phY/SQrSSKrSSKJr SSKJrJrJrJ r J r "SS5r Sr Sr S rS rS rS rS rSr"SS5rSr"SS\5rSr"SS\5rSr"SS\5rSr"SS\5rSrSSjrg) )ContrastMatrix TreatmentPolySumHelmertDiffN) PatsyError)repr_pretty_delegaterepr_pretty_implsafe_issubdtype no_picklingassert_no_picklingc,\rSrSrSrSr\rSr\ r Sr g)raYA simple container for a matrix used for coding categorical factors. Attributes: .. attribute:: matrix A 2d ndarray, where each column corresponds to one column of the resulting design matrix, and each row contains the entries for a single categorical variable level. Usually n-by-n for a full rank coding or n-by-(n-1) for a reduced rank coding, though other options are possible. .. attribute:: column_suffixes A list of strings to be appended to the factor name, to produce the final column names. E.g. for treatment coding the entries will look like ``"[T.level1]"``. c[R"U5UlX lURRS[ U5:wa [ S5eg)Nz(matrix and column_suffixes don't conform)npasarraymatrixcolumn_suffixesshapelenr )selfrrs gC:\Users\julio\OneDrive\Documentos\Trabajo\IdeasFrscas\Cabanna\env\Lib\site-packages\patsy/contrasts.py__init__ContrastMatrix.__init__*sEjj( . ;;  Q 3#7 7GH H 8cH[XURUR/5 gN)r rr)rpcycles r _repr_pretty_ContrastMatrix._repr_pretty_2s4;;0D0D"EFr)rrN) __name__ __module__ __qualname____firstlineno____doc__rr __repr__r"r __getstate____static_attributes__rrrrs!&I $HGLrrcD[SS/SS//SS/5n[R"UR[R"S55(deUR SS/:Xde[ U5 SSKnUR[[S/S//SS/5 [U5 g)Nrrab) rr array_equalreyerreprpytestraisesr r)cmr4s rtest_ContrastMatrixr78s !Q!Q(3* 5B >>"))RVVAY / // /  #s ++ +H MM*nsQCj3*Errc[U[5(aU$[U[5(aURS5$[ U5$![a [ U5s$f=f)Nutf-8) isinstancestrbytesdecodeUnicodeDecodeErrorr3)objs r_obj_to_readable_strr@Ks\#s C   ::g& &Cy" 9  sA A"!A"cSnU"SS5 U"SS5 U"SS5 U"SS5 U"SRS5S5 U"SRS 5S 5 g) NcP[U5n[U5[LdeX!:Xdegr)r@typer;)r?expectedgots rt$test__obj_to_readable_str..tXs("3'CyCrr1g?z1.0asdfu€r9z iso-8859-15zb'\xa4')encode)rFs rtest__obj_to_readable_strrKWsY aIc5Mffffhoog)hoom$j1rcTUVs/sHnSU<[U5<S3PM sn$s snf)N[])r@)prefixlevelslevels r _name_levelsrRjs%JP Q& 4U ; <& QQ Qs%c0[SSS/5SS/:Xdeg)Nr.r/cz[ab]z[ac])rRr,rrtest__name_levelsrUns c3Z (VV,< << US:aU[U5- nSUs=::a[U5:dO [ SU<S35eU$[ SU<S35e)Nrzspecified level z is out of rangez not found)indexr:intrr )rP level_refs r _get_levelr]vsl||I&&)S!! q= V $IY,V,YPQ Q yB CCrc`[/SQS5S:Xde[/SQS5S:Xde[/SQS5S:Xde[/SQS5S:XdeSSKnUR[[SS/S5 UR[[SS/S 5 UR[[SS/S 5 g) Nr.r/rTrr0r/rr0rrr.rT)r]r4r5r )r4s rtest__get_levelrcs oq )Q .. . or *a // / os +q 00 0 i #q (( ( MM*j3*a8 MM*j3*b9 MM*j3*c:rc2\rSrSrSrSSjrSrSr\r Sr g) raTreatment coding (also known as dummy coding). This is the default coding. For reduced-rank coding, one level is chosen as the "reference", and its mean behaviour is represented by the intercept. Each column of the resulting matrix represents the difference between the mean of one level and this reference level. For full-rank coding, classic "dummy" coding is used, and each column of the resulting matrix represents the mean of the corresponding level. The reference level defaults to the first level, or can be specified explicitly. .. ipython:: python # reduced rank dmatrix("C(a, Treatment)", balanced(a=3)) # full rank dmatrix("0 + C(a, Treatment)", balanced(a=3)) # Setting a reference level dmatrix("C(a, Treatment(1))", balanced(a=3)) dmatrix("C(a, Treatment('a2'))", balanced(a=3)) Equivalent to R ``contr.treatment``. The R documentation suggests that using ``Treatment(reference=-1)`` will produce contrasts that are "equivalent to those produced by many (but not all) SAS procedures". NcXlgr reference)rrhs rrTreatment.__init__s"rc[U5$r)rXrrPs rcode_with_interceptTreatment.code_with_intercepts 6""rc lURcSnO[XR5n[R"[ U5S- 5n[R "USU2SS24[R "S[ U5S- 45X2S2SS2445n[SUSUXS-S-5n[XE5$)NrrzT.) rhr]rr2rvstackzerosrRr)rrPrhr2 contrastsnamess rcode_without_intercept Treatment.code_without_intercepts >> !I"6>>:IffS[1_%II )Q 1c&kAo*>!?ZQR]AS T T6*9#51}8O#OPi//rrgr) r$r%r&r'r(rrlrsr r*r+r,rrrrs<## 0Lrrcr[5nUR/SQ5nUR/SQ:Xde[R"UR /SQ/SQ/SQ/5(deUR /SQ5nURSS/:Xde[R"UR SS/S S/SS //5(de[S S 9R /SQ5nURS S/:Xde[R"UR S S/SS/SS //5(de[S S 9R /SQ5nURS S/:Xde[R"UR S S/SS/SS //5(de[S S 9R /SQ5nURS S/:Xde[R"UR S S/SS/SS //5(de[5R /SQ5nURSS/:Xde[R"UR SS/S S/SS //5(deg)Nr_)z[a]z[b]z[c])rrr)rrr)rrrz[T.b]z[T.c]rrrgz[T.a]r/raz[T.1]z[T.0])rrlrrallcloserrst1rs rtest_Treatmentrzs B  # #O 4F  ! !%: :: : ;;v}}y)Y&G H HH H  & & 7F  ! !gw%7 77 7 ;;v}}1v1v1v&> ? ?? ?  # : :? KF  ! !gw%7 77 7 ;;v}}1v1v1v&> ? ?? ?  $ ; ;O LF  ! !gw%7 77 7 ;;v}}1v1v1v&> ? ?? ?  % < <_ MF  ! !gw%7 77 7 ;;v}}1v1v1v&> ? ?? ?[ / / :F  ! !gw%7 77 7 ;;v}}1v1v1v&> ? ?? ?rc8\rSrSrSrS SjrSrSrSr\ r Sr g) raeOrthogonal polynomial contrast coding. This coding scheme treats the levels as ordered samples from an underlying continuous scale, whose effect takes an unknown functional form which is `Taylor-decomposed`__ into the sum of a linear, quadratic, etc. components. .. __: https://en.wikipedia.org/wiki/Taylor_series For reduced-rank coding, you get a linear column, a quadratic column, etc., up to the number of levels provided. For full-rank coding, the same scheme is used, except that the zero-order constant polynomial is also included. I.e., you get an intercept column included as part of your categorical term. By default the levels are treated as equally spaced, but you can override this by providing a value for the `scores` argument. Examples: .. ipython:: python # Reduced rank dmatrix("C(a, Poly)", balanced(a=4)) # Full rank dmatrix("0 + C(a, Poly)", balanced(a=3)) # Explicit scores dmatrix("C(a, Poly([1, 2, 10]))", balanced(a=3)) This is equivalent to R's ``contr.poly``. (But note that in R, reduced rank encodings are always dummy-coded, regardless of what contrast you have set.) NcXlgrscores)rrs rr Poly.__init__s rcB[U5nURnUc[R"U5n[R"U[ S9n[U5U:wa[ SU<S[U5<S35eXDR5-nURS5[R"U5RS5-n[RRU5upgU[R"[R"U55-nU[R"[R"US-SS 95-nSUSS2S 4'/S QnU[S U5V s/sH n S U <3PM sn - nUSUnU(a [!Xh5$[!USS2SS24USS5$s sn f)N)dtypeznumber of levels (z#) does not match number of scores ())r`r)rr`r0r)axisr) .Constant.Linear .Quadratic.Cubic^)rrrarangerfloatr meanreshapelinalgqrsigndiagsqrtsumranger) r interceptrPnrraw_polyqrrris r _code_eitherPoly._code_eithersT K >YYq\FF%0 v;! ,-s6{<  ++->>'*biil.B.B7.KKyy||H% RWWRWWQZ   RWWRVVAqDq) **!Q$@ a 4 11, 44bq  !!+ +"!AqrE(E!"I6 65sFc&URSU5$)NTrrks rrlPoly.code_with_intercept s  v..rc&URSU5$)NFrrks rrsPoly.code_without_intercept#s  //rr~r) r$r%r&r'r(rrrlrsr r*r+r,rrrrs# D7>/0Lrrcv[5nUR/SQ5nUR/SQ:Xde/SQ/SQ/SQ/n[UR5 [ R "URU5(deUR/SQ5nURSS/:Xde[UR5 [ R "URSS /S S /S S //5(de[/S QS9R/SQ5nUR/SQ:Xde[UR5 [ R "UR/SQ/SQ/SQ/5(de[/SQS9R/SQ5nUR/SQ:Xde[UR5 [ R "UR/SQ/SQ/SQ/5(deS SKnUR[[S S/S9R/SQ5 UR[[S555nUR/SQ:Xdeg)Nr_)rrr)r;f>, p ?)rr>, p )r;f?rrrrrrrr)r r~)rg gQ}.?)rg?Q?g3)rgGUg?guCz?)rr )rg9UgHA?)rg)U?gM lOb)rgWl?gQ?r)rrrrz^4z^5) rrlrprintrrrwrsr4r5r listr)ryrrDr4s r test_Polyr)s  B  # #O 4F  ! !%K KK K 6"4H  &-- ;;v}}h / // /  & & 7F  ! !i%> >> > &-- ;; "$5 6 " # !#4 5     % 9 9/ JF  ! !%K KK K &-- ;; 7 7 6     % 9 9/ JF  ! !%K KK K &-- ;; 6 6 5     MM*d1a&1EEW  # #DqN 3F  ! !&  rc>\rSrSrSrS SjrSrSrSrSr \ r S r g) rimaGDeviation coding (also known as sum-to-zero coding). Compares the mean of each level to the mean-of-means. (In a balanced design, compares the mean of each level to the overall mean.) For full-rank coding, a standard intercept term is added. One level must be omitted to avoid redundancy; by default this is the last level, but this can be adjusted via the `omit` argument. .. warning:: There are multiple definitions of 'deviation coding' in use. Make sure this is the one you expect before trying to interpret your results! Examples: .. ipython:: python # Reduced rank dmatrix("C(a, Sum)", balanced(a=4)) # Full rank dmatrix("0 + C(a, Sum)", balanced(a=4)) # Omit a different level dmatrix("C(a, Sum(1))", balanced(a=3)) dmatrix("C(a, Sum('a1'))", balanced(a=3)) This is equivalent to R's `contr.sum`. NcXlgromit)rrs rr Sum.__init__s rcbURc[U5S- $[XR5$)Nr)rrr]rks r_omit_i Sum._omit_is) 99 v;? "fii0 0rc[U5nURU5n[R"US- 5n[R"X"S- 45nUSU2SS24USU2SS24'SXSSS24'XCS2SS24XSS-S2SS24'U$Nrr`)rrrr2empty)rrPromit_ir2outs r _sum_contrastSum._sum_contrasts Kf%ffQUmhhq5z"gvgqj/GVGQJAI"7A:QJL!O rcURU5n[R"[R"[ U55UR 45nS/UR -n[X45$)N[mean])rsr column_stackonesrrrr)rrPcontrastrrs rrlSum.code_with_interceptsS..v6"''#f+"6!HI#*x'?'??f66rcURU5nURU5nUSUXS-S-n[U[SU55$)NrzS.)rrrrR)rrPrrincluded_levelss rrsSum.code_without_interceptsM##F+f% &/FA:<,@@fl4&IJJrrr) r$r%r&r'r(rrrrlrsr r*r+r,rrrrms(:17 K Lrrc.[5nUR/SQ5nUR/SQ:Xde[R"UR /SQ/SQ/SQ/5(deUR /SQ5nURSS/:Xde[R"UR SS /S S/S S //5(deUR /S Q5nURS S /:Xde[R"UR SS /S S/S S //5(de[SS9nUR/SQ5nUR/SQ:Xde[R"UR /SQ/SQ/SQ/5(deUR /SQ5nURSS/:Xde[R"UR SS /S S /S S//5(deUR /SQ5nURSS/:Xde[R"UR S S /SS /S S//5(de[SS9nUR/SQ5nUR/SQ:Xde[R"UR /SQ/SQ/SQ/5(deUR /SQ5nURSS/:Xde[R"UR S S /SS /S S//5(de[SS9nUR/SQ5nUR/SQ:Xde[R"UR /SQ/SQ/SQ/5(deUR /SQ5nURSS/:Xde[R"UR S S /SS /S S//5(deg)Nr_)r[S.a][S.b])rrr)rrrrr`r`rrrrr`)r`rvrbz[S.-1]z[S.-2]r)rr[S.c]r)rrr0z[S.0]z[S.2]rb)rrrr.)rrlrrrwrrs)ryrt2t3t4s rtest_SumrsJ B  # #O 4F  ! !%A AA A ;;v}}y)[&I J JJ J  & & 7F  ! !gw%7 77 7 ;;v}}1v1vBx&@ A AA A  & &| 4F  ! !h%9 99 9 ;;v}}1v1vBx&@ A AA A !B  # #O 4F  ! !%A AA A ;;v}}y+y&I J JJ J  & & 7F  ! !gw%7 77 7 ;;v}}1vBx!Q&@ A AA A  & &y 1F  ! !gw%7 77 7 ;;v}}Bx!Q!Q&@ A AA A "B  # #O 4F  ! !%A AA A ;;v}}{Iy&I J JJ J  & & 7F  ! !gw%7 77 7 ;;v}}Bx!Q!Q&@ A AA A #B  # #O 4F  ! !%A AA A ;;v}}{Iy&I J JJ J  & & 7F  ! !gw%7 77 7 ;;v}}Bx!Q!Q&@ A AA Arc.\rSrSrSrSrSrSr\r Sr g)riaHelmert contrasts. Compares the second level with the first, the third with the average of the first two, and so on. For full-rank coding, a standard intercept term is added. .. warning:: There are multiple definitions of 'Helmert coding' in use. Make sure this is the one you expect before trying to interpret your results! Examples: .. ipython:: python # Reduced rank dmatrix("C(a, Helmert)", balanced(a=4)) # Full rank dmatrix("0 + C(a, Helmert)", balanced(a=4)) This is equivalent to R's `contr.helmert`. c[U5n[R"X"S- 45n[R"SU5USS[R"US- 5'SU[R "US- 5'U$r)rrrpr diag_indices triu_indices)rrPrcontrs r_helmert_contrastHelmert._helmert_contrastsd K !U$,.IIaOab "//!a%()(*booa!e$% rc [R"[R"[U55UR U545n[ SS/[ USS5-5n[X#5$)NH.rr)rrrrrrRrr)rrPrrs rrlHelmert.code_with_intercepts[?? WWS[ !4#9#9&#A B 'tk]T&*=M-MNh88rc VURU5n[U[SUSS55$)Nrr)rrrRrrPrs rrsHelmert.code_without_intercept s,))&1h T6!":(FGGrr,N) r$r%r&r'r(rrlrsr r*r+r,rrrrs.,9HLrrc [5n/SQS4HnURU5nUR/SQ:Xde[R"UR /SQ/SQ/SQ/SQ/5(deUR U5nUR/SQ:Xde[R"UR /SQ/S Q/S Q/S Q/5(aMe g) Nr.r/rTd)z [H.intercept][H.b][H.c][H.d])rr`r`r`)rrr`r`)rrr0r`)rrr)rrr)r`r`r`r)rr0r`)rrr)rrlrrrwrrs)ryrPrs r test_Helmertrs B')=>''/%%)UUUU{{ MM nm\ J    **62%%)DDDD{{ MML+z9M    ?rc.\rSrSrSrSrSrSr\r Sr g)ri aBackward difference coding. This coding scheme is useful for ordered factors, and compares the mean of each level with the preceding level. So you get the second level minus the first, the third level minus the second, etc. For full-rank coding, a standard intercept term is added (which gives the mean value for the first level). Examples: .. ipython:: python # Reduced rank dmatrix("C(a, Diff)", balanced(a=3)) # Full rank dmatrix("0 + C(a, Diff)", balanced(a=3)) c [U5n[R"X"S- 45n[R"SU5n[R"XD5n[R "US- 5upg[R "U5nXR- [U5- X6UXx4'[R"XDSSS25n [R"US- 5upg[R "U5nU [U5- X6US-Xx4'U$r) rrrprrepeatrargsortr tril_indices) rrPnlevelsr int_range upper_introw_icol_i col_order lower_ints r_diff_contrastDiff._diff_contrast4sf+'Q;/0IIa) IIi3 w{3 JJu% 5>5HE M 5 I 001IIi4R49 w{3 JJu% 8AE'N8RI"E$445 rc[R"[R"[U55UR U545n[ U[ SU55$)ND.)rrrrrrrRrs rrlDiff.code_with_interceptGsA??BGGCK$8$:M:Mf:U#VWh T6(BCCrc VURU5n[U[SUSS55$)Nrr`)rrrRrs rrsDiff.code_without_interceptKs,&&v.h T6#2;(GHHrr,N) r$r%r&r'r(rrlrsr r*r+r,rrrr s&&DILrrc[5nUR/SQ5nUR/SQ:Xde[R"UR /SQ/SQ/SQ/SQ/5(deUR /SQ5nUR/SQ:Xde[R"UR /SQ/S Q/S Q/S Q/5(deg) Nr)[D.a][D.b][D.c]z[D.d])rп)r?rr)rr?r)rrr?)rrr)rrr)rrr)rrr)rrr)rrlrrrwrrsrxs r test_diffrRs B  # #$8 9F  ! !%I II I ;; - , + *      & &'; >!3D-EF  ++F33..v66rr) __all__numpyrpatsyr patsy.utilr r r r rrr7r@rKrRrUrXr]rcrrzobjectrrrrrrrrr r,rrrs LD & 2&R=I D ;11h@0K6K\AH>&>B#BL9f9x  /6/dB7r