals0]]#  " "ennT\\JE r*)r[rZr\rYr])FNNN)rm __module__ __qualname____firstlineno____doc__rcrrnrtrwr{rrrrr __getstate____static_attributes__r3r*rrrsI8TX LC !   Lr*rcB[S5nUR5S:XdeU[S5:XdeU[S5:wde[U5[[S55:Xde[U5[[S55:wdeUR0SS05S:XdeUR0SS05S:Xde[ U5S:XdeUR be[SSS9nUR S:Xde[SS S S S 9nUR0S/S Q05nUR /S Q:XdeURS :XdeURS :XdeSSK nUR[[SS S9 UR[[SS S9 [[S55 g)Nr"r#r r zLookupFactor('a')asdf)r]cTCONTRAST)r r )rarbr)r r r rnc)rb)r) rrrzrreprr]rrbrrQrRr^r )l_a l_with_originl_cboxrQs rtest_LookupFactorrs s C 88:   ,s# ## # ,s# ## # 9\#./ // / 9\#./ // / 88Ba !Q && & 88Ba !Q && & 9+ ++ + ::   V4M   6 )) ) sdZPV WC ((2Y' (C 88y  <<: %% % ::   MM*lD:MF MM*lDM@|C()r*)__all__rnumpyr7patsyrpatsy.categoricalr patsy.utilrr rr)rrUobjectrrr3r*rrsG 46&R F5p@,V6Vr*r*